SEARCH · PubMed Health

Results for “cost-effectiveness evaluation”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

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

At least 37 records · Page 2Linked to original sources

PubMed2026

Effectiveness of peer recovery support services for substance use disorders: A systematic review of healthcare utilization, behavioral health, and engagement outcomes.

BACKGROUND: Peer recovery support services (PRS) delivered by individuals with lived experience of substance use, are increasingly incorporated into substance use disorder (SUD) care systems to improve care engagement, reduce acute care use, and support recovery. However, existing systematic reviews have focused on substance use outcomes, with limited attention to healthcare utilization, psychosocial functioning, and outcomes across settings, and populations. METHODS: This systematic review, registered in PROSPERO (CRD42023469279), synthesized peer-reviewed studies from 2003 to 2026 evaluating PRS for individuals with alcohol or drug-related SUD. Using MEDLINE, Embase, PsycINFO, and CINAHL, the review included 53 studies primarily conducted in high-income countries that reported quantitative outcomes across substance use, healthcare utilization, behavioral health, and treatment engagement. Risk of bias was assessed using Cochrane RoB 2, ROBINS-I, and ROBINS-E tools. RESULTS: Overall, evidence was most favorable for selected treatment-linkage and engagement outcomes, whereas findings for substance use, emergency department use, hospitalization, overdose, and mortality were inconsistent. Uncontrolled longitudinal studies frequently reported improvements in depression and anxiety, but no randomized trials evaluated these outcomes, limiting causal inference. Exploratory cross-study patterns suggested that sustained navigation, practical assistance, and repeated peer contact were more often present in programs reporting favorable outcomes; however, these components were not independently evaluated. Substantial heterogeneity, frequent multicomponent interventions, high risk of bias in many nonrandomized studies, and limited long-term and economic data constrain conclusions. CONCLUSIONS: Findings support the promise of PRS while underscoring the need for more rigorous comparative studies, cost-effectiveness data, and further research in low- and middle-income countries.

Humans↗

PubMed2026

Interfacial engineering of cobalt tungstate-halloysite nanotube nanocomposite for electrochemical detection of synthetic vanillin in food matrices.

In processed foods and medicine, synthetic vanillin is widely used, although excessive intake poses toxicological risks. Due to the rising usage of synthetic vanillin in food products and associated health hazards, quick, sensitive, and reliable analytical methods are needed to precisely measure vanillin in complex food matrices. This work introduces a CoWO4@F-HNT/GCE nanocomposite as an efficient electrocatalytic modifier for glassy carbon electrodes aimed at trace-level synthetic vanillin detection. Structural and microscopic analyses confirmed phase-pure monoclinic CoWO4, preservation of the tubular aluminosilicate framework, and homogeneous nanoparticle anchoring on F-HNT. Differential pulse voltammetry provided a broad linear range from 0.01 to 372.14 μM and a low detection limit of 4.3 nM, together with excellent selectivity against common interferents, good cycling stability, and high inter-electrode reproducibility. These characteristics position the CoWO4@F-HNT-modified electrode as a cost-effective and reliable platform for on-site quality control of synthetic vanillin in complex food matrices.

Benzaldehydes↗

PubMed2026

A point-of-use SERS assay for rapid detecting difenoconazole and flusilazole residues in fruit juices using Au/COF substrate.

We developed a ready-to-use surface-enhanced Raman scattering (SERS) sensor for rapid, pretreatment-free detection of difenoconazole (DIF) and flusilazole (FLU) in peach and lychee juices. The substrate combines Au nanoparticles (AuNPs) with covalent organic frameworks (COF) and is implemented on a portable 25-well plate, enabling in situ testing. Juices can be directly applied to the SERS-active Au/COF composite, allowing simultaneous adsorption and signal generation. The correlation between SERS intensity and logarithmic concentration yielded R-values between 0.925 and 0.986, meeting the monitoring needs of non-laboratory scenarios. The entire workflow completes within 12 min, offering a faster alternative to conventional methods while maintaining high sensitivity and reproducibility. Detection limits reach 0.96-1.22 ppb for DIF and FLU, both of which are below the regulatory maximum residue limits. Distinct SERS fingerprints enable reliable discrimination of mixed residues across juice matrices, supporting rapid on-site monitoring and cost-effective pesticide surveillance.

Triazoles↗

PubMed2026

Effectiveness of Caregiver-Mediated Spoken Language Interventions for Children Under Five at Risk of Developmental Language Disorder: A Systematic Review and Meta-Analysis.

BACKGROUND AND AIMS: Caregiver-mediated interventions are commonly used by Speech and Language Therapists to support early language development. Developmental Language Disorder (DLD) is associated with reduced quality of life throughout the lifespan. Understanding factors that predict intervention success is essential for developing appropriate, cost-effective therapy provision for the approximately 12% of preschool children who present with early markers for Developmental Language Disorder (DLD). This systematic review and meta-analysis examined the effectiveness of caregiver-mediated spoken language interventions for under-fives at risk of DLD, and factors influencing intervention effectiveness. METHODS: A systematic review following PRISMA guidelines was conducted. Five electronic databases were searched to identify experimental studies comparing caregiver-mediated spoken language interventions to control conditions in under-fives presenting with risk factors for DLD. Risk factors included prematurity, socioeconomic factors, caregiver language development concerns, and formal or informal language screening or assessment scores. Twenty-six experimental studies with 1407 child participants were included in qualitative synthesis. Meta-analysis was performed on nine Randomised Controlled Trials involving 947 children. RESULTS: Effectiveness was examined for outcomes including child language gains, child wellbeing, inclusion and attainment. Meta-analysis indicated a significant effect of caregiver-mediated spoken language interventions on language outcomes compared to treatment-as-usual, non-language intervention or waitlist control conditions. Non-language outcomes were evaluated via qualitative synthesis. Interventions significantly improved language development trajectories for under-fives presenting with risk factors or early markers for DLD. CONCLUSION AND IMPLICATIONS: This review contributes to the growing evidence base demonstrating that caregiver-mediated interventions can positively impact language development and wellbeing outcomes for children under five at risk of DLD. These findings support the implementation of caregiver-mediated environmental language interventions in clinical practice to maximise accessibility and cost-effectiveness while delivering optimal outcomes for vulnerable populations. WHAT THIS PAPER ADDS: What is already known on this subject Previous research on caregiver-mediated spoken language interventions has highlighted gaps in the evidence regarding the impact of risk factors, demographic characteristics, dosage and intervention components on child language outcomes. Developmental Language Disorder has relatively high population prevalence, estimated at 7%. Prevalence is associated with risk factors including low household socioeconomic status (SES), prematurity and late language emergence. In contrast to its prevalence, there is low public and professional awareness of DLD and a low diagnostic rate. Therefore, a strengthened evidence base and additional insights into the factors affecting success of family-based interventions is important in order to increase the effectiveness of service provision and care planning for this underserved population. Timely and effective intervention with young children presenting with early markers for DLD has the potential to offer lifelong improvement to their wellbeing, inclusion and attainment outcomes. Recent systematic reviews of the effectiveness of caregiver-mediated language interventions had differences in population age range and diagnostic inclusion criteria. What this paper adds to existing knowledge Our review examines the effectiveness of caregiver-mediated early spoken language interventions on child language, attainment and wellbeing, and on caregiver self-efficacy and adherence to language support strategies. Our population was children under five presenting with risk factors for Developmental Language Disorder, in the absence of other neurodevelopmental or genetic conditions such as intellectual disability or autism. This review adds depth and detail to the evidence base supporting the effectiveness of caregiver-mediated spoken language interventions in improving outcomes for this population of young children, and factors that influence their success. What are the potential or actual clinical implications of this work? The high prevalence of Developmental Language Disorder, estimated at around 7% of the population, and the strong association with risk factors including low SES, prematurity and late language emergence, coupled with the low awareness of DLD and low diagnostic rate, mean that a strengthened evidence base and additional insights into the factors affecting success of family-based interventions can increase the effectiveness of service provision and care planning for this population. Timely and effective intervention in this group of young children has the potential to improve wellbeing and attainment outcomes across the lifespan. This review contributes to our understanding of how to implement cost-effective, socially valid and maximally engaging partnership working with families of young children at risk for DLD.

Humans↗

PubMed2026

Recent advances in electrode materials for electrochemical detection of zearalenone.

Zearalenone (ZEN) is an estrogenic mycotoxin commonly found in cereals, animal feed, and processed foods, making it an important concern for food safety and public health. Conventional chromatographic and immunological methods can detect ZEN; however, they often require expensive instruments, lengthy sample preparation, and skilled personnel, which restrict their use for rapid and on-site testing. Electrochemical sensors have attracted enormous interest of the scientific community because of their high sensitivity, rapid response, low cost, miniaturization potential, and compatibility with portable systems. The analytical performance of the electrochemical sensors is strongly influenced by electrode materials, morphology, conductivity, porosity, surface functionality, and the efficiency of bioreceptor immobilization. Despite several reviews on mycotoxin detection, a systematic assessment connecting electrode-material design, modification strategies, sensing mechanisms, and electroanalytical performance specifically for ZEN sensing remain limited. This review critically evaluates recent advances in metal oxides, carbon-based materials, metal-organic- and covalent organic frameworks, MXenes, polymers, and hybrid composites for electrochemical ZEN detection. Particular attention has been given to their roles in electron transfer, analyte enrichment, selectivity, and real-sample analysis. The review also compares the major limitations of current sensing systems, including complex fabrication, matrix interference, insufficient long-term stability, poor inter-electrode reproducibility, and limited scalability. Finally, future directions for developing robust, cost-effective, portable, and commercially viable ZEN sensors are discussed.

Journal Article↗

PubMed2026

Evaluation of one-step amplicon-based targeted enrichment for SARS-CoV-2 whole-genome sequencing using the Midnight amplicon scheme.

Genomic surveillance proved invaluable during the COVID-19 pandemic for tracking SARS-CoV-2 variants and guiding outbreak responses, underscoring the ongoing need to reduce whole-genome sequencing (WGS) costs and improve workflow efficiency to ensure accessibility in resource limited settings. Here, we evaluated a one-step reverse transcription polymerase chain reaction (RT-PCR) approach using the Midnight V2 primer scheme for targeted amplification of the SARS-CoV-2 genome, assessed its compatibility with Illumina sequencing, and compared its performance to a well-established two-step method. Initially, we determined optimal RT-PCR reaction conditions using the Midnight V2 primer panel for the one-step RT-PCR kit and scaled reaction volumes for both RT-PCR and library preparation. Clinical specimens (n = 53) that had undergone routine WGS for surveillance purposes using the established two-step RT-PCR method were compared using the one-step RT-PCR assay. For samples with genome completeness greater than 70%, both methods gave comparable results with similar sequence coverage and 100% concordance for lineage assignment. Further investigation revealed a higher percentage of reads aligning to the SARS-CoV-2 genome with a greater depth of coverage using the one-step method compared to the two-step method. Finally, analysis of scaled one-step and library reaction volumes revealed significant cost savings for samples undergoing WGS. Overall, the results presented here verify the accuracy and reproducibility of one-step targeted amplification and offer an efficient and cost-effective workflow for routine SARS-CoV-2 genomic surveillance.

Humans↗

PubMed2026

Scalable medium-density genotyping platforms for cultivar identification, pedigree authentication, marker-assisted and genomic selection, and other applications in strawberry.

A broad spectrum of high-density genotyping approaches, including single-nucleotide polymorphism (SNP) arrays, genotyping-by-sequencing, and whole-genome reduced-representation sequencing, have been shown to perform well in strawberry (Fragaria × ananassa), despite the inherent complexity of the octoploid genome. While these approaches are effective, their routine deployment in breeding programs can be constrained by cost, computational requirements, and workflow complexity. In parallel, many breeding programs continue to rely on locus-specific assays for marker-assisted selection, resulting in fragmented and inefficient genotyping strategies. Here, we describe medium-density amplicon-based genotyping platforms for strawberry designed to provide cost-effective, turnkey solutions that integrate markers used for marker-assisted selection with genome-wide markers suitable for genomic prediction in a single laboratory assay. These platforms were developed by targeting 1,650 or 4,811 target SNPs via amplicon sequencing, and are interoperable with existing high-density genotyping resources, including a widely used 50K SNP array, thereby facilitating data integration across platforms. We benchmarked their performance relative to the 50K SNP array across breeding-relevant applications, including identity and purity testing, pedigree authentication, marker-assisted selection, and genomic selection, and further evaluated the feasibility of genotype imputation to enhance genome-wide information content. Across analyses, the 1,650- and 4,811-amplicon platforms produced results comparable to higher-density platforms while substantially reducing genotyping cost and analytical overhead. This work demonstrates that targeted amplicon-based genotyping can support efficient, scalable, and integrated genome-informed breeding, enabling the routine application of both marker-assisted and genomic selection within strawberry breeding workflows. Open-source R workflows are provided to support streamlined analyses in breeding contexts.

Fragaria↗

PubMed2026

Enhancing Hemoglobin Bart's hydrops fetalis syndrome prevention: a single-tube multiplex real-time PCR assay for the comprehensive detection of four significant α0-thalassemia deletions (--SEA, --THAI, --CR, and --SA) found in Thailand.

BACKGROUND: Hemoglobin (Hb) Bart's hydrops fetalis is a major public health concern in Southeast Asia, particularly in Thailand. Current screening strategies target the two most common α0 -thalassemia deletions (--SEA and --THAI). METHOD: In this study, we developed a single-tube multiplex real-time PCR assay for the simultaneous detection of four clinically relevant α0-thalassemia deletions (--SEA, --THAI, --CR, and --SA). The assay was validated using 538 clinical samples with diverse thalassemia genotypes and compared against conventional gap-PCR as the reference method. Analytical performance, including sensitivity, specificity, and limit of detection (LOD), was evaluated. In addition, clinical utility was assessed in 22 prenatal diagnosis cases at risk of Hb Bart's hydrops fetalis. RESULTS: The study cohort demonstrated substantial genetic heterogeneity, comprising 43 distinct genotypes. The developed assay achieved 100% sensitivity and specificity for all targeted deletions, with complete concordance with gap-PCR results. No cross-reactivity was observed with α+-thalassemia. The assay demonstrated a high analytical sensitivity with a LOD of 9.76 × 10-3 ng per reaction. Whereas in prenatal diagnosis, all 22 fetal genotypes were accurately identified, including five cases of homozygous --SEA and one rare compound heterozygous --SEA/--CR fetus. CONCLUSIONS: This study presents a rapid, accurate, and cost-effective multiplex real-time PCR assay capable of detecting both common and rare α0-thalassemia deletions in a single reaction. The assay demonstrates strong potential for implementation in routine clinical laboratories and large-scale population screening, contributing to improved prevention and control of severe thalassemia syndromes in high-prevalence regions.

Humans↗

PubMed2026

Research progress and application prospects of multi-omics integration strategies in precision risk stratification of type 1 diabetes mellitus.

Type 1 diabetes (T1D) is a chronic metabolic disease mediated by autoimmunity. Its pathogenesis involves complex interactions between genetic susceptibility and environmental factors. Conventional T1D risk stratification primarily relies on genetic markers, islet autoantibodies, and glycemic indicators. Although these biomarkers remain indispensable in current clinical practice, they are often insufficient when used alone to accurately identify ultra-early high-risk individuals, predict disease progression rates, or support individualized preventive strategies. Consequently, more comprehensive molecular approaches are needed to improve precision risk stratification. In recent years, the rapid development of multi-omics technologies has provided new strategies for precise risk stratification of T1D. This narrative review critically evaluates how multi-omics integration strategies can improve precision risk stratification throughout the T1D disease continuum by integrating complementary molecular information from genomics, transcriptomics, proteomics, metabolomics, epigenomics, and the microbiome. Particular emphasis is placed on stage-specific biomarker discovery, multi-omics data integration frameworks, artificial intelligence-assisted prediction models, biomarker validation, and the opportunities and challenges associated with clinical translation. Current evidence suggests that integrated multi-omics approaches have the potential to improve risk prediction accuracy, distinguish heterogeneous disease trajectories, identify individuals at imminent risk of progression, and provide biologically informed targets for precision intervention. However, important challenges remain, including data harmonization, external validation, model interpretability, cost-effectiveness, and integration into routine clinical screening programs. Future research should prioritize prospective multicenter cohorts, standardized analytical pipelines, externally validated prediction models, and clinically interpretable multi-omics frameworks to facilitate the translation of precision risk stratification into routine T1D prevention and management.

Humans↗

PubMed2026

Standardized Xenograft Models for Preclinical Cancer Research.

Xenograft models are the principal in vivo platform of preclinical oncology and the most established experimental link between cell culture and clinical investigation. From the carcinogen-exposed rabbit models of the early twentieth century through the current generation of humanized patient-derived xenograft (PDX) systems, these platforms have evolved in response to the demands of translational cancer research. This review critically examines the biological principles, methodological standards, and translational applications of the principal xenograft platforms in current use. Cell line-derived xenograft (CDX) models remain the most widely used and most cost-effective modality for preclinical efficacy testing, offering the reproducibility, scalability, and accessibility that have sustained their role across oncology drug development pipelines for decades. PDX models have emerged as the preferred platform for co-clinical trial design, predictive biomarker discovery, and personalized oncology applications, preserving the genomic landscape, intratumor heterogeneity, and histological architecture of the donor tumor across serial passages. The engraftment biology of PDX systems, including immunodeficient host strain selection, implantation site, tumor source, and passage biology, is reviewed, together with humanized and autologous humanized configurations that extend the platform to immune checkpoint inhibitors, bispecific T-cell engagers, and chimeric antigen receptor T (CAR-T) cell therapy evaluation. This review addresses preclinical-to-clinical translation as a function of immunological divergence, incomplete tumor microenvironment recapitulation, and standardization. Formal frameworks, including the PDX Model Minimal Information (PDX-MI) standard and the Minimal Information for Standardization of Humanized Mice (MISHUM), are examined alongside global biobank infrastructure and emerging AI-driven translational modeling approaches.

Animals↗

PubMed2026

Integrating GWAS and Transcriptome Analysis Identifies Candidate Genes for Kernel Starch Quality Traits in Maize.

Maize (Zea mays L.) starch quality is a complex trait with significant implications for grain processing and industrial applications. However, the genetic basis underlying starch quality, particularly for gelatinization and thermodynamic properties, remains poorly understood. In this study, we evaluated 12 starch quality traits, including seven gelatinization characteristics, four thermodynamic traits, and kernel starch content (KSC) in a diverse panel of 335 maize inbred lines. Considerable phenotypic variation was observed for all traits. A total of 228 quantitative trait loci (QTLs) were significantly associated with 12 starch quality traits through genome-wide association studies (GWAS). By integrating a dynamic transcriptome analysis of two maize inbred lines with contrasting starch quality, we identified 60 candidate genes. One gene, waxy1, encoding a starch synthase, was found to be associated with enthalpy of gelatinization (ΔHgel) and pasting temperature (Ptemp). Six variants in waxy1 contributed to natural variation in ΔHgel and Ptemp, and a cost-effective InDel and two PARMS-based molecular markers were developed and validated in 144 maize inbred lines, enabling efficient marker-assisted selection. Our findings provide key genes and molecular markers for high-quality maize breeding with improved starch properties.

Zea mays↗

PubMed2026

Holistic approaches for improvement of maize resistance against lodging stress: current status and future perspective.

Lodging is a major constraint in maize production, causing significant yield losses, reduced grain quality, and harvesting inefficiencies, thereby posing a serious challenge to global food security and climate-resilient agriculture. This review synthesizes current knowledge on the genetic, physiological, and agronomic determinants of maize lodging resistance and evaluates holistic strategies for improving tolerance to lodging stress. Recent advances in quantitative trait locus (QTL) mapping, genome-wide association studies (GWAS), functional gene characterization, genome editing, high-throughput phenotyping, and precision agronomy have provided powerful tools to enhance stalk biomechanics, root anchorage, and adaptive plant architecture. Integrating genomic discovery with advanced phenomics and optimized agronomic management offers a scalable framework for accelerating the development of high-yielding, lodging-resilient maize cultivars. However, critical gaps remain in understanding the genetic coordination between stalk strength and root system architecture, integrating multi-omics approaches to unravel regulatory networks, validating genome-editing interventions across diverse agro-ecologies, and developing environment-responsive predictive breeding models and cost-effective phenotyping tools, particularly for stress-prone regions. Addressing these challenges through coordinated multi-environment trials and integrative molecular-agronomic strategies will facilitate the translation of genomic discoveries into climate-resilient, high-performing maize cultivars. By consolidating molecular insights with applied breeding and management practices, this review provides a comprehensive framework that guides researchers in designing genome-informed and field-validated approaches to improve maize resistance to lodging stress and support sustainable crop production systems.

Zea mays↗

PubMed2026

Machine learning for population-level risk prediction of future cholangiocarcinoma.

BACKGROUND: The poor prognosis of cholangiocarcinoma (CCA) is largely driven by rapid, asymptomatic disease progression, which usually results in a late diagnosis in the absence of established screening strategies. An early, cost-effective, and universally applicable risk assessment strategy would therefore be valuable. METHODS: We developed machine learning (ML) models on prospective, multimodal data from 487,495 UK Biobank (UKB) participants, of whom 649 developed CCA during follow-up. Data from England (80%) were utilised for ML development via five-fold cross-validation, and then all models were tested on withheld data from Scotland, Wales, and Newcastle (20%). Iterative ablation studies reduced inputs from >150 features across demographic data, lifestyle, health records, blood parameters, genomics, and metabolomics to models built on five and ten routinely available clinical parameters. These were externally validated in the Penn Medicine Biobank (PMBB; n = 2638; 28 CCA), All of Us Research Program (AOU; n = 330,433; 362 CCA), Japan Medical Data Centre Claims Database (JMDC; n = 8,425,522; 723 CCA) and TriNetX (n = 728,886; 1592 CCA). FINDINGS: We show that ML models integrating biliary-disease associated health records and Gamma glutamyltransferase can stratify risk of future CCA. Evaluation on the UKB test set as well as three independent cohorts revealed robust performance and generalisability across ethnicities. We achieved AUROCs of 0.71 [95% CI: 0.703-0.711], 0.77 [95% CI: 0.764-0.778 ], 0.796 [95% CI: 0.795-0.798] and 0.8 [95% CI: 0.794-0.805] for UKB, PMBB, AOU, and JMDC respectively, with respective AUPRCs of 0.014 [95% CI: 0.009-0.018], 0.042 [95% CI: 0.037-0.048], 0.038 [95% CI: 0.033-0.042] and 0.001 [95% CI: 0.001-0.001]. In AOU, application of the Youden J-optimised threshold yielded a number needed to screen of 79. Separate models for intra- and extrahepatic CCA did not improve performance. In line with the pathophysiology, performance declined for longer intervals between assessment and event. A group-level analysis in the TriNetX cohort revealed hazard ratios of up to 82.5 [95% CI: 26.4-257.96]. We provide extensive interpretability results and release all source codes used to develop the presented models. INTERPRETATION: We provide a comprehensive framework for early CCA risk stratification in the general population, identifying key predictors, and demonstrating the potential of data-driven models in personalised screening for hepatobiliary cancer. FUNDING: German Cancer Aid (grant #70115730), Junior Principal Investigator Fellowship programme of RWTH Aachen Excellence strategy.

Humans↗

PubMed2026

Artificial intelligence-assisted histopathological diagnosis of endocervical gastric-type adenocarcinoma: a multicenter model development and validation study.

Endocervical gastric-type adenocarcinoma (GAS) is one of the most aggressive subtypes of cervical cancer and is frequently underdiagnosed due to morphological ambiguity, leading to delayed diagnosis. Despite the availability of molecular and genomic assays, their high cost, complexity, and limited reproducibility restrict clinical use. This study therefore proposes a highly sensitive artificial intelligence (AI)-assisted diagnostic system for GAS based exclusively on H&E-stained histopathological images. We included 309 slides from 96 GAS cases collected at Peking University Third Hospital from January 2018 to January 2025, representing the largest GAS cohort reported to date for AI research. In addition, we incorporated other morphologically analogous diseases, encompassing a total of 1,320 slides sourced from four categories: normal cervical mucosa (NORM), benign endocervical lesion entities (BELE), HPV-associated adenocarcinoma (HPVA), and endometrioid carcinoma with mucinous differentiation (ECMD). We developed GASPath, based on a novel multiple instance learning framework that efficiently captures fine-grained morphological variations from H&E-stained images. Beyond internal validation, GASPath was evaluated across 12 independent retrospective cohorts and further subjected to large-scale real-world validation on more than 7,000 samples from March 2024 to April 2025. Across three stages, GASPath demonstrated high performance. In internal validation (Stage I), it achieved an accuracy of 0.980 (95% CI 0.977-0.983) and an ROC-AUC of 0.995 (95% CI 0.994-0.997). In external validation (Stage II), the sensitivity reached 0.902 and improved to 0.968 with proposed strategies. For biopsy samples, GASPath achieved an ROC-AUC of 0.990 (95% CI 0.984-0.997). In large-scale real-world deployment (Stage III, n = 7,056), GASPath achieved a balanced accuracy of 0.953, with 100% sensitivity for GAS (45/45 cases correctly identified). The heatmaps highlight morphological features of GAS that are easily underestimated, such as irregular, angulated glands, subtle loss of nuclear polarity, and mild cytologic atypia, which show substantial morphological overlap with other diagnostic categories. GASPath enables high-sensitivity detection of GAS in routine H&E-stained slides, obviating the need for extensive auxiliary testing while preventing underdiagnosis and misdiagnosis. This advancement addresses a critical gap by streamlining diagnostic workflows without compromising accuracy. Its implementation could enable cost-effective, scalable AI-assisted diagnostics, potentially transforming the early detection and management of this aggressive cancer subtype.

Female↗

PubMed2026

Influence of endodontic access on the fracture resistance, retention and microleakage of full-coverage restorations in vitro: A systematic review and meta-analysis.

BACKGROUND: Endodontic access through retained full-coverage restorations (FCRs) is a preferred option for patients because of its high cost-effectiveness. However, the clinical performance of FCRs after repaired access cavity remains insufficiently characterized. This systematic review investigates the effects of endodontic access cavity preparation through retained FCRs on fracture resistance, retention, and microleakage based on in vitro studies. METHODS: A comprehensive search was performed in PubMed, Web of Science, and Scopus databases. Studies investigating the influence of endodontic access on the fracture resistance, retention, and microleakage of FCRs were included. Two independent reviewers conducted study selection, data extraction, and risk-of-bias assessment using the QUIN tool. Meta-analysis was employed to estimate fracture resistance and retention, with sensitivity analysis and subgroup evaluation also performed. Microleakage was summarized qualitatively. RESULTS: Twentythree studies were included: fracture resistance (n = 15), retention (n = 5), and microleakage (n = 3). Endodontic access significantly reduced fracture resistance for zirconia (p = 0.0002) and lithium disilicate (LD) restorations (p = 0.007), but not for resin-matrix ceramic (RMC) restorations (p = 0.25). Abutment tooth type contributed to heterogeneity within the LD and RMC subgroups. Retention was significantly reduced when access cavities were left unrepaired (p = 0.03), whereas appropriate repair protocols restored or enhanced retention relative to baseline. Accelerated aging increased microleakage in retained FCRs. Surface pretreatments and flowable resin liners tended to reduce microleakage, but findings were inconsistent. CONCLUSIONS: Endodontic access significantly reduces fracture resistance of zirconia and LD FCRs, whereas RMC restorations show no significant change. Appropriate repair protocols can restore or improve retention, potentially exceeding original values. Limited evidence suggests that effective sealing is achievable with appropriate materials. However, well-designed and in-vivo researches are needed to provide more detailed clinical guidance. CLINICAL SIGNIFICANCE: When performing endodontic access through retained FCRs, reduced fracture resistance must be carefully considered for zirconia and LD restorations, while RMC restorations may be exempt from this concern. Loss of retention with access can be restored after repair. Surface pretreatment and flowable resin liners help decrease microleakage.

Humans↗

PubMed2026

Performance comparison of rapid and native barcoding methods for Oxford Nanopore sequencing of Poliovirus Viral Protein 1 (VP1) amplicons.

Accurate and timely sequencing of poliovirus is critical for global eradication efforts, particularly for molecular epidemiology based on the typing region of the genome, viral protein 1 (VP1). While Oxford Nanopore Technologies (ONT) sequencing has expanded capabilities for poliovirus surveillance, the relative performance of different ONT library preparation methods, including ligation-based (Native Barcoding) and transposase-based (Rapid Barcoding) approaches, has not been systematically evaluated. In this study, we compared rapid barcoding and native barcoding workflows for sequencing VP1 amplicons from 17 type 2 poliovirus-positive samples, each processed in triplicate. Native barcoding generated significantly more sequencing output, producing approximately 2.3-fold greater total read yield than rapid barcoding, and demonstrated higher run-to-run reproducibility (R2 = 0.979-0.998 vs. 0.847-0.929, respectively; p < 0.001). In addition, native barcoding generated 80% of the total yield achieved by rapid barcoding within approximately 7 h, whereas rapid barcoding required approximately 40 h to reach the same output. Despite these differences, both methods produced identical VP1 consensus sequences across all samples, with comparable read quality (median per-base Q-scores of approximately Q17-Q18). Rapid barcoding provided substantial practical advantages, reducing hands-on library preparation time (55 vs. 200 min) and per-sample cost ($12.82 vs. $16.54), while simplifying workflow and reducing technical complexity. These findings indicate that sequencing yield may not be a determinant of downstream analytical outcomes for poliovirus VP1 ONT sequencing. Rapid barcoding therefore represents a cost-effective and efficient approach for routine poliovirus surveillance, whereas native barcoding remains advantageous in applications requiring rapid data generation or maximal sequencing depth.

Poliovirus↗

PubMed2026

Conference report: the third Bacterial Genome Sequencing Pan-European Network conference.

The third Bacterial Genome Sequencing Pan-European Network conference, held in Engelberg, Switzerland (12-15 January 2026), brought together experts from six European countries to discuss the implementation of bacterial genome sequencing in clinical microbiology and public health. Key themes included regulatory frameworks (In Vitro Diagnostic Regulation, General Data Protection Regulation), standardization, quality control, data sharing, economic evaluation, and the integration of artificial intelligence and long-read sequencing into diagnostic workflows. Across presentations, panel discussions, and workshops, participants emphasized that successful implementation of genome sequencing requires more than technical capacity: it depends on robust validation, sustainable funding, interoperable data standards, ethical governance, and interdisciplinary collaboration. The meeting highlighted that sequencing should remain question-driven and clinically meaningful, balancing cost, turnaround time, and public health impact. Overall, the conference reinforced the need for coordinated European efforts to advance responsible, standardized, and sustainable genomic surveillance and diagnostics.

bacterial genome sequencing↗

PubMed2026

MIS-TLIF Versus Open TLIF in Combined Lumbar Stenosis and Low-Grade Spondylolisthesis : Of Discharge Timing and Treatment Pricing.

STUDY DESIGN: An open-label, randomized, noninferiority clinical trial. OBJECTIVE: To determine the effectiveness of the MIS-TLIF over the O-TLIF in patients with symptomatic lumbar stenosis combined with low-grade spondylolisthesis by comparing the clinical efficacy and safety. SUMMARY OF BACKGROUND DATA: In patients with combined lumbar spinal stenosis and spondylolisthesis, it remains uncertain whether minimally invasive fusion surgery is noninferior to the open approach. MATERIALS AND METHODS: We conducted an open-label, noninferiority trial involving patients with symptomatic lumbar stenosis combined with low-grade spondylolisthesis. Patients were randomly assigned in a 1:1 ratio to undergo either MIS-TLIF or open TLIF surgery. The primary endpoint was the reduction in the Oswestry disability index (ODI) score from baseline to three months postsurgery, with a noninferiority margin of 12 points. Secondary outcomes included three-month changes from baseline in back and leg pain, neuropathic pain, satisfaction with treatment, intraoperative data, and cost-effectiveness. RESULTS: In the modified intention-to-treat population, the mean difference was 0.4, with the corresponding 90% CI of -5.7 to 6.5, having a lower bound below the noninferiority margin of 12. Similar results were obtained by analysis of the per-protocol population. 82.8% of patients achieved the MCID for the ODI. Results for secondary outcomes (clinical scales, complications) showed no significant differences between the treatment groups (all P >0.05). Although the open TLIF group had a hospital stay that was 1.5 days longer ( P =0.005) and required additional analgesia more frequently ( P =0.026), direct costs were 10.5% higher in the MIS-TLIF group ( P <0.001). CONCLUSIONS: This is the first high-quality study comparing open TLIF and MIS-TLIF with a validated primary endpoint. Among patients with combined lumbar degenerative stenosis and degenerative spondylolisthesis, MIS-TLIF resulted in clinical outcomes at three months that were noninferior to those with open TLIF.

Humans↗