Infectious disease alters sleep patterns in rabbits, but the recuperative value of enhanced sleep during infectious disease has not been experimentally verified. To evaluate the relationship between specific sleep patterns and the clinical response to infectious disease, we classified sleep patterns in rabbits inoculated with E. coli, S. aureus, or C. albicans on the basis of the duration of the period of enhanced sleep. Patterns characterized by a long period of enhanced sleep were associated with a more favorable prognosis and less severe clinical signs than were patterns characterized by relatively short periods of enhanced sleep followed by prolonged sleep suppression. A contrasting analysis of these data indicated that animals that eventually died demonstrated reduced sleep compared to rabbits that survived the infection. These observations are consistent with the hypothesis that dynamic changes in sleep over the course of an infectious disease aid in recuperation.

Saccharomyces cerevisiae lives in boom and bust nutritional environments. Sophisticated regulatory systems have evolved to rapidly cope with these changes while preserving intracellular homeostasis. Target of Rapamycin Complex 1 (TorC1), is a serine/threonine kinase complex and a principle nitrogen-responsive regulator. TorC1 is activated by excess nitrogen and downregulated by limiting nitrogen. Two of TorC1’s many downstream targets are Gln3 and Gat1—GATA-family transcription activators—whose localization and function are Nitrogen Catabolite Repression- (NCR-) sensitive. In nitrogen replete environments, TorC1 is activated, thereby inhibiting the ^PTap42-Sit4 and ^PTap42-PP2A (Pph21/Pph22-Tpd3, Pph21,22-Rts1/Cdc55) phosphatase complexes. Gln3 is phosphorylated, sequestered in the cytoplasm and NCR-sensitive transcription repressed. In nitrogen-limiting conditions, TorC1 is downregulated and ^PTap42-Sit4 and ^PTap42-PP2A are active. They dephosphorylate Gln3, which dissociates from Ure2, relocates to the nucleus, and activates transcription. A paradoxical observation, however, led us to suspect that Gln3 control was more complex than appreciated, i.e., Sit4 dephosphorylates Gln3 more in excess than in limiting nitrogen conditions. This paradox motivated us to reinvestigate the roles of these phosphatases in Gln3 regulation. We discovered that: (i) Sit4 and PP2A actively function both in conditions where TorC1 is activated as well as down-regulated; (ii) nuclear Gln3 is more highly phosphorylated than when it is sequestered in the cytoplasm; (iii) in nitrogen-replete conditions, Gln3 relocates from the nucleus to the cytoplasm, where it is dephosphorylated by Sit4 and PP2A; and (iv) in nitrogen excess and limiting conditions, Sit4, PP2A, and Ure2 are all required to maintain cytoplasmic Gln3 in its dephosphorylated form.

This article describes a rationale and approach for modifying the traditional rural-urban commuting area (RUCA) coding scheme used to classify U.S. ZIP codes to enable suburban/rural vs. urban core comparisons in health outcomes research that better reflect current geographic differences in access to care in U.S. populations at risk for health disparities. The proposed method customization is being employed in the Patient-Centered Outcomes Research Institute-funded Management Of Diabetes in Everyday Life (MODEL) study to assess heterogeneity of treatment effect for patient-centered diabetes self-care interventions across the rural-urban spectrum. The proposed suburban/rural vs. urban core classification scheme modification is based on research showing that increasing suburban poverty and rapid conversion of many rural areas into suburban areas in the U.S. has resulted in similar health care access problems in areas designated as rural or suburban. • The RUCA coding scheme was developed when a much higher percentage of U.S. individuals resided in areas with very low population density. • Using the MODEL study example, this study demonstrates that the RUCA classification scheme using ZIP codes does not reflect real differences in health care access experienced by medically underserved study participants. • Both internal and external validation data suggest that the proposed suburban/rural vs. urban core customization of the RUCA geographic coding scheme better reflects real differences in healthcare access and is better able to assess the differential impact of clinical interventions designed to address geographic differences in access among vulnerable populations.

Triple-negative breast cancer (TNBC) is an aggressive form of breast cancer that is non-responsive to hormonal therapies and disproportionately impact women of African ancestry. We previously showed that TN breast tumors have a distinct microbial signature that differs from less aggressive breast tumor subtypes and normal breast tissues. However, it is unknown whether these differences in breast tumor microbiota may be driven by alterations in microbial metabolites, leading to potentially protective or pathogenic consequences. The goal of this global metabolomic profiling study was to investigate alterations in microbial metabolism pathways in normal and breast tumor tissues, including TNBC, of non-Hispanic black (NHB) and non-Hispanic white (NHW) women. In this study, we profiled the microbiome (16S rRNA) from breast tumor tissues and analyzed 984 metabolites from a total of 51 NHB and NHW women. Breast tumor tissues were collected from 15 patients with TNBC, 12 patients with less aggressive luminal A-type (Luminal) breast cancer, and 24 healthy controls for comparison using UHPLC-tandem mass spectrometry. Principal component analysis and hierarchical clustering of the global metabolomic profiling data revealed separation between metabolic signatures of normal and breast tumor tissues. Random forest analysis revealed a unique biochemical signature associated with elevated lipid metabolites and lower levels of microbial-derived metabolites important in controlling inflammation and immune responses in breast tumor tissues. Significant relationships between the breast microbiome and the metabolome, particularly lipid metabolism, were observed in TNBC tissues. Further investigations to determine whether alterations in sphingolipid, phospholipid, ceramide, amino acid, and energy metabolism pathways modulate Fusobacterium and Tenericutes abundance and composition to alter host metabolism in TNBC are necessary to help us understand the risk and underlying mechanisms and to identify potential microbial-based targets.