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Objective:To construct a multi-dimensional surgical equipment management and control platform based on artificial intelligence and Internet of Things(AIoT)to assist with the refinement and intelligent management medical equipment in hospital operating rooms.Methods:A multi-dimensional surgical equipment control platform based on AIoT was established by integrating the Internet of Things(IoT),big data analysis,indoor positioning technology,artificial intelligence(AI)technology and other technologies to collect real-time process data of surgical equipment such as endoscopy and electrosurgical,and to open up the relationships among information systems relating to surgical equipment,such as hospital information system(HIS),laboratory information system(LIS),radiology information system(RIS)and operation anesthesia management system(OAMS),so as to provide technical support for efficiency analysis,benefit analysis and assets management of surgical equipment.The platform was composed of 3 layers:data extraction layer,data engine layer and AI data analysis layer,including 4 functional modules:automatic data acquisition,deep data fusion,data mining and analysis and data visualization.Results:This platform was launched in Shanghai Municipal Hospital of Traditional Chinese Medicine in June 2022,and had realized achieving intelligent daily management such as indoor positioning of operating room equipment,one click inventory.A set of performance analysis method based on IoT and integrated with information systems was established to automatically count the utilization efficiency and cost-effectiveness of key surgical equipment to realize intelligent service,intelligent management,and digital operation.Conclusion:The construction and application of this platform improved the efficiency of medical equipment in operating rooms,reduced the cost and increased the efficiency,assisted in the refinement and intelligent management of hospital surgical equipment,and provided data support for scientific decision-making of hospital managers.
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Based on the analysis of the network layout and functional structure of the central monitoring system,the daily maintenance strategy and common fault maintenance methods were discussed.In terms of function structure,the central monitoring system of inpatient ward was divided into four modules:network architecture,monitoring terminal,central monitoring and data management,which realized the functions of monitoring patients'vital signs,data transmission display,analysis and alarm.In the event of failure of equipment,the source of structural components was analyzed based on the fault phenomenon,and the failure handling was carried out by one by one.In the process of dealing with network faults,the signals before and after the switch were detected and analyzed according to the fault scope.When abnormal results of physiological parameters were found,the factors such as human operation,patient cooperation,and equipment hardware and software failures were considered at the same time.The cause of the failure was eliminated according to the results of the observation and test;the equipment returned to normal service after the failure.Medical personnel and equipment engineers should be familiar with the network layout of the central monitoring system,carry out routine maintenance,carefully make troubleshoot faults in maintenance and standardize operation and constantly improve the operation quality of the central monitoring system.
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Objective To explore the effects of different acupoints,different target organs,and different interventions on acupoint efficacy based on ACU&MOX-DATA platform;To illustrate and visualize whether the above factors have the characteristics of"specific effect"or"common effect"of acupoint efficacy.Methods The multi-source heterogeneous data were integrated from the original omics data and public omics data.After standardization,differential gene analysis,disease pathology network analysis,and enrichment analysis were performed using Batch Search and Stimulation Mode modules in ACU&MOX-DATA platform under the conditions of different acupoints,different target organs,and different interventions.Results Under the same disease state and the same intervention,there were differences in effects among different acupoints;under the same disease state,the same acupoint and intervention,the responses produced by different target organs were not completely consistent;under the same disease state and acupoint,there were differences in effects among different intervention measures.Conclusion Based on the analysis of ACU&MOX-DATA platform,it is preliminary clear that acupoints,target organs,and interventions are the key factors affecting acupoint efficacy.Meanwhile,the above results have indicated that there are specific or common regulatory characteristics of acupoint efficacy.Applying ACU&MOX-DATA platform to analyze and visualize the critical scientific problems in the field of acupuncture and moxibustion can provide references for deepening acupoint cognition,guiding clinical acupoint selection,and improving clinical efficacy.
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Data analysis models may assist the transmission of traditional Chinese medicine （TCM） experience and clinical diagnosis and treatment， and the possibility of constructing a “data-knowledge” dual-drive model was explored by taking gastric precancerous state as an example. Data-driven is to make clinical decisions around data analysis， and its syndrome-differentiation decision-making research relies on hidden structural models and partially observable Markov decision-making processes to identify the etiology of diseases， syndrome elements， evolution of pathogenesis， and syndrome differentiation protocols； knowledge-driven is to make use of data and information to promote decision-making and action processes， and its syndrome-differentiation decision-making research relies on convolutional neural networks to improve the accuracy of local disease identification and syndrome differentiation. The “data-knowledge” dual-driven model can make up for the shortcomings of single-drive numerical simulation accuracy， and achieve a balance between local disease identification and macroscopic syndrome differentiation. On the basis of previous research， we explored the construction method of diagnostic assisted decision-making platform for gastric precancerous state， and believed that the diagnostic and decision-making ability of doctors can be extended through the assistance of machines and algorithms. Meanwhile， the related research methods were integrated and the core features of gastric precancerous state based on TCM syndrome differentiation and endoscopic pathology diagnosis and prediction were obtained， and the elements of endoscopic pathology recognition based on TCM syndrome differentiation were explored， so as to provide ideas for the in-depth research and innovative application of cutting-edge data analysis technology in the field of intelligent TCM syndrome differentiation.
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Objective:To discuss and analyze the current situation of the application and approval of new Chinese medicine in China; To provide a reference for the research and development of new Chinese medicines in the future.Methods:The drug registration data were retrieved from Xanda database from January 1, 2016 to December 31, 2022, and the information of new approval and application of new Chinese medicines during this periods was systematically organized from the aspects of the number of registered varieties, registration categories, therapeutic areas, prescription sources, dosage form distribution, development cycle, clinical research and control drugs.Results:From 2016 to 2022, the total number of application for new Chinese medicines was 265. The number of registration classification 1.1 of new compound drugs was the largest. The dosage forms of new drugs were mainly granules, capsules, and tablets. Indications mainly focused on respiratory, neuropsychiatric, digestion and cardio-cerebrovascular diseases, etc. From 2016 to 2022, the total number of approval for new Chinese medicines was 29, of these, 19 from 2021 to 2022. The number of registration classification 1.1 of new Chinese medicines was the largest. The treatment fields are mainly respiratory system, gynecology and neuropsychiatric diseases, etc. The dosage forms of new drugs were mainly granules, capsules, and tablets. The number of drugs in prescriptions was 6-15. High-frequency drugs included Glycyrrhizae Radix et Rhizoma, Ephedrae Herba, Scutellariae Radix, Pinelliae Rhizoma, Poria and Gypsum Fibrosum. Phase Ⅱ and phase Ⅲ of the clinical trials had the largest number. The development period was approximately between 10-20 years. The most prescription source of new drugs was clinical experienced prescriptions and hospital pharmaceutics.Conclusion:The results show that China has been gradually building-up a relatively complete ecosystem for research and development of new Chinese medicines, helping to develop more high-quality Chinese medicines.
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The recording and analysis of activities of calcium signals in neurons is of critical importance in the field of neuroscience.Over the past three decades,various fluorescent calcium imaging techniques not only have been used in the imaging study of functional activities of neuronal communities,but also can be combined with specific markers to record the functional activities of specific types of neuronal communities.To analyze neural activities at the cellular level,a series of preprocessing such as motion correction,cell body recognition,calcium signal extraction and peak deconvolution is required for the collected video.However,current methods for manual preprocessing are time-consuming and laborious,so computer automatic analysis technology is urgently needed to quickly repair the jitter in the video,identify the position and outline of a single cell,extract its activity trajectory and infer the action potential peak.In this paper,the methods of calcium imaging data processing used in recent years are summarized,and the future developments are predicted.
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ObjectiveTo provide more basic information of comparative medicine for the study of biological changes and pathogenesis of COVID-19 by systematical sorting and analyzing the transcriptome data.MethodsFollowing a retrieval strategy, using COVID-19 and SARS-CoV-2 as key words, transcriptome datasets related to COVID-19 from January 2020 to May 2023 were collected from GEO, ArrayExpress and GEN Transcriptome databases. The composition, distribution, and research application of COVID-19 transcriptome data resources were analyzed. Data distribution was visually displayed and correlation analysis was performed. The research applications and limitations of existing COVID-19 transcriptome data were analyzed from the perspectives of clinical medicine and comparative medicine, focusing on clinical-related molecular mechanisms, biomarkers and related immune responses, treatment intervention strategies, etc. The research value and application prospects were discussed.Results A total of 975 sets of COVID-19 transcriptome data were included. Among three databases, datasets from humans accounted for the highest proportion, namely 71.9%, 77.9%, and 90%, respectively. Species other than humans, such as mice, were the main sources of data, with the respiratory and nervous systems having the highest distribution of data. Twenty-seven datasets were associated with clinical significance. Analysis revealed that respiratory tract injury and other related molecular mechanisms were obtained through transcriptome data mining. Biomarkers such as cfDNA could be used as therapeutic targets. The severity of COVID-19 infection was associated with cell changes and disorders represented by M1 macrophages. Comparative medical analysis showed that mice, hamsters, and other animals were susceptible to SARS-CoV-2. Rhesus monkeys and cynomolgus monkeys exhibited infection characteristics highly similar to human. Apart from respiratory symptoms, hamsters also exhibited digestive system symptoms. SARS-CoV-2 can replicate in the respiratory organs of various susceptible animals, the intestines of ferrets and the ears of minks, resulting in interstitial pneumonia, diffuse lung injury and other pathological changes of varying degrees. Based on the differences in immune responses, hamsters can be used for neutralizing antibody reaction research.Conclusion Currently there is a wealth of COVID-19 transcriptome data, but there is a lack of comparative transcriptome research. Transcriptomics can be combined with comparative medicine to further explore the differences in comparative medicine of COVID-19.
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ABSTRACT Objective: to describe a guide for the development of systematic reviews of observational studies and systematization of international guidelines and tools, focusing on diverse evidence for innovation and clinical practice. Method: this theoretical-conceptual study was initiated during the development of a systematic review with meta-analysis of observational studies, using international guidelines and tools. Results: a guide was constructed to develop systematic reviews of observational studies. Diverse information about several stages and requirements for conducting a systematic review based on international guidelines and tools was systematized, aiming to ensure scientific rigor in manuscripts written by professionals from the health area. Conclusion: this study contributes to research in the health area by innovatively synthesizing guidance on the systematic review method and approaches. The references herein used serve as a starting point for understanding the procedures and international tools necessary for a systematic review of observational studies.
RESUMEN Objetivo: describir una guía para desarrollar revisiones sistemáticas de estudios observacionales y sistematizar pautas y herramientas internacionales, concentrándose en evidencias para la innovación y la práctica clínica. Método: este estudio teórico-conceptual se inició mientras se desarrollaba una revisión sistemática con metaanálisis de estudios observacionales en la que se utilizaron directrices y herramientas internacionales. Resultados: se elaboró una guía para desarrollar revisiones sistemáticas de estudios observacionales. Se sistematizó diversa información sobre varias etapas y requisitos para realizar una revisión sistemática basada en directrices y herramientas internacionales, con el objetivo de garantizar el rigor científico en los manuscritos redactados por profesionales del área de salud. Conclusión: este estudio representa un innovador aporte a la investigación en el área de salud porque sintetiza las pautas sobre el método y los enfoques de las revisiones sistemáticas. Las referencias utilizadas en este trabajo son un buen punto de partida para comprender los procedimientos y las herramientas internacionales necesarios para una revisión sistemática de estudios observacionales.
RESUMO Objetivo: descrever um guia para o desenvolvimento de revisões sistemáticas de estudos observacionais, sistematização de orientações e ferramentas internacionais, com foco em evidências para inovação e prática clínica. Método: este estudo teórico-conceitual foi iniciado durante o desenvolvimento de uma revisão sistemática com metanálise de estudos observacionais em que foram usadas diretrizes e ferramentas internacionais. Resultados: foi construído um guia para desenvolver revisões sistemáticas de estudos observacionais. Foram sistematizadas informações sobre várias etapas e requisitos para realizar revisão sistemática pautada em diretrizes e ferramentas internacionais, visando rigor científico nos manuscritos redigidos por profissionais da área da saúde. Conclusão: este estudo é uma contribuição à pesquisa na área da saúde que inova ao sintetizar a orientação sobre o método e abordagens de revisão sistemática. As referências aqui usadas são um ponto de partida para compreender os procedimentos e ferramentas internacionais necessários a uma revisão sistemática de estudos observacionais.
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RESUMO Este artigo analisa a dimensão de qualidade clareza metodológica do Cadastro Nacional de Estabelecimentos de Saúde (CNES), considerando a abordagem das formas de contratação inseridas no sistema. Trata-se de uma pesquisa documental com abordagem qualitativa, que analisou o CNES e seus documentos. Foram selecionados os documentos que contemplaram os descritores: tabela de vínculos de profissionais e/ou formas de contratação. A partir do conceito adotado para a dimensão de qualidade clareza metodológica, foram delineadas as categorias acessibilidade, conteúdo, variáveis, linguagem e usabilidade. No período de 2005 a 2020, foram publicados 17 documentos. Desses, três documentos se sobressaíram: o Leia-me da versão, a Tabela de Domínios e o Manual de preenchimento do CNES. O site do CNES passava por uma reestruturação, e nem todas as funcionalidades estavam devidamente implementadas. O site atual apresentou uma interface mais moderna e de fácil compreensão. A mudança da variável esfera administrativa para natureza jurídica, em 2015, pode dificultar a análise em série histórica. Evidencia-se que o CNES carece de melhor atenção quanto à clareza metodológica, considerando a abordagem das formas de contratação dos profissionais de saúde, inseridas no sistema.
ABSTRACT This article analyzes the quality dimension of methodological clarity of the National Registry of Health Establishments (CNES), considering the approach to forms of contracting in the system. This is a documentary research with a qualitative approach, which analyzed the CNES and its documents. Documents that included the following were selected: table of professional relationships and/or forms of hiring. Based on the concept adopted for the dimension of methodological clarity quality, the categories accessibility, content, variables, language, and usability were outlined. In the period from 2005 to 2020, 17 documents were published. Of those, three documents stood out: The version's Readme, the Domain Table, and the CNES Filling Manual. The CNES website underwent restructuring and not all features were completed. The current website has a more modern and easy-to-understand interface. The change from the administrative sphere variable to the legal nature, in 2015, may make historical series analysis difficult. It is evident that the CNES pays more attention to methodological clarity, considering the approach to the ways of hiring health professionals, included in the system.
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Gait data analysis, is giving mixing results regarding locomotion changes associated to Amyotrophic Lateral Sclerosis (ALS) development; the need has been claimed for new tools. We applied a nonlinear identification approach to the study of gait data from both healthy and ALS patients, available from Physionet.org. Kernel nonparametric nonlinear autoregression allowed to obtain noise-free realizations (NFR) that mimicked original traces, though correlation between original data and corresponding NFR was lower among ALS patients (p=0.03), suggesting a higher contribution of stochastic influences. Visual inspection of phase portraits, reconstructed from NFR via Takens theorem application, suggested dynamics differences between control subjects and patients. This was confirmed when phase portrait features were quantified and submitted to discriminant analysis (89% of correct classifications; 24/28). Application of a nonlinear dissimilarity measure for comparing pairs gait recordings, defined as a distance between underlying nonlinear autoregressive functions allowed an excellent separation between ALS and controls, via multidimensional scaling. Obtained projection map clearly suggested that ALS traces lay in a narrower dynamical space. This might reflect the known fact about neuronal degeneration accompanying ALS progression. When dissimilarity matrix principal components were introduced as predicting variables, discriminant analysis yielded an 82% of correct classifications (23/28). Overall, our results suggest that a nonlinear identification approach, centered in the characterization of the dynamics of the gait process can bring new insights to gait data interpretation.
El análisis de datos de la marcha, está dando resultados mixtos con respecto a los cambios de locomoción asociados con el desarrollo de la esclerosis lateral amiotrófica (ELA). Se ha reivindicado la necesidad de nuevas herramientas de análisis de datos de la marcha. Aplicamos un enfoque de identificación no lineal al estudio de los datos de la marcha de pacientes sanos y con ELA, disponibles en Physionet.org. La auto-regresión no lineal no paramétrica del núcleo, permitió obtener realizaciones libres de ruido (NFR) que imitaban las trazas originales, aunque la correlación entre los datos originales y la NFR correspondiente fue menor entre los pacientes con ELA (p = 0,03), lo que sugiere una mayor contribución de las influencias estocásticas. La inspección visual de los retratos de fase, reconstruidos a partir de NFR mediante la aplicación del teorema de Takens, sugirió diferencias dinámicas entre los sujetos de control y los pacientes. Esto se confirmó cuando se cuantificaron las características del retrato de fase y se sometieron a un análisis discriminante (89 % de clasificaciones correctas; 24/28). La aplicación de una medida de disimilitud no lineal para comparar registros de marcha de pares, definida como una distancia entre funciones auto-regresivas no lineales subyacentes, permitió una excelente separación entre ALS y controles, a través de una escala multidimensional. El mapa de proyección obtenido sugirió claramente que las huellas de ALS se encuentran en un espacio dinámico más estrecho. Esto podría reflejar el hecho conocido sobre la degeneración neuronal que acompaña a la progresión de la ELA. Cuando se introdujeron los componentes principales de la matriz de disimilitud como variables predictoras, el análisis discriminante arrojó un 82% de clasificaciones correctas (23/28). En general, nuestros resultados sugieren que un enfoque de identificación no lineal, centrado en la caracterización de la dinámica del proceso de la marcha, puede aportar nuevos conocimientos a la interpretación de los datos de la marcha.
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A generation of new science has evolved with the development of bioinformatics and computational biology, which have molecular biology as an integrated part. In the past decade, technological advances have promoted a prominent development in expertise and knowledge in the molecular basis of phenotypes. In Bioinformatics, biological data is evaluated by computational science and processed in a more statistical and meaningful way. It includes the collection classification storage and evaluation of biochemical and organic statistics using computers in particular as implemented in molecular genetics and genomics. Computational Biology and Bioinformatics are emerging branches of science and include the use of techniques and concepts from informatics statistics, mathematics, chemistry, biochemistry, physics and linguistics. Therefore, bioinformatics and computational biology have sought to triumph over many challenges of which a few are listed in this overview. This evaluation intends to provide insight into numerous bioinformatics databases and their uses in the analysis of biological records exploring approaches emerging methodologies strategies tools that can provide scientific meaning to the information generated.
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Abstract@#As the compositional nature of "constant sum" of physical activity, sedentary behavior and sleep are widely recognized, the methodological and result limitations of previous studies that considered physical activity, sedentary behavior, or sleep as independent influences on physical fitness and health have been highlighted. At present,physical activity guidelines of various countries have shifted from local recommendations based on physical activity amount to global recommendations based on 24 h time frame. From the perspective of time use, the content of daily schedule of children and adolescents also has the attribute of "constant sum" of compositional data, and the reduction of students homework burden and extracurricular discipline training after "double reduction" inevitably means an increase in the time allocated to other activities. From the perspective of time use, the paper focuses on physical fitness and health promotion strategies in the context of "double reduction".
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Objective@#To examine the relationship between 24 hour movement behavior and physical fitness of pupils by using compositional analyses, so as to provide a theoretical basis for physical activity promotion and physical fitness improvement.@*Methods@#By random cluster sampling method, 120 students of grade 4 and 5 from the Second Experimental Primary School of Yingze District of Taiyuan were selected. Physical fitness was evaluated by the indicators of the Protocol of National Physical Training Standard and 20 meter shuttle run. The movement behavior was measured by accelerometer. The relationship between each behavior and physical fitness was analysed by component multiple linear regression, and the effect of replacement of components on physical fitness was discussed.@*Results@#Girls 1minute situps were lower than boys（24.79±7.77，28.21±6.52），and sitting forward flexion was higher than boys[9.00（5.00，14.00），5.20（1.00，9.75）cm]（ t/Z =2.60，-3.15， P ＜0.05）. Boys showed higher light physical activity(LPA), moderate to vigorous physical activity(MVPA) and lower sedentary behavior(SB), while girls showed lower LPA, MVPA and higher SB. MVPA was positively correlated with the performance of 30 second rope skipping and 20 meter shuttle run ( β= 13.19, 7.90, P <0.05). Sleep(SLP), SB, and LPA were not significantly correlated with physical fitness. After re allocating 10 min MVPA to SB and SLP，the performance of 30 second rope skipping and 20 meter shuttle run increased by 2.25，2.28 and 1.28 ,1.34 times，respectively，while significantly decreased after reverse reallocation ( P <0.05). MVPA replaced LPA，the 20 meter shuttle run performance increased 1.46 times，while decreased significantly in reverses ( P <0.05).@*Conclusion@#MVPA is positively correlated with the speed and endurance of pupils. There are gender differences in movement behavior patterns and physical fitness. Children, especially girls, should be encouraged to raise exercise awareness and increase PA, especially MVPA.
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Objective@#To systematically review the associations of physical activity (PA), sedentary behavior (SB) and sleep with obesity, as well as isotemporal substitution effects among behaviors, determined with compositional data analysis methods, to provide a reference for obesity interventions among children and adolescents.@*Methods@#Studies in the CNKI, Wanfang, PubMed, SPORTDiscus, Web of Science and Medline databases were searched from January 1, 2014 to May 1, 2022. Two experienced reviewers independently completed document screening, data extraction and quality assessment.@*Results@#Sixteen articles were included, with a methodological quality score range of 7-12 points. Moderate to vigorous physical activity (MVPA), sleep and obesity were negatively correlated, and substituting other behaviors with MVPA decreased obesity risk. The substitution time ranged from 1.5 min/day to 60 min/day. Light physical activity(LPA) and SB were positively correlated with obesity.@*Conclusion@#MVPA is the primary focus of obesity interventions in children and adolescents, and extra 60 min of MVPA per week on the existing level of physical activity may be the minimum necessary to decrease the risk of obesity.
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Objective@#The method of compositional data analysis was used to explore the relationship between 24 hour movement behavior and obesity indicators, and to examine the difference of quantitative effect on obesity indicators when one behavior replaced another behavior, so as to provide specific movement behavior advice for weight control in children and adolescents.@*Methods@#In June 2021, 231 students from eight classes in a primary school and a middle school in Taiyuan City, Shanxi Province were voluntarily recruited by using random cluster sampling. ActiGraph GT3X+ accelerometer was used to measure 24 hour movement behavior and Inbody J20 body composition analyzer was used to measure body composition. The relationship between each component and obesity indicators was analyzed by compositional multivariate linear regression model. In addition, 30 minutes of one behavior was used to replace another behavior to predict the effect difference of the outcomes.@*Results@#After adjusting for covariates such as height, weight, age, and sex, compared with time spent in sedentary behavior(SB), sleep (SLP) and light physical activity (LPA), time spent on moderate to vigorous physical activity (MVPA) was positively correlated with fat free mass index (FFMI) ( β= 0.40, P ＜0.05), negatively correlated with waist circumference (WC) ( β=-2.50, P ＜0.05) and waist hip ratio (WHR) ( β= -0.04 , P ＜0.05). Compared with SB, SLP and MVPA, time spent on LPA was positively correlated with WHR ( β=0.06, P < 0.05 ). If MVPA of 30 min/d replaces SLP, SB, and LPA respectively, WC and WHR decrease 1.10,1.10,1.34 cm and 0.02, 0.02 ,0.02 respectively, and FFMI increases 0.19,0.19,0.15 kg/m 2 respectively.@*Conclusion@#In 24 h movement behavior, with consistent level of sedentary behavior, sleep or low intensity movement behavior, maintaining a high level of MVPA and replacing sedentary with active activities are crucial for optimal abdominal fat and fat free mass in children and adolescents.
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Under the organization of Renji Hospital, Shanghai Jiao Tong University School of Medicine, a specialized disease database of inflammatory bowel disease (IBD) cohort was deployed, and a brief introduction of the database was made in this article. The IBD data set was established by referring to domestic and foreign standards. Through data extraction, cleaning, normalization and other information processing technologies, data from multi‑source heterogeneous platform were arranged to form a specialized major disease database of IBD cohort and the efficiency and quality of data collection in clinical practice, teaching and scientific research were guaranteed. The display and personalized export capacities of the database can promote the researches on IBD and assist the clinical decision‑making. It provides not only efficient, comprehensive and reliable research‑level data support for scientific research, but also a precise guidance for diagnosis and treatment of the disease. Furthermore, it can excavate the potential clinical principles based on medical big data.
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@#Abstract: Objective To analyze the epidemiological characteristics and related factors of norovirus in Guangxi from 2015 to 2020, and to provide scientific recommendations for norovirus prevention and control. Methods The foodborne diseases surveillance data were collected from 11 sentinel hospitals through the National Foodborne Disease Monitoring and Reporting System from 2015 to 2020. R software with version 4.0.3 was used for descriptive and statistical analysis, including epidemic curve, chi-square test, and trend chi-square and so on. Logistic regression was used to analyze norovirus-related factors, OR values and 95% confidence intervals were calculated respectively with the statistical test level of P<0.05. Results There were 1 008 norovirus cases detected, with a detection rate of 12.75% (1 008/7 903). Children with age less than 5 years (OR=1.43, 95%CI: 1.13-1.82) and patients at age 20-45 (OR=1.45, 95%CI: 1.13-1.87) were high risk population. The detection rate was higher in autumn (OR=1.29, 95%CI: 1.08-1.53) but lower in summer (OR=0.67, 95%CI: 0.55-0.80). In addition, the tourist area (Guilin City) presented a higher detection rate than other areas (OR=1.41, 95%CI: 1.10-1.80). Aquatic products (OR=1.40, 95%CI: 1.03-1.91), meat and dairy products (OR=1.31, 95%CI: 1.06-1.61) were high-risk foods for norovirus infection. The prevention and control policies of COVID-19 can reduce the possibility of norovirus by 61% (OR=0.39, 95%CI: 0.31-0.49) showed a declining trend (Trend χ2=85.33, P<0.001). In addition, prolonged visit time can lead to 19%-23% decrease in the detection rate of norovirus (OR24-48 hours=0.81, 95%CI: 0.70-0.95; OR>48 hours=0.77, 95%CI: 0.63-0.93). Conclusions The epidemic of norovirus presented seasonal and regional distribution in Guangxi with a declining detection rate trend in diarrhea patients during recent 6 years. Young children were high-risk population in infection norovirus. The intake of seafood can increase the risk of norovirus infection. The prevention and control policies of COVID-19 can sharply decrease the possibility of infection norovirus. The monitoring of key foods such as seafood should be strengthened, and the early screening of suspected cases should be taken. The norovirus monitoring should be improved to ensure the health of the population.
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The establishment of mental health assessment system provides a new way for the early diagnosis of mental health problems, in view of the growing population of mental diseases and problems and the uneven distribution of mental health resources. In the mental health assessment system, intelligent assistant diagnosis can assist or help psychiatrists improve their work efficiency. Intelligent assistant diagnosis provides technical support for predictive screening and auxiliary diagnosis of mental health problems. It is an intelligent diagnosis research based on big data analysis and machine learning in mental health assessment system. This article mainly reviews the application methods, the application progress in the field of mental health, as well as related technical issues and safety issues, and prospects the future research development.
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With the gradual maturity of sequencing technology, many microbiome studies have published, driving the emergence and advance of related analysis tools. R language is the widely used platform for microbiome data analysis for powerful functions. However, tens of thousands of R packages and numerous similar analysis tools have brought major challenges for many researchers to explore microbiome data. How to choose suitable, efficient, convenient, and easy-to-learn tools from the numerous R packages has become a problem for many microbiome researchers. We have organized 324 common R packages for microbiome analysis and classified them according to application categories (diversity, difference, biomarker, correlation and network, functional prediction, and others), which could help researchers quickly find relevant R packages for microbiome analysis. Furthermore, we systematically sorted the integrated R packages (phyloseq, microbiome, MicrobiomeAnalystR, Animalcules, microeco, and amplicon) for microbiome analysis, and summarized the advantages and limitations, which will help researchers choose the appropriate tools. Finally, we thoroughly reviewed the R packages for microbiome analysis, summarized most of the common analysis content in the microbiome, and formed the most suitable pipeline for microbiome analysis. This paper is accompanied by hundreds of examples with 10,000 lines codes in GitHub, which can help beginners to learn, also help analysts compare and test different tools. This paper systematically sorts the application of R in microbiome, providing an important theoretical basis and practical reference for the development of better microbiome tools in the future. All the code is available at GitHub github.com/taowenmicro/EasyMicrobiomeR.
الموضوعات
Software , Microbiota , Sequence Analysis, DNA , Languageالملخص
Chromatin three-dimensional genome structure plays a key role in cell function and gene regulation. Single-cell Hi-C techniques can capture genomic structure information at the cellular level, which provides an opportunity to study changes in genomic structure between different cell types. Recently, some excellent computational methods have been developed for single-cell Hi-C data analysis. In this paper, the available methods for single-cell Hi-C data analysis were first reviewed, including preprocessing of single-cell Hi-C data, multi-scale structure recognition based on single-cell Hi-C data, bulk-like Hi-C contact matrix generation based on single-cell Hi-C data sets, pseudo-time series analysis, and cell classification. Then the application of single-cell Hi-C data in cell differentiation and structural variation was described. Finally, the future development direction of single-cell Hi-C data analysis was also prospected.