Heat exchanges in wet suits

Flow of water under foam neoprene wet suits could halve insulation that the suits provided, even at rest in cold water. On the trunk conductance of this flow was approximately 6.6 at rest and 11.4 W . m-2 . C-1 exercising; on the limbs, it was only 3.4 at rest and 5.8 W . m-2 . degrees C-1 exercising; but during vasoconstriction in the cold, skin temperatures on distal parts of limbs were lower than were those of the trunk, allowing adequate metabolic responses. In warm water, minor postural changes and movement made flow under suits much higher, approximately 60 on trunk and 30 W . m-2 . degrees C-1 on limbs, both at rest and at work. These changes in flow allowed for a wide range of water temperatures at which people could stabilize body temperature in any given suit, neither overheating when exercising nor cooling below 35 degrees C when still. Even thin people with 4- or 7- mm suits covering the whole body could stabilize their body temperatures in water near 10 degrees C in spite of cold vasodilatation. Equations to predict limits of water temperature for stability with various suits and fat thicknesses are given.     

Fatal perinatal sarcocystosis in a lamb

A 3-wk-old lamb died because of neurological disease. The predominant microscopic lesions were in the brain and spinal cord and consisted of nonsuppurative encephalomyelitis with severe gliosis throughout the gray and white matter. Immature and mature schizonts, 15.7 x 10.6 microns (8-30 x 6-18 microns), occurred in capillaries and were structurally similar to those of Sarcocystis tenella.     

Multiomic Metabolic Enrichment Network Analysis Reveals Metabolite–Protein Physical Interaction Subnetworks Altered in Cancer

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings.