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PubMed2026

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

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

Humans↗

PubMed2026

Genome-wide identification and expression profiling of HSD3B and SDR42E1 genes in the Pacific oyster (Crassostrea gigas): potential associations with gonadal development.

Sex steroids are lipid-soluble signaling molecules that regulate sex differentiation, reproductive development and physiological homeostasis in animals. 3β-Hydroxysteroid dehydrogenase/Δ5-Δ4 isomerase (3β-HSD) is a key steroidogenic enzyme, whereas SDR42E1, an extended short-chain dehydrogenase/reductase, has been implicated in sterol- and steroid-related metabolism. However, the composition, evolutionary relationships and expression patterns of the HSD3B- and SDR42E1-related genes in bivalve gonadal development remain poorly characterized. In this study, five PF01073-containing genes, comprising three CgHsd3b and two CgSdr42e1 genes, were identified in the Pacific oyster Crassostrea gigas. Phylogenetic analysis separated the proteins into HSD3B-related and SDR42E1-related groups, and gene-structure and motif analyses indicated subfamily-level divergence. All five proteins retained the SDR domain but differed in exon-intron structure and motif composition. Each contained the extended-SDR TGxxGxxG motif, whereas exact classical [ST]GxxxGxG and NNAG motifs were absent. Tyr- and Lys-equivalent residues were conserved, while the HSD3B1 Ser-equivalent position contained Thr in two C. gigas proteins and Ser in one. These features support their classification as extended-SDR proteins but do not establish enzymatic activity or substrate specificity. The three CgHsd3b genes were dispersed on one chromosome, whereas CgSdr42e1-1 and CgSdr42e1-2 were adjacent on another chromosome, suggesting a possible local duplication event for the CgSdr42e1 pair. Public RNA-seq data showed distinct tissue- and gonadal-stage expression patterns, with several genes displaying gonad-biased or female-stage-associated expression. Independent RT-qPCR profiling of the representative genes CgHsd3b-3 and CgSdr42e1-1 detected stage-dependent expression, although tissue rankings differed from those in the public RNA-seq datasets. These differences may reflect the use of independent biological samples, tissue composition, normalization procedures, and platform-specific measurements. Because enzymatic assays, metabolite measurements, cellular localization, and functional perturbation were not performed, the results identify candidate genes whose expression is associated with gonadal development rather than demonstrating regulatory roles. This study provides a comparative framework for future functional investigation of sterol- and steroid-related metabolism in bivalves.

Animals↗

PubMed2026

Beyond predictive performance: A systematic review and critical methodological appraisal of AI/ML and conventional modelling strategies in breast, colorectal, and pancreatic Cancer.

BACKGROUND: Predictive modelling for cancer risk, treatment-related complications, and survival is central to precision oncology. Conventional logistic regression (LR) and Cox proportional hazards (CoxPH) regression remain widely used but are limited when modelling nonlinear interactions, high-dimensional imaging features, and multimodal clinical-metabolic predictors. Artificial intelligence (AI) and machine learning (ML) methods offer expanded capability through automated feature extraction, ensemble learning, and flexible survival modelling, but the evidence on when AI/ML adds value over conventional models across cancer sites and predictive tasks remains fragmented. OBJECTIVE: To systematically evaluate the methodological performance, validation strategies, and translational limitations of AI/ML models compared with conventional statistical models in published predictive-modelling studies for breast, colorectal, or pancreatic cancer. METHODS: PubMed, Scopus, and Web of Science were searched for studies published between January 2019 and March 2025. Two reviewers independently conducted title-and-abstract screening, full-text eligibility assessment, and PROBAST risk-of-bias assessment. Sixty-five studies (n = 907,567 participants) were narratively synthesised by cancer site, predictive task, model family, comparator, validation strategy, predictor modality, and calibration or explainability reporting. RESULTS: The 65 studies comprised breast cancer (n = 35), colorectal cancer (n = 21), and pancreatic cancer (n = 9). AI/ML superiority over LR and CoxPH was task- and data-dependent. CNN- and U-Net-based models predominated in imaging and body-composition tasks, tree-based ensembles consistently outperformed LR for tabular perioperative complication prediction, and CoxPH remained competitive, and in the largest pancreatic risk study, superior to XGBoost (C-index 0.802 vs 0.723) in well-structured datasets. PROBAST analysis-domain risk was moderate in 54 of 65 studies (83%), driven by limited external validation, sparse calibration reporting (11/65), and few decision-curve analyses (7/65). CONCLUSION: AI/ML adds the most methodological value in imaging-derived feature extraction and nonlinear perioperative prediction, while conventional regression remains preferable in large, structured datasets with linear predictors. Clinical translation requires standardised body-composition definitions, external validation, calibration assessment, decision-curve analysis, and explainability, in line with TRIPOD+AI and CLAIM standards.

Humans↗

PubMed2026

External ventricular drain safety campaign and opportunities for global neuroanesthesiology quality and safety.

PURPOSE OF REVIEW: This review describes the conceptualization and implementation of the External Ventricular Drain (EVD) Safety Campaign, a global patient safety initiative by the Society for Neuroscience in Anesthesiology and Critical Care. It summarizes recent literature on EVD insertion and maintenance, highlights opportunities to advance quality and safety in neuroanesthesiology, and outlines priorities and a framework for future work. RECENT FINDINGS: The Society for Neuroscience in Anesthesiology and Critical Care launched a global initiative to improve EVD management. EVD insertion and maintenance remain key areas of ongoing research and quality improvement, particularly in reducing complications. SUMMARY: The EVD Safety Campaign provides a structured framework to improve care delivery and patient outcomes worldwide. Continued focus on standardization, education, and complication reduction, especially infection prevention, will be essential to advancing the field.

Humans↗

PubMed2026

Genetic overlap between estimated glomerular filtration rate and cardiovascular disease identifies potential targets for cardiorenal syndrome.

Heart and kidney diseases frequently coexist, but the genetic basis of this relationship remains unclear. We analyzed genetic data from large-scale studies to investigate how kidney function (estimated glomerular filtration rate, eGFR) and six common cardiovascular diseases share genetic risk factors. Using MiXeR method, and conjunctional false discovery rate (conjFDR) to identify overlapping genetic regions, we found 478 shared genomic loci between eGFR and cardiovascular diseases. These shared genes are involved in tissue development and structure. We also identified 29 genes that could be targeted by existing medications approved by the US Food and Drug Administration, such as PRKAG2, PDE1A, and IGF1R. Among these, genetically predicted higher level of IGF1R expression is associated with a higher eGFR, which reflects good kidney function and is protective against cardiorenal diseases, such as atrial fibrillation, and myocardial infarction. These findings reveal genetic overlap between kidney function and cardiovascular diseases, highlighting potential targets for understanding and treating cardiorenal syndrome.

Humans↗

PubMed2026

Morphology-engineered NiFe@C nanocages boosting electrochemical quantification of ractopamine in meat samples.

It is essential to acquire efficient electrocatalysts to develop ractopamine (RAC) electrochemical sensors. Herein, we report the synthesis of a series of carbon coated NiFe alloy nanostructures (e.g., NiFe@C nanoparticles, nanocubes and nanocages) using NiFe Prussian blue analogue (PBA) as the precursor. The NiFe@C nanocages exhibited the best electrocatalytic performance for RAC sensing. This is attributed to the embedded NiFe alloy nanoparticles that provide abundant active sites, and the unique nanocage structure facilitates electron transfer pathways while offering a high specific surface area. The resulting sensor achieves a low detection limit (LOD) of 54 nM (S/N = 3) within a linear range of 0.2-12 μM. Moreover, the sensor demonstrates good reproducibility, stability, and excellent long-term stability. Practical applicability was confirmed in meat samples, yielding satisfactory recovery rates ranging from 98% to 108%. A feasible strategy was introduced herein for rational design of metal@carbon electrocatalysts.

Phenethylamines↗

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

Peptide molecular lock-engineered nanobodies enable an oriented dual-modal immunoassay for reliable detection of Cronobacter sakazakii.

Conventional nanobody ELISAs for trace Cronobacter sakazakii in powdered infant formula suffer from random orientation and low signal output. We developed an oriented dual-modal immunoassay that combines site-specific biotinylation via a C-terminal AviTag and a peptide molecular lock, enabling controlled surface orientation while preserving nanobody structural integrity. This strategy was further integrated with phage-displayed nanobodies for multivalent amplification and both fluorescent and colorimetric readouts. The assay exhibited a broad linear range of 103-106 CFU/mL, with limits of detection (LODs) of 6.70 × 102 CFU/mL for fluorescence and 1.55 × 103 CFU/mL for colorimetry, showing improved sensitivity compared with the conventional passive adsorption-based Nb-ELISA evaluated in this study. XGBoost-based multimodal fusion improved quantitative accuracy, and SHAP analysis elucidated modality contributions. In spiked powdered infant formula samples, recoveries ranged from 92.1% to 118% with coefficients of variation below 5.98%, confirming acceptable matrix tolerance and analytical reliability.

Cronobacter sakazakii↗

PubMed2026

Dual signal-enhanced immunochromatographic test strip based on Au@PtNPs: From sensitive detection of thiamethoxam to multiplex pesticide screening in vegetables.

Immunochromatographic test strip (ICTS) is a rapid analytical technique widely used in environmental and food detection owing to its merits of simple operation and short analysis time. Herein, three-dimensional nanoflower-structured gold‑platinum nanoparticles (Au@PtNPs) were synthesized via a seed-growth method. Compared with conventional gold nanoparticles (AuNPs), Au@PtNPs exhibited stronger signal intensity, excellent catalytic performance, and efficient antibody binding efficiency. Colorimetric Au@PtNPs-ICTS and catalytic colorimetric Au@PtNPs-ICTS were developed for the sensitive detection of thiamethoxam (THI) in vegetables. The limits of detection (LODs) for colorimetric Au@PtNPs-ICTS and catalytic colorimetric Au@PtNPs-ICTS quantitative analysis were 0.18 ng/mL and 0.093 ng/mL, respectively, representing approximately 3-fold and 6-fold improvement compared to AuNPs-ICTS (0.56 ng/mL). Furthermore, highly sensitive detection of multiple pesticide residues (chlorpyrifos, acetamiprid, and imidacloprid) was achieved by replacing the corresponding target antigens and antibodies, which further verified the universality of this immunochromatographic strategy.

Thiamethoxam↗

PubMed2026

Assessment and CommuniCation ExcelLEnce foR sAfe paTient outcomEs (ACCELERATE): A stepped-wedge cluster randomised trial evaluating the effectiveness of a nurse-led assessment and handover communication intervention on patient adverse events.

BACKGROUND: Patients continue to experience harm from undetected deterioration, falls and pressure injuries. We aimed to implement and evaluate an organisational, ward-level nurse-led assessment and communication intervention to proactively reduce patient adverse events. METHODS: A stepped-wedge cluster randomised Trial over 12-months was conducted at three metropolitan hospitals. Our intervention comprised a comprehensive, systematic patient assessment at shift commencement; a structured patient-centred bedside nurse-to-nurse clinical handover; and multidisciplinary communication consisting of nurse participation in medical ward rounds. Evidence-based implementation strategies informed intervention delivery to nine clusters (20-35 bed-wards with ≥70% permanent nurses) over three sequential 14-week steps. Routinely collected patient-level data were used to measure intervention effect. The primary outcome was a composite measure of medical emergency team calls, unplanned intensive care unit admissions, in-hospital falls; and stage 2-4 pressure injuries. Secondary outcomes were: individual measures of the primary outcome; nurse-reported perceptions of safety culture; organisational readiness to change; barriers to physical assessment; staff engagement; and patient-reported experience measures of safety and overall hospital experience. Analyses were adjusted for age, sex, hospital, pre/post intervention, and Trial step (fortnight), with random effects for ward and patient. RESULTS: There were 13,753 eligible admissions. No change was observed in the primary composite outcome measure (odds ratio (OR) [95% confidence interval (CI)]: 0.99 [0.77, 1.28]; p = 0.95). There was no significant difference in medical emergency team calls (OR [95% CI]: 1.02 [0.75, 1.39]; p = 0.91); unplanned intensive care unit admissions (OR [95% CI]: 1.35 [0.57, 3.20]; p = 0.50) and falls (OR [95% CI]: 1.53 [0.96, 2.45]; p = 0.07). However, stage 2-4 pressure injuries significantly decreased by 41% (OR [95% CI]: 0.59 [0.38, 0.93]; p = 0.02); a significant absolute effect improvement of 0.8% ([95% CI: 0.3%-1.3%], p < 0.01). There were statistically significant improvements in nurses' overall perceptions of Safety Attitudes (Pre: 74.6, Post: 79.7; p = 0.02), and the Organisational Readiness to Change subscales of, leader culture (Pre: 3.73, Post 3.91; p = 0.02), leadership behaviour (Pre: 3.85, Post: 4.11; p = 0.03), and general resources (Pre: 3.06, Post: 3.30; p = 0.03). A statistically significant decrease in Barriers to Physical Assessment (Pre: 2.48, Post: 2.24; p <0.001) and in six of seven sub-scales was observed. Patients' overall Measure of Safety remained high, but unchanged (Pre: 3.94 Post: 3.92; p = 0.07). CONCLUSION: The ACCELERATE Trial demonstrated that nurse-driven initiatives, emphasising structured physical assessments by nurses, patient-centred clinical handovers, and multidisciplinary communication, significantly: reduced pressure injuries; decreased nurses' perceived barriers to performing physical assessments; and improved leadership behaviour, communication, and ward safety culture perceptions. Results highlight the transformative potential of this approach, which now warrants testing at scale for broader implementation. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ID: ACTRN12621000265875.

Humans↗

PubMed2026

Perioperative care for patients with opioid exposure and opioid use disorder: screening and treatment strategies.

PURPOSE OF REVIEW: The prevalence of opioid tolerance, dependence, and use disorder is increasing among patients presenting for surgical care, yet perioperative management strategies for these patients remain inconsistent. This review examines the impact of preoperative opioid exposure on surgical outcomes, the scope of untreated opioid use disorder (OUD) among surgical patients, and advances in clinical and systems-level approaches to perioperative care. RECENT FINDINGS: Preoperative opioid exposure independently predicts worse surgical outcomes, including higher opioid consumption, readmissions, complications, and mortality, in a dose-dependent manner. Perioperative opioid exposure predicts persistent opioid use after surgery, with the duration of exposure a stronger predictor of subsequent OUD than daily dose. Data-driven prescribing guidelines and structured opioid tapering reduce overprescribing without compromising pain control. Among surgical patients with diagnosed OUD, approximately two-thirds do not receive medications for opioid use disorder (MOUD), though treatment engagement and maintenance substantially improve outcomes. Evidence now clearly supports perioperative buprenorphine continuation over interruption. SUMMARY: Effective perioperative management of opioid-complex surgical patients requires systematic screening, evidence-based prescribing, MOUD continuation, and institutional infrastructure. The primary barrier is shifting from evidence generation to implementation.

Humans↗

PubMed2026

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↗

PubMed2026

Identification of aquaporin (AQP) genes in the noble scallop Chlamys nobilis and characterization of their expression under low-temperature stress.

Aquaporins (AQPs) are transmembrane channel proteins essential for water homeostasis and cellular stress responses. In marine bivalves, their roles in cold tolerance remain poorly understood despite frequent winter mortality events in aquaculture. Here, we identified nine AQP genes in the genome of the economically important noble scallop Chlamys nobilis. Phylogenetic analysis revealed strong conservation with other bivalve AQPs, and structural features, including conserved NPA motifs and ar/R selectivity filters, support their canonical water/glycerol transport functions. Tissue-specific expression profiling showed predominant enrichment in osmoregulatory tissues (gills, intestine) and gonads. Under both chronic and acute low-temperature stress from 23 °C to 9 °C, most CnAQP genes exhibited transient upregulation followed by suppression. Notably, CnAQP4 displayed sustained upregulation, implicating it as a key mediator of long-term cold adaptation. Promoter analysis further revealed abundant cis-elements linked to growth and development as well as immune regulation. Our findings provide the first comprehensive characterization of the AQP family in C. nobilis, highlighting its critical role in maintaining cellular integrity during cold stress and offering molecular targets for selective breeding of cold-tolerant scallop strains.

Animals↗

PubMed2026

Access to maternity services for women asylum seekers and refugees: A transnational document analysis of international, European regional, and United Kingdom governance.

Women asylum seekers and refugees face persistent barriers to maternity care (antenatal, intrapartum and postnatal care) across high-income countries, yet the upstream governance shaping access remains under-examined. Although legally distinct, both groups share protection-seeking experiences and are addressed jointly in governance documents. This study examined and synthesised how international (macro), European regional (meso), and United Kingdom (UK, micro) governance documents frame and operationalise maternity service access. Sixty-four documents were analysed using the READ framework. Inductive analysis of macro and meso documents identified six access dimensions: universal coverage; cultural and linguistic adaptation; rights-based approaches; multi-agency collaboration; data, monitoring and accountability; and quality of care. These dimensions structured assessment of UK governance, with jurisdictions rated strong, moderate or weak. Alignment was fragmented: Wales, Scotland and Northern Ireland exempted asylum seekers from charging, whereas England retained charging provisions. Multi-agency collaboration was consistently articulated, yet none of the 35 UK government documents focused on maternity access for this population, and none required outcome monitoring disaggregated by asylum or refugee status. UK governance appears coordinated in form but fragmented in substance. UK-wide minimum standards and routine recording of these data, with safeguards against immigration-related use, could strengthen coherence and accountability and improve visibility of inequities.

Refugees↗

PubMed2026

AI-driven snapshot hyperspectral imaging for on-line sorting systems in food industry: From real-time sensing to intelligent decision-making.

High-throughput food sorting requires rapid, non-destructive detection of external defects, foreign materials, and internal quality attributes in heterogeneous food matrices. Conventional scanning hyperspectral imaging may suffer from motion-induced spatial-spectral mismatches, whereas snapshot hyperspectral imaging (S-HSI) captures spectral images within a single integration time. However, its advantage is limited by trade-offs in resolution, signal-to-noise ratio (SNR), reconstruction uncertainty, and calibration stability, which are further amplified by variable tissue structure, surface reflection, moisture, and fat distribution in foods. This review critically examines artificial intelligence (AI)-driven S-HSI for on-line food sorting within a sensing-representation-decision-execution framework. Compact architectures are compared according to their physical constraints, food-sorting suitability, and ability to support mapping between spectral responses and physicochemical quality attributes. AI strategies are reviewed for spectral reconstruction, image restoration, spatial-spectral representation, band selection, uncertainty-aware decision-making, and edge implementation. AI can partially compensate for snapshot-specific limitations, but current evidence remains largely limited to laboratory or prototype studies. Future work should link system performance to food safety and quality outcomes by reporting throughput, decision latency, calibration drift, missed-detection risk, false-rejection cost, and closed-loop sorting success.

Hyperspectral Imaging↗

PubMed2026

Genome-wide identification and expression analysis of the CREB/ATF family and its potential role in melanogenesis in the Manila clam (Ruditapes philippinarum).

Ruditapes philippinarum is an economically important bivalve species in China, and shell color is a trait of ecological and commercial significance. Melanin is a key determinant of shell color, and members of the CREB/ATF family have been reported to participate in melanogenesis in other organisms. In this study, members of the CREB/ATF family were systematically identified at the whole-genome level based on genomic and transcriptomic datasets, followed by analyses of their phylogenetic relationships, gene structures, and expression patterns. A total of six CREB/ATF family members were identified and classified into five subfamilies. Expression profiling and RT-qPCR validation revealed that most CREB/ATF genes were highly expressed in the mantle and displayed clear differences among shell-color phenotypes. Except for RpATF4 and RpCREBZF, most members exhibited relatively high expression levels in dark-colored shell strains, particularly in black and zebra-striped clams. Moreover, most genes showed low expression during early embryonic and larval stages but increased expression at the single-siphon spat and juvenile stages. These results suggest that the CREB/ATF family may be involved in melanin-associated shell-color regulation in R. philippinarum, providing important candidate genes and a theoretical basis for further elucidating the molecular mechanisms of shell-color formation in mollusks.

Animals↗

PubMed2026

From pathobiology to prescribing in obesity-driven HFpEF: A systematic review and practical therapeutic framework.

Heart failure with preserved ejection fraction (HFpEF) is increasingly driven by obesity and cardiometabolic dysfunction. In this phenotype, the dominant biology extends beyond congestion alone and includes visceral and epicardial adiposity, systemic inflammation, impaired myocardial energetics, endothelial dysfunction, and exertional elevation in filling pressures. We performed a PRISMA-compliant systematic review with structured narrative evidence synthesis to evaluate pharmacological therapy in obesity-driven HFpEF, searching PubMed/MEDLINE, Scopus, Web of Science Core Collection, ClinicalTrials.gov, and WHO ICTRP through December 2025. Eighteen reports were included in the final qualitative synthesis. The available evidence supports sodium-glucose cotransporter 2 inhibitors as the pharmacological foundation because they provide the most mature outcome data across the preserved ejection fraction spectrum. Semaglutide improves symptoms, physical limitations, exercise capacity, and body weight in dedicated obesity-related HFpEF trials, whereas tirzepatide extends this signal by improving clinical status and reducing worsening heart failure events. Finerenone broadens the therapeutic platform in HF with mildly reduced or preserved ejection fraction, although obesity-specific data remain indirect. Conventional neurohormonal therapies retain a selective role, but they are not the principal biological match for this phenotype. Obesity-driven HFpEF should therefore be managed as a cardiometabolic syndrome with heart failure expression, using a phenotype-based sequence that links diagnosis, decongestion, SGLT2 inhibition, obesity-directed therapy, and selective adjunctive intensification.

Humans↗

PubMed2026

Integrated analysis uncovers exogenous induction and molecular regulation of erinacine A accumulation in Hericium erinaceus.

Erinacine A, a cyathane-type diterpenoid mainly from Hericium erinaceus mycelia, exhibits prominent neurotrophic and neuroprotective activities, making it a promising candidate for managing neurodegenerative diseases. However, its low abundance and unclear genetic regulatory mechanisms hinder its application as a nutraceutical. This study aimed to decipher its regulatory mechanisms and enhance production. Four exogenous inducers were screened, with salicylic acid (SA) and ergosterol (ERG) significantly increasing erinacine A content by 62.21% and 146.70% at 20 days, respectively. Transcriptome and WGCNA of inducer-treated sample identified darkorange and magenta modules associated with erinacine A biosynthesis, with the eri gene cluster enriched in the darkorange module and eriG and eriF as hub genes. Forward genetic analysis via QTL mapping of the HeD127 dikaryon population revealed significant phenotypic variation in erinacine A content (0.341-13.085 mg/g) and identified two loci (erA-1 and erA-2) explaining 18.63% of phenotypic variation. Integrating these forward and reverse genetic analyses revealed that salicylic acid and ergosterol synergistically regulate core carbon metabolic pathways to augment acetyl-CoA supply for the mevalonate pathway, suppressed competitive metabolism, enhanced diterpene skeleton construction and structural modification. These results deepen our understanding of the genetic and molecular basis governing accumulation of erinacine A, and facilitate its application in neuroprotective pharmaceuticals.

Diterpenes↗