OBJECTIVE To systematically review the current application of discrete choice experiment （DCE） in the value assessment and preference measurement of orphan medicinal product （OMP）， and to provide a reference for the standardized use of this methodology in China. METHODS The systematic search was conducted across Chinese and English databases including CNKI， Wanfang Data， VIP， CBM， PubMed， Web of Science， Medline， and Embase. Original studies that employed DCE to evaluate the value or preferences related to OMP were included. The methodological quality and reporting completeness of the included studies were assessed using the ISPOR Conjoint Analysis Checklist and the DIRECT Checklist， respectively. Respondent populations， attribute setting， and the relative importance of attributes were summarized and analyzed. RESULTS Eight eligible studies were included； all studies demonstrated high-quality reporting and methodological rigor. Respondents comprised the general public， patients/caregivers， policymakers， and other stakeholders. The number of DCE attributes ranged from 4 to 13 （median＝7.5）. Through thematic synthesis， these attributes were categorized into three dimensions， namely “disease-related” “treatment-related” and “economic/financial-related” along with 14 secondary criteria. The most frequently included secondary criteria were treatment efficacy （13 occurrences）， disease severity （9 occurrences）， safety （7 occurrences）， unmet medical need （6 occurrences）， and treatment cost （5 occurrences）. Rankings of relative importance identified treatment efficacy as the most valued criterion across most studies， followed by health insurance financing. CONCLUSIONS DCE applications in the value assessment of OMP have begun to converge on a relatively consistent core attribute framework and selection preference. Future research should further promote the use of DCE to inform attribute and criterion selection in multi-criteria decision analysis frameworks for OMP.

OBJECTIVES: To investigate the role and mechanism of copper overload-mediated endoplasmic reticulum stress (ERS) in vascular endothelial injury in Kawasaki disease (KD). METHODS: Four-week-old male C57BL/6 mice were randomly divided into four groups: control, KD, KD plus copper chelator tetrathiomolybdate (TTM), and KD plus ERS inhibitor AMG PERK 44 (AMG) (n=20 per group). A KD mouse model was established using Candida albicans extract. Human umbilical vein endothelial cells (HUVECs) were divided into control (intervention with healthy children's serum), KD (intervention with KD patients' serum), and KD+TTM (intervention with KD patients' serum plus 20 µmol/L TTM). Copper deposition in mouse heart tissue was assessed using rubeanic acid staining. Vascular pathological changes were observed using hematoxylin-eosin staining and measurement of abdominal aortic diameter and area. ERS activation was detected by transmission electron microscopy and immunofluorescence. HUVEC viability, apoptosis, and functional changes were evaluated using CCK8, flow cytometry, cell scratch assay, and angiogenesis experiments. ERS marker protein expression levels were measured by Western blot. RESULTS: Compared to the KD group, the KD+TTM and KD+AMG groups showed reduced copper deposition in the vascular wall, decreased swelling of coronary endothelial cells and endoplasmic reticulum, reduced inflammatory cell infiltration, and less abdominal aortic lesion expansion. The abdominal aortic diameter and area, and the fluorescence intensity of ERS marker proteins (GRP78 and CHOP) were significantly lower (P<0.05). Compared to the KD group, the KD+TTM group exhibited increased cell viability, tube number, and scratch healing rate, along with decreased apoptosis rate and expression of ERS marker proteins (GRP78, CHOP, ATF6, and p-PERK) (P<0.05). CONCLUSIONS Copper overload aggravates vascular endothelial injury in KD by activating the ERS pathway. TTM can exert protective effects on the endothelium by regulating copper metabolism and inhibiting the ERS pathway.
Endoplasmic Reticulum Stress ; Copper/toxicity* ; Male ; Mucocutaneous Lymph Node Syndrome/metabolism* ; Animals ; Humans ; Endoplasmic Reticulum Chaperone BiP ; Mice, Inbred C57BL ; Mice ; Human Umbilical Vein Endothelial Cells ; Apoptosis ; Endothelium, Vascular/injuries*

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To explore the application value of Xuanbai Chengqi Decoction combined with enteral nutrition support in the treatment of acute exacerbation of chronic obstructive pulmonary disease(AECOPD)guided by the theory of simultaneous treatment of lung and intestine.Methods A total of 92 patients with AECOPD were randomly divided into an observation group and a control group,46 cases in each group.Both groups were given routine symptomatic treatment.In addition,the control group was given enteral nutrition support intervention,and the observation group was given Xuanbai Chengqi Decoction combined with enteral nutrition support intervention.The course of treatment lasted for two weeks.The changes in the nutritional parameters such as serum albumin(ALB),prealbumin(PA),and transferrin(TF),and in the distribution of intestinal flora of the two groups were observed before and after treatment.After treatment,the clinical efficacy and the incidence of adverse reactions were compared between the two groups.Results(1)After two weeks of treatment,the total effective rate of the observation group was 97.83％(45/46),and that of the control group was 82.61％(38/46).The comparison between the two groups(tested by chi-square test)showed that the therapeutic efficacy of the observation group was significantly superior to that of the control group,and the difference was statistically significant(P＜0.05).(2)After treatment,the serum levels of nutritional parameters of ALB,PA and TF in the two groups were significantly higher than those before treatment(P＜0.05),and the increase of serum ALB,PA and TF levels in the observation group was significantly superior to that in the control group,the differences being statistically significant(P＜0.05 or P＜0.01).(3)After treatment,the number of Lactobacillus and Bifidobacterium strains of intestinal flora in the two groups was significantly higher than that before treatment(P＜0.05),and the number of Enterococcus strain was significantly lower than that before treatment(P＜0.05).The increase in the number of Lactobacillus and Bifidobacterium strains and the decrease in the number of Enterococcus strains in the observation group were significantly superior to those in the control group,and the differences were statistically significant(P＜0.05 or P＜0.01).(4)The incidence of adverse reactions in the observation group was 4.35％(2/46),which was significantly lower than that in the control group(19.57％,9/46).The difference between the two groups was statistically significant(P＜0.05).Conclusion Significant clinical efficacy has been achieved after the application of Xuanbai Chengqi Decoction combined with enteral nutrition support in treating AECOPD patients with lung heat and bowel excess syndrome guided by the theory of simultaneous treatment of lung and intestine.The combined therapy is effective on improving the nutritional status and intestinal flora imbalance of patients,and reducing the incidence of adverse reactions.

Objective To achieve automatic segmentation of cell nuclei in gastrointestinal cancer pathological images by using a deep learning algorithm,so as to assist in the quantitative analysis of subsequent pathological images.Methods A total of 59 patients with gastrointestinal cancer treated in Ruijin Hospital,Shanghai Jiao Tong University School of Medicine from Jan 2022 to Feb 2022,were selected as the research objects.Python and LabelMe were used for data anonymization,image segmentation,and region of interest annotation of patients'pathological images.A total of 944 pathological images were included,and 9 703 nuclei were annotated.Then,a new semantic segmentation model based on deep learning was constructed.The model introduced deformable attention transformer(DAT)to realize automatic,accurate and efficient segmentation of pathological image nuclei.Finally,multiple segmentation evaluation criteria are used to evaluate the model's performance.Results The mean absolute error of the segmentation results of the model proposed in this paper was 0.112 6,and the dice coefficient(Dice)was 0.721 5.Its effect was significantly better than the U-net baseline model,and it was ahead of models such as ResU-net++,R2Unet and R2AttUnet.Moreover,the segmentation results were relatively stable with good generalization.Conclusion The segmentation model established in this study can accurately identify and segment the nuclei in the pathological images,with good robustness and generalization,which is helpful to play an auxiliary diagnostic role in practical applications.

A new cadinane-type sesquiterpenoid, pogocablene P (1), and a new natural product with cyclohexanone skeleton, pogocablone A (2), were isolated from the EtOAc soluble fraction of the aerial parts of Pogostemon cablin by several chromatographic methods, such as silica gel, Sephadex LH-20, ODS and high performance liquid chromatography (HPLC), and so on. Their structures were identified by means of mass spectrometry and nuclear magnetic resonance spectroscopy. In addition, the absolute configuration of compound 2 was determined by electronic circular dichroism (ECD) calculation. Furthermore, the anti-influenza virus and anti-inflammatory activities of compounds 1 and 2 were evaluated.

OBJECTIVES: To study the role and mechanism of platelet-derived growth factor BB (PDGF-BB) on platelet production in Kawasaki disease (KD) mice and human megakaryocytic Dami cells through in vitro and invivo experiments. METHODS: ELISA was used to measure the expression of PDGF in the serum of 40 children with KD and 40 healthy children. C57BL/6 mice were used to establish a model of KD and were then randomly divided into a normal group, a KD group, and an imatinib group (30 mice in each group). Routine blood test was performed for each group, and the expression of PDGF-BB, megakaryocyte colony forming unit (CFU-MK), and the megakaryocyte marker CD41 were measured. CCK-8, flow cytometry, quantitative real-time PCR, and Western blot were used to analyze the role and mechanism of PDGF-BB in platelet production in Dami cells. RESULTS: PDGF-BB was highly expressed in the serum of KD children (P<0.001). The KD group had a higher expression level of PDGF-BB in serum (P<0.05) and significant increases in the expression of CFU-MK and CD41 (P<0.001), and the imatinib group had significant reductions in the expression of CFU-MK and CD41 (P<0.001). In vitro experiments showed that PDGF-BB promoted Dami cell proliferation, platelet production, mRNA expression of PDGFR-β, and protein expression of p-Akt (P<0.05). Compared with the PDGF-BB group, the combination group (PDGF-BB 25 ng/mL + imatinib 20 μmol/L) had significantly lower levels of platelet production, mRNA expression of PDGFR-β, and protein expression of p-Akt (P<0.05). CONCLUSIONS PDGF-BB may promote megakaryocyte proliferation, differentiation, and platelet production by binding to PDGFR-β and activating the PI3K/Akt pathway, and the PDGFR-β inhibitor imatinib can reduce platelet production, which provides a new strategy for the treatment of thrombocytosis in KD.
Child ; Humans ; Animals ; Mice ; Mice, Inbred C57BL ; Becaplermin ; Imatinib Mesylate/therapeutic use* ; Mucocutaneous Lymph Node Syndrome/drug therapy* ; Phosphatidylinositol 3-Kinases ; Proto-Oncogene Proteins c-akt ; Thrombocytosis/etiology* ; RNA, Messenger

Objective: To establish a predictive model for survival benefit of patients with intrahepatic cholangiocarcinoma (ICC) who received adjuvant chemotherapy after radical resection. Methods: The clinical and pathological data of 249 patients with ICC who underwent radical resection and adjuvant chemotherapy at 8 hospitals in China from January 2010 to December 2018 were retrospectively collected. There were 121 males and 128 females,with 88 cases>60 years old and 161 cases≤60 years old. Feature selection was performed by univariate and multivariate Cox regression analysis. Overall survival time and survival status were used as outcome indicators,then target clinical features were selected. Patients were stratified into high-risk group and low-risk group,survival differences between the two groups were analyzed. Using the selected clinical features, the traditional CoxPH model and deep learning DeepSurv survival prediction model were constructed, and the performance of the models were evaluated according to concordance index(C-index). Results: Portal vein invasion, carcinoembryonic antigen>5 μg/L,abnormal lymphocyte count, low grade tumor pathological differentiation and positive lymph nodes>0 were independent adverse prognostic factors for overall survival in 249 patients with adjuvant chemotherapy after radical resection (all P<0.05). The survival benefit of adjuvant chemotherapy in the high-risk group was significantly lower than that in the low-risk group (P<0.05). Using the above five features, the traditional CoxPH model and the deep learning DeepSurv survival prediction model were constructed. The C-index values of the training set were 0.687 and 0.770, and the C-index values of the test set were 0.606 and 0.763,respectively. Conclusion: Compared with the traditional Cox model, the DeepSurv model can more accurately predict the survival probability of patients with ICC undergoing adjuvant chemotherapy at a certain time point, and more accurately judge the survival benefit of adjuvant chemotherapy.

Objectives: To construct a nomogram for prediction of intrahepatic cholangiocarcinoma (ICC) lymph node metastasis based on inflammation-related markers,and to conduct its clinical verification. Methods: Clinical and pathological data of 858 ICC patients who underwent radical resection were retrospectively collected at 10 domestic tertiary hospitals in China from January 2010 to December 2018. Among the 508 patients who underwent lymph node dissection,207 cases had complete variable clinical data for constructing the nomogram,including 84 males,123 females,109 patients≥60 years old,98 patients<60 years old and 69 patients were pathologically diagnosed with positive lymph nodes after surgery. Receiver operating characteristic curve was drawn to calculate the accuracy of preoperative imaging examinations to determine lymph node status,and the difference in overall survival time was compared by Log-rank test. Partial regression squares and statistically significant preoperative variables were screened by backward stepwise regression analysis. R software was applied to construct a nomogram,clinical decision curve and clinical influence curve,and Bootstrap method was used for internal verification. Moreover,retrospectively collecting clinical information of 107 ICC patients with intraoperative lymph node dissection admitted to 9 tertiary hospitals in China from January 2019 to June 2021 was for external verification to verify the accuracy of the nomogram. 80 patients with complete clinical data but without lymph node dissection were divided into lymph node metastasis high-risk group and low-risk group according to the score of the nomogram among the 858 patients. Log-rank test was used to compare the overall survival of patients with or without lymph node metastasis diagnosed by pathology. Results: The area under the curve of preoperative imaging examinations for lymph node status assessment of 440 patients was 0.615,with a false negative rate of 62.8% (113/180) and a false positive rate of 14.2% (37/260). The median survival time of 207 patients used to construct a nomogram with positive or negative postoperative pathological lymph node metastases was 18.5 months and 27.1 months,respectively (P<0.05). Five variables related to lymph node metastasis were screened out by backward stepwise regression analysis,which were combined calculi,neutrophil/lymphocyte ratio,albumin,liver capsule invasion and systemic immune inflammation index,according to which a nomogram was constructed with concordance index(C-index) of 0.737 (95%CI: 0.667 to 0.806). The C-index of external verification was 0.674 (95%CI:0.569 to 0.779). The calibration prediction curve was in good agreement with the reference curve. The results of the clinical decision curve showed that when the risk threshold of high lymph node metastasis in the nomogram was set to about 0.32,the maximum net benefit could be obtained by 0.11,and the cost/benefit ratio was 1∶2. The results of clinical influence curve showed that when the risk threshold of high lymph node metastasis in the nomogram was set to about 0.6,the probability of correctly predicting lymph node metastasis could reach more than 90%. There was no significant difference in overall survival time between patients with high/low risk of lymph node metastasis assessed by the nomogram and those with pathologically confirmed lymph node metastasis or without lymph node metastasis (Log-rank test:P=0.082 and 0.510,respectively). Conclusion: The prediction accuracy of preoperative nomogram for ICC lymph node metastasis based on inflammation-related markers is satisfactory,which can be used as a supplementary method for preoperative diagnosis of lymph node metastasis and is helpful for clinicians to make personalized decision of lymph node dissection for patients with ICC.