Objective:To explore the predictive value of changes in prealbumin for the prognosis of patients with hepatitis B virus-associated acute-on-chronic liver failure (HBV-ACLF) after artificial liver treatment.Methods:From January 1, 2018 to December 31, 2021, the clinical data (including prealbumin, platelet count, lymphocyte count, alanine transaminase (ALT), etc.) of 87 patients with HBV-ACLF who received artificial liver treatment at the Department of Gastroenterology of the General Hospital of Western Theater Command PLA were retrospectively collected. The 90-day survival status of all the patients was followed up, and the patients were divided into the survival group and the mortality group according to the survival status. The clinical characteristics and the changes of prealbumin on day 1 to 3, day 3 to 7, and day 1 to 7 after artificial liver treatment were compared between the 2 groups. Multivariate logistic regression analysis was used to analyze the independent influencing factors of the 90-day prognosis of HBV-ACLF patients after artificial liver treatment, and the nomogram prediction model was established and the receiver operating characteristic curve (ROC) was drawn to assess the area under the curve (AUC). Hosmer-Lemeshow goodness-of-fit test, calibration curve and clinical decision curve were performed to evaluate the goodness of fit, consistency and clinical value of the prediction model. Paired t-test and Mann-Whitney U test were used for statistical analysis. Results:There were 69 cases enrolled into the survival group, and 18 cases enrolled into the mortality group. The levels of albumin, prealbumin, platelet count, lymphocyte count, and ALT before treatment, and the level of prealbumin at the 3rd day after treatment of the survival group were all higher than those of the mortality group (32.5 (30.6, 35.2) g/L vs. 29.4 (27.6, 32.3) g/L, 66.0 (52.5, 81.5) mg/L vs. 56.5 (39.2, 65.0) mg/L, 103.0 (72.5, 145.0)×10 9/L vs. 63.5 (40.0, 92.5)×10 9/L, 1.1 (0.8, 1.4)×10 9/L vs. 0.9 (0.5, 1.1)×10 9/L, (514.7±86.4) U/L vs. (328.2±93.4) U/L, 90.0 (69.5, 102.5) mg/L vs.68.5(60.0, 75.8) mg/L), and the age, the level of total bilirubin, international normalized ratio, and prothrombin time before treatment of the survival group were all lower than those of the mortality group (48.0 (42.0, 57.0) years old vs. 48.5 (47.0, 56.0) years old, 323.9 (261.2, 409.2) μmol/L vs. 452.2 (405.8, 510.8) μmol/L, 1.5 (1.3, 1.9) vs. 1.9 (1.4, 2.1), 17.3 (14.6, 20.8) s vs. 21.4 (16.6, 23.2) s), and the differences were statistically significant ( Z=-3.38, -2.87, -2.38 and -2.01, t=2.39, Z=-4.11, 3.00, 3.64, 2.18 and 2.37; all P<0.05). The change of prealbumin on day 1 to 3 after treatment in the mortality group was greater than that in the survival group (-0.182 (-0.321, -0.026) vs. -0.043 (-0.133, 0.093)), and the difference was statistically significant ( Z=-3.42, P=0.001). The results of multivariate logistic regression analysis showed that the age, total bilirubin before treatment, and the change of prealbumin on day 1 to 3 after treatment were independent influencing factors for the 90-day prognosis in HBV-ACLF patients after artificial liver treatment (all P<0.05), and the nomogram model was established based on the above 3 factors. The results of ROC analysis showed that the AUC of the prediction model was 0.933 (95% confidence interval: 0.866 to 1.000, P<0.001), with a sensitivity of 0.933 and a specificity of 0.825. The results of the Hosmer-Lemeshow goodness-of-fit test showed that the prediction model had a good fit( P=0.700). The results of calibration curve analysis indicated that the actual curve of the prediction model was close to the calibration curve, with an average absolute error of 0.034, the consistency between the predicted probability and the actual probability was good. The clinical decision curve analysis suggested that the prediction model had significant clinical benefits. Conclusions:The changes of prealbumin after artificial liver treatment in HBV-ACLF patients can reflect the recovery of liver function. The nomogram prediction model based on the change of prealbumin on day 1 to 3 after treatment, age, and total bilirubin before treatment can better predict the 90-day prognosis of HBV-ACLF patients after artificial liver treatment.

Objective To investigate the geographical distribution patterns and influencing factors of suitable habitats for the desert medicinal plant Cynomorium songaricum Rupr under current climatic conditions;To provide a basis for its resource conservation and sustainable utilization.Methods The MaxEnt model was used to analyze potential suitable habitats for Cynomorium songaricum Rupr.Geographical Detector model was used to identify key environmental factors affecting habitat suitability.Surface cover data were overlaid to assess the distribution of sandy and Gobi regions within suitable habitats,enabling a quantitative evaluation of actual potential suitable areas.Results Model predictions indicated a total suitable habitat area of approximately 2.98×106 km2,representing 30.99%of China's mainland area.Highly suitable habitats are concentrated in desert and Gobi regions of Gansu,Xinjiang,Inner Mongolia,Qinghai and Ningxia.Among climatic factors,precipitation of the coldest quarter(bio19),solar radiation in August(srad8),and mean temperature of the coldest quarter(bio11)significantly influence Cynomorium songaricum Rupr distribution.The interaction between temperature and solar radiation intensity exhibited the highest explanatory power for habitat distribution patterns(q=0.82).Overlay analysis with surface cover data estimated the actual potential suitable area at approximately 9.70×105 km2,with sandy regions comprising 5.73×105 km2 and Gobi regions 3.98×105 km2.Conclusion By integrating multi-source data and modeling approaches,this study delineates the potential suitable habitats for Cynomorium songaricum Rupr across China and evaluates the spatial distribution characteristics and influencing factors of suitable habitats in Cynomorium songaricum Rupr.These findings offer a foundation for conserving wild Cynomorium songaricum Rupr resources,optimizing ecological planting regions,and promoting sustainable industry development.

Objective To analyze the spatial distribution pattern of the potential suitable habitats for the Tibetan medicinal plant Sinopodophyllum hexandrum under current climatic conditions and the factors influencing the spatial differentiation of the habitats.Methods Based on the maximum entropy model,a species distribution model was established using selected species distribution data and environmental variable data.The geographic detector and the interaction detector were applied to quantify the factors affecting the spatial differentiation of the suitable area.By overlaying the suitable area with land cover types,the distribution characteristics of potential arable land and forest land within the potential suitable area were quantified.Results Under the current climatic conditions,altitude,precipitation in July,precipitation during the warmest season,water vapor pressure in June,precipitation in December,and the highest temperature in February are the key environmental factors affecting the distribution of Sinopodophyllum hexandrum.Under the current climatic conditions,the potential geographical distribution range of Sinopodophyllum hexandrum covers an area of 1.30×106 km2.Considering land cover types,the actual suitable area for Sinopodophyllum hexandrum is 6.13×105 km2,including 4.25×105 km2 of forest land and 1.88×105 km2 of arable land.The highly suitable forest areas are mainly distributed in the Aba Tibetan and Qiang Autonomous Prefecture,Ganzi Tibetan Autonomous Prefecture of Sichuan Province,Diqing Tibetan Autonomous Prefecture,Nujiang Lisu Autonomous Prefecture of Yunnan Province and Linzhi City within the Tibet Autonomous Region.The highly suitable arable land areas are mainly distributed in the Linxia Hui Autonomous Prefecture,Dingxi City,Tianshui City,and Longnan City of Gansu Province,with sporadic belt-like distributions in Sichuan Province,Yunnan Province and the Tibet Autonomous Region.Conclusion The study can provide evidence for the protection of wild Sinopodophyllum hexandrum resources and the selection of optimal planting areas.

Objective To analyze the spatial distribution pattern of the potential suitable habitats for the Tibetan medicinal plant Sinopodophyllum hexandrum under current climatic conditions and the factors influencing the spatial differentiation of the habitats.Methods Based on the maximum entropy model,a species distribution model was established using selected species distribution data and environmental variable data.The geographic detector and the interaction detector were applied to quantify the factors affecting the spatial differentiation of the suitable area.By overlaying the suitable area with land cover types,the distribution characteristics of potential arable land and forest land within the potential suitable area were quantified.Results Under the current climatic conditions,altitude,precipitation in July,precipitation during the warmest season,water vapor pressure in June,precipitation in December,and the highest temperature in February are the key environmental factors affecting the distribution of Sinopodophyllum hexandrum.Under the current climatic conditions,the potential geographical distribution range of Sinopodophyllum hexandrum covers an area of 1.30×106 km2.Considering land cover types,the actual suitable area for Sinopodophyllum hexandrum is 6.13×105 km2,including 4.25×105 km2 of forest land and 1.88×105 km2 of arable land.The highly suitable forest areas are mainly distributed in the Aba Tibetan and Qiang Autonomous Prefecture,Ganzi Tibetan Autonomous Prefecture of Sichuan Province,Diqing Tibetan Autonomous Prefecture,Nujiang Lisu Autonomous Prefecture of Yunnan Province and Linzhi City within the Tibet Autonomous Region.The highly suitable arable land areas are mainly distributed in the Linxia Hui Autonomous Prefecture,Dingxi City,Tianshui City,and Longnan City of Gansu Province,with sporadic belt-like distributions in Sichuan Province,Yunnan Province and the Tibet Autonomous Region.Conclusion The study can provide evidence for the protection of wild Sinopodophyllum hexandrum resources and the selection of optimal planting areas.

Objective To investigate the geographical distribution patterns and influencing factors of suitable habitats for the desert medicinal plant Cynomorium songaricum Rupr under current climatic conditions;To provide a basis for its resource conservation and sustainable utilization.Methods The MaxEnt model was used to analyze potential suitable habitats for Cynomorium songaricum Rupr.Geographical Detector model was used to identify key environmental factors affecting habitat suitability.Surface cover data were overlaid to assess the distribution of sandy and Gobi regions within suitable habitats,enabling a quantitative evaluation of actual potential suitable areas.Results Model predictions indicated a total suitable habitat area of approximately 2.98×106 km2,representing 30.99%of China's mainland area.Highly suitable habitats are concentrated in desert and Gobi regions of Gansu,Xinjiang,Inner Mongolia,Qinghai and Ningxia.Among climatic factors,precipitation of the coldest quarter(bio19),solar radiation in August(srad8),and mean temperature of the coldest quarter(bio11)significantly influence Cynomorium songaricum Rupr distribution.The interaction between temperature and solar radiation intensity exhibited the highest explanatory power for habitat distribution patterns(q=0.82).Overlay analysis with surface cover data estimated the actual potential suitable area at approximately 9.70×105 km2,with sandy regions comprising 5.73×105 km2 and Gobi regions 3.98×105 km2.Conclusion By integrating multi-source data and modeling approaches,this study delineates the potential suitable habitats for Cynomorium songaricum Rupr across China and evaluates the spatial distribution characteristics and influencing factors of suitable habitats in Cynomorium songaricum Rupr.These findings offer a foundation for conserving wild Cynomorium songaricum Rupr resources,optimizing ecological planting regions,and promoting sustainable industry development.

Objective:To explore the predictive value of changes in prealbumin for the prognosis of patients with hepatitis B virus-associated acute-on-chronic liver failure (HBV-ACLF) after artificial liver treatment.Methods:From January 1, 2018 to December 31, 2021, the clinical data (including prealbumin, platelet count, lymphocyte count, alanine transaminase (ALT), etc.) of 87 patients with HBV-ACLF who received artificial liver treatment at the Department of Gastroenterology of the General Hospital of Western Theater Command PLA were retrospectively collected. The 90-day survival status of all the patients was followed up, and the patients were divided into the survival group and the mortality group according to the survival status. The clinical characteristics and the changes of prealbumin on day 1 to 3, day 3 to 7, and day 1 to 7 after artificial liver treatment were compared between the 2 groups. Multivariate logistic regression analysis was used to analyze the independent influencing factors of the 90-day prognosis of HBV-ACLF patients after artificial liver treatment, and the nomogram prediction model was established and the receiver operating characteristic curve (ROC) was drawn to assess the area under the curve (AUC). Hosmer-Lemeshow goodness-of-fit test, calibration curve and clinical decision curve were performed to evaluate the goodness of fit, consistency and clinical value of the prediction model. Paired t-test and Mann-Whitney U test were used for statistical analysis. Results:There were 69 cases enrolled into the survival group, and 18 cases enrolled into the mortality group. The levels of albumin, prealbumin, platelet count, lymphocyte count, and ALT before treatment, and the level of prealbumin at the 3rd day after treatment of the survival group were all higher than those of the mortality group (32.5 (30.6, 35.2) g/L vs. 29.4 (27.6, 32.3) g/L, 66.0 (52.5, 81.5) mg/L vs. 56.5 (39.2, 65.0) mg/L, 103.0 (72.5, 145.0)×10 9/L vs. 63.5 (40.0, 92.5)×10 9/L, 1.1 (0.8, 1.4)×10 9/L vs. 0.9 (0.5, 1.1)×10 9/L, (514.7±86.4) U/L vs. (328.2±93.4) U/L, 90.0 (69.5, 102.5) mg/L vs.68.5(60.0, 75.8) mg/L), and the age, the level of total bilirubin, international normalized ratio, and prothrombin time before treatment of the survival group were all lower than those of the mortality group (48.0 (42.0, 57.0) years old vs. 48.5 (47.0, 56.0) years old, 323.9 (261.2, 409.2) μmol/L vs. 452.2 (405.8, 510.8) μmol/L, 1.5 (1.3, 1.9) vs. 1.9 (1.4, 2.1), 17.3 (14.6, 20.8) s vs. 21.4 (16.6, 23.2) s), and the differences were statistically significant ( Z=-3.38, -2.87, -2.38 and -2.01, t=2.39, Z=-4.11, 3.00, 3.64, 2.18 and 2.37; all P<0.05). The change of prealbumin on day 1 to 3 after treatment in the mortality group was greater than that in the survival group (-0.182 (-0.321, -0.026) vs. -0.043 (-0.133, 0.093)), and the difference was statistically significant ( Z=-3.42, P=0.001). The results of multivariate logistic regression analysis showed that the age, total bilirubin before treatment, and the change of prealbumin on day 1 to 3 after treatment were independent influencing factors for the 90-day prognosis in HBV-ACLF patients after artificial liver treatment (all P<0.05), and the nomogram model was established based on the above 3 factors. The results of ROC analysis showed that the AUC of the prediction model was 0.933 (95% confidence interval: 0.866 to 1.000, P<0.001), with a sensitivity of 0.933 and a specificity of 0.825. The results of the Hosmer-Lemeshow goodness-of-fit test showed that the prediction model had a good fit( P=0.700). The results of calibration curve analysis indicated that the actual curve of the prediction model was close to the calibration curve, with an average absolute error of 0.034, the consistency between the predicted probability and the actual probability was good. The clinical decision curve analysis suggested that the prediction model had significant clinical benefits. Conclusions:The changes of prealbumin after artificial liver treatment in HBV-ACLF patients can reflect the recovery of liver function. The nomogram prediction model based on the change of prealbumin on day 1 to 3 after treatment, age, and total bilirubin before treatment can better predict the 90-day prognosis of HBV-ACLF patients after artificial liver treatment.

Ardisia Crenata Radix is a traditional Chinese medicinal plant that belongs to the Myrsinaceae family,and its main active components are coumarins,saponins,flavonoids,and volatile oil.Bergenin,ardisicrenoside A,ardisicrenoside B,ardisiacripin A,ardisiacripin B,and embelin were identified as active anticancer compounds in in-depth studies into the anti-tumor effects of Ardisia Crenata Radix.They show high therapeutic potential in oral cancer,nasopharyngeal carcinoma,liver cancer,colon cancer,bladder cancer,cervical cancer,and leukemia,mainly by inducing tumor cell apoptosis,increasing tumor cytotoxicity,inhibiting cell proliferation,inhibiting tumor cell metastasis and migration,and inducing cell regulatory enzyme cascade reactions.However,most preclinical experimental data on cinnabar root's anti-tumor mechanism have not been verified in high-quality,multi-sample,and repeated randomized controlled trials,and there are a lack of clinical research data on tumor prognosis,pharmacodynamics,and pharmacokinetics.Accurate research experiments and clinical trials should be designed to further explore the pharmacological effects of Ardisia Crenata Radix.

Objective To establish the rapid identification method of Hedysari Radix wild and cultivated products by integrating the identification characteristics of TCM traits obtained by intelligent senses such as electronic nose and colorimeter based on the multivariate statistical analysis method;To provide new ideas and methods for the formulation of commodity specification standards and the application research of market quality control for Hedysari Radix.Methods Totally 29 batches of samples of Hedysari Radix were detected based on colorimeter and electronic nose technology to obtain their sensory information,and the effective components of Hedysari Radix were determined by high performance liquid chromatography(HPLC)and other methods for joint analysis.After establishing the optimal experimental conditions of Hedysari Radix electronic nose,multivariate statistical analysis methods,such as principal component analysis(PCA),orthogonal partial least squares-discriminant analysis(OPLS-DA)and clustering analysis,were used to establish the identification model of Hedysari Radix wild and cultivated commodities.Results The optimum test conditions of Hedysari Radix electronic nose(particle size of 65 mesh):the sample weight was 2.0 g,the optimum temperature of the sample was 50℃,and the time was 25 min.A single intelligent sensory result could not quickly and accurately identify the two,but the fusion information could quickly identify the wild and cultivated commodities of Hedysari Radix,and the chemical composition had a certain correlation with the color and taste.Conclusion Electronic nose and colorimeter can quickly and accurately distinguish wild and cultivated Hedysari Radix after multivariate statistical analysis,which is simple and feasible.The combined analysis of its related properties and active components can be used for the quality evaluation of Hedysari Radix.

Objective:To analyze the correlation between sleep midpoint and sleep quality in insomnia patients with type 2 diabetes mellitus (T2DM).Methods:By adopting current situation investigation research, total of 150 T2DM patients hospitalized in the Department of Endocrinology, the First Affiliated Hospital of Guizhou University of Traditional Chinese Medicine from November 2021 to July 2022 were selected as the research objects. The general information questionnaire, Pittsburgh Sleep Quality Index (PSQI), anxiety scale (SAS) and Depression Scale (SDS) were used to investigate, and then analysis the datum.Results:Among 150 T2DM insomnia patients, 41 cases (27.33%) were in the early midpoint sleep group, 37 cases (24.67%) were in the middle midpoint sleep group, and 72 cases (48.00%) were in the late midpoint sleep group. There were significant differences in the distribution of sex, age and BMI level among different sleep midpoint groups ( χ2=7.24, 13.36, 15.93, all P<0.05). The scores of time to fall asleep at the midpoint of sleep in the 3 groups were (2.12 ± 1.25), (2.65 ± 0.79), (2.33 ± 1.02), the difference was significant ( F=2.14, P<0.05); the daytime disability scores in the 3 groups were (1.39 ± 1.36), (2.16 ± 1.12), (1.85 ± 1.32), the difference was significant ( F=3.17, P<0.05). Logistic regression analysis of disorder showed that the time to fall asleep ( OR=4.922, P<0.05) and daytime disability ( OR=4.043, P<0.05) had significant influence to the middle midpoint of sleep group when the early midpoint of sleep group as the control, while the male ( OR=2.182, P<0.05), 50 - 70 years old ( OR=5.005, P<0.05) and BMI over fat side ( OR=3.488, P<0.05) had significant influence to the late midpoint of sleep group. Conclusions:Medical staff should pay attention to the sleep quality of T2DM patients, pay attention to the sleep midpoint of patients, and improve patients′cognition of healthy sleep patterns.

Medulloblastoma (MB) is a common yet highly heterogeneous childhood malignant brain tumor, however, clinically effective molecular targeted therapy is lacking. Modulation of hedgehog (HH) signaling by epigenetically targeting the transcriptional factors GLI through bromodomain-containing protein 4 (BRD4) has recently spurred new interest as potential treatment of HH-driven MB. Through screening of current clinical BRD4 inhibitors for their inhibitory potency against glioma-associated oncogene homolog (GLI) protein, the BRD4 inhibitor