Objective: To analyze the demographic characteristics of patients with red blood cell transfusion reactions, the usage of red blood cell preparations, and the differences in the composition ratio of adverse reactions based on multi-center data from the Haemovigilance Network, in order to reveal the clinical characteristics of red blood cell transfusion and its underlying issues. Methods: Clinical data of patients who experienced transfusion reactions after red blood cell transfusion in the Haemovigilance Network from 2018 to 2023 were collected. The demographic characteristics of patients who experienced transfusion reactions with different types of red blood cell preparations, the utilization of these preparations, and the differences of the composition ratios of transfusion reactions were analyzed. Count data were expressed as numbers (n) or percentages (%), and comparisons between groups were performed using the Chi-square test. Results: Red blood cell transfusion reactions were more common in females (53.56%), with the majority of patients aged 50-69 years (35.54%). The Han polulation accounted for the vast majority of patients (92.77%), and patients in the hematology and obstetrics/gynecology departments had a relatively high proportion of transfusion reactions (13.26% and 14.26%, respectively). Leukocyte-reduced red blood cells and suspended red blood cells were the most common types of transfusion reactions reported among red blood cell preparations. Allergic reactions and non-hemolytic febrile reactions were the most common transfusion reactions, and there were significant differences in the composition ratios of allergic reactions (χ =869.89, P<0.05) and non-hemolytic febrile reactions (χ =812.75, P<0.05) across various types of red blood cell preparations. Conclusion: There are differences in the demographic characteristics and composition ratio of transfusion reactions among different red blood cell preparations. The management of red blood cell transfusion reactions should be tailored to patient characteristics and conditions, and the selection and use of blood products should be optimized to reduce or avoid the occurrence of transfusion reactions, such as considering the use of washed red blood cells for patients with a history of transfusion allergies or those prone to allergies.

Objective:To analyze the predictive effects of the Big Five personality traits and emotions on self-management behaviors in patients with type 2 diabetes mellitus (T2DM).Methods:This study was a cross-sectional research. From 2016 to 2020, community interventions for self-management among patients with chronic diseases were conducted in Hangzhou, targeting patients with type 2 diabetes recruited from 69 community health service centers across the city. The data for this study were derived from the baseline information collected during the community intervention. The Chinese Big Five Personality Inventory (CBF-PI-15), the Type 2 Diabetes Self-Management Scale (2-DSCS), the Self-Rating Anxiety Scale (SAS), and the Self-Rating Depression Scale (SDS) were employed for questionnaire assessments. Biochemical indicators, including postprandial 2-hour blood glucose, glycated hemoglobin (HbA 1c), total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C), were measured. Spearman correlation analysis was used to examine the relationship between personality traits, relevant biochemical indicators, and self-management behaviors. Hierarchical regression analysis was employed to assess the predictive effects of the Big Five personality traits and emotions on self-management behaviors after controlling for demographic characteristics and factors related to health status. Results:A total of 839 patients were included in this study, comprising 518 females (61.75%) and 321 males (38.25%), with an average age of (66.92±8.67) years and an average disease duration of (8.87±6.91) years. There were significant differences in self-management behavior scores among patients with varying disease durations, educational levels, treatment methods, and levels of anxiety and depression ( t/F=6.172, 3.340, 4.699, 16.007, 27.127, all P<0.05). Neuroticism showed a negative correlation with various dimensions of self-management behaviors ( r=-0.130--0.073), while conscientiousness and agreeableness were positively correlated with various dimensions of self-management behaviors ( r=0.072-0.215). Dietary control score was negatively correlated with HbA 1c and LDL-C ( r=-0.106, -0.077), and regular exercise score was negatively correlated with postprandial 2-hour blood glucose, HbA 1c, TG, TC, HDL-C, and LDL-C ( r=-0.115--0.071). The total score of the 2-DSCS was negatively correlated with HbA 1c, TG, and TC ( r=-0.104--0.071). Patients with a disease duration exceeding 15 years and those receiving insulin injections or a combination of oral medication and insulin injections had higher total 2-DSCS score ( β=0.085, 0.146, 0.118, all P<0.05). Conversely, patients with higher HbA 1c and SDS standard scores had lower total 2-DSCS score ( β=-0.151, -0.328, both P<0.05), while those with higher agreeableness scores had higher total 2-DSCS score ( β=0.143, P<0.05). Conclusion:The traits of neuroticism, conscientiousness, and agreeableness within the Big Five Personality Traits, as well as anxiety and depressive emotions, are correlated with self-management behaviors. Specifically, agreeableness has a positive predictive effect on self-management behaviors, whereas depressive emotions have a negative predictive effect.

Objective To explore the brain damage of SD rats under different time points of hypobaric hypoxia exposure.Methods A rat high-altitube cerebral edema(HACE)model was constructed by simulating an altitude of 6 000 m in a hypobaric hypoxia animal experimental chamber.Thirty-six SD male rats were randomly divided into the control group and the hypobaric hypoxia exposure 3,7 and 14 d groups,with 9 rats in each group.Except for the control group,the rats in each group were continuously exposed to hypobaric hypoxia for 3,7,and 14 d.At the end of the modeling period,serum was collected by blood sampling via the abdominal aorta,and brain tissue samples were taken.The wet-to-dry ratio(W/D)of brain tissue was calculated,and the levels of relevant oxidative enzymes in serum and brain tissue were measured.The expression levels of hypoxia-inducible factor-1α(HIF-1α)and aquaporin 4(AQP4)mRNAs in brain tissue were detected by real-time fluorescence quantitative polymerase chain reaction.Results The W/D of brain tissues in the control group and the group exposed to hypobaric hypoxia for 3,7 and 14 d were 4.46±0.12,4.98±0.16,5.07±0.18 and 4.95±0.07;the superoxide dismutase contents were(111.86±2.45),(90.73±1.48),(79.64±2.56)and(55.33±1.45)U·g-1;the glutathione contents were(126.91±5.18),(125.26±1.53),(56.20±2.17)and(122.73±1.78)μg·mL-1;the malondialdehyde contents were(230.94±2.00),(362.65±3.28),(407.34±3.47)and(237.50±1.59)nmol·g-1;the relative expression levels of HIF-1 α mRNA were 1.00±0,2.99±0.49,4.72±0.49 and 1.91±0.28;the relative expression levels of AQP4 mRNA were 1.00±0,2.62±0.34,8.38±0.84 and 5.27±0.42,respectively.Statistically significant differences were found between the above indexes in the 3,7 and 14 d of hypobaric hypoxia exposure group compared with the control group(P＜0.05,P＜0.01).Conclusion Different time of hypobaric hypoxia exposure can up-regulate the expression of AQPs proteins in HACE rats and cause the disruption of the blood-brain barrier,and the HACE model constructed in the hypobaric hypoxia chamber with 6 000 m intervention for 7 d was more stable.

Objective:To explore the structural relationship between WMSDs in the upper limbs and various risk factors in the occupational population in China, based on a large sample epidemiological survey and structural equation analysis, and to establish a structural equation model, so as to lay a foundation for the prevention and control of such diseases.Methods:The Chinese version of the Musculoskeletal Disorders Electronic Questionnaire was used to conduct a nationwide survey on the prevalence of WMSDs in the upper extremity. Six factors related to WMSDs in the upper extremity were extracted by the classification standard of adverse ergonomic factors and their source and confirmatory factor analysis, including work organization, work type, upper extremity work posture, individual factors, upper extremity fatigue and upper extremity WMSDs. The structural equation analysis was carried out and the structural equation model was established.Results:The incidence of WMSDs and fatigue in the upper limbs was 24.44% and 43.76%, respectively. The adjusted structural equation model fitting indicators were generally up to the standard (GFI=1.000, AGFI=1.000, RMSEA=0.043, NFI=0.808, TLI=0.784) . The four exogenous latent variables of work organization, work type, upper limb work posture and individual factors were correlated. There was a strong positive correlation between job type and upper limb work posture ( r=0.865) , a moderate positive correlation between work organization and job type and upper limb work posture ( r=0.570, 0.490) , and a weak negative correlation between individual factors and the other three exogenous latent variables. Upper limb work posture and individual factors had direct effects on upper limb WMSDs, and the effect coefficients were 0.10 and 0.06, respectively. Upper limb fatigue played a mediating role between work organization, work type, upper limb work posture and upper limb WMSDs. The effect coefficient was 0.46, and the composition ratios of indirect effects were 100.0%, 100.0%, and 38.3%, respectively. The direct path effect of upper limb work posture, individual factors and upper limb WMSDs was weaker than the mediating path through upper limb fatigue. Conclusion:When carrying out the prevention and control of upper limbWMSDs, it is necessary to comprehensively consider the pathogenesis path of upper limb muscle fatigue and upper limb WMSDs caused by work organization, work type, and upper limb work posture, so as to provide theoretical reference for improving the prevention and control level of such diseases.

Objective To explore the brain damage of SD rats under different time points of hypobaric hypoxia exposure.Methods A rat high-altitube cerebral edema(HACE)model was constructed by simulating an altitude of 6 000 m in a hypobaric hypoxia animal experimental chamber.Thirty-six SD male rats were randomly divided into the control group and the hypobaric hypoxia exposure 3,7 and 14 d groups,with 9 rats in each group.Except for the control group,the rats in each group were continuously exposed to hypobaric hypoxia for 3,7,and 14 d.At the end of the modeling period,serum was collected by blood sampling via the abdominal aorta,and brain tissue samples were taken.The wet-to-dry ratio(W/D)of brain tissue was calculated,and the levels of relevant oxidative enzymes in serum and brain tissue were measured.The expression levels of hypoxia-inducible factor-1α(HIF-1α)and aquaporin 4(AQP4)mRNAs in brain tissue were detected by real-time fluorescence quantitative polymerase chain reaction.Results The W/D of brain tissues in the control group and the group exposed to hypobaric hypoxia for 3,7 and 14 d were 4.46±0.12,4.98±0.16,5.07±0.18 and 4.95±0.07;the superoxide dismutase contents were(111.86±2.45),(90.73±1.48),(79.64±2.56)and(55.33±1.45)U·g-1;the glutathione contents were(126.91±5.18),(125.26±1.53),(56.20±2.17)and(122.73±1.78)μg·mL-1;the malondialdehyde contents were(230.94±2.00),(362.65±3.28),(407.34±3.47)and(237.50±1.59)nmol·g-1;the relative expression levels of HIF-1 α mRNA were 1.00±0,2.99±0.49,4.72±0.49 and 1.91±0.28;the relative expression levels of AQP4 mRNA were 1.00±0,2.62±0.34,8.38±0.84 and 5.27±0.42,respectively.Statistically significant differences were found between the above indexes in the 3,7 and 14 d of hypobaric hypoxia exposure group compared with the control group(P＜0.05,P＜0.01).Conclusion Different time of hypobaric hypoxia exposure can up-regulate the expression of AQPs proteins in HACE rats and cause the disruption of the blood-brain barrier,and the HACE model constructed in the hypobaric hypoxia chamber with 6 000 m intervention for 7 d was more stable.

Objective:To analyze the predictive effects of the Big Five personality traits and emotions on self-management behaviors in patients with type 2 diabetes mellitus (T2DM).Methods:This study was a cross-sectional research. From 2016 to 2020, community interventions for self-management among patients with chronic diseases were conducted in Hangzhou, targeting patients with type 2 diabetes recruited from 69 community health service centers across the city. The data for this study were derived from the baseline information collected during the community intervention. The Chinese Big Five Personality Inventory (CBF-PI-15), the Type 2 Diabetes Self-Management Scale (2-DSCS), the Self-Rating Anxiety Scale (SAS), and the Self-Rating Depression Scale (SDS) were employed for questionnaire assessments. Biochemical indicators, including postprandial 2-hour blood glucose, glycated hemoglobin (HbA 1c), total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C), were measured. Spearman correlation analysis was used to examine the relationship between personality traits, relevant biochemical indicators, and self-management behaviors. Hierarchical regression analysis was employed to assess the predictive effects of the Big Five personality traits and emotions on self-management behaviors after controlling for demographic characteristics and factors related to health status. Results:A total of 839 patients were included in this study, comprising 518 females (61.75%) and 321 males (38.25%), with an average age of (66.92±8.67) years and an average disease duration of (8.87±6.91) years. There were significant differences in self-management behavior scores among patients with varying disease durations, educational levels, treatment methods, and levels of anxiety and depression ( t/F=6.172, 3.340, 4.699, 16.007, 27.127, all P<0.05). Neuroticism showed a negative correlation with various dimensions of self-management behaviors ( r=-0.130--0.073), while conscientiousness and agreeableness were positively correlated with various dimensions of self-management behaviors ( r=0.072-0.215). Dietary control score was negatively correlated with HbA 1c and LDL-C ( r=-0.106, -0.077), and regular exercise score was negatively correlated with postprandial 2-hour blood glucose, HbA 1c, TG, TC, HDL-C, and LDL-C ( r=-0.115--0.071). The total score of the 2-DSCS was negatively correlated with HbA 1c, TG, and TC ( r=-0.104--0.071). Patients with a disease duration exceeding 15 years and those receiving insulin injections or a combination of oral medication and insulin injections had higher total 2-DSCS score ( β=0.085, 0.146, 0.118, all P<0.05). Conversely, patients with higher HbA 1c and SDS standard scores had lower total 2-DSCS score ( β=-0.151, -0.328, both P<0.05), while those with higher agreeableness scores had higher total 2-DSCS score ( β=0.143, P<0.05). Conclusion:The traits of neuroticism, conscientiousness, and agreeableness within the Big Five Personality Traits, as well as anxiety and depressive emotions, are correlated with self-management behaviors. Specifically, agreeableness has a positive predictive effect on self-management behaviors, whereas depressive emotions have a negative predictive effect.

Objective:To explore the structural relationship between WMSDs in the upper limbs and various risk factors in the occupational population in China, based on a large sample epidemiological survey and structural equation analysis, and to establish a structural equation model, so as to lay a foundation for the prevention and control of such diseases.Methods:The Chinese version of the Musculoskeletal Disorders Electronic Questionnaire was used to conduct a nationwide survey on the prevalence of WMSDs in the upper extremity. Six factors related to WMSDs in the upper extremity were extracted by the classification standard of adverse ergonomic factors and their source and confirmatory factor analysis, including work organization, work type, upper extremity work posture, individual factors, upper extremity fatigue and upper extremity WMSDs. The structural equation analysis was carried out and the structural equation model was established.Results:The incidence of WMSDs and fatigue in the upper limbs was 24.44% and 43.76%, respectively. The adjusted structural equation model fitting indicators were generally up to the standard (GFI=1.000, AGFI=1.000, RMSEA=0.043, NFI=0.808, TLI=0.784) . The four exogenous latent variables of work organization, work type, upper limb work posture and individual factors were correlated. There was a strong positive correlation between job type and upper limb work posture ( r=0.865) , a moderate positive correlation between work organization and job type and upper limb work posture ( r=0.570, 0.490) , and a weak negative correlation between individual factors and the other three exogenous latent variables. Upper limb work posture and individual factors had direct effects on upper limb WMSDs, and the effect coefficients were 0.10 and 0.06, respectively. Upper limb fatigue played a mediating role between work organization, work type, upper limb work posture and upper limb WMSDs. The effect coefficient was 0.46, and the composition ratios of indirect effects were 100.0%, 100.0%, and 38.3%, respectively. The direct path effect of upper limb work posture, individual factors and upper limb WMSDs was weaker than the mediating path through upper limb fatigue. Conclusion:When carrying out the prevention and control of upper limbWMSDs, it is necessary to comprehensively consider the pathogenesis path of upper limb muscle fatigue and upper limb WMSDs caused by work organization, work type, and upper limb work posture, so as to provide theoretical reference for improving the prevention and control level of such diseases.

ObjectiveTo explore the molecular mechanism implicated in the treatment of primary myelofibrosis （PMF） using Chinese medicinal herbs （CMH） by bioinformatics and molecular dynamics. MethodsData mining was performed to find the high-frequency CMH in treating PMF between the year of 1985 and 2024 by searching CNKI， Chinese Science and Technology Journal Database （CCD）， and China Academic Journal Database （CSPD）. TCMSP， SwissTargetPrediction and related reports were used to collect the main active ingredients of high-frequency CMH and their targets. The PMF datasets GSE44426 and GSE124281 were downloaded from GEO database， and R software was used for data normalization and differentially expressed genes （DEGs） screening. Key module hub genes were obtained by weighted gene co-expression network analysis （WGCNA） analysis. The common intersection genes of active ingredient targets， DEGs and key module hub genes of CMH were selected， and the target network was generated using Cytoscape 3.9.2 software. The core target network was generated by topological analysis， while key pathways were selected by GO and KEGG pathway enrichment analysis， and protein interaction relationships were obtained from the String database， so as to construct drug-ingredient-target network and protein interaction network （PPI） relationship diagrams. Discovery Studio 2020 software was used to perform molecular docking， and the GROMACS program was used to perform molecular dynamics simulation. ResultsA total of 21 prescriptions were collected involving 121 herbs. There were 9 herbs with a frequency ≥10 times， which were Danshen （Radix et Rhizoma Salviae Miltiorrhizae）， Huangqi （Radix Astragali）， Baizhu （Rhizoma Atractylodis Macrocephalae）， Danggui （Radix Angelicae Sinensis）， Dangshen （Radix Codonopsis）， Gancao （Radix et Rhizoma Glycyrrhizae）， Baishao （Radix Paeoniae Alba）， Fuling （Poria） and Shudihuang （Radix Rehmanniae Praeparata） from high- to low-frequency. A total of 98 active ingredients and 1125 potential targets were obtained from 9 high-frequency CMH. GSE44426 and GSE124281 data sets screened out 24 gene samples， including 14 of the healthy control group and 10 of the PMF group， and identified 319 DEGs between the two groups， including 122 up-regulated genes and 197 down-regulated genes. WGCNA screened out 24 co-expression module genes and found that the five modules closely related to the onset of PMF were MEpink， MEdarkred， MEblack， MEgrey， and MEturquoise， involving 7112 key module hub genes. The GO and KEGG enrichment analyses indicated that lipids and the atherosclerosis pathways were mainly involved in the mechanism of above high-frequency CMH in treating PMF， which included six hub protein targets： HSP90AA1， HSP90AB1， SRC， MAPK1， IL1B and IL10. From the drug-ingredient-target network， seven active ingredients of CMH targeting at these six hub targets were found， including verbascoside， verbascos isoflavone， kaempferol， luteolin， naringenin， quercetin and pachymic acid. The molecular docking and molecular dynamics analyses showed that the key CMH were Shudihuang， Huangqi， Baishao， Danshen， Gancao and Fuling， and among the seven active ingredients， calycosin had the highest binding affinity with HSP90AB1. ConclusionThe main CMH for the treatment of PMF may be Shudihuang， Huangqi， Baishao， Danshen， Gancao and Fuling， and the active ingredients include verbascoside， verbascos isoflavones， kaempferol， luteolin， naringenin， quercetin and pachymic acid. The relevant targets are HSP90AA1， HSP90AB1， SRC， MAPK1， IL-10， and IL-1β， and the most critical pathways are lipid and atherosclerosis pathways.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

Objective:To analyze the distribution characteristics of work-related musculoskeletal disorders (WMSDs) among the occupational population in China's key industries during the period from 2018 to 2023, and to provide data support for the formulation of targeted prevention strategies.Methods:Between January 1, 2018, and December 31, 2023, a cross-sectional epidemiological survey and a retrospective investigation were conducted in seven geographical regions of North China, East China, Central China, South China, Southwest China, Northwest China, and Northeast China, using a combination of epidemiological cross-sectional and retrospective surveys. The industries were stratified according to the degree of closeness to WMSDs, the size of the occupational population, and the importance of the national economy, and then cluster sampling was conducted according to the size of the enterprises (large, medium, and small) within each stratum. Representative enterprises were selected, and workers who had been employed for more than one year and met the inclusion criteria were selected as the study subjects. The survey subjects completed the Chinese version of the Musculoskeletal Disorders Survey Questionnaire online by scanning a QR code. A total of 88, 609 valid questionnaires were collected. Continuous data were described by means and standard deviations, and the standardized incidence rates of WMSDs were evaluated using chi-square tests to compare the standardized incidence rates of different body parts.Results:The standardized prevalence rate of WMSDs among the frontline working population in China was 36.7%, with the top three being the neck (21.37%), shoulders (18.23%), and lower back (14.92%). There was a statistically significant difference in the standardized prevalence rate of WMSDs between different body parts (χ 2=47577.82, P<0.05). The lowest standardized prevalence rate of WMSDs was found in the southeast coastal region of China (32.54%), while the highest was in the northwest (49.70%) and northeast regions (46.16%). The standardized prevalence rate of WMSDs decreased from 42.88% in 2018 to 29.94% in 2023. The micro-enterprise observation group had a higher concentration of WMSDs in the neck (20.66%), lower back (17.95%), and shoulders (17.79%), while the large enterprise observation group had a higher concentration in the neck (20.54%), shoulders (17.52%), and lower back (14.65%). Among the industries surveyed, the highest standardized prevalence rate of WMSDs was found in the healthcare industry (53.18%), followed by the toy manufacturing industry (50.54%), the automotive manufacturing industry (43.39%), general aviation services (42.71%), and the ship and related equipment manufacturing industry (40.56%). The standardized prevalence rate of WMSDs among women was significantly higher than that of men ( OR value=1.44, P<0.05). In addition, the standardized prevalence rate of WMSDs with multiple affected body parts (four or more body parts affected simultaneously) was higher, and the risk of WMSDs increased with subjective fatigue, showing a significant "S-shaped" trend (the OR value was 2.19, 3.16, 4.71, 5.49, and 3.97 when the RPE was 13, 15, 17, 19, and 20, respectively. χ 2trend=17.23, P<0.001) . Conclusion:The distribution characteristics of WMSDs in key industries in China show obvious differences in different parts, regions, time, enterprise scale, industry and population attributes. Agriculture, pharmaceutical manufacturing, packaging and decoration and other printing industries have a high proportion of WMSDs in multiple parts at the same time and in a single site. It is necessary to study and implement precise preventive measures according to specific regions, industries and enterprise scales, as well as the characteristics of multi-site WMSDs, so as to effectively protect the health and well-being of the working population.