Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0020473 (hyperlipidemia)
 15,891 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

The flavonoid dihydromyricetin (DMY) is the main component of Ampelopsis grossedentata (Hand-Mazz) W. T. Wang (AG), a daily beverage and folk medicine used in Southern China to treat jaundice hepatitis, cold fever, and sore throat. Recently, DMY and AG were shown to have a beneficial effect on lipid metabolism disorder. However, the mechanisms of how DMY and AG protect the liver during lipid metabolism disorder remain unclear. In this study, we first analyzed the chemical compounds of AG by HPLC-DAD-ESI-IT-TOF-MS n . Of the 31 compounds detected, 29 were identified based on previous results. Then, the effects of DMY and AG on high-fat diet hamster livers were studied and the metabolite levels and metabolic pathway activity of the liver were explored by 1H NMR metabolomics. Compared to the high-fat diet group, supplementation of AG and DMY attenuated the high-fat-induced increase in body weight, liver lipid deposition, serum triglycerides and total cholesterol levels, and normalized endogenous metabolite concentrations. PCA and PLS-DA score plots demonstrated that while the metabolic profiles of hamsters fed a high-fat diet supplemented with DMY or AG were both far from those of hamsters fed a normal diet or a high-fat diet alone, they were similar to each other. Our data suggest that the underlying mechanism of the protective effect of DMY and AG might be related to an attenuation of the deleterious effect of high-fat diet-induced hyperlipidemia on multiple metabolic pathways including amino acid metabolism, ketone body metabolism, energy metabolism, tricarboxylic acid cycle, and enhanced fatty acid oxidation.
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PMID:Metabolomics of the Protective Effect of Ampelopsis grossedentata and Its Major Active Compound Dihydromyricetin on the Liver of High-Fat Diet Hamster. 3207 9

(1) Background: Different clinical presentations in COVID-19 are described to date, from mild to severe cases. This study aims to identify different clinical phenotypes in COVID-19 pneumonia using cluster analysis and to assess the prognostic impact among identified clusters in such patients. (2) Methods: Cluster analysis including 11 phenotypic variables was performed in a large cohort of 12,066 COVID-19 patients, collected and followed-up from 1 March to 31 July 2020, from the nationwide Spanish Society of Internal Medicine (SEMI)-COVID-19 Registry. (3) Results: Of the total of 12,066 patients included in the study, most were males (7052, 58.5%) and Caucasian (10,635, 89.5%), with a mean age at diagnosis of 67 years (standard deviation (SD) 16). The main pre-admission comorbidities were arterial hypertension (6030, 50%), hyperlipidemia (4741, 39.4%) and diabetes mellitus (2309, 19.2%). The average number of days from COVID-19 symptom onset to hospital admission was 6.7 (SD 7). The triad of fever, cough, and dyspnea was present almost uniformly in all 4 clinical phenotypes identified by clustering. Cluster C1 (8737 patients, 72.4%) was the largest, and comprised patients with the triad alone. Cluster C2 (1196 patients, 9.9%) also presented with ageusia and anosmia; cluster C3 (880 patients, 7.3%) also had arthromyalgia, headache, and sore throat; and cluster C4 (1253 patients, 10.4%) also manifested with diarrhea, vomiting, and abdominal pain. Compared to each other, cluster C1 presented the highest in-hospital mortality (24.1% vs. 4.3% vs. 14.7% vs. 18.6%; p < 0.001). The multivariate study identified age, gender (male), body mass index (BMI), arterial hypertension, chronic obstructive pulmonary disease (COPD), ischemic cardiopathy, chronic heart failure, chronic hepatopathy, Charlson's index, heart rate and respiratory rate upon admission >20 bpm, lower PaO2/FiO2 at admission, higher levels of C-reactive protein (CRP) and lactate dehydrogenase (LDH), and the phenotypic cluster as independent factors for in-hospital death. (4) Conclusions: The present study identified 4 phenotypic clusters in patients with COVID-19 pneumonia, which predicted the in-hospital prognosis of clinical outcomes.
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PMID:Predicting Clinical Outcome with Phenotypic Clusters in COVID-19 Pneumonia: An Analysis of 12,066 Hospitalized Patients from the Spanish Registry SEMI-COVID-19. 3313 19