ObjectiveTo elucidate the critical role of rehabilitation medical records (including electronic records) in rehabilitation medicine's clinical practice and management, comprehensively analyzed the structure, core content and data standards of rehabilitation medical records, to develop a standardized medical record data architecture and core dataset suitable for rehabilitation medicine and to explore the application of rehabilitation data in performance evaluation and payment. MethodsBased on the regulatory documents Basic Specifications for Medical Record Writing and Basic Specifications for Electronic Medical Records (Trial) issued by National Health Commission of China, and referencing the World Health Organization (WHO) Family of International Classifications (WHO-FICs) classifications, International Classification of Diseases (ICD-10/ICD-11), International Classification of Functioning, Disability and Health (ICF), and International Classification of Health Interventions (ICHI Beta-3), this study constructed the data architecture, core content and data standards for rehabilitation medical records. Furthermore, it explored the application of rehabilitation record summary sheets (home page) data in rehabilitation medical statistics and payment methods, including Diagnosis-related Groups (DRG), Diagnosis-Intervention Packet (DIP) and Case Mix Index. ResultsThis study proposed a systematic standard framework for rehabilitation medical records, covering key components such as patient demographics, rehabilitation diagnosis, functional assessment, rehabilitation treatment prescriptions, progress evaluations and discharge summaries. The research analyzed the systematic application methods and data standards of ICD-10/ICD-11, ICF and ICHI Beta-3 in the fields of medical record terminology, coding and assessment. Constructing a standardized data structure and data standards for rehabilitation medical records can significantly improve the quality of data reporting based on the medical record summary sheet, thereby enhancing the quality control of rehabilitation services, effectively supporting the optimization of rehabilitation medical insurance payment mechanisms, and contributing to the establishment of rehabilitation medical performance evaluation and payment based on DRG and DIP. ConclusionStructured rehabilitation records and data standardization are crucial tools for quality control in rehabilitation. Systematically applying the three reference classifications of the WHO-FICs, and aligning with national medical record and electronic health record specifications, facilitate the development of a standardized rehabilitation record architecture and core dataset. Standardizing rehabilitation care pathways based on the ICF methodology, and developing ICF- and ICD-11-based rehabilitation assessment tools, auxiliary diagnostic and therapeutic systems, and supporting terminology and coding systems, can effectively enhance the quality of rehabilitation records and enable interoperability and sharing of rehabilitation data with other medical data, ultimately improving the quality and safety of rehabilitation services.

Neuroscience is a significant frontier discipline within the natural sciences and has become an important interdisciplinary frontier scientific field. Brain is one of the most complex organs in the human body, and its structural and functional analysis is considered the “ultimate frontier” of human self-awareness and exploration of nature. Driven by the strategic layout of “China Brain Project”, Chinese scientists have conducted systematic research focusing on “understanding the brain, simulating the brain, and protecting the brain”. They have made breakthrough progress in areas such as the principles of brain cognition, mechanisms and interventions for brain diseases, brain-like computation, and applications of brain-machine intelligence technology, aiming to enhance brain health through biomedical technology and improve the quality of human life. Due to limited understanding and comprehension of neuroscience, there are still many important unresolved issues in the field of neuroscience, resulting in a lack of effective measures to prevent and protect brain health. Therefore, in addition to actively developing new generation drugs, exploring non pharmacological treatment strategies with better health benefits and higher safety is particularly important. Epidemiological data shows that, exercise is not only an indispensable part of daily life but also an important non-pharmacological approach for protecting brain health and preventing neurodegenerative diseases, forming an emerging research field known as motor neuroscience. Basic research in motor neuroscience primarily focuses on analyzing the dynamic coding mechanisms of neural circuits involved in motor control, breakthroughs in motor neuroscience research depend on the construction of dynamic monitoring systems across temporal and spatial scales. Therefore, high spatiotemporal resolution detection of movement processes and movement-induced changes in brain structure and neural activity signals is an important technical foundation for conducting motor neuroscience research and has developed a set of tools based on traditional neuroscience methods combined with novel motor behavior decoding technologies, providing an innovative technical platform for motor neuroscience research. The protective effect of exercise in neurodegenerative diseases provides broad application prospects for its clinical translation. Applied research in motor neuroscience centers on deciphering the regulatory networks of neuroprotective molecules mediated by exercise. From the perspectives of exercise promoting neurogenesis and regeneration, enhancing synaptic plasticity, modulating neuronal functional activity, and remodeling the molecular homeostasis of the neuronal microenvironment, it aims to improve cognitive function and reduce the incidence of Parkinson’s disease and Alzheimer’s disease. This has also advanced research into the molecular regulatory networks mediating exercise-induced neuroprotection and facilitated the clinical application and promotion of exercise rehabilitation strategies. Multidimensional analysis of exercise-regulated neural plasticity is the theoretical basis for elucidating the brain-protective mechanisms mediated by exercise and developing intervention strategies for neurological diseases. Thus,real-time analysis of different neural signals during active exercise is needed to study the health effects of exercise throughout the entire life cycle and enhance lifelong sports awareness. Therefore, this article will systematically summarize the innovative technological developments in motor neuroscience research, review the mechanisms of neural plasticity that exercise utilizes to protect the brain, and explore the role of exercise in the prevention and treatment of major neurodegenerative diseases. This aims to provide new ideas for future theoretical innovations and clinical applications in the field of exercise-induced brain protection.

Objective: To investigate the iodine nutrition status of children in water borne iodine excess areas in Hebei Province, so as to provide references for scientific prevention and control of water borne iodine excess hazards. Methods: From March to September each year during 2018 to 2023, a cross sectional survey was conducted in 39 water borne iodine excess counties (measured in 2017) from 5 cities (Cangzhou, Hengshui, Xingtai, Handan and Langfang) in Hebei Province. The survey included the detection of iodine content in residents drinking water, the measurement of thyroid volume in children aged 6-12, the detection of salt iodine and urinary iodine. The iodine nutrition status and water iodine distribution of 6-12 year-old children were evaluated from different perspectives such as years, gender, and age. Kruskal-Wallis H- test, Mann-Whitney U test and Chi square test were used for group comparison. Results: A total of 38 755 children were surveyed from 2018 to 2023, and 1 270 drinking water samples were tested across the province. The mass volume concentration of iodine in water showed a decreasing trend over the years ( Z= -30.87, P <0.01). Among 38 470 salt samples monitored from children s home, 24 790 were not non iodized salt, with a non iodized salt rate of 64.44%. A total of 31 989 urine samples were collected from children aged 8-10 years, with the median urine iodine was 245.94 μg/L. Comparing the results of urinary iodine in children from different years, the median urinary iodine from 2018 to 2023 were 328.0, 339.3, 267.8, 279.1, 291.3, 186.5 μg/L, respectively, with statistically significant differences ( H= 4 138.40 , P <0.01). Further pairwise comparisons showed that the median urinary iodine of children in 2023 was lower than in all other years ( Z =-51.59 to -11.41, all P <0.01). Among children aged 6-12 years, 1 150 cases of goiter were detected and the rate of goiter was 3.0%; and the goiter rates in boys and girls were 2.8% and 3.1%, with no significant difference between the sexes ( χ 2= 2.76, P >0.05). There were significant differences in the rate of goiter among different years and ages ( χ 2=324.02, 191.61, both P <0.05). Conclusions With the progress of water reform in water borne iodine excess areas of Hebei Province, children s iodine nutrition has reduced from excessive state to suitable state. It is necessary to continue to expand the coverage of water based iodine reduction projects, and strengthen the monitoring of iodine nutrition status of key populations in water borne iodine excess areas.

ObjectiveTo evaluate the efficacy and safety of Xiaoji Hufei Formula in protecting children with close contact exposure to influenza， and to provide reference and evidence-based support for better clinical prevention and treatment of influenza in children. MethodsA multicenter， prospective， non-randomized， parallel， controlled trial was conducted from October 2021 to May 2022 in five hospitals， including Dongfang Hospital of Beijing University of Chinese Medicine. Confirmed influenza cases and influenza-like illness （ILI） cases were collected， and eligible children with close contact exposure to these cases were recruited in the outpatient clinics. According to whether the enrolled close contacts were willing to take Xiaoji Hufei formula for influenza prevention， they were assigned to the observation group （108 cases） or the control group （108 cases）. Follow-up visits were conducted on days 7 and 14 after enrollment. The primary outcomes were the incidence of ILI and the rate of laboratory-confirmed influenza. Secondary outcomes included traditional Chinese medicine （TCM） symptom score scale for influenza， influenza-related emergency （outpatient） visit rate， influenza hospitalization rate， and time to onset after exposure to influenza cases. ResultsA total of 216 participants were enrolled， with 108 in the observation group and 108 in the control group. Primary outcomes： （1） Incidence of ILI： The incidence was 12.0% （13/108） in the observation group and 23.1% （25/108） in the control group， with the observation group showing a significantly lower incidence （χ²=4.6， P<0.05）. （2） Influenza confirmation rate： 3.7% （4/108） in the observation group and 4.6% （5/108） in the control group， with no statistically significant difference. Secondary outcomes： （1） TCM symptom score scale： after onset， nasal congestion and runny nose scores differed significantly between the two groups （P<0.05）， while other symptoms such as fever， sore throat， and cough showed no significant differences. （2） Influenza-related emergency （outpatient） visit rate： 84.6% （11 cases） in the observation group and 96.0% （24 cases） in the control group， with no significant difference. （3） Time to onset after exposure： The median onset time after exposure to index patients was 7 days in the observation group and 4 days in the control group， with a statistically significant difference （P<0.05）. ConclusionIn previously healthy children exposed to infectious influenza cases under unprotected conditions， Xiaoji Hufei formula prophylaxis significantly reduced the incidence of ILI. Xiaoji Hufei Formula can be recommended as a specific preventive prescription for influenza in children.

ObjectiveTo evaluate the efficacy and safety of Xiaoji Hufei Formula in protecting children with close contact exposure to influenza， and to provide reference and evidence-based support for better clinical prevention and treatment of influenza in children. MethodsA multicenter， prospective， non-randomized， parallel， controlled trial was conducted from October 2021 to May 2022 in five hospitals， including Dongfang Hospital of Beijing University of Chinese Medicine. Confirmed influenza cases and influenza-like illness （ILI） cases were collected， and eligible children with close contact exposure to these cases were recruited in the outpatient clinics. According to whether the enrolled close contacts were willing to take Xiaoji Hufei formula for influenza prevention， they were assigned to the observation group （108 cases） or the control group （108 cases）. Follow-up visits were conducted on days 7 and 14 after enrollment. The primary outcomes were the incidence of ILI and the rate of laboratory-confirmed influenza. Secondary outcomes included traditional Chinese medicine （TCM） symptom score scale for influenza， influenza-related emergency （outpatient） visit rate， influenza hospitalization rate， and time to onset after exposure to influenza cases. ResultsA total of 216 participants were enrolled， with 108 in the observation group and 108 in the control group. Primary outcomes： （1） Incidence of ILI： The incidence was 12.0% （13/108） in the observation group and 23.1% （25/108） in the control group， with the observation group showing a significantly lower incidence （χ²=4.6， P<0.05）. （2） Influenza confirmation rate： 3.7% （4/108） in the observation group and 4.6% （5/108） in the control group， with no statistically significant difference. Secondary outcomes： （1） TCM symptom score scale： after onset， nasal congestion and runny nose scores differed significantly between the two groups （P<0.05）， while other symptoms such as fever， sore throat， and cough showed no significant differences. （2） Influenza-related emergency （outpatient） visit rate： 84.6% （11 cases） in the observation group and 96.0% （24 cases） in the control group， with no significant difference. （3） Time to onset after exposure： The median onset time after exposure to index patients was 7 days in the observation group and 4 days in the control group， with a statistically significant difference （P<0.05）. ConclusionIn previously healthy children exposed to infectious influenza cases under unprotected conditions， Xiaoji Hufei formula prophylaxis significantly reduced the incidence of ILI. Xiaoji Hufei Formula can be recommended as a specific preventive prescription for influenza in children.

Implementation Science is an interdisciplinary field dedicated to systematically studying how to effectively translate evidence-based research findings into practical application and implementation. In the health-related context, it focuses on enhancing the efficiency and quality of healthcare services, thereby facilitating the transition from scientific evidence to real-world practice. This article elaborates on Theories, Models, and Frameworks (TMF) within health-related Implementation Science, clarifying their basic concepts and classifications, and discussing their roles in guiding implementation processes. Furthermore, it reviews and prospects current research from three aspects: the constituent elements of TMF, their practical applications, and future directions. Five representative frameworks are emphasized, including the Consolidated Framework for Implementation Research (CFIR), the Practical Robust Implementation and Sustainability Model (PRISM), the Exploration, Preparation, Implementation, Sustainment (EPIS)framework, the Behavior Change Wheel (BCW), and the Normalization Process Theory (NPT). Additionally, resources such as the Dissemination & Implementation Models Webtool and the T-CaST tool are introduced to assist researchers in selecting appropriate TMFs based on project-specific needs.

Objective To establish a high performance liquid chromatography-tandem mass spectrometry(HPLC-MS/MS)for the simultaneous determination of gefitinib,erlotinib,nillotinib and imatinib plasma concentrations and analyze the results.Methods The plasma samples were treated with acetonitrile precipitation and separated by Diamonsil C18 column(150 mm ×4.6 mm,3.5 μm)with mobile phase of 0.1％formic acid water(A)-0.1％formic acid acetonitrile(B).The flow rate of gradient elution was 0.7 mL·min-1,and the column temperature was 40 ℃ and the injection volume was 3 μL.Using arotinib as the internal standard,the scanning was carried out by using electrospray ionization source in positive ionization mode with multi-reaction monitoring.The specificity,standard curve,lower limit of quantitation,precision,accuracy,recovery rate,matrix effect and stability of the method were investigated.The concentrations of imatinib and erlotinib in 20 patients with chronic myelogenous leukemia(CML)and gefitinib and erlotinib in 3 patients with non-small cell lung cancer were measured.Results The standard curves of the four drugs were as follows,gefitinib:y=2.536 × 10-3x+9.362 × 10-3(linear range 20-2 000 ng·mL-1,R2=0.996 6);erlotinib:y=3.575× 10-3x+7.406 × 10-3(linear range 50-5 000 ng·mL-1,R2=0.994 9);nilotinib:y=1.945 x 10-3x+0.015 643(linear range 50-5 000 ng·mL-1,R2=0.990 6);imatinib:y=4.56 x 10-3x+0.010 451(linear range 100～104 ng·mL-1,R2=0.9963).RSD of intra-day and inter-day were less than 10％,and the accuracy ranged from 90％to 110％,and the recovery rates were 91.35％to 98.93％(RSD＜10％);the matrix effect ranged from 91.64％to 107.50％(RSD＜10％).Determination of 23 patients showed that the blood concentration of nilotinib ranged from 623.76 to 2 934.13 ng·mL-1,and the blood concentration of imatinib ranged from 757.77 to 2 637.71 ng·mL-1,and the blood concentration of gefitinib ranged from 214.76 to 387.40 ng·mL-1.The serum concentration of erlotinib was 569.57 ng·mL-1.Conclusion The method of this research is simple,fast,sensitive and dedicated,which can be monitored by the concentration of clinical blood.

ObjectiveExisting artificial vision devices can be divided into two types: implanted devices and extracorporeal devices, both of which have some disadvantages. The former requires surgical implantation, which may lead to irreversible trauma, while the latter has some defects such as relatively simple instructions, limited application scenarios and relying too much on the judgment of artificial intelligence (AI) to provide enough security. Here we propose a system that has voice interaction and can convert surrounding environment information into tactile commands on head and neck. Compared with existing extracorporeal devices, our device can provide a larger capacity of information and has advantages such as lower cost, lower risk, suitable for a variety of life and work scenarios. MethodsWith the latest remote wireless communication and chip technologies, microelectronic devices, cameras and sensors worn by the user, as well as the huge database and computing power in the cloud, the backend staff can get a full insight into the scenario, environmental parameters and status of the user remotely (for example, across the city) in real time. In the meanwhile, by comparing the cloud database and in-memory database and with the help of AI-assisted recognition and manual analysis, they can quickly develop the most reasonable action plan and send instructions to the user. In addition, the backend staff can provide humanistic care and emotional sustenance through voice dialogs. ResultsThis study originally proposes the concept of “remote virtual companion” and demonstrates the related hardware and software as well as test results. The system can not only achieve basic guide functions, for example, helping a person with visual impairment to shop in supermarkets, find seats at cafes, walk on the streets, construct complex puzzles, and play cards, but also can meet the demand for fast-paced daily tasks such as cycling. ConclusionExperimental results show that this “remote virtual companion” is applicable for various scenarios and demands. It can help blind people with their travels, shopping and entertainment, or accompany the elderlies with their trips, wilderness explorations, and travels.

Objective To summarize the epidemiological and clinical features of infectious diseases of the central nervous system(CNS)by a single-center analysis.Methods A retrospective analysis was conducted on the data of 1247 cases of CNS infectious diseases diagnosed and treated in the First Medical Center of PLA General Hospital from 2001 to 2020.Results The data for this group of CNS infectious diseases by disease type in descending order of number of cases were viruses 743(59.6％),Mycobacterium tuberculosis 249(20.0％),other bacteria 150(12.0％),fungi 68(5.5％),parasites 18(1.4％),Treponema pallidum 18(1.4％)and rickettsia 1(0.1％).The number of cases increased by 177 cases(33.1％)in the latter 10 years compared to the previous 10 years(P<0.05).No significant difference in seasonal distribution pattern of data between disease types(P>0.05).Male to female ratio is 1.87︰1,mostly under 60 years of age.Viruses are more likely to infect students,most often at university/college level and above,farmers are overrepresented among bacteria and Mycobacterium tuberculosis,and more infections of Treponema pallidum in workers.CNS infectious diseases are characterized by fever,headache and signs of meningeal irritation,with the adductor nerve being the more commonly involved cranial nerve.Matagenomic next-generation sequencing improves clinical diagnostic capabilities.The median hospital days for CNS infectious diseases are 18.00(11.00,27.00)and median hospital costs are ￥29,500(￥16,000,￥59,200).The mortality rate from CNS infectious diseases is 1.6％.Conclusions The incidence of CNS infectious diseases is increasing last ten years,with complex clinical presentation,severe symptoms and poor prognosis.Early and accurate diagnosis and standardized clinical treatment can significantly reduce the morbidity and mortality rate and ease the burden of disease.

Objective To build the early predictive model for chronic kidney disease(CKD)in hypertension and diabetes patients in the community.Methods The CKD patients were recruited from 4 health care centers in 4 urban areas in Kunming.The control group was residents without hypertension and diabetes(n = 1267).The disease group was residents with hypertension and/or diabetes(n = 566).The questionnaire survey,physical examination,laboratory testing,and 5 SNPs gene types in the PVT1 gene.The risk factors,which were filtered with logistics regression,were used to build predictive models.Four machine learning algorithms were built:support vector machine(SVM),random forest(RF),Na?ve Bayes(NB),and artificial neural network(ANN)models.Results Thirteen indicators included in the final diagnostic model:age,disease type,ethnicity,blood urea nitrogen,creatinine,eGFR from MDRD,ACR,eGFR from EPI2009,PAM13 score,sleep quality survey,staying-up late,PVT1 SNP rs11993333 and rs2720659.The accuracy,specificity,Kappa value,AUC of ROC,and PRC of ANN are greater than those of the other 3 models.The sensitivity of RF is the highest among 4 types of machine learning.Conclusions The ANN predictive model has a good ability of efficiency and classification to predict CKD with hypertension and/or diabetes patients in the community.