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It has been 3 years since the first appearance of COVID-19 in China. During this time, social isolation was widely used as an important method to fight it. However, this measure had many negative effects on the mental health of college students. To better understand this issue, this study aims to explore the impact of social isolation and COVID-19-related stress on psychological distress among Chinese college students. Additionally, resilience has been evaluated as a key component of stress resistance in this situation. Coronavirus Stress Measure (CSM), the Connor-Davidson Resilience Scale (CD-RISC) and the Brief Symptom Inventory (BSI) were used in this study. A total of 388 Chinese college students participated in the survey via the Internet. Two groups (isolated group vs. non-isolated group) were divided according to whether they have been isolated from their classmates and families. Data analysis adopts t-test, F test and mediate effect analysis by SPSS21.0. (1) All factors, except resilience, were found to have lower scores in the isolated group; (2) significant correlations were found between all factors; (3) resilience partially mitigated the impact of COVID-19 stress on psychological symptoms. Social isolation has been found to be a significant factor contributing to negative psychological distress in Chinese college students. The COVID-19-related stress may increase the likelihood of psychological suffering among isolated group. Resilience can help reduce the negative effects of COVID-19 stress on college students. Therefore, providing appropriate psychological support tailored to different isolation situations is crucial. [ABSTRACT FROM AUTHOR]

Early and differential diagnosis of sepsis is essential to avoid unnecessary antibiotic use and further reduce patient morbidity and mortality. Here, we aimed to identify predictors of sepsis and advance a machine-learning strategy to predict sepsis-induced respiratory tract infection (RTI). Patients with sepsis and RTI were selected via retrospective analysis, and essential population characteristics and laboratory parameters were recorded. To improve the performance of the primary model and avoid over-fitting, a recursive feature elimination with cross-validation (RFECV) strategy was used to screen the optimal subset of biomarkers and construct nine machine-learning models based on this subset; the average accuracy, precision, recall, and F1-score were used for evaluation of the models. We identified 430 patients with sepsis and 686 patients with RTI. A total of 39 features were collected, with 23 features identified for initial model construction. Using the RFECV algorithm, we found that the XGBoost classifier, which only needed to include seven biomarkers, demonstrated the best performance among all prediction models, with an average accuracy of 89.24 ± 2.28, while the Ridge classifier, which included 11 biomarkers, had an average accuracy of only 83.87 ± 4.69. The remaining models had prediction accuracies greater than 88%. We developed nine models for predicting sepsis using a strategy that combined RFECV with machine learning. Among these models, the XGBoost classifier, which included seven biomarkers, showed the best performance and highest accuracy for predicting sepsis and may be a promising tool for the timely identification of sepsis. [ABSTRACT FROM AUTHOR]

Background: Complex interconnections are evident among gut microbiota, circulating metabolites, inflammatory cytokines, and the pathogenesis of abdominal aortic aneurysms (AAA), with the causal dynamics yet to be comprehensively elucidated. The primary objective of this study was to elucidate the potential causal relationships involving gut microbiota-mediated plasma metabolites, inflammatory cytokines, and AAA. Methods: We utilized data from genome-wide association studies predominantly comprising individuals of European ancestry, encompassing four major gut microbiota signatures, 233 plasma metabolite signatures (N = 136,016), 91 inflammatory cytokine signatures (N = 14,824), and AAA signatures (N = 1,458,875). Mendelian randomization (MR), employed in a two-sample format, was utilized as a tool to investigate the potential causal pathways from gut microbiota to the development of AAA. Additionally, a two-step MR approach was employed to dissect the impact of plasma metabolites and inflammatory cytokines on the relationship between gut microbiota and AAA and to ascertain the mediated fractions. Results: Our findings indicate that five phylum or family-identical bacteria, 175 plasma metabolites, and seven inflammatory factors are causally associated with AAA. Among them, five bacterial species from the same phylum or family, identified from different GWAS data, were strongly associated with AAA. Of these, two exhibited negative causality and three exhibited positive causality. We found that the phylum Firmicutes and the families Oscillospiraceae might reduce the risk of AAA, whereas the families Prevotellaceae, Sutterellaceae, and Aminobacteriaceae might increase the risk of AAA. Further screening indicated that phylum Firmicutes id.1672 (GCST90017114) may confer a protective effect against AAA by reducing triglyceride levels in medium/small high-density lipoprotein (HDL). Conclusion: MR analysis has delineated a causal pathway from gut microbiota, through plasma circulating metabolites and inflammatory cytokines, to the pathogenesis of AAA. The role of intestinal flora and certain biomarkers may provide a reference for the diagnosis of AAA, and contribute to the prevention, diagnosis, and treatment of AAA disease. [ABSTRACT FROM AUTHOR]

Magnesium dicarbide (MgC2) at high pressure has been systematically investigated using the first-principle methods. Ten possible structures were studied and three of them (Cmcm, C2/m, P-3m1) were found to be dynamically and mechanically stable under the given pressure. The calculated formation enthalpies indicated that the Cmcm structure was thermodynamically unstable while the C2/m and P-3m1 structures were thermodynamically stable. The interesting thing was that the P-3m1 structure of MgC2 could also be as potential hard materials owing to their Vickers hardness closing to 40 GPa with increasing pressure. The Cmcm and C2/m structures presented ductile behaviour while P-3m1 structure displayed brittle character. The elastic anisotropy of Young's modulus E and shear modulus G became smaller with the increasing pressure, and the P-3m1 structure possessed a lower anisotropy in E and G than Cmcm and C2/m structures. The Cmcm and C2/m structures of MgC2 had metallic characteristic; however, the P-3m1 structure of MgC2 was semiconductor with an indirect band gap. [ABSTRACT FROM AUTHOR]

To explore the predictive value of neutrophil–lymphocyte ratio (NLR) at presentation for delayed neurological sequelae (DNS) in carbon monoxide (CO) poisoning. This single-center retrospective observational study included a total of 253 consecutive patients who visited the emergency department (ED) due to acute CO intoxication between 7 October 2015 and 31 December 2019. The included patients had a history of coma and their blood routine was measured within one hour of ED admission. They were divided into two groups according to the presence of DNS, including those who developed DNS (DNS group) and those who did not (non-DNS group). A total of 171 patients were included in this research, and 49 (28.7%) developed DNS. The median NLR at ED admission was obviously higher in the DNS group (10.60 [9.69–15.34]) than in the non-DNS group (7.53 [5.86–8.56]) (p < 0.001). Multivariate analysis indicated that a high NLR (adjusted odds ratio (AOR): 1.78, 95% confidence interval (CI): 1.46–2.18) and the occurrence of acute brain lesions (AOR: 7.50, 95%CI: 2.86–19.68) on diffusion-weighted imaging were independent predictors of DNS. The NLR was more than 8.97. The prediction of occurrence of DNS had a sensitivity of 93.88% and a specificity of 84.43%. Kappa value was 0.713. The predicted results showed good authenticity and consistency. The level of NLR at presentation had good predictive value for the development of DNS, showing the superior value for clinical application. [ABSTRACT FROM AUTHOR]

Objective: To examine whether spironolactone could reduce the severity of obstructive sleep apnea (OSA) and lower blood pressure in patients with resistant hypertension.Methods: This was a blank-controlled, single-center study. Patients with resistant hypertension and moderate-to-severe OSA (apnea–hypopnea index >15 events/h) were enrolled and randomly assigned to the therapy or control group. Patients in the therapy group were administered spironolactone 20 mg once daily (up to 40 mg once daily for 4 weeks, if required) in addition to original antihypertensive medication. Follow-up was 12 weeks.Results: Thirty patients were enrolled (n= 15 per group). After 12 weeks of follow-up, apnea–hypopnea index (21.8 ± 15.7 vs. 1.8 ± 12.8,p< 0.05), hypopnea index (9.8 ± 11.1 vs. −2.7 ± 16.8,p< 0.05), oxygen desaturation index (20.8 ± 15.0 vs. 0.3 ± 16.1,p< 0.05), clinical blood pressure, ambulatory blood pressure, and plasma aldosterone level (9.8 ± 6.3 vs. 2.9 ± 6.7,p< 0.05) were reduced significantly in the therapy group compared with the control group. No side effects were reported.Conclusions: Spironolactone reduced the severity of OSA and reduced blood pressure in resistant hypertension patients with moderate-to-severe OSA. These findings may assist in the treatment of OSA in patients with resistant hypertension. [ABSTRACT FROM AUTHOR]

A phase transition of MgS under high pressure is investigated using a first-principles method. It is found from energy-volume calculations that the rock-salt (B1) phase of MgS transforms into a FeSi-type (B28) phase at 143 GPa. The calculated ground-state parameters in the B1 phase are in excellent agreement with available experimental and theoretical data.Ab initiophonon calculations are also performed to investigate the structural behaviour of MgS under high pressure. An unstable transverse acoustic mode and a phase transition from B1 to B28 phase at ~143.7 GPa driven by this soft mode are predicted. The B28 structure of MgS is stable up to 350 GPa according to lattice dynamics calculations. [ABSTRACT FROM AUTHOR]