145 research outputs found
Cardiac arrhythmias in patients with COVID-19.
The emergence of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a major global public health concern. Although SARS-CoV-2 causes primarily respiratory problems, concurrent cardiac injury cannot be ignored since it may be an independent predictor for adverse outcomes. Cardiac arrhythmias are often observed in patients with COVID-19, especially in severe cases, and more likely contribute to the high risk of adverse outcomes. Arrhythmias should be regarded as one of the main complications of COVID-19. Mechanistically, a number of ion channels can be adversely affected in COVID-19, leading to alterations in cardiac conduction and/or repolarization properties, as well as calcium handling, which can predispose to cardiac arrhythmogenesis. In addition, several antimicrobials that are currently used as potential therapeutic agents for COVID-19, such as chloroquine, hydroxychloroquine and azithromycin, have uncertain benefit, and yet may induce electrocardiographic QT prolongation with potential ventricular pro-arrhythmic effects. Continuous electrocardiogram monitoring, accurate and prompt recognition of arrhythmias are important. The present review focuses on cardiac arrhythmias in patients with COVID-19, its underlying mechanisms, and proposed preventive and therapeutic strategies
Results from the centers for disease control and prevention's predict the 2013-2014 Influenza Season Challenge
Background: Early insights into the timing of the start, peak, and intensity of the influenza season could be useful in planning influenza prevention and control activities. To encourage development and innovation in influenza forecasting, the Centers for Disease Control and Prevention (CDC) organized a challenge to predict the 2013-14 Unites States influenza season. Methods: Challenge contestants were asked to forecast the start, peak, and intensity of the 2013-2014 influenza season at the national level and at any or all Health and Human Services (HHS) region level(s). The challenge ran from December 1, 2013-March 27, 2014; contestants were required to submit 9 biweekly forecasts at the national level to be eligible. The selection of the winner was based on expert evaluation of the methodology used to make the prediction and the accuracy of the prediction as judged against the U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet). Results: Nine teams submitted 13 forecasts for all required milestones. The first forecast was due on December 2, 2013; 3/13 forecasts received correctly predicted the start of the influenza season within one week, 1/13 predicted the peak within 1 week, 3/13 predicted the peak ILINet percentage within 1 %, and 4/13 predicted the season duration within 1 week. For the prediction due on December 19, 2013, the number of forecasts that correctly forecasted the peak week increased to 2/13, the peak percentage to 6/13, and the duration of the season to 6/13. As the season progressed, the forecasts became more stable and were closer to the season milestones. Conclusion: Forecasting has become technically feasible, but further efforts are needed to improve forecast accuracy so that policy makers can reliably use these predictions. CDC and challenge contestants plan to build upon the methods developed during this contest to improve the accuracy of influenza forecasts. © 2016 The Author(s)
Increased capsaicin receptor TRPV1 in skin nerve fibres and related vanilloid receptors TRPV3 and TRPV4 in keratinocytes in human breast pain
BACKGROUND: Breast pain and tenderness affects 70% of women at some time. These symptoms have been attributed to stretching of the nerves with increase in breast size, but tissue mechanisms are poorly understood. METHODS: Eighteen patients (n = 12 breast reduction and n = 6 breast reconstruction) were recruited and assessed for breast pain by clinical questionnaire. Breast skin biopsies from each patient were examined using immunohistological methods with specific antibodies to the capsaicin receptor TRPV1, related vanilloid thermoreceptors TRPV3 and TRPV4, and nerve growth factor (NGF). RESULTS: TRPV1-positive intra-epidermal nerve fibres were significantly increased in patients with breast pain and tenderness (TRPV1 fibres / mm epidermis, median [range] – no pain group, n = 8, 0.69 [0–1.27]; pain group, n = 10, 2.15 [0.77–4.38]; p = 0.0009). Nerve Growth Factor, which up-regulates TRPV1 and induces nerve sprouting, was present basal keratinocytes: some breast pain specimens also showed NGF staining in supra-basal keratinocytes. TRPV4-immunoreactive fibres were present in sub-epidermis but not significantly changed in painful breast tissue. Both TRPV3 and TRPV4 were significantly increased in keratinocytes in breast pain tissues; TRPV3, median [range] – no pain group, n = 6, 0.75 [0–2]; pain group, n = 11, 2 [1-3], p = 0.008; TRPV4, median [range] – no pain group, n = 6, [0–1]; pain group, n = 11, 1 [0.5–2], p = 0.014). CONCLUSION: Increased TRPV1 intra-epidermal nerve fibres could represent collateral sprouts, or re-innervation following nerve stretch and damage by polymodal nociceptors. Selective TRPV1-blockers may provide new therapy in breast pain. The role of TRPV3 and TRPV4 changes in keratinocytes deserve further study
Genomic profiling of plasmablastic lymphoma using array comparative genomic hybridization (aCGH): revealing significant overlapping genomic lesions with diffuse large B-cell lymphoma
<p>Abstract</p> <p>Background</p> <p>Plasmablastic lymphoma (PL) is a subtype of diffuse large B-cell lymphoma (DLBCL). Studies have suggested that tumors with PL morphology represent a group of neoplasms with clinopathologic characteristics corresponding to different entities including extramedullary plasmablastic tumors associated with plasma cell myeloma (PCM). The goal of the current study was to evaluate the genetic similarities and differences among PL, DLBCL (AIDS-related and non AIDS-related) and PCM using array-based comparative genomic hybridization.</p> <p>Results</p> <p>Examination of genomic data in PL revealed that the most frequent segmental gain (> 40%) include: 1p36.11-1p36.33, 1p34.1-1p36.13, 1q21.1-1q23.1, 7q11.2-7q11.23, 11q12-11q13.2 and 22q12.2-22q13.3. This correlated with segmental gains occurring in high frequency in DLBCL (AIDS-related and non AIDS-related) cases. There were some segmental gains and some segmental loss that occurred in PL but not in the other types of lymphoma suggesting that these foci may contain genes responsible for the differentiation of this lymphoma. Additionally, some segmental gains and some segmental loss occurred only in PL and AIDS associated DLBCL suggesting that these foci may be associated with HIV infection. Furthermore, some segmental gains and some segmental loss occurred only in PL and PCM suggesting that these lesions may be related to plasmacytic differentiation.</p> <p>Conclusion</p> <p>To the best of our knowledge, the current study represents the first genomic exploration of PL. The genomic aberration pattern of PL appears to be more similar to that of DLBCL (AIDS-related or non AIDS-related) than to PCM. Our findings suggest that PL may remain best classified as a subtype of DLBCL at least at the genome level.</p
Recurrent Fusion Genes in Gastric Cancer: CLDN18-ARHGAP26 Induces Loss of Epithelial Integrity.
Genome rearrangements, a hallmark of cancer, can result in gene fusions with oncogenic properties. Using DNA paired-end-tag (DNA-PET) whole-genome sequencing, we analyzed 15 gastric cancers (GCs) from Southeast Asians. Rearrangements were enriched in open chromatin and shaped by chromatin structure. We identified seven rearrangement hot spots and 136 gene fusions. In three out of 100 GC cases, we found recurrent fusions between CLDN18, a tight junction gene, and ARHGAP26, a gene encoding a RHOA inhibitor. Epithelial cell lines expressing CLDN18-ARHGAP26 displayed a dramatic loss of epithelial phenotype and long protrusions indicative of epithelial-mesenchymal transition (EMT). Fusion-positive cell lines showed impaired barrier properties, reduced cell-cell and cell-extracellular matrix adhesion, retarded wound healing, and inhibition of RHOA. Gain of invasion was seen in cancer cell lines expressing the fusion. Thus, CLDN18-ARHGAP26 mediates epithelial disintegration, possibly leading to stomach H(+) leakage, and the fusion might contribute to invasiveness once a cell is transformed. Cell Rep 2015 Jul 14; 12(2):272-285
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 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
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
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