Yuliang Zhan

Severe acute respiratory syndrome (SARS) is an acute infectious disease of the respiratory system. Although a novel coronavirus has been identified as the causative agent of SARS, the pathogenic mechanisms of SARS are not understood. In this study, sera were collected from healthy donors, patients with SARS, patients with severe SARS, and patients with SARS in convalescence. The serum concentrations of interleukin-1 (IL-1), IL-4, IL-6, IL-8, IL-10, tumor growth factor beta (TGF-beta), tumor necrosis factor alpha (TNF-alpha), and gamma interferon (IFN-gamma) were measured by enzyme-linked immunosorbent assays (ELISA). The concentrations of IL-1 and TNF-alpha were not significantly different in different groups. The IL-6 concentration was increased in SARS patients and was significantly elevated in severe SARS patients, but the IL-6 concentrations were similar in convalescent patients and control subjects, suggesting that there was a positive relationship between the serum IL-6 concentration and SARS severity. The concentrations of IL-8 and TGF-beta were decreased in SARS patients and significantly reduced in severe SARS patients, but they were comparable in convalescent SARS patients and control subjects, suggesting that there was a negative relationship between the IL-8 and TGF-beta concentrations and SARS severity. The concentrations of IFN-gamma, IL-4, and IL-10 showed significant changes only in convalescent SARS patients. The IFN-gamma and IL-4 levels were decreased, while the levels of IL-10 were increased, and the differences between convalescent SARS patients and other patient groups were statistically significant. These results suggest that there are different immunoregulatory events during and after SARS and may contribute to our understanding of the pathogenesis of this syndrome.

AIM: To investigate the species distribution and antifungal susceptibility profiles of yeast isolates causing invasive infections across Beijing. MATERIALS & METHODS: A total of 1201 yeast isolates recovered from blood and other sterile body fluids were correctly identified by matrix-assisted laser desorption/ionization TOF MS supplemented by DNA sequencing. Antifungal susceptibility testing was performed according to the Clinical and Laboratory Standards Institute broth microdilution method. RESULTS: Candida (95.5%) remained the most common yeast species isolated; Candida albicans (38.8%) and Candida parapsilosis (22.6%) were the leading species of candidemia. Azole resistances were mainly observed in Candida glabrata and Candida tropicalis isolates. CONCLUSION: This study outlined the epidemiologic data of invasive yeast infections and highlighted the need for continuous monitoring of azole resistances among C. glabrata and C. tropicalis isolates in Beijing.

Objective: Inflammation and malnutrition are critical in heart failure (HF) progression. This study evaluated the prognostic value of inflammation- and nutrition-related indicators for mortality in HF. Methods: Retrospective analysis of 1999-2018 NHANES data (101,316 participants, 1,500 HF patients) assessed indicators including advanced lung cancer inflammation index (ALI), monocyte-to-albumin ratio (MAR), neutrophil-to-albumin ratio (NAR), red cell distribution width-to-albumin ratio (RAR), prognostic nutritional index (PNI), geriatric nutritional risk index (GNRI), hemoglobin-albumin-lymphocyte-platelet (HALP) score and controlling nutritional status (CONUT) score. Associations with all-cause and cardiovascular mortality were analyzed via Kaplan-Meier curves, Cox regression, restricted cubic spline, time-dependent ROC, and random survival forest (RSF). Results: A total of 1,500 HF patients were included in the final analysis. Kaplan-Meier analysis demonstrated that elevated MAR, NAR, RAR, and CONUT scores were linked to higher mortality, whereas elevated ALI, PNI, GNRI, and HALP scores were associated with lower mortality in HF patients. After false discovery rate (FDR) correction, the majority of indicators (including ALI, RAR) remained significantly associated with mortality in multivariable Cox models. Time-dependent ROC analysis demonstrated that RAR exhibited the strongest predictive ability for 1-year all-cause mortality (AUC = 0.768, 95% CI: 0.718-0.819) and cardiovascular mortality (AUC = 0.788, 95% CI: 0.725-0.851). In contrast, ALI showed the best predictive performance for mortality at 3 years (all-cause: AUC = 0.690, 95% CI: 0.654-0.726; cardiovascular: AUC = 0.705, 95% CI: 0.655-0.756), 5 years (all-cause: AUC = 0.679, 95% CI: 0.647-0.711; cardiovascular: AUC = 0.677, 95% CI: 0.633-0.721), and 10 years (all-cause: AUC = 0.691, 95% CI: 0.657-0.725; cardiovascular: AUC = 0.699, 95% CI: 0.656-0.742). These findings were consistent with the C-index results. RSF analysis, validated by an internal hold-out test, consistently identified ALI as a leading predictor of mortality risk. Conclusion: Compared with other inflammation- and nutrition-related indicators, RAR and ALI may provide superior predictive value for short-term and long-term mortality risk, respectively, in HF patients.