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Exploring the mechanism of aroma production in fermented cherry juice by L. brevis LD1.0600 using flavomics and whole genome analysis.

This study focused on L.brevis LD1.0600 with excellent fermentation traits: it analyzed genome-wide key regulatory genes for micro-metabolites, combined with fermented cherry juice flavor metabolomics data, and used machine learning to explore correlations between gene regulation, metabolite production, and flavor formation. The SVM model screened and verified fermented cherry juice VOCs; through OAV and flavor wheel analysis, LD1.0600 emerged as the top-performing strain, with a sweet, fruity dominant aroma. Key aroma-active components (OAV > 100) included 2-methoxy-4-vinylphenol, benzaldehyde, 2-methyl-butanoic acid and hexanoic acid, and 2-methoxy-4-vinylphenol and hexanoic acid elevated by LD1.0600-regulated genes (Chrom1-001884, Chrom1-000925, fabF and Chrom1-000199). At the same time, through research, a "strain screening-SVM screening of DVCs-OAV screening of key aroma components-whole genome sequencing of flavor regulatory genes" system was established. This system can not only be applied to the screen fermentation strains, but also can be extended to the application of other fermentation products.

Fermentation

From host response to genomic targets: electrochemical biosensing of tuberculosis biomarkers.

Tuberculosis (TB) remains one of the leading causes of death from a single infectious agent worldwide, with timely diagnosis continuing to be a major challenge, particularly in resource-limited settings. Conventional TB diagnostic methods are limited by low sensitivity, long turnaround times, and an inability to reliably differentiate latent from active disease. Biomarker-based diagnostic strategies have therefore gained increasing attention as they offer the potential to improve early detection, disease differentiation, and treatment monitoring. Herein, we examine electrochemical biosensing strategies for TB diagnostics using a biomarker-class-driven framework, covering host-response biomarkers (IFN-γ and TNF-α), pathogen-derived antigens (ESAT6, CFP10, CFP10-ESAT6, MPT64, Ag85, HspX and LpqH), cell-wall signatures and whole-cell markers (LAM and whole cell Mtb), and genomic markers (Mtb DNA and IS6110). Through structured comparison of recognition elements, biointerface designs, signal amplification strategies, electrochemical techniques, matrices, and validation levels, this review identifies the most promising technical approaches for different TB biomarker classes. It further highlights key translational bottlenecks, including limited clinical validation, buffer-based testing, complex multistep amplification, redox-probe dependence, matrix fouling, and insufficient evidence of manufacturability. This review therefore provides practical guidance for developing electrochemical TB biosensors that are analytically sensitive, clinically relevant, and suitable for decentralized diagnostic applications.

Biosensing Techniques

Assessing AI literacy and attitudes among medical students: implications for integration into healthcare practice.

PURPOSE: This study aims to assess AI literacy and attitudes among medical students and explore their implications for integrating AI into healthcare practice. DESIGN/METHODOLOGY/APPROACH: A quantitative research design was employed to comprehensively evaluate AI literacy and attitudes among 374 Lusaka Apex Medical University medical students. Data were collected from April 3, 2024, to April 30, 2024, using a closed-ended questionnaire. The questionnaire covered various aspects of AI literacy, perceived benefits of AI in healthcare, strategies for staying informed about AI, relevant AI applications for future practice, concerns related to AI algorithm training and AI-based chatbots in healthcare. FINDINGS: The study revealed varying levels of AI literacy among medical students with a basic understanding of AI principles. Perceptions regarding AI's role in healthcare varied, with recognition of key benefits such as improved diagnosis accuracy and enhanced treatment planning. Students relied predominantly on online resources to stay informed about AI. Concerns included bias reinforcement, data privacy and over-reliance on technology. ORIGINALITY/VALUE: This study contributes original insights into medical students' AI literacy and attitudes, highlighting the need for targeted educational interventions and ethical considerations in AI integration within medical education and practice.

Students, Medical

Ensemble DNA methylation clock demonstrates Immune-metabolic aging signatures associated with mortality.

Aging is a multifactorial process that is best described in terms of the progressive acquisition of multiple layers of phenotypic changes, such as epigenetic modifications, inflammation, and metabolic dysregulation. DNA methylation clocks have been extensively used to construct epigenetic clocks based on the DNAm profiles that can be used to estimate biological age and predict age-associated outcomes. Nevertheless, the vast majority of clocks constructed so far have been based on linear models, which are unlikely to fully account for the heterogeneity and non-linearity of survival-related DNAm signatures. In this work, we constructed a heterogeneous stacked ensemble survival model based on DNAm data obtained from the Framingham Heart Study. We first identified 190 CpG loci using elastic net Cox regression and subsequently constructed a survival prediction model based on the fusion of five complementary survival models by means of a neural network meta-learner. The prediction power of the survival model was evaluated in an external validation cohort, where we observed strong performance for predicting all-cause mortality that significantly exceeded PhenoAge and was statistically comparable to GrimAge. These performance estimates were derived in cohorts of European ancestry and externally validated in postmenopausal women aged 50-79 years, and should therefore be interpreted as applicable only to demographically similar populations.

Humans

Instruments for measuring body image in breast cancer patients: a systematic review of measurement properties.

PURPOSE: To evaluate the psychometric properties of PROMs for measuring body image in breast cancer patients. METHODS: In December 2024, a psychometric systematic review was performed in the nine databases. The COSMIN checklist was employed to evaluate the methodological quality and psychometric properties of the included body image measures. The level of evidence was assessed using the GRADE framework, and final recommendations were formulated for the scale. RESULTS: Thirty-eight articles evaluating fifteen PROMs were included in this review. Structural validity, internal consistency, and hypothesis testing had been most frequently evaluated. Measurement error had not been assessed for all PROMs. Twelve instruments show potential application value but require further research. The BAS-BC, PSPP, and ASI-R are not recommended for use, as these instruments do not meet the strict COSMIN thresholds for full recommendation. CONCLUSION: The BIS can be recommended as a temporary screening tool for assessing body image outcome in clinical practice. The BIRS can be tentatively advised for measuring specific postoperative body image changes. However, further comprehensive studies are required to validate the psychometric properties of existing PROMs.

Female

A transcription factor-focused CRISPR screen identifies SKI as a BCL11A-independent repressor of ζ-globin.

The regulation of α-like globin genes, particularly the embryonic ζ-globin gene (HBZ), remains incompletely understood. To identify transcriptional regulators of HBZ, we establish a GFP reporter system based on the HBZ-P2A-GFP allele in erythroid cell lines and conduct a CRISPR/Cas9 screen targeting 1639 transcription factors. This screen identifies SKI as a potent HBZ repressor. Functional validation shows that SKI loss increases HBZ expression without impairing erythropoiesis, whereas SKI overexpression suppresses HBZ. Tet-on-inducible SKI overexpression and auxin-inducible SKI degradation indicate that SKI rapidly represses HBZ transcription. Transcriptome profiling further reveals that SKI deletion activates HBZ while minimally affecting other erythroid genes. Mechanistically, genome-wide occupancy analyses show that SKI binds the distal enhancers HS-10 and HS-40, with partial co-occupancy by BCL11A. Despite this overlap, dual knockout of SKI and BCL11A synergistically increases HBZ expression, as does base editing of the SKI-binding site within HS-10. We also identify a naturally occurring variant (chr16:193207G>A) within this enhancer in α-thalassemia patients with elevated ζ-globin levels. Together, these findings establish SKI as a direct, BCL11A-independent transcriptional repressor of ζ-globin. This work advances our understanding of globin gene regulation and suggests targeted ζ-globin reactivation as a potential therapeutic strategy for α-thalassemia.

Enhancer

Multiscale Modeling Primer: Focus on Chromatin and Epigenetics.

A central challenge in modern biology is to understand how molecular interactions produce cellular and organismal functions across vast spatiotemporal scales. Nowhere is this challenge more apparent than in the study of chromatin, where meters of DNA compact into a micron-sized nucleus. How this polymer folds is a dynamic process, regulated by epigenetic modifications-chemical changes to DNA and histones that involve only a handful of atoms. These small changes cooperate to produce emergent, higher-order structures that define cellular identity and function. To explain this system, we must integrate static, high-resolution snapshots from techniques like cryo-EM with dynamic, lower-resolution data from microscopy and genomics. Multiscale computational models are essential tools that bridge these experimental gaps and reveal the mechanisms of emergent behavior. However, the communication divide between experimental biologists and quantitative modelers often hampers progress. This primer addresses that gap. It first introduces the fundamental biology of chromatin and epigenetics at an introductory level for non-biologists audiences. We then survey the landscape of computational approaches, from atomistic to systems-level models, and connect them to the experimental data that inform and validate them at an introductory level for non-computationalists. We argue that the next frontier will require us to build integrative models that can predict how molecular perturbations mechanistically alter cellular phenotypes, which will open a new era of chromatin-targeted therapeutics.

Chromatin Dynamics

Virtual, Augmented, and Mixed Reality Technologies in Neurosurgical Training: Enhancing Skills and Surgical Outcomes: A Systematic Review.

OBJECTIVE: To systematically review the role of virtual reality (VR), augmented reality (AR), and mixed reality (MR) in neurosurgical education and training. DESIGN: Systematic review conducted in accordance with the PRISMA guidelines. SETTING: A comprehensive search was performed across PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar for English-language studies published between 1 January 2020 and 30 April 2026. PARTICIPANTS: Studies involving neurosurgeons, fellows, residents, and medical students (maximum sample size: n = 48) were included. RESULTS: Of 7,204 initially identified studies, 25 met the inclusion criteria. VR was primarily used for surgical simulation (100% of VR studies) and anatomical education (62.5%). AR demonstrated broader applications, including preoperative planning (40%) and intraoperative support (30%). MR was evenly distributed across simulation, planning, and intraoperative support (40% each). The most frequently improved outcomes were training effectiveness (52%) and technical proficiency (44%). Methodological quality scores, assessed using the Modified Medical Education Research Study Quality Instrument (MMERSQI), ranged from 39.5 to 84.5, indicating varied rigor. CONCLUSION: VR, AR, and MR technologies show potential to enhance surgical precision, technical skills, and educational outcomes in neurosurgical training. However, standardization of methodologies and cost-effective solutions remain essential. Future research should focus on long-term clinical impact and integration of AI-driven training models.

Virtual Reality

Tripled-Stranded Antisense Oligonucleotide for Biomarker-Activated Suppression of Essential Genes.

Conditional activation of antisense oligonucleotides (ASOs) is a promising strategy for selective suppression of cancer cells without affecting normal cells. In this study, we developed a tripled-stranded ASO (tsASO) that is rendered inactive through complexation with two additional oligonucleotides. The key innovation is the use of partial overlap between the parent ASO and the biomarker sequence, combined with toehold-mediated strand displacement, enabling precise conditional activation. The tsASO effectively triggered RNase H-mediated degradation of DYNC1I2 and DARS1 RNAs exclusively in the presence of the ERBB2 sequence. In cell-free systems, the tsASO demonstrated high cleavage efficiency (up to 81%), comparable to the parent ASO efficiency, with minimal background activity in the absence of the biomarker sequence, validating the concept at the molecular level. However, in cells using lipid-based transfection, the tsASO exhibited nonspecific cytotoxicity that did not correlate with biomarker presence or target gene expression. Detailed analysis showed no clear support for known sequence-driven toxicity mechanisms (CpG/TLR9, G-quadruplexes) in the nonimmune cell lines, suggesting that the primary limitation is intracellular delivery rather than the tsASO design. Future work should focus on optimizing delivery platforms to achieve controlled cellular uptake and biomarker-dependent release, unlocking the therapeutic potential of this conditional gene silencing approach.

Oligonucleotides, Antisense

TWIST2-dependent transcriptional activation of TPI1 mediates TGF-β1-driven fibroblast activation in pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal interstitial lung disease characterized by aberrant profibrotic signaling and excessive extracellular matrix deposition, accompanied by fibroblast-to-myofibroblast transition. Despite extensive investigation, the molecular mechanisms underlying IPF pathogenesis remain incompletely understood. Here, we investigated the role of triosephosphate isomerase 1 (TPI1) in IPF progression and its regulation by transforming growth factor-β (TGF-β) signaling. Loss-of-function analyses identified TPI1 as a downstream effector of TGF-β1, as its knockdown markedly suppressed fibrotic marker expression, fibroblast proliferation, and migration. Mechanistically, TWIST2 was shown to function as a direct transcriptional regulator of TPI1, binding to its promoter and promoting transcriptional activation. Rescue experiments further confirmed that the TWIST2-TPI1 axis is central to the progression of pulmonary fibrosis. Notably, knockdown of either TPI1 or TWIST2 effectively attenuated TGF-β1-induced fibrotic phenotypes. Collectively, these findings define the TGF-β1/TWIST2/TPI1 signaling axis as an important regulator of pathogenic fibroblast behavior and pro-fibrotic responses through transcriptional control of TPI1, highlighting its potential as a therapeutic target for IPF.

Twist-Related Protein 1

Efficacy and Safety of the C3 Inhibitor Pegcetacoplan in Paroxysmal Nocturnal Hemoglobinuria: A Systematic Review and Meta-Analysis.

OBJECTIVE: To evaluate the efficacy and safety of the complement C3 inhibitor pegcetacoplan in patients with paroxysmal nocturnal hemoglobinuria (PNH). METHODS: PubMed, Embase, Web of Science, and Cochrane Library were systematically searched for studies reporting pegcetacoplan use in PNH. Outcomes included transfusion-requirement, hemoglobin normalization, mean hemoglobin levels, lactate dehydrogenase normalization, reticulocyte count normalization, and safety endpoints. Pooled proportions with 95% confidence intervals were calculated using random-effects models, and heterogeneity was assessed using the I2 statistic. RESULTS: Five studies comprising 271 patients were included. Transfusion avoidance was observed in 80.6% of patients, with a pooled transfusion-requirement rate of 19.4%. LDH normalization occurred in 68.5% of patients (I2 = 0%). Hemoglobin normalization was observed in 42.9%, while reticulocyte count normalization reached 66%. Any-grade adverse events occurred in 83.5% of patients, most commonly pyrexia, headache, and dizziness. Serious adverse events occurred in 16.6%, decreasing to 12% after sensitivity analysis. Breakthrough hemolysis was reported in 14.8%, and infections in 17%. CONCLUSION: Pegcetacoplan demonstrates consistent efficacy signals across key hematologic endpoints and an acceptable safety profile, supporting its potential role as an important therapeutic option, particularly in patients with persistent extravascular hemolysis despite C5 inhibition.

Humans

Transcriptomic analysis reveals the molecular mechanisms underlying the inhibition of Mytilus edulis attachment by biofouling control agents.

This study combined acute toxicity assays, phenotypic quantification, and transcriptomic profiling to systematically investigate the inhibitory effects and molecular regulatory mechanisms of a novel alkylamine-based antifouling agent on survival, byssus secretion, and attachment behavior of juvenile Mytilus edulis. The 96 h-LC50 of the agent to juvenile M. edulis was 8.84 mg/L, and 10 mg/L of the agent completely inhibited mussel attachment within 24 h, significantly reducing byssal thread number, length, and diameter while increasing detachment frequency, resulting in irreversible attachment failure. Transcriptomic analysis identified 2746 differentially expressed genes, which were mainly enriched in pathways including signal transduction, immune defense, stress response, cytoskeleton organization, and protein binding. KEGG and GSEA enrichment revealed that the antifouling agent activated the MAPK stress signaling pathway, disturbed transcriptional regulation, and impaired intracellular homeostasis and cytoskeletal stability, thereby synergistically suppressing the expression of key byssal protein genes including mfp-1 and mfp-3 and ultimately blocking byssus synthesis and adhesion. This study clarifies the multi-pathway molecular mechanism underlying antifouling agent-induced attachment inhibition in M. edulis, and provides core molecular targets and theoretical support for developing efficient, specific antifouling activity, and potentially applicable marine antifouling technologies.

Animals

Mapping Wastewater Pathogens and Their Associated Environmental and Public Health Risk Factors: A Systematic Review and Meta-Analysis.

BACKGROUND: Wastewater-based epidemiology (WBE) has emerged as a critical tool for public health surveillance, yet its application across diverse pathogens and geographical settings remains inconsistent. This systematic review synthesizes global evidence on wastewater surveillance to identify associated risk factors. METHODS: Following PRISMA 2020 guidelines (PROSPERO: CRD420261297382), a systematic search was conducted across PubMed, Scopus, Google Scholar, and Web of Science for studies published between 2000 and 2025. RESULTS: Thirty-nine peer-reviewed studies were included. The evidence base is geographically skewed toward the European Region (48.7%) and the Americas (23.1%), with significant underrepresentation in LMICs. Viruses were the primary biological target (89.7%), followed by bacteria (7.7%) and parasites (2.6%). A proportion meta-analysis of 31 eligible studies demonstrated a pooled wastewater pathogen detection prevalence of 62% (95% CI: 47.5-74.6%), with the European Region yielding the highest regional estimate (73%) and the African Region the lowest (8.3%). Conventional PCR and sequencing methods showed higher pooled detection rates (92.4% and 90.1%, respectively) than RT-qPCR (47.9%). CONCLUSION: WBE provides a robust early-warning system indicating a need for broader pathogen diversity, incorporating bacterial and parasitic surveillance and expansion into rural and resource-limited regions.

Contamination

Selective and sensitive colorimetric sensing of carbosulfan based on BiO2-x/Bi2O2.75 nanosheets with excellent haloperoxidase-like activity.

The development of colorimetric methods based on directly inhibiting nanozyme activity for pesticide detection has attracted considerable attention. In this study, we report a novel colorimetric sensing strategy utilizing BiO2-x/Bi2O2.75 nanosheets (BiO2-x/Bi2O2.75 NSs) with haloperoxidase (HPO)-like activity for the rapid and sensitive detection of carbosulfan (CBS) in foods. Oxygen-vacancy-rich BiO2-x/Bi2O2.75 NSs with HPO-like activity were rationally constructed. Kinetic studies revealed a remarkable Michaelis-Menten constant (Km) of 0.014 mM for I-, indicating a higher affinity for iodide ions than other reported HPO-like nanozymes, as evidenced by its lower Km. Under acidic conditions, CBS tends to be hydrolyzed to produce reductive sulfide species, which directly inhibit the iodoperoxidase-like activity of BiO2-x/Bi2O2.75 NSs, enabling selective detection with a limit of detection (LOD) of 0.18 μg/mL and a linear range of 0.20-100 μg/mL. When the concentration of interfering pesticides and substances was 5 times that of CBS, the sensor remained unaffected, exhibiting excellent stability and specificity. This work contributes to the detection of CBS in complex food matrices, bridging the application gap of HPO-like nanozymes in pesticide detection and providing a promising method for food safety detection.

Colorimetry

Protein sorting and proteostasis mechanisms in CFTR-related exocrine pancreas dysfunction: A systematic narrative review.

The pancreas consists of exocrine and endocrine compartments. In the exocrine pancreas, cystic fibrosis transmembrane conductance regulator (CFTR) functions mainly in ductal epithelial cells as a chloride and bicarbonate channel. Its activity depends on proper protein folding, trafficking, and localization to the apical membrane. This systematic narrative review aims to synthesize the available evidence on the role of protein sorting machinery in CFTR channelopathies and its contribution to exocrine pancreatic dysfunction. A thorough search was conducted using PRISMA criteria on PubMed, Wiley Online Library, and Scopus for studies published in English between January 2000 and November 2025. Twenty studies that met the inclusion criteria were included in this review. Pathogenic CFTR variants impair protein folding, endoplasmic reticulum (ER) exit, and endosomal recycling, resulting in reduced apical membrane expression and stability. These defects disrupt the localization of associated transporters and secretory proteins, impair ductal bicarbonate secretion, alter zymogen handling, and promote acinar injury, although these claims are supported mainly by indirect experimental models and therefore require clinical confirmation. CFTR channelopathies in the exocrine pancreas encompass both ion transport defects and broader disruptions of protein sorting machinery. CFTR may contribute to the assembly, stabilization, or localization of selected apical transport complexes, and its loss can secondarily alter epithelial organization. Therapeutic approaches targeting both channel correction and intracellular trafficking may improve pancreatic function and mitigate disease progression.

Humans

Identifying and Prioritizing Core Components of Relationship Education Programs: a Case Study of an Artificial Intelligence (AI) Assisted Systematic Review.

The field of prevention science seeks to identify and implement effective strategies to address social, emotional, and health challenges. A critical aspect of this endeavor is determining the core components of prevention programs that drive positive outcomes. This article presents a case study utilizing artificial intelligence (AI)-assisted systematic review methods to identify key components of healthy marriage and relationship education programs. Given the growing body of research in this domain, AI tools offer a promising means to enhance the efficiency and accuracy of literature reviews. This study employed AI to screen, code, and validate research articles, demonstrating its effectiveness in expediting systematic reviews while maintaining high accuracy in inclusion screening. This case study involved a systematic review of 22,028 resources (identified from PsycINFO, Academic Search Ultimate, and Google) and a final data set of 268 relevant studies. AI screening was integral in effectively conducting multiple rounds of screening. However, findings also highlight challenges in AI-assisted qualitative data abstraction, underscoring the continued need for human expertise in complex coding tasks. The study contributes to the ongoing discourse on integrating AI into prevention science methodologies and offers insights for optimizing AI applications in systematic reviews.

Artificial Intelligence

Influenza as a Less Commonly Recognized Cause of Hemophagocytic Lymphohistiocytosis: A Systematic Review of Case Reports and Case Series.

Hemophagocytic lymphohistiocytosis (HLH) is a life-threatening hyper-inflammatory condition that can be triggered by viral infections. However, influenza is not commonly recognized as a cause of HLH, and there is no comprehensive synthesis of influenza-associated HLH in the literature to guide clinicians. We conducted a systematic search of Pubmed and Embase to identify case reports and case series on influenza-associated HLH, and included 29 articles involving 47 patients. Their age ranged from 2 months to 72 years. 67% were males. Influenza A accounted for 91.3% of the cases, predominantly H1N1 (90.2%). All patients had fever, 60% had anemia, 69.7% had thrombocytopenia, 46.6% had leukopenia, 61.3% had splenomegaly, 71.4% had hypertriglyceridemia, and 94.7% had elevated ferritin levels. 97.6% had hemophagocytosis on biopsy. Antiviral therapy was administered in 89.5% of patients. HLH-directed therapy included corticosteroids (77%), intravenous immunoglobulin (36%), and etoposide (23.1%). Intensive care was required in 95.2% of cases. Overall survival was 53.2%. Survival rate was 50% among patients who received either antiviral therapy alone or HLH-directed therapy alone, compared with 65.4% among those who received both. Further studies are necessary to establish standardized diagnostic and therapeutic protocols for influenza-associated HLH.

Humans

A Letter Matters: ADRB2 rs1042713 c.46A Modulates Anti-osteogenic Effect of Epinephrine in Human Mesenchymal Stem Cells.

Osteoporosis (OP) is a systemic bone disease affecting millions worldwide, characterized by long-term asymptomatic development that manifests in low-energy fractures. Due to their high stability, genetic markers represent a promising strategy for early diagnostics. The ADRB2 rs1042713 polymorphism is one such marker, considered as a potential predictor for OP. Although the anti-osteogenic role of the β2-adrenergic receptor is well-established, debate continues on which allele (G or A) of this polymorphism drives bone deterioration. In this study, we examined the influence of the ADRB2 rs1042713 G/G and A/A variants on osteogenic differentiation in patient-derived mesenchymal stem cells (MSCs) under treatment with the endogenous agonist epinephrine. We show that epinephrine (whose levels are often elevated in comorbid conditions) drastically impairs osteogenic differentiation, specifically at the matrix mineralization stage in MSCs A/A. Epinephrine fails to activate the canonical β2-adrenergic receptor pathway and promotes receptor perinuclear and nuclear localization in MSCs A/A. Crucially, metformin, a common anti-diabetic drug, rescues this anti-osteogenic effect. These results open new perspectives for early diagnostics by identifying epinephrine sensitivity as a critical factor, while also suggesting a potential therapeutic strategy to counteract epinephrine detrimental effect in individuals carrying the ADRB2 rs1042713 A-allele.

Humans