GEMPAK5 user's guide, version 5.0

GEMPAK is a general meteorological software package used to analyze and display conventional meteorological data as well as satellite derived parameters. The User's Guide describes the GEMPAK5 programs and input parameters and details the algorithms used for the meteorological computations

GEMPAK5. Part 1: GEMPAK5 programmer's guide, version 5.0

GEMPAK is a general meteorological software package used to analyze and display conventional meteorological data as well as satellite derived parameters. The Programmer's Guide describes the subroutines which can be used to build new GEMPAK programs. Part 1 contains GEMPAK subroutines

Interstitial chemotherapy with biodegradable BCNU (Gliadel®) wafers in the treatment of malignant gliomas

Malignant gliomas represent the majority of primary brain tumors, and the prognosis of the patients afflicted with these tumors has been historically dismal, with almost uniform progressive neurologic impairment and rapid death. Even with multimodal treatment using surgery, focal radiation, and chemotherapy, no major strides were made until recently. The development of interstitial BCNU wafers (carmustine wafers, Gliadel®) has led to promising results in the treatment of a selected patients with malignant gliomas, as well as with other intracranial malignancies.BCNU is one of the first systemic chemotherapies which had obtained United States Food and Drug Administration (FDA) approval for the treatment of brain tumors. However, systemic use has been hampered by the modest prolongation of survival and by the prolonged myelosuppression and potentially fatal pulmonary toxicity. The development of interstitial therapies with BCNU represented a great step forward, allowing direct delivery to the tumor bed, with virtually no systemic toxicities. Clinical studies of BCNU wafers have showed good efficacy in both newly diagnosed and recurrent gliomas, as well as a possible therapeutic role in other primary or secondary intracranial malignancies. New studies are currently underway trying to improve the efficacy of the BCNU wafers (Gliadel®) by combining them with different systemic chemotherapies. An overview of the current knowledge ranging from the preclinical developments, to the efficacy and safety seen in the clinical trials and in clinical practice following the drug approval to the future avenues of research is therefore timely

Le Forum, Vol. 44 #4

https://digitalcommons.library.umaine.edu/francoamericain_forum/1106/thumbnail.jp

Placenta Imaging Workshop 2018 report:Multiscale and multimodal approaches

The Centre for Medical Image Computing (CMIC) at University College London (UCL) hosted a two-day workshop on placenta imaging on April 12th and 13th 2018. The workshop consisted of 10 invited talks, 3 contributed talks, a poster session, a public interaction session and a panel discussion about the future direction of placental imaging. With approximately 50 placental researchers in attendance, the workshop was a platform for engineers, clinicians and medical experts in the field to network and exchange ideas. Attendees had the chance to explore over 20 posters with subjects ranging from the movement of blood within the placenta to the efficient segmentation of fetal MRI using deep learning tools. UCL public engagement specialists also presented a poster, encouraging attendees to learn more about how to engage patients and the public with their research, creating spaces for mutual learning and dialogue

Stage-Specific Pathways of Leishmania infantum chagasi Entry and Phagosome Maturation in Macrophages

The life stages of Leishmania spp. include the infectious promastigote and the replicative intracellular amastigote. Each stage is phagocytosed by macrophages during the parasite life cycle. We previously showed that caveolae, a subset of cholesterol-rich membrane lipid rafts, facilitate uptake and intracellular survival of virulent promastigotes by macrophages, at least in part, by delaying parasitophorous vacuole (PV)-lysosome fusion. We hypothesized that amastigotes and promastigotes would differ in their route of macrophage entry and mechanism of PV maturation. Indeed, transient disruption of macrophage lipid rafts decreased the entry of promastigotes, but not amastigotes, into macrophages (P<0.001). Promastigote-containing PVs were positive for caveolin-1, and co-localized transiently with EEA-1 and Rab5 at 5 minutes. Amastigote-generated PVs lacked caveolin-1 but retained Rab5 and EEA-1 for at least 30 minutes or 2 hours, respectively. Coinciding with their conversion into amastigotes, the number of promastigote PVs positive for LAMP-1 increased from 20% at 1 hour, to 46% by 24 hours, (P<0.001, Chi square). In contrast, more than 80% of amastigote-initiated PVs were LAMP-1+ at both 1 and 24 hours. Furthermore, lipid raft disruption increased LAMP-1 recruitment to promastigote, but not to amastigote-containing compartments. Overall, our data showed that promastigotes enter macrophages through cholesterol-rich domains like caveolae to delay fusion with lysosomes. In contrast, amastigotes enter through a non-caveolae pathway, and their PVs rapidly fuse with late endosomes but prolong their association with early endosome markers. These results suggest a model in which promastigotes and amastigotes use different mechanisms to enter macrophages, modulate the kinetics of phagosome maturation, and facilitate their intracellular survival

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment