The construction of a training system for visiting physicians in the department of rare diseases in China is an important measure to improve the overall diagnosis and treatment capacity for rare diseases and address the critical challenge of insufficient knowledge and skills among clinicians in practice. This article systematically describes the visiting physician training system established by the Department of Rare Diseases at Peking Union Medical College Hospital. It summarizes the training objectives and positioning, design logic, and learning modules of the system, aiming to provide a reference for the construction of the specialized talent team for rare diseases in China.

OBJECTIVE To investigate the risk factors for sodium valproate （VPA）-induced hyperammonemia in neurocritical patients， and to construct a risk prediction model. METHODS Clinical data were retrospectively collected from 172 neurocritical patients who received VPA treatment in the Department of Critical Care Medicine， the Fourth Affiliated Hospital of Soochow University from January 2022 to June 2025. Patients were divided into the hyperammonemia group （73 cases） and the normal group （99 cases） based on their blood ammonia levels. Univariate analysis and LASSO regression analysis were used to screen for predictive variables. Independent factors were identified through multivariate Logistic regression analysis， and a nomogram was constructed accordingly. The performance of the model was evaluated using receiver operating characteristic （ROC） curve， calibration curve， and decision curve analysis （DCA）. RESULTS Combination of univariate analysis and LASSO regression analysis screened out seven predictive variables： body mass index （BMI）≥24.0 kg/m 2 ， concomitant use of benzodiazepines， VPA blood concentration， hemoglobin， serum urea， average daily VPA dose， and albumin. Multivariate Logistic regression analysis showed that concomitant use of benzodiazepines， BMI≥24.0 kg/m 2 ， VPA blood concentration， albumin and serum urea level （with odds ratios of 1.615， 1.538， 1.623， 1.942 and 0.637， respectively； 95% confidence intervals of 1.128-2.359， 1.059-2.251， 1.112-2.431， 1.106-3.598 and 0.402-0.980， respectively） were all significantly associated with VPA-induced hyperammonemia in neurocritical patients （ P ＜0.05）. The nomogram prediction model constructed based on these variables was evaluated， showing that the area under the ROC curve was 0.810 for the test set and 0.844 for the validation set. The calibration curves closely approximated t he actual curves， and the application of this model could improve the clinical net benefit. CONCLUSIONS Concomitant use of benzodiazepines， BMI≥24.0 kg/m 2 ， high VPA blood concentration and high albumin level are independent risk factors for VPA-induced hyperammonemia in neurocritical patients， while high serum urea level is an independent protective factor. The risk prediction model constructed based on these factors exhibits good discrimination， consistency， and clinical applicability， making it applicable for predicting the risk of VPA-induced hyperammonemia in neurocritical patients.

OBJECTIVE To analyze the current status and challenges in importing rare disease drugs in China， providing references for optimizing the import process and improving relevant policies. METHODS Questionnaires and interviews were conducted with stakeholders involved in rare disease drug importation， including government departments， multinational pharmaceutical enterprises， healthcare institutions， and patient organizations. This explored the current situation and challenges encountered by each party. Expert opinions were synthesized to propose improvement suggestions. RESULTS A questionnaire survey of representatives from 25 multinational pharmaceutical companies in the rare disease field revealed that these companies had a strong willingness to import rare disease drugs， with 58.33% of them practicing diverse import models. However， significant challenges hindered this process， including unclear regulations （54.17%）， complex approval procedures （45.83%）， and excessively long approval cycles （41.67%）， negatively impacting their motivation. Meanwhile， interviews with 13 experts from government departments， healthcare institutions， pharmaceutical enterprises， and patient organizations identified deficiencies in policy design， approval processes， sampling inspection costs， and communication efficiency with regulators. Additionally， the drug import model in special medical zones also required improvement. CONCLUSIONS The importation of rare disease drugs in China faces challenges such as incomplete policies， inflexible regulatory mechanisms， and insufficient communication channels. It is recommended to enhance the rare disease definition criteria， optimize import incentive policies， and refine regulatory models， so as to further optimize the import process of rare disease drugs and improve relevant policies.

Dent disease is a rare X-linked recessive renal tubular disease characterized by low molecular weight proteinuria，hypercalcemia and nephrocalcinosis. It is also a major cause of tubular proteinuria in children. According to different causative genes，Dent disease can be divided into three types：type 1 is caused by mutations in the CLCN5 gene，accounting for about 60%-70%；type 2 is caused by mutations in the OCRL gene，accounting for about 15%-20%；type 3 has a similar clinical phenotype but no known pathogenic gene mutations. CLCN5 encodes the voltage-dependent 2Cl -/1H +exchange channel CIC-5，which is involved in proximal renal tubule endocytosis. Its mutations can cause a variety of proximal tubular dysfunction symptoms，mainly including low molecular weight proteinuria. The use of gene detection technology has resulted in an increase in reports on Dent disease year after year. At present，the specific mechanism underlying Dent disease remains unknown. This article reviews the research progress of CLCN5，hoping to provide new insight for the mechanism research of CLCN5 and the specific treatment of Dent disease type 1.

Objective To investigate the clinical efficacy of fasting nasogastric administration of sesame oil combined with multi-frequency vibrational abdominal massage in stroke patients with consti-pation undergoing nasogastric feeding.Methods A total of 50 stroke patients with nasogastric feeding were selected as study subjects and randomly divided into control group and study group,with 25 pa-tients in each group.The control group received routine nursing care plus multi-frequency vibrational abdominal massage,while the study group received fasting nasogastric administration of 20 mL of sesa-me oil on the basis of the control group's treatment.After 15 days of intervention,the defecation condi-tions[constipation clinical symptom score(CSS),stool consistency(Bristol stool scale),and stool volume]were compared between the two groups.Results After treatment,the CSS score in the study group was lower than that in the control group[(6.52±2.52)versus(12.64±3.32),P＜0.05].The normal stool consistency(types Ⅳ and Ⅴ on the Bristol stool scale)in the study group was higher than that in the control group(76.0％versus 8.0％,P＜0.05).The stool volume in the study group was higher than that in the control group[(303.00±93.79)g versus(196.40±60.27)g,P＜0.05].The total effective rate of defecation in the study group was 96.0％,which was higher than 32.0％in the control group(P＜0.05).The Patient Assessment of Constipation-Quality of Life(PAC-QOL)score in the study group was lower than that in the control group[(40.07±5.67)versus(63.07±7.46),P＜0.05].Conclusion Fasting nasogastric administration of sesame oil com-bined with multi-frequency vibrational abdominal massage can promote the recovery of intestinal function and improve constipation symptoms in stroke patients with nasogastric feeding.

Objective:To investigate the application value of dual-energy computer tomo-graphy (CT) multi-parameter imaging in predicting the pathological grade of pancreatic ductal adeno-carcinoma (PDAC).Methods:The retrospective cohort study was conducted. The clinicopatholo-gical data of 147 patients with PDAC who were admitted to The Fifth Affiliated Hospital of Wenzhou Medical University from January 2017 to August 2023 were collected. There were 102 males and 45 females, aged (59±10)years. All patients underwent preoperative dual-energy CT examination and postoperative histopathological examination. The 147 patients were divided into a training set of 103 cases and a test set of 44 cases by stratified random sampling at a ratio of 7∶3. The training set was used to construct the prediction model, and the test set was used to verify the effectiveness of prediction model. Observation indicators: (1) analysis of factors affecting the pathological grade of PDAC patients in the training set; (2) construction and evaluation of the fusion prediction model for pathological grade of PDAC. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Univariate and multivariate analyses were conducted using the Logistic regression model. The performance of the model was evaluated by receiver operating characteristic (ROC) curve, and the area under the curve (AUC), accuracy, sensitivity and specificity were calculated. The Delong test was used to analyze the effec-tiveness of model. The calibration curve and decision curve of Hosmer-Lemeshow test were used to evaluate the consistency and clinical application value of the nomogram, respectively. Results:(1) Analysis of factors affecting the pathological grade of PDAC patients in the training set. Results of multivariate analysis showed that tumor cystic necrosis, vascular invasion, standardized iodine concentration (NIC) in venous phase, effective atomic number (Zeff) in venous phase, and energy spectrum curve slope (λ HU) in venous phase were all independent factors affecting the pathological grade of PDAC patients in the training set ( odds ratio=4.326, 3.887, 4.155, 5.389, 3.164, 95% confidence interval as 1.167-16.033, 1.111-13.592, 1.707-10.113, 1.284-22.613, 1.247-8.028, P<0.05). (2) Construction and evaluation of the fusion prediction model for pathological grade of PDAC. Accor-ding to the results of multivariate analysis, tumor cystic necrosis, vascular invasion, NIC in venous phase, Zeff in venous phase and λ HU in venous phase were all included to construct the clinical-imaging fusion prediction nomogram model. The AUC, accuracy, sensitivity and specificity of the fusion prediction model in the training set were 0.938 (95% confidence interval as 0.896-0.981), 87.38%, 89.74% and 85.94%, respectively. The above indicators of the fusion prediction model in the test set were 0.893 (95% confidence interval as 0.802-0.985), 84.09%, 82.35% and 85.19%, respectively. Results of Delong test showed that there was no significant difference in AUC between the training set and the test set ( Z=0.343, P>0.05). Results of Hosmer-Lemeshow test showed that the fusion prediction model had a good fit in the training set and the test set ( χ2=3.042, 7.545, P>0.05). Results of calibration curve showed that the predictive ability of the fusion prediction model was good. Conclusions:Multiple parameters in venous phase of the dual-energy CT can be used as imaging markers for preoperative evaluation of the pathological grade of patients with PDAC. Establishing a clinical-imaging fusion prediction model can effectively predict the pathological grade of PDAC.

Objective:To investigate the application value of dual-energy computer tomo-graphy (CT) multi-parameter imaging in predicting the pathological grade of pancreatic ductal adeno-carcinoma (PDAC).Methods:The retrospective cohort study was conducted. The clinicopatholo-gical data of 147 patients with PDAC who were admitted to The Fifth Affiliated Hospital of Wenzhou Medical University from January 2017 to August 2023 were collected. There were 102 males and 45 females, aged (59±10)years. All patients underwent preoperative dual-energy CT examination and postoperative histopathological examination. The 147 patients were divided into a training set of 103 cases and a test set of 44 cases by stratified random sampling at a ratio of 7∶3. The training set was used to construct the prediction model, and the test set was used to verify the effectiveness of prediction model. Observation indicators: (1) analysis of factors affecting the pathological grade of PDAC patients in the training set; (2) construction and evaluation of the fusion prediction model for pathological grade of PDAC. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Univariate and multivariate analyses were conducted using the Logistic regression model. The performance of the model was evaluated by receiver operating characteristic (ROC) curve, and the area under the curve (AUC), accuracy, sensitivity and specificity were calculated. The Delong test was used to analyze the effec-tiveness of model. The calibration curve and decision curve of Hosmer-Lemeshow test were used to evaluate the consistency and clinical application value of the nomogram, respectively. Results:(1) Analysis of factors affecting the pathological grade of PDAC patients in the training set. Results of multivariate analysis showed that tumor cystic necrosis, vascular invasion, standardized iodine concentration (NIC) in venous phase, effective atomic number (Zeff) in venous phase, and energy spectrum curve slope (λ HU) in venous phase were all independent factors affecting the pathological grade of PDAC patients in the training set ( odds ratio=4.326, 3.887, 4.155, 5.389, 3.164, 95% confidence interval as 1.167-16.033, 1.111-13.592, 1.707-10.113, 1.284-22.613, 1.247-8.028, P<0.05). (2) Construction and evaluation of the fusion prediction model for pathological grade of PDAC. Accor-ding to the results of multivariate analysis, tumor cystic necrosis, vascular invasion, NIC in venous phase, Zeff in venous phase and λ HU in venous phase were all included to construct the clinical-imaging fusion prediction nomogram model. The AUC, accuracy, sensitivity and specificity of the fusion prediction model in the training set were 0.938 (95% confidence interval as 0.896-0.981), 87.38%, 89.74% and 85.94%, respectively. The above indicators of the fusion prediction model in the test set were 0.893 (95% confidence interval as 0.802-0.985), 84.09%, 82.35% and 85.19%, respectively. Results of Delong test showed that there was no significant difference in AUC between the training set and the test set ( Z=0.343, P>0.05). Results of Hosmer-Lemeshow test showed that the fusion prediction model had a good fit in the training set and the test set ( χ2=3.042, 7.545, P>0.05). Results of calibration curve showed that the predictive ability of the fusion prediction model was good. Conclusions:Multiple parameters in venous phase of the dual-energy CT can be used as imaging markers for preoperative evaluation of the pathological grade of patients with PDAC. Establishing a clinical-imaging fusion prediction model can effectively predict the pathological grade of PDAC.

OBJECTIVE To provide suggestions for improving the path and system construction of patient engagement in drug regulation in China.METHODS By reviewing initiatives and experiences from the United States(U.S.),European Union(EU),and Japan in promoting patient engagement,this study summarizes the roles and contributions of patients in the entire drug regulatory process internationally.Combining China's current progress and challenges in patient engagement,specific proposals are formulated to refine regulatory pathways and institutional systems.RESULTS&CONCLUSIONS With growing global emphasis on patient engagement as a regulatory strategy,countries or regions such as the U.S.,EU,and Japan have established clear policies,designated oversight agencies,and developed diversified pathways for patient engagement.Patients contribute to regulatory processes through advisory meetings,direct decision-making roles,and leveraging lived experiences and expertise to optimize drug evaluation and monitoring.In contrast,China's patient engagement remains primarily limited to clinical value-oriented drug development,lacking formal policy guidance.It is recommended that China,based on its existing policy system,further strengthen the construction of a safeguard system for patient engagement,improve the capacity building and pathway models for patient participation in pharmaceutical regulation,and promote the continuous development of patient engagement in pharmaceutical regulation in our country.

Objective To analyze the awareness of retinopathy of prematurity (ROP) among medical workers in Neonatal Intensive Care Unit (NICU) and obstetrical department, and parents of premature infants in Xiangyang area of Hubei Province. Methods This study used a questionnaire survey to select 115 parents of premature infants who underwent ROP screening from October 2020 to October 2022 and 85 neonatologists and obstetricians in NICU and obstetrics departments of Xiangyang Central Hospital in Hubei Province. The basic situation of premature infants was recorded, and the questionnaires were used to investigate the cognitive status of parents of premature infants, neonatologists, and obstetricians on ROP-related knowledge, and the results were recorded. Results A total of 115 valid questionnaires were collected from parents. Fifty-four parents (46.96%) had heard of ROP, and 61 parents (53.04%) had never heard of ROP. Among all parents who had heard of ROP, 10 parents (18.52%) learned through online queries or friends, 41 parents (75.93%) learned through NCIU doctors, and 1 guardian learned through NCIU nurses, 1 through obstetricians, and 1 through obstetric nurses. There were significant differences in the ways parents heard about ROP (χ²=122.709, P < 0.001). A total of 95 valid questionnaires were collected from medical staff, and only 7 medical staff could correctly write the ROP screening criteria, all of whom were NICU doctors. The NICU doctors had a higher rate of informing parents of premature infants about ROP than NICU nurses, obstetricians, and obstetric nurses (P < 0.05). Conclusion Parents of premature infants who undergo ROP screening in Xiangyang, Hubei Province have a serious lack of knowledge about ROP-related knowledge, and education level is an important factor influencing parents' understanding of ROP-related knowledge. Medical staff in relevant departments should also strengthen their learning of ROP-related knowledge. NICU doctors play the most important role in promoting ROP, and the publicity of ROP-related knowledge should be strengthened.

Objective To investigate the prognostic value of N6-methyladenosine (m⁶A) modification related genes and immune infiltration in colorectal cancer (CRC) and construct a risk model for predicting outcome of patients. Methods The transcriptome data and matched clinical information of CRC patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. The prognostic value of m⁶A modification related genes and immune infiltration were investigated using the consensus clustering method and single sample gene set enrichment analysis. The weighted gene co-expression network analysis (WGCNA) was used to identify prognostic genes related with m⁶A modification and immune infiltration. Lasso regression analysis was used to construct a multi-gene risk model. The expression differences of prognostic genes identified were further validated through expression differential analysis in the Gene Expression Profiling Interactive Analysis (GEPIA) database. Finally, the Kaplan-Meier was used to evaluate the predicting performance of the model in different subgroups and external validation cohorts. Results Both the m⁶A modification and immune infiltration phenotype could effectively stratify the prognosis of CRC patients from the TCGA cohort. Most m⁶A modification related genes were significantly correlated with immune infiltration in CRC tissues. Four following prognostic genes were selected using the WGCNA method combined with Lasso regression analysis: intelectin-1, lymphocyte antigen 6 complex locus G6D, atonal homolog 1 and matrix metalloproteinase 28. In colorectal cancer tissues, the expression levels of lymphocyte antigen 6 complex locus G6D and matrix metalloproteinase 28 exhibited significant differences compared to adjacent non-cancerous tissues (P < 0.05). The risk model constructed based on the above prognostic genes can effectively identify the potential risk population with poor prognosis in different clinical subgroups of the TCGA cohort and the GEO validated cohort. Conclusion A risk model based on m⁶A modification and immune infiltration could effectively predict the clinical outcome of CRC patients, and related prognostic genes have potential to be developed as molecular targets for CRC therapy.