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Tissue-derived extracellular matrix hydrogels instruct epigenetic adaptation in metastatic colonization.

The extracellular matrix (ECM) plays a central role in regulating tumor progression and metastatic colonization by providing biochemical and mechanical signals that shape cancer cell fate. However, most organoid culture systems rely on basement membrane extracts that fail to reproduce the tissue-specific extracellular environments encountered during metastasis. Here, we develop tissue-derived decellularized matrix hydrogels to reconstruct organ-specific microenvironments and investigate epigenetic adaptation to ECM cues during metastatic colonization. Patient-derived colorectal cancer organoids cultured in colon-derived matrices exhibited enhanced maintenance of stem-like phenotypes and colon-specific chromatin accessibility landscapes compared with cultures grown in basement membrane extracts, demonstrating improved physiological relevance for primary tumor modeling. When exposed to matrices derived from secondary organs, the organoids showed distinct growth phenotypes accompanied by rapid, tissue-dependent chromatin accessibility remodeling, indicating that ECM composition alone can reshape regulatory programs governing metastatic adaptation. Notably, liver-derived matrices selectively activated hepatocyte nuclear factor 4 alpha (HNF4A)-associated transcriptional networks and created a context-specific dependence on c-MET signaling for survival. Functional perturbation of HNF4A or c-MET signaling confirmed that both are required for organoid formation specifically within the liver matrix environment. Together, these findings establish tissue-derived matrix hydrogels as instructive bioactive materials that actively regulate cancer cell epigenetic states and reveal microenvironment-specific therapeutic vulnerabilities during early metastatic colonization.

Journal Article

Cis-regulatory variation in the MdCKX6 promoter is associated with allele-specific expression and fruit size in apple.

Fruit size is a key determinant of apple fruit quality and market value and is strongly influenced by phytohormone-regulated cell proliferation and expansion during early fruit development. Cytokinin oxidase/dehydrogenase (CKX) enzymes regulate cytokinin homeostasis by irreversibly degrading active cytokinins, but the contribution of natural variation in CKX genes to fruit size remains poorly understood. Here, we identified MdCKX6 as a candidate regulator of fruit growth in apple (Malus domestica). MdCKX6 exhibited pronounced allele-specific expression during fruit development in the cultivar 'Royal Gala'. Sequence analysis identified a promoter SNP associated with differential promoter activity and allele-specific expression. Genotyping of diverse apple cultivars and wild Malus accessions revealed a significant association between MdCKX6 promoter genotype and fruit size. Cultivars carrying low-expression alleles produced larger fruits, whereas high-expression alleles were associated with smaller fruits. To investigate gene function, MdCKX6 was overexpressed in tomato, resulting in reduced fruit size. Histological analyses of the transgenic tomato fruit revealed smaller pericarp cells. Transcriptome analysis of transgenic fruits revealed widespread changes in genes associated with cell-cycle regulation, cell wall modification, hormone-related processes, and transcriptional regulation. Together, these results identify MdCKX6 as a potential negative regulator of apple fruit growth and reveal an association between cis-regulatory variants, gene expression, and fruit size. This study provides new insights into the role of cytokinin metabolism in fruit development and highlights regulatory variation in MdCKX6 as a potential target for apple breeding.

Malus

Review of regulatory requirements for benefit-risk assessment for medical devices: uncovering existing methodologies.

INTRODUCTION: A positive benefit-risk profile is a prerequisite for the market approval of medical devices. However, regulations are often criticized for providing limited information on benefit-risk assessment (BRA) despite growing expectations for quantitative methods. A clearer understanding of regulatory requirements, existing methodologies, and unresolved issues is needed. AREAS COVERED: Relevant regulatory documents referencing BRA for medical devices were systematically identified, with a primary focus on the European regulation followed by screening to extract BRA‑related requirements and any explicitly or implicitly described methods. The findings were analyzed and consolidated by BRA context, type, objective, methodological description, and implementation, thereby establishing a basis for the BRA methodological landscape. EXPERT OPINION: BRA is not a single concept, but a set of context‑dependent assessments across lifecycle of a medical device. BRA within clinical evaluation framed into BRAs of risk management holds a pivotal role and is supported by the most detailed methodological guidance, although BRAs in other contexts are important. A structured overview of existing BRA requirements clarifies their treatment across regulatory documents. By differentiating BRA contexts, types, objectives, and required methodological detail, the analysis supports a more transparent understanding of BRA and helps identify priorities for methodological refinement and interface clarification.

Risk Assessment

Associations of Illness Perception, Resignation Coping, and Social Support With Self-Regulatory Fatigue in Patients With Type 2 Diabetes: A Cross-Sectional Study.

AIMS: To examine the associations among illness perception, resignation coping, social support, and self-regulatory fatigue (SRF) in patients with Type 2 diabetes mellitus. The study specifically explores whether resignation coping and social support exhibit indirect associations with SRF in the context of illness perception. DESIGN: A cross-sectional study. METHODS: From November 2024 to October 2025, a convenience sample of 302 adult patients with T2DM was recruited from a tertiary general hospital in China. Participants completed validated instruments with established psychometric properties, namely the Brief Illness Perception Questionnaire, the Medical Coping Modes Questionnaire, the Perceived Social Support Scale, and the Self-Regulatory Fatigue Scale. Statistical analyses included Spearman correlation and serial mediation analysis using the PROCESS Macro (Model 6) with bias-corrected bootstrapping. RESULTS: SRF was positively correlated with negative illness perception (r&#x2009;=&#x2009;0.579, p&#x2009;<&#x2009;0.01) and resignation coping (r&#x2009;=&#x2009;0.612, p&#x2009;<&#x2009;0.01), and negatively correlated with social support (r&#x2009;=&#x2009;-0.598, p&#x2009;<&#x2009;0.01). Serial mediation analysis revealed that illness perception was associated with SRF through indirect pathways involving resignation coping and social support. Resignation coping and social support mediated the association between illness perception and self-regulatory fatigue, both individually and sequentially. CONCLUSIONS: Negative illness perception correlates with higher SRF. This observed correlation is additionally linked to indirect pathways involving resignation coping and lower social support. Collectively, these findings highlight a pattern of interrelated cognitive (illness perception), behavioural (resignation coping), and resource (social support) factors that are associated with self-regulatory fatigue in this cross-sectional study. IMPLICATIONS FOR THE PROFESSION: The findings offer a clear, evidence-based framework for nursing practice. They highlight the potential value of integrated assessment and intervention that simultaneously addresses patients' illness beliefs, maladaptive coping strategies, and social support systems, which are associated with lower SRF and better diabetes self-management. REPORTING METHOD: This study adheres to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for cross-sectional studies. PATIENT OR PUBLIC CONTRIBUTION: Patients participated solely as research participants by providing survey data. They were not involved in the study design, implementation, data analysis, interpretation, or manuscript preparation. All patients provided written informed consent prior to questionnaire completion.

Humans

Unveiling the molecular basis of gonadal development: Multi-omics uncovers sex-related genes and steroid pathways in Sinonovacula constricta.

The razor clam Sinonovacula constricta is an economically important cultured mollusk in China, but the molecular mechanism of its gonadal development and sexual differentiation remains unclear. This study integrated gonadal transcriptomic, proteomic, and metabolomic analysis to identify key sex-related molecules. Transcriptome analysis identified 2795 DELs and 6497 DEGs between sexes, including the sex-related genes Fem-1b, Fem-1c, GUCY1B2 and FAT4, as well as a regulatory network of 39 lncRNA-mRNA pairs involving Tektin-4, Ropporin-1, Histone H1, and FoxN4. Proteomic analysis revealed 3217 DEPs: Tektin family members, Ropporin-1 and Tssk proteins were upregulated in the testis, while histone H1 and FAT4 were upregulated in the ovary. Metabolomic analysis detected 409 DEMs, with uridine identified as a potential sex differential marker (upregulated in the ovary), and 23 gonadal development-related DEMs showed sex-specific upregulation. Integrative transcriptome-proteome analysis identified 1543 co-expressed DEGs/DEPs enriched in nucleosome assembly, oxidative phosphorylation, and carbon metabolism, including key sex-related genes AKAP14, Tektin/Tssk families, Histone H1, and FAT4. Transcriptome-metabolome integration identified 32 shared KEGG pathways (e.g., biosynthesis of unsaturated fatty acids, pyrimidine metabolism), while proteome-metabolome integration revealed 5 (positive ion) and 6 (negative ion) co-enriched pathways, with alanine, aspartate and glutamate metabolism and oxidative phosphorylation being functionally relevant to gonadal development. Collectively, these results reveal the molecular basis of gonadal development, highlight critical sex-related genes and steroid metabolic pathways, and provide valuable resources for future reproduction and breeding in S. constricta.

Animals

Decoding the spatiotemporal patterns of food spoilage microbial communities: Integrating multi-omics and artificial intelligence to enable precision preservation.

In the global food supply chain, food wastage caused by spoilage has resulted in significant economic losses, food shortages, and environmental pressure. This process is fundamentally driven by the spatiotemporal dynamics of microbial communities. However, traditional research methods struggle to elucidate the complex mechanisms of spatial heterogeneity, interspecies interactions, and functional succession. This limits the development of effective preservation strategies. This review systematically reviews the cutting-edge progress of integrating multi-omics technologies and artificial intelligence (AI) to study food spoilage microbial communities, breaking through this bottleneck. We propose an intelligent theoretical framework that could potentially analyze microbial metabolic activities and predict dynamic shelf life if implemented. The conceptual framework integrates multidimensional data, including spatial metabolomics, temporal metatranscriptomics, single-cell transcriptomics, and longitudinal metagenomics. It can also be combined with AI models, such as graph neural networks. The article elaborates on the principles and applications of spatio-temporal monitoring technologies, such as nano secondary ion mass spectrometry, hyperspectral imaging, and the Internet of Things sensing. Through illustrative cases of typical perishable foods, it also explores how such a multi-omics - AI system might be applied to spoilage warning and precise intervention. Additionally, the article addresses the current challenges in data coverage, model generalization, and federated learning implementation. Then the research further explores emerging areas such as engineered probiotics, edge AI, and microfluidic sensing. These areas are targeted at transforming food preservation from an empirical control approach to a data-driven, precise regulatory framework. This transformation provides theoretical support and technical approaches for developing a smart, sustainable food preservation system.

Multiomics

Variants in the interferon regulatory factor 5 gene confer genetic risk for systemic lupus erythematosus in a Han Chinese population.

BACKGROUND: Interferon regulatory factor 5 (IRF5), integral to interferon signaling pathways, has been identified as a susceptibility locus for systemic lupus erythematosus (SLE). Nevertheless, the relationship between IRF5 variants and SLE risk within the Han Chinese demographic remains inadequately characterized. MATERIALS AND METHODS: Genotyping of two functional single nucleotide variants (SNVs) in IRF5 was conducted in 167 individuals with SLE and 246 healthy controls utilizing sequence-specific primer polymerase chain reaction (PCR-SSP). Chi-square and Fisher's exact tests were employed to assess associations. RESULTS: The rs10954213 variant demonstrated a significant association with SLE susceptibility under the recessive model (GG vs. AG+AA, OR = 2.20, 95% CI: 1.30-3.75, p&#x2009;=&#x2009;0.003, adjusted p [pc]&#x2009;=&#x2009;0.030) and homozygous model (GG vs. AA, OR = 2.43, 95% CI: 1.36-4.42, p&#x2009;=&#x2009;0.003, pc = 0.032). Similarly, the rs2004640 variant was associated with an increased risk of SLE across allelic (T vs. G, OR = 1.66, 95% CI: 1.22-2.26, p&#x2009;=&#x2009;0.001, pc = 0.011), dominant (TG+TT vs. GG, OR = 1.77, 95% CI: 1.19-2.63, p&#x2009;=&#x2009;0.005, pc = 0.047), and homozygous models (TT vs. GG, OR = 3.72, 95% CI: 1.58-8.78, p&#x2009;=&#x2009;0.002, pc = 0.016). Haplotype analysis identified protective haplotype HT1 (A/G, OR = 0.54, 95% CI: 0.41-0.73, p&#x2009;<&#x2009;0.001) and risk haplotype HT4 (G/T, OR = 2.51, 95% CI: 1.42-4.42, p&#x2009;=&#x2009;0.001). CONCLUSIONS: These findings indicate that IRF5 gene variants substantially modulate susceptibility to SLE in the Han Chinese population. They hold potential as biomarkers for evaluating SLE risk and offer valuable perspectives into disease pathogenesis.

Adult

A translational framework for early-phase inner-ear gene therapy: clinical trial design, regulatory strategy, and ethical considerations.

PURPOSE OF REVIEW: Hereditary hearing loss has historically been approached as a diagnostic category rather than a therapeutically modifiable disease. Recent advances in molecular genetics, cochlear gene delivery, and first-in-human clinical trials are changing that. This review summarizes contemporary progress in the genetics of hearing loss, with emphasis on emerging gene-based therapies, clinical trial design, regulatory and ethical considerations, and practical implications for otolaryngologists as biologic treatment enters clinical practice. RECENT FINDINGS: Early clinical trials targeting OTOF -related DFNB9 deafness have demonstrated satisfactory safety profiles and meaningful auditory recovery, establishing the first proof-of-concept for cochlear gene therapy in humans, culminating in the April 2026 FDA approval of Otarmeni. Genetic diagnoses are increasingly informing prognosis, cochlear implant counseling, and therapeutic candidacy. Preclinical research continues to expand toward recessive, dominant, and syndromic hearing loss using gene replacement, antisense, RNA interference, and genome-editing strategies. Substantial challenges remain, including heterogeneous outcome measures, uncertain long-term efficacy, regulatory complexity, and inequitable global access. SUMMARY: The genetics of hearing loss is transitioning from a diagnostic modality to an interventional one. Widespread clinical impact will require advances in vector engineering, equitable implementation, multidisciplinary counseling, and integration with established rehabilitation pathways. For otolaryngologists, genetic literacy is becoming essential to contemporary hearing care.

Humans

Decoding bipotency: a transient regulatory state bridging totipotency and lineage commitment.

Early mammalian embryogenesis entails a coordinated transition from totipotency to the first lineage bifurcation, giving rise to embryonic lineages and the extra-embryonic trophectoderm. The mechanisms by which totipotency is resolved into lineage-primed states remain incompletely understood. Emerging evidence supports a non-binary model in which cells traverse a continuum of potency states, passing through a transient bipotent intermediate that retains both embryonic and extra-embryonic potential while exiting totipotency. Here, we synthesize recent advances in the mechanisms that establish, maintain, and resolve bipotency. We emphasize the coordinated roles of transposable elements, transcription factors, and signaling pathways in regulating this transition. We also highlight newly developed bipotent stem cell models and their implications in generating advanced embryo models in vitro. Notably, current insights are largely derived from mouse systems; given key differences between mouse and human early embryogenesis, extending these findings to human models remains a critical next step.

Animals

Integrated single-cell and bulk transcriptomic analysis identifies a novel senescent fibroblast subtype associated with poor prognosis in acral melanoma.

BACKGROUND: Acral melanoma (AM) exhibits significant intratumoral heterogeneity, but its tumor microenvironment (TME) and immune regulation remain unclear. This study aims to dissect TME heterogeneity and establish a prognostic model based on key cell subpopulations. METHODS: We collected AM single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA). Unsupervised clustering, CellChat, and Scissor analysis were performed to characterize cellular heterogeneity, cell-cell communication, and prognosis-related cell subpopulations. Kaplan-Meier analysis was used to assess the prognostic value of key genes, which were further validated by multiplex immunohistochemistry (mIHC). RESULTS: In AM, Mel_C2, C7, and C9 with high SEMA6A and KIT expression were strongly linked to poor prognosis. We further identified a senescent fibroblast subpopulation (sCAF_CDKN2A) characterized by high fibroblast senescence signature (FSS) scores. Integrating Scissor analysis of fibroblast subtypes with bulk prognostic data, we identified COL3A1, VCAN, and KIT as prognosis-associated genes upregulated in poor-outcome-related fibroblast subsets. Cell-cell communication analysis revealed that sCAF_CDKN2A engages in an immunosuppressive network, interacting with regulatory T cells (Tregs) via MIF signaling and receiving signals from exhausted CD8+ T cells through PPIA-BSG interactions. Using transcription factor expression patterns from these fibroblast subtypes, we constructed a prognostic model that effectively stratified patients into distinct risk groups with significant differences in overall survival (OS). mIHC confirmed significantly higher protein levels of SEMA6A and COL3A1 in tumor tissues compared to matched normal tissues. CONCLUSIONS: We established a novel prognostic model for AM and identified sCAF_CDKN2A as an immunosuppressive senescent fibroblast subpopulation driving poor prognosis.

Acral melanoma

Adeno-Associated Virus Gene Therapy Translation: Lessons from Early Regulatory Meetings.

The Platform Vector-Gene Therapy (PaVe-GT) program is a National Institutes of Health (NIH) initiative that aims to develop adeno-associated virus (AAV) gene therapies for four monogenic rare diseases, two organic acidemias and two congenital myasthenic syndromes. PaVe-GT's platform-based approach identifies and diminishes redundancies and applies efficiencies in preclinical, clinical, and regulatory activities. The program's hypothesis is that implementing these efficiencies can accelerate clinical trial initiation. Based on its platform-centric experience and public-serving mission, the PaVe-GT program actively shares its scientific and regulatory learnings with the public to benefit the development of similar gene therapy products for rare diseases. PaVe-GT's first investigational AAV gene therapy candidate is AAV serotype 9 human propionyl-CoA carboxylase alpha subunit (AAV9-hPCCA) for propionic acidemia caused by PCCA deficiency, which received initial feedback from the Food and Drug Administration (FDA) in an INitial Targeted Engagement for Regulatory Advice on CBER/Center for Drug Evaluation and Research (CDER) ProducTs (INTERACT) meeting. Upon further product development that took into consideration the FDA's initial advice, the program obtained the Agency's feedback in pre-investigational new drug (IND) (Type B) and Type C meetings. Here, we share our experience from these meetings, including strategy, preparation, pre- and post-meeting feedback from the FDA, and lessons learned during the AAV9-hPCCA regulatory process, which the program plans to apply across the PaVe-GT platform. Topics discussed in the regulatory meetings included animal model and efficacy studies, toxicology study plans, manufacturing of the investigational AAV product, and clinical trial design. The main lessons learned from the pre-IND and Type C meetings for AAV9-hPCCA are: (1) Pharmacology/Toxicology studies in a single rodent species are sufficient for filing an initial IND; (2) FDA feedback guides product quality improvements and early development of a quantitative potency assay; (3) use of biomarkers as potential surrogate endpoints in a future efficacy trial benefits from collection of data in the natural history study and the first-in-human Phase 1/2 study; and (4) evidence from the Phase 1/2 clinical trial could be leveraged to support a license application. Lightly redacted regulatory documents and comprehensive templates developed by the PaVe-GT team are available on the PaVe-GT website.

Dependovirus

PaNDA: Efficient Optimization of Phylogenetic Diversity in Networks.

Phylogenetic diversity (PD) plays an important role in biodiversity, conservation, and evolutionary studies by measuring the diversity of a set of taxa based on their phylogenetic relationships. In phylogenetic trees, a subset of k taxa with maximum PD can be found by a simple and efficient greedy algorithm. However, this algorithmic tractability is lost when considering phylogenetic networks, which incorporate reticulate evolutionary events such as hybridization and horizontal gene transfer. To address this challenge, we introduce PaNDA (Phylogenetic Network Diversity Algorithms), the first software package and interactive graphical user-interface for exploring, visualizing, and maximizing diversity in phylogenetic networks. PaNDA includes a novel algorithm to find a subset of k taxa with maximum diversity, running in polynomial time for networks of bounded scanwidth, a measure of tree-likeness of a network that grows slower than the well-known level measure. This algorithm considers the variant of PD on networks in which the branch lengths of all paths from the root to the selected taxa contribute towards their diversity. We demonstrate the scalability of this algorithm on simulated networks, successfully analyzing level-15 networks with up to 200 taxa in seconds. We also provide a proof-of-concept analysis using a phylogenetic network on Xiphophorus species, illustrating how the tool can support diversity studies based on real genomic data. The software is easily installable and freely available at https://github.com/nholtgrefe/panda. Additionally, we extend the definition of PD to semi-directed phylogenetic networks, which are mixed graphs increasingly used in phylogenetic analysis to model uncertainty of the root location. We prove that finding a subset of k taxa with maximum diversity remains NP-hard on semi-directed networks, but do present a polynomial-time algorithm for networks with bounded level.

network

The future of TCR-Treg therapies is renewables.

Cell therapy has longstanding roots in haematopoietic stem cell transplantation and early immune cell transfers in infectious disease and transplantation, where patient- or donor-derived cells have achieved therapeutic benefit in selected contexts. The modern era has been driven largely by oncology, with engineered modalities such as tumour-infiltrating lymphocytes, CAR-T cells and TCR-engineered T cells delivering transformative responses but requiring complex, costly manufacturing. These platforms are now being adapted for autoimmune diseases to induce durable, antigen-specific immune tolerance, yet broad application is limited by safety concerns, process complexity and access. Non-engineered cell therapies for autoimmunity, including mesenchymal stem cells, polyclonal regulatory T cells and tolerogenic dendritic cells, have shown acceptable safety and proof-of-principle for immune re-education, but clinical responses have been modest and inconsistent, with limited scalability. Engineered approaches such as CAR-T cells can induce reversible B cell depletion in B cell-mediated rheumatic diseases but only addresses antibody-driven pathology and not T cell-mediated autoimmunity. TCR-engineered Tregs have emerged as a promising antigen-specific strategy, offering localized, antigen-linked suppression with bystander tolerance. Preclinical and early clinical data suggest superior potency, stability and disease control compared with polyclonal Tregs at similar or lower doses, but translation is constrained by the rarity and fragility of Tregs and by labour-intensive, CAR-T-like manufacturing. This review highlights emerging solutions for closed, automated and decentralised production, and discusses allogeneic approaches using gene-edited or banked Tregs with HLA engineering or matching. Together, these advances support the development of scalable, "off-the-shelf" TCR-Treg products with potential to provide safe, affordable tolerance-restoring therapies for autoimmune disease.

Humans

Non-destructive prediction of lead content in oilseed rape leaves by fluorescence hyperspectral technology based on neural network.

Based on fluorescence hyperspectral imaging (FHSI), this study targeted rapid, non-destructive quantification of lead (Pb) content in oilseed rape leaves treated with varying silicon (Si) concentrations, acquiring fluorescence spectra over the 484.43-1001.61&#xa0;nm wavelength range. To optimize spectral data quality, preprocessing methods (Savitzky-Golay smoothing, first derivative, detrending) were comprehensively compared. Characteristic wavelengths were then selected via interval variable iterative shrinkage, which effectively compressed data dimensionality and reduced computational load. A hybrid SE-CL1DA model, fusing a 1D convolutional neural network, a long short-term memory network and SE attention mechanism was constructed, with Bayesian optimization tuning hyperparameters to boost stability. The BO-SE-CL1DA outperformed both traditional machine learning and insufficiently optimized deep learning model (Rp2=0.9609, RMSE&#xa0;=&#xa0;0.0377&#xa0;mg/kg, RPD&#xa0;=&#xa0;5.1736), thus enabling accurate Pb estimation, supporting Si-regulated heavy metal stress management and facilitating agricultural contamination monitoring.

Plant Leaves

Comparative analyses of olfactory receptor repertoires in Schizothorax fish based on the chromosome-level genomes: Implications for regulatory roles of dietary differentiation and ploidy variation.

The olfactory receptor (OR) genes constitute the molecular basis of fish olfaction, mediating survival behaviors and environmental adaptation while coevolving with habitat-driven evolution. Schizothorax, a cyprinid genus endemic to the Qinghai-Tibetan Plateau, exhibits remarkable dietary divergence and ploidy variation in response to plateau environmental changes, which presumably facilitates the adaptive evolution of OR genes. However, the evolutionary patterns of OR genes associated with trophic divergence and ploidy variation in this genus remain unclear. In this study, three species were selected: the herbivorous diploid S. macropogon, the carnivorous diploid S. lantsangensis, and the herbivorous tetraploid S. curvilabiatus. S. macropogon possessed 142 OR genes (92.25% functional), primarily located on chromosomes 14 and 24, with the fewest sequence clusters. Such compact gene repertoire and highly overlapping chromosomal clusters indicated specialization for a herbivorous olfactory niche. S. lantsangensis contained 127 OR genes (93.70% functional), concentrated on chromosomes 4 and 5, with fewer sequence clusters and a scattered distribution, reflecting evolution of OR genes under carnivorous feeding habits. The herbivorous tetraploid S. curvilabiatus exhibited striking features: 316 OR genes (94.30% functional), the most subfamilies, unique &#x3b5; and &#x3ba; OR subfamilies, and species-specific motifs. These characteristics revealed that ploidy, rather than herbivory, dominated OR gene evolution. In conclusion, dietary differentiation and ploidy variation together drove olfactory adaptive evolution in Schizothorax, providing new insights into vertebrate OR gene ecological adaptation.

Animals

Ultra-high-field 7T MRI reveals neural abnormalities of attention networks in relation to cognitive impairment in hypertension.

Hypertension is a significant risk factor for cognitive impairment (CI), yet the corresponding neural network abnormalities remain underexplored. In this study, we examined the associations among global and domain-specific cognitive dysfunction, neuroimaging measures, and blood pressure in a subgroup of hypertensive patients with CI (N&#xa0;=&#xa0;41) from a randomized controlled trial who underwent ultra-high-field 7&#xa0;T MRI. Structural atrophy related to CI was localized to regions overlapping the attention networks. Both whole-brain and within-network dysfunction of the attention networks were associated with worse global cognitive performance. Notably, hyperconnectivity within key attention network hubs, including the right anterior insula and posterior intraparietal sulcus, was associated with declined processing speed in hypertensive patients, mediating the association between pulse pressure and processing speed. These findings provide new insights into the neural pathophysiology of hypertension-related CI and suggest potential network-based targets for intervention.

Magnetic Resonance Imaging

Unraveling the c-Myc-CASC19/HDAC1-NPM1 epigenetic axis: A novel regulatory circuitry and therapeutic target in gastric carcinogenesis.

Mounting evidence implicates long non-coding RNA cancer susceptibility candidate 19 (CASC19) in the pathogenesis of diverse malignancies. However, its functional role and molecular mechanisms in gastric cancer (GC) remain elusive. Herein, we identified a novel 717-bp transcript isoform of CASC19 in GC cells. This study aimed to delineate the biological functions and underlying mechanisms of this novel CASC19 transcript in GC pathogenesis. CASC19 was significantly upregulated in GC tissues and cell lines, correlating with adverse clinicopathological features and poor prognosis in GC patients. Functional investigations demonstrated that CASC19 overexpression potentiated GC cell proliferation, metastasis, and epithelial-mesenchymal transition, whereas CASC19 knockdown attenuated these malignant phenotypes and suppressed tumorigenesis in xenograft models. Mechanistically, CASC19 functioned as a molecular scaffold by recruiting histone deacetylase 1 (HDAC1) to the nucleophosmin 1 (NPM1) promoter. This recruitment sustained H3K27 deacetylation, thereby transcriptionally repressing NPM1 promoter activity and accelerating gastric carcinogenesis. Crucially, Depletion of HDAC1 or NPM1 partial rescued CASC19-mediated oncogenic effects. Intriguingly, the transcription factor c-Myc was found to transcriptionally activate CASC19 through direct binding to its promoter region. Collectively, our findings indicate that the c-Myc-CASC19/HDAC1-NPM1 axis acts as a potential prognostic biomarker candidate for GC and may represent a therapeutic vulnerability worthy of future investigation.

Humans

Understanding FDA's reasons for nonapproval: A systematic review of complete response letters in cell and gene therapy.

BACKGROUND AIMS: Cell and gene therapy products face unique regulatory challenges due to their biological complexity and the stringent expectations for manufacturing control, analytical testing, and clinical assessment. As the pipeline grows, understanding the drivers of FDA non&#x2011;approval is increasingly important for improving first&#x2011;cycle success and reducing development delays. In this study, we aimed to characterize the frequency and impact of refuse&#x2011;to&#x2011;file actions, major amendments, and complete response letters issued for biologics licensing applications; and to identify recurring patterns of deficiencies contributing to delayed approval. METHODS: Publicly available documents were extracted from the FDA website. Data from each approved cell and gene therapy product's regulatory history-including complete responses, major amendments, inspection timing, and cited deficiencies-were compiled and categorized across clinical, quality, and labeling domains. RESULTS: Analysis showed that informational deficiencies were common across modalities. Major amendments occurred in roughly half of applications, and complete responses had the most significant impact. Quality deficiencies appeared in all complete responses and were the predominant barrier, while clinical and labeling issues were less frequent but meaningful when present. CONCLUSION: Overall, these findings highlight the need for proactive FDA engagement, comprehensive readiness, and early inspection preparation to reduce regulatory risk and improve first cycle approval outcomes.

Humans