ObjectiveTo investigate the clinical features of tumor-induced acute pancreatitis （TIAP）， to construct and validate a predictive model for TIAP， and to provide help for early identification in clinical practice. MethodsA retrospective analysis was performed for the clinical data of 3 051 patients with acute pancreatitis （AP） who were admitted to The First Affiliated Hospital of Xinjiang Medical University from January 2020 to January 2026， among whom there were 72 patients with TIAP. To reduce class imbalance， 216 patients with non-tumor-related AP （2 979 patients） were randomly selected as conventional group using sex-stratified sampling， resulting in a cohort of 288 patients， and this cohort was randomly divided into a training set with 201 patients and a test set with 87 patients at a ratio of 7∶3. The two groups were compared in terms of general information and laboratory markers. The independent-samples t test was used for comparison of normally distributed continuous data between two groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups； the chi-square test was used for comparison of categorical data between two groups. Recursive feature elimination and least absolute shrinkage and selection operator regression were used for screening of characteristic variables， and five machine learning models were constructed， i.e.， logistic regression model， random forest model， support vector machine model， extreme gradient boosting model， and light gradient boosting machine model. The receiver operating characteristic curve and the precision-recall curve were used to assess model performance； the calibration curve was used to assess goodness of fit； decision curve analysis was used to evaluate clinical applicability and practicality； Shapley additive explanations were used to assess model interpretability. ResultsIn the training set of 201 patients， there were 52 patients （25.9%） in the TIAP group， and in the test set of 87 patients， there were 20 patients （23.0%） in the TIAP group. Compared with the conventional group， the TIAP group had a significantly higher proportion of patients with pancreatic duct dilatation （χ²=79.474， P<0.05）， a significantly higher age （Z=-5.838， P<0.05）， and significantly lower levels of white blood cell count （Z=5.630， P<0.05）， amylase （Z=2.606， P<0.05）， hemoglobin （Z=5.038， P<0.05）， and neutrophil percentage （Z=5.269， P<0.05）， as well as a lower level of direct bilirubin （Z=0.936， P>0.05）. The five machine learning models constructed based on these seven variables had a certain predictive ability， among which the logistic regression model had the best performance in the test set， with an area under the curve of 0.893 （95% confidence interval： 0.821 — 0.953）， an average precision of 0.654 in the precision-recall curve， good calibration， and good clinical benefits based on the decision curve analysis. ConclusionThe predictive model for TIAP based on pancreatic duct dilatation， age， white blood cell count， amylase， hemoglobin， neutrophil percentage， and direct bilirubin shows good predictive performance and can provide important guidance for the early diagnosis of TIAP.

ObjectiveTo study the effects of applying different microbial fertilizers on the growth and rhizosphere soil environment of Codonopsis pilosula and provide a theoretical basis for ecological cultivation of this medicinal plant. MethodsSeven groups were designed， including CK （no application of microbial fertilizer）， T1 （Trichoderma longibrachiatum fertilizer）， T2 （Bacillus subtilis fertilizer）， T3 （Trichoderma viride fertilizer）， T4 （compound microbial fertilizer）， T5 （C. pilosula stems and leaves fermented with compound microbial fertilizer）， and T6 （Scutellaria baicalensis stems and leaves fermented with T. viride fertilizer）. The physiological indicators， yield， and quality of C. pilosula and the physicochemical properties， enzyme activities， and microbial diversity in the rhizosphere soil of different fertilizer treatments were measured. ResultsGroup T1 showed slight decreases in soluble protein content （SPC） and superoxide dismutase （SOD）. Groups T2-T6 showed increases in physiological indicators such as proline （Pro）， soluble solids content （SSC）， SPC， catalase （CAT）， and peroxidase （POD） and a decrease in malondialdehyde （MDA） in C. pilosula leaves. All the fertilizer treatments increased the yield of C. pilosula and the total polysaccharide content in the roots. T1， T2， T3， T4， and T5 increased the total flavonoid content in the roots. Meanwhile， T4 increased the total saponin content in the roots. All the fertilizer treatments reduced the pH and increased the electric conductivity （EC）， soil organic matter （SOM）， and alkaline nitrogen （AN） in the soil. T2 and T5 increased the available phosphorus （AP）， and T3， T4， T5， and T6 increased the available potassium （AK） in the soil. All the fertilizer treatments increased the activities of urease， sucrase， and CAT in the soil. Except that T1 decreased the bacterial diversity in the soil， other fertilizer treatments significantly increased bacterial and fungal diversity in the soil. Different fertilizer treatments significantly affected the composition of bacterial and fungal communities in the soil. At the phylum level， the dominant bacterial phyla included Proteobacteria， Acidobacteriota， and Bacteroideta， and the dominant fungal phyla were Ascomycota， Mortierellomycota， and unclassified_fungi in the rhizosphere soil of C. pilosula after bacterial fertilizer treatment. At the genus level， unclassified Gemmatimonadaceae， Sphingomonas， and unclassified Vicinamibacteraceae were the dominant bacterial genera， while unidentified， unclassified Fungi， and unclassified Sordariomycetes were the dominant fungal genera in the rhizosphere soil. The results of redundancy analysis indicated that the main physicochemical factors affecting changes of microbial communities in the rhizosphere soil of C. pilosula were pH， EC， AK， AN， AP， and soil organic matter （SOM） in the soil. The correlation heatmap showed that Bryobacter had significantly positive correlations with EC， AK， and AN. There was a significantly negative correlation between Fusarium and SOM. In summary， applying an appropriate amount of microbial fertilizer can promote the growth and improve the rhizosphere soil environment of C. pilosula. ConclusionThe compound microbial fertilizer and the C. pilosula stems and leaves fermented with compound microbial fertilizer can improve the soil nutrients， growth， development， yield， and quality of C. pilosula， and thus they can be applied to the artificial cultivation of C. pilosula.

ObjectiveTo study the effects of applying different microbial fertilizers on the growth and rhizosphere soil environment of Codonopsis pilosula and provide a theoretical basis for ecological cultivation of this medicinal plant. MethodsSeven groups were designed， including CK （no application of microbial fertilizer）， T1 （Trichoderma longibrachiatum fertilizer）， T2 （Bacillus subtilis fertilizer）， T3 （Trichoderma viride fertilizer）， T4 （compound microbial fertilizer）， T5 （C. pilosula stems and leaves fermented with compound microbial fertilizer）， and T6 （Scutellaria baicalensis stems and leaves fermented with T. viride fertilizer）. The physiological indicators， yield， and quality of C. pilosula and the physicochemical properties， enzyme activities， and microbial diversity in the rhizosphere soil of different fertilizer treatments were measured. ResultsGroup T1 showed slight decreases in soluble protein content （SPC） and superoxide dismutase （SOD）. Groups T2-T6 showed increases in physiological indicators such as proline （Pro）， soluble solids content （SSC）， SPC， catalase （CAT）， and peroxidase （POD） and a decrease in malondialdehyde （MDA） in C. pilosula leaves. All the fertilizer treatments increased the yield of C. pilosula and the total polysaccharide content in the roots. T1， T2， T3， T4， and T5 increased the total flavonoid content in the roots. Meanwhile， T4 increased the total saponin content in the roots. All the fertilizer treatments reduced the pH and increased the electric conductivity （EC）， soil organic matter （SOM）， and alkaline nitrogen （AN） in the soil. T2 and T5 increased the available phosphorus （AP）， and T3， T4， T5， and T6 increased the available potassium （AK） in the soil. All the fertilizer treatments increased the activities of urease， sucrase， and CAT in the soil. Except that T1 decreased the bacterial diversity in the soil， other fertilizer treatments significantly increased bacterial and fungal diversity in the soil. Different fertilizer treatments significantly affected the composition of bacterial and fungal communities in the soil. At the phylum level， the dominant bacterial phyla included Proteobacteria， Acidobacteriota， and Bacteroideta， and the dominant fungal phyla were Ascomycota， Mortierellomycota， and unclassified_fungi in the rhizosphere soil of C. pilosula after bacterial fertilizer treatment. At the genus level， unclassified Gemmatimonadaceae， Sphingomonas， and unclassified Vicinamibacteraceae were the dominant bacterial genera， while unidentified， unclassified Fungi， and unclassified Sordariomycetes were the dominant fungal genera in the rhizosphere soil. The results of redundancy analysis indicated that the main physicochemical factors affecting changes of microbial communities in the rhizosphere soil of C. pilosula were pH， EC， AK， AN， AP， and soil organic matter （SOM） in the soil. The correlation heatmap showed that Bryobacter had significantly positive correlations with EC， AK， and AN. There was a significantly negative correlation between Fusarium and SOM. In summary， applying an appropriate amount of microbial fertilizer can promote the growth and improve the rhizosphere soil environment of C. pilosula. ConclusionThe compound microbial fertilizer and the C. pilosula stems and leaves fermented with compound microbial fertilizer can improve the soil nutrients， growth， development， yield， and quality of C. pilosula， and thus they can be applied to the artificial cultivation of C. pilosula.

Invasive fungal infections (IFIs) have become prominent global health threats, escalating the burden on public health systems. The increasing occurrence of invasive fungal infections is due primarily to the extensive application of chemotherapy, immunosuppressive therapies, and broad-spectrum antifungal agents. At present, therapeutic practices utilize multiple categories of antifungal agents, such as azoles, polyenes, echinocandins, and pyrimidine analogs. Nevertheless, the clinical effectiveness of these treatments is progressively weakened by the emergence of drug resistance, thereby substantially restricting their therapeutic utility. Consequently, there is an imperative need to expedite the discovery of novel antifungal agents. This review seeks to present an exhaustive synthesis of novel antifungal drugs and candidate agents that are either under current clinical investigation or anticipated to progress into clinical evaluation. These emerging compounds exhibit unique benefits concerning their modes of action, antimicrobial spectra, and pharmacokinetic characteristics, potentially leading to improved therapeutic outcomes relative to conventional antifungal regimens. It is anticipated that these novel therapeutic agents will furnish innovative treatment modalities and enhance clinical outcomes in managing invasive fungal infections.

Objective:To review the application of internet cognitive behavioral therapy (CBT) in perinatal women with negative emotions, point out the limitations of existing studies, and put forward development suggestions for future research.Methods:Using the Scope review guide published by Joanna Briggs Institute as the methodological framework, eight Chinese and English databases including China National Knowledge Infrastructure (CNKI), Wanfang, PubMed and Web of Science were searched until July 1, 2024, and the literatures were collected and analyzed.Results:A total of 18 literatures were included. The interventionists of internet cognitive behavioral therapy were mostly psychologists; the intervention methods were mostly in the form of partial participation of therapists, and the intervention platforms were mostly websites. The intervention content was centered on mental health education, emotional monitoring, cognitive reconstruction, behavioral activation training, and problem solving. There were 15 studies that demonstrated that internet cognitive behavioral therapy was effective, and three studies showed that internet cognitive behavioral therapy was not effective in improving negative emotions in perinatal women, but perinatal women responded to treatment.Conclusions:The Internet cognitive behavioral therapy can effectively improve the negative emotions of perinatal pregnant women, but the long-term effect is not clear. Future studies can expand the sample size and follow up the effect for a long time.

Objective To analyze the ecological suitability of Codonopsis pilosula;To provide theoretical reference for expanding the planting scale of Codonopsis pilosula in Shanxi Province.Methods Information on the distribution of Codonopsis pilosula samples through the fourth survey of TCM resources in Shanxi Province and literature review;the MaxEnt model and ArcGIS 10.8 geographic information system software were used to analyze the ecological factors affecting the distribution of Codonopsis Radix in Shanxi Province,and the suitable distribution areas of Codonopsis pilosula in Shanxi Province were predicted.Results The predicted distribution areas of Codonopsis pilosula in Shanxi Province by the model were highly consistent with the actual distribution area;the AUC of the training set was 0.945,indicating good prediction results.The predominant ecological factors(contributing)impacting the distribution of Codonopsis pilosula included vegetation type(31.1%),the standard deviation of seasonal temperature fluctuations(25.0%),slope(8.3%),mean January precipitation(5.3%),mean May precipitation(5.0%),and elevation(4.9%)etc.The optimal vegetation types conducive to the proliferation of Codonopsis pilosula were identified as temperate deciduous shrubs,temperate grasslands,temperate coniferous forests,and temperate deciduous broad-leaved forests.The standard deviation of seasonal temperature change was within the range of 92 to 108,the slope gradient was from 14° to 30°,mean January precipitation was of 4 to 6.8 mm,mean May precipitation was of 33.5 to 58 mm,and elevation ranged from 1 100 to 2 800 meters.Codonopsis pilosula was mainly distributed in Lucheng,Qinxian and Qinyuan counties in the eastern part of Taiyue Mountain in Changzhi City;Pu County,Fenxi County,Fenyang City of Lyuliang City in the Lyuliang Mountain Range and Yushe County of Jinzhong City in the northern part of Taiyue Mountain.The most suitable area in Shanxi Province was 14 109.67 km2,the suitable area encompassed 22 837.62 km2,the relatively suitable area covered 41 982.96 km2,while the unsuitable area extended over 77 769.75 km2.Conclusion The geographical distribution data of Codonopsis pilosula resources in Shanxi Province may serve as a basis for further examination of regional zoning,with the establishment of wild cultivation bases for Codonopsis pilosula in proximity to various mountain ranges,such as the Taihang Mountains.Moreover,the artificial cultivation conditions can be modified in accordance with the optimal growth environment of Codonopsis pilosula,thereby optimizing the management of Codonopsis resources.

Objective To analyze the ecological suitability of Codonopsis pilosula;To provide theoretical reference for expanding the planting scale of Codonopsis pilosula in Shanxi Province.Methods Information on the distribution of Codonopsis pilosula samples through the fourth survey of TCM resources in Shanxi Province and literature review;the MaxEnt model and ArcGIS 10.8 geographic information system software were used to analyze the ecological factors affecting the distribution of Codonopsis Radix in Shanxi Province,and the suitable distribution areas of Codonopsis pilosula in Shanxi Province were predicted.Results The predicted distribution areas of Codonopsis pilosula in Shanxi Province by the model were highly consistent with the actual distribution area;the AUC of the training set was 0.945,indicating good prediction results.The predominant ecological factors(contributing)impacting the distribution of Codonopsis pilosula included vegetation type(31.1%),the standard deviation of seasonal temperature fluctuations(25.0%),slope(8.3%),mean January precipitation(5.3%),mean May precipitation(5.0%),and elevation(4.9%)etc.The optimal vegetation types conducive to the proliferation of Codonopsis pilosula were identified as temperate deciduous shrubs,temperate grasslands,temperate coniferous forests,and temperate deciduous broad-leaved forests.The standard deviation of seasonal temperature change was within the range of 92 to 108,the slope gradient was from 14° to 30°,mean January precipitation was of 4 to 6.8 mm,mean May precipitation was of 33.5 to 58 mm,and elevation ranged from 1 100 to 2 800 meters.Codonopsis pilosula was mainly distributed in Lucheng,Qinxian and Qinyuan counties in the eastern part of Taiyue Mountain in Changzhi City;Pu County,Fenxi County,Fenyang City of Lyuliang City in the Lyuliang Mountain Range and Yushe County of Jinzhong City in the northern part of Taiyue Mountain.The most suitable area in Shanxi Province was 14 109.67 km2,the suitable area encompassed 22 837.62 km2,the relatively suitable area covered 41 982.96 km2,while the unsuitable area extended over 77 769.75 km2.Conclusion The geographical distribution data of Codonopsis pilosula resources in Shanxi Province may serve as a basis for further examination of regional zoning,with the establishment of wild cultivation bases for Codonopsis pilosula in proximity to various mountain ranges,such as the Taihang Mountains.Moreover,the artificial cultivation conditions can be modified in accordance with the optimal growth environment of Codonopsis pilosula,thereby optimizing the management of Codonopsis resources.

Objective:To review the application of internet cognitive behavioral therapy (CBT) in perinatal women with negative emotions, point out the limitations of existing studies, and put forward development suggestions for future research.Methods:Using the Scope review guide published by Joanna Briggs Institute as the methodological framework, eight Chinese and English databases including China National Knowledge Infrastructure (CNKI), Wanfang, PubMed and Web of Science were searched until July 1, 2024, and the literatures were collected and analyzed.Results:A total of 18 literatures were included. The interventionists of internet cognitive behavioral therapy were mostly psychologists; the intervention methods were mostly in the form of partial participation of therapists, and the intervention platforms were mostly websites. The intervention content was centered on mental health education, emotional monitoring, cognitive reconstruction, behavioral activation training, and problem solving. There were 15 studies that demonstrated that internet cognitive behavioral therapy was effective, and three studies showed that internet cognitive behavioral therapy was not effective in improving negative emotions in perinatal women, but perinatal women responded to treatment.Conclusions:The Internet cognitive behavioral therapy can effectively improve the negative emotions of perinatal pregnant women, but the long-term effect is not clear. Future studies can expand the sample size and follow up the effect for a long time.

Objective To establish the distribution zoning of Ziziphus jujuba var.spinosa in Shanxi Province;To help the development of Z.jujuba var.spinosa industry in Shanxi Province.Methods Combined with the information of longitude and latitude of sample points from the forth national survey resources and environment factors data in Grid Database of Spatial Information of TCM Resources,the MaxEnt model and ArcGIS were applied to analyze the main environmental factors affecting the suitability distribution of Z.jujuba var.spinosa.Results Dominant ecological factors for the suitability distribution of Z.Jujuba var.spinosa were vegetation type,lowest temperature of coldest month,monthly precipitation in November,monthly precipitation in October,altitude,and slope.The reclassified suitability grid data of ArcGIS software showed that Z.jujuba var.spinosa suitability distribution area including 0.73×104 km2 of high suitability area,1.41×104 km2 of medium suitability area and 4.33×104 km2 of low suitability area.The potential suitable distribution areas of Z.jujuba var.spinosa were mainly concentrated in the central and southern Shanxi Province.Conclusion This study shows that the most suitable growth area of Z.jujuba var.spinosa is mainly located in central and southern Shanxi Province,which can provide reference for the development,utilization and standardized planting of wild resources of Z.jujuba var.spinosa.

Objective To grasp the main environmental factors affecting the growth of Astragalus membranaceus(Fisch.)Bge.var.mongholicus(Bge.)Hsiao;To predict the distribution of suitable areas of Astragalus membranaceus(Fisch.)Bge.var.mongholicus(Bge.)Hsiao in Shanxi Province;To provide references for the rational distribution of the resources in Shanxi Province.Methods This study utilized the sample point longitude and latitude information collected in the"Fourth Survey of Chinese Materia Medica Resources"database in Shanxi Province.The data were supplemented by searching the China Digital Herbarium and retrieving related literature records.347 sample points distribution data and environmental factors were added to the MaxEnt model.The main environmental factors and contribution rates affecting the geographical distribution of Astragalus membranaceus(Fisch.)Bge.var.mongholicus(Bge.)Hsiao were screened out.The ArcGIS software was used to divide the ecological suitable area of Astragalus membranaceus(Fisch.)Bge.var.mongholicus(Bge.)Hsiao in Shanxi Province.Results The area under the ROC curve of the established MaxEnt model was 0.909,indicating that the model prediction results were accurate.The model screened 19 environmental factors.Among them,climate factor was the most important environmental factor,followed by biological factor and topographic factor,and soil factor had the least influence.The potential suitable areas of Astragalus membranaceus(Fisch.)Bge.var.mongholicus(Bge.)Hsiao in Shanxi Province were mainly distributed in the northern mountainous areas,presenting a trend of gradually decreasing suitability levels from north to south.Under the current climate conditions,the most suitable area for Astragalus membranaceus(Fisch.)Bge.var.mongholicus(Bge.)Hsiao in Shanxi Province was 15 424 km2,the suitable area was 19 856 km2,the sub suitable area was 59 436 km2,and the unsuitable area was 61 894 km2.Conclusion Based on MaxEnt model and ArcGIS software,this study predicts the distribution of suitable areas of Astragalus membranaceus(Fisch.)Bge.var.mongholicus(Bge.)Hsiao in Shanxi Province,which has certain reference value for the protection and rational distribution of Astragalus membranaceus(Fisch.)Bge.var.mongholicus(Bge.)Hsiao resources in Shanxi Province.