Spectrophotovoltaic orbital power generation

A system with 1000 : 1 concentration ratio is defined, using a cassegrain telescope as the first stage concentration (270 x) and compound parabolic concentrators (CPC) for the second stage concentration of 4.7 x for each spectral band. Using reported state of the art (S.O.A.) solar cells device parameters and considering structural losses due to optics and beamsplitters, the efficiencies of one to four cell systems were calculated with efficiencies varying from approximately 22% to 30%. Taking into account cost of the optics, beamsplitter, radiator, and the cost of developing new cells the most cost effective system is the GaAs/Si system

Integrative miRNA-mRNA Profiling of Adipose Tissue Unravels Transcriptional Circuits Induced by Sleep Fragmentation

Obstructive sleep apnea (OSA) is a prevalent condition and strongly associated with metabolic disorders. Sleep fragmentation (SF) is a major consequence of OSA, but its contribution to OSA-related morbidities is not known. We hypothesized that SF causes specific perturbations in transcriptional networks of visceral fat cells, leading to systemic metabolic disturbances. We simultaneously profiled visceral adipose tissue mRNA and miRNA expression in mice exposed to 6 hours of SF during sleep, and developed a new computational framework based on gene set enrichment and network analyses to merge these data. This approach leverages known gene product interactions and biologic pathways to interrogate large-scale gene expression profiling data. We found that SF induced the activation of several distinct pathways, including those involved in insulin regulation and diabetes. Our integrative methodology identified putative controllers and regulators of the metabolic response during SF. We functionally validated our findings by demonstrating altered glucose and lipid homeostasis in sleep-fragmented mice. This is the first study to link sleep fragmentation with widespread disruptions in visceral adipose tissue transcriptome, and presents a generalizable approach to integrate mRNA-miRNA information for systematic mapping of regulatory networks

Lactic Acidosis Triggers Starvation Response with Paradoxical Induction of TXNIP through MondoA

Although lactic acidosis is a prominent feature of solid tumors, we still have limited understanding of the mechanisms by which lactic acidosis influences metabolic phenotypes of cancer cells. We compared global transcriptional responses of breast cancer cells in response to three distinct tumor microenvironmental stresses: lactic acidosis, glucose deprivation, and hypoxia. We found that lactic acidosis and glucose deprivation trigger highly similar transcriptional responses, each inducing features of starvation response. In contrast to their comparable effects on gene expression, lactic acidosis and glucose deprivation have opposing effects on glucose uptake. This divergence of metabolic responses in the context of highly similar transcriptional responses allows the identification of a small subset of genes that are regulated in opposite directions by these two conditions. Among these selected genes, TXNIP and its paralogue ARRDC4 are both induced under lactic acidosis and repressed with glucose deprivation. This induction of TXNIP under lactic acidosis is caused by the activation of the glucose-sensing helix-loop-helix transcriptional complex MondoA:Mlx, which is usually triggered upon glucose exposure. Therefore, the upregulation of TXNIP significantly contributes to inhibition of tumor glycolytic phenotypes under lactic acidosis. Expression levels of TXNIP and ARRDC4 in human cancers are also highly correlated with predicted lactic acidosis pathway activities and associated with favorable clinical outcomes. Lactic acidosis triggers features of starvation response while activating the glucose-sensing MondoA-TXNIP pathways and contributing to the “anti-Warburg” metabolic effects and anti-tumor properties of cancer cells. These results stem from integrative analysis of transcriptome and metabolic response data under various tumor microenvironmental stresses and open new paths to explore how these stresses influence phenotypic and metabolic adaptations in human cancers

Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis

In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists’ gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for organizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed

Glucose sensing by MondoA:Mlx complexes: A role for hexokinases and direct regulation of thioredoxin-interacting protein expression

Glucose is a fundamental metabolite, yet how cells sense and respond to changes in extracellular glucose concentration is not completely understood. We recently reported that the MondoA:Mlx dimeric transcription factor directly regulates glycolysis. In this article, we consider whether MondoA:Mlx complexes have a broader role in sensing and responding to glucose status. In their latent state, MondoA:Mlx complexes localize to the outer mitochondrial membrane, yet shuttle between the mitochondria and the nucleus. We show that MondoA:Mlx complexes accumulate in the nucleus in response to glucose and 2-deoxyglucose (2-DG). Furthermore, nuclear localization of MondoA:Mlx depends on the enzymatic activity of hexokinases. These enzymes catalyze conversion of glucose to glucose-6-phosphate (G6P), which is the first step in the glycolytic pathway. Together, these findings suggest that MondoA:Mlx monitors intracellular G6P concentration and translocates to the nucleus when levels of this key metabolite increase. Transcriptional profiling experiments demonstrate that MondoA is required for >75% of the 2-DG-induced transcription signature. We identify thioredoxin-interacting protein (TXNIP) as a direct and glucose-regulated MondoA:Mlx transcriptional target. Furthermore, MondoA:Mlx complexes, via their regulation of TXNIP, are potent negative regulators of glucose uptake. These studies suggest a key role for MondoA:Mlx complexes in the adaptive transcriptional response to changes in extracellular glucose concentration and peripheral glucose uptake