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PubMed2026

Premenarche risk factors for future dysmenorrhoea: a prospective cohort study.

BACKGROUND: Dysmenorrhoea, or pain during menstruation, is common in adolescence and is often dismissed or left untreated. Dysmenorrhoea can interfere with daily functioning and can lead to other chronic pain conditions; however, little is known about the risk factors for dysmenorrhoea. We aimed to characterise premenarche risk factors for the presence and severity of future dysmenorrhoea. METHODS: In this prospective cohort study, we obtained data for female adolescents from the population-based Adolescent Brain Cognitive Development Study (USA) who were premenarchal at baseline (age 9-10 years) and had both reached menarche and completed the Menstrual Cycle Survey at 3-year follow-up (age 12-13 years). Parents or guardians provided sociodemographic information and completed the Child Behavior Checklist, the Sleep Disturbance Scale for Children, and the Pubertal Development Scale, which captured data on non-painful somatic symptoms, attention problems, anxiety, depression, sleep disturbances, and pubertal development at baseline. Our primary objective was to analyse associations between dysmenorrhoea at 3-year follow-up (status and severity) with select symptom domains (sleep problems, attention problems, somatic symptoms, anxious or depressive symptoms, and baseline pain status) at baseline. We also investigated associations between dysmenorrhoea and participant characteristics (pubertal status, race or ethnicity, and income-to-needs ratio) that underlie social determinants of health. Differences by race were tested using Fisher exact tests. Differences by ethnicity and baseline pain status were tested using χ2 tests. Differences in continuous variables were assessed using ANOVA. Wilcoxon-Rank Sum tests were used in analyses of sleep problems, attention problems, and somatic symptoms, and ANOVA was used for pubertal status and income-to-needs ratio. Multinomial logistic regression was used to test associations with dysmenorrhoea severity, and linear regression was used to test associations with dysmenorrhoea status and menstrual pain interference. FINDINGS: 2254 female adolescents were included in this study. 1299 (57·6%) participants developed dysmenorrhoea at age 12-13 years, and 247 (19·0% of those with dysmenorrhoea) reported severe dysmenorrhoea. Non-painful somatic symptoms were prospectively associated with future dysmenorrhoea (odds ratio [OR] 1·17 [95% CI 1·04-1·32]; p=0·0070), whereas anxiety or depression, sleep disturbances, and attention problems were not. Sleep disturbances were prospectively associated with menstrual pain interference (β coefficient 0·16 [95% CI 0·01-0·31]). Advanced pubertal status at ages 9-10 years was prospectively associated with risk of dysmenorrhoea 3 years later (OR 1·79 [95% CI 1·47-2·17]; p<0·0001), as was lower income-to-needs ratio (0·96 [0·93-1·00]; p=0·031). Black (1·38 [1·05-1·83]; p=0·024) and Hispanic (1·34 [1·03-1·68]; p=0·010) young females were at a significantly greater risk of experiencing dysmenorrhoea than were White and non-Hispanic young females, respectively. INTERPRETATION: Sociodemographic characteristics and clinical symptoms present before menarche might help to identify at-risk individuals for dysmenorrhoea before pain becomes a lifelong issue. FUNDING: The National Institute of Nursing Research, the National Institute of Diabetes and Digestive and Kidney Diseases, and the Eunice Kennedy Shriver National Institute for Child Health and Human Development.

Humans↗

PubMed2026

AI Health message intervention: The role of message customization and message source in breast cancer screening among women of color.

OBJECTIVES: To examine the effectiveness of breast cancer screening messages with varying levels of customization (generic, targeted, and tailored) and to compare AI-generated versus human-generated messages. METHODS: A between-subjects experimental design with a control condition was employed. Message content followed a standardized structure and varied by level of customization: generic, targeted (demographic-based), and tailored (perceived susceptibility- and barrier-based). Messages were developed by either the authors or GenAI (ChatGPT-4o). A total of 391 participants recruited via Prolific were randomly assigned to five groups (generic, targeted-human, targeted-AI, tailored-human, and tailored-AI). Self-efficacy, behavioral intentions, attitudes, and message believability were measured using different scales. RESULTS: Customized (tailoring and targeting) health messages performed comparably to generic messages in shaping positive health outcomes. GenAI-generated messages also produced outcomes comparable to those of human-generated messages under standardized conditions. Significant negative indirect effects through message believability for the human-tailored condition was found relative to the generic condition. CONCLUSIONS: GenAI may be a useful tool for developing and customizing scalable health messages. Its effectiveness depends not only on customization but also on maintaining message quality, including readability, clarity, coherence, naturalness, and credibility. PRACTICAL IMPLICATIONS: GenAI may support health practitioners in developing customized and scalable breast cancer messages. However, professional review remains necessary to ensure that the message is culturally appropriate, responsive to patient concerns, and suitable for use alongside patient-provider communication.

Humans↗

PubMed2026

Simultaneous determination of imiquimod and terbinafine in skin permeation studies: Validation of a liquid chromatography method with fluorescence detection.

Chromoblastomycosis is a chronic, neglected subcutaneous mycosis posing significant therapeutic challenges. A topical strategy combining terbinafine (TBF), an antifungal, with imiquimod (IMQ), a TLR-7/8 agonist immunomodulator, has emerged a promising alternative. However, no validated analytical method is currently available to simultaneously quantify both drugs in skin, which is crucial for novel formulation development. This study reports the development and validation of a simple HPLC method with fluorescence detection (excitation 236 nm, emission 340 nm) for the simultaneous determination of TBF and IMQ extracted from porcine skin. Separation was achieved on a C8 reversed-phase column (125 × 4.0 mm, 5 μm) using a mobile phase of methanol and water (60,40, v/v), both containing 0.1% formic acid at a flow rate of 0.8 mL/min. The method showed excellent linearity (r > 0.999) over 0.01-1.0 μg/mL for IMQ and 0.1-2.0 μg/mL for TBF. Intra- and inter-day precision demonstrated coefficients of variation below 5%, and recovery rates from skin (79-105%) confirmed accuracy. Limits of detection were 0.001 μg/mL for IMQ and 0.004 μg/mL for TBF, with quantification limits of 0.02 μg/mL and 0.16 μg/mL, respectively. This selective, sensitive, and reproducible method represents a valuable analytical tool for supporting the development and quality control of topical formulations for chromoblastomycosis and other fungal skin diseases.

Animals↗

PubMed2026

Analysis of deep learning techniques in computer-aided diagnosis for meniscus injuries: a systematic literature review.

Meniscus informatics is a growing subject of study in the healthcare industry. One of the major hindrances to the healthcare system's transformation is obtaining knowledge and meaningful information from complicated, high-dimensional and diverse sources. Modern biomedical research, for instance, has seen an increase in the use of complex, dissimilar, poorly documented, and generally unstructured electronic health records, imaging, sensor data and text, even after many current techniques have been used to extract more robust and useful elements from the data for analysis. New efficient standards for building end-to-end learning models from complex data are therefore needed. Therefore, the current study aims to examine the most recent research on the use of deep learning techniques for diagnosing meniscus tears and recommend creating comprehensive and meaningful interpretable structures that might benefit the healthcare industry. We also draw attention to shortcomings and the need for better technique development, and we provide new perspectives about this exciting new development in the field.

Humans↗

PubMed2026

A Dynamic Nomogram to Predict Metabolic Dysfunction-Associated Fatty Liver Disease in Patients with Metabolic Syndrome.

BACKGROUND: Metabolic syndrome (MetS) involves multiple metabolic disorders. This study aimed to identify high-risk populations for metabolic dysfunction-associated fatty liver disease (MAFLD) in patients with MetS and to establish a dynamic predictive nomogram. METHODS: A total of 627 patients with MetS from six regions in Zhejiang Province were enrolled and categorized into MAFLD and non-MAFLD groups, then randomly assigned to training and validation sets at a ratio of 7:3. Independent predictors of MAFLD were identified using least absolute shrinkage and selection operator regression and multivariable logistic regression analyses. These predictors were then used to construct a dynamic nomogram. RESULTS: A total of 627 patients with MetS were included in the final analysis, of whom 77.0% (483/627) were diagnosed with MAFLD. Multivariable logistic regression analysis identified body mass index (BMI), waist circumference (WC), total cholesterol (TC), alanine aminotransferase (ALT), MetS-defined dysglycemia, and education level as independent risk factors for MAFLD. MetS-defined dysglycemia showed the highest odds ratio (OR) for MAFLD development [OR = 1.87, 95% confidence interval (CI): 1.07-3.29]. Although the number of MetS components and the metabolic syndrome score were significantly associated with MAFLD in univariate analysis, they were not independently associated with MAFLD in the multivariate model. A dynamic nomogram for predicting MAFLD risk in patients with MetS was developed and internally validated. The area under the receiver operating characteristic curve was 0.834 (95% CI: 0.787-0.880) in the training set and 0.839 (95% CI: 0.771-0.899) in the validation set, indicating strong predictive performance. Bootstrap internal validation demonstrated good agreement between predicted and observed outcomes in calibration curves. Decision curve analysis further indicated favorable clinical applicability of the nomogram. CONCLUSION: BMI, WC, TC, ALT, MetS-defined dysglycemia, and education level are independent risk factors for MAFLD. A dynamic nomogram for predicting MAFLD risk in patients with MetS was successfully developed and validated.

Humans↗

PubMed2026

Molecular adaptation of caspase genes to salinity stress in the tropical sea cucumber Stichopus monotuberculatus: A comparative analysis across echinoderms.

Apoptosis is an essential physiological process that plays a critical role in development and tissue homeostasis. Caspases, as central regulators of apoptosis, are crucial in controlling inflammation and cell death. In this study, we investigated the caspase gene family in Stichopus monotuberculatus to explore their potential roles in salinity stress adaptation. Five caspase genes were identified from the genome of S. monotuberculatus, including Smcaspase3, Smcaspase6, Smcaspase8a, Smcaspase8b, and Smcaspase8c. Phylogenetic analysis revealed that these Smcaspase genes clustered into distinct caspase subfamilies and showed high conservation with homologs from other echinoderms and representative vertebrates. Conserved motif and gene structure analyses showed relatively similar structural patterns within each clade, whereas divergence was observed among different subfamilies. Promoter analysis identified numerous cis-acting elements related to gene regulation, immune response, and growth and development. Expression profiling under salinity stress showed that Smcaspase8a was significantly upregulated, particularly under prolonged stress, whereas the other genes exhibited limited transcriptional responses. Our findings highlight caspase function in salinity stress and provide the foundation of molecular salinity adaptation mechanisms in S. monotuberculatus.

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

Emerging techniques of CRISPR/Cas system in antiviral therapy and diagnostics: Applications, limitations, and translational perspectives.

The CRISPR/Cas (clustered regularly interspaced short palindromic repeats) system is a versatile technology for developing antiviral medicines and editing viral genomes in both diagnostics and vaccine synthesis. Emerging insights into class 2 effectors, such as Cas9, Cas12, and Cas13, which target viral DNA and RNA, have revolutionized vaccines against viruses such as HIV, HPV, HBV, and EBV. Innovative diagnostic techniques such as SHERLOCK, DETECTR, and FELUDA have demonstrated system's diversity and accuracy in detecting the virus markers, supporting clinical decision-making, indicating adaptability and precision of CRISPR. This review critically evaluates CRISPR's role in RNA editing, emphasizing its importance for functional genomics and development of recombinant vaccines. Translational challenges are critically discussed, including off-target effects, delivery limitations, and ethical issues, for which unique approaches such as high-fidelity Cas variants, non-viral delivery systems, and bioethical frameworks are evaluated to address these limitations. This review also covers other social implications, such as accessibility and biosecurity risks, associated with CRISPR technologies Collectively, these advances underscore the transformative potential of CRISPR technologies in shaping next-generation antiviral diagnostics and therapeutics.

CRISPR-Cas Systems↗

PubMed2026

Leveraging environmental applications and risks of coal gangue: A critical review on authigenic inorganic heavy metals, organic contaminants, and the removal of exogenetic contaminants.

Coal gangue (CG) as bulk solid waste has seriously threatened the ecosystem. Therefore, identifying the key risk drivers and exploring feasible disposal methods for CG are essential for developing a sustainable strategy. However, there is currently a lack of comprehensive information that balances the contamination risks with the valuable constituents present in CG, which hinders its full potential for sustainable use without negative environmental impacts. Given the complex composition and associated risks, we propose that addressing the critical properties related to contamination is crucial for the efficient utilization of CG. On this premise, we summarized several practical resource pathways (ecological multifunctional materials, extraction of rare elements, and soil additives) that are more favorable for sustainable development relative to conventional disposals. Meanwhile, we also propose that coupling disposals could intensely reduce CG's environmental footprints and capital costs. Consequently, regardless of the number of challenges to be solved, we believe the CG has broad application prospects, and we hope this review will promote the conversion of CG into an asset with lower ecological and social impacts.

Metals, Heavy↗

PubMed2026

Machine learning-based prediction of unplanned readmission and construction of an online calculator for elderly patients with mild ischemic stroke.

OBJECTIVE: To screen for independent risk factors for unplanned readmission in elderly patients with mild ischemic stroke, and to construct and validate an online risk prediction calculator based on an interpretable machine learning model, thereby providing a promising practical tool for accurate clinical assessment of 30‑day all‑cause unplanned readmission risk in this population. METHODS: A prospective cohort study was conducted, including 1050 patients aged ≥ 60 years with mild ischemic stroke admitted between August 2023 and September 2024. Participants were randomly divided into a training set (840 cases) and a test set (210 cases) at a ratio of 8:2. Risk factors were screened by univariate analysis and multivariable Logistic regression. Four machine learning models, namely LightGBM, XGBoost, Random Forest, and K‑Nearest Neighbors (KNN), were developed and their performance was evaluated using AUC, accuracy, sensitivity, and specificity as metrics. The SHAP framework was used for interpretability analysis, and an online calculator was subsequently developed based on the optimal model. RESULTS: Univariate analysis showed significant differences (P < 0.05) in 13 factors including age, smoking, AIP, TyG index, HALP score, etc. Multivariable Logistic regression identified age (OR = 9.752), smoking (OR = 5.171), AIP (OR = 6.691), TyG index (OR = 4.393), HALP score (OR = 2.831), and ≥ 2 comorbidities (OR = 3.664) as independent risk factors. All four machine learning models demonstrated good predictive performance. Based on a comprehensive evaluation of multiple metrics and computational efficiency, the LightGBM model exhibited the best predictive performance (AUC = 0.884, accuracy = 0.829, sensitivity = 0.812, specificity = 0.875). SHAP analysis showed that age, AIP, TyG index, smoking, and HALP score were key predictors. An online calculator developed based on this model enables individualized risk predictions. CONCLUSION: Key risk factors associated with 30‑day unplanned readmission in elderly patients with mild ischemic stroke were identified. The LightGBM model demonstrated high predictive accuracy, and together with the interpretability analysis and online calculator, offers a practical tool to support clinical risk assessment. However, this tool requires future external validation.

Humans↗

PubMed2025

The molecular mechanism of cuproptosis and research progress in pancreatic diseases.

PURPOSE: Cuproptosis has been proven to be a novel mode of cell death, distinct from other types of cell death such as necrosis, ferroptosis, pyroptosis, and apoptosis. This study aims to systematically review the molecular mechanisms of cuproptosis in recent years and its research progress in pancreatic diseases. METHODS: By searching PubMed and Web of Science databases, 113 key literatures were included for thematic analysis, covering the molecular mechanism of cuproptosis and its role in the occurrence and development of pancreatic cancer, acute and chronic pancreatitis, diabetes, pancreatic cyst, pancreatic injury and pancreatic neuroendocrine tumor. RESULTS: Cuproptosis refers to the accumulation of copper ions in cells, which leads to instability of ferritin and aggregation of acylated proteins, resulting in oxidative stress-related cell death. Recent studies have shown that cuproptosis plays an important role in the occurrence and development of various pancreatic diseases, such as pancreatic cancer, acute and chronic pancreatitis, diabetes, pancreatic cysts, pancreatic injuries and pancreatic neuroendocrine tumor. The inducers of cuproptosis, such as disulfiram, chloroquinolones, and perilla phenols, alleviate pancreatic cancer by promoting cell cuproptosis. Copper chelators such as tetraethylenepentamine and tetrathiomolybdate promote the recovery of pancreatic injury by inhibiting cell cuproptosis. CONCLUSIONS: Cuproptosis plays a crucial role in the pathogenesis of pancreatic diseases. Further research on the cuproptosis pathway may become a potential target for the treatment of pancreatic diseases.

Animals↗

PubMed2026

Proteomic responses of the oil palm pest Metisa plana (Psychidae) to farnesyl acetate exposure.

Metisa plana Walker (Lepidoptera: Psychidae) is a major defoliator of oil palm in Malaysia, causing substantial economic losses. Farnesyl acetate (FA), a sesquiterpenoid compound, has been proposed as a potential insecticidal agent against M. plana, yet its molecular impact on larval physiology remains poorly understood. Here, we employed label-free quantitative proteomics, functional enrichment analysis, and targeted transcript assessment to characterize the temporal proteomic response of M. plana larvae at 7 and 14 days after treatment (DAT) with FA. Principal component analysis revealed robust separation between treated and control samples at both time points, indicating sustained treatment-driven proteomic restructuring. Early exposure (7 DAT) elicited a heterogeneous response involving stress-associated proteins, redox enzymes, and cytoskeletal regulators, whereas later exposure (14 DAT) produced a consolidated profile characterized by metabolic reprogramming, downregulation of ribosomal proteins, induction of heat shock proteins, and enrichment of RNA surveillance and mitochondrial pathways. Targeted transcript analysis qualitatively supported proteomic trends for HSP83 and aldehyde dehydrogenase X, although limited amplification precluded quantitative inference. Collectively, these findings demonstrate that FA exposure drives a shift from acute proteomic perturbation toward a maintenance-oriented physiological state, prioritizing proteostasis, energy management, and stress adaptation over growth and development. This integrated molecular perspective provides mechanistic insight into the chronic effects of FA, highlighting its potential to suppress larval performance and informing the development of biorational, physiology-based pest management strategies in non-model insects.

Animals↗

PubMed2026

Mitigating pH-induced instability in deruxtecan-based ADCs: an onboard-mixing icIEF approach for robust charge heterogeneity characterization.

Accurate charge variant analysis of antibody-drug conjugates (ADCs) is essential for understanding product heterogeneity and ensuring quality control. However, Deruxtecan (DXd)-based ADCs present a unique analytical challenge due to the intrinsic instability of the payload, where the lactone ring readily undergoes hydrolysis under alkaline conditions, resulting in time-dependent shifts in charge distribution during imaged capillary isoelectric focusing (icIEF). In this study, we describe the development of an onboard-mixing icIEF method designed to minimize pH-induced degradation during sample preparation. By separating ADC samples from carrier ampholytes (CAs) prior to injection and enabling real-time mixing within the instrument, this approach effectively suppresses premature lactone ring opening and stabilizes charge variant profiles. Comparative studies between conventional premixing and onboard-mixing approach demonstrated that the latter significantly enhances reproducibility, particularly for acidic variants that are highly sensitive to structural conversion. Comprehensive method validation confirmed excellent precision, linearity, and sensitivity, with consistent performance across run-to-run and intra-day analyses. The results underscore the importance of controlling microenvironmental pH exposure in the analysis of chemically instable ADCs. The proposed onboard-mixing strategy provides a robust and efficient solution for icIEF-based characterization, reducing analytical artifacts while simplifying method development. This approach is broadly applicable to ADCs and other biotherapeutics containing pH-sensitive functional groups.

Hydrogen-Ion Concentration↗

PubMed2026

The gonadal matrisome and its correlation with sex change in the ricefield eel Monopterus albus.

The matrisome is a comprehensive list of genes in the genome of an organism, which encodes proteins constituting or interacting with the extracellular matrix (ECM). The gonadal ECM is important for folliculogenesis and spermatogenesis. This study characterized the composition of the matrisome and the expression of matrisome genes in the gonad of ricefield eel, a protogynous sex-changing teleost, during sex change. A total of 838 matrisome genes were identified in the genome of ricefield eel through an in-silico orthology-based approach, of which 482, 443, 429, and 570 matrisome genes were shown to be expressed in the gonads of female (F), early intersexual (EI), mid-intersexual (MI), and late intersexual (LI) fish, respectively. Differentially expressed matrisome genes (DEMGs) were observed across all the sexual stages as well as in each category of ECM components. Analysis of DEMGs in the comparison between EI and F revealed dramatic upregulation of adam8a, mmp9, and s100a11 while downregulation of col4a5, col15a1b, clec3ba, f13a1, and ccl44, which were further confirmed by qPCR analysis. Together, these findings revealed significant changes in the expression of many matrisome genes, particularly three regulator genes, adam8a, mmp9 and f13a1, as female ricefield eels initiate sex change, suggesting that gonadal tissues undergo dramatic remodeling involving the regression of ovarian tissues and the development of testicular tissues to facilitate this process. These data provide valuable resources for further unraveling the roles of matrisome genes in gonadal development of ricefield eel and other vertebrates.

Animals↗

PubMed2026

Bacteroides cellulosilyticus-derived 2-hydroxyphenylacetic acid rectifies hepatic lipid homeostasis in MASLD by targeting the PPARγ-CD36 axis.

The gut microbiota plays an important role in the occurrence and development of metabolic dysfunction-associated steatotic liver disease (MASLD), but the specific molecular mechanisms involved have not been fully elucidated. In this study, human cohort studies were performed to identify that the relative abundance of Bacteroides cellulosilyticus (B. cellulosilyticus) was significantly decreased in patients with MASLD. Through the integration of metagenomic and metabolomic analyses, it was confirmed that B. cellulosilyticus and its metabolite 2-hydroxyphenylacetic acid (2HPAA) are key factors regulating the occurrence and development of MASLD. Single-cell sequencing and lipidomic analyses revealed that 2HPAA can enter the liver through the enterohepatic circulation to exert regulatory effects. Specifically, 2HPAA inhibits the peroxisome proliferator-activated receptor γ (PPARγ) signaling pathway, thereby suppressing the expression of the fatty acid transporter CD36. Meanwhile, 2HPAA regulates lipid metabolism in hepatocytes by significantly enhancing palmitate conversion efficiency and inhibiting CD36 palmitoylation. This dual regulatory effect on CD36 expression and palmitoylation can reduce lipid accumulation in hepatocytes and ultimately alleviate MASLD progression. These findings reveal the mechanism by which B. cellulosilyticus and 2HPAA alleviate MASLD by targeting the PPARγ-CD36 pathway. This work provides a new perspective for the study of gut microbiota-host interactions in regulating liver diseases.

PPAR gamma↗

PubMed2026

Distinct cell morphotypes of Aureobasidium melanogenum ZN exhibit differential functional profiles in promoting maize growth.

Black yeast-like fungi of the genus Aureobasidium exhibit morphological plasticity, but whether distinct cellular states within the same genetic background are associated with different plant growth-promoting functions remains unclear. Here, yeast-like cells (YL), swollen cells (SC), and chlamydospores (CH) of Aureobasidium melanogenum ZN were characterized. YL was associated mainly with siderophore production and laccase activity, SC with extracellular polysaccharide accumulation, and CH with phosphate mobilization and higher ammonia and IAA production. Whole-genome and comparative genomic analyses revealed a shared repertoire related to nutrient acquisition, auxin-associated metabolism, extracellular oxidation, and carbohydrate remodeling, with expansions in nutrient- and cell-surface-related gene families. Transcriptomic and metabolomic analyses showed distinct deployment of these capacities, with CH exhibiting broad reprogramming of tryptophan-associated, nitrogen, phosphate, central-carbon, and amino-acid metabolism. In maize, CH at the optimal inoculation concentration of 105 CFU·mL-1 produced the strongest growth promotion, increasing plant height, dry biomass, root length, root surface area, and root volume by 58.6%, 365.1%, 191.0%, 194.3%, and 222.4%, respectively. Consistent with this pronounced growth phenotype, maize root transcriptomics showed coordinated CH-induced responses involving root development, nutrient transport, redox regulation, and root-interface remodeling. Root-zone tracking showed greater short-term stability and persistence of CH. These findings identify cellular state as an important functional dimension of Aureobasidium-plant interactions and provide a basis for developing fungal inoculants with defined beneficial cellular states.

Zea mays↗

PubMed2026

Muscular fiber properties and multi-omics investigation of larval and adult locomotor muscle in Microhyla fissipes.

During metamorphosis, Microhyla fissipes undergoes a critical transition from an aquatic to a terrestrial lifestyle, accompanied by significant remodeling of skeletal muscle. Notably, larval tail muscle degenerates, while adult hindlimb muscle develops. However, the molecular mechanisms that orchestrate these muscle type-specific adaptations to the changing environment remain unclear. In this study, histological observation, transcriptomics, and metabolomics were integrated to compare locomotor muscles from two stages: larval muscle from tail versus adult muscle from hindlimb. Our results revealed that adult muscle fibers exhibited reduced diameter and shorter sarcomere length compared to those of tadpoles. Transcriptomic analysis identified 4103 differentially expressed genes (DEGs), including 2182 up-regulated and 1921 down-regulated genes. Up-regulated genes were mainly involved in energy metabolism and cellular homeostasis pathways, including PPAR signaling and oxidative phosphorylation, whereas down-regulated genes were associated with carbohydrate metabolism and cell proliferation pathways, such as glycolysis/gluconeogenesis and PI3K-Akt signaling. Metabolic profiling indicated a metabolic shift from anaerobic to aerobic energy production, with 57 differential metabolites identified, mainly involved in protein metabolism and insulin-related pathways. Integrated multi-omics analysis further highlighted the AMPK and FoxO signaling pathways play key roles in this process. In conclusion, our findings demonstrate that the metabolic and structural differences between larval and adult skeletal muscles are mediated by AMPK- and FoxO-dependent signaling pathways, providing novel insights into the molecular mechanisms underlying adaptive development and locomotor transition in anuran amphibians.

Animals↗

PubMed2026

An allograft inflammatory factor enhances sperm viability by modulating intracellular calcium in oyster Crassostrea gigas.

As an important aquaculture bivalve, the Pacific oyster Crassostrea gigas faces severe constraints in artificial reproduction, where low sperm motility often leads to fertilization failure and limits the sustainable development of the oyster aquaculture industry. In the present study, the variation of sperm from different oyster individuals was observed, and high-quality sperm possessed intact, elongated flagella with no structural abnormalities, while low-quality sperm showed shortened flagella with frequent tangling or coiling defects. Transcriptomic analysis comparing high- and low-quality sperm revealed significantly reduced expression of genes associated with sperm motility and release (CgAIF1, CgAchR, CgSEX), sperm quality and development (CgEP4, CgIFi2b), and cryoprotection (CgISPs) in low-quality sperm. Notably, an allograft inflammatory factor (designed as CgAIF1) encoding EF-hand domain, known as Ca2+ binding activity, was among the most significantly downregulated in low-motility sperm. CgAIF1 is highly expressed in haemocytes, ganglia, and gonads of oysters. Incubation with the recombinant AIF1 protein (rCgAIF1) significantly improved sperm curvilinear velocity, thereby enhancing the overall motility of C. gigas sperm. Furthermore, rCgAIF1 incubation increased intracellular Ca2+ levels (2.13-fold at 30 min, 2.71-fold at 60 min) and superoxide dismutase (SOD) activity (1.44-fold at 30 min, 1.24-fold at 60 min) in sperm, suggesting potential roles in calcium homeostasis regulation and antioxidant defense. In conclusion, this study demonstrates that CgAIF1 significantly enhances motility of oyster sperm, providing a scientific basis for artificial breeding and seed production in oyster aquaculture.

Animals↗