BACKGROUND:In recent years,many studies have confirmed that assembloids can make up for the shortcomings of organoids,which cannot fully reproduce the interaction between cell and cell and between cell and matrix.Since the assembloids construction methods are in the early stage of development,there is no unified standard. OBJECTIVE:To review the current construction methods,applications,advantages,and disadvantages of assembloids,guide the development and improvement of vitro cell models. METHODS:PubMed,CNKI,and WanFang databases were searched with English search terms"assembloids,organoids,tumor microenvironment,organoids AND assemble,organoids AND microenvironment"and Chinese search terms"assembloids,organoids,tumor microenvironment,organoid reorganization,multicellular model".Totally 94 articles were screened out for review after excluding irrelevant articles and deduplication. RESULTS AND CONCLUSION:(1)According to the different sources of cells,the construction of assembloids can be divided into three methods:self-assembly,direct-assembly,and mixed-assembly.According to the differences of cell culture methods,it can be divided into suspension culture method,matrix culture method,organ chip culture method,and 3D bio-printing.(2)The process of self-assembly covers early stages of cell and tissue development,so it has broad prospects in the fields of organ development and developmental disorders.The function of differentiated mature cells is relatively perfect,and the assembloids directly assembled by them have more potential in the study of functional disorders and cell-damaging diseases.Self-assembly may be better in organ transplantation,and direct-assembly will be more suitable for the repair of tissue damage.Mixed-assembly combines the advantages of the former two and is mostly used to explore the physiological and pathological mechanisms of cells in the microenvironment,as well as drug screening.(3)Although different assembloids have their own advantages,they all face the problem of imperfect vasculature system,then,each method has its own limitations,for example,the degree of cell differentiation in self-assembly assembloids may still be different from that in vivo,and the fixed cell types in direct-assembly models cannot simulate complex microenvironments in vivo.These are urgent problems to be solved.(4)In the future,with the continuous improvement of assembloids culture technology,scientists can assemble biomimetic organoids with more complex tissues in vitro,providing infinitely realistic models for the study of physiological and pathological processes of human tissue and organ.

Objective:To examine the influence of acute hypoxemia on central venous pressure (CVP) and diastolic blood pressure (DBP) in critical patients assisted by mechanical ventilation.Methods:We retrospectively analyzed the clinical data of critical patients assisted by mechanical ventilation in Medical Information Mart for Intensive Care Ⅲ (MIMIC-Ⅲ) database. Influence of acute hypoxemia on CVP and diastolic blood pressure (DBP) were evaluated. Hypoxemia was defined according to oxygenation index (OI) (OI≤100 as severe, 100

Objective:To identify disease-causing variation in a Chinese family with Axenfeld-Rieger syndrome (ARS) through the analysis of clinical symptoms and hereditary information.Methods:The method of pedigree investigation was adopted.A Chinese ARS family including 15 family members of 3 generations was recruited in the Second Affiliated Hospital of Harbin Medical University in 2018.There were 3 patients in the family.The family history and clinical data were collected.Ophthalmic and general examinations were carried out in all the members included.DNA and RNA were extracted from collected peripheral venous blood samples of 2-5 ml from each member.Whole exome sequencing was used to screen the variations in the proband.Suspected variations screened through searching population databases and bioinformatics analysis were verified by Sanger sequencing and real-time quantitative PCR.Conservation analysis and deleteriousness prediction of suspected variations were conducted.The pathogenecity of candidate rare variations were evaluated according to the American College of Medical Genetics and Genomics (ACMG) standards and guidelines.This study followed the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of the Second Affiliated Hospital of Harbin Medical University (No.KY2019-231).Written informed consent was obtained from each subject or custodian prior to entering the study cohort.Results:The 3 patients all had typical ARS clinical features in eyes, teeth and umbilicus, and carried the same heterozygous variant, c.525delC (p.Asp175Glufs *) in the PITX2 gene, which were not found in other members, indicating co-segregation.The relative expression of PITX2 mRNA was 0.672±0.063 in the patients, which was significantly lower than 1.015±0.179 in the healthy controls ( t=8.847, P<0.001).This variant was not recorded in dbSNP, 1000G, gnomeAD, ExAC, Korea1K and EVS databases, and it was labelled as deleterious by MutationTaster.The affected conservative amino acid sequences were found in 9 species.The variant was determined as pathogenic according to the ACMG standards and guidelines. Conclusions:The c.525delC (p.Asp175Glufs *) mutation of PITX2 gene is pathogenic in the pedigree.This is the first time that this mutation has been reported in Chinese family with ARS.

Breathing pattern parameters refer to the characteristic pattern parameters of respiratory movements, including the breathing amplitude and cycle, chest and abdomen contribution, coordination, etc. It is of great importance to analyze the breathing pattern parameters quantificationally when exploring the pathophysiological variations of breathing and providing instructions on pulmonary rehabilitation training. Our study provided detailed method to quantify breathing pattern parameters including respiratory rate, inspiratory time, expiratory time, inspiratory time proportion, tidal volume, chest respiratory contribution ratio, thoracoabdominal phase difference and peak inspiratory flow. We also brought in "respiratory signal quality index" to deal with the quality evaluation and quantification analysis of long-term thoracic-abdominal respiratory movement signal recorded, and proposed the way of analyzing the variance of breathing pattern parameters. On this basis, we collected chest and abdomen respiratory movement signals in 23 chronic obstructive pulmonary disease (COPD) patients and 22 normal pulmonary function subjects under spontaneous state in a 15 minute-interval using portable cardio-pulmonary monitoring system. We then quantified subjects' breathing pattern parameters and variability. The results showed great difference between the COPD patients and the controls in terms of respiratory rate, inspiratory time, expiratory time, thoracoabdominal phase difference and peak inspiratory flow. COPD patients also showed greater variance of breathing pattern parameters than the controls, and unsynchronized thoracic-abdominal movements were even observed among several patients. Therefore, the quantification and analyzing method of breathing pattern parameters based on the portable cardiopulmonary parameters monitoring system might assist the diagnosis and assessment of respiratory system diseases and hopefully provide new parameters and indexes for monitoring the physical status of patients with cardiopulmonary disease.
Humans ; Lung ; Pulmonary Disease, Chronic Obstructive ; Respiration ; Tidal Volume ; Wearable Electronic Devices

This paper aims to study the accuracy of cardiopulmonary physiological parameters measurement under different exercise intensity in the accompanying (wearable) physiological parameter monitoring system. SensEcho, an accompanying physiological parameter monitoring system, and CORTEX METALYZER 3B, a cardiopulmonary function testing system, were used to simultaneously collect the cardiopulmonary physiological parameters of 28 healthy volunteers (17 males and 11 females) in various exercise states, such as standing, lying down and Bruce treadmill exercise. Bland-Altman analysis, correlation analysis and other methods, from the perspective of group and individual, were used to contrast and analyze the two types of equipment to measure parameters of heart rate and breathing rate. The results of group analysis showed that the heart rate and respiratory rate data box charts collected by the two devices were highly consistent. The heart rate difference was (-0.407 ± 3.380) times/min, and the respiratory rate difference was (-0.560 ± 7.047) times/min. The difference was very small. The Bland-Altman plot of the heart rate and respiratory rate in each experimental stage showed that the proportion of mean ± 2SD was 96.86% and 95.29%, respectively. The results of individual analysis showed that the correlation coefficients of the whole-process heart rate and respiratory rate data were all greater than 0.9. In conclusion, SensEcho, as an accompanying physiological parameter monitoring system, can accurately measure the human heart rate, respiration rate and other key cardiopulmonary physiological parameters under various sports conditions. It can maintain good stability under various sports conditions and meet the requirements of continuous physiological signal collection and analysis application under sports conditions.

To achieve continuously physiological monitoring on hospital inpatients, a ubiquitous and wearable physiological monitoring system SensEcho was developed. The whole system consists of three parts: a wearable physiological monitoring unit, a wireless network and communication unit and a central monitoring system. The wearable physiological monitoring unit is an elastic shirt with respiratory inductive plethysmography sensor and textile electrocardiogram (ECG) electrodes embedded in, to collect physiological signals of ECG, respiration and posture/activity continuously and ubiquitously. The wireless network and communication unit is based on WiFi networking technology to transmit data from each physiological monitoring unit to the central monitoring system. A protocol of multiple data re-transmission and data integrity verification was implemented to reduce packet dropouts during the wireless communication. The central monitoring system displays data collected by the wearable system from each inpatient and monitors the status of each patient. An architecture of data server and algorithm server was established, supporting further data mining and analysis for big medical data. The performance of the whole system was validated. Three kinds of tests were conducted: validation of physiological monitoring algorithms, reliability of the monitoring system on volunteers, and reliability of data transmission. The results show that the whole system can achieve good performance in both physiological monitoring and wireless data transmission. The application of this system in clinical settings has the potential to establish a new model for individualized hospital inpatients monitoring, and provide more precision medicine to the patients with information derived from the continuously collected physiological parameters.

The analysis of big data in medical field cannot be isolated from the high quality clinical database, and the construction of first aid database in our country is still in the early stage of exploration. This paper introduces the idea and key technology of the construction of multi-parameter first aid database. By combining emergency business flow with information flow, an emergency data integration model was designed with reference to the architecture of the Medical Information Mart for Intensive Care III (MIMIC-III), created by Computational Physiology Laboratory of Massachusetts Institute of Technology (MIT), and a high-quality first-aid database was built. The database currently covers 22 941 medical records for 19 814 different patients from May 2015 to October 2017, including relatively complete information on physiology, biochemistry, treatment, examination, nursing, etc. And based on the database, the first First-Aid Big Data Datathon event, which 13 teams from all over the country participated in, was launched. The First-Aid database provides a reference for the construction and application of clinical database in China. And it could provide powerful data support for scientific research, clinical decision making and the improvement of medical quality, which will further promote secondary analysis of clinical data in our country.
Big Data ; Critical Care ; Databases, Factual ; Humans ; Medical Informatics

Objective To study the distribution of diseases in Medical Information Mart for Intensive Care Ⅲ(MIMIC-Ⅲ) database in order to provide reference for clinicians and engineers who use MIMIC-Ⅲ database to solve clinical research problems. Methods The exploratory data analysis technologies were used to explore the distribution characteristics of diseases and emergencies of patients (excluding newborns) in MIMIC-Ⅲ database were explored; then, neonatal gestational age, weight, length of hospital stay in intensive care unit (ICU) were analyzed with the same method. Results In the MIMIC-Ⅲ database, 46 428 patients were admitted for the first time, and 49 214 ICU records were recorded. There were 26 076 males and 20 352 females; the median age was 60.5 (38.6, 75.6) years, and most patients were between 60 and 80 years old. The first diagnosis in the disease spectrum analysis was firstly ranked by circulatory diseases (32%), followed by injury and poisoning (14%), digestive system disease (8%), tumor (7%), respiratory disease (6%) and so on. Patients with ischemic heart disease accounted for the largest proportion of circulatory disease (42%), the proportion of these patients gradually increased with age of 60-70 years old, then decreased. However, the proportion of patients with cerebrovascular disease declined first and then increased with age, which was the main cause of death of circulatory system disease (ICU mortality was 22.5%). Injury and poisoning patients showed a significant decrease with age. Digestive system diseases were younger than the general population (most people aged between 50 to 60 years), and non-infectious enteritis and colitis were the main causes of death (ICU mortality was 18.3%). Respiratory infections were predominant in infected patients (34%), but circulatory system infections were the main cause of death (ICU mortality was 25.6%). Secondly, in the neonatal care unit, premature infants accounted for the vast majority (82%). As the gestational age increased, the duration of ICU was decreased, and the mortality was decreased. Conclusions The diseases distribution of patients can be provided by MIMIC-Ⅲ database, which helps to grasp the overview of the volume and age distribution of the target patients in advance, and carry out the next step of research. Meanwhile, it points out the important role of exploratory data analysis in electronic health records analysis.

Medical practice generates and stores immense amounts of clinical process data, while integrating and utilization of these data requires interdisciplinary cooperation together with novel models and methods to further promote applications of medical big data and research of artificial intelligence. A "Datathon" model is a novel event of data analysis and is typically organized as intense, short-duration, competitions in which participants with various knowledge and skills cooperate to address clinical questions based on "real world" data. This article introduces the origin of Datathon, organization of the events and relevant practice. The Datathon approach provides innovative solutions to promote cross-disciplinary collaboration and new methods for conducting research of big data in healthcare. It also offers insight into teaming up multi-expertise experts to investigate relevant clinical questions and further accelerate the application of medical big data.

Objective To construct a database containing multiple kinds of diseases that can provide "real world"data for first-aid clinical research. Methods Structured or non-structured information from hospital information system, laboratory information system, emergency medical system, emergency nursing system and bedside monitoring instruments of patients who visited department of emergency in PLA General Hospital from January 2014 to January 2018 were extracted. Database was created by forms, code writing, and data process. Results Emergency Rescue Database is a single center database established by PLA General Hospital. The information was collected from the patients who had visited the emergency department in PLA General Hospital since January 2014 to January 2018. The database included 530 585 patients' information of triage and 22 941 patients' information of treatment in critical rescue room, including information related to human demography, triage, medical records, vital signs, lab tests, image and biological examinations and so on. There were 12 tables (PATIENTS, TRIAGE_PATIENTS, EMG_PATIENTS_VISIT, VITAL_SIGNS, CHARTEVENTS, MEDICAL_ORDER, MEDICAL_RECORD, NURSING_RECORD, LAB_TEST_MASTER, LAB_RESULT, MEDICAL_EXAMINATION, EMG_INOUT_RECORD) that containing different kinds of patients' information. Conclusions The setup of high quality emergency databases lay solid ground for scientific researches based on data. The model of constructing Emergency Rescue Database could be the reference for other medical institutions to build multiple-diseases databases.