The RIP140 Gene Is a Transcriptional Target of E2F1

RIP140 is a transcriptional coregulator involved in energy homeostasis and ovulation which is controlled at the transcriptional level by several nuclear receptors. We demonstrate here that RIP140 is a novel target gene of the E2F1 transcription factor. Bioinformatics analysis, gel shift assay, and chromatin immunoprecipitation demonstrate that the RIP140 promoter contains bona fide E2F response elements. In transiently transfected MCF-7 breast cancer cells, the RIP140 promoter is transactivated by overexpression of E2F1/DP1. Interestingly, RIP140 mRNA is finely regulated during cell cycle progression (5-fold increase at the G1/S and G2/M transitions). The positive regulation by E2F1 requires sequences located in the proximal region of the promoter (−73/+167), involves Sp1 transcription factors, and undergoes a negative feedback control by RIP140. Finally, we show that E2F1 participates in the induction of RIP140 expression during adipocyte differentiation. Altogether, this work identifies the RIP140 gene as a new transcriptional target of E2F1 which may explain some of the effect of E2F1 in both cancer and metabolic diseases

Simulations of radical and ion fluxes on wafer in a Cl<SUB>2</SUB>/Ar ICP discharge : Confrontation with GaAs and GaN etch experiments

International audienceA two-dimensional fluid model is used to study an industrial Ar/Cl2 inductively coupled plasma discharge designed to etch III-V samples. The effect of rf power, gas pressure, and chlorine content on the fluxes of reactive species reaching the wafer is numerically investigated. To understand how the etch process is influenced by the discharge conditions, simulation results are confronted with GaAs and GaN etch experiments performed in the same reactor geometry. When the source power is increased, the measured etch rate increase is consistent with the Cl radical and ion fluxes increase shown in the simulation, as well as the ion energy decrease due to the constant value of the wafer-holder power. Increasing the gas pressure results in a moderate increase in the etch rate due to the lower magnitude, lower mean energy, and anisotropy of the ion flux at high pressure. When the chlorine content is increased, the total ion flux decreases while Cl and Cl2 neutral fluxes increase significantly. A good correlation is obtained between calculated fluxes and etch characteristics, analyzed with scanning electron microscope images of etch profiles

Pharmacokinetic analysis of mizolastine in healthy young volunteers after single oral and intravenous doses: noncompartmental approach and compartmental modeling

International audienceThis paper presents the analysis of the kinetics of a new antihistamine, mizolastine, in 18 healthy volunteers, from concentrations measured after an intravenous infusion and two different oral administrations: tablet and capsule. Two approaches were used to analyze these data: (i) a noncompartmental approach implemented in PHARM-NCA; (ii) a compartmental modeling approach implemented in a new S-PLUS library, NLS2, Which allows the estimation of variance parameters simultaneously with the kinetics parameters. For the compartmental modeling approach, two-compartment open models were used. According to the Akaike criterion, the best model describing the kinetics of mizolastine after oral administration was the zero-order absorption model. The kinetic parameters obtained with PHARM-NCA and NLS2 were similar. The estimated duration of absorption was greater for the tablets than for the capsules (with means equal to 1.13 hr and 0.84 hr respectively). After an intravenous infusion, the mean estimated clearance was 4.9 L:hr, the mean lambda_2-phase apparent volume of distribution was 89.6 L and the mean terminal half-life was 12.9 hr

Growth and characterisation of single crystals of ternary chalcogenides for laser applications

Bulk single crystals up to 20 mm in diameter and 40 mm long for LiInS2 and up to 10 mm, 20 mm, respectively, for LiInSe2 have been grown. Their colour changed from colourless to rose for the first one and from yellow to dark red for the other All crystals have wurtzite-type lattice (Pna2(1) space group), lattice parameters were determined. A band gap was found to be 3.72 and 3.57 eV for LiInS2 and 3.02, 2.86 eV for LiInSe2 at 80 and 300 K, respectively. Colour variations are due to point defects, first of all to interstitial sulfur; resulting in additional wide absorption bands in the shortwave part of transparency range. For LiInS2 the SHG phase matching conditions were found to be similar for samples of different colour and some difference from Boyd\u27s predictions of 1973 was shown: for XY plane Delta phi similar to +3 degrees at 2.6 mum and Delta phi similar to +3 to -5 degrees at 4-5 mum. Nonlinear susceptibility for LiInS2 was estimated: d(eff)(XY) similar to3.4 pm/V relative to Boyd\u27s valise as 10.6 pm/V A proper illumination gives a photoinduced change of LiInSe2 colour from dark red to yellow as a result of changes in point defects charge state

A specific and unusual nuclear localization signal in the DNA binding domain of the Rev-erb orphan receptors

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Biomedical Text Link Prediction for Drug Discovery: A Case Study with COVID-19

Link prediction in artificial intelligence is used to identify missing links or derive future relationships that can occur in complex networks. A link prediction model was developed using the complex heterogeneous biomedical knowledge graph, SemNet, to predict missing links in biomedical literature for drug discovery. A web application visualized knowledge graph embeddings and link prediction results using TransE, CompleX, and RotatE based methods. The link prediction model achieved up to 0.44 hits@10 on the entity prediction tasks. The recent outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), also known as COVID-19, served as a case study to demonstrate the efficacy of link prediction modeling for drug discovery. The link prediction algorithm guided identification and ranking of repurposed drug candidates for SARS-CoV-2 primarily by text mining biomedical literature from previous coronaviruses, including SARS and middle east respiratory syndrome (MERS). Repurposed drugs included potential primary SARS-CoV-2 treatment, adjunctive therapies, or therapeutics to treat side effects. The link prediction accuracy for nodes ranked highly for SARS coronavirus was 0.875 as calculated by human in the loop validation on existing COVID-19 specific data sets. Drug classes predicted as highly ranked include anti-inflammatory, nucleoside analogs, protease inhibitors, antimalarials, envelope proteins, and glycoproteins. Examples of highly ranked predicted links to SARS-CoV-2: human leukocyte interferon, recombinant interferon-gamma, cyclosporine, antiviral therapy, zidovudine, chloroquine, vaccination, methotrexate, artemisinin, alkaloids, glycyrrhizic acid, quinine, flavonoids, amprenavir, suramin, complement system proteins, fluoroquinolones, bone marrow transplantation, albuterol, ciprofloxacin, quinolone antibacterial agents, and hydroxymethylglutaryl-CoA reductase inhibitors. Approximately 40% of identified drugs were not previously connected to SARS, such as edetic acid or biotin. In summary, link prediction can effectively suggest repurposed drugs for emergent diseases

AlGaN/GaN : processing and characterisation at TIGER laboratory

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AlGaN/GaN : processing and characterisation at TIGER laboratory

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