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.

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 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 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 analyze the microflora structure and abundance of ileum and colon of SPF male SD rats by high-throughput sequencing technique. MethodsThe ileal and colonic lumen contents of 30 SPF male SD rats were collected, the total bacterial DNA in the contents was extracted and amplified by PCR. The V3-V4 region of bacterial 16S rRNA in the samples was sequenced using Illumina NovaSeq sequencing platform. Then the species structure and abundance of the intestinal flora were analyzed at the phylum and genus level based on validated data. The diversity and differences between ileal and colonic flora were analyzed using the QIIME software (amplicon) analysis tool. The Tax4Fun program was applied to predict the dominant gene enrichment pathways of ileal and colonic flora. ResultsAt the phylum level, the dominant microflora in the ileum of male SD rats were Firmicutes and Actinobacteria, accounting for more than 98%. The dominant colonic microbial community were mainly Firmicutes and Bacteroidetes, accounting for more than 95%. At the genus level, Lactobacillus and Alistipes were the predominant bacteria in the ileum. The colon was dominated by Lactobacillus and Romboutsia. In terms of flora diversity, the alpha diversity of colonic flora including richness index (Chao1 index) and diversity index (Shannon index) were significantly higher than those of ileum (P < 0.01), and the structural variability of the composition of its flora species was smaller than that of ileum; the ileal flora with significant structural variability were mainly of the phylum Firmicutes, Romboutsia, Peptostreptococcaceae, while the colonic flora had significant structural differences in Bacteroidales. In terms of flora function, the ileal flora dominant genes were significantly enriched in lipid-like metabolism, polyketide metabolism, membrane transport, biodegradation and other pathways, while the colonic flora dominant genes were significantly enriched in glycan biosynthesis metabolism, energy metabolism, biosynthesis of cofactor and vitamins and other products, and other pathways. ConclusionThere are significant differences in structure and abundance between the ileal and colonic flora of SPF male SD rats, and the abundance and diversity of colonic flora are higher than those of ileal flora.

Objective:To investigate the distribution of pathogenic bacteria of bloodstream infection after chemotherapy in patients with acute leukemia (AL), to analyze the risk factors for the occurrence of adverse events and to construct a nomogram model to predict the occurrence of adverse events.Methods:The clinical data of 313 AL patients with bloodstream infection who were admitted to the First Hospital of Jilin University from January 2018 to December 2020 were retrospectively analyzed, and the incidence, fatality and distribution characteristics of pathogenic bacteria after chemotherapy in AL patients were analyzed; the occurrence of adverse events (death or infectious shock) in patients with different clinicopathological characteristics were compared. Unconditional logistic binary regression model multifactor analysis was used to screen independent risk factors for the occurrence of adverse events in AL patients with bloodstream infection after chemotherapy; the nomogram model for predicting the occurrence of adverse events was developed by using R software; the Hosmer-Lemeshow test was used to verify the predictive effect of the model.Results:Of the 313 AL patients, the overall fatality rate was 4.2% (13/313), the all-cause fatality rate of bloodstream infection was 3.5% (11/313). Of the 313 cases, 254 cases (81.1%) were Gram-negative bacteria infection, mainly including 115 cases (45.3%) of Escherichia coli, 80 cases (31.5%) of Klebsiella pneumoniae, and 29 cases (11.4%) of Pseudomonas aeruginosa, and 10 cases (3.9%) died; 51 cases (16.3%) were Gram-positive cocci infection, mainly including 22 cases (43.1%) of Streptococcus spp., 20 cases (39.2%) of Staphylococcus spp., 7 cases (13.7%) of Enterococcus faecalis, and 0 case died; 8 cases (2.6%) were fungal infection, including 4 cases (1.3%) of Candida tropicalis, 2 cases (0.6%) of Candida subsmoothis, 1 case (0.3%) of Candida smooth, 1 case (0.3%) of new Cryptococcus, and 3 cases (37.5%) died. The differences in the occurrence rates of adverse events were statistically significant when comparing different treatment stage, risk stratification, timing of sensitive antibiotic use, total duration of fever, and glucocorticoid use in chemotherapy regimen, infecting bacteria carbapenem resistance, and leukemia remission (all P < 0.05). The results of logistic binary regression analysis showed that the use of glucocorticoid in chemotherapy regimen, the total duration of fever ≥7 d, the timing of sensitive antibiotic use ≥24 h, and carbapenem resistance of the infecting bacteria were independent risk factors for the occurrence of adverse events in AL patients with bloodstream infection after chemotherapy (all P < 0.05). A nomogram prediction model for the occurrence of adverse events in AL patients with bloodstream infection was established, and the nomogram model was calibrated and validated with good calibration and discrimination. Conclusions:The pathogenic bacteria of bloodstream infection after chemotherapy in AL patients is mainly Gram-negative bacteria, and the presence of glucocorticoid in chemotherapy regimen, long total duration of fever, poor timing of sensitive antibiotics, and infecting bacteria carbapenem resistance are risk factors for the occurrence of adverse events in AL patients with bloodstream infection after chemotherapy, and the nomogram prediction model based on these factors has a reliable predictive ability for the occurrence of adverse events.

Objective: To evaluate the prognostic significance of combining ISS-Ⅲ and high risk cytogenetic abnormalities [HRCAs, including 1q gain/amplification and del (17p) ] in patients with newly-diagnosed multiple myeloma (NDMM) . Methods: The clinical characteristics and relevant variables were retrospectively analyzed in a total of 270 NDMM patients diagnosed between November 2009 and May 2018. ISS-Ⅲ stage and HRCAs [detected by FISH, including 1q gain/amplification and del (17p) ] were defined as risk factors (hit) . Based to the number of hit per case, these patients were divided into four groups carrying 0 to 3 risk factors, respectively. Progress-free survival (PFS) and overall survival (OS) were then analyzed using the Kaplan-Meier estimator. Results: Patients who carried single hit (n=120, 44.4%) had shorter median PFS (23.0 vs 28.9 months; P>0.05) and OS (42.3 vs 53.7 months; P>0.05) than those with no risk factors (n=66, 24.4%) . Of note, the outcome of patients who had two or more risk factors (double/triple, n=84, 31.1%) was much worse than those with either no or one risk factor, indicated by significantly reduced median PFS (14.5 months; HR=1.584, 95%CI 1.082-2.319; P=0.003 for double/triple vs single hit) and OS (18.4 months, HR=2.299, 95%CI 1.485-3.560; P<0.001 for double/triple vs single hit) . Strikingly, patients who had three risk factor (triple hit, n=5, 1.9%) displayed the poorest survival with extraordinarily shorter PFS (0.9-15.1 months) and OS (0.9-18.9 months) compared to those carrying two risk factors (double hit) . Analogous results were obtained when different combinations of ISS stages and HRCAs were analyzed. Conclusion These results suggest a potential but rather important role of combining multiple (e.g. double or triple) adverse factors determined via the routine ISS staging and FISH detection of cytogenetic abnormalities in risk stratification and prognostic prediction, which might be helpful to identify high risk patients more precisely at diagnosis. It also raised a possibility that a small group of ISS-Ⅲ patients carrying both 1q gain/amplification and del (17p) might represent an "extremely-high risk" subset of MM.

Objectives: To evaluate the clinical characteristics and prognosis of high risk cytogenetic abnormalities (HRCA) and various combinations of cytogenetic abnormality in patients with newly-diagnosed multiple myeloma (NDMM) . Methods: This retrospective study collected 182 NDMM patients in the First Affiliated Hospital of Jilin University between Nov. 2009 and May 2018. HRCA included 1q+, del (17p) , t (4;14) , and t (14;16) detected by FISH, and non-HRCA included del (13q) , t (11;14) detected by FISH. The clinical characteristics among three groups, including cases who carrying a single HRCA, 1 HRCA in combination with non-HRCA and cases carrying two or more HRCAs (double/triple-hit) were observed. Kaplan-Meier curve was used to analyze both progression-free survival (PFS) and overall survival (OS) for the three groups. Results: The survivals of patients with 1 HRCA in combination with non-HRCA were similar to those with two or more HRCAs (double/triple-hit) , the median PFS (mPFS) was 19.1 m vs 12.1 m (P=0.248) and median OS (mOS) was 29.6 m vs 29.3 m (P=0.774) . Furthermore, the prognosis of these two groups were both inferior to patients with a single HRCA, respectively. (mPFS: 32.2 m, P=0.040, P=0.001; mOS: 42.3 m, P=0.021, P=0.041) . Strikingly, both the mPFS and the mOS of patients with 1 HRCA in combination with non-HRCA (regardless of high risk or not) were significantly shorter than that of cases with a single HRCA (mPFS: 15.1 m vs 32.2 m, HR=2.126, 95%CI 1.176-3.843, P=0.005; mOS: 29.3 m vs 42.3 m, HR=1.442, 95%CI 0.705-2.950, P=0.011) . Conclusion It is of prognostic significance value for detecting double/triple-hit based on FISH cytogenetics in NDMM.

Objective: To investigate the effect of 1q21 amplification (1q) on the therapeutic response and prognosis of bortezomib(Btz) in the treatment of newly diagnosed multiple myeloma (MM) patients. Methods: A total of 180 newly diagnosed MM were included for analyses of clinical characteristics, cytogenetics, objective response rate (ORR), progression-free survival (PFS) and overall survival (OS), retrospectively. Gene expression profiling (GEP) was analyzed using publicly available R2 platform. Results: ① In 180 patients, 1q was found in 51.1% cases. Of them, 174 patients had complete follow-up data, including 88 cases with 1q and 86 without 1q (non-1q). ②Incidence of 1q was positively associated with percentage of IGH rearrangement (72.2%, P=0.017) and 1p deletion (1p) (27.8%, P=0.040). ③ The median PFS was 15.0 and 20.3 months for the 1q group and non-1q group, and the median OS was 29.4 and 44.0 months, respectively. Both PFS and OS of 1q group was significantly shorter than those of the non-1q group (P=0.029 and 0.038, respectively). Multivariate analysis further revealed that 1q was an independent prognostic factor for both PFS (HR=1.910, 95% CI 1.105-3.303, P=0.020) and OS (HR=2.353, 95% CI 1.090-5.078, P=0.029). ④ In 91 evaluable cases with 1q, very good partial remission (VGPR) rate was higher after treatment with Btz than those without Btz (62.1% vs 40.0%, P=0.032). Of note, the patients with 1q who received auto-HSCT after induction with Btz had significantly longer PFS than those without auto-HSCT (19 months vs 13 months, P=0.048). ⑤GEP analysis revealed that 1q21 amplification predominantly up-regulated expression of >50% genes within 1q21 region, and also altered expression of 28% genes in chromosome 1 and 10% genes in whole genome, particularly related to DNA repair and cell cycle. Conclusions 1q is an independent adverse prognostic factor in patients with newly diagnosed MM. It is often associated with 1p deletion and IGH rearrangement. Patients with 1q respond well to Btz-based regimen, but they fail to gain long-term benefit from this treatment itself. However, auto-HSCT following Btz induction might improve survival of patients with 1q, suggesting a potential strategy to treat this high-risk subset of MM. GEP analysis warrants further attention in understanding the mechanisms underlying the high-risk of 1q.