A 69-year-old woman with Parkinson's disease (Hoehn and Yahr stage 1.0) developed dyspnea and fever five weeks after initiation of low-dose zonisamide. Laboratory tests revealed marked neutropenia and thrombocytopenia, and chest CT showed bilateral pleural effusion. All abnormalities resolved completely within ten days after discontinuation of zonisamide. To our knowledge, such a combination of agranulocytosis and pleural effusion associated with zonisamide has not been previously reported, and this rare adverse event warrants clinical attention.

Chronic obstructive pulmonary disease (COPD) is increasingly recognized as a systemic condition associated with an elevated risk of cognitive impairment, particularly in domains of executive function and attention, presenting a pattern distinct from Alzheimer's disease. This review synthesizes evidence from multimodal neuroimaging studies to characterize the cerebral alterations in COPD and frame them within the context of accelerated brain aging. Patients with COPD exhibit widespread structural brain changes, including reduced gray matter volume in cognitively critical regions, such as prefrontal cortex, cingulate gyrus, hippocampus, and basal ganglia. Concurrently, white matter damage is evident as microstructural abnormalities in tracts including the cingulum bundle and corona radiata, alongside white matter hyperintensities. These microstructural abnormalities are characterized by decreased fractional anisotropy and increased mean diffusivity. Furthermore, neurovascular uncoupling, indicated by an imbalanced ratio of cerebral blood flow to degree centrality in frontal-temporal areas, contributes to network inefficiency. These neuroimaging abnormalities are closely associated with deficits in executive function, attention, and visuospatial abilities. The underlying pathophysiology involves synergistic effects of systemic hypoxia, chronic inflammation, and neurovascular-coupling dysfunction, which collectively promote a cascade of brain injury resembling accelerated aging. Elucidating this unique neuropathological profile not only enhances the understanding of COPD-related cognitive decline but also highlights potential shared mechanisms with broader brain aging processes, offering insights for early diagnosis and targeted intervention strategies.

Sepsis-associated acute respiratory distress syndrome (ARDS) is a severe inflammatory lung disorder with high mortality. Bruceine A (BA), a quassinoid from Brucea javanica, exhibits anti-inflammatory and immunomodulatory activities, but its role in ARDS is unclear.

This study evaluated the protective effects of BA in lipopolysaccharide (LPS)-induced ARDS and explored its underlying mechanisms.

Thirty-six C57BL/6 mice were randomized into four groups: Control, LPS, LPS+BA and LPS+dexamethasone (Dex). Lung injury was assessed by histopathology, wet/dry weight ratio and TUNEL assay. Cytokine levels (TNF-α, IL-6, IL-1β, IL-10) were measured by ELISA. Macrophage polarization markers (iNOS, COX-2, Arg-1, YM1, CD206) and NF-κB pathway proteins were evaluated using immunohistochemistry and Western blotting.

BA significantly alleviated LPS-induced lung injury, reducing edema, tissue damage and alveolar apoptosis. It suppressed proinflammatory cytokines while enhancing IL-10. BA shifted macrophage polarization from proinflammatory M1 toward anti-inflammatory M2 phenotypes. Furthermore, BA inhibited NF-κB activation, evidenced by reduced phosphorylated p65 and restored IκBα levels. These effects were comparable to Dex.

BA protects against LPS-induced ARDS in mice by modulating cytokine release, promoting M2 macrophage polarization and suppressing NF-κB activation. These findings suggest BA as a promising natural immunomodulatory agent for inflammatory lung diseases.

Acute respiratory distress syndrome (ARDS) is a life-threatening condition characterized by high mortality with no specific treatments. Fibroblast growth factor 10 (FGF10) is recognized for its tissue repair and anti-inflammatory roles in injured lungs; however, its clinical relevance and mechanistic role in ARDS remain unclear.

Serum FGF10 levels were measured in patients with ARDS and analyzed for associations with clinical outcomes. An LPS-induced mouse model of acute lung injury (ALI) was used to evaluate the effects of FGF10 treatment in vivo. Single-cell RNA sequencing of lineage-traced alveolar epithelial cells (AECs) was performed to identify transcriptional changes following FGF10 administration. In vitro co-culture systems involving macrophages or neutrophils with AECs were established to investigate immune cell-specific mechanisms.

We found that serum FGF10 levels were significantly reduced in ARDS patients, and this reduction correlated with poor prognosis. Moreover, FGF10 treatment alleviated lung inflammation by decreasing inflammatory cell infiltration and pro-inflammatory cytokine release in mice. Leveraging single-cell RNA sequencing of lineage tracing alveolar epithelial cells (AECs), we identified that the mRNA expression of Ripk1, Casp8, and Casp3 were decreased after FGF10 treatment. In in vitro co-culture experiments, we noticed that FGF10 did not inhibit macrophage pyroptosis. Instead, FGF10 effectively blocked the downstream RIPK1/caspase-8/caspase-3/gasdermin E (GSDME) signaling pathway in AECs. Additionally, FGF10 suppressed AMP-activated protein kinase (AMPK) activation by modulating ATP production, thereby preventing RIPK1 cleavage.

FGF10 alleviates acute lung injury by inhibiting AMPK-RIPK1/caspase-8/caspase-3/GSDME-mediated pyroptosis in AECs primed by distinct immune cell populations, supporting its potential as a therapeutic strategy for ARDS.

Our study reveals a marked decrease of serum FGF10 levels in ARDS patients, correlating with P/F ratio, hospitalisation days and mortality rates. We clarify how FGF10 prevents AECs' pyroptosis triggered by different immune cell infiltrations in different ways. FGF10 restored ATP levels to attenuate RIPK1 phosphorylation via AMPK to disrupt pyroptosis in the AECs.

Middle meningeal artery embolization (MMAE) combined with surgery has emerged as a promising option for treating non-acute subdural haematomas (non-aSDH). This meta-analysis aimed to evaluate the efficacy, safety, and clinical utility of adjunctive MMAE and compare them with conventional surgery alone for non-aSDH. Seven English and Chinese databases were searched to identify eligible randomized controlled trials (RCTs) and prospective cohort studies (PCSs) from inception to June 2025. The primary efficacy outcome was treatment failure, and the primary safety outcome was complications. The secondary outcomes included favourable outcomes, mortality, changes in SDH thickness, and length of hospital stay (LOS). Ten RCTs and three PCSs were analysed. Compared with surgery alone, adjunctive MMAE significantly reduced the risk of treatment failure (RR = 0.53, 95% CI: 0.40-0.69, high certainty). Adjunctive MMAE was also associated with a non-significant trend towards fewer complications (RR = 0.86, 95% CI: 0.71-1.04, moderate certainty) and lower mortality (RR = 0.72, 95% CI: 0.43-1.21, moderate certainty), with these trends being more pronounced in Chinese studies. However, no significant differences were observed in favourable outcomes (mRS 0-2; RR = 1.00, 95% CI: 0.96-1.04, moderate certainty), haematoma-thickness change (MD = -0.22 mm, 95% CI: -0.96 to 0.53, moderate certainty), or length of hospital stay (MD = -0.59 days, 95% CI: -2.49 to 1.31, low certainty). Adjunctive MMAE significantly reduces treatment failure and is associated with a non-significant trend towards fewer complications and lower mortality. No significant improvements are observed in favourable outcomes, haematoma-thickness change, or length of hospital stay.

The incidence of acute ischemic stroke (AIS) is increasing among young to middle-aged adults (18-64 years), posing substantial socioeconomic and healthcare challenges. This study aimed to evaluate the diagnostic and predictive value AHR, Klotho, and sdLDL-C in AIS and across different TOAST etiological subtypes in this age group.

We retrospectively enrolled young to middle-aged patients with first-ever AIS and age- and sex-matched stroke-free controls. All participants underwent DWI and additional vascular assessments, including MRA, CTA, and/or DSA. Clinical characteristics, imaging findings, and laboratory parameters were statistically analyzed. Patients were classified into TOAST subtypes for etiological analysis.

Multivariate logistic regression identified male sex, DBP, FPG, LDL-C, and DWM as independent risk factors for AIS. The most common TOAST subtype was SAO, followed by SUE and LAA. Compared to controls, AIS patients exhibited significantly higher AHR and sdLDL-C levels and lower Klotho levels (all P < 0.001). ROC analysis demonstrated that the combined use of AHR, Klotho, and sdLDL-C had high diagnostic accuracy for AIS (AUC = 0.971), with the highest predictive value observed for LAA subtype (AUC > 0.9).

In young to middle-aged adults, male sex, elevated DBP, FPG, LDL-C, and DWM are independent risk factors for AIS. AHR and sdLDL-C are positively associated with AIS risk, while Klotho is inversely associated. The combined biomarker panel (AHR, Klotho, and sdLDL-C) demonstrates strong diagnostic utility, particularly for identifying the LAA subtype. These findings provide valuable insight into early risk stratification and classification of AIS in younger populations.

Early detection of major cardiac defects is crucial for the management and prognosis of affected pregnancies. This study evaluated the effectiveness of routine first-trimester ultrasounds in detecting major cardiac defects in singleton pregnancies.

This retrospective study (2015-2023) at a tertiary center included 35,230 singleton pregnancies undergoing routine ultrasounds at 11-14, 20-24, 28-34, and 34-38 weeks. High-resolution equipment and standardized protocols were used to assess fetal nuchal translucency and cardiac structure.

Among the 35,230 pregnancies studied, 270 cases (0.8%) of major heart defects were identified. Hypoplastic left heart syndrome (HLHS) was detected in 31 cases with a 90% detection rate, while ventricular septal defects (VSD) were the most common, found in 128 cases with a lower detection rate of 16%. Pregnancy outcomes varied significantly with gestational age: 55.9% of early detections (11-13 weeks) led to termination, while 63.9% of mid-term detections (18-22 weeks) resulted in live births. The first-trimester ultrasound scans demonstrated 100% sensitivity and Negative Predictive Value (NPV), with a specificity of 93.85% and a Positive Predictive Value (PPV) of 90.27%. The Kappa value of 0.917 indicated moderate agreement between early and later scans. Notably, early diagnosis (11-13 weeks) was associated with a higher rate of pregnancy terminations, while later diagnoses corresponded to higher live birth rates.

Routine first-trimester ultrasounds effectively detect major cardiac defects early. However, the high sensitivity but low specificity necessitates follow-up scans to confirm findings and reduce false positives, ultimately enhancing prenatal care.

The objective of this study is to demonstrate the clinical applicability of 3D Slicer-assisted volume calculations through the analysis of results from single/burr-hole craniostomy (sBHC/dBHC), and mini-craniotomy procedures for the management of chronic subdural hematomas (cSDHs). A total of 163 patients with cSDH between January 1, 2020, and December 31, 2024, were admitted to our department. sBHC, dBHC or mini-craniotomy procedures were performed. Baseline characteristics, radiological features, and surgical and postoperative parameters were evaluated for all three procedures. Volumetric calculations were performed by employing 3D Slicer. Mini-craniotomy was performed in 67 patients (41.1%), sBHC in 54 (33.1%), and dBHC in 42 (25.8%). The overall recurrence rate was 20.9%, being lowest after mini-craniotomy (10.4%), followed by dBHC (19%) and sBHC (35.2%) (p = 0.004). Although mini-craniotomy achieved superior evacuation efficiency, surgical technique was not independently associated with recurrence after accounting for volumetric factors. In the primary model, each 10 mL increase in residual hematoma volume (RHV) increased the odds of recurrence ≈ 35-fold (p < 0.001). Both RHV and hematoma evacuation rate (HER) independently predicted recurrence, showing excellent discrimination (Area under the curve [AUC] = 0.965 and 0.961). Optimal cutoffs were ≈ 19 mL for RHV and 68% for HER, confirmed by cross-validation and sensitivity analyses. RHV and HER independently predicted recurrence, whereas surgical technique lost significance after accounting for these volumetric factors. Thresholds of ≈ 19 mL (RHV) and 68% (HER) may guide postoperative monitoring. 3D Slicer provides a simple, accessible tool for recurrence prediction in cSDH.

The study aims to investigate the risk factors for comorbid anxiety in patients with coronary heart disease (CHD) and its association with noise exposure, to improve anxiety symptoms through noise reduction management, and to maintain optimal psychological well-being.

Retrospective analysis was performed on clinical data from 138 CHD patients hospitalized between June 2023 and December 2024. Participants were stratified into an anxiety group (n = 78) and a nonanxiety group (n = 60) based on the presence of clinically significant anxiety during hospitalization. Between-group comparisons were performed on noise levels (dB), baseline characteristics, sleep quality [assessed by the Pittsburgh Sleep Quality Index (PSQI)], and disease-related parameters. The correlation between noise exposure and anxiety in CHD patients was quantified, and determinants of anxiety were identified. Noise reduction management was implemented, and a comparison of the Self-Rating Anxiety Scale (SAS) scores before and after noise reduction was performed.

The nonanxiety group showed significantly lower SAS scores (47.25 ± 2.47) than the anxiety group (55.64 ± 3.85; t = 14.706, P < 0.05). Pearson correlation analysis indicated a positive association between noise exposure and anxiety (r = 0.522, P < 0.05). Compared with the nonanxiety group, the anxiety group had higher rates of multivessel disease (≥3 vessels), prior percutaneous coronary intervention (PCI) history, PSQI scores, and noise levels (all P < 0.05). According to the univariate logistic regression analysis, the anxiety determinants included poor sleep quality, multivessel disease, elevated noise exposure, and prior PCI (odds ratios = 7.352, 2.240, 1.329, 2.266; all P < 0.05). Postmanagement data showed reduced noise levels and SAS scores compared with the baseline (all P < 0.05).

Patients with CHD are prone to anxiety, with hospital noise being a potential risk factor. Risk factors include poor sleep quality, multiple diseased vessels, high noise levels, and prior PCI history. Clinical attention should be paid to patients' emotional states, and noise reduction management can effectively alleviate anxiety.

To develop and validate machine learning (ML) models integrating two-dimensional speckle tracking echocardiography (2D-STE) parameters with clinical variables for robust identification of severe coronary artery disease (sCAD).

In this retrospective cohort study, five distinct ML models (Random Forest [RF], Support Vector Machine [SVM], K-Nearest Neighbors [KNN], Multi-Layer Perceptron [MLP], and Extremely Randomized Trees [Extra Trees]) were constructed to identify sCAD on a cohort of 204 patients (80% training set, 20% independent test set). Within the independent test set, two junior sonographers' diagnostic performance for sCAD was compared first without and then with ML assistance over a 2-week interval. SHapley Additive exPlanations (SHAP) analysis was applied to visualize and interpret the models, identifying key features driving sCAD prediction accuracy, with results visualized through dependence diagrams and force plot. Furthermore, a clinical nomogram integrating key predictors identified by ML models was developed to enable individualized quantification of sCAD risk.

Utilizing five features, the MLP demonstrated the best performance with an area under the curve (AUC) of 0.870 and a sensitivity of 0.944. The SHAP visualization analysis for this model indicated that "LV AP4 Endo Peak L. Time SD" significantly influenced its predictions. The MLP model (AUC = 0.870) outperformed both junior sonographers (AUC = 0.687) and a nomogram constructed from ML-selected features (AUC = 0.712). Additionally, the results revealed that junior sonographers achieved significantly improved performance when assisted by the ML models.

The developed ML models could differentiate patients with angiography-confirmed sCAD from those without. Importantly, these models significantly improved the diagnostic performance of junior sonographers when used as an assistive tool.