Icahn School of Medicine at Mount Sinai

About: Icahn School of Medicine at Mount Sinai is a education organization based out in New York, New York, United States. It is known for research contribution in the topics: Population & Medicine. The organization has 37488 authors who have published 76057 publications receiving 3704104 citations. The organization is also known as: Mount Sinai School of Medicine.

Diabetes and advanced glycation endproducts.

Abstract: Bio-reactive advanced glycation endproducts (AGE) alter the structure and function of molecules in biological systems and increase oxidative stress. These adverse effects of both exogenous and endogenously derived AGE have been implicated in the pathogenesis of diabetic complications and changes associated with ageing including atherosclerosis, renal, eye and neurological disease. Specific AGE receptors and nonreceptor mechanisms contribute to these processes but also assist in the removal and degradation of AGE. The final disposal of AGE depends on renal clearance. Promising pharmacologic strategies to prevent AGE formation, reduce AGE toxicity, and/or inactivate AGE are under investigation.

Artificial intelligence-enabled rapid diagnosis of patients with COVID-19.

Abstract: For diagnosis of coronavirus disease 2019 (COVID-19), a SARS-CoV-2 virus-specific reverse transcriptase polymerase chain reaction (RT-PCR) test is routinely used. However, this test can take up to 2 d to complete, serial testing may be required to rule out the possibility of false negative results and there is currently a shortage of RT-PCR test kits, underscoring the urgent need for alternative methods for rapid and accurate diagnosis of patients with COVID-19. Chest computed tomography (CT) is a valuable component in the evaluation of patients with suspected SARS-CoV-2 infection. Nevertheless, CT alone may have limited negative predictive value for ruling out SARS-CoV-2 infection, as some patients may have normal radiological findings at early stages of the disease. In this study, we used artificial intelligence (AI) algorithms to integrate chest CT findings with clinical symptoms, exposure history and laboratory testing to rapidly diagnose patients who are positive for COVID-19. Among a total of 905 patients tested by real-time RT-PCR assay and next-generation sequencing RT-PCR, 419 (46.3%) tested positive for SARS-CoV-2. In a test set of 279 patients, the AI system achieved an area under the curve of 0.92 and had equal sensitivity as compared to a senior thoracic radiologist. The AI system also improved the detection of patients who were positive for COVID-19 via RT-PCR who presented with normal CT scans, correctly identifying 17 of 25 (68%) patients, whereas radiologists classified all of these patients as COVID-19 negative. When CT scans and associated clinical history are available, the proposed AI system can help to rapidly diagnose COVID-19 patients.

The origin and development of nonlymphoid tissue CD103+ DCs

Abstract: CD103+ dendritic cells (DCs) in nonlymphoid tissues are specialized in the cross-presentation of cell-associated antigens. However, little is known about the mechanisms that regulate the development of these cells. We show that two populations of CD11c+MHCII+ cells separated on the basis of CD103 and CD11b expression coexist in most nonlymphoid tissues with the exception of the lamina propria. CD103+ DCs are related to lymphoid organ CD8+ DCs in that they are derived exclusively from pre-DCs under the control of fms-like tyrosine kinase 3 (Flt3) ligand, inhibitor of DNA protein 2 (Id2), and IFN regulatory protein 8 (IRF8). In contrast, lamina propria CD103+ DCs express CD11b and develop independently of Id2 and IRF8. The other population of CD11c+MHCII+ cells in tissues, which is CD103−CD11b+, is heterogenous and depends on both Flt3 and MCSF-R. Our results reveal that nonlymphoid tissue CD103+ DCs and lymphoid organ CD8+ DCs derive from the same precursor and follow a related differentiation program.

Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for CYP2D6 and CYP2C19 Genotypes and Dosing of Selective Serotonin Reuptake Inhibitors

Abstract: Selective serotonin reuptake inhibitors (SSRIs) are primary treatment options for major depressive and anxiety disorders. CYP2D6 and CYP2C19 polymorphisms can influence the metabolism of SSRIs, thereby affecting drug efficacy and safety. We summarize evidence from the published literature supporting these associations and provide dosing recommendations for fluvoxamine, paroxetine, citalopram, escitalopram, and sertraline based on CYP2D6 and/or CYP2C19 genotype (updates at www.pharmgkb.org).

The Consortium to Establish a Registry for Alzheimer's Disease (CERAD). Part VI. Family history assessment: A multicenter study of first-degree relatives of Alzheimer's disease probands and nondemented spouse controls

Abstract: Although familial factors in Alzheimer9s disease (AD) are well established, uniform family-history assessment in genetic and epidemiologic studies of AD is needed to reconcile the divergent estimates of the cumulative risk of this illness among relatives of AD probands. To answer the need, the Consortium to Establish a Registry for Alzheimer9s Disease (CERAD) has developed a standardized Family History Assessment of AD to identify the presence of AD, Parkinson9s disease (PD), and Down9s syndrome (DS) in family members. This paper describes the use of this new assessment instrument in 118 patients with AD (estimated mean age at onset [± SD] = 64.5 ± 7.7 years) and their nondemented spouses who were enrolled in 11 different CERAD sites in the U.S. The first-degree relatives of the probands with AD had a significantly greater cumulative risk (p