Predictive value of fasting blood glucose and TG/HDL-C ratio in non-diabetic patients with COVID-19

Objective: To investigate the predictive values of fasting blood glucose and triglyceride/high-density lipoprotein cholesterol ratio (TG/HDL-C) in non-diabetic patients with COVID-19. Methods: A total of 39 non-diabetic patients with COVID-19 admitted to the Fourth Hospital of Xi'an from December 2021 to January 2022 were included. And 34 health examination subjects from the Second Affiliated Hospital of Xi'an Jiaotong University were matched as health control according to their propensity score. The clinical characteristics and laboratory test results between groups were compared, and the predictive value of fasting glucose and TG/HDL-C in non-diabetic COVID-19 patients was analyzed by logistic regression and receiver operating curve (ROC). Results: COVID-19 patients were either mild (30 cases) or common type (9 cases) with mild symptoms and good clinical prognosis. The median age was 29.0 (20.0, 49.0) years, 24 (61.5%) were males. Fasting blood glucose (4.30+or-0.47 mmol/L) and HDL-C [1.07 (0.86, 1.30) mmol/L] levels in COVID-19 patients were significantly lower than healthy controls [5.15+or-0.70 mmol/L, 2.24 (1.77, 3.05) mmol/L], the differences were statistically significant (t=6.277, P < 0.001;Z=6.026, P < 0.001). However, low density lipoprotein cholesterol (LDL-C) [2.40 (1.81, 2.91) mmol/L] and TG/HDL-C [0.91 (0.54, 1.52)] in COVID-19 patients were significantly increased compared to healthy controls [1.11 (0.99, 1.30) mmol/L, 0.54 (0.33, 0.90)], and the differences were statistically significant (Z=-6.271, -2.801, all P < 0.005). Logistic regression analysis showed that fasting blood glucose on admission could be an independent protective factor (OR:0.020, 95% CI: 0.003 ~ 0.150) and elevated TG/HDL-C be a risk factor (OR:4.802, 95% CI: 1.249 ~ 18.460) for COVID-19 infection among non-diabetic populations. The ROC curve showed that fasting blood glucose and TG/HDL-C were good at predicting the risk of COVID-19, and the area under the curve (AUC) were 0.871 and 0.708, respectively, and was 0.895 when combined. Conclusion: Decreased fasting blood glucose and elevated TG/HDL-C would be risk factors for COVID-19 infection in the non-diabetic population, and both have good predictive value for the incidence of COVID-19.

Wnt5a/ß-catenin axis is involved in the downregulation of AT2 lineage by PAI-1.

Failure to regenerate injured alveoli functionally and promptly causes a high incidence of fatality in coronavirus disease 2019 (COVID-19). How elevated plasminogen activator inhibitor-1 (PAI-1) regulates the lineage of alveolar type 2 (AT2) cells for re-alveolarization has not been studied. This study aimed to examine the role of PAI-1-Wnt5a-ß catenin cascades in AT2 fate. Dramatic reduction in AT2 yield was observed in Serpine1Tg mice. Elevated PAI-1 level suppressed organoid number, development efficiency, and total surface area in vitro. Anti-PAI-1 neutralizing antibody restored organoid number, proliferation and differentiation of AT2 cells, and ß-catenin level in organoids. Both Wnt family member 5A (Wnt5a) and Wnt5a-derived N-butyloxycarbonyl hexapeptide (Box5) altered the lineage of AT2 cells. This study demonstrates that elevated PAI-1 regulates AT2 proliferation and differentiation via the Wnt5a/ß catenin cascades. PAI-1 could serve as autocrine signaling for lung injury repair.

Urban greenspace helps ameliorate people's negative sentiments during the COVID-19 pandemic: The case of Beijing.

The COVID-19 pandemic has had negative effects on people's mental health worldwide, especially for those who live in large cities. Studies have reported that urban greenspace may help lessen these adverse effects, but more research that explicitly considers urban landscape pattern is needed to understand the underlying processes. Thus, this study was designed to examine whether the resident sentiments in Beijing, China changed before and during the pandemic, and to investigate what urban landscape attributes - particularly greenspace - might contribute to the sentiment changes. We conducted sentiment analysis based on 25,357 geo-tagged microblogs posted by residents in 51 neighborhoods. We then compared the resident sentiments in 2019 (before the COVID-19) with those in 2020 (during the COVID-19) using independent sample t-tests, and examined the relationship between resident sentiments and urban greenspace during the COVID-19 pandemic phases using stepwise regression. We found that residents' sentiments deteriorated significantly from 2019 to 2020 in general, and that urban sentiments during the pandemic peak times showed an urban-suburban trend that was determined either by building density or available greenspace. Although our analysis included several other environmental and socioeconomic factors, none of them showed up as a significant factor. Our study suggests the effects of urban greenspace and building density on residents' sentiments increased during the COVID-19 pandemic and that not all green spaces are equal. Increasing greenspace, especially within and near neighborhoods, seems critically important to helping urban residents to cope with public health emergencies such as global pandemics.

Development of a Physiologically Based Pharmacokinetic Model for Hydroxychloroquine and Its Application in Dose Optimization in Specific COVID-19 Patients.

In Feb 2020, we developed a physiologically-based pharmacokinetic (PBPK) model of hydroxychloroquine (HCQ) and integrated in vitro anti-viral effect to support dosing design of HCQ in the treatment of COVID-19 patients in China. This, along with emerging research and clinical findings, supported broader uptake of HCQ as a potential treatment for COVID-19 globally at the beginning of the pandemics. Therefore, many COVID-19 patients have been or will be exposed to HCQ, including specific populations with underlying intrinsic and/or extrinsic characteristics that may affect the disposition and drug actions of HCQ. It is critical to update our PBPK model of HCQ with adequate drug absorption and disposition mechanisms to support optimal dosing of HCQ in these specific populations. We conducted relevant in vitro and in vivo experiments to support HCQ PBPK model update. Different aspects of this model are validated using PK study from 11 published references. With parameterization informed by results from monkeys, a permeability-limited lung model is employed to describe HCQ distribution in the lung tissues. The updated model is applied to optimize HCQ dosing regimens for specific populations, including those taking concomitant medications. In order to meet predefined HCQ exposure target, HCQ dose may need to be reduced in young children, elderly subjects with organ impairment and/or coadministration with a strong CYP2C8/CYP2D6/CYP3A4 inhibitor, and be increased in pregnant women. The updated HCQ PBPK model informed by new metabolism and distribution data can be used to effectively support dosing recommendations for clinical trials in specific COVID-19 patients and treatment of patients with malaria or autoimmune diseases.