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.

Lung cancer is the most common malignant tumor worldwide, ranking first in both incidence and mortality rates. According to the latest statistics from the International Agency for Research on Cancer (IARC), approximately 2.5 million new cases and around 1.8 million deaths from lung cancer occurred in 2022, placing a tremendous burden on global healthcare systems. The high mortality rate of lung cancer is closely linked to its subtle early symptoms, which often lead to diagnosis at advanced stages. This not only complicates treatment but also results in substantial economic losses. Current treatment options for lung cancer include surgery, radiotherapy, chemotherapy, targeted drug therapy, and immunotherapy. Among these, immunotherapy has emerged as the most groundbreaking advancement in recent years, owing to its unique antitumor mechanisms and impressive clinical benefits. Unlike traditional therapies such as radiotherapy and chemotherapy, immunotherapy activates or enhances the patient’s immune system to recognize and eliminate tumor cells. It offers advantages such as more durable therapeutic effects and relatively fewer toxic side effects. The main approaches to lung cancer immunotherapy include immune checkpoint inhibitors, tumor-specific antigen-targeted therapies, adoptive cell therapies, cancer vaccines, and oncolytic virus therapies. Among these, immune checkpoint inhibitors and tumor-specific antigen-targeted therapies have received approval from the U.S. Food and Drug Administration (FDA) for clinical use in lung cancer, significantly improving outcomes for patients with advanced non-small cell lung cancer. Although other immunotherapy strategies are still in clinical trials, they show great potential in improving treatment precision and efficacy. This article systematically reviews the latest research progress in lung cancer immunotherapy, including the development of novel immune checkpoint molecules, optimization of treatment strategies, identification of predictive biomarkers, and findings from recent clinical trials. It also discusses the current challenges in the field and outlines future directions, such as the development of next-generation immunotherapeutic agents, exploration of more effective combination regimens, and the establishment of precise efficacy prediction systems. The aim is to provide a valuable reference for the continued advancement of lung cancer immunotherapy.

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.

ObjectiveTo investigate the possible mechanism of Shufeng Jiedu capsules （SFJD） in alleviating influenza A （H1N1） virus pneumonia and focus on its effect on Toll-like receptor （TLR） signaling pathway in respiratory epithelial cells. MethodsA mouse model of viral pneumonia was established via the A/PR/8/34 （PR8） strain of influenza A virus. Mice were randomly divided into a normal group， a PR8 infection （PR8） group， and an SFJD group （8.4 g·kg^-1）， with 10 mice in each group. The day of infection was designated as day 1. The SFJD group was administered intragastrically at a volume of 20 mL·kg^-1 daily， while the normal and PR8 groups were given an equal volume of deionized water. Micro-computed tomography （Micro-CT） was performed on day 5， and the mice were dissected to collect their lungs， after which the lung index was calculated to verify the therapeutic effect of SFJD. Single-cell sequencing was used to analyze the differentially expressed genes in respiratory epithelial cells. Multiplex fluorescence immunohistochemistry was employed to detect the expression of TLR， tumor necrosis factor receptor-associated factor 6 （TRAF6）， and myeloid differentiation factor 88 （MyD88） proteins in epithelial cell adhesion molecule （EpCAM）-positive cells， and the proportion of respiratory epithelial cells expressing TLR pathway proteins was calculated. Respiratory epithelial cells were then sorted by flow cytometry， and Western blot was used to detect the expression of TLR， MyD88， TRAF6， Toll-interleukin receptor domain-containing adaptor inducing interferon-β （TRIF）， inhibitor of κB kinase α （IKKα）， and nuclear factor-κB （NF-κB） in the sorted epithelial cells. Enzyme-linked immunosorbent assay （ELISA） was used to measure the levels of interleukin-1β （IL-1β） and tumor necrosis factor-α （TNF-α） in lung tissue. ResultsAt the transcriptional level， SFJD reversed the expression of TLR signaling pathway genes in respiratory epithelial cells， downregulating multiple TLR signaling pathway-related genes （P<0.01）. At the protein level， SFJD significantly reduced the proportion of respiratory epithelial cells expressing TLR3 （P<0.05）， the expression levels of TLR2， TLR3， TLR4， TRIF， TRAF6， IKKα， and NF-κB in epithelial cells（P<0.05， P<0.01）， as well as the levels of pro-inflammatory cytokines IL-1β and TNF-α in lung tissue （P<0.01）. ConclusionSFJD may alleviate viral pneumonia by suppressing the expression of TLR in respiratory epithelial cells and their subsequent signaling cascades.

Basket trial, as an innovative clinical trial design concept, marks the transformation of medical research from the traditional large-scale and single-disease treatment to the precise and individualized treatment. By gradually incorporating the Bayesian method during development, the trial design becomes more scientific and reasonable and increases its efficiency. The fundamental principle of the Bayesian method is the utilization of prior knowledge in conjunction with new observational data to dynamically update the posterior probability. This flexibility enhances the basket trial's capacity to effectively adapt to variations during the research process. Consequently, it enables researchers to dynamically adjust research strategies based on accumulated data and improve the predictive accuracy regarding treatment responses. In addition, the design concept of the basket trial aligns with the traditional Chinese medicine(TCM) principle of "homotherapy for heteropathy". The principle of "homotherapy for heteropathy" emphasizes that under certain conditions, different diseases may have the same treatment. Similarly, basket trials allow using a uniform trial design across multiple diseases, offering enhanced operational and significant practical value in the realm of TCM, particularly within the context of syndrome-based disease research. By introducing basket trials, the design of TCM clinical studies will be more scientific and yield higher-quality evidence. This study systematically categorized various Bayesian methods and models utilized in basket trials, evaluated their strengths and weaknesses, and identified their appropriate application contexts, so as to offer a practical guide for designing basket trials in the realm of TCM.
Bayes Theorem ; Humans ; Medicine, Chinese Traditional/methods* ; Research Design ; Clinical Trials as Topic/methods* ; Drugs, Chinese Herbal/therapeutic use*

This study aims to explore the medication rules and mechanisms of treating chronic renal failure(CRF) by Jinling medical school based on data mining, network pharmacology, and experimental validation systematically and deeply. Firstly, the study selected the papers published by the inherited clinicians in Jinling medical school in Chinese journals using the subject headings named "traditional Chinese medicine(TCM) + chronic renal failure", "TCM + chronic renal inefficiency", or "TCM + consumptive disease" in China National Knowledge Infrastructure, Wanfang, and VIP Chinese Science and Technology Periodical Database and screened TCM formulas for treating CRF according to inclusion and exclusion criteria. The study analyzed the frequency of use of single TCM and the four properties, five tastes, channel tropism, and efficacy of TCM used with high frequency and performed association rule and clustering analysis, respectively. As a result, a total of 215 TCM formulas and 235 different single TCM were screened, respectively. The TCM used with high frequency included Astragali Radix, Rhei Radix et Rhizoma, Salviae Miltiorrhizae Radix et Rhizoma, Poria, and Atractylodis Macrocephalae Rhizoma(top 5). The single TCM characterized by "cold properties, sweet flavor, and restoring spleen channel" and the TCM with the efficacy of tonifying deficiency had the highest frequency of use, respectively. Then, the TCM with the rules of "blood-activating and stasis-removing" and "diuretic and dampness-penetrating" appeared. In addition, the core combination of TCM [(Hexin Formula, HXF)] included "Astragali Radix, Rhei Radix et Rhizoma, Poria, Salviae Miltiorrhizae Radix, and Angelicae Sinensis Radix". The network pharmacology analysis showed that HXF had 91 active compounds and 250 corresponding protein targets including prostaglandin-endoperoxide synthase 2(PTGS2), PTGS1, sodium voltage-gated channel alpha subunit 5(SCN5A), cholinergic receptor muscarinic 1(CHRM1), and heat shock protein 90 alpha family class A member 1(HSP90AA1)(top 5). Gene Ontology(GO) function analysis revealed that the core targets of HXF predominantly affected biological processes, cellular components, and molecular functions such as positive regulation of transcription by ribonucleic acid polymerase Ⅱ and DNA template transcription, formation of cytosol, nucleus, and plasma membrane, and identical protein binding and enzyme binding. Kyoto Encyclopedia of Genes and Genomes(KEGG) analysis revealed that CRF-related genes were involved in a variety of signaling pathways and cellular metabolic pathways, primarily involving "phosphatidylinositol 3-kinase(PI3K)-protein kinase B(Akt) pathway" and "advanced glycation end products-receptor for advanced glycation end products". Molecular docking results showed that the active components in HXF such as isomucronulatol 7-O-glucoside, betulinic acid, sitosterol, and przewaquinone B might be crucial in the treatment of CRF. Finally, a modified rat model with renal failure induced by adenine was used, and the in vivo experimental confirmation was performed based on the above-mentioned predictions. The results verify that HXF can regulate mitochondrial autophagy in the kidneys and the PI3K-Akt-mammalian target of rapamycin(mTOR) signaling pathway activation at upstream, so as to alleviate renal tubulointerstitial fibrosis and then delay the progression of CRF.
Data Mining ; Drugs, Chinese Herbal/chemistry* ; Network Pharmacology ; Humans ; Kidney Failure, Chronic/metabolism* ; Medicine, Chinese Traditional ; China

OBJECTIVES: To explore the predictive factors for hemodynamically significant patent ductus arteriosus (hsPDA) in preterm infants and to construct a nomogram prediction model for hsPDA occurrence in this population. METHODS: A retrospective analysis was conducted on the clinical data of preterm infants with gestational age <32 weeks diagnosed with patent ductus arteriosus (PDA) who were delivered at Nanjing Women and Children's Healthcare Hospital from January 2020 to December 2022. The subjects were divided into an hsPDA group (52 cases) and a non-hsPDA group (176 cases) based on the presence of hsPDA. Univariate analysis and multivariate logistic regression analysis were performed to screen predictive variables regarding the general information of the infants at birth, maternal pregnancy and delivery conditions, and relevant indicators during hospitalization. A nomogram prediction model for hsPDA occurrence was constructed using R software in preterm infants. Internal validation was performed using the Bootstrap method. Finally, the predictive model was evaluated for calibration, discrimination ability, and clinical utility. RESULTS: Multivariate regression analysis showed that the ratio of the left atrium to aorta diameter (LA/AO), mode of delivery (vaginal), and duration of mechanical ventilation were independent predictive factors for hsPDA in preterm infants (P<0.05). Based on the results of univariate analysis and multivariate logistic regression analysis, variables used to construct the nomogram prediction model for hsPDA risk included: LA/AO ratio, mode of delivery (vaginal), duration of mechanical ventilation, 5-minute Apgar score, and the presence of neonatal respiratory distress syndrome requiring surfactant therapy. The area under the receiver operating characteristic curve for this model was 0.876 (95%CI: 0.824-0.927), and the calibrated curve was close to the ideal reference line, indicating good calibration. The Hosmer-Lemeshow test demonstrated that the model fit well, and the clinical decision curve was above the extreme curves. CONCLUSIONS The nomogram prediction model, constructed using five variables (LA/AO ratio, vaginal delivery, duration of mechanical ventilation, 5-minute Apgar score, and the presence of neonatal respiratory distress syndrome requiring surfactant therapy), has reference significance for predicting the occurrence of hsPDA in preterm infants and provides valuable guidance for the early clinical identification of hsPDA.
Humans ; Ductus Arteriosus, Patent/etiology* ; Nomograms ; Female ; Infant, Newborn ; Infant, Premature ; Retrospective Studies ; Male ; Hemodynamics ; Logistic Models ; Pregnancy

BACKGROUND: Based on the China-VHD database, this study sought to develop and validate a Valvular Heart Disease- specific Age-adjusted Comorbidity Index (VHD-ACI) for predicting mortality risk in patients with VHD. METHODS & RESULTS: The China-VHD study was a nationwide, multi-centre multi-centre cohort study enrolling 13,917 patients with moderate or severe VHD across 46 medical centres in China between April-June 2018. After excluding cases with missing key variables, 11,459 patients were retained for final analysis. The primary endpoint was 2-year all-cause mortality, with 941 deaths (10.0%) observed during follow-up. The VHD-ACI was derived after identifying 13 independent mortality predictors: cardiomyopathy, myocardial infarction, chronic obstructive pulmonary disease, pulmonary artery hypertension, low body weight, anaemia, hypoalbuminaemia, renal insufficiency, moderate/severe hepatic dysfunction, heart failure, cancer, NYHA functional class and age. The index exhibited good discrimination (AUC, 0.79) and calibration (Brier score, 0.062) in the total cohort, outperforming both EuroSCORE II and ACCI (P < 0.001 for comparison). Internal validation through 100 bootstrap iterations yielded a C statistic of 0.694 (95% CI: 0.665-0.723) for 2-year mortality prediction. VHD-ACI scores, as a continuous variable (VHD-ACI score: adjusted HR (95% CI): 1.263 (1.245-1.282), P < 0.001) or categorized using thresholds determined by the Yoden index (VHD-ACI ≥ 9 vs. < 9, adjusted HR (95% CI): 6.216 (5.378-7.184), P < 0.001), were independently associated with mortality. The prognostic performance remained consistent across all VHD subtypes (aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation, tricuspid valve disease, mixed aortic/mitral valve disease and multiple VHD), and clinical subgroups stratified by therapeutic strategy, LVEF status (preserved vs. reduced), disease severity and etiology. CONCLUSION The VHD-ACI is a simple 13-comorbidity algorithm for the prediction of mortality in VHD patients and providing a simple and rapid tool for risk stratification.

BACKGROUND: Modern acupuncture anesthesia is a combination of Chinese and Western medicine that integrates the theories of acupuncture with anesthesia. However, some clinical studies of acupuncture anesthesia lack specific descriptions of randomization, allocation concealment, and blinding processes, with subsequent systematic reviews indicating a risk of bias. OBJECTIVE: Clinical trial registration is essential for the enhancement of the quality of clinical trials. This study aims to summarize the status of clinical trial registrations for acupuncture anesthesia listed on the World Health Organization International Clinical Trials Registry Platform (ICTRP). SEARCH STRATEGY: We searched the ICTRP for clinical trials related to acupuncture anesthesia registered between January 1, 2001 and May 31, 2023. Additionally, related publications were retrieved from PubMed, Cochrane Library, Embase, China National Knowledge Infrastructure, China Science and Technology Journal Database, and Wanfang Data. Registrations and publications were analyzed for consistency in trial design characteristics. INCLUSION CRITERIA: Clinical trials that utilized one of several acupuncture-related therapies in combination with pharmacological anesthesia during the perioperative period were eligible for this review. DATA EXTRACTION AND ANALYSIS: Data extracted from articles included type of surgical procedure, perioperative symptoms, study methodology, type of intervention, trial recruitment information, and publication information related to clinical enrollment. RESULTS: A total of 166 trials related to acupuncture anesthesia from 21 countries were included in the analysis. The commonly reported symptoms in the included studies were postoperative nausea and vomiting (19.9%) and postoperative pain (13.3%). The concordance between the publications and the trial protocols in the clinical registry records was poor, with only 31.7% of the studies being fully compatible. Inconsistency rates were high for sample size (39.0%, 16/41), blinding (36.6%, 15/41), and secondary outcome indicators (24.4%, 10/41). CONCLUSION The volume of acupuncture anesthesia clinical trials registered in international trial registries over the last 20 years is low, with insufficient disclosure of results. Postoperative nausea and vomiting as well as postoperative pain, are the most investigated for acupuncture intervention. Please cite this article as: Li Y, Liu YN, Guo Z, Gu ME, Wang WJ, Zhu Y, Zhuang XJ, Chen LM, Zhou J, Li J. Current situation of clinical trial registration in acupuncture anesthesia: A scoping review. J Integr Med. 2025; 23(3): 256-263.
Humans ; Acupuncture Analgesia ; Acupuncture Therapy ; Anesthesia ; Clinical Trials as Topic ; Registries

Background: Immunocompromised patients with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection often have prolonged viral shedding, and some are clinically suspected of reinfection with different SARSCoV-2 variants. However, data on this issue are limited. This study investigated the SARS-CoV-2 variants in serially collected respiratory samples from immunocompromised patients with prolonged viral shedding for over 12 weeks or relapsed viral shedding after at least 2 weeks of viral clearance. Materials and Methods: From February 2022 to September 2023, we prospectively enrolled immunocompromised patients with coronavirus disease 2019 who had hematologic malignancies or had undergone transplantation and were admitted to a tertiary hospital. Weekly saliva or nasopharyngeal swabs were collected from enrolled patients for at least 12 weeks after diagnosis. Genomic RNA polymerase chain reaction (PCR) was performed on samples, and those testing positive underwent viral culture to isolate the live virus. Spike gene full sequencing via Sanger sequencing and real-time reverse transcription-PCR for detecting mutation genes were conducted to identify SARSCoV-2 variants. Results: Among 116 enrolled patients, 20 with prolonged or relapsed viral shedding were screened to identify the variants. Of these 20 patients, 7 (35%) exhibited evidence of re-infection; one of 8 patients with prolonged viral shedding and 6 of 12 with relapsed viral shedding were reinfected with SARS-CoV-2. Conclusion Our data suggest that approximately one-third of immunocompromised patients with persistent or relapsed viral shedding had reinfection with different variants of SARS-CoV-2.