Chrysin for Neurotrophic and Neurotransmitter Balance in Parkinson's Disease.

1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) has a direct impact on the dopaminergic neurons in the substantia nigra pars compacta (SNpc), dopamine in the striatum (ST), homovanillic acid (HVA), neurotrophic factors of the SNpc, and ST regions leading to Parkinson's disease (PD). Dopaminergic neuron atrophy in the SNpc and dopamine degradation in the ST have an explicit link to disrupted homeostasis of the neurotrophic factor brain-derived neurotrophic factor (BDNF) of the SNpc and ST regions. Chrysin is a flavonoid with a pharmacological potential that directly influences neurotrophic levels as well as neurotransmitters.

Independent Predictors of Mortality in COVID-19 Myocardial Injury: The Role of Troponin Levels, GRACE Score, SOFA Score, and TIMI Score.

Background Coronavirus disease 2019 (COVID-19) infection is associated with troponin elevation, which is associated with increased mortality. However, it is not clear if troponin elevation is independently linked to increased mortality in COVID-19 patients. Although there is considerable literature on risk factors for mortality in COVID-19-associated myocardial injury, the Global Registry of Acute Coronary Events (GRACE), Thrombolysis in Myocardial Infarction (TIMI), and Sequential Organ Failure Assessment (SOFA) scores have not been studied in COVID-19-related myocardial injury.

A Narrative Review of Existing Options for COVID-19-Specific Treatments.

The new coronavirus disease 2019 (COVID-19) was declared a global pandemic in early 2020. The ongoing COVID-19 pandemic has affected morbidity and mortality tremendously. Even though multiple drugs are being used throughout the world since the advent of COVID-19, only limited treatment options are available for COVID-19.

Diagnostic and prognostic capabilities of a biomarker and EMR-based machine learning algorithm for sepsis.

Sepsis is a major cause of mortality among hospitalized patients worldwide. Shorter time to administration of broad-spectrum antibiotics is associated with improved outcomes, but early recognition of sepsis remains a major challenge. In a two-center cohort study with prospective sample collection from 1400 adult patients in emergency departments suspected of sepsis, we sought to determine the diagnostic and prognostic capabilities of a machine-learning algorithm based on clinical data and a set of uncommonly measured biomarkers.