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This is a protocol for a Cochrane review (flexible). The objectives are as follows: To assess neonatal complications, specifically neonatal mortality and morbidities, in late-preterm and early-term infants compared to full-term newborns.
BACKGROUND: Mycoplasma genitalium (MG) is increasingly characterized by high rates of macrolide and fluoroquinolone resistance. International guidelines recommend resistance-guided therapy; however, access to genotypic testing is limited, and randomized trial evidence is lacking. We assessed the efficacy of moxifloxacin and azithromycin without resistance assays. METHODS: This monocentric, open-label, superiority, randomized controlled trial enrolled adults with MG infection detected by multiplex PCR, randomized 1:1 to receive moxifloxacin 400 mg daily for 10 days or azithromycin 500 mg daily for 6 days. A test of cure was performed ≥28 days after treatment completion. The primary endpoint was microbiological cure in the intention-to-treat (ITT) and per-protocol (PP) populations. Subgroup analyses assessed symptomatic versus asymptomatic infections, doxycycline exposure, re-treatment, and sexual behavior. RESULTS: Among 358 randomized participants, 87.0% of those treated with moxifloxacin and 61.2% of those treated with azithromycin achieved microbiological cure in the ITT analysis (absolute risk difference 25.8%, 95% CI 16.5, 35.2). The superiority of moxifloxacin was confirmed in the ITT and PP populations. Moxifloxacin remained superior across most subgroups, whereas azithromycin showed comparable efficacy only among heterosexual individuals. Doxycycline coadministration did not improve outcomes. Both regimens were well tolerated, with only one case of discontinuation. CONCLUSIONS: Moxifloxacin demonstrated superior efficacy compared to azithromycin for treating MG infection in the absence of resistance testing. These randomized data support the use of moxifloxacin as a first-line option when resistance assays are unavailable and may inform treatment strategies.
BACKGROUND: Sober Living Houses (SLHs) adopt a social model approach, which emphasizes peer helping. Although SLHs appear to be effective, little is known regarding why. This longitudinal study examined whether higher SLH social model adherence produces better resident outcomes by increasing resident helping. METHODS: Baselines were conducted with 205 residents entering 28 SLHs, with follow-ups through 6 months. Measures included 1-month perceived SLH social model adherence; 2-month help given to and received from SLH residents; and 6-month alcohol use and severity. Analyses were lagged, multivariate mediation models accounting for clustering within SLH. Separate models examined help given and received for each outcome, yielding four model tests. RESULTS: The hypothesized model was unsupported, with all four tests showing nonsignificant indirect effects. However, exploratory post-hoc tests showed significant indirect effects between higher 1-month resident helping and better 6-month alcohol outcomes via higher 1-month SLH social model adherence. Effects held across three of four model tests. CONCLUSIONS: Results suggest that residences adhering to social model principles do not achieve better outcomes by stimulating helping, but rather that more resident helping may foster a supportive SLH social environment, which itself drives better outcomes. Thus, residences might emphasize both resident helping and social model principles.
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.
BACKGROUND: Accurately distinguishing malignant pleural effusion (MPE) from non-malignant pleural effusion is clinically important, but the generalisability and methodological quality of machine-learning (ML) models remain uncertain. METHODS: We searched eight databases to 23 April 2026. Diagnostic performance was pooled using random-effects and Reitsma bivariate models, and study quality was assessed using PROBAST+AI. RESULTS: Forty-two studies were included; 17 contributed to the AUC meta-analysis and 14 to the bivariate analysis. The pooled AUC was 0.90 (95 % CI 0.85-0.94; 95 % prediction interval 0.62-0.98), with sensitivity of 0.80 (95 % CI 0.77-0.83) and specificity of 0.87 (95 % CI 0.79-0.92). Only nine studies reported external, temporal or independent validation. Externally validated studies had a lower pooled AUC than studies without external validation (0.83 vs 0.92), with lower specificity observed in the two externally validated studies contributing sensitivity and specificity data. All 42 development assessments had high overall quality concerns, and all 42 model evaluations were judged at high risk of bias. CONCLUSIONS: ML models showed good apparent accuracy for distinguishing MPE from non-MPE, but the evidence was limited by substantial heterogeneity, high risk of bias and scarce external validation. The pooled estimates reflect the average performance of different selected models rather than the expected accuracy of a single clinical test. ML models should be regarded as adjuncts to existing diagnostic pathways until they are confirmed by rigorous multicentre prospective external validation and clinical-impact studies.
INTRODUCTION: Latinos face increased Alzheimer's disease (AD) risk but are underrepresented in studies of APOE genotype disclosure. We evaluated the psychological impacts of APOE disclosure in the Información de la Enfermedad de Alzheimer para Latinos (IDEAL) study, a randomized controlled trial among Latinos in New York City. METHODS: Latino northern Manhattan residents without self-reported AD (mean age 52, 69% women, 49% college graduates) were randomized in the period August 2021 to July 2024 to receive AD risk estimates to age 85 incorporating APOE genotype, family history, and ethnicity (disclosure) or the same factors excluding APOE (non-disclosure). Bilingual genetic counselors delivered risk estimates to both groups, unmasked to randomization. Follow-up surveys were completed 6 weeks, 9 months, and 15 months after risk delivery. Primary outcomes were impact of genetic testing in AD (IGT-AD) and Impact of Event Scale-Revised (IES-R). Secondary outcomes were changes from baseline in depression, anxiety, and perceived AD threat. Analyses used intention-to-treat with multiple imputation. RESULTS: Disclosure (N = 194) and non-disclosure (N = 180) groups did not differ on IGT-AD (mean disclosure-non-disclosure difference [MD] at 6 weeks: -1.5, p = 0.14; 9 months: -1.2, p = 0.35; 15 months: -2.0, p = 0.07), IES-R (MD at 6 weeks: 0.00, p = 0.98; 9 months: 0.01, p = 0.84; 15 months: 0.03, p = 0.64), or change in secondary outcomes. Occurrence of disclosure-related adverse events was similar in the disclosure (N = 2) and non-disclosure (N = 3) groups. DISCUSSION: In this Latino cohort, APOE disclosure did not have clinically significant adverse psychological effects, addressing an important evidence gap. TRIAL REGISTRATION: ClinicalTrials.gov NCT04471779.
Feline obesity is an increasingly important health problem influenced by both genetic predisposition and husbandry practices. This study investigated the prevalence and phenotypic relevance of the feline proopiomelanocortin (POMC) c.28G > C (p.Gly10Arg) variant in a Vietnamese cat population and evaluated environmental factors associated with obesity. A total of 63 clinically healthy cats were classified as normal weight (body condition score [BCS] 5-6/9; n = 40) or obese (BCS ≥7/9; n = 23). Genotyping was performed using a newly developed PCR-restriction fragment length polymorphism assay and validated by Sanger sequencing. Ventral subcutaneous adipose tissue (VSAT) thickness was measured ultrasonographically as an objective indicator of adiposity. Genotyping revealed a high prevalence of the risk-associated C allele, with 45/63 cats (71.4%) carrying the GC genotype and 18/63 (28.6%) carrying the CC genotype, whereas the GG genotype was not detected, giving a Callele frequency of 64.3%. Obese cats had significantly greater body weight and VSAT thickness than normal-weight cats. Neuter status and ad libitum feeding were significantly associated with obesity, whereas diet type, housing, exercise frequency, and begging behavior were not. Although genotype distribution did not differ significantly between normal and obese cohorts, obese CC cats showed significantly greater VSAT thickness than obese GC cats, indicating an allele-dosage effect on adiposity. These findings suggest that the POMC c.28G > C variant is a useful risk-informative marker and that combining genetic screening with objective fat assessment may support earlier identification and prevention of feline obesity in Vietnam under routine laboratory conditions and guide personalized management strategies in practice.
BACKGROUND: Long-acting injectable cabotegravir plus rilpivirine (LA CAB+RPV) is approved for virally suppressed people with human immunodeficiency virus (HIV), but evidence for its use in those with persistent viremia and adherence challenges remains limited. METHODS: We conducted a multicenter, open-label, randomized study involving oral antiretroviral therapy (ART)-experienced people with HIV who had been diagnosed with HIV for at least 12 months and a most recent HIV-1 RNA level of at least 200 copies per milliliter. Participants with resistance-associated mutations to CAB or RPV were excluded. Eligible participants were randomly assigned in a 1:1 ratio to receive immediate LA CAB+RPV or to continue standard oral therapy until Week 24 (delayed switch group). The primary endpoint was the proportion of participants with an HIV-1 RNA level of less than 200 copies per milliliter at Week 24. RESULTS: Of 61 randomized participants, 45 met eligibility criteria and were included in the analysis; 91% were male, and the median baseline HIV-1 RNA was 35,000 copies/mL. At Week 24, viral suppression was achieved in 88.0% (22/25) in the immediate LA group versus 55.0% (11/20) in the delayed switch group (relative risk for failure to achieve viral suppression, 0.27; 95% CI, 0.08-0.86; p = 0.026). The effect of LA CAB+RPV was sustained through Week 52. CONCLUSIONS: Among people with HIV and viremia associated with adherence challenges, immediate initiation of LA CAB+RPV resulted in higher rates of viral suppression than continued oral ART, supporting its use beyond populations with stable suppression.
Predicting peak microbial pollution events in downstream coastal bathing waters caused by combined sewer overflows (CSOs) is essential for protecting public health. In urban areas, wastewater effluents, CSOs, and surface runoff can contribute to elevated microorganism loads to downstream waters. These pressures are likely to be intensified by growing population density and more frequent heavy rainfalls due to climate change. This study developed a process-based model to simulate Escherichia coli (E. coli) emissions, transport, and fate from the initial sources to coastal beaches. A three-year retrospective simulation (2017-2019) shows that E. coli concentrations in CSO discharges varied widely across the catchment (4.6 - 7.3 (log10 CFU 100 ml-1)). 99th percentile E. coli concentrations (4.0 (log10 CFU 100 ml-1)) at the inland water outlet were dominated by local CSO emissions, whereas 90th percentile E. coli concentrations (3.6 (log10 CFU 100 ml-1)) reflected cumulative upstream contributions from both CSO and effluent emissions. With the simulation accuracy of 89%, the model reliably reproduced the E. coli dynamics on the downstream beach and showed strong performance in representing peak concentrations based on Complementary Cumulative Distribution Function (CCDF) analysis. The process-based model enables quantitative tracking of source contributions and identification of pollution hotspots, providing support for mitigation measures. The study lays down a source-to-sea modelling framework for representing pollution transport across the aquatic continuum and provides a transferable tool for microbial pollution forecasting and climate adaptation planning.
TOPIC: This systematic review and meta-analysis evaluated the literature-pooled association between statins and dry eye disease (DED). CLINICAL RELEVANCE: Statins, a common treatment modality for dyslipidemia, have been proposed as a potential contributor to DED via their activity in meibomian gland epithelial cells. However, single studies show mixed evidence, and there remains an unmet clinical need to clarify whether statin exposure is associated with DED. METHODS: This review was reported in accordance with the Preferred Reporting Items for Systematic Reviews of Interventions (PRISMA) 2020 statement and was registered a priori on PROSPERO (CRD420251238004). Ovid MEDLINE, Embase, CINAHL, Web of Science, CENTRAL, and the reference lists of relevant reviews were searched from inception to November 2025 for studies reporting the association between statin use and DED. Random-effects meta-analysis using inverse-variance weighting was conducted to pool effect estimates as odds ratios with 95% confidence intervals (CIs). Study risk of bias was appraised using the ROBINS-E tool, and the certainty of the evidence was reported using the GRADE framework. RESULTS: Six observational studies were included in the meta-analysis (n = 560,821; 356,012/559,141 [63.7%] statin users). The pooled analysis revealed a significant positive association between statins and DED (odds ratio 1.09, 95% CI 1.05-1.13, P < .001), with an absolute risk difference of 10.2 more DED cases per 1000 (95% CI 5.5 more to 15.2 more). This result was derived from very low-certainty evidence given limitations in study design and serious inconsistency. Subgroup and sensitivity analyses for risk of bias (P = .123), method of outcome ascertainment (P = .737), type of effect estimate (P = .496), and leave-one-out analyses showed no evidence of effect modification and demonstrated consistent direction of association across studies. CONCLUSION: Statin use was associated with a small but statistically significant increase in DED, limited by very low-certainty evidence. Physicians should monitor for and educate patients on ocular surface symptoms in patients using statins with pre-existing DED risk factors. Future studies should use standardized DED diagnostic criteria to investigate the impact of statin dose, type, and duration to better characterize this potential association.
BACKGROUND AND PURPOSE: Robust optimisation offers an alternative to conventional margin-based photon radiotherapy planning by explicitly modelling uncertainty, but practice is variable and not standardised. MATERIALS AND METHODS: A scoping review was conducted to map robust optimisation for photon external beam radiotherapy. Electronic searches of Scopus, PubMed and Google Scholar (2000-2025, English language) identified planning studies that incorporated modelled uncertainties into the optimisation process and reported at least one robustness-related outcome. Data were charted on clinical context, uncertainty models, optimisation paradigms, robustness metrics and evidence for clinical implementation. RESULTS: Seventy-one studies were included. Most investigated prostate, breast or lung cancer and used intensity-modulated radiotherapy or volumetric-modulated arc therapy in commercial or research treatment planning systems. Scenario-based worst-case (minimax) optimisation was the dominant paradigm in clinically oriented work, while chance-constrained, conditional value at-risk, distributionally robust and adaptive formulations were confined to small methodological series. Uncertainty modelling focused mainly on rigid set-up error; fewer studies incorporated respiratory motion, inter-fraction anatomical change, dose-calculation uncertainty or biological variation. Robustness was evaluated with diverse scenario-based dose-volume metrics, probabilistic coverage measures, composite robustness indices and, less often, biological endpoints. Direct clinical implementation reports were scarce. CONCLUSION: Robust photon planning is technically feasible and generally maintains or improves target coverage and organ sparing compared with margin-based planning. However, heterogeneity in uncertainty models, optimisation configuration and robustness reporting limits comparison and synthesis. Pragmatic minimum standards are proposed to support future consensus and wider clinical adoption.
BackgroundIndividuals with type 2 diabetes mellitus (T2DM) face increased risk of cognitive decline and dementia. Multidomain lifestyle interventions offer a non-pharmacological strategy to support brain health in this high-risk group.ObjectiveThis study examined the acceptability of a culturally adapted FINGER-based intervention among adults living with T2DM in rural border regions of Ireland (BRAIN-Diabetes Trial).MethodsA 6-month pilot randomized controlled trial was conducted. The intervention group received a multidomain program targeting diet, physical activity, and computerized cognitive training (CCT). The control group received standard care. Acceptability was assessed using questionnaires (all participants) and semi-structured interviews (intervention participants). Quantitative data were analyzed descriptively and qualitative data using template analysis, guided by four a-priori themes: trial participation and engagement, dietary behavior change, exercise behavior change, and CCT behavior change.ResultsQuestionnaire data (intervention: n = 28; control: n = 36) indicated high overall acceptability. Dietary and exercise components were rated most positively, while CCT component was less well received. Interviews (n = 25) highlighted facilitators to trial engagement, including perceived health improvements, and social connection, with time constraints and limited personalization as barriers. Dietary change was supported by tailored guidance but hindered by cost and availability. Facilitators for exercise included accessible resources and perceived benefits, with barriers including competing priorities. CCT engagement was mixed, with challenges including digital access and repetitiveness.ConclusionsThe Brain-Diabetes intervention was acceptable and feasible among adults with T2DM. Personalized support and accessible resources were key to engagement. Future work should refine delivery to enhance scalability and long-term adherence among high-risk groups.
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by the progressive loss of motor neurons, with most cases lacking a clear genetic basis. Emerging evidence highlights the involvement of non-coding RNAs, particularly circular RNAs (circRNAs), in disease onset and progression. Here, we investigated circRNAs implicated in ALS and related motor neuron diseases (MNDs). Here, we provide a general overview of circular RNA metabolism and cellular functions. We then present our systematic literature review that identified ALS-associated circRNAs, followed by in silico analyses of 15 circular RNA candidates that were selected based on the most compelling data regarding ALS. Our results revealed that several circular RNAs regulate ALS-related genes, such as unfolded protein response, oxidative stress, cell cycle regulation, and apoptosis. Protein-RNA interaction analysis further showed that ALS-related circRNAs can sponge 20 RNA-binding proteins. Additionally, molecular docking analysis demonstrated that ALS-associated FUS variants significantly alter its binding affinity to circular RNAs. RNA-seq data from ALS patients confirmed significant alterations in the expression of host genes of ALS-related circRNAs and hub proteins in ALS-affected CNS tissues. Collectively, our findings identify circRNAs as potential key contributors to ALS pathogenesis.
Soil pollution poses significant risks to ecosystems and human health, necessitating accurate source identification and apportionment to guide mitigation strategies. This systematic review evaluates the application of Positive Matrix Factorization (PMF) and other receptor models in soil pollution studies, focusing on analytical procedures, tracer indicators, and environmental applications. This review aims to provide a comprehensive framework for conducting soil source apportionment studies, aiding policymakers in designing effective, region-specific environmental management strategies by compiling global trends and methodological insights. The study addresses sampling protocols, emphasizing representativeness and quality control. Data from 500 peer-reviewed publications highlight the dominance of research in China, Eastern Europe, and South Asia, with agricultural soils being the most frequently studied. Key findings reveal that traffic emissions (20.8 %) and industrial activities (19.4 %) are the primary global contributors to soil contamination, with regional variations such as coal combustion in cold climates and agricultural inputs in developing regions. Policy recommendations include stricter industrial regulations, sustainable agricultural practices, and targeted remediation efforts based on source-specific risks.
INTRODUCTION: Risk prediction models for gestational diabetes mellitus (GDM) offer potential for early identification and targeted prevention. External validation is crucial to assess model performance across diverse populations. Despite the availability of numerous GDM prediction models, limited evidence exists on their external validation frequency, methodological quality, and clinical applicability. This systematic review evaluated externally validated GDM prediction models, focusing on methodological rigor, reporting standards, and clinical relevance to inform future research and implementation. MATERIAL AND METHODS: Databases including Ovid MEDLINE, Embase, Scopus, Emcare, and CINAHL were searched up to May 1, 2025. Studies reporting external validation of GDM risk prediction models were included. Two reviewers independently screened studies. Data were extracted using the CHARMS framework, and risk of bias and applicability were assessed using PROBAST+AI. The study protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO; CRD420251125758). RESULTS: Twenty-six studies validated 33 models, with validation sample sizes ranging from 50 to 75 161. Over half used the IADPSG criteria to define GDM. Discrimination metrics were commonly reported, but calibration, overall performance, and clinical utility were often lacking. Meta-analysis was feasible for only four models: Teede et al., Nanda et al., Naylor et al., and Van Leeuwen et al., each showing fair discrimination. The Teede et al. model was the most widely validated, with 11 external validations across six continents and a pooled AUC of 0.72 (95% CI: 0.67-0.76). Despite fewer validations, the Nanda et al. model achieved the highest pooled discrimination (5 validations; pooled AUC 0.77, 95% CI: 0.74-0.80). The Naylor et al. and van Leeuwen et al. models also underwent meta-analysis, as sufficient external validation studies were available to support comparative performance assessment. Notably, 69.23% of studies had a high risk of bias. CONCLUSIONS: While many models showed acceptable predictive performance, most validations were methodologically weak. Future studies should follow best-practice guidelines and promote scalable validation strategies, such as algorithm sharing, to enhance clinical utility.
AIMS: To compare the efficacy and safety of insulin glargine 100 U/mL plus lixisenatide (iGlarLixi) with insulin degludec plus insulin aspart (IDegAsp) by baseline age, Type 2 diabetes (T2D) duration and glycated haemoglobin (HbA1c) in the Soli-D study. MATERIALS AND METHODS: In Soli-D, Chinese adults with T2D suboptimally controlled on oral antidiabetic drugs (OADs) were randomized to iGlarLixi or IDegAsp for 24 weeks. These post hoc analyses evaluated glycaemic efficacy, insulin dose, body weight and hypoglycaemia outcomes in subgroups defined by baseline age (< 65, ≥ 65 years), T2D duration (< 10, ≥ 10 years) and HbA1c (≥ 7% to ≤ 8% [≥ 53 to ≤ 64 mmol/mol], > 8% to ≤ 9% [> 64 to ≤ 75 mmol/mol], > 9% [> 75 mmol/mol]). RESULTS: Among 582 participants (iGlarLixi n = 291; IDegAsp n = 291), baseline age was < 65 years in 442 and ≥ 65 years in 140; T2D duration was < 10 years in 366 and ≥ 10 years in 216; and HbA1c was ≥ 7% to ≤ 8% in 205, > 8% to ≤ 9% in 209 and > 9% in 168. At Week 24, HbA1c reductions were greater with iGlarLixi versus IDegAsp, with no treatment-by-subgroup interactions for baseline age, T2D duration or HbA1c. Change in other glycaemic outcomes, insulin dose and body weight generally showed no interaction across subgroups. Total insulin daily doses during treatment and hypoglycaemia event rates were consistently lower with iGlarLixi versus IDegAsp in all subgroups. CONCLUSIONS: iGlarLixi provides improved glycaemic control at lower insulin doses with reduced risk of hypoglycaemia in Chinese adults with suboptimally controlled T2D on OADs, regardless of baseline age, disease duration or HbA1c.
Tumor necrosis factor (TNF) is rapidly induced after ischemic stroke, but its proposed cell-specific and sex-dependent functions during post-stroke inflammation remain insufficiently understood. Here, we investigated the role of microglia-derived TNF in the acute and subacute response to permanent middle cerebral artery occlusion (pMCAO). Tnf expression was transiently upregulated after stroke, becoming significant at 4 h, peaking at 12-24 h, and returning to baseline by 5 days. In situ hybridization confirmed strong Tnf expression in the infarct and peri-infarct regions. Whole-brain transcriptomic profiling showed that global TNF deficiency reshaped the early post-ischemic response, shifting it from microglia-associated phagocytic and wound-healing pathways toward an interferon-related inflammatory signature. To define the specific contribution of microglial TNF, we used inducible Cx3cr1CreER:Tnffl/fl mice. Microglial TNF deletion had no effect on infarct volume in males at 24 h or 5 days after pMCAO, but significantly increased infarct size in females at both time points. In both sexes, brain TNF levels peaked at 24 h and were significantly reduced in Cx3cr1CreER:Tnffl/fl mice, confirming microglia as a major source of early post-ischemic TNF. However, downstream consequences diverged by sex. At 5 days, male Cx3cr1CreER:Tnffl/fl mice showed reduced microglial reactivity and 18 kDa translocator protein (TSPO) signal, with no change in T-cell infiltration, and exhibited increased density of mature oligodendrocytes. In contrast, female Cx3cr1CreER:Tnffl/fl mice displayed enhanced microglial reactivity, increased TSPO binding, higher peri-infarct T-cell infiltration, and reduced oligodendrocyte density and myelin integrity. Together, these findings identify microglial TNF as a sex-dependent regulator of post-stroke inflammation and myelin injury.
BACKGROUND: The increasing prevalence of non-tuberculous mycobacteria pulmonary disease (NTM PD) is a burden to public health. Successful management of NTM PD critically depends on accurate species identification and reliable drug susceptibility testing to guide appropriate antibiotic therapy. Emerging molecular technologies offer rapid diagnostic solutions compared to conventional methods, but their performance varies. This study aims to provide a comprehensive evaluation of current molecular techniques for NTM identification and to present a global antibiotic resistance profile. METHODS: A systematic literature search was conducted in PubMed and Web of Science for studies published between 2005 and 2024. Studies applying molecular methods for NTM identification and resistance detection in humans were included. Data on study characteristics, diagnostic methods, sample types, sample sizes, identification sensitivity, and drug susceptibility results were extracted. Meta-analysis was performed using R with the meta4diag package. The quality of included studies was assessed using the QUADAS-2 tool. RESULTS: The analysis included 49 studies on NTM identification and 33 studies on antibiotic resistance. For species identification, all evaluated molecular technologies (MALDI-TOF MS, PCR-based methods, Sequencing, DNA chip, and DNA strip) demonstrated high pooled sensitivities (>0.92). Subgroup analysis revealed that sample type significantly affected performance for MALDI-TOF MS. Preliminary analysis of antibiotic resistance rates revealed varying patterns. For slowly growing mycobacteria, a significantly high Ethambutol resistance rate was observed in M. avium (69.20%). Among rapidly growing mycobacteria, resistance to Imipenem was notable (54.22%), and Clarithromycin resistance varied significantly within the Mycobacterium abscessus complex. CONCLUSION: Emerging molecular technologies have revolutionized the methodology for NTM identification with excellent performance. However, their performance can be influenced by sample type, particularly for MALDI-TOF MS. The alarming and heterogeneous antibiotic resistance patterns also highlight the critical need for rapid and accurate species identification and drug susceptibility testing to inform effective therapeutic strategies. Key messagesMolecular technologies demonstrate high accuracy for NTM identification.Antibiotic resistance is a serious concern with variations among NTM species and subspecies.Rapid and accurate species identification and drug susceptibility testing are crucial for guiding effective clinical management of NTM PD.