ObjectiveTo monitor the real-time changes in ammonia concentration in the laboratory animal facility environment before, during, and after the air conditioning system stops supplying air, so as to provide a basis and reference for developing emergency plans for the shutdown of the air conditioning system. MethodsThe laboratory animal facilities of the Wuhan Institute of Biological Products were used as the research object. Ammonia concentration detectors were used to monitor ammonia concentration continuously in the environment of conventional rabbit production facility, SPF hamster production facility, and SPF guinea pig experimental facility before and after the passive shutdown due to repairs and active maintenance shutdown of the air conditioning system, as well as the time for the ammonia concentration to return to daily levels after resuming air supply. ResultsUnder both shutdown modes of the air conditioning system, the trend of ammonia concentration changes in different laboratory animal facilities was consistent, showing a rapid increase after shutdown and a rapid decrease after resuming air supply. Under active maintenance shutdown, the maximum ammonia concentrations in the conventional rabbit production facilities, SPF hamster production facilities, and SPF guinea pig experimental facilities were 9.81 mg/m³, 14.27 mg/m³, and 6.98 mg/m³, respectively. Within 12 minutes after resuming air supply, ammonia concentration could return to normal daily levels. Under passive long-term shutdown, ammonia concentration value was positively correlated with the duration of air supply suspension. As the shutdown duration increased, ammonia concentration continued to increase. The maximum ammonia concentration values in the three facilities occurred at 88 minutes (38.06 mg/m³), 40 minutes (18.43 mg/m³), and 34 minutes (15.61 mg/m³) after air supply suspension, respectively.Within 11 minutes after resuming air supply, ammonia concentration could return to normal daily levels. ConclusionShutdown of the air conditioning system causes a rapid increase in ammonia concentration in laboratory animal facilities, and the rise in ammonia concentration is positively correlated with the duration of air supply suspension. Therefore, when an emergency shutdown of the air-conditioning system is required due to maintenance or other reasons, backup fans should be provided in accordance with the requirements of GB 50447-2008 "Architectural and Technical Code for Laboratory Animal Facilities". Older facilities should make adequate preparations and develop a scientifically sound emergency plan.

Objective To study the role of Healthcare Failure Mode and Effect Analysis(HFMEA)in reducing the risk of healthcare-associated infection.Methods Using HFMEA to identify,analyze and evaluate the risks leading to hospital infec-tions,screening out the high-risk events of hospital infections,ultimately determining cleaning management,hand hygiene,and management of patients with multi-drug resistant bacteria as 3 failure modes,and identifying 9 items such as poor personnel ac-ceptance ability as potential failure causes,implementing risk control and intervention for them,and comparing the effects before and after the improvement.Results Except for the potential failure cause of weak awareness of hospital-acquired infections a-mong cleaning staff,the RPN values of the other eight potential failure causes showed significant differences after HFMEA inter-vention(P＜0.05).The compliance rate of hand hygiene,the cleaning qualification rate of cleaning staff were both improved,and the differences were statistically significant(P＜0.01).In terms of the management of patients with multi-drug resistant bac-teria,the implementation rate of isolation measures,the standardization of cleaning,the standardization of medical procedures,the compliance rate of hand hygiene and the qualification rate of accompanying education for caregivers all significantly increased(P＜0.05).Conclusion HFMEA can effectively control the risk of hospital-acquired infections to a certain extent and reduce the occurrence of hospital-acquired infection events.

Objective To explore the preoperative non-invasive prediction of early postoperative glioma recurrence using multi-modal conventional MRI radiomics.Methods A retrospective analysis of the clinical and MRI data of 83 glioma patients who met the inclusion criteria was conducted.The Kruskal-Wallis test was used to compare clinical factors between recurrent and non-recurrent groups.The automated segmentation of the entire tumor lesion for glioma patients was accomplished with VB-Net algorithm,a deep learning approach developed by United Imaging Healthcare;and the extraction of radiomics features from preoperative T1CE and T2WI images was carried out on URP platform.The optimal feature combination was determined using the maximum relevance and minimum redundancy and least absolute shrinkage and selection operator methods.Logistic regression and five-fold cross-validation were employed to analyze radiomics features and construct 4 prediction models,namely T2WI model,T1CE model,T2WI+T1CE model,and imaging-clinical fusion model.The diagnostic performances of these models were evaluated and compared using the area under the receiver operating characteristic curve(AUC)and the Delong test.In addition,the model sensitivity and specificity were calculated.Results Postoperatively,there were 40 recurrent cases and 43 non-recurrent cases.The clinical factors such as glioma grade showed statistical significance between two groups(P<0.05),while gender and age did not show significant statistical differences(P>0.05).For the single-sequence radiomics models,T1CE model(AUC:0.804)outperformed T2WI model(AUC:0.702).The multi-modal combined model exhibited a higher AUC than the single-sequence prediction models,with an AUC of 0.849,a sensitivity of 72.5%,and a specificity of 79.1%.The imaging-clinical fusion model whose predictive efficiency was close to that of multi-modal combined model(P=0.303)also performed well in forecasting postoperative glioma recurrence,with an AUC of 0.839,a sensitivity of 72.5%,and a specificity of 79.1%.Conclusion The multi-modal conventional MRI radiomics model can better predict early postoperative glioma recurrence.The imaging-clinical fusion model that includes glioma grade does not have the diagnostic performance superior to that of radiomics model.

Objective To study the role of Healthcare Failure Mode and Effect Analysis(HFMEA)in reducing the risk of healthcare-associated infection.Methods Using HFMEA to identify,analyze and evaluate the risks leading to hospital infec-tions,screening out the high-risk events of hospital infections,ultimately determining cleaning management,hand hygiene,and management of patients with multi-drug resistant bacteria as 3 failure modes,and identifying 9 items such as poor personnel ac-ceptance ability as potential failure causes,implementing risk control and intervention for them,and comparing the effects before and after the improvement.Results Except for the potential failure cause of weak awareness of hospital-acquired infections a-mong cleaning staff,the RPN values of the other eight potential failure causes showed significant differences after HFMEA inter-vention(P＜0.05).The compliance rate of hand hygiene,the cleaning qualification rate of cleaning staff were both improved,and the differences were statistically significant(P＜0.01).In terms of the management of patients with multi-drug resistant bac-teria,the implementation rate of isolation measures,the standardization of cleaning,the standardization of medical procedures,the compliance rate of hand hygiene and the qualification rate of accompanying education for caregivers all significantly increased(P＜0.05).Conclusion HFMEA can effectively control the risk of hospital-acquired infections to a certain extent and reduce the occurrence of hospital-acquired infection events.

Objective To explore the preoperative non-invasive prediction of early postoperative glioma recurrence using multi-modal conventional MRI radiomics.Methods A retrospective analysis of the clinical and MRI data of 83 glioma patients who met the inclusion criteria was conducted.The Kruskal-Wallis test was used to compare clinical factors between recurrent and non-recurrent groups.The automated segmentation of the entire tumor lesion for glioma patients was accomplished with VB-Net algorithm,a deep learning approach developed by United Imaging Healthcare;and the extraction of radiomics features from preoperative T1CE and T2WI images was carried out on URP platform.The optimal feature combination was determined using the maximum relevance and minimum redundancy and least absolute shrinkage and selection operator methods.Logistic regression and five-fold cross-validation were employed to analyze radiomics features and construct 4 prediction models,namely T2WI model,T1CE model,T2WI+T1CE model,and imaging-clinical fusion model.The diagnostic performances of these models were evaluated and compared using the area under the receiver operating characteristic curve(AUC)and the Delong test.In addition,the model sensitivity and specificity were calculated.Results Postoperatively,there were 40 recurrent cases and 43 non-recurrent cases.The clinical factors such as glioma grade showed statistical significance between two groups(P<0.05),while gender and age did not show significant statistical differences(P>0.05).For the single-sequence radiomics models,T1CE model(AUC:0.804)outperformed T2WI model(AUC:0.702).The multi-modal combined model exhibited a higher AUC than the single-sequence prediction models,with an AUC of 0.849,a sensitivity of 72.5%,and a specificity of 79.1%.The imaging-clinical fusion model whose predictive efficiency was close to that of multi-modal combined model(P=0.303)also performed well in forecasting postoperative glioma recurrence,with an AUC of 0.839,a sensitivity of 72.5%,and a specificity of 79.1%.Conclusion The multi-modal conventional MRI radiomics model can better predict early postoperative glioma recurrence.The imaging-clinical fusion model that includes glioma grade does not have the diagnostic performance superior to that of radiomics model.

Objective:To construct bacterial cytoplasmic membrane nanovesicles(BMV)with overexpressing programmed death 1(PD-1),denoted as BMV-PD-1 and evaluate the targeting efficacy of BMV-PD-1 towards transplanted lung tumor tissues in mice.Methods:The fusion plasmid ClyA-PD-1-EGFP fused by PD-1 and Cytolysin A(ClyA)was transferred into Escherichia coli BL21-Codonplus through plasmid transformation.Laser confocal microscopy,SDS-PAGE,and WB were used to detect the expression of the fusion protein ClyA-PD-1-EGFP.Bacterial membranes were extracted and processed with an extruder to generate BMV-PD-1.TEM and NTA were utilized to assess the morphology,size distribution,and zeta potential of BMV-PD-1,while WB was used to verify the presence of PD-1 protein.Laser confocal imaging was conducted to monitor the uptake of BMV-PD-1 by Lewis lung cancer cells.A C57BL/6J mouse subcutaneous transplant tumor model of LLC lung cancer cells was constructed,and the tumor targeting of BMV-PD-1 was evaluated by small animal imaging system.Results:Laser confocal microscopy images demonstrated that the plasmid ClyA-PD-1-EGFP was transferred into BL21-Codonplus and successfully expressed into protein.SDS-PAGE results suggested that ClyA-PD-1-EGFP was overexpressed in BL21-Codonplus.WB analysis indicated that PD-1 was expressed in bacteria and highly expressed in BMV-PD-1(P<0.001).NTA and TEM analyses revealed that BMV-PD-1 were spherical vesicles with a diameter of(145±14)nm and a negative surface charge.Laser confocal imaging showed that the high expression of PD-1 significantly increased the uptake of BMV-PD-1 by lung cancer cells(P<0.01).In vivo imaging of small animals further confirmed that the high expression of PD-1 can effectively improve cancer targeting of BMV-PD-1(P<0.01).Conclusion:In this study,bacterial plasma membrane nanovesicles BMV-PD-1 with high PD-1 expression are successfully constructed,and it is found that PD-1 overexpression markedly improve the mouse lung cancer xenograft tissue targeting specificity of BMV-PD-1,laying the groundwork for further development of BMV-PD-1 as a carrier for targeted drug delivery systems in tumors.

Objective To investigate the current postoperative physical activity levels of lung cancer patients after a month and to analyze the influencing factors.Methods From January to December 2023,a total of 1,195 lung cancer patients from 16 hospitals in eastem,central and westem China were selected as the survey subjects by the convenient sampling method.A cross-sectional survey was conducted by General Information Questionnaires,Health-Related Physical Fitness Surveys,MD Anderson Symptom Inventory,Hospital Anxiety and Depression Scale,Social Support Rating Scale,Self-Rated Abilities for Health Practices Scale,and the International Physical Activity Questionnaire.Results 36 questionnaires with missing data exceeding 10％and 13 duplicate questionnaires were excluded,resulting in the analysis of 1,146 questionnaires.After a month postoperatively,lung cancer patients with moderate and low levels of physical activity were 732(63.9％)and 204(17.8％),respectively.Multivariate regression analysis showed that the influencing factors included residence,average monthly family income,regional lymph node staging,family history of lung cancer,grip strength,hemoglobin,and depression score(P＜0.05).Conclusion The physical activity level of lung cancer patients a month after surgery is influenced by a combination of sociodemographic,disease-related,health-related physical fitness,and psychological factors.Clinical healthcare professionals should accurately assess the physical activity levels of lung cancer patients,identify those with insufficient physical activity,and develop and implement personalized intervention strategies based on their physical condition and potential influencing factors to enhance their physical activity levels and improve their quality of life.

Abstract: Objective To explore the trend of maternal mortality in Hainan Province during the period of 2003-2022, both in the province and in urban and rural areas, and to forecast the maternal mortality rate for the period 2023-2025. Methods The 2003-2022 data collected from Hainan Province's three-tier network for maternal mortality surveillance was examined using the Chi-square test for trend (CMH) to analyze the province-wide and urban-rural maternal mortality trends. The time series model forecasting using exponential smoothing was used to predict the maternal mortality rate in Hainan Province from 2023 to 2025. Results　From 2003 to 2022, a total of 201 011 616 live births and 463 maternal deaths were reported in Hainan Province, with a maternal mortality rate of 23.03 per 100 000. Over 20 years, the maternal mortality rate in Hainan Province showed a downward trend, with an annual rate of decline of -4.13%. The rate decreased significantly during this period.. From 2003 to 2022, the maternal mortality rate in rural areas of Hainan Province was 25.74/100 000 (373/1 448 943), and it was significantly higher than that in urban areas, 16.04/100 000 (90/561 173). In the first 10 years, the gap between urban and rural areas progressively reduced, but it widened significantly in the last decade, especially after 2017. The maternal mortality rate was significantly lower in urban than rural areas, and the differences had statistical significance. The annual rates of decline in maternal mortality in Hainan Province and in urban and rural areas from 2003 to 2022 were -5.0% and -3.71%, respectively, showing a negative growth with the decrease rate in rural areas lower than urban areas. The maternal mortality rate in Hainan Province showed a fluctuating downward trend, different from the stable trend of national decrease. The mortality rates for direct obstetric causes of death (233 cases) and indirect obstetric causes of death (230 cases) were 11.59/100 000 and 11.44/100 000, respectively. The results of the maternal mortality review showed a predominance of avoidable deaths (315 cases, 68.03%). Brown's cubic exponential smoothing predicted the maternal mortality rate in Hainan Province for 2023-2025 as 9.45/100 000, 8.17/100 000, and 6.89/100 000. Conclusions　The maternal mortality rate in Hainan Province is largely influenced by maternal deaths in rural areas, and maternal health care in rural areas should be emphasized. Measures such as intervening to address the main factors influencing avoidable maternal deaths, strengthening high-risk maternal management, improving the level of critical maternal care, and providing subsidies for critical maternal care can sustainably reduce the maternal mortality rate in Hainan.

Abstract： Objective　To establish a screening-diagnosis-evaluation system of neonatal congenital heart disease (CHD) suitable for Hainan Province based on the application of percutaneous blood oxygen saturation measurement and cardiac auscultation screening, and to provide a basis for further promotion of the evaluation effect. Methods　Screening agencies (all midwifery institutions) used the "double index method" to screen newborns for congenital heart disease. Those who were screened positive for any index were transferred to diagnostic institutions (the people's hospitals of all cities and counties and some tertiary hospitals) for echocardiography examination within 1 week. Those with abnormal results were transferred to the treatment institution (two tertiary hospitals) for reconfirmation and evaluation. All data were managed online. Results　In this study, 96 913 newborns born in midwifery institutions in 19 cities and counties were screened, with a response rate of 99.44%. The ratio of male infants (50 836) to female infants (46 077) was 1.10∶1. A total of 2 284 positive patients were screened by dual index method, and ultrasound diagnosis was performed, with the rate of cardiac ultrasonography of 98.07% (2 240/2 284) and a high response rate. A total of 238 cases of congenital heart disease were diagnosed (incidence rate of 0.25%), with the top three main types were ventricular septal defect, atrial septal defect, and patent ductus arteriosus. The sensitivity (88.24%) and Youden index (0.86) of dual-indicator screening for CHD detection were significantly higher than the other separate indicators. Through Kappa consistency test analysis, the consistency of dual-indicator screening with simple heart murmur screening results was excellent, with a Kappa coefficient value of 0.835 (>0.75); the consistency of dual-indicator screening and simple POX screening results was good, with a Kappa coefficient value of 0.429 (between 0.40-0.75), and the differences were statistically significant (P<0.001). By the end of the study, 136 children had undergone open-chest/occlusion surgery, with good postoperative recovery, and the rest were followed up. Conclusions　The neonatal CHD screening-diagnosis-assessment technology system established in this study, with close connections between various blocks, high screening response rate and echocardiography examination rate, is beneficial for the early diagnosis and treatment of CHD children, and has certain application value in institutions at all levels in Hainan Province, and is worth further promotion.

Abstract: Objective　To evaluate the free thalassaemia screening programme for preconception and pregnancy in Hainan Province, and to provide a theoretical basis for optimizing the screening process for thalassaemia. Methods From November 2020 to July 2021, a survey was conducted on 10 396 adults with Hainan household registration who participated in the Epidemiological Survey of Thalassemia in Hainan Residents in 19 cities and counties of Hainan Province. All of them underwent routine blood tests, haemoglobin electrophoresis tests and genetic tests for thalassaemia. The optimal diagnostic cut-off values for mean corpuscular volume (MCV), mean corpuscular haemoglobin (MCH), and haemoglobin adult type 2 (HbA2) were determined using screening test indexes such as receiver operating characteristic curve and sensitivity. The diagnostic effectiveness of different primary screening programs for thalassemia gene carriers was evaluated. Results Using the existing MCV single-indicator thalassemia primary screening protocol in Hainan Province, where individuals with MCV<82 fL undergo thalassemia gene testing, resulted in a high missed diagnosis rate (34.06%) and low sensitivity (65.94%). The optimal cut-off values for MCV screening for alpha-and beta-thalassaemia were 84.45 fL and 79.05 fL, respectively; the optimal cut-off values for MCH screening for alpha-and beta-thalassaemia were 27.95 pg and 25.15 pg, respectively. The optimal cut-off value for HbA2 screening for alpha-thalassaemia was less than 2.55% and greater than 3.35% for beta-thalassaemia. The "combined HbA2 or MCH or MCV screening protocol" with the cut-off values recommended in this study had a better performance in primary screening for thalassemia, with the highest sensitivity (92.96%) and negative predictive value (92.67%) and the lowest underdiagnosis rate (7.04%), statistically significant differences compared with the existing protocol (P<0.05). Conclusions The current process of screening for thalassemia in Hainan Province may lead to missed diagnoses. The combined use of MCV, MCH and HbA2 for thalassemia screening, adopting locally suitable cutoff values for primary screening indicators, can improve the incidence of missed reporting of thalassemia and enhance diagnostic effectiveness.