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Factors associated with additional intervention requirement following ESWL in pediatric patients with urolithiasis.

OBJECTIVE: To identify predictors of additional intervention following extracorporeal shock wave lithotripsy (ESWL) in pediatric patients and to develop a clinically applicable predictive model. MATERIALS AND METHODS: This retrospective cohort study included 647 pediatric patients who underwent ESWL between 2015 and 2025. Demographic, clinical, and radiological variables were analyzed. Univariable and multivariable logistic regression analyses were performed to identify independent predictors of additional intervention. Model performance was evaluated using receiver operating characteristic curve analysis. RESULTS: Additional intervention was required in 65 patients (10.0%). On multivariable analysis, stone size 10-20 mm (OR: 3.04, p = 0.003), moderate (OR: 2.16, p = 0.049) and severe hydronephrosis (OR: 6.05, p < 0.001), and multiple stones (OR: 3.52, p = 0.030) were identified as independent risk factors. Increasing age (OR: 0.84, p = 0.026), history of urolithiasis (OR: 0.41, p = 0.006), and lower calyx location (OR: 0.14, p = 0.034) were associated with a reduced risk. The model demonstrated good discriminative performance (AUC: 0.794), with a sensitivity of 72% and specificity of 75%. Internal validation using bootstrap resampling demonstrated stable model performance, yielding a corrected AUC of 0.732. CONCLUSION: Stone burden, hydronephrosis severity, and stone multiplicity are key determinants of additional intervention after ESWL in pediatric patients. The proposed model shows good predictive performance and may support individualized risk stratification and clinical decision-making.

Humans

Integrated bioinformatics analysis reveals cross-talking hub genes and therapeutic agents between sepsis and acute myocardial infarction.

BACKGROUND: Sepsis and acute myocardial infarction (AMI) are two significant diseases that may share overlapping etiological mechanisms. This study aims to systematically identify core genes common to both conditions and to explore their potential as therapeutic targets and drug candidates through an integrative analysis of clinical data and bioinformatics. METHODS: The AMI dataset was obtained from the GEO database, and RNA sequencing data were collected from blood samples of patients with sepsis at our hospital. Common genes were identified using differential expression gene analysis (DEG) and weighted gene co-expression network analysis (WGCNA). Functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, were performed. A protein-protein interaction (PPI) network was constructed, and hub genes were identified using the MCC/Degree algorithm. Diagnostic value was assessed via receiver operating characteristic curve analysis. Immune infiltration patterns, single-cell sequencing data, and molecular docking simulations were employed to evaluate immune relevance and identify potential therapeutic compounds. RESULTS: A total of 417 genes were identified between sepsis and AMI, with enrichment analysis revealing significant involvement in inflammatory responses. Three hub genes-JAK2, MYD88, and TIMP1-were selected for further investigation. ROC curves confirmed their strong diagnostic performance for both diseases. Immune infiltration analysis showed that these core genes were significantly correlated with the infiltration levels of various immune cell types. Molecular docking indicated that quercetin exhibited stable binding affinity with the proteins encoded by these genes. qPCR validation further confirmed the upregulation of these three genes, supporting the anti-inflammatory effects of quercetin as a potential targeted therapy. CONCLUSION: JAK2, MYD88, and TIMP1 were identified as shared core genes in sepsis and AMI. These genes not only serve as potential diagnostic biomarkers but also offer novel targets for developing common therapeutic strategies for both conditions. Furthermore, quercetin emerges as a promising candidate for targeted treatment.

Humans

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

Post-exercise rehydration: a randomized cross-over trial comparing a 100% fruit juice, a glucose-based sports drink, and water.

BACKGROUND: Previous studies indicate that sports drinks may improve rehydration, compared to water, an effect likely achieved by manufacturing sports drinks to contain carbohydrates and sodium. However, there is a growing preference for natural products and a "food first" approach to sports nutrition. Fruit juices naturally contain similar concentrations of carbohydrates to sports drinks, but fruit juices may produce a more stable blood glucose profile. Fruit juices also naturally contain electrolytes, particularly potassium, but their potential as effective rehydration alternatives to sports drinks, which have higher sodium concentrations, is not well understood. This study compared the rehydration efficacy and glucose responses following consumption of a 100% fruit juice (Raw Hydrate&#xae;; FRU), a glucose-based sports drink (SPO), and water (WAT) after exercise-induced hypohydration. Importantly, rehydration beverages were matched for water volume, rather than total volume, to ensure that any potential differences in water balance were not due to unequal water volumes between trials, a limitation affecting previous rehydration research. METHODS: After familiarization, 17 adults (age: 28&#x2009;&#xb1;&#x2009;8&#x2009; years; BMI: 23.8&#x2009;&#xb1;&#x2009;2.9&#x2009;kg/m2) completed three trials in a randomized cross-over design. The participants cycled in the heat (~35&#xb0;C) to induce ~2% body mass loss (BML), then rehydrated over a 1&#x2009;h period in a laboratory (~21&#xb0;C) with a water volume equivalent to 150% of BML from either FRU, SPO, or WAT. This was followed by an additional 4&#x2009;h of seated rest (5&#x2009;h rehydration period), when blood glucose was measured (0, 0.25, 0.5, 0.75, 1, 1.5, and 2&#x2009;h after beverage consumption), and all urine produced was collected. RESULTS: During the 5&#x2009;h rehydration period, there was no effect of trial on total urine volume (FRU: 1266&#x2009;&#xb1;&#x2009;403&#x2009;mL, SPO: 1338&#x2009;&#xb1;&#x2009;361&#x2009;mL, WAT: 1394&#x2009;&#xb1;&#x2009;360&#x2009;mL; P&#x2009;=&#x2009;0.156) or water retention (FRU: 42&#x2009;&#xb1;&#x2009;12%, SPO: 37&#x2009;&#xb1;&#x2009;10%, WAT: 35&#x2009;&#xb1;&#x2009;11%; P&#x2009;=&#x2009;0.059). The blood glucose area under the curve differed by trial (P&#x2009;<&#x2009;0.001), with all beverages significantly different from each other (FRU: 10.12&#x2009;&#xb1;&#x2009;0.72 mmol/L/2h, SPO: 12.48&#x2009;&#xb1;&#x2009;1.34 mmol/L/2h, WAT: 7.90&#x2009;&#xb1;&#x2009;0.47 mmol/L/2h; P&#x2009;<&#x2009;0.003). CONCLUSION: Rehydration efficacy was similar between all beverages, but each elicited a distinct glycemic response. For sports drink consumers seeking a natural alternative or implementing a "food first" nutritional strategy, switching to a 100% fruit juice will not compromise rehydration effectiveness, but may elicit a lower blood glucose response. Although, it should be noted that an additional three participants were withdrawn from the study because of gastrointestinal issues after consuming the 100% fruit juice. This was likely a product of the present study's design, where a large volume of 100% fruit juice (average ~2,300 mL) was consumed in a short period of time (1&#x2009;h). Whilst this is a commonly used study design to robustly assess the rehydration efficacy of different beverages, future studies should distribute fluid intake over a longer duration, in order to improve ecological validity and reduce the risk of gastrointestinal issues.

Humans

Plasma proteome profiling identifies XPNPEP3 as a novel biomarker associated with metabolic dysfunction-associated steatotic liver disease in patients with type 2 diabetes mellitus.

OBJECTIVE: To identify plasma protein differences between type 2 diabetes mellitus (T2DM) patients with and without metabolic dysfunction-associated steatotic liver disease (MASLD), and to evaluate the diagnostic potential of X-prolyl aminopeptidase 3 (XPNPEP3) for identifying MASLD in T2DM patients. METHODS: Twenty T2DM inpatients were categorized into groups with and without MASLD and their plasma samples&#xa0;were analyzed using data-independent acquisition mass spectrometry, followed by bioinformatics analysis to identify differentially expressed proteins. The cohort was then expanded to 84 patients, and plasma XPNPEP3 levels were validated by enzyme-linked immunosorbent assay. Correlation between XPNPEP3 and clinical indicators were evaluated, and diagnostic performance was determined via receiver operating characteristic (ROC) analysis. Immunohistochemistry was employed to compare hepatic XPNPEP3 expression between the two groups. RESULTS: Proteomic analysis identified 176 differentially expressed proteins, with XPNPEP3 exhibiting the most significant down-regulation by fold change. In the validation cohort, plasma XPNPEP3 was significantly lower in T2DM+MASLD versus T2DM alone. XPNPEP3 levels were negatively correlated with diabetes duration, liver function markers, and triglyceride levels, and was identified as an independent factor inversely associated with MASLD in T2DM.ROC analysis demonstrated strong diagnostic performance for XPNPEP3, further enhanced when combined with BMI and diabetes duration.&#xa0; Immunohistochemistry confirmed reduced hepatic XPNPEP3 expression in T2DM+MASLD patients. CONCLUSIONS: Lower plasma XPNPEP3 is independently associated with MASLD in T2DM patients and demonstrates strong diagnostic potential, positioning XPNPEP3 as a promising biomarker for diagnosing MASLD in T2DM patients and a novel target for non-invasive diagnostic tool development.

Humans

Assay-dependent variability in peptide biomarker quantification: experimental evidence from renalase in chronic kidney disease.

BACKGROUND: Renalase is a promising biomarker for kidney disease, but published levels vary widely between studies. We hypothesised that variability in commercial enzyme-linked immunosorbent assays (ELISAs) kits and matrix effects (serum vs plasma) drive these inconsistencies. METHODS: Paired serum and plasma samples from 56 participants (28 chronic kidney disease (CKD) stages 2-5, 28 healthy controls) were tested using three commercial renalase ELISAs (BTLAB, Cloud-Clone, EIAab). We assessed intra-assay precision, inter-assay agreement (Spearman's rank correlation and Bland-Altman analysis on log10-transformed values), matrix effects, and associations with estimated glomerular filtration rate (eGFR). Diagnostic performance was evaluated by Receiver operating characteristic (ROC) analysis. RESULTS: Inter-assay renalase concentrations differed markedly (up to orders of magnitude), with weak inter-assay correlations (r&#x2009;&#x2264;&#x2009;0.25). Bland-Altman analyses revealed large, systematic biases between kits. Only the BTLAB assay showed consistent serum/plasma agreement, a significant correlation with eGFR (&#x3c1;&#x2009;&#x2248;&#x2009;0.32-0.42, p&#x2009;<&#x2009;0.05), and moderate discriminatory performance for CKD in serum (AUC = 0.70) and plasma (AUC = 0.68). Cloud-Clone and EIAab produced divergent results and strong matrix-dependent biases. CONCLUSIONS: Observed variability among commercial ELISA platforms may compromise comparability between studies. Harmonisation, standardised reference materials, and cross-validation are necessary before renalase assays can be used reliably in clinical practice.

Humans

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&#xa0;>&#xa0;5&#xa0;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&#xa0;>&#xa0;5&#xa0;cm2 after PVI, four variables-age&#xa0;&#x2265;&#xa0;75&#xa0;years, left atrial diameter&#xa0;>&#xa0;44&#xa0;mm, estimated glomerular filtration rate&#xa0;<&#xa0;60&#xa0;mL/min/1.73&#xa0;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&#xa0;=&#xa0;336), a significant treatment-by-score interaction was observed (P&#xa0;<&#xa0;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&#xa0;=&#xa0;494), a qualitatively similar interaction pattern was observed for additional ablation beyond PVI (interaction P&#xa0;=&#xa0;0.029), although the ablation strategy differed from LVA-guided ablation. CONCLUSIONS: Among patients with persistent AF and mapped LVA >5&#xa0;cm2, the ALID score identified heterogeneity in response to adjunctive LVA ablation. These hypothesis-generating findings require prospective validation before clinical implementation.

Humans

Cine-derived mitral annular relaxation velocity for detection of preclinical left ventricular diastolic dysfunction.

OBJECTIVES: Imaging diastolic dysfunction in pre-clinical heart failure (HF) is challenging. We evaluated a novel cardiac MRI (CMR) biomarker, CMR e-prime (CMR-MARV), in patients at risk of HF. METHODS: In this substudy of the PARABLE trial (NCT04687111), 236 patients (71.6&#xa0;&#xb1;&#xa0;7.7&#xa0;years, 61.6% male) fulfilling trial-defined ALVDD citeria underwent CMR with measurement of mitral annular relaxation velocity (CMR-MARV) at four mitral annular anchor points. Diastolic strain rates from FT were also assessed. Twenty-five age- and sex-matched controls were included (73.8&#xa0;&#xb1;&#xa0;3.1&#xa0;years, 52% male). Group differences were tested with t-tests, diagnostic accuracy with ROC analysis, and predictors of diastolic dysfunction with adjusted logistic regression. RESULTS: Compared with controls, patients had significantly higher indexed maximal left atrial volume (LAVimax), LV end-diastolic and end-systolic volumes, and LV mass (all p&#xa0;<&#xa0;0.001). Of FT variables, only peak diastolic longitudinal velocity differed between groups (p&#xa0;<&#xa0;0.001). In multivariate models, CMR-MARV correlated with radial, circumferential, and longitudinal diastolic strain rates, radial and longitudinal diastolic velocities (all p&#xa0;<&#xa0;0.001), echocardiographic e' (r&#xa0;=&#xa0;0.20, p&#xa0;=&#xa0;0.007), LV mass (r&#xa0;=&#xa0;-0.18, p&#xa0;=&#xa0;0.008), LAVimax (r&#xa0;=&#xa0;-0.18, p&#xa0;=&#xa0;0.008), and NT-proBNP (r&#xa0;=&#xa0;-0.30, p&#xa0;<&#xa0;0.0001). LAVimax and CMR-MARV were strongly independently associated with ALVDD (AUC 0.89 and 0.76, respectively; p&#xa0;<&#xa0;0.0001). A combined model (LAVimax + CMR-MARV) achieved excellent discrimination (AUC 0.91, 95% CI 0.86-0.97, p&#xa0;<&#xa0;0.0001). Independent predictors included LAVimax, CMR-MARV, and peak diastolic longitudinal velocity (all p&#xa0;<&#xa0;0.001). CONCLUSION: CMR-MARV provides a simple cine-derived measure of longitudinal relaxation that correlates with established structural and biochemical markers of diastolic burden. Within an at-risk population, it offers incremental functional information beyond conventional parameters and may support multiparametric CMR phenotyping of preclinical diastolic dysfunction.

Aged

Biomass burning contributions to Mexico City's atmospheric CO2 estimated using a multi-isotope approach.

Fossil fuel combustion dominates anthropogenic emissions worldwide; however, special attention should be addressed to biomass burning, since it is an increasingly important contributor under warmer, drier fire-weather conditions exacerbated by climate change. These emissions could impact the atmospheric composition of heavily urbanized environments. To assess the influence of biomass burning, along with fossil fuels combustion and soil and plant respiration on Mexico City's atmospheric composition, we conducted a year-long (December 2023-December 2024) isotopic monitoring of atmospheric CO2, combining radiocarbon (&#x394;14C), CO2 stable isotopes (&#x3b4;13C, &#x3b4;18O), and CO/CO2 ratios. Once defined the isotopic signatures and the characteristic CO/CO2 that describe the sources, we performed Monte Carlo simulations under two tracer modalities (&#x394;14C + CO/CO2 and &#x394;14C + CO2 stable isotopes) for source apportionment. Results show that during the dry season, particularly in March-April, atmospheric &#x394;14C values approached and overlapped background levels despite Mexico City's fossil-fuel dominance, indicating enhanced non-fossil inputs. Moreover, backward HYSPLIT trajectories supported that these elevated &#x394;14C values coincided with regional wildfire activity. Monte Carlo results attributed up to &#x223c;34 %-60 % of local CO2 to biomass burning in April, followed by March with contributions of &#x223c;31 %-49 %. Since these biomass burning figures contrast with the official emissions inventory of Mexico City metropolitan area, which assigns <1 % of total CO2 emissions to biomass burning, this study could exhibit the emissions inventory underestimation of this source, and thus, the need to reassess and incorporate top-down isotopic constraints in fire-affected urban regions.

Mexico

Malaria rapid diagnostic tests: performance, pitfalls, and progress.

PURPOSE OF REVIEW: Malaria rapid diagnostic tests (RDTs) have revolutionized malaria diagnosis in endemic settings. RDTs are simple to use and accurate for clinical cases, although sensitivity is reduced at parasite densities below 200&#x200a;parasites/&#x3bc;l. However, increasing prevalence of hrp2/3 gene deletions in certain areas threaten utility of histidine-rich protein 2 (HRP2)-based RDTs, and lingering HRP2 antigenemia can generate false-positive results after parasite clearance. This review summarizes current performance of malaria RDTs, threats to their validity, and recent innovations to improve their performance and continued role in malaria diagnosis. RECENT FINDINGS: Most World Health Organization (WHO) prequalified RDTs perform well for clinical diagnosis, with only occasional exceptions, including a recently reported issue affecting several countries. RDT sensitivity is generally related to malaria transmission intensity, with higher proportions of false-negative results in lower-transmission areas. Newly prequalified lactate dehydrogenase (pLDH)-based RDTs perform well for both Plasmodium falciparum in areas with >5% hrp2/3 gene deletions&#xa0;and for Plasmodium vivax diagnosis. Several point-of-care alternatives to RDTs, including micro-fluidic devices, hemozoin-detecting devices, and automated hematology analyzers, have shown promising results in small studies, but require larger-scale trials before widespread use. SUMMARY: RDTs remain a critical tool in clinical diagnosis of malaria, and newer pLDH-based tests perform well in areas where hrp2/3 gene deletions threaten validity of HRP2-based RDTs.

Humans

Overcoming the hurdles: A systematic review of barriers to self-initiated exercise in trauma recovery.

There is substantial quantitative evidence in support of exercise as beneficial for trauma recovery, particularly in targeting the neurobiological mechanisms disrupted by trauma. It is therefore important to understand the circumstances under which individuals may avoid exercise, ultimately preventing them from accessing the wellbeing benefits. Some qualitative articles have identified the factors which may prevent an individual from choosing to engage in exercise outside of a structured intervention (self-initiated exercise), but there lacks a synthesis across these differing articles. This systematic review aimed to synthesise qualitative evidence on trauma survivors' experience of barriers to self-initiated exercise. A systematic search of six databases was conducted to identify peer-reviewed qualitative findings on the perceived barriers to self-initiated exercise engagement, with six articles meeting the inclusion criteria. Thematic synthesis revealed three key themes: Searching for Safety, Staying With The Trauma, and Costs of Exercise and Trauma. In their decision to exercise, trauma survivors negotiate many barriers: the physiological, social, and environmental threats to their safety, trauma-related dissociation, and the costs of both exercise and trauma weighed against competing recovery needs. The small number of included studies reflects the emerging nature of research in this area, but it may limit the transferability of the findings. Nonetheless, as the first of its kind, this systematic review collates the experience of barriers as a first meaningful, exploratory step towards addressing them in future research. Taken together, the findings underscore the importance of a trauma-informed approach to ensure exercise remains unimpeded for trauma survivors.

Humans

Artificial intelligence for dental caries detection: An umbrella review.

Artificial intelligence (AI) has been proposed as a tool to improve dental caries detection across imaging modalities; however, its clinical value remains uncertain. This umbrella review aimed to synthesize and critically appraise systematic reviews evaluating AI for caries detection and diagnosis. An umbrella review was conducted following PRIOR guidance (PROSPERO CRD420261340728). Searches were performed in MEDLINE, Embase, Scopus, Web of Science, and Google Scholar up to 15 March 2026. Methodological quality was assessed using AMSTAR 2, and overlap of primary studies was quantified using the corrected covered area (CCA). Seventeen systematic reviews were included, of which five reported diagnostic test accuracy meta-analyses using bivariate or HSROC models. Across these meta-analyses, pooled sensitivity ranged from 0.76 to 0.94 and specificity from 0.85 to 0.91. Most systems were based on deep learning models applied to bitewing radiographs and intraoral photographs. However, substantial heterogeneity was observed in imaging modalities, lesion thresholds, analytical tasks, and evaluation metrics. In addition, a high degree of overlap across reviews and recurrent methodological limitations, including reliance on retrospective datasets, limited external validation, and inconsistent reporting, substantially weaken the reliability of the evidence. Although AI models demonstrate high diagnostic performance under experimental conditions, current evidence does not support their use as stand-alone diagnostic tools. Their clinical applicability remains limited, and implementation should be restricted to decision-support contexts until robust prospective validation demonstrates meaningful impact on clinical decision-making and patient outcomes.

Dental Caries

The radiographic effect of cage subsidence on neuroforamina after anterior cervical discectomy and fusion.

STUDY DESIGN: Retrospective Cohort Study. OBJECTIVE: The objective of this study is to investigate the effect of cage subsidence on neuroforaminal area after anterior cervical discectomy and fusion (ACDF) utilizing computed tomography (CT). SUMMARY OF BACKGROUND DATA: Restoration of disc height via implantation of an interbody device provides an indirect decompression of the cervical neuroforamina. Interbody cage subsidence is a potential postoperative occurrence, but the effect of this on neuroforaminal area has yet to be characterized. METHODS: A retrospective review was conducted of patients who underwent one- to four-levels of ACDF utilizing an interbody device with anterior plating. Cage subsidence, neuroforaminal area, height and width were measured on CT scans preoperatively and at least 6&#xa0;months postoperatively. Levels with a cumulative sum of cranial and caudal subsidence greater than 4&#xa0;mm were classified as severely subsided, while levels with cumulative subsidence less than 4&#xa0;mm were classified as non-severely subsided. RESULTS: A total of 83 patients (151 levels) were included in this retrospective analysis. Average endplate subsidence was 3.2&#xa0;&#xb1;&#xa0;1.9&#xa0;mm. Non-severely subsided levels demonstrated a greater perioperative increase in neuroforaminal area (7.9 vs 2.1&#xa0;mm2, p&#xa0;<&#xa0;0.001), neuroforaminal height (1.1 vs 0.4&#xa0;mm, p&#xa0;<&#xa0;0.001) and neuroforaminal width (0.7 vs 0.1&#xa0;mm, p&#xa0;<&#xa0;0.001) compared to severely subsided levels. Interbody subsidence significantly predicted a decreased change in neuroforaminal height, width and area (p&#xa0;<&#xa0;0.001). Severe subsidence was associated with an increased rate of pseudarthrosis, but similar reoperation rates and recurrent neurologic deficits between the two groups. CONCLUSIONS: Severe subsidence of interbody cages after an ACDF was associated with a decreased perioperative change in neuroforaminal dimensions. This decrease in the size of the neuroforamen may reduce the effect of indirect decompression of the nerve root.

Humans

Development and validation of a comprehensive prognostic model for 28-day ICU mortality in non-traumatic subarachnoid hemorrhage: an analysis based on the MIMIC-IV database.

BACKGROUND: Due to the complex pathophysiology of non-traumatic subarachnoid hemorrhage (SAH), accurate risk prediction remains a challenge. Our aim is to develop and validate a comprehensive prognostic model that integrates demographic characteristics, vital signs, laboratory parameters, and more, to provide clinical decision-making support in real-world practice. METHODS: We conducted a retrospective cohort study of 785 Non-traumatic subarachnoid hemorrhage patients. The cohort was randomly divided into a training set (n&#xa0;=&#xa0;549) and a validation set (n&#xa0;=&#xa0;236). Feature selection was performed using LASSO regression, followed by backward stepwise Cox regression for optimization. A nomogram was constructed based on independent predictive factors, and model performance was assessed using discrimination, calibration, and decision curve analysis. To prevent immortal-time bias, all predictors were anchored to a fixed early (first-24-hour) measurement window, treatment variables were modelled as binary indicators rather than cumulative exposures, and a five-model sensitivity analysis with baseline-severity adjustment was performed. RESULTS: The development of our model followed a systematic approach: first, 15 potential predictive factors were selected via LASSO regression, which were then refined to 12 independent predictors using backward stepwise Cox regression. The final predictive factors included: Ventilation, AHT, Nimodipine 60&#xa0;mg, Age, SAPS.II, Input amount, Calcium total, Platelet count, White blood cells, Anion gap, pH, and Chloride. The integrated model demonstrated excellent predictive ability for 7-day, 14-day, and 21-day mortality in both the training set (AUC: 0.972, 0.934, 0.898) and the validation set (AUC: 0.968, 0.948, 0.911). Calibration curves and decision curve analysis confirmed the model's reliability and clinical utility across different time points. We constructed a nomogram for individualized risk prediction. Univariate Kaplan-Meier survival analysis demonstrated significant stratification of survival outcomes by each predictor, while restricted cubic spline analysis revealed non-linear relationships between continuous variables and mortality risk. Random survival forest analysis identified the top three predictive factors (Nimodipine 60&#xa0;mg, Ventilation, AHT) and compared them with our full 12-variable model, confirming superior performance of the integrated model at all time points. At the 28-day primary endpoint, the model achieved a time-dependent AUC of 0.898 (training) and 0.904 (validation); after restricting predictors to the early baseline window, the leakage-controlled model retained good discrimination (validation C-index 0.803). CONCLUSIONS: Our ICU 28-day mortality prognosis model demonstrated robust performance in predicting ICU 28-day mortality in non-traumatic subarachnoid hemorrhage. The model, through the nomogram, provides individualized risk assessment, aiding clinical decision-making and patient stratification.

Humans

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

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

Animals

An individualized nomogram for predicting progression-free survival in systemic anaplastic large cell lymphoma: a multicenter, retrospective, and internally validated study.

OBJECTIVES: To develop an individualized nomogram for predicting disease progression risk in systemic anaplastic large cell lymphoma (sALCL). METHODS: Independent predictors of progression-free survival (PFS) were identified using Cox regression in a multicenter retrospective cohort of 109 sALCL patients (2010-2022). These were incorporated into a three-factor nomogram, evaluated via bootstrapped internal validation (1000 resamples), ROC analysis, C-index, decision curve analysis (DCA), and clinical impact curve (CIC). RESULTS: A total of 29 PFS events occurred during a median follow-up of 31 months. Multivariable modelling selected serum &#x3b2;2-microglobulin elevation, extranodal disease, and front-line chemotherapy choice (CHOP versus CHOPE or BV+CHP) as autonomous progression drivers. Upon internal bootstrap validation, the nomogram yielded strong prognostic accuracy, achieving AUCs of 0.81, 0.85 and 0.87 for 1-, 3- and 5-year progression-free survival, alongside a corrected C-index of 0.779 (95% CI: 0.699 - 0.861). Calibration plots showed close agreement between predicted and observed outcomes, while DCA confirmed superior net clinical benefit versus conventional IPI or Ann Arbor stratification across multiple decision thresholds. CONCLUSION: This first sALCL-specific nomogram integrates clinical and treatment variables to provide personalized PFS risk estimation. While internally validated, this exploratory, observation-based tool requires external validation and recalibration in prospective cohorts before clinical implementation.

Humans

Comparative effectiveness of percutaneous coronary intervention strategies for coronary small-vessel disease: a network meta-analysis of randomized trials.

BACKGROUND: Coronary small-vessel disease (SVD) remains challenging for percutaneous coronary intervention (PCI) because small lumens magnify restenosis and ischemic risk. Multiple devices are available, yet their comparative performance is uncertain. This study evaluated and ranked PCI strategies for SVD. METHODS: A systematic review and network meta-analysis was conducted in accordance with PRISMA. PubMed, Embase, the Cochrane Central Register of Controlled Trials, Web of Science, and Google Scholar were searched from inception to 15 August 2025. Eligible studies were English-language randomized controlled trials enrolling adults with angiographic SVD defined as reference vessel diameter &#x2264;3.0&#x2009;mm, comparing PCI strategies, and reporting target lesion revascularization (TLR), binary restenosis (BR), or myocardial infarction (MI). A frequentist random-effects network meta-analysis generated odds ratios (ORs) with 95% confidence intervals (CIs) and treatment rankings using the surface under the cumulative ranking curve (SUCRA). RESULTS: Thirty-nine trials including 14,503 patients met the criteria. For TLR (37 studies; 11,980 patients), the highest SUCRA values were observed with sirolimus-eluting stents (SES 90.1%), zotarolimus-eluting stents (ZES 83.9%), and everolimus-eluting stents (EES 82.2%). For BR (32; 6,468), SES, ZES, and paclitaxel-coated balloons (DCB-PTX) ranked highest (95.0%, 80.0%, and 78.3%). For MI (37; 11,602), SES, DCB-PTX, and ZES ranked highest (79.0%, 78.7%, and 68.5%). Representative effects showed SES reduced TLR versus bare-metal stents (BMS) (OR, 0.25; 95% CI, 0.15-0.43) and MI versus BMS (OR, 0.41; 95% CI, 0.21-0.79). Conventional approaches such as BMS, plain old balloon angioplasty (POBA), and gold-plated balloon angioplasty (GPBA) ranked lowest across outcomes. CONCLUSION: SES provides the most consistent clinical benefit for coronary SVD. ZES, EES, and DCB-PTX are effective alternatives in selected settings, whereas BMS, POBA, and GPBA are less effective. These findings offer comparative evidence to guide device selection in SVD.

Humans

Beyond predictive performance: A systematic review and critical methodological appraisal of AI/ML and conventional modelling strategies in breast, colorectal, and pancreatic Cancer.

BACKGROUND: Predictive modelling for cancer risk, treatment-related complications, and survival is central to precision oncology. Conventional logistic regression (LR) and Cox proportional hazards (CoxPH) regression remain widely used but are limited when modelling nonlinear interactions, high-dimensional imaging features, and multimodal clinical-metabolic predictors. Artificial intelligence (AI) and machine learning (ML) methods offer expanded capability through automated feature extraction, ensemble learning, and flexible survival modelling, but the evidence on when AI/ML adds value over conventional models across cancer sites and predictive tasks remains fragmented. OBJECTIVE: To systematically evaluate the methodological performance, validation strategies, and translational limitations of AI/ML models compared with conventional statistical models in published predictive-modelling studies for breast, colorectal, or pancreatic cancer. METHODS: PubMed, Scopus, and Web of Science were searched for studies published between January 2019 and March 2025. Two reviewers independently conducted title-and-abstract screening, full-text eligibility assessment, and PROBAST risk-of-bias assessment. Sixty-five studies (n&#xa0;=&#xa0;907,567 participants) were narratively synthesised by cancer site, predictive task, model family, comparator, validation strategy, predictor modality, and calibration or explainability reporting. RESULTS: The 65 studies comprised breast cancer (n&#xa0;=&#xa0;35), colorectal cancer (n&#xa0;=&#xa0;21), and pancreatic cancer (n&#xa0;=&#xa0;9). AI/ML superiority over LR and CoxPH was task- and data-dependent. CNN- and U-Net-based models predominated in imaging and body-composition tasks, tree-based ensembles consistently outperformed LR for tabular perioperative complication prediction, and CoxPH remained competitive, and in the largest pancreatic risk study, superior to XGBoost (C-index 0.802 vs 0.723) in well-structured datasets. PROBAST analysis-domain risk was moderate in 54 of 65 studies (83%), driven by limited external validation, sparse calibration reporting (11/65), and few decision-curve analyses (7/65). CONCLUSION: AI/ML adds the most methodological value in imaging-derived feature extraction and nonlinear perioperative prediction, while conventional regression remains preferable in large, structured datasets with linear predictors. Clinical translation requires standardised body-composition definitions, external validation, calibration assessment, decision-curve analysis, and explainability, in line with TRIPOD+AI and CLAIM standards.

Humans