Genomic analysis of the function of the transcription factor gata3 during development of the Mammalian inner ear

We have studied the function of the zinc finger transcription factor gata3 in auditory system development by analysing temporal profiles of gene expression during differentiation of conditionally immortal cell lines derived to model specific auditory cell types and developmental stages. We tested and applied a novel probabilistic method called the gamma Model for Oligonucleotide Signals to analyse hybridization signals from Affymetrix oligonucleotide arrays. Expression levels estimated by this method correlated closely (p<0.0001) across a 10-fold range with those measured by quantitative RT-PCR for a sample of 61 different genes. In an unbiased list of 26 genes whose temporal profiles clustered most closely with that of gata3 in all cell lines, 10 were linked to Insulin-like Growth Factor signalling, including the serine/threonine kinase Akt/PKB. Knock-down of gata3 in vitro was associated with a decrease in expression of genes linked to IGF-signalling, including IGF1, IGF2 and several IGF-binding proteins. It also led to a small decrease in protein levels of the serine-threonine kinase Akt2/PKB beta, a dramatic increase in Akt1/PKB alpha protein and relocation of Akt1/PKB alpha from the nucleus to the cytoplasm. The cyclin-dependent kinase inhibitor p27(kip1), a known target of PKB/Akt, simultaneously decreased. In heterozygous gata3 null mice the expression of gata3 correlated with high levels of activated Akt/PKB. This functional relationship could explain the diverse function of gata3 during development, the hearing loss associated with gata3 heterozygous null mice and the broader symptoms of human patients with Hearing-Deafness-Renal anomaly syndrome

Analysis of cancer metabolism with high-throughput technologies

<p>Abstract</p> <p>Background</p> <p>Recent advances in genomics and proteomics have allowed us to study the nuances of the Warburg effect – a long-standing puzzle in cancer energy metabolism – at an unprecedented level of detail. While modern next-generation sequencing technologies are extremely powerful, the lack of appropriate data analysis tools makes this study difficult. To meet this challenge, we developed a novel application for comparative analysis of gene expression and visualization of RNA-Seq data.</p> <p>Results</p> <p>We analyzed two biological samples (normal human brain tissue and human cancer cell lines) with high-energy, metabolic requirements. We calculated digital topology and the copy number of every expressed transcript. We observed subtle but remarkable qualitative and quantitative differences between the citric acid (TCA) cycle and glycolysis pathways. We found that in the first three steps of the TCA cycle, digital expression of aconitase 2 (<it>ACO2</it>) in the brain exceeded both citrate synthase (<it>CS</it>) and isocitrate dehydrogenase 2 (<it>IDH2</it>), while in cancer cells this trend was quite the opposite. In the glycolysis pathway, all genes showed higher expression levels in cancer cell lines; and most notably, digital gene expression of glyceraldehyde-3-phosphate dehydrogenase (<it>GAPDH</it>) and enolase (<it>ENO</it>) were considerably increased when compared to the brain sample.</p> <p>Conclusions</p> <p>The variations we observed should affect the rates and quantities of ATP production. We expect that the developed tool will provide insights into the subtleties related to the causality between the Warburg effect and neoplastic transformation. Even though we focused on well-known and extensively studied metabolic pathways, the data analysis and visualization pipeline that we developed is particularly valuable as it is global and pathway-independent.</p

Autophagy mediates degradation of nuclear lamina

Z.D. is supported by a fellow award from the Leukemia & Lymphoma Society. B.C.C. is supported by career development awards from the Dermatology Foundation, Melanoma Research Foundation, and American Skin Association. S.L.B., P.D.A. and R.M. are supported by NIA P01 grant (P01AG031862). S.L.B. is also supported by NIH R01 CA078831. R.D.G. is supported by R01 GM106023 and the Progeria Research Foundation

Splenectomy Normalizes Hematocrit in Murine Polycythemia Vera

Splenic enlargement (splenomegaly) develops in numerous disease states, although a specific pathogenic role for the spleen has rarely been described. In polycythemia vera (PV), an activating mutation in Janus kinase 2 (JAK2V617) induces splenomegaly and an increase in hematocrit. Splenectomy is sparingly performed in patients with PV, however, due to surgical complications. Thus, the role of the spleen in the pathogenesis of human PV remains unknown. We specifically tested the role of the spleen in the pathogenesis of PV by performing either sham (SH) or splenectomy (SPL) surgeries in a murine model of JAK2V617F-driven PV. Compared to SH-operated mice, which rapidly develop high hematocrits after JAK2V617F transplantation, SPL mice completely fail to develop this phenotype. Disease burden (JAK2V617) is equivalent in the bone marrow of SH and SPL mice, however, and both groups develop fibrosis and osteosclerosis. If SPL is performed after PV is established, hematocrit rapidly declines to normal even though myelofibrosis and osteosclerosis again develop independently in the bone marrow. In contrast, SPL only blunts hematocrit elevation in secondary, erythropoietin-induced polycythemia. We conclude that the spleen is required for an elevated hematocrit in murine, JAK2V617F-driven PV, and propose that this phenotype of PV may require a specific interaction between mutant cells and the spleen

Deep reinforcement learning for drone navigation using sensor data

Mobile robots such as unmanned aerial vehicles (drones) can be used for surveillance, monitoring and data collection in buildings, infrastructure and environments. The importance of accurate and multifaceted monitoring is well known to identify problems early and prevent them escalating. This motivates the need for flexible, autonomous and powerful decision-making mobile robots. These systems need to be able to learn through fusing data from multiple sources. Until very recently, they have been task specific. In this paper, we describe a generic navigation algorithm that uses data from sensors on-board the drone to guide the drone to the site of the problem. In hazardous and safety-critical situations, locating problems accurately and rapidly is vital. We use the proximal policy optimisation deep reinforcement learning algorithm coupled with incremental curriculum learning and long short-term memory neural networks to implement our generic and adaptable navigation algorithm. We evaluate different configurations against a heuristic technique to demonstrate its accuracy and efficiency. Finally, we consider how safety of the drone could be assured by assessing how safely the drone would perform using our navigation algorithm in real-world scenarios

A primary care database study of asthma among patients with and without opioid use disorders

Substance misuse is associated with poor asthma outcome and death. People with opioid use disorder (OUD) may be at particular risk, however, there have been no case-control studies of asthma care and outcomes in this patient group. A primary care database study of patients with asthma aged 16–65 years was conducted using a matched case-control methodology. The dataset comprised 275,151 adults with asthma, of whom 459 had a clinical code indicating a lifetime history of OUD. Cases with a history of OUD were matched to controls 1:3 by age, gender, smoking status and deprivation index decile. Attendance at annual review (30%) and for immunisation (25%) was poor amongst the overall matched study population (N = 1832). Compared to matched controls, cases were less likely to have attended for asthma review during the previous 12 months (OR = 0.60, 95% CI 0.45–0.80) but had similar immunisation rates. Higher rates of ICS (OR = 1.50, 1.13–1.98) and oral prednisolone use (OR = 1.71, 1.25–2.40) were seen amongst those with a history of OUD and 7.2% had a concurrent diagnosis of COPD (OR = 1.86, 1.12–2.40). We found that people with asthma and a history of OUD have worse outcomes on several commonly measured metrics of asthma care. Further research is required to identify reasons for these findings, the most effective strategies to help this vulnerable group access basic asthma care, and to better understand long-term respiratory outcomes

Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

A Genome-Wide Identification Analysis of Small Regulatory RNAs in Mycobacterium tuberculosis by RNA-Seq and Conservation Analysis

We propose a new method for smallRNAs (sRNAs) identification. First we build an effective target genome (ETG) by means of a strand-specific procedure. Then we propose a new bioinformatic pipeline based mainly on the combination of two types of information: the first provides an expression map based on RNA-seq data (Reads Map) and the second applies principles of comparative genomics leading to a Conservation Map. By superimposing these two maps, a robust method for the search of sRNAs is obtained. We apply this methodology to investigate sRNAs in Mycobacterium tuberculosis H37Rv. This bioinformatic procedure leads to a total list of 1948 candidate sRNAs. The size of the candidate list is strictly related to the aim of the study and to the technology used during the verification process. We provide performance measures of the algorithm in identifying annotated sRNAs reported in three recent published studies