Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

OBJECTIVE To investigate the current status of monitoring indicators related to the"Perioperative In-fection Control"in medical institutions above the secondary level in Guizhou Province,and to delve into the imple-mentation of key measures for infection prevention and control during the perioperative period for patients under-going surgical operations.METHODS Based on the"Implementation Plan for the'Perioperative Infection Control'Initiative in Guizhou Province",a"Case Investigation Form on Key Measures for Infection Prevention and Control During the Perioperative Period for Patients Undergoing Surgical Operation"was developed.A total of 138 medi-cal institutions participated in the case investigation,and a total of 2 128 cases were investigated.RESULTS The overall monitoring indicators for the"Perioperative Infection Control"initiative in the 138 medical institutions a-bove the secondary level in Guizhou Province were at a relatively low level.The skin cleansing compliance rate was 80.32％,the hair removal compliance rate was 16.43％,the prophylactic antibacterial drug administration rate within 0.5-1 hour before surgery was 55.94％and the antibacterial drug discontinuation rate within 24 hours after prophylactic medication for type Ⅰ incision surgeries was 56.48％.The hair removal compliance rate was higher in tertiary medical institutions(19.21％)than in secondary medical institutions(14.34％)(P=0.039).The distri-bution of the four monitoring indicators varied in clinical departments and surgery types,with statistically signifi-cant differences(P＜0.05).The preferred method for surgical site skin cleansing in medical institutions across the province was local wiping,primarily with clean water(57.21％).The primary method for hair removal was razors(68.82％),and hair removal on the day of surgery was most common(61.75％).CONCLUSIONS Conduc-ting a survey on the current status of"Perioperative Infection Control"initiative monitoring indicators in medi-cal institutions in Guizhou Province helps to understand the implementation of key measures for perioperative in-fection prevention and control and set intervention targets,thus providing references for establishing a dynam-ic monitoring indicator change mechanism.

This paper reported a case of simultaneous twin pregnancy and successful delivery in each horn of uterus didelphys. The patient had a history of adverse pregnancies and was diagnosed with a uterus didelphys with double cervix through hysteroscopy, although the uterine cavity morphology was normal. This pregnancy was conceived naturally, with the last menstrual period on December 21, 2023. The patient underwent regular prenatal check-ups at Xi'an People's Hospital (Xi'an Fourth Hospital). Early pregnancy ultrasound confirmed simultaneous twin pregnancy in each horn of uterus didelphys. Multiple ultrasounds showed no fetal growth restriction or other abnormalities. At 37 weeks of gestation, the patient experienced chest tightness and shortness of breath due to polyhydramnios, and one fetus was in the cephalic position while the other was in the breech position, posing a high risk for vaginal delivery. Therefore, an elective cesarean section was performed at 37 weeks and one day of gestation, delivering a male infant weighing 3 260 g and a female infant weighing 2 400 g. The 1-,5-, and 10-minute Apgar scores were all 10 points, with favorable maternal and neonatal outcomes.

Objective To observe the correlations of metabolite levels in medial prefrontal cortex(mPFC)and cancer-related depression(CRD)in patients with non-small cell lung cancer(NSCLC).Methods Totally 38 NSCLC patients were prospectively enrolled and divided into CRD group(n=23)and non CRD group(n=15)based on Hamilton depression scale(HAMD-17).Meanwhile,22 healthy individuals were taken as control group.1 H-MR spectroscopy was performed using Meshcher-Garwood point resolved spectroscopy sequence,then metabolite levels of mPFC were measured,and their correlations with HAMD-17 score were analyzed.Results Significant differences of gamma-aminobutyric acid(GABA)+/Water and glutamate/glutamine complex(Glx)/Water in mPFC were found among 3 groups.GABA+/Water in mPFC of CRD group was significantly lower than that of the other 2 groups(both P＜0.05),and Glx/Water in mPFC of CRD group was significantly lower than that of control group(P=0.034).In NSCLC patients,GABA+/Water in mPFC was negatively correlated with HAMD-17 score(r=-0.491,P=0.002).Conclusion GABA+/Water in mPFC was negatively correlated with HAMD-17 score in NSCLC patients.

Objective:To investigate the efficacy and potential mechanism of sulfasalazine (SASP) therapy for intrahepatic cholestasis.Methods:Forty SD rats were randomly divided into a normal group (carboxymethylcellulose sodium 0.5%), a model group (carboxymethylcellulose sodium 0.5%), a SASP group (sulfasalazine 150 mg/kg), and an ursodeoxycholic acid (UDCA 100 mg/kg) group, with ten rats in each group. The cholestatic liver injury model was induced using α-naphthylisothiocyanate. Blood samples were collected to detect liver biochemistry and cholestasis indexes. Rat liver tissue was collected for hematoxylin-eosin staining and Mason staining. Liver tissue was analyzed using transcriptome sequencing, real-time reverse transcription quantitative polymerase chain reaction, Western blotting and flow cytometry. Simultaneously, the level of inflammatory factors, total cholesterol, and total bile acids were measured in liver tissue. A t-test or a nonparametric test was selected based on the distribution and variance characteristics of the data. Results:The serum levels of alanine aminotransferase [(386.88±155.77) U/L], aspartate aminotransferase [(593.13±251.44) U/L], alkaline phosphatase [(561.25±167.54) U/L], total bilirubin [(38.00±29.75) mol/L] and total bile acids [(191.31±91.48) mol/L] were significantly lower in the SASP than the model groups [(778.75±313.59) U/L, (1 159.38±274.62) U/L, (801.25±161.28) U/L, (86.63±27.83) mol/L, (432.63±151.54) mol/L, P<0.05]. Liver histopathology showed that the inflammatory cells in the manifold area, the bile duct proliferation and dilation, and the collagen deposition in the manifold area were significantly improved under the pathological state of cholestasis in the SASP group. The results of transcriptome sequencing demonstrated that SASP activated the peroxisome proliferator actived receptor α (PPAR α) and inhibited Th17 cell differentiation. The PPARα mRNA level in the liver tissue of rats was significantly increased in the SASP group compared with that in the model group [(0.41±0.28) vs. (0.16±0.04), P<0.05], and the expression of 3-hydroxy-3-methylglutaryl coenzyme A reductase was decreased compared with that in the model group [(3.09±1.16) vs. (8.19±2.19), P<0.05], which was also verified at the protein level. The concentrations of total cholesterol [(0.31±0.34) mmol/g] and total bile acids [(2.58±0.99) μmol/g] were lower than the model group [(0.83±0.62) mmol/g and (4.07±0.91) μmol/g] ( P<0.05), and at the same time it was accompanied by lower levels of inflammatory factors ( P<0.05). SASP treatment decreased the expression of retinoic acid receptor-related orphan receptor γt gene ( P<0.05) and the proportion of Th17 ( P<0.05). Conclusion:SASP can improve cholestatic liver injury, and its mechanism is related to the activation of peroxisome proliferator-activated receptor α and the inhibition of Th17 cell differentiation.

Objective:This study aimed to analyze the genetic variation of the human papillomavirus (HPV) type 39 genomes and to predict and screen the dominant T-cell and B-cell epitopes of the viral early proteins (E1, E2, E6, E7) and late proteins (L1, L2).Methods:A total of 70 full-length sequences of HPV39 variants were retrieved from the clinical samples and the National Center for Biotechnology Information (NCBI) to construct a phylogenetic tree, analyze genetic polymorphisms, and predict the physicochemical properties of the viral proteins. Next, T-cell and B-cell epitopes were predicted using IEDB and ABCpred, and potential dominant epitopes were further selected based on parameters such as the secondary structure of the epitope region, peptide flexibility, hydrophilicity, surface accessibility and antigenicity. Finally, a homology analysis of the potential dominant epitopes was performed with 12 high-risk HPV types.Results:HPV39 variants from different sources can be clustered into two lineages (A and B), each exhibiting distinct mutation patterns. The mutation rate was the highest in E7 and the lowest in E1 among the different viral genes. However, these nucleotide/amino acid mutations did not significantly impact the physicochemical properties of the viral proteins. After prediction and screening, 5 and 6 potential dominant B-cell epitopes were identified in both L1 and L2, respectively. E1, E2, E6, and E7 yielded 18, 10, 4, and 1 potential dominant HLA-I restricted T-cell epitopes, respectively. Additionally, E1, E2, and E6 yielded 7, 3, and 2 potential dominant HLA-II restricted T-cell epitopes, respectively. Homology analysis indicated that T-cell dominant epitopes in E1, E2, and E6, as well as B-cell epitopes in L2, showed high homology (93%-100%) with HPV68, HPV33, HPV45, and HPV59.Conclusions:Bioinformatics analysis and prediction revealed that HPV39 variants can be clustered into two main evolutionary branches, A and B, each exhibiting a specific mutation pattern. The viral proteins contain potential dominant T-cell and B-cell epitopes that can be further investigated, providing valuable theoretical support for the development of HPV39-related peptide-based vaccines and therapeutics.

Objective:To explore the application of machine learning (ML) models based on radiomics and dosiomics to the assessment of hematologic toxicity (HT) in patients with locally advanced cervical cancer, and to preliminarily explore the comprehensive application of multi-omics features.Methods:A retrospective study was conducted on the clinical data, planning computed tomography (CT) images, and dose files of 205 patients with locally advanced cervical cancer who received concurrent chemoradiotherapy at the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, from January 2022 to June 2023. Patients were categorized according to the severity of HT. Radiomics and dosiomics features were extracted from the same regions of interest (ROIs), followed by feature selection utilizing a random forest algorithm. Then, radiomics, dosiomics, and hybrid models were established based on extreme gradient boosting (XGBoost). The classification performance of these models was assessed by calculating their sensitivity, specificity, and area under the receiver operating characteristic curve (AUC).Results:The radiomics model yielded sensitivity, specificity, and AUC of 0.42, 0.86, and 0.78, respectively. The dosiomics model exhibited sensitivity, specificity, and AUC of 0.50, 0.90, and 0.74, respectively. In contrast, the hybrid model achieved sensitivity, specificity, and AUC of 0.50, 0.83, and 0.83, respectively. These findings suggest that the hybrid model possessed an enhanced classification capability compared to the individual radiomics and dosiomics models.Conclusions:It is feasible to use ML models based on radiomics and dosiomics to conduct the classification and prediction of HT in patients with locally advanced cervical cancer treated with concurrent chemoradiotherapy. Furthermore, integrating both radiomics features and dosiomics features can improve the classification performance of relevant prediction models, thus holding application potentials to optimize treatment strategies for patients with locally advanced cervical cancer.

Traditional Chinese medicine(TCM) resources are an important foundation for the theory and practice of TCM. Rare and endangered TCM, as a significant component of these resources, plays an essential role. Conducting research on substitutes for rare and endangered TCM resources is of great significance for alleviating resource shortages, promoting the sustainable utilization of TCM, and advancing TCM modernization. This paper reviews the conservation achievements of rare and endangered Chinese medicinal materials in China and organizes the substitution methods for these materials. Currently, the main substitution approaches include introduction and domestication, tissue culture, varietal replacement, and artificial synthesis. Furthermore, this paper proposes the following approaches for researching the application scenarios of rare and endangered medicinal materials, i.e., tracing the historical context of their use to clarify foundational principles; verifying disease classifications to strengthen the clinical application scenarios of these materials; analyzing the evolution patterns of prescription formulations to strengthen the mining of the compatibility application scenarios of rare and endangered medicinal materials; scientifically evaluating to strengthen the application scenario research and development of endangered Chinese patent medicine industry. These efforts aim to promote the scientific substitution and sustainable utilization of rare and endangered medicinal materials and their substitutes.
Drugs, Chinese Herbal/chemistry* ; Humans ; Medicine, Chinese Traditional ; China ; Plants, Medicinal/growth & development* ; Endangered Species ; Conservation of Natural Resources ; Animals

Geniposidic acid(GA), a natural iridoid, exists in the roots, stems, leaves, flowers, bark, fruits, and seeds of medicinal plants of Rubiaceae, Eucommiaceae, and Plantaginaceae. Modern pharmacological studies have revealed that GA has multiple pharmacological activities, including organ-protective, anti-inflammatory, antioxidative, anti-osteoporosis, anti-neurodegenerative, and anti-cardiovascular effects. GA can enhance cell/organism defenses by upregulating key anti-inflammatory and antioxidant cytokines, while downregulating key node proteins in pro-inflammatory signaling pathways such as AhR and TLR4/MyD88, thereby exerting pharmacological effects such as organ protection. Pharmacokinetic investigations have suggested that after oral administration, GA can be distributed in multiple organs(kidney, liver, heart, spleen, lung, etc.). In addition, the pharmacokinetic behavior of GA could be significantly altered under disease conditions, as demonstrated by a marked increase in systematic exposure. This article comprehensively summarizes the reported pharmacological activities and mechanisms and systematically analyzes the pharmacokinetic characteristics and key parameters of GA, with the aim of providing a theoretical basis and scientific reference for the precise clinical application of GA-related Chinese patent medicines, as well as for the investigation and development of innovative drugs based on GA.
Humans ; Drugs, Chinese Herbal/chemistry* ; Animals ; Iridoid Glucosides/chemistry* ; Plants, Medicinal/chemistry* ; Anti-Inflammatory Agents/pharmacology*

PURPOSE: Septic shock is associated with high mortality and poor outcomes among sepsis patients with coagulopathy. Although traditional statistical methods or machine learning (ML) algorithms have been proposed to predict septic shock, these potential approaches have never been systematically compared. The present work aimed to develop and compare models to predict septic shock among patients with sepsis. METHODS: It is a retrospective cohort study based on 484 patients with sepsis who were admitted to our intensive care units between May 2018 and November 2022. Patients from the 908th Hospital of Chinese PLA Logistical Support Force and Nanchang Hongdu Hospital of Traditional Chinese Medicine were respectively allocated to training (n=311) and validation (n=173) sets. All clinical and laboratory data of sepsis patients characterized by comprehensive coagulation indexes were collected. We developed 5 models based on ML algorithms and 1 model based on a traditional statistical method to predict septic shock in the training cohort. The performance of all models was assessed using the area under the receiver operating characteristic curve and calibration plots. Decision curve analysis was used to evaluate the net benefit of the models. The validation set was applied to verify the predictive accuracy of the models. This study also used Shapley additive explanations method to assess variable importance and explain the prediction made by a ML algorithm. RESULTS: Among all patients, 37.2% experienced septic shock. The characteristic curves of the 6 models ranged from 0.833 to 0.962 and 0.630 to 0.744 in the training and validation sets, respectively. The model with the best prediction performance was based on the support vector machine (SVM) algorithm, which was constructed by age, tissue plasminogen activator-inhibitor complex, prothrombin time, international normalized ratio, white blood cells, and platelet counts. The SVM model showed good calibration and discrimination and a greater net benefit in decision curve analysis. CONCLUSION The SVM algorithm may be superior to other ML and traditional statistical algorithms for predicting septic shock. Physicians can better understand the reliability of the predictive model by Shapley additive explanations value analysis.
Humans ; Shock, Septic/blood* ; Machine Learning ; Male ; Female ; Retrospective Studies ; Middle Aged ; Aged ; Sepsis/complications* ; ROC Curve ; Cohort Studies ; Adult ; Intensive Care Units ; Algorithms ; Blood Coagulation ; Critical Illness