Active Control of Polariton-Enabled Long-Range Energy Transfer

Optical control is achieved on the excited state energy transfer between spatially separated donor and acceptor molecules, both coupled to the same optical mode of a cavity. The energy transfer occurs through the formed hybrid polaritons and can be switched on and off by means of ultraviolet and visible light. The control mechanism relies on a photochromic component used as donor, whose absorption and emission properties can be varied reversibly through light irradiation, whereas in-cavity hybridization with acceptors through polariton states enables a 6-fold enhancement of acceptor/donor contribution to the emission intensity with respect to a reference multilayer. These results pave the way for synthesizing effective gating systems for the transport of energy by light, relevant for light-harvesting and light-emitting devices, and for photovoltaic cells.Comment: 52 pages, 40 Figures, 202

A Low Protein Diet Increases the Hypoxic Tolerance in Drosophila

Dietary restriction is well known to increase the life span of a variety of organisms from yeast to mammals, but the relationships between nutrition and the hypoxic tolerance have not yet been considered. Hypoxia is a major cause of cell death in myocardial infarction and stroke. Here we forced hypoxia-related death by exposing one-day-old male Drosophila to chronic hypoxia (5% O(2)) and analysed their survival. Chronic hypoxia reduced the average life span from 33.6 days to 6.3 days when flies were fed on a rich diet. A demographic analysis indicated that chronic hypoxia increased the slope of the mortality trajectory and not the short-term risk of death. Dietary restriction produced by food dilution, by yeast restriction, or by amino acid restriction partially reversed the deleterious action of hypoxia. It increased the life span of hypoxic flies up to seven days, which represented about 25% of the life time of an hypoxic fly. Maximum survival of hypoxic flies required only dietary sucrose, and it was insensitive to drugs such as rapamycin and resveratrol, which increase longevity of normoxic animals. The results thus uncover a new link between protein nutrition, nutrient signalling, and resistance to hypoxic stresses

Oxygen Sensing in Drosophila: Multiple Isoforms of the Prolyl Hydroxylase Fatiga Have Different Capacity to Regulate HIFα/Sima

Background: The Hypoxia Inducible Factor (HIF) mediates cellular adaptations to low oxygen. Prolyl-4-hydroxylases are oxygen sensors that hydroxylate the HIF alpha-subunit, promoting its proteasomal degradation in normoxia. Three HIFprolyl hydroxylases, encoded by independent genes, PHD1, PHD2, and PHD3, occur in mammals. PHD2, the longest PHD isoform includes a MYND domain, whose biochemical function is unclear. PHD2 and PHD3 genes are induced in hypoxia to shut down HIF dependent transcription upon reoxygenation, while expression of PHD1 is oxygen-independent. The physiologic significance of the diversity of the PHD oxygen sensors is intriguing. Methodology and Principal Findings: We have analyzed the Drosophila PHD locus, fatiga, which encodes 3 isoforms, FgaA, FgaB and FgaC that are originated through a combination of alternative initiation of transcription and alternative splicing. FgaA includes a MYND domain and is homologous to PHD2, while FgaB and FgaC are shorter isoforms most similar to PHD3. Through a combination of genetic experiments in vivo and molecular analyses in cell culture, we show that fgaB but not fgaA is induced in hypoxia, in a Sima-dependent manner, through a HIF-Responsive Element localized in the first intron of fgaA. The regulatory capacity of FgaB is stronger than that of FgaA, as complete reversion of fga loss-of-function phenotypes is observed upon transgenic expression of the former, and only partial rescue occurs after expression of the latter. Conclusions and Significance: Diversity of PHD isoforms is a conserved feature in evolution. As in mammals, there are hypoxia-inducible and non-inducible Drosophila PHDs, and a fly isoform including a MYND domain co-exists with isoforms lacking this domain. Our results suggest that the isoform devoid of a MYND domain has stronger regulatory capacity than that including this domain.Fil:Acevedo, J.M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil:Centanin, L. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil:Dekanty, A. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil:Wappner, P. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina

Drosophila Genome-Wide RNAi Screen Identifies Multiple Regulators of HIF–Dependent Transcription in Hypoxia

Hypoxia-inducible factors (HIFs) are a family of evolutionary conserved alpha-beta heterodimeric transcription factors that induce a wide range of genes in response to low oxygen tension. Molecular mechanisms that mediate oxygen-dependent HIF regulation operate at the level of the alpha subunit, controlling protein stability, subcellular localization, and transcriptional coactivator recruitment. We have conducted an unbiased genome-wide RNA interference (RNAi) screen in Drosophila cells aimed to the identification of genes required for HIF activity. After 3 rounds of selection, 30 genes emerged as critical HIF regulators in hypoxia, most of which had not been previously associated with HIF biology. The list of genes includes components of chromatin remodeling complexes, transcription elongation factors, and translational regulators. One remarkable hit was the argonaute 1 (ago1) gene, a central element of the microRNA (miRNA) translational silencing machinery. Further studies confirmed the physiological role of the miRNA machinery in HIF–dependent transcription. This study reveals the occurrence of novel mechanisms of HIF regulation, which might contribute to developing novel strategies for therapeutic intervention of HIF–related pathologies, including heart attack, cancer, and stroke

Chronic Hypoxia Impairs Muscle Function in the Drosophila Model of Duchenne's Muscular Dystrophy (DMD)

Duchenne's muscular dystrophy (DMD) is a severe progressive myopathy caused by mutations in the DMD gene leading to a deficiency of the dystrophin protein. Due to ongoing muscle necrosis in respiratory muscles late-stage DMD is associated with respiratory insufficiency and chronic hypoxia (CH). To understand the effects of CH on dystrophin-deficient muscle in vivo, we exposed the Drosophila model for DMD (dmDys) to CH during a 16-day ascent to the summit of Mount Denali/McKinley (6194 meters above sea level). Additionally, dmDys and wild type (WT) flies were also exposed to CH in laboratory simulations of high altitude hypoxia. Expression profiling was performed using Affymetrix GeneChips® and validated using qPCR. Hypoxic dmDys differentially expressed 1281 genes, whereas the hypoxic WT flies differentially expressed 56 genes. Interestingly, a number of genes (e.g. heat shock proteins) were discordantly regulated in response to CH between dmDys and WT. We tested the possibility that the disparate molecular responses of dystrophin-deficient tissues to CH could adversely affect muscle by performing functional assays in vivo. Normoxic and CH WT and dmDys flies were challenged with acute hypoxia and time-to-recover determined as well as subjected to climbing tests. Impaired performance was noted for CH-dmDys compared to normoxic dmDys or WT flies (rank order: Normoxic-WT ≈ CH-WT> Normoxic-dmDys> CH-dmDys). These data suggest that dystrophin-deficiency is associated with a disparate, pathological hypoxic stress response(s) and is more sensitive to hypoxia induced muscle dysfunction in vivo. We hypothesize that targeting/correcting the disparate molecular response(s) to hypoxia may offer a novel therapeutic strategy in DMD

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Il risparmio postale tra amministrazione pubblica e sistema finanziario (1975-2005)

Il saggio ricostruisce la storia del risparmio postale in Italia dal 1975 al 2005, con particolare attenzione alla nascita del Bancoposta e alle trasformazione istituzionali e organizzative dell'Amministrazione postale e della Cassa depositi e prestiti

Il risparmio postale tra amministrazione pubblica e sistema finanziario (1975-2005)

Il saggio ricostruisce la storia del risparmio postale in Italia dal 1975 al 2005, con particolare attenzione alla nascita del Bancoposta e alle trasformazione istituzionali e organizzative dell'Amministrazione postale e della Cassa depositi e prestiti