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Association between anaemia and osteoporosis: a systematic review and meta-analysis.

BACKGROUND: Osteoporosis significantly impacts global morbidity. Recent evidence suggests anaemia may contribute to osteoporosis risk. This systematic review and meta-analysis investigates this association. METHODS: PubMed, Scopus, EBSCO, and ScienceDirect were searched for papers. Studies with definition of anaemia and assessing osteoporosis outcomes were included. Meta-analysis utilized random-effects models (DerSimonian-Laird method), and study quality was assessed via Newcastle-Ottawa Scale (NOS). Analyses were performed using R Studio. RESULT: Eighteen studies (861,540 participants) were analyzed. Anaemia significantly increased osteoporosis risk in univariate analysis (OR 1.62; 95% CI 1.33-1.98; p&#x2009;<&#x2009;0.001), despite high heterogeneity (I2 = 92.7%). The results remain significant in studies that reported multivariate analysis (OR 2.01; 95% CI 1.26-3.21; p&#x2009;=&#x2009;0.004). Sensitivity analyses confirmed the robustness of our result. CONCLUSION: Anaemia significantly associated with osteoporosis, emphasizing the need for targeted screening in anaemic individuals. Further studies should consider incorporating anaemia into osteoporosis and fracture prediction tools.

Humans

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

OBJECTIVE: To screen for independent risk factors for unplanned readmission in elderly patients with mild ischemic stroke, and to construct and validate an online risk prediction calculator based on an interpretable machine learning model, thereby providing a promising practical tool for accurate clinical assessment of 30&#x2011;day all&#x2011;cause unplanned readmission risk in this population. METHODS: A prospective cohort study was conducted, including 1050 patients aged&#xa0;&#x2265;&#xa0;60&#xa0;years with mild ischemic stroke admitted between August 2023 and September 2024. Participants were randomly divided into a training set (840 cases) and a test set (210 cases) at a ratio of 8:2. Risk factors were screened by univariate analysis and multivariable Logistic regression. Four machine learning models, namely LightGBM, XGBoost, Random Forest, and K&#x2011;Nearest Neighbors (KNN), were developed and their performance was evaluated using AUC, accuracy, sensitivity, and specificity as metrics. The SHAP framework was used for interpretability analysis, and an online calculator was subsequently developed based on the optimal model. RESULTS: Univariate analysis showed significant differences (P&#xa0;<&#xa0;0.05) in 13 factors including age, smoking, AIP, TyG index, HALP score, etc. Multivariable Logistic regression identified age (OR&#xa0;=&#xa0;9.752), smoking (OR&#xa0;=&#xa0;5.171), AIP (OR&#xa0;=&#xa0;6.691), TyG index (OR&#xa0;=&#xa0;4.393), HALP score (OR&#xa0;=&#xa0;2.831), and&#xa0;&#x2265;&#xa0;2 comorbidities (OR&#xa0;=&#xa0;3.664) as independent risk factors. All four machine learning models demonstrated good predictive performance. Based on a comprehensive evaluation of multiple metrics and computational efficiency, the LightGBM model exhibited the best predictive performance (AUC&#xa0;=&#xa0;0.884, accuracy&#xa0;=&#xa0;0.829, sensitivity&#xa0;=&#xa0;0.812, specificity&#xa0;=&#xa0;0.875). SHAP analysis showed that age, AIP, TyG index, smoking, and HALP score were key predictors. An online calculator developed based on this model enables individualized risk predictions. CONCLUSION: Key risk factors associated with 30&#x2011;day unplanned readmission in elderly patients with mild ischemic stroke were identified. The LightGBM model demonstrated high predictive accuracy, and together with the interpretability analysis and online calculator, offers a practical tool to support clinical risk assessment. However, this tool requires future external validation.

Humans

A versatile reversed-phase liquid chromatography charged aerosol detection method for streamlined monitoring of QS-21 content and stability in liposomal adjuvant formulations.

Identifying and quantifying an active adjuvant along with its degradants in drug formulations is essential for ensuring the safety and efficacy of the drug product. QS-21 is a potent adjuvant that is being evaluated in several clinical trials and is currently formulated in licensed vaccines that protect against shingles, malaria, and RSV. In aqueous environments, QS-21 is subject to hydrolytic degradation that is influenced by pH and temperature, resulting in the formation of a degradant known as QS-21 Hydrolyzed Product, QS-21 HP, which can occur during manufacturing and/or prolonged storage. The intact QS-21 and QS-21 HP induce distinct immune response profiles, making it critical to monitor the degradation of QS-21 in vaccine adjuvant formulations. To date, there has been a paucity of reliable assays for QS-21, its isomers, and degradant QS-21 HP in liposomal adjuvant formulations available that can be transferred seamlessly in quality control (QC) environments. Herein, we introduce a simple and QC-friendly liquid chromatography coupled to a charged aerosol detector (LC-CAD) enabled by stationary phase screening combined with in silico method development optimization. The method exploits 2.7&#xa0;&#x3bc;m fused-core phenyl hexyl particles, ensuring its versatility in standard and ultra-high pressure LC systems. This approach demonstrates a high correlation between predicted retention time (RT) and experimental outcomes with overall &#x2206;RT&#xa0;<&#xa0;4%. In addition, this assay shows great linearity, precision, specificity, and accuracy to advance process development characterization of new vaccine formulations.

Liposomes

Risk prediction models for blood transfusion in patients undergoing total hip and knee arthroplasty: a systematic review and meta-analysis.

OBJECTIVE: To systematically review and evaluate published risk prediction models for perioperative blood transfusion in patients undergoing total hip or knee arthroplasty (THA/TKA). METHODS: We systematically searched PubMed, Web of Science, the Cochrane Library, and Embase from inception to May 31, 2025. Two researchers independently screened the literature, extracted data, and assessed the risk of bias and applicability using the Prediction model Risk Of Bias Assessment Tool (PROBAST). The area under the receiver operating characteristic curve (AUC) values were pooled via a meta-analysis using Stata 18.0. RESULTS: d Fourteen studies containing 36 prediction models were included. The incidence of blood transfusion among THA/TKA patients ranged from 3.2% to 30.8%. Preoperative hemoglobin (Hb) level, tranexamic acid (TXA) use, operative duration, intraoperative blood loss, and age were the most frequently incorporated predictors. Model sensitivity ranged from 58% to 94.5%, and specificity ranged from 71.3% to 94%. Meta-analysis showed that the pooled AUC value of the 13 validated models was 0.87 (95% CI: 0.85-0.90), suggesting good discriminatory performance. All models were rated as having a high risk of bias. The applicability of four studies was rated as unclear. CONCLUSION: Although the included studies demonstrated promising discriminative ability of prediction models for blood transfusion in THA/TKA, all were assessed as having a high risk of bias using the PROBAST tool. Therefore, future research should prioritize the development of models with larger sample sizes, rigorous study designs, and multicenter external validation.

Humans

Mining Stored-Specimen Studies for Information about Cancer Natural History.

The advent of new multicancer early detection tests and publication of early diagnostic results have generated expectations of clinical benefit from multicancer screening. The clinical benefit of a cancer screening test depends critically on disease natural history, which is typically learned from prospective screening studies. Retrospective studies of stored blood specimens are important in learning about a test's preclinical diagnostic performance but have rarely been used to infer natural history. The extent to which these studies might be harnessed to also learn natural history is discussed in the context of an article in this issue that infers the combined natural history of a range of cancers targeted by a multicancer early detection test using a case-control subsample of specimens from a large cohort study. The critical question concerns the identifiability of key transition rates in multistate models of natural history alongside state-specific sensitivities. The article suggests that these parameters are estimable within a Bayesian framework that leverages prior information about test sensitivity from diagnostic studies. We offer a heuristic discussion of identifiability in this setting and encourage formal study to determine the extent to which models with varying degrees of complexity may be learned from stored-specimen studies. See related article by Dai et al., p. 1535.

Humans

Integrative machine learning and transcriptomic analysis reveals molecular mechanisms underlying low survival rate in larval Chinese Bahaba (Bahaba taipingensis).

Chinese Bahaba (Bahaba taipingensis) is a Class I protected marine fish endemic to China. Low larvae survival during artificial breeding severely hinder population recovery. To investigate the molecular mechanism of high mortality in larval fish, this study performed RNA-seq on liver from naturally deceased (ND) and mass-dead (MD) individuals, combined with least absolute shrinkage and selection operator (LASSO) regression and random forest (RF) algorithms to screen for core signature genes. A total of 873 differentially expressed genes (DEGs) were identified, including 112 upregulated and 761 downregulated genes. GO and KEGG enrichment analyses revealed significant enrichment in amino acid metabolism disorders, one&#x2011;carbon folate pool impairment, PPAR signaling abnormalities, ECM-receptor interaction, focal adhesion pathway, indicating widespread metabolic suppression accompanied by extracellular matrix remodeling and signaling disturbances in the livers of MD fish. MAD pre-filtering combined with dual machine learning algorithms yielded 18 robust core signature genes, among which SLC38A4, MMP1, FADD, FKBP5, and APOB were consistently identified as high-frequency core genes by both algorithms. SLC38A4 exhibited the highest importance score in the RF model and was significantly downregulated, making it the primary molecule distinguishing ND from MD phenotypes. ROC curve analysis showed that both models achieved an AUC of 1.000 (95% CI lower bound: 0.610), confirming the precise discriminatory ability of the core genes. GSEA further demonstrated significant enrichment of this core gene set in ND samples. This study provides the first systematic elucidation of the molecular mechanisms underlying liver dysfunction in low survival rate B. taipingensis, characterized by amino acid transport impairment, metabolic reprogramming, and structural remodeling, offering theoretical foundations for health assessment, early mortality risk warning, and artificial breeding conservation of this species.

Animals

Measurement of low-density lipoprotein cholesterol and other circulating lipids in Brazil: a systematic literature review.

Accurate laboratory assessment of circulating lipids underpins cardiovascular risk stratification, yet clinical interpretation depends not only on the assays but on the formula chosen to estimate low-density lipoprotein cholesterol (LDL-C). This review integrates the 2019-2025 evidence on laboratory methods for triglycerides (TG), total cholesterol (TC), and high-density lipoprotein cholesterol (HDLC), and on the formulas estimating LDL-C, VLDL-C, and non-HDL cholesterol, to determine how these should be measured, reported, and harmonized in Brazil, where lipid thresholds are adapted from international consensus. A PRISMA 2020 systematic search (PROSPERO CRD420251241064) of PubMed/MEDLINE, Scopus, SciELO, LILACS, Web of Science, and Embase retrieved 57,915 records; after removing 38,210 duplicates, 19,705 titles/abstracts were screened, 312 full texts assessed, and 25 sources included. Enzymatic colorimetric assays remain standard for TG, TC, and HDLC. For LDL-C, Martin/Hopkins classifies more accurately than Friedewald (89.6% vs 83.2% correct categorization in 5,051,467 patients), particularly at high TG and low LDL-C, while Sampson/NIH and modified Sampson/NIH extend reliable estimation into hypertriglyceridemia and very low LDL-C; direct measurement is reserved for TG beyond the validated range. Although the review centers on the Friedewald, Martin/Hopkins, and Sampson/NIH families that dominate guideline practice, other published equations exist and are addressed in context. In Brazil, atherogenic-lipid thresholds are risk-based decision limits rather than reference intervals; national surveys describe lipid distributions but were not designed to establish them. Analytical standardization through traceability programs, multicenter validation of formulas, and-where the distribution-based construct applies (HDLC, pediatrics)-nationally derived reference intervals are priorities for equitable cardiovascular risk assessment in Brazil.

Humans

Rationale, design, and experiences from the vanguard phase of the bariatric surgery for the reduction of cardiovascular events (BRAVE) trial.

BACKGROUND: Observational studies suggest that metabolic/bariatric surgery (MBS) reduces mortality and major adverse cardiovascular events in patients with obesity, but adequately powered randomized trials (RCTs) are lacking. The Bariatric Surgery for the Reduction of Cardiovascular Events (BRAVE) trial was designed to address this evidence gap. METHODS: BRAVE is an investigator-initiated, multi-center, open-label RCT with blinded endpoint adjudication comparing MBS vs guideline-based medical weight management (MWM) in adults with obesity and high-risk cardiovascular disease (CVD). Eligible participants have a body-mass index &#x2265;35 kg/m&#xb2; or &#x2265;30 kg/m&#xb2; with type 2 diabetes or age >55 years, and prior myocardial infarction (MI), coronary intervention, heart failure (HF), atrial fibrillation (AF) with elevated CHA&#x2082;DS&#x2082;-VASc score, cerebrovascular disease, or peripheral arterial disease. Participants are randomized 1:1 to MBS (sleeve gastrectomy, Roux-en-Y gastric bypass, or duodenal switch) or MWM, which includes dietary, behavioral, and pharmacologic therapies. The primary outcome is the composite of all-cause death, MI, stroke, HF events, coronary revascularization, AF hospitalization, and renal events. A vanguard phase of 200 participants was implemented to optimize recruitment and logistics. RESULTS: As of October 2025, 2,514 individuals have been screened from 17 centers in Canada, Brazil, Italy and Spain, with 444 entered MBS work-up, and 200 have been randomized. The randomized cohort (mean age 59.8 years; 37% female; mean BMI 44.0 kg m&#x207b;&#xb2;) has high burden of hypertension (82%), diabetes (45%), coronary artery disease (44%), HF (39%), and AF (48%). Recruitment barriers were identified and addressed through targeted education and enhanced patient engagement. CONCLUSIONS: BRAVE is the first large RCT evaluating whether MBS safely reduces major cardiovascular events compared with medical therapy in high-risk patients with obesity. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT05531474.

Humans

Obstructive sleep apnea and idiopathic intracranial hypertension: a systematic review and meta-analysis.

OBJECTIVE: To determine the pooled prevalence of obstructive sleep apnea (OSA) among adults with idiopathic intracranial hypertension (IIH) using polysomnography (PSG) and the Berlin Questionnaire screening. NATURE: IIH is a vision-threatening disorder characterized by elevated intracranial pressure. OSA shares overlapping risk factors and pathophysiological mechanisms with IIH, including nocturnal hypoxia and hypercapnia. Clarifying OSA prevalence in IIH is clinically important for diagnosis and management. METHODS: For this prospectively registered systematic review and meta-analysis (PROSPERO: CRD420251132794), we searched MEDLINE, Embase, and CENTRAL from inception to August 23, 2025, for studies reporting PSG-confirmed OSA or Berlin Questionnaire positivity in adults with IIH. Risk of bias was assessed using ROBINS-I and RoB-2, and certainty of evidence was checked using the Grading of Recommendations, Assessment, Development and Evaluation tool. Random-effects meta-analyses of proportions generated pooled prevalence estimates. Subgroup analyses excluded high-risk studies, leave-one-out analyses assessed robustness, and funnel plots evaluated publication bias. RESULTS: Eleven studies met the inclusion criteria. Across 9 PSG-based studies (n&#x202f;=&#x202f;299), the pooled prevalence of OSA in IIH was 0.44 (95% CI: 0.26-0.63; I&#xb2;&#x202f;=&#x202f;90.5%). Leave-one-out analyses showed stable results (39%-50%). Excluding high-risk studies (4 studies; n&#x202f;=&#x202f;132) yielded a pooled prevalence of 0.53 (95% CI: 0.32-0.74). Four Berlin Questionnaire studies (n&#x202f;=&#x202f;154) showed a pooled prevalence of 0.65 (95% CI: 0.54-0.74; I&#xb2;&#x202f;=&#x202f;0%). Funnel plot asymmetry suggested publication bias, and certainty of evidence was very low. CONCLUSIONS: OSA is common among patients with IIH, supporting routine objective sleep evaluation. Prospective studies are needed to clarify this association.

Humans

Selective monitoring of trace-level catechin and myricetin in herbal and aqueous matrices using magnetic MIP-DSPME: Optimization via design of experiments.

A novel dispersive solid-phase microextraction approach utilizing a magnetic molecularly imprinted polymer (MMIP) integrated with HPLC-UV detection was developed for the concurrent quantification of catechin and myricetin in herbal extracts and aqueous samples. The sorbent was engineered as a core-shell nanocomposite, consisting of a selective polymer layer deposited onto Fe3O4@SiO2-APTMS magnetic nanoparticles. Dual-template imprinting using catechin and myricetin generated complementary binding cavities within the polymer framework. Experimental variables influencing extraction were systematically screened and subsequently optimized. A Plackett-Burman design was first applied to identify the most influential factors, with pH and sorption time identified as the dominant variables. These parameters were subsequently fine-tuned using a central composite design, and the optimization process was completed in only 30 experimental runs. The sorption characteristics of the imprinted sorbent (MMIP) were compared with those of its non-imprinted counterpart (MNIP). The MMIP demonstrated markedly higher maximum binding capacities (Qmax), reaching 119.3&#xa0;mg&#xa0;g-1 for myricetin and 112.1&#xa0;mg&#xa0;g-1 for catechin, whereas the corresponding values for the MNIP were 32.55 and 32.08&#xa0;mg&#xa0;g-1, respectively. Moreover, the affinity constants (KL&#xa0;=&#xa0;0.760-0.950&#xa0;L&#xa0;mg-1) were approximately 2.3-fold higher for the MMIP, confirming its stronger and more selective interactions with the target analytes. The selectivity coefficients for the targeted flavonoids relative to structurally related compounds, including ferulic acid, p-coumaric acid, melatonin, and curcumin, exceeded 3.5 for the MMIP, whereas the corresponding values for the MNIP were close to 1.1, demonstrating the high molecular recognition capability of the imprinted sorbent. Method validation demonstrated limits of detection (LODs) of 0.33-0.59&#xa0;ng&#xa0;mL-1 and limits of quantification (LOQs) of 1.10-1.96&#xa0;ng&#xa0;mL-1, and excellent linearity over the concentration range of 5.0-5500&#xa0;ng&#xa0;mL-1 (R2&#xa0;>&#xa0;0.998). The method achieved recoveries of 93.96% to 105.69% with RSDs below 5.5%, while the preconcentration factors ranged from 209 to 229. Furthermore, the sorbent retained more than 95% of its extraction efficiency after four consecutive reuse cycles and more than 80% after six cycles, demonstrating excellent stability and reusability. The proposed method was successfully applied to the analysis of six medicinal plant extracts and water samples, showing negligible matrix interference and superior sensitivity, selectivity, and operational simplicity compared with conventional solid-phase extraction methods.

Flavonoids

Whole genome sequencing of unusual Hepatitis C virus subtypes and drug resistance analysis during direct-acting antiviral therapy in India.

INTRODUCTION AND OBJECTIVES: Pangenotypic direct-acting antivirals (DAA) are effective against highly prevalent Hepatitis C virus (HCV) subtypes, but have been clinically validated almost exclusively in high-income countries. Unusual HCV subtypes may carry natural polymorphisms, potentially impacting DAA susceptibility. We conducted full-genome characterization and resistance analysis of unusual HCV subtypes in patients receiving DAA treatment. PATIENTS AND METHODS: In this prospective hospital-based study, eligible patients were screened for anti-HCV antibodies and active infection was confirmed by diagnostic 5'NCR-based HCV RNA detection. Genotyping was performed by core region sequencing, and viral load quantified by real-time PCR. For whole genome sequencing, multiplex primers were designed using alignments of global reference sequences. Sequencing was carried out using the Oxford Nanopore Technology platform. Phylogenetic analysis used multiple sequence alignment and the HCV-GLUE resource for resistance-associated substitution (RAS) analysis. RESULTS: Predominant genotype was genotype 3 in 64.3% (n = 45); genotype 6 in 21.4% (n = 15); and genotype 1 in 14.2% (n = 10). Unusual HCV subtype 6xa was detected in two patients and showed no NS5A resistance mutations. One genotype 3b patient relapsed at 24 weeks post-DAA treatment completion and carried NS5A resistance-associated substitutions 30 K and 31 M both at baseline and at relapse, conferring high-level resistance to NS5A inhibitors. CONCLUSION: This is the first report from India of whole genome sequencing of HCV subtype 6xa. The identification of NS5A resistance mutations in the 3b relapse case underscores challenges for global HCV elimination strategies.

Humans

Predictive Models for Hypoglycemia Risk in Haemodialysis Patients With Diabetic Kidney Disease: Systematic Review and Meta-Analysis.

AIM: To provide evidence for selecting and developing reliable clinical assessment tools for hypoglycemia in diabetic kidney disease patients during haemodialysis. DESIGN: Review. METHODS: Systematic searches were performed in 9 Chinese and English databases to collect literature regarding the development of hypoglycemia risk prediction models in haemodialysis patients with diabetic kidney disease. Two reviewers independently performed literature screening, data extraction, risk-of-bias assessment, and applicability evaluation. The Prediction Model Risk of Bias Assessment Tool was used to assess the risk of bias and applicability of the included studies. Meta-analysis was conducted using R software. DATA SOURCES: CNKI, Wanfang, VIP, CBM, PubMed, Cochrane Library, EMbase, Web of Science, and CINAHL. The search period covered from the establishment date of each database to December 2025. RESULTS: Six studies, comprising six prediction models, were included. Two studies performed internal validation, and three conducted external validation. All models reported the area under the curve, ranging from 0.813 to 0.866, and calibration measures. Four studies were rated as having a high risk of bias, while all six demonstrated good overall applicability. The meta-analysis showed that the pooled AUC value of the six studies was 0.846 (95% CI: 0.823-0.867). CONCLUSION: Research on hypoglycemia risk prediction models in haemodialysis patients with diabetic kidney disease remains in the developmental stage. Although the included prediction models exhibited satisfactory apparent discriminatory ability and clinical applicability, most of the original studies suffered from a high risk of bias and lacked adequate validation. The true predictive performance and clinical application value of these models remain to be further verified. Accordingly, routine and unconditional clinical application is not recommended at this stage. Future studies should include more high-quality, multicenter external validation and develop models with high generalizability, favourable clinical applicability, and robust predictive performance to facilitate early identification of hypoglycemia risk in this population. IMPACT: This study systematically evaluated the hypoglycemia risk prediction models for diabetic kidney disease patients during haemodialysis, and the research on hypoglycemia risk prediction models for maintenance haemodialysis patients during dialysis is still in the development stage. This study provides a reference for clinical medical staff to select or develop hypoglycemia risk prediction and assessment tools for diabetic kidney disease patients during haemodialysis. REPORTING METHOD: This study was conducted in accordance with the relevant guidelines of the EQUATOR Network and followed the TRIPOD-SRMA Checklist. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution. TRIAL REGISTRATION: PROSPERO: CRD420251243352.

Humans

In Situ Hybridization and RT-PCR Detection of Nervous Necrosis Virus in Fourfinger Threadfin, Eleutheronema tetradactylum, in Taiwan.

Between April and July 2020, suspected outbreaks of nervous necrosis virus (NNV) infection were observed in fourfinger threadfin (Eleutheronema tetradactylum) fingerling hatcheries in Pingtung County, southern Taiwan. Affected fish exhibited spiral swimming behaviour and abdominal distension, resulting in mortality rates between 50% and 100%. Histopathological examination showed severe vacuolation in the brain and ocular tissues, with large oval and/or irregular basophilic cytoplasmic inclusion bodies in the brain. Phylogenetic analysis of the viral replicase (RNA1) and capsid protein (RNA2) genes revealed high nucleotide sequence identities among the isolates in this study, with sequence similarity rates of 96.9%-99% for RNA1 and 98.2%-99.0% for RNA2 compared to RGNNV reference strains available in the NCBI GenBank database. This is the first detection of betanodavirus in fourfinger threadfin in Taiwan, using RT-PCR and ISH. A positive correlation between elevated water temperatures and disease severity indicates the need for year-round surveillance and genomic analysis to clarify the epidemiology of FTNNV. The data suggest that infected eggs may facilitate the vertical transmission of Betanodavirus. Crucially, utilising virus-free broodstock, alongside routine health screening and environmental control, is essential for mitigating NNV risks in fourfinger threadfin aquaculture.

Animals

A Multi-omics Regulated Cell Death Framework Defines Immune Phenotypes and Guides Precision Therapy in Colorectal Cancer.

Colorectal cancer (CRC) is molecularly and immunologically heterogeneous, contributing to variable treatment response. Because regulated cell death (RCD) intersects with tumor metabolism, immune regulation, and therapeutic susceptibility, we built an RCD-centered framework for CRC stratification. Multi-cohort transcriptomic data were used to infer RCD subtypes with non-negative matrix factorization (NMF) and non-negative least squares (NNLS). Genomic, bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomic datasets were integrated to characterize subtype-associated biology. Machine-learning models were developed for immunotherapy response and survival-risk estimation. Candidate compounds were screened by GDSC2-based drug-sensitivity modeling and molecular docking, and FSTL3 was functionally assessed in vitro. The framework separated CRC samples into two RCD-related phenotypes resembling immune-hot and immune-cold states. RCD1 showed immune activation and higher mutational burden, whereas RCD2 showed immune-suppressed features, intratumoral heterogeneity, and aggressive biology. RCD-associated signatures showed potential for predicting immunotherapy response and survival risk. Dasatinib was prioritized for immune-cold, high-risk tumors, with preliminary evidence supporting its activity in CRC cells, while functional assays suggested a role for FSTL3 in growth, invasion, epithelial-mesenchymal transition, and apoptosis regulation. These findings suggest that RCD-based multi-omics analysis may refine CRC stratification and help generate therapeutic hypotheses.

Colorectal cancer

Systematic Review on the Effectiveness of Photobiomodulation Therapy on Enhancing Musculoskeletal Rehabilitation Outcomes after Total Knee and Hip Arthroplasty.

BACKGROUND: Total knee and hip arthroplasty (TKA/THA) effectively alleviate chronic pain and improve joint function and quality of life. However, postoperative recovery is often hindered by pain, edema, restricted range of motion (ROM), and muscle weakness, necessitating structured physical rehabilitation. Photobiomodulation Therapy (PBMT) has been proposed as an adjunct modality to enhance rehabilitation outcomes. This systematic review evaluates the efficacy of PBMT in reducing postoperative pain and edema as well as improving ROM and functional performance compared with placebo or standard physical therapy in post-arthroplasty patients. METHODS: A systematic search of PubMed, ProQuest, ScienceDirect, and Google Scholar was conducted from inception to May 31, 2025. Only prospective controlled trials assessing PBMT effects on postoperative pain, swelling, ROM, or functional performance following TKA or THA were included. Case reports, uncontrolled studies, and trials focusing on unrelated outcomes were excluded. Article selection involved title, abstract, and full-text screening, with additional studies identified through reference lists. The review is registered in PROSPERO (CRD420251123169). RESULTS: Four randomized controlled trials (RCTs; n = 133 participants) met the inclusion criteria, three studies focused on TKA, and one study examined THA. PBMT significantly improved postoperative pain and edema reduction in three trials, while two studies demonstrated enhanced ROM and functional outcomes compared with control or placebo interventions. PEDro scores ranged from 8 to 10, indicating moderate-to-high methodological quality. CONCLUSIONS: PBMT shows promising short-term benefits in reducing postoperative pain and swelling and improving functional performance after knee or hip arthroplasty. However, due to heterogeneity in treatment parameters and limited high-quality trials, conclusive evidence remains insufficient. Future large-scale RCTs with standardized PBMT parameters and extended follow-up are warranted to confirm its clinical efficacy.

Humans

Cannabis and cannabinoids for the treatment of mental and substance use disorders and symptoms: A systematic review and meta-analysis of experimental and observational studies.

BACKGROUND: Interest in cannabinoids for mental and substance use disorders is increasing. We examined experimental and observational evidence for treating these disorders and their symptoms. METHODS: Systematic review and meta-analysis (PROSPERO CRD42023467536). We searched CENTRAL, MEDLINE, Embase and PsycINFO to May 2025 for studies of cannabinoids in adults (&#x2265;18 years) with ADHD, anxiety, depression, PTSD, psychosis or Tourette syndrome, or alcohol, cannabis, opioid or tobacco use disorders. Two reviewers screened, extracted and assessed quality using a risk-of-bias tool and GRADE. RESULTS: We included 82 experimental and 118 observational studies. In RCTs, cannabinoids reduced anxiety symptoms (SMD=-0.40; 95% CI: -0.57, -0.23; I&#xb2;=90%) and, in one small trial, PTSD symptoms (SMD=-2.60; 95% CI: -4.58, -0.62; n=20), with trivial-to-no effect on depression (SMD=-0.20; 95% CI: -0.43, 0.04; I&#xb2;=91.6%), ADHD, psychosis and Tourette syndrome. Much anxiety and depression evidence came from symptoms measured as secondary outcomes in other primary conditions. Cannabinoids worsened cannabis use disorder severity in one RCT (SMD=2.35; 95% CI: 1.49, 3.21), with no effect on craving or withdrawal; evidence for alcohol, opioid and tobacco use disorders was very limited. Observational studies suggested improvements but had high risk of bias. The only significant safety finding was increased withdrawals due to adverse events with THC (OR=2.78; 95% CI: 1.66, 4.65). Certainty was predominantly very low. DISCUSSION: The evidence base shows very low certainty, high heterogeneity and methodological limitations, and is insufficient to support cannabinoids as first-line treatment. Signals for anxiety and PTSD are limited by indirectness and low certainty; no benefit was evident for depression; THC-related safety signals warrant careful consideration.

Humans

Bergamottin, a bioactive component of bergamot: dual inhibition of Japanese encephalitis virus internalization and genome replication.

Japanese encephalitis virus (JEV) is associated with high mortality and severe neurological sequelae, and existing prevention and control strategies remain insufficient. Therefore, the development of novel antiviral agents is of critical public health importance. This study systematically evaluated the antiviral activity and underlying mechanism of bergamottin, a natural product. Bergamottin exhibited significant dose-dependent inhibitory effects against JEV in multiple cell lines, including BHK-21, HuH-7, and Vero cells, demonstrating potent antiviral efficacy. Mechanistic investigations revealed that bergamottin primarily targeted the internalization and replication stages of the JEV life cycle, thereby effectively suppressing viral proliferation. Additionally, adaptive mutation screening indicated that the D389G mutation in envelope protein E confers drug resistance by potentially changing E protein conformation or reducing endocytic efficiency. In vivo experiment, bergamottin significantly reduced viral loads in mouse brain tissue and effectively improved the survival rate of infected mice. Our findings indicated that bergamottin exerted antiviral activity by dual targeting of key steps in the viral life cycle, making it a highly promising candidate for anti-JEV therapy. Further exploration of the antiviral properties of bergamottin is expected to facilitate its clinical development as a treatment for JEV infection.

Animals

Comparative analysis of histological and transcriptomic characteristics in caudal muscles of nile crocodiles (Crocodylus niloticus), siamese crocodiles (Crocodylus siamensis), and their hybrids.

Crocodylus niloticus and Crocodylus siamensis are high-value aquaculture species. C. niloticus is large-bodied but less abundant, while C. siamensis grows fast but is small-sized. Their hybrids combine parental advantages, yet relevant research is scarce. This study compared the histological and transcriptomic characteristics of the caudal muscle across the three taxa. HE staining indicated that C. niloticus had significantly larger myofiber diameters (p&#xa0;<&#xa0;0.05); C. siamensis had the smallest, and the myofiber density of hybrids was much closer to that of C. siamensis. Masson's trichrome staining indicated that C. niloticus had the thickest collagen fibers (p&#xa0;<&#xa0;0.05), C. siamensis the thinnest, and hybrids exhibited highly similar histological traits to C. siamensis. C. niloticus had higher LDH and SDH activities in caudal muscles, whereas the hybrid crocodile indicated the highest CK activity. Transcriptomic analysis identified numerous differentially expressed genes (DEGs), which were enriched in growth, muscle metabolism, and energy allocation pathways via GO/KEGG annotations. PPI analysis screened 24 hub genes related to energy metabolism. This study systematically reveals caudal muscle differences, providing insights into growth-related molecular mechanisms and theoretical support for crocodile artificial breeding.

Animals