TRENDS IN CHOLESTEROL AND LIPOPROTEINS ARE ASSOCIATED WITH ACUTE RESPIRATORY DISTRESS SYNDROME INCIDENCE AND DEATH AMONG SEPSIS PATIENTS.

Objective: Compare changes in cholesterol and lipoprotein levels occurring in septic patients with and without acute respiratory distress syndrome (ARDS) and by survivorship. Methods: We reanalyzed data from prospective sepsis studies. Cholesterol and lipoprotein levels were analyzed using univariate testing to detect changes between septic patients with or without ARDS, and among ARDS survivors compared with nonsurvivors at enrollment (first 24 h of sepsis) and 48 to 72 h later.

HDL and persistent inflammation immunosuppression and catabolism syndrome.

Purpose Of Review: This study reviews the mechanisms of HDL cholesterol immunomodulation in the context of the mechanisms of chronic inflammation and immunosuppression causing persistent inflammation, immunosuppression and catabolism syndrome (PICS) and describes potential therapies and gaps in current research.

Recent Findings: Low HDL cholesterol is predictive of acute sepsis severity and outcome. Recent research has indicated apolipoprotein is a prognostic indicator of long-term outcomes.

Lipid and Lipoprotein Dysregulation in Sepsis: Clinical and Mechanistic Insights into Chronic Critical Illness.

In addition to their well-characterized roles in metabolism, lipids and lipoproteins have pleiotropic effects on the innate immune system. These undergo clinically relevant alterations during sepsis and acute inflammatory responses. High-density lipoprotein (HDL) plays an important role in regulating the immune response by clearing bacterial toxins, supporting corticosteroid release, decreasing platelet aggregation, inhibiting endothelial cell apoptosis, reducing the monocyte inflammatory response, and inhibiting expression of endothelial cell adhesion molecules.

Glucagon Resistance and Decreased Susceptibility to Diabetes in a Model of Chronic Hyperglucagonemia.

Elevation of glucagon levels and increase in α-cell mass are associated with states of hyperglycemia in diabetes. Our previous studies have highlighted the role of nutrient signaling via mTOR complex 1 (mTORC1) regulation that controls glucagon secretion and α-cell mass. In the current studies we investigated the effects of activation of nutrient signaling by conditional deletion of the mTORC1 inhibitor, TSC2, in α-cells (αTSC2).

How do physician demographics, training, social media usage, online presence, and wait times influence online physician review scores for spine surgeons?

OBJECTIVEThe purpose of this study was to assess the impact of certain demographics, social media usage, and physician review website variables for spine surgeons across Healthgrades.com (Healthgrades), Vitals.com (Vitals), and Google.

Analysis of Internet Review Site Comments for Spine Surgeons: How Office Staff, Physician Likeability, and Patient Outcome Are Associated With Online Evaluations.

Study Design: Observational study.

Objective: To evaluate how online patient comments will affect website ratings for spine surgeons.

Summary Of Background Data: With the ever-growing utilization of physician review websites, healthcare consumers are assuming more control over whom they choose for care.

How social media, training, and demographics influence online reviews across three leading review websites for spine surgeons.

Background Context: The future of health care is consumer driven with a focus on outcome metrics and patient feedback. Physician review websites have grown in popularity and are guiding patients to certain health-care providers, for better or worse. No prior study has specifically evaluated Internet reviews of spine surgeons, determined if social media (SM) correlates with patient reviews, or evaluated Google as a physician review website.

Fuzzy ARTMAP prediction of biological activities for potential HIV-1 protease inhibitors using a small molecular data set.

Obtaining satisfactory results with neural networks depends on the availability of large data samples. The use of small training sets generally reduces performance. Most classical Quantitative Structure-Activity Relationship (QSAR) studies for a specific enzyme system have been performed on small data sets.