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A systematic review of macaque brain stimulation: Trends and future directions.

Neurostimulation techniques can powerfully modulate neural circuit activity and provide causal insights into the relationship between brain function and behavior. Macaque monkeys have long been a key animal model for brain stimulation studies. While stimulating the macaque brain with one or a few electrodes has already taught us much about brain function and dysfunction, recent technological advances promise a future with more precise stimulation using many more electrodes. However, such possibilities also increase the number of choices an experimenter has when designing their study. We can learn from a rich past, but a comprehensive overview of which brain regions have been studied and with what stimulation parameters is lacking. Here, we present a PRISMA-compliant systematic review of 734 macaque brain stimulation studies using electrical and/or optogenetic stimulation. We find a striking bias in which brain areas have traditionally been stimulated: a mere 10 brain regions account for half of all studies, with the remainder of studies investigating approximately 150 other areas. Across studies, stimulation frequency robustly predicted direct behavioral effects independent of brain region, while amplitude did not. Future studies could more systematically explore less studied regions through lower stimulation frequencies (e.g., 20-50 Hz) alongside established ranges (∼200 Hz). Tools such as fMRI or optical imaging can capture neural circuit engagement evoked by these frequencies, even when behavioral effects are absent or remain subtle. Our synthesis offers a guide towards the next steps in high-channel-count, high-precision stimulation approaches.

Animals

Complement component C4 and neuroimaging in psychiatry: A systematic review.

INTRODUCTION: Genomic, transcriptomic, and proteomic studies suggest that the complement system contributes to the pathophysiology of various psychiatric disorders partly through neurodevelopmental effects linked to C4A protein levels variations. We conducted a systematic review to characterize how brain micro- and macrostructure and connectivity vary with proxies of in vivo brain C4A protein levels in both psychiatric and general-population cohorts. METHODS: We used Medline, Web of Science, and Embase, and included all studies published before April 14, 2025. Inclusion criteria were: (1) inclusion of healthy controls and/or individuals with psychiatric disorders assessed according to recognized diagnostic manuals (DSM or ICD); (2) use of MRI-based neuroimaging; and (3) use of genomic, transcriptomic and/or proteomic approaches as proxies of in vivo brain C4A proteins levels. RESULTS: From 317 identified articles, 11 were included. Associations between C4A levels and brain structure were heterogeneous across regions. Only the mOFC, dlPFC, and entorhinal cortex were implicated in more than one study. Findings for the mOFC and dlPFC varied by the type of metrics and clinical status, whereas higher C4A levels were more consistently associated with smaller entorhinal cortex surface area and cortical thickness in pediatric, middle-aged, and older general-population cohorts. In addition, one study found higher genetically predicted C4A expression to be associated with higher TSPO levels. CONCLUSION: The limited number of available studies and their methodological heterogeneity make synthesis challenging. However, biological hypotheses such as excessive synaptic pruning or broader inflammatory effects on the brain may provide plausible explanatory frameworks for the reported associations.

Humans

The global potential of freshwater microbes for plastic degradation.

Plastic pollution is becoming increasingly severe on a global scale, and the potential for biodegradation as a treatment method that is environmentally friendly merits greater attention. A significant number of genes that associated the degradation of plastic (PDAGs) have been identified, however, the distribution of these genes among microorganisms in global inland waters remains to be elucidated. A global-scale meta-analysis was conducted, incorporating approximately 1000 metagenome datasets of inland waters across seven continents. A total of 13,109 metagenome-assembled genomes (MAGs) were obtained by means of metagenomics binning, and 22,621 PDAGs were identified from these. Among these recognized PDAGs, phenylacetaldehyde dehydrogenase (PAD) was the most dominant (n = 16,664), followed by catalase (n = 5931). The predominant hosts for PAD and catalase were identified as Gamma-proteobacteria and Bacteroidia, respectively. The largest number of both PAD and catalase was found in MAGs from North America, while the average gene number in single MAG was highest in MAGs from Oceania. In accordance with the prediction of traits, PDAG-carrying MAGs from Europe demonstrated the fastest growth rate and the lowest optimal growth rate. Furthermore, 25 styrene monooxygenase (StyA) enzymes were identified, which were found to cluster into two distinct groups hosted by Alpha-proteobacteria and Gamma-proteobacteria, respectively. Moreover, 11 MAGs were observed to possess the complete pathway of polystyrene degradation. These results explored the potential of inland water microorganisms as a biological resource for plastic degradation and provided valuable microbial reference information that can be used to develop biological treatment technologies for mitigating plastics.

Plastics

Prevalence and cardiometabolic impact of mild autonomous cortisol secretion in primary aldosteronism: a systematic review and meta-analysis.

Many primary aldosteronism (PA) patients harbor concomitant mild autonomous cortisol secretion (MACS), termed "Connshing syndrome." The prevalence and cardiometabolic impact of this co-secretion have not been quantitatively synthesized. To determine the pooled prevalence of MACS in PA and evaluate its association with cardiovascular (CV) events, type 2 diabetes mellitus (T2DM), and obesity. PubMed, Embase, Cochrane, Web of Science, and Scopus through January 2026. Following PRISMA 2020 and MOOSE guidelines (PROSPERO: CRD420261334965), studies reporting MACS prevalence [post-1 mg dexamethasone suppression test (DST) cortisol ≥1.8 μg/dl] in PA were included. Prevalence was pooled using random-effects models. Odds ratios (ORs) were calculated for cardiometabolic outcomes. Certainty was evaluated using GRADE. Fourteen studies (2356 patients) were included. Pooled MACS prevalence was 26.2% [95% confidence interval (CI): 24.1-28.4; I2 = 24.2%; prediction interval: 21.6-31.4%], consistent across European (27.0%) and East Asian (25.2%) cohorts ( P = 0.62). MACS + PA patients had higher odds of CV events (OR 1.60; 95% CI: 1.07-2.38; P = 0.021) and T2DM (OR 1.37; 95% CI: 1.00-1.86; P = 0.048), but not obesity (OR 1.10; P = 0.411). Sensitivity analyses confirmed robustness. GRADE certainty was moderate for prevalence and low for CV events. Approximately one in four PA patients has MACS, associated with a 60% higher CV event risk. These findings support routine DST screening in PA and have implications for perioperative management and cardiometabolic risk stratification.

Humans

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

Longitudinal whole-genome analysis of bluetongue virus identifies conserved serotype-specific genomes and distinct genomic constellations within a Colorado sheep flock (2021-2023).

Bluetongue virus (BTV) is a segmented double-stranded RNA virus of ruminants transmitted by Culicoides spp. biting midges. Although the genome consists of ten segments, classification into serotypes is primarily based on genome segment 2. However, reassortment among genomic segments is a major driver of BTV evolution and diversity. This study used longitudinal whole-genome sequencing to characterize BTV genomes collected from 2021 to 2023 within a single sheep flock in Colorado, where multiple serotypes co-circulate. Whole-genome sequences were generated from fourteen blood samples representing four serotypes: BTV-6, -11, -13, and -17. Longitudinal sampling identified multiple BTV serotypes within individual sheep across consecutive years. Tanglegram analysis comparing segment phylogenies to the segment 2 tree demonstrated incongruent topologies across all genomic segments, suggestive of reassortment or the circulation of distinct genomic constellations. Nucleotide-level comparisons revealed high sequence homology among same-serotype samples from the same year, while the greatest genetic divergence was observed among BTV-17 genomes collected in different years. Additionally, all BTV-13 genomes contained a previously undescribed nonsynonymous substitution in segment 10 predicted to extend the encoded protein by three amino acids. Together, these findings demonstrate that highly conserved BTV genomes and distinct genomic constellations can be detected at the flock level across multiple years. This longitudinal whole-genome approach reveals the genetic complexity of endemic BTV populations, including novel variants and genomic patterns consistent with reassortment that are lost with conventional serotyped-based approaches, highlighting the need to integrate whole-genome characterization into endemic BTV monitoring programs.

Animals

GSTT1 promotes stemness and FGFR inhibitor sensitivity in pancreatic cancer through regulation of CD133 (PROM1).

Pancreatic ductal adenocarcinoma (PDA) is among the deadliest malignancies, driven by metastatic progression and profound cellular heterogeneity. We previously identified glutathione S-transferase theta 1 (GSTT1) as a regulator of a slow-cycling, highly metastatic tumor cell population, suggesting that GSTT1High cells may possess stem-like properties. Here, we define the functional and molecular features of this subpopulation in metastatic PDA. Using a mCherry-tagged Gstt1 reporter system in metastatic murine PDAC cells, we enriched for Gstt1High cells and observed increased tumor sphere formation, accompanied by upregulation of stemness-associated genes including PROM1 (CD133) and activation of Wnt and FGF signaling pathways. In human PDA models, CD133HighGSTT1High cells exhibited enhanced tumor sphere initiation and expansion compared to other populations, defining a maximal stem-like state. Notably, sensitivity to FGFR inhibitors was observed only under tumor sphere conditions, highlighting a context-dependent therapeutic vulnerability. Mechanistically, FGFR3 expression correlated with GSTT1 and CD133 levels, and FGF signaling was required to sustain this state. GSTT1 knockdown reduced CD133 protein levels, impaired tumor sphere formation, and altered sensitivity to FGFR inhibition. These findings were largely recapitulated in patient-derived PDA organoids, where GSTT1 and PROM1 co-expression predicted increased tumor sphere formation and enhanced response to the multi-kinase inhibitor Nintedanib. Together, these results identify a GSTT1HighCD133High stem-like subpopulation in metastatic PDA and identify an FGFR-dependent signaling axis that sustains this state, representing a potential therapeutic vulnerability.

AC133 Antigen

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

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

Multiomics

Mindfulness and Sex Education for Sexual Dysfunction in Breast Cancer Survivors: Mediators and Moderators of Treatment Outcome.

Mindfulness-based cognitive therapy (MBCT) and supportive-expressive sex education therapy (STEP) are effective group treatments for sexual dysfunction after breast cancer (BrCa). We explored mediators and moderators of outcomes following the 8-week groups. BrCa survivors (n = 116, mean age = 49.9 ± 9.5) were randomized to group and completed measures before, immediately after, and 6 months after treatment. Mediators assessed were changes in depression, chronic pain acceptance, pain catastrophizing, and trait mindfulness. Potential moderators included age, treatment expectations, baseline mental health, cancer treatment duration, use of chemotherapy, and adjuvant endocrine therapy. Longitudinal mediation and moderation were assessed using linear mixed models. Increases in pain acceptance mediated improvements in sexual desire and reductions in both sexual distress and vaginal pain. Decreases in pain catastrophizing mediated improvements in sexual distress. Higher expectations for treatment led to greater reductions in sexual distress. Those with low baseline anxiety showed greater improvements in desire and distress. Low baseline depression predicted greater improvements in desire, but only in the STEP arm. Older STEP participants improved significantly more than younger STEP participants. Cancer-related treatment variables, and the impact of adjuvant endocrine therapy, had differential effects on outcomes based on the treatment arm of the study. In conclusion, treatments aimed at improving pain acceptance and pain catastrophizing are likely to promote improvements in sexual health among BrCa survivors, and factoring in patients' expectations about treatment improvements, depression and anxiety, age, duration of cancer treatment, chemotherapy, and adjuvant hormonal therapy may help to guide treatment recommendations for sexual dysfunction.

Humans

Integrated photoelectrocatalytic reduction and oxidation processes to achieve efficient degradation of fluoxetine in pharmaceutical wastewater.

Fluorinated organic compounds have been frequently detected in aquatic environments, with the widespread use of fluorinated drugs. The existing processes of urban sewage treatment plants are difficult to completely remove these pollutants containing the persistent C-F bonds. In this work, an integrated system of UV-activated sulfite and UV-assisted electrochemical oxidation was innovatively constructed for efficient degradation of fluoxetine. For the UV-activated sulfite unit system, when the sulfite dosage was 0.5 mmol/L and the initial pH was about 10, the defluorination efficiency of 5 mg/L fluoxetine wastewater under nitrogen atmosphere was about 98 %. Subsequently, the UV-assisted electrochemical oxidation unit system was employed to treat the reduced wastewater mentioned above. When the sodium chloride dosage was 25 mmol/L, the initial pH was about 5, and the current density was 30 mA/cm2, the total organic carbon (TOC) removal of the wastewater arrived at 65 %. Active species capture experiments and ESR tests confirmed that hydrated electrons, hydroxyl, and chlorine radicals were the main components for the efficient degradation of fluoxetine. According to the analysis of Fukui function and HPLC-MS, the degradation pathway of pollutants was proposed including defluorination and mineralization. Meanwhile, the toxicity of intermediates was predicted using the ECOSAR program. In addition, the verification test of actual wastewater treatment indicated that the defluorination and TOC removal efficiency of fluorouracil by the integrated system were similar to those for fluoxetine. This work provided a new approach for the efficient degradation of fluorinated organic pollutants in pharmaceutical wastewater.

Fluoxetine

Symptom assessment and health-related quality of life in children with lower urinary tract dysfunction: A retrospective cross-sectional study.

INTRODUCTION: Lower urinary tract dysfunction (LUTD) significantly impacts children's health-related quality of life (HRQoL), but key determinants of this impairment remain incompletely understood within a patient-centered framework. METHODS: This retrospective cross-sectional study enrolled 272 children with LUTD. Clinical symptoms were assessed using the Dysfunctional Voiding Scoring System (DVSS) and the Overactive Bladder Symptom Score (OABSS), and HRQoL via the Pediatric Quality of Life Inventory (PedsQL&#x2122;) 4.0 Generic Core Scales. RESULTS: The mean total PedsQL score was 83.66 &#xb1; 16.07, with the School Functioning domain being the most impaired (73.75 &#xb1; 20.94). Univariate analysis identified older age (&#x2265;11 years), daytime urinary leakage, overactive bladder (OAB) symptoms, and abnormal DVSS scores as factors associated with reduced HRQoL (all P < 0.05); multivariate regression further confirmed only older age and abnormal DVSS were independent influencing factors (both P < 0.001). A significant negative correlation existed between the total DVSS score and the total PedsQL score (r = -0.390, P < 0.01), indicating that greater symptom severity predicts poorer overall HRQoL. CONCLUSION: This study indicates that in children with LUTD, the severity of voiding dysfunction (quantified by DVSS) is inversely correlated with HRQoL. Voiding dysfunction impairs multiple domains of daily functioning, including physical well-being, emotional adjustment, social interaction, and school performance. Shifting from a symptom-focused to a patient-centered care model and integrating routine HRQoL assessment into standard clinical management can optimize clinical practice for pediatric LUTD.

Humans

Influence of soil types with different soil-forming process on the qualitative and quantitative detection of microplastics by near-infrared spectroscopy.

Microplastics (MPs) have become a pressing global environmental threat, with soils-acting as sinks for MPs from multiple sources-gaining increasing attention. Near-infrared (NIR) spectroscopy offers a promising tool for MPs detection due to its rapid, non-destructive, and field-applicable features. Although previous studies have focused on the effects of individual soil components on the NIR detection performance of MPs, there is still a lack of systematic research on how the complex background-formed by the coupling of multiple physicochemical properties in natural soils-affects detection performance. This study focuses on soil types with different soil-forming processes, selected five representative agricultural soils to systematically evaluate how the combinations of physicochemical properties they represented affect the performance of NIR-based qualitative and quantitative analysis of MPs in soils. The results demonstrated that soil type significantly affected both the spectral response and detection performance of MPs. Brown Pedocals and Brown Earth exhibited clearer characteristic absorption and stronger linear responses, achieving higher identification accuracy under low (<1.5 %) or zero MPs concentrations and the best quantitative performance (R2 &#x2265; 0.988, prediction set root mean square error (RMSEP) &#x2264; 0.110 %). In contrast, Phaeozem and Red Soil were more prone to misclassification at low concentrations, while Fluvo-aquic Soil showed the poorest quantitative performance. This study is the first to reveal, at a holistic level, the critical constraints posed by natural soil complexity on the NIR detection of MPs, offering targeted empirical evidence to support the application of NIR technology in real-world soil environments.

Soil

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

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

[Analysis of clinical phenotypes and pathogenicity of a c.4476+5G>T variant of SCN1A gene in a Chinese pedigree affected with Genetic epilepsy with febrile seizures plus].

OBJECTIVE: To explore the pathogenicity and characteristics of a heterozygous splicing variant of SCN1A gene in a Chinese pedigree affected with Genetic epilepsy with febrile seizures plus (GEFS+). METHODS: A retrospective analysis was carried out on the clinical data and results of genetic testing of a GEFS+ pedigree consisting of 5 members who had visited the First Affiliated Hospital of Zhengzhou University on July 1, 2024. Pathogenicity of the splicing variant of the SCN1A gene was validated with a minigene splicing assay. This study was approved by the Medical Ethics Committee of the the First Affiliated Hospital of Zhengzhou University (Ethics No.: KS-2018-KY-36). RESULTS: The proband, a 24-year-old female, presented with FS in conjunct with focal seizures, and both of her younger brothers had Dravet syndrome. All of the three patients had carried a c.4476+5G>T variant of the SCN1A gene, which was unreported previously. Minigene experiment verified that the variant could cause loss of the first 7 bps of exon 24 and 138 bps from exon 23 of the SCN1A gene, resulting in alteration p.V1447_1495delfs*6 and affecting splicing. Based on the guidelines from American College of Medical Genetics and Genomics (ACMG), the variant was predicted as likely pathogenic (PVS1+PM2_Supporting). CONCLUSION: The c.4476+5G>T variant at an intronic site of the SCN1A gene probably underlay the pathogenesis of GEFS+ in this pedigree.

Adult

Fungal drivers of mycotoxin contamination in wheat: Early warning and plasma-based control.

Mycotoxin contamination in wheat is a major food safety concern; however, quantitative evidence linking fungal community signals, mycotoxin exceedance risk, and wheat quality traits in naturally contaminated wheat remains limited. In this study, wheat samples were collected from mycotoxin-prone monitoring sites under unusually rainy conditions in 2022 to explore early-warning indicators and post-harvest mitigation strategies. According to the National Food Safety Standard of China GB 2761-2017, aflatoxin B1 (AFB1), deoxynivalenol (DON), and zearalenone (ZEN) exceeded the maximum limits in 52.24, 47.76, and 23.88% of samples, respectively; 38.81% exceeded the reference EU threshold for T-2 toxin, and 46.27% showed co-contamination with at least two mycotoxins above their respective thresholds. Although Alternaria, Cladosporium, and Epicoccum dominated the fungal community, Fusarium abundance was significantly associated with DON contamination and Fusarium-damaged kernels (FDKs). Mediation analysis identified DON as a significant mediator linking Fusarium abundance to FDKs, accounting for 68.41% of the total effect. In addition, Fusarium abundance above 3.70% showed strong predictive performance for DON exceedance, with an area under the curve of 0.906, indicating its potential as an early-warning indicator. Culture-based assays confirmed the toxigenic potential of Aspergillus and Fusarium isolates under simulated temperature and moisture conditions. After optimization using a toxin-spiked wheat flour model, dielectric barrier discharge cold plasma degraded AFB1, DON, and ZEN by 29.30-35.68%, disrupted the morphology of toxigenic fungi, and did not significantly affect wheat quality. This study provides practical insights into mycotoxin risk warning and post-harvest mitigation in wheat.

Triticum

Symptom Networks and Core Symptoms in Patients with Solid Tumors Undergoing Chemotherapy: A Systematic Review.

OBJECTIVES: To summarize symptom network characteristics in patients with solid tumors undergoing chemotherapy and synthesize evidence on core symptoms, bridge symptoms, and temporal associations. METHODS: We systematically searched eight databases through October 2025 to identify studies that applied symptom network analysis to adults with solid tumors receiving chemotherapy. Eligible studies assessed symptoms using cross-sectional, longitudinal, or interventional designs. Two reviewers independently screened articles and extracted data on study characteristics, symptom assessment, and network outcomes. Methodological quality was assessed using the National Institutes of Health Study Quality Assessment Tool. RESULTS: Twenty-seven studies involving 13,452 participants were included, yielding 79 symptom networks. Fatigue was the most frequently identified core symptom (10/20, 50%), whereas sadness, lack of appetite, and nausea each occurred in 10% of studies, with variation across cancer types, treatment phases, and latent classes. Bridge symptoms included disturbed sleep, lack of appetite, and dry mouth (2/7, 28.6%). Studies evaluating temporal associations found that symptoms such as sadness, dyspnea, somnolence, and dry mouth predicted subsequent changes in appetite, distress, nausea, and other outcomes. Strength metrics showed acceptable stability (correlation stability coefficients: 0.28-0.83). CONCLUSIONS: Fatigue was frequently identified as a central symptom across studies, largely reflecting evidence from breast cancer studies. Core symptoms varied across cancer types, treatment phases, and latent classes, suggesting heterogeneity. IMPLICATIONS FOR NURSING PRACTICE: These findings highlight the importance of considering relationships among symptoms in clinical care. Focusing on key symptoms such as fatigue, while tailoring management strategies to cancer-specific symptom patterns, may support more effective symptom management.

Humans

A systematic review and meta-analysis to estimate the global prevalence of leptospirosis in sheep.

Leptospirosis in sheep is a zoonotic concern considering sheep may act as potential reservoirs for Leptospira spp. infection to humans. This study aimed to estimate the pooled prevalence of leptospirosis in sheep worldwide. A comprehensive literature search was conducted across databases following PRISMA guidelines. Meta-analyses were performed using a random effect model in R software (version 4.3.1) to calculate pooled prevalence with 95% confidence intervals (CI). Subgroup analyses were performed based on prevalence types, diagnostic methods and continental regions to explore sources of heterogeneity. A total of 138 studies comprising 54,174 samples and 10,299 positive detections were included in this study. The global pooled prevalence of leptospirosis in sheep was 15.69% (95% CI: 12.69-19.25) with overall heterogeneity (I2) 98%. The prediction interval ranged from 1.09% to 75.91%, indicating wide inter-study variability. The seroprevalence was 16.16% (95% CI: 12.91-20.04) and infection prevalence was 12.98% (95% CI: 8.07-20.22), showing no significant difference (P&#xa0;=&#xa0;0.40). In addition, the prevalence of leptospirosis in sheep differed significantly across diagnostic methods and continents (P&#xa0;<&#xa0;0.01), indicating substantial variation influenced by both methodological and geographical factors. The funnel plot revealed marked asymmetry, suggesting potential publication bias which was confirmed by Egger's regression test (P&#xa0;<&#xa0;0.01). In conclusion, leptospirosis is widely prevalent in sheep globally, with marked geographical and methodological heterogeneity. These findings highlight the epidemiological importance of sheep in leptospirosis transmission and underscore the need for improved surveillance, standardized diagnostic approaches, and targeted control strategies within a One Health framework.

Animals