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From play to laws: language in biology.

One perspective on the emergence of the child prodigy is derived from comparing the role of unique forms of abstraction in those disciplines in which the child has been wondrously creative. Music, mathematics, poetry, and computer programming have all witnessed the child as a creative force; biology has not. Perhaps it is the lack of a suitable abstraction, symbols, and rules for their use that hampers both the child prodigy and the expert in their pursuit of understanding living cells. Repurposing existing languages has yet to accelerate that understanding; perhaps it is time to nudge the evolution of language to better serve the description and prediction of the behavior of living systems.

Biology↗

vLIP, a viral lipase homologue, is a virulence factor of Marek's disease virus.

The genome of Marek's disease virus (MDV) has been predicted to encode a secreted glycoprotein, vLIP, which bears significant homology to the alpha/beta hydrolase fold of pancreatic lipases. Here it is demonstrated that MDV vLIP mRNA is produced via splicing and that vLIP is a late gene, due to its sensitivity to inhibition of DNA replication. While vLIP was found to conserve several residues essential to hydrolase activity, an unfavorable asparagine substitution is present at the lipase catalytic triad acid position. Consistent with structural predictions, purified recombinant vLIP did not show detectable activity on traditional phospholipid or triacylglyceride substrates. Two different vLIP mutant viruses, one bearing a 173-amino-acid deletion in the lipase homologous domain, the other having an alanine point mutant at the serine nucleophile position, caused a significantly lower incidence of Marek's disease in chickens and resulted in enhanced survival relative to two independently produced vLIP revertants or parental virus. These data provide the first evidence that vLIP enhances the replication and pathogenic potential of MDV. Furthermore, while vLIP may not serve as a traditional lipase enzyme, the data indicate that the serine nucleophile position is nonetheless essential in vivo for the viral functions of vLIP. Therefore, it is suggested that this particular example of lipase homology may represent the repurposing of an alpha/beta hydrolase fold toward a nonenzymatic role, possibly in lipid bonding.

Amino Acid Sequence↗

Discovery of diverse anellovirus sequences in Thai human sequencing data.

UNLABELLED: Anelloviruses are part of the normal human viral flora. Although their diversity in humans has been investigated in many countries, and despite their initial detection in Thailand in 1999, knowledge of Thai anelloviruses remains very limited. This study analyzed 1,175 whole-genome sequencing data sets from Thai individuals to mine for potential anellovirus sequences. Our analyses detected anellovirus sequences in 149 data sets (12.68%), uncovering 434 partial anellovirus sequences and 77 complete genome sequences, characterized by the presence of terminal redundancy, complete orf1, and the conserved untranslated region upstream of the orf1 gene. Sequence analyses indicated that these viruses belong to seven genera, including Alphatorquevirus, Betatorquevirus, Gammatorquevirus, Hetorquevirus, Lamedtorquevirus, Samektorquevirus, and Yodtorquevirus. Notably, Hetorquevirus, Lamedtorquevirus, Samektorquevirus, and Yodtorquevirus had not previously been reported in Thailand. Phylogenetic analysis of ORF1 protein sequences showed that Thai anelloviruses form multiple phylogenetic clusters with non-Thai anelloviruses, indicating frequent cross-country transmission and multiple origins of the virus in Thailand. Furthermore, sequence similarity network analysis identified 33 potentially novel anellovirus species in our data set. Our findings greatly expand the knowledge of anellovirus diversity in Thailand and demonstrate the potential of human whole-genome sequencing data as a valuable resource for viral discovery. Lastly, we highlight and discuss some challenges with the use of the current pairwise sequence similarity-based classification scheme, in particular, how gaps can influence similarity calculation and potentially lead to inconsistencies with a phylogenetic-based classification scheme. IMPORTANCE: Anelloviruses are widespread in humans, yet their diversity remains poorly characterized in many regions, including Thailand. Here, we demonstrate that human sequencing data sets, originally generated without the intention for virome research, can be effectively mined for anellovirus sequences, including complete genomes. Our findings reveal a substantial number of previously unreported anelloviruses in Thailand, significantly expanding the known diversity of the virus. We also highlight potential limitations of the current anellovirus species classification scheme, which is based on pairwise orf1 sequence similarity analysis with a hard threshold cutoff at 69%. Our results reveal that the current scheme can sometimes yield taxonomic groupings that are inconsistent with phylogenetic relationships, particularly when significant alignment gaps are present. Overall, our results show that existing human sequencing data can be effectively repurposed for virus discovery research and suggest the need for more robust and phylogenetically informed classification frameworks as viral sequence databases continue to expand.

Humans↗

A single-case foodborne botulism outbreak caused by Clostridium botulinum type A1(B5) in diced garlic in Newfoundland and Labrador, 2024.

Foodborne botulism is a severe neuroparalytic disease caused by ingestion of foods containing botulinum neurotoxins, produced by Clostridium botulinum. In 2024, a 74-year-old woman from Newfoundland and Labrador with complete bilateral flaccid paralysis and respiratory distress was hospitalized and required intubation. From the broader differential diagnosis list, botulism was favoured prior to laboratory confirmation. Serum and feces samples initially tested negative for botulinum neurotoxins by mouse bioassay, yet viable C. botulinum type A was recovered from the feces. Food history investigation included some diced garlic in a repurposed coffee container that tested negative for botulinum neurotoxins by mouse bioassay, but viable C. botulinum type A was recovered from the sample. Both the fecal and garlic enrichment cultures were positive for bont/A and bont/B genes by real-time PCR. Whole genome sequencing revealed that both fecal and garlic isolates were highly similar with conserved gene synteny, including an intact bont/A1 gene and a disrupted (silent) bont/B5 gene encoded on the chromosome. This single-case foodborne botulism outbreak from Newfoundland and Labrador in 2024 was caused by C. botulinum type A1(B5) in diced garlic.

Aged↗

Proteome-wide Mendelian randomisation of lung function to identify potential therapeutic targets for respiratory disease.

BACKGROUND: Despite multiple clinical trials, disease-modifying treatments for COPD are currently limited. Since many drugs target proteins, identifying causality between proteins and lung function informs understanding of COPD pathophysiology and may suggest novel targets. We used Mendelian randomisation (MR) to prioritise proteins as potentially causal for imparied lung function. For prioritised proteins, we explored their potential suitability as drug targets by predicting their effects on a range of clinical outcomes. METHODS: We used genome-wide association study (GWAS) data on 2923 proteins (n=48&#x2009;195, UK Biobank) to identify single genetic variants (protein quantitative trait loci (cis-pQTLs)) associated with protein levels (p&#x2264;5&#xd7;10-9, variant &#x2264;100&#x2005;kb of a transcription start site). We performed cis-pQTL-MR analyses of four spirometric traits (n=149&#x2009;166, 36 independent cohorts). Sensitivity analyses included colocalisation and reverse direction MR. We report associations between cis-pQTLs for prioritised proteins and multiple clinical respiratory outcomes, and use phenome-wide analysis to explore potential adverse effects or drug repurposing opportunities. FINDINGS: 1841 proteins had a suitable cis-pQTL. We implicated 16 proteins as potentially causal for lung function (p<1.71&#xd7;10-5): seven proteins have not been implicated by previous lung function GWAS or MR (CCND2, DTD1, PILRA, PTPRK, TDRKH, GRHPR, NUDT5), and we provide corroborative evidence for 10 proteins. We add to the literature identifying surfactant protein D (SFTPD) as a candidate, yet predict that integrin subunit alpha V (ITGAV) inhibition could impair some lung function measures, mimicking adverse results from a recent trial. INTERPRETATION: Our approach identifies proteins (some novel) that are potentially therapeutic targets for respiratory disease, and which warrant follow-up for utility and safety.

Journal Article↗

Evidence for dual pathways of Tc1/mariner domestication in Drosophila.

BACKGROUND: The domestication of transposable elements is a key source of evolutionary innovation, yet the pathways by which their functional modules are repurposed by the host remain poorly understood. The Tc1/mariner superfamily is a widespread group of DNA transposons, but the prevalence and patterns of their domestication are underexplored. RESULTS: We performed a systematic genomic screen across 43 drosophilid species using stringent criteria for molecular domestication. This analysis identified five high-confidence, evolutionarily conserved genes derived from Tc1/mariner transposases. Phylogenetic and structural analyses suggest domestication via two distinct molecular pathways: co-option of the DNA-binding module and co-option of the catalytic domain. The DNA-binding module pathway includes CG4570, the previously known genes cag and toy (the latter fused with a homeodomain), and a lineage-restricted gene in the Drosophila obscura group that exhibits signatures of recent domestication. In contrast, the catalytic domain pathway is represented solely by CG14478. Structural modeling reveals that CG14478 protein preserves a canonical DDE endonuclease fold. Co-expression network analysis suggests potential cellular roles of these genes: CG14478 is linked to RNA/chromatin-related processes, CG4570 to cell cycle/chromosome functions, cag to ciliary and nuclear functions, and toy to neuronal development. CONCLUSIONS: This study establishes a stringent framework for identifying domesticated TEs, demonstrating that Tc1/mariner elements are co-opted via two distinct pathways: retention of either catalytic or DNA-binding modules. Our findings suggest that domestication is a dynamic continuum, ranging from recent, lineage-specific events to ancient, conserved genes, and underscore how genomic conflict with TEs can drive eukaryotic evolution and regulatory complexity.

Animals↗

Assessing the comorbidity between asthma and depression through polygenic risk scoring and time-to-event models.

BACKGROUND: Patients with asthma have an increased risk of developing depression, affecting their quality of life. To date, the processes contributing to this comorbidity remain unclear. METHODS: We integrated two large genome-wide association studies (88,486 patients with asthma and 447,859 controls; 412,024 patients with depression and 1,587,577 controls) with cross-sectional and longitudinal information available from the All of Us Research Program (N&#x2009;=&#x2009;87,167) through polygenic risk scoring (PRS), Cox proportional-hazards models, one-sample Mendelian randomization (MR), and gene-set and drug-repurposing analyses. RESULTS: We observed that depression PRS was associated with increased asthma risk (hazard ratio, HR&#x2009;=&#x2009;1.13, 95% CI&#x2009;=&#x2009;1.09-1.17), also when accounting for comorbidity status (HR&#x2009;=&#x2009;1.08, 95% CI&#x2009;=&#x2009;1.04-1.12). Conversely, the effect of asthma PRS was null after accounting for comorbidity status. One-sample MR analysis showed an effect of depression genetic liability on asthma, ranging from beta&#x2009;=&#x2009;0.36&#x2009;&#xb1;&#x2009;0.03 when considering a linear relationship to beta&#x2009;=&#x2009;3.21&#x2009;&#xb1;&#x2009;0.31 when considering possible nonlinear relationships. Conversely, the effect of asthma genetic risk on depression was null after accounting for potential confounders. The gene-set analyses showed that asthma and depression polygenic risks share biological processes, molecular functions, and cellular components related to the immune system and the lung-brain axis. CONCLUSIONS: Genetic predisposition contributes to asthma-depression comorbidity through direct effects and shared pathogenic processes. These findings highlight the potential to develop targeted interventions to prevent and treat the co-occurrence of respiratory and neuropsychiatric disorders.

Comorbidity↗

Thyroid-stimulating hormone receptor mediates peripheral-central neuroimmune crosstalk in autoimmune thyroid diseases.

BACKGROUND: Organ-specific autoimmune diseases, particularly Graves' disease (GD) and its extrathyroidal manifestation, Graves' orbitopathy (GO), are characterized by systemic autoimmunity that may extend its impact to the central nervous system (CNS). While thyroid-stimulating hormone receptor (TSHR) is the primary driver of pathological remodeling in the thyroid and orbital tissues, emerging evidence suggests it is also expressed in the brain and may participate in neuroimmune signaling. However, the molecular mechanisms linking peripheral TSHR-driven autoimmunity to these extended systemic features remain unclear. Thus, GD and GO provide a unique window to investigate how peripheral autoantibodies influence CNS involvement as part of its broader pathological spectrum. METHODS: Genome-wide association studies (GWAS) and post-GWAS analyses were integrated with bulk RNA sequencing, single-cell and spatial transcriptomics, and brain imaging phenotypes to comprehensively characterize peripheral and central alterations in GD and GO. Mendelian randomization was applied to test causal relationships between genetic variants and brain signatures. Structural biology analyses were further conducted including protein-protein docking, small-molecule docking, and normal mode dynamics to identify prospective modulators of TSHR. Immunofluorescence staining was performed in a GO mouse model to validate the colocalization of potential interacted proteins in the specific brain region. RESULTS: Brain imaging-derived phenotypes (IDPs) alterations in GO and GO were systematically analyzed to identify neuroanatomical and functional alterations. TSHR was further identified as a shared genetic driver across peripheral and central compartments. TSHR was expressed in spiny projection neurons, microglia, and peripheral T cells, with cell-cell communication analyses highlighting TSHR-mediated interactions among neurons, endothelial cells, and microglia. Immunofluorescence staining in a GO mouse model confirmed the colocalization of TSHR with FN1 and GNAS in the basal ganglia, providing tissue-level validation of the computationally predicted ligand-receptor interactions. Immune profiling further showed immune alterations in GD and GO. Structural modeling supported plausible physical interfaces between TSHR and interacting proteins, and small-molecule screening identified three repurposable compounds - venetoclax, irinotecan, and dutasteride - with predicted favorable docking scores and stable binding poses in our simulations. CONCLUSIONS: These findings demonstrate that TSHR acts as a molecular hub mediating peripheral-central neuroimmune crosstalk in GD and GO. The results support a broader "disease-molecule axis" framework that links genetic susceptibility with multi-level immune and neural mechanisms. This work provides mechanistic insights relevant to the development of TSHR-targeted therapies, with implications for both peripheral immune modulation and central regulation. However, the limited sample size, lack of longitudinal follow-up, and absence of in vivo validation warrant cautious interpretation and further investigation.

Receptors, Thyrotropin↗

Multi-omics uncovers the pleiotropic genetic mechanisms linking MASLD and cardiometabolic syndromes.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) and cardiovascular-kidney-metabolic (CKM) syndrome are interrelated conditions with shared pathophysiological features; however, the genetic architecture underlying their relationship has not been fully elucidated. Deciphering this shared genetic basis holds promise for advancing mechanistic insights and therapeutic discovery. METHODS: We performed an integrated genome-wide cross-trait analysis using GWAS summary statistics for MASLD and 38 CKM traits. Our analysis estimated genetic correlations, inferred causal relationships, and identified pleiotropic variants. Candidate causal genes and druggable targets were subsequently prioritized through integrating multi-omics data. RESULTS: MASLD exhibited significant genetic correlations with 16 CKM traits, especially metabolic and cardiovascular conditions. Bidirectional causal relationships were observed between MASLD and T2D, adiposity, and lipid traits. We discovered 116 pleiotropic loci, including 65 shared causal variants such as rs429358 near APOE, which exerted influence across multiple traits. Gene-based analyses prioritized 152 unique candidate pleiotropic genes, enriched in lipid and cholesterol metabolism, and highly expressed in the liver, adipose, and immune-related cell types, such as macrophages and endothelial cells. Multi-omics integration validated 131 genes using eQTL and pQTL data from multiple tissues and cohorts. Notably, FTO and APOE emerged as central pleiotropic hubs, and druggability evaluation highlighted APOE, LPL, PPARG, and GPBAR1 as established therapeutic targets for metabolic diseases. CONCLUSION: This study provides a comprehensive map of the shared genetic architecture between MASLD and CKM syndrome, reveals novel causal genes and repurposable drug targets, and offers insights into precision medicine approaches for cardiometabolic and liver diseases.

Humans↗

Establishment of a prognostic model based on ER stress-related cell death genes and proposing a novel combination therapy in acute myeloid leukemia.

BACKGROUND: Acute myeloid leukemia (AML) is a highly heterogeneous malignancy, presenting significant challenges in accurately predicting patient prognosis. Dysregulation of endoplasmic reticulum (ER) stress and resistance to programmed cell death (PCD) are hallmarks of AML cells. However, the prognostic significance of the interplay between ER stress and cell death pathways in AML remains largely unexplored. METHODS: We analyzed RNA sequencing and clinical data from 887 AML patients across 4 cohorts to develop an ER stress-related cell death index (ERCDI) using 10 machine-learning algorithms with 117 unique combinations. Survival and time-dependent Receiver Operating Characteristic Curve (ROC) analyses were performed to assess the model's efficacy. Clinical characteristics, the tumor immune microenvironment, and drug sensitivity differences between the high- and low-risk groups were also analyzed. The CMap database was used to identify potential therapeutic drugs. In vitro and in vivo experiments, including CCK-8, colony formation, flow cytometry, Transwell assays, and xenograft mouse models, were conducted to evaluate the effects of the target genes and candidate drugs. RESULTS: The ERCDI demonstrated strong prognostic and predictive performance for prognosis in AML patients. Furthermore, the ERCDI effectively predicted immunotherapy and chemotherapy outcomes and was associated with the immune features of the different risk groups. DNA damage-inducible transcript 4 protein (DDIT4), a key gene associated with ERCDI, is related to poor prognosis in AML patients with high expression. Additionally, the knockdown of DDIT4 significantly inhibited AML cell proliferation, induced cell apoptosis, and promoted cell cycle arrest. Chaetocin was subsequently identified as a candidate compound for AML treatment. Subsequent experiments suggested that combining chaetocin and venetoclax is a potentially promising therapeutic strategy for AML. CONCLUSION: The ERCDI provides personalized risk assessment and treatment recommendations for individual AML patients. The combined use of chaetocin and venetoclax can potentially be repurposed for AML therapy.

Humans↗

PGM1 deficiency is linked to sarcomeric and mitochondrial dysfunction in patient-derived iPSC-cardiomyocytes.

BACKGROUND: PGM1-congenital disorder of glycosylation (PGM1-CDG) is frequently associated with cardiomyopathy. Although galactose therapy corrects glycosylation defects, cardiac dysfunction typically persists, suggesting a glycosylation-independent mechanism. Recent evidence of mitochondrial abnormalities in PGM1-deficient human and murine heart, together with the association of PGM1 with the Z-disk protein LDB3 (ZASP/Cypher), suggests a critical role for PGM1 in cardiomyocyte structural and energetic homeostasis. We hypothesized that PGM1-related cardiomyopathy arises from a glycosylation-independent disruption of Z-disk-mitochondrial coupling driven by loss of PGM1-LDB3 interactions, resulting in mitochondrial energy failure and impaired contractile function. METHODS: Induced pluripotent stem cell-derived cardiomyocytes (iCMs) were generated from PGM1-deficient patient fibroblasts. Multielectrode array (MEA) recordings, untargeted (glyco)proteomics, and pathway analysis were performed to assess functional and molecular changes. Key findings were validated using tracer metabolomics and mitochondrial respiration assays. RESULTS: PGM1-deficient iCMs exhibited reduced beating frequency, impaired contractility, and prolonged contraction kinetics. Proteomic analyses revealed depletion of Z-disk components, including LDB3. AlphaFold3 structural modeling predicted a direct interaction between PGM1 and LDB3, implicating PGM1 in Z-disk integrity, which was confirmed in vitro. In addition, mitochondrial proteins were severely depleted, prompting us to investigate mitochondrial function. Functional validation confirmed extensive metabolic rewiring, energy depletion, and severely impaired mitochondrial respiration. Finally, the in silico drug repurposing identified possible therapeutic options that could target PGM1-deficient cardiomyopathy. CONCLUSION: Our data suggests PGM1 is key regulator of cardiomyocyte function, linking sarcomeric Z-disk integrity with mitochondrial metabolism. These mechanistic insights offer a foundation for developing targeted therapies for PGM1-CDG and potentially other cardiomyopathies involving Z-disk dysfunction.

Humans↗

Genetic and epigenetic underpinnings of biological aging: a multi-omics study integrating Mendelian randomization, spatial transcriptomics, and drug target discovery.

Inflammaging represents a hallmark of biological aging, yet the causal inflammatory mediators driving multi-dimensional epigenetic aging and their effector genes remain poorly characterized at the genetic level. We developed a four-tier analytical framework integrating causal screening, multi-omics effector gene mapping, spatial transcriptomics, and drug target evaluation. Two-sample Mendelian randomization (MR) of 91 circulating inflammatory proteins against six aging phenotypes identified IL-12B, IFNG, and IL-2 as the most robust pro-aging mediators with consistent effects across independent outcomes. Using multi-omics summary-based MR (SMR) as the core analytical engine, we integrated four-layer whole-blood molecular QTL resources eQTL (eQTLGen, n = 31,684), sQTL (GTEx, n = 755), pQTL (INTERVAL + SCALLOP, n = 34,232), and mQTL (McRae et al., n = 1,980) - with GWAS summary statistics for four epigenetic age acceleration measures. At a stringent threshold (P_SMR < 1&#xd7;10&#x207b;&#xb9;&#xb2;), seven high-confidence effector genes were identified: NHLRC1, TPMT, SELP, and RIPPLY3 for IEAA; ZNF373A and PLDN for HannumAA; and EDARADD for PhenoAA. The chromosome 6p21 NHLRC1-TPMT locus, overwhelmingly driven by methylation QTL signals (-log&#x2081;&#x2080;P = 26.06), emerged as the dominant genetic node of epigenetic aging. Spatial projection via gsMap onto a mouse E16.5 embryo atlas (121,767 cells) revealed preferential enrichment in smooth muscle and lung, with EDARADD showing marked specificity in mucosal epithelium. Cross-database drug target mining classified TPMT and SELP as repurposable known targets and NHLRC1 as a high-priority novel druggable candidate. This study provides multi-omics convergent causal evidence for inflammation-driven epigenetic aging and delivers genetically anchored targets for precision anti-aging intervention.

Aging↗

Multi-omics Mendelian randomization integrating RNA-seq, eQTL and pQTL data revealed CPXM1 as a potential drug target for osteoporosis.

Osteoporosis, a prevalent skeletal disorder characterized by decreased bone mineral density and increased fracture risk, continues to be a major global health concern. Traditional treatments for osteoporosis have limited efficacy and safety profiles, highlighting the need for novel therapeutic targets. This study integrates multi-omics data, including RNA-seq, expression quantitative trait loci (eQTL), and protein quantitative trait loci (pQTL) data, through Mendelian randomization (MR) to identify potential drug targets for osteoporosis. By leveraging bidirectional two-sample MR analysis, we identified CPXM1 (Carboxypeptidase X, M14 family member 1) as a novel gene that is causally linked to osteoporosis risk. Through transcriptomic and proteomic validation, we demonstrate that CPXM1 was upregulated in aged bone tissues and osteoporotic conditions in both human and murine models. Gene set enrichment analysis (GSEA) revealed significant dysregulation of bone homeostasis pathways, including increased extracellular matrix degradation and suppression of osteoblast differentiation in aged mice. Furthermore, phenome-wide association studies (PheWAS) confirmed minimal off-target effects of CPXM1, reinforcing its potential as a therapeutic target. Finally, computational drug repurposing predicted several promising drug candidates, including Doxorubicin, 5-Fluorouracil, and 2-Methylcholine, which may target CPXM1 pathways for osteoporosis treatment. These findings highlight CPXM1 as a potential biomarker and therapeutic target, offering new avenues for osteoporosis therapy.

Osteoporosis↗

Rhythm profiling using COFE reveals multi-omic circadian rhythms in human cancers in vivo.

The study of ubiquitous circadian rhythms in human physiology requires regular measurements across time. Repeated sampling of the different internal tissues that house circadian clocks is both practically and ethically infeasible. Here, we present a novel unsupervised machine learning approach (COFE) that can use single high-throughput omics samples (without time labels) from individuals to reconstruct circadian rhythms across cohorts. COFE can simultaneously assign time labels to samples and identify rhythmic data features used for temporal reconstruction, while also detecting invalid orderings. With COFE, we discovered widespread de novo circadian gene expression rhythms in 11 different human adenocarcinomas using data from The Cancer Genome Atlas (TCGA) database. The arrangement of peak times of core clock gene expression was conserved across cancers and resembled a healthy functional clock except for the mistiming of a few key genes. Moreover, rhythms in the transcriptome were strongly associated with the cancer-relevant proteome. The rhythmic genes and proteins common to all cancers were involved in metabolism and the cell cycle. Although these rhythms were synchronized with the cell cycle in many cancers, they were uncoupled with clocks in healthy matched tissue. The targets of most of FDA-approved and potential anti-cancer drugs were rhythmic in tumor tissue with different amplitudes and peak times. These findings emphasize the utility of considering "time" in cancer therapy, and suggest a focus on clocks in healthy tissue rather than free-running clocks in cancer tissue. Our approach thus creates new opportunities to repurpose data without time labels to study circadian rhythms.

Humans↗

The AI Revolution: Shaping the Present and Future of Pharmaceutical Research and Development.

The transformative role of artificial intelligence (AI) in the pharmaceutical industry is examined, with a focus on its significant contributions to drug discovery, development, and clinical trial processes. It highlights the inefficiencies and high costs associated with traditional drug development and explores how AI and machine learning (ML) can enhance these processes by analyzing extensive biological datasets. The historical context of AI in pharmaceutical development is examined, noting how advances in computational power and data accessibility have facilitated innovative methodologies, such as predictive analytics and natural language processing. Contemporary trends reveal the integration of AI technologies in drug design, repurposing, and patient response forecasting. This study also addresses the challenges of participant recruitment for clinical trials and proposes AI-driven solutions to optimize patient selection and data management. Furthermore, it discusses AI's role in tailored medicine, emphasizing its potential for advancing precision therapy through targeted drug development and personalized treatment strategies. The importance of digital tools, genomic data analysis, and AI-driven imaging technologies for customizing therapeutic approaches is underscored, along with the regulatory and ethical challenges posed by AI deployment in healthcare. This study illustrates the complexities of AI applications in the pharmaceutical sector, offering insights into both successful and unsuccessful initiatives. The findings suggest that the digitalization of the pharmaceutical industry and enhanced AI integration hold promise for developing safer and more effective therapeutic strategies, while also identifying obstacles to their widespread adoption and optimal functionality.

Artificial intelligence↗

A survey of videodisc and interactive videodisc projects in North America: Part I.

Selected videodisc (VD) and interactive videodisc (IVD) programs, projects and topics are presented in two articles in this and a subsequent issue of the journal. Part I reviews the impact of Information Science developments on image management. The American Society of Hematology Slide Bank and other specific applications in urology, paediatric neurology, obstetrical nursing, medical decision making, dental diagnosis and treatment (DDT), and paediatric cardiology, are reviewed as educational and informatics research projects. This is followed by a section on three-dimensional reconstructions of the brain which stresses digital images. Multi-purposing and repurposing are reviewed in two prototype programs. A discussion of the multidisciplinary Slice of Life projects completes this first article.

Computer Graphics↗

Ferroptosis in Oral Cancer: Mechanistic Insights and Clinical Prospects.

Ferroptosis, an iron-dependent form of regulated cell death characterized by lipid peroxidation, has emerged as a pivotal vulnerability in oral squamous cell carcinoma (OSCC). This review provides an overview of ferroptosis mechanisms and their implications for OSCC pathobiology and therapy. OSCC cells exhibit heightened reliance on anti-ferroptotic defenses such as GPX4, SLC7A11, FSP1, and Nrf2, and disrupting these pathways suppresses tumor growth and restores sensitivity to chemotherapy, radiotherapy, and immunotherapy. Genetic and epigenetic regulators, including p53, PER1, circ_0000140, and STARD4-AS1, critically modulate ferroptotic sensitivity, while metabolic enzymes such as ACSL4, LPCAT3, and TPI1 link ferroptosis to cellular plasticity and resistance. Preclinical studies highlight the promise of small-molecule inhibitors, repurposed agents (e.g., sorafenib, artesunate, trifluoperazine), natural compounds (e.g., piperlongumine, Evodia lepta, quercetin), and nanomedicine platforms for targeted ferroptosis induction. We further address ferroptosis within the tumor microenvironment, highlighting its immunogenic and context-dependent dual roles, and summarize genomic and transcriptomic evidence linking ferroptosis-related genes to patient prognosis. Beyond cancer, ferroptosis also contributes to non-malignant oral diseases, including pulpitis, periodontitis, and infection-associated inflammation, where inhibitors may protect tissues. Despite these advances, clinical translation is constrained by the lack of safe ferroptosis inducers and validated biomarkers. Future research should focus on developing pharmacologically viable GPX4 inhibitors, refining biomarker-driven patient stratification, and designing multimodal regimens that combine ferroptosis induction with standard therapies while preserving immune and tissue integrity. Ferroptosis therefore represents both a mechanistic framework and a translational opportunity to reshape oral oncology and broader oral disease management.

Humans↗

A comprehensive review of AI innovations for tackling antimicrobial resistance.

Antimicrobial resistance (AMR) represents a major global public health concern, rendering available antimicrobials ineffective and leading to infections that are difficult to treat. Artificial intelligence (AI) has been increasingly applied across the AMR continuum, including resistance prediction, rapid diagnostics, new antimicrobial discovery, drug repurposing, antimicrobial surveillance, and clinical decision support. In this review, we aim to highlight recent developments in the use of artificial intelligence (AI) to address antimicrobial resistance (AMR). In addition, we review computational methods that help interpret genomic, phenomic, clinical, and epidemiological data to support the development of treatment strategies and novel antimicrobial agents. The key issues addressed include data quality, model interpretability, external validation, regulatory requirements, privacy, and fairness. While AI is not a complete solution to AMR, it can certainly strengthen the global AMR response by complementing key areas of AMR such as antimicrobial stewardship, infection prevention, laboratory diagnostics, and global surveillance.

Antimicrobial resistance (AMR)↗