SEARCH · Search PubMed

Results for “tick vector”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

37 records · Page 2Linked to original sources

PubMed2026

Autodissemination stations suppress Aedes notoscriptus mosquitoes and reduce Buruli ulcer risk in urban Australia: a randomized controlled field trial.

Aedes notoscriptus are mosquito vectors implicated in transmission of Mycobacterium ulcerans. This bacterium causes a destructive infection of skin and soft tissue called Buruli ulcer. Here we ran a randomized controlled trial in an urban Buruli ulcer endemic area in Melbourne, Australia to test whether autodissemination mosquito control stations, containing pyriproxyfen (larvicide) and Beauveria bassiana (entomopathogenic fungus), suppress Ae. notoscriptus populations. Six geographic areas each received 100 autodissemination stations for 8 weeks, and six control areas received no stations between 25 January 2024 and 21 March 2024. The primary outcome measure was mosquito population numbers. After the trial, there was a 70% average reduction in mosquito egg counts among the six intervention areas compared to control areas (P = 0.0076). In an ad hoc analysis, we then explored human Buruli ulcer notifications in treatment and control areas. After accounting for the 4.8-month mean incubation period, there was an 83% reduction in infection likelihood coinciding with peak intervention effect (intervention zones 1 case, control zones 6 cases, incidence ratio rate 0.167, 95% CI 0.0026-1.054, P = 0.047). The effect was not observed during the same time period in the year previous or following 2024, when no interventions were undertaken. A strong correlation (R2 = 0.85) was observed between decreased disease risk and mosquito suppression. These data show that autodissemination traps can effectively lower urban mosquito populations and reduce the threat of Buruli ulcer in humans.

Animals↗

PubMed2026

In Vivo Genome Editing Approach to Disrupt Hydroxyacid Oxidase 1 for the Treatment of Primary Hyperoxaluria Type 1.

Primary hyperoxaluria type 1 (PH1) is a rare autosomal recessive disorder that leads to kidney and liver failure. PH1 is caused by a mutation in the alanine glyoxylate aminotransferase (AGXT) gene, which encodes a key metabolic enzyme that converts glyoxylate to glycine in the liver. Inability to metabolize glyoxylate leads to oxalate overproduction, yielding insoluble calcium oxalate crystals; accumulation of these crystals leads to progressive organ failure. Here, we used a novel, minimally disruptive genome-editing approach to disrupt the mechanism of action of hydroxyacid oxidase 1 (HAO1), an upstream enzyme in the glyoxylate metabolic pathway. Successful gene editing and disruption of the HAO1 gene is expected to increase levels of glycolate, a harmless intermediate of the glycine metabolic pathway, thereby preventing the formation of calcium oxalate crystals. We intravenously administered an adeno-associated virus (AAV) vector expressing the M1HAO1 meganuclease to both wild-type and Agxt-/- mice, a mouse model of PH1. We observed >30% editing of HAO1 in Agxt-/- mice, correlating with a dose-dependent increase in serum glycolate levels. At the highest dose tested, urine glycolate levels increased by 79%, with a concomitant 75% decrease in urine oxalate levels. We also evaluated in vivo targeting in rhesus macaques injected with AAV expressing two different versions of the HAO1 meganuclease. Dose-dependent editing of hepatic DNA and RNA was achieved, and serum glycolate levels changed in a manner consistent with successful liver editing; additionally, the treatment was well tolerated. Our results indicate that AAV-delivered meganucleases can effectively target HAO1 in mice and nonhuman primates to achieve high levels of HAO1 gene editing. Moreover, increased glycolate levels in serum indicate that this intervention significantly impacts the HAO1-mediated glycolate-to-glyoxylate pathway. These data suggest that this approach may represent an effective treatment for PH1.

Hyperoxaluria, Primary↗

PubMed2026

Efficient rDNA-mediated multi-copy integration of gene clusters in Aureobasidium melanogenum.

Aureobasidium melanogenum is a promising non-conventional yeast chassis for synthetic biology. However, techniques recombining large genetic fragments, such as gene clusters, are still unavailable, hindering further metabolic reprogramming in this chassis. To achieve multi-copy integration of genes, we employed highly repetitive ribosomal DNA (rDNA) sequences in A. melanogenum as homologous recombination sites for large genetic fragments. First, integration efficiency of three different regions of A. melanogenum rDNA were investigated: RNA polymerase I promoter region (rDNA1, 1.0 kb), partial 26S rDNA region (rDNA2, 1.0 kb), and RNA polymerase I terminator region (rDNA3, 1.0 kb). Our findings revealed that the highest copy numbers and expression stability were observed for the short heterologous green fluorescent protein gene (gfp, 0.7 kb) and the long native polyketide synthase gene (pks, 7.0 kb) after rDNA1-mediated integration. Specifically, the copy numbers reached 7.0 and 8.0 for gfp and pks, respectively, and they remained stably expressed in the genome after 120-h subculturing. Furthermore, an 11.0 kb gene cluster (comprising the native pks, phosphopantetheinyl transferase (npg1), and scytalone dehydratase genes (scd) responsible for melanin biosynthesis) was integrated at the rDNA1 site, resulting in stable recombination with 15.0 copies and an approximately 12-fold increase in melanin production. Overall, the convenience and efficiency of the proposed rDNA-mediated multi-copy insertion strategy will facilitate superior metabolic engineering of A. melanogenum chassis cells.

Multigene Family↗

PubMed2026

Hemotropic mono- and coinfections in Colombian ruminants: descriptive occurrence and host-related factors associated with coinfection in cattle.

Hemotropic pathogens such as Anaplasma, Babesia, Mycoplasma, and Trypanosoma are endemic to cattle and can cause coinfections, complicating disease dynamics and control. However, the host-related factors influencing these infections under tropical conditions remain poorly understood. This study aimed to investigate the occurrence of hemotropic monoinfections and coinfections in ruminants tested for hemotropic pathogens and to identify host-related factors associated with coinfection in cattle under field conditions in Colombia. A total of 104 animals were included: 91 cattle, 10 buffaloes, and 3 goats. Among the cattle, 34 (37.4%) exhibited monoinfections, 47 (51.6%) had coinfections, and 10 tested negative. In buffaloes, seven (70%) presented monoinfections, and two (20%) presented coinfections; in goats, one had a monoinfection, and one had a coinfection, most frequently involving Mycoplasma spp. The predominant coinfection patterns were Anaplasma + Mycoplasma and Mycoplasma + Trypanosoma, particularly in Bos indicus cattle. Bivariate and multivariable analyses revealed that breed was the strongest predictor of coinfection, with animals of less common breeds showing 93% lower odds (aOR = 0.07; 95% CI: 0.02-0.30; p < 0.001). Bos taurus individuals also tended toward lower odds of coinfection in the multivariable model, although this trend did not reach statistical significance. Our findings demonstrate a high frequency of hemotropic coinfections in cattle, particularly those involving Mycoplasma spp., and highlight the influence of host-related factors on infection dynamics. These results underscore the importance of integrating demographic and genetic information into surveillance and prevention strategies to improve the management of hemotropic infections in tropical livestock systems.

Animals↗

PubMed2026

Adeno-Associated Virus Gene Therapy Translation: Lessons from Early Regulatory Meetings.

The Platform Vector-Gene Therapy (PaVe-GT) program is a National Institutes of Health (NIH) initiative that aims to develop adeno-associated virus (AAV) gene therapies for four monogenic rare diseases, two organic acidemias and two congenital myasthenic syndromes. PaVe-GT's platform-based approach identifies and diminishes redundancies and applies efficiencies in preclinical, clinical, and regulatory activities. The program's hypothesis is that implementing these efficiencies can accelerate clinical trial initiation. Based on its platform-centric experience and public-serving mission, the PaVe-GT program actively shares its scientific and regulatory learnings with the public to benefit the development of similar gene therapy products for rare diseases. PaVe-GT's first investigational AAV gene therapy candidate is AAV serotype 9 human propionyl-CoA carboxylase alpha subunit (AAV9-hPCCA) for propionic acidemia caused by PCCA deficiency, which received initial feedback from the Food and Drug Administration (FDA) in an INitial Targeted Engagement for Regulatory Advice on CBER/Center for Drug Evaluation and Research (CDER) ProducTs (INTERACT) meeting. Upon further product development that took into consideration the FDA's initial advice, the program obtained the Agency's feedback in pre-investigational new drug (IND) (Type B) and Type C meetings. Here, we share our experience from these meetings, including strategy, preparation, pre- and post-meeting feedback from the FDA, and lessons learned during the AAV9-hPCCA regulatory process, which the program plans to apply across the PaVe-GT platform. Topics discussed in the regulatory meetings included animal model and efficacy studies, toxicology study plans, manufacturing of the investigational AAV product, and clinical trial design. The main lessons learned from the pre-IND and Type C meetings for AAV9-hPCCA are: (1) Pharmacology/Toxicology studies in a single rodent species are sufficient for filing an initial IND; (2) FDA feedback guides product quality improvements and early development of a quantitative potency assay; (3) use of biomarkers as potential surrogate endpoints in a future efficacy trial benefits from collection of data in the natural history study and the first-in-human Phase 1/2 study; and (4) evidence from the Phase 1/2 clinical trial could be leveraged to support a license application. Lightly redacted regulatory documents and comprehensive templates developed by the PaVe-GT team are available on the PaVe-GT website.

Dependovirus↗

PubMed2026

Global molecular and serological evidence of dengue and chikungunya infection: a systematic review and meta-analysis of 158,608 tested participants.

INTRODUCTION: Dengue virus (DENV) and chikungunya virus (CHIKV) are Aedes-borne arboviruses with overlapping clinical manifestations, shared vectors, and substantial diagnostic challenges in co-endemic settings. This systematic review and meta-analysis synthesized published evidence on molecular detection, serological positivity, and DENV-CHIKV dual positivity/co-infection in human clinical, surveillance, and community-based study populations. CONTENT: Following PRISMA 2020 guidance, five bibliographic databases (PubMed/MEDLINE, Scopus, Web of Science, ScienceDirect, and Google Scholar) and supplementary grey-literature/preprint sources were searched for English-language studies published from 1 January 1980 to 31 December 2024. No prospective PROSPERO or OSF protocol registration was available. Eligible records reported extractable numerators and denominators for DENV and/or CHIKV in humans using recognized molecular or serological assays. A total of 196 studies comprising 158,608 tested or suspected participants were included in the extraction table. The pooled CHIKV estimate was 14.0 % (95 % CI: 12.0-16.4; I2=97.5 %), with molecular and serological estimates of 9.8 and 15.7 %, respectively. The pooled DENV estimate was 13.8 % (95 % CI: 10.9-17.3; I2=99.0 %), with molecular and serological estimates of 13.1 % (95 % CI: 7.9-21.0) and 14.3 % (95 % CI: 10.2-19.8), respectively. DENV-CHIKV dual positivity/co-infection was 52.9 % (95 % CI: 48.7-57.1) among studies that tested and reported both outcomes. Country-level estimates varied widely and should be interpreted as summaries of available studies rather than nationally representative burden estimates. Funnel-plot asymmetry was statistically significant in DENV analyses but not in the overall CHIKV analysis. SUMMARY: Available evidence indicates extensive but highly heterogeneous DENV and CHIKV positivity across selected clinical and surveillance populations. The pooled estimates should be interpreted cautiously because of substantial between-study heterogeneity, diagnostic variability, outbreak-period sampling, and uneven geographic representation. OUTLOOK: The findings support integrated arboviral surveillance, multiplex diagnostics, and vector-control preparedness in co-endemic regions.

Humans↗

PubMed2026

Functional role and regulatory network of miR-22-3p in chicken hepatic lipid metabolism.

Although microRNA-22-3p (miR-22-3p) is abundantly expressed in the avian liver, its epigenetic role in lipid homeostasis remains largely uncharacterized. To elucidate its in vivo function, 14-day-old female Qingyuan Partridge chickens were intravenously injected with lentiviral vectors to establish miR-22-3p overexpression and knockdown models. Phenotypic analysis demonstrated that miR-22-3p knockdown significantly elevated hepatic triglyceride (TG) levels (p < 0.05) and drove marked steatosis, whereas its overexpression reduced TG content. Transcriptome sequencing (RNA-Seq) revealed profound metabolic remodeling, identifying 23 core lipid-associated genes (e.g., ELOVL6, FADS2, ACSBG2, and PTGIS) heavily enriched in steroid biosynthesis, fatty acid metabolism, and elongation pathways. In conclusion, miR-22-3p functions as a bidirectional epigenetic rheostat that negatively regulates hepatic lipid deposition by orchestrating a multilayered polygenic network, providing novel molecular targets for mitigating avian metabolic disorders and optimizing production traits in indigenous poultry breeds.

Animals↗

PubMed2026

Functional neuroimaging subtypes of obsessive-compulsive disorder: A systematic review and meta-analysis.

Obsessive-compulsive disorder (OCD) exhibits substantial clinical heterogeneity that may reflect underlying neurobiological diversity. Neuroimaging-based subtyping may advance precision psychiatry by identifying biologically distinct subgroups with differential treatment responses. This study systematically synthesized evidence from functional neuroimaging subtyping studies in OCD to identify reproducible neurobiological subtypes, characterize their clinical profiles, and establish a consensus-based classification framework. We reviewed 40 original studies employing machine learning, clustering, normative modeling, or classification approaches, encompassing approximately 8,150 patients. Consensus clustering identified three reproducible neurobiological subtypes. The Limbic-Hyperactive subtype, comprising approximately 40% of patients, exhibited amygdala and insula hyperconnectivity, elevated anxiety levels, predominant contamination and washing symptoms, and favorable response to cognitive-behavioral therapy. The Fronto-Striatal-Hypoconnected subtype, comprising approximately 35% of patients, demonstrated reduced orbitofrontal-striatal connectivity, cognitive inflexibility, predominant checking and ordering symptoms, and a favorable response to selective serotonin reuptake inhibitors. The Global-Disrupted subtype, comprising approximately 25% of patients, exhibited widespread connectivity disruption, greater symptom severity, and poor treatment response. Support vector machine classification achieved 81.5% accuracy for subtype assignment, though classification of OCD versus healthy controls showed limited generalizability in multisite settings (AUC 0.567-0.673). These findings support a neuroimaging-based framework for personalized treatment selection but require prospective validation.

Humans↗

PubMed2026

A translational framework for early-phase inner-ear gene therapy: clinical trial design, regulatory strategy, and ethical considerations.

PURPOSE OF REVIEW: Hereditary hearing loss has historically been approached as a diagnostic category rather than a therapeutically modifiable disease. Recent advances in molecular genetics, cochlear gene delivery, and first-in-human clinical trials are changing that. This review summarizes contemporary progress in the genetics of hearing loss, with emphasis on emerging gene-based therapies, clinical trial design, regulatory and ethical considerations, and practical implications for otolaryngologists as biologic treatment enters clinical practice. RECENT FINDINGS: Early clinical trials targeting OTOF -related DFNB9 deafness have demonstrated satisfactory safety profiles and meaningful auditory recovery, establishing the first proof-of-concept for cochlear gene therapy in humans, culminating in the April 2026 FDA approval of Otarmeni. Genetic diagnoses are increasingly informing prognosis, cochlear implant counseling, and therapeutic candidacy. Preclinical research continues to expand toward recessive, dominant, and syndromic hearing loss using gene replacement, antisense, RNA interference, and genome-editing strategies. Substantial challenges remain, including heterogeneous outcome measures, uncertain long-term efficacy, regulatory complexity, and inequitable global access. SUMMARY: The genetics of hearing loss is transitioning from a diagnostic modality to an interventional one. Widespread clinical impact will require advances in vector engineering, equitable implementation, multidisciplinary counseling, and integration with established rehabilitation pathways. For otolaryngologists, genetic literacy is becoming essential to contemporary hearing care.

Humans↗

PubMed2026

Revealing potential biomarkers and metabolic mechanisms of ovarian aging in hens during late laying period based on machine learning and metabolomics.

Ovarian function decline during the late laying period represents a major bottleneck for the economic efficiency of the global poultry industry. However, the underlying metabolic mechanisms and reliable early-warning biomarkers for ovarian aging remain poorly understood. In this study, we performed the first untargeted LC-MS/MS metabolomics analysis of ovarian tissues from Taihe silky fowls at peak laying (30 weeks) and late laying (50 weeks) stages, and employed an ensemble machine learning strategy integrating LASSO, random forest, and support vector machine (SVM) algorithms to identify high-confidence core biomarkers of ovarian aging. Gene expression analysis was further conducted to validate the potential molecular mechanisms. Our results showed that the metabolic profiles of ovarian tissues differed significantly between the two groups. A total of 6 core biomarkers were identified, 4 of which were long-chain acylcarnitines. Mechanistic analysis revealed that downregulation of key genes in the carnitine shuttle system led to impaired mitochondrial fatty acid β-oxidation, which in turn triggered excessive oxidative stress and compromised ovarian endocrine function. In conclusion, this study identifies long-chain acylcarnitines as potential metabolic biomarkers for ovarian aging in Taihe silky fowls. These findings provide novel insights into the metabolic basis of poultry ovarian aging and lay a theoretical foundation for the precise regulation of reproductive performance in indigenous poultry breeds.

Animals↗

PubMed2026

Impact of climate change on pediatric health outcomes.

Climate change has become one of the most critical health issues globally in the twenty-first century with children bearing the disproportionate burden of the burden since they are more vulnerable than adults because of their physiological, behavioral, and developmental capacities. It is a systematic review that rates the evidence of the relationship between climatic exposures such as heat, air-pollution, and extreme weather events and pediatric health outcomes. The number of peer-reviewed studies involved was 23 published in 2000-2025, which represented different geographic areas and study designs and assessed acute and chronic health outcomes. The Newcastle-Ottawa Scale and the ROBINS-I tool were used to evaluate the methodological quality, and the majority of the studies had low to moderate risks of bias. The narrative synthesis shows that there are always links between air pollutants especially PM2.5, NO2 and O3 and respiratory morbidity, prevalence of asthma and hospitalization of children. Amplified temperatures as well as heat waves were associated with increased cases of heat illness, dehydration, and febrile state in infants and young children. There were elevated cases of diarrheal and vector-related infections, especially in low-resource settings, which were linked to extreme weather events especially floods. Although the overall results were similar, significant differences in the regions and methods were found, and low-income countries show little evidence. In addition, exposures as analyzed in most studies were usually considered individually, which may have underestimated the cumulative or compound climate risks.

Humans↗

PubMed2026

ChIP-seq profiling identifies diapause-regulated H3K27me3 targets in the fat body of Culex pipiens.

Culex pipiens, a principal vector of significant arboviruses, survives winter through diapause, a hormonally controlled inactive phase that enhances endurance under severe cold circumstances. Recent data suggests that epigenetic processes, namely histone post-translational modifications (hPTMs), play a crucial role in regulating seasonal dormancy. Prior studies from our laboratory indicated a decrease in the methylation of Histone 3 (H3K27me3) in diapausing fat body tissue, associated with elevated expression of the histone demethylase UTX. Nonetheless, the precise genomic areas impacted by these chromatin alterations remained unidentified. We used chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) to delineate the genome-wide distribution of H3K27me3 across fat body chromatin in diapausing (D) and non-diapausing (ND) female Cx. pipiens. Notably, the higher signal at transcription start sites (TSSs) reflects localized redistribution rather than a global decrease, as diapausing fat bodies retain less H3K27me3 overall but concentrate it at promoters. To investigate the functional significance of these chromatin alterations, we confirmed a number of target loci via ChIP-qPCR and assessed gene expression with qRT-PCR. We identified many critical genes that were markedly increased in diapausing mosquitoes, exhibiting an inverse relation to H3K27me3 enrichment. Our data demonstrates different H3K27me3 chromatin landscapes between diapausing and non-diapausing Cx. pipiens, corroborating a hypothesis of selective, locus-specific repression in the non-diapause state and its targeted removal during diapause to permit activation of dormancy-associated genes. These results suggest that chromatin remodeling is a core driver of the diapause switch.

Animals↗

PubMed2026

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

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

Humans↗

PubMed2026

An automated geometric modeling framework in GATE for the design and optimization of high-sensitivity converging-beam SPECT collimators.

Objective.The trade-off between detection sensitivity and spatial resolution is a fundamental challenge in designing organ-dedicated Single-photon emission computed tomography (SPECT) collimators. While converging-hole geometries offer a solution, their optimization is often hindered by the lack of flexible computational tools capable of modeling large-scale, non-parallel hole arrays. This study aims to develop an automated geometric modeling framework to facilitate the design and evaluation of complex converging- and diverging-hole collimators within standard Monte Carlo environments.Approach.We developed a specialized modeling framework by implementing custom C++ classes and a vector-based alignment algorithm within GATE. This platform enables automated, orientation-consistent construction of large-scale converging arrays not natively supported by standard implementations. A high-sensitivity pure cone-beam collimator (CBC) was designed using this framework. The evaluation used hot-rod, disc, and Jaszczak phantoms for physical characterization, while XCAT and dedicated brain models were employed for clinical tasks, including cardiac, brain perfusion, and DaTscan SPECT simulations.Main results.The CBC achieved a nearly fourfold sensitivity increase compared to a conventional low-energy high-resolution parallel-hole collimator at a 20 cm radius of rotation, while maintaining comparable spatial resolution. Despite a 52.3% field of view reduction, the CBC yielded a 2.2-fold noise reduction (CV: 11.7% vs 25.9%) and mitigated partial volume effects via geometric magnification. XCAT and brain phantom simulations confirmed enhanced anatomical definition and contrast recovery in cardiac, perfusion, and DaTscan tasks.Significance.This work provides an efficient computational tool for rapid design space exploration of advanced collimator geometries. The results demonstrate that the proposed CBC design offers a significant sensitivity advantage, making it highly suitable for high-performance, small-volume clinical applications such as brain and cardiac molecular imaging.

Tomography, Emission-Computed, Single-Photon↗

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

Analysis of end-stage renal disease mediated by cuproptosis-related genes.

OBJECTIVE: The complex pathophysiological mechanism of end-stage renal disease (ESRD) has not been fully understood. Cuproptosis is a newly discovered type of programmed cell death. Therefore, this study attempts to clarify the relationship between cuproptosis-related genes (CRGs) and the phenotype of ESRD. MATERIALS AND METHODS: The National Center for Biological Information Gene Expression Omnibus database was applied to obtain the GSE37171 dataset comprising whole-genome microarray analysis of peripheral blood samples. A 3 : 1 case-control design was employed with 75 ESRD patients and 20 healthy controls who were frequency-matched for age, sex, and ethnicity. Based on differentially expressed genes (DEGs) and genes related to cuproptosis, CRGs were identified. Thereafter, we explored two different subpopulations based on the cuproptosis gene and analyzed their expression and immune infiltration. Genes specific to the CRG cluster were identified through the weighted gene co-expression network analysis algorithm, and the best prediction model was determined and verified by four machine learning methods. RESULTS: The study identified 14 differentially expressed CRGs, among which ATP7B, SLC31A1, LIAS, LIPT1, DLD, MTF1, CDKN2A, DBT, and DLST had relatively high expression levels in the ESRD samples. Compared with the control group, expression levels of FDX1, DLAT, PDHA1, PDHB, and GLS were significantly lower in the ESRD group, and CRGs played a key role in the regulation of immune infiltration in ESRD. Two cuproptosis-related molecular clusters were identified in the ESRD samples. Cluster2 was more correlated with the immune infiltration of ESRD. By analyzing the intersection points between CRG cluster and key genes of ESRD, a total of 888 specific DEGs were identified. Functional differences related to specific DEGs were further explored using gene set variation analysis. Five significant genes (SMC5, USP47, USP53, AGA, and DMXL1) were identified by the support vector machine model as key predictors for ESRD disease risk, achieving an area under the curve (AUC) of 1.00 in internal validation. However, external validation in independent cohorts is required prior to clinical application. Individual gene analysis showed an AUC > 0.81 in discriminating ESRD patients from healthy controls, and the expression of all 5 genes in ESRD patients was significantly lower than in the control group. CONCLUSION: This study clarified the relationship between CRGs and the phenotype of ESRD, analyzed their specific roles in the immune microenvironment, and obtained a predictive model, providing new insights for the study of its potential therapeutic targets.

Humans↗

PubMed2026

Health-Related quality of life (HRQoL) and health state utility values (HSUV) in patients with head and neck Cancer: A systematic review and Meta-Analysis.

BACKGROUND: Head and neck cancer (HNC) and its treatment can substantially impair speech, swallowing, eating, appearance, and social functioning, resulting in persistent reductions in health-related quality of life (HRQoL). Although the EuroQol 5-Dimensions questionnaire (EQ-5D) is widely used to assess generic HRQoL and derive health state utility values (HSUVs), EQ-5D-based evidence in HNC has not been comprehensively synthesized. This study aimed to summarize EQ-5D-based HRQoL and HSUVs in HNC, estimate pooled utility and EQ-VAS scores, explore subgroup differences, and identify predictors of poorer HRQoL. METHODS: A systematic review and meta-analysis was conducted according to PRISMA guidelines and registered in PROSPERO (CRD420261307907). PubMed, EMBASE, Web of Science, Cochrane Library, and Scopus were searched from inception to February 10, 2026. Studies reporting baseline EQ-5D utility values and/or EQ-VAS scores in patients with HNC were included. Random-effects meta-analyses using the DerSimonian-Laird (DL) estimator with the Hartung-Knapp-Sidik-Jonkman (HKSJ) adjustment were performed to pool mean scores. Between-study variance (τ2) and 95 % prediction intervals (PI) were calculated to capture parameter dispersion. Subgroup analyses were conducted across clinical and methodological vectors. RESULTS: Twenty studies involving 7,403 patients were included. The pooled mean EQ-5D utility score was 0.79 (95 % CI: 0.75-0.83; τ2 = 0.0011; 95 % PI: 0.72-0.86). The pooled mean EQ-VAS score was 69.36 (95 % CI: 65.71-73.01; τ2 = 38.4586; 95 % PI: 55.11-83.61). Extreme heterogeneity was observed (I2 = 96.4 % and 97.1 %, respectively). Utility values were significantly higher in studies utilizing the EQ-5D-5 L than the EQ-5D-3 L version (0.82 vs. 0.76). By tumor subsite, nasopharyngeal cancer showed the highest utility value (0.85, exploratory), whereas oral cancer demonstrated the lowest (0.73). Adjusted multivariable models revealed that advanced stage, high treatment intensity, severe pharyngolaryngeal pain, dysphagia, malnutrition, and older age were robust predictors of poorer HRQoL. CONCLUSIONS: Patients with HNC experience substantial and persistent HRQoL impairment, with meaningful variations driven by tumor subsites and instrument versions. In light of the extreme heterogeneity, these pooled findings establish a macro-level, broad reference estimate rather than a fixed target. These parameters directly inform localized survivorship care planning, health technology evaluations, and cost-utility decision-making modeling in head and neck oncology.

Humans↗

PubMed2026

Spinal meningiomas: histopathological grading using a benchmark radiomics model with notes on disease control.

OBJECTIVE: Spinal meningiomas (SMs) are common primary spinal tumors for which surgery is considered the first-line treatment when safe and feasible. The ability to extrapolate the tumor grade from preoperative imaging may significantly inform early patient expectation-setting regarding recurrence. Building on radiomics studies in cranial meningiomas, the authors aimed to construct a benchmark radiomics model to preoperatively identify the histological grade of SMs. METHODS: Institutional surgical records from May 2012 to November 2025 were queried for pathology-confirmed meningiomas below the foramen magnum, with preoperative contrast-enhanced imaging available for segmentation. SMs were classified as low-grade (WHO grade 1) and high-grade (WHO grade 2 tumors and grade 1 tumors with atypia). Tumors were manually segmented, and features were extracted using the PyRadiomics software package. An ensemble model of k-nearest neighbors, random forest, and support vector machine classifiers was trained using nested cross-validation on a subset of 10 features to differentiate tumor grades. Clinical data for the cohort were also extracted, and disease control in an adjunctive clinical series was assessed. RESULTS: Seventy-four patients were included in radiomics analysis, with an area under the receiver operating characteristic curve of 0.879 and a mean F1 score of 0.748. The model's top 5 features were all texture features that differed significantly (p < 0.05) across low- and high-grade SMs. These included measures of tumor textural and contrast-enhancement heterogeneity, with overlap with features reported in radiomics models for histological grading of intracranial meningiomas. Fifty-five patients with a median radiographic follow-up of 22.2 (range 1.9-86.4) months remained for clinical analysis after exclusion of patients with less than 1 month of follow-up and syndromic meningiomas. Four recurrences occurred at a median of 20.8 (range 1.8-41.8) months. High-grade tumor pathology did not significantly impact progression-free survival (p = 0.682, log-rank test; Cox regression high vs low grade hazard ratio [HR] 0.62, 95% CI 0.06-6.11, p = 0.685). Subtotal resection was associated with poorer progression-free survival than gross-total resection (p = 0.004, log-rank test; Cox regression subtotal vs gross-total resection HR 10.62, 95% CI 1.46-77.05, p = 0.019). These findings remain contextualized within a relatively limited follow-up window and small recurrence event count, suggesting a need to characterize the interplay between tumor grade and extent of resection as drivers of local disease control in SMs. CONCLUSIONS: A preoperative radiomics model can stratify high-grade SMs using open-source tools applied to single-institution data.

Humans↗