BACKGROUND: Circadian syndrome (CircS) may be closely linked to lifestyle, psychological, and occupational factors, but evidence is lacking. This study aimed to explore complex associations between lifestyle, psychological and occupational factors and CircS among employed people in southwestern China. METHODS: In this study, network analysis was used to identify complex associations between lifestyle, psychological and occupational factors and CircS in employed people from the Chinese Cohort of Working Adults (CCWA). The centrality of each variable was estimated by strength centrality index, which was calculated by the sum of edge weights connected to the variable. Bridge in the network was identified as the variables in the top 80 th percentile of overall bridge strength, which was defined as the most strongly connected variables across lifestyle, psychological and occupational factors and CircS. The differences were assessed in network structures between subgroups divided by the median score of the variable with the strongest bridge strengthen. RESULTS: Among 31,105 participants from CCWA, 5213 (16.76%) had CircS. In the constructed network, anxiety (edge weights: 0.28), smoking (edge weights: 0.15), drinking (edge weights: 0.10), perceived noise at work (edge weights: 0.08), and implicit health attitude (edge weights: -0.02) were directly related to CircS, with 83.31% of the variance for CircS explained by these neighboring factors. Anxiety was the most central variable (strength centrality: 1.20) in the network and the strongest bridge (bridge strength: 0.84) connecting all domains of variables. A stronger association between anxiety and CircS was observed in the network of participants with more severe anxiety (edge weight: 0.23) than those with less severe anxiety (edge weight: 0.03). CONCLUSION Anxiety had the strongest association with CircS and was the central factor with the highest strength centrality, also the bridge with the highest bridge strength in the network.
Humans ; Male ; Female ; Adult ; China ; Middle Aged ; Life Style ; Chronobiology Disorders/epidemiology*

The excipient processing is an essential part of traditional Chinese medicine processing, and understanding its scientific connotations is a critical scientific issue that urgently needs resolution. Building upon a foundation where the composition of traditional Chinese medicine substances is fundamentally clear, this paper applies the techniques and methods of chemoinformatics to the study of the excipient processing mechanism. Relevant information on traditional Chinese medicines processed with four kinds of excipients (wine, vinegar, salt and honey) was collected, including properties, taste, meridian tropism, chemical components, etc. Molecular descritors and skeletons corresponding to each chemical component were calculated using chemoinformatics to characterize the properties and structural features of the components. Characteristic components associated with the four excipients (wine, vinegar, salt and honey) were explored through multivariate statistical analysis and Murcko skeleton analysis. Further analysis, taking honey-processed Astragali Radix as an example, the focus was on the impact of the processing excipient honey on the solubility and permeability of its characteristic pharmacologically active components (isoflavones). It was discovered that the excipient honey can increase their solubility and permeability, emphasizing that the impact of processing excipients on the pharmacological classification properties is a key breakthrough in elucidating the mechanism of excipient processing. In summary, this study analyzed the characteristic components associated with the processing excipients "wine, vinegar, salt and honey" based on their composition characteristics, providing data support for the research on the mechanism of excipient processing from a biopharmaceutical perspective.

Objective To investigate the risk factors for bronchopulmonary dysplasia(BPD)in twin preterm infants with a gestational age of<34 weeks,and to provide a basis for early identification of BPD in twin preterm infants in clinical practice.Methods A retrospective analysis was performed for the twin preterm infants with a gestational age of<34 weeks who were admitted to 22 hospitals nationwide from January 2018 to December 2020.According to their conditions,they were divided into group A(both twins had BPD),group B(only one twin had BPD),and group C(neither twin had BPD).The risk factors for BPD in twin preterm infants were analyzed.Further analysis was conducted on group B to investigate the postnatal risk factors for BPD within twins.Results A total of 904 pairs of twins with a gestational age of<34 weeks were included in this study.The multivariate logistic regression analysis showed that compared with group C,birth weight discordance of>25%between the twins was an independent risk factor for BPD in one of the twins(OR=3.370,95%CI:1.500-7.568,P<0.05),and high gestational age at birth was a protective factor against BPD(P<0.05).The conditional logistic regression analysis of group B showed that small-for-gestational-age(SGA)birth was an independent risk factor for BPD in individual twins(OR=5.017,95%CI:1.040-24.190,P<0.05).Conclusions The development of BPD in twin preterm infants is associated with gestational age,birth weight discordance between the twins,and SGA birth.

Objective:To explore the association between occupational noise perception and cardiovascular disease (CVD), depression symptoms, as well as their comorbidity in occupational population and provide evidence for the prevention and control of physical and mental illnesses.Methods:A cross-sectional survey design was adopted, based on baseline data in population in 28 prefectures in Sichuan Province and Guizhou Province, and 33 districts (counties) in Chongqing municipality from Southwest Occupational Population Cohort from China Railway Chengdu Group Co., Ltd. during October to December 2021. A questionnaire survey was conducted to collect information about noise perception, depressive symptoms, and the history of CVD. Latent profile analysis model was used to determine identify noise perception type, and multinomial logistic regression analysis was conducted to explore the relationship between different occupational noise perception types and CVD, depression symptoms and their comorbidity.Results:A total of 30 509 participants were included, the mean age was (36.6±10.5) years, and men accounted for 82.0%. The direct perception of occupational noise, psychological effects and hearing/sleep impact of occupational noise increased the risk for CVD, depressive symptoms, and their comorbidity. By using latent profile analysis, occupational noise perception was classified into four levels: low, medium, high, and very high. As the level of noise perception increased, the association with CVD, depressive symptoms, and their comorbidity increased. In fact, very high level occupational noise perception were found to increase the risk for CVD, depressive symptoms, and their comorbidity by 2.14 (95% CI: 1.73-2.65) times, 8.80 (95% CI: 7.91-9.78) times, and 17.02 (95% CI: 12.78-22.66) times respectively compared with low-level occupational noise perception. Conclusions:Different types of occupational noise perception are associated with CVD and depression symptom, especially in the form of CVD complicated with depression symptom. Furthermore, the intensity of occupational noise in the work environment should be reduced to lower the risk for physical and mental health.

Objective:To understand the influence of unhealthy lifestyle on diabetic dyslipidemia and the key influencing factors in occupational population and provided scientific evidence for the prevention of diabetic dyslipidemia.Methods:Based on baseline data and follow-up data of Southwest Occupational Population Cohort from China Railway Chengdu Group Co., Ltd. during 2021. Diabetic dyslipidemia was defined as diabetes plus one or more forms of dyslipidemia, and unhealthy lifestyle factors included smoking, alcohol consumption, unhealthy dietary patterns, low physical activity, and abnormal BMI. Multivariate logistic regression model was used to analyze the relationship between unhealthy lifestyle scores and diabetic dyslipidemia, network analysis was used to find and explore the key lifestyles influencing glycolipid metabolism.Results:A total of 25 631 subjects were included. People with unhealthy lifestyle score 2 and 3 were 1.93 (95% CI: 1.31-2.86) times and 2.37 (95% CI: 1.60-3.50) times more likely to have diabetes with ≥1 forms of dyslipidemia than those with scores of 0; People with unhealthy lifestyle score 1, 2 and 3 were 1.98 (95% CI: 1.08-3.61) times, 2.87 (95% CI: 1.60-5.14) times and 3.95 (95% CI: 2.22-7.06) times more likely to have diabetes with ≥2 forms of dyslipidemia than those with score 0. Network analysis found that abnormal BMI and HDL-C were the "bridge nodes" that link unhealthy lifestyles with diabetic dyslipidemia. Conclusion:The higher the score of unhealthy lifestyle, the higher the risk for diabetic dyslipidemia, abnormal BMI and HDL-C are key factors influencing the association between unhealthy lifestyle and diabetic dyslipidemia.

Objective:To investigate the association between alcohol consumption and hypertension and SBP, DBP and the mediating effects of body mass index (BMI) and lipid level in occupational population, and provide reference for the intervention and prevention of hypertension.Methods:Based on the data of Southwest Occupational Population Cohort from China Railway Chengdu Group Co., Ltd., the information about the demographic characteristics, behavior and lifestyle, blood pressure and lipids level of the participants were collected through questionnaire survey, physical examination and blood biochemical test. Logistic/linear regression was used to analyze the association between alcohol consumption and hypertension, SBP and DBP. The individual and joint mediating effects of BMI, HDL-C, LDL-C, TG, and TC were explored through causal mediating analysis. A network analysis was used to explore the correlation between alcohol consumption, BMI and lipid levels, and hypertension.Results:A total of 22 887 participants were included, in whom 1 825 had newly detected hypertension. Logistic regression analysis found that current/former drinkers had a 33% increase of risk for hypertension compared with never-drinkers ( OR=1.33, 95% CI:1.19-1.48). Similarly, alcohol consumption could increase SBP ( β=1.05, 95% CI:0.69-1.40) and DBP ( β=1.10, 95% CI:0.83-1.38). Overall, BMI and lipid levels could mediate the associations between alcohol consumption and hypertension, SBP and DBP by 21.91%, 28.40% and 22.64%, respectively. BMI and TG were the main mediators, and they were also the two nodes with the highest edge weight and bridge strength centrality in the network of alcohol consumption, BMI, lipid levels and hypertension. Conclusions:Alcohol consumption was associated with increased risk for hypertension, and BMI and TG were important mediators and key nodes in the network. It is suggested that paying attention to the alcohol consumption, BMI and TG might help prevent hypertension in occupational population.

As artificial intelligence technology rapidly advances, its deployment within the medical sector presents substantial ethical challenges. Consequently, it becomes crucial to create a standardized, transparent, and secure framework for processing medical data. This includes setting the ethical boundaries for medical artificial intelligence and safeguarding both patient rights and data integrity. This consensus governs every facet of medical data handling through artificial intelligence, encompassing data gathering, processing, storage, transmission, utilization, and sharing. Its purpose is to ensure the management of medical data adheres to ethical standards and legal requirements, while safeguarding patient privacy and data security. Concurrently, the principles of compliance with the law, patient privacy respect, patient interest protection, and safety and reliability are underscored. Key issues such as informed consent, data usage, intellectual property protection, conflict of interest, and benefit sharing are examined in depth. The enactment of this expert consensus is intended to foster the profound integration and sustainable advancement of artificial intelligence within the medical domain, while simultaneously ensuring that artificial intelligence adheres strictly to the relevant ethical norms and legal frameworks during the processing of medical data.
Artificial Intelligence/legislation & jurisprudence* ; Humans ; Consensus ; Computer Security/standards* ; Confidentiality/ethics* ; Informed Consent/ethics*

In the outbreak of COVID-19,triage procedures based on epidemiology were implemented in a local hospital in Changsha to control the transmission of SARS-CoV-2 and avoid healthcare-associated infection.This re-trospective study analyzed the data collected during the triage period and found that COVID-19 patients were en-riched 7 folds into the Section A designated for patients with obvious epidemiological history.On the other side,nearly triple amounts of visits were received at the Section B for patients without obvious epidemiological history.8 COVID-19 cases were spotted out of 247 suspected patients.More than 50％of the suspected patients were submi-tted to multiple rounds of nucleic acid analysis for SARS-CoV-2 infection.Of the 239 patients who were diagnosed as negative of the virus infection,188 were successfully revisited and none was reported as COVID-19 case.Of the 8 COVID-19 patients,3 were confirmed only after multiple rounds of nucleic acid analysis.Besides comorbidities,delayed sharing of epidemiological history added complexity to the diagnosis in practice.The triaging experience and strategy will be helpful for the control of infectious diseases in the future.

Uric acid (UA) is the final product of purine metabolism in human body,and its metabolic disorder will induce hyperuricemia (HUA).The occurrence and development of HUA are associated with a variety of pathological mechanisms such as oxidative stress injury,activation of inflammatory cytokines,and activation of renin-angiotensin-aldosterone system.These mechanisms directly or indirectly affect the bioavailability of endogenous nitric oxide (NO).The decrease in NO bioavailability is common in the diseases with high concentration of UA as an independent risk factor.In this review,we summarize the mechanisms by which high concentrations of UA affect the endogenous NO bioavailability,with a focus on the mechanisms of high-concentration UA in decreasing the synthesis and/or increasing the consumption of NO.This review aims to provide references for alleviating the multisystem symptoms and improving the prognosis of HUA,and lay a theoretical foundation for in-depth study of the correlations between HUA and other metabolic diseases.
Humans ; Nitric Oxide ; Uric Acid ; Hyperuricemia ; Biological Availability ; Cytokines

Objective:To analyze the biological characteristics, phylogenic features and clinical significance of SQ219 and SQ220 isolated from clinical sputum and midstream urine specimens.Methods:The culture and biochemical characteristics of the two strains were observed. VITEK2 System, drug sensitivity testing and MALDI-TOF mass spectrometry were used for bacterial identification. Phylogenetic analysis based on 16S rRNA and core genome was performed. The average nucleotide identity (ANI) based on whole genome sequences was calculated.Results:SQ219 and SQ220 were Gram-stain-negative, aerobic, catalase- and oxidase-positive, and non-motile bacteria. Their optimum growth was observed in NaCl-free medium at 30℃ and pH7. Flexirubin-type pigments were produced by SQ220 on Colombia blood agar, but not by SQ219. Both SQ219 and SQ220 were resistant to aztreonam, amikacin, tobramycin and colistin, which was consistent with the drug resistance phenotype of genus Chryseobacterium. The genome sequences of SQ219 and SQ220 were 5.08 Mb and 4.80 Mb in length, and the G+ C contents were 36.72% and 36.36%, respectively. Both strains carried β-lactam resistance gene ( blaCGA). 16S rRNA phylogenetic analysis showed that SQ219 and SQ220 were closely related to Chryseobacterium gambrini DSM18014 T with the similarities of 98.93% and 98.36%, respectively. Core genome phylogenetic analysis revealed that SQ219 and SQ220 were highly homologous to Chryseobacterium gambrini DSM18014 T. However, the ANI values between the two strains and Chryseobacterium gambrini DSM18014 T were 92.49% and 93.27%, respectively, below the threshold for prokaryotic species identification. Conclusions:Based on the phenotypic and phylogenetic data, SQ219 and SQ220 represent a novel species of the genus Chryseobacterium. This study would help promote the understanding of the evolution of Chrysobacterium and provide reference for the identification of new species of Chrysobacterium.