Objective To investigate the causal relationship between metabolic syndrome and breast cancer by using a bidirectional two-sample Mendelian randomization (MR) approach. Methods Genome-wide association study (GWAS) summary statistics for metabolic syndrome and breast cancer were acquired from the Integrative Epidemiology Unit GWAS database and the GWAS Catalog, with populations encompassing the United States and East Asia. A bidirectional causal design was employed: a forward analysis with metabolic syndrome as the exposure and breast cancer as the outcome, followed by a reverse analysis wherein their roles were interchanged. The inverse-variance weighting (IVW) method was primarily used for effect estimation, supplemented by MR-Egger regression, the weighted median method, the simple mode method, and the weighted mode method. Instrument variable strength was screened using the F-statistic (F>10). Robustness of the results was assessed through heterogeneity tests, horizontal pleiotropy tests, forest plots, and leave-one-out sensitivity analyses. Results The IVW analysis indicated no significant causal relationship between metabolic syndrome and breast cancer (OR=1.00, 95%CI: 0.97-1.03), P>0.05). Sensitivity analyses yielded consistent results, suggesting the good robustness of the study findings. Conclusion This study found no evidence to support a causal relationship, either positive or negative, between metabolic syndrome and breast cancer.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

Objective:To describe epidemiological characteristics and their influencing factors of diabetes and pre-diabetes among adult residents in Hainan Province and provide a theoretical basis to develop epidemic prevention and control strategies for diabetes.Methods:This study used a two-stage unequal proportion cluster sampling method, and 32 857 subjects (≥18 years old) were collected from 24 cities/counties/districts in Hainan Province. All the subjects were investigated with questionnaires, physical examination, and laboratory tests from January to June 2023. The χ2 and Mantel-Haenszel trend χ2 tests were used to analyze the data. Multivariate logistic regression was used to analyze the factors influencing diabetes and pre-diabetes. SPSS 23.0 software was used to analyze the data. Results:The crude prevalence of diabetes and pre-diabetes in adult residents of Hainan Province were 18.1% and 22.8%, while the weighted rates were 13.7% and 20.7%, respectively. The results of multivariate logistic regression analysis showed that: aging (30-39 years old: OR=2.65, 95% CI: 2.06-3.41; 40-49 years old: OR=5.64, 95% CI: 4.40-7.24; 50- 59 years old: OR=9.88, 95% CI: 7.71-12.67; 60-69 years old: OR=18.34, 95% CI: 14.28-23.55; 70-79 years old: OR=21.30, 95% CI: 16.41-27.65; 80 years old and above: OR=24.13, 95% CI: 17.94-32.46), nationality (Li minority group: OR=1.50, 95% CI: 1.38-1.63; other ethnic groups: OR=1.53, 95% CI: 1.20-1.94), urban ( OR=1.12, 95% CI: 1.04-1.21), central obesity ( OR=2.14, 95% CI: 2.01-2.29), higher frequency of alcohol consumption (5-7 day/week: OR=1.24, 95% CI: 1.11-1.38), physical inactivity ( OR=1.09, 95% CI: 1.02-1.17) were risk factors for diabetes, while aging (30-39 years old: OR=1.53, 95% CI: 1.31-1.79; 40-49 years old: OR=2.36, 95% CI: 2.01-2.76; 50-59 years old: OR=3.03, 95% CI: 2.58-3.55; 60-69 years old: OR=4.22, 95% CI: 3.58-4.97; 70-79 years old: OR=5.05, 95% CI: 4.23-6.04; 80 years old and above: OR=6.08, 95% CI: 4.86-7.61), nationality: (Li minority group: OR=1.18, 95% CI: 1.10-1.28; other ethnic groups: OR=1.40, 95% CI: 1.14-1.71), urban ( OR=1.12, 95% CI: 1.04-1.19), central obesity ( OR=1.72, 95% CI: 1.62-1.83), higher frequency of alcohol consumption (1-4 day/week: OR=1.12, 95% CI: 1.01-1.23; 5-7 day/week: OR=1.35, 95% CI: 1.22-1.49) were risk factors for pre-diabetes. Conclusions:The epidemic situation of diabetes and pre-diabetes among adult residents in Hainan Province was not optimistic. In order to control the development of abnormal blood glucose, measures and targeted health education should be carried out to strengthen the screening, treatment, and management of people with abnormal blood glucose among different populations.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To systematically evaluate the fairness of traditional Chinese medicine (TCM) healthcare resource allocation at the prefecture-level in China using the healthcare resource agglomeration degree (HRAD) method, so as to provide empirical evidence for optimizing resource distribution.Methods:Data on TCM healthcare resources (including the number of TCM institutions, public TCM hospitals, TCM hospital beds, and TCM healthcare technicians) were collected from 333 prefecture-level regions in 2023. The HRAD method was employed to assess fairness in geographic allocation (HRAD i) and population-based allocation (HRAD i/PAD i). A multi-indicator comprehensive evaluation was conducted using the entropy weight method to determine weighting coefficients. Results:Significant disparities were observed in the geographic agglomeration of TCM resources (HRAD i) in China. Resource-rich regions (HRAD i>5) were primarily concentrated in eastern and some central-western provinces, while resource-scarce regions (HRAD i<1) were mainly distributed in western, northeastern, and parts of central and eastern provinces. Analysis of population-based fairness (HRAD i/PAD i) revealed that most prefecture-level cities nationwide had ratios<1, with only 8 provinces having more cities with ratios>1 than<1. The comprehensive evaluation showed that top-ranked cities in the east (e.g., Hangzhou, Dongying, Shenzhen), central region (e.g., Taiyuan, Zhengzhou), and west (e.g., Hainan Prefecture, Alxa League) were predominantly core cities or sparsely populated areas. Conclusions:China′s prefecture-level TCM healthcare resource allocation exhibits significant geographic and population-based inequities, with excessive concentration in provincial capitals and developed cities. Urgent strategies are needed to optimize resource allocation, enhance fairness and accessibility, including promoting the decentralization of high-quality resources, strengthening regional collaborative support, enhancing talent attraction in underdeveloped areas, and leveraging information technology to improve efficiency.

Objective:To analyze the baseline characteristics and prognostic factors of Pneumocystis carinii pneumonia (PCP) in patients with liver diseases (LD), and to develop the nomogram prognosis model. Methods:The patients with liver diseases complicated with PCP (LD-PCP) who admitted to Beijing Youan Hospital, Capital Medical University from January 1st, 2021 to October 31st, 2024 were enrolled in this study. This study was a retrospective case-control study. Data were collected, including baseline characteristics at admission and clinical outcomes. Multivariate logistic regression analysis was employed to identify the independent risk factors of poor prognosis in LD-PCP patients. Subsequently, a nomogram was developed to construct the prognostic model. The performance of this model was evaluated using the receiver operater characteristic (ROC) curve and calibration curve.Results:A total of 61 patients with LD-PCP were enrolled, including 21 in the death group and 40 in the survival group. Multivariate logistic regression analysis revealed that co-infection with Aspergillus and elevated lactate dehydrogenase (LDH) levels were independent risk factors for mortality in patients with LD-PCP (odds ratio ( OR)=12.802, 95% confidence interval ( CI) 1.334 to 122.845, P=0.027; OR=1.009, 95% CI 1.002 to 1.016, P=0.014). The predictive value of prognostic model based on the nomogram was better evidenced by the ROC curve, which yielded an area under the curve (AUC) of 0.835 (95% CI 0.725 to 0.944), with the sensitivity of 71.4% and the specificity of 87.5%. The predictive accuracy of the model was further validated by the calibration curve, and the Brier value was 0.151, the model fitting line had a high degree of agreement with the standard reference line ( P=0.953). Conclusions:Co-infection with Aspergillus and LDH levels are independent risk factors for the poor prognosis of patients with LD-PCP. The prognosis model based on the nomogram has better predictive value and clinical practicality, which could identify high-risk patients in the early stage, and provide theoretical guidance on the patient management.

This study aimed to introduce a modified Byars staged procedure and investigate its application value in patients with severe hypospadias. We retrospectively analyzed the clinical data of patients with severe hypospadias admitted to the First Affiliated Hospital of Sun Yat-sen University (Guangzhou, China) between October 2012 and October 2022. In total, 31 patients underwent the conventional Byars procedure (conventional group), and 45 patients underwent the modified Byars staged procedure (modified group). Our modified strategy was built upon the standard Byars procedure by incorporating glansplasty during the first stage and employing a Y-shaped flap in conjunction with a glandular tunnel for urethroplasty during the second stage. Notably, there were no statistically significant differences in the preoperative baseline characteristics, duration of surgery, amount of blood loss, or occurrence of postoperative complications, including urethral fistula, stricture and diverticulum, or penile curvature, between the conventional and modified groups. However, there was a significantly lower incidence of coronal sulcus fistula (0 vs 16.1%, P = 0.02) and glans dehiscence (0 vs 12.9%, P = 0.02) in the surgical group than that in the conventional group. In addition, the modified group exhibited a notably greater rate of normotopic urethral opening (100.0% vs 83.9%, P = 0.01) and a higher mean score on the Hypospadias Objective Penile Evaluation (HOPE; mean ± standard error of mean: 8.6 ± 0.2 vs 7.9 ± 0.3, P = 0.02) than did the conventional group. In conclusion, the modified Byars staged procedure significantly reduced the risks of glans dehiscence and coronal sulcus fistula. Consequently, it offers a promising approach for achieving favorable penile esthetics, thereby providing a reliable therapeutic option for severe hypospadias.
Humans ; Hypospadias/surgery* ; Male ; Retrospective Studies ; Urologic Surgical Procedures, Male/methods* ; Child, Preschool ; Child ; Postoperative Complications/etiology* ; Urethra/surgery* ; Plastic Surgery Procedures/methods* ; Surgical Flaps ; Penis/surgery* ; Treatment Outcome ; Infant

Neutrophil extracellular traps (NETs), intricate reticular structures released by activated neutrophils, play a pivotal regulatory role in the pathogenesis of malignant tumors. Lung cancer is one of the most prevalent malignancies globally, with persistently high incidence and mortality rates. Recent studies have revealed that NETs dynamically modulate the tumor microenvironment through unique pathological mechanisms, exhibiting complex immunoregulatory characteristics during the progression of lung cancer, and this discovery has increasingly become a focal point in tumor immunology research. This paper provides a comprehensive review of the latest advancements in NETs research related to lung cancer, offering an in-depth analysis of their impact on lung cancer progression, their potential diagnostic value, and the current state of research on targeting NETs for lung cancer prevention and treatment. The aim is to propose novel strategies to enhance therapeutic outcomes and improve the prognosis for lung cancer patients.
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Extracellular Traps/immunology* ; Humans ; Lung Neoplasms/metabolism* ; Neutrophils/metabolism* ; Animals ; Tumor Microenvironment

OBJECTIVE: To evaluate the efficacy and safety of Shexiang Tongxin Dropping Pill (STDP) in treating stable angina patients with phlegm-heat and blood-stasis syndrome by exercise duration and metabolic equivalents. METHODS: This multicenter, randomized, double-blind, placebo-controlled clinical trial enrolled stable angina patients with phlegm-heat and blood-stasis syndrome from 22 hospitals. They were randomized 1:1 to STDP (35 mg/pill, 6 pills per day) or placebo for 56 days. The primary outcome was the exercise duration and metabolic equivalents (METs) assessed by the standard Bruce exercise treadmill test after 56 days of treatment. The secondary outcomes included the total angina symptom score, Chinese medicine (CM) symptom scores, Seattle Angina Questionnaire (SAQ) scores, changes in ST-T on electrocardiogram and adverse events (AEs). RESULTS: This trial enrolled 309 patients, including 155 and 154 in the STDP and placebo groups, respectively. STDP significantly prolonged exercise duration with an increase of 51.0 s, compared to a decrease of 12.0 s with placebo (change rate: -11.1% vs. 3.2%, P<0.01). The increase in METs was significantly greater in the STDP group than in the placebo group (change: -0.4 vs. 0.0, change rate: -5.0% vs. 0.0%, P<0.01). The improvement of total angina symptom scores (25.0% vs. 0.0%), CM symptom scores (38.7% vs. 11.8%), reduction of nitroglycerin consumption (100.0% vs. 11.3%), and all domains of SAQ, were significantly greater with STDP than placebo (all P<0.01). The changes in Q-T intervals at 28 and 56 days from baseline were similar between the two groups (both P>0.05). Twenty-five participants (16.3%) with STDP and 16 (10.5%) with placebo experienced AEs (P=0.131), with no serious AEs observed. CONCLUSION STDP could improve exercise tolerance in patients with stable angina and phlegm-heat and blood stasis syndrome, with a favorable safety profile. (Registration No. ChiCTR-IPR-15006020).
Humans ; Double-Blind Method ; Drugs, Chinese Herbal/adverse effects* ; Male ; Female ; Middle Aged ; Angina, Stable/physiopathology* ; Aged ; Syndrome ; Treatment Outcome ; Placebos ; Tablets