Objective To review and summarize the latest development of the therapy for the Duchenne muscular dystrophy (DMD). Methods The recently-published articles related to the therapies for DMD were extensively reviewed and briefly summarized. Results The therapeutic approaches for DMD included the gene therapy, the cell therapy, and the pharmacological therapy.The gene therapy and the cell therapy were focused on the treatment for the cause of DMD by the delivery of the missing gene, the modification of the mutated gene, and the transfer of the normal cells including the stem cells, while the pharmacological therapy dealt with the downstream events caused by the dystrophin gene defect, slowed down the pathologic progress of DMD, and improved the DMD patient's life quality and life span, by medication and other factor treatments. Conclusion There is still no cure for DMD because of various difficulties in replacing or repairing the defected gene and of the multifaceted nature of the severe symptoms. Therefore, it is imperative for us to find out a more effective treatment that can solve these problems.

This paper introduces the construction,function and application of the system of mediacl information virtual rerence desk based on ASP.NET consists of FAQ,E-mail and real-time service.

OBJECTIVE: To explore clinical rules based on the big data of the emergency department of the Second Affiliated Hospital of Guangzhou Medical University, and to establish an integrated platform for clinical research in emergency, which was finally applied to clinical practice. METHODS: Based on the hospital information system (HIS), laboratory information system (LIS), emergency specialty system, picture archiving and communication systems (PACS) and electronic medical record system of the Second Affiliated Hospital of Guangzhou Medical University, the structural and unstructured information of patients in the emergency department from March 2019 to April 2022 was extracted. By means of extraction and fusion, normalization and desensitization quality control, the database was established. In addition, data were extracted from the database for adult patients with pre screening triage level III and below who underwent emergency visits from March 2019 to April 2022, such as demographic characteristics, vital signs during pre screening triage, diagnosis and treatment characteristics, diagnosis and grading, time indicators, and outcome indicators, independent risk factors for poor prognosis in patients were analyzed. RESULTS: (1) The data of 338 681 patients in the emergency department of the Second Affiliated Hospital of Guangzhou Medical University from March 2019 to April 2022 were extracted, including 15 modules, such as demographic information, triage information, visit information, green pass and rescue information, diagnosis information, medical record information, laboratory examination overview, laboratory information, examination information, microbiological information, medication information, treatment information, hospitalization information, chest pain management and stroke management. The database ensured data visualization and operability. (2) Total 140 868 patients with pre-examination and triage level III and below were recruited from the emergency department database. The gender, age, type of admission to the hospital, pulse, blood pressure, Glasgow coma scale (GCS) and other indicators of the patients were included. Taking emergency admission to operating room, emergency admission to intervention room, emergency admission to intensive care unit (ICU) or emergency death as poor prognosis, the poor prognosis prediction model for patients with pre-examination and triage level III and below was constructed. The receiver operator characteristic curve and forest map results showed that the model had good predictive efficiency and could be used in clinical practice to reduce the risk of insufficient emergency pre-examination and triage. CONCLUSIONS The establishment of high-quality clinical database based on big data in emergency department is conducive to mining the clinical value of big data, assisting clinical decision-making, and improving the quality of clinical diagnosis and treatment.
Adult ; Humans ; Big Data ; Emergency Service, Hospital ; Triage/methods* ; Intensive Care Units ; Hospitalization ; Retrospective Studies