Objective To investigate the predictive value of preoperative combined detection of neutrophil-to-lymphocyte ratio (NLR) and prothrombin time-international normalized ratio to albumin ratio (PTAR) for early abdominal infection after liver transplantation. Methods Clinical data of 287 recipients who underwent liver transplantation at the Liver Transplant Center of Beijing Friendship Hospital, Affiliated to Capital Medical University, from January 2020 to April 2024 were retrospectively analyzed. The patients were divided into infection group (n=60) and non-infection group (n=227) based on whether abdominal infection occurred within 30 days after surgery. The distribution characteristics of pathogens and infection time in infected patients were analyzed. Spearman correlation analysis was used to assess the correlation between NLR, PTAR, Child-Pugh score and preoperative model for end-stage liver disease (MELD) score. Univariate and multivariate logistic regression analyses were performed to identify risk factors for abdominal infection. Receiver operating characteristic (ROC) curves were plotted for NLR, PTAR, and the combined prediction model to evaluate their predictive efficacy for abdominal infection after liver transplantation. Based on the cutoff value of the combined model, recipients were divided into low-risk and high-risk groups, and Kaplan-Meier analysis was used to compare the cumulative incidence of abdominal infection within 30 days after surgery between the two groups. Results Among the 287 recipients who underwent liver transplantation, 60 developed bacterial or fungal abdominal infections postoperatively. A total of 86 strains were isolated from infected patients, with Gram-negative bacteria accounting for 58%, Gram-positive bacteria for 36%, and fungi for 5%. Preoperative NLR and PTAR were positively correlated with Child-Pugh and MELD scores (all 1 > r > 0, P < 0.05). Logistic regression analysis showed that preoperative NLR, preoperative PTAR, postoperative ICU stay duration and postoperative biliary leakage were risk factors for abdominal infection within 30 days after surgery. The area under the curve (AUC) for NLR, PTAR, Child-Pugh score and MELD score were 0.771, 0.735, 0.650 and 0.741, respectively. The AUC for the combined NLR and PTAR prediction model was 0.824 (95% confidence interval: 0.763-0.885, P < 0.001), with a cutoff value of 0.168. Kaplan-Meier analysis showed that the cumulative incidence of abdominal infection within 30 days after surgery was lower in the low-risk group than in the high-risk group, with statistically significant difference (P < 0.001). Conclusions Preoperative NLR and PTAR are independent risk factors for abdominal infection within 30 days after liver transplantation. The combined prediction model of NLR and PTAR may effectively identify high-risk recipients for early abdominal infection after liver transplantation, providing basis for early intervention.

Since the promulgation of the first Drug Administration Law of the People's Republic of China 40 years ago in 1984, China has undergone four main stages in the traditional Chinese medicine(TCM) regulation: the initial establishment of TCM regulation rules(1984-1997), the formation of a modern TCM regulatory system(1998-2014), the reform of the review and approval system for new TCM drugs(2015-2018), and the construction of a scientific regulation system for TCM(2019-2024). Over the past five years, a series of milestone achievements of TCM regulation in China have been achieved in the six aspects, including its strategic objectives and the establishment of a science-based regulatory system, the reform of the review and approval system for new TCM drugs, the optimization and improvement of the TCM standard system and its formation mechanism, comprehensive enhancement of regulatory capabilities for TCM safety, international harmonization of TCM regulation and its role in promoting innovation. Looking ahead, centered on advancing TCMRS to establish a sound regulatory framework tailored to the unique characteristics of TCM, TCM regulation will evolve into new reform patterns, advancing and extending across eight critical fronts, including the legal framework and policy architecture, the review and approval system for new TCM drugs, the quality standard and management system of TCM, the comprehensive quality & safety regulation and traceability system, the research and transformation system for TCMRS, AI-driven innovations in TCM regulation, the coordination between high-quality industrial development and high-level regulation, and the leadership in international cooperation and regulatory harmonization. In this way, a unique path for the development of modern TCM regulation with Chinese characteristics will be pioneered.
Humans ; China ; Drugs, Chinese Herbal/standards* ; History, 20th Century ; History, 21st Century ; Medicine, Chinese Traditional/trends*

Approximately 30%-40% of epilepsy patients do not respond well to adequate anti-seizure medications (ASMs), a condition known as pharmacoresistant epilepsy. The management of pharmacoresistant epilepsy remains an intractable issue in the clinic. Its early prediction is important for prevention and diagnosis. However, it still lacks effective predictors and approaches. Here, a classical model of pharmacoresistant temporal lobe epilepsy (TLE) was established to screen pharmacoresistant and pharmaco-responsive individuals by applying phenytoin to amygdaloid-kindled rats. Ictal electroencephalograms (EEGs) recorded before phenytoin treatment were analyzed. Based on ictal EEGs from pharmacoresistant and pharmaco-responsive rats, a convolutional neural network predictive model was constructed to predict pharmacoresistance, and achieved 78% prediction accuracy. We further found the ictal EEGs from pharmacoresistant rats have a lower gamma-band power, which was verified in seizure EEGs from pharmacoresistant TLE patients. Prospectively, therapies targeting the subiculum in those predicted as "pharmacoresistant" individual rats significantly reduced the subsequent occurrence of pharmacoresistance. These results demonstrate a new methodology to predict whether TLE individuals become resistant to ASMs in a classic pharmacoresistant TLE model. This may be of translational importance for the precise management of pharmacoresistant TLE.
Epilepsy, Temporal Lobe/diagnosis* ; Animals ; Drug Resistant Epilepsy/drug therapy* ; Electroencephalography/methods* ; Rats ; Anticonvulsants/pharmacology* ; Neural Networks, Computer ; Male ; Humans ; Phenytoin/pharmacology* ; Adult ; Disease Models, Animal ; Female ; Rats, Sprague-Dawley ; Young Adult ; Convolutional Neural Networks

OBJECTIVE: This study aims to elucidate the therapeutic potential of osthole for the treatment of atopic dermatitis (AD), focusing on its ability to alleviate chronic pruritus (CP) and the underlying molecular mechanisms. METHODS: In this study, we investigated the anti-inflammatory effects of osthole in both a 2,4-dichloronitrobenzene (DNCB)-induced AD mouse model and tumor necrosis factor-α (TNF-α) and interferon-γ (IFN-γ) stimulated huma immortalized epidermal (HaCaT) cells. The anti-itch effect of osthole was specifically assessed in the AD mouse model. Using methods such as hematoxylin and eosin (HE) staining, enzyme-linked immunosorbent assay (ELISA), western blot (WB), quantitative real-time PCR (qRT-PCR), and immunofluorescence staining. RESULTS: Osthole improved skin damage and clinical dermatitis scores, reduced scratching bouts, and decreased epidermal thickness AD-like mice. It also reduced the levels of interleukin (IL)-31 and IL-31 receptor A (IL-31 RA) in both skin tissues and HaCaT cells. Furthermore, Osthole suppressed the protein expression levels of phosphor-p65 (p-p65) and phosphor-inhibitor of nuclear factor kappa-Bα (p-IκBα). Meanwhile, it increased the protein expression levels of peroxisome proliferator-activated receptor α (PPARα) and PPARγ in HaCaT cells. CONCLUSION These findings indicated that osthole effectively inhibited CP in AD by activating PPARα, PPARγ, repressing the NF-κB signaling pathway, as well as the expression of IL-31 and IL-31 RA.

OBJECTIVE: To investigate the association between ABO blood types and gestational diabetes mellitus (GDM) risk. METHODS: A prospective birth cohort study was conducted. ABO blood types were determined using the slide method. GDM diagnosis was based on a 75-g, 2-h oral glucose tolerance test (OGTT) according to the criteria of the International Association of Diabetes and Pregnancy Study Groups. Logistic regression was applied to calculate the odds ratios ( ORs) and 95% confidence intervals ( CIs) between ABO blood types and GDM risk. RESULTS: A total of 30,740 pregnant women with a mean age of 31.81 years were enrolled in this study. The ABO blood types distribution was: type O (30.99%), type A (26.58%), type B (32.20%), and type AB (10.23%). GDM was identified in 14.44% of participants. Using blood type O as a reference, GDM risk was not significantly higher for types A ( OR = 1.05) or B ( OR = 1.04). However, women with type AB had a 19% increased risk of GDM ( OR = 1.19, 95% CI = 1.05-1.34; P < 0.05), even after adjusting for various factors. This increased risk for type AB was consistent across subgroup and sensitivity analyses. CONCLUSION The ABO blood types may influence GDM risk, with type AB associated with a higher risk. Incorporating it-either as a single risk factor or in combination with other known factors-could help identify individuals at risk for GDM before or during early pregnancy.
Humans ; Female ; Pregnancy ; Diabetes, Gestational/etiology* ; ABO Blood-Group System ; Adult ; Prospective Studies ; Risk Factors ; Young Adult

Objective:To investigate the correlation between cranial imaging changes and clinical detection indicators in newborns infected with human cytomegalovirus（HCMV），and to provide a basis for the assessment and monitoring of clinical HCMV infection.Methods:A total of 87 newborns with HCMV infection treated in Shengjing Hospital of China Medical University from August 2016 to December 2017 were selected.According to the cranial imaging examination results，they were divided into an abnormal group（25 cases）and a normal group（62 cases）.The HCMV-DNA copy number of peripheral blood mononuclear cell（PBMC）was detected by real time PCR，and the clinical data of two groups of newborns were analyzed.Logistic regression was used for multivariate analysis，and drawed receiver operating characteristic（ROC）curve to evaluate the predictive value of each indicator for cranial imaging examination results.Results:Compared with the normal group，the newborns in abnormal cranial imaging group had smaller gestational age（29.29w vs 33.00w， P=0.004），lower birth weight（1 393.00g vs 1 835.00g， P=0.003），lower hemoglobin levels（87.00 g/L vs 98.00 g/L， P=0.025），and significantly higher PBMC HCMV-DNA copy number（80.00% vs 51.61%， P=0.015），with statistically significant differences.The area under the ROC curve of the predictive value of PBMC HCMV-DNA quantitative detection for cranial imaging results was 0.671（ P=0.016），with high sensitivity compared with HCMV-IgM antibody and urinary HCMV-DNA quantification.Logistic regression analysis showed that there was a certain correlation between PBMC HCMV-DNA quantification，gender，and total bilirubin levels and changes in cranial imaging（ P<0.05）.Three indicators combined to predict the area under ROC curve of abnormal cranial imaging results was 0.860（95% CI：0.743~0.976）. Conclusion:PBMC HCMV-DNA quantitative detection has a certain correlation with the cranial imaging changes of newborns with symptomatic HCMV infection，which can provide a reference for risk assessment of nervous system injury.

Objective To analyze the quality of 19 batches of Ginseng Formula Granules from 11 different manufacturers by using Ginseng water Extract reference substance(GWERS)as references.Methods Thin layer chromatography(TLC)identification and feature map detection were carried out according to the identification items and characteristic maps of Ginseng Formula Granules standard(YBZ-PFKL-2021186)issued by the National Medical Products Administration.Results The results of TLC analysis showed that the 19 batches of Ginseng Formula Granules-labeled samples could be divided into three categories.The overall pattern of the first type of samples was consistent with that of GWERS,and the similarity was high.Pseudoginsenoside F11,a unique component of American ginseng,was detected in the second type of samples.Four blue fluorescent spots were observed in the third type of samples compared to GWERS.HPLC results indicated that all 19 batches of Ginseng Formula Granules showed eight characteristic peaks at the same retention time as that of GWERS chromatogram.Two more chromatographic peaks were found in the chromatogram of three batches of samples from one manufacturer compared to the chromatogram of other samples,whose similarity to the GWERS chromatogram was less than 0.65.The similarity between the chromatogram of the remaining 16 sample and GWERS chromatogram was higher than 0.94.Conclusion At present,the quality of Ginseng Formula Granules on the market varies greatly.It was suspected that American ginseng might appear among them.The application of GWERS for quality analysis of Ginseng Formula Granules has better applicability to the control medicinal materials.

Liver ischemia-reperfusion injury (IRI) is a significant factor contributing to liver dysfunction following surgical procedures such as liver transplantation and hepatectomy, and its pathogenesis is closely associated with oxidative stress and immune responses. However, effective prevention and therapeutic strategies are still lacking. Short-chain fatty acids (SCFAs), primarily produced by the fermentation of gut microbiota, are the major source of these acids in the human body. Research has indicated that SCFAs play a significant role in oxidative stress and immune response. This review primarily focuses on the advancements on the role of SCFAs, the main metabolic byproducts of gut microbiota, in liver IRI, with a view to provide insights for the development of prevention and treatment strategies for liver IRI.

Objective:This study aims to analyze the clinical characteristics of elderly patients with lung adenocarcinoma and to construct a predictive model for assessing their survival.Methods:We conducted a retrospective analysis of clinical data sourced from the SEER database for patients aged 60 years or older who were diagnosed with lung adenocarcinoma between 2013 and 2018.Cox regression analysis was employed to identify independent prognostic factors affecting the survival of elderly lung adenocarcinoma patients, leading to the development of a nomogram model.The discriminative ability and calibration of the nomogram were assessed using the C-index and calibration curve.Each patient's total risk score was calculated based on the predictive model, and patients were stratified according to the quartiles of their total risk scores.The Kaplan-Meier method and Log-rank test were utilized to evaluate survival differences among the identified risk groups.Results:Among 38, 852 lung adenocarcinoma patients, 17, 200 were males and 21, 652 were females.Significant differences in survival rates were observed among lung adenocarcinoma patients based on age, gender, marital status, histological grade, TNM stage, tumor size, and the presence of bone, brain, or liver metastases, as well as the type of treatment received, including surgical treatment, radiation therapy, and chemotherapy(all P<0.001).The C-index of the training model was 0.815(95% CI: 0.811-0.819), while the validation model yielded a C-index of 0.810(95% CI: 0.804-0.816).The prediction model demonstrated higher Area Under Curve(AUC)values of 0.746, 0.768, and 0.775 for 1-year, 3-year, and 5-year survival in the modeling dataset, respectively, and 0.747, 0.770, and 0.777 in the validation dataset.Furthermore, the risk stratification model effectively distinguished patients at varying levels of risk( P<0.001). Conclusions:Age, gender, marital status, histological grade, TNM stage, tumor size, and the presence of bone, brain, and liver metastases, along with treatment modalities such as surgery, radiotherapy, and chemotherapy, were identified as independent prognostic factors for elderly patients with lung adenocarcinoma.The risk prediction model developed in this study effectively differentiates between patients at varying levels of risk, which holds significant implications for predicting treatment responses in elderly lung adenocarcinoma patients and advancing the practice of precision medicine.