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.

PURPOSE: To methodically assess the effectiveness of augmentative plating (AP) and exchange nailing (EN) in managing nonunion following intramedullary nailing for long bone fractures of the lower extremity. METHODS: PubMed, EMBASE, Web of Science, and the Cochrane Library were searched to gather clinical studies regarding the use of AP and EN techniques in the treatment of nonunion following intramedullary nailing of lower extremity long bones. The search was conducted up until May 2023. The original studies underwent an independent assessment of their quality, a process conducted utilizing the Newcastle-Ottawa scale. Data were retrieved from these studies, and meta-analysis was executed utilizing Review Manager 5.3. RESULTS: This meta-analysis included 8 studies involving 661 participants, with 305 in the AP group and 356 in the EN group. The results of the meta-analysis demonstrated that the AP group exhibited a higher rate of union (odds ratio: 8.61, 95% confidence intervals (CI): 4.12 - 17.99, p < 0.001), shorter union time (standardized mean difference (SMD): -1.08, 95% CI: -1.79 - -0.37, p = 0.003), reduced duration of the surgical procedure (SMD: -0.56, 95% CI: -0.93 - -0.19, p = 0.003), less bleeding (SMD: -1.5, 95% CI: -2.81 - -0.18, p = 0.03), and a lower incidence of complications (relative risk: -0.17, 95% CI: -0.27 - -0.06, p = 0.001). In the subgroup analysis, the time for union in the AP group in nonisthmal and isthmal nonunion of lower extremity long bones was shorter compared to the EN group (nonisthmal SMD: -1.94, 95% CI: -3.28 - -0.61, p < 0.001; isthmal SMD: -1.08, 95% CI: -1.64 - -0.52, p = 0.002). CONCLUSION In the treatment of nonunion in diaphyseal fractures of the long bones in the lower extremity, the AP approach is superior to EN, both intraoperatively (with reduced duration of the surgical procedure and diminished blood loss) and postoperatively (with an elevated union rate, shorter union time, and lower incidence of complications). Specifically, in the management of nonunion of lower extremity long bones with non-isthmal and isthmal intramedullary nails, AP demonstrated shorter union time in comparison to EN.
Humans ; Bone Nails/adverse effects* ; Bone Plates/adverse effects* ; Femoral Fractures/surgery* ; Fracture Fixation, Intramedullary/methods* ; Fractures, Ununited/surgery* ; Lower Extremity/injuries*

PURPOSE: We carried out the study aiming to explore and analyze the risk factors, the distribution of pathogenic bacteria, and their antibiotic-resistance characteristics influencing the occurrence of surgical site infection (SSI), to provide valuable assistance for reducing the incidence of SSI after traumatic fracture surgery. METHODS: A retrospective case-control study enrolling 3978 participants from January 2015 to December 2019 receiving surgical treatment for traumatic fractures was conducted at Tangdu Hospital of Air Force Medical University. Baseline data, demographic characteristics, lifestyles, variables related to surgical treatment, and pathogen culture were harvested and analyzed. Univariate analyses and multivariate logistic regression analyses were used to reveal the independent risk factors of SSI. A bacterial distribution histogram and drug-sensitive heat map were drawn to describe the pathogenic characteristics. RESULTS: Included 3978 patients 138 of them developed SSI with an incidence rate of 3.47% postoperatively. By logistic regression analysis, we found that variables such as gender (males) (odds ratio (OR) = 2.012, 95% confidence interval (CI): 1.235 - 3.278, p = 0.005), diabetes mellitus (OR = 5.848, 95% CI: 3.513 - 9.736, p < 0.001), hypoproteinemia (OR = 3.400, 95% CI: 1.280 - 9.031, p = 0.014), underlying disease (OR = 5.398, 95% CI: 2.343 - 12.438, p < 0.001), hormonotherapy (OR = 11.718, 95% CI: 6.269 - 21.903, p < 0.001), open fracture (OR = 29.377, 95% CI: 9.944 - 86.784, p < 0.001), and intraoperative transfusion (OR = 2.664, 95% CI: 1.572 - 4.515, p < 0.001) were independent risk factors for SSI, while, aged over 59 years (OR = 0.132, 95% CI: 0.059 - 0.296, p < 0.001), prophylactic antibiotics use (OR = 0.082, 95% CI: 0.042 - 0.164, p < 0.001) and vacuum sealing drainage use (OR = 0.036, 95% CI: 0.010 - 0.129, p < 0.001) were protective factors. Pathogens results showed that 301 strains of 38 species of bacteria were harvested, among which 178 (59.1%) strains were Gram-positive bacteria, and 123 (40.9%) strains were Gram-negative bacteria. Staphylococcus aureus (108, 60.7%) and Enterobacter cloacae (38, 30.9%) accounted for the largest proportion. The susceptibility of Gram-positive bacteria to Vancomycin and Linezolid was almost 100%. The susceptibility of Gram-negative bacteria to Imipenem, Amikacin, and Meropenem exceeded 73%. CONCLUSION Orthopedic surgeons need to develop appropriate surgical plans based on the risk factors and protective factors associated with postoperative SSI to reduce its occurrence. Meanwhile, it is recommended to strengthen blood glucose control in the early stage of admission and for surgeons to be cautious and scientific when choosing antibiotic therapy in clinical practice.
Humans ; Surgical Wound Infection/epidemiology* ; Male ; Female ; Risk Factors ; Retrospective Studies ; Middle Aged ; Adult ; Case-Control Studies ; Fractures, Bone/surgery* ; Aged ; Drug Resistance, Bacterial ; Logistic Models ; Anti-Bacterial Agents/therapeutic use* ; Incidence ; Bacteria/drug effects*

Objective This study aims to explore the efficacy and complication rates of the transcranial approach(TCA)and extended endoscopic endonasal approach(EEEA)for the treatment of craniopharyngiomas based on the QST classification,providing a scientific reference for clinical decision-making on surgical approach.Methods A total of 151 patients who underwent craniopharyngioma surgery at our center from January 2018 to December 2023 were enrolled.The patients were categorized into Q-CP(suprasellar type),S-CP(infundibular type),and T-CP(tuberal type)according to the QST classification.Systematic collection and analysis were performed on the outcomes of TCA and EEEA treatments,respectively.The differences in effectiveness between the two approaches were evaluated based on the QST classification.Results The improvement rate of visual symptoms was overall higher in the EEEA group than in the TCA group(59.1%vs.36.5%,P=0.006),and the visual deterioration rate was lower(3.0%vs.14.1%,P=0.006).However,the incidence of cerebrospinal fluid leakage was higher in the EEEA group(15.2%vs.3.5%,χ2=4.986,P=0.026).The incidence of postoperative seizures(8.2%vs.0,P=0.019),brain contusions(10.6%vs.0,P=0.005),and subdural hematoma(9.4%vs.0%,P=0.01)was higher in the TCA group.For patients with Q-CP type,the EEEA group had a higher rate of total tumor resection(92.9%vs.65.2%,P=0.025)and a lower recurrence rate(3.6%vs.21.7%,P=0.047),with shorter hospital stays and lower postoperative costs.The TCA group had higher intraoperative blood loss in this type(300 mL vs.200 mL,Z=-2.261,P=0.024).For S-CP type patients,the EEEA group showed a higher rate of total tumor resection(91.3%vs.74.2%)and a lower recurrence rate(0 vs.12.9%,P=0.031),with lower postoperative hospital costs.In T-CP type,due to the deeper location,EEEA showed limitations in protecting hypothalamic function and the TCA group had a better postoperative hypothalamic function score(P=0.035).Conclusion Based on QST classification,EEEA has advantages in Q-CP and S-CP types and is recommended as the preferred surgical procedure;In the T-CP type,TCA surgery is more helpful in protecting hypothalamic function.

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.

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.