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PubMed2026

Genomic determinants underlying biogenic amine detoxification phenotypes in food-associated lactic acid bacteria: Mechanism, evolutionary origin, and relevance to fermented food safety.

Biogenic amines (BAs) are toxic metabolites that accumulate in fermented foods and pose significant food safety concerns. Although several lactic acid bacteria (LAB) have previously been reported to exhibit strain-specific BA-degrading phenotypes, the genetic determinants underlying these activities have remained largely uncharacterized. Here, we analyzed 8251 LAB genomes to validate BA-degrading phenotypes. We predicted five BA-associated genes, including two direct biogenic amine-degrading genes (BADGs), mco and patA, and three polyamine-modifying genes (PMGs), speG, paiA, and bltD. Among BADGs, mco was broadly distributed across LAB and strongly enriched across food-associated niches. patA, organized within a conserved potD-glnB-potABC-patA cassette, is a putative, functionally distinct BADG in LAB, revealing a nitrogen-responsive polyamine uptake-catabolism module. Phylogenomics, phylogenetic reconciliation, and synteny analysis established that all five genes entered the LAB through episodic horizontal gene transfer followed by lineage-specific fixation. GC compositional bias and mobile genetic element association further corroborated the horizontal origin of the two BADGs. Structural analysis confirmed the conservation of catalytic core residues of BADGs across LAB, indicating strong purifying selection. Phenotype-to-genotype correlation with experimentally reported LAB suggested mco as a reliable genomic predictor of degrading phenotype. Integration of degradation and biosynthetic profiles predicted multiple LAB species capable of both synthesizing and degrading BA, along with 1823 genomes with degradation potential but lacking detectable BA biosynthesis genes. This study provides the first large-scale genome framework linking BA-degrading phenotypes with their genetic determinants in LAB and offers a rational basis for selecting BA-detoxifying strains for fermented food applications.

Biogenic Amines↗
PubMed2026

A randomized trial of viral vector and adjuvanted protein HBV therapeutic vaccine in people with chronic hepatitis B on nucleos(t)ide analogs.

BACKGROUND: This study assessed the safety, efficacy, and immunogenicity of a therapeutic immunization strategy aimed at reaching a functional cure for chronic hepatitis B (CHB), relying on a heterologous prime-boost with viral vectors ChAd155-hIi-HBV and MVA-HBV, combined with sequential or concomitant administration of adjuvanted recombinant HBV proteins (HBc-HBs/AS01B). METHODS: This single-blind, randomized, controlled, first-in-human, phase 1/2 trial enrolled adults aged 18-65 years with HBeAg-negative CHB, virally suppressed on nucleos(t)ide analogs (NAs), with HBsAg >50 IU/mL. Participants received NAs and the following regimens of 4 doses (8-week intervals): sequential administration of ChAd155-hIi-HBV, MVA-HBV, and 2 HBc-HBs/AS01B doses; co-administration of ChAd155-hIi-HBV+HBc-HBs/AS01B, followed by 3 co-administered MVA-HBV+HBc-HBs/AS01B doses; 4 HBc-HBs/AS01B doses; 2 placebo doses followed by ChAd155-hIi-HBV and MVA-HBV administered alone or with HBc-HBs/AS01B; or 4 placebo doses. Safety, efficacy (≥1-log decrease in quantitative (q)HBsAg or HBsAg loss 24 weeks post-dose 4 [day (D)337]), antibody, and T-cell responses were evaluated. RESULTS: In all, 134 participants were vaccinated. Grade 3 solicited adverse events (AEs) (median duration: 2-3 days) were more frequent after co-administration (systemic: 59.3%; administration-site: 33.3%) than sequential administration (systemic: 10.3%; administration-site: 12.8%) of high-dose viral vectors and proteins. No vaccine-related or fatal serious AEs were reported. After 4 doses, no participant had HBsAg loss or ≥1-log decrease in qHBsAg (D337 vs. D1). Co-administration induced the strongest anti-HBs response (73.7% achieved anti-HBs ≥10 mIU/mL 2 weeks post-dose 4 vs. 40.0% after sequential administration). Both sequential and co-administration induced HBc-specific CD4+ and CD8+ T-cell responses, with a prime-boost effect of the viral vectors. CONCLUSIONS: Heterologous prime-boost with ChAd155-hIi-HBV and MVA-HBV, combined with sequential or co-administration of HBc-HBs/AS01B, had an acceptable safety profile, were moderately immunogenic, but no participants showed the expected efficacy outcome.

Humans↗
PubMed2026

Social Isolation and Loneliness Among Older Asian Immigrants Through the Lens of Sense of Coherence: Systematic Review of Qualitative Studies.

AIM: To explore the meaning older Asian immigrants attribute to social isolation and loneliness, their management strategies, utilisation of resources and impact on health. DESIGN: Systematic review of qualitative studies. DATA SOURCES: AgeLine, CINAHL, MEDLINE, ProQuest, PsycINFO, Scopus, and Web of Science databases were searched in September 2024. METHODS: Inclusion criteria: participants were Asian immigrants to Western countries aged 65 and over, community-living and experiencing social isolation and loneliness. Antonovsky's Sense of Coherence was used to frame the thematic analysis. RESULTS: Ten papers were included and analysed deductively using elements of the sense of coherence framework: • Comprehensibility: Social isolation and loneliness are viewed as multifaceted, influenced by cultural and environmental dislocation, language barriers, intergenerational conflicts, deteriorating health and mobility, and socioeconomic challenges. • Manageability: included engaging in culture-specific community programs, family and ethnic community support and living within ethnic enclaves mitigated isolation and loneliness. • Meaningfulness: Strong family ties, active community involvement, spirituality, volunteerism, and cultural practices fostered resilience. However, accepting the changing values of their new world, living independently, and carving their own niche provided meaning to their transformed reality. CONCLUSION: Older Asian immigrants experience social isolation and loneliness through a cultural lens, shaped by migration experiences, language barriers, and shifting family dynamics. Cultural roots, family ties, spirituality, community, acceptance, and independence enhance sense of coherence. Recognising the dynamic interplay between cultural identity, resilience, and adaptation is key to understanding their lived experience. IMPLICATIONS FOR THE PROFESSION AND PATIENT CARE: This review informs culturally sensitive interventions, guiding healthcare, community services, and policy to support social participation, mitigate loneliness through ethno-specific activities, and improve the quality of life for aging immigrant populations in Western countries. REPORTING METHOD: The review was undertaken and reported using the PRISMA guidelines. PATIENT OR PUBLIC INVOLVEMENT: None. PROTOCOL REGISTRATION: PROSPERO (CRD42023425752).

Humans↗
PubMed2026

Artificial intelligence in genitourinary oncology: publication trends and systematic review.

OBJECTIVE: To conduct an analysis of publication trends and a systematic review of randomized controlled trials (RCTs) to characterize the current state of artificial intelligence (AI) use in genitourinary (GU) oncology, as AI has emerged as a transformative tool in healthcare with potential applications in diagnostics, treatment planning, and prognostication. METHODS: We searched the Medical Literature Analysis and Retrieval System Online (MEDLINE), Excerpta Medica dataBASE (EMBASE; Ovid), and Cumulative Index to Nursing and Allied Health Literature (CINAHL) Ultimate for studies related to AI and GU oncology, excluding non-English papers, non-human studies, review articles, and articles using AI solely for manuscript writing. Publication trends were analysed from 2013 to 2023 and categorized by study design and cancer type. RCTs were evaluated through systematic review using Covidence (Veritas Health Innovation Ltd, Melbourne, Victoria, Australia) for screening and data extraction. Two reviewers independently assessed all studies, with risk of bias (RoB) evaluated using the Cochrane RoB 2.0 tool. RESULTS: Of 2409 articles identified, 1220 met inclusion criteria. These included 962 retrospective articles, 175 prospective studies, 79 studies with combined retrospective/prospective methods, and four RCTs. Studies most commonly addressed prostate (n = 923), renal (n = 274), and urothelial (n = 194) cancers. Publications grew from 14 in 2013 to 362 in 2023, with substantial acceleration in 2019. Four RCTs were identified - one in urothelial cancer and three in prostate cancer. Two RCTs evaluated AI-based diagnostics, demonstrating improved performance over conventional methods; the remaining two RCTs evaluated AI in prognostication and treatment planning, showing improved gains in imaging interpretation and operational efficiency. RoB varied across studies, primarily related to randomisation and deviations from intended interventions. CONCLUSIONS: Artificial intelligence research in GU oncology has grown, although high-level evidence from RCTs remains limited. Existing trials underscore AI's promise in diagnostics, prognostication, and treatment planning, and the rapidly evolving nature of this field warrants continued prospective investigation.

Humans↗
PubMed2026

Diagnostic communication in functional neurological disorder: A systematic review and meta-analysis of patient acceptance and clinical outcomes.

OBJECTIVES: Diagnostic disclosure is a key therapeutic moment in Functional Neurological Disorder (FND). This systematic review aimed to evaluate quantitative evidence on diagnostic acceptance, understanding, satisfaction, symptom outcomes, and healthcare utilisation following diagnostic disclosure in FND, and to conduct a meta-analysis of diagnostic acceptance. METHODS: Systematic searches of PubMed, Scopus, PsycINFO, and Web of Science identified quantitative studies in adults with FND. Screening followed predefined inclusion criteria. Data were extracted using a structured template and risk of bias was assessed using the Newcastle-Ottawa Scale. A random-effects meta-analysis of proportions was conducted using the Freeman-Tukey transformation. RESULTS: Fifteen studies were included, four of which contributed to the meta-analysis (n = 481). Reported diagnostic acceptance rates ranged from 38.7% to 90%, although the timing and method of assessment varied across studies. Pooled acceptance was 0.68 (95% CI 0.44-0.88), with substantial heterogeneity. Structured or reinforced communication was frequently associated with improved understanding and satisfaction, although its superiority for diagnostic acceptance was not established. In some studies, diagnostic acceptance was associated with more favourable clinical outcomes, although findings were inconsistent. Some studies reported reductions in healthcare utilisation or costs following satisfactory diagnostic explanation, whereas others found no sustained overall reduction. CONCLUSIONS: Diagnostic communication in FND is associated with differences in acceptance, understanding, and downstream clinical and healthcare outcomes. Approximately two-thirds of patients were reported as accepting the diagnosis following disclosure, although the timing and method of assessment varied substantially across studies. Empathic and evidence-informed communication may enhance understanding and engagement, although its effects on healthcare use and recovery remain uncertain. PRACTICE IMPLICATIONS: Diagnostic disclosure should be delivered clearly, empathically, and with reinforcement over time. Written information, reputable educational resources, and opportunities for follow-up clarification may support patient understanding and engagement, although stronger comparative evidence is needed.

Humans↗
PubMed2026

Effectiveness and usability of artificial intelligence-powered assistive technologies in Supporting daily activities of children with cerebral palsy: a systematic review.

BACKGROUND: Cerebral Palsy (CP) is the main cause of motor disabilities in childhood, necessitating innovative approaches to rehabilitation and assistive technology (AT). Simultaneously, artificial intelligence (AI) is increasingly being integrated into devices to create more adaptive, personalized, and effective AT. This systematic review aimed to evaluate the effectiveness and usability of AI-powered assistive technologies designed to support daily activities and rehabilitation in children with CP. MATERIALS AND METHODS: Five databases, including Scopus, Web of Science, PubMed, Embase, and IEEE Xplore, were systematically searched, and 23 articles were included in the final analysis. Articles were identified, selected, and categorized into emerging thematic areas based on the primary function and application of the technology. RESULTS: Five key thematic topics were identified: 1) AI-driven motor rehabilitation and gait training for functional mobility; 2) intelligent assessment and monitoring systems for clinical decision support; 3) AI-supported communication, social interaction, and intention recognition tools; 4) gamified and virtual reality-based interventions to enhance engagement and usability; and 5) smart assistive systems supporting daily living and independent mobility. The findings demonstrate a strong trend toward the application of AI technologies in personalized, engaging, and data-driven interventions for children with CP. However, the field is predominantly in the proof-of-concept stage, with limitations including small sample sizes, lack of long-term clinical validation, challenges in user-centered design, and usability for children with CP. CONCLUSION: AI-powered assistive technologies hold significant potential for transforming the care of children with CP by enabling highly personalized and engaging interventions. To actualize this potential, future work must realize that practical application remains challenging owing to limited clinical validation, technological integration, and usability barriers for children with CP. Future research must prioritize user-centered design and multidisciplinary collaboration to ensure that AI and robotic advancements improve the usability and quality of life for children with CP.

Humans↗
PubMed2026

Generation of spCAS9 expressing human mesenchymal stem cell line to study gene function during osteoblast differentiation.

Human bone marrow-derived stromal cells (hMSCs) are a great resource for studying how genes influence cell fate and differentiation into various cell types like osteoblasts, adipocytes, and chondrocytes, among other cell types. However, genetic manipulation of primary hMSCs has been challenging due to their short lifespan and cellular senescence after limited passaging. Their low and unstable transfection efficiency also complicates gene delivery or inactivation, hindering long-term functional studies. The limited lifespan has been effectively solved by immortalizing hMSCs with telomerase reverse transcriptase (hMSCs-TERT). The use of these cells is ideal for functional studies of osteoblast and adipocyte differentiation through genetic manipulation, providing a stable and reliable model. Here, we have engineered a stable CAS9 expressing hMSC-TERT cell line (hMSC-TERTCAS9) via lentiviral transduction. The constitutive expression of spCas9 enables efficient and reproducible gene editing. We demonstrate the potential of these hMSC-TERTCAS9 cells for generating gene disruptions using plasmid delivery of guide RNAs as a fast and efficient strategy for targeted genome editing. The edited cells can be sorted and expanded as single cells to obtain homogenous clonal cell lines with mono- as well as bi-allelic gene deletions, a crucial step for producing reliable experimental results. We further validate this cell line as a powerful tool for studying gene function during hMSC proliferation and differentiation, providing 3 distinct examples of its utility. Through the generation of indels, single-cell sorting, and clonal selection, we have efficiently inactivated the vitamin D receptor and created both larger (256 nucleotides) gene disruptions in Forkhead box protein O1 and precise removals of a small genomic sequence (73 nucleotides) coding for microRNA MIR675. This novel hMSC-TERTCAS9 cell line represents a significant advancement, offering a stable, efficient, and versatile platform for advanced genetic studies, high-throughput screening, and the creation of reliable cellular disease models.

CRISPR-Cas9↗
PubMed2026

Harnessing Endogenous Plasticity Rather than Reprogramming of Mature Cells Will Advance Regenerative Medicine, Cancer Treatment and Rejuvenation.

The successful culture of human embryonic stem (hES) cells from inner cell mass cells of blastocyst stage 'spare' embryos in 1998, followed by induced pluripotent stem (iPS) cells in 2006, which allowed somatic cells to be reprogrammed to pluripotency using the Yamanaka factors, transformed regenerative biology and inspired extensive global efforts towards developing pluripotent stem cell-based applications. However, hES and iPS cells, as well as organoids generated from them, largely retain fetal-like characteristics, which limits their relevance for clinical translation. Concurrently, the prevailing assumption published in leading journals that adult tissues lack endogenous stem cells has led to the belief that mature cells dedifferentiate and reprogram during in vivo regeneration upon chronic injury, and that the appearance of embryonic/fetal markers in diabetes, heart failure, cancer, and many other chronic disease states reflects dedifferentiation of mature cells. We suggest that the prevailing concepts of dedifferentiation and reprogramming, both in vitro and in vivo, require careful re-evaluation. Adult somatic cells possibly do not truly dedifferentiate, neither in vitro nor in vivo. Instead, tissue-resident, pluripotent, very small embryonic-like stem cells (VSELs) in multiple organs account for the observed biology. In vitro "reprogramming" responses to Yamanaka factors likely reflect selective activation and expansion of VSELs/early progenitors rather than the dedifferentiation/ reprogramming of mature adult somatic cells. Likewise, the embryonic/fetal-like signatures reported in multiple disease states including cancer reflect expansion of immature tissue-specific progenitors that arise from VSELs but fail to differentiate normally due to a damaged microenvironment in vivo. Therapeutic strategies involving transplantation of MSCs, MUSE cells, or their secreted exosomes improve disease outcomes, possibly by restoring the damaged niche that supports functional tissue repair by VSELs. Although direct evidence to support this is lacking at present, recognising the central role of VSELs/progenitors and their niche in maintaining tissue homeostasis in vivo could resolve existing roadblocks and guide more effective endogenous regenerative therapies for diseased tissues and age-related dysfunctions.

Humans↗
PubMed2026

Proteome-level evidence that tebuconazole, both alone and in interaction with thiacloprid, affects epigenetic events in bumblebee heads.

Tebuconazole, a widely used ergosterol biosynthesis-inhibiting fungicide, can affect nontargets, especially when combined with insecticides. We employed label-free quantitative proteomics to investigate the effects of long-term exposure to sublethal concentrations (100 μg/L) of tebuconazole, either by itself or alongside the neonicotinoid thiacloprid (100 μg/L), on the heads of Bombus terrestris workers. A Bayesian factor power analysis revealed that the experiment produced conclusive proteomic results. Tebuconazole treatment revealed eleven differentially abundant proteins, which increased elevenfold with thiacloprid. The proteins that changed in the same direction in both treatments suggest the occurrence of epigenetic events because they are involved in histone trimethylation (H3K4me3), pre-mRNA processing, and folate (vitamin B9) metabolism. Following co-exposure, the abundance of histone H2A.V and its associated proteins was affected. Two important detoxification-related proteins, CYP6BE1 and CYP6AQ1 (honey bee homologs), were identified, as well as proteins that suggest hormonal and neurotoxic effects. Overall, this study suggests that tebuconazole affects key epigenetic processes in bumblebee heads at the proteome level, though this was not confirmed at the biological level or through orthogonal methods. The tested chemicals were previously found to affect trimethylations, but not H3K4me3. We suggest analyzing the different trimethylations, their interplay, and associated hallmarks, such as folate levels. SIGNIFICANCE: The effects of pesticides and their combinations on organisms can be unexpected until they are examined using modern, complex methods. High-throughput proteomics can provide data on important biochemical processes affected by pesticides, offering a different perspective to that at the expression level. Despite their low acute toxicity, a group of fungicides that inhibit (ergo)sterol biosynthesis (EBI or SBI) are considered dangerous to pollinators, including bumblebees. This is due to the increasing toxicity of insecticides through the inhibition of cytochrome P450 detoxification enzymes. We found that tebuconazole had a similar effect on epigenetic events when used alone or in combination with the insecticide thiacloprid. Key proteins suggest that H3K4 histone trimethylation (H3K4me3) was impacted. To our knowledge, this expands the existing evidence suggesting that tebuconazole/triazole fungicides affect histone trimethylation H3K27me3. Since literature shows that thiacloprid affects H3K9me3, it is possible that thiacloprid and tebuconazole interact in these epigenetic events that affect each other. Overall, our results suggest that tebuconazole affects proteins involved in histone trimethylation, pre-mRNA processing, and folate metabolism. These are all hallmarks of epigenetic processes and were further extended by the co-exposure of tebuconazole and thiacloprid to more differently abundant proteins. Additionally, the results provide data on cytochrome P450s of the CYP6 family, which act as detoxifying proteins, as well as proteins that indicate hormonal and neurotoxic effects in bumblebee heads. Finally, the results of the Bayesian power analysis confirmed the meaningfulness of the proteomic data analyzed in this study. If the new findings obtained at the proteome level are verified by different methods, the full extent of the side effects of tebuconazole can be revealed.

Animals↗
PubMed2026

Control of foreign DNA: emerging roles of xenogeneic silencers.

Bacteria continuously acquire foreign DNA through horizontal gene transfer, yet its successful integration depends on regulatory mechanisms that balance genome protection with evolutionary innovation. Xenogeneic silencers are central to this process: they preferentially bind AT-rich DNA, a common feature of many horizontally acquired genetic elements, and repress its transcription. Recent studies, however, reveal a much broader regulatory repertoire. Beyond transcriptional repression, these proteins contribute to chromosome organization by forming higher-order nucleoprotein complexes and phase-separated condensates that shape bacterial nucleoid architecture. Furthermore, they play roles in regulating bacteriophage infection cycles, including mechanisms by which phages hijack host silencing activities for their own benefit. Their extensive regulatory reach, spanning virulence genes, biofilm formation, specialized metabolite production, and mobile genetic elements (MGEs), underscores their central role in connecting environmental signals, including fluctuations in the second messenger c-di-GMP, with gene expression, and genome organization. The diversification of xenogeneic silencers across bacterial chromosomes, plasmids, phages, and other MGEs highlights their evolutionary significance. Together, these recent findings position xenogeneic silencers as dynamic regulatory modules that shape the fate of foreign DNA across the horizontal gene transfer network.

Gene Transfer, Horizontal↗
PubMed2026

Metabolic engineering of Candida yeasts for biotechnological applications.

Candida yeasts represent a versatile yet underexploited platform for industrial biotechnology. These yeasts utilize a remarkably broad range of carbon sources, particularly for hydrophobic carbon sources, coupled with robust growth and diverse biosynthetic capacities, making them promising hosts for sustainable production of chemicals, fuels, and proteins. Despite these advantages, industrial deployment of Candida species has been hindered by concerns regarding opportunistic pathogenicity and the historical lack of efficient genetic manipulation tools, leading to a substantial gap between metabolic potential and practical utilization. Recent advances in functional genomics, genome editing, and systems metabolic engineering are rapidly overcoming these barriers, enabling more precise and efficient strain development. In this review, we systematically summarize recent progress in the metabolic engineering of Candida species as microbial cell factories, with particular emphasis on expanding genetic toolkits, utilizting renewable and non-conventional carbon sources, and biosynthesizing high-value compounds. In addition, we propose a biosafety-oriented classification framework to support their safe industrial deployment. Finally, we discuss current challenges and emerging opportunities, emphasizing that the synergy of synthetic biology and artificial intelligence-driven design holds the key to unlocking the biotechnological potential of Candida yeasts.

Candida↗
PubMed2026

Single-organ proteomics in Drosophila melanogaster larva.

The combination of genetic accessibility, organ complexity, evolutionary conservation, and cost-efficiency makes Drosophila melanogaster (Dm) a well-known model system for biomedical and fundamental biological research. Proteomic analysis of single organs enables the identification and quantification of proteins expressed in specific organs. This will help to uncover specific biological functions and unique protein profiles that are not detectable in whole-organism analyses. In this study we have isolated single organs form Dm larvae, and we have performed a deep proteomics mapping by following a minimal manipulation preparation procedure. The combined dataset across all organs comprised 9132 identified proteins. As anticipated, principal component analysis (PCA) revealed clear separation between the proteomes of most organs, confirming distinct protein profiles. These findings demonstrate the applicability of the sample preparation strategy for high-resolution proteomic characterization of individual organs in Drosophila. Given the extensive genetic tools available for this model organism, our approach has the potential to open new avenues for proteomic studies in Drosophila melanogaster and any other biological systems where the sample amount is limiting. SIGNIFICANCE STATEMENT: Drosophila melanogaster is a well-known model system for biomedical and fundamental biological research that serves as a valuable in vivo model organism due to its high degree of evolutionary conservation with higher vertebrates, tractable genetics, and logistical efficiency. However, the proteome of Drosophila at single organ level has been elusive to date, due to several factors like low sensitivity of previous generation mass spectrometers and sample preparation procedures, difficult isolation of some organs. In this study we have applied a compilation of advanced methods including minimal sample manipulation together with simple, straightforward and efficient protein extraction and digestion methods. Obtained peptides were minimally handled to be analyzed by applying specific and sensitive nLC methods coupled on-line to state-of-the-art MS/MS system. Altogether, the applied strategy allowed us to get the first single organ study to date for this animal. These datasets represent a significative resource for future genomic, transcriptomic and proteomic studies in Drosophila, as multi-omic integration requires deep proteomics to translate data into functional biochemistry, and serves as a critical bridge and an indispensable standalone resource across the genomic, transcriptomic, and proteomic landscapes.

Animals↗
PubMed2026

Machine learning-ready genomic biomarkers: ATF3 polymorphisms predict postoperative analgesic demand through AI-compatible phenotyping.

PURPOSE: To determine whether ATF3 polymorphisms can serve as genetic biomarkers for machine learning-based precision analgesia by establishing a genotype-phenotype association suitable for predictive modeling of postoperative opioid requirements. METHODS: In a prospective cohort of 167 adults undergoing abdominal surgery, ATF3 SNPs rs3122721 and rs3125293 were genotyped. A structured dataset architecture was developed to represent genetic profiles as input features for supervised learning models, enabling translational analysis of genotype‑dependent opioid consumption over 72 h. RESULTS: Patients with homozygous genotypes of the ATF3 SNPs had significantly higher opioid requirements than non‑carriers, despite reporting similar subjective pain scores. This consistent genotype‑dependent pattern provided a clinically relevant phenotype suitable for integration into predictive algorithms. CONCLUSION: ATF3 genotyping offers a promising biomarker for computationally informed precision analgesia. By linking genomic variability to clinically meaningful outcomes within a structured clinical and genomic framework, this approach supports the future development of risk-stratified clinical decision-support systems to optimize postoperative pain management.Trial registration ChiCTR1900021991, registered 30 April 2019. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s13755-026-00480-9.

ATF3↗
PubMed2026

Moderate expression and activity of flocculins underlie the characteristic flocculation phenotype of Saccharomyces pastorianus.

Flocculation is a key technological trait in lager brewing, governing fermentation performance, yeast recovery, and beer quality. In the allo-aneuploid hybrid yeast Saccharomyces pastorianus, the genetic basis of flocculation remains poorly resolved due to its complex dual sub-genome architecture. Here, we systematically re-annotated and functionally characterized the complete FLO gene repertoire of the Group II strain CBS 1483. Thirteen FLO genes were identified, including allelic variants and a previously uncharacterized adhesin, Flo12, containing a Hyphal_reg_CWP domain instead of the canonical PA14 lectin-binding domain. Structural modeling revealed strong conservation of Ca²+-binding residues in PA14 domains, alongside repeat-region diversification likely contributing to functional variability. Using optogenetic expression in a FLO-null background, we demonstrated that SpcI-FLO9-1 and SpcI-FLO9-2_1 are the strongest drivers of flocculation, exhibiting NewFlo-like sugar sensitivity. Transcriptomic analysis during 17°P wort fermentation showed dynamic induction of these genes coinciding with flocculation onset. Surprisingly, deletion of both loci in CBS 1483 did not abolish but only delayed sedimentation in wort, accompanied by improved maltose utilization and attenuation. These findings reveal functional redundancy and compensatory mechanisms within the FLO network of lager yeast, highlighting the genetic complexity underlying flocculation, and providing a molecular framework to inform yeast selection, strain development, and optimization of the lager fermentation processes.IMPORTANCEFlocculation, the process by which yeast cells aggregate and settle, is essential for producing clear, high-quality lager beer, and for efficient yeast recovery during brewing. However, the genetic basis of this trait in lager yeast has remained poorly understood because these strains possess unusually complex hybrid genomes. In this study, we systematically identified and characterized the complete set of flocculation genes in the industrial lager yeast Saccharomyces pastorianus CBS 1483. We demonstrated that lager yeast flocculation is not controlled by a single dominant gene, but instead emerges from the combined action of several moderately active adhesion proteins that are expressed at low levels during fermentation. Surprisingly, deleting the two strongest candidate genes only delayed, rather than eliminated, sedimentation, revealing a robust compensatory network that preserves brewing performance. These findings refine the current understanding of yeast flocculation and provide a molecular framework for developing brewing strains with improved fermentation efficiency, product consistency, and flavor quality.

Saccharomyces pastorianus↗
PubMed2026

Clinical applications of digital twin technology in In Vitro Fertilisation.

BACKGROUND: Digital twin technology, originating from aerospace and manufacturing industries, has emerged as a transformative tool in healthcare. In vitro fertilisation (IVF) faces persistent challenges including suboptimal embryo selection, unpredictable treatment outcomes, and limited personalisation of protocols. Despite advances in assisted reproductive technology, existing literature exhibits fragmentation: artificial intelligence applications in embryo selection, ovarian stimulation, and endometrial assessment have been developed independently without systematic integration into comprehensive treatment frameworks. Digital twin technology offers unprecedented opportunities to create virtual replicas of biological systems, enabling real-time monitoring, predictive modelling, and personalised treatment strategies. AIM: This narrative review aims to critically examine the current applications of digital twin technology in IVF, evaluate its potential benefits and limitations, synthesize existing evidence into an integrative conceptual model, and identify future directions for implementation in reproductive medicine. METHOD: A comprehensive narrative review was conducted using PubMed, Scopus, Web of Science, and IEEE Xplore databases. A narrative review approach was selected over systematic review to accommodate the heterogeneity of evidence types in this emerging field, including theoretical frameworks, simulation studies, and proof-of-concept implementations that would be excluded from systematic reviews. Search terms included "digital twin," "IVF," "in vitro fertilisation," "assisted reproductive technology," "embryo selection," and "predictive modelling." Studies published between 2015 and 2025 were included, focusing on original research articles, systematic reviews, and proof-of-concept studies describing digital twin applications in reproductive medicine. RESULTS: Digital twin technology in IVF demonstrates significant potential across multiple domains including embryo development simulation, ovarian response prediction, endometrial receptivity modelling, and personalised stimulation protocols. Current applications integrate artificial intelligence, machine learning algorithms, time-lapse imaging, and omics data to create comprehensive virtual models. Early evidence suggests improvements in embryo selection accuracy, ovarian response prediction, and treatment protocol optimization, though large-scale randomized controlled trials remain limited. Implementation challenges include data integration complexity, computational requirements, regulatory considerations, and validation requirements. CONCLUSION: Digital twin technology represents a paradigm shift in IVF practice, offering personalised, predictive, and precision medicine approaches. This review synthesizes existing evidence to propose an integrative conceptual model for digital twin implementation across the IVF treatment spectrum, identifies critical knowledge gaps, and establishes research priorities to advance clinical translation. Despite current limitations, continued advancement promises improved success rates and patient outcomes.

Humans↗
PubMed2026

Comparative effectiveness of game-based learning modalities in nursing and medical education: a systematic review and Bayesian network meta-analysis.

BACKGROUND: Game-based learning (GBL) is increasingly used in healthcare education, but educators must choose among diverse modalities (e.g., quiz platforms, apps, serious games and metaverse environments). Comparative evidence on which modalities perform best across learning domains (knowledge, attitudes, and practice) remains limited. AIM: To compare the effects of distinct GBL modalities on knowledge, attitudes, and practice outcomes in nursing and medical education and to explore whether comparative effects differ by learner group (pre-licensure students and in-service professionals). DESIGN: PRISMA-NMA-aligned systematic review and Bayesian network meta-analysis. METHODS: We searched eight databases and trial registries through September 2, 2024, for randomized controlled trials comparing GBL with traditional teaching (TT). Outcomes were transformed to a 0-100 scale and analysed as change from baseline in Bayesian consistency models; random-effects models were selected using deviance information criterion (DIC). Risk of bias was assessed using RoB 2. We report mean differences (MDs) with 95% credible intervals (CrIs) versus TT, ranking probabilities, and subgroup NMAs by learner group. RESULTS: Thirty-one RCTs (n = 3439) were included; 15 contributed complete data to the network. Risk of bias was low in 15 trials and raised some concerns in 16. The network was modest for knowledge (11 trials) and sparse for attitudes (3) and practice (4). Compared with TT, metaverse-based learning showed improved attitudes (MD 15; 95% CrI 12 to 18), based on a single trial. For knowledge and practice, Kahoot-based quizzes (MD 9.1; 95% CrI -8.9 to 27) and app-based learning (MD 4.6; 95% CrI -4.4 to 14) had the highest estimated mean improvements, but credible intervals were wide and included the null for most comparisons. Subgroup rankings differed by learner group, but several comparisons were imprecise and uncertainty was substantial, particularly in sparse networks. CONCLUSIONS: GBL modalities may improve learning outcomes compared with TT, but relative effects appear domain-specific and the certainty of rankings is limited by sparse evidence and imprecision. Future trials should prioritise head-to-head comparisons, robust outcome measurement, and longer-term retention and transfer outcomes in both student and in-service populations.

Humans↗
PubMed2026

The effect of tDCS on emotion-related risk-taking behavior and delay discounting in adults with ADHD.

INTRODUCTION: Adults with Attention Deficit Hyperactivity Disorder (ADHD) often engage in risky behaviors due to impaired decision-making processes. This study aims to investigate the effects of transcranial direct current stimulation (tDCS) over the dorsolateral prefrontal cortex (dlPFC) and ventromedial prefrontal cortex (vmPFC) on emotion-related risk-taking behavior and delay discounting in adults with ADHD. METHODS: Thirty adults with ADHD underwent three tDCS conditions, administered in a randomized order with at least one week between sessions: (1) left dlPFC anode/right vmPFC cathode, (2) left dlPFC cathode/right vmPFC anode, and (3) sham stimulation. In each session, participants completed the Delay Discounting Task (DDT) and the Modified Balloon Analogue Risk Task (mBART) under three emotional conditions (neutral, positive, and negative) which were induced using emotionally congruent photographs and sounds. Galvanic skin responses (GSR) were also recorded. In the DDT, both area under the curve (AUC) values and log-transformed discounting rates (log k) were calculated for small, medium, and large reward magnitudes (RM). Exploratory electric field modeling was also performed to characterize current distribution. RESULTS: The findings demonstrated task-specific effects of tDCS on decision-making. Although no overall tDCS effect was observed on DDT performance, significant tDCS × RM interactions emerged, particularly for smaller rewards. In contrast, exploratory analyses suggested that tDCS affected all mBART scores. Emotional condition did not influence consistently behavioral performance in either task, whereas both emotional stimulation and tDCS significantly affected GSR responses. However, exploratory electric field modeling indicated a broad prefrontal current distribution extending beyond the intended cortical targets. CONCLUSIONS: These findings suggest preliminary evidence that prefrontal tDCS can influence risk-related decision-making and autonomic responses in adults with ADHD. However, its effects on delay discounting appear to be context-dependent and limited to specific RMs. Future studies combining neuroimaging with individualized electric field modeling are needed to clarify the neural mechanisms underlying the observed effects of tDCS and to optimize stimulation protocols in adults with ADHD.

Humans↗
PubMed2026

Mul-PheG2P: decoupled learning and prediction-space fusion enables robust and interpretable multi-phenotype genomic prediction.

Genomic prediction of multiple phenotypes is crucial in modern plant breeding; however, existing methods struggle with negative transfer and lack interpretability, particularly across high-dimensional small-sample data and diverse species. To address this, we propose Mul-PheG2P, a novel paradigm based on decoupled learning and predictive space fusion. It employs a two-stage design: first training phenotype-specific encoders using genetic data, then decoupling phenotype-specific learning from cross-phenotype aggregation via an interpretable prediction layer. Mul-PheG2P outperforms existing methods across diverse crop datasets, including maize (Zea mays), wheat (Triticum aestivum), and tomato (Solanum lycopersicum). It provides a multi-scale interpretability chain: at the macro level, it quantifies phenotypic contributions via attention-based weighting; at the micro level, Integrated Gradients reveal the genetic basis of predictions. Notably, the model successfully identified the CCT (CONSTANS, CO-like, and TOC) motif regulating photoperiodism and the SQUAMOSA (SQUAMOSA promoter binding protein) promoter for inflorescence development, confirming its ability to capture functional biological mechanisms. These results highlight the high performance and interpretability of Mul-PheG2P, showcasing its value for low-cost, large-scale screening to advance precision breeding.

Phenotype↗