The development of the rare disease discipline is a crucial pathway for enhancing the diagnosis and treatment of rare diseases, cultivating specialized professionals, and fostering technological innovation. Currently, China' rare disease discipline is accelerating its development driven by both policy and demand. However, it still faces multi-dimensional challenges, including an incomplete clinical management mechanism, a shortage of interdisciplinary talents, a weak scientific research system, and limited outreach capacity. To address these challenges, this paper proposes and constructs an integrated development system with clinical diagnosis and treatment as the foundation, talent cultivation as the engine, scientific research as the support, and disciplinary outreach capacity as the extension. Specific strategies include: enhancing clinical management through artificial intelligence-assisted diagnosis systems and multidisciplinary collaboration platforms; strengthening the talent pool through textbooks, curricula, and hierarchical training mechanisms; bolstering research collaboration and translational outcomes by leveraging international data-sharing platforms, national rare disease medical centers, the State Key Laboratory of Complex Severe and Rare Diseases, and the National Key Scientific Infrastructure for Translational Medicine; and expanding grassroots outreach and public awareness through the National Rare Disease Diagnosis and Treatment Collaboration Network, the National Rare Disease Quality Control Center, and integrated media communication channels. In the future, the rare disease discipline should further deepen the integration of medicine and engineering, expand international cooperation, focus on the translational closed loop, improve the regional collaboration network, so as to build a more resilient and dynamic disciplinary ecosystem, and ultimately achieve a comprehensive improvement in the diagnosis and treatment of rare diseases.

To evaluate the application value of the Peyton four-step teaching method in the standardized training of intestinal ultrasound and compare it with traditional teaching methods, so as to provide an optimized approach for clinical ultrasound training.

OBJECTIVE To systematically evaluate risk prediction models for chemotherapy-induced myelosuppression in pediatric patients with malignant tumors， evaluate their modeling strategies， key predictors， and predictive performance， and provide evidence-based references for clinical decision-making and research. METHODS A literature search was conducted across 11 databases， including CNKI， Wanfang Data， and PubMed， for relevant studies published before April 2025. Two reviewers independently performed literature screening and data extraction， and the risk of bias and applicability of the models were evaluated using the PROBAST tool. RESULTS Ultimately， seven studies were selected， of which four were English articles and three were Chinese articles， involving 12 risk prediction models. Although model discrimination was good （AUC 0.748-0.981）， only two models underwent external validation； furthermore， calibration was inadequately reported in three studies. PROBAST indicated that all models exhibited a high risk of bias， with major issues including a predominance of retrospective designs， inadequate sample representativeness， and lack of blinding. However， in terms of applicability， all models received favorable evaluations. In terms of modeling methods， most studies employed traditional logistic regression approaches to construct models， while only a minority introduced machine learning algorithms and conducted systematic comparisons among multiple algorithms. Models developed using machine learning methods significantly outperformed those constructed with traditional statistical methods. CONCLUSIONS The existing risk prediction models for myelosuppression after chemotherapy in children with malignant tumors demonstrate potential in clinical risk early warning. However， they generally suffer from design and methodological limitations， such as a predominance of retrospective single-center designs， few events per variable， opaque handling of missing data， and inconsistent reporting of model coefficients. Future studies should adopt prospective designs， incorporate machine learning with key clinical predictors， and follow TRIPOD reporting guidelines to enhance scientific rigor and clinical utility.

ObjectiveBased on the theory of "spleen governing transportation and transformation"， this study investigates the efficacy of Atractylodis Macrocephalae Rhizoma processed with Aurantii Fructus Immaturus juice（AMR-AFI） in improving slow-transit constipation（STC）， as well as the synergistic regulatory mechanism involving the microbiota-metabolism axis， thereby elucidating the scientific basis of its processing theory. MethodsAnimals were randomly divided into the control group， model group， positive drug（mosapride） group（3 mg·kg^-1）， and low-， medium-， and high-dose groups of AMR-AFI（3.9， 7.8， 15.6 g·kg^-1）. Except for the control group， the remaining five groups were induced with STC using loperamide hydrochloride. Following modeling， interventions were administered. All groups received continuous administration for 15 d， during which fecal samples， colon tissue， and serum were collected. Constipation improvement was assessed by measuring fecal moisture content and small intestinal propulsion rate， histological morphology of colonic tissue was observed via hematoxylin-eosin（HE） staining， and the levels of interleukin（IL）-6， tumor necrosis factor（TNF）-α， and IL-2 in serum were detected using enzyme-linked immunosorbent assay（ELISA）. Furthermore， the microbial community structure in mouse feces was analyzed by 16S rRNA sequencing， while transcriptomic sequencing was employed to screen differentially expressed genes in colonic tissue， followed by gene ontology（GO） and Kyoto Encyclopedia of Genes and Genomes（KEGG） enrichment analyses. Finally， Spearman correlation analysis was conducted to explore the association between differential microbiota and differential genes. ResultsCompared with the control group， the intestinal propulsion rate and fecal moisture content in the model group were significantly decreased（P<0.01）， while serum levels of IL-6， TNF-α， and IL-2 were significantly elevated（P<0.01）. HE staining showed damage and shedding of colonic mucosal epithelial cells， along with a reduction in goblet cells in the model group. In comparison with the model group， all treatment groups improved the pathological state of the colonic mucosa to varying degrees and reduced serum levels of IL-6， TNF-α， and IL-2（P<0.01）. Among these， the high-dose group of AMR-AFI significantly increased the intestinal propulsion rate and fecal moisture content of rats（P<0.05， P<0.01）. Further transcriptomic analysis revealed that a total of 104 differentially expressed genes were identified from comparisons between the model group and the control group， as well as between the model group and the high-dose group of AMR-AFI. These genes were mainly enriched in pathways closely related to STC pathogenesis， such as arachidonic acid metabolism and aldosterone-regulated sodium reabsorption. 16S rRNA sequencing results indicated that AMR-AFI reversed the structural imbalance of the gut microbiota in model mice， increased species richness， downregulated the relative abundance of pro-inflammatory bacteria such as Parasutterella， and enriched beneficial and butyrate-producing bacteria， including Lachnospiraceae_NK4A136_group， Ruminococcaceae， and Lachnospiraceae. Spearman correlation analysis further showed that the beneficial bacteria enriched in the AMR-AFI group were negatively correlated with genes involved in the arachidonic acid metabolic pathway and positively correlated with genes in the aldosterone-regulated sodium reabsorption pathway. In contrast， pro-inflammatory bacteria in the model group exhibited the opposite correlation trends. ConclusionAMR-AFI can effectively exert synergistic therapeutic effects on STC by regulating intestinal microbiota， arachidonic acid-mediated inflammatory metabolism， and aldosterone-regulated water-salt balance pathways.

ObjectiveThis study systematically analyzed the arginine metabolic dysregulation in the rat model of heart failure （HF）， providing a modern scientific basis for elucidating the pathogenesis of HF and offering new insights for the prevention and treatment of HF with traditional Chinese medicine （TCM）. MethodsA thoracotomy was performed to ligate the left anterior descending coronary artery of rats， which induced acute myocardial ischemia and thus led to the development of post-myocardial infarction heart failure. The rats were divided into a sham surgery group and a model group， with eight rats in each group. Serum targeted metabolomics analysis was performed using ultra-performance liquid chromatography-triple quadrupole mass spectrometry （UPLC-TQ-S）， and the spatial distribution of metabolites in cardiac tissue was observed using airflow-assisted desorption electrospray ionizationmass spectrometry imaging （AFADESI-MSI）. Targets associated with HF and arginine metabolism were screened from databases including GeneCards and the Gene Expression Omnibus （GEO）， a protein-protein interaction （PPI） network was constructed， and enrichment analysis of the Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway and Gene Ontology （GO） was performed. Finally， molecular docking was conducted to verify the binding between core metabolic components and key targets， and potential TCMs were predicted based on the core pathways and targets. ResultsCompared with the sham surgery group， the levels of arginine and citrulline in the serum of model rats were significantly decreased （P<0.01）， while those of proline， ornithine， creatine， creatinine and glutamate were significantly increased （P<0.05， P<0.01）. Cardiac mass spectrometry imaging showed a decreased abundance of arginine in the local myocardial tissue. Bioinformatics analysis identified 24 core functional targets， such as the angiotensin-converting enzyme （ACE）， neuronal nitric oxide synthase （NOS1）， 5-hydroxytryptamine receptor 2A （HTR2A）， and epidermal growth factor receptor （EGFR）， and enrichment analysis indicated that these targets were significantly involved in the calcium signaling pathway， neuroactive ligand-receptor interactions， and phosphatidylinositol signaling pathway. Molecular docking confirmed strong binding activities between arginine， citrulline and HTR2A， as well as between creatine， creatinine and EGFR. Based on pathway-target prediction， potential TCM interventions， such as ginseng and magnolia， were identified. ConclusionThis study revealed characteristic arginine metabolic disorder in HF， and the core targets of HF were closely associated with the phosphatidylinositol signaling pathway. It provides a modern biological interpretation of the pathogenesis of HF in TCM from the perspectives of metabolites and signaling pathways， and offers valuable insights for targeted therapy of HF and the development of TCM.

Uveal melanoma(UM)is the most common primary intraocular malignancy in adults, characterized by high invasiveness and unique metastatic biological features. Although local treatments(such as proton beam therapy and brachytherapy)can effectively control the primary lesion, approximately 50% of patients eventually develop distant metastasis, with the liver being the primary target organ(occurring in 90% of cases). This highlights a paradigm shift in treatment focus from mere local control to systemic prevention and management. For metastatic UM(mUM), current treatment strategies encompass biomarker-guided molecular targeted therapy, immunotherapy(including Tebentafusp, vaccines, and oncolytic virus therapy), and liver-directed therapy. Focusing on the synergy between local and systemic prevention and control, this article systematically elaborates on the precision local treatment for primary UM, the decision-making pathway for systemic treatment of metastatic UM based on molecular subtyping, the integration of local and systemic therapies for liver metastases, and the translational value of nanomedicine in addressing therapeutic bottlenecks. It provides insights for optimizing clinical management of mUM and developing novel therapeutic strategies.

ObjectiveBased on the theory of "spleen governing transportation and transformation"， this study investigates the efficacy of Atractylodis Macrocephalae Rhizoma processed with Aurantii Fructus Immaturus juice（AMR-AFI） in improving slow-transit constipation（STC）， as well as the synergistic regulatory mechanism involving the microbiota-metabolism axis， thereby elucidating the scientific basis of its processing theory. MethodsAnimals were randomly divided into the control group， model group， positive drug（mosapride） group（3 mg·kg^-1）， and low-， medium-， and high-dose groups of AMR-AFI（3.9， 7.8， 15.6 g·kg^-1）. Except for the control group， the remaining five groups were induced with STC using loperamide hydrochloride. Following modeling， interventions were administered. All groups received continuous administration for 15 d， during which fecal samples， colon tissue， and serum were collected. Constipation improvement was assessed by measuring fecal moisture content and small intestinal propulsion rate， histological morphology of colonic tissue was observed via hematoxylin-eosin（HE） staining， and the levels of interleukin（IL）-6， tumor necrosis factor（TNF）-α， and IL-2 in serum were detected using enzyme-linked immunosorbent assay（ELISA）. Furthermore， the microbial community structure in mouse feces was analyzed by 16S rRNA sequencing， while transcriptomic sequencing was employed to screen differentially expressed genes in colonic tissue， followed by gene ontology（GO） and Kyoto Encyclopedia of Genes and Genomes（KEGG） enrichment analyses. Finally， Spearman correlation analysis was conducted to explore the association between differential microbiota and differential genes. ResultsCompared with the control group， the intestinal propulsion rate and fecal moisture content in the model group were significantly decreased（P<0.01）， while serum levels of IL-6， TNF-α， and IL-2 were significantly elevated（P<0.01）. HE staining showed damage and shedding of colonic mucosal epithelial cells， along with a reduction in goblet cells in the model group. In comparison with the model group， all treatment groups improved the pathological state of the colonic mucosa to varying degrees and reduced serum levels of IL-6， TNF-α， and IL-2（P<0.01）. Among these， the high-dose group of AMR-AFI significantly increased the intestinal propulsion rate and fecal moisture content of rats（P<0.05， P<0.01）. Further transcriptomic analysis revealed that a total of 104 differentially expressed genes were identified from comparisons between the model group and the control group， as well as between the model group and the high-dose group of AMR-AFI. These genes were mainly enriched in pathways closely related to STC pathogenesis， such as arachidonic acid metabolism and aldosterone-regulated sodium reabsorption. 16S rRNA sequencing results indicated that AMR-AFI reversed the structural imbalance of the gut microbiota in model mice， increased species richness， downregulated the relative abundance of pro-inflammatory bacteria such as Parasutterella， and enriched beneficial and butyrate-producing bacteria， including Lachnospiraceae_NK4A136_group， Ruminococcaceae， and Lachnospiraceae. Spearman correlation analysis further showed that the beneficial bacteria enriched in the AMR-AFI group were negatively correlated with genes involved in the arachidonic acid metabolic pathway and positively correlated with genes in the aldosterone-regulated sodium reabsorption pathway. In contrast， pro-inflammatory bacteria in the model group exhibited the opposite correlation trends. ConclusionAMR-AFI can effectively exert synergistic therapeutic effects on STC by regulating intestinal microbiota， arachidonic acid-mediated inflammatory metabolism， and aldosterone-regulated water-salt balance pathways.

ObjectiveThis study systematically analyzed the arginine metabolic dysregulation in the rat model of heart failure （HF）， providing a modern scientific basis for elucidating the pathogenesis of HF and offering new insights for the prevention and treatment of HF with traditional Chinese medicine （TCM）. MethodsA thoracotomy was performed to ligate the left anterior descending coronary artery of rats， which induced acute myocardial ischemia and thus led to the development of post-myocardial infarction heart failure. The rats were divided into a sham surgery group and a model group， with eight rats in each group. Serum targeted metabolomics analysis was performed using ultra-performance liquid chromatography-triple quadrupole mass spectrometry （UPLC-TQ-S）， and the spatial distribution of metabolites in cardiac tissue was observed using airflow-assisted desorption electrospray ionizationmass spectrometry imaging （AFADESI-MSI）. Targets associated with HF and arginine metabolism were screened from databases including GeneCards and the Gene Expression Omnibus （GEO）， a protein-protein interaction （PPI） network was constructed， and enrichment analysis of the Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway and Gene Ontology （GO） was performed. Finally， molecular docking was conducted to verify the binding between core metabolic components and key targets， and potential TCMs were predicted based on the core pathways and targets. ResultsCompared with the sham surgery group， the levels of arginine and citrulline in the serum of model rats were significantly decreased （P<0.01）， while those of proline， ornithine， creatine， creatinine and glutamate were significantly increased （P<0.05， P<0.01）. Cardiac mass spectrometry imaging showed a decreased abundance of arginine in the local myocardial tissue. Bioinformatics analysis identified 24 core functional targets， such as the angiotensin-converting enzyme （ACE）， neuronal nitric oxide synthase （NOS1）， 5-hydroxytryptamine receptor 2A （HTR2A）， and epidermal growth factor receptor （EGFR）， and enrichment analysis indicated that these targets were significantly involved in the calcium signaling pathway， neuroactive ligand-receptor interactions， and phosphatidylinositol signaling pathway. Molecular docking confirmed strong binding activities between arginine， citrulline and HTR2A， as well as between creatine， creatinine and EGFR. Based on pathway-target prediction， potential TCM interventions， such as ginseng and magnolia， were identified. ConclusionThis study revealed characteristic arginine metabolic disorder in HF， and the core targets of HF were closely associated with the phosphatidylinositol signaling pathway. It provides a modern biological interpretation of the pathogenesis of HF in TCM from the perspectives of metabolites and signaling pathways， and offers valuable insights for targeted therapy of HF and the development of TCM.

Objective: To develop a prediction model for mild cognitive impairment (MCI) risk among the elderly, so as to provide a tool for MCI early screening. Methods : From July 2022 to September 2024, a multi-stage stratified random cluster sampling method was used to recruit permanent residents aged ≥65 years from the Xinjiang Uygur Autonomous Region as study participants. Data on sociodemographic characteristics, nutritional status, body composition indices, bone mineral density, and handgrip strength were collected through questionnaires and physical examinations. Sarcopenia was defined based on appendicular skeletal muscle index and handgrip strength. MCI was assessed using the Mini-Mental State Examination, with adjustments for educational level. Participants were randomly divided into a training set and a validation set in a 7∶3 ratio. LASSO regression and multivariable logistic regression models were employed to screen for predictors and construct an MCI risk prediction model. The predictive performance of the model was evaluated using receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Results: A total of 1 641 participants were surveyed, including 755 males (46.01%) and 886 females (53.99%). The majority of participants were aged 65-<75 years, comprising 1 154 individuals (70.32%). MCI was detected in 517 participants, corresponding to a detection rate of 31.51%. Resultsfrom LASSO regression and multivariate logistic regression analysis showed that residence (rural, OR = 2.323, 95% CI: 1.682-3.210), age (75-<85 years, OR = 1.405, 95% CI: 1.019-1.937; ≥85 years, OR = 3.655, 95% CI: 1.696-7.875), educational level (primary school, OR = 0.341, 95% CI: 0.247-0.472; junior high school, OR = 0.255, 95% CI: 0.160-0.408; high school, OR = 0.286, 95% CI: 0.154-0.531; bachelor's degree or above, OR = 0.120, 95% CI: 0.041-0.351), history of alcohol consumption (yes, OR = 3.216, 95% CI: 2.164-4.779), risk of malnutrition (yes, OR = 1.464, 95% CI: 1.064-2.014), sarcopenia (yes, OR = 3.197, 95% CI: 2.332-4.385), and waist-to-hip ratio (abnormal, OR = 1.540, 95% CI: 1.159-2.048) were identified as predictive factors for MCI among the elderly. In the training set, the area under the ROC curve, sensitivity, and specificity were 0.788, 0.719, and 0.712, respectively. In the validation set, the corresponding values were 0.784, 0.913, and 0.542, respectively. DCA demonstrated that the model provided a higher clinical net benefit for predicting MCI risk when the risk threshold probability ranged from 0.124 to 0.764. Conclusion The prediction model developed in this study demonstrates good discriminative ability and clinical utility, indicating its substantial value for predicting the MCI risk among the elderly.

The common marmoset (Callithrix jacchus), a primate species belonging to the genus Callithrix in the family Callitrichidae, has multiple advantages including small body size, short reproductive cycle, early sexual maturity, 1-3 offspring per litter, and ease of experimental manipulation. It also exhibits behavioral characteristics such as vocal communication and strict monogamy. Common marmosets present unique advantages in neuroscience and brain disease research and are widely used in biomedical fields including neuroscience, gene editing, and ethology. Experimental common marmosets (hereinafter referred to as "experimental marmosets") require management of breeding and use to ensure traceable pedigrees and prevention of inbreeding. Existing management systems developed for rodents or Macaca often cannot effectively meet the practical needs of experimental marmoset management in key aspects such as pedigree tracking and inbreeding warning. To address this issue, the Laboratory Animal Center of the Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences (hereinafter referred to as "the Center") designed and developed a second-generation information management system for marmosets in 2021 based on its first-generation information management system, and the second-generation system was launched in 2023. This second-generation system adopts a B/S architecture, is modular, and features front-end and back-end separation. It uses mainstream technical frameworks, including Spring Boot, MySQL, and Redis, and integrates 16 functional modules such as basic information, pedigree tree, breeding and experimental selection database, microchip identification management, and ethical supervision. Compared with the first-generation system, the second-generation system optimizes the pedigree tree and basic information modules. It also adds new functions, including purpose-based database partitioning, animal status tracking, abnormal alerts, automatic microchip identification task generation, inbreeding warning, ethical document upload and review, and record management. Together, these form a systematic and refined management and service system covering the entire breeding and experimental use of experimental marmosets. From 2023 to 2025, the practical application at the center shows that it has significantly improved the management efficiency and service level of the experimental marmoset management unit, and can provide a reference for the development of information management systems in other institutions using marmosets.