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PubMed2025

Improving Community-Based Care for Adolescents with ADHD: a Randomized Controlled Trial of Artificial Intelligence-Assisted Fidelity Supports.

Cognitive-behavioral treatments (CBTs) for adolescents with ADHD demonstrate promise of long-term effects on outcome. However, their implementation in routine care community clinics faces barriers that impact quantity, efficiency, and quality of delivery, as well as client outcomes. This study is a randomized controlled trial designed to evaluate the impact of an AI-assisted service delivery model on therapist implementation of Supporting Teens' Autonomy Daily (STAND), a CBT blended with Motivational Interviewing (MI) for adolescents with ADHD. Adolescents with ADHD (N = 51), who were clients at three community mental health agencies, received treatment from 23 therapists. There was randomization of adolescents and therapists to AI-assisted or standard implementation supports. In addition to standard supports (i.e., training, standard facilitation resources, technical assistance, case supervision), AI-assisted support package included digitized facilitation resources housed in a clinical dashboard (Care4), feedback on content fidelity, and AI-generated feedback on MI implementation quality. The AI-assisted group was associated with more efficient treatment delivery and lower number of appointments attended by the adolescent. There was also a significant decrement in MI quality over time in the AI-assisted group compared to the standard support group. Feedback in focus groups indicated that therapists perceived a task-oriented mindset to be associated with receipt of the AI-assisted support package, leading therapists to prioritize efficiency over relational aspects of therapy. Following the results of this trial, a future, larger RCT should examine the impact of the AI-assisted implementation model on mental health outcomes and cost savings to organizations, third party payers, and clients. Trial registration number: NCT05135065; https://www.clinicaltrials.gov ; Registered September 2021.

Humans↗

PubMed2026

What's the meta now? More updates on the problems with systematic reviews.

BACKGROUND: Systematic reviews are intended to provide trustworthy evidence synthesis, yet previous iterations of this living review have identified numerous recurring problems in their conduct and reporting. This article presents the third version and second update of the living systematic review examining issues raised across the academic literature. METHODS: Using consistent eligibility criteria and methods from earlier versions, literature searches were updated to May 2025. Eligible meta-research and editorial articles describing problems with systematic reviews were analyzed to identify emerging themes. Additionally, four basic indicators of methodological quality of the included meta-research were presented across review versions. RESULTS: The update included 209 additional articles. Critically low methodological quality and absence of protocols remained among the most frequently reported issues in systematic reviews across disciplines and journals but notably in evidence underpinning clinical practice guidelines. Spin in abstracts and conflicts of interest continued to be common. Apparent improvements in reporting quality were inconsistent, with modest gains in some full-text reporting but persistent deficiencies in abstracts. Authorship diversity of systematic reviews improved in gender representation but remained geographically concentrated in high-income countries, and primary research included in reviews similarly lacked global representativeness. The issue of misalignment between systematic review evidence bases and global burden of disease bring the total number of problems with systematic reviews to 69. Emerging use of automation and artificial intelligence was variably reported. Descriptive comparison of meta-research articles over the three versions of this living review suggests a greater proportion meeting basic quality indicators in more recent updates. CONCLUSION: Across successive updates, problems with systematic reviews remain widespread and consistent rather than isolated. Incremental reporting improvements coexist with persistent concerns about transparency, bias, and representativeness. Future efforts should prioritize evaluating interventions and aligning research incentives to support genuinely trustworthy evidence synthesis.

Humans↗

PubMed2026

Regional genomic analysis of lineage distribution and transferable multidrug resistance among chicken-associated Salmonella Kentucky isolates in China.

Salmonella enterica serovar Kentucky is an important multidrug-resistant foodborne pathogen in the poultry meat supply chain. Although recent broader genomic studies have elucidated the population structure and epidemiological significance of major lineages in China (e.g., ST198 and ST314), the regional dynamics within local poultry supply chains remain insufficiently characterized. In this study, 31 chicken meat-derived isolates from Shanghai and 39 publicly available genomes from China were analyzed using antimicrobial susceptibility testing, whole-genome sequencing, phylogenetic analysis, conjugation experiments, and complete sequencing of representative plasmids. This enabled a systematic characterization of the molecular epidemiological features of the population and the mechanisms underlying resistance dissemination. Population genomic analysis revealed a lineage composition markedly different from the global epidemiological pattern: ST314 was the predominant sequence type among the Shanghai chicken-derived isolates (74.2%), whereas the internationally recognized high-risk clone ST198 accounted for only 25.8% of the local isolates. However, risk stratification analysis indicated that although ST198 was detected less frequently, it carried a significantly greater burden of acquired resistance genes and therefore represented a higher-risk resistant lineage. Functional and structural validation further elucidated the molecular basis of resistance dissemination within this high-risk lineage. Conjugation experiments confirmed the co-transfer of a multidrug resistance module carrying blaTEM-1 and blaCTX-M-267 to the recipient strain Escherichia coli J53. Complete plasmid analysis revealed that these two β-lactam resistance genes were co-localized on a 242-kb transferable plasmid flanked by Tn1331, Tn3, and multiple transposase-associated elements, thereby providing a structural basis for their horizontal transfer. This study provides important molecular epidemiological evidence for lineage-specific surveillance and risk-stratified control of resistant Salmonella in the poultry meat supply chain and further underscores the need for continuous monitoring of mobile genetic elements within a One Health framework.

Animals↗

PubMed2026

Mechanisms of Hematopoietic Stem Cell Aging and Emerging Rejuvenation Strategies.

Hematopoietic stem cell (HSCs) aging is a complex biological process driven by both cell-intrinsic alterations and extrinsic cues from the bone marrow niche. Understanding these mechanisms is critical for developing therapies against aging-related hematopoietic disorders. This review synthesizes recent advances in the molecular mechanisms underlying HSCs aging, including microenvironmental aging, genomic instability, epigenetic dysregulation, mitochondrial dysfunction, and aberrant nuclear mechanotransduction. We summarize that the functional decline of HSCs during aging drives a compensatory expansion of the phenotypically defined stem cell pool, leading to an aberrant increase in cell number. We also highlight aging-associated HSCs heterogeneity, including CD150high and P-selectin-positive subsets that enrich for myeloid-biased or functionally compromised HSCs states while emphasizing that surface phenotype alone may not fully indicate functional rejuvenation. Finally, we discuss emerging rejuvenation strategies-including targeting myeloid-biased HSCs, modulating inflammatory pathways, and implementing epigenetic or metabolic interventions-supported by cutting-edge technologies such as single-cell multi-omics, gene editing, and computational modeling. These approaches hold promise for counteracting age-related hematopoietic decline and restoring immune competence.

Humans↗

PubMed2026

SGLF-Net:Staged Global-to-Local Cross-Scale Fusion Network for Colonoscopic Polyp Segmentation.

Polyp segmentation in colonoscopy images plays a pivotal role in computer-aided medical diagnosis and the early prevention of colorectal cancer. However, existing methods often suffer from performance degradation when confronted with extreme polyp scale variation and polyp boundary ambiguity. To address these challenges, we propose the Staged Global-to-Local Cross-Scale Fusion Network (SGLF-Net), which adopts a novel staged global-to-local learning paradigm to progressively refine segmentation from coarse global semantics to fine-grained local details. Specifically, the Global Semantic Perception Stage integrates a Swin Transformer Encoder and a Dynamic Attentive Decoder (DAD) to construct comprehensive multi-scale contextual representations. The Local Detail Refinement Stage employs an Edge-aware Dynamic Attentive Decoder (E-DAD) to enhance structural fidelity and boundary precision through explicit edge-guided supervision. Furthermore, we introduce the Cross Spatial-Scale Feature Aggregation and Reconstitution (CSSAR) module, equipped with hybrid attention mechanisms, to facilitate efficient semantic structural interaction between the two cascaded stages. Extensive experiments on five public benchmark datasets demonstrate that SGLF-Net consistently outperforms state-of-the-art methods in both segmentation accuracy and boundary preservation.

Journal Article↗

PubMed2026

Genomic and food-safety evaluation of Staphylococcus chromogenes in Chinese dairy milk.

Non-aureus staphylococci and mammaliicocci (NASM) cause mastitis and may contaminate milk and dairy products. Milk samples (n = 1916) from cows with subclinical or clinical mastitis (SCM and CM, respectively) were collected from 28 large-scale (> 500 lactating cows) Chinese dairy farms. Overall, 999 NASM isolates representing 19 species were identified by MALDI-TOF MS and cpn60 sequencing, with Staphylococcuschromogenes, Mammaliicoccus sciuri and Staphylococcus haemolyticus being most prevalent. Antimicrobial resistance (AMR) was determined with disc diffusion; non-susceptible to penicillin was most common (SCM, 30% and CM, 29%) whereas cefoxitin non-susceptible NASM accounted for 8-10% of isolates; among these, 12.5% carried mecA but none carried mecC. Galleria mellonella was used to assess virulence of 78 strains of S. chromogenes, a dominant species; subsequently, 32 strains, representing higher- and lower-virulence in the Galleria model, were selected for whole-genome sequencing and comparative genomics. S. chromogenes isolates from CM had higher virulence (p < 0.05) than those from SCM. The 32 genomes comprised 20 sequence types, indicating high genetic diversity. No robust genomic marker of Galleria virulence phenotype was identified in this selected WGS subset. Acquired resistance genes (n = 5) were detected, including a first report of fusC in S. chromogenes; the fusC-positive isolate had an elevated fusidic acid MIC (8 mg/L). Although S. chromogenes persisted in milk at 4 °C, pasteurization (64 °C for 30 min) reduced viable counts to below detection. This study provided new insights into the prevalence, AMR, genomic diversity, and dairy-chain relevance of milk-derived NASM, particularly S. chromogenes. However, the genomic findings were based on an intentionally selected WGS subset and should be interpreted as hypothesis-generating rather than population-representative.

Animals↗

PubMed2026

Peripheral pain threshold, glycaemic status, and LAMP3 genetic variation: A community-based analysis.

Diabetic polyneuropathy is a common complication of diabetes, yet substantial inter-individual variation in peripheral pain perception suggests underlying genetic influences. This population-based study investigated clinical, metabolic, and genetic determinants of pain threshold using intraepidermal electrical stimulation in 906 participants from the Iwaki Health Promotion Project 2017. Genome-wide association analysis identified 12 loci showing suggestive associations, among which a missense variant in LAMP3 (rs482912) was prioritized as a biologically plausible candidate. Phenotype-stratified analyses showed that individuals carrying the CT or CC genotypes had lower PINT indices than those with the TT genotype, indicating reduced pain thresholds. Notably, the CC genotype retained an association with lower pain threshold using intraepidermal electrical stimulation under conditions of metabolic stress, including impaired glucose tolerance, elevated HbA1c, and obesity, whereas this association was attenuated in the presence of hypertension. Single-cell RNA sequencing analysis of human skin revealed that LAMP3-positive mature dendritic cells, enriched in immunoregulatory molecules, exhibited transcriptional enrichment of inflammatory, antigen-presenting, and nociception-related pathways, including NF-κB, JAK-STAT, cytokine signaling, and neuroimmune sensitization cascades. Autopsy-based skin analysis further demonstrated genotype-associated differences in dermal LAMP3-positive cell infiltration and CD8-positive T-cell abundance, while CD4-positive T-cell abundance and intraepidermal nerve fiber density remained unchanged across genotypes. Taken together, these findings suggest a potential association between LAMP3 variation and individual differences in peripheral pain threshold and provide biological context supporting a role for neuroimmune interactions in early sensory modulation under metabolic stress. Given the suggestive genetic evidence and indirect mechanistic data, these observations should be interpreted as exploratory and hypothesis-generating.

Humans↗

PubMed2026

Activity of Aztreonam-avibactam and Ceftazidime-Avibactam against Enterobacterales and Pseudomonas aeruginosa causing infections in patients hospitalized in hematology, oncology, and transplant units from United States medical centres (2019-2024).

Immunosuppression increases the risks and severity of infections and is associated with a higher incidence of infection with multidrug-resistant (MDR) pathogens. We evaluated the antimicrobial susceptibility of Enterobacterales and Pseudomonas aeruginosa from patients hospitalized in hospital units where the frequency of immunosuppressed patients is very high. Bacterial isolates were consecutively collected (1/patient) from 75 US medical centres in 2019-2024 and susceptibility tested by broth microdilution. Enterobacterales (n = 2,407) and P. aeruginosa (n = 485) from patients hospitalized in hematology, oncology, and transplant units were evaluated. Carbapenem-resistant Enterobacterales (CRE) were screened for β-lactamases by whole genome sequencing. Enterobacterales were mainly from bloodstream infection (BSI; 53.6%) and urinary tract infection (19.9%) and P. aeruginosa were mainly from BSI (37.9%) and pneumonia (35.0%). Aztreonam-avibactam, ceftazidime-avibactam, and meropenem-vaborbactam were highly active against Enterobacterales (99.9-99.4% susceptible), including MDR isolates (99.6-98.1% susceptible), but only aztreonam-avibactam exhibited good activity against CRE (95.8% susceptible). Ceftolozane-tazobactam showed good activity against Escherichia coli (95.7% S) and Klebsiella pneumoniae (92.8% S), but limited activity against Enterobacter cloacae species complex (75.9% susceptible). All (100.0%) carbapenemase (CBase)-producing CRE isolates were aztreonam-avibactam-susceptible while 77.4% were ceftazidime-avibactam-susceptible and 67.7% were meropenem-vaborbactam-susceptible. The most common CBases were KPC (41.7%), NDM (12.5%), and OXA-48 types (10.4%). Metallo-β-lactamases represented 23.5% of CBases and were identified in 16.7% of CREs. The most active agents against P. aeruginosa were ceftazidime-avibactam (95.7% susceptible), ceftolozane-tazobactam (94.8% susceptible), and tobramycin (91.5% susceptible). Piperacillin-tazobactam and meropenem were active against 81.4% and 82.5% of P. aeruginosa, respectively, and aztreonam-avibactam inhibited 78.6% of P. aeruginosa at ≤8 mg/L.

Humans↗

PubMed2026

Effectiveness and usability of artificial intelligence-powered assistive technologies in Supporting daily activities of children with cerebral palsy: a systematic review.

BACKGROUND: Cerebral Palsy (CP) is the main cause of motor disabilities in childhood, necessitating innovative approaches to rehabilitation and assistive technology (AT). Simultaneously, artificial intelligence (AI) is increasingly being integrated into devices to create more adaptive, personalized, and effective AT. This systematic review aimed to evaluate the effectiveness and usability of AI-powered assistive technologies designed to support daily activities and rehabilitation in children with CP. MATERIALS AND METHODS: Five databases, including Scopus, Web of Science, PubMed, Embase, and IEEE Xplore, were systematically searched, and 23 articles were included in the final analysis. Articles were identified, selected, and categorized into emerging thematic areas based on the primary function and application of the technology. RESULTS: Five key thematic topics were identified: 1) AI-driven motor rehabilitation and gait training for functional mobility; 2) intelligent assessment and monitoring systems for clinical decision support; 3) AI-supported communication, social interaction, and intention recognition tools; 4) gamified and virtual reality-based interventions to enhance engagement and usability; and 5) smart assistive systems supporting daily living and independent mobility. The findings demonstrate a strong trend toward the application of AI technologies in personalized, engaging, and data-driven interventions for children with CP. However, the field is predominantly in the proof-of-concept stage, with limitations including small sample sizes, lack of long-term clinical validation, challenges in user-centered design, and usability for children with CP. CONCLUSION: AI-powered assistive technologies hold significant potential for transforming the care of children with CP by enabling highly personalized and engaging interventions. To actualize this potential, future work must realize that practical application remains challenging owing to limited clinical validation, technological integration, and usability barriers for children with CP. Future research must prioritize user-centered design and multidisciplinary collaboration to ensure that AI and robotic advancements improve the usability and quality of life for children with CP.

Humans↗

PubMed2026

Risk factors and management strategies for needle disengagement from the visual field in pediatric robot-assisted laparoscopic pyeloplasty.

OBJECTIVE: This study aimed to identify risk factors for suture needle disengagement from the visual field during pediatric robot-assisted laparoscopic pyeloplasty (RALP) and propose effective strategies for prevention and management. METHODS: A retrospective cohort study analyzed clinical data from 339 pediatric patients who underwent RALP for ureteropelvic junction obstruction (UPJO) at a single institution between August 2017 and December 2020. Patients were categorized based on the occurrence of needle disengagement from the visual field. Various patient demographics and surgical procedural factors were evaluated. Univariate and multivariate logistic regression, along with LASSO regression, identified independent risk and protective factors. RESULTS: Needle disengagement occurred in 38 (11.21%) of 339 cases. Multivariate logistic regression identified five independent risk factors for needle disengagement: use of a 3-mm auxiliary trocar (OR = 4.69, 95% CI: 1.98-12.53, P < 0.001), non-standard needle holder use (OR = 2.32, 95% CI: 1.04-5.18, P = 0.038), unshaped suture needles (OR = 3.16, 95% CI: 1.44-7.19, P = 0.005), simultaneous use of ≥2 intra-abdominal sutures (OR = 2.46, 95% CI: 1.15-5.48, P = 0.023), and clamping the needle shank during withdrawal (OR = 3.42, 95% CI: 1.40-8.21, P = 0.006). Conversely, sufficient assistant experience (>10 cases) was identified as a protective factor (OR = 0.39, 95% CI: 0.18-0.88, P = 0.021). CONCLUSION: Suture needle disengagement from the visual field during pediatric RALP is associated with specific technical and instrumental factors. Implementing targeted strategies-such as mandating specialized needle holders, preoperative needle shaping, a single-needle workflow, prioritizing clamping the suture thread over the needle shank during withdrawal, and ensuring adequate assistant training-has the potential to significantly reduce significantly mitigate the risk of needle loss and enhance overall surgical safety in pediatric RALP.

Humans↗

PubMed2026

Transcriptomic insights into thermal stress reveal physiological trade-off between thermal stress adaptation and reproductive investment in Spodoptera litura.

Spodoptera litura, a highly polyphagous lepidopteran pest, poses a major threat to agricultural productivity due to its remarkable adaptability to diverse environmental conditions. Although heat stress is known to trigger transcriptional reprogramming in insects, the molecular mechanisms underlying thermal stress responses in S. litura remain poorly understood. In the present study, fourth-instar larvae were exposed to acute heat stress (44 °C) and compared with control conditions (27 ± 1 °C) to investigate heat-induced transcriptional alterations affecting physiology and reproduction. High-quality RNA-Seq data achieved more than 80% mapping efficiency, with a total of 15,782 transcripts were identified. Transcriptome analysis of S. litura larvae showed 323 differentially expressed genes (DEGs), of which 262 genes were significantly upregulated and 61 were downregulated in heat-stressed larvae compared to the control group. The DEGs were associated with stress response, reproduction, signalling, proteostasis, detoxification, oxidative stress, metabolism, development, and chromatin regulation. Heat shock proteins genes, including HSP70, HSP90, and HSP27, together with co-chaperones such as TRET-1, STIP1, and Starvin, were strongly upregulated, indicating enhanced cellular protection against protein damage and oxidative stress under heat stress. Conversely, key reproductive and cell cycle-related genes, including BARR, CAPD2, FEO, CDK2 and MORULA, were significantly downregulated, suggesting reproductive impairment and developmental arrest. RT-qPCR validation corroborated the RNA-Seq findings, demonstrating a heat-induced physiological trade-off that prioritizes survival over reproduction. Consistent with these molecular responses, heat-stressed insects exhibited marked reproductive impairment, including significant reductions in gonadosomatic index, eupyrene sperm bundle count, mating frequency, mating success, female calling behaviour, copulation duration, fecundity, and egg fertility. Collectively, these findings provide comprehensive insights into the molecular basis of thermal adaptation in S. litura and demonstrate that acute heat stress compromises reproductive fitness while activating conserved stress-response pathways that promote short-term survival.

Animals↗

PubMed2026

Data-centric, robust, and explainable multimodal deep learning for clinical decision support: A systematic review.

PURPOSE: Multimodal deep learning is increasingly proposed for clinical decision support (CDS) under a "data-centric" framing that prioritizes label quality, missing-modality robustness, distribution shift, calibration, and explainability. Prior reviews have examined multimodal medical AI, CDS, and data-centric methods separately, but none address their intersection. We mapped the modalities, fusion strategies, and data-centric and explainability techniques used in this recent literature, quantified how often each is implemented rather than merely mentioned, assessed deployment-relevant evidence (external validation, clinical-outcome measurement, equity), and formally appraised study-level risk of bias. METHODS: Following the PRISMA 2020 statement (PROSPERO CRD420261427815; registered retrospectively), we screened 150 records and included primary, clinical, multimodal studies that applied machine or deep learning to a decision-support task and reported at least one quantitative result. Two reviewers screened and extracted data with consensus adjudication. Each study was coded against pre-specified operational definitions, separating implemented or empirically evaluated techniques from those only mentioned. Study-level risk of bias was assessed with PROBAST + AI. Synthesis was narrative. RESULTS: Thirty-one studies met inclusion; 30 (97%) were published between 2024 and 2026, with a median of three modalities (range 2-6), most commonly structured EHR (71%) and imaging (39%). Data-centric techniques were frequently reported (74-84% across label-noise, distribution-shift, calibration, missing-modality and class-imbalance handling; equity 61%). However, external validation was reported in only 4/31 studies (13%), a clinical or provider outcome in 3/31 (10%), and no study reported routine deployment. Overall risk of bias was high in 27/31 studies (87%), driven by the analysis domain. CONCLUSION: Within this recent, self-selected slice of the field, technical robustness and explainability techniques are widely reported but rarely validated out-of-distribution or against clinical outcomes, and the underlying evidence is at high risk of bias. Progress requires external multi-site validation, clinical-outcome measurement, formal bias appraisal, and adherence to AI reporting standards (e.g., TRIPOD + AI) before deployment can be justified.

Deep Learning↗

PubMed2026

Proteomics in environmental pollution research: Advances, challenges, and future directions.

Environmental proteomics has emerged as a powerful approach for elucidating the molecular mechanisms underlying pollutant-induced biological effects. Although this field has developed rapidly, the systematic review of recent proteomics applications in environmental pollution research remains limited. This review explored the emerging roles of toxicoproteomics in biomarker discovery and mechanistic elucidation, as well as ecotoxicoproteomics in ecological risk assessment and bioremediation strategies. Here, we review the field, highlighting recent trends such as the integration of proteomics with genomics, transcriptomics, and metabolomics to provide a comprehensive view of biological responses to environmental stressors. We further discuss the growing application of artificial intelligence in improving proteomics data interpretation and accelerating biomarker discovery. In addition, recent technological advances in environmental proteomics are highlighted, including next-generation tissue microarray proteomics, nanoscale proteomics, single-cell proteomics, and spatial proteomics. Despite its potential, proteomics faces challenges, such as high operational costs, computational complexity in analysis, and technical limitations in low-abundance protein detection. We propose that the convergence of proteomics with artificial intelligence and multi-omics approaches offers promising solutions to these challenges, enhancing the practical application of proteomics in environmental monitoring and risk assessment.

Proteomics↗

PubMed2026

Predicting ACL injury risk in athletes: A systematic review of machine learning-based models.

BACKGROUND: Early ACL injury risk identification in athletes is essential. This systematic review examines machine learning (ML) models for predicting ACL injuries, evaluating their methodological quality, performance, and reliability. METHOD: A comprehensive electronic search was conducted across PubMed, Scopus, Web of Science, and IEEE Xplore databases, supplemented by Google Scholar for grey literature, covering articles published between January 1, 2015, and August 30, 2025. Eligible studies were appraised using the Prediction Model Study Risk of Bias Assessment Tool (PROBAST) for methodological quality and risk of bias, and the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) guidelines for quality of evidence. RESULTS: Ten studies were included. PROBAST showed eight studies had moderate risk of bias and two low risk. TRIPOD found only two studies met quality criteria. ML models included logistic regression (n = 5), support vector machines (n = 4), k-nearest neighbor (n = 3), decision trees (n = 3), random forests (n = 5), neural networks (n = 2), linear discriminant analysis (n = 1), and pre-trained CNNs (n = 1). AUC ranged from 0.63 to 0.98. Accuracy (reported in six studies) ranged from 26% to 95%; however, these values should be interpreted with caution due to the absence of confidence intervals, lack of class imbalance handling, and limited external validation across studies. Tree-based ensemble methods such as random forest achieved competitive accuracy (74-86%), while SVM, a non-ensemble classifier, reported accuracy ranging from 71% to 95%; however, the highest values were obtained in studies with notably small sample sizes (n = 12 to n = 39), raising concerns about overfitting and generalizability. CONCLUSION: Current ML algorithms show promise for identifying athletes at high ACL injury risk and detecting relevant risk factors. Although study quality was generally satisfactory, future research should prioritize external validation and model interpretability to support clinical translation.

Humans↗

PubMed2026

Proteomic and phosphoproteomic profiles of time-dependent dynamic changes in LPS-induced macrophage polarization.

The temporal proteomic and phosphoproteomic reprogramming during early M1 macrophage polarization (0-6 h) remains poorly understood. We performed time-resolved proteomic and phosphoproteomic analyses of LPS-stimulated RAW264.7 macrophages at seven time points within 6 h. Time-clustering of differentially expressed molecules revealed two patterns: initial change with partial recovery, and sustained dysregulation. Upregulated proteins and phosphorylation sites were enriched in the Rho GTPase signaling pathway, T-cell receptor signaling pathway, NF-κB cascade, osteoclast differentiation pathway, and antiviral immune pathway. Downregulated pathways were associated with cell cycle regulation, chromatin remodeling, RNA metabolism, and mRNA processing, indicating resource reallocation to prioritize acute inflammatory responses. Kinase-substrate network analysis confirmed the mitogen-activated protein kinase (MAPK), cyclin-dependent kinase (CDK), protein kinase B (AKT), and ribosomal S6 kinase (RSK) families as core upstream phosphorylation regulators. Integrated analysis revealed synergistic and antagonistic relationships between proteomic and phosphoproteomic changes. This study provides a temporal molecular atlas of M1 polarization, delineating inflammatory signaling dynamics and offering a basis for therapeutic target discovery in inflammatory diseases. SIGNIFICANCE: Macrophage M1 polarization is a central event in innate immune defense against pathogenic invasion, yet its dysregulation is a pivotal driver of the onset and progression of a broad spectrum of inflammation-associated disorders, spanning autoimmune diseases, infectious conditions and inflammatory bone diseases, making the dissection of its molecular regulatory mechanisms an urgent research priority in immunology and translational medicine. Dynamic molecular events within 0-6 h after LPS stimulation are critical for initiating and shaping M1 inflammatory activation, yet systematic time-resolved proteomic and phosphoproteomic profiling remains insufficient.In this study, we comprehensively characterized temporal proteome and phosphoproteome changes at seven consecutive time points during macrophage polarization, clarified two distinct dynamic molecular patterns, identified core signaling pathways and key kinase regulators involved in inflammatory reprogramming, and uncovered the leading role of post-translational phosphorylation modifications in initiating polarization. This work delineates the time-series molecular atlas of early macrophage activation, provides novel insights into the temporal regulatory mechanism of inflammatory signaling networks, and lays a solid experimental foundation for exploring new intervention targets and regulatory nodes in clinical translational research.

Lipopolysaccharides↗

PubMed2026

Effects of Cognitive Behavioral Couple Therapy With Integrated Mindfulness on Mindful Attention, Depressive Symptoms, and Dyadic Adjustment in Low-Income Couples: A Pilot Randomized Clinical Trial.

Psychosocial distress can exacerbate marital conflict, maladjustment, and mental health vulnerability. This pilot randomized clinical trial examined cognitive-behavioral couple therapy (CBCT) integrated with mindfulness in low-income Brazilian couples (per-capita household income up to one minimum wage). Thirty-four participants (17 heterosexual couples) were randomized (independent computer-generated sequence) to an experimental (n = 16) or waitlist control group (n = 18). We assessed dyadic adjustment, mindful attention, marital social skills, and depressive symptoms (R-DAS, MAAS, IHSC, BDI-II) at baseline, post-treatment, and 3-month follow-up. The intervention was eight 80-min conjoint sessions plus daily home exercises. Time × group effects favored the experimental group for dyadic adjustment, mindful attention, and depressive symptoms (all p < 0.001, = 0.20-0.37), but not marital social skills (p = 0.14). Because two outcomes differed at baseline, effects were confirmed with baseline- and dependence-adjusted sensitivity analyses. These findings provide preliminary evidence that CBCT with mindfulness may benefit disadvantaged couples.

Adult↗

PubMed2026

The role of the external genitalia score (EGS) in evaluation of disorders of sex development.

OBJECTIVE: To investigate the utility of the External Genitalia Score (EGS) in the diagnosis of disorders of sex development (DSD) and decision-making regarding gender assignment in affected patients. METHODS: A retrospective cohort study was conducted, enrolling 114 DSD patients aged <2 years (88 reared as males, 26 reared as females) treated at our hospital between April 2005 and June 2023, alongside 40 hypospadias patients aged <2 years who underwent surgery at our institution from January to July 2023. Demographic data (age) and EGS assessments of external genitalia were collected for all participants. Statistical analyses included independent samples t-tests, Mann-Whitney U tests and Receiver Operating Characteristic (ROC) curve analysis. Specifically, EGS scores were compared between the hypospadias group and the male-reared subgroup of the DSD cohort; additionally, EGS scores were contrasted between male-reared and female-reared DSD subgroups. RESULTS: The mean age was 20.3 months in the hypospadias group, 17.9 months in the male-reared DSD group, and 18.8 months in the female-reared DSD group. EGS ranged from 5.5 to 11.5 (median 10.5) in the hypospadias group and from 1 to 12 (median 4.75) in the DSD group. ROC curve analysis was performed to compare EGS scores between the hypospadias group and the male-reared DSD subgroup. The optimal diagnostic threshold was determined by maximizing the Youden index (sensitivity + specificity - 1), which balances sensitivity and specificity. A cut-off value of ≤8.50 was identified as indicative of DSD; clinically, patients with an EGS score <9 should be prioritized for DSD screening. Further comparison between male-reared and female-reared DSD subgroups yielded a threshold of 4.00. Clinically, an EGS score ≤4 may suggest a preference for female gender assignment. DISCUSSION: The EGS scale is a reliable, valid, and clinically feasible tool for characterizing external genitalia in DSD patients. An EGS score of 9 can serve as an indicator for initiating detailed sex development evaluation in hypospadias patients. While gender assignment in DSD is a complex, multifactorial process, EGS scores showed a significant association with the sex of rearing in our cohort. In settings where major determinants are balanced, EGS may serve as an adjunctive descriptive parameter rather than a standalone decision-making tool.

Humans↗

PubMed2026

Analyzing salinity tolerance in grass carp (Ctenopharyngodon idella): Insights from genome-wide association study and genomic selection.

Grass carp (Ctenopharyngodon idella) is one of the most widely cultured freshwater fish species globally. However, the expansion of its farming scale faces severe limitation owing to freshwater scarcity; therefore, the development of strains with greater salinity tolerance is key for expanding production using brackish water resources. To investigate the genetic basis of salinity tolerance in grass carp, a genome-wide association study (GWAS) was conducted using 200 individuals representing extreme phenotypes, namely salinity-tolerant and salinity-sensitive groups. In total, 17 single nucleotide polymorphisms (SNPs) related to salinity tolerance were detected, which were distributed across 11 chromosomes. Through gene annotation, 38 candidate genes were obtained from these loci. Enrichment analysis revealed these candidate genes are primarily implicated in key biological processes, including osmotic regulation, energy metabolism, and stress responses. Analyses of different SNP densities revealed that the 5 K SNP density panel can balance prediction accuracy and computational efficiency. The BayesA model achieved the highest prediction accuracy under the GWAS_Evenly selection strategy, with substantial reductions in mean absolute error and mean square error. This study reveals the genetic mechanisms of salinity tolerance in grass carp, which might be optimized through genomic selection, and provides insights for selectively breeding new varieties with greater salinity tolerance.

Animals↗