Early Enteral Administration of a Complex Lipid Emulsion Supplement Prevents Postnatal Deficits in Docosahexaenoic and Arachidonic Acids and Increases Tissue Accretion of Lipophilic Nutrients in Preterm Piglets.

BACKGROUND: Preterm delivery and current nutrition strategies result in deficiencies of critical long-chain fatty acids (FAs) and lipophilic nutrients, increasing the risk of preterm morbidities. We sought to determine the efficacy of preventing postnatal deficits in FAs and lipophilic nutrients using an enteral concentrated lipid supplement in preterm piglets. METHODS: Preterm piglets were fed a baseline diet devoid of arachidonic acid (AA) and docosahexaenoic acid (DHA) and randomized to enteral supplementation as follows: (1) Intralipid (IL), (2) complex lipid supplement 1 (CLS1) with an AA:DHA ratio of 0.25, or (3) CLS2 with an AA:DHA ratio of 1.2. On day 8, plasma and tissue levels of FAs and lipophilic nutrients were measured and ileum histology performed. RESULTS: Plasma DHA levels decreased in the IL group by day 2. In contrast, DHA increased by day 2 compared with birth levels in both CLS1 and CLS2 groups. The IL and CLS1 groups demonstrated a continued decline in AA levels during the 8-day protocol, whereas AA levels in the CLS2 group on day 8 were comparable to birth levels. Preserving AA levels in the CLS2 group was associated with greater ileal villus height and muscular layer thickness. Lipophilic nutrients were effectively absorbed in plasma and tissues. CONCLUSIONS: Enteral administration of CLS1 and CLS2 demonstrated similar increases in DHA levels compared with birth levels. Only CLS2 maintained AA birth levels. Providing a concentrated complex lipid emulsion with an AA:DHA ratio > 1 is important in preventing postnatal AA deficits.

Efficient measurement and factorization of high-order drug interactions in Mycobacterium tuberculosis.

Combinations of three or more drugs are used to treat many diseases, including tuberculosis. Thus, it is important to understand how synergistic or antagonistic drug interactions affect the efficacy of combination therapies. However, our understanding of high-order drug interactions is limited because of the lack of both efficient measurement methods and theoretical framework for analysis and interpretation. We developed an efficient experimental sampling and scoring method [diagonal measurement of n-way drug interactions (DiaMOND)] to measure drug interactions for combinations of any number of drugs. DiaMOND provides an efficient alternative to checkerboard assays, which are commonly used to measure drug interactions. We established a geometric framework to factorize high-order drug interactions into lower-order components, thereby establishing a road map of how to use lower-order measurements to predict high-order interactions. Our framework is a generalized Loewe additivity model for high-order drug interactions. Using DiaMOND, we identified and analyzed synergistic and antagonistic antibiotic combinations against Mycobacteriumtuberculosis. Efficient measurement and factorization of high-order drug interactions by DiaMOND are broadly applicable to other cell types and disease models.