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.

Mycophenolic acid (MPA), the active moiety of both mycophenolate mofetil (MMF) and enteric-coated mycophenolate sodium (EC-MPS), serves as a primary immunosuppressant for maintaining solid organ transplants. Therapeutic drug monitoring (TDM) enhances treatment outcomes through tailored approaches. This study aimed to develop an evidence-based guideline for MPA TDM, facilitating its rational application in clinical settings. The guideline plan was drawn from the Institute of Medicine and World Health Organization (WHO) guidelines. Using the Delphi method, clinical questions and outcome indicators were generated. Systematic reviews, Grading of Recommendations Assessment, Development, and Evaluation (GRADE) evidence quality evaluations, expert opinions, and patient values guided evidence-based suggestions for the guideline. External reviews further refined the recommendations. The guideline for the TDM of MPA (IPGRP-2020CN099) consists of four sections and 16 recommendations encompassing target populations, monitoring strategies, dosage regimens, and influencing factors. High-risk populations, timing of TDM, area under the curve (AUC) versus trough concentration (C₀), target concentration ranges, monitoring frequency, and analytical methods are addressed. Formulation-specific recommendations, initial dosage regimens, populations with unique considerations, pharmacokinetic-informed dosing, body weight factors, pharmacogenetics, and drug‍-‍drug interactions are covered. The evidence-based guideline offers a comprehensive recommendation for solid organ transplant recipients undergoing MPA therapy, promoting standardization of MPA TDM, and enhancing treatment efficacy and safety.
Mycophenolic Acid/administration & dosage* ; Drug Monitoring/methods* ; Humans ; Organ Transplantation ; Immunosuppressive Agents/administration & dosage* ; Delphi Technique

Background and Aims:Intrahepatic cholangiocarcinoma(ICC)is a highly malignant liver tumor,with an increasing incidence worldwide,particularly in Asia.Although radical surgical resection is currently the only potentially curative treatment,the high recurrence rate and low postoperative overall survival(OS)rate of ICC remain major clinical challenges.Adjuvant therapy(AT)and neoadjuvant therapy(NAT)are important strategies to reduce postoperative recurrence and prolong OS.Several studies have shown certain efficacy of these treatments.However,the specific efficacy and safety of combined NAT and AT in ICC treatment require further validation.This study was conducted to evaluate the value of combining NAT and AT in improving the therapeutic outcomes of ICC patients through a multicenter retrospective analysis,so as to provide scientific evidence for optimizing treatment strategies.Methods:The clinicopathologic data of 576 patients with ICC who underwent radical resection and were pathologically confirmed from 13 hospitals in China between December 2011 and December 2017 were retrospectively collected.Patients were grouped based on their treatment modality:NAT+AT group,AT group,and non-NAT/AT group.The three patient groups were matched pairwise in a 1∶1 ratio using propensity score matching(PSM)to balance baseline data.The Kaplan-Meier method was used to analyze OS and disease-free survival(DFS),and subgroup analyses were conducted according to the 8th edition of the AJCC TNM staging system.Results:A total of 395 ICC patients were included in the final analysis,with 42 patients(10.6%)in the NAT+AT group,62 patients(15.7%)in the AT group,and 291 patients(73.7%)in the non-NAT/AT group.Before PSM,significant differences were observed between groups in terms of CA19-9,liver function Child-Pugh classification,intraoperative blood loss,surgical margin,differentiation grade,vascular invasion,ECOG score,and lymph node dissection ratio(all P<0.05).After PSM,there were no significant differences in baseline characteristics between the groups(all P>0.05).After matching,the median OS and DFS in the NAT+AT group were significantly better than in the AT and non-NAT/AT groups(both P<0.05),while there were no significant differences in OS and DFS between the AT and non-NAT/AT groups(both P>0.05).Subgroup analysis showed that in TNM stage I patients,DFS in the NAT+AT group was significantly better than in the non-NAT/AT group(P<0.05),but OS was not significantly different(P>0.05).In TNM stage Ⅱ and Ⅲ patients,both OS and DFS in the NAT+AT and AT groups were significantly better than in the non-NAT/AT group(both P<0.05),and DFS in the NAT+AT group was significantly better than in the AT group in TNM stage Ⅲ patients(P<0.05).Conclusion:NAT combined with AT provides better survival benefits for patients with locally advanced ICC,but its benefit for early-stage ICC patients is limited.However,the retrospective design and sample size limitations of this study may affect the stability of the results,and future large-sample,multicenter,prospective studies are needed for further validation.

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.

Objective The combined entropy weight technique for order preference by similarity to an ideal solution(TOPSIS)and rank sum ratio(RSR)methods were utilized to rate the protective performance of ice hockey helmets,and the effectiveness and influencing factors of the rating system,as well as the relationship between protective performance and purchase price were explored.Methods The linear acceleration data during impact drops of twenty-four ice hockey helmets were collected using a uniaxial accelerometer in a collision test machine after low and ambient temperature treatments.The protective performance of ice hockey helmets was rated using the STAR model combined with the entropy weight TOPSIS and RSR methods.One-way ANOVA or the Kruskal-Wallis H test was employed to assess the differences in protective performance among helmets across different grade groups.The correlation between different indicators was analyzed by Pearson's correlation coefficient.Results The comprehensive protective performance ratings of the CCM TACKS 310,IBX,BAUD,and WARRIORS COVERT RS PRO helmets were classified as poor,whereas the BAUER REAKT 150,HYPERLITE,and REAKT 200 helmets were rated as excellent.The remaining helmets were rated as moderate.There was a moderate to high positive correlation between the ambient temperature STAR(A)and Rowson's STAR values,the comprehensive Ti and low temperature Ti,the comprehensive T,and ambient temperature Ti(P＜0.05).The comprehensive Ti satisfied the homogeneity of variance(P＞0.05)and exhibited significant differences among groups(P＜0.05).Significant differences were found in the low temperature indicators among different groups(P＜0.05),and their weight coefficients ranked among the top three.The ambient temperature indicators were not affected by the protective performance grade(P＞0.05).A weak positive correlation existed between the comprehensive Ti and purchase price(P＜0.05).Conclusions According to the energy absorption test protocol,the combined entropy weight TOPSIS and RSR methods can efficiently rate the comprehensive protective performance of ice hockey helmets.The effectiveness of using low temperature indicators for the comprehensive evaluation and rating of ice hockey helmet protective performance is superior to that of ambient temperature indicators and purchase price.Consumers are advised not to use price as a criterion for evaluating the comprehensive protective performance of ice hockey helmets.

In response to the new requirements for course instruction outlined in the revised training program for medical imaging program, this study integrated medical imaging technology courses based on the principle of outcome-oriented education and by leveraging self-developed digital resources, with imaging methods as the entry point. The core elements of the course teaching were re-optimized and reorganized to transcend the temporal and spatial limitations of course delivery, enabling the rational application of diverse teaching methods. This approach facilitated the integration of knowledge across three specialized courses, namely medical imaging physics, medical imaging equipment, and medical imaging examination techniques, and achieved full-dimensional and whole-process teaching evaluation. While reducing the number of hours allocated to theoretical instruction, the teaching objectives were achieved with high quality, providing a reference for the integration of digital technologies into the teaching of medical imaging and related disciplines.

Background and Aims:Intrahepatic cholangiocarcinoma(ICC)is a highly malignant liver tumor,with an increasing incidence worldwide,particularly in Asia.Although radical surgical resection is currently the only potentially curative treatment,the high recurrence rate and low postoperative overall survival(OS)rate of ICC remain major clinical challenges.Adjuvant therapy(AT)and neoadjuvant therapy(NAT)are important strategies to reduce postoperative recurrence and prolong OS.Several studies have shown certain efficacy of these treatments.However,the specific efficacy and safety of combined NAT and AT in ICC treatment require further validation.This study was conducted to evaluate the value of combining NAT and AT in improving the therapeutic outcomes of ICC patients through a multicenter retrospective analysis,so as to provide scientific evidence for optimizing treatment strategies.Methods:The clinicopathologic data of 576 patients with ICC who underwent radical resection and were pathologically confirmed from 13 hospitals in China between December 2011 and December 2017 were retrospectively collected.Patients were grouped based on their treatment modality:NAT+AT group,AT group,and non-NAT/AT group.The three patient groups were matched pairwise in a 1∶1 ratio using propensity score matching(PSM)to balance baseline data.The Kaplan-Meier method was used to analyze OS and disease-free survival(DFS),and subgroup analyses were conducted according to the 8th edition of the AJCC TNM staging system.Results:A total of 395 ICC patients were included in the final analysis,with 42 patients(10.6%)in the NAT+AT group,62 patients(15.7%)in the AT group,and 291 patients(73.7%)in the non-NAT/AT group.Before PSM,significant differences were observed between groups in terms of CA19-9,liver function Child-Pugh classification,intraoperative blood loss,surgical margin,differentiation grade,vascular invasion,ECOG score,and lymph node dissection ratio(all P<0.05).After PSM,there were no significant differences in baseline characteristics between the groups(all P>0.05).After matching,the median OS and DFS in the NAT+AT group were significantly better than in the AT and non-NAT/AT groups(both P<0.05),while there were no significant differences in OS and DFS between the AT and non-NAT/AT groups(both P>0.05).Subgroup analysis showed that in TNM stage I patients,DFS in the NAT+AT group was significantly better than in the non-NAT/AT group(P<0.05),but OS was not significantly different(P>0.05).In TNM stage Ⅱ and Ⅲ patients,both OS and DFS in the NAT+AT and AT groups were significantly better than in the non-NAT/AT group(both P<0.05),and DFS in the NAT+AT group was significantly better than in the AT group in TNM stage Ⅲ patients(P<0.05).Conclusion:NAT combined with AT provides better survival benefits for patients with locally advanced ICC,but its benefit for early-stage ICC patients is limited.However,the retrospective design and sample size limitations of this study may affect the stability of the results,and future large-sample,multicenter,prospective studies are needed for further validation.

Objective The combined entropy weight technique for order preference by similarity to an ideal solution(TOPSIS)and rank sum ratio(RSR)methods were utilized to rate the protective performance of ice hockey helmets,and the effectiveness and influencing factors of the rating system,as well as the relationship between protective performance and purchase price were explored.Methods The linear acceleration data during impact drops of twenty-four ice hockey helmets were collected using a uniaxial accelerometer in a collision test machine after low and ambient temperature treatments.The protective performance of ice hockey helmets was rated using the STAR model combined with the entropy weight TOPSIS and RSR methods.One-way ANOVA or the Kruskal-Wallis H test was employed to assess the differences in protective performance among helmets across different grade groups.The correlation between different indicators was analyzed by Pearson's correlation coefficient.Results The comprehensive protective performance ratings of the CCM TACKS 310,IBX,BAUD,and WARRIORS COVERT RS PRO helmets were classified as poor,whereas the BAUER REAKT 150,HYPERLITE,and REAKT 200 helmets were rated as excellent.The remaining helmets were rated as moderate.There was a moderate to high positive correlation between the ambient temperature STAR(A)and Rowson's STAR values,the comprehensive Ti and low temperature Ti,the comprehensive T,and ambient temperature Ti(P＜0.05).The comprehensive Ti satisfied the homogeneity of variance(P＞0.05)and exhibited significant differences among groups(P＜0.05).Significant differences were found in the low temperature indicators among different groups(P＜0.05),and their weight coefficients ranked among the top three.The ambient temperature indicators were not affected by the protective performance grade(P＞0.05).A weak positive correlation existed between the comprehensive Ti and purchase price(P＜0.05).Conclusions According to the energy absorption test protocol,the combined entropy weight TOPSIS and RSR methods can efficiently rate the comprehensive protective performance of ice hockey helmets.The effectiveness of using low temperature indicators for the comprehensive evaluation and rating of ice hockey helmet protective performance is superior to that of ambient temperature indicators and purchase price.Consumers are advised not to use price as a criterion for evaluating the comprehensive protective performance of ice hockey helmets.

In response to the new requirements for course instruction outlined in the revised training program for medical imaging program, this study integrated medical imaging technology courses based on the principle of outcome-oriented education and by leveraging self-developed digital resources, with imaging methods as the entry point. The core elements of the course teaching were re-optimized and reorganized to transcend the temporal and spatial limitations of course delivery, enabling the rational application of diverse teaching methods. This approach facilitated the integration of knowledge across three specialized courses, namely medical imaging physics, medical imaging equipment, and medical imaging examination techniques, and achieved full-dimensional and whole-process teaching evaluation. While reducing the number of hours allocated to theoretical instruction, the teaching objectives were achieved with high quality, providing a reference for the integration of digital technologies into the teaching of medical imaging and related disciplines.