Xinhui People's Hospital

Our work aims to develop and evaluate a combined model that integrates clinical features, conventional computed tomography angiography (CTA) features, and radiomics features of perivascular adipose tissue (PVAT) to identify asymptomatic carotid stenosis (ACS) patients at high risk for short-term stroke. We enrolled 582 ACS patients confirmed by CTA from three medical centers and divided them into a training set (n = 188), an internal validation set (n = 85), and two independent external validation sets (set 1, n = 157; set 2, n = 152). Radiomics features of PVAT were extracted from CTA images, and dimensionality reduction was performed to identify predictive features. Five machine learning classifiers were employed to construct radiomics models, and the model with the highest AUC was selected to generate the radiomics score (Rad-score). Clinical factors associated with stroke were determined using univariate and multivariate logistic regression analyses to construct a clinical model. A combined model integrating clinical factors and the Rad-score was subsequently developed, and a nomogram was created to provide a visual tool for stroke risk prediction. We assessed model performance comprehensively through calibration curves, discrimination analysis, reclassification, and clinical application. A total of nine optimal radiomics features were ultimately selected from the CTA images. Across the four datasets, the AUC values of the five classifier models ranged from 0.643 to 0.869, 0.716 to 0.826, 0.651 to 0.858, and 0.638 to 0.848, respectively, with the XGBoost model demonstrating the best performance. The combined model, incorporating hypertension, soft plaque, and the Rad-score as variables, achieved AUCs of 0.911, 0.868, 0.882, and 0.871, respectively, across the four datasets. A combined model based on PVAT imaging features around carotid plaques can effectively predict the short-term stroke risk in ACS patients. This model may be expected to provide an important auxiliary tool for clinical prognosis assessment and treatment decisions, with potential clinical application value.

The rapid advancement of remote sensing technology has facilitated the extensive use of high-resolution satellite imagery for building change detection (BCD), supporting applications such as urban planning, disaster assessment, and land monitoring. While deep learning (DL) methods have shown strong potential in BCD tasks, comparative studies on their performance remain limited. This study conducts a systematic evaluation of representative DL-based BCD approaches on high-resolution imagery, using standard metrics to assess their accuracy and generalization. The goal is to identify effective models, highlight current limitations, and provide insights for future improvements.We compare direct-prediction and taskdecoupling architectures, assess multimodal (optical and SAR) fusion, and highlight scenarios where each method excels or falters. The results clarify performance gaps, confirm the benefits of task decoupling and data fusion, and outline directions for more robust BCD algorithms.

Background Although metabolic and bariatric surgery (MBS) remains an effective intervention for severe obesity, postoperative weight regain persists as a significant clinical challenge. Probiotics have emerged as a potential adjunct therapy to optimize outcomes, but their efficacy in weight management remains controversial. This meta-analysis evaluates the effect of probiotics supplementation on weight management in patients following MBS. Methods A comprehensive search strategy was executed across four databases (PubMed, Embase, Scopus and Cochrane Library) from inception to April 10th, 2025. Inclusion criteria encompassed randomized controlled trials comparing probiotics with placebo in patients with severe obesity undergoing MBS. Primary outcomes including percent excess weight loss (%EWL), postoperative body mass index (BMI), and BMI reduction. Data were pooled using the random-effects model. Results A total of 13 trials included 693 patients were finally analyzed in the meta-analysis. Pooled analysis demonstrated no significant difference in %EWL (MD 0.39, 95% CI −1.90 to 2.68, I2=43%), postoperative BMI (MD 0.07, 95% CI −0.21 to 0.35, I2=26%), and BMI reduction (MD −0.05, 95% CI −0.53 to 0.44, I2=60%) between probiotics and control groups. Subgroup analyses stratified by surgery type, probiotic formulation and treatment duration similarly revealed no clinically meaningful effects. Conclusions Current evidence does not support the routine use of probiotics for enhancing weight loss after MBS, regardless of surgical technique and treatment duration. Further large-scale trials standardizing strains, dosages, and outcome metrics are warranted.

ABSTRACT Zhang raised comments about the phylogenetic analysis in Wang et al. (2025). Due to the incorrect upload of supplementary materials in Wang et al. (2025), it caused confusion among other researchers, and the phylogenetic results provided in the original text were also incorrect. This paper compared the differences between the erroneous matrix and the correct one, and provided explanations for different character codings. It also presented the correct phylogenetic results. This error does not affect the classification results and the conclusions of the original paper.

BACKGROUNDBreast hamartomas are rare benign breast tumors, with an incidence rate of 0.8%-4.8%. Further, the coexistence of hamartomas and carcinoma is also uncommon. Our case report presents a unique instance where invasive ductal carcinoma (IDC) and ductal carcinoma in situ were found both inside and outside a breast hamartoma. This is the second case reported in the literature.CASE SUMMARYA 51-year-old woman presented with a 6.0 cm breast tumor on mammography and ultrasound, with suspicious areas indicative of malignant transformation. Biopsy of the suspicious area confirmed IDC with intraductal carcinoma. Breast magnetic resonance imaging showed typical hamartoma changes with irregular areas of abnormal enhancement both inside and outside. A breast-conserving surgery was performed, and postoperative pathology confirmed mammary hamartoma, concurrent with IDC and intraductal carcinoma occurring both inside and outside the hamartoma. Subsequently, appropriate adjuvant therapy was initiated. Currently, the patient is in good condition. Breast cancer may be located both inside and outside the ipsilateral mammary hamartoma, which is difficult to detect preoperatively, especially when there is a focus of intraductal carcinoma, requiring accurate assessment of the tumor extent by modern imaging techniques. Early detection of the coexistence of cancer is clinically important as it can alter patient management.CONCLUSIONThis case emphasizes the importance of modern imaging techniques in accurately evaluating mammary hamartomas associated with malignancies prior to surgery.

Acute myocardial infarction (AMI) represents a significant global mortality factor. Alterations in nicotinamide metabolism within the myocardium post-AMI can influence the progression of the condition. Additionally, melanin plays a crucial role in nicotinamide metabolism and exhibits anti-inflammatory properties. Nevertheless, the diagnostic biomarkers for AMI that are based on nicotinamide metabo-lism and melanin-associated genes remain poorly defined. In this study, the AMI transcriptomic data from the Gene Expression Omnibus were analyzed to identify differentially expressed genes (DEGs) intersecting with nicotinamide metabolism and melatonin-related genes. Machine learning algorithms, including RandomForest, least absolute shrinkage and selection operator, and support vector machine-recursive feature elimination, were applied to select feature genes. Diagnostic markers were further evaluated based on area under the curve from receiver operating characteristic analysis. We identified 14 candidate genes, refined to 4 key genes, with NAMPT and BST1 ultimately selected as diagnostic biomarkers. These were used to classify AMI into two molecular subtypes. Immune landscape analysis revealed increased infiltration of monocytes, neutrophils, macrophages, and parainflammation in AMI. Enrichment analyses showed DEGs were mainly involved in innate immune response and cytokine production. Additionally, hsa-miR-34a-5p and hsa-miR-181b-5p were identified as potential regulators of NAMPT and BST1. In summary, NAMPT and BST1 are promising diagnostic biomarkers associated with nicotinamide metabolism and melatonin in AMI. The molecular subtyping based on these genes will enhance the management and hierarchical treatment of AMI, offering significant implications for clinical diagnosis and therapeutic strategies.

Current clinical practice uses a one-size-fits-all approach to define reference intervals for the results of diagnostic tests about thyroid function. This approach does not recognize subgroup differences according to age, sex, or race. To identify age-, sex-, and race-specific reference intervals for the common diagnostic tests that measure thyroid function and to examine how these new reference intervals reclassify persons into disease categories when compared with current reference intervals. Cross-sectional analysis. Data from the U.S. NHANES (National Health and Nutrition Examination Survey) supplemented with data from a multicenter Chinese study. A nationally representative sample from NHANES aged 20 years or older (n = 8308) supplemented with a Chinese database of routine health checkups from 49 hospitals in 10 provinces aged 18 years or older (n = 314 302). The thyroid function reference interval was defined as the interval of diagnostic indicator levels from the 2.5th (lower limit) to the 97.5th (upper limit) percentile by age, sex, and race subgroups. In 8308 NHANES participants, the 97.5th percentile levels of thyroid-stimulating hormone (TSH) increased with age, whereas total triiodothyronine (TT3) levels declined with age and total thyroxine (TT4) levels were stable across different ages. Women had higher TT4 levels, and White participants had higher TSH levels. Using current reference intervals, the prevalence of subclinical hypothyroidism increased from 2.4% for ages 20 to 29 years to 5.9% for ages 70 years and older. In contrast, using age-, sex-, and race-specific reference intervals reclassified 48.5% of persons with subclinical hypothyroidism as normal, especially women and White participants, and reclassified 31.2% of persons with subclinical hyperthyroidism as normal, especially women, Black participants, and Hispanic participants. When compared with the findings from U.S. participants, many of the findings from 314 302 Chinese participants were similar. Cross-sectional data; sample size limitations for subgroup. These findings should help establish more accurate reference intervals for thyroid diseases and facilitate development of a consensus about how to define and manage those diseases. National Key Research and Development Program of China and National Natural Science Foundation.