A Multi-wavelength Survey of AGN in Massive Clusters: AGN Detection and Cluster AGN Fraction

We aim to study the effect of environment on the presence and fuelling of Active Galactic Nuclei (AGN) in massive galaxy clusters. We explore the use of different AGN detection techniques with the goal of selecting AGN across a broad range of luminosities, AGN/host galaxy flux ratios, and obscuration levels. From a sample of 12 galaxy clusters at redshifts 0.5 < z < 0.9, we identify AGN candidates using optical variability from multi-epoch HST imaging, X-ray point sources in Chandra images, and mid-IR SED power-law fits through the Spitzer IRAC channels. We find 178 optical variables, 74 X-ray point sources, and 64 IR power law sources, resulting in an average of ~25 AGN per cluster. We find no significant difference between the fraction of AGN among galaxies in clusters and the percentage of similarly-detected AGN in field galaxy studies (~2.5%). This result provides evidence that galaxies are still able to fuel accretion onto their supermassive black holes, even in dense environments. We also investigate correlations between the percentage of AGN and cluster physical properties such as mass, X-ray luminosity, size, morphology class and redshift. We find no significant correlations among cluster properties and the percentage of AGN detected.Comment: 68 pages, 22 figures, 15 table

Predominance of enterovirus B and echovirus 30 as cause of viral meningitis in a UK population.

BACKGROUND/OBJECTIVES: Enteroviruses are the most common cause of aseptic or lymphocytic meningitis, particularly in children. With reports of unusually severe neurological disease in some patients infected with enterovirus D68 in North America, and a recent increase in the number of paediatric enterovirus meningitis cases presenting in this UK Midlands population, a retrospective regional surveillance study was performed. STUDY DESIGN: Cerebrospinal fluid (CSF) samples received were tested using the polymerase chain reaction (PCR) for HSV-1/2, VZV, enteroviruses and parechoviruses. Enterovirus PCR positive CSF samples were sent for further serotyping. A phylogenetic tree was constructed of the echovirus 30 VP1 sequences, where sufficient sample remained for sequencing. RESULTS: The number of enterovirus positive CSFs from each year were: 21 (2008), 7 (2011), 53 (2012), 58 (2013) and 31 (2014). Overall, 163 of the 170 serotyped enteroviruses belonged to the species B (echovirus 5, 6, 7, 9, 11, 13, 16, 17, 18, 21, 25, 30; coxsackie B1, B2, B3, B4, B5, A9), with only 7 belonging to species A (coxsackie A2, A6, A16 and enterovirus 71). Echovirus 30 was the predominant serotype overall, identified in 43 (25.3%) of samples, with a significantly higher proportion in the adult age group (37.3%) compared to the infant age group (12.3%). Phylogenetic analysis showed that these UK Midlands echovirus 30 VP1 sequences clustered most closely with those from Europe and China. CONCLUSION: This study showed a continued predominance of echovirus 30 as a cause of viral meningitis, particularly in adults, though more surveillance is needed

Genetic Diversity and Dispersal of DENGUE Virus among Three Main Island Groups of the Philippines during 2015-2017

Dengue has been one of the major public health concerns in the Philippines for more than a century. The annual dengue case burden has been increasing in recent years, exceeding 200,000 in 2015 and 2019. However, there is limited information on the molecular epidemiology of dengue in the Philippines. We, therefore, conducted a study to understand the genetic composition and dispersal of DENV in the Philippines from 2015 to 2017 under UNITEDengue. Our analyses included 377 envelope (E) gene sequences of all 4 serotypes obtained from infections in 3 main island groups (Luzon, Visayas, and Mindanao) of the Philippines. The findings showed that the overall diversity of DENV was generally low. DENV-1 was relatively more diverse than the other serotypes. Virus dispersal was evident among the three main island groups, but each island group demonstrated a distinct genotype composition. These observations suggested that the intensity of virus dispersal was not substantive enough to maintain a uniform heterogeneity among island groups so that each island group behaved as an independent epidemiological unit. The analyses suggested Luzon as one of the major sources of DENV emergence and CAR, Calabarzon, and CARAGA as important hubs of virus dispersal in the Philippines. Our findings highlight the importance of virus surveillance and molecular epidemiological analyses to gain deep insights into virus diversity, lineage dominance, and dispersal patterns that could assist in understanding the epidemiology and transmission risk of dengue in endemic regions

Modelling lockdown and exit strategies for COVID-19 in Singapore.

BACKGROUND: With at least 94 countries undergoing or exiting lockdowns for contact suppression to control the COVID-19 outbreak, sustainable and public health-driven exit strategies are required. Here we explore the impact of lockdown and exit strategies in Singapore for immediate planning. METHODS: We use an agent-based model to examine the impacts of epidemic control over 480 days. A limited control baseline of case isolation and household member quarantining is used. We measure the impact of lockdown duration and start date on final infection attack sizes. We then apply a 3-month gradual exit strategy, immediately re-opening schools and easing workplace distancing measures, and compare this to long-term social distancing measures. FINDINGS: At baseline, we estimated 815 400 total infections (21.6% of the population). Early lockdown at 5 weeks with no exit strategy averted 18 500 (2.27% of baseline averted), 21 300 (2.61%) and 22 400 (2.75%) infections for 6, 8 and 9-week lockdown durations. Using the exit strategy averted a corresponding 114 700, 121 700 and 126 000 total cases, representing 12.07-13.06% of the total epidemic size under baseline. This diminishes to 9 900-11 300 for a late 8-week start time. Long-term social distancing at 6 and 8-week durations are viable but less effective. INTERPRETATION: Gradual release exit strategies are critical to maintain epidemic suppression under a new normal. We present final infection attack sizes assuming the ongoing importation of cases, which require preparation for a potential second epidemic wave due to ongoing epidemics elsewhere. FUNDING: Singapore Ministry of Health, Singapore Population Health Improvement Centre

Uncoupling the functions of CALM in VAMP sorting and clathrin-coated pit formation.

CALM (clathrin assembly lymphoid myeloid leukemia protein) is a cargo-selective adaptor for the post-Golgi R-SNAREs VAMPs 2, 3, and 8, and it also regulates the size of clathrin-coated pits and vesicles at the plasma membrane. The present study has two objectives: to determine whether CALM can sort additional VAMPs, and to investigate whether VAMP sorting contributes to CALM-dependent vesicle size regulation. Using a flow cytometry-based endocytosis efficiency assay, we demonstrate that CALM is also able to sort VAMPs 4 and 7, even though they have sorting signals for other clathrin adaptors. CALM homologues are present in nearly every eukaryote, suggesting that the CALM family may have evolved as adaptors for retrieving all post-Golgi VAMPs from the plasma membrane. Using a knockdown/rescue system, we show that wild-type CALM restores normal VAMP sorting in CALM-depleted cells, but that two non-VAMP-binding mutants do not. However, when we assayed the effect of CALM depletion on coated pit morphology, using a fluorescence microscopy-based assay, we found that the two mutants were as effective as wild-type CALM. Thus, we can uncouple the sorting function of CALM from its structural role

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

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

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