Objective Objective To analyze the potential spatial factors affecting the genetic differentiation of Oncomelania hupensis robertsoni in Yunnan Province. Methods A total of 13 administrative villages were selected from schistosomiasis-endemic areas of Yunnan Province as O. hupensis snail sampling sites. At least 200 snails were collected in each site, and the spatial variable data of each site were recorded, including longitude, latitude and altitude. Thirty active and Schistosoma japonicum uninfected O. hupensis snails were selected from each sampling site by means of the crawling method and the cercarial shedding method. Genomic DNA was extracted from O. hupensis snails. Following PCR amplification, purification of PCR amplification products and sequencing, the gene sequences of O. hupensis snail samples were spliced and edited using the DNAstar software and the NCBI database to yield the complete mitochondrial sequences of O. hupensis snails at each sampling site, and the mitochondrial genetic distance matrix of O. hupensis robertsoni was calculated at each sampling site. The geographical coordinates of each sampling site were marked using the software ArcGIS 10.2, and the straight-line geographical distance between each sampling site was calculated. The altitude difference, longitude difference and latitude difference between each sampling site were calculated using the Excel software, and the correlation between the mitochondrial genetic distance matrix of O. hupensis robertsoni and each spatial variable matrix was examined by using the Mantel test at 13 sampling sites in Yunnan Province. Results Among the 13 O. hupensis snail sampling sites in Yunnan Province, the largest mitochondrial genetic distance of O. hupensis robertsoni snail populations was seen between Anding Village, Nanjian Yi Autonomous County and Caizhuang Village, Midu County (26.244 2), and the largest geographical distance was seen between Dongyuan Village, Gucheng District and Cangling Village, Chuxiong County (272.64 km). The highest altitude difference was seen between Anding Village, Nanjian Yi Autonomous County and Dongyuan Village, Gucheng District (1 086.10 m), and the largest longitude difference was found between Qiandian Village, Eryuan County and Cangling Village, Chuxiong County (1.86°), while the largest latitude difference was measured between Leqiu Village, Nanjian Yi Autonomous County and Dongyuan Village, Gucheng District (1.81°). In addition, the mitochondrial genetic distance of O. hupensis robertsoni snail populations was positively correlated with altitude at 13 snail sampling sites in Yunnan Province (r = 0.542 8, P < 0.001), and showed no significant correlations with geographical distance (r = 0.093 4, P > 0.05), longitude (r = −0.199 5, P > 0.05) or latitude (r = 0.205 7, P > 0.05). Conclusion Altitude may be a potential spatial factor affecting the genetic differentiation of O. hupensis robertsoni in Yunnan Province.

ObjectiveTo establish a geographical origin identification model for Foeniculi Fructus from Haiyuan， providing a new technical reference for the protection of Haiyuan's geo-authentic medicinal materials and its designation as a national geographical indication agricultural product. MethodsSamples of Foeniculi Fructus were collected from eight producing areas， including Minqin （Gansu）， Bozhou （Anhui）， Qingdao （Shandong）， Dezhou （Shandong）， Urumqi （Xinjiang）， Nujiang （Yunnan）， Gutuo （Inner Mongolia）， and Haiyuan （Ningxia）. Gas chromatography-ion mobility spectrometry （GC-IMS） was used to detect the volatile organic compounds （VOCs） in samples from these geographic origins. VOCs were qualitatively analyzed through dual matching with the National Institute of Standards and Technology （NIST） mass spectral database and the IMS drift time database. Using the Reporter module and Gallery Plot visualization tools within the LAV analytical platform， VOC fingerprint profiles characterizing geographic origins were constructed. A non-targeted analytical strategy was adopted， and 97 VOCs detected via GC-IMS were subjected to principal component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） based on their differential distribution patterns to construct an origin identification model for Foeniculi Fructus from Haiyuan region. Key discriminative markers were screened using variable importance in projection （VIP） values greater than 1. ResultsA total of 97 VOCs were identified， including alcohols， aldehydes， ketones， esters， organic acids， terpenoids， ethers， alkenes， and benzenes. The PLS-DA model， based on VOCs data obtained by GC-IMS， effectively distinguished Foeniculi Fructus in Haiyuan region from those of other origins. During cross-validation， the model achieved a prediction parameter （Q²） of 0.976 and a goodness-of-fit parameter （R²） of 0.936， with no overfitting observed in permutation testing. Twelve key flavor markers with VIP > 1 were identified as characteristic indicators of Haiyuan origin. ConclusionA stable and highly predictive origin identification model for Foeniculi Fructus from Haiyuan was successfully established using GC-IMS technology， PLS-DA， and VIP-based marker screening. This model provides a novel technical strategy for accurately distinguishing Foeniculi Fructus in Haiyuan region from other regional varieties and offers new technical support for its protection as a geo-authentic medicinal material and a nationally designated geographical indication agricultural product in China.

ObjectiveTo establish a geographical origin identification model for Foeniculi Fructus from Haiyuan， providing a new technical reference for the protection of Haiyuan's geo-authentic medicinal materials and its designation as a national geographical indication agricultural product. MethodsSamples of Foeniculi Fructus were collected from eight producing areas， including Minqin （Gansu）， Bozhou （Anhui）， Qingdao （Shandong）， Dezhou （Shandong）， Urumqi （Xinjiang）， Nujiang （Yunnan）， Gutuo （Inner Mongolia）， and Haiyuan （Ningxia）. Gas chromatography-ion mobility spectrometry （GC-IMS） was used to detect the volatile organic compounds （VOCs） in samples from these geographic origins. VOCs were qualitatively analyzed through dual matching with the National Institute of Standards and Technology （NIST） mass spectral database and the IMS drift time database. Using the Reporter module and Gallery Plot visualization tools within the LAV analytical platform， VOC fingerprint profiles characterizing geographic origins were constructed. A non-targeted analytical strategy was adopted， and 97 VOCs detected via GC-IMS were subjected to principal component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） based on their differential distribution patterns to construct an origin identification model for Foeniculi Fructus from Haiyuan region. Key discriminative markers were screened using variable importance in projection （VIP） values greater than 1. ResultsA total of 97 VOCs were identified， including alcohols， aldehydes， ketones， esters， organic acids， terpenoids， ethers， alkenes， and benzenes. The PLS-DA model， based on VOCs data obtained by GC-IMS， effectively distinguished Foeniculi Fructus in Haiyuan region from those of other origins. During cross-validation， the model achieved a prediction parameter （Q²） of 0.976 and a goodness-of-fit parameter （R²） of 0.936， with no overfitting observed in permutation testing. Twelve key flavor markers with VIP > 1 were identified as characteristic indicators of Haiyuan origin. ConclusionA stable and highly predictive origin identification model for Foeniculi Fructus from Haiyuan was successfully established using GC-IMS technology， PLS-DA， and VIP-based marker screening. This model provides a novel technical strategy for accurately distinguishing Foeniculi Fructus in Haiyuan region from other regional varieties and offers new technical support for its protection as a geo-authentic medicinal material and a nationally designated geographical indication agricultural product in China.

Lymphoma has become one of the fastest growing haematological tumour, and effective self-management is an important means for patients to reduce symptom burden and improve quality of life. This article reviews the concept and development of self-management in lymphoma patients, the current status of self-management, influencing factors and intervention models, and proposes recommendations for self-management interventions, with the aim of providing a reference for conducting related research.

Lymphoma has become one of the fastest growing haematological tumour, and effective self-management is an important means for patients to reduce symptom burden and improve quality of life. This article reviews the concept and development of self-management in lymphoma patients, the current status of self-management, influencing factors and intervention models, and proposes recommendations for self-management interventions, with the aim of providing a reference for conducting related research.

Objective To review the research on the application of clinical decision support system(CDSS)involving nurses in depression both domestically and internationally.Methods 10 Chinese and English databases including PubMed,Web of Science,Scopus,CINAHL,PsycINFO,Embase,Cochrane Library,CNKI,Wanfang Database,and VIP were searched until March,2024.The eligible literature of the application of CDSS involving nurses in depression was selected to analyze the basic characteristics of studies,the functions,characteristics,feasibility,and effectiveness of CDSS.Results Finally,16 English articles involving 13 CDSS were included.This study found that nurses participating in CDSS can improve the degree of depression in patients,but its application in depression management is mainly for screening,and few CDSS can propose personalized depression management programs based on the psychological and social factors of patients.Conclusion The CDSS involving nurses can promote the screening of depression and improve depression in patients,but it fails to propose a personalized depression management program.Future research can develop CDSS based on electronic medical record systems to facilitate nurses'screening for depression and further develop an intelligent management module for CDSS to provide intelligent and personalized management solutions for patients with depression.

Objective To investigate the capability for distinguishing between the morphology of Oncomelania hupensis and Tricula snails and its influencing factors among schistosomiasis control professionals in Yunnan Province, so as to evaluate the interference of Tricula snails with O. hupensis surveys. Methods O. hupensis and Tricula snails were sampled from 9 schistosomiasis-endemic counties (districts) in Yunnan Province. The capability for distinguishing between O. hupensis and Tricula snails was evaluated using online questionnaire surveys and field blind tests among schistosomiasis control professionals, and the proportions of correct judgment, misjudgment and missed judgment were calculated. Univariate and multivariate logistic regression models were created using the software SPSS 25.0, and factors affecting the proportion of correct judgments of O. hupensis snails were identified among schistosomiasis control professionals. Results Questionnaire surveys and field blind tests showed that the overall proportions of correct judgments of O. hupensis snails were 56.77% (2 305/4 060) and 68.28% (1 556/2 279) among schistosomiasis control professionals in Yunnan Province, respectively. Univariate logistic regression analysis of online questionnaire surveys identified gender [odds ratio (OR) = 1.244, 95% confidential interval (CI): (1.073, 1.441), P < 0.05], professional title [OR = 0.628, 1.741, 95% CI: (0.453, 0.871), (1.109, 2.734), both P < 0.05], working duration [OR = 0.979, 95% CI: (0.971, 0.987), P < 0.05] and classification of schistosomiasis epidemics in endemic foci [OR = 1.410, 0.293, 0.523, 95% CI: (1.103, 1.804), (0.237, 0.361), (0.416, 0.657), all P < 0.05] as factors affecting the proportion of correct judgments of O. hupensis snails among schistosomiasis control professionals in Yunnan Province, and multivariate logistic regression analysis after adjustments showed that the proportion of O. hupensis snail misjudgments was 1.179 times higher among male schistosomiasis control professionals than among females [OR = 1.179, 95% CI: (1.006, 1.382), P < 0.05], and 1.474 times higher among schistosomiasis control professionals in schistosomiasis-elimination areas with snails than in areas without snails [OR = 1.474, 95% CI: (1.145, 1.898), P < 0.05], and the proportions of missed judgments of O. hupensis snails were 0.284 [OR = 0.284, 95% CI: (0.225, 0.359), P < 0.05] and 0.523 times [OR = 0.523, 95% CI: (0.412, 0.664), P < 0.05] higher among schistosomiasis control professionals in transmission-interruption areas with snails and schistosomiasis-elimination areas with snails than in schistosomiasis-elimination areas without snails. Univariate logistic regression analysis of field blind tests showed age [OR = 2.381, 95% CI: (1.677, 3.381), P < 0.05], professional title [OR = 1.688, 95% CI: (1.103, 2.582), P < 0.05］, working duration [OR = 0.970, 95% CI: (0.956, 0.984), P < 0.05] and classification of schistosomiasis epidemics in endemic foci [OR = 0.262, 0.593, 95% CI: (0.188, 0.364), (0.420, 0.837), both P < 0.05] as factors affecting the proportion of correct judgments of O. hupensis snails among schistosomiasis control professionals in Yunnan Province, and multivariate logistic regression analysis after adjustments showed the proportions of missed judgments of O. hupensis snails were 0.263 [OR = 0.263, 95% CI: (0.176, 0.394), P < 0.05] and 0.604 times [OR = 0.604, 95% CI: (0.416, 0.875), P < 0.05] higher among schistosomiasis control professionals in transmission-interruption areas with snails and schistosomiasis-elimination areas with snails than in schistosomiasis-elimination areas without snails. Conclusions Schistosomiasis control professionals in Yunnan Province have a low accuracy rate for distinguishing between the morphology of O. hupensis and Tricula snails, and gender and classification of schistosomiasis epidemics in endemic foci are factors that affect their ability to distinguish. The presence of Tricula snails causes a high degree of interference with O. hupensis surveys in O. hupensis snail-infested areas of Yunnan Province. Reinforced training for distinguishing between O. hupensis and Tricula snails is required among schistosomiasis control professionals in Yunnan Province.

Objective To predict the potential geographic distribution of Oncomelania hupensis in Yunnan Province using random forest (RF) and maximum entropy (MaxEnt) models, so as to provide insights into O. hupensis surveillance and control in Yunnan Province. Methods The O. hupensis snail survey data in Yunnan Province from 2015 to 2016 were collected and converted into O. hupensis snail distribution site data. Data of 22 environmental variables in Yunnan Province were collected, including twelve climate variables (annual potential evapotranspiration, annual mean ground surface temperature, annual precipitation, annual mean air pressure, annual mean relative humidity, annual sunshine duration, annual mean air temperature, annual mean wind speed, ≥ 0 ℃ annual accumulated temperature, ≥ 10 ℃ annual accumulated temperature, aridity and index of moisture), eight geographical variables (normalized difference vegetation index, landform type, land use type, altitude, soil type, soil textureclay content, soil texture-sand content and soil texture-silt content) and two population and economic variables (gross domestic product and population). Variables were screened with Pearson correlation test and variance inflation factor (VIF) test. The RF and MaxEnt models and the ensemble model were created using the biomod2 package of the software R 4.2.1, and the potential distribution of O. hupensis snails after 2016 was predicted in Yunnan Province. The predictive effects of models were evaluated through cross-validation and independent tests, and the area under the receiver operating characteristic curve (AUC), true skill statistics (TSS) and Kappa statistics were used for model evaluation. In addition, the importance of environmental variables was analyzed, the contribution of environmental variables output by the models with AUC values of > 0.950 and TSS values of > 0.850 were selected for normalization processing, and the importance percentage of environmental variables was obtained to analyze the importance of environmental variables. Results Data of 148 O. hupensis snail distribution sites and 15 environmental variables were included in training sets of RF and MaxEnt models, and both RF and MaxEnt models had high predictive performance, with both mean AUC values of > 0.900 and all mean TSS values and Kappa values of > 0.800, and significant differences in the AUC (t = 19.862, P < 0.05), TSS (t = 10.140, P < 0.05) and Kappa values (t = 10.237, P < 0.05) between two models. The AUC, TSS and Kappa values of the ensemble model were 0.996, 0.954 and 0.920, respectively. Independent data verification showed that the AUC, TSS and Kappa values of the RF model and the ensemble model were all 1, which still showed high performance in unknown data modeling, and the MaxEnt model showed poor performance, with TSS and Kappa values of 0 for 24%(24/100) of the modeling results. The modeling results of 79 RF models, 38 MaxEnt models and their ensemble models with AUC values of > 0.950 and TSS values of > 0.850 were included in the evaluation of importance of environmental variables. The importance of annual sunshine duration (SSD) was 32.989%, 37.847% and 46.315% in the RF model, the MaxEnt model and their ensemble model, while the importance of annual mean relative humidity (RHU) was 30.947%, 15.921% and 28.121%, respectively. Important environment variables were concentrated in modeling results of the RF model, dispersed in modeling results of the MaxEnt model, and most concentrated in modeling results of the ensemble model. The potential distribution of O. hupensis snails after 2016 was predicted to be relatively concentrated in Yunnan Province by the RF model and relatively large by the MaxEnt model, and the distribution of O. hupensis snails predicted by the ensemble model was mostly the joint distribution of O. hupensis snails predicted by RF and MaxEnt models. Conclusions Both RF and MaxEnt models are effective to predict the potential distribution of O. hupensis snails in Yunnan Province, which facilitates targeted O. hupensis snail control.

Objective:To evaluate the effect of melatonin on prefrontal cortex ischemia-induced cognitive impairment in rats and to investigate the receptor mechanism.Methods:Clean-grade adult male Sprague-Dawley rats, weighing 300 g, were selected, and a catheter was implanted into the prefrontal cortex.The experiment was performed in two parts.Experiment Ⅰ Twenty-four rats, in which catheters were successfully inserted into the prefrontal cortex, were assigned into 3 groups ( n=8 each) using a random number table method: control group (group C), model group (group M) and melatonin group (group ME). Normal saline 0.5 μl was injected into the prefrontal cortex in group C, 1 μmol/L endothelin 0.5 μl was microinjected into the prefrontal cortex in group M, and 1 μmol/L endothelin and 1 μmol/L melatonin 0.5 μl were injected into the prefrontal cortex in group ME.Experiment Ⅱ Forty-four rats, in which catheters were successfully inserted into the prefrontal cortex, were assigned into 4 groups ( n=11 each) using a random number table method: model group (group M), melatonin group (group ME), MT 1/2R antagonist luzindole + melatonin group (group L + ME) and MT 2R antagonist 4p-pdot + melatonin group (group P + ME). In group M, 1 μmol/l endothelin 0.5 μl was microinjected into the prefrontal cortex.In group ME, 1 μmol/L endothelin + 1 μmol/L melatonin 0.5 μl was injected into the prefrontal cortex.In group L + ME, 1 μmol/L endothelin + 1 μmol/L MT 1/2R antagonist + 1 μmol/L melatonin 0.5 μl was injected into the prefrontal cortex.In group P + ME, 1 μmol/L endothelin + 1 μmol/L MT 2R antagonist + 1 μmol/L melatonin 0.5 μl was injected into the prefrontal cortex.T-maze and the open field tests were performed at 1 week after administration. Results:Experiment Ⅰ There was no significant difference in the locomotor speed in open field test among C, M and ME groups ( P>0.05). The rate of correct selection in T-maze test was significantly lower in M and ME groups than in group C and higher in group ME than in group M( P<0.05). Experiment Ⅱ There was no significant difference in the locomotor speed in open field test among the four groups( P>0.05). Compared with group M, the rate of correct selection in open field test was significantly increased in ME and P+ ME groups ( P<0.05), and no significant change was found in group L+ ME ( P>0.05). Compared with group ME, the rate of correct selection in open field test was significantly decreased in group L+ ME ( P<0.05), and no significant change was found in group P+ ME( P>0.05). Conclusion:Melatonin can attenuate prefrontal cortex ischemia-induced cognitive impairment in the rats, and the mechanism is related to activation of MT 1R.

Objective To evaluate systematically the effect of ventilator circuit changes on incidence of ventilator-associated pneumonia(VAP).Methods Literatures about the effect of ventilator circuit changes on occurrence of VAP were searched from PubMed,Cochrane Library,CNKI,VIP,and Wanfang database,incidence of VAP in pa-tients who received circuit changes at different intervals was compared,odds ratio (OR)and 95%CI were as effect index of the study,RevMan 5.2 software was used for data analysis.Results A total of 12 literatures were included,including 18003 patients using ventilators.According to the interval of ventilator circuit changes,patients were divided into 1-day group (n=191),2-day group(n=8932),3-day group(n=228),and 7-day group(n=8652).Meta analysis showed that circuit changed every 7 days had a lower risk of VAP than that changed once ev-ery day (OR,3.72[95%CI,1.50,9.23]),there was no significant difference in risk of VAP between 7-day group and 2-day group (OR,1.17[95%CI,1.00,1.37])as well as 7-day group and 3-day group(OR,0.77 [95%CI, 0.49,1 .23]).Conclusion Patients who received circuit changes every 7 days have a lower risk of developing VAP than those who received circuit changes once per day,so change the ventilator circuit in patients with mechanical ventilation every 7 days is more reasonable.