Heart failure with preserved ejection fraction (HFpEF) has become a major health issue because of its high mortality, high heterogeneity, and poor prognosis. Using genomic data to classify patients into different risk groups is a promising method to facilitate the identification of high-risk groups for further precision treatment. Here, we applied six machine learning models, namely kernel partial least squares with the genetic algorithm (GA-KPLS), the least absolute shrinkage and selection operator (LASSO), random forest, ridge regression, support vector machine, and the conventional logistic regression model, to predict HFpEF risk and to identify subgroups at high risk of death based on gene expression data. The model performance was evaluated using various criteria. Our analysis was focused on 149 HFpEF patients from the Framingham Heart Study cohort who were classified into good-outcome and poor-outcome groups based on their 3-year survival outcome. The results showed that the GA-KPLS model exhibited the best performance in predicting patient risk. We further identified 116 differentially expressed genes (DEGs) between the two groups, thus providing novel therapeutic targets for HFpEF. Additionally, the DEGs were enriched in Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways related to HFpEF. The GA-KPLS-based HFpEF model is a powerful method for risk stratification of 3-year mortality in HFpEF patients.

BackgroundProgressive loss of articular cartilage is a central hallmark in many joint disease, however, the relative importance of individual proteolytic pathways leading to cartilage erosion is at present unknown. We therefore investigated the time-dependant release ex vivo of MMP- and aggrecanase-derived fragments of aggrecan and type II collagen into the supernatant of bovine cartilage explants cultures using neo-epitope specific immunoassays, and to associate the release of these fragments with the activity of proteolytic enzymes using inhibitors.FindingsBovine cartilage explants were cultured in the presence or absence of the catabolic cytokines oncostatin M (OSM) and tumor necrosis factor alpha (TNFα). In parallel, explants were co-cultured with protease inhibitors such as GM6001, TIMP1, TIMP2 and TIMP3. Fragments released into the supernatant were determined using a range of neo-epitope specific immunoassays; (1) sandwich 342FFGVG-G2 ELISA, (2) competition NITEGE373ELISA (3) sandwich G1-NITEGE373 ELISA (4) competition 374ARGSV ELISA, and (5) sandwich 374ARGSV-G2 ELISA all detecting aggrecan fragments, and (6) sandwich CTX-II ELISA, detecting C-telopeptides of type II collagen. We found that (1) aggrecanase-derived aggrecan fragments are released in the early (day 2-7) and mid phase (day 9-14) into the supernatant from bovine explants cultures stimulated with catabolic cytokines, (2) the release of NITEGE373 neo-epitopes are delayed compared to the corresponding 374ARGSV fragments, (3) the MMP inhibitor GM6001 did not reduce the release of aggrecanase-derived fragment, but induced a further delay in the release of these fragments, and finally (4) the MMP-derived aggrecan and type II collagen fragments were released in the late phase (day 16-21) only.ConclusionOur data support the model, that aggrecanases and MMPs act independently in the processing of the aggrecan molecules, and furthermore that suppression of MMP-activity had little if any effect on the quantity of aggrecanase-derived fragments released from explants cultures.

Proprotein convertase subtilisin/kexin type 9 (PCSK9) plays a key role in cholesterol homeostasis and atherogenesis. However, there are only limited rodent models, with a functional low-density lipoprotein receptor (LDLR) pathway and cholesteryl ester transfer protein (CETP) to evaluate the drug candidates targeting the PCSK9/LDLR pathway, that are translatable to humans. Here, by using our recently generated LDLR heterozygote (Ldlr+/−) hamster model with functional LDLR pathway and CETP function, we seek to evaluate the effect of a PCSK9 antibody, evolocumab, on dyslipidemia and atherosclerosis compared with ezetimibe, an effective inhibitor of cholesterol absorption, as a positive therapeutic control. We show that the plasma levels of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) were significantly increased in Ldlr+/− hamsters fed a high-fat high-cholesterol (HFHC) diet; therefore, areas of atherosclerotic lesion in the aorta were obviously increased and positively correlated with plasma LDL-C and TC. Circulating free PCSK9 was downregulated by the HFHC diet and was undetectable in the evolocumab treated group, as expected. Most importantly, either evolocumab or ezetimibe treatment prevented HFHC diet-induced hyperlipidemia and subsequent atherosclerotic plaque formation. The results indicate that Ldlr+/− hamsters fed an HFHC diet represent an ideal rodent model to evaluate drug candidates that affect LDLR pathways.

Purpose At present, it has been found that managing patients with a redetected positive RNA test after recovery from foreign-imported coronavirus disease 2019 (COVID-19) cases in China is challenging. The purpose of the current study was to describe the clinical characteristics of these patients. Methods This retrospective cohort study included 137 COVID-19 patients who were discharged from the Xi’an Public Health Center from 28 July 2020 to 31 December 2021. We compared the clinical characteristics between positive retest patients and non-positive retest patients. Results 137 COVID-19 patients entered our study, 27 (19.7%) cases of COVID-19 with a redetected positive RNA test by the end of the follow-up period. Fever [(n = 31 (22.6%)], cough [n = 26 (18.9%)] and sore throat [n = 20 (14.5%)] were the most common initial symptoms among the foreign-imported COVID-19 patients, and there were almost no significant differences in initial symptoms between positive retest patients and non-positive retest patients. The positive retest patients had a higher lymphocyte count (p = 0.031) and lymphocyte percentage (p = 0.007) during readmission. There were generally no significant differences in other routine blood test findings, IgG and IgM antibody responses, between positive retest patients and non-positive retest patients, or in positive retest patients over time (before, during, or after positive patient detection). After readmission, positive retest patients displayed fewer symptoms or no obvious disease progression and more sustained remission by CT imaging. Conclusion Our findings revealed that the clinical characteristics at the time of initial diagnosis were not closely related to redetected positive RNA tests after recovery from foreign-imported COVID-19 cases. Positive retest patients had virtually no symptoms and displayed no obvious disease progression during readmission. These findings provide important information and clinical evidence for the effective management of foreign-imported COVID-19 patients during their convalescent phase.