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 explore the value of preoperative 18F-fluorodeoxyglucose ( 18F-FDG) positron emission tomography (PET) metabolic heterogeneity parameters in predicting tumor deposits (TD) in colorectal cancer (CRC). Methods:A retrospective analysis was conducted on 91 CRC patients who underwent surgical treatment at the Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School from February 2013 to March 2024. All patients underwent preoperative 18F-FDG PET/CT examination. The LIFEx-7.5.15 software was used to delineate the primary lesion with 40% of maximum standardized uptake value (SUV max) as the relative threshold, and metabolic parameters were extracted. Intratumoral metabolic heterogeneity parameters included cumulative SUV histogram area under the curve (AUC-CSH), heterogeneity index (HI), heterogeneity factor (HF), and coefficient of variation (CV). The presence of TD was confirmed by postoperative pathological examination. Differences in data between the TD group and non-TD (NTD) group were compared. Binary logistic regression analysis was used to identify independent risk factors for TD, and receiver operating characteristic (ROC) curve was used to evaluate the predictive efficacy of each parameter for TD. Results:Postoperative pathological diagnosis showed that 27 patients were included in the TD group and 64 in the NTD group. There were statistically significant differences between the TD group and NTD group in CV ( Z=-3.145, P=0.002) and the proportion of patients with carcinoembryonic antigen (CEA) >10 ng/ml (χ 2=10.751, P=0.001), while no statistically significant differences were found in HI, HF, or AUC-CSH (all P>0.05). Binary logistic regression analysis showed that CV was an independent risk factor for TD. ROC curve analysis showed that the area under the ROC curve (AUC) of CV for predicting TD was 0.709(95% CI: 0.593-0.826), which was higher than that of other metabolic heterogeneity parameters. Conclusions:The preoperative 18F-FDG PET/CT metabolic heterogeneity parameter CV has value in predicting TD in CRC patients.

Objective:To explore the value of preoperative 18F-fluorodeoxyglucose ( 18F-FDG) positron emission tomography (PET) metabolic heterogeneity parameters in predicting tumor deposits (TD) in colorectal cancer (CRC). Methods:A retrospective analysis was conducted on 91 CRC patients who underwent surgical treatment at the Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School from February 2013 to March 2024. All patients underwent preoperative 18F-FDG PET/CT examination. The LIFEx-7.5.15 software was used to delineate the primary lesion with 40% of maximum standardized uptake value (SUV max) as the relative threshold, and metabolic parameters were extracted. Intratumoral metabolic heterogeneity parameters included cumulative SUV histogram area under the curve (AUC-CSH), heterogeneity index (HI), heterogeneity factor (HF), and coefficient of variation (CV). The presence of TD was confirmed by postoperative pathological examination. Differences in data between the TD group and non-TD (NTD) group were compared. Binary logistic regression analysis was used to identify independent risk factors for TD, and receiver operating characteristic (ROC) curve was used to evaluate the predictive efficacy of each parameter for TD. Results:Postoperative pathological diagnosis showed that 27 patients were included in the TD group and 64 in the NTD group. There were statistically significant differences between the TD group and NTD group in CV ( Z=-3.145, P=0.002) and the proportion of patients with carcinoembryonic antigen (CEA) >10 ng/ml (χ 2=10.751, P=0.001), while no statistically significant differences were found in HI, HF, or AUC-CSH (all P>0.05). Binary logistic regression analysis showed that CV was an independent risk factor for TD. ROC curve analysis showed that the area under the ROC curve (AUC) of CV for predicting TD was 0.709(95% CI: 0.593-0.826), which was higher than that of other metabolic heterogeneity parameters. Conclusions:The preoperative 18F-FDG PET/CT metabolic heterogeneity parameter CV has value in predicting TD in CRC patients.

Cosmetics may be an important source of human exposure to per-and polyfluoroalkyl substances(PFASs),posing risks to human health.In this study,a nontarget screening method for PFASs in cosmetics was developed using ultra-high performance liquid chromatography-high-resolution mass spectrometry(UHPLC-Q-Orbitrap HRMS)based on the Kendrick mass defect(KMD).The sample was extracted by ultrasonic assisted extraction prior to being analyzed by UHPLC-Q-Orbitrap HRMS.Acquisition of HRMS data was achieved in both full scan and data-dependent(Full MS/dd MS2)mode.The data collected by HRMS were imported into an in-lab built R script for processing.Samples retained the mass spectra peaks with KMD values in the range of 0.85-1 or 0-0.15 for in-and out-of-library matching;when KMD deviation(δKMD)<0.001 and CF 2 mass error(δMS)<15 ppm,it was considered as a potential PFASs homologues.According to matches of parent ions(MS),fragment ions(MS2)and retention time(RT)with the in-house built PFASs database,the screened and identified potential PFASs were categorized to 5 confidence levels(CL1-CL5).A total of 15 kinds of PFASs homologues with confidence level of CL3 and above were screened from 13 cosmetics products and 8 cosmetic raw materials,including perfluoroalkyl alcohol,hydroperfluoroalkyl sulfonic acid,chloroperfluoroalkyl sulfonic acid,etc.with concentrations ranging from 1.9 ng/g to 98.1 ng/g.The nontarget screening method could be used to screen and identify PFASs homologues feasibly and therefore provided data basis for management and control of PFASs addition in cosmetics.

OBJECTIVE: To examine the effectiveness of Chinese medicine (CM) Lianhua Qingwen Granule (LHQW) and Jingyin Gubiao Prescription (JYGB) in asymptomatic or mild patients with Omicron infection in the shelter hospital. METHODS: This single-center retrospective cohort study was conducted in the largest shelter hospital in Shanghai, China, from April 10, 2022 to May 30, 2022. A total of 56,244 asymptomatic and mild Omicron cases were included and divided into 4 groups, i.e., non-administration group (23,702 cases), LHQW group (11,576 cases), JYGB group (12,112 cases), and dual combination of LHQW and JYGB group (8,854 cases). The length of stay (LOS) in the hospital was used to assess the effectiveness of LHQW and JYGB treatment on Omicron infection. RESULTS: Patients aged 41-60 years, with nadir threshold cycle (C_T) value of N gene <25, or those fully vaccinated preferred to receive CM therapy. Before or after propensity score matching (PSM), the multiple linear regression showed that LHQW and JYGB treatment were independent influence factors of LOS (both P<0.001). After PSM, there were significant differences in LOS between the LHQW/JYGB combination and the other groups (P<0.01). The results of factorial design ANOVA proved that the LHQW/JYGB combination therapy synergistically shortened LOS (P=0.032). CONCLUSIONS Patients with a nadir C_T value <25 were more likely to accept CM. The LHQW/JYGB combination therapy could shorten the LOS of Omicron-infected individuals in an isolated environment.
Humans ; Drugs, Chinese Herbal/therapeutic use* ; Male ; Female ; Middle Aged ; Adult ; China/epidemiology* ; Hospitalization ; COVID-19 Drug Treatment ; COVID-19/epidemiology* ; SARS-CoV-2 ; Retrospective Studies ; Treatment Outcome ; Length of Stay ; Young Adult ; Aged

Objective To investigate the predictive value of a nomogram model constructed based on imaging combined with prostate-specific antigen(PSA)and its related parameters for biopsy in patients with PSA levels of 4-10 ng/mL.Methods The serological and imaging data of 191 patients who were detected for PSA and related indicators and underwent the first biopsy of prostate by transrectal ultrasound at Zhongshan City People's Hospital and/or Yunfu Hospital of TCM from January 2018 to December 2023 were analyzed retrospectively.Multivariate Logistic regression identified independent risk factors for prostate cancer,and a nomogram model was developed for patients with PSA levels of 4-10 ng/mL.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curves,calibration curves,and decision curves.Results The multivariate Logistic regression analysis showed that free PSA,prostate volume,transition zone volume,PSA density,and the prostate imaging-reporting and data system(PI-RADS v2.1)score were independent risk factors for prostate cancer.The model incorporating these significant variables demonstrated the best performance,with an area under the curve(AUC)of 0.750(95%CI:0.678-0.821),sensitivity of 72.7%,specificity of 77.2%,and accuracy of 74.9%.The calibration curve indicated good agreement between the predicted probability and the actual probability of prostate cancer;and the decision curve analysis further confirmed that the model had high clinical utility.Conclusion The constructed nomogram prediction model can effectively estimate the preoperative risk of prostate cancer in patients with PSA levels of 4-10 ng/mL,providing clinicians with an intuitive tool to adjust treatment plans based on the assessed risk,thereby optimizing patient outcomes.

Background and Objectives: Real-world clinical data, outside of clinical trials and expert centers, on adverse events related to the use of SyncCardia total artificial heart (TAH) remain limited. We aim to analyze adverse events related to the use of SynCardia TAH reported to the Food and Drug Administration (FDA)’s Manufacturers and User Defined Experience (MAUDE) database. Methods: We reviewed the FDA’s MAUDE database for any adverse events involving the use of SynCardia TAH from 1/01/2012 to 9/30/2020. All the events were independently reviewed by three physicians. Results: A total of 1,512 adverse events were identified in 453 “injury and death” reports in the MAUDE database. The most common adverse events reported were infection (20.2%) and device malfunction (20.1%). These were followed by bleeding events (16.5%), respiratory failure (10.1%), cerebrovascular accident (CVA)/other neurological dysfunction (8.7%), renal dysfunction (7.5%), hepatic dysfunction (2.2%), thromboembolic events (1.8%), pericardial effusion (1.8%), and hemolysis (1%). Death was reported in 49.4% of all the reported cases (n=224/453).The most common cause of death was multiorgan failure (n=73, 32.6%), followed by CVA/other non-specific neurological dysfunction (n=44, 19.7%), sepsis (n=24, 10.7%), withdrawal of support (n=20, 8.9%), device malfunction (n=11, 4.9%), bleeding (n=7, 3.1%), respiratory failure (n=7, 3.1%), gastrointestinal disorder (n=6, 2.7%), and cardiomyopathy (n=3, 1.3%). Conclusions Infection was the most common adverse event following the implantation of TAH. Most of the deaths reported were due to multiorgan failure. Early recognition and management of any possible adverse events after the TAH implantation are essential to improve the procedural outcome and patient survival.

Objective To investigate the clinical efficacy of mitral valve repair technique in the treatment of rheumatic mitral valve lesions. Methods The clinical data of patients diagnosed with rheumatic mitral valve lesions and undergoing mitral valve repair under extracorporeal circulation in our department from 2021 to 2022 were retrospectively analyzed. Results A total of 100 patients were collected, including 78 females and 22 males with an average age of 52 years. There were no secondary open heart or death in the whole group. Extracorporeal circulation time was 136.3±33.1 min, aortic cross-clamping time was 107.6±27.5 min, ventilator use time was 12.9±5.9 h, ICU stay was 2.6±1.4 d, and vasoactive medication use was 823.4±584.4 mg. Before and after the surgery, there were statistical differences in the left ventricular end diastolic diameter, left atrial end systolic diameter, effective mitral valve orifice area, shortening rate of left ventricular short axis, mitral E-peak blood flow velocity, mean mitral transvalvular pressure difference, mitral pressure half-time, and cardiac function graded by New York Heart Association (P＜0.05). While there was no statistical difference in left ventricular ejection fraction or left ventricular end-diastolic volume (P>0.05). Conclusion Overall repair of rheumatic mitral valve lesions can significantly improve the cardiac function and hemodynamics of the patients, and is a good choice for patients with rheumatic mitral valve lesions.

Objective To investigate the predictive value of a nomogram model constructed based on imaging combined with prostate-specific antigen(PSA)and its related parameters for biopsy in patients with PSA levels of 4-10 ng/mL.Methods The serological and imaging data of 191 patients who were detected for PSA and related indicators and underwent the first biopsy of prostate by transrectal ultrasound at Zhongshan City People's Hospital and/or Yunfu Hospital of TCM from January 2018 to December 2023 were analyzed retrospectively.Multivariate Logistic regression identified independent risk factors for prostate cancer,and a nomogram model was developed for patients with PSA levels of 4-10 ng/mL.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curves,calibration curves,and decision curves.Results The multivariate Logistic regression analysis showed that free PSA,prostate volume,transition zone volume,PSA density,and the prostate imaging-reporting and data system(PI-RADS v2.1)score were independent risk factors for prostate cancer.The model incorporating these significant variables demonstrated the best performance,with an area under the curve(AUC)of 0.750(95%CI:0.678-0.821),sensitivity of 72.7%,specificity of 77.2%,and accuracy of 74.9%.The calibration curve indicated good agreement between the predicted probability and the actual probability of prostate cancer;and the decision curve analysis further confirmed that the model had high clinical utility.Conclusion The constructed nomogram prediction model can effectively estimate the preoperative risk of prostate cancer in patients with PSA levels of 4-10 ng/mL,providing clinicians with an intuitive tool to adjust treatment plans based on the assessed risk,thereby optimizing patient outcomes.

The last essential enzyme in the biosynthetic pathway of trilobatin, phloretin-4'-O glycosyltransferase (P4'-OGT), catalyzes the conversion of trilobatin to phloretin in vitro. However, only a few P4'-OGTs have been found in plants. This study used Malus domestica phloretin-4'-O glycosyltransferase (MdPh-4'-OGT) as a query to identify and clone two UDP-glucuronosyltransferase (UGT) genes, designated UGT74L2 and UGT74L3, from the transcriptome of Andrographis paniculata. According to a phylogenetic tree analysis, UGT74L2 and UGT74L3 belonged to the UGT74 family, which has been linked to several activities in other species. The in vitro enzymatic reaction demonstrated that UGT74L2 could particularly catalyze the formation of trilobatin from phloretin, but UGT74L3 had no effects. By using Ni-NTA affinity chromatography to extract the soluble UGT74L2 recombinant protein, the enzymatic kinetics of the activity was investigated using phloretin as the substrate. The results showed that the optimal temperature and pH for UGT74L2 enzymatic reaction were 40 ℃ and 8.0 (Tris-HCl system), respectively. Three metal ions (Ca²⁺, Mn²⁺ and Co²⁺) showed inhibitory effect on the activity of UGT74L2, while Mg²⁺ could improve the activity of UGT74L2. Other tested metal ions have no significant effect on UGT74L2. The results of enzymatic kinetic parameters that the K_m value was 29.84 μmol·L^-1, the k_cat was 0.02 s^-1, and the k_cat·K_m^-1 was 572.6 mol^-1·s^-1. By homology modeling, molecular docking and mutation experiments, we found that multiple amino acids residues around the substrate binding pocket play quite an important role during catalytic process, In summary, we identified a novel P4'-OGT gene from medicinal plant Andrographis paniculata and provided a new efficient catalyst to synthesize trilobatin. Meanwhile, this study provides a reference for mining new efficient glycosylation modules from plants.