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Dennis Wang

Bio: Dennis Wang is an academic researcher from University of Sheffield. The author has contributed to research in topics: Cancer & Medicine. The author has an hindex of 26, co-authored 74 publications receiving 5159 citations. Previous affiliations of Dennis Wang include Yale University & University of Washington.


Papers
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Journal ArticleDOI
TL;DR: The data show the utility of viral RNA monitoring in municipal wastewater for SARS-CoV-2 infection surveillance at a population-wide level and in communities facing a delay between specimen collection and the reporting of test results, immediate wastewater results can provide considerable advance notice of infection dynamics.
Abstract: We measured severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentrations in primary sewage sludge in the New Haven, Connecticut, USA, metropolitan area during the Coronavirus Disease 2019 (COVID-19) outbreak in Spring 2020. SARS-CoV-2 RNA was detected throughout the more than 10-week study and, when adjusted for time lags, tracked the rise and fall of cases seen in SARS-CoV-2 clinical test results and local COVID-19 hospital admissions. Relative to these indicators, SARS-CoV-2 RNA concentrations in sludge were 0–2 d ahead of SARS-CoV-2 positive test results by date of specimen collection, 0–2 d ahead of the percentage of positive tests by date of specimen collection, 1–4 d ahead of local hospital admissions and 6–8 d ahead of SARS-CoV-2 positive test results by reporting date. Our data show the utility of viral RNA monitoring in municipal wastewater for SARS-CoV-2 infection surveillance at a population-wide level. In communities facing a delay between specimen collection and the reporting of test results, immediate wastewater results can provide considerable advance notice of infection dynamics. Testing sewage for the novel coronavirus reveals epidemiological trends.

672 citations

Journal ArticleDOI
TL;DR: Overall, RHA1 appears to have evolved to simultaneously catabolize a diverse range of plant-derived compounds in an O2-rich environment and is established as an important model for studying actinomycete physiology.
Abstract: Rhodococcus sp. RHA1 (RHA1) is a potent polychlorinated biphenyl-degrading soil actinomycete that catabolizes a wide range of compounds and represents a genus of considerable industrial interest. RHA1 has one of the largest bacterial genomes sequenced to date, comprising 9,702,737 bp (67% G+C) arranged in a linear chromosome and three linear plasmids. A targeted insertion methodology was developed to determine the telomeric sequences. RHA1's 9,145 predicted protein-encoding genes are exceptionally rich in oxygenases (203) and ligases (192). Many of the oxygenases occur in the numerous pathways predicted to degrade aromatic compounds (30) or steroids (4). RHA1 also contains 24 nonribosomal peptide synthase genes, six of which exceed 25 kbp, and seven polyketide synthase genes, providing evidence that rhodococci harbor an extensive secondary metabolism. Among sequenced genomes, RHA1 is most similar to those of nocardial and mycobacterial strains. The genome contains few recent gene duplications. Moreover, three different analyses indicate that RHA1 has acquired fewer genes by recent horizontal transfer than most bacteria characterized to date and far fewer than Burkholderia xenovorans LB400, whose genome size and catabolic versatility rival those of RHA1. RHA1 and LB400 thus appear to demonstrate that ecologically similar bacteria can evolve large genomes by different means. Overall, RHA1 appears to have evolved to simultaneously catabolize a diverse range of plant-derived compounds in an O(2)-rich environment. In addition to establishing RHA1 as an important model for studying actinomycete physiology, this study provides critical insights that facilitate the exploitation of these industrially important microorganisms.

625 citations

Journal ArticleDOI
Katherine A Twohig1, Tommy Nyberg2, Asad Zaidi1, Simon Thelwall1  +604 moreInstitutions (2)
TL;DR: In this paper, the authors compared the severity of the delta variant compared with the alpha variant by determining the relative risk of hospital attendance outcomes and found that outbreaks of the Delta variant in unvaccinated populations might lead to a greater burden on health-care services than the alpha variants.
Abstract: Background The SARS-CoV-2 delta (B.1.617.2) variant was first detected in England in March, 2021. It has since rapidly become the predominant lineage, owing to high transmissibility. It is suspected that the delta variant is associated with more severe disease than the previously dominant alpha (B.1.1.7) variant. We aimed to characterise the severity of the delta variant compared with the alpha variant by determining the relative risk of hospital attendance outcomes. Methods This cohort study was done among all patients with COVID-19 in England between March 29 and May 23, 2021, who were identified as being infected with either the alpha or delta SARS-CoV-2 variant through whole-genome sequencing. Individual-level data on these patients were linked to routine health-care datasets on vaccination, emergency care attendance, hospital admission, and mortality (data from Public Health England's Second Generation Surveillance System and COVID-19-associated deaths dataset; the National Immunisation Management System; and NHS Digital Secondary Uses Services and Emergency Care Data Set). The risk for hospital admission and emergency care attendance were compared between patients with sequencing-confirmed delta and alpha variants for the whole cohort and by vaccination status subgroups. Stratified Cox regression was used to adjust for age, sex, ethnicity, deprivation, recent international travel, area of residence, calendar week, and vaccination status. Findings Individual-level data on 43 338 COVID-19-positive patients (8682 with the delta variant, 34 656 with the alpha variant; median age 31 years [IQR 17-43]) were included in our analysis. 196 (2·3%) patients with the delta variant versus 764 (2·2%) patients with the alpha variant were admitted to hospital within 14 days after the specimen was taken (adjusted hazard ratio [HR] 2·26 [95% CI 1·32-3·89]). 498 (5·7%) patients with the delta variant versus 1448 (4·2%) patients with the alpha variant were admitted to hospital or attended emergency care within 14 days (adjusted HR 1·45 [1·08-1·95]). Most patients were unvaccinated (32 078 [74·0%] across both groups). The HRs for vaccinated patients with the delta variant versus the alpha variant (adjusted HR for hospital admission 1·94 [95% CI 0·47-8·05] and for hospital admission or emergency care attendance 1·58 [0·69-3·61]) were similar to the HRs for unvaccinated patients (2·32 [1·29-4·16] and 1·43 [1·04-1·97]; p=0·82 for both) but the precision for the vaccinated subgroup was low. Interpretation This large national study found a higher hospital admission or emergency care attendance risk for patients with COVID-19 infected with the delta variant compared with the alpha variant. Results suggest that outbreaks of the delta variant in unvaccinated populations might lead to a greater burden on health-care services than the alpha variant. Funding Medical Research Council; UK Research and Innovation; Department of Health and Social Care; and National Institute for Health Research.

450 citations

Journal ArticleDOI
TL;DR: This paper presents Combenefit, new free software tool that enables the visualization, analysis and quantification of drug combination effects in terms of synergy and/or antagonism, and provides laboratory scientists with an easy and systematic way to analyze their data.
Abstract: Motivation: Many drug combinations are routinely assessed to identify synergistic interactions in the attempt to develop novel treatment strategies. Appropriate software is required to analyze the results of these studies. Results: We present Combenefit, new free software tool that enables the visualization, analysis and quantification of drug combination effects in terms of synergy and/or antagonism. Data from combinations assays can be processed using classical Synergy models (Loewe, Bliss, HSA), as single experiments or in batch for High Throughput Screens. This user-friendly tool provides laboratory scientists with an easy and systematic way to analyze their data. The companion package provides bioinformaticians with critical implementations of routines enabling the processing of combination data. Availability and Implementation: Combenefit is provided as a Matlab package but also as standalone software for Windows (http://sourceforge.net/projects/combenefit/). Contact: Giovanni.DiVeroli@cruk.cam.ac.uk. Supplementary information:Supplementary data are available at Bioinformatics online.

444 citations


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01 Jan 2012

3,692 citations

Journal ArticleDOI
12 Oct 2017-Nature
TL;DR: It is found that local genetic variation affects gene expression levels for the majority of genes, and inter-chromosomal genetic effects for 93 genes and 112 loci are identified, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease.
Abstract: Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease.

3,289 citations

Journal ArticleDOI
TL;DR: The basic virology of SARS-CoV-2 is described, including genomic characteristics and receptor use, highlighting its key difference from previously known coronaviruses.
Abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible and pathogenic coronavirus that emerged in late 2019 and has caused a pandemic of acute respiratory disease, named ‘coronavirus disease 2019’ (COVID-19), which threatens human health and public safety. In this Review, we describe the basic virology of SARS-CoV-2, including genomic characteristics and receptor use, highlighting its key difference from previously known coronaviruses. We summarize current knowledge of clinical, epidemiological and pathological features of COVID-19, as well as recent progress in animal models and antiviral treatment approaches for SARS-CoV-2 infection. We also discuss the potential wildlife hosts and zoonotic origin of this emerging virus in detail. In this Review, Shi and colleagues summarize the exceptional amount of research that has characterized acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and coronavirus disease 2019 (COVID-19) since this virus has swept around the globe. They discuss what we know so far about the emergence and virology of SARS-CoV-2 and the pathogenesis and treatment of COVID-19.

2,904 citations

20 Sep 2013
TL;DR: Afatinib is associated with prolongation of PFS when compared with standard doublet chemotherapy in patients with advanced lung adenocarcinoma and EGFR mutations.
Abstract: Purpose The LUX-Lung 3 study investigated the efficacy of chemotherapy compared with afatinib, a selective, orally bioavailable ErbB family blocker that irreversibly blocks signaling from epidermal growth factor receptor (EGFR/ErbB1), human epidermal growth factor receptor 2 (HER2/ErbB2), and ErbB4 and has wide-spectrum preclinical activity against EGFR mutations. A phase II study of afatinib in EGFR mutation-positive lung adenocarcinoma demonstrated high response rates and progression-free survival (PFS). Patients and Methods In this phase III study, eligible patients with stage IIIB/IV lung adenocarcinoma were screened for EGFR mutations. Mutation-positive patients were stratified by mutation type (exon 19 deletion, L858R, or other) and race (Asian or non-Asian) before two-to-one random assignment to 40 mg afatinib per day or up to six cycles of cisplatin plus pemetrexed chemotherapy at standard doses every 21 days. The primary end point was PFS by independent review. Secondary end points included tumor response, overall survival, adverse events, and patient-reported outcomes (PROs). Results A total of 1,269 patients were screened, and 345 were randomly assigned to treatment. Median PFS was 11.1 months for afatinib and 6.9 months for chemotherapy (hazard ratio [HR], 0.58; 95% CI, 0.43 to 0.78; P = .001). Median PFS among those with exon 19 deletions and L858R EGFR mutations (n = 308) was 13.6 months for afatinib and 6.9 months for chemotherapy (HR, 0.47; 95% CI, 0.34 to 0.65; P = .001). The most common treatmentrelated adverse events were diarrhea, rash/acne, and stomatitis for afatinib and nausea, fatigue, and decreased appetite for chemotherapy. PROs favored afatinib, with better control of cough, dyspnea, and pain. Conclusion Afatinib is associated with prolongation of PFS when compared with standard doublet chemotherapy in patients with advanced lung adenocarcinoma and EGFR mutations.

2,380 citations