Objective To realize unifying gas source adapter's standards for different medical gas use equipment while the one be connected to different terminal units of central gas source, and terminal's pressure control of the medical gas pipe network, and medical gas uninterrupted supply for partial department in hospital. Methods A general fast adapter for terminal units of medical gas use equipment and central gas source was designed and developed, and its operation methods were explained. It was used and connected into different terminal units for unified format and universality. Results It was convenient and effective in the clinical application in clinical test. Conclusion The general fast adapter is simply manufactured, and achieves the resources shared of the medical gas use equipment. It has good perspective for clinical surgery applying.

Objective: To explore the performance of machine learning prediction models in forecasting student absenteeism due to respiratory symptoms caused by air pollution in short term, aiming to provide a methodological reference for early warning systems of school diseases. Methods: Utilizing data from shortterm sequences of student absenteeism due to respiratory symptoms in Jiangsu Province from September 2019 to October 2022, the study integrated average concentrations of atmospheric pollutants. A univariate distributed lag nonlinear model was employed to select optimal lag variables for the pollutants. An extreme gradient boosting(XGBoost) algorithm model was developed to predict the frequency of absenteeism due to respiratory symptoms and compared with the seasonal autoregressive integrated moving average with exogenous factors(SARIMAX) model. Results: Between 2019 and 2022, an average of 9 709 students per day in Jiangsu Province were absent due to respiratory symptoms. The daily average air quality index (AQI) was 76.96,with mass concentrations of PM2.5, PM10, NO2, and O3 averaging at 35.75, 61.13, 28.89, 104.81 μg/m3, respectively. Granger causality tests indicated that AQI, PM2.5, PM10, NO2, and O3 were significant predictors of absenteeism frequency due to respirutory symptoms(F=1.46,1.79,1.67,3.41,2.18,P<0.01). The singleday lag effects of PM2.5, PM10, NO2, and O3 reached their peak relative risk (RR) values at lag4, lag0, lag0, lag4 respectively. When integrating these optimal lag variables for the pollutants, the XGBoost model demonstrated superior predictive performance to the SARIMAX model, reducing the mean absolute error (MAE) from 2.251 to 0.475, mean absolute percentage error (MAPE) from 0.429 to 0.080, and root mean square error (RMSE) from 2.582 to 0.713; at the P75 percentile alert threshold, the sensitivity improved from 0.086 to 0.694 and specificity from 0.979 to 0.988, with the Youden index increasing from 0.065 to 0.682. Conclusions The XGBoost model exhibits robust predictive performance and effective early warning capabilities for shortterm sequences of student absenteeism due to respiratory symptoms caused by air pollution. Schools could timely adopt this model to preemptively detect and control disease outbreaks, thereby enhancing school health management.

Objective:To investigate the current situations and development requirements of emergency testing among secondary and tertiary hospitals in China.Methods:The data were collected from secondary and tertiary hospitals via online questionnaire across 31 provinces in China from February 1 to March 1, 2021. The questionnaire involves various aspects of emergency testing, including area of emergency laboratory, staffs and equipment configuration, inspection items, Turn-around time (TAT), reagents and consumables management, pre-analysis quality control, laboratory information system, critical values management and biosafety, etc.Results:A total of 2 187 questionnaires were obtained, and 1 503 valid questionnaires from 755 secondary hospitals and 748 tertiary hospitals were finally analyzed. The research data showed that daily average number of patients visiting emergency department exceeding 300 person-time in 29.41% (220/748) tertiary hospitals, but that number was less than 100 person-time in 76.69% (579/755) secondary hospitals; daily average emergency tests exceeding 5 000 was reported in 24.47% (183/748) tertiary hospitals, and less than 2 000 was reported in 93.51% (706/755) secondary hospitals; the area of emergency laboratory was less than 100 m 2 in 68.79% (238/346) tertiary hospitals with independent emergency testing laboratory; there were no fixed staffs of emergency testing in 56.02% (842/1 503) hospitals; the biochemical/immunoassay analyzer in 8.65% (130/1 503) hospitals did not have STAT position; one hundred and twenty-six hospitals (8.38%) did not have stock in and stock out record for reagents and consumes materials; the conventional statistical analysis of unqualified specimen was not carried out in 24.62% (370/1 503) hospitals; priority on emergent specimen was not set in 58.62% (881/1 503) hospitals; whole process monitoring function was not equipped in 48.64% (731/1 503) hospitals; there was no conventional communication working mechanism with clinicians on critical value in 7.32% (110/1 503) hospitals; overall, 50.23% (755/1 503) participants did not consider that biosafety risks exist in their emergency testing laboratory. Conclusions:This survey objectively presents the current situations and future development requirements of emergency testing among secondary and tertiary hospitals in China. The survey also reflects that some important process and concepts need to be improved, and extensive attention should be paid by laboratory and hospital administrator, in the area such as communication with clinician, site construction and staff configuration, administration on the priority of emergency testing, administration on the reagent and consumable materials, laboratory informatization construction, laboratory biosafety, and so on.

OBJECTIVETo investigate if there are microsatellite loci in the long arm of chromosome 6 that have close relationship with non-small cell lung cancer.

METHODSMultiple PCR approach was used to analyze the 18 loci in the long arm of chromosome 6. The PCR products were analyzed in PAGE, and then the electrophoresis maps were analyzed with Gene Scan(TM) and Genotyper(TM).

RESULTSThere were different frequencies of loss of heterozygosity (LOH) in different loci (varying from 3.85% to 38.45%). The total frequency of LOH in 41 gastric cancers was 58.5%(24/41). Eight loci with the LOH frequency higher than 20% were mainly located in 2 regions: 6q24 and 6q27. The accurate location is 6q24-6q25.3 [D6S1699(35%), D6S409(23.33%), D6S441(33.33%)] and 6q26-27 [D6S1550(38.45%), D6S264(20%), D6S1585(25%), D6S446(33.33%), D6S281(30.77%)].

CONCLUSIONThere may be tumor suppressor genes located in the region of 6q24 and 6q27, which have close relationship with non-small cell lung cancer.

Carcinoma, Non-Small-Cell Lung ; genetics ; Chromosome Mapping ; Chromosomes, Human, Pair 6 ; Genes, Tumor Suppressor ; Humans ; Loss of Heterozygosity ; genetics ; Lung Neoplasms ; genetics ; Polymerase Chain Reaction ; methods

Objective:To construct a recombinant bioluminescent bacteriophage (HT7) targeting Escherichia coli, and evaluate its ability to identify Escherichia coli. Methods:Initially, pCRISPR-sg (1-10) and PFN-1000 plasmid strains were constructed by genetic engineering, and the most efficient small guild RNA (sgRNA) were screened by bilayer plate. By the gene editing technique, which comprised homologous recombination and clustered regularly interspaced short palin dromic repeats (CRISPR)-Cas system, the Nanoluc luciferase gene was integrated into the downstream non-coding region of 10A gene of T7 phage, to constructe the bioluminescent phage HT7 successfully. The difference of biological characteristics between HT7 phage and T7 phage was evaluated by plaque assay and liquid amplification assay. In addition, 51 strains of Escherichia coli, 20 strains of Klebsiella pneumoniae, 14 strains of Staphylococcus aureus, 6 strains of Enterococcus faecium, 5 strains of Enterococcus faecalis, 3 strains of Acinetobacter baumannii and 1 strain of Pseudomonas aeruginosa were collected and isolated to evaluate the limit of detection and specificity of HT7 phage. Results:Among the 10 CRISPR-targeted cleavage systems constructed, sgRNA8 exhibited the highest cleavage efficiency, with a cleavage rate of 0.18. After three rounds of recombination screening using the pCas9/pCRISPR/PFN-1000 triple-plasmid system, PCR validation yielded recombinant phage bands at 2 798 bp, indicating the successful construction of the HT7 phage. The recombinant phage showed significant differences in biological characteristics in terms of lysis efficiency ( P<0.001), one-step growth curve ( P=0.001), and infection multiplicity ( P=0.031). Both lysis burst time and log growth node were extended by 10 min, with the optimal infection multiplicity being 0.1. Clinical sample testing identified lysis of 6 strains of Escherichia coli within 4.5 h, while other strains remained unaffected, with detection of pathogenic bacteria below 10 CFU/ml. Conclusions:The developed pCas9/pCRISPR/PFN-1000 triple-plasmid editing system efficiently edits the bacteriophage genome. The constructed HT7 fluorescent bacteriophage enables the detection of Escherichia coli below 10 CFU/ml within 4.5 hours, demonstrating low detection limits and high detection specificity.

Objective: To survey the conduction and evaluate the effectiveness of extracorporeal membrane oxygenation (ECMO) therapy in pediatric intensive care unit (PICU) in China mainland. Methods: In a questionnaire-based survey, we retrospectively reviewed the application of ECMO in children's hospital and general hospital in China mainland to summarize and analyze the categories of diseases and prognosis of children treated with ECMO therapy. Results: By December 31, 2017, a total of 23 hospitals using ECMO, including 22 tertiary referral hospitals and 1 secondary hospital, among which 16 were children′s hospitals and 7 were general hospitals. Thirty-seven ECMO equipment was available. A total of 518 patients treated with ECMO, within whom 323 (62.4%) successfully weaned from ECMO and 262 (50.6%) survived to discharge. Among 375 pediatric patients, 233 (62.1%) were successfully weaned from ECMO and 186 (49.6%) survived to discharge. Among 143 newborn patients, 90 (62.9%) successfully weaned from ECMO, 76 (53.1%) survived to discharge. ECMO was applied in veno-arterial (VA) mode to 501 (96.7%) patients, veno-venous (VV) mode to 14 (2.7%) patients, and VV-VA conversion mode to 3 (0.6%) patients. Sixty-nine patients required extracorporeal cardiopulmonary resuscitation (ECPR), including 20 newborn patients (29.0%) and 38 pediatric patients (71.0%), who were all with cardiovascular disease. Neonatal respiratory distress syndrome (26/61), persistent pulmonary hypertension of the newborn (PPHN) (12/61), and meconium aspiration syndrome (MAS) (11/61) are the most common pulmonary diseases in newborn patients; among whom, infants with PPHN had highest survival rate (10/12), followed by MAS (9/11). Among newborn patients with cardiovascular diseases, those who admitted were after surgery for congenital cardiac disease were the most common (54/82), while those with septic shock had the highest survival rate (2/3). In pediatric pulmonary diseases, acute respiratory distress syndrome was the most common (42/93), while plastic bronchitis was with the highest survival rate (4/4), followed by viral pneumonia (13/16). Among pediatric cardiovascular diseases, congenital cardiac defect was the most common (124/282), while fulminant myocarditis had the highest survival rate (54/77). Conclusion The application of ECMO as a rescue therapy for children with severe cardiopulmonary failure has dramatically developed in China mainland.

In the context of the rapid development of big data in the healthcare field, deep learning (DL), as a machine learning algorithm that provides a more flexible solution for image and speech recognition as well as natural language processing, has the ability to extract important information from medical data into valuable knowledge and it has received unprecedented attention in many real-world tasks. This paper briefly introduces common network structure of deep learning and its latest research progress in the field of medical laboratory. In addition, this review also exploreed some of the inherent challenges and prospective research directions about deep learning that affecting in the medical laboratory.