Objective To analyze the effect of releasing the lower pulmonary ligament on right residual lung expansion after right upper lobe resection under different body mass index (BMI) levels. Methods The clinical data of patients who underwent thoracoscopic right upper lobe resection in the First Affiliated Hospital with Nanjing Medical University from 2021 to 2022 were retrospectively analyzed. Patients were divided into a group A (17 kg/m2＜BMI≤23 kg/m2), a group B (23 kg/m2＜BMI≤29 kg/m2) and a group C (BMI＞29 kg/m2) according to BMI. The presence of residual cavity was judged by chest X-ray at 7-10 days after operation, the degree of compensation change of the right main bronchus angle was measured, and the changes in lung volume were determined by CT three-dimensional reconstruction. Results A total of 157 patients who underwent thoracoscopic right upper lobe resection were included, including 71 males and 86 females, with an average age of (59.7±11.2) years. There were 50 patients in the group A, 75 patients in the group B, and 32 patients in the group C. In the group A, compared with those without releasing the lower pulmonary ligament, patients with releasing had a lower incidence of postoperative residual cavity (P=0.016), greater changes in bronchus angle (P<0.001), and smaller changes in lung volume (P<0.001). In the group B and C, there was no significant effect of releasing the lower pulmonary ligament on postoperative residual cavity, bronchus angle, and lung volume changes (P>0.05). Conclusion For patients with thin and long body shape and low BMI, releasing the lower pulmonary ligament is helpful to promote the expansion of the residual lung after right upper lobe resection and reduce the occurrence of postoperative residual cavity in patients.

Tuberous sclerosis complex (TSC) is an autosomal dominant genetic disorder primarily caused by pathogenic variants in the TSC1 or TSC2 genes. It is characterized by multisystem hamartomatous lesions and neuropsychiatric manifestations. Here we report a young male patient with TSC involving multiple organs, caused by a heterozygous frameshift mutation in TSC2 (c.2071delC, p.Arg691Alafs^*7). The patient initially presented with classic facial angiofibromas and hypomelanotic macules, and subsequently developed psychiatric and behavioral disturbances with auditory hallucinations. Neuroimaging revealed an intracranial mass lesion, which was confirmed as a subependymal giant cell astrocytoma on postoperative histopathology following surgery performed at an outside institution. After admission, the patient underwent a comprehensive diagnostic workup, and multidisciplinary treatment evaluation revealed extensive multisystem involve-ment, including the nervous system, skin, kidneys, lungs, heart, eyes, pancreas, liver and bones. Combined with relevant literature, this article discusses the molecular mechanisms, clinical phenotypes, and comprehensive management of TSC, in order to provide a reference for the standardized and individualized management of this disease.

The recombinant human thyroid-stimulating hormone (rhTSH) can be used for differentiated thyroid cancer (DTC) preparation before ¹³¹I therapy, and follow-up. Since its approval by the American Food and Drug Administration (FDA) in 1998, rhTSH has been clinically used in European countries, the United States, and other countries for nearly 30 years. In April 2024, China’s first independently developed rhTSH agent was approved. Based on clinical experience and evidence from domestic and international studies, an expert consensus on the application of rhTSH has been developed following thorough consultations among experts. The consensus offers evidence-based recommendations to guide the appropriate use of rhTSH in clinical practice.

Objective To predict the lymph node metastasis status of patients with invasive pulmonary adenocarcinoma by constructing machine learning models based on primary tumor radiomics, peritumoral radiomics, and habitat radiomics, and to evaluate the predictive performance and generalization ability of different imaging features. Methods A retrospective analysis was performed on the clinical data of 1 263 patients with invasive pulmonary adenocarcinoma who underwent surgery at the Department of Thoracic Surgery, Jiangsu Province Hospital, from 2016 to 2019. Habitat regions were delineated by applying K-means clustering (average cluster number of 2) to the grayscale values of CT images. The peritumoral region was defined as a uniformly expanded area of 3 mm around the primary tumor. The primary tumor region was automatically segmented using V-net combined with manual correction and annotation. Subsequently, radiomics features were extracted based on these regions, and stacked machine learning models were constructed. Model performance was evaluated on the training, testing, and internal validation sets using the area under the receiver operating characteristic curve (AUC), F1 score, recall, and precision. Results After excluding patients who did not meet the screening criteria, a total of 651 patients were included. The training set consisted of 468 patients (181 males, 287 females) with an average age of (58.39±11.23) years, ranging from 29 to 78 years, the testing set included 140 patients (56 males, 84 females) with an average age of (58.81±10.70) years, ranging from 34 to 82 years, and the internal validation set comprised 43 patients (14 males, 29 females) with an average age of (60.16±10.68) years, ranging from 29 to 78 years. Although the habitat radiomics model did not show the optimal performance in the training set, it exhibited superior performance in the internal validation set, with an AUC of 0.952 [95%CI (0.87, 1.00)], an F1 score of 84.62%, and a precision-recall AUC of 0.892, outperforming the models based on the primary tumor and peritumoral regions. Conclusion The model constructed based on habitat radiomics demonstrated superior performance in the internal validation set, suggesting its potential for better generalization ability and clinical application in predicting lymph node metastasis status in pulmonary adenocarcinoma.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

Nutritional support therapy is one of the extremely important treatment methods for patients in the intensive care unit. Timely and effective nutritional support regimens can improve patients' immune function, reduce complications, and optimize clinical outcomes. Energy expenditure is influenced by multiple factors, including patients' baseline characteristics (such as physical condition, gender, age) and dynamic changes in indicators (such as body temperature, nutritional support regimens, and therapeutic interventions). The currently recognized "gold standard" for accurately assessing energy metabolism in clinical practice is the indirect calorimetry system, also known as the metabolic cart. This device monitors carbon dioxide production and oxygen consumption in real time and uses specific algorithms to estimate the metabolic proportions of the three major nutrients (carbohydrates, fats, and proteins) in energy expenditure. An appropriate nutrient ratio helps maintain the balance between supply and demand in the body's nutritional metabolism. In the management of critically ill patients, the application of the metabolic cart enables personalized nutritional therapy, avoiding over- or under-supply of energy and optimizing the use of medical resources. Furthermore, with real-time, quantitative data support from the energy metabolism monitoring system, clinicians can develop more precise nutritional intervention strategies, thereby improving patient prognosis. This article provides a systematic review of the technical features of the metabolic cart and its application value in various critical care scenarios, aiming to offer a reference for indirect calorimetry in clinical practice.
Humans ; Critical Illness/therapy* ; Nutritional Support ; Energy Metabolism ; Calorimetry, Indirect

OBJECTIVE: The objective of our study was to evaluate the vaccine effectiveness (VE) of the pentavalent rotavirus vaccine (RV5) among < 5-year-old children in three provinces of China during 2020-2024 via a propensity score-matched test-negative case-control study. METHODS: Electronic health records and immunization information systems were used to obtain data on acute gastroenteritis (AGE) cases tested for rotavirus (RV) infection. RV-positive cases were propensity score matched with RV-negative controls for age, visit month, and province. RESULTS: The study included 27,472 children with AGE aged 8 weeks to 4 years at the time of AGE diagnosis; 7.98% (2,192) were RV-positive. The VE (95% confidence interval, CI) of 1-2 and 3 doses of RV5 against any medically attended RV infection (inpatient or outpatient) was 57.6% (39.8%, 70.2%) and 67.2% (60.3%, 72.9%), respectively. Among children who received the 3rd dose before turning 5 months of age, 3-dose VE decreased from 70.4% (53.9%, 81.1%) (< 5 months since the 3rd dose) to 63.0% (49.1%, 73.0%) (≥ 1 year since the 3rd dose). The three-dose VE rate was 69.4% (41.3%, 84.0%) for RVGE hospitalization and 57.5% (38.9%, 70.5%) for outpatient-only medically attended RVGE. CONCLUSION Three-dose RV5 VE against rotavirus gastroenteritis (RVGE) in children aged < 5 years was higher than 1-2-dose VE. Three-dose VE decreased with time since the 3rd dose in children who received the 3rd dose before turning five months of age, but remained above 60% for at least one year. VE was higher for RVGE hospitalizations than for medically attended outpatient visits.
Humans ; Rotavirus Vaccines/immunology* ; China/epidemiology* ; Case-Control Studies ; Child, Preschool ; Infant ; Rotavirus Infections/epidemiology* ; Male ; Propensity Score ; Female ; Vaccine Efficacy ; Gastroenteritis/virology* ; Vaccines, Attenuated ; Rotavirus

Atherosclerosis(As)is one of the main causes of death in the global population.The main causes are hyperlipidemia,hypertension,obesity,etc.However,after avoiding traditional risks,As may still progress.In recent years,the role of microbial infection factors in As has been increasingly valued.This article reviews the correlation be-tween infection and As,and focuses on introducing the research progress on the mechanisms by which microbial infections such as Helicobacter pylori,Chlamydia pneumoniae,human immunodeficiency virus(HIV),and cytomegalovirus promote the development of As,aiming to discover the correlation between microbial infections and As and provide new ideas for the prevention and treatment of As.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Isosteviol is a tetracyclic diterpenoid compound obtained by hydrolysis of natural stevia glycoside under acidic conditions. It has many pharmacological activities, such as anti-tumor, hypoglycemic, anti-inflammatory and antibacterial. Due to its low water solubility, low activity and low bioavailability, isosteviol has poor performance. In order to overcome these shortcomings, scholars have obtained a large number of isosteviol derivatives with novel structures and excellent activity. In this paper, we review the recent progress in the research on the structure modification, biological activity, structure-activity relationship and microbial transformation of isosteviol, in order to provide a reference for the development of new drugs of isosteviol and its derivatives.