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PubMed2026

Comparison between measured and synthesized posterior lead electrocardiograms during percutaneous coronary intervention-induced myocardial ischemia.

BACKGROUND: Posterior/inferolateral myocardial ischemia is frequently underrecognized on standard 12‑lead electrocardiography (ECG). Synthesized posterior leads derived from the standard 12‑lead ECG have been proposed as an alternative to directly measured posterior leads; however, their accuracy under controlled ischemic conditions has not been fully validated. METHODS: We prospectively enrolled 26 consecutive patients undergoing percutaneous coronary intervention (PCI) in whom simultaneously recorded measured and synthesized posterior lead ECGs (V7-V9) were obtained during balloon-induced myocardial ischemia. ST-segment deviation was measured at the ST junction (STJ), 40 ms (ST1), and 80 ms (ST2) thereafter. Agreement between measured and synthesized posterior leads was assessed using Pearson correlation and Bland-Altman analyses. As an exploratory patient-level analysis, diagnostic performance was compared with reciprocal anterior ST-segment depression (V1-V4). RESULTS: Strong correlations were observed between measured and synthesized posterior lead ST-segment deviations (V7: r = 0.89; V8: r = 0.86; V9: r = 0.83; all P < 0.001). Bland-Altman analysis demonstrated minimal systematic bias (within ±0.004 mV) and narrow limits of agreement. Synthesized posterior leads showed higher diagnostic performance than reciprocal anterior ST-segment depression (AUC 0.917 vs. 0.708), although the difference was not statistically significant (DeLong test, P = 0.197). Using a 0.05 mV threshold, synthesized posterior leads demonstrated 83.3% sensitivity, 100% specificity, and 96.2% overall accuracy. CONCLUSIONS: Synthesized posterior leads closely reproduced measured posterior lead ST-segment deviations during percutaneous coronary intervention (PCI)-induced myocardial ischemia, supporting the technical validity of posterior lead reconstruction. Larger prospective studies are warranted to determine whether synthesized posterior leads provide incremental diagnostic value beyond careful interpretation of the standard 12‑lead ECG.

Humans↗

PubMed2026

Impact of estimated total blood volume on NT-proBNP response to angiotensin receptor-neprilysin inhibition in acute heart failure: Insights from the PREMIER study.

BACKGROUND: Sacubitril/valsartan (Sac/Val) reduces N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels in acute heart failure (AHF), particularly in patients with reduced ejection fraction. However, whether estimated total blood volume (TBV), calculated using anthropometric equations, is associated with heterogeneity in biomarker response remains uncertain. METHODS: This post hoc exploratory sub-analysis of the PREMIER randomized trial evaluated whether baseline estimated TBV was associated with heterogeneity in NT-proBNP reduction after Sac/Val compared with angiotensin-converting enzyme inhibitor/angiotensin receptor blocker (ACEI/ARB) therapy. Estimated TBV was calculated using validated anthropometric equations and dichotomized at the median (4.05 L). Patients were further stratified by left ventricular ejection fraction (LVEF <40% vs ≥40%). The primary endpoint was the proportional change in NT-proBNP from baseline to Week 8. RESULTS: Among 376 patients, 372 with baseline estimated TBV data were analyzed. In the high TBV group, Sac/Val was associated with greater NT-proBNP reduction than ACEI/ARB (-56% vs -32%; ratio of change, 0.67; 95% confidence interval, 0.53-0.84; P = .001), whereas no significant difference was observed in the low TBV group (P for heterogeneity = 0.063). In patients with LVEF <40%, Sac/Val was associated with greater NT-proBNP reduction in both TBV groups. In patients with LVEF ≥40%, Sac/Val was associated with greater NT-proBNP reduction in the high TBV group, whereas the point estimate in the low TBV group numerically favored ACEI/ARB. CONCLUSIONS: In this exploratory post hoc analysis, higher estimated TBV was associated with greater NT-proBNP reduction after Sac/Val, particularly among patients with LVEF ≥40%. These findings are hypothesis-generating and require external validation. TRIAL REGISTRATION: ClinicalTrials.gov, NCT05164653; Japan Registry of Clinical Trials, jRCTs021210046.

Humans↗

PubMed2026

Transcriptomic responses of gill and intestinal tissues in Nile tilapia (Oreochromis niloticus) to bacterial infection following sequential nanoimmersion and hydrogel-based multivalent vaccination.

Bacterial pathogens, including Flavobacterium oreochromis, Aeromonas veronii, Streptococcus agalactiae, and Edwardsiella tarda, represent major infectious threats to Nile tilapia (Oreochromis niloticus). A multivalent vaccination strategy integrating cationic nanoemulsion immersion with oral hydrogel boosters was developed to investigate tissue-specific immune responses at the transcriptomic level. Gill tissues were collected following immersion challenge and intestinal tissues following intraperitoneal injection challenge, reflecting the physiologically relevant infection biology of each pathogen and the mechanistic rationale of each delivery platform. RNA sequencing (RNA-seq) generated high-quality datasets (mapping rate > 81.64%) with strong concordance to quantitative real-time PCR (qRT-PCR) validation (r = 0.83). Comparative transcriptomic analysis revealed distinct yet complementary immune signatures between tissues. Gill transcriptomes were enriched in phagosome, focal adhesion, extracellular matrix-receptor interaction (ECM-receptor interaction), and cytokine-cytokine receptor interaction pathways, accompanied by increased expression of major histocompatibility complex class I/II (MHC class I/II), mannose receptor, αVβ3 integrin, and calnexin, indicating innate activation, enhanced phagocytic capacity, epithelial barrier reinforcement, and adaptive immune coordination. Intestinal transcriptomes showed predominant enrichment of adaptive immune pathways, including the intestinal immune network for immunoglobulin (Ig) production, Forkhead box O (FoxO) signaling, and mitogen-activated protein kinase (MAPK) signaling, with increased expression of T-cell receptor (TCR), inducible T-cell co-stimulator ligand (ICOS-L), C-X-C chemokine receptor type 4 (CXCR4), and polymeric immunoglobulin receptor (pIgR), reflecting T and B cell coordination, lymphocyte trafficking, and mucosal immunoglobulin transport, alongside innate engagement through phagosome pathway enrichment. Shared upregulation of MHC class II, B-cell receptor (BCR) signaling, integrin alpha M (ITGAM), and immunoglobulin-associated components across both tissues suggests coordinated mucosal immune activation through a conserved immune module, warranting direct experimental validation. Collectively, these findings provide transcriptomic evidence that this vaccination strategy elicits an integrated, tissue-specialized immune response, advancing mechanistic understanding of gill and intestinal immunity in vaccine-induced protection of teleost fish.

Animals↗

PubMed2026

Use of Wearable Sensors in Angelman Syndrome: A Systematic Review.

BACKGROUND: Wearable sensors are a promising method for collecting clinical trial outcome data for people with Angelman syndrome (AS). However, there has yet to be a systematic probe into the ways in which wearable sensors have been successfully used in AS. The current study aims to provide a quantitative summary of wearable sensors used in AS, including contexts of use and psychometric properties, and to present key narrative highlights. METHOD: Literature searches were performed in three electronic databases: APA PsycInfo, PubMed and Web of Science Core Collection. Data items were categorized into four categories: sample characteristics, study methodological details, wearable sensor characteristics and psychometric properties assessed. Sample characteristics included sample size, age, biological sex, race/ethnicity and cognitive/developmental functioning. Study methodological details were subdivided into study design and setting. Wearable sensor characteristics included sensor type, placement site, means of attachment, assessed construct and sensor-related data loss. Psychometric properties assessed included reliability and validity of sensor-derived data. RESULTS: We identified 16 articles through our systematic review. Wearable sensors were used to study sleep (n = 10, 62.5%), language (n = 2, 12.5%), gait (n = 2, 12.5%), caregiver proximity (n = 1, 6.3%), EEG power (n = 1, 6.3%), and arousal (n = 1, 6.3%) in AS through actigraphs, vocalization recorders, inertial sensors, radio-frequency identification watches, wireless EEG caps, and functional near-infrared spectroscopy caps, respectively. Findings from these studies broadly indicate that wearable sensors are feasible, reliable and valid for assessing a range of behaviours relevant to AS. CONCLUSIONS: Wearable sensors are a promising solution to enhance assessments in AS. However, with the small extant literature characterized by small sample sizes and restricted focus on a few relevant features in AS, there remains ample opportunities to explore the use of wearable sensors in people with AS. Additional studies will better inform clinical decision-making and ultimately improve the lives of people with AS and their families.

Humans↗

PubMed2026

Machine learning vs. traditional methods for predicting postoperative cardiac complications after non-cardiac surgery: a systematic review and Bayesian network meta-analysis.

INTRODUCTION: Accurate prediction of peri-operative cardiac complications is critical to optimise pre-operative decision-making. Traditional risk prediction scores, such as the Revised Cardiac Risk Index, show only modest discrimination. Machine learning can model complex, non-linear relationships but their predictive performance compared with traditional scores remains unclear. METHODS: We performed a systematic review and Bayesian network meta-analysis. The primary outcome was postoperative adverse cardiac events following non-cardiac surgery. Prediction models were assessed relative to the Revised Cardiac Risk Index. As many studies evaluated multiple versions of each model type, the highest performing ('best version') and lowest performing ('worst version') results were analysed. Models were ranked using the surface under the cumulative ranking curve (SUCRA). RESULTS: Thirteen studies evaluating 54 models and 927,113 patients were included. Machine learning approaches generally outperformed traditional risk scores. Automated machine learning ranked highest (SUCRA 96.6) showed the greatest improvement in the best version analysis (mean difference (MD) 0.28 (95%CrI 0.16-0.40)) and remained superior in the sensitivity analysis (MD 0.30 (95%CrI 0.14-0.45)). Gradient boosting models showed superior performance over the Revised Cardiac Risk Index across analysis (best version: MD 0.20 (95%CrI 0.14-0.26), worst version: MD 0.18 (95%CrI 0.12-0.25), SUCRA 82.4). The Gupta Perioperative Risk for Myocardial Infarction or Cardiac Arrest score outperformed the Revised Cardiac Risk Index in the best version analysis (MD 0.16 (95%CrI 0.01-0.32)). Between-study heterogeneity was low. None of the included studies externally validated their machine learning models and only six were judged to be at low risk of bias. DISCUSSION: Most machine learning models showed better discrimination than traditional risk scores, with automated machine learning and gradient boosting models ranking highest. However, study quality, calibration reporting and absence of external validation limit immediate clinical adoption. Prospective, multicentre evaluation is required before integration of these models into peri-operative practice.

Humans↗

PubMed2026

Predicting ACL injury risk in athletes: A systematic review of machine learning-based models.

BACKGROUND: Early ACL injury risk identification in athletes is essential. This systematic review examines machine learning (ML) models for predicting ACL injuries, evaluating their methodological quality, performance, and reliability. METHOD: A comprehensive electronic search was conducted across PubMed, Scopus, Web of Science, and IEEE Xplore databases, supplemented by Google Scholar for grey literature, covering articles published between January 1, 2015, and August 30, 2025. Eligible studies were appraised using the Prediction Model Study Risk of Bias Assessment Tool (PROBAST) for methodological quality and risk of bias, and the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) guidelines for quality of evidence. RESULTS: Ten studies were included. PROBAST showed eight studies had moderate risk of bias and two low risk. TRIPOD found only two studies met quality criteria. ML models included logistic regression (n = 5), support vector machines (n = 4), k-nearest neighbor (n = 3), decision trees (n = 3), random forests (n = 5), neural networks (n = 2), linear discriminant analysis (n = 1), and pre-trained CNNs (n = 1). AUC ranged from 0.63 to 0.98. Accuracy (reported in six studies) ranged from 26% to 95%; however, these values should be interpreted with caution due to the absence of confidence intervals, lack of class imbalance handling, and limited external validation across studies. Tree-based ensemble methods such as random forest achieved competitive accuracy (74-86%), while SVM, a non-ensemble classifier, reported accuracy ranging from 71% to 95%; however, the highest values were obtained in studies with notably small sample sizes (n = 12 to n = 39), raising concerns about overfitting and generalizability. CONCLUSION: Current ML algorithms show promise for identifying athletes at high ACL injury risk and detecting relevant risk factors. Although study quality was generally satisfactory, future research should prioritize external validation and model interpretability to support clinical translation.

Humans↗

PubMed2026

Candidate biomarkers for early Giardia duodenalis infection revealed by time-resolved secretome proteomics.

Giardia duodenalis is a zoonotic protozoan parasite that causes giardiasis in humans and other mammals. Early diagnosis remains challenging because current diagnostic methods, including microscopy and enzyme-linked immunosorbent assays (ELISAs), primarily detect established infections. Consequently, a critical diagnostic gap exists during the early stage of infection within the first 2-48 h following exposure. To address this limitation, we characterized the proteins released by in vitro-cultured G. duodenalis trophozoites under serum-free conditions and evaluated their potential as early diagnostic biomarkers. Proteomic analysis of culture supernatants collected during early trophozoite incubation identified 31,773 peptides corresponding to 2504 quantifiable proteins. Temporal profiling showed distinct secretion patterns, including proteins that peaked during the early stage, progressively accumulated over time, or remained persistently abundant throughout the incubation period. Based on their secretion characteristics and predicted immunogenic properties, five candidate biomarkers were selected for further evaluation. Polyclonal antibodies raised against selected candidates successfully detected the corresponding proteins in serum-free culture supernatants, providing preliminary evidence for their potential utility as early-stage diagnostic targets. These findings identify stage-associated candidate proteins that may serve as a resource for future early giardiasis diagnostic development, provide a valuable resource for investigating host-parasite interactions, and establish a foundation for future diagnostic assay development. However, further validation in clinical and biological samples is required to confirm their diagnostic applicability. SIGNIFICANCE: Giardiasis, caused by Giardia duodenalis, is a major diarrheal disease worldwide. Although enzyme-linked immunosorbent assays (ELISAs) provide rapid detection, their diagnostic utility is limited by the lack of biomarkers capable of identifying infection during its earliest stages, creating a critical gap in the detection of active infection within 2-48 h following exposure. Using data-independent acquisition proteomics, this study provides a time-resolved characterization of proteins released by G. duodenalis trophozoites into serum-free culture supernatants. Our findings reveal temporal secretion dynamics of protein secretion and identify candidate biomarkers with potential utility for the development of early-stage diagnostic assays pending rigorous biological and clinical validation. In addition, this proteomic resource provides a foundation for investigating host-parasite interactions and may facilitate the development of future point-of-care diagnostic strategies.

Giardiasis↗

PubMed2026

Association of time-averaged systemic immune-inflammation indices with in-hospital mortality after intracerebral hemorrhage: a retrospective study.

BACKGROUND: Systemic inflammation plays a central role in secondary brain injury following intracerebral hemorrhage (ICH). Although inflammatory indices such as the neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI) are linked to poor outcomes, their associations with mortality are commonly assumed to be linear, potentially overlooking nonlinear patterns where mortality risk rises steeply at higher levels. METHODS: We conducted a retrospective study using the MIMIC-IV database, including 440 patients with non-traumatic ICH who were alive and remained in the ICU for at least 72 h after admission. Mean NLR, SII, and SIRI were calculated from measurements obtained during this period. Multivariable logistic regression and restricted cubic spline (RCS) analyses were applied to assess their independent and nonlinear associations with in-hospital mortality. Model discrimination and calibration were internally validated using 1,000 bootstrap resamples. RESULTS: The in-hospital mortality rate was 26.1%. After multivariable adjustment, NLR and SIRI remained independently associated with mortality. Patients in the highest SIRI quartile had the highest risk of death (aOR = 5.12; 95% CI: 2.57-12.24; p < 0.001). RCS analysis revealed a significant nonlinear association between SIRI and mortality (p-nonlinearity < 0.05), showing a steep risk increase at higher SIRI levels. Adding SIRI to the base model provided a modest improvement in discrimination (AUC 0.762 to 0.785, p = 0.045) and significantly improved risk reclassification (cNRI = 0.4778, p < 0.001; IDI = 0.0240, p = 0.0151). CONCLUSIONS: Among patients with ICH who met the 72-hour eligibility criterion, higher 72-hour average SIRI was independently associated with in-hospital mortality. As a time-averaged measure, SIRI should be interpreted as a dynamic marker integrating the initial inflammatory state and the early clinical course rather than as a purely baseline prognostic factor. Although adding SIRI to the base model modestly improved discrimination and risk reclassification, it should be considered a candidate prognostic marker requiring external validation before clinical application.

Humans↗

PubMed2026

Application of SPI-guided analgesia in laparoscopic gynecologic surgery: a randomized controlled trial evaluating the remifentanil-sparing effect and predictive value of time-weighted SPI.

This study aimed to achieve two primary objectives: (1) to evaluate the opioid-sparing effect of Surgical Pleth Index (SPI)-directed analgesia during surgery via a randomized controlled trial (RCT), and (2) to propose and preliminarily assess a novel dynamic metric, Threshold-based Time-Weighted SPI (Tb-TW-SPI), which integrates stimulus intensity and duration, for its predictive efficacy regarding postoperative moderate-to-severe pain. Employing an RCT combined with exploratory analysis, 61 patients undergoing elective laparoscopic gynecologic surgery were randomized into an SPI-directed analgesia group or a conventional analgesia group. The primary outcome was total intraoperative remifentanil consumption. Postoperatively, an exploratory analysis of the control group data evaluated the correlation between Tb-TW-SPI and Numeric Rating Scale (NRS) pain scores in the post-anesthesia care unit (PACU), calculating its predictive value for moderate-to-severe pain (NRS ≥ 4). Results: The SPI-directed group required significantly less intraoperative remifentanil than the conventional group [median (IQR): 5.84(5.02,6.62)vs. 6.96(5.81,8.19)µg/kg/h; P = 0.016]. Postoperative pain scores did not differ significantly between groups (P > 0.05). Exploratory analysis of the conventional analgesia group revealed that Tb-TW-SPI values were significantly higher in patients with moderate-to-severe postoperative pain (NRS ≥ 4) compared to those without (P = 0.0417).The area under the ROC curve for Tb-TW-SPI predicting this pain was 0.74 (95% CI: 0.52-0.96), with 67% sensitivity and 76% specificity at an optimal cutoff of 1210. This RCT suggests that SPI-directed analgesia can safely and moderately reduce intraoperative remifentanil consumption. Furthermore, the proposed Tb-TW-SPI metric, in this exploratory analysis, suggests potential for predicting postoperative pain, though this finding requires validation in larger cohorts with higher-frequency SPI sampling, offering a new direction for SPI interpretation. Large-scale, multicenter trials are warranted to validate the predictive utility of Tb-TW-SPI. Clinical Trial Registration, China Clinical Trial Registry: ChiCTR2400088444.

Humans↗

PubMed2026

ALID score for treatment-effect heterogeneity of adjunctive low-voltage area ablation in persistent atrial fibrillation: A post hoc analysis of SUPPRESS-AF.

BACKGROUND: In persistent atrial fibrillation (AF), the incremental benefit of adjunctive low-voltage area (LVA) ablation beyond pulmonary vein isolation (PVI) remains inconsistent. OBJECTIVE: To examine whether a simple clinical score characterizes treatment-effect heterogeneity of adjunctive LVA ablation among patients with mapped LVA > 5 cm2 and to perform an exploratory supportive analysis in an independent randomized cohort. METHODS: In this post-hoc analysis of SUPPRESS-AF, which included patients with persistent AF and mapped LVA > 5 cm2 after PVI, four variables-age ≥ 75 years, left atrial diameter > 44 mm, estimated glomerular filtration rate < 60 mL/min/1.73 m2, and absence of diabetes-were combined into the ALID score (0-4). Patients were stratified into low (0-1), intermediate (2), and high (3-4) score groups. Because EARNEST-PVI did not use LVA-guided ablation or select patients based on mapped LVA, it was analyzed as an exploratory supportive cohort rather than as an external validation cohort. RESULTS: In SUPPRESS-AF (n = 336), a significant treatment-by-score interaction was observed (P < 0.001). Adjunctive LVA ablation was associated with increased recurrence in the low-score stratum (HR 3.92; 95% CI 1.50-10.20) and reduced recurrence in the high-score stratum (HR 0.48; 95% CI 0.26-0.86). In EARNEST-PVI (n = 494), a qualitatively similar interaction pattern was observed for additional ablation beyond PVI (interaction P = 0.029), although the ablation strategy differed from LVA-guided ablation. CONCLUSIONS: Among patients with persistent AF and mapped LVA >5 cm2, the ALID score identified heterogeneity in response to adjunctive LVA ablation. These hypothesis-generating findings require prospective validation before clinical implementation.

Humans↗

PubMed2026

Targeting SIRT6: the design and therapeutic implications of activators and inhibitors.

Sirtuin 6 (SIRT6) is an NAD+-dependent deacylase that maintains genomic stability, regulates metabolism, and influences aging, making it an attractive but challenging therapeutic target. Pharmacological modulation of SIRT6 holds promise for cancer and metabolic disorders, yet its context-dependent functions demand precise intervention strategies. Potent, selective, and drug-like chemical probes are therefore essential to dissect SIRT6 biology and to validate its therapeutic potential. This review critically evaluates recent medicinal chemistry advances in SIRT6 modulation. We focus on structure-guided design strategies and structure-activity relationships (SAR) that have transformed initial hits into optimized leads for both activators and inhibitors, highlighting the remaining challenges in achieving isoform selectivity and drug-like properties.

Sirtuins↗

PubMed2026

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

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

Humans↗

PubMed2026

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

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

Humans↗

PubMed2026

Breastfeeding Outcomes After Radiofrequency Ablation and Surgical Excision of Fibroadenomas Compared to Natural History: A Retrospective Cohort Study.

BACKGROUND: Fibroadenomas, common benign breast tumors in women of reproductive age, are increasingly managed with minimally invasive radiofrequency ablation (RFA) or surgical excision. However, their impact on breastfeeding outcomes remains underexplored. We aimed to assess breastfeeding ability and breast tissue changes in women treated with RFA or surgery compared to those with untreated fibroadenomas. METHODS: In this retrospective cohort study, we evaluated 153 women with biopsy-confirmed fibroadenomas across five groups: RFA with prior breastfeeding (RFA-PreBF; n = 26), RFA with posttreatment breastfeeding (RFA-PostBF; n = 22), surgical excision with prior breastfeeding (Surgical-PreBF; n = 30), surgical excision with posttreatment breastfeeding (Surgical-PostBF; n = 20), and noninterventional with breastfeeding (Observation-BF; n = 55). Breastfeeding ability was assessed using a 5-point scale, and breast tissue changes were evaluated via ultrasound at 18 months, and all breastfeeding attempts occurred at a minimum of 12 months postprocedure. Fisher's exact test compared complete lactation failure rates, and a power analysis validated the study design (Fig. 1). FINDINGS: The combined RFA group (n = 48) had a higher complete lactation failure rate (14.6%) than the Observation-BF group (3.6%; Fisher's exact test, p = 0.045). Similarly, the combined surgical group (n = 50) had a higher complete lactation failure rate (16.0%) than the Observation-BF group (p = 0.034). When pooled, the combined intervention group (n = 98) showed a complete lactation failure rate of 15.3% versus 3.6% in the Observation-BF group. Residual tissue correlated with lactation impairment in the RFA group (Spearman's ρ, p < 0.05). Ultrasound showed no tumor recurrence, with cystic changes in some cases not linked to breastfeeding impairment. Power analysis confirmed 80% power to detect a medium effect size (f = 0.25, Fig. 1), supporting the study's robustness.7 RFA-PreBF (n = 26), RFA-PostBF (n = 22), Surgical-PreBF (n = 30), Surgical-PostBF (n = 20), and Observation-BF (n = 55). Breastfeeding ability was assessed using a 5-point scale, and breast tissue changes were evaluated via ultrasound at 18 months. Fisher's exact test compared complete lactation failure rates, and a power analysis validated the study design (Fig. 1).[Figure: see text]Interpretation:RFA and surgical excision are effective for fibroadenoma management but increase the risk of complete lactation failure compared to untreated fibroadenomas. Careful patient selection, precise procedural techniques, and vigilant posttreatment monitoring are essential to optimize breastfeeding outcomes, particularly for women planning future pregnancies.

Humans↗

PubMed2026

Postoperative Curvature Loss in Three-Level Anterior Cervical Discectomy and Fusion With Zero-Profile Device.

PURPOSE: Cervical curvature loss is a frequent complication following 3-level anterior cervical discectomy and fusion (ACDF) using a Zero-Profile device. Consequently, the capacity of this device to maintain cervical sagittal alignment in 3-level ACDF remains highly controversial. This study aimed to identify potential predictors for postoperative curvature loss (PCL) and evaluate its impact on clinical outcomes. METHODS: A total of 113 patients who underwent ACDF for 3-level cervical degenerative disc disease (CDDD) between January 2021 and December 2023 were retrospectively reviewed. Demographic data, radiological parameters, and clinical outcomes were analyzed. Radiographic measures included cervical curvature, T1 slope, C2-7 sagittal vertical axis, and titanium plate and endplate (TPE) distance. Clinical outcomes were assessed using the Visual Analog Scale (VAS), Neck Disability Index (NDI), and Japanese Orthopaedic Association (JOA) scores. Statistical analyses were performed using paired and independent t-tests, as well as Pearson correlation coefficients. RESULTS: The average curvature loss was 6.82° from 1 week postoperatively to the final follow-up (p < 0.001). However, the final curvature (11.65°) was maintained, representing a 4.33° improvement compared to preoperative values. Significant correlations were observed between PCL and preoperative curvature (r = -0.368, p = 0.013), preoperative T1 slope (r = -0.546, p < 0.001), ∆T1 slope (r = 0.443, p = 0.002), and ∆TPE distance (r = 0.417, p = 0.004). PCL did not correlate with Japanese Orthopaedic Association (JOA) scores or arm VAS scores at the final follow-up. Nevertheless, patients with a PCL ≥ 6° exhibited significantly higher neck VAS (p = 0.028) and NDI scores (p = 0.041). CONCLUSION: Although contiguous 3-level ACDF with a Zero-Profile device may result in PCL, it preserves an improved cervical lordosis compared to the preoperative baseline. Low preoperative curvature and a low preoperative T1 slope are potentially predictive factors for PCL. Postoperative changes in TPE distance and T1 slope are significantly associated with PCL, suggesting a potential biomechanical link that requires direct validation. Furthermore, PCL may lead to higher neck VAS and NDI scores. Consequently, the Zero-Profile device may require careful consideration in 3-level CDDD patients presenting with low preoperative curvature and a low T1 slope. Importantly, the 6° PCL threshold identified is preliminary and requires prospective validation before clinical application.

Humans↗

PubMed2026

Quality of life and gender identity in females with congenital adrenal hyperplasia after genital restoration surgery: A single-center experience.

BACKGROUND: Legislation restricting surgical interventions in children with differences of sex development (DSD) has intensified debate about female genital restoration surgery (FGRS) in patients with congenital adrenal hyperplasia (CAH). Long-term patient-reported outcomes are needed regarding the optimal timing of surgery. OBJECTIVE: We aimed to assess health-related quality of life (HRQoL), gender identity, and family satisfaction regarding surgical timing and outcome in females with CAH following genital restoration surgery. STUDY DESIGN: Cross-sectional survey of CAH patients who underwent surgery between January 2007 to December 2016 at our institution. Validated instruments (KINDL questionnaire for HRQoL, Utrecht Gender Dysphoria Scale, UGDS) and structured telephone interviews were employed. RESULTS: Data on HRQoL was available for 25 patients (self- and/or parent-reported) out of 56 eligible patients (45% response rate). Median age at first surgery was 6 months (range: 3-137 months). Patients' age at time of participation ranged from 2 to 28 years. All had 21-hydroxylase deficiency (92% salt-wasting form) with Prader grades ranging from II-V. Wound dehiscence requiring secondary suturing occurred in 15% of patients with primary surgery at our center, while only one (4%) patient developed vaginal stenosis after early primary vaginoplasty. Two additional patients (8%) with prior outside surgery required vaginal revision after FGRS at age 12. HRQoL scores were comparable to healthy reference populations across most age groups. Children aged 3-6 and adolescents and young adults showed no significant difference from reference values, while children aged 7-13 showed a slight elevation. None of five patients ≥14 years demonstrated gender dysphoria (all UGDS scores <40, threshold ≥40). 14 patients and families were also interviewed by telephone. All preferred early surgical timing. No family expressed regret about the decision or preferred delayed surgery. DISCUSSION: This study provides validated intermediate-term patient- and parent-reported outcomes after FGRS in CAH. Key limitations include the small sample size, single-center design, and young age of most patients. Selection bias may exist, though participating families included those who underwent revision surgery. The absence of a non-operated comparison group reflects current clinical reality, as nearly all CAH patients with urogenital sinus underwent surgical correction. CONCLUSIONS: Females with CAH reported normal HRQoL and a comfortable female gender identity after early FGRS. The patients and their families expressed a preference for early surgery. However, there is need for longer-term follow-up to assess sexual function and reproductive outcomes as well comparison of outcomes with a non-operated group.

Humans↗

PubMed2026

Hierarchical modeling of tumor subtypes in cell lines using large-scale genomic datasets.

Cancer cell lines (CLs) are widely used to study tumor biology and drug response, yet their translational relevance is often limited by inaccurate subtype annotations. Existing CL-tumor matching approaches are frequently constrained by flat classification schemes, weak subtype definitions, and the exclusion of normal tissue references, leading to potential confounding of tumor-specific and tissue-of-origin signals. To address these limitations, a hierarchical classification (HC) framework is presented in which CLs are aligned with patient tumors across biological resolutions, from organ to molecular subtype. Gene expression profiles from 802 CLs, 5,612 tumors from The Cancer Genome Atlas (TCGA) , and 8,939 non-cancerous tissues were integrated to separate oncogenic signals from tissue-specific signals. Node-specific features were selected using maximum relevance minimum redundancy, and balanced accuracies of 89% in cross-validation and 75%, and 80% on external datasets were achieved. Through the framework, 43 CLs were reassigned, and clinically relevant underrepresented subtypes were identified.

cancer cell lines↗

PubMed2026

Viral surveillance beyond detection: JMTV and the need for ensemble approaches in emerging virus discovery.

The recent report by T. Murillo, L. E. Enrique Chaves-González, S. Temmam, S. Bermúdez, et al. (Microbiol Spectr 14:e04078-25, 2026, https://doi.org/10.1128/spectrum.04078-25) expands the known geographic and ecological range of Jingmen tick virus (JMTV) by detecting the virus in Amblyomma mixtum ticks collected from horses in Costa Rica. This is an important finding because A. mixtum can feed on wildlife, domestic animals, and humans, creating a possible interface for virus movement across various hosts. The study also places the Costa Rican virus in a wider phylogenetic context, linking it to JMTV diversity reported from other regions. However, the detection of viral RNA in ticks should not be interpreted as proof of local disease, human infection, or active transmission, especially in the absence of supporting results. Instead, it reflects an important signal for careful viral surveillance. Here, I discuss how JMTV illustrates the need for ensemble approaches that combine field sampling, phylogeny, segment-level genome analysis, serology, experimental validation, and data-driven virus discovery tools.

emerging viruses↗