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Extracellular vesicle therapy in neurological disorders

Extracellular vesicles (EVs) are vital for cell-to-cell communication, transferring proteins, lipids, and nucleic acids in various physiological and pathological processes. They play crucial roles in immune mo...

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Machine learning enabled classification of lung cancer cell lines co-cultured with fibroblasts with lightweight convolutional neural network for initial diagnosis

Identification of lung cancer subtypes is critical for successful treatment in patients, especially those in advanced stages. Many advanced and personal treatments require knowledge of specific mutations, as w...

Beyond glycan barriers: non-cognate ligands and protein mimicry approaches to elicit broadly neutralizing antibodies for HIV-1

Human immunodeficiency virus type 1 (HIV-1) vaccine immunogens capable of inducing broadly neutralizing antibodies (bNAbs) remain obscure. HIV-1 evades immune responses through enormous diversity and hides its...

Plexin C1 influences immune response to intracellular LPS and survival in murine sepsis

Intracellular sensing of lipopolysaccharide (LPS) is essential for the immune response against gram-negative bacteria and results in activation of caspase-11 and pyroptotic cell death with fatal consequences i...

EpCAM-targeted betulinic acid analogue nanotherapy improves therapeutic efficacy and induces anti-tumorigenic immune response in colorectal cancer tumor microenvironment

Betulinic acid (BA) has been well investigated for its antiproliferative and mitochondrial pathway-mediated apoptosis-inducing effects on various cancers. However, its poor solubility and off-target activity h...

Low-level HIV-1 viremia affects T-cell activation and senescence in long-term treated adults in the INSTI era

Around 10% of people with HIV (PWH) exhibit a low-level viremia (LLV) under antiretroviral therapy (ART). However, its origin and clinical significance are largely unknown, particularly at viremias between 50 ...

Gene therapy for ultrarare diseases: a geneticist’s perspective

Gene therapy has made considerable strides in recent years. More than 4000 protein-coding genes have been implicated in more than 6000 genetic diseases; next-generation sequencing has dramatically revolutioniz...

Targeted nanotherapeutics for the treatment of Helicobacter pylori infection

Helicobacter pylori infection is involved in gastric diseases such as peptic ulcer and adenocarcinoma. Approved antibiotherapies still fail in 10 to 40% of the infected patients and, in this scenario, targeted na...

Variants of human DECTIN-1 rs16910526 are linked to differential reactive oxygen species production and susceptibility to tuberculosis

Dectin-1 is a transmembrane receptor that plays a pivotal role in recognising fungi and Mycobacterium tuberculosis (Mtb) . A specific variant, DECTIN-1 rs16910526, results in a truncated receptor that disrupts mem...

Retraction Note: Inhibitors of apoptosis proteins in experimental benign prostatic hyperplasia: effects of Serenoa repens , selenium and lycopene

Development of novel antimicrobials with engineered endolysin lysecd7-smap to combat gram-negative bacterial infections.

Among the non-traditional antibacterial agents in development, only a few targets critical Gram-negative bacteria such as carbapenem-resistant Pseudomonas aeruginosa , Acinetobacter baumannii or cephalosporin-resi...

BUB1B monoallelic germline variants contribute to prostate cancer predisposition by triggering chromosomal instability

Prostate cancer (PrCa) is the most frequently diagnosed cancer in men. Variants in known moderate- to high-penetrance genes explain less than 5% of the cases arising at early-onset (< 56 years) and/or with fam...

Enteroviruses: epidemic potential, challenges and opportunities with vaccines

Enteroviruses (EVs) are the most prevalent viruses in humans. EVs can cause a range of acute symptoms, from mild common colds to severe systemic infections such as meningitis, myocarditis, and flaccid paralysi...

Intracellular domain of epithelial cell adhesion molecule induces Wnt receptor transcription to promote colorectal cancer progression

Epithelial cell adhesion molecule (EpCAM) has been widely studied as a tumor antigen due to its expression in varieties of solid tumors. Moreover, the glycoprotein contributes to critical cancer-associated cel...

Unraveling the differential mechanisms of revascularization promoted by MSCs & ECFCs from adipose tissue or umbilical cord in a murine model of critical limb-threatening ischemia

Critical limb-threatening ischemia (CLTI) constitutes the most severe manifestation of peripheral artery disease, usually induced by atherosclerosis. CLTI patients suffer from high risk of amputation of the lo...

A glimpse into viral warfare: decoding the intriguing role of highly pathogenic coronavirus proteins in apoptosis regulation

Coronaviruses employ various strategies for survival, among which the activation of endogenous or exogenous apoptosis stands out, with viral proteins playing a pivotal role. Notably, highly pathogenic coronavi...

CPEB2-activated axonal translation of VGLUT2 mRNA promotes glutamatergic transmission and presynaptic plasticity

Local translation at synapses is important for rapidly remodeling the synaptic proteome to sustain long-term plasticity and memory. While the regulatory mechanisms underlying memory-associated local translatio...

Dual inhibition of SUMOylation and MEK conquers MYC-expressing KRAS -mutant cancers by accumulating DNA damage

KRAS mutations frequently occur in cancers, particularly pancreatic ductal adenocarcinoma, colorectal cancer, and non-small cell lung cancer. Although KRAS G12C inhibitors have recently been approved, effective pr...

Exosomes: a review of biologic function, diagnostic and targeted therapy applications, and clinical trials

Exosomes are extracellular vesicles generated by all cells and they carry nucleic acids, proteins, lipids, and metabolites. They mediate the exchange of substances between cells,thereby affecting biological pr...

Cholestasis-induced phenotypic transformation of neutrophils contributes to immune escape of colorectal cancer liver metastasis

Cholestasis is a common yet severe complication that occurs during the advancement of liver metastasis. However, how cholestasis impacts the development, treatment, and tumor microenvironment (TME) of liver me...

Enterovirus-A71 exploits RAB11 to recruit chaperones for virus morphogenesis

Enterovirus 71 (EV-A71) causes Hand, Foot and Mouth Disease (HFMD) in children and has been associated with neurological complications. The molecular mechanisms involved in EV-A71 pathogenesis have remained el...

The double whammy of ER-retention and dominant-negative effects in numerous autosomal dominant diseases: significance in disease mechanisms and therapy

The endoplasmic reticulum (ER) employs stringent quality control mechanisms to ensure the integrity of protein folding, allowing only properly folded, processed and assembled proteins to exit the ER and reach ...

Beyond traditional translation: ncRNA derived peptides as modulators of tumor behaviors

Within the intricate tapestry of molecular research, noncoding RNAs (ncRNAs) were historically overshadowed by a pervasive presumption of their inability to encode proteins or peptides. However, groundbreaking...

Adipocyte pyroptosis occurs in omental tumor microenvironment and is associated with chemoresistance of ovarian cancer

Ovarian carcinoma (OC) is a fatal malignancy, with most patients experiencing recurrence and resistance to chemotherapy. In contrast to hematogenous metastasizing tumors, ovarian cancer cells disseminate withi...

Correction: Excess glucose alone depress young mesenchymal stromal/stem cell osteogenesis and mitochondria activity within hours/days via NAD + / SIRT1 axis

The original article was published in Journal of Biomedical Science 2024 31 :49

The glycosylation deficiency of flavivirus NS1 attenuates virus replication through interfering with the formation of viral replication compartments

Flavivirus is a challenge all over the world. The replication of flavivirus takes place within membranous replication compartments (RCs) derived from endoplasmic reticulum (ER). Flavivirus NS1 proteins have be...

Osteosarcoma in a ceRNET perspective

Osteosarcoma (OS) is the most prevalent and fatal type of bone tumor. It is characterized by great heterogeneity of genomic aberrations, mutated genes, and cell types contribution, making therapy and patients ...

Immunoglobulin and T cell receptor repertoire changes induced by a prototype vaccine against Chagas disease in naïve rhesus macaques

A vaccine against Trypanosoma cruzi , the agent of Chagas disease, would be an excellent additional tool for disease control. A recombinant vaccine based on Tc24 and TSA1 parasite antigens was found to be safe and...

Revolution in sepsis: a symptoms-based to a systems-based approach?

Severe infection and sepsis are medical emergencies. High morbidity and mortality are linked to CNS dysfunction, excessive inflammation, immune compromise, coagulopathy and multiple organ dysfunction. Males ap...

Development of a highly effective combination monoclonal antibody therapy against Herpes simplex virus

Infections with Herpes simplex virus (HSV)-1 or -2 usually present as mild chronic recurrent disease, however in rare cases can result in life-threatening conditions with a large spectrum of pathology. Monoclo...

USP9X-mediated REV1 deubiquitination promotes lung cancer radioresistance via the action of REV1 as a Rad18 molecular scaffold for cystathionine γ-lyase

Radioresistance is a key clinical constraint on the efficacy of radiotherapy in lung cancer patients. REV1 DNA directed polymerase (REV1) plays an important role in repairing DNA damage and maintaining genomic...

Tumor necrosis factor-inducible gene 6 protein and its derived peptide ameliorate liver fibrosis by repressing CD44 activation in mice with alcohol-related liver disease

Alcohol-related liver disease (ALD) is a major health concern worldwide, but effective therapeutics for ALD are still lacking. Tumor necrosis factor-inducible gene 6 protein (TSG-6), a cytokine released from m...

Characterization of the genetic variation and evolutionary divergence of the CLEC18 family

The C-type lectin family 18 (CLEC18) with lipid and glycan binding capabilities is important to metabolic regulation and innate immune responses against viral infection. However, human CLEC18 comprises three p...

Pivotal functions and impact of long con-coding RNAs on cellular processes and genome integrity

Recent advances in uncovering the mysteries of the human genome suggest that long non-coding RNAs (lncRNAs) are important regulatory components. Although lncRNAs are known to affect gene transcription, their m...

Somatic PDGFRB activating variants promote smooth muscle cell phenotype modulation in intracranial fusiform aneurysm

The fusiform aneurysm is a nonsaccular dilatation affecting the entire vessel wall over a short distance. Although PDGFRB somatic variants have been identified in fusiform intracranial aneurysms, the molecular...

A G-quadruplex-binding platinum complex induces cancer mitochondrial dysfunction through dual-targeting mitochondrial and nuclear G4 enriched genome

G-quadruplex DNA (G4) is a non-canonical structure forming in guanine-rich regions, which play a vital role in cancer biology and are now being acknowledged in both nuclear and mitochondrial (mt) genome. Howev...

Excess glucose alone depress young mesenchymal stromal/stem cell osteogenesis and mitochondria activity within hours/days via NAD + /SIRT1 axis

The impact of global overconsumption of simple sugars on bone health, which peaks in adolescence/early adulthood and correlates with osteoporosis (OP) and fracture risk decades, is unclear. Mesenchymal stromal...

The Correction to this article has been published in Journal of Biomedical Science 2024 31 :61

Contribution of extracellular vesicles for the pathogenesis of retinal diseases: shedding light on blood-retinal barrier dysfunction

Retinal degenerative diseases, including diabetic retinopathy (DR) and age-related macular degeneration (AMD), loom as threats to vision, causing detrimental effects on the structure and function of the retina...

Exploiting urine-derived induced pluripotent stem cells for advancing precision medicine in cell therapy, disease modeling, and drug testing

The field of regenerative medicine has witnessed remarkable advancements with the emergence of induced pluripotent stem cells (iPSCs) derived from a variety of sources. Among these, urine-derived induced pluri...

Targeting cathepsin S promotes activation of OLF1-BDNF/TrkB axis to enhance cognitive function

Cathepsin S (CTSS) is a cysteine protease that played diverse roles in immunity, tumor metastasis, aging and other pathological alterations. At the cellular level, increased CTSS levels have been associated wi...

Campylobacter jejuni virulence factors: update on emerging issues and trends

Campylobacter jejuni is a very common cause of gastroenteritis, and is frequently transmitted to humans through contaminated food products or water. Importantly, C. jejuni infections have a range of short- and l...

Membrane lipid remodeling eradicates Helicobacter pylori by manipulating the cholesteryl 6'-acylglucoside biosynthesis

Helicobacter pylori , the main cause of various gastric diseases, infects approximately half of the human population. This pathogen is auxotrophic for cholesterol which it converts to various cholesteryl α-glucosi...

Dengue virus pathogenesis and host molecular machineries

Dengue viruses (DENV) are positive-stranded RNA viruses belonging to the Flaviviridae family. DENV is the causative agent of dengue, the most rapidly spreading viral disease transmitted by mosquitoes. Each yea...

Targeting NLRP3 signaling reduces myocarditis-induced arrhythmogenesis and cardiac remodeling

Myocarditis substantially increases the risk of ventricular arrhythmia. Approximately 30% of all ventricular arrhythmia cases in patients with myocarditis originate from the right ventricular outflow tract (RV...

T cell expressions of aberrant gene signatures and Co-inhibitory receptors (Co-IRs) as predictors of renal damage and lupus disease activity

Systemic lupus erythematosus (SLE) is distinguished by an extensive range of clinical heterogeneity with unpredictable disease flares and organ damage. This research investigates the potential of aberrant sign...

Applications of peptides in nanosystems for diagnosing and managing bacterial sepsis

Sepsis represents a critical medical condition stemming from an imbalanced host immune response to infections, which is linked to a significant burden of disease. Despite substantial efforts in laboratory and ...

Enhancement of NETosis by ACE2-cross-reactive anti-SARS-CoV-2 RBD antibodies in patients with COVID-19

High levels of neutrophil extracellular trap (NET) formation or NETosis and autoantibodies are related to poor prognosis and disease severity of COVID-19 patients. Human angiotensin-converting enzyme 2 (ACE2) ...

Attenuating mitochondrial dysfunction and morphological disruption with PT320 delays dopamine degeneration in MitoPark mice

Mitochondria are essential organelles involved in cellular energy production. Changes in mitochondrial function can lead to dysfunction and cell death in aging and age-related disorders. Recent research sugges...

Longitudinal alterations in brain perfusion and vascular reactivity in the zQ175DN mouse model of Huntington’s disease

Huntington’s disease (HD) is marked by a CAG-repeat expansion in the huntingtin gene that causes neuronal dysfunction and loss, affecting mainly the striatum and the cortex. Alterations in the neurovascular co...

Antimicrobial peptide thanatin fused endolysin PA90 (Tha-PA90) for the control of Acinetobacter baumannii infection in mouse model

This study addresses the urgent need for infection control agents driven by the rise of drug-resistant pathogens such as Acinetobacter baumannii . Our primary aim was to develop and assess a novel endolysin, Tha-P...

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Journal of Biomedical Science is supported by the National Science and Technology Council (NSTC) , Taiwan.

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Journal of Biomedical Science

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Endothelial adherens junctions and the actin cytoskeleton: an 'infinity net'?

A recent paper in BMC Biology reports that actin stress fibers in adjacent cultured endothelial cells are linked through adherens junctions. This organization might provide a super-cellular network that could ena...

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Robust and specific inhibition of microRNAs in Caenorhabditis elegans

MicroRNAs (miRNAs) are small non-coding RNAs that regulate the expression of numerous target genes. Yet, while hundreds of miRNAs have been identified, little is known about their functions. In a recent report...

Genome of a songbird unveiled

An international collaborative effort has recently uncovered the genome of the zebra finch, a songbird model that has provided unique insights into an array of biological phenomena.

The mathematics of sexual attraction

Pollen tubes follow attractants secreted by the ovules. In a recent paper in BMC Plant Biology , Stewman and colleagues have quantified the parameters of this attraction and used them to calibrate a mathematical m...

Diversity lost: are all Holarctic large mammal species just relict populations?

Population genetic analyses of Eurasian wolves published recently in BMC Evolutionary Biology suggest that a major genetic turnover took place in Eurasian wolves after the Pleistocene. These results add to the gr...

Hybridization and speciation in angiosperms: arole for pollinator shifts?

The majority of convincingly documented cases of hybridization in angiosperms has involved genetic introgression between the parental species or formation of a hybrid species with increased ploidy; however, ho...

Evolution underground: shedding light on the diversification of subterranean insects

A recent study in BMC Evolutionary Biology has reconstructed the molecular phylogeny of a large Mediterranean cave-dwelling beetle clade, revealing an ancient origin and strong geographic structuring. It seems li...

A modern circadian clock in the common angiosperm ancestor of monocots and eudicots

The circadian clock enhances fitness through temporal organization of plant gene expression, metabolism and physiology. Two recent studies, one in BMC Evolutionary Biology , demonstrate through phylogenetic analys...

Scale-eating cichlids: from hand(ed) to mouth

Two recent studies in BMC Biology and Evolution raise important questions about a textbook case of frequency-dependent selection in scale-eating cichlid fishes. They also suggest a fascinating new line of researc...

Top dogs: wolf domestication and wealth

A phylogeographic analysis of gene sequences important in determining body size in dogs, recently published in BMC Biology , traces the appearance of small body size to the Neolithic Middle East. This finding stre...

No better time to FRET: shedding light on host pathogen interactions

Understanding the spatio-temporal subversion of host cell signaling by bacterial virulence factors is key to combating infectious diseases. Following a recent study by Buntru and co-workers published in BMC Biolo...

Making progress in genetic kin recognition among vertebrates

A recent study in BMC Evolutionary Biology has shown that genetically similar individual ring-tailed lemurs are also more similar in their scent composition, suggesting a possible mechanism of kin recognition. Th...

Regeneration review reprise

There have been notable advances in the scientific understanding of regeneration within the past year alone, including two recently published in BMC Biology . Increasingly, progress in the regeneration field is be...

Acoel and platyhelminth models for stem-cell research

Acoel and platyhelminth worms are particularly attractive invertebrate models for stem-cell research because their bodies are continually renewed from large pools of somatic stem cells. Several recent studies,...

Madm (Mlf1 adapter molecule) cooperates with Bunched A to promote growth in Drosophila

The TSC-22 domain family (TSC22DF) consists of putative transcription factors harboring a DNA-binding TSC-box and an adjacent leucine zipper at their carboxyl termini. Both short and long TSC22DF isoforms are ...

Bunched and Madm: a novel growth-regulatory complex?

By combining Drosophila genetics and proteomics Gluderer et al. report in this issue of Journal of Biology the isolation of a novel growth-regulatory complex consisting of Bunched and Madm. Future study of this c...

Q&A: What can microfluidics do for stem-cell research?

Regulation of metabolism in caenorhabditis elegans longevity.

The nematode Caenorhabditis elegans is a favorite model for the study of aging. A wealth of genetic and genomic studies show that metabolic regulation is a hallmark of life-span modulation. A recent study in BMC ...

Reprogramming of the non-coding transcriptome during brain development

A recent global analysis of gene expression during the differentiation of neuronal stem cells to neurons and oligodendrocytes indicates a complex pattern of changes in the expression of both protein-coding tra...

The THO complex as a key mRNP biogenesis factor in development and cell differentiation

The THO complex is a key component in the co-transcriptional formation of messenger ribonucleoparticles that are competent to be exported from the nucleus, yet its precise function is unknown. A recent study in B...

SnoPatrol: how many snoRNA genes are there?

Small nucleolar RNAs (snoRNAs) are among the most evolutionarily ancient classes of small RNA. Two experimental screens published in BMC Genomics expand the eukaryotic snoRNA catalog, but many more snoRNAs remain...

Sometimes one just isn't enough: do vertebrates contain an H2A.Z hyper-variant?

How much functional specialization can one component histone confer on a single nucleosome? The histone variant H2A.Z seems to be an extreme example. Genome-wide distribution maps show non-random (and evolutio...

Apical polarity in three-dimensional culture systems: where to now?

Delineation of the mechanisms that establish and maintain the polarity of epithelial tissues is essential to understanding morphogenesis, tissue specificity and cancer. Three-dimensional culture assays provide...

The water flea Daphnia - a 'new' model system for ecology and evolution?

Daphnia pulex is the first crustacean to have its genome sequenced. Availability of the genome sequence will have implications for research in aquatic ecology and evolution in particular, as addressed by a series...

Top ten in Journal of Biology in 2009: stem cells, influenza, pit bulls, Darwin, and more

The bacterial pathogen listeria monocytogenes : an emerging model in prokaryotic transcriptomics.

A major challenge in bacterial pathogenesis is understanding the molecular basis of the switch from saprophytism to virulence. Following a recent whole-genome transcriptomic analysis using tiling arrays, an ar...

Forward genetics in Tribolium castaneum : opening new avenues of research in arthropod biology

A recent paper in BMC Biology reports the first large-scale insertional mutagenesis screen in a non-drosophilid insect, the red flour beetle Tribolium castaneum . This screen marks the beginning of a non-biased, '...

Mapping the protistan 'rare biosphere'

The use of cultivation-independent approaches to map microbial diversity, including recent work published in BMC Biology , has now shown that protists, like bacteria/archaea, are much more diverse than had been re...

Scribble at the crossroads

Although proteins involved in determining apical-basal cell polarity have been directly linked to tumorigenesis, their precise roles in this process remain unclear. A recent report in BMC Biology clarifies the si...

Q&A: Quantitative approaches to planar polarity and tissue organization

Gene regulation, evolvability and the limits of genomics, the transcriptome of human monocyte subsets begins to emerge.

Human monocytes can be divided into subsets according to their expression or lack of the cell-surface antigen CD16. In papers published recently in the Journal of Proteome Research and in BMC Genomics , two groups...

Chromatin 'programming' by sequence - is there more to the nucleosome code than %GC?

The role of genomic sequence in directing the packaging of eukaryotic genomes into chromatin has been the subject of considerable recent debate. A new paper from Tillo and Hughes shows that the intrinsic therm...

Fishing for the signals that pattern the face

Zebrafish are a powerful system for studying the early embryonic events that form the skull and face, as a model for human craniofacial birth defects such as cleft palate. Signaling pathways that pattern the p...

Coordinated gene expression by post-transcriptional regulons in African trypanosomes

The regulation of gene expression in trypanosomes is unique. In the absence of transcriptional control at the level of initiation, a subset of Trypanosoma brucei genes form post-transcriptional regulons in which ...

Promoter architecture and the evolvability of gene expression

Evolutionary changes in gene expression are a main driver of phenotypic evolution. In yeast, genes that have rapidly diverged in expression are associated with particular promoter features, including the prese...

Adaptations of proteins to cellular and subcellular pH

Bioinformatics-based searches for correlations between subcellular localization and pI or charge distribution of proteins have failed to detect meaningful correlations. Recent work published in BMC Biology finds ...

TBP2 is a general transcription factor specialized for female germ cells

The complexity of the core promoter transcription machinery has emerged as an additional level of transcription regulation that is used during vertebrate development. Recent studies, including one published in BM...

Generalized immune activation as a direct result of activated CD4 + T cell killing

In addition to progressive CD4 + T cell immune deficiency, HIV infection is characterized by generalized immune activation, thought to arise from increased microbial exposure resulting from diminishing immunity.

Life and death as a T lymphocyte: from immune protection to HIV pathogenesis

Detailed analysis of T cell dynamics in humans is challenging and mouse models can be important tools for characterizing T cell dynamic processes. In a paper just published in Journal of Biology , Marques et al . s...

What we still don't know about AIDS

The gene complement of the ancestral bilaterian - was urbilateria a monster.

Expressed sequence tag analyses of the annelid Pomatoceros lamarckii , recently published in BMC Evolutionary Biology , are consistent with less extensive gene loss in the Lophotrochozoa than in the Ecdysozoa, but ...

The nature of cell-cycle checkpoints: facts and fallacies

The concept of checkpoint controls revolutionized our understanding of the cell cycle. Here we revisit the defining features of checkpoints and argue that failure to properly appreciate the concept is leading ...

An expanded evolutionary role for flower symmetry genes

CYCLOIDEA (CYC) -like TCP genes are critical for flower developmental patterning. Exciting recent breakthroughs, including a study by Song et al. published in BMC Evolutionary Biology , demonstrate that CYC -like ge...

Mechanisms of ubiquitin transfer by the anaphase-promoting complex

The anaphase-promoting complex (APC) is a ubiquitin-protein ligase required for the completion of mitosis in all eukaryotes. Recent mechanistic studies reveal how this remarkable enzyme combines specificity in...

Targeting TNF-α for cancer therapy

As the tumor vasculature is a key element of the tumor stroma, angiogenesis is the target of many cancer therapies. Recent work published in BMC Cell Biology describes a fusion protein that combines a peptide pre...

TEs or not TEs? That is the evolutionary question

Transposable elements (TEs) have contributed a wide range of functional sequences to their host genomes. A recent paper in BMC Molecular Biology discusses the creation of new transcripts by transposable element i...

Molecular machines or pleiomorphic ensembles: signaling complexes revisited

Signaling complexes typically consist of highly dynamic molecular ensembles that are challenging to study and to describe accurately. Conventional mechanical descriptions misrepresent this reality and can be a...

Ockham's broom: A new series

Adaptation by introgression.

Both selective and random processes can affect the outcome of natural hybridization. A recent analysis in BMC Evolutionary Biology of natural hybridization between an introduced and a native salamander reveals th...

Journal of Biology

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Individual variation in life-history timing: synchronous presence, asynchronous events and phenological compensation in a wild mammal.

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Invasibility of a North American soil ecosystem to amphibian-killing fungal pathogens

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Single and combined exposure to ‘bee safe’ pesticides alter behaviour and offspring production in a ground-nesting solitary bee ( Xenoglossa pruinosa )

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Proceedings b.

Proceedings B is the Royal Society’s flagship biological research journal, accepting original articles and reviews of outstanding scientific importance and broad general interest. The main criteria for acceptance are that a study is novel, and has general significance to biologists. Articles published cover a wide range of areas within the biological sciences, many have relevance.

Chronotype variation drives night-time sentinel-like behaviour in hunter–gatherers

• David R. Samson ,
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Attention deficits linked with proclivity to explore while foraging

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Poorly differentiated XX/XY sex chromosomes are widely shared across skink radiation

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Field study suggests that sex determination in sea lamprey is directly influenced by larval growth rate

• Nicholas S. Johnson ,
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Biological identifications through DNA barcodes

• Paul D. N. Hebert ,
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Importance of pollinators in changing landscapes for world crops

• Alexandra-Maria Klein ,
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VII. Note on regression and inheritance in the case of two parents

• Karl Pearson  and
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Barcoding animal life: cytochrome c oxidase subunit 1 divergences among closely related species

• Paul D.N. Hebert ,
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A global analysis of the impacts of urbanization on bird and plant diversity reveals key anthropogenic drivers

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• Rearrangement of 3D genome organization in breast cancer epithelial - mesenchymal transition and metastasis organotropism Priyojit Das , Rebeca San Martin , Tian Hong , Rachel Patton McCord bioRxiv 2024.08.23.609227; doi: https://doi.org/10.1101/2024.08.23.609227
• Predicting the alternative conformation of a known protein structure based on the distance map of AlphaFold2 Jiaxuan Li , Zefeng Zhu , Chen Song bioRxiv 2024.06.09.598121; doi: https://doi.org/10.1101/2024.06.09.598121
• Serpina1e mediates the exercise-induced enhancement of hippocampal memory Hyunyoung Kim , Sanghee Shin , Jong-Seo Kim , Hyungju Park , Jeongho Han bioRxiv 2024.08.11.607526; doi: https://doi.org/10.1101/2024.08.11.607526
• Sensitive and modular amplicon sequencing of Plasmodium falciparum diversity and resistance for research and public health Andrés Aranda-Díaz , Eric Neubauer Vickers , Kathryn Murie , Brian Palmer , Nicholas Hathaway , Inna Gerlovina , Simone Boene , Manuel Garcia-Ulloa , Pau Cisteró , Thomas Katairo , Francis Ddumba Semakuba , Bienvenu Nsengimaana , Hazel Gwarinda , Carla García-Fernández , Clemente Da Silva , Debayan Datta , Shahiid Kiyaga , Innocent Wiringilimaana , Sindew Mekasha Fekele , Jonathan B. Parr , Melissa Conrad , Jaishree Raman , Stephen Tukwasibwe , Isaac Ssewanyana , Eduard Rovira-Vallbona , Cristina M. Tato , Jessica Briggs , Alfredo Mayor , Bryan Greenhouse bioRxiv 2024.08.22.609145; doi: https://doi.org/10.1101/2024.08.22.609145
• Scene context and attention independently facilitate MEG decoding of object category Olga Leticevscaia , Talia Brandman , Marius V. Peelen bioRxiv 2024.06.30.601374; doi: https://doi.org/10.1101/2024.06.30.601374
• A CRISPR-Nonhomologous End-Joining-based strategy for rapid and efficient gene disruption in Mycobacterium abscessus Sanshan Zeng , Yanan Ju , Md Shah Alam , Ziwen Lu , H.M. Adnan Hameed , Lijie Li , Xirong Tian , Cuiting Fang , Xiange Fang , Jie Ding , Xinyue Wang , Jinxing Hu , Shuai Wang , Tianyu Zhang bioRxiv 2024.01.29.577284; doi: https://doi.org/10.1101/2024.01.29.577284
• Separation of telomere protection from length regulation by two different point mutations at amino acid 492 of RTEL1 Riham Smoom , Catherine Lee May , Dan Lichtental , Emmanuel Skordalakes , Klaus H Kaestner , Yehuda Tzfati bioRxiv 2024.02.26.582005; doi: https://doi.org/10.1101/2024.02.26.582005
• Simulating the growth of TAF15 inclusions in neuron soma Andrey V Kuznetsov bioRxiv 2024.07.14.603428; doi: https://doi.org/10.1101/2024.07.14.603428
• Shared and distinct neural signatures of feature and spatial attention Anmin Yang , Jinhua Tian , Wenbo Wang , Jia Liu , Liqin Zhou , Ke Zhou bioRxiv 2023.08.20.554014; doi: https://doi.org/10.1101/2023.08.20.554014
• Monitoring DNA double strand break repair in Saccharomyces cerevisiae at high throughput and high resolution Yael Shalev Ezra , Alon Saguy , Gaia Levin , Lucien E. Weiss , Onit Alalouf , Yoav Shechtman bioRxiv 2024.08.23.609327; doi: https://doi.org/10.1101/2024.08.23.609327

What We Publish

Plos biology article types.

PLOS Biology considers works of exceptional significance, originality, and relevance in all areas of biological science, including both primary research, meta-analyses and Magazine articles . Our publication options are outlined below.

Research-based content

PLOS Biology publishes seven different types of research reports. All research articles are compatible with our easy, format-free submission process, and offer options for preprints, published peer review history, and publishing uncorrected proofs. Most, with rare exception, are also protected by our scooping policy , ensuring that your research will not be rejected for novelty within six-months of the publication of a complementary or confirmatory research publication. We evaluate all research based on the important questions it answers and its potential to impact an international scientific community as well as educators, policy makers, patient advocacy groups, and society more broadly.

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Meta-Research Articles

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Magazine articles

Our magazine section features non-research articles that cover topical issues and are accessible to a broad audience while remaining scientifically rigorous. Magazine readers include scientists, scientific educators, students, physicians, patients, and the interested public. There is no publication fee for magazine articles.

Our magazine section is divided into Front Matter and In-depth Analysis subsections. Front Matter articles are short, focussed and provide opinion on topical issues, community resources or commentary on PLOS Biology articles. In-depth Analyses are long-form articles providing forward-looking analysis of a given topic, highlighting gaps in our current understanding or putting forward community recommendations or guidelines. We do not publish traditional review articles.

Most magazine articles are comissioned by the editors, but we do publish some unsolicted content. If you have a suggestion for any of our current magazine categories, we will consider the idea. Before finalizing the piece, we recommend that you discuss it with us by sending a presubmission enquiry via email to [email protected] . Before submitting, consult our General Guidelines for Magazine Submissions , as well as the guidelines for the specific article type you are interested in.

If you have any questions about submitting an idea or article for consideration in the magazine section, email our editorial team at  [email protected] .

General Guidelines for Magazine Submissions

Magazine content is intended for the broader biological community including students, scientists, and the educated general reader. It is therefore important that the writing style be concise, clear and accessible. Avoid specialist terms, abbreviations and jargon. Editors will make suggestions to make your piece more accessible, as well as cuts or additions that could strengthen the article. Our aim is to make the editorial process rigorous and consistent, but not intrusive or overbearing.

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Front Matter

Editorials are written in-house by members of the editorial staff or by members of the Editorial Board.

Perspectives

The Perspectives section provides experts with a forum to comment on topical or controversial issues of broad interest. They address controversial issues or those at the interface between science and policy or science and society; present a policy position aimed at influencing policy decisions; examine and make recommendations on scientific and publishing practices. These are meant to be short, opinionated, Op-ed type of pieces.

The ideal Perspective conveys a sense of urgency. Some things to think about would be:

• Is this topic of immediate concern?
• Is the topic relevant to a pressing regional or global issue
• Does the piece offer a novel point of view on a scientific or policy issue, or on topical events?
• Does is make specific, practical proposals to address the issue?

Controversial articles are welcomed, but the text should acknowledge that a position is in fact controversial and provide readers with enough background on the differing views.

Our Perspectives aim to engage a broad and diverse audience—it is therefore important to ensure that they are written in an accessible, persuasive, and stimulating style that appeals to both specialists and non-specialist readers. Perspectives are usually assessed in-house with our Editorial Board, but we reserve the right to peer-review them if needed. Commissioning does not guarantee publication. Editors work closely with authors to ensure that articles are written in an engaging, succinct, yet rigorous manner.

Guidelines for a Perspective

Example Perspectives

Lowe-Power T, Dyson L, Polter AM (2021) A generation of junior faculty is at risk from the impacts of COVID-19. PLoS Biol 19(5): e3001266. https://doi.org/10.1371/journal.pbio.3001266

Bourne PE (2021) Is “bioinformatics” dead? PLoS Biol 19(3): e3001165. https://doi.org/10.1371/journal.pbio.3001165

Primers provide concise and accessible context to a PLOS Biology research article of broad and current interest. Primers are commissioned and published alongside a research article that would benefit from additional context and/or explanation.

Above all, Primers should demystify an area of biology, avoid and/or explain technical jargon and provide critical and forward-thinking analysis about how the research article fits into the current state of the field and its future. A good Primer will briefly discuss (but not exhaustively review) what we know and what questions we have yet to answer for a particular field. It will then introduce the new findings and describe in roughly three paragraphs the advance represented in the related research article, highlighting its significance, not only for the discipline in question, but across disciplines. The Primer should then explain what the findings suggest in terms of next steps: what new avenues of investigation are opened, what new experiments can be tried, what new ideas can now be tested going forward? Ideally, Primers also offer insight into what big questions are likely to remain unanswered for many years (for whatever reasons).

We encourage the use of a figure to illustrate key concepts/mechanism/conclusions in an informative, easy-to-understand manner.

Primers are usually assessed by our Editorial Board, but we reserve the right to peer-review externally if needed. Commissioning does not guarantee publication. Editors work closely with authors to ensure that articles are written in an engaging, succinct, yet rigorous manner.

Guidelines for a Primer

Example Primer

Kazanova A, Rudd CE (2021) Programmed cell death 1 ligand (PD-L1) on T cells generates Treg suppression from memory. PLoS Biol 19(5): e3001272. https://doi.org/10.1371/journal.pbio.3001272

Guizetti J, Frischknecht F (2021) Apicomplexans: A conoid ring unites them all. PLoS Biol 19(3): e3001105. https://doi.org/10.1371/journal.pbio.3001105

Community Pages

Community Pages provide individuals, networks and organizations with the opportunity to highlight resources, tools, or initiatives of benefit to the scientific community and beyond (including science education and public engagement in science). All resources or tools, and the outputs of initiatives must be open and accessible to all.

Contributors must resist the temptation of self-promotion and instead focus on conveying information to a diverse audience.Community Pages should be written in a succinct, accessible, semi-journalistic style that captures the interest of both specialists and non-specialist readers. We encourage the use of 1-2 figures to illustrate key concepts in an informative, easy to grasp manner; or the use of text boxes for background, self-contained information.

Community Pages are peer-reviewed and commissioning does not guarantee publication. Editors work closely with authors to ensure that articles are written in an engaging, succinct, yet rigorous manner.

Guidelines for a Community Page

Example Community Pages

Weissgerber TL (2021) Training early career researchers to use meta-research to improve science: A participant-guided “learn by doing” approach. PLoS Biol 19(2): e3001073. https://doi.org/10.1371/journal.pbio.3001073

McCullagh EA, Nowak K, Pogoriler A, Metcalf JL, Zaringhalam M, Zelikova TJ (2019) Request a woman scientist: A database for diversifying the public face of science. PLoS Biol 17 (4): e3000212. https://doi.org/10.1371/journal. pbio.3000212

Formal Comments

Formal Comments are intended to provide a formal outlet for the discussion and interpretation of research findings associated with specific articles published in PLOS Biology . They are designed to ensure that readers obtain a balanced view of a scientific or meta-scientific/policy question, especially in areas of debate/controversy. Formal Comments are peer-reviewed and indexed in PubMed.

Formal Comments must be coherent, concise, and well-argued, and are subject to the PLOS Biology criteria for publication . Editors will, as a matter of course, invite the authors of the original article to submit a response to the Formal Comment. Any revisions (of the Formal Comment or the response) will be shared with the authors of the associated comment.

Guidelines for Formal Comments

Example Formal Comment

Rees WE, Wackernagel M (2013) The Shoe Fits, but the Footprint is Larger than Earth. PLoS Biol 11(11): e1001701. https://doi.org/10.1371/journal.pbio.1001701​ ​

Example Formal Comment - Response

Blomqvist L, Brook BW, Ellis EC, Kareiva PM, Nordhaus T, Shellenberger M (2013) The Ecological Footprint Remains a Misleading Metric of Global Sustainability. PLoS Biol 11(11): e1001702. https://doi.org/10.1371/journal.pbio.1001702

In-Depth Analysis

Essays are opinionated articles on a topic of interest to scientists and to a broader audience, including the general public. Unlike traditional review articles, which include a comprehensive account of a field, Essays take an imaginative approach to a provocative question, with an engaging but rigorous investigation of the problem. We encourage authors of Essays to select the most representative references to convey their points and avoid exhaustively covering the relevant literature.

The remit of Essays is very broad. They might:

• take stock of progress in a field from a personal point of view
• explore the implications of recent advances that promise to have broad-ranging consequences on a field
• comment on a topical or controversial area of research
• discuss key ideas or educational strategies to enhance understanding of fundamental biological questions
• offer historical/philosophical reflections on contemporary biology
• analyze scientific issues with policy implications

Our Essays aim to engage a broad and diverse audience—it is therefore important to ensure that they are written in an accessible, semi-journalistic style that captures the interest of both specialists and non-specialist readers. We encourage the use of figures to illustrate key concepts in an informative, easy to grasp manner; as well as the use of text boxes for background, self-contained information.

Essays are peer-reviewed and commissioning does not guarantee publication.

Guidelines for an Essay

Example Essays

Rees T, Bosch T, Douglas AE (2018) How the microbiome challenges our concept of self. PLoS Biol 16(2): e2005358. https://doi.org/10.1371/journal.pbio.2005358 Konig C, Weigelt P, Schrader J, Taylor A, Kattge J, Kreft H (2019) Biodiversity data integration—the significance of data resolution and domain. PLoS Biol 17(3): e3000183. https://doi.org/10.1371/journal.pbio.3000183

Unsolved Mysteries

Unsolved Mysteries discuss a topic of biological or medical importance that is poorly understood and in need of research attention—e.g., an unexplored or challenging question, an emerging opportunity, or a recent puzzling phenomenon. The articles are intended to stimulate the scientific community to think about future research possibilities outside their areas of expertise. The articles should be aimed at a very broad audience of biologists—an unsolved mystery in a neuroscience topic should be accessible to ecologists and biophysicists, for example.   The article should include a discussion of the basic science relevant to the topic, why it is biologically or medically important, what work has been done on the topic (if any), major challenges to understanding the question at hand, competing hypotheses, and what advances would be necessary to shed light on the problem. Ideally the structure of the article should reflect the mystery (e.g. subsections with questions as headings). The article should end with a discussion of possible means to a solution

Unsolved Mysteries are peer-reviewed and commissioning does not guarantee publication. Editors work closely with authors to ensure that articles are written in an engaging, succinct, yet rigorous manner.

Guidelines for an Unsolved Mystery

Example Unsolved Mysteries

Margolis L, Sadovsky Y (2019) The biology of extracellular vesicles: The known unknowns. PLoS Biol 17(7): e3000363. https://doi.org/10.1371/journal.pbio.3000363

Vogels CBF, Ru¨ckert C, Cavany SM, Perkins TA, Ebel GD, Grubaugh ND (2019) Arbovirus coinfection and co-transmission: A neglected public health concern? PLoS Biol 17(1): e3000130. https://doi.org/10.1371/journal.pbio.3000130

Consensus View

Consensus View articles present a comprehensive analysis by an independent and usually multidisciplinary panel of experts who make specific recommendations on important scientific, publishing or policy issues.

Consensus Views are peer-reviewed and commissioning does not guarantee publication. Editors work closely with authors to ensure that articles are written in an engaging, succinct, yet rigorous manner.

Guidelines for a Consensus View

Example Consensus View

Brown TM, Brainard GC, Cajochen C, Czeisler CA, Hanifin JP, Lockley SW, et al. (2022) Recommendations for daytime, evening, and nighttime indoor light exposure to best support physiology, sleep, and wakefulness in healthy adults. PLoS Biol 20(3): e3001571. https://doi.org/10.1371/journal.pbio.3001571

Kent BA, Holman C, Amoako E, Antonietti A, Azam JM, Ballhausen H, et al. (2022) Recommendations for empowering early career researchers to improve research culture and practice. PLoS Biol 20(7): e3001680. https://doi.org/10.1371/journal.pbio.3001680

Vimercati G, Probert AF, Volery L, Bernardo-Madrid R, Bertolino S, Céspedes V, et al. (2022) The EICAT+ framework enables classification of positive impacts of alien taxa on native biodiversity. PLoS Biol 20(8): e3001729. https://doi.org/10.1371/journal.pbio.3001729

Retired Article Types

Book Review/Science in the Media. These short reviews critiqued books, films, plays, and other media that deal with some aspect of the biological sciences.  

• Education. Although we no longer publish Education articles as a separate article type, we continue publishing them as part of the Education Series. The format selected (Essay, Perspective, or Community Page) depends on the aims of each article.
• Historical and Philosophical Perspectives. The Historical and Philosophical Perspectives section provided professional historians and philosophers of science with a forum to reflect on topical issues in contemporary biology.
• Obituaries.
• Open Highlights. Written in-house by members of the editorial staff, Open Highlights used recent publication as keystones around which to nucleate a short synthesis of several related research articles from PLOS and the wider Open Access corpus.
• Research Matters. Brief pieces by leading scientists explaining why the research carried out in their laboratories - and those of their collaborators and their colleagues - matters to lay audiences. 
• Series. Series were recurrent themed articles on specific topics, including Education, Public Engagement with Science, Cool Tools, and Where Next?
• Synopses. Selected PLOS Biology research articles are accompanied by a synopsis written for a general audience to provide non-experts with insight into the significance of the published work. They are commissioned only.

Post-Publication Notices

PLOS publishes Editorial Notes, Corrections, Expressions of Concern, and Retraction notices, as needed, to address issues that arise after a PLOS article has been published.

Biological Research

Special series on Microbial Interactions

The nine articles of this special issue of  Biological Research  address biochemical and genetic determinants of microbial response and tolerance to stressors in different biological models and environmental contexts. Individual articles provide a broad exploration of our current knowledge of response to stressors, with a special emphasis on metal metabolism and toxic compounds.

Special series on Antarctic Research

This special issue on Antarctic research in Biological Research comprises of recent studies, related to the discovery of several new enzymes and biotechnological applications that allow to expand the knowledge of Antarctic organisms and their potential applications.

• Most accessed

Inhibition of forward and reverse transport of Ca 2+ via Na + /Ca 2+ exchangers (NCX) prevents sperm capacitation

Authors: Marc Yeste, Adeel Ahmad, Estel Viñolas, Sandra Recuero, Sergi Bonet and Elisabeth Pinart

Selective disruption of synaptic NMDA receptors of the hippocampal trisynaptic circuit in Aβ pathology

Authors: Rocio Alfaro-Ruiz, Alejandro Martín-Belmonte, Carolina Aguado, Ana Esther Moreno-Martínez, Yugo Fukazawa and Rafael Luján

Placental growth factor mediates pathological uterine angiogenesis by activating the NFAT5-SGK1 signaling axis in the endometrium: implications for preeclampsia development

Authors: Janet P. Raja Xavier, Toshiyuki Okumura, Melina Apweiler, Nirzari A. Chacko, Yogesh Singh, Sara Y Brucker, Satoru Takeda, Florian Lang and Madhuri S Salker

Dissecting reactive astrocyte responses: lineage tracing and morphology-based clustering

Authors: Lina M. Delgado-García, Ana C. Ojalvo-Sanz, Thabatta K. E. Nakamura, Eduardo Martín-López, Marimelia Porcionatto and Laura Lopez-Mascaraque

Neuronal repair after spinal cord injury by in vivo astrocyte reprogramming mediated by the overexpression of NeuroD1 and Neurogenin-2

Authors: Zuliyaer Talifu, Chunjia Zhang, Xin Xu, Yunzhu Pan, Han Ke, Zehui Li, Wubo Liu, Huayong Du, Xiaoxin Wang, Feng Gao, Degang Yang, Yingli Jing, Yan Yu, Liangjie Du and Jianjun Li

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Awareness and current knowledge of breast cancer

Authors: Muhammad Akram, Mehwish Iqbal, Muhammad Daniyal and Asmat Ullah Khan

Stress and defense responses in plant secondary metabolites production

Authors: Tasiu Isah

Fate of nitrogen in agriculture and environment: agronomic, eco-physiological and molecular approaches to improve nitrogen use efficiency

Authors: Muhammad Anas, Fen Liao, Krishan K. Verma, Muhammad Aqeel Sarwar, Aamir Mahmood, Zhong-Liang Chen, Qiang Li, Xu-Peng Zeng, Yang Liu and Yang-Rui Li

Coping with drought: stress and adaptive mechanisms, and management through cultural and molecular alternatives in cotton as vital constituents for plant stress resilience and fitness

Authors: Aziz Khan, Xudong Pan, Ullah Najeeb, Daniel Kean Yuen Tan, Shah Fahad, Rizwan Zahoor and Honghai Luo

Biotechnological applications of archaeal enzymes from extreme environments

Authors: Ma. Ángeles Cabrera and Jenny M. Blamey

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Archival content.

Biological Research , formerly Archives of Experimental Medicine and Biology , was founded in 1964 and transferred to BioMed Central in 2014. An electronic archive of articles published between 1999 and 2013 can be found in the SciELO database.

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To find more information on research funders and institutions worldwide that fund open access article-processing charges (APCs) visit this page .

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Editor’s profile

Manuel J Santos, Editor-in-Chief

Dr Santos is an Associate Professor in the Faculty of Biological Sciences and Medicine at the Pontificia Catholic University of Chile.

Dr Santos received his MD from the University of Chile and his PhD in Cell and Molecular Biology from the Pontificia Catholic University of Chile. He majored in Medical Genetics at The John Hopkins University (USA) and The René Descartes University of Paris (France), and held a post doctorate position in Cell Biology and Genetics at the Rockefeller University (USA).

His research has focused on the biogenesis of cellular organelles, particularly peroxisomes. A pioneer in this field, his research lead him to discover a new type of human genetic disease, the peroxisomal biogenesis disorders, which include Zellweger Syndrome. More recently his research has centered on studying the role of peroxisomes in Alzheimer’s disease, and he also works in the field of bioethics.

Over the span of his career, Dr Santos has published more than 70 peer reviewed papers and been the President of the Society of Biology of Chile, the Genetics Society of Chile and the Bioethical Society of Chile.

About the Society

The Chilean Biology Society (Sociedad de Biología de Chile), previously the Biological Society of Santiago, was founded in late 1928 as a subsidiary of The Societé de Biologie of Paris, France. For several years the summaries of its communications were published in Comps Rendú of the Societé de Biologie du Paris. The Society is currently a member of the International Union of Biological Sciences (IUBS).

The Chilean Biology Society promotes theoretical and experimental studies and research leading to advancement in and dissemination of the biological sciences for the benefit of the community. To accomplish this, the Society organizes periodic scientific meetings in which scientists communicate, comment and discuss research carried out in Chilean or foreign research laboratories. In addition, relations and cooperation with similar domestic and foreign institutions are stimulated, and communication by all appropriate means of biological research carried out in Chile. 

Members of the Society will receive a discount on Biological Research 's article-processing charge when they provide a discount code (which members can obtain by emailing the Society) during the submission process.  The discounted article-processing charge for Society members is £1150 in 2023.

The Society also publishes Revista Chilena de Historia Natural ( Chilean Journal of Natural History, founded in 1897).

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Citation Impact 2023 Journal Impact Factor: 4.3 5-year Journal Impact Factor: 6.6 Source Normalized Impact per Paper (SNIP): 1.354 SCImago Journal Rank (SJR): 1.300 Speed 2023 Submission to first editorial decision (median days): 22 Submission to acceptance (median days): 155 Usage 2023 Downloads: 489,080 Altmetric mentions: 731

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Collection  15 July 2019

Top 50: Life and Biological Sciences

We are pleased to share with you the 50 most read  Nature Communications life and biological sciences articles* published in 2018. Featuring authors from around the world, these papers highlight valuable research from an international community.

Browse all Top 50 subject area collections here .

*Based on data from  altmetric.com , covering January-December 2018

Embryos and embryonic stem cells from the white rhinoceros

The Southern (SWR) and Northern (NWR) are two subspecies of the White Rhinoceros with the NWR being almost extinct. Here, using assisted reproduction technology, the authors produce and cryopreserve SWR purebred and NWR-SWR hybrid embryos developed to the blastocyst stage, and also generate embryonic stem cell lines, in an attempt to save genes of the NWR.

• Thomas B. Hildebrandt
• Robert Hermes
• Cesare Galli

Scutoids are a geometrical solution to three-dimensional packing of epithelia

Cell arrangement in the plane of epithelia is well studied, but its three-dimensional packing is largely unknown. Here the authors model curved epithelia and predict that cells adopt a geometrical shape they call “scutoid”, resulting in different apical and basal neighbours, and confirm the presence of scutoids in curved tissues.

• Pedro Gómez-Gálvez
• Pablo Vicente-Munuera
• Luis M. Escudero

Similar neural responses predict friendship

Though we are often friends with people similar to ourselves, it is unclear if neural responses to perceptual stimuli are also similar. Here, authors show that the similarity of neural responses evoked by a range of videos was highest for close friends and decreased with increasing social distance.

• Carolyn Parkinson
• Adam M. Kleinbaum
• Thalia Wheatley

Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function

Cognitive function is associated with health and important life outcomes. Here, the authors perform a genome-wide association study for general cognitive function in 300,486 individuals and identify genetic loci that implicate neural and cell developmental pathways in this trait.

• Gail Davies
• Ian J. Deary

Wing bone geometry reveals active flight in Archaeopteryx

Archaeopteryx had a mix of traits seen in non-flying dinosaurs and flying birds, leading to debate on whether it had powered flight. Here, Voeten et al. compare wing bone architecture from Archaeopteryx and both flying and non-flying archosaurs, supporting that Archaeopteryx had powered flight but with a different stroke than that of modern birds.

• Dennis F. A. E. Voeten
• Sophie Sanchez

Hunting regulation favors slow life histories in a large carnivore

Hunting and harvesting are generally expected to select for faster life histories in the exploited species. Here, the authors analyse data from a hunted population of brown bears in Sweden and show that regulations protecting females with dependent young lead hunting to favor prolonged maternal care.

• Joanie Van de Walle
• Gabriel Pigeon
• Fanie Pelletier

Closed-loop stimulation of temporal cortex rescues functional networks and improves memory

Memory lapses can occur due to ineffective encoding, but it is unclear if targeted brain stimulation can improve memory performance. Here, authors use a closed-loop system to decode and stimulate periods of ineffective encoding, showing that stimulation of lateral temporal cortex can enhance memory.

• Youssef Ezzyat
• Paul A. Wanda
• Michael J. Kahana

Genome-wide study of hair colour in UK Biobank explains most of the SNP heritability

Natural hair colour in Europeans is a complex genetic trait. Here, the authors carry out a genome-wide association study using UK BioBank data, suggesting that in combination with pigmentation genes, variants with roles in hair texture and growth can affect hair colouration or our perception of it.

• Michael D. Morgan
• Erola Pairo-Castineira
• Ian J. Jackson

Diffusion markers of dendritic density and arborization in gray matter predict differences in intelligence

Previous studies suggest that individual differences in intelligence correlate with circuit complexity and dendritic arborization in the brain. Here the authors use NODDI, a diffusion MRI technique, to confirm that neurite density and arborization are inversely related to measures of intelligence.

• Christoph Fraenz
• Rex E. Jung

Industrial brewing yeast engineered for the production of primary flavor determinants in hopped beer

Production of aromatic monoterpene molecules in hop flowers is affected by genetic, environmental, and processing factors. Here, the authors engineer brewer’s yeast for the production of linalool and geraniol, and show pilot-scale beer produced by engineered strains reconstitutes some qualities of hop flavor.

• Charles M. Denby
• Rachel A. Li
• Jay D. Keasling

A bony-crested Jurassic dinosaur with evidence of iridescent plumage highlights complexity in early paravian evolution

A number of paravian dinosaurs have been described from the Jurassic Yanliao biota, but these have tended to be morphologically similar to Archaeopteryx . Here, Hu. describe the new paravian dinosaur, Caihong juji gen. et sp. nov., which possesses a suite of unusual skeletal and feather characteristics.

• Julia A. Clarke

Single-dose testosterone administration increases men’s preference for status goods

Testosterone is believed to be involved in social rank-related behavior. Here, the authors show that one dose of testosterone increases men’s preference for “high status” goods and brands, suggesting a role for testosterone in modern consumer behavior in men.

• H. Plassmann

Development of an oral once-weekly drug delivery system for HIV antiretroviral therapy

Poor adherence to daily antiretrovirals can significantly affect treatment efficacy, but oral long-acting antiretrovirals are currently lacking. Here, the authors develop a once-weekly oral dosage form for anti-HIV drugs, assess its pharmacokinetics in pigs, and model its impact on viral resistance and disease epidemics.

• Ameya R. Kirtane
• Omar Abouzid
• Giovanni Traverso

Smartphone app for non-invasive detection of anemia using only patient-sourced photos

Anemia has a global prevalence of over 2 billion people and is diagnosed via blood-based laboratory test. Here the authors describe a smartphone app that can estimate hemoglobin levels and detect anemia by analyzing pictures of fingernail beds taken with a smartphone and without the need of any external equipment.

• Robert G. Mannino
• David R. Myers
• Wilbur A. Lam

Sleep loss causes social withdrawal and loneliness

Loneliness markedly increases mortality and morbidity, yet the factors triggering loneliness remain largely unknown. This study shows that sleep loss leads to a neurobehavioral phenotype of human social separation and loneliness, one that is transmittable to non-sleep-deprived individuals.

• Eti Ben Simon
• Matthew P. Walker

Gender differences in individual variation in academic grades fail to fit expected patterns for STEM

Men are over-represented in the STEM (science, technology, engineering and mathematics) workforce even though girls outperform boys in these subjects at school. Here, the authors cast doubt on one leading explanation for this paradox, the ‘variability hypothesis’.

• R. E. O’Dea
• S. Nakagawa

The spread of low-credibility content by social bots

Online misinformation is a threat to a well-informed electorate and undermines democracy. Here, the authors analyse the spread of articles on Twitter, find that bots play a major role in the spread of low-credibility content and suggest control measures for limiting the spread of misinformation.

• Chengcheng Shao
• Giovanni Luca Ciampaglia
• Filippo Menczer

Tailed giant Tupanvirus possesses the most complete translational apparatus of the known virosphere

Giant viruses are the largest viruses of the known virosphere and their genetic analysis can provide insights into virus evolution. Here, the authors discover Tupanvirus, a unique giant virus that has an unusually long tail and contains the largest translational apparatus of the known virosphere.

• Jônatas Abrahão
• Lorena Silva
• Bernard La Scola

Genome-wide meta-analysis implicates mediators of hair follicle development and morphogenesis in risk for severe acne

Acne vulgaris is a chronic inflammation of the skin, the genetic basis of which is incompletely understood. Here, Petridis et al. perform GWAS and meta-analysis for acne in 26,722 individuals and identify 12 novel risk loci that implicate structure and maintenance of the skin in severe acne risk.

• Christos Petridis
• Alexander A. Navarini
• Michael A. Simpson

Patterns of island change and persistence offer alternate adaptation pathways for atoll nations

Inundation and erosion could make many atoll islands uninhabitable over the next century. Here the authors present an analysis of change in the atoll nation of Tuvalu that shows a 2.9% increase in land area over the past four decades, with 74% of islands increasing in size, despite rising sea levels.

• Paul S. Kench
• Murray R. Ford
• Susan D. Owen

Blood–brain barrier opening in Alzheimer’s disease using MR-guided focused ultrasound

Magnetic resonance-guided focused ultrasound with injected microbubbles has been used to temporarily open the blood–brain barrier (BBB) in animal models of Alzheimer's disease (AD). Here, the authors use this technology to non-invasively open the BBB in 5 patients with mild-to-moderate AD in a phase I trial, and show that the procedure is safe.

• Nir Lipsman
• Sandra E. Black

Cultural hitchhiking and competition between patrilineal kin groups explain the post-Neolithic Y-chromosome bottleneck

A population bottleneck 5000-7000 years ago in human males, but not females, has been inferred across several African, European and Asian populations. Here, Zeng and colleagues synthesize theory and data to suggest that competition among patrilineal kin groups produced the bottleneck pattern.

• Tian Chen Zeng
• Marcus W. Feldman

Caffeine-inducible gene switches controlling experimental diabetes

Control of transgene expression should ideally be easy and with minimal side effects. Here the authors present a synthetic biology-based approach in which the caffeine in coffee regulates a genetic circuit controlling glucagon-like peptide 1 expression in diabetic mice.

• Daniel Bojar
• Leo Scheller
• Martin Fussenegger

Assembly of 913 microbial genomes from metagenomic sequencing of the cow rumen

Microbes in the cow rumen are crucial for the breakdown of plant material. Here, Stewart et al. assemble over 900 bacterial and archaeal genomes from the cow rumen microbiome, revealing new species and genes encoding enzymes with potential roles in carbohydrate metabolism.

• Robert D. Stewart
• Marc D. Auffret
• Mick Watson

Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathways

The UK Biobank provides data for three depression-related phenotypes. Here, Howard et al. perform a genome-association study for broad depression, probable major depressive disorder (MDD) and hospital record-coded MDD in up to 322,580 UK Biobank participants which highlights excitatory synaptic pathways.

• David M. Howard
• Mark J. Adams
• Andrew M. McIntosh

Fungal networks shape dynamics of bacterial dispersal and community assembly in cheese rind microbiomes

Interactions with other microbes may inhibit or facilitate the dispersal of bacteria. Here, Zhang et al. use cheese rind microbiomes as a model to show that physical networks created by filamentous fungi can affect the dispersal of motile bacteria and thus shape the diversity of microbial communities.

• Yuanchen Zhang
• Erik K. Kastman
• Benjamin E. Wolfe

Epidemiology is a science of high importance

Epidemiology dates back to the Age of Pericles in 5th Century B.C., but its standing as a ‘true’ science in 21st century is often questioned. This is unexpected, given that epidemiology directly impacts lives and our reliance on it will only increase in a changing world.

A low-gluten diet induces changes in the intestinal microbiome of healthy Danish adults

Gluten-free diets are increasingly common in the general population. Here, the authors report the results of a randomised cross-over trial involving middle-aged, healthy Danish adults, showing evidence that a low-gluten diet leads to gut microbiome changes, possibly due to variations in dietary fibres.

• Lea B. S. Hansen
• Henrik M. Roager
• Oluf Pedersen

In utero nanoparticle delivery for site-specific genome editing

The correction of genetic defects in utero could allow for improved outcomes of gene therapy. Here, the authors demonstrate safe delivery of nanoparticles to fetal mouse tissues, and show that nanoparticles containing peptide nucleic acids to edit the beta-globin gene are effective in a mouse model of beta-thalassemia.

• Adele S. Ricciardi
• Raman Bahal
• W. Mark Saltzman

The effects of death and post-mortem cold ischemia on human tissue transcriptomes

RNA levels in post-mortem tissue can differ greatly from those before death. Studying the effect of post-mortem interval on the transcriptome in 36 human tissues, Ferreira et al. find that the response to death is largely tissue-specific and develop a model to predict time since death based on RNA data.

• Pedro G. Ferreira
• Manuel Muñoz-Aguirre
• Roderic Guigó

Gimap5-dependent inactivation of GSK3β is required for CD4 + T cell homeostasis and prevention of immune pathology

Loss of function GIMAP5 mutation is associated with lymphopenia, but how it mediates T cell homeostasis is unclear. Here the authors study Gimap5 −/− mice and a patient with GIMAP5 deficiency to show how this GTPAse negatively regulates GSK3β activity to prevent DNA damage and cell death.

• Andrew R. Patterson
• Mehari Endale
• Kasper Hoebe

3D virtual reconstruction of the Kebara 2 Neandertal thorax

How different Neandertal morphology was from that of modern humans has been a subject of long debate. Here, the authors develop a 3D virtual reconstruction of the thorax of an adult male Neandertal, showing similar size to modern humans, yet with greater respiratory capacity due to its different shape.

• Asier Gómez-Olivencia
• Alon Barash

Exercise induces new cardiomyocyte generation in the adult mammalian heart

The adult mammalian heart has a limited cardiomyogenic capacity. Here the authors show that intensive exercise leads to a 4.6-fold increase in murine cardiomyocyte proliferation requiring the expression of miR-222, and that exercise induces an extended cardiomyogenic response in the murine heart after infarction.

• Carolin Lerchenmüller
• Anthony Rosenzweig

Double-layered protein nanoparticles induce broad protection against divergent influenza A viruses

Relatively well conserved domains of influenza A virus (IAV) proteins are potential candidates for the development of a universal IAV vaccine. Here, Deng et al . combine two such conserved antigens (M2e and HA stalk) in a double-layered protein nanoparticle and show that it protects against divergent IAVs in mice.

• Teena Mohan
• Bao-Zhong Wang

Intellectual synthesis in mentorship determines success in academic careers

While successful mentors tend to train successful students in academic career, it’s unclear how mentorship determines chances of a success in a trainee. Here, Liénard and colleagues analyze approximately 20 K mentor/trainee relationships in life sciences, and find that success of trainees is associated with an intellectual synthesis between their mentors’ research.

• Jean F. Liénard
• Titipat Achakulvisut
• Stephen V. David

Effective weight control via an implanted self-powered vagus nerve stimulation device

Developing new technologies for the neuromodulation of the vagus nerve can enable therapeutic strategies for body weight control in obese patients. Here, the authors present a battery-free self-powered implantable vagus nerve stimulation system that electrically responds to stomach movement.

• Xudong Wang

Olfactory receptor OR2AT4 regulates human hair growth

Increasing evidence suggest that olfactory receptors can carry additional functions besides olfaction. Here, Chéret et al. show that stimulation of the olfactory receptor ORT2A4 by the odorant Sandalore ® stimulates growth of human scalp hair follicles ex vivo, suggesting the use of ORT2A4-targeting odorants as hair growth-promoting agents.

• Jérémy Chéret
• Marta Bertolini

A diminutive perinate European Enantiornithes reveals an asynchronous ossification pattern in early birds

Fossil juvenile Mesozoic birds are exceedingly rare and can provide important insight into the early evolution of avian development. Here, Knoll et al. describe one of the smallest known Mesozoic avians, which indicates a clade-wide asynchronous pattern of osteogenesis and great variation in basal bird hatchling size and skeletal maturation tempo.

• Fabien Knoll
• Luis M. Chiappe
• Jose Luis Sanz

A diverse suite of pharmaceuticals contaminates stream and riparian food webs

Pharmaceuticals are widespread contaminants in surface waters. Here, Richmond and colleagues show that dozens of pharmaceuticals accumulate in  food chains of streams, including in predators in adjacent terrestrial ecosystems.

• Erinn K. Richmond
• Emma J. Rosi
• Michael R. Grace

An intrinsic association between olfactory identification and spatial memory in humans

Olfaction, the sense of smell, may have originally evolved to aid navigation in space, but there is no direct evidence of a link between olfaction and navigation in humans. Here the authors show that olfaction and spatial memory abilities are correlated and rely on similar brain regions in humans.

• Louisa Dahmani
• Raihaan M. Patel
• Véronique D. Bohbot

Systematic generation of biophysically detailed models for diverse cortical neuron types

Neocortical circuits exhibit diverse cell types that can be difficult to build into computational models. Here the authors employ a genetic algorithm-based parameter optimization to generate multi-compartment Hodgkin-Huxley models for diverse cell types in the Allen Cell Types Database.

• Nathan W. Gouwens
• Anton Arkhipov

Brain and psychological determinants of placebo pill response in chronic pain patients

People vary in the extent to which they feel better after taking an inert, placebo, treatment, but the basis for individual placebo response is unclear. Here, the authors show how brain structural and functional variables, as well as personality traits, predict placebo response in those with chronic back pain.

• Etienne Vachon-Presseau
• Sara E. Berger
• A. Vania Apkarian

Generalized leaky integrate-and-fire models classify multiple neuron types

Simplified neuron models, such as generalized leaky integrate-and-fire (GLIF) models, are extensively used in network modeling. Here the authors systematically generate and compare GLIF models of varying complexity for their ability to classify cell types in the Allen Cell Types Database and faithfully reproduce spike trains.

• Corinne Teeter
• Ramakrishnan Iyer
• Stefan Mihalas

Dietary stearic acid regulates mitochondria in vivo in humans

Dietary fatty acids have different effects on human health. Here, the authors show that ingestion of the fatty acid C18:0, but not of C16:0, rapidly leads to fusion of mitochondria and fatty acid oxidation in humans, possibly explaining the health benefits of C18:0.

• Deniz Senyilmaz-Tiebe
• Daniel H. Pfaff
• Aurelio A. Teleman

Engineering human pluripotent stem cells into a functional skeletal muscle tissue

The generation of functional skeletal muscle tissue from human pluripotent stem cells has not been reported. Here, the authors describe engineering of contractile skeletal muscle bundles in culture, which become vascularized and maintain functionality when transplanted into mice.

• Lingjun Rao
• Nenad Bursac

Topical ferumoxytol nanoparticles disrupt biofilms and prevent tooth decay in vivo via intrinsic catalytic activity

Ferumoxytol is a nanoparticle formulation approved for systemic use to treat iron deficiency. Liu et al. show that topical use of ferumoxytol, in combination with low concentrations of H 2 O 2 , disrupts intractable oral biofilms and prevents tooth decay in vitro and in an animal model.

• Pratap C. Naha

Honey bee Royalactin unlocks conserved pluripotency pathway in mammals

Royal jelly is the queen-maker for the honey bee that also has effects on longevity, fertility, and regeneration in mammals. Here the authors provide evidence that its major protein component Royalactin, and the mammalian structural analog Regina, maintain pluripotency in mouse ESCs by activating a ground-state pluripotency-like gene network.

• Derrick C. Wan
• Stefanie L. Morgan
• Kevin C. Wang

Deoxyribose and deoxysugar derivatives from photoprocessed astrophysical ice analogues and comparison to meteorites

Sugars are known to form from the UV photoprocessing of ices under astrophysical conditions. Here, the authors report the detection of deoxyribose, the sugar of DNA, and other deoxysugars from the UV photoprocessing of H 2 O:CH 3 OH ice mixtures, which are compared with materials from carbonaceous meteorites.

• Michel Nuevo
• George Cooper
• Scott A. Sandford

Genomic evidence of speciation reversal in ravens

Speciation reversal is known mainly from recently diverged lineages that have come into secondary contact following anthropogenic disturbance. Here, Kearns et al. use genomic and phylogenomic analyses to show that the Common Raven ( Corvus corax ) was formed by the ancient fusion of two non-sister lineages of ravens.

• Anna M. Kearns
• Marco Restani
• Kevin E. Omland

Analysis of 3800-year-old Yersinia pestis genomes suggests Bronze Age origin for bubonic plague

Yersinia pestis has caused infections (plague) in humans since the Early Bronze Age (5000 years ago). Here, Spyrou et al. reconstruct Y. pestis genomes from Late Bronze Age individuals, and find genomic evidence compatible with flea-mediated transmission causing bubonic plague.

• Maria A. Spyrou
• Rezeda I. Tukhbatova
• Johannes Krause

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Artificial Intelligence in Biological Sciences

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Artificial intelligence (AI), currently a cutting-edge concept, has the potential to improve the quality of life of human beings. The fields of AI and biological research are becoming more intertwined, and methods for extracting and applying the information stored in live organisms are constantly being refined. As the field of AI matures with more trained algorithms, the potential of its application in epidemiology, the study of host–pathogen interactions and drug designing widens. AI is now being applied in several fields of drug discovery, customized medicine, gene editing, radiography, image processing and medication management. More precise diagnosis and cost-effective treatment will be possible in the near future due to the application of AI-based technologies. In the field of agriculture, farmers have reduced waste, increased output and decreased the amount of time it takes to bring their goods to market due to the application of advanced AI-based approaches. Moreover, with the use of AI through machine learning (ML) and deep-learning-based smart programs, one can modify the metabolic pathways of living systems to obtain the best possible outputs with the minimal inputs. Such efforts can improve the industrial strains of microbial species to maximize the yield in the bio-based industrial setup. This article summarizes the potentials of AI and their application to several fields of biology, such as medicine, agriculture, and bio-based industry.

1. Introduction

There is no precise definition of artificial intelligence (AI) so far, but in general it refers to the ability of any machines which can simulate the intelligences of higher organisms. The field of AI has important roots in almost every branch of research including philosophy, mathematics, computing, psychology and biology [ 1 ]. An ideal AI system would be self-aware, logical and able to learn from experience. It would also be able to perceive and react to external environments. With the aid of algorithms based on machine learning (ML) and deep learning (DL) approaches, such an intelligent system could be developed to carry out activities that require human intellect [ 2 ]. John McCarthy in the 1956 first coined the term “artificial intelligence (AI) for an intelligent machine system at the Dartmouth Conference [ 2 ]. The earliest significant work in AI includes the contribution of mathematician Alan Mathison Turing. He proposed his ideas in a public lecture in London about the concept of self-learning and self-instructed machines that learn from their own experiences as a human being does [ 3 , 4 ]. Due to his initial observation and conceptualization of facts about smart machines, Alan Turing is widely regarded as the father of AI and modern computer science. He was an early proponent of the theory that the human brain functions essentially like a digital computer [ 5 ]. He pioneered the experiment known as “The Turing Test”, which became a pivotal moment in the development of AI ( Figure 1 ). His paper titled ‘Computing Machinery and Intelligence,’ looked into the possibility of a non-living computer thinking like a human and was a landmark in this area [ 3 ]. Several other additional significant events paved the way for the development of the AI we see today ( Figure 2 ). An AI program written by Arthur Samuel in 1952 for the IBM 701 prototype and a ‘virtual rat’ trained to move through a predefined path based on a neural network by John Holland were such groundbreaking preliminary works [ 6 , 7 ]. In 1973, a group of Japanese engineers created the first humanoid robot, which had several distinct capabilities for a machine at the time, including the ability to walk upright, hold objects and converse in Japanese.

Alan Turing designed the Turing Test in 1950. This test includes three participants, a human interrogator, an intelligent machine and another human who we can call A, B and C, respectively. A is not aware of the identity of B and C, and A can send and receive response in only the form of text messages from B and C. A may ask B and C, a variety of questions, and based on their response, if A is unable to distinguish which one of B and C is a computer, then computer B may be considered as intelligent with thinking ability. If a human interrogator A could not distinguish the difference between another human and a computer, then the computer must be intelligent enough to be considered human. This test simply is to figure out whether or not a machine has ability to think.

Timelines highlighting the important breakthroughs in the evolutionary path of artificial intelligence and its application in various fields.

Another significant event in the AI timeline was the construction of IBM’s supercomputer, Deep Blue, which was capable of playing chess completely indistinguishable from humans. It was the first artificial intelligence to defeat Grandmaster Garry Kasparov in a timed match [ 8 ] ( Figure 2 ). Successful use of AI planning and perception approaches may be seen in NASA’s space-based autonomous vehicles, which use technology to steer and move on their own without human intervention [ 4 ]. DL and ML are crucial elements of AI that train themselves by picking up knowledge from data of various sources that are either generated directly or indirectly from the natural intelligence system. The more these deep learning and machine learning algorithms are trained using data from various sources, the more advanced, intelligent and self-aware artificial systems may be developed ( Figure 3 ) [ 9 ].

Schematic representation of major components of artificial intelligence and the continuous learning process with the help of natural intelligence to make smarter machines.

AI may be classified into two broad categories, Narrow or Weak AI and Artificial General Intelligence or Strong AI. Weak AI makes some attempt to copy or mimic human cognitional thought; it enables the automation of the majority of tasks in ways that humans are incapable of [ 10 ]. The most visible examples of weak AI on a daily basis include Tesla’s autopilot feature, facial recognition on our smartphones, Google’s search engine, Instagram’s AI for understanding user interests, Apple’s Siri and Amazon’s Alexa. Strong AI is a far more advanced and complex notion than weak AI. Strong AI is not restricted by human-made laws, and it thinks and controls the system entirely on its own. In layman’s terms, it is a program or a machine that simulates precise human cognitive or intellectual qualities, such as emotions or strong problem-solving abilities [ 11 , 12 ]. A weak AI program is designed to accomplish only one task at a time; a strong AI can efficiently perform numerous tasks simultaneously [ 13 ]. Although, self-awareness is the most essential and unique quality that distinguishes strong AI from weak AI, it is still in the early stages of development, and there are no real-life applications we can observe [ 13 ].

There are techniques used in AI which include a lot of variations, for example, the rule-based systems that are based on symbolic representations and work on inferences. AI systems have an ANN-based system which is designed to work on the interface with other neurons and connection weights [ 14 ]. Despite all of these, they all share four characteristics. Firstly, they have the feature of knowledge representation. Rule-based systems, frame-based systems and semantic networks use a series of if–then rules, whereas artificial neural networks use connections and connection weights [ 15 ]. Second, AI engineered systems are capable of learning. As self-learning entities [ 16 ], they gather data, such as by choosing the appropriate connection weights for an artificial neural network or defining the rules for a rule-based expert system. Third, they have the rules which can be implicit or explicit in an AI system. The fourth is the search, which can be incorporated into the system in several ways. For instance, it can be used to find the states that lead to a solution more quickly or to find the best set of connection weights for an ANN by minimizing the fitness function [ 1 ]. Depending on the algorithm employed, AI can also be divided into “rule-based”, also known as AI in general terms, and “non-rule-based”, also known as ML. In rule-based algorithms, conditioned branching and instructions are provided in order to obtain the best solution. For instance, the algorithm would be completely true to the instruction and merge the numbers when the case is defined as, “when subject numbers of two different datasets are the same, they should be treated as duplicates and need to be merged”. A rule-based algorithm works well when there are few options available. However, the development of a rule-based algorithm is quite challenging in complex scenarios. ML, on the other hand, develops rules directly from established training input and implements them in the ML algorithms via statistical methods. Thus, ML focuses on quickly recognizing patterns from a huge volume of information to provide findings that are more reliable than manual analysis and predictions [ 17 ].

AI has now made its way into the biological field, demonstrating its worth through innovative and cutting-edge procedures [ 18 ]. Additionally, the world has seen a true revolution in the field of information technology (IT), leading to the production and storage of an enormous amount of data, not just in the field of technology but in other areas as well in recent years. Both information technology and biology have flourished during the past half-century. According to Moore’s law, the number of transistors on a chip will double about once every two years. It is a consequence of and driver for the rapid growth of information technology [ 19 ]. Computational resources are inextricably linked to big data, which encompasses annotated and raw information due to the ever-increasing volume and complexity of data from multiple sources [ 20 , 21 ]. Because of developments in sequencing and other high-throughput techniques, the biosciences and biotech industries have made remarkable strides in recent years [ 22 ]. AI-based algorithms have the capacity to effectively store and process large amounts of raw, unstructured data and make them available for quick extraction, which is necessary to build an intelligent computing system with complex decision-making capability [ 23 , 24 ]. Such advancement in data generation, storage and analysis allows the development of a wide range of products and services in different sectors including biosciences [ 19 ]. While advances in computing and the Internet ushered in the third industrial revolution and laid the groundwork for AI’s meteoric rise, Big Data and the analytics it spawned have allowed us to take our intelligence to new heights [ 25 ]. AI is now considered a major invention of the fourth industrial revolution [ 26 ]. Experiments that would have taken years to execute are now feasible and often inexpensive due to recent advances in data and methodology. Raw data in a variety of formats are generated as a result of these experimental analyses. The ability to store and analyze data with the help of AI has created new possibilities for the academic community, scientific researchers and the biotech industry. Various applications of AI are used in biology, including the precise identification of the 3D geometry of biological molecules such as proteins which is one of the most critical tasks and useful in biological research. Moreover, in biological science, AI plays a critical role in promoting innovation not only in laboratories, but also throughout the lifecycle of a medication or chemical product [ 27 ]. Furthermore, AI-based tools and applications help automate complicated production procedures, thereby meeting the fast-rising demand for medications, chemicals for use in industry and food and other bio-based raw materials. ML, a subset of AI, aids in the prediction of outcomes by executing massive permutations and combinations of datasets available for the drug molecules to determine the best combination without relying on traditional manual methods in the lab [ 28 ]. Although traditional model-driven methods are still useful for analyzing biological data, they lack the ability to use vast amounts of available data, or even big data, to uncover information, forecast data behavior and comprehend complex data linkages. The extensive use of big data is becoming increasingly important in biotechnology and bioinformatics as it continues to grow and becomes available to academicians and scientists for analysis throughout the world [ 29 ]. These data are quantified in terms of multi-omics, such as genomics, transcriptomics, proteomics, and metabolomics, from different biological sources and need to be properly annotated and analyzed to understand complex biological systems. AI and deep neural network designs might efficiently analyze genomic data to determine the genetic basis of a trait and to uncover genetic markers linked with certain traits [ 30 , 31 ]. The use of AI may aid in deciphering complex links across diverse information hidden in data to obtain meaningful insights from them. As a result, the incorporation of AI approaches is now widely observed in the field of biological science and is expected to increase further in the near future as this technology matures [ 2 ]. Furthermore, medical images and drug responses contribute complex but significant data and need efficient algorithmic programs to analyze them. Therefore, ML- and DL-based AI is garnering much attention due to their capabilities for faster processing of huge data and extraction of meaningful information. AI-based digital image processing, drug designing and virtual drug tests might transform medical science in the near future [ 32 , 33 ].

The current review article highlights how Artificial Intelligence, and its components could be used in the medical, agricultural, and bio-based industrial sectors to make human life more sustainable.

2. AI in Medical Science

Medical science and biotechnology advancements have opened new avenues for developing medications and antibiotics. AI has enormous potential for widespread applications in the pharmaceutical industry ( Figure 4 ). With AI, novel therapeutic molecules based on known target structures can be discovered [ 34 ]. A branch of AI known as ML is commonly employed in disease diagnosis since it leverages the outcomes of diagnostic testing to improve the accuracy of results [ 35 ]. AI allows researchers to manage challenging issues, including quantitative and predictive epidemiology, precision-based medicines and host–pathogen interactions [ 36 ]. AI can help in disease detection and diagnosis and make computer code more accessible to non-technical individuals [ 37 ]. Predictive epidemiology, individual-based precision medicine and the analysis of host–pathogen interactions are examples of research areas that could benefit from machine and deep learning breakthroughs [ 38 ]. These approaches aid with disease diagnosis and individual case identification, more accurate forecasts and fewer mistakes, faster decision making and better risk analysis ( Figure 4 ). The growing number of tissue biomarkers and the complexity of their evaluations significantly promote the use of AI-based techniques. These AI-based biomarkers help physicians in the prediction and analysis of the diagnosis, patient responses to the treatment and patient survival [ 39 ]. More realistic models of complex socio-biological systems are achievable because of knowledge representation and reasoning modelling [ 40 ]. ML-based methods can also be used to improve the efficiency and reliability of epidemiological models [ 41 , 42 ]. ML advances helped develop ten cellular parameters algorithmic program-based models that can accurately distinguish benign from malignant tumors [ 43 ].

A conceptual model that illustrates the application possibilities of artificial intelligence in the disciplines of health, agriculture, animal science and industrial biotechnology.

It is important to take into account individual differences in genetics, ecology and lifestyle in precision medicine [ 44 ]. Medical practitioners recognize that the metabolic, physical, physiological and genetic makeup of an individual affects how their body responds to drugs in a certain way. Despite this, we are currently employing an umbrella approach that treats all patients, regardless of their varying conditions, with the same drug. However, due in large part to advances in AI, a new era of personalized medicine, in which pharmaceuticals are tailored to the body’s needs and adaptability, is evolving. Although the transition appears to be simple, it entails a significant amount of data collection, processing, maintenance and execution [ 45 ]. Moreover, millions of prediction analyses will be included in the process to identify the best therapeutic candidate molecules for a particular case. Using this strategy, physicians and clinicians may better predict which disease treatment and preventative strategies will be most effective for particular patient groups ( Figure 4 ). Researchers could use AI in DNA, RNA and protein studies to better visualize the effects of drug doses on living tissue over time and reorganize signaling networks during therapy [ 46 , 47 ]. Based on AI, IBM Watson assists in the creation of the appropriate treatment plan for a patient depending on the patient’s medical history and personal data, including genetic makeup [ 48 ]. An AI-based system of personalized medicine will not only reduce treatment cost but also minimize the side effects of drugs in the patient [ 49 ]. In addition to saving time and improving patient care, AI can also simplify gene editing, radiography and drug management planning procedure [ 50 ]. Furthermore, electronic health records (EHRs) can be improved with evidence-based clinical decision support systems [ 44 , 51 , 52 ]. AI involves massive processing capacity (supercomputers), algorithms that can learn at a phenomenal rate (deep learning) and a new strategy that utilizes physicians’ cognitive talents ( Table 1 ). This technique can contribute to the development of innovative theoretical models of disease pathophysiology and can help forecast major adverse effects of prolonged medications [ 53 ]. In a recent study, an AI-based approach was found to be very beneficial for the early identification, diagnosis, prognosis and treatment of myopia [ 54 ]. In cardiology, dermatology and oncology, deep learning algorithms outperform physicians at least in the diagnosis of disease [ 55 , 56 , 57 ]. Evidently, computer algorithms can detect metastatic breast cancer in sentinel lymph node biopsies in full slide images with an accuracy rate of more than 91 percent, and this was raised to 99.5 percent when physician inputs were added [ 58 ]. One of the proven applications of AI in risk analysis is for diagnosing heart malfunctioning through cardiovascular imaging. It includes automated monitoring of any deviations from normal conditions based on image processing, myocardial function and the detection and analysis of coronary atherosclerotic plaques [ 59 ]. The YOLOV3 algorithm was used for AI-based medical image segmentation for 3D printing and naked eye 3D visualization to detect the prostate in T2-weighted MRI images (AIMIS3D) [ 59 ]. There are several variables that might be efficiently analyzed through AI, such as determining which conditions are resistant to certain antibiotics and not to others [ 60 ]. Such analysis can support physicians and significantly decrease unnecessary testing and costs in medical care.

AI in disease detection and prediction modelling.

It is important to underline the importance of combining these algorithms with medical expertise ( Table 1 ). New pharmaceutical compounds can be discovered via data analysis using AI, which reduces the need for clinical trials, allowing medications to be brought to market more quickly without compromising their safety [ 32 ]. Moreover, we may be able to forecast the onset of genetically predisposed diseases considerably earlier with the help of AI [ 50 ]. Patients will also be able to prevent and treat certain inherited diseases.

One of the applications of AI in the pharmaceutical industry is “Open Targets”, which is a relatively new strategic effort to explore the relationship between drug targets and diseases, as well as how certain genes are linked to diseases [ 67 ]. SPIDER is another AI technique that is being designed to determine the role of natural products in drug discovery [ 68 ]. Furthermore, quantitative structure–activity relationship (QSAR) studies are particularly useful in creating novel effective medications in a very short period of time using a computer simulation tool [ 69 ]. A QSAR model based on a radial basis function (RBF) artificial neural network (ANN) model that was trained using particle swarm optimization (PSO) technique was used in a recent study to predict the pKa values of 74 different types of drugs [ 69 ]. Natural language processing (NLP), ML, and robotic process automation are clearly the three key areas of advancement for AI in the field of medicine [ 70 , 71 ]. Natural Language Processing has recently been used to enhance colonoscopy analysis, improving accurate detection of adenoma and polyps [ 72 ]. Additionally, an ML approach may be used to predict diseases such as atrial fibrillation and urinary tract infections in certain patient groups by using models such as support vector machine (SVM) based on clinical features of the disease [ 73 , 74 , 75 ]. Similar initiatives have been utilized to improve heart disease prognosis using a heart-murmur-detecting technology [ 76 ]. The FDA has already approved up to 29 AI-based medical devices and algorithms in various fields of medical sciences [ 77 ].

The first AI-based model approved by the FDA in the healthcare sector was a diagnostic model based on an autonomous AI system, IDx-DR. This model was successfully used in to detect diabetic retinopathy with sensitivity, specificity and imageability of 87.2%, 90.7% and 96.1%, respectively, in a sample size of 819 subjects over 10 primary care units in the United States. The model was trained with a diversified sample dataset consisting of individuals of different ages, races and sex, thus minimizing the chances of errors in different groups [ 78 ]. Several randomized clinical trials (RCTs) have also been performed to test the efficacy and safety of AI and ML models in clinical practice. In an RCT (Registration number: ChiCTR-DDD-17012221), the impact of a deep-leaning-based automated polyp identification algorithm on polyp detection accuracy and adenoma detection rates (ADRs) was evaluated. In this RCT, successive patients were randomly assigned to go through colonoscopy either with or without the help of the automated polyp identification model that provided a simultaneous optical notification and sound alert upon polyp discovery. Results obtained from patients who have undergone the automated AI-based detection system outperformed the control cohorts of ADR and the average amount of adenoma and polyps detected per coloscopy. This automated technology can thus be pertinent in treatment regimens and routine practices for improved identification of colon polyps due to its great sensitivity, high precision and stable outcomes [ 79 ]. The introduction of AI systems in medical decision making has also resulted in the cost-effectiveness of complete medical treatment. In a study, the use of a procalcitonin-based decision algorithm (PCTDA) for hospitalized sepsis and lower respiratory tract infection patients led to a shortened duration of stay, lowered antibiotic administration, lesser artificial ventilation periods and decreased number of patients with infections and antibiotic resistance. On average, PCTDA-based treatment brought about a 49% and 23% decrease in overall expenses from conventional treatment for sepsis and lower respiratory tract infections, respectively [ 80 ]. The pharmaceutical industry will better grasp genetic information with improved AI and ML skills ( Figure 4 ). Evidently, when integrated with ML and NLP, robotic process automation has significant applications and has the potential to reshape medical science in the near future [ 81 ]. Despite the tremendous advancements we have observed, there is still a lot of work to be done before AI-based therapy becomes a reality.

3. AI in Agricultural Biotechnology

Face recognition [ 82 ], cancer prediction in tissue [ 83 ] and metabolic flux analysis [ 84 ] are just a few examples of significant advances made with AI approaches, and there is a potential to achieve a similar revolution in the agricultural field. According to a report published by the United Nations’ Food and Agriculture Organization (FAO), the world’s population will reach more than 9 billion by 2050 [ 85 ]. Population expansion will eventually put a strain on the agriculture sector’s ability to provide food. In order to feed the world’s growing population and advance the nation’s economy, agriculture is essential [ 86 ]. It is a significant source of revenue for a number of countries, including India.

Agriculture occupies around 38% of the planet’s total land surface [ 85 ]. The majority of agricultural activities are now manual, and agriculture may significantly benefit from automation in terms of obtained yield and invested inputs. The implementation of technological breakthroughs in agriculture may contribute to the change in rural economies and villagers’ livelihoods [ 87 , 88 ]. Agricultural techniques are generally designed to overcome a variety of obstacles, including pest infestation, inefficient use of pesticides and fertilizers, weeds, drought and a lack of an adequate irrigation system, inefficient harvesting, storage and finally marketing. The agricultural sector could be transformed by AI intervention in the areas of soil management, water requirement assessment, precise mapping of fertilizer need, pesticide, insecticide, herbicide need, yield prediction and overall crop management ( Figure 5 ) [ 89 , 90 , 91 ]. With the advancement of AI-based technology, drones and robots are being used to improve real-time monitoring of crops, harvesting and subsequent processing [ 92 ]. AI and ML techniques are currently being used by biotechnology companies to design and train autonomous robots capable of performing key agricultural activities such as crop harvesting at a much faster rate than traditional methods [ 89 ]. The data collected by drones are processed and evaluated using deep learning and computer vision techniques [ 93 ]. Machine learning approaches assist in the access and forecast of a wide range of environmental variables that influence agricultural output, such as weather fluctuations and the arrival of the monsoon in India [ 89 , 94 , 95 ]. As mentioned elsewhere, AI-based solutions in the agricultural industry help to improve efficiency and control numerous aspects such as crop yield, soil profile, crop irrigation, content sensing, weeding and crop monitoring ( Figure 5 ) [ 89 , 96 ].

Agricultural fields where artificial intelligence (AI) could have a positive impact.

Traditional and older morphological characteristic inspection is time-consuming, error-prone and costly. The machine vision method might be easily applied in agricultural practices, which can speed up and simplify the procedure while being more precise and accurate [ 93 ]. Identification and selection of improved varieties may speed up and make the process easier by using automated non-invasive, rapid scoring of various plant features through high-throughput phenotyping methods [ 97 ]. Due to the tools of AI and IoT, swarm intelligence and drone technology can now be employed for several agricultural activities [ 98 ]. Recent developments in DL- and ML-based algorithm design to estimate the price of agricultural products may enable farmers to receive a higher return on their labor and investment [ 99 ]. For effective irrigation, artificial neural networks, fuzzy logic and meta-heuristic algorithms have recently been developed [ 100 , 101 ]. According to a recent study, convolutional neural network (CNN), which takes into account several environmental variables, is one of the most trustworthy ML algorithms to estimate soybean and maize yields [ 102 ]. Recent advances in AI-based biosensors for early disease detection in crop plants, even in asymptomatic plants, have the potential to greatly minimize product loss caused by biotic stressors [ 103 ]. AI-based drone technologies such as EfficientNetV2, which are designed to detect and classify plant diseases with accuracy and precision of 99.99% and 99.63%, respectively, are one of the promising automated technologies for the monitoring of plant health in a time-saving and cost-effective manner [ 104 ]. For the detection of bacterial spot disease in plants, a hybrid AI model based on convolutional autoencoder (CAE) and CNN has also achieved 99.35% and 99.38% in the training and testing periods, respectively, [ 105 ].

The use of AI may make it simpler to identify potential targets in big genome data for genetic manipulation and design effective synthetic promoters in efforts to improve agronomic traits in plants [ 106 , 107 ]. The growing necessities for smart agriculture have resulted in substantial advancements in the area of AI-based agricultural forecasting and prediction, which has improved crop productivity to a great extent [ 93 ]. A similar attempt was made in a recent study where image datasets were analyzed by employing AI algorithms, namely ANN and genetic algorithm (GA)-based platforms, for the prediction of crop yield in an optimized manner [ 108 ]. During the training period, the model obtained a maximum validation accuracy of 98.19%, whereas a maximum accuracy of 97.75% was yielded during the test period [ 108 ]. This model worked effectively under limited resource restrictions and less data, producing optimal results [ 108 ]. In another significant study, a new methodology for predicting agricultural yield in greenhouse crops employing recurrent neural network (RNN) and temporal convolutional network (TCN) algorithms was proposed [ 109 ]. Based on previous environmental and production data, this approach can be utilized to estimate greenhouse crop yields more accurately than its standard ML and deep learning peers [ 109 ].

Furthermore, this experimental investigation has also demonstrated the crucial importance of previous yield datasets in correctly predicting future crop productivity [ 109 , 110 ]. Several million individuals in developing nations have benefited from the green revolution by preventing and combining high-yield crops, synthetic fertilizers and water. However, owing to widespread misuse of herbicides, pesticides and fertilizers, the green revolution could not be considered fully “green”. Certain approaches for high-yielding crops typically need a large amount of agro-chemicals and water [ 111 ]. AI-based approaches are being developed to reduce the reliance on noxious agro-chemicals and to attain a state of sustainability in agriculture [ 79 ]. For optimizing agricultural resources, a remote sensing assisted control system (RSCS) has been developed [ 112 ]. This methodology makes use of AL and ML technology to improve environmental sustainability while fostering novel agricultural product development planning. When analyzed with other techniques, the findings revealed that the RSCS demonstrated the highest precision, performance, data transfer rate, productivity, irrigation management and carbon dioxide release ratio of 95.1, 96.35, 92.3, 94.2, 94.7 and 21.5%, respectively, [ 112 ]. Thus, AI models have the potential to manage agricultural products and productivity in a “green” manner. In another study, an AI and machine vision-based smart sprayer was developed to spray herbicides specifically to weed targets, thus reducing weedicide overuse and environmental contamination. This sophisticated technology combined a cutting-edge weed detection concept, a unique rapid and precise spraying method and a weed mapping model with 71% and 78% precision and recall, respectively, [ 113 ]. Due to limited collecting techniques and a lack of integration of diverse data sources, data gathering from agricultural regions linked to soil hydration, crop quality or insect infestations frequently depend on manual analysis.

Meanwhile, as the industry becomes more digital, the combination of remote sensing for computerized screening and analytical techniques with datasets for soil studies, weather predictions, etc., and sophisticated AI models is reducing the need for agrochemicals [ 93 ]. In this regard, the substantial NaLamKI action plan that seeks to create AI-based open access software that could greatly help the agricultural industry has received funding from the German government. This plan seeks to develop datasets by combining information from different sensors in order to optimize different farming practices with the help of AI and ML technologies [ 93 , 114 ]. Similar governmental initiatives are required in large numbers to make farmers adapt AI on a greater scale.

In agriculture, integrating precise image-based features with omics data may aid in finding critical traits involved in stress tolerance and acclimatization mechanisms [ 115 ], as well as contribute to the development of climate resilient cropss. Farmers will be able to generate more output with less input, increase the quality of their output and ensure a faster time to market for their harvested crops owing to AI-based technology adaptation [ 93 ] ( Table 2 ). Although first-generation AI can be employed in the surveyance and classification of omics data, it is tailored for the handling of specific problems related to single-omics datasets without integrating data from other modalities [ 93 , 116 ]. In agricultural biotechnology, next-generation AI is fundamentally envisioned to dynamically ameliorate and handle large multi-omics datasets in addition to predicting the breeding value of complex traits across different environmental conditions [ 116 ].

Recently developed AI-based algorithms in the agricultural sector.

4. AI and Industrial Biotechnology

Industrial biotechnology, sometimes known as white biotechnology, is the modern application of biotechnology to the sustainable processing and manufacturing of commodities, chemicals and fuels from renewable sources using live cells and their enzymes. The demand for industrial chemicals, medicines, food-grade chemicals and other biochemistry-related raw materials has increased dramatically over the previous decade [ 121 ]. ML and AI-based technologies may aid in the design of novel pharmaceuticals and the identification of their efficacy and adverse effects before their actual production, drastically reducing the time spent bringing a drug from the lab to the market for ordinary people [ 32 ]. Microorganisms and plant/animal cells are used in biotechnological processing to make products in a variety of sectors, including drugs, pharmaceuticals, food and feed, disinfectants, pulp and textiles. In order to detect outages, optimize machinery for efficient manufacture and improve product quality, the Internet of things, ML and AI could be used effectively [ 122 ]. AI-based computer models are becoming increasingly widespread, and robotics and machine learning could be used to develop the best optimum growth conditions for the strains, as well as the degree to which valuable products can be obtained ( Figure 4 ). For instance, AI or response surface methodologies (RSM) -based approaches have been used in the high-level production of amylases from Rhizopus microsporous, using various agro-industrial wastes for optimal experimentation designs [ 123 ]. Similarly, AI algorithms such as artificial neural networks (ANN) and genetic algorithms (GA) have been integrated for the optimization of fermentation media to produce glucansucrase from Leuconostoc dextranicum . A 6% rise in glucansucrase activity was predicted by the integrated ANN-GA model over a regression-based prediction approach [ 124 ]. The application of the integrated ANN-GA model for the optimization of cellulase production by Trichoderma stromaticum under solid-state fermentation has been reported recently, and a 31.58-fold increase in cellulase production was achieved after optimization with the AI model [ 125 ].

AI-based technologies have also been used to scale up and optimize bioprocesses for enzyme production on pilot scales. A low-cost method for increasing the synthesis of extracellular laccase from Staphylococcus arlettae utilizing tea waste was performed in a study. RSM and ANN coupled with GA were two consecutive statistical methods that were employed to increase enzyme production and resulted in a sixteen times rise in enzyme yield. Moreover, a pilot scale bioprocess was established utilizing the ideal parameters identified by GA, namely tea waste (2.5%) NaCl (4.95 mM), L-DOPA (5.65 mM) and 37℃ temperature, which improved the enzyme production by 72 times [ 126 ]. Furthermore, some AI models based on the fuzzy expert system are also capable of monitoring wastewater treatment plants on a pilot scale [ 127 ].

Biofuel is one of the most important bioproducts for which the industrial production process can be enhanced using ML and AI for maximum output. In the bioenergy sector, AI-based approaches have been used to predict biomass feedstock properties, bioenergy end-uses, and bioenergy supply chains and have developed an integrated ANN-Taguchi method model for the prediction and maximization of biofuel production via torrefaction and pyrolysis [ 128 , 129 ]. Optimization and design of experimental factors were performed using the Taguchi method which led to the attainment of maximum biofuel yield up to 99.42%, whereas ANN showed linear regression prediction of 0.9999 for biochar and 0.9998 for bio-oils.

Integrated ANN-GA models have been used in the modeling and optimization of the methanolysis process of waste peanut shells for the generation of biofuels. Biofuel yield optimized by the RSM model was 16.49%, whereas that of the ANN-GA model was reported to be 17.61%. This shows that integrated ANN-GA has better optimization potential than the RSM model alone [ 130 ]. ML-based bioprocess models have also been constructed with the help of AI-based methods such as ANN, CNN, (long short-term memory networks) LSTMs, kNNs (k-nearest neighbors) and RF (random forests) for predicting the accumulation of carbohydrates in cyanobacteria biomass cultivated in wastewater for biofuel production. The finest results for approximation of system dynamics were achieved with a 1D-CNN with a mean square error of 0.0028 [ 131 ]. Textiles, new chemicals and biodegradable biopolymer synthesis could all benefit from similar processes [ 132 ]. Furthermore, it may be used to assist in the development of synthesis techniques for such biochemicals that produce the highest yield with the least amount of input ( Figure 4 ). Additionally, AI could assist in real-time forecasting of market demand for medications or chemicals. AI and ML have also helped in the production of metabolites. Systems metabolic engineering is a process that helps in the rapid production of high-performing microbial strains for the long-term production of chemicals and minerals. The increasing availability of bio big data, such as omics data, has resulted in an application for ML techniques across various stages of systems metabolic engineering, such as host strain selection, metabolic pathway reconstruction, metabolic flux optimization and fermentation [ 19 ]. Various machine learning algorithms, including deep learning, have facilitated in optimizing the bioprocess parameters and exploring a larger metabolic space that is linked to the biosynthesis of a target bioproduct [ 133 ]. This trend is also influencing biotechnology businesses to adopt ML techniques more frequently in the creation of their production systems and platform technologies [ 134 ]. In the brewery industry, AI has demonstrated promising potential to overcome fundamental shortcomings and enhance production through knowledge accumulation and automated control. In a study, AI models were constructed using aroma profiles and spectroscopic data obtained from commercial alcohol for assessing the quality traits and aroma of beer. The intelligent models resulted in highly accurate predictions for six major beer aromas [ 135 ]. Smart e-nose technologies based on ANN models have also been developed to assess the presence of different chemicals such as ethanol, methane, carbon monoxide, hydrogen sulfide, ammonia, and so forth in beer [ 136 ]. A study was involved in the development of a computer program that simulated the operation of a highly customizable three-layer feed-forward multilayer perception neural network, which using data from prior experiments, could forecast changes in the parameters of white wine alcoholic fermentation. This work provided a befitting approach for the digitalization of brewing processes, thus enabling it to be acclimatized to other intelligent and knowledge-based frameworks [ 137 ]. Another study led to the development of an innovative knowledge-based approach for controlling the batch fermentation of alcohol employed in making white wine. The primary sources of information used in developing the AI model were different case studies and experimental results, as well as the knowledge obtained from brewery experts regarding different parameters related to optimization and control of the overall process. Using the monitoring, regulation and data acquisition software of the fermentation bioreactor, an application for automated process control was developed [ 138 ]. The further incorporation of control systems, processes and innovative advancements can be greatly facilitated by such kinds of AI models, thus supporting sustainable development.

5. Challenges and limitations

Despite their immense potential, AI-based technologies have yet to make their way into everyday practice. AI models can improve the accessibility of various biological sectors; however, they may also exacerbate pre-existing discrepancies. Since AI models are extremely reliant on the datasets on which they are developed as well as the labels connected with them, prejudices against the underrepresented in the learning algorithms might be reinforced [ 139 ]. Several factors must be considered to properly assess the resilience of some deep neural networks. For the development of AI models, metadata must be created, retrieved and cleansed. Programs should further be designed and evaluated under the oversight of field professionals for analysis and correction of inaccuracies committed in practice [ 140 ]. In spite of significant advances in the design of AI and ML-based models in recent years, few have been incorporated into healthcare, and many prospects for adopting these models for everyday usage remain untapped. CNNs, for instance, were initially used in study designs commencing in 2015, primarily on dental radiographs, with the first clinical uses for these tools only recently emerging [ 141 ]. Unavailability and inaccessibility of clinical data due to organizational policies, insufficient reproducibility in processing datasets and assessing outcomes and residual concerns around accountability and transparency to patients remain the most common hurdles in adapting AI in routine medical and dental practices [ 142 ]. Moreover, several models have been reported to be inaccurate in predicting the clinical diagnosis. For example, an AI algorithm that can diagnose and classify chest X-rays using NLP to radiological records was developed [ 82 , 143 ]. These classifications were subsequently utilized in the training of a deep learning network to detect abnormalities in pictures, with a specific focus on recognizing a pneumothorax [ 144 ]. However, after a thorough examination, the presence of a chest tube in the majority of the reports identified as pneumothorax raised questions that the algorithm has been recognizing chest tubes instead of pneumothorax as envisioned [ 143 ]. Another example of non-interpretative results of a clinical AI-based system is DeepGestalt, a tool for analyzing facial dysmorphology. This tool performed poorly when identifying people with Down syndrome who were of African heritage (36.8%) compared to those who were of European origin (80%) [ 145 ]. The diagnoses of Down syndrome among people of African lineage increased to 94.7% when the model was retrained using cases of people with the condition [ 145 ]. Due to various marginalization in training datasets, genetic disease susceptibility modeling is also predisposed to differential performance across demographic groups [ 146 ]. Furthermore, it has been observed that while ML approaches may perform better in studies for developing disease risk prediction models, the presentation of the data may be more complex. There is also a possibility that the amount of computational time required by ML approaches varies depending on the size of the data [ 147 ]. Thus, it is crucial to acknowledge that the utilization of AI-based approaches will not always lead to improvised categorization or better prediction than present methods. AI is a tool that should be employed within the proper context to address a pertinent question or resolve a significant issue [ 148 ]. Similarly, in other biological fields such as agriculture, automation in practices employing AI and ML-based approaches leverages a lot of potential for sustainable farming. However, in the agricultural sector, the collection, analysis and utilization of data for productivity present a number of obstacles. Privacy and security of data are the two major challenges that farmers must address to survive in the digital age. In most cases, the farmers are uninformed of the collection, usage, and more concerningly, the purposes for which their personal details are being utilized [ 149 ]. Data mining allows corporations to rely on individuals in order to acquire massive agricultural data, which may be sufficient to develop and evaluate the behavioral and psychiatric pictures of the respondents [ 150 ]. To stop data from being misused, farmers require assurance that their information will be utilized to generate innovative ideas and agricultural solutions rather than to gain a competitive advantage. As mentioned elsewhere, the AI-based drone technology has emerged as a highly effective approach in agriculture [ 87 ]. However, drones, particularly those equipped with high-resolution lenses, infrared cameras, competent programs and sensors, are highly expensive for small farmers. Moreover, to operate drones, one needs authorization according to its operative and regulative provisions of the law of land [ 151 ]. Furthermore, weather imparts a huge influence on the operation of drones [ 152 ]. Traditional data mining methodologies are primarily developed for relational datasets; however, they are not completely adequate for geographically scattered data [ 153 ]. To revolutionize agriculture with AI-based technologies, innovative data mining approaches are needed.

In the industrial biotechnology sector, establishing defined and viable protocols for adopting an algorithm and assessing dataset size remain a major challenge. To design such protocols, it would be necessary to have a thorough knowledge of the effects/efficacy of various algorithms as well as training datasets to address numerous bioindustry challenges. Furthermore, increased accessibility, good documentation and superior data acquisition methods are still required to develop, operate and optimize bioenergy systems and bioreactor designs [ 128 ]. In some AI models, when the input is inadequate, particularly for large dimensional datasets, the algorithm may only recall every single variable as a special instance instead of learning the information, resulting in errors and lower training efficacy [ 154 ]. Additionally, numerous ANN-represented systems are frequently chastised for having black-box characteristics. Nonetheless, the paucity of comparative works across different AI–ML designs renders it challenging to present a clear direction for future studies or practical implementation [ 155 ]. There still exist challenges that need to be overcome including inefficient data integration which arises due to the diversity of the datasets inclusive of candidate data, metadata, processed data, raw data and lack of proper skill set and expertise related to the subject [ 156 ]. In this context, it is necessary to overcome these ambiguities by utilizing new AI algorithms to achieve a thorough alignment between the anticipated outcomes and the empirical studies [ 157 ]. Thus, more extensive datasets and relative studies are required to develop AI and ML-based models for real-time monitoring and control of bioreactors and bioprocesses.

6. Conclusions

One of the great achievements we have seen in the era of Industry 4.0 is the ability of a machine to replicate the capacities of living systems, particularly the intelligence of a human. The ability to recognize objects and make decisions is a crucial characteristic of biological systems. AI can currently recognize objects and make decisions using many of the cognitive and perceptual abilities of live systems. The potential of AI might be utilized to the biological world, including medical research, agriculture, and bio-based industries, for our sustainable way of life. The early prediction and identification of disease and its precise treatment based on personalized medicine even while the diseases are in asymptomatic conditions are examples of key areas in medical science that might benefit from AI. This would not only save millions of lives but also reduce medical costs. In addition to the medical field, AI-based efficient algorithms and programs have been recently developed to ensure effective inputs and outputs in farming, a practice known as precision farming. Agricultural practices such as soil management, water need analysis, exact modeling of fertilizer requirement, pesticides, insecticides, herbicides, yield projection and overall crop management could also be revolutionized by AI intervention. This would help to meet the world’s rising population’s demand for food. When we talk about large-scale production, many variable factors lead to increasing costs, which are major challenges. Recently, AI-based programs and computer models have proven to be very efficient at optimizing the suitable conditions to obtain the maximum desired product, whether for agricultural, medical, biotech, or lifestyle uses, at minimum cost. The efficient production of bio-enzymes is just one of such successes, and it is easy to envision how the biotech industry will be transformed by the application of AI, which will help to reduce production costs, one of the biggest challenges facing the industry today.

Acknowledgments

Authors are thankful to Amity University Jharkhand for the support provided under NTCC and PEARL Scheme.

Funding Statement

This research received no external funding.

Author Contributions

Conceptualization, D.K.P.; writing—original draft preparation, A.B.; writing—review and editing, A.B., S.K. and D.K.P.; supervision, D.K.P. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Informed consent statement, data availability statement, conflicts of interest.

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Virtual reality immersive simulations for a forensic molecular biology course—a quantitative comparative study.

1. Introduction

2. materials and methods, 2.1. vr simulation design and development, 2.2. forensic molecular biology vr prototype, 2.3. simulation scenario and activities.

• Identify forensic evidence (blood samples) in a crime scene.
• Propose and apply appropriate evidence collection methods.
• Handle effectively genomic DNA from the collected human bloodstains.
• Perform diagnostic DNA profiling and analyzing tests using laboratory equipment.
• Interpret diagnostic DNA analysis test results accurately.
• Moreover, students will be able to develop the following transversal skills:
• Ability to analyze and solve problems.
• Ability to communicate and cooperate in professional settings.

2.4. Evaluation of the VR Forensic Module

3.1. data analysis, 3.2. findings, 3.2.1. demographics, 3.2.2. impact of instructional modalities on learners’ perceptions, 3.2.3. factors influencing learners’ attitude toward vr-based simulations, 4. discussion and conclusions, 5. limitations and future work recommendations, supplementary materials, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest, appendix a. data collection instrument.

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Share and Cite

Ewais, A.; Mystakidis, S.; Khalilia, W.; Diab, S.; Christopoulos, A.; Khasib, S.; Yahya, B.; Hatzilygeroudis, I. Virtual Reality Immersive Simulations for a Forensic Molecular Biology Course—A Quantitative Comparative Study. Appl. Sci. 2024 , 14 , 7513. https://doi.org/10.3390/app14177513

Ewais A, Mystakidis S, Khalilia W, Diab S, Christopoulos A, Khasib S, Yahya B, Hatzilygeroudis I. Virtual Reality Immersive Simulations for a Forensic Molecular Biology Course—A Quantitative Comparative Study. Applied Sciences . 2024; 14(17):7513. https://doi.org/10.3390/app14177513

Ewais, Ahmed, Stylianos Mystakidis, Walid Khalilia, Shadi Diab, Athanasios Christopoulos, Said Khasib, Baha Yahya, and Ioannis Hatzilygeroudis. 2024. "Virtual Reality Immersive Simulations for a Forensic Molecular Biology Course—A Quantitative Comparative Study" Applied Sciences 14, no. 17: 7513. https://doi.org/10.3390/app14177513

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• Impact of climate change on plant-pollinator interactions.
• Genetic diversity and conservation of endangered species.
• Evolutionary patterns in mimicry and camouflage in organisms.

Biology Research Topics for Undergraduates 

• Effects of different fertilizers on plant growth and soil health.
• Investigating the biodiversity of a local freshwater ecosystem.
• Evolutionary origins of a specific animal adaptation.
• Genetic diversity and disease susceptibility in human populations.
• Role of specific genes in regulating the immune response.

Cell and Molecular Biology Research Topics 

• Molecular mechanisms of DNA replication and repair.
• Role of microRNAs in post-transcriptional gene regulation.
• Investigating the cell cycle and its control mechanisms.
• Molecular basis of mitochondrial diseases and therapies.
• Cellular responses to oxidative stress and their implications in ageing.

These topics cover a broad range of subjects within biology, offering plenty of options for research projects. Remember that you can further refine these topics based on your specific interests and research goals.

Frequently Asked Questions 

What are some good research topics in biology?

A good research topic in biology will address a specific problem in any of the several areas of biology, such as marine biology, molecular biology, cellular biology, animal biology, or cancer biology.

A topic that enables you to investigate a problem in any area of biology will help you make a meaningful contribution. 

How to choose a research topic in biology?

Choosing a research topic in biology is simple. 

Follow the steps:

• Generate potential topics. 
• Consider your areas of knowledge and personal passions. 
• Conduct a thorough review of existing literature.
•  Evaluate the practicality and viability. 
• Narrow down and refine your research query. 
• Remain receptive to new ideas and suggestions.

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For several years, Research Prospect has been offering students around the globe complimentary research topic suggestions. We aim to assist students in choosing a research topic that is both suitable and feasible for their project, leading to the attainment of their desired grades. Explore how our services, including research proposal writing , dissertation outline creation, and comprehensive thesis writing , can contribute to your college’s success.

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Should you use MLA or APA citation style in your dissertation, thesis, or research paper? Choose by reading this comprehensive blog.

If you are looking for research paper format, then this is your go-to guide, with proper guidelines, from title page to the appendices.

Academic integrity: a commitment to honesty and ethical conduct in learning. Upholding originality and proper citation are its cornerstones.

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Senior thesis examples.

Graduating seniors in Biological Sciences have the option of submitting a senior thesis for consideration for Honors and Research Prizes .  Below are some examples of particularly outstanding theses from recent years (pdf):

Sledd Thesis

Grounds for Discovery

New research on coffee acidity charts a roadmap for better roasting.

• by Jessica Heath
• August 22, 2024

Nutty, sweet, bitter and salty: These are common flavor notes in a cup of coffee. But there is also a brightness or acidity, reminiscent of citrus, called "perceived sourness," that is an inherent trait of the brew. In fact, this sourness is so important to coffee that there's a whole scoring category for it in cupping competitions. 

A 2021 paper by researchers from the University of California, Davis' Coffee Center in the College of Engineering , including William Ristenpart , co-director of the center and professor of chemical engineering, revealed that the perceived sourness of coffee is strongly correlated to its titratable acidity, or TA, which is the measure of the total amount of acids present. Prior to this publication, the coffee industry had associated the sourness with the coffee's pH levels. 

Laudia Anokye-Bempah, a Ph.D. student in biological systems engineering, used this finding as a starting point for her research, investigating how TA changes during roasting. Her goal is to bring roasters' attention to the importance of TA to perceived sourness, one of the dominant flavor profiles in brewed coffee. Her findings were recently published in Nature . 

Crafting the Roast

To gather the data, Anokye-Bempah and a team of researchers, including Timothy Styczynski , head roaster for the Coffee Center, defined seven roast profiles by their heat applications versus time measured inside the roaster, representing a variety of profiles typically used in the coffee industry. 

For instance, the "Fast Start" profile involved a high initial heat application followed by a steady decrease in roast energy, while the "Slow Start" profile began with a low initial heat application followed by a gradual acceleration in roast energy. 

Using these roast profiles, Anokye-Bempah and a team of undergraduate researchers roasted coffee beans from different countries of origin and post-harvesting processing methods: African-washed coffee from Uganda's Sipi Falls, honey-processed coffee from Ataco in El Salvador and an Indonesian-washed coffee from Sumatra.

Each roast lasted 16 minutes to allow sufficient time to investigate subtle changes in the TA from the green coffee stage to the burnt or charred coffee stage. The researchers collected samples, approximately 13 grams each, at one-minute intervals, resulting in a total of 17 samples (from minute 0 to 16) for each of the seven roast profiles.  

The samples were immediately cooled in liquid nitrogen to prevent any further chemical changes outside the roaster and then transported to the lab, where they were ground and brewed for TA analysis.  

Pouring Over the Details

The corresponding data showed that for all three coffees and across all roast profiles, the TA significantly increased from the beginning of the roast to the "first crack" phase (when the coffee beans make a popping or cracking sound) where it peaked, and then continuously decreased until the end of the roast. 

While these findings aligned with previous studies, Anokye-Bempah and her team made additional key observations. Firstly, TA consistently peaked during the first crack, regardless of the roast profile or coffee origin. Secondly, by the onset of the second crack, the TA decreased to approximately its initial value at the beginning of the roast. 

While the TA remained consistent across roast profiles, the different roast profiles did affect the TA dynamics. For example, the "Fast Start" profile led to quicker changes in TA compared to the "Slow Start" profile. The team also found no significant differences in TA dynamics across the various coffee origins and postharvest processing methods that were tested. 

Charting Coffee's Research Horizon

Anokye-Bempah believes that key insights into coffee quality parameters, such as TA, can provide valuable information to people in the coffee industry, giving them more control over the flavor of their coffee. 

"There's only so much you can do to alter the sensory properties of your coffee at the brewing stage," she said. "The roasting process offers far greater control over your coffee's flavor."

Anokye-Bempah's goal with her research at the Coffee Center is to create a coffee roasting control chart, similar to the industry's brewing control chart, which indicates how strong or weak coffee would be depending on the amount of coffee grounds, water and time. Anokye-Bempah says that a lot more research and data are required to create one for roasting. Luckily, she already has many of these measurements in the queue.  

"This data on titratable acidity is just one measurement out of 16 different measurements we made. More exciting results are still to come."

Media Resources

• Jessica Heath, Content Specialist, [email protected]  

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William D. Ristenpart

• Chemical Engineering

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