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.

ObjectiveTo investigate the application value of a multimodal model integrating radiomics features， deep learning features， and clinical structured data in predicting severe acute pancreatitis （SAP）， and to provide more accurate tools for the early identification of SAP in clinical practice. MethodsThe patients with acute pancreatitis （AP） who attended The First Affiliated Hospital of Soochow University， Jintan Hospital Affiliated to Jiangsu University， and Suzhou Yongding Hospital from January 1， 2017 to December 31， 2023 were included. Related data were collected， including demographic information， previous medical history， etiology， laboratory test data， and systemic inflammatory response syndrome （SIRS） within 24 hours after admission， as well as imaging data within 72 hours after admission， while related scores were calculated， including Ranson score， modified CT severity index （MCTSI）， bedside index for severity in acute pancreatitis （BISAP）， and systemic inflammatory response syndrome， albumin， blood urea nitrogen and pleural effusion （SABP） score. The model was constructed in the following process： （1） three-dimensional CT images were used to extract and identify radiomics features， and a radiomics classification model was established based on the extreme gradient Boost （XGBoost） algorithm； （2） U-Net is used to perform semantic segmentation of three-dimensional CT images， and then the results of segmentation were imported into 3D ResNet50 to construct a deep learning classification model； （3） the predicted values of the above two models were integrated with clinical structured data to establish a multimodal model based on the XGBoost algorithm. The variable importance plot and local interpretability plot were used to perform visual interpretation of the model. The independent samples t-test was used for comparison of normally distributed continuous data between groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between groups； the chi-square test or Fisher’s exact test was used for comparison of categorical data between groups. The receiver operating characteristic （ROC） curve was plotted for each model and existing scoring systems， and the area under the ROC curve （AUC） was calculated to assess their performance； the Delong test was used for comparison of AUC. ResultsA total of 609 patients who met the criteria were included， among whom 114 （18.7%） developed SAP. In this study， the data of 426 patients from The First Affiliated Hospital of Soochow University was used as the training set， and the data of 183 patients from Jintan Hospital Affiliated to Jiangsu University and Suzhou Yongding Hospital were used as the independent test set. The multimodal model had an AUC of 0.914 in the test set， which was significantly higher than the AUC of traditional scoring systems such as MCTSI （AUC=0.827）， Ranson score （AUC=0.675）， BISAP （AUC=0.791）， and SABP score （AUC=0.648）； in addition， the multimodal model showed a significant improvement in performance compared with the radiomics classification model （AUC=0.739） and the deep learning classification model （AUC=0.685） （the Delong test： Z=-3.23， -4.83， -3.48， -4.92， -4.31， and -4.59， all P <0.01）. The top 10 variables in terms of importance in the multimodal model were pleural effusion， predicted value of the deep learning model， predicted value of the radiomics model， triglycerides， calcium ions， SIRS， white blood cell count， age， platelets， and C-reactive protein， suggesting that the above variables had significant contributions to the performance of the model in predicting SAP. ConclusionBased on structured data， radiomic features， and deep learning features， this study constructs a multicenter prediction model for SAP based on the XGBoost algorithm， which has a better predictive performance than existing traditional scoring systems and unimodal models.

The sympathetic nervous system(SNS)plays a pivotal role in maintaining organ homeosta-sis and the pathogenesis of various ailments.Studies have unveiled a profound interconnection between sympathet-ic nerves and the development of liver cirrhosis,cirrhotic cardiomyopathy,and hepatorenal syndrome.Therefore,researchers have proposed SNS as a candidate therapeutic target for liver-related disorders.This article reviewed the research progress of sympathetic nerves in liver cirrhosis,cirrhotic cardiomyopathy,and hepatorenal syn-drome,aiming to enrich the knowledge about the roles of sympathetic nerves in cirrhosis and its complications and provide new ideas for the treatment of liver cirrhosis and its complications.

Objective To explore the clinical significance and gene mutation profiles of renal transplant patients with unconjugated hyperbilirubinemia (Gilbert's syndrome).Methods Genomic DNA was extracted from peripheral blood samples of 8 renal transplant patients with Gilbert'S syndrome.UGT1A1 * 6 and UGT1A1 * 28 genotypes were identified through digital fluorescence molecular hybridization and DNA sequencing.Results There are 2 cases of UGT1A1 * 28 heterozygous mutant,3 cases of UGT1A1 * 6 homozygous mutant,2 case of UGT1A1 * 6 heterozygous mutant,1 case of UGT1A1 * 28 heterozygous mutant combined with UGT1A1 * 6 heterozygous mutant.Conclusion There is a higher heterozygous or homozygous gene mutation rate of UGT1A1 * 6 and UGT1A1 * 28 in renal transplant patients with Gilbert's syndrome.Genetic mutation of UGT1A1 * 6 and UGT1A1 * 28 may be the reason of Gilbert's syndrome after renal transplant.

Objective To evaluate the effect of ditching for drain on the control of the breed of Oncomelania hupensis snails in beaches of Dongting Lake. Methods From November,2009 to November,2012,an O. hupensis snail infested beach of the Yueyang jail and an O. hupensis snail infested beach of Junshan District were selected as research fields in the eastern Dongting Lake area,and the former,as the intervention field,was performed with the ditching for drain by excavators and the latter,as the control field,was not. Results Before the project implemented,the average soil moisture contents on the beaches in dry seasons of the two fields were both about 35.56%. After the project implemented,in the intervention field,the average soil mois?ture content was 26.53%which was significantly lower than that(35.56%)in the control field(F=6.53,P<0.05). The under?ground water levels in different heights in the intervention field were lower than those in the control field (χ2 = 33.33,P <0.05). Before the project implemented,the natural death rates of the snails were 0.98%and 0.89%in the two research fields re?spectively(P>0.05),and after the project implemented(in 2012),no adult and young snails were found in the interventional field,but in the control field,the average densities of living snails and young snails were 29.37 snails/0.1 m2 and 213±108.45 snails/0.1 m2 respectively. Conclusion The intervention of ditching for drain can decrease the soil moisture contents quickly and change the ecological condition,therefore,can control the breed of O. hupensis snails in the beaches of Dongting Lake.

The purpose of this study was to compare the pharmacokinetic profiles of tetramethylpyrazine phosphate (TMPP) in plasma and extracellular fluid of the cerebral cortex of rats via three delivery routes: intranasal (i.n.), intragastric (i.g.) and intravenous (i.v.) administration. After i.n., i.g. and i.v. administration of a single-dose at 10 mg/kg, cerebral cortex dialysates and plasma samples drawn from the carotid artery were collected at timed intervals. The concentration of TMPP in the samples was analyzed by HPLC. The area under the concentration-time curve (AUC) and the ratio of the AUCbrain to the AUCplasma (drug targeting efficiency, DTE) was calculated to evaluate the brain targeting efficiency of the drug via these different routes of administration. After i.n. administration, TMPP was rapidly absorbed to reach its peak plasma concentration within 5 min and showed a delayed uptake into cerebral cortex (t max=15 min). The ratio of the AUCbrain dialysates value between i.n. route and i.v. injection was 0.68, which was greater than that obtained after i.g. administration (0.43). The systemic bioavailability obtained with i.n. administration was greater than that obtained by the i.g. route (86.33% vs. 50.39%), whereas the DTE of the nasal route was 78.89%, close to that of oral administration (85.69%). These results indicate that TMPP is rapidly absorbed from the nasal mucosa into the systemic circulation, and then crosses the blood-brain barrier (BBB) to reach the cerebral cortex. Intranasal administration of TMPP could be a promising alternative to intravenous and oral approaches.

ObjectiveTo investigate the effects of lipopolysaccharide (LPS) on mRNA expression of iron metabolism related genes. Methods Ten male mice (2 months) were injected intraperitoneally with lipopolysaccharide(0.5 μg/g). After 6 hours, mice were sacrificed and then sera, liver and spleen were collected. The mice blood routine was measured. The serum iron and total iron binding capacity (TIBC) were determined with reagent kit. The quasi-quantitative reverse transcription polymerase chain reaction (RT-PCR) was performed for mRNA of hepatic hepcidin(HP), ferroportin1(Fpn1), transferrin receptor 1(TfR1) and spleenic HP, Fpn1 and interleukin-6(IL-6). Results The serum iron and TIBC were reduced in mice injected LPS, which exhibited mild anemia(P＜0.05) . LPS can increase the expression of hepatic hepcidin and decrease Fpn1 and TfR1 in liver after LPS administration 6 hours(P＜0.05). In spleen, IL-6 was upregulated and Fpn1 downregulated(P＜0.05). Conclusion LPS can influence serum iron through regulating the mRNA expression of hepatic and spleenic iron metabolism related genes, such as HP, Fpn1 and TfR1.

Objective To observe the effects of calcium cyanamide (Rongbao) on the histological and morphological changes of Oncomelania hupensis snails in order to explore its molluscicidal mechanisms.Methods The serial snails' slides were fixed after soaking in a concentration of Rongbao leached liquor at different time.The histological and morphological changes of the snails were compared among these slides.Results After soaking in the Rongbao leached liquor for 48 h,the mantle epithelia,respiratory epithelia of the gill,liver cells,and muscle cells of gastropods were injured seriously,which resulted in the death of the snails directly.The death rates of the snails were 96.70% and 100% after soaking in the Rongbao leached liquor for 48 h and 72 h,respectively.Conclusion Rongbao is an effective molluscicide by damaging the several snail tissues.