Ascorbic acid supplementation of a high sucrose diet on rat oral tissue glycoprotein and lipid levels

PLEASE NOTE: This work is protected by copyright. Downloading is restricted to the BU community: please click Download and log in with a valid BU account to access. If you are the author of this work and would like to make it publicly available, please contact [email protected] (M.Sc.D.)--Boston University, Henry M. Goldman School of Graduate Dentistry, 1983 (Nutritional sciences)Bibliography : leaves 43-45.The objective of this study was to explore some major biochemical parameters in selected oral tissues (oral mucosa and submandibular salivary glands) following the feeding of diets high in sucrose and/or ascorbic acid; any observations would be compared to hepatic tissue. The animals selected for this study were forty (40) twenty-one day old male rats. The rats were divided into four dietary groups (control group, control plus ascorbic acid, high sucrose group, and the high sucrose plus ascorbic acid). At the end of fourteen days) analyses for DNA, total protein,protein-bound hexoses, protein-bound fucose, total lipids, neutral lipids, polar lipids, free fatty acids, triglycerides, mono and di-glycerides, methyl ester derivatives of free fatty acids) lysophosphatidyl choline) sphingomyelin, phosphatidyl choline, phosphatidyl inositol and serine, phosphatidyl ethanolamine, phosphatidic acid, cholesterol, and cholesterol esters were determined. The lipid analyses were carried out only in the salivary glands while the other analyses were determined for all tissues. The results showed that those rats fed the high sucrose diet supplemented with ascorbic acid had a significant increase in hepatic protein-bound hexose levels. This suggests a possible increase of internal glycosylations. In oral mucosa, the high sucrose regimen favored lower levels of bound hexoses. When such a diet was supplemented with ascorbic acid, the hexose levels were restored to control values. In submandibular salivary glands, ascorbic acid supplementation only elevated the total cholesterol level and had little or no effect on the other lipid fractions. These findings support the need for additional research on specific biochemical systems following such dietary manipulations. Such research should include mature animals as well

Legionella pneumophila Secretes a Mitochondrial Carrier Protein during Infection

The Mitochondrial Carrier Family (MCF) is a signature group of integral membrane proteins that transport metabolites across the mitochondrial inner membrane in eukaryotes. MCF proteins are characterized by six transmembrane segments that assemble to form a highly-selective channel for metabolite transport. We discovered a novel MCF member, termed Legionella nucleotide carrier Protein (LncP), encoded in the genome of Legionella pneumophila, the causative agent of Legionnaire's disease. LncP was secreted via the bacterial Dot/Icm type IV secretion system into macrophages and assembled in the mitochondrial inner membrane. In a yeast cellular system, LncP induced a dominant-negative phenotype that was rescued by deleting an endogenous ATP carrier. Substrate transport studies on purified LncP reconstituted in liposomes revealed that it catalyzes unidirectional transport and exchange of ATP transport across membranes, thereby supporting a role for LncP as an ATP transporter. A hidden Markov model revealed further MCF proteins in the intracellular pathogens, Legionella longbeachae and Neorickettsia sennetsu, thereby challenging the notion that MCF proteins exist exclusively in eukaryotic organisms

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Guidelines for Quality Management of Apallic Syndrome / Vegetative State.

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