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PubMed2026

Routine methods misidentify Serratia spp.: Limitations of MALDI-TOF MS revealed by whole-genome sequencing.

Accurate species-level identification within the genus Serratia remains challenging due to extensive phenotypic overlap and high genomic relatedness among closely related and recently described taxa. This study presents an evaluation of routine and genome-based identification approaches applied to clinical Serratia isolates, integrating phenotypic assays, MALDI-TOF MS (Bruker Daltonics), 16S rRNA gene sequencing, and Whole-Genome Sequencing (WGS). A total of 103 isolates collected from a teaching hospital were analyzed. WGS was performed on a subset of isolates. Conventional biochemical methods classified all isolates as Serratia marcescens, whereas MALDI-TOF MS identified 60.1% as S. marcescens, 11.6% as S. ureilytica, and 28.1% just at the genus level. Peak analysis from MALDI-TOF MS revealed specific peaks associated with S. marcescens and S. ureilytica, but limited discriminatory power. WGS of six isolates initially identified as S. ureilytica by MALDI-TOF MS revealed reclassification as Serratia sarumanii (n = 5) and Serratia montpellierensis (n = 1), supported by Average Nucleotide Identity (ANI), Average Amino Acid Identity (AAI), and Digital DNA-DNA Hybridization (dDDH) thresholds. In contrast, 16S rRNA analysis showed limited species-level resolution. Phylogenomic and SNP-based analyses confirmed these classifications with strong support. Overall, this study underscores the critical role of high-resolution genomic approaches for precise species identification and highlights the need for continuous expansion and curation of MALDI-TOF MS reference databases to support reliable clinical diagnostics and epidemiological surveillance of emerging Serratia species.

Spectrometry, Mass, Matrix-Assisted Laser Desorpti↗

PubMed2026

Exploratory identification and cellular functional characterization of ppiabl as a candidate gene associated with growth traits in Paralichthys olivaceus.

The Japanese flounder (Paralichthys olivaceus) is an important mariculture species. However, the genetic mechanisms underlying its growth traits remain poorly understood. To explore the genetic basis of growth variation, whole-genome resequencing was performed in a cultured cohort of 60 individuals, followed by exploratory genome-wide association analysis and candidate-gene prioritization. The results revealed heritability estimates of 0.40 for body weight and 0.24 for body length, with substantial overlap in associated loci between the two traits. Exploratory association and variant-annotation analyses prioritized ppiabl, which carries a nonconservative missense variant, as a candidate gene for further investigation. Tissue expression analysis showed that ppiabl was highly expressed in muscle tissue. This gene encodes a protein belonging to the conserved peptidyl-prolyl cis-trans isomerase family. In Japanese flounder primary muscle cells, ppiabl knockdown was associated with altered expression of growth-related genes and an increased G1-phase fraction, whereas overexpression produced changes in the opposite direction. In line with this, fast-growing individuals were found to have significantly larger muscle fiber areas than slow-growing ones. These findings suggest that ppiabl may be involved in muscle-related cellular processes associated with growth variation in Japanese flounder, although its contribution to whole-animal growth requires further validation. Overall, this exploratory study prioritizes ppiabl as a candidate gene potentially associated with growth-related cellular processes in Japanese flounder, although validation in larger independent populations and in vivo models is required.

Animals↗

PubMed2026

Cross-tissue multi-omics integration highlights BPHL and mitochondrial targets in Alzheimer's disease.

BACKGROUND: Mitochondrial dysfunction is a hallmark of Alzheimer's disease (AD), yet specific molecular targets remain to be fully characterized. METHODS: A summary-data-based Mendelian randomization (SMR) framework integrated AD genome-wide association study (GWAS) statistics (39,918 cases) with blood DNA methylation quantitative trait loci (mQTL), gene expression (eQTL), and protein (pQTL) data for 1136 mitochondria-related genes. Associations were assessed using Bayesian colocalization and HEIDI testing. Tissue relevance was evaluated in four brain regions (hippocampus, amygdala, cortex, frontal cortex) using GTEx and external transcriptomic datasets. RESULTS: Screening identified eight candidates supported across blood mQTL and eQTL layers. Stepwise central nervous system (CNS) evaluation singled out biphenyl hydrolase-like (BPHL) as the consistent candidate. Higher genetically predicted BPHL expression was associated with reduced AD risk across the hippocampus (OR=0.920, 95% CI 0.873-0.970), amygdala (OR=0.925, 95%CI 0.880-0.973), cortex (OR=0.943, 95% CI 0.908-0.978), and frontal cortex (OR=0.938, 95%CI 0.901-0.976). These findings aligned with protein-protein interactions connecting BPHL to respiratory complexes and lower BPHL expression in independent AD brains. Functional enrichment converged on oxidative phosphorylation pathways. CONCLUSIONS: By integrating multi-omics data with tissue-specific validation, this study nominates BPHL as a consistent protective candidate in the brain. These findings provide genetic support for mitochondrial molecular perturbations in AD, offering insights for future validation.

Alzheimer Disease↗

PubMed2026

Prioritizing Parkinson's disease risk-associated mitochondrial candidate genes via multi-omics integrative analysis.

BACKGROUND: Mitochondrial dysfunction has been implicated in Parkinson's disease (PD), but the genetically regulated mitochondrial genes associated with PD risk remain incompletely defined. METHODS: We conducted a summary-data-based genetic epidemiology study integrating summary-based Mendelian randomization (SMR), Heterogeneity in dependent instruments (HEIDI) filtering, and Bayesian colocalization to prioritize mitochondrial-related molecular features associated with PD risk. Mitochondrial-related genes were defined using MitoCarta3.0. Genetically predicted gene expression and plasma protein abundance were evaluated using expression quantitative trait loci (eQTL) data from eQTLGen and GTEx v8, and protein quantitative trait loci (pQTL) data was assessed using International Parkinson's Disease Genomics Consortium (IPDGC) as the discovery genome-wide association study (GWAS) and FinnGen as the replication dataset. Prespecified QTL analyses were interpreted using FDR correction, HEIDI filtering, and colocalization support. DNA methylation QTL analysis, mitochondrial phenotype MR, and single-nucleus RNA-seq analysis were performed as complementary analyses. RESULTS: In the primary eQTL analysis, higher genetically predicted TTC19 expression was associated with lower PD risk (OR = 0.80, 95% CI: 0.74-0.87, PPH4 = 0.80), whereas higher MALSU1 expression was associated with increased PD risk (OR = 2.21, 95% CI: 1.59-3.06, PPH4 = 0.96). Both associations survived FDR correction, passed HEIDI filtering, and showed colocalization support. GTEx whole-blood data supported the direction of the TTC19 association. No mitochondrial protein reached significance after FDR correction and colocalization filtering in the primary pQTL analysis. Complementary methylation analysis highlighted cg06270993 as an exploratory regulatory signal for MALSU1. CONCLUSIONS: This MR-colocalization study prioritizes TTC19 and MALSU1 as genetically supported mitochondrial-related candidate genes associated with PD risk. Further validation is required to define their functional roles in PD pathogenesis.

Humans↗

PubMed2026

Retinal microstructural alterations as early phenotypes of depression in radiogenomics analysis.

BACKGROUND: With the increasing prevalence of depression, there is an urgent clinical need for early screening in depression. The retina offers a promising window for early screening in depression due to its rapid, non-invasive, objective, eye-brain correlated characteristics, but previous research has yielded conflicting alterations in retinal microstructure in depression. METHODS: We screened retinal optical coherence tomography and brain magnetic resonance imaging data in the UK Biobank to enroll 23,225 participants for retinal study of depression occurrence, and 1475 participants for the eye-brain association study. We also used genetic data (ID: ebi-a-GCST90014267 and ukb-d-20,448) from the Integrative Epidemiology Unit Open Genome-Wide Association Study for Mendelian randomization analysis. We used Cox regression to assess the association between retinal microstructure and depression risk, Mendelian randomization to infer causality, and mediation analysis to explore retina-brain pathway association. RESULTS: The Cox regression analysis showed that retinal ganglion cell-inner plexiform layer (GCIPL) thickness remained a significant predictor of depression. The Mendelian randomization analysis indicated a positive statistical association between GCIPL thickness and depression. Moreover, there was a significant positive correlation (all p < 0.001) between the volume of specific depression-related brain regions and the GCIPL thickness. Adjusting for age, sex, and head size, the mediation analysis provided preliminary evidence for a potential anatomical pathway linking retinal GCIPL thickness to depression-related brain regions through primary visual cortex and secondary visual cortex volumes. CONCLUSION: Thickened retinal GCIPL is a potential early phenotype of depression and has a potential association pathway with depression-related brain regions using a radiogenomics approach.

Humans↗

PubMed2026

Genetic evidence for a causal relationship between melatonin metabolism and depression.

To investigate the causal relevance of melatonin metabolism, which provides the biological basis for circulating melatonin levels, to specific depression symptom subtypes, we performed a targeted systematic review of melatonin metabolism pathways in the human brain and liver. Using two-sample Mendelian randomization (MR), we assessed the causal effects of metabolism pathways and/or individual genes on major depressive disorder (MDD) and nine symptom subtypes derived from Patient Health Questionnaire-9 (PHQ-9). Instrumental variables (IVs) were expression quantitative trait loci (eQTL) for eight individual genes, one synthesis route, and three degradation routes. Results were assessed using Bayesian colocalization and phenome-wide association analyses. At the pathway-level, the genetically proxied synthesis-route signal was associated with PHQ-9 Assessment 5 (PHQ9A5, OR: 0.89, 95% CI: 0.85-0.93), but sensitivity analyses suggested this association was primarily driven by TPH1 and may reflect serotonin-related biology. In contrast, higher brain melatonin degradation raised the risk of both PHQ9A1 (OR: 1.03, 95% CI: 1.02-1.04) and PHQ9A7 (OR: 1.03, 95% CI: 1.02-1.03). Within degradation, up-regulation of the kynurenine sub-pathway increased the odds of PHQ9A3 (OR: 1.05, 95% CI: 1.02-1.07), PHQ9A4 (OR = 1.04, 95% CI: 1.02-1.06) and PHQ9A7 (OR: 1.05, 95% CI: 1.02-1.07). Gene-level analyses were largely concordant, except for SULT1A1, whose higher expression was genetically protective for PHQ9A3 but risk-increased for PHQ9A1 and PHQ9A4. Overall, these results demonstrate that melatonin metabolism exerts symptom-specific and pathway-specific causal effects on depression. A stratified view of melatonin's role may help optimize the application of exogenous melatonin supplementation.

Melatonin↗

PubMed2026

Pervasive hybridization and introgression in Diervilleae (Caprifoliaceae).

Diervilleae (Caprifoliaceae) is a horticulturally important lineage with striking floral diversity and a long history of interspecific crossing, suggesting reticulate evolution. We integrated nuclear SNPs and whole plastome data to reconstruct a phylogenomic backbone for the tribe and to identify hybrids, cultivated accessions, and introgression among lineages. Nuclear and plastid phylogenies consistently recover Weigela and Diervilla as reciprocally monophyletic and resolve four major lineages within Weigela, providing a reproducible framework for revising sectional limits and species boundaries. Cultivated accessions form a well supported clade sister to W. florida and show predominantly W. florida ancestry while retaining contributions from multiple wild lineages, consistent with recurrent crossing, backcrossing, and selection. Analyses of wild populations reveal recurrent hybrids and enable plausible parental combinations to be inferred. Tests across the genome further indicate strong evidence for historical introgression across Diervilleae, with the strongest signals involving W. middendorffiana, W. maximowiczii, and Diervilla. Fossil evidence, divergence time estimation, and paleodistribution modelling together suggest range expansion during the Miocene and Pliocene followed by climate driven contraction, providing a spatiotemporal context for episodic contact, introgression, and the East Asia-North America disjunction.

Hybridization, Genetic↗

PubMed2026

Quo vadis, BGA? A collaborative EDNAP exercise on the challenges and progress in forensic biogeographical ancestry inference.

There is a broad consensus that forensic tests for the prediction of externally visible characteristics (EVC) and analysis of biogeographic ancestry (BGA) of an individual are technically reliable. However, interpretation of the results and population-specific genotype distribution patterns remains challenging. EVC and BGA analyses provide valuable information for population genetics studies and as investigative leads for criminal cases, as well as for historical and contemporary identification tests. However, inaccurate or incorrect predictions, for example, from subjective bias in the interpretations made, have the potential to misdirect police investigations. The legal situation regarding EVC and BGA testing varies by country: ranging from countries where it is explicitly prohibited, to those without specific regulations on biogeographic ancestry prediction, and others that have already enacted laws governing its use. The reluctance to utilize these analyses is not only due to legal restrictions and data protection concerns, but also to initial limited sets of sufficiently comprehensive forensic DNA assays. Forensic BGA marker panels typically contain up to ∼300 SNPs. This relatively small number of genetic markers, along with limited reference population data, complicates the interpretation of results from donors of unknown origin. This paper presents the results of a collaborative EDNAP study, which, for the first time, evaluated the approach to reporting EVC and BGA data between international laboratories. For the study, DNA from nine individuals with self-reported ancestry was collected and analysed using various forensic panels differing in the number and composition of ancestry-informative markers genotyped, comprising: the Precision ID mtDNA Whole Genome Panel, the VISAGE Basic Tool and the VISAGE Enhanced Tool for Appearance and Ancestry Prediction, and the Ion AmpliSeq™ PhenoTrivium Panel. To ensure full data protection, all SNP genotypes and uniparental marker haplotypes obtained were not shared with third parties. Instead, the genetic data were analysed using a range of commonly used population analysis software packages. These analysis outcomes were then distributed to twelve European forensic laboratories (both academic and law enforcement institutions), who were asked to prepare reports based on their interpretation of the phenotypes and ancestry they inferred from the analysis data. A questionnaire sent alongside the genetic information, aimed to evaluate which difficulties were encountered by the participants in processing the BGA analysis data they were given.

Humans↗

PubMed2026

Stage-specific ROMO1 in rheumatoid arthritis: predictive immune insights into the MIF pathway and HLA-DR/IL2RA axis via integrated GWAS, transcriptomic, single-cell, and spatial profiling.

Emerging evidence links reactive oxygen species modulator 1 (ROMO1), a key mitochondrial ROS regulator, to rheumatoid arthritis (RA) pathogenesis. However, its exact mechanism remains elusive given the conflicting evidence about its specific function. We used a four-level integrative framework combining multi-omics data and literature‑supported mechanistic inference. At the genetic level, Mendelian randomization (MR) was performed to explore potential causal relationships between ROMO1, IL2RA, HLA-DR, MIF, and RA risk, followed by differential expression analysis and machine learning-based feature selection to identify key mROS genes. The temporal expression dynamics of ROMO1 were assessed in RA progression. At the cellular and tissue levels, we integrated single-cell RNA sequencing and spatial transcriptomics to map cell-type-specific expression and synovial localization of ROMO1-related immune cells and pathways. Finally, our multi-omics findings were contextualized with literature-supported mechanistic inference. (1) MR results were consistent with a potential protective effect of ROMO1 on RA (OR = 0.52) and its potential regulation of risk factors IL2RA (OR = 0.46) and HLA-DR (OR = 0.40). Conversely, IL2RA (OR = 1.42), HLA-DR (OR = 1.88), and MIF (OR = 1.17) were positively associated with RA risk. Additionally, ROMO1 was identified as a top candidate diagnostic predictor with stage-specific dynamics: downregulated in the early but upregulated in the late/remission stages. (2) Single-cell RNA sequencing showed ROMO1's cell-specific expression in CD14+ HLA-DR+ CD74+ monocytes and CD4+ IL2RA+ T cells. Cell communication analysis further suggested that these cells may participate in MIF pathway regulation. Spatial transcriptomics subsequently identified that ROMO1-related cells localized to synovial pathological regions, with MIF pathway changes correlated with RA progression. (3) Finally, literature-supported mechanistic inference suggests that ROMO1 may modulate mROS levels to promote anti-inflammatory M2 macrophage polarization, which could theoretically contribute to reduced systemic inflammation and the alleviation of multi-organ decline in RA. This integrated multi-omics investigation, supported by literature-based mechanistic inference, suggests ROMO1 as a stage-dependent biomarker candidate and potential immune regulator in RA.

Humans↗

PubMed2026

Genomic identification and functional characterization of the nuclear receptor gene family in relation to sex determination and gonad development in the Pacific oyster (Crassostrea gigas).

Nuclear receptors (NRs) are a large superfamily of transcription factors that control a wide range of physiological processes by modulating the expression of downstream target genes. Numerous studies have confirmed that NR family members play critical and conserved roles in sex determination and gonadal development across metazoans. However, in mollusks, systematic characterization of NRs and their potential functions in gonadal regulation remain largely unexplored. In this study, 46 NR gene family members in the Pacific oyster (Crassostrea gigas) were identified and assigned to eight subfamilies. All NR family members contain at least one of the two core domains (DNA-binding domain, DBD; ligand-binding domain, LBD), and conserved exon-intron structures were observed within the same subgroup, indicating their evolutionary conservation. Furthermore, expression profiling revealed high expression of CgNR2F, CgNR5A1-1, and CgNR0B1 in undifferentiated gonads, suggesting their potential involvement in sex determination. CgNR1A and CgNR2E5 were specifically expressed in female gonads and exhibited female-biased expression patterns, indicating a putative role in ovarian development. Moreover, CgNR3A and CgNR3B showed high expression levels during the undifferentiated stage and early male development stage, implying their possible participation in male gonadal development and gametogenesis. These results expand the understanding of the NR gene family in C. gigas and help elucidate the potential functions of NR genes in sex determination and gonadal development.

Animals↗

PubMed2026

Identification and characterization of G protein-coupled receptors in the nocturnal halictid bee Megalopta genalis.

G protein-coupled receptors (GPCRs) are one of the largest families of membrane proteins in insects, regulating vision, neural signal transduction, and various physiological behaviors. Megalopta genalis exhibits a unique facultatively eusocial lifestyle and possesses adaptations for nocturnal activity; however, its GPCR family has not yet been systematically characterized. In this study, we performed genome-wide identification, phylogenetic analysis, and expression profiling of GPCRs in M. genalis by integrating genomic annotation and transcriptomic analysis. The results showed that a total of 99 GPCRs were identified in the genome of M. genalis, which were classified into four major families. Here, we show that M. genalis has undergone lineage-specific GPCR repertoire remodeling, marked by the expansion of novel orphan receptors and the systematic loss of multiple receptor subtypes, such as the neuropeptide receptors MIP-R and NPFR. Moreover, opsins have formed a diverse array of combinations and non-GPCR odorant receptors have undergone significant expansion via tandem duplication. Together, these features may represent part of the molecular repertoire associated with the adaptation of M. genalis to a nocturnal lifestyle. Furthermore, transcriptomic analysis revealed distinct spatiotemporal expression divergence within each of the Mth/Mthl and Fz GPCR families, suggesting functional specialization across development and adult tissues. This study provides the first systematic identification and initial functional characterization of GPCRs in M. genalis, revealing an evolutionary pattern characterized by the coexistence of contraction and expansion within the GPCR family. These findings lay a foundation for further studies aimed at elucidating the roles of these GPCRs in regulating M. genalis physiology and behavior.

Animals↗

PubMed2026

UNCX/SIN3A-Mediated H4K8 decrotonylation suppresses FOXO3 to drive TNBC progression and docetaxel resistance.

Triple-negative breast cancer (TNBC) remains a clinically challenging subtype characterized by aggressive behavior and limited treatment options. Though docetaxel remains a cornerstone chemotherapy for TNBC, the frequent emergence of resistance highlights the urgent need to identify novel therapeutic targets. In this study, we report that uncoordinated homeobox (UNCX) is upregulated in docetaxel-resistant breast cancer cells, genomically amplified in breast cancer, and associated with poor survival in breast carcinoma patients. Functional studies revealed that UNCX promotes breast cancer cell proliferation, migration and reduces the docetaxel sensitivity. Mechanistically, UNCX functions as a transcriptional repressor by recruiting the SIN3A complex. Genome-wide profiling indicated that the UNCX/SIN3A complex directly binds to the promoters of tumor-suppressor genes including FOXO3, and represses their transcription by removing histone H4K8 crotonylation (H4K8cr). Additionally, the UNCX/SIN3A complex enhances FOXO3 phosphorylation and inhibits its nuclear translocation, further inhibiting its activity. Notably, SIN3A knockdown, FOXO3 overexpression, or crotonylation restoration effectively reverses UNCX-induced malignant phenotypes. These findings collectively establish the UNCX/SIN3A-H4K8cr-FOXO3 axis as a pivotal epigenetic regulator of TNBC progression and chemoresistance, revealing new avenues for targeted therapeutic development against this aggressive breast cancer subtype.

Humans↗

PubMed2026

Innovations in microbial physical mutagenesis for food fermentation: An overview from traditional to emerging technologies.

Microbial strains serve as an important factor affecting fermentation efficiency and product quality. To obtain superior strains, mutation breeding is a classic strategy. Compared to chemical mutagenesis, physical mutagenesis directly induces genomic changes, providing notable advantages such as the elimination of chemical residues and environmental sustainability, hence rendering it a favored method for enhancing food-grade microorganisms. Conventional physical mutagenesis mostly depends on UV, rays, high pressure, or space radiation. As physical technologies advance, emerging methods such as ion implantation, plasma, microwave, ultrasound, and pulsed light are widely utilized for genetic modification. Mutagenesis technologies are progressively transitioning from single-effect to multi-effect synergy. Recent evaluations indicate that emerging technologies can enhance microbial mutation efficiency at the application level relative to established technologies. Nonetheless, the systematic clarification and comparative analysis at the mechanistic level remain inadequate, hindering intuitive comprehension of the qualities and distinctions across techniques. Furthermore, physical mutagenesis encounters several significant obstacles, such as cellular damage, limited rates of advantageous mutations, and laborious screening processes. This review carefully elucidates the mechanisms and properties of physical mutagenesis technology and delineates the distinctions among approaches through comparative analysis. Simultaneously, solutions for optimizing mutagenesis are presented to tackle the principal challenges mentioned above. This review aims to offer a theoretical foundation and practical guidance for the enhanced application of physical mutagenesis technologies in microbial breeding.

Mutagenesis↗

PubMed2026

Hippocampal teneurin-4 knockdown promotes depression-like behavioral phenotypes by disrupting oligodendrocyte differentiation in mice.

Depression is one of the most prevalent mental disorders worldwide. The limited clinical efficacy of current antidepressants highlights identifying new therapeutic targets. Emerging evidence suggests that dysfunction of oligodendrocyte lineage cells contributes to the pathophysiology of depression. Teneurin-4 (Tenm4), a transmembrane protein that promotes oligodendrocyte differentiation and myelination, has been implicated in psychiatric disorders in genome-wide association studies; however, its causal role remains unclear. To determine whether Tenm4 contributes to depressive-like behavioral phenotypes, we examined Tenm4 protein expression in mice exposed to repeated forced swimming stress and generated hippocampal Tenm4 knockdown (Tenm4KD) mice. Chronic stress reduced Tenm4 expression levels in the hippocampus. Mice with hippocampus-specific Tenm4KD exhibited depressive-like behaviors, accompanied by reduced hippocampal myelin basic protein. Importantly, administration of clemastine, a myelin formation promoter, inhibited the reduction of myelin and attenuated depression-like behavioral phenotypes. Immunohistochemical analysis showed that Tenm4KD significantly decreased the number of mature oligodendrocyte cells and increased in the number of oligodendrocyte precursor cells, without changes in the total number of oligodendrocyte lineage cells. This study provides the first evidence that hippocampal Tenm4 deficiency induces depression-like behavior phenotypes through impaired oligodendrocyte differentiation and promoting demyelination. Our results identify Tenm4 as a molecular regulator of stress-induced behavioral phenotypes and suggest that it might represent a potential therapeutic target for mood disorders associated with demyelination.

Animals↗

PubMed2026

Fyn signaling in the medial prefrontal cortex regulates resistance to stress-induced object recognition impairments in male rats.

Genome-wide association studies on patients with depression have identified FYN and FYB, an FYN-binding protein, as being linked to depression. We have reported that experimental manipulations in gene expression in the medial prefrontal cortex (mPFC) alter stress-induced object recognition impairments in animals. Therefore, we examined the impact of alterations in FYN and FYB expression in the mPFC of adult male rats on resistance to stress-induced impairments in object recognition. Animals with virus-mediated knockdown or overexpression of Fyn in the mPFC were subjected to either a brief 20-min restraint with 20 intermittent tail shocks, which does not induce object recognition impairment, or a prolonged 60-min restraint with 60 intermittent tail shocks, which does. In an object recognition task, control rats maintained intact object recognition following a brief stress, whereas rats with Fyn knockdown or overexpression in the mPFC showed impaired object recognition. Prolonged stress impaired object recognition in both control rats and rats with Fyn knockdown or overexpression. Additionally, rats with Fyn knockdown in the mPFC exhibited fewer c-Fos-positive cells in the mPFC in response to brief stress, accompanied by a trend toward increased c-Fos in the amygdala compared with control rats. Fyn knockdown also reduced Fyb expression in the mPFC. Furthermore, Fyb knockdown in the mPFC impaired object recognition following brief stress, suggesting that the observed effects are consistent with involvement of a coupled Fyn-Fyb signaling axis rather than Fyn alone. These findings suggest that altered Fyn-related signaling in the mPFC may underlie the resistance to stress-induced object recognition impairments.

Animals↗

PubMed2026

Using Organoids to Unlock the Potential of Human Torpor for Spaceflight.

PURPOSE OF REVIEW: This paper reviews the current understanding of the potential for humans to enter a state of torpor/hibernation, and discusses the possibility of inducing torpor in astronauts for long-duration space travel, including some of the physiological, technological, and ethical considerations associated with its implementation. By exploring means to induce torpor in various human organoid systems, we hope such research can provides insights to comprehensive solutions to overcome some of the major hurdles that limit the potential for human to enter a state of torpor during long-duration deep-space missions, and contribute to the ongoing efforts to make such missions more feasible and safer for astronauts. RECENT FINDINGS: On future deep space missions such as NASA's planned missions to the Moon, Mars, and near-Earth asteroids, astronauts will be continuously exposed to environments that are radically different from those on Earth, each presenting multiple logistical and physiological challenges. Beyond the well-documented physiological effects of microgravity, space travelers will encounter a complex radiation environment that may contribute to significant short- and long-term adverse effects on human physiology and increase the risk of cancer and other diseases. Besides these physical challenges, life support systems must also be designed to mitigate psychological impacts of long-term isolation and confinement - all of which collectively pose formidable engineering problems. Hibernation/torpor is a state of prolonged inactivity and metabolic depression used by a wide variety of mammals to survive periods of cold temperatures and food scarcity, including some primates and perhaps even an extinct early line of hominins that lived nearly half a million years ago. Since modern humans share common ancestry with these hominins and hibernating primates, it is likely the human genome encodes the necessary genetic information to hibernate, or at least enter the similar, more transient state of torpor. The reduced body activity, lowered metabolism, and decreased energy requirements that characterize torpor suggest that developing means of inducing such a state in astronauts could address these challenges, including providing a degree of radioprotection. SUMMARY: This review explores the potential application of human torpor as a countermeasure to address the many challenges posed by long-duration spaceflight beyond low-Earth orbit (LEO), discusses various natural hibernating model systems for studying means of inducing a torpor-like state in humans, and highlights the vast potential of using human organoids to test and validate mechanisms that govern induction and maintenance of torpor to identify the means to one day safely induce this state in astronauts to provide additional protection from the myriad stressors of spaceflight.

Astronaut Health↗

PubMed2026

Potential Links Between Physiological and Perceptual Strain in High Heat Stress.

The physiological strain index (PhSI) is widely used to quantify thermoregulatory and cardiovascular strain during heat stress. However, direct physiological measurements may not always be feasible in occupational or athletic settings. Therefore, this study aimed to examine the relationship and agreement between perceptual strain and integrated physiological strain indices during high heat stress. Ten healthy, physically active, non-heat-acclimated males (29 (7) yr; 1.79 (0.11) m; 77.4 (9.3) kg) completed two randomized crossover exercise trials in hot-dry (HD) and warm-humid (WH) environments with equivalent wet-bulb globe temperatures. Heart rate, rectal temperature, skin temperature, rating of perceived exertion, and thermal sensation were measured at baseline and every 15 minutes during 60 minutes of cycling. Physiological strain index (PhSI), adaptive physiological strain index (aPhSI), and perceptual strain index (PeSI) were calculated using validated equations. Repeated-measures correlation analyses demonstrated very strong associations between PeSI and both PhSI and aPhSI under HD (Rrm = 0.940-0.943) and WH (Rrm = 0.980-0.982; all p < 0.001). Receiver operating characteristic analyses demonstrated good-to-excellent discrimination of physiological strain by PeSI (AUC = 0.895-0.969). Mixed-effects analyses showed that higher PeSI values were associated with increased PhSI (β = 1.325, p < 0.001) and aPhSI (β = 1.459, p < 0.001). However, Bland-Altman analyses demonstrated relatively small mean biases (0.4-0.9 AU) but wide limits of agreement (-2.8 to 4.2 AU), indicating that PeSI and physiological strain indices are not interchangeable. These findings suggest that PeSI may serve as a practical adjunctive or screening indicator of physiological strain when direct physiological measurements are unavailable.

Humans↗

PubMed2026

AI-enabled viral genomics: from virus discovery to host prediction and emerging variant forecasting.

The rapid expansion of metagenomic sequencing has generated vast repositories of viral sequence data that far outpace our capacity to interpret them using conventional approaches. Highly divergent sequences, sparse functional annotation, and taxonomically uneven sampling present fundamental challenges for reference-dependent methods, which lose sensitivity precisely for novel and understudied viruses with high public health relevance. Artificial intelligence (AI) provides a new avenue to address these challenges by enabling predictive inference from viral genomes and proteins while reducing dependence on sequence similarity. In this Review, we discuss representative advances in AI for virus discovery, taxonomic classification and functional annotation, prediction of host range and zoonotic potential, and efforts toward forecasting emerging variants. These advances are transforming viral genomics from a largely descriptive discipline into one with increasing predictive capability. We also critically assess the major challenges that constrain current approaches, including the availability of high-quality and representative datasets, rigorous model evaluation, biological interpretability and responsible governance for increasingly capable AI models.

Artificial Intelligence↗