Stroke is the leading cause of death and disability among adults in China， and its common complications include digestive system abnormalities， cognitive impairment， depression， stroke-associated pneumonia， and hemiplegia. The combination of traditional Chinese and Western medicine has great potential in treating post-stroke complications. Xinglou Chengqitang （XLCQT） is a representative prescription of alleviating the disease in the upper part by treating the lower part. It has definite therapeutic effect and high safety. Clinically， XLCQT is often used to treat stroke and its complications. However， the quantity and quality of clinical trials of XLCQT in treating post-stroke complications need to be improved. Additionally， since the basic research is weak， the material basis and multi-target mechanism for the efficacy of this prescription are unknown. This article reviews XLCQT in terms of the pharmacodynamic basis， medicinal properties， safety evaluation， and progress in clinical research and mechanisms in treating post-stroke complications. This article summarizes 22 key active ingredients of XLCQT in treating acute stroke complicated with syndrome of phlegm heat and fu-organ excess. Among these key active ingredients， resveratrol， kaempferol， luteolin， chrysoeriol， apigenin， （+）-catechin， and adenosine have good pharmacokinetic properties and high bioavailability. The mechanisms of XLCQT in treating post-stroke complications are complex， including inflammatory response， brain-gut axis， hypothalamic-pituitary-adrenal （HPA） axis， intestinal flora， neurotrophic factors， autophagy， oxidative stress， and free radical damage. This review helps to deeply understand the pharmacodynamic basis and mechanisms of XLCQT in treating post-stroke complications and provides a theoretical basis for the clinical application of XLCQT against post-stroke complications and the development of drugs.

Objective To investigate the expression profile, prognostic value, gene co-expression network, and immunomodulatory role of BRF1 in a pan-cancer context, and to explore its biological functions and molecular regulatory mechanisms in esophageal squamous cell carcinoma (ESCC). Methods The pan-cancer dataset from The Cancer Genome Atlas (TCGA) was utilized to analyze the differential expression of BRF1 in tumor versus normal tissues, its association with patient survival, pathway enrichment for co-expressed genes, and immune features (including immune checkpoints, cytokines, and immune cell infiltration). The expression profile of BRF1 in ESCC was validated using the Gene Expression Omnibus (GEO) database. In vitro, BRF1 was knocked down in ESCC cells using siRNA. Cell proliferation and migration were assessed by MTT and Transwell assays, respectively. The expression levels of proliferation- and migration-related proteins were detected by Western blotting. The correlation between BRF1 and ferroptosis was analyzed using TCGA data. Results BRF1 was significantly upregulated in over 20 types of cancer, and its high expression was associated with poor prognosis in patients with adrenocortical carcinoma and prostate adenocarcinoma. BRF1 was found to positively regulate the T-cell-mediated cell death pathway in esophageal adenocarcinoma and was associated with the circadian rhythm regulation pathway in pancreatic adenocarcinoma. The correlation of BRF1 with immune checkpoints, cytokine networks, and immune cell infiltration was found to be cancer type-specific. In vitro experiments demonstrated that knocking down BRF1 significantly inhibited the proliferation of ESCC cells, accompanied by the downregulation of the proliferation marker PCNA. Cell migration was also significantly impaired, with decreased expression of Vimentin and MMPs and increased expression of E-cadherin. Furthermore, the expression of BRF1 was positively correlated with that of ferroptosis-antagonizing genes, such as GPX4, HSPA5, and SLC7A11. Conclusion BRF1 plays complex roles in pan-cancer, participating in the regulation of tumorigenesis, progression, and immune infiltration. BRF1 promotes the proliferation and migration of ESCC cells, a mechanism potentially associated with the regulation of ferroptosis resistance. These findings suggest that BRF1 could be a potential therapeutic target for ESCC.

Objective To construct a lung cancer surgery-oriented disease-specific database covering the entire perioperative care pathway, thereby improving the quality and usability of key surgical data elements. Methods Real-world clinical data were extracted from a single-center thoracic surgery department. A standardized data model was established based on the open electronic health record (openEHR) standard. Large language model (LLM), optical character recognition (OCR), and artificial intelligence (AI)-driven techniques were employed to extract, structure, and perform quality control on unstructured clinical narratives, imaging reports, and radiological data, with a focus on capturing surgically relevant perioperative indicator. Results A multimodal database comprising 19 917 patients was established, including 7 930 males and 11 987 females, with ages ranging from 15 to 97 (61.7±9.7) years. The database includes 582 structured data variables, textual report data corresponding to 69 clinical indicators, 13 000 pulmonary function test PDF reports, and chest CT imaging data from 16 884 patients. This database comprehensively covers major information relevant to surgical diagnosis and treatment of lung cancer, significantly improving the completeness and granularity of surgical detail data. Large language models (LLMs) and optical character recognition (OCR) technologies enhanced the efficiency of converting unstructured data into structured formats, while a multi-level manual verification process ensured data accuracy and traceability. The database supports real-world research including comparisons of surgical procedures, prediction of postoperative complications, prognosis assessment, and multimodal data association analyses.

Objective: To develop a modified calculation formula for renal tumor volume and tumor contact surface area (CSA) based on the modeling results of 3D Slicer software, and to create a webpage of the calculation formula for use. Methods: The general information and tumor anatomical data of 98 patients who underwent partial nephrectomy during Jan.2021 and Jul.2023 in the Second Affiliated Hospital of Xi'an Jiaotong University were retrospectively analyzed.The imaging data were input into 3D Slicer software in the form of Dicom files for tumor and ipsilateral kidney modeling to obtain tumor anatomical data.The relationship between tumor anatomical parameters and tumor volume and CSA was analyzed using multifactorial linear regression.The initial modified formulas (V2, C2) and the optimized modified formulas (V3, C3) for tumor volume over CSA were established, respectively, after insignificant variables were eliminated.The mean square error (MSE) and Akaike information criterion (AIC) of the modified and traditional formulas (V1, C1) were compared, and the formula with the smallest MSE and AIC was selected as the optimal tumor volume and CSA calculation formula.The median tumor volume and CSA obtained from 3D modeling were used as the cutoff values.The optimal formula and conventional formula were applied to calculate tumor volume and CSA for all patients, and risk stratification was performed for all patients based on these cutoff values, and the perioperative indicators of patients in the upper and lower groups were compared.Finally, an online calculation tool was developed based on HTML. Results: Based on multifactorial linear regression analysis, we obtained the modified tumor volume calculation formula: V=0.382abc+2.488a+2.372b－4.146c+1.948（V2）, V=0.469abc－4.586c+13.816（V3）; the modified tumor CSA calculation formula CSA=2.469a －2.262L －19.23a+6.206b+1.212c+18.017L+1.616h－3.97h －2.185h/h －0.388（C2）, CSA=2.376a －2.144L －20.157a+5.024b+1.128c+17.578L+2.525h－2.634（C3）.Both of the modified volume formula (MSE=151.298 vs. 127.807 vs. 104.106) and modified CSA formula (MSE=309.878 vs.23.556 vs.30.388) had smaller errors compared to the conventional formula.The modified volume calculation formula showed that bleeding was more and thermal ischemia time was longer in patients with larger tumor volumes than in patients with smaller tumor volumes (P<0.05); and the modified CSA calculation formula showed that bleeding was more, surgery and thermal ischemia time were longer in patients with high CSA than in patients with low CSA (P＜0.05).Finally, V3 and C3 are selected as the best calculation formula, and a web page (https://lizihao-bot.github.io/RCC-Calculate/) was established for easy use. Conclusion: This study combined data from a medical information technology platform with numerical modeling methods to provide a faster and more accurate method to calculate the renal tumor volume and CSA.Meanwhile, a webpage version of the tool was developed to enhance its practicability.

OBJECTIVE To construct ensemble learning models for predicting high-use days of budesonide based on meteorological factors， thereby providing reference for hospital pharmacy management. METHODS Meteorological data for 2024 and outpatient budesonide usage data from the jurisdiction of Sanming Hospital of Integrated Traditional Chinese and Western Medicine were collected. High-use days were defined as the 75th percentile of outpatient budesonide usage， and a corresponding dataset was established. The prediction task was formulated as a classification problem， and three ensemble learning models were developed： Random Forest， Extreme Gradient Boosting （XGBoost）， and Histogram-based Gradient Boosting Classifier. Model performance was evaluated using accuracy， precision， recall， F1-score， and log-loss. Model interpretability was analyzed using Shapley Additive Explanations （SHAP）. RESULTS The Histogram-based Gradient Boosting Classifier achieved the best performance （accuracy＝0.75， F1-score＝0.48）， followed by XGBoost （accuracy＝0.74， F1-score＝0.43） and Random Forest （accuracy＝0.72， F1-score＝0.22）. SHAP results suggested that the prediction results of the last two models have the highest correction. CONCLUSIONS Ensemble learning models can effectively predict high-use days of budesonide， with the Histogram- based Gradient Boosting Classifier demonstrating the best predictive performance. Low temperature， high humidity， and low atmospheric pressure show significant positive impacts on the prediction of daily budesonide usage.

This paper presents an automatic acquisition and analytic procedure of acupuncture manipulation based on optical navigation, aiming at solving the shortcomings of existing acquisition methods of acupuncture manipulation. An acquisition holder installed at the handle tail of filiform needle was designed to display the movement trajectory of the needle during acupuncture delivery by collecting the movement trajectory of holder. The 3-month old male Bama miniature pig was selected as the experimental subject, and 6 points, "Bojian" "Qiangfeng" "Housanli" "Xiaokua" "Huiyang" (BL35) and "Baihui" (GV20), were selected during acupuncture manipulation. The optical navigation system was used to collect the real-time data, and these data were per-processed and analyzed using mean filtering and Fourier transform. The acupuncture procedure was divided into 3 stages, inserting, lifting-thrusting, and twisting. The results showed that the accuracy was 96.3% at lifting-thrusting stage, and that was 100.0% at twisting stage. The decomposition effect of the entire procedure was satisfactory. This study provides a new approach to the quantitative analysis of acupuncture manipulation. In the future, it needs to further optimize the algorithm and expand the sample size so as to improve the accuracy of this analytic technique.
Acupuncture Therapy/methods* ; Male ; Animals ; Swine ; Acupuncture Points ; Humans ; Swine, Miniature ; Needles

BACKGROUND: Neoadjuvant immunochemotherapy has emerged as an indispensable therapeutic modality for non-small cell lung cancer (NSCLC). However, its clinical application experience remains limited, and the associations between various clinical factors and treatment benefits remain undefined. This study aims to evaluate the efficacy and safety of neoadjuvant immunochemotherapy in patients with stage IB-IIIB NSCLC in a real-world setting, analyze survival outcomes among subgroups with diverse clinical characteristics, and identify potential clinical predictive factors for pathological response. METHODS: This study included patients with stage IB-IIIB NSCLC who underwent radical lung resection after 2-4 cycles of neoadjuvant immunochemotherapy at Peking University People's Hospital between August 2019 and March 2024. Medical records and follow-up information were collected to analyze therapeutic response, adverse events and survival outcomes. Logistic analysis was used to identify clinical predictors of pathological response. RESULTS: Among 183 enrolled patients, 116 (63.4%) were stage III. Grade 3-4 immune-related adverse events (irAEs) occurred in 39 (21.3%) patients. Radiographic complete response (CR) or partial response (PR) was achieved in 118 (64.5%) patients. R0 resection was achieved in 180 (98.4%) patients. Major pathologic response (MPR) was observed in 107 (58.5%) patients, with 78 (42.6%) achieving pathologic complete response (pCR). Squamous cell carcinoma and radiographic objective response were associated with pathological response (pCR/MPR). With a median follow-up of 22.1 [interquartile range (IQR): 18.3-32.2] months, the 2-year event-free survival (EFS) and overall survival (OS) rates were 82.5% and 90.4%, respectively. Achievement of pathological response (pCR/MPR) was correlated with prolonged survival outcomes. CONCLUSIONS Neoadjuvant immunochemotherapy is safe and effective for patients with stage IB-IIIB NSCLC. Patients achieving pCR or MPR exhibit significantly better survival benefits from neoadjuvant immunochemotherapy. Squamous cell carcinoma and radiographic objective response can serve as clinical predictors of pathological response.
Humans ; Carcinoma, Non-Small-Cell Lung/mortality* ; Male ; Lung Neoplasms/mortality* ; Female ; Middle Aged ; Neoadjuvant Therapy/adverse effects* ; Aged ; Neoplasm Staging ; Adult ; Immunotherapy/adverse effects* ; Treatment Outcome ; Retrospective Studies

OBJECTIVES: Tiletamine, a veterinary anesthetic, has emerged as a novel psychoactive substance and has been abused in many parts of the world, causing great harm to public health. However, the sensitivity of existing detection methods cannot meet the needs of forensic practice. This study aims to establish an ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method for the determination of tiletamine and its metabolite desethyltiletamine in human biological samples, and to verify its applicability in forensic practice. METHODS: SKF_525A was used as the internal standard. Biological samples were extracted with acetonitrile containing 1 ng/mL SKF_525A, vortexed for 10 min, ultrasonicated for 20 min, centrifuged at 10 000 r/min for 10 min, and 500 μL of the supernatant was filtered through a 0.22 μm membrane. Analyses were performed using an ACQUITY UPLC H-Class PLUS system and an XEVO TQ-S Micro triple quadrupole mass spectrometer. An ACQUITY UPLC^® BEH C18 (1.7 µm, 2.1 mm×100 mm) column at a flow rate of 0.3 mL/min was used, and four mobile phase systems were tested to optimize separation. Detection used positive electrospray ionization (ESI+) in multiple reaction monitoring (MRM) mode, with quantifier ion transitions of mass to charge 224.043→179.016 for tiletamine and mass to charge 196.08→151.06 for desethyltiletamine. Calibration curves were established over 0.1-200 ng/mL in spiked blood samples. The linear range, limit of detection (LOD), and limit of quantification (LOQ) were determined. Low (5 ng/mL), medium (20 ng/mL), and high (100 ng/mL) concentrations of tiletamine were spiked into blood, liver, and kidney to evaluate precision, accuracy, matrix effect, recovery, and stability. Finally, actual forensic case samples were tested to validate applicability. RESULTS: The established UPLC-MS/MS method achieved simultaneous detection of tiletamine and desethyltiletamine in human biological samples, with retention times of 3.42 min and 2.82 min, respectively. Using mobile phase A (20 mmol/L ammonium acetate and 0.1% formic acid in water) and mobile phase B (acetonitrile) produced the best separation. In blood, tiletamine showed good linearity from 0.1-200 ng/mL (r=0.992, R²=0.983), LOD 0.03 ng/mL, LOQ 0.1 ng/mL, recovery 92%-107%, and matrix effect 71%-99%. In liver and kidney, recoveries were 91%-98% and 93%-104%, and matrix effects were 69%-96% and 72%-100%, respectively. Intra- and inter-day precision [expressed as relative standard deviation (RSD)] and accuracy [expressed as relative error (RE)] were within 15%, and samples were stable at -20 ℃. Tiletamine was detected in actual case samples at 0.37 μg/mL (blood), 0.15 μg/g (liver), 0.11 μg/g (kidney) in case 1, and 8.75 ng/mL (blood) in case 2; desethyltiletamine was also detected in blood. CONCLUSIONS The UPLC-MS/MS method is efficient, accurate, and sensitive, and is suitable for detecting tiletamine and desethyltiletamine in human biological samples.
Tandem Mass Spectrometry/methods* ; Humans ; Chromatography, High Pressure Liquid/methods* ; Substance Abuse Detection/methods* ; Liquid Chromatography-Mass Spectrometry

Antibody (Ab) humanization is critical to reduce immunogenicity and enhance efficacy in the preclinical phase of the development of therapeutic Abs originated from animal models. Computational suggestions have long been desired, but available tools focused on immunogenicity calculation of whole Ab sequences and sequence segments, missing the individual residue sites. This study introduces Site-specific Immunogenicity for Therapeutic Antibody (SITA), a novel computational framework that predicts B-cell immunogenicity score for not only the overall antibody, but also individual residues, based on a comprehensive set of amino acid descriptors characterizing physicochemical and spatial features for antibody structures. A transfer-learning-inspired framework was purposely adopted to overcome the scarcity of Ab-Ab structural complexes. On an independent testing dataset derived from 13 Ab-Ab structural complexes, SITA successfully predicted the epitope sites for Ab-Ab structures with a receiver operating characteristic (ROC)-area unver the ROC curve (AUC) of 0.85 and a precision-recall (PR)-AUC of 0.305 at the residue level. Furthermore, the SITA score can significantly distinguish immunogenicity levels of whole human Abs, therapeutic Abs and non-human-derived Abs. More importantly, analysis of an additional 25 therapeutic Abs revealed that over 70% of them were detected with decreased immunogenicity after modification compared to their parent variants. Among these, nearly 66% Abs successfully identified actual modification sites from the top five sites with the highest SITA scores, suggesting the ability of SITA scores for guide the humanization of antibody. Overall, these findings highlight the potential of SITA in optimizing immunogenicity assessments during the process of therapeutic antibody design.