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Are there any common effects in preclinical models of micro- and nanoplastic (MNP) exposure? A systematic review.

Micro- and nanoplastics (MNPs) are emerging contaminants detected in food sources and the marine food chain, raising concerns about human health. Although no causal relationship has been established between MNP exposure and specific diseases, growing evidence suggests adverse developmental, behavioral, cognitive and biochemical effects. This systematic review synthesized evidence from common preclinical neurotoxicology models, including C. elegans, D. rerio, D. melanogaster, in vitro systems and rodents, to identify convergent developmental, behavioral and biochemical outcomes. The protocol was preregistered in OSF, followed PRISMA-P guidelines, applied PICOS criteria, and assessed methodological quality using the European Commission's ToxRTool. Overall, 185 studies were included. Consistent findings showed impaired survival and disrupted development across all models. Behavioral alterations affecting anxiety, memory, learning, sociability and locomotor activity were also consistently reported. In addition, numerous studies identified disruptions in the serotonergic (5-HT) system, including changes in neurotransmitter levels, transporters and metabolic enzymes. Despite methodological heterogeneity, these findings indicate that MNP exposure produces reproducible neurodevelopmental and neurochemical alterations across experimental models. Future studies should improve methodological harmonization, strengthen cross-model comparability and identify robust biomarkers and key mechanisms underlying MNP-induced neurotoxicity, facilitating translation to human health risk assessment frameworks.

Animals

Improving insurance deduction identification: a hybrid artificial intelligence model using machine learning and expert systems.

PURPOSE: Financial challenges in healthcare systems worldwide, especially in low- and middle-income countries like Iran, have increased hospitals' reliance on insurance reimbursements. Unrecognized insurance deductions often cause severe financial shortages, making efficient deduction management crucial. This study aimed to design a hybrid intelligent system for identifying and predicting insurance deductions by combining machine learning and expert system frameworks. DESIGN/METHODOLOGY/APPROACH: A mixed-methods design was applied in four stages. First, a scoping review identified the causes and patterns of insurance deductions. Second, interviews with 15 insurance experts produced a validated checklist and a dataset from inpatient billing records. Third, using the CRISP-DM methodology, machine learning algorithms were developed and tested in SPSS Modeler alongside a fuzzy expert system developed in MATLAB. Finally, the model was validated using the holdout method. FINDINGS: Four categories of deduction drivers were identified: service provision, registration errors, document submission issues, and revenue conversion processes. The CHAID decision tree outperformed other algorithms with a 99% precision rate and the lowest Mean Absolute Error (9.43). A brief assessment of potential overfitting was conducted to ensure that the CHAID model's high accuracy was interpreted cautiously and supported by the validation results. The fuzzy expert system with validated rules was adaptable for deduction classification, especially for cases unsuitable for quantitative modeling. ORIGINALITY/VALUE: The hybrid model improves detection and prevention of deductions, offering actionable insights for hospital administrators, insurers, and policymakers. Its implementation can enhance hospital information systems, streamline claims processing, and optimize revenue management amid financial constraints.

Machine Learning

Artificial Intelligence Cannot Replace Peer Reviewers but May Help Editors Triage: A Comparative Analysis of a Large Language Model and Human Reviewer Recommendations at the American Journal of Sports Medicine.

BACKGROUND: The peer review system faces increasing strain from rising manuscript volumes, reviewer fatigue, and well-documented interreviewer disagreement. Large language models (LLMs) have shown potential to support the peer review process, but their ability to replicate editorial decisions at high-impact medical journals and their utility as manuscript screening tools remain unknown. PURPOSE: To compare the agreement between an LLM and the final editorial decision on manuscripts submitted to the American Journal of Sports Medicine and to evaluate the potential of LLMs as a manuscript screening tool. STUDY DESIGN: Cross-sectional agreement study. METHODS: Fifty-four manuscripts randomly selected from submissions to the American Journal of Sports Medicine (September 2024-October 2024) were reviewed by a locally deployed LLM (Ministral 3 14B; Mistral AI) using a standardized prompt. The artificial intelligence (AI) produced a categorical recommendation (reject, cascade, revision, or accept) and a numerical score (0-100) for each manuscript. Agreement with the final editorial decision was assessed by Cohen kappa (4-category model) for pooled human reviewers (n = 139 reviews) and the AI (n = 54). Screening performance was evaluated by positive predictive value (PPV), sensitivity, and specificity. RESULTS: Pooled human reviewers demonstrated fair agreement with the final decision (&#x3ba; = 0.181 [P < .001]; 42.4% agreement), while the AI demonstrated slight, nonsignificant agreement (&#x3ba; = 0.126 [P = .099]; 37.0% agreement). The AI recommended revision for 61.1% of manuscripts, of which 72.7% were ultimately rejected or cascaded, demonstrating systematic "revision bias." When the AI recommended rejection, 54.5% of those manuscripts were ultimately rejected and 27.3% were cascaded; when the AI recommended cascade, 50% were rejected and 50% were cascaded. However, when the AI recommended rejection or cascade (n = 21), 90.5% received a final decision of rejection or cascade (PPV, 90.5%; specificity, 81.8%). Manuscripts with an AI score <70 were rejected or cascaded 88.0% of the time (PPV, 88.0%). CONCLUSION: AI cannot replicate the nuanced judgment of human peer reviewers at a high-impact sports medicine journal. When AI recommended rejection or cascade, 90.5% of manuscripts received that final decision (descriptive PPV, 90.5%; 95% CI, 71.1%-97.3%), suggesting potential utility as an exploratory first-pass screening tool warranting further validation in larger cohorts. However, AI could not reliably distinguish manuscripts destined for outright rejection from those that would be cascaded to a sister journal-an important limitation for editorial triage applications.

Sports Medicine

Volumetric bone marrow cellularity (VBMC) assessment from routinely processed trephines using three-dimensional x-ray histology and gaussian peak modelling.

Objective.Bone marrow cellularity is routinely estimated from a small number of two-dimensional histology sections, making assessment sensitive to section representativeness, processing artefacts and observer interpretation. Three-dimensional (3D) x-ray histology (XRH), using x-ray computed microtomography (&#xb5;CT), enables non-destructive whole-block imaging of trephine biopsies. This study evaluated whether XRH combined with Gaussian peak modelling could provide a pragmatic whole-block volumetric bone marrow cellularity (VBMC) estimate from formalin-fixed paraffin-embedded (FFPE) trephine biopsy blocks.Approach.Six routinely processed FFPE bone marrow trephine blocks were imaged using &#xb5;CT-based XRH at &#x223c;15 &#xb5;m spatial resolution. VBMC was defined as the red-marrow (RM) fraction of the marrow soft-tissue compartment, RM/(RM + intra-biopsy wax), with wax serving as the volumetric proxy for adipocyte/yellow marrow space. Whole-volume greyscale histograms were modelled using a three-peak Gaussian approach representing intra-biopsy wax, RM and demineralised trabecular matrix. Peak-height and area-under-the-curve metrics were compared with whole-volume 3D segmentation and clinical two-dimensional (2D) cellularity estimates.Main Results.Gaussian peak modelling successfully approximated the segmented tissue-phase distributions. The peak-height-derived VBMC metric showed the closest agreement with whole-volume 3D segmentation, with an average absolute percentage difference of 9.3%, compared with 18.6% for clinical expert 2D cellularity estimates. The area-under-the-curve metric followed similar trends but consistently overestimated VBMC. Clinical 2D cellularity broadly followed whole-biopsy trends but showed one discordant case not explained by slice-position sampling alone. XRH also enabled unrestricted virtual reslicing and visualisation of sectioning-associated artefacts prior to further microtomy.Significance.Pre-sectioning XRH combined with Gaussian peak modelling provides a rapid, segmentation-free route to volumetric cellularity estimation from intact clinical FFPE trephine blocks. The approach supports objective whole-biopsy assessment while remaining compatible with routine histopathology workflows, reflecting the expected limitations of section-based visual estimation despite its role as the current clinical standard. In the near term, it could provide a non-disruptive adjunct to conventional 2D cellularity reporting, pending larger validation studies.

Imaging, Three-Dimensional

Applications of metal-organic frameworks in smart packaging for food freshness indication: a comprehensive review.

Smart packaging is extensively studied for its multifunctional capabilities in antimicrobial activity, preservation, and atmosphere modification. Recently emerged metal-organic frameworks (MOFs) freshness-indicating packaging becomes a key research direction in smart packaging owing to its distinctive functions and physicochemical properties. As multifunctional materials, the unique porous structure and tunable properties of MOFs provide a distinctive approach for developing food packaging applications dedicated to food freshness indication. Existing MOFs-based smart packaging still faces potential safety risks and technical challenges in practical applications, and there remains a lack of integrated discussion that combines synthesis strategies, packaging design, optimization, and safety assessment. This review elaborates on the application of MOFs in freshness-indicating smart packaging, focusing on diverse MOFs synthesis strategies, the formats of smart packaging, types of indicator signals, and qualitative/quantitative analytical methods. It also delves into the methodology concepts of MOFs-based smart packaging and evaluates MOFs safety in food packaging by addressing potential risks. Studies show that MOFs-based smart packaging achieves qualitative and semi-quantitative analysis of food freshness through multiple signal modalities such as visible color change, fluorescence, and photothermal effects. This review emphasizes that safe MOFs design is critically important and should comply with the overall migration limit of <10 mg/dm2 specified in Regulation (EC) No 1935/2004, lanthanide element limit of <0.05 mg/kg, and FDA threshold of 1.5 &#x3bc;g/person/day. Comprehensive safety assessment and intelligent sensing platforms will constitute pivotal directions for advancing MOFs-based smart packaging toward practical application.

Food Packaging

A Standardized Nursing-Led Protocol Integrated Pain, Sleep, Medication Adherence, and Symptom Management in Postherpetic Neuralgia.

Postherpetic neuralgia (PHN) is a persistent neuropathic pain condition after herpes zoster that frequently coexists with sleep disturbance, medication-related problems, and fluctuating symptoms. This study evaluated whether a standardized nursing-led protocol could improve multidimensional short-term outcomes beyond usual care. In this prospective, parallel-group randomized controlled trial, 128 adults with PHN were allocated 1:1 to usual care or usual care plus an eight-week protocol integrating structured pain assessment, sleep monitoring, medication-adherence support, and rule-based digital symptom monitoring. The primary outcome was the between-group difference in change in Numeric Rating Scale (NRS) pain score from baseline to Week 8. Secondary outcomes included Pittsburgh Sleep Quality Index (PSQI), MMAS-8 medication adherence, symptom burden, pain-related nocturnal awakenings, breakthrough pain, rescue analgesic use, adverse events, rule-based alerts, and nursing satisfaction. Week-8 data were available for 116 participants (57 usual care; 59 protocol). Mean NRS scores decreased from 7.19 &#xb1; 1.08 to 4.82 &#xb1; 1.53 in the usual-care group and from 7.28 &#xb1; 1.05 to 3.24 &#xb1; 1.28 in the protocol group. An NRS reduction of at least 2 points occurred in 49.1% and 76.3% of participants, respectively. The protocol group also showed larger improvements in PSQI, MMAS-8, symptom burden, and nocturnal awakenings, with fewer breakthrough-pain episodes and less rescue-analgesic use. These findings support further evaluation of the standardized nursing-led protocol in preregistered multicenter trials with intention-to-treat analyses and longer follow-up.

Humans

Specific Instruments for Caregiving Competence Among Family Caregivers of Cancer Patients: A COSMIN Systematic Review of Psychometric Properties.

OBJECTIVE: To evaluate and summarize the psychometric properties of specific instruments for caregiving competence among family caregivers of cancer patients. METHODS: Systematically searched eight databases for studies published up to November 2025. The methodological quality and psychometric properties of the instruments were evaluated using COSMIN 2.0. Evidence grades were rated using the modified GRADE system (four grades: "High," "Moderate," "Low," and "Very Low"), and recommendations were formulated (Category A: recommended, Category B: potential with further validation, and Category C: not recommended). RESULTS: Seven studies were included, comprising three specific instruments: the Care Competency Scale for Family Caregivers in Home Palliative Care (CCSHPC) (n = 1), the Caregiver Caregiving Self-Efficacy Scale-Oral Cancer (CSES-OC) (n = 1), and the Caring Ability of Family Caregivers of Patients with Cancer Scale (CAFCPCS) (n = 5). Both the CCSHPC and CAFCPCS received Category B recommendations, demonstrating "adequate" content validity with evidence grades rated "very low" and "low," respectively. The CAFCPCS also shows good structural validity ("moderate") and internal consistency ("low") in some cultural contexts. The CSES-OC is a Category C recommendation, with high-quality evidence indicating "inadequate" criterion validity. CONCLUSION: Few specific instruments exist, and most did not strictly follow COSMIN guidelines. The CAFCPCS is provisionally recommended based on relative evidence superiority rather than complete psychometric validation. Further cross-cultural and localized instrument development is warranted. IMPLICATIONS FOR NURSING PRACTICE: Use well-validated specific instruments to identify strengths and weaknesses in the caregiving competencies of family caregivers of cancer patients, enabling them to deliver high-quality home-based cancer care.

Female

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

A chromosomal gtrB homolog and dam differentially contribute to dry-heat and high hydrostatic pressure resistance in Salmonella enterica.

Salmonella enterica can persist in low-moisture foods and shows enhanced dry-heat resistance under low water activity, posing significant food safety challenges. However, the genetic basis of extreme dry-heat resistance and its relationship with other processing stresses remain unclear. In this study, twelve S. enterica strains were screened for dry-heat treatment at 60&#xa0;&#xb0;C and 80&#xa0;&#xb0;C, with S. Infantis CICC21649 identified as the most resistant strain. Comparative genomics and transcriptional analysis identified candidate genes related to envelope integrity and regulation, including gtrB and dam. Deletion of the chromosomal gtrB homolog reduced dry-heat resistance, producing an additional 0.91-log10 reduction relative to the parent strain at 80&#xa0;&#xb0;C. Deletion of dam caused broader stress sensitivity, reducing resistance to both dry heat and high hydrostatic pressure, with the stronger phenotype observed under high hydrostatic pressure. Proteomic analysis of the chromosomal gtrB homolog mutant revealed broad alterations in envelope-associated proteins, transport functions, oxidative stress pathways, and central metabolism under dry-heat stress. These findings indicate that the chromosomal gtrB homolog is an important contributor to extreme dry-heat resistance, whereas dam contributes to resistance against both dry-heat and high hydrostatic pressure, likely through a broader regulatory role in stress adaptation. These results reveal distinct structural and regulatory layers underlying stress adaptation in S. enterica and provide practical guidance for low-moisture food processing by highlighting the need to account for strain-dependent and stress-specific resistance during process validation.

Hydrostatic Pressure

Imaging&#x2011;based models for predicting cerebrovascular complications of carotid stenosis.

This is a protocol for a Cochrane review (prognosis). The objectives are as follows: Primary objective To systematically review and critically appraise multivariable prognostic models developed for adults (&#x2265;&#x202f;18&#x202f;years) with carotid stenosis in which imaging biomarkers (e.g. plaque characteristics derived from magnetic resonance imaging (MRI), computed tomography (CT), or ultrasound) constitute the core predictors. The primary focus is to evaluate the predictive performance of these models for cerebrovascular complications - specifically ipsilateral ischaemic stroke and transient ischaemic attack (TIA) - which are the clinical outcomes to be predicted. Where feasible, we will summarise and compare the models' discrimination (C&#x2011;statistic/area under the curve (AUC)) and calibration (calibration&#x2011;in&#x2011;the&#x2011;large, calibration slope, observed&#x2011;to&#x2011;expected ratio) across studies, and assess their potential for clinical application and external validation. For the purpose of defining symptomatic carotid stenosis as an eligibility criterion and subgroup variable, we will include studies that also considered retinal ischaemia (e.g. retinal embolism, amaurosis fugax) as a qualifying event. Secondary objectives To describe the combinations of imaging markers, modelling techniques, sample sizes, and variable&#x2011;selection strategies used in the development of the included models To evaluate the performance of these models for additional secondary clinical outcomes: plaque progression or regression, incident high&#x2011;risk imaging features, and the transition from asymptomatic to symptomatic disease To explore whether predictive performance differs according to imaging modality (MRI versus CT versus contrast&#x2011;enhanced ultrasound (CEUS)) or technical protocol (e.g. 3&#x202f;T versus 1.5&#x202f;T, spectral CT versus conventional CT) For studies that report both cerebrovascular and broader cardiovascular outcomes (major adverse cardiovascular events, myocardial infarction, etc.), we will only extract the performance metrics relating to cerebrovascular events for the primary analysis. Performance metrics for cardiovascular outcomes will be considered exploratory and will not form part of the main synthesis.

Humans

New insights into soil amendment: Impact of humic acid on typical antibiotic resistance in agricultural soil.

Humic acid (HA) addition can improve agricultural soil, but little is known about how it affects the soil resistome. In this study, we used selective agar plate combined with quantitative PCR (qPCR) and 16S rRNA gene sequencing to investigate how HA influences antibiotic resistant bacteria (ARB) and antibiotic resistant genes (ARGs) in soil contaminated with erythromycin and kanamycin. 0.1 % HA reduced the abundance of culturable erythromycin-resistant bacteria (ERB), while promoting the growth of kanamycin-resistant bacteria (KRB). Lysinibacillus and Paenibacillus were the dominant genera in ERB and KRB, respectively, governing the changes in their abundances. At this concentration, the Lysinibacillus abundance in ERB decreased from 96.74 % to 70.57 %. Meanwhile, that of Paenibacillus in KRB increased from 33.40 % to 77.44 %. The copy number of ermF decreased after HA addition, while that of ermB increased. Furthermore, 0.1 % HA significantly reduced the copy number and relative abundance of aadA1 and aac(6')-Ib (aka aacA4)-03 in the soil. Changes in these two types of ARB and ARGs were primarily driven by shifts in the microbial community structure. Soil physicochemical properties, particularly increased organic matter (OM), altered the absolute abundance of ermB. Meanwhile, changes in intI1 abundance determined the risk associated with aadA1 and aac(6')-Ib (aka aacA4)-03. These findings emphasize the dual role of HA in the dissemination of antibiotic resistance in agricultural soils and highlight the necessity of considering dose-dependent effects when applying HA as a soil amendment.

Soil Microbiology

Genome-wide identification of the HSP70 superfamily in tropical sea cucumber Stichopus monotuberculatus and their expression analysis under low-salinity stress.

Heat shock proteins (HSPs) are a group of evolutionarily conserved molecular chaperones that serve as indispensable core regulators in preserving cellular homeostasis and orchestrating organismal stress responses. The tropical sea cucumber Stichopus monotuberculatus, a high-value aquaculture species, is sensitive to fluctuations in environmental salinity-a challenge that has emerged as a critical bottleneck limiting its large-scale commercial cultivation. However, no systematic investigation has been conducted to characterize the HSP70 superfamily in S. monotuberculatus and elucidate its functional roles in salinity adaptation. In the present study, we performed a comprehensive genome-wide scan and identified 19 HSP70 superfamily genes in the S. monotuberculatus genome, with the HSP70IV subfamily showing remarkable gene expansion, containing 8 distinct copies. Phylogenetic analysis, conserved motif identification, and gene structure characterization demonstrated high evolutionary conservation within each HSP subfamily. These genes were unevenly distributed across the chromosomes of S. monotuberculatus, and prediction of cis-acting elements revealed that their upstream regulatory regions were enriched with numerous functional elements associated with stress response and immune regulation. Salinity stress experiments revealed that under severe low-salinity conditions (18&#x2030;), the expression levels of SmHSPA14L and multiple HSP70IV subfamily members were significantly elevated, while SmHYOU1D was significantly downregulated; in contrast, only subtle changes were detected in the expression of most HSP70 genes under moderate low-salinity stress (24&#x2030;). These findings strongly suggest that HSP70 genes, particularly the expanded HSP70IV subfamily, may act as key modulators in the low-salinity stress response. This work provides valuable insight into the molecular mechanisms underlying salinity adaptation in tropical sea cucumbers.

Animals

A multi-scale fusion model based on multi-phase contrast-enhanced CT for predicting pancreatic cancer resectability.

Purpose.Develop a multi-scale fusion model (MSFM) based on multi-phase contrast-enhanced computed tomography (CECT) to predict pancreatic cancer (PC) resectability, thereby assisting expert decision-making.Methods.This retrospective study enrolled 280 patients with PC from four institutions, which were randomly divided into a training cohort (202 patients) and an independent test cohort (78 patients). Three-phase CECT images (arterial, venous, and delayed phases) were used for modeling. The MSFM comprises two sub-networks: (1) a multi-phase fusion network for extracting cross-phase shared fusion features, (2) a phase-specific branch network for capturing phase-specific features; and a post-fusion strategy to generate the final predictive score by integrating the shared fusion features and three groups of phase-specific features. Additionally, a human-machine fusion deep learning model (HMfDL) was constructed by fusing the predictive score of the MSFM with expert assessments.Results.In the independent test, the MSFM achieved an AUC (area under the receiver operating characteristic curve) of 0.8385 (95% CI: 0.7521-0.9249), accuracy of 84.62%, sensitivity of 72.00%, and specificity of 90.57%. This performance outperformed single-phase models (AUC range: 0.7638-0.7781), two-phase models (AUC range: 0.7826-0.7864), and ten states-of-the-art classifiers (AUC range: 0.7404-0.7796). The HMfDL further improved the performance, reaching an AUC of 0.8626 (95% CI: 0.7853-0.9400), accuracy of 91.03%, sensitivity of 80.00%, and specificity of 96.23%. Notably, the HMfDL corrected 58.82% of misdiagnosis made by experts.Conclusions. The MSFM effectively fuses multi-phase CECT to enable highly accurate predictions of PC resectability, and provides valuable support for expert decision-making through HMfDL.

Humans

The composition of the periostracum in the razor clam Sinonovacula constricta and the mantle's response to sulfide.

The razor clam Sinonovacula constricta inhabits sulfide-rich intertidal sediments and exhibits remarkable tolerance to this toxicant, yet the role of its periostracum in sulfide adaptation remains poorly understood. In this study, we investigated the composition and structure of the periostracum proteins, and the response of the mantle to sulfide stress. Scanning electron microscopy and energy-dispersive X-ray spectroscopy revealed that the periostracum is approximately 10&#xa0;&#x3bc;m thick and contains 1.43&#xa0;wt% sulfur, and proteomic analysis further confirmed the presence of organic sulfur (Cys/Met-rich proteins), suggesting its involvement in sulfur deposition. Using LC-MS/MS, we identified 77 high-confidence proteins from the periostracum, which were classified into six functional categories: enzymes, framework proteins, immune-related proteins, calcium ion-related proteins, other proteins, and proteins with unknown functions. Phylogenetic analyses of representative proteins revealed bivalve-specific evolutionary patterns, with several proteins exclusively present in Bivalvia, such as Unknown protein 2 and 7, which possess signal peptides and low-complexity domains. For the sulfide exposure experiment, razor clams were subjected to three Na2S concentrations (0, 10, and 100&#xa0;&#x3bc;M). qPCR analysis showed that, compared with the control group, Chitin-binding protein 3 and Tyrosinase were significantly upregulated in the mantle, peaking in the 100&#xa0;&#x3bc;M group at 48&#xa0;h (5677.84-fold and 157.20-fold, respectively), whereas Collagen and Cadherin 3 were generally suppressed. This study represents one of the most comprehensive proteomic profiles of the razor clam periostracum and highlights the mantle's potential role in sulfide tolerance, offering insights for sulfur-tolerant aquaculture breeding and bioremediation applications.

Animals

Comparative transcriptome analysis reveals ncRNA-mediated regulatory networks associated with muscle crispiness in grass carp.

Non-coding RNAs (ncRNAs) have been demonstrated to be involved in muscle development and to function as key regulators. However, the molecular mechanism underlying muscle crispiness in grass carp (GC) remains poorly understood, and whether these ncRNAs are involved in its regulation is still unknown. In the current investigation, differentially expressed (DE) RNAs (including lncRNAs, circRNAs, miRNAs, and mRNAs) were identified; concomitantly, target genes prediction was conducted, and functional and signaling pathway enrichment analyses were performed. Pathways related to muscle crispiness were identified, and the competitive endogenous RNA (ceRNA) (lncRNA/circRNA-miRNA-mRNA) regulatory network was further constructed. The results showed that a total of 126 DE-lncRNAs, 17 DE-circRNAs, 329 DE-miRNAs, and 442 DE-mRNAs were identified in muscle tissues of both the GC and crisp grass carp (CGC). GO and KEGG enrichment analyses revealed that target genes of DE-ncRNAs were significantly enriched in signaling pathways, including structural constituents of muscle, apoptosis, oxidative phosphorylation, and regulation of actin cytoskeleton, suggesting that these pathways may be involved in muscle texture remodeling. Subsequently, DE-RNAs enriched in related pathways were identified, and a core ceRNA regulation network comprising 3 lncRNAs, 4 circRNAs, 3 miRNAs, and 17 mRNAs was constructed. Additionally, 10 DE-RNAs from randomly selected groups were validated by qRT-PCR. Our findings not only provide scientific evidence elucidating the molecular mechanisms underlying muscle crispiness in GC but also establish a foundation for studying changes in muscle textural qualities across other fish species.

Animals

ReMeDy: A Flexible Statistical Framework for Region-Based Detection of DNA Methylation Dysregulation.

Region-based epigenome-wide association studies have demonstrated improved statistical power and biological interpretability compared with probe-wise analyses of DNA methylation data. However, most existing region-based methods characterize methylation dysregulation primarily through changes in mean methylation levels associated with a phenotype of interest. Substantial evidence indicates that phenotype-associated methylation alterations may also manifest through changes in methylation variability or through joint shifts in mean and variability. Despite this, no existing statistical framework jointly models mean-variance methylation changes in a region-based manner. We propose ReMeDy, a flexible statistical framework that uses a hierarchical likelihood approach within a generalized linear model setting to identify differentially methylated regions, variably methylated regions, and regions exhibiting joint differential and variable methylation at a genome-wide scale. Unlike existing models, ReMeDy operates directly on biologically defined co-methylated regions, allowing it to naturally capture spatial correlation inherent in DNA methylation array data, while avoiding reliance on heuristic, user-defined tuning parameters such as smoothing spans and kernel bandwidths that can substantially influence results and introduce subjectivity. Through extensive simulation studies and comprehensive benchmarking against popular models, we demonstrate that ReMeDy maintains false discovery and Type-I error rates at nominal levels while achieving consistently higher statistical power across a wide range of realistic scenarios. Application to population-level DNA methylation data further shows that ReMeDy identifies biologically meaningful regions and pathways implicated in complex human diseases that are not captured by conventional mean-based analyses alone. ReMeDy is implemented as an open-source R package and is freely available at https://github.com/SChatLab/ReMeDy.

DNA Methylation

Systematic review of machine learning approaches for predicting sickle cell crisis and mortality risk at the climate-health nexus.

BACKGROUND: Sickle cell anemia (SCA) is a severe genetic blood disorder characterized by recurrent vaso-occlusive crises and increased mortality, with the greatest burden occurring in low- and middle-income countries. Climatic and environmental conditions, including temperature variability, humidity, rainfall, air pollution, and seasonal changes, have been associated with disease exacerbation. However, the extent to which these factors have been incorporated into predictive models remains unclear. This study systematically reviews the application of machine learning (ML) models for predicting SCA crises and mortality in relation to climate and environmental factors. METHODOLOGY: The PRISMA guidelines were used, and 34 peer-reviewed studies published between 2005 and 2026 were analyzed to identify the climate variables, ML approaches employed, and predictive performance. The reviewed studies applied a range of ML techniques, including artificial neural networks, random forests, support vector machines, decision trees, logistic regression, and deep learning models. Temperature, humidity, rainfall, wind speed, air quality indicators, and seasonal patterns were the most frequently examined environmental variables. RESULTS: The findings indicate that most existing models rely predominantly on clinical and demographic data, with limited integration of climate information and inadequate representation of high-burden regions, especially Sub-Saharan Africa. Studies incorporating environmental variables reported improved predictive performance and highlighted the potential of climate-informed early warning systems for SCA management. CONCLUSION: The review recommends development of interdisciplinary, climate-aware ML frameworks, expansion of longitudinal environmental datasets, and increased research in underrepresented regions to support climate-resilient and patient-centered SCA care.

Humans

Redefining the real problem in psychedelic trials: Why fighting the Lessebo matters more than blinding integrity.

Imperfect blinding is not specific to psychedelic trials. In randomized trials, treatment allocation is frequently correctly guessed, yet blinding integrity is rarely assessed outside of psychedelic research and is generally not considered a barrier in regulatory evaluation. The intense debate in psychedelics may reflect a broader double standard affecting mental health research, when uncertainties arising from imperfect blinding are confounded by those linked to patient-reported outcome measures. Indeed, people living with mental disorders are often viewed as unreliable reporters, despite well-documented limitations of clinician-rated scales and the absence of robust biological markers of symptomatic change. Importantly, it is the maintenance of reasonable doubt of treatment allocation that sustains internal validity and ethical feasibility of placebo-controlled designs, rather than perfect blinding. Concerns about expectancy bias in psychedelic trials are closely tied to blinding debates. When allocation is inferred, expectations may cluster in the arm perceived as active or in stereotyped experiences and influence outcomes differently in active and control arms, leading to a risk of lessebo, a negative placebo effect due to the negative expectation related to receiving a placebo. However, we argue that an underrecognized mechanism of lessebo is disappointment. This risk may reflect insufficient clinical management of disappointment rather than pre-treatment expectation alone. We therefore propose shifting the emphasis from preserving inevitably imperfect blinding towards mitigating disappointment in both arms. Establishing non-stereotyped expectations prior to treatment through structured psychoeducation, strengthened therapeutic alliance, and realistic preparation would help avoid lessebo effects. Such strategies would enhance ethical rigor, interpretability, and the clinical usefulness of psychedelic trials.

Humans