COVID-19: Review of a 21st Century Pandemic from Etiology to Neuro-psychiatric Implications.

COVID-19 is a severe infectious disease that has claimed >150,000 lives and infected millions in the United States thus far, especially the elderly population. Emerging evidence has shown the virus to cause hemorrhagic and immunologic responses, which impact all organs, including lungs, kidneys, and the brain, as well as extremities. SARS-CoV-2 also affects patients', families', and society's mental health at large. There is growing evidence of re-infection in some patients. The goal of this paper is to provide a comprehensive review of SARS-CoV-2-induced disease, its mechanism of infection, diagnostics, therapeutics, and treatment strategies, while also focusing on less attended aspects by previous studies, including nutritional support, psychological, and rehabilitation of the pandemic and its management. We performed a systematic review of >1,000 articles and included 425 references from online databases, including, PubMed, Google Scholar, and California Baptist University's library. COVID-19 patients go through acute respiratory distress syndrome, cytokine storm, acute hypercoagulable state, and autonomic dysfunction, which must be managed by a multidisciplinary team including nursing, nutrition, and rehabilitation. The elderly population and those who are suffering from Alzheimer's disease and dementia related illnesses seem to be at the higher risk. There are 28 vaccines under development, and new treatment strategies/protocols are being investigated. The future management for COVID-19 should include B-cell and T-cell immunotherapy in combination with emerging prophylaxis. The mental health and illness aspect of COVID-19 are among the most important side effects of this pandemic which requires a national plan for prevention, diagnosis and treatment.

Genetic Risk of Alzheimer's Disease: Three Wishes Now That the Genie is Out of the Bottle.

The availability and increasing popularity of direct-to-consumer genetic testing for the presence of an APOE4 allelle led the Alzheimer's Foundation of America Medical, Scientific and Memory Screening Advisory Board to identify three critical areas for attention: 1) ensure consumer understanding of test results; 2) address and limit potential negative consequences of acquiring this information; and 3) support linking results with positive health behaviors, including potential clinical trial participation. Improving access to appropriate sources of genetic counseling as part of the testing process is critical and requires action from clinicians and the genetic testing industry. Standardizing information and resources across the industry should start now, with the input of consumers and experts in genetic risk and health information disclosure. Direct-to-consumer testing companies and clinicians should assist consumers by facilitating consultation with genetic counselors and facilitating pursuit of accurate information about testing.

DTI measures identify mild and moderate TBI cases among patients with complex health problems: A receiver operating characteristic analysis of U.S. veterans.

Standard MRI methods are often inadequate for identifying mild traumatic brain injury (TBI). Advances in diffusion tensor imaging now provide potential biomarkers of TBI among white matter fascicles (tracts). However, it is still unclear which tracts are most pertinent to TBI diagnosis. This study ranked fiber tracts on their ability to discriminate patients with and without TBI. We acquired diffusion tensor imaging data from military veterans admitted to a polytrauma clinic (Overall n = 109; Age: M = 47.2, SD = 11.3; Male: 88%; TBI: 67%). TBI diagnosis was based on self-report and neurological examination. Fiber tractography analysis produced 20 fiber tracts per patient. Each tract yielded four clinically relevant measures (fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity). We applied receiver operating characteristic (ROC) analyses to identify the most diagnostic tract for each measure. The analyses produced an optimal cutpoint for each tract. We then used kappa coefficients to rate the agreement of each cutpoint with the neurologist's diagnosis. The tract with the highest kappa was most diagnostic. As a check on the ROC results, we performed a stepwise logistic regression on each measure using all 20 tracts as predictors. We also bootstrapped the ROC analyses to compute the 95% confidence intervals for sensitivity, specificity, and the highest kappa coefficients. The ROC analyses identified two fiber tracts as most diagnostic of TBI: the left cingulum (LCG) and the left inferior fronto-occipital fasciculus (LIF). Like ROC, logistic regression identified LCG as most predictive for the FA measure but identified the right anterior thalamic tract (RAT) for the MD, RD, and AD measures. These findings are potentially relevant to the development of TBI biomarkers. Our methods also demonstrate how ROC analysis may be used to identify clinically relevant variables in the TBI population.