In recent years， diabetic nephropathy （DN） has become an increasingly serious health challenge worldwide， and its morbidity and mortality rates are rapidly increasing. The patients suffering from the disease tend to be younger. DN is not only accompanied by a wide range of renal pathological changes， such as renal hypertrophy， inflammatory cell infiltration， expansion of the tethered membrane stroma， and thickening of the basement membrane but is also the main cause of end-stage renal disease and death in patients with diabetes mellitus. Therefore， it is particularly urgent to explore new strategies for the prevention and treatment of DN. The pathogenesis of DN is intricate and complex， with current research focusing on multifactorial interactions between metabolic and hemodynamic factors， such as hypoxia， inflammatory responses， and fibrotic processes. Notably， hypoxia plays a pivotal role in the initiation and progression of DN. Hypoxia-inducible factor （HIF-1α）， as a key regulatory protein commonly found in hypoxic cells， has a profound impact on various physiological and pathological processes， such as cell metabolism， vascular neogenesis， oxidative stress， and apoptosis. With its unique theoretical system and therapeutic approach， traditional Chinese medicine has demonstrated significant advantages in coping with hypoxic diseases and can slow down the progression of DN by regulating the expression level of HIF-1α and its downstream signaling molecules and exerting anti-inflammatory， antioxidant， and antifibrotic effects， which has positive clinical significance for drug development and early prevention and treatment of DN.

OBJECTIVE To explore the pharmacokinetic characteristics of 3 blood-absorbed components of Xiangshao sanjie oral liquid in rats with hyperplasia of mammary gland （HMG）. METHODS Female SD rats were divided into control group and HMG group according to body weight， with 6 rats in each group. The HMG group was given estrogen+progesterone to construct HMG model. After modeling， two groups were given 1.485 g/kg of Xiangshao sanjie oral liquid （calculated by crude drug） intragastrically， once a day， for 7 consecutive days. Blood samples were collected before the first administration （0 h）， and at 5， 15， 30 minutes and 1， 2， 4， 8， 12， 24 hours after the last administration， respectively. Using chlorzoxazone as the internal standard， the plasma concentrations of ferulic acid， paeoniflorin and rosmarinic acid in rats were detected by UPLC-Q/TOF-MS. The pharmacokinetic parameters [area under the drug time curve （AUC0－24 h， AUC0－∞）， mean residence time （MRT0－∞）， half-life （t1/2）， peak time （tmax）， peak concentration （cmax）] were calculated by the non-atrioventricular model using Phoenix WinNonlin 8.1 software. RESULTS Compared with the control group， the AUC0－24 h， AUC0－∞ and cmax of ferulic acid in the HMG group were significantly increased （P＜0.05）； the AUC0－24 h， AUC0－∞ ， MRT0－∞ ， t1/2 and cmax of paeoniflorin increased， but there was no significant difference between 2 groups （P＞0.05）； the AUC0－24 h and MRT0-∞ of rosmarinic acid were significantly increased or prolonged （P＜0.05）. C ONCLUSIONS In HMG model rats， the exposure of ferulic acid， paeoniflorin and rosmarinic acid in Xiangshao sanjie oral liquid all increase， and the retention time of rosmarinic acid is significantly prolonged.

ObjectiveTo investigate the expression of serum Aldo-keto reductase family 1 member B10 （AKR1B10） in patients with hepatocellular carcinoma （HCC） in northern China， and to provide a new and valuable biomarker for the clinical diagnosis of HCC. MethodsThis study was conducted among 102 patients with HCC， 119 patients with benign liver disease， and 132 patients with other malignant tumors who attended The Affiliated Hospital of Chengde Medical University and 148 healthy individuals who underwent physical examination from May 2020 to May 2024. ELISA and chemiluminescence were used to measure the serum levels of AKR1B10 and alpha-fetoprotein （AFP）. The Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups， and the Kruskal-Wallis H test was used for comparison between three groups and further comparison between two groups； the chi-square test was used for comparison of categorical data between groups. The area under the ROC curve （AUC） was used to assess diagnostic efficiency. ResultsThe expression level of AKR1B10 was 3 053.79 （1 475.67‍ ‍—‍ ‍4 605.86） pg/mL in the HCC group， 1 324.42 （659.68‍ ‍—‍ ‍2 023.88） pg/mL in the benign liver disease group， 660.68 （377.56‍ ‍—‍ ‍2 087.77） pg/mL in the other malignant tumor group， and 318.30 （82.73‍ ‍—‍ ‍478.82） pg/mL in the healthy group， with a significant difference between the four groups （H=240.86， P<0.001）， and further comparison between two groups showed that the HCC group had a significantly higher level than the other three groups （all P<0.001）. The ROC curve analysis of the HCC group and the other three groups showed that serum AKR1B10 had an optimal cut-off value of 1 584.97 pg/mL in the diagnosis of HCC， with an AUC of 0.86 （95% confidence interval ［CI］： 0.82‍ ‍—‍ ‍0.90）， a sensitivity of 74.3%， and a specificity of 85.2%. Compared with each indicator alone， a combination of AKR1B10 and AFP could improve the sensitivity （81.8%） and specificity （91.4%） of HCC diagnosis. AKR1B10 had an AUC of 0.84 （95%CI： 0.78‍ ‍—‍ ‍0.90） in the diagnosis of patients with early- or middle-stage HCC， with a sensitivity of 76.2% and a specificity of 81.2%. AKR1B10 had an AUC of 0.85 （95%CI： 0.77‍ ‍—‍ ‍0.92） in the diagnosis of patients with AFP-negative HCC， with a sensitivity of 81.6% and a specificity of 79.9%. ConclusionAKR1B10 is a promising serological marker for the diagnosis of HCC， and a combination of AKR1B10 and AFP can improve the detection rate of HCC patients in northern China， especially those with early- or middle-stage HCC and AFP-negative HCC.

ObjectiveBased on a new method for animal model evaluation， this study aims to analyze the characteristics of diseases and syndromes of existing animal models of attention deficit hyperactivity disorder （ADHD） from both traditional Chinese medicine （TCM） and western medical perspectives and propose suggestions for improvement. MethodsA systematic search of the China National Knowledge Infrastructure （CNKI） and PubMed was conducted for literature on ADHD animal models. According to TCM and western medical diagnostic criteria， core and accompanying symptoms of the models were assigned with scores to comprehensively evaluate the clinical consistency. ResultsThe selection of experimental animals for ADHD models primarily involved rodents， with modeling methods including genetic， chemical induction， and environmental induction. The average consistency of clinical diseases and syndromes with TCM and western medicine was 45.19% and 49.42%， respectively. The spontaneously hypertensive （SHR） rats and nicotine/smoking models had the highest consistency with TCM， while the social isolation models had the highest consistency with western medicine. Most models were guided by western medicine theories， which can meet the surface validity and structural validity requirements of western medicine but lacked precise differentiation of TCM syndromes. ConclusionExisting ADHD animal models primarily focus on a single genotype or environmental factor， lacking comprehensive consideration of multigenic interactions and environmental factors. Moreover， the selection of model evaluation indicators is relatively singular， primarily focusing on "disease" indicators， while TCM "syndrome" indicators have not been fully considered. It is recommended to introduce a "formula-to-syndrome" approach in the preparation of TCM models for ADHD and establish and improve an evaluation system of animal models combining diseases and syndromes， so as to provide a solid foundation for future experimental research.

ObjectiveTo explore the characteristics of traditional Chinese medicine （TCM） syndromes in the patients with concurrent knee osteoarthritis （KOA） and postmenopausal osteoporosis （PMOP） and provide a scientific basis for precise TCM syndrome differentiation， diagnosis， and treatment of such concurrent diseases. MethodsA prospective， multicenter， cross-sectional clinical survey was conducted to analyze the characteristics of TCM syndromes in the patients with concurrent PMOP and KOA. Excel 2021 was used to statistically analyze the general characteristics of the included patients. Continuous variables were reported as x¯±s， and binary variables were reported as percentages. UCINET and Gephi were used to construct a complex "isease-syndrome-symptom" network for in-depth mining. Topological structure indicators， edge connection information between nodes， and weighted adjacency matrices were calculated by UCINET and Python. Gephi was used for complex network visualization. ResultsA total of 157 patients with concurrent PMOP and KOA from 12 TCM hospitals or community health service centers were selected for the collection of TCM syndrome and symptom information. A total of 4 main TCM syndromes were obtained， which were kidney-Yang deficiency （47.13%）， liver-kidney Yin deficiency （36.94%）， spleen-kidney Yang deficiency （8.92%）， and kidney Yin-Yang deficiency （7.01%）. In addition， 10 concurrent syndromes （mainly Qi stagnation and blood stasis， Qi and blood deficiency， spleen Yang deficiency， and cold-dampness） were identified. Based on the results of comprehensive frequency statistics and complex network analysis， as well as TCM theoretical knowledge and relevant guidelines， the general characteristics of concurrent PMOP and KOA and the main TCM syndromes in the dimensions of physical symptoms， pain， tongue and pulse manifestations， and defecation and urination were obtained. ConclusionThe main TCM syndromes in the patients with concurrent PMOP and KOA may be kidney Yang deficiency， liver-kidney Yin deficiency， spleen-kidney Yang deficiency， and kidney Yin-Yang deficiency， among which kidney Yang deficiency and liver-kidney Yin deficiency are the core TCM syndromes.

ObjectiveBased on a new method for animal model evaluation， this study aims to analyze the characteristics of diseases and syndromes of existing animal models of attention deficit hyperactivity disorder （ADHD） from both traditional Chinese medicine （TCM） and western medical perspectives and propose suggestions for improvement. MethodsA systematic search of the China National Knowledge Infrastructure （CNKI） and PubMed was conducted for literature on ADHD animal models. According to TCM and western medical diagnostic criteria， core and accompanying symptoms of the models were assigned with scores to comprehensively evaluate the clinical consistency. ResultsThe selection of experimental animals for ADHD models primarily involved rodents， with modeling methods including genetic， chemical induction， and environmental induction. The average consistency of clinical diseases and syndromes with TCM and western medicine was 45.19% and 49.42%， respectively. The spontaneously hypertensive （SHR） rats and nicotine/smoking models had the highest consistency with TCM， while the social isolation models had the highest consistency with western medicine. Most models were guided by western medicine theories， which can meet the surface validity and structural validity requirements of western medicine but lacked precise differentiation of TCM syndromes. ConclusionExisting ADHD animal models primarily focus on a single genotype or environmental factor， lacking comprehensive consideration of multigenic interactions and environmental factors. Moreover， the selection of model evaluation indicators is relatively singular， primarily focusing on "disease" indicators， while TCM "syndrome" indicators have not been fully considered. It is recommended to introduce a "formula-to-syndrome" approach in the preparation of TCM models for ADHD and establish and improve an evaluation system of animal models combining diseases and syndromes， so as to provide a solid foundation for future experimental research.

ObjectiveTo explore the characteristics of traditional Chinese medicine （TCM） syndromes in the patients with concurrent knee osteoarthritis （KOA） and postmenopausal osteoporosis （PMOP） and provide a scientific basis for precise TCM syndrome differentiation， diagnosis， and treatment of such concurrent diseases. MethodsA prospective， multicenter， cross-sectional clinical survey was conducted to analyze the characteristics of TCM syndromes in the patients with concurrent PMOP and KOA. Excel 2021 was used to statistically analyze the general characteristics of the included patients. Continuous variables were reported as x¯±s， and binary variables were reported as percentages. UCINET and Gephi were used to construct a complex "isease-syndrome-symptom" network for in-depth mining. Topological structure indicators， edge connection information between nodes， and weighted adjacency matrices were calculated by UCINET and Python. Gephi was used for complex network visualization. ResultsA total of 157 patients with concurrent PMOP and KOA from 12 TCM hospitals or community health service centers were selected for the collection of TCM syndrome and symptom information. A total of 4 main TCM syndromes were obtained， which were kidney-Yang deficiency （47.13%）， liver-kidney Yin deficiency （36.94%）， spleen-kidney Yang deficiency （8.92%）， and kidney Yin-Yang deficiency （7.01%）. In addition， 10 concurrent syndromes （mainly Qi stagnation and blood stasis， Qi and blood deficiency， spleen Yang deficiency， and cold-dampness） were identified. Based on the results of comprehensive frequency statistics and complex network analysis， as well as TCM theoretical knowledge and relevant guidelines， the general characteristics of concurrent PMOP and KOA and the main TCM syndromes in the dimensions of physical symptoms， pain， tongue and pulse manifestations， and defecation and urination were obtained. ConclusionThe main TCM syndromes in the patients with concurrent PMOP and KOA may be kidney Yang deficiency， liver-kidney Yin deficiency， spleen-kidney Yang deficiency， and kidney Yin-Yang deficiency， among which kidney Yang deficiency and liver-kidney Yin deficiency are the core TCM syndromes.

Osteoarthritis （OA） and stroke are common clinical diseases that reduce patients' quality of life and place a burden on families and society. Ruyi Zhenbaowan， a classic prescription in Tibetan medicine， have the functions of clearing heat， awakening the brain and opening orifices， relaxing tendons and promoting meridian circulation， and eliminating yellow water. Clinically， they are used to treat osteoarthritis， post-stroke sequelae， neuropathic pain， and other related conditions. Modern pharmacological studies have demonstrated their anti-inflammatory， analgesic， and nerve-repairing effects. However， current research remains insufficient regarding the appropriate indications， timing， and efficacy of this medicine in treating relevant diseases. To enhance clinicians' understanding of this medicine and promote its standardized and rational clinical use， a panel of national experts， including clinical specialists， Tibetan medicine practitioners， pharmacologists， and methodologists， formulated this consensus based on clinical experience and evidence-based practice. The Cochrane systematic review framework， the Grading of Recommendations Assessment， Development and Evaluation （GRADE） system， and the nominal group method were employed to generate seven graded recommendations and 19 consensus-based suggestions. These recommendations clearly define the key points in the clinical application of Ruyi Zhenbaowan， including therapeutic indications， dosage and administration， treatment duration， and medication safety. The consensus specifically addresses the clinical efficacy， appropriate timing of administration， dosage strategies， treatment cycles， and combination medication strategies for treating osteoarthritis and stroke and provides an overview of safety considerations. The aim is to provide standardized guidance for hospitals and healthcare institutions nationwide to ensure the rational application of Ruyi Zhenbaowan in the treatment of osteoarthritis and stroke， reduce medication-related risks， and further leverage its clinical advantages. This consensus has been approved and issued by the China Association of Chinese Medicine， with the standard number GS/CACM 369-2024.

With the increasing utilization of cancer therapy, the incidence of lung injury associated with these treatments continues to rise. The recognition of pulmonary toxicity related to cancer therapy has become increasingly critical, for which interstitial lung disease (ILD) is a common cause of mortality. Cancer therapy-related ILD (CT-ILD) can result from a variety of treatments including chemotherapy, targeted therapy, immune checkpoint inhibitors, antibody-drug conjugates, and radiotherapy. CT-ILD may progress rapidly and even be life-threatening; therefore, prompt diagnosis and timely treatment are crucial for effective management. This review aims to provide valuable information on the risk factors associated with CT-ILD; elucidate its underlying mechanisms; discuss its clinical features, imaging, and histological manifestations; and emphasize the clinical-related views of its diagnosis. In addition, this review provides an overview of grading, typing, and staging treatment strategies used for the management of CT-ILD.
Humans ; Lung Diseases, Interstitial/diagnosis* ; Neoplasms/therapy* ; Risk Factors ; Immune Checkpoint Inhibitors/adverse effects* ; Antineoplastic Agents/therapeutic use*

BACKGROUND: Postoperative pulmonary complications (PPCs) are major adverse events in neurosurgical patients. This study aimed to develop and validate machine learning models predicting PPCs after neurosurgery. METHODS: PPCs were defined according to the European Perioperative Clinical Outcome standards as occurring within 7 postoperative days. Data of cases meeting inclusion/exclusion criteria were extracted from the anesthesia information management system to create three datasets: The development (data of Huashan Hospital, Fudan University from 2018 to 2020), temporal validation (data of Huashan Hospital, Fudan University in 2021) and external validation (data of other three hospitals in 2023) datasets. Machine learning models of six algorithms were trained using either 35 retrievable and plausible features or the 11 features selected by Lasso regression. Temporal validation was conducted for all models and the 11-feature models were also externally validated. Independent risk factors were identified and feature importance in top models was analyzed. RESULTS: PPCs occurred in 712 of 7533 (9.5%), 258 of 2824 (9.1%), and 207 of 2300 (9.0%) patients in the development, temporal validation and external validation datasets, respectively. During cross-validation training, all models except Bayes demonstrated good discrimination with an area under the receiver operating characteristic curve (AUC) of 0.840. In temporal validation of full-feature models, deep neural network (DNN) performed the best with an AUC of 0.835 (95% confidence interval [CI]: 0.805-0.858) and a Brier score of 0.069, followed by Logistic regression (LR), random forest and XGBoost. The 11-feature models performed comparable to full-feature models with very close but statistically significantly lower AUCs, with the top models of DNN and LR in temporal and external validations. An 11-feature nomogram was drawn based on the LR algorithm and it outperformed the minimally modified Assess respiratory RIsk in Surgical patients in CATalonia (ARISCAT) and Laparoscopic Surgery Video Educational Guidelines (LAS VEGAS) scores with a higher AUC (LR: 0.824, ARISCAT: 0.672, LAS: 0.663). Independent risk factors based on multivariate LR mostly overlapped with Lasso-selected features, but lacked consistency with the important features using the Shapley additive explanation (SHAP) method of the LR model. CONCLUSIONS: The developed models, especially the DNN model and the nomogram, had good discrimination and calibration, and could be used for predicting PPCs in neurosurgical patients. The establishment of machine learning models and the ascertainment of risk factors might assist clinical decision support for improving surgical outcomes. TRIAL REGISTRATION ChiCTR 2100047474; https://www.chictr.org.cn/showproj.html?proj=128279 .
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Algorithms ; Lung Diseases/etiology* ; Machine Learning ; Neurosurgical Procedures/adverse effects* ; Postoperative Complications/diagnosis* ; Risk Factors ; ROC Curve