Introduction Statins may reduce a cytokine storm, which has been hypothesized as a possible mechanism of severe COVID-19 pneumonia. The aim of this study was to conduct a systematic review and meta-analysis to report on adverse outcomes among COVID-19 patients by statin usage. Methods Literatures were searched from January 2019 to December 2020 to identify studies that reported the association between statin usage and adverse outcomes, including mortality, ICU admissions, and mechanical ventilation. Studies were meta-analyzed for mortality by the subgroups of ICU status and statin usage before and after COVID-19 hospitalization. Studies reporting an odds ratio (OR) and hazard ratio (HR) were analyzed separately. Results Thirteen cohorts, reporting on 110,078 patients, were included in this meta-analysis. Individuals who used statins before their COVID-19 hospitalization showed a similar risk of mortality, compared to those who did not use statins (HR 0.80, 95% CI: 0.50, 1.28; OR 0.62, 95% CI: 0.38, 1.03). Patients who were administered statins after their COVID-19 diagnosis were at a lower risk of mortality (HR 0.53, 95% CI: 0.46, 0.61; OR 0.57, 95% CI: 0.43, 0.75). The use of statins did not reduce the mortality of COVID-19 patients admitted to the ICU (OR 0.65; 95% CI: 0.26, 1.64). Among non-ICU patients, statin users were at a lower risk of mortality relative to non-statin users (HR 0.53, 95% CI: 0.46, 0.62; OR 0.64, 95% CI: 0.46, 0.88). Conclusion Patients administered statins after COVID-19 diagnosis or non-ICU admitted patients were at lower risk of mortality relative to non-statin users.

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Sixty peony root training samples of the same age were collected from various regions in Korea and China, and their genetic diversity was investigated for 23 chloroplast intergenic space regions. All samples were genetically indistinguishable, indicating that the DNA-based techniques employed were not appropriate for determining the samples' regions of origin. In contrast, (1)H-nuclear magnetic resonance ((1)H-NMR) spectroscopy-based metabolomics coupled with multivariate statistical analysis revealed a clear difference between the metabolic profiles of the Korean and Chinese samples. Orthogonal projections on the latent structure-discrimination analysis allowed the identification of potential metabolite markers, including γ-aminobutyric acid, arginine, alanine, paeoniflorin, and albiflorin, that could be useful for classifying the samples' regions of origin. The validity of the discrimination model was tested using the response permutation test and blind prediction test for internal and external validations, respectively. Metabolomic data of 21 blended samples consisting of Korean and Chinese samples mixed at various proportions were also acquired by (1)H-NMR analysis. After data preprocessing which was designed to eliminate uncontrolled deviations in the spectral data between the testing and training sets, a new statistical procedure for estimating the mixing proportions of blended samples was established using the constrained least squares method for the first time. The predictive procedure exhibited relatively good predictability (adjusted R (2) = 0.7669), and thus has the potential to be used in the quality control of peony root by providing correct indications for a sample's geographical origins.

Careful preoperative evaluation of the vascular anatomy is essential to conducting successful anterior lumbar surgery. The determination of an appropriate approach can contribute to a reduction of unnecessary vascular retraction and a consequent decrease in vascular complications.

Cache is a roadblock towards low supply voltage (Vcc). It is mainly because low Vcc incurs process variation-induced bit errors in large SRAM in cache. Existing approaches for low Vcc cache suffer from low performance due to reduced effective capacity, long latency to correct errors, and increased misses due to accesses to faulty words. In our work, we propose a word-level sub-block disable-based method which increases the utilization of available cache capacity. Our key idea is to minimize accesses to faulty words. To do that, we propose utilizing access behavior history in allocating cache resource with faulty words. In addition, we propose remapping cache words inside of cache line in order to better match both access and error patterns. Experimental results show that the proposed method gives average 21.8% (up to 34.0%) performance improvement with a small area overhead in L1 and L2 caches.