Objective To simultaneously collect and analyze the kinematic and dynamic parameters for two techniques of traditional Chinese cervical manipulation ( TCCM), and quantitatively describe its biomechanical characteristics. Methods A senior practitioner completed the TCCM (positioning and directional rotation pulling, lateral flexion, respectively) on 10 healthy subjects, and the fluorescent marker balls were pasted on the operator to capture manipulation movements. The dynamic parameters and the surface electromyography ( sEMG) signals were collected by pressure-sensitive gloves and wireless sEMG acquisition system. Results The upper arm muscle was the main force muscle during TCCM, and biceps brachii had the highest contribution rate. The range of motion (ROM), speed, pulling force, and time during cervical spine positioning and directional rotation pulling were all greater than those during cervical spine lateral flexion. The integrate electromyography ( iEMG) and root mean square (RMS) for each muscle of the operator during cervical spine positioning and directional rotation pulling were higher than those during cervical spine lateral flexion. Conclusions The overall ROM, three-dimensional (3D) motion angle, load intensity and time during CCTM have the characteristics of high speed, low amplitude and strong force, reflecting the biomechanical characteristics of ‘ cunjin ’ ( one-inch punch ) in traditional Chinese medicine. This study provides references for further standardizing manual teaching and training and improving clinical safety.

OBJECTIVE: To evaluate the application of three-in-one intelligent screening in outpatient pre-inspection in children's hospital. METHODS: We randomly enrolled 100 children pre-screened by traditional method in the outpatient department of Children's Hospital of Zhejiang University from February 6th to 16th, 2020, and another 100 children by the intelligent three-in-one mode from February 17th to 27th, 2020. The traditional triage was conducted by nurses based on face-to-face, one-by-one interview of the epidemiological history and consultation department, and the temperature was measured before manual triage. The intelligent three-in-one model combined online rapid pre-inspection and triage, on-site manual confirmation, as well as synchronized online health education system. For on-line registered patients, the system automatically sent the COVID-19 epidemiological pre-screening triage questionnaire one hour before the appointment, requiring parents to complete and submit online before arriving at the hospital. The on-site registered patients were controlled at 100 m away from the hospital entrance. The nurses guided the parents to scan the QR code and fill in the COVID-19 epidemiological pre-examination triage questionnaire. At the entrance of the hospital, the nurse checked the guidance sheet and took the temperature again. The children with red guidance sheet were checked again and confirmed by pre-examination nurses, and accompanied to the isolation clinic through COVID-19 patients-only entrance. The children with yellow guidance sheet were guided to fever clinic. The children with green guidance sheet could go with their parents to the designated area, and then went to the corresponding consultation area. Health education was carried out throughout the treatment, and the system automatically posted the corresponding outpatient instructions and education courses. Parents would read the courses on their mobile phones and counsel online. The time of pre-examination and the coincidence rate of triage were compared between the two groups. RESULTS: The three-in-one intelligent pre-inspection mode took an average of (25.6±8.0) s for each child, which was significantly shorter than the traditional pre-inspection mode (74.8±36.4) s ( CONCLUSIONS The three-in-one intelligent pre-inspection model can effectively shorten the patient pre-check time, with similar triage coincidence rate to traditional model.
Adult ; Betacoronavirus ; COVID-19 ; Child ; Coronavirus Infections/diagnosis* ; Humans ; Internet ; Outpatient Clinics, Hospital ; Pandemics ; Pneumonia, Viral/diagnosis* ; SARS-CoV-2 ; Surveys and Questionnaires ; Time ; Triage/standards*

Advances in high-throughput sequencing (HTS) have fostered rapid developments in the field of microbiome research, and massive microbiome datasets are now being generated. However, the diversity of software tools and the complexity of analysis pipelines make it difficult to access this field. Here, we systematically summarize the advantages and limitations of microbiome methods. Then, we recommend specific pipelines for amplicon and metagenomic analyses, and describe commonly-used software and databases, to help researchers select the appropriate tools. Furthermore, we introduce statistical and visualization methods suitable for microbiome analysis, including alpha- and beta-diversity, taxonomic composition, difference comparisons, correlation, networks, machine learning, evolution, source tracing, and common visualization styles to help researchers make informed choices. Finally, a step-by-step reproducible analysis guide is introduced. We hope this review will allow researchers to carry out data analysis more effectively and to quickly select the appropriate tools in order to efficiently mine the biological significance behind the data.