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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

From prediction to mechanism: Explainable AI uncovers plasma and CSF proteomic signatures of Alzheimer's disease.

Alzheimer's disease (AD) plasma and cerebrospinal fluid (CSF) proteomics can distinguish AD from cognitively normal controls, but the generalizability of machine learning performance and the recurrence of biological signals across datasets require cautious interpretation. We developed an explainable artificial intelligence framework spanning two fluids and four ADNI proteomic datasets, covering 2082 modality specific samples, all analysed internally within ADNI. Phase 1 analysed plasma using a 119 analyte NULISA and targeted UPENN panel (n = 727; 216 CE, 511 controls). Phase 2 extended the analysis to CSF using SOMAscan7k, TMT-MS and targeted SET2, with Elecsys Aβ42, Aβ40, total tau and p-tau181 as anchor biomarkers. Only SOMAscan was subject-independent relative to Phase 1 plasma; TMT-MS and SET2 overlapped with Phase 1 for 96.0% and 97.7% of subjects and therefore are not independent replication cohorts. Under subject-level splits with fold internal preprocessing, we compared Elastic Net, Explainable Boosting Machines and gradient boosted trees with SHAP-based explanations. Among the candidate pipelines, we selected the pipeline with the highest held-out test ROC AUC for each platform; the selected values were 0.927 in plasma and 0.954-0.973 across the three CSF datasets. Because the same held out test performance was used for pipeline selection and headline reporting, these are optimistically selected single-holdout estimates, not unbiased estimates of generalizable or clinical performance. Explanations identified five recurring biological axes within ADNI: cholinergic (ACHE), tau/14-3-3 (YWHAG, YWHAZ, YWHAB, YWHAE), neuro-axonal (NEFL, NEFH), microglial/complement (CHIT1, SMOC1, CHI3L1, C7, CFH) and synaptic (NPTXR, NPTX2, DLG4, SYT5, VSNL1, ELAVL2). CSF analyses showed synaptic vesicle-cycle enrichment (q = 2 × 10-6), and CSF YWHAG correlated strongly with total tau (ρ = 0.87). Cross-fluid directional concordance was modest overall (54-57%) but increased to 73-80% among mapped analyte/protein rows reaching q < 0.05 in CSF. These findings provide hypothesis-generating, internally supported evidence within ADNI. Independent external cohorts with locked pipelines are required to evaluate generalizable performance and biological reproducibility; the overlapping TMT-MS and SET2 analyses should not be interpreted as independent replication.

Alzheimer Disease↗

PubMed2026

Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation necrosis (RN) from true tumor progression, which conventional MRI and even advanced imaging techniques often cannot reliably resolve. Recent advances in artificial intelligence (AI) offer the potential to address these diagnostic limitations. This systematic review synthesizes current literature on AI applications for MRI-based diagnostic decision support in BM patients undergoing SRS, with a focus on radiomics and deep learning tools for distinguishing RN from progression, classifying molecular and histologic subtypes, and predicting treatment response. METHODS: A systematic review was performed in accordance with PRISMA guidelines. PubMed, Web of Science, and Scopus were searched using a targeted query combining terms related to AI, brain metastasis, diagnosis or imaging, and SRS. After screening 483 records and applying strict inclusion and exclusion criteria, 18 studies published between 2015 and 2025 were included. Data were extracted on study design, cohort characteristics, imaging modality, AI methodology, validation strategy, and reported diagnostic performance. RESULTS: Among the 18 included studies, AI models demonstrated strong performance across diagnostic tasks in the BM-SRS pathway. The differentiation of RN from true tumor progression was the most extensively studied application, addressed by 14 of 18 studies, with reported AUCs ranging from 0.71 to 0.94. Support vector machines, random-forest ensembles, convolutional neural networks, and transformer-based multimodal architectures were widely used. The literature evolved from single-sequence radiomic classifiers in 2018 to multimodal deep learning frameworks fusing imaging with clinical and genomic data in 2025. Contrast-enhanced T1-weighted MRI was the dominant imaging input, and texture-based radiomic features (GLCM, GLSZM, GLDM, and wavelet-derived features) were the most consistently predictive. The highest-performing models reached AUCs of 0.85-0.91 through multimodal integration of imaging with clinical and genomic features, and consistently outperformed expert neuroradiologist read on matched cases. Remaining studies addressed longitudinal segmentation-based detection of local failure and adverse radiation effects, BRAF mutation status in melanoma BM, early Gamma Knife treatment response, and primary tumor histology classification, with more variable performance. CONCLUSION: AI models, particularly those integrating MRI-derived radiomic features with clinical and genomic data, show high accuracy in supporting diagnostic decisions for BM patients treated with SRS. The post-SRS differentiation of radiation necrosis from true tumor progression has reached the greatest level of maturity and is closest to clinical translation, with potential to reduce unnecessary biopsies, personalize surveillance intervals, and rationalize treatment-pathway decisions. Other diagnostic applications, including molecular subtyping and primary tumor histology classification, remain exploratory and require further multicenter validation. Integration of AI tools into multidisciplinary tumor-board workflows, combined with prospective validation and standardized reporting, will be essential to realize the full clinical benefits of AI in SRS for brain metastases.

Humans↗

PubMed2026

Evaluation of three Aspergillus antibody assays for screening of chronic pulmonary aspergillosis: prospective diagnostic accuracy study.

OBJECTIVES: Chronic pulmonary aspergillosis (CPA) is a frequent complication of pulmonary tuberculosis (PTB), particularly in high-burden settings where access to reliable serological diagnostics remains limited. We evaluated the diagnostic performance of two immunochromatographic technology (ICT) lateral flow assays (LFAs) and an ELISA for CPA screening among patients with active or previously treated PTB. METHODS: In this two-year prospective multicentre diagnostic evaluation, serum from adults with prior or active PTB was tested using the Era Biology Aspergillus IgG ICT LFA, LDBio Aspergillus IgG/IgM ICT LFA, and Bordier Aspergillus fumigatus IgG ELISA. CPA diagnosis was established using a consensus composite reference standard incorporating clinical, immunological, radiological, and microbiological criteria. The Bordier ELISA was used as part of the immunological component of the consensus CPA diagnosis, with a cutoff optical density of ≥1.0. Diagnostic accuracy, agreement statistics, receiver operating characteristic analysis, and latent class analysis (LCA) were performed. RESULTS: Among 340 participants, 24 (7.06%) had CPA. Proportion of participants with positive antibody tests among all tested individuals were 6.76% for LDBio ICT LFA, 20.0% for Era Biology ICT LFA, and 11.47% for Bordier ELISA. Against consensus CPA diagnosis, Bordier ELISA showed 87.50% sensitivity and 94.30% specificity, LDBio ICT LFA 58.33% sensitivity and 97.15% specificity, and Era Biology LFA 66.67% sensitivity and 83.54% specificity. LCA estimated CPA prevalence at 7.72%. LCA-derived sensitivities and specificities were 86.58% and 99.92% for LDBio ICT LFA, 83.39% and 85.31% for Era Biology LFA, and 79.10% and 94.19% for Bordier ELISA. CONCLUSIONS: The Bordier ELISA showed high sensitivity and specificity, while the LDBio ICT LFA demonstrated very high specificity with strong LCA-derived performance. These findings support the use of ELISA for laboratory diagnosis and ICT as a point-of-care screening tool for CPA in resource-limited settings. Era Biology Aspergillus IgG LFA demonstrated moderate sensitivity and acceptable diagnostic performance, indicating its potential utility as a supplementary screening assay for CPA in settings where rapid, point-of-care testing is required.

Humans↗

PubMed2026

Diffusion MRI radiomics in meningiomas: imaging correlates of tumor grade and intraoperative consistency.

OBJECTIVE: Despite advancements in imaging studies, the preoperative prediction of the biological behavior and intraoperative consistency of intracranial meningiomas remains limited. This study evaluated the association of volumetric diffusion-based and texture-derived radiomic features extracted from routine MRI with histopathological aggressiveness and intraoperative tumor consistency. METHODS: Ninety-seven intracranial meningiomas resected at two tertiary centers were retrospectively analyzed. Volumetric segmentation was performed on contrast-enhanced T1-weighted MRI and coregistered to apparent diffusion coefficient (ADC) maps. Data on first-order diffusion metrics and selected texture features were collected. The associations between World Health Organization (WHO) grade and Ki-67 index were assessed using nonparametric tests and Spearman correlation analysis. Independent factors associated with intraoperative tumor consistency (Zada grades 1-5) were evaluated via multivariate ordinal logistic regression analysis that adjusted for tumor volume, skull base location, calcification status, and WHO grade. Secondary receiver operating characteristic (ROC) curve analyses were performed to differentiate solid (Zada grades 4-5) from soft (Zada grades 1-2) tumors. ROC analyses were performed within the study cohort and were intended as exploratory assessments of discriminative performance. RESULTS: The mean ADC (ADCmean) and the 10th percentile of the ADC decreased significantly with increasing WHO grade (p < 0.001). ADCmean had a moderate inverse correlation with the Ki-67 index (r = -0.42, p < 0.001) and intraoperative tumor consistency (r = -0.45, p < 0.001). In the multivariate analysis, the ADCmean remained independently associated with increasing tumor firmness. Each 0.1 × 10-3 mm2/sec increase corresponded to a 38% reduction in the odds of belonging to a higher consistency category (OR 0.62, 95% CI 0.51-0.74, p < 0.001). The ROC analysis showed good discrimination for solid tumors (area under the curve 0.847, 95% CI 0.742-0.953) and soft tumors (area under the curve 0.824, 95% CI 0.714-0.935). Texture features had weaker associations with intraoperative tumor consistency. CONCLUSIONS: Volumetric diffusion-derived metrics, particularly ADCmean, are associated with both histopathological aggressiveness and intraoperative tumor firmness in meningiomas. Diffusion imaging may reflect a graded microstructural continuum rather than a purely dichotomous property, providing complementary preoperative insights into surgical complexity.

Humans↗

PubMed2026

Is There a Difference in Occurrence of Complications Between Adults With Hemoglobin SS and Hemoglobin SC Disease: An Extended Systematic Review.

Sickle cell disease (SCD) is characterized by both acute and chronic complications. The clinical manifestation of these complications differs between genotypes. Given the large amount of research already published, this systematic review aims to offer a complete overview of types of sickle cell complications between adults in the most common genotypes Hemoglobin SS (HbSS) and Hemoglobin SC (HbSC), putting options for further research into perspective. An extensive literature search was performed to study all available evidence on these complications. This review was performed according to the "Preferred Reporting Items for Systematic Reviews and Meta-Analyses" (PRISMA) statement guidelines, and was performed on January 2, 2024. A total of 710 references were identified. After careful screening, 521 records were excluded based on title and abstract and other exclusion criteria. In total, 158 articles were excluded after full-text assessment. Our analysis of 31 studies highlights key differences in complications between HbSS and HbSC genotypes in sickle cell disease (SCD). Vaso-occlusive crises (VOCs) remain the most common acute complication in both genotypes. HbSS patients experience more frequent VOCs, while HbSC patients generally have a milder clinical course when it comes to acute complications. Chronic complications, particularly in the ocular and pulmonary systems, are more prevalent in HbSC patients. However, as acute complications are more common in HbSS and chronic complications more common in HbSC, both genotypes face progressive organ damage due to recurrent ischemic injury and inflammation.

Humans↗

PubMed2026

Efficacy of the NMIC-150 system in identifying extended-spectrum beta-lactamases in clinical isolates.

Extended-spectrum beta-lactamases (ESBLs) are significant contributors to the growing global crisis of antimicrobial resistance. This study evaluated the performance of the NMIC-150 System for susceptibility testing of third-generation cephalosporins (3GCs) and assessed whether ceftazidime-avibactam and aztreonam-avibactam could identify ESBL-producing carbapenem-resistant Enterobacterales (CREs). A total of 278 non-duplicate clinical isolates (Klebsiella pneumoniae, E. coli, and Proteus mirabilis) were analyzed. Antimicrobial susceptibility was determined using reference broth microdilution (BMD) and the NMIC-150 System. ESBL production was defined as an ≥eight-fold reduction in the minimum inhibitory concentration (MIC) of 3GCs in the presence of clavulanic acid, according to CLSI criteria. Whole-genome sequencing was performed to characterize ESBL and carbapenemase genes among 3GC-resistant isolates. A Random Forest model was used to predict ESBL-producing isolates based on MIC values. The NMIC-150 System demonstrated over 90% categorical and essential agreement with BMD for ceftazidime and ceftriaxone, along with robust predictive performance via Random Forest analysis. These findings suggest that the NMIC-150 System is a reliable platform for 3GC susceptibility testing and that an ≥eight-fold MIC reduction with ceftazidime-avibactam or aztreonam-avibactam may serve as a phenotypic indicator of ESBL production in CRE isolates. In conclusion, the NMIC-150 System shows potential for routine antimicrobial resistance surveillance and may facilitate the rapid identification of ESBL-producing CREs in clinical settings.

Microbial Sensitivity Tests↗

PubMed2026

A reanalysis of the Hitachi cohort study evaluating the effectiveness of low-dose CT screening for lung cancer.

The effectiveness of low-dose thoracic computed tomography (CT) screening for lung cancer for non-smokers or light smokers has been unclear. The results of the Hitachi cohort study performed by the conventional multivariable analysis suggested the reduction of lung cancer mortality by thoracic CT screening, but also revealed the lower all-cause mortality in the CT group, which indicated the existence of self-selection bias. Because the background of the subjects in the CT screening group and that in the X-ray screening group were very different, it is critical to adjust appropriately the confounding factors. In this brief report, we describe a re-evaluation of the results of the Hitachi Cohort Study performed by using more flexible methods, propensity score matching and inverse probability weighting.

epidemiology/public health↗

PubMed2026

Automated CEAP Classification of Venous Duplex Reports Using Multimodal Artificial Intelligence.

OBJECTIVE: To develop and internally validate a prototype multimodal artificial intelligence system for automated CEAP (Clinical, Etiological, Anatomical and Pathophysiological) classification of venous duplex ultrasound (VDUS) reports, integrating natural language processing of free-text components with computer vision analysis of hand-drawn anatomical diagrams. METHODS: Single centre retrospective observational study using routinely collected clinical data. One thousand consecutive venous duplex ultrasound reports from Cambridge University Hospitals NHS Foundation Trust, UK (July 2024 - May 2025) were labelled according to the CEAP classification, excluding the Etiological component, which could not be reliably determined from duplex reports alone. Transfer learning was applied using ClinicalBERT for text and MobileNetV3 for diagrammatic data. Clinical classes were predicted from request line text. Text- and image-based pathophysiological models were developed for four anatomical territories (Great Saphenous Vein, Small Saphenous Vein, Deep system, Perforators), combined using late fusion with probability averaging. RESULTS: The clinical CEAP model achieved accuracy of 0.91, macro-F1 of 0.82, and macro-AUC of 0.98. Pathophysiological prediction varied, with text models broadly outperforming image models. Fusion yielded heterogeneous benefits, improving SSV performance but reducing Deep system accuracy. The performance of the final pathophysiological CEAP fusion models varied across anatomical territories: accuracy ranged from 0.70-0.92 and macro-AUC from 0.80-0.92. CONCLUSION: This study demonstrates the feasibility of automated CEAP classification from VDUS reports. Despite class imbalance affecting minority class predictions, the strong discriminatory performance validates this multimodal ML model for extracting clinically meaningful information from real-world data. This approach offers potential, pending external validation, to streamline vascular services through automated triage and guideline-compliant decision making.

Artificial intelligence↗

PubMed2025

Enhanced fracture detection on radiographs with AI assistance for clinicians: a systematic review and meta-analysis.

BACKGROUND: Emergency radiographic interpretation for fractures is prone to missed or misdiagnoses. Artificial intelligence (AI) is expected to become a powerful tool to assist clinicians in fracture detection. PURPOSE: A systematic review and meta-analysis was performed to assess whether AI improves clinicians' ability to detect fractures on radiographs. MATERIALS AND METHODS: A literature search was conducted in PubMed, Web of Science, and Cochrane Library for studies published between January 1, 2010, and October 10, 2025. A meta-analysis of diagnostic accuracy studies was performed using a Summary Receiver Operating Characteristic (SROC) curve. The quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Subgroup analysis and meta-regression were conducted to explore potential sources of heterogeneity. RESULTS: A total of 26 studies were included . The pooled sensitivity of clinicians increased from 77% (95% CI: 72-81) to 87% (95% CI: 83-90) with AI assistance, while the pooled specificity improved from 88% (95% CI: 85-90) to 92% (95% CI: 89-94). The corresponding AUC values were 0.90 (95% CI: 0.87-0.92) before and 0.95 (95% CI: 0.93-0.97) after AI assistance. Eight studies were rated as high risk of bias. Subgroup analysis and meta-regression identified potential sources of heterogeneity, including fracture location, AI model type, high risk of bias, and reference standards. CONCLUSION: AI assistance significantly improves clinicians' diagnostic performance in detecting fractures on radiographs for extremity and trunk fractures.

Humans↗

PubMed2026

The effect of olfactory training and odor exposure on visual selective attention.

Olfactory training (OT) is a well-established, non-invasive intervention that improves olfactory function by repeated, structured exposure to odorants. Beyond sensory outcomes, it also influences multiple aspects of cognition. Yet, its influence on attention, a fundamental process underlying many cognitive domains, remains unclear. This study examined the impact of a 12-week OT program on visual selective attentional performance and the effect of on-task odor exposure. Ninety-four healthy participants were initially included, and randomized into OT or placebo groups. Participants completed the d2 Test of Attention simultaneously with and without odor exposure in a randomized sequence at baseline, post-training, and a follow-up four weeks after stopping the training. The d2 test measures commission errors, omission errors, and concentration performance. Ninety-three participants (OT=51, placebo=42) completed baseline measurement, 74 (OT=39, placebo=35) returned for post-training session, and 57 participants (OT=29, placebo=28) returned for the follow-up appointment. Results showed that OT did not significantly improve d2 test performance. In the primary model, on-task PEA exposure reduced commission errors compared to the odorless condition, suggesting a possible transient effect of olfactory input on the inhibitory control in the context of the d2 attentional test. This effect, however, was no longer significant once the follow-up data were included and should be regarded as preliminary. Overall, these findings raise the possibility of a distinction between relatively long-term OT and short-term odor exposure: while OT did not improve visual selective attention, brief on-task odor exposure may transiently enhance inhibitory control during attentional tasks, a possibility that remains to be confirmed.

Humans↗

PubMed2026

Response-optimised training improves learning of a complex motor task and closely related motor tasks.

Regular physical exercise is essential for promoting healthy aging and longevity. In older adults with varying physical and cognitive decline, optimising exercise interventions is crucial to maximise benefits. A promising approach to achieve this goal is by adjusting task demands to individual abilities in turn preventing over- or underloading their abilities. In the field of motor learning, it is currently unclear whether such an optimised training improves not only performance on the trained task but also transfers to untrained motor and cognitive tasks. We conducted a randomized, single-blinded, 6-week dynamic balance training (DBT) with healthy older adults (n = 30). Training was tailored to individual balance ability. Participants were assigned to either suboptimal (high or low difficulty) or optimal (moderate difficulty) training groups. Transfer effects were assessed via cognitive tasks (memory and executive) and motor tasks (untrained DBT variations and other balance tasks) measured pre-, mid- and post-intervention. Multivariate longitudinal statistical analysis showed higher performance gains in the optimal training group in three out of six sessions compared to the suboptimal groups, especially under testing conditions with high task demands. The optimal group also showed greater improvements in near motor transfer tasks mid- and post-intervention, while no significant differences were observed in the cognitive tasks. Within-group DBT learning positively correlated with transfer gains, highlighting the role of training response in achieving transfer. In conclusion, optimised task difficulty in balance training enhances both task-specific performance and related motor skills, supporting the use of personalised interventions to maintain function and independence in older adults.

Humans↗

PubMed2026

Axial Length Adjustment and AL/R Ratio Optimization of IOL Power Calculation in Extremely Long Eyes.

PURPOSE: To evaluate the accuracy of modern intraocular lens (IOL) power calculation formulas and axial length (AL) adjustment methods in eyes with AL ≥ 30.0 mm. DESIGN: Retrospective consecutive cross-sectional study. PARTICIPANTS AND CONTROLS: A total of 308 eyes (308 patients) with AL ≥ 30.00 mm were included. METHODS: Accuracy of modern online formulas, alone or with established AL adjustments methods, was analyzed. Subgroup analyses were performed based on AL, keratometry (K), anterior chamber depth (ACD), lens thickness (LT), and AL-to-corneal radius (AL/R) ratio. MAIN OUTCOME MEASURES: Predictive accuracy was evaluated using the formula performance index (FPI), root mean square absolute prediction error (RMSAE), standard deviation (SD) of prediction error (PE), and percentage of eyes within ±0.25 and ±0.50 diopters (D). RESULTS: Overall, Holladay 1 combined with the nonlinear polynomial Wang-Koch axial length adjustment (H1-PWK) demonstrated the best overall performance, achieving the lowest SD (0.40), RMSAE (0.40), and highest FPI (0.494). A tendency toward hyperopic error was observed in eyes with AL ≥ 32.0 mm, K ≥ 46.0 D. The AL/R ratio showed a significant positive correlation with PE in the Ladas Super formula, Barrett Universal II, EVO, PEARL-DGS, and Hoffer QST formulas. Spline-based regression analysis indicated that the transition point of AL/R from myopic to hyperopic PE varied across different formulas. CONCLUSIONS: H1-PWK provides robust refractive accuracy in extremely long eyes. The AL/R ratio may provide a useful composite biometric stratification parameter compared to AL alone.

Humans↗

PubMed2026

Cisplatin-Induced Hearing Loss Prevention With Intratympanic Therapy Systematic Review and Meta-Analysis.

INTRODUCTION: Cisplatin-induced hearing loss (CIHL) is a well-described, long-term consequence of cisplatin treatment for malignancy. Intratympanic (IT) injections have been trialed to prevent CIHL in humans. To provide clarity on which agents have been studied through IT injection and to review their efficacy for hearing loss prevention, we performed a systematic review and meta-analysis. DATA SOURCES: OVID Medline, Embase, Web of Science, and Cochrane Library were queried. METHODS: Databases were searched in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Prospective randomized trials were included, and a systematic review was performed for all studies. Demographic, audiometric, and therapeutic data were collected. Random-effects models were used to compare across studies, and subgroup analyses were performed for each IT agent. RESULTS: The initial database search yielded 1017 articles, which were screened according to inclusion and exclusion criteria. Ten studies were identified, involving a total of 284 patients. Studies included data on IT dexamethasone, IT N-acetylcysteine (NAC), and IT sodium thiosulfate (STS). Pooled analysis across all agents and frequencies did not reveal a significant difference in hearing thresholds between treatment and control ears [prediction interval [-3.77, 3.20], negative favors treatment). Subgroup analysis of IT dexamethasone [-1.74, 3.80] and IT NAC [-1.02, 4.64] also did not demonstrate significant differences. STS data were not amenable to pooled analysis; however, one study demonstrated a significant decrease in ASHA-defined ototoxicity (40% vs. 85%, P =0.0027). CONCLUSIONS: To date, no IT agent has consistently prevented CIHL, although limited data suggest that IT STS may decrease ototoxicity. More trials are necessary to fully elucidate these effects.

Humans↗

PubMed2026

A randomized study of antibiotic prophylaxis after hypospadias repair in children.

BACKGROUND AND OBJECTIVE: Antibiotic resistance is a challenge in contemporary world. Urethroplasty for hypospadias is one of the most common urological surgeries performed around the world, yet, there is still no consensus on the use of antibiotics pre- and post-operatively. Our objective was to analyze the effectiveness of antibiotic prophylaxis and therapy before, during, and after hypospadias repair in children. METHODS: A prospective randomized trial was carried out including patients with coronal hypospadias who underwent urethroplasty performed by one surgeon. Urethral catheters were used in all cases for 10 days. Study participants were randomly assigned in a 1:1:1 ratio to receive a single intraoperative administration of antibiotics (Group I); an intraoperative antibiotic prophylaxis and antibiotic therapy for 10 days until the removal of urethral catheter (Group II); no antibiotic administration (Group III). Randomization was performed using computer-generated permuted blocks with randomly varying block sizes, prepared by an independent statistician. The results were analyzed using the analysis of variance (ANOVA). The following criteria were compared: postoperative functional complications, such as: urethral fistula, stenosis, diverticulum; wound infection symptoms: hyperemia of surgical site, pain during palpation, and symptomatic urinary tract infection. RESULTS: A total of 300 patients were included in the study. Two patients (2%) in Group I, two patients (2%) in Group II, and four patients (4%) in Group III had urethral fistulas, requiring surgery 6 months after primary repair, yet without statistical difference between groups. We found no significant difference in frequency of symptomatic UTIs between three groups (p = 0.182). CONCLUSION: There is no effect of antibiotic prophylaxis and therapy on the frequency of postoperative surgical and infectious complications after urethroplasty for coronal hypospadias repair in children.

Humans↗

PubMed2026

Comparative effects of 12-week resistance training on unstable and stable surfaces on muscle stiffness, muscle co-activation, and balance in older patients with knee osteoarthritis.

OBJECTIVE: This randomized trial compared the effects of unstable resistance training (URT), involving resistance exercises on unstable surfaces, and stable resistance training (SRT), performed on stable surfaces, on muscle stiffness, co-activation, and balance in older adults with knee osteoarthritis (KOA). We hypothesized that URT would yield greater improvements by enhancing neuromuscular adaptability. METHODS: Fifty patients with KOA were randomly assigned to the URT group (n = 25) or the SRT group (n = 25). After attrition, 46 participants (URT: n = 23; SRT: n = 23) completed the intervention and were included in the final analysis. Both groups completed a 12-week supervised lower-limb resistance training program (3 sessions/week) consisting of 10 exercises performed under either unstable or stable support conditions. RESULTS: After 12 weeks of intervention, both groups showed significant reductions in pain intensity (p < 0.001). However, compared with the SRT group, the URT group demonstrated significantly greater reductions in quadriceps stiffness (p < 0.05), selected hamstring stiffness outcomes (p < 0.05), and quadriceps-hamstring co-activation (p < 0.001), alongside superior improvements in both dynamic balance and static balance (all p < 0.05). CONCLUSION: While both training modalities are effective for pain relief, URT elicited greater improvements in balance-related performance and neuromuscular-mechanical outcomes than SRT in older adults with KOA. These findings suggest that incorporating unstable support conditions into resistance training may provide additional rehabilitation benefits for this population.

Humans↗

PubMed2026

Plasma proteomics reveal SERPINA1 and CD59 as candidate biomarkers for COVID-19 severity stratification and prognosis prediction.

BACKGROUND: COVID-19 has been closely associated with coagulation abnormalities. However, existing biomarkers, including D-dimer and fibrin degradation products (FDP), exhibit limited accuracy in stratifying disease severity and predicting long-term clinical outcomes. OBJECTIVES: This study aimed to use proteomic analysis to identify plasma biomarkers associated with COVID-19 severity and prognosis, and validate their predictive utility for mortality and thromboembolic complications. METHODS: Plasma proteomic profiles were analyzed across three COVID-19 severity classes. Differential expression analysis and functional analysis were performed. Clustering analysis was used to identify proteins correlated with disease severity. Candidate biomarkers were validated in an independent cohort. Predictive performance of the biomarkers for mortality, sepsis and venous thromboembolism was evaluated using bootstrap-corrected ROC analyses and multivariable regression analyses. RESULTS: Proteomic analysis revealed progressive involvement of the coagulation and complement pathway with increasing disease severity. SERPINA1 and CD59 were identified as candidate biomarkers and exhibited significantly higher plasma levels in severe cases. Bootstrap-corrected ROC analyses demonstrated strong predictive performance: SERPINA1 achieved AUCs of 0.775 and 0.924 for 30-day and 12-month mortality, and CD59 achieved AUCs of 0.720 for sepsis; the combined model further improved prediction of 12-month mortality (AUC 0.946) and sepsis (AUC 0.904), outperforming D-dimer and FDP. Multivariable regression confirmed their independent prognostic value. CONCLUSION: This exploratory study identifies SERPINA1 and CD59 as candidate prognostic biomarkers in COVID-19, highlighting the role of coagulation and complement-related pathways in disease severity and warranting further prospective validation.

Humans↗

PubMed2026

Novel splice site variants in GBA1 are associated with Gaucher disease and genotype-phenotype correlations.

BACKGROUND: Variants in GBA1 are associated with neurodegenerative disease. This study aimed to explore pathogenic GBA1 variants. METHODS: Four patients with progressive myoclonic epilepsy (PME) and extremely low β-glucosidase levels were recruited. Whole-exome sequencing and long-range PCR were performed to identify GBA1 variants. Bioinformatic analyses were used to predict the impact of the identified variants. A literature review was performed to explore the genotype-phenotype correlations. GBA1 expression data across different brain regions and developmental stages were analyzed using the BrainSpan database. RT-PCR was performed to verify the splicing effects. RESULTS: Compound heterozygous GBA1 variants were identified in four patients. Five distinct variants were detected, including two novel splice site variants (c.308-2A>G and c.762-2A>C) and three previously reported variants. All identified variants were rare or absent in gnomAD. Splice site variants c.308-2A>G and c.762-2A>C were predicted to cause aberrant splicing. Minigene-based splicing assays coupled with RT-PCR and Sanger sequencing confirmed that both variants cause complete exon skipping (exon 4 and exon 7, respectively). All patients presented with PME onset in childhood/adolescence, intellectual regression, low β-glucosidase, and diffuse brain atrophy and were subsequently diagnosed with Gaucher disease type 3. GBA1 expression in the brain showed two distinct peaks: one in infancy and another after five years of age. The onset age of PME aligned with the second GBA1 expression peak (after five years of age). CONCLUSION: This study identified compound heterozygous GBA1 variants, including two novel candidate pathogenic splice site variants, in Gaucher disease type 3 patients, expanding the known mutational spectrum.

Humans↗