Objective:To analyze the prognostic factors of patients with liver cirrhosis and portal vein thrombosis (PVT), and to construct a prognostic prediction model based on machine learning methods.Methods:The clinical data of 388 patients with liver cirrhosis and PVT admitted to the Fifth Medical Center of PLA General Hospital from January 2022 to April 2024 were retrospectively collected and analyzed, including 243 males and 145 females, aged (56.9±10.9) years. A total of 388 patients were randomly divided into the training set ( n=310) and the testing set ( n=78) in a 4∶1 ratio. The Boruta algorithm was used to screen the key features in the training set, and then four machine learning algorithms, including random forest, support vector machine, generalized linear model and Bayesian, were used to establish a survival prediction model. Model performance was evaluated by the receiver operating characteristic (ROC) curves of the test set and the training set. The patients were followed up for 1 year for survival. Sort the importance of features based on the SHAP value. Results:There were 250 patients (80.6%) who survived and 60 (19.4%) who died. The model for end-stage liver disease score, total bilirubin, serum creatinine, prothrombin time, international normalized ratio, D-dimer, white blood cell count, severe ascites ratio, and Child-Pugh grade C ratio of liver function in the death group were higher than those in the survival group, and the red blood cell count and hematocrit were lower than those in the survival group, and the differences were statistically significant (all P<0.05). The areas under the ROC curve for predicting survival by random forest, support vector machine, generalized linear model and Bayesian model were 0.92, 0.78, 0.81 and 0.71 in the training set, and the area under the ROC curve in the testing set were 0.81, 0.72, 0.67 and 0.68, respectively. Random forest had the best prediction performance, with an accuracy of 81.7%, a sensitivity of 84.6%, and a specificity of 76.9% in the testing set. In the analysis of the importance of characteristic parameters of the random forest model, total bilirubin, red blood cells, hematocrit, serum creatinine, ascites classification, etc. had a relatively high contribution to the model. Conclusion:In the survival prediction model of patients with liver cirrhosis and PVT based on machine learning algorithm, the random forest model had high prediction performance, and total bilirubin may be the most important factor affecting the survival prognosis of patients.

Objective:To analyze the prognostic factors of patients with liver cirrhosis and portal vein thrombosis (PVT), and to construct a prognostic prediction model based on machine learning methods.Methods:The clinical data of 388 patients with liver cirrhosis and PVT admitted to the Fifth Medical Center of PLA General Hospital from January 2022 to April 2024 were retrospectively collected and analyzed, including 243 males and 145 females, aged (56.9±10.9) years. A total of 388 patients were randomly divided into the training set ( n=310) and the testing set ( n=78) in a 4∶1 ratio. The Boruta algorithm was used to screen the key features in the training set, and then four machine learning algorithms, including random forest, support vector machine, generalized linear model and Bayesian, were used to establish a survival prediction model. Model performance was evaluated by the receiver operating characteristic (ROC) curves of the test set and the training set. The patients were followed up for 1 year for survival. Sort the importance of features based on the SHAP value. Results:There were 250 patients (80.6%) who survived and 60 (19.4%) who died. The model for end-stage liver disease score, total bilirubin, serum creatinine, prothrombin time, international normalized ratio, D-dimer, white blood cell count, severe ascites ratio, and Child-Pugh grade C ratio of liver function in the death group were higher than those in the survival group, and the red blood cell count and hematocrit were lower than those in the survival group, and the differences were statistically significant (all P<0.05). The areas under the ROC curve for predicting survival by random forest, support vector machine, generalized linear model and Bayesian model were 0.92, 0.78, 0.81 and 0.71 in the training set, and the area under the ROC curve in the testing set were 0.81, 0.72, 0.67 and 0.68, respectively. Random forest had the best prediction performance, with an accuracy of 81.7%, a sensitivity of 84.6%, and a specificity of 76.9% in the testing set. In the analysis of the importance of characteristic parameters of the random forest model, total bilirubin, red blood cells, hematocrit, serum creatinine, ascites classification, etc. had a relatively high contribution to the model. Conclusion:In the survival prediction model of patients with liver cirrhosis and PVT based on machine learning algorithm, the random forest model had high prediction performance, and total bilirubin may be the most important factor affecting the survival prognosis of patients.

BACKGROUND: The presence of fibrosis is a criterion for subtype classification in the newly updated hypersensitivity pneumonitis (HP) guidelines. The present study aimed to summarize differences in clinical characteristics and prognosis of non-fibrotic hypersensitivity pneumonitis (NFHP) and fibrotic hypersensitivity pneumonitis (FHP) and explore factors associated with the presence of fibrosis. METHODS: In this prospective cohort study, patients diagnosed with HP through a multidisciplinary discussion were enrolled. Collected data included demographic and clinical characteristics, laboratory findings, and radiologic and histopathological features. Logistic regression analyses were performed to explore factors related to the presence of fibrosis. RESULTS: A total of 202 patients with HP were enrolled, including 87 (43.1%) NFHP patients and 115 (56.9%) FHP patients. Patients with FHP were older and more frequently presented with dyspnea, crackles, and digital clubbing than patients with NFHP. Serum levels of carcinoembryonic antigen, carbohydrate antigen 125, carbohydrate antigen 153, gastrin-releasing peptide precursor, squamous cell carcinoma antigen, and antigen cytokeratin 21-1, and count of bronchoalveolar lavage (BAL) eosinophils were higher in the FHP group than in the NFHP group. BAL lymphocytosis was present in both groups, but less pronounced in the FHP group. Multivariable regression analyses revealed that older age, <20% of lymphocyte in BAL, and ≥1.75% of eosinophil in BAL were risk factors for the development of FHP. Twelve patients developed adverse outcomes, with a median survival time of 12.5 months, all of whom had FHP. CONCLUSIONS Older age, <20% of lymphocyte in BAL, and ≥1.75% of eosinophil in BAL were risk factors associated with the development of FHP. Prognosis of patients with NFHP was better than that of patients with FHP. These results may provide insights into the mechanisms of fibrosis in HP.
Humans ; Bronchoalveolar Lavage Fluid ; Prospective Studies ; Alveolitis, Extrinsic Allergic/diagnosis* ; Fibrosis ; Carbohydrates

Objective To investigate the effect of dapagliflozin on blood pressure variability(BPV)and left ventricular mass index(LVMI)in patients with type 2 diabetes mellitus(T2DM)and hypertension.Methods Patients with T2DM complicated with hypertension admitted to Lishui Central Hospital from August 2021 to August 2022 were selected as the study subjects,and were treated with conventional treatment(control group)and dapagliflozin treatment(test group),respectively.The changes of BPV index,LVMI,blood glucose level and the incidence of adverse reactions were compared between the two groups.Results A total of 94 patients with T2DM and hypertension were included in the study,including 47 patients in the test group and 47 in the control group.The 24-hour diastolic blood pressure(DBP),24-hour systolic blood pressure(SBP),24-hour systolic standard deviation(SSD),24-hour diastolic standard deviation(DSD),fasting blood glucose(FBG),2-hour blood glucose(PG),glycated hemoglobin glycosylated hemoglobin(HbA1c),body mass index(BMI)and LVMI of the patients with T2DM and hypertension were significantly decreased in the two groups(P<0.05),and the 24-hour SBP,24-hour DBP,24-hour SSD,24-hour DSD,FPG,2-hour PG,HbA1c,BMI and LVMI in the test group were lower than those in the control group(P<0.05).The total incidence of adverse reactions between the test group and the control group was 10.64% and 4.26% ,respectively,and the difference was not statistically significant(P>0.05).Conclusion Dapagliflozin can reduce LVMI and improve BPV and blood glucose levels in patients with T2DM and hypertension,and has a good safety profile.

ObjectiveTo investigate the effect of Shunao Jieyu decoction on intestinal flora in patients with post-stroke depression. MethodSixty patients with post-stroke depression of Qi stagnation， blood stasis， and phlegm obstruction were selected and divided into a treatment group （30 cases， Shunao Jieyu decoction） and a control group （n=30， paroxetine hydrochloride tablets） according to the random number table. All patients were treated correspondingly for eight weeks. The scores of traditional Chinese medicine（TCM） syndrome， Hamilton rating scale for depression（HAMD）， National Institutes of Health stroke scale（NIHSS）， and activities of daily living（ADL）before and after treatment were compared between the two groups. High-throughput sequencing was used to analyze the diversity of fecal flora and the distribution of taxonomical levels in two groups before and after treatment. ResultThe post-treatment TCM syndrome score， HAMD score， and NIHSS score were lower than those before treatment in the same group （P<0.05）， while the post-treatment ADL score was higher than that before treatment （P<0.05）. Compared with the control group after treatment， the treatment group showed decreased TCM syndrome score （P<0.05）. No significant difference was observed in the HAMD score， NIHSS score and ADL score between the two groups after treatment. The total effective rate of the treatment group was 90% （27/30）， which was superior to 66.3% （19/30） of the control group （χ²=5.863， P<0.05）. After treatment， the average values of Chao1 index， Observed species index， Shannon index， Simpson index， and Pielou's evenness index of intestinal flora diversity in the treatment group increased without significant difference， while the average value of the Good's Coverage index remained unchanged in the same group. At the phylum level， the abundance of Bacteroidetes increased. At the family level， the abundance of Bacteroidaceae increased. At the genus level， the abundance of Bacteroidetes increased. ConclusionShunao Jieyu decoction can effectively improve the clinical TCM symptoms of patients with post-stroke depression， relieve neurological impairment， improve the ability of daily living， and change the diversity and abundance of the intestinal flora of patients at different taxonomic levels.

Objective To investigate the expression and possible role of hypoxia-inducible factor-1 (HIF-1) at the maternal-fetal interface following Toxoplasma gondii infection during early pregnancy. Methods Twenty pregnant C57BL/6 mice, each weighing 16 to 20 g, were randomly divided into 4 groups, including the 12-d control group, 12-d infection group, 18-d control group and 18-d infection group. Mice in the 12-d and 18-d infection groups were injected intraperitoneally with 150 tachyzoites of the T. gondii PRU strain on day 6 of pregnancy, while mice in the 12-d control and 18-d control groups were injected with the same volume of phosphate buffered saline (PBS). Mice in the control and infection groups were sacrificed on days 12 and 18 of pregnancy, and the placental and uterine specimens of the pregnant mice in each group were sampled for pathological examinations. The mRNA expression of HIF-1α, HIF-1β and vascular endothelial growth factor (VEGF) was quantified using quantitative fluorescent real-time PCR (qPCR) assay in the placental and uterine specimens, and the correlation between HIF-1α and VEGF mRNA expression was examined. In addition, and the HIF-1α expression was detected using immunohistochemical staining in the placental and uterine specimens of pregnant mice. Results Compared with the 12-d and 18-d control groups, adverse pregnant outcomes were observed in mice in 12-d and 18-d infection groups, such as teratism and placental dysplasia. HE staining showed swelling and blood stasis of cells, sinusoid reduction and inflammatory cell infiltration in the labyrinth area of the placenta specimens of mice in 12-d and 18-d infection groups relative to 12-d and 18-d control groups, and columnar epithelial cell injury and inflammatory cell infiltration were seen in the mouse uterine specimens in both infection groups. qPCR assay detected significantly higher HIF-1α (F = 132.6, P < 0.05) and HIF-1β mRNA expression (F = 286.9, P < 0.05) in the placental specimens and lower HIF-1α (F = 111.5, P < 0.05) and HIF-1β mRNA expression (F = 55.2, P < 0.05) in the uterine specimens in the 12-d infection group than in the 12-day control group, and significantly lower HIF-1α and HIF-1β mRNA expression was detected in the placental and uterine specimens in the 18-d infection group than in the 18-day control group (F = 215.8, 418.9, 156.8 and 200.1; all P values < 0.05). Significantly lower VEGF-A (F = 426.2, P < 0.05), VEGF-B (F = 104.6, P < 0.05) and VEGF-C mRNA expression (F = 566.9, P < 0.05) in the placental specimens and higher VEGF-A (F = 426.2, P < 0.05), VEGF-B (F = 104.6, P < 0.05) and VEGF-C mRNA expression (F = 566.9, P < 0.05) in the uterine specimens were detected in the 12-d infection group than in the 12-d control group, and higher VEGF-A, VEGF-B and VEGF-C mRNA expression was found in the placental and uterine specimens in the 18-d infection group than in the 18-d control group (F = 521.9, 100.6, 275.9, 224.6, 108.2 and 333.4; all P values < 0.05). Immunohistochemical staining showed strongly and mildly positive HIF-1α expression in the mouse placental labyrinth area in the 12-d and 18-d infection groups relative to 12-d and 18-d control groups, while no HIF-1α expression was detected in mouse uterine specimens. Conclusions HIF-1α expression appears a tendency towards a rise in the second trimester and a reduction in the third trimester in mice following T. gondii infection during early pregnancy, which is contrary to the changing tendency of VEGF-A, VEGF-B, and VEGF-C expression. It is hypothesized that HIF-1α inhibits placental angiogenesis in mice during pregnancy through suppressing VEGF expression, resulting in adverse pregnant outcomes.

Objective: To investigate the prevalence of allergic rhinitis (AR) in 3 central cities (Chifeng, Hohhot, Ordos) and the surrounding rural areas of Inner Mongolia region, and to look for possible risk factors related to the disease. Methods: From March to October of 2019, a multi-stage stratified random sampling epidemiological survey was conducted in Chifeng, Hohhot, Ordos and rural areas. The AR-related factors of the population were obtained in the form of face-to-face questionnaire survey, and the skin prick test (SPT) was taken for the participants. AR disease was diagnosed according to the "Guidelines for the Diagnosis and Treatment of Allergic Rhinitis (2015, Tianjin)". The daily airborne pollen situation in the three regions was monitored during the same period. SPSS 23.0 was used to analyze all survey results. Results: A total of 6 818 questionnaires were recovered, with 6 393 valid questionnaires. The self-reported prevalence of AR was 27.72% (1 772/6 393) and the confirmed prevalence of AR was 17.10% (1 093/6 393). The prevalence of perennial AR was 1.83% (117/6 393) while the prevalence of seasonal AR was 15.27% (976/6 393). The prevalence of AR diagnosed in females was higher than that in males (19.19% vs 15.34%, χ²=16.594, P<0.001) and the prevalence of females in the two age groups of 36-45 years and 46-55 years was significantly higher than that of males (18.17% vs 9.73%, 14.13% vs 7.25%, χ² value was 23.848, 18.772, respectively, all P<0.001). The prevalence of confirmed diagnoses in ethnic minorities was higher than that of Han nationality, and the prevalence of confirmed diagnoses in urban areas was higher than that in rural areas (23.13% vs 16.20%, 27.27% vs 9.71%, χ² value was 24.516, 336.024, respectively, all P<0.001). The main nasal symptoms of AR patients were sneezing (91.31%), nasal congestion (85.91%) and nasal itching (85.00%). The most common concomitant disease of AR was allergic conjunctivitis (73.99%). Asthma (OR=6.629), food allergy (OR=3.236), drug allergy (OR=1.786), application of antibiotics (OR=1.553), recent home decoration (OR=2.307), and smoking (OR=1.322) were the AR related risk factors. The highest proportion of SPT positive reactions was Artemisia annua (80.15%). The peak period of clinical symptoms of AR patients in Inner Mongolia region was July to September, which was consistent with the second peak period of airborne pollen monitoring. Conclusions: The prevalence of AR in central cities and the surrounding rural areas of Inner Mongolia region is 17.10%, and Artemisia species is the most important pollen allergen in this area. History of asthma, food allergy, drug allergy, antibiotic use, home decoration and smoking history are the related risk factors for AR.
Adult ; Allergens ; China/epidemiology* ; Female ; Humans ; Male ; Middle Aged ; Pollen ; Prevalence ; Rhinitis, Allergic/epidemiology* ; Rhinitis, Allergic, Seasonal ; Urbanization

Adult ; Endocarditis/surgery* ; Endocarditis, Bacterial/surgery* ; Hospital Mortality ; Humans ; Male ; Middle Aged ; Retrospective Studies ; Risk Factors ; Young Adult

Objective: To establish a method for the determination of bilastine in human plasma, and evaluate the uncertainty by LC-MS/MS. Methods: The uncertainty sources were obtained from the whole process of the determination including repeatability, e-quipment error, weighting, solution preparation, calibration fitting and plasma sample handling. The uncertainty and synthesized un-certainty of each component were calculated, and then the expanded uncertainty was obtained. Results: The expanded uncertainty for low (15 ng·ml-1), medium (400 ng·ml-1) and high(1 200 ng·ml-1) level of bilastine was 1. 45 ng·ml-1, 28. 72 ng·ml-1 and 74. 61 ng·ml-1, respectively (k=2, P=95% ). Conclusion: The uncertainty in the determination of bilastine in human plasma is mainly caused by equipment error, solution preparation, protein precipitation and calibration fitting (especially at low level).

Histone deacetylase (HDAC) is a kind of protease,which plays an important role in the structural modification of chromosomes and the regulation of gene expression.Its excessive expression in cancer cells causes acetylation imbalance,which is closely related to the occurrence of tumor.The high efficiency and low toxicity of histone deacetylase inhibitor (HDACi) has been widely recognized as anti-tumor drug with the deepening of the study in epigenetics.It is expected to bring more breakthroughs in the treatment of tumor.