The First VERITAS Telescope

The first atmospheric Cherenkov telescope of VERITAS (the Very Energetic Radiation Imaging Telescope Array System) has been in operation since February 2005. We present here a technical description of the instrument and a summary of its performance. The calibration methods are described, along with the results of Monte Carlo simulations of the telescope and comparisons between real and simulated data. The analysis of TeV $\gamma$-ray observations of the Crab Nebula, including the reconstructed energy spectrum, is shown to give results consistent with earlier measurements. The telescope is operating as expected and has met or exceeded all design specifications.Comment: Accepted by Astroparticle Physic

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy

Pengaruh Pemberian Ketotifen terhadap Jumlah Sel Fibroblas dan Kepadatan Sel Kolagen pada Luka Insisi Tikus Wistar

Ingga Hadian, S-501202027. PENGARUH PEMBERIAN KETOTIFEN TERHADAP JUMLAH SEL FIBROBLAS DAN KEPADATAN SEL KOLAGEN PADA LUKA INSISI TIKUS WISTAR. Pembimbing I : DR. Untung Alfianto, dr, Sp.Bs, Pembimbing II : dr. Ardana Tri Arianto. Msi. Med. Sp.An-KNA. Program studi Magister Kedokteran Keluarga, Minat Utama Ilmu Biomedik, Fakultas Kedokteran Universitas Sebelas Maret, Surakarta, 2016. Latar Belakang : Sel mast merupakan salah satu yang berperan dalam proses inflamasi pada penyembuhan luka. Sel mast dikaitkan dengan kejadian luka kronis, sehingga sel mast diduga ikut memelihara proses inflamasi secara berlebihan. Hambatan pada degranulasi sel mast diharapkan akan mempercepat penyembuhan luka yang ditandai dengan meningkatnya jumlah sel fibroblas dan kepadatan sel kolagen. Ketotifen mampu mengurangi dreganulasi sel Mast dan mengurangi pelepasan Histamin, protease sel Mast, myeloperoxidase, leukotriens, PAF dan bermacam-macam Prostaglandin. Ketotifen juga menghambat agregasi polimorfonuklear serta mengurangi respon inflamasi dan mempercepat migrasi fibroblas di fase proliferasi. Tujuan :Mengetahui perbedaan jumlah sel fibroblas dan kepadatan sel kolagen pada tikus wistar yang diberikan Ketotifen oral dosis 0.3 mg/kg dibandingkan plasebo pada penyembuhan luka insisi tikus wistar. Metode : Penelitian ini termasuk true eksperimental laboratorik dengan desain Randomized Controlled Trial yang menggunakan tikus wistar sebagai obyek penelitian. 14 tikus Wistar dibagi dalam 2 kelompok, masing masing kelompok terdiri atas 7 tikus Wistar. Kelompok 1 merupakan kelompok kontrol yang dilakukan insisi sepanjang 2cm pada kulit punggung tikus dan diberikan plasebo per oral selama 6 hari. Kelompok 2 merupakan kelompok perlakuan yang dilakukan insisi sepanjang 2cm pada kulit punggung tikus dan diberikan Ketotifen 0,3 mg/kgBB per oral setiap 12 jam selama 6 hari. Analisis data untuk membandingkan rerata antar kedua kelompok yaitu kelompok perlakuan dan kelompok kontrol menggunakan uji independent samples t-test, dengan tingkat kemaknaan p < 0,05 (dikatakan bermakna secara statistik). Hasil : Pada kelompok kontrol didapatkan rerata persentase kepadatan sel kolagen sebesar 26,05 %, sedangkan pada kelompok Ketotifen didapatkan rerata persentase kepadatan sel kolagen sebesar 36,13 %. Untuk jumlah sel fibroblas pada kelompok kontrol didapatkan rerata sebesar 423 per lapang pandang, sedangkan pada kelompok Ketotifen didapatkan rerata sebesar 555,43 per lapang pandang. Kesimpulan : Ketotifen mempercepat penyembuhan luka ditandai dengan peningkatan sel fibroblas dan sel kolagen. Kata Kunci : Sel Mast, Ketotifen, Sel fibroblas, Serabut Kolagen. ABSTRACT Ingga Hadian, S-501202027. EFFECTS OF KETOTIFEN ON FIBROBLAST CELL COUNT AND COLLAGEN DENSITY ON INCISED WISTAR RATS. DR. Untung Alfianto, dr., Sp.BS, dr. Ardana Tri Arianto, Msi, Med, Sp.An-KNA. Background: Mast cells have a pivotal role in every healing process that involves inflammation of the cells, usually in wounds of chronic nature. If the degranulation process of the mast cells are inhibited, the healing process of the wound will accelerate, indicated by a raise in fibroblast cells and collagen density. Ketotifen are shown to inhibit the degranulation process and decreasing the release of histamin, mast cells proteases, myeloperoxidases, leukotriens, PAF, and various prostaglandins. Ketotifen can also inhibit the aggregation of polymorphonuclear cells, increasing the rate of fibroblast migration in the proliferation phase. This study was aimed to identify the effects of ketotifen on fibroblast cell count and collagen density tested on a wistar rats model. Methods: This study was a true laboratoric experimental study with randomized controlled trial using wistar rats model as objects. 14 rats were divided into two groups, each group contained seven rats. The first group was the control group, where the rats were incised 2 cm above the back skin, and were given per oral placebo for 6 days. The second group were given the same treatment, only the rats were given ketotifen 0.3 mg/kg per oral, every 12 hours lasting 6 days. The data were then collected and tested with independent sample t-test, with p value less than 0,05 is statistically significant. Results: In the control group, the mean percentage of the thickest collagen density were marked at 26.05%, whereas in the treatment group collagen density were marked at 36.13%. The mean fibroblast cell count were marked at 423 and 555.43 each viewing field, on the control group and the treatment group respectively. Conclusion: Ketotifen can accelerate the healing process, marked by the significant increase in collagen density and fibroblast cell count. Keywords: mast cells, ketotifen, fibroblast cells, collagen fibers

Multiwavelength observations of a TeV-Flare from W comae

We report results from an intensive multiwavelength campaign on the intermediate-frequency-peaked BL Lacertae object W Com (z = 0.102) during a strong outburst of very high energy gamma-ray emission in 2008 June. The very high energy gamma-ray signal was detected by VERITAS on 2008 June 7-8 with a flux F(>200 GeV) =(5.7 0.6) × 10-11 cm-2 s -1, about three times brighter than during the discovery of gamma-ray emission from W Com by VERITAS in 2008 March. The initial detection of this flare by VERITAS at energies above 200 GeV was followed by observations in high-energy gamma rays (AGILE; E γ≥ 100 MeV), X-rays (Swift and XMM-Newton), and at UV, and ground-based optical and radio monitoring through the GASP-WEBT consortium and other observatories. Here we describe the multiwavelength data and derive the spectral energy distribution of the source from contemporaneous data taken throughout the flare. © 2009. The American Astronomical Society. All rights reserved

The Great Markarian 421 Flare of 2010 February: Multiwavelength Variability and Correlation Studies

We report on variability and correlation studies using multiwavelength observations of the blazar Mrk 421 during the month of 2010 February, when an extraordinary flare reaching a level of ∼27 Crab Units above 1 TeV was measured in very high energy (VHE) γ-rays with the Very Energetic Radiation Imaging Telescope Array System (VERITAS) observatory. This is the highest flux state for Mrk 421 ever observed in VHE γ-rays. Data are analyzed from a coordinated campaign across multiple instruments, including VHE γ-ray (VERITAS, Major Atmospheric Gamma-ray Imaging Cherenkov), high-energy γ-ray (Fermi-LAT), X-ray (Swift, Rossi X-ray Timing Experiment, MAXI), optical (including the GASP-WEBT collaboration and polarization data), and radio (Metsahovi, Owens Valley Radio Observatory, University of Michigan Radio Astronomy Observatory). Light curves are produced spanning multiple days before and after the peak of the VHE flare, including over several flare "decline" epochs. The main flare statistics allow 2 minute time bins to be constructed in both the VHE and optical bands enabling a cross-correlation analysis that shows evidence for an optical lag of ∼25-55 minutes, the first time-lagged correlation between these bands reported on such short timescales. Limits on the Doppler factor (δ ⪆ 33) and the size of the emission region (δ-1RB≲ 3.8 × 1013cm) are obtained from the fast variability observed by VERITAS during the main flare. Analysis of 10 minute binned VHE and X-ray data over the decline epochs shows an extraordinary range of behavior in the flux-flux relationship, from linear to quadratic to lack of correlation to anticorrelation. Taken together, these detailed observations of an unprecedented flare seen in Mrk 421 are difficult to explain with the classic single-zone synchrotron self-Compton model.</p

The Immune Landscape of Cancer

We performed an extensive immunogenomic anal-ysis of more than 10,000 tumors comprising 33diverse cancer types by utilizing data compiled byTCGA. Across cancer types, we identified six im-mune subtypes\u2014wound healing, IFN-gdominant,inflammatory, lymphocyte depleted, immunologi-cally quiet, and TGF-bdominant\u2014characterized bydifferences in macrophage or lymphocyte signa-tures, Th1:Th2 cell ratio, extent of intratumoral het-erogeneity, aneuploidy, extent of neoantigen load,overall cell proliferation, expression of immunomod-ulatory genes, and prognosis. Specific drivermutations correlated with lower (CTNNB1,NRAS,orIDH1) or higher (BRAF,TP53,orCASP8) leukocytelevels across all cancers. Multiple control modalitiesof the intracellular and extracellular networks (tran-scription, microRNAs, copy number, and epigeneticprocesses) were involved in tumor-immune cell inter-actions, both across and within immune subtypes.Our immunogenomics pipeline to characterize theseheterogeneous tumors and the resulting data areintended to serve as a resource for future targetedstudies to further advance the field

Oncogenic Signaling Pathways in The Cancer Genome Atlas

Genetic alterations in signaling pathways that control cell-cycle progression, apoptosis, and cell growth are common hallmarks of cancer, but the extent, mechanisms, and co-occurrence of alterations in these pathways differ between individual tumors and tumor types. Using mutations, copy-number changes, mRNA expression, gene fusions and DNA methylation in 9,125 tumors profiled by The Cancer Genome Atlas (TCGA), we analyzed the mechanisms and patterns of somatic alterations in ten canonical pathways: cell cycle, Hippo, Myc, Notch, Nrf2, PI-3-Kinase/Akt, RTK-RAS, TGFb signaling, p53 and beta-catenin/Wnt. We charted the detailed landscape of pathway alterations in 33 cancer types, stratified into 64 subtypes, and identified patterns of co-occurrence and mutual exclusivity. Eighty-nine percent of tumors had at least one driver alteration in these one alteration potentially targetable by currently available drugs. Thirty percent of tumors had multiple targetable alterations, indicating opportunities for combination therapy

Insights into the high-energy γ-ray emission of Markarian 501 from extensive multifrequency observations in the Fermi era

We report on the γ-ray activity of the blazar Mrk 501 during the first 480 days of Fermi operation. We find that the average Large Area Telescope (LAT) γ-ray spectrum of Mrk 501 can be well described by a single power-law function with a photon index of 1.78 ± 0.03. While we observe relatively mild flux variations with the Fermi-LAT (within less than a factor of two), we detect remarkable spectral variability where the hardest observed spectral index within the LAT energy range is 1.52 ± 0.14, and the softest one is 2.51 ± 0.20. These unexpected spectral changes do not correlate with the measured flux variations above 0.3 GeV. In this paper, we also present the first results from the 4.5 month long multifrequency campaign (2009 March 15-August 1) on Mrk 501, which included the Very Long Baseline Array (VLBA), Swift, RXTE, MAGIC, and VERITAS, the F-GAMMA, GASP-WEBT, and other collaborations and instruments which provided excellent temporal and energy coverage of the source throughout the entire campaign. The extensive radio to TeV data set from this campaign provides us with the most detailed spectral energy distribution yet collected for this source during its relatively low activity. The average spectral energy distribution of Mrk 501 is well described by the standard one-zone synchrotron self-Compton (SSC) model. In the framework of this model, we find that the dominant emission region is characterized by a size ≲0.1 pc (comparable within a factor of few to the size of the partially resolved VLBA core at 15-43 GHz), and that the total jet power (≃1044 erg s-1) constitutes only a small fraction (∼10-3) of the Eddington luminosity. The energy distribution of the freshly accelerated radiating electrons required to fit the time-averaged data has a broken power-law form in the energy range 0.3 GeV-10 TeV, with spectral indices 2.2 and 2.7 below and above the break energy of 20 GeV. We argue that such a form is consistent with a scenario in which the bulk of the energy dissipation within the dominant emission zone of Mrk 501 is due to relativistic, proton-mediated shocks. We find that the ultrarelativistic electrons and mildly relativistic protons within the blazar zone, if comparable in number, are in approximate energy equipartition, with their energy dominating the jet magnetic field energy by about two orders of magnitude. © 2011. The American Astronomical Society

Machine Learning Detects Pan-cancer Ras Pathway Activation in The Cancer Genome Atlas

Precision oncology uses genomic evidence to match patients with treatment but often fails to identify all patients who may respond. The transcriptome of these \u201chidden responders\u201d may reveal responsive molecular states. We describe and evaluate a machine-learning approach to classify aberrant pathway activity in tumors, which may aid in hidden responder identification. The algorithm integrates RNA-seq, copy number, and mutations from 33 different cancer types across The Cancer Genome Atlas (TCGA) PanCanAtlas project to predict aberrant molecular states in tumors. Applied to the Ras pathway, the method detects Ras activation across cancer types and identifies phenocopying variants. The model, trained on human tumors, can predict response to MEK inhibitors in wild-type Ras cell lines. We also present data that suggest that multiple hits in the Ras pathway confer increased Ras activity. The transcriptome is underused in precision oncology and, combined with machine learning, can aid in the identification of hidden responders. Way et al. develop a machine-learning approach using PanCanAtlas data to detect Ras activation in cancer. Integrating mutation, copy number, and expression data, the authors show that their method detects Ras-activating variants in tumors and sensitivity to MEK inhibitors in cell lines