CD4+ T cell recovery during suppression of HIV replication: an international comparison of the immunological efficacy of antiretroviral therapy in North America, Asia and Africa

Background: Even among HIV-infected patients who fully suppress plasma HIV RNA replication on antiretroviral therapy, genetic (e.g. CCL3L1 copy number), viral (e.g. tropism) and environmental (e.g. chronic exposure to microbial antigens) factors influence CD4 recovery. These factors differ markedly around the world and therefore the expected CD4 recovery during HIV RNA suppression may differ globally. Methods: We evaluated HIV-infected adults from North America, West Africa, East Africa, Southern Africa and Asia starting non-nucleoside reverse transcriptase inhibitor-based regimens containing efavirenz or nevirapine, who achieved at least one HIV RNA level <500/µl in the first year of therapy and observed CD4 changes during HIV RNA suppression. We used a piecewise linear regression to estimate the influence of region of residence on CD4 recovery, adjusting for socio-demographic and clinical characteristics. We observed 28 217 patients from 105 cohorts over 37 825 person-years. Results: After adjustment, patients from East Africa showed diminished CD4 recovery as compared with other regions. Three years after antiretroviral therapy initiation, the mean CD4 count for a prototypical patient with a pre-therapy CD4 count of 150/µl was 529/µl [95% confidence interval (CI): 517-541] in North America, 494/µl (95% CI: 429-559) in West Africa, 515/µl (95% CI: 508-522) in Southern Africa, 503/µl (95% CI: 478-528) in Asia and 437/µl (95% CI: 425-449) in East Africa. Conclusions: CD4 recovery during HIV RNA suppression is diminished in East Africa as compared with other regions of the world, and observed differences are large enough to potentially influence clinical outcomes. Epidemiological analyses on a global scale can identify macroscopic effects unobservable at the clinical, national or individual regional leve

MicroRNA profiling study reveals MIR-150 in association with metastasis in nasopharyngeal carcinoma

© 2017 The Author(s). MicroRNAs (miRNAs) are small non-coding RNAs that play a crucial role in pathogenesis of human cancers. Several miRNAs have been shown to involve in nasopharyngeal carcinoma (NPC) pathogenesis through alteration of gene networks. A global view of the miRNA expression profile of clinical specimens would be the best way to screen out the possible miRNA candidates that may be involved in disease pathogenesis. In this study, we investigated the expression profiles of miRNA in formalin-fixed paraffin-embedded tissues from patients with undifferentiated NPC versus non-NPC controls using a miRNA real-time PCR platform, which covered a total of 95 cancer-related miRNAs. Hierarchical cluster analysis revealed that NPC and non-NPC controls were clearly segregated. Promisingly, 10 miRNA candidates were differentially expressed. Among them, 9 miRNAs were significantly up-regulated of which miR-205 and miR-196a showed the most up-regulated in NPC with the highest incidence percentage of 94.1% and 88.2%, respectively, while the unique down-regulated miR-150 was further validated in patient sera. Finally, the in vitro gain-of-function and loss-of-function assays revealed that miR-150 can modulate the epithelial-mesenchymal-transition property in NPC/HK-1 cells and led to the cell motility and invasion. miR-150 may be a potential biomarker for NPC and plays a critical role in NPC tumourigenesis.Link_to_subscribed_fulltex

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

Proceedings of Abstracts, School of Physics, Engineering and Computer Science Research Conference 2022

© 2022 The Author(s). This is an open-access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. For further details please see https://creativecommons.org/licenses/by/4.0/. Plenary by Prof. Timothy Foat, ‘Indoor dispersion at Dstl and its recent application to COVID-19 transmission’ is © Crown copyright (2022), Dstl. This material is licensed under the terms of the Open Government Licence except where otherwise stated. To view this licence, visit http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3 or write to the Information Policy Team, The National Archives, Kew, London TW9 4DU, or email: [email protected] present proceedings record the abstracts submitted and accepted for presentation at SPECS 2022, the second edition of the School of Physics, Engineering and Computer Science Research Conference that took place online, the 12th April 2022

ARIA 2016 : Care pathways implementing emerging technologies for predictive medicine in rhinitis and asthma across the life cycle

The Allergic Rhinitis and its Impact on Asthma (ARIA) initiative commenced during a World Health Organization workshop in 1999. The initial goals were (1) to propose a new allergic rhinitis classification, (2) to promote the concept of multi-morbidity in asthma and rhinitis and (3) to develop guidelines with all stakeholders that could be used globally for all countries and populations. ARIA-disseminated and implemented in over 70 countries globally-is now focusing on the implementation of emerging technologies for individualized and predictive medicine. MASK [MACVIA (Contre les Maladies Chroniques pour un Vieillissement Actif)-ARIA Sentinel NetworK] uses mobile technology to develop care pathways for the management of rhinitis and asthma by a multi-disciplinary group and by patients themselves. An app (Android and iOS) is available in 20 countries and 15 languages. It uses a visual analogue scale to assess symptom control and work productivity as well as a clinical decision support system. It is associated with an inter-operable tablet for physicians and other health care professionals. The scaling up strategy uses the recommendations of the European Innovation Partnership on Active and Healthy Ageing. The aim of the novel ARIA approach is to provide an active and healthy life to rhinitis sufferers, whatever their age, sex or socio-economic status, in order to reduce health and social inequalities incurred by the disease.Peer reviewe

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

Tests of analytical hadronisation models using event shape moments in {\epem} annihilation

Predictions of analytical models for hadronisation, namely the dispersive model, the shape function and the single dressed gluon approximation, are compared with moments of hadronic event shape distributions measured in \epem annihilation at centre-of-mass energies between 14 and 209 GeV. In contrast to Monte Carlo models for hadronisation, analytical models require to adjust only two universal parameters, the strong coupling and a second quantity parametrising nonperturbative corrections. The extracted values of as are consistent with the world average and competitive with previous measurements. The variance of event shape distributions is compared with predictions given by some of these models. Limitations of the models, probably due to unknown higher order corrections, are demonstrated and discussed.Comment: Ref.s [19,36] added and footnote 1 adjuste