Author: "Andrea Edwards" - Searchworks@Jio Institute Digital Library Search Results

106 results on '"Andrea Edwards"'

1. Quitting smoking after a cancer diagnosis is associated with high-risk neutrophil-to-lymphocyte ratio among tobacco use-related cancer survivors

Author: You Lu, Katherine Kwong, James Wells, Andrea Edwards, Zhong Chen, Tung-Sung Tseng, and Kun Zhang
Subjects: Medicine, Science
Abstract: Abstract Quitting smoking could potentially minimize the risk of a high neutrophil-to-lymphocyte ratio (NLR) among tobacco use-related (TUR) cancer survivors. A total of 1263 TUR cancer survivors aged 20 to 85 years old were investigated using data from the National Health and Nutritional Examination Survey 1999–2018. The primary outcome was the NLR, which was defined as having two levels: high-risk (≥ 3) and low-risk (
Published: 2023
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2. Influence of CYP2D6 metabolizer status on ondansetron efficacy in pediatric patients undergoing hematopoietic stem cell transplantation: A case series

Author: Andrea Edwards, Ashley Teusink‐Cross, Lisa J. Martin, Cynthia A. Prows, Parinda A. Mehta, and Laura B. Ramsey
Subjects: Therapeutics. Pharmacology, RM1-950, Public aspects of medicine, RA1-1270
Abstract: Abstract Chemotherapy‐induced nausea and vomiting (CINV) is commonly experienced by patients receiving antineoplastic agents prior to hemopoietic stem cell transplant (HSCT). Ondansetron, a 5‐HT3 antagonist metabolized by CYP2D6, is an antiemetic prescribed to treat short‐term CINV, but some patients still experience uncontrolled nausea and vomiting while taking ondansetron. Adult CYP2D6 ultrarapid metabolizers (UMs) are at higher risk for CINV due to rapid ondansetron clearance, but similar studies have not been performed in pediatric patients. We performed a retrospective chart review of 128 pediatric HSCT recipients who received ondansetron for CINV prevention and had CYP2D6 genotyping for 20 alleles and duplication detection. The number of emetic episodes for each patient was collected from the start of chemotherapy through 7 days after HSCT. The average age of the cohort was 6.6 years (range: 0.2–16.7) and included three UMs, 72 normal metabolizers, 47 intermediate metabolizers, and six poor metabolizers. Because UMs are the population at risk for inefficacy, we describe the course of treatment for these three patients, as well as the factors influencing emesis: chemotherapy emetogenicity, diagnosis, and duration of ondansetron administration. The cases described support guidelines recommending non‐CYP2D6 metabolized antiemetics (e.g., granisetron) when a patient is a known CYP2D6 UM, but pediatric studies with a larger sample of CYP2D6 UMs are needed to validate our findings.
Published: 2022
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3. Cot-side imaging of functional connectivity in the developing brain during sleep using wearable high-density diffuse optical tomography

Author: Julie Uchitel, Borja Blanco, Liam Collins-Jones, Andrea Edwards, Emma Porter, Kelle Pammenter, Jem Hebden, Robert J Cooper, and Topun Austin
Subjects: High-density diffuse optical tomography, HD-DOT, Cot-side neuroimaging, Newborn neuroimaging, Resting state functional connectivity, Functional connectivity, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: Studies of cortical function in newborn infants in clinical settings are extremely challenging to undertake with traditional neuroimaging approaches. Partly in response to this challenge, functional near-infrared spectroscopy (fNIRS) has become an increasingly common clinical research tool but has significant limitations including a low spatial resolution and poor depth specificity. Moreover, the bulky optical fibres required in traditional fNIRS approaches present significant mechanical challenges, particularly for the study of vulnerable newborn infants. A new generation of wearable, modular, high-density diffuse optical tomography (HD-DOT) technologies has recently emerged that overcomes many of the limitations of traditional, fibre-based and low-density fNIRS measurements. Driven by the development of this new technology, we have undertaken the first cot-side study of newborn infants using wearable HD-DOT in a clinical setting. We use this technology to study functional brain connectivity (FC) in newborn infants during sleep and assess the effect of neonatal sleep states, active sleep (AS) and quiet sleep (QS), on resting state FC. Our results demonstrate that it is now possible to obtain high-quality functional images of the neonatal brain in the clinical setting with few constraints. Our results also suggest that sleep states differentially affect FC in the neonatal brain, consistent with prior reports.
Published: 2023
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4. Trajectory of post-traumatic stress and depression among children and adolescents following single-incident trauma

Author: Joyce Zhang, Richard Meiser-Stedman, Bobby Jones, Patrick Smith, Tim Dalgleish, Adrian Boyle, Andrea Edwards, Devasena Subramanyam, Clare Dixon, Lysandra Sinclaire-Harding, Susanne Schweizer, Jill Newby, and Anna McKinnon
Subjects: ptsd, depression, comorbidity, trajectory, gbtm, lcga, computational phenotyping, Psychiatry, RC435-571
Abstract: Objective Post-traumatic stress disorder and depression have high comorbidity. Understanding their relationship is of clinical and theoretical importance. A comprehensive way to understand post-trauma psychopathology is through symptom trajectories. This study aims to look at the developmental courses of PTSD and depression symptoms and their interrelationship in the initial months post-trauma in children and adolescents. Methods Two-hundred-and-seventeen children and adolescents aged between eight and 17 exposed to single-event trauma were included in the study. Post-traumatic stress symptoms (PTSS) and depression symptoms were measured at 2 weeks, 2 months and 9 months, with further psychological variables measured at the 2-week assessment. Group-based trajectory modelling (GBTM) was applied to estimate the latent developmental clusters of the two outcomes. Logistic regression was used to identify predictors associated with high symptom groups. Results The GBTM yielded a three-group model for PTSS and a three-group model for depression. PTSS trajectories showed symptoms reduced to a non-clinical level by 9 months for all participants (if they were not already in the non-clinical range): participants were observed to be resilient (42.4%) or recovered within 2 months (35.6%), while 21.9% experienced high level PTSS but recovered by 9 months post-trauma. The depression symptom trajectories predicted a chronic non-recovery group (20.1%) and two mild symptom groups (45.9%, 34.0%). Further analysis showed high synchronicity between PTSS and depression groups. Peri-event panic, negative appraisals, rumination and thought suppression at 2 weeks predicted slow recovery from PTSS. Pre-trauma wellbeing, post-trauma anxiety and negative appraisals predicted chronic depression. Conclusions Post-trauma depression was more persistent than PTSS at 9 months in the sampled population. Cognitive appraisal was the shared risk factor to high symptom groups of both PTSS and depression.
Published: 2022
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5. Insufficient Lycopene Intake Is Associated With High Risk of Prostate Cancer: A Cross-Sectional Study From the National Health and Nutrition Examination Survey (2003–2010)

Author: You Lu, Andrea Edwards, Zhong Chen, Tung-Sung Tseng, Mirandy Li, Gabrielle V. Gonzalez, and Kun Zhang
Subjects: prostate cancer, PSA, lycopene, obesity, living status, Public aspects of medicine, RA1-1270
Abstract: Although lycopene intake and risk of prostate cancer have been explored for decades, recent studies show that Non-Hispanic Black Prostate Cancer (PCa) patients benefit less than Non-Hispanic White patients from a lycopene intake intervention program. This study examined whether a lycopene intake-related racial disparity exists in reducing the risk of PCa in healthy adults. Data on healthy, cancer-free Non-Hispanic Black (NHB) men (n = 159) and Non-Hispanic White (NHW) men (n = 478) from the 2003 to 2010 NHANES dataset were analyzed. Total lycopene intake from daily diet, age, living status, race/ethnicity, education level, poverty income ratio, body mass index, and smoking status were studied as independent variables. The combination of total Prostate-Specific Antigen (PSA) level and the ratio of free PSA was set as criteria for evaluating the risk of PCa. Multivariable logistic regression was used in race-stratified analyses to compute odds ratios (OR) and 95% confidence intervals (95% CI) comparing high PCa risk with low PCa risk. We found, in the whole population, race/ethnicity was the only factor that influenced lycopene intake from the daily diet. NHB men consumed less lycopene than NHW men (3,716 vs. 6,487 (mcg), p = 0.01). Sufficient lycopene intake could reduce the risk of PCa (OR: 0.40, 95% CI: 0.18–0.85, p = 0.02). Men aged between 66 and 70 had high PCa risk (OR: 3.32, 95% CI: 1.12–9.85, p = 0.03). Obesity served as a protective factor against the high risk of PCa (OR: 0.25, 95% CI: 0.12–0.54, p = 0.001). NHW men aged between 66 and 70 had a high risk of PCa (OR: 4.01, 95% CI: 1.02–15.73, p = 0.05). Obese NHW men also had lower risk of PCa (OR: 0.18, 95% CI: 0.07–0.47 p = 0.001). NHB men had a high risk of PCa compared to NHW men (OR: 2.27, 95% CI: 1.35–3.81 p = 0.004). NHB men who were living without partners experienced an even higher risk of PCa (OR: 3.35, 95% CI: 1.01–11.19 p = 0.07). Sufficient lycopene intake from daily food could serve as a protector against PCa. Such an association was only observed in NHW men. Further studies are needed to explore the dose-response relationship between lycopene intake and the association of PCa risk in NHB men.
Published: 2021
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6. Seeking the exclusive binding region of phenylalkylamine derivatives on human T‐type calcium channels via homology modeling and molecular dynamics simulation approach

Author: You Lu, Ming Li, Gi Young Lee, Na Zhao, Zhong Chen, Andrea Edwards, and Kun Zhang
Subjects: homology modeling, phenylalkylamine, selective binding, T‐type calcium channels, virtual drug screening, Therapeutics. Pharmacology, RM1-950
Abstract: Abstract Pharmaceutical features of phenylalkylamine derivatives (PAAs) binding to calcium channels have been studied extensively in the past decades. Only a few PAAs have the binding specificity on calcium channels, for example, NNC 55‐0396. Here, we created the homology models of human Cav3.2, Cav3.3 and use them as a receptor on the rigid docking tests. The nonspecific calcium channel blocker mibefradil showed inconsistent docking preference across four domains; however, NNC 55‐0396 had a unique binding pattern on domain II specifically. The subsequent molecular dynamics (MD) simulations identified that Cav3.1, Cav3.2, and Cav3.3 share domain II when Ca2+ appearing in the neighbor region of selective filters (SFs). Moreover, free‐energy perturbation analysis suggests single mutation of lysine at P‐loop domain III, or threonine at the P‐loop domain II largely reduced the total amount of hydration‐free energy in the system. All these findings suggest that P‐loop and segment six domain II in the T‐type calcium channels (TCCs) are crucial for attracting the PAAs with specificity as the antagonist.
Published: 2021
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7. Functional imaging of the developing brain with wearable high-density diffuse optical tomography: A new benchmark for infant neuroimaging outside the scanner environment

Author: Elisabetta Maria Frijia, Addison Billing, Sarah Lloyd-Fox, Ernesto Vidal Rosas, Liam Collins-Jones, Maria Magdalena Crespo-Llado, Marta Perapoch Amadó, Topun Austin, Andrea Edwards, Luke Dunne, Greg Smith, Reuben Nixon-Hill, Samuel Powell, Nicholas L. Everdell, and Robert J. Cooper
Subjects: High-Density Diffuse Optical Tomography, Functional Near-Infrared Spectroscopy, Optical Neuroimaging, Infant Cognitive Development, Infant Neuroimaging, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: Studies of cortical function in the awake infant are extremely challenging to undertake with traditional neuroimaging approaches. Partly in response to this challenge, functional near-infrared spectroscopy (fNIRS) has become increasingly common in developmental neuroscience, but has significant limitations including resolution, spatial specificity and ergonomics. In adults, high-density arrays of near-infrared sources and detectors have recently been shown to yield dramatic improvements in spatial resolution and specificity when compared to typical fNIRS approaches. However, most existing fNIRS devices only permit the acquisition of ~20–100 sparsely distributed fNIRS channels, and increasing the number of optodes presents significant mechanical challenges, particularly for infant applications. A new generation of wearable, modular, high-density diffuse optical tomography (HD-DOT) technologies has recently emerged that overcomes many of the limitations of traditional, fibre-based and low-density fNIRS measurements. Driven by the development of this new technology, we have undertaken the first study of the infant brain using wearable HD-DOT. Using a well-established social stimulus paradigm, and combining this new imaging technology with advances in cap design and spatial registration, we show that it is now possible to obtain high-quality, functional images of the infant brain with minimal constraints on either the environment or on the infant participants. Our results are consistent with prior low-density fNIRS measures based on similar paradigms, but demonstrate superior spatial localization, improved depth specificity, higher SNR and a dramatic improvement in the consistency of the responses across participants. Our data retention rates also demonstrate that this new generation of wearable technology is well tolerated by the infant population.
Published: 2021
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8. Inferring Personalized and Race-Specific Causal Effects of Genomic Aberrations on Gleason Scores: A Deep Latent Variable Model

Author: Zhong Chen, Andrea Edwards, Chindo Hicks, and Kun Zhang
Subjects: deep latent variable model, causal effect inference, prostate cancer, racial disparity, genomic aberrations, Gleason scores, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Extensive research has examined socioeconomic factors influencing prostate cancer (PCa) disparities. However, to what extent molecular and genetic mechanisms may also contribute to these inequalities still remains elusive. Although various in vitro, in vivo, and population studies have originated to address this issue, they are often very costly and time-consuming by nature. In this work, we attempt to explore this problem by a preliminary study, where a joint deep latent variable model (DLVM) is proposed to in silico quantify the personalized and race-specific effects that a genomic aberration may exert on the Gleason Score (GS) of each individual PCa patient. The core of the proposed model is a deep variational autoencoder (VAE) framework, which follows the causal structure of inference with proxies. Extensive experimental results on The Cancer Genome Atlas (TCGA) 270 European-American (EA) and 43 African-American (AA) PCa patients demonstrate that ERG fusions, somatic mutations in SPOP and ATM, and copy number alterations (CNAs) in ERG are the statistically significant genomic factors across all low-, intermediate-, and high-grade PCa that may explain the disparities between these two groups. Moreover, compared to a state-of-the-art deep inference method, our proposed method achieves much higher precision in causal effect inference in terms of the impact of a studied genomic aberration on GS. Further validation on an independent set and the assessment of the genomic-risk scores along with corresponding confidence intervals not only validate our results but also provide valuable insight to the observed racial disparity between these two groups regarding PCa metastasis. The pinpointed significant genomic factors may shed light on the molecular mechanism of cancer disparities in PCa and warrant further investigation.
Published: 2020
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9. Identification of Single Nucleotide Polymorphism in Red Clover (Trifolium pratense L.) Using Targeted Genomic Amplicon Sequencing and RNA-seq

Author: Wenli Li, Heathcliffe Riday, Christina Riehle, Andrea Edwards, and Randy Dinkins
Subjects: red clover, single-nucleotide polymorphism, targeted amplicon sequencing, RNA-seq, self-incompatibility, Plant culture, SB1-1110
Abstract: Red clover (Trifolium pratense L.) is a diploid, naturally cross-pollinated, cool-season species. As a perennial forage legume, red clover is mostly cultivated in temperate regions worldwide. Being a non-model crop species, genomic resources for red clover have been underdeveloped. Thus far, genomic analysis used in red clover has mainly relied on simple sequence repeat (SSR) markers. However, SSR markers are sparse in the genome and it is often difficult to unambiguously map them using short reads generated by next generation sequencing technology. Single nucleotide polymorphisms (SNPs) have been successfully applied in genomics assisted breeding in several agriculturally important species. Due to increasing importance of legumes in forage production, there is a clear need to develop SNP based markers for red clover that can be applied in breeding applications. In this study, we first developed an analytical pipeline that can confidently identify SNPs in a set of 72 different red clover genotypes using sequences generated by targeted amplicon sequencing. Then, with the same filtering stringency used in this pipeline, we used sequences from publicly available RNA-seq data to identify confident SNPs in different red clover varieties. Using this strategy, we have identified a total of 69,975 SNPs across red clover varieties. Among these, 28% (19,116) of them are missense mutations. Using Medicago truncatula as the reference, we annotated the regions affected by these missense mutations. We identified 2,909 protein coding regions with missense mutations. Pathway analysis of these coding regions indicated several biological processes impacted by these mutations. Specifically, three domains (homeobox domain, pentatricopeptide repeat containing plant-like, and regulator of Vps4 activity) were identified with five or more missense SNPs. These domain might also be a functional contributor in the molecular mechanisms of self-incompatibility in red clover. Future in-depth sequence diversity analysis of these three genes may yield valuable insights into the molecular mechanism involved in self-incompatibility in red clover.
Published: 2019
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10. Significant Prognostic Features and Patterns of Somatic Mutations in Human Cancers

Author: Wensheng Zhang, Andrea Edwards, Erik K Flemington, and Kun Zhang
Subjects: Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: TP53 is the most frequently altered gene in human cancers. Numerous retrospective studies have related its mutation and abnormal p53 protein expression to poor patient survival. Nonetheless, the clinical significance of TP53 ( p53 ) status has been a controversial issue. In this work, we aimed to characterize TP53 somatic mutations in tumor cells across multiple cancer types, primarily focusing on several less investigated features of the mutation spectra, and determine their prognostic implications. We performed an integrative study on the clinically annotated genomic data released by The Cancer Genome Atlas. Standard statistical methods, such as the Cox proportional hazards model and logistic regression, were used. This study resulted in several novel findings. They include the following: (1) similar to previously reported cases in breast cancer, the mutations in exons 1 to 4 of TP53 were more lethal than those in exons 5 to 9 for the patients with lung adenocarcinomas; (2) TP53 mutants tended to be negatively selected in mammalian evolution, but the evolutionary conservation had various clinical implications for different cancers; (3) conserved correlation patterns (ie, consistent co-occurrence or consistent mutual exclusivity) between TP53 mutations and the alterations in several other cancer genes (ie, PIK3CA, PTEN, KRAS, APC, CDKN2A , and ATM ) were present in several cancers in which prognosis was associated with TP53 status and/or the mutational characteristics; (4) among TP53 -mutated tumors, the total mutation burden in other driver genes was a predictive signature ( P < .05, false discovery rate
Published: 2017
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11. Mapping cortical haemodynamics during neonatal seizures using diffuse optical tomography: A case study

Author: Harsimrat Singh, Robert J. Cooper, Chuen Wai Lee, Laura Dempsey, Andrea Edwards, Sabrina Brigadoi, Dimitrios Airantzis, Nick Everdell, Andrew Michell, David Holder, Jeremy C. Hebden, and Topun Austin
Subjects: Diffuse optical tomography (DOT), Neonatal seizures, Functional near infrared spectroscopy (fNIRS), Hypoxic–ischaemic encephalopathy (HIE), Computer applications to medicine. Medical informatics, R858-859.7, Neurology. Diseases of the nervous system, RC346-429
Abstract: Seizures in the newborn brain represent a major challenge to neonatal medicine. Neonatal seizures are poorly classified, under-diagnosed, difficult to treat and are associated with poor neurodevelopmental outcome. Video-EEG is the current gold-standard approach for seizure detection and monitoring. Interpreting neonatal EEG requires expertise and the impact of seizures on the developing brain remains poorly understood. In this case study we present the first ever images of the haemodynamic impact of seizures on the human infant brain, obtained using simultaneous diffuse optical tomography (DOT) and video-EEG with whole-scalp coverage. Seven discrete periods of ictal electrographic activity were observed during a 60 minute recording of an infant with hypoxic–ischaemic encephalopathy. The resulting DOT images show a remarkably consistent, high-amplitude, biphasic pattern of changes in cortical blood volume and oxygenation in response to each electrographic event. While there is spatial variation across the cortex, the dominant haemodynamic response to seizure activity consists of an initial increase in cortical blood volume prior to a large and extended decrease typically lasting several minutes. This case study demonstrates the wealth of physiologically and clinically relevant information that DOT–EEG techniques can yield. The consistency and scale of the haemodynamic responses observed here also suggest that DOT–EEG has the potential to provide improved detection of neonatal seizures.
Published: 2014
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12. Somatic mutations favorable to patient survival are predominant in ovarian carcinomas.

Author: Wensheng Zhang, Andrea Edwards, Erik Flemington, and Kun Zhang
Subjects: Medicine, Science
Abstract: Somatic mutation accumulation is a major cause of abnormal cell growth. However, some mutations in cancer cells may be deleterious to the survival and proliferation of the cancer cells, thus offering a protective effect to the patients. We investigated this hypothesis via a unique analysis of the clinical and somatic mutation datasets of ovarian carcinomas published by the Cancer Genome Atlas. We defined and screened 562 macro mutation signatures (MMSs) for their associations with the overall survival of 320 ovarian cancer patients. Each MMS measures the number of mutations present on the member genes (except for TP53) covered by a specific Gene Ontology (GO) term in each tumor. We found that somatic mutations favorable to the patient survival are predominant in ovarian carcinomas compared to those indicating poor clinical outcomes. Specially, we identified 19 (3) predictive MMSs that are, usually by a nonlinear dose-dependent effect, associated with good (poor) patient survival. The false discovery rate for the 19 "positive" predictors is at the level of 0.15. The GO terms corresponding to these MMSs include "lysosomal membrane" and "response to hypoxia", each of which is relevant to the progression and therapy of cancer. Using these MMSs as features, we established a classification tree model which can effectively partition the training samples into three prognosis groups regarding the survival time. We validated this model on an independent dataset of the same disease (Log-rank p-value < 2.3 × 10(-4)) and a dataset of breast cancer (Log-rank p-value < 9.3 × 10(-3)). We compared the GO terms corresponding to these MMSs and those enriched with expression-based predictive genes. The analysis showed that the GO term pairs with large similarity are mainly pertinent to the proteins located on the cell organelles responsible for material transport and waste disposal, suggesting the crucial role of these proteins in cancer mortality.
Published: 2014
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13. Inferring polymorphism-induced regulatory gene networks active in human lymphocyte cell lines by weighted linear mixed model analysis of multiple RNA-Seq datasets.

Author: Wensheng Zhang, Andrea Edwards, Erik K Flemington, and Kun Zhang
Subjects: Medicine, Science
Abstract: Single-nucleotide polymorphisms (SNPs) contribute to the between-individual expression variation of many genes. A regulatory (trait-associated) SNP is usually located near or within a (host) gene, possibly influencing the gene's transcription or/and post-transcriptional modification. But its targets may also include genes that are physically farther away from it. A heuristic explanation of such multiple-target interferences is that the host gene transfers the SNP genotypic effects to the distant gene(s) by a transcriptional or signaling cascade. These connections between the host genes (regulators) and the distant genes (targets) make the genetic analysis of gene expression traits a promising approach for identifying unknown regulatory relationships. In this study, through a mixed model analysis of multi-source digital expression profiling for 140 human lymphocyte cell lines (LCLs) and the genotypes distributed by the international HapMap project, we identified 45 thousands of potential SNP-induced regulatory relationships among genes (the significance level for the underlying associations between expression traits and SNP genotypes was set at FDR < 0.01). We grouped the identified relationships into four classes (paradigms) according to the two different mechanisms by which the regulatory SNPs affect their cis- and trans- regulated genes, modifying mRNA level or altering transcript splicing patterns. We further organized the relationships in each class into a set of network modules with the cis- regulated genes as hubs. We found that the target genes in a network module were often characterized by significant functional similarity, and the distributions of the target genes in three out of the four networks roughly resemble a power-law, a typical pattern of gene networks obtained from mutation experiments. By two case studies, we also demonstrated that significant biological insights can be inferred from the identified network modules.
Published: 2013
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14. The sequence structures of human microRNA molecules and their implications.

Author: Zhide Fang, Ruofei Du, Andrea Edwards, Erik K Flemington, and Kun Zhang
Subjects: Medicine, Science
Abstract: The count of the nucleotides in a cloned, short genomic sequence has become an important criterion to annotate such a sequence as a miRNA molecule. While the majority of human mature miRNA sequences consist of 22 nucleotides, there exists discrepancy in the characteristic lengths of the miRNA sequences. There is also a lack of systematic studies on such length distribution and on the biological factors that are related to or may affect this length. In this paper, we intend to fill this gap by investigating the sequence structure of human miRNA molecules using statistics tools. We demonstrate that the traditional discrete probability distributions do not model the length distribution of the human mature miRNAs well, and we obtain the statistical distribution model with a decent fit. We observe that the four nucleotide bases in a miRNA sequence are not randomly distributed, implying that possible structural patterns such as dinucleotide (trinucleotide or higher order) may exist. Furthermore, we study the relationships of this length distribution to multiple important factors such as evolutionary conservation, tumorigenesis, the length of precursor loop structures, and the number of predicted targets. The association between the miRNA sequence length and the distributions of target site counts in corresponding predicted genes is also presented. This study results in several novel findings worthy of further investigation that include: (1) rapid evolution introduces variation to the miRNA sequence length distribution; (2) miRNAs with extreme sequence lengths are unlikely to be cancer-related; and (3) the miRNA sequence length is positively correlated to the precursor length and the number of predicted target genes.
Published: 2013
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15. miRNA-mRNA correlation-network modules in human prostate cancer and the differences between primary and metastatic tumor subtypes.

Author: Wensheng Zhang, Andrea Edwards, Wei Fan, Erik K Flemington, and Kun Zhang
Subjects: Medicine, Science
Abstract: Recent studies have shown the contribution of miRNAs to cancer pathogenesis. Prostate cancer is the most commonly diagnosed cancer in men. Unlike other major types of cancer, no single gene has been identified as being mutated in the majority of prostate tumors. This implies that the expression profiling of genes, including the non-coding miRNAs, may substantially vary across individual cases of this cancer. The within-class variability makes it possible to reconstruct or infer disease-specific miRNA-mRNA correlation and regulatory modular networks using high-dimensional microarray data of prostate tumor samples. Furthermore, since miRNAs and tumor suppressor genes are usually tissue specific, miRNA-mRNA modules could potentially differ between primary prostate cancer (PPC) and metastatic prostate cancer (MPC). We herein performed an in silico analysis to explore the miRNA-mRNA correlation network modules in the two tumor subtypes. Our analysis identified 5 miRNA-mRNA module pairs (MPs) for PPC and MPC, respectively. Each MP includes one positive-connection (correlation) module and one negative-connection (correlation) module. The number of miRNAs or mRNAs (genes) in each module varies from 2 to 8 or from 6 to 622. The modules discovered for PPC are more informative than those for MPC in terms of the implicated biological insights. In particular, one negative-connection module in PPC fits well with the popularly recognized miRNA-mediated post-transcriptional regulation theory. That is, the 3'UTR sequences of the involved mRNAs (∼620) are enriched with the target site motifs of the 7 modular miRNAs, has-miR-106b, -191, -19b, -92a, -92b, -93, and -141. About 330 GO terms and KEGG pathways, including TGF-beta signaling pathway that maintains tissue homeostasis and plays a crucial role in the suppression of the proliferation of cancer cells, are over-represented (adj.p
Published: 2012
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16. miRNA-mediated relationships between Cis-SNP genotypes and transcript intensities in lymphocyte cell lines.

Author: Wensheng Zhang, Andrea Edwards, Dongxiao Zhu, Erik K Flemington, Prescott Deininger, and Kun Zhang
Subjects: Medicine, Science
Abstract: In metazoans, miRNAs regulate gene expression primarily through binding to target sites in the 3' UTRs (untranslated regions) of messenger RNAs (mRNAs). Cis-acting variants within, or close to, a gene are crucial in explaining the variability of gene expression measures. Single nucleotide polymorphisms (SNPs) in the 3' UTRs of genes can affect the base-pairing between miRNAs and mRNAs, and hence disrupt existing target sites (in the reference sequence) or create novel target sites, suggesting a possible mechanism for cis regulation of gene expression. Moreover, because the alleles of different SNPs within a DNA sequence of limited length tend to be in strong linkage disequilibrium (LD), we hypothesize the variants of miRNA target sites caused by SNPs potentially function as bridges linking the documented cis-SNP markers to the expression of the associated genes. A large-scale analysis was herein performed to test this hypothesis. By systematically integrating multiple latest information sources, we found 21 significant gene-level SNP-involved miRNA-mediated post-transcriptional regulation modules (SNP-MPRMs) in the form of SNP-miRNA-mRNA triplets in lymphocyte cell lines for the CEU and YRI populations. Among the cognate genes, six including ALG8, DGKE, GNA12, KLF11, LRPAP1, and MMAB are related to multiple genetic diseases such as depressive disorder and Type-II diabetes. Furthermore, we found that ~35% of the documented transcript intensity-related cis-SNPs (~950) in a recent publication are identical to, or in significant linkage disequilibrium (LD) (p
Published: 2012
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17. Cost-sensitive sparse group online learning for imbalanced data streams.

Author: Zhong Chen 0003, Victor S. Sheng, Andrea Edwards, and Kun Zhang 0012
Published: 2024
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18. An effective cost-sensitive sparse online learning framework for imbalanced streaming data classification and its application to online anomaly detection.

Author: Zhong Chen 0003, Victor S. Sheng, Andrea Edwards, and Kun Zhang 0012
Published: 2023
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19. Proximal Cost-sensitive Sparse Group Online Learning.

Author: Zhong Chen 0003, Huixin Zhan, Victor S. Sheng, Andrea Edwards, and Kun Zhang 0012
Published: 2022
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20. Projection Dual Averaging Based Second-order Online Learning.

Author: Zhong Chen 0003, Huixin Zhan, Victor S. Sheng, Andrea Edwards, and Kun Zhang 0012
Published: 2022
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21. Driver gene detection through Bayesian network integration of mutation and expression profiles.

Author: Zhong Chen 0003, You Lu, Bo Cao, Wensheng Zhang 0005, Andrea Edwards, and Kun Zhang 0012
Published: 2022
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22. CSRDA: Cost-sensitive Regularized Dual Averaging for Handling Imbalanced and High-dimensional Streaming Data.

Author: Zhong Chen 0003, Zhide Fang, Victor S. Sheng, Andrea Edwards, and Kun Zhang 0012
Published: 2021
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23. Fusion Lasso and Its Applications to Cancer Subtype and Stage Prediction.

Author: Zhong Chen 0003, Andrea Edwards, and Kun Zhang 0012
Published: 2020
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24. Adaptive robust local online density estimation for streaming data.

Author: Zhong Chen 0003, Zhide Fang, Victor S. Sheng, Jiabin Zhao, Wei Fan 0001, Andrea Edwards, and Kun Zhang 0012
Published: 2021
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25. A deep imputation and inference framework for estimating personalized and race-specific causal effects of genomic alterations on PSA.

Author: Zhong Chen 0003, Bo Cao, Andrea Edwards, Hongwen Deng, and Kun Zhang 0012
Published: 2021
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26. Online Density Estimation over Streaming Data: A Local Adaptive Solution.

Author: Zhong Chen 0003, Zhide Fang, Jiabin Zhao, Wei Fan 0001, Andrea Edwards, and Kun Zhang 0012
Published: 2018
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27. Learning discriminative subregions and pattern orders for facial gender classification.

Author: Zhong Chen 0003, Andrea Edwards, Yongsheng Gao 0001, and Kun Zhang 0012
Published: 2019
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28. CSTG: An Effective Framework for Cost-sensitive Sparse Online Learning.

Author: Zhong Chen 0003, Zhide Fang, Wei Fan 0001, Andrea Edwards, and Kun Zhang 0012
Published: 2017
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29. Proceedings of the 13th International Newborn Brain Conference: Neuro-imaging studies

Author: Ramy Abramsky, Rebeka Acosta, Laura Acosta Izquierdo, Bushra Albeshri, Mountasser Almouqdad, Yasmeen Asfour, Suzan Asfour, Topun Austin, Ashley Bach, Jim Barkovich, Richard Beare, Nadya Ben Fadel, Angelika Berger, Borja Blanco, Martijn Boomsma, Samudragupta Bora, Vivian Boswinkel, Theresa Chin, Liam Collins-Jones, Robert Cooper, Gautam Dagur, Jorge Davila, Linda de Vries, Laxmikant Shesrao, null Deshmukh, Gregor Dovjak, Andrea Edwards, Mohamed El-Dib, Hoda Elshibiny, Dafna Eshel, Ron Eshel, Donna Ferriero, Dawn Gano, Olivia Girvan, Hannah Glass, Katharina Goeral, Agneta Golan, Michelle Gurvitz, Terrie Inder, Dima Jamjoom, Nadja Kadom, Gregor Kasprian, Thanaa Khalil, Katrin Klebermass-Schrehof, Jake Kleinmahon, Martine Krüse-Ruijter, Hannah Lambing, Sarah Lee, Alexander Leemans, Lara Leijser, Brigitte Lemyre, Yi Li, Camille Maltais-Bilodeau, Kyla Marks, Charles McCulloch, Sarah Milla, Elka Miller, Aradhana Mishra, Nicholas Mitsakakis, Khorshid Mohammad, Susanne Mulder-de Tollenaer, Chelsea Munster, Jacqueline Nijboer, Jacqueline Nijboer-Oosterveld, Ingrid Nijholt, Rosa Novoa, Cynthia Ortinau, Emma Porter, Daniela Prayer, Deepti Reddy, Stephanie Redpath, Elizabeth Rogers, Victor Schmidbauer, James Scott, Elizabeth Sewell, Eilon Shany, Ilan Shelef, Elizabeth Singh, Cornelis Slump, Tina Steele, Eniko Szakmar, Chantal Tax, Kirsten Thiim, Julie Uchitel, Jochen van Osch, Gerda van Wezel-Meijler, Anouk Verschuur, Mei-Nga Wu-Smit, Edward Yang, and Hussein Zein
Subjects: Pediatrics, Perinatology and Child Health
Published: 2022
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30. The modularity and dynamicity of miRNA-mRNA interactions in high-grade serous ovarian carcinomas and the prognostic implication.

Author: Wensheng Zhang 0005, Andrea Edwards, Wei Fan 0001, Erik K. Flemington, and Kun Zhang 0012
Published: 2016
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31. RS-Forest: A Rapid Density Estimator for Streaming Anomaly Detection.

Author: Ke Wu, Kun Zhang 0012, Wei Fan 0001, Andrea Edwards, and Philip S. Yu
Published: 2014
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32. Classifying Imbalanced Data Streams via Dynamic Feature Group Weighting with Importance Sampling.

Author: Ke Wu, Andrea Edwards, Wei Fan 0001, Jing Gao 0004, and Kun Zhang 0012
Published: 2014
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33. Using a parallel genetic algorithm to design vibratory bowl feeders.

Author: Andrea Edwards
Published: 2004
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34. Breaking the computational barrier: a divide-conquer and aggregate based approach for Alu insertion site characterisation.

Author: Kun Zhang 0012, Wei Fan 0001, Prescott Deininger, Andrea Edwards, Zujia Xu, and Dongxiao Zhu
Published: 2009
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35. Imaging Functional Brain Connectivity in the Newborn Infant using High Density Diffuse Optical Tomography

Author: Julie Uchitel, Borja Blanco, Liam Collins-Jones, Emma Porter, Andrea Edwards, Kelle Pammenter, Robert J. Cooper, and Topun Austin
Published: 2022
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36. Influence of CYP2D6 metabolizer status on ondansetron efficacy in pediatric patients undergoing hematopoietic stem cell transplantation: A case series

Author: Laura B. Ramsey, Andrea Edwards, Cynthia A. Prows, Lisa J. Martin, Ashley Teusink-Cross, and Parinda A. Mehta
Subjects: Adult, medicine.medical_specialty, Adolescent, Nausea, medicine.drug_class, Vomiting, medicine.medical_treatment, Population, Antineoplastic Agents, Hematopoietic stem cell transplantation, Granisetron, General Biochemistry, Genetics and Molecular Biology, Ondansetron, Internal medicine, medicine, Antiemetic, Humans, General Pharmacology, Toxicology and Pharmaceutics, education, Child, Retrospective Studies, education.field_of_study, Chemotherapy, business.industry, General Neuroscience, Hematopoietic Stem Cell Transplantation, Infant, General Medicine, Cytochrome P-450 CYP2D6, Child, Preschool, Antiemetics, medicine.symptom, business, medicine.drug
Abstract: Chemotherapy-induced nausea and vomiting (CINV) is commonly experienced by patients receiving antineoplastic agents prior to hemopoietic stem cell transplant (HSCT). Ondansetron, a 5-HT3 antagonist metabolized by CYP2D6, is an antiemetic prescribed to treat short-term CINV, but some patients still experience uncontrolled nausea and vomiting while taking ondansetron. Adult CYP2D6 ultrarapid metabolizers (UMs) are at higher risk for CINV due to rapid ondansetron clearance, but similar studies have not been performed in pediatric patients. We performed a retrospective chart review of 128 pediatric HSCT recipients who received ondansetron for CINV prevention and had CYP2D6 genotyping for 20 alleles and duplication detection. The number of emetic episodes for each patient was collected from the start of chemotherapy through 7 days after HSCT. The average age of the cohort was 6.6 years (range: 0.2-16.7) and included three UMs, 72 normal metabolizers, 47 intermediate metabolizers, and six poor metabolizers. Because UMs are the population at risk for inefficacy, we describe the course of treatment for these three patients, as well as the factors influencing emesis: chemotherapy emetogenicity, diagnosis, and duration of ondansetron administration. The cases described support guidelines recommending non-CYP2D6 metabolized antiemetics (e.g., granisetron) when a patient is a known CYP2D6 UM, but pediatric studies with a larger sample of CYP2D6 UMs are needed to validate our findings.
Published: 2021

37. Azithromycin in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

Author: Eugenia Abaleke, Mustafa Abbas, Sadia Abbasi, Alfie Abbott, Ashraf Abdelaziz, Sherif Abdelbadiee, Mohamed Abdelfattah, Basir Abdul, Althaf Abdul Rasheed, Rezan Abdul-Kadir, Abdulfatahi Abdulmumeen, Niyaz Abdulshukkoor, Kula Abdusamad, Yazeed Abed El Khaleq, Mai Abedalla, Abeer UA Abeer Ul Amna, Adebanke Aboaba, Hani Abo-Leyah, Ahmed Abou-Haggar, Mahmoud Abouibrahim, Miriam Abraham, Tizzy Abraham, Abraheem Abraheem, Judith Abrams, Hyacinth-John Abu, Ahmad Abu-Arafeh, Syed M Abubacker, Akata Abung, Yaa Aceampong, Devikumar Acharya, Janet Acheson, Andres Acosta, Catherine Acton, Jacqueline Adabie-Ankrah, Fiona Adam, Matthew Adam, Huzaifa Adamali, Carol Adams, Kate Adams, Richard Adams, Tim Adams, Malgorzata Adamus, Kirsty Adcock, Aderonke Adebiyi, Ken Adegoke, Vicki Adell, Aldrin Adeni, Sherna Adenwalla, Oluwasegun A Adesemoye, Emmanuel O Adewunmi, Joyce Adeyemi, Elizabeth Adeyeye, Gabrielle Adkins, Adnan Adnan, John Aeron-Thomas, Lynn Afari, Debbie Affleck, Carmel Afnan, Deborah Afolabi, Muhammad Afridi, Rachel Agbeko, Chris Agbo, Sunil Aggarwal, Arameh Aghababaie, Judith Agwada-Akeru, Kwame A Agyapong, Shafana Ahamed Sadiq, Mohamed H Ahammed Nazeer, Jonathan Ah-Chuen, Mahin Ahmad, Ashar Ahmed, Bilal Ahmed, Forizuddin Ahmed, Iram Ahmed, Irshad Ahmed, Liban Ahmed, Maria C Ahmed, Muhammad S Ahmed, Naseer Ahmed, Nausheen Ahmed, Osama Ahmed, Rajia A Ahmed, Rizwan Ahmed, Saif Ahmed, Sammiya Ahmed, Sara Ahmed, Syed H Ahmed, Roa Ahmed Ali, Sana Ahmer, Dhiraj Ail, Adam Ainsley, Mark Ainsworth, Myriam Aissa, Lucy Aitchson, Lindianne Aitken, Bini Ajay, Abdulakeem Ajibode, Ayesha Ajmi, Muhammad N Akhtar, Nasim Akhtar, Suha Akili, Oludoyinsola Akindolie, Yinka Akinfenwa, Olugbenga Akinkugbe, Ibrahim Akinpelu, Umeh Akudo, Asma Al Balushi, Majd Al Dakhola, Narendra Aladangady, Sajid Alam, Abbas Al-Asadi, Kyriaki Alatzoglou, Lorraine Albon, Stephen Alcorn, Aggie Aldana, David Alderdice, Rayan Aldouri, Jonathan Aldridge, Nicolas Aldridge, Ana Alegria, Alison Alexander, John Alexander, Peter DG Alexander, Julyan Al-Fori, Bahij Al-Hakim, Shams Al-Hity, Ali Ali, Anyat Ali, Fawzia R Ali, Jawad Ali, Mariam Ali, Mohammad Ali, Oudai Ali, Sakina Ali, Syed Ali, Abid Alina, Katrin Alizaedeh, Maithem Al-Jibury, Moutaz Alkhusheh, Alison Allanson, Robert Allcock, Eireann Allen, Jonathan Allen, Kerry Allen, Louise Allen, Rebecca Allen, Sam Allen, Sharon Allen, Simon Allen, Kathryn Allison, Bethan Allman, Lynne Allsop, Christine Almadenboyle, Hassan Al-Moasseb, Magda Al-Obaidi, Lina Alomari, Akram Al-Rabahi, Bahar Al-Ramadhani, Zayneb Al-Saadi, Warkaq Al-Shamkhani, Bashar Al-Sheklly, Mary Alvarez, Maysaa Alzetani, Susan Amamou, Sakarai Ambalavanan, Sarah-Jayne Ambler, Robert Ambrogetti, Chris Ambrose, Amir Ameen, Maria R Amezaga, Allison Amin, Amina Amin, Kanish Amin, Amjad Amjad, Victoria Amosun, Khaled Amsha, Atul Anand, Samantha Anandappa, Julie Anderson, Laura Anderson, Michelle Anderson, Nicola Anderson, Rachel Anderson, Rory Anderson, Prematie Andreou, Angela 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Robert Brown, Steven Brown, Tom Brown, Charlotte Browne, Duncan Browne, Rachel Browne, Stephen Brownlee, David Bruce, Johanna Bruce, Michelle Bruce, Wojciech Brudlo, Nigel Brunskill, Luke Brunton, Margaret Brunton, Jade Bryant, Mark Bryce, Maya Buch, Ruaridh Buchanan, Amanda Buck, Elizabeth Buckingham, Laura Buckley, Philip Buckley, Sarah Buckley, Carol Buckman, George Bugg, Ramadan Bujazia, Shanzay Bukhari, Richard Bulbulia, Alex Bull, Damian Bull, Rhian Bull, Thomas Bull, Sam Bullard, Naomi Bulteel, Katherine Bunclark, Roneleeh Bungue-Tuble, Caroline Burchett, Christy Burden, Thomas G Burden, Sarah Burge, Mika Burgess, Sophia Burgess, Emma Burke, Sara Burnard, Caroline Burnett, Amy Burns, Collette Burns, James Burns, Karen Burns, Daniel Burrage, Kate Burrows, Claire Burston, Ben Burton, Fiona Burton, Angus Butchart, Aaron Butler, Jo Butler, Joanne Butler, Joshua Butler, Peter Butler, Susan Butler, Al-Tahoor Butt, Caryl Butterworth, Nicola Butterworth-Cowin, Robert Buttery, Heather Button, Daniel Buttress, Jane Byrne, Wendy Byrne, Victoria Byrne-Watts, Ruth Cade, Donna Cairney, Claire Calderwood, James Calderwood, Giorgio Calisti, Debbie Callaghan, Jennifer Callaghan, Claire Callens, Caroline Calver, Melissa Cambell-Kelly, Tracey Camburn, David R Cameron, Eleanor Cameron, Fraser Cameron, Sheena Cameron, Christian Camm, Renee FD Cammack, Alison Campbell, Amy Campbell, Barbara Campbell, Bridget Campbell, Debbie Campbell, Helen Campbell, Hilary Campbell, Jonathan Campbell, Mark Campbell, Robyn Campbell, Wynny Campbell, Quentin Campbell Hewson, Laura Camrasa, Julie Camsooksai, Shaula M Candido, Cielito Caneja, Johnathon Cann, Ruby Cannan, Emma Cannon, Michael Cannon, Petra Cannon, Vivienne Cannons, Jane Cantliff, Ben Caplin, Angelika Capp, Thomas Capstick, Simon Carley, Tammy Carlin, Samantha Carmichael, Margaret Carmody, Mandy Carnahan, Charlotte Caroline, Patrick Carr, Sharon Carr, Anna Carrasco, Zoe Carrington, Jonathan Carter, Paul Carter, Penny Carter, Douglas 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Dosanjh, Paula Dospinescu, Andrew Dougherty, Katie Douglas, Lucy Dowden, Michelle Dower, Sud Dowling, Hayley Downe, Nicola Downer, Charlotte Downes, Rob Downes, Thomas Downes, Damian Downey, Louise Downs, Simon Dowson, Cornel Dragan, Cristina Dragos, Chelsea Drake, Victoria Drew, Olivia Drewett, Celine Driscoll, Helena Drogan, Ronald Druyeh, Simon Drysdale, Hazel Dube, Judith Dube, Stephen Duberley, Simon Dubrey, Roger Duckitt, Hayley Duckles-Leech, Nicola Duff, Helen Duffy, Lionel Dufour, Annette Duggan, Parveen Dugh, Janice Duignan, Simon Dummer, Andrew Duncan, Barrie Duncan, Christopher Duncan, Fullerton Duncan, Alessia Dunn, Damian Dunn, Laura Dunn, Karen Dunne, Fiona Dunning, Aidan Dunphy, Venkat Duraiswamy, Beatriz Duran, Ingrid DuRand, Alison Durie, Emily Durie, Laura Durrans, Hannah Durrington, Akshay Dwarakanath, Laasya Dwarakanath, Ellen Dwyer, Claudia Dyball, Harvey Dymond, Tom Dymond, Chris Eades, Melissa Earwaker, Nicholas Easom, Clare East, Jack Easton, Ruth Eatough, Oluwadamilola Ebigbola, Martin Ebon, Sinan Eccles, Chloe Eddings, Michael Eddleston, Maureen Edgar, Katharine Edgerley, Mary Edmondson, Tracy Edmunds, Alexandra Edwards, Andrea Edwards, Catherine Edwards, Joy Edwards, Kennedy Edwards, Mandy Edwards, Steven Edwards, Jenny Eedle, Dawn Egginton, Sarah Eisen, Ugochukwu Ekeowa, Mohamed Ekoi, Ayomide Ekunola, Kate El Bouzidi, Ashley Elden, Jennifer Elder, Haifa Eldew, Diana Eleanor, Maysoon Elfadil, Eman Elfar, Mayy M Elgamal, Amr Elgohary, Stellios Elia, Jennifer Elias, Tania Elias, Nadia Elkaram, Amin Elkhawad, Andrew V Elkins, Julie Ellam, Nikki Ellard, Laura Nicola Ellerton, Amy Elliott, Fiona Elliott, Kerry Elliott, Valmai Elliott, Annie Ellis, Hayley Ellis, Kaytie Ellis, Tak-Yan Ellis, Yvette Ellis, Rahma Elmahdi, Einas Elmahi, Omer Elneima, Mohamed Elokl, Ahmed Elradi, Mohamed Elsaadany, Sally El-Sayeh, Hana El-Sbahi, Tarek Elsefi, Karim El-Shakankery, Sarah Elyoussfi, Jonathan Emberson, John Emberton, Julian Emmanuel, Ingrid Emmerson, Charis Emmett, Michael Emms, Marieke Emonts, Angila Engden, Katy English, Nicola Entwistle, Hene Enyi, Ruth Erin Jones, Agota Ermenyi, Hanif Esmail, Ajmal Eusuf, Brynach Evans, Chris Evans, Debra Evans, Gail Evans, Gareth Evans, Jennifer Evans, Lynn Evans, Melanie Evans, Mim Evans, Morgan Evans, Ranoromanana Evans, Teriann Evans, Terry J Evans, Caroline Everden, Lynsey Evison, Jacqueline Faccenda, Leila Fahel, Youstina Fahmay, Sara Fairbairn, Andy Fairclough, Louise Fairlie, Anne Fajardo, Euan Falconer, John Fallon, David Faluyi, Qayyum Farah, Novin Fard, Amr Farg, Adam Farmer, Katie Farmer, Toni Farmery, Frances Farnworth, Samantha Farnworth, Faiyaz Farook, Hadia Farooq, Sidrah Farooq, Fiona Farquhar, Aaron Farrell, Barbara Farrell, James Farthing, Syeda Farzana, Rahmatu Fasina, Azam Fatemi, Mina Fatemi, Nibah Fatimah, Saul N Faust, Joe Fawke, Sinmidele Fawohunre, Alex Feben, Federico Fedel, Christopher Fegan, Mae Felongco, Lynsey Felton, Tim Felton, Kate Fenlon, Andrea Fenn, Isabelle Fenner, Ciara Fenton, Melisa Fenton, Cameron Ferguson, Jenny Ferguson, Kathryn Ferguson, Katie Ferguson, Lisa Ferguson, Susan Ferguson, Susie Ferguson, Victoria Ferguson, Denzil Fernandes, Candida Fernandez, Eduardo Fernandez, Sonia Fernandez Lopez, Ahmed Feroz, Pietro Ferranti, Thais Ferrari, Catarina Ferreira-De Almeida, Alexandra Ferrera, Emma Ferriman, Nicholas Fethers, Ben Field, Janet Field, Andra Fielding, Julie Fielding, Sarah Fielding, Asma Fikree, Sarah Ann Filson, Joanne Finch, Laurie Finch, Natalie Fineman, Adam Finn, Joanne Finn, Sofia Fiouni, Jo Fiquet, James Fisher, Neil Fisher, Daniel Fishman, Krystofer Fishwick, Marie Fisk, Jan Flaherty, Michael Flanagan, Charles Flanders, Julie Fleming, Lucy Fleming, Paul Fleming, William Flesher, Alison Fletcher, Lucy Fletcher, Sophie Fletcher, Christopher Flood, Jonathan Flor, Vincent Florence, Sharon Floyd, Adama Fofana, Georgina Fogarty, Linda Folkes, Aiwyne Foo, Andrew Foot, Jayne Foot, Jane Forbes, Kathryn Forcer, Jamie Ford, Jennifer Foreman, Caroline Fornolles, Adam Forrest, Ellie Forsey, Thomas Forshall, Elliot Forster, Julian Forton, Emily Foster, Joseph Foster, Rachel A Foster, Tracy Foster, Angela Foulds, Ian Foulds, Folakemi Fowe, Emily Fowler, Robert Fowler, Stephen Fowler, Caroline Fox, Claire Fox, Heather Fox, Jonathan Fox, Lauren Fox, Natalie Fox, Simon Fox, Sarah-Jane Foxton, Rebecca Frake, Alex Francioni, Olesya Francis, Rebecca Francis, Sarah Francis, Theodora Francis-Bacon, Victoria Francois, Sharon Frayling, Martyn Fredlund, Michael Freeborn, Carol Freeman, Elaine Freeman, Hannah Freeman, Nicola Freeman, Clare Freer, Eleanor French, Anastasia Fries, Matthew Frise, Renate Fromson, Claire Froneman, John Frost, Victoria Frost, Rachel Frowd, Arun Fryatt, Bridget Fuller, Elizabeth Fuller, Tracy Fuller, Duncan Fullerton, Sarah Funnell, John Furness, Hassina Furreed, Waqas Gaba, Elizabeth Gabbitas, Claire Gabriel, Joshua Gahir, Katarzyna Gajewska-Knapik, Christopher Gale, Hugo Gale, Swetha Gali, Bernadette Gallagher, Edith Gallagher, Jude Gallagher, William Gallagher, Catherine Galloway, Emma Galloway, Jacqui Galloway, James Galloway, Laura Gamble, Liz Gamble, Brian Gammon, Jaikumar Ganapathi, Ramesh Ganapathy, Kaminiben Gandhi, Sarah Gandhi, Usha Ganesh, Abrar Gani, Iris Garcia Deniz, Antoni D Gardener, Danielle Gardiner, Emma Gardiner, Kirsty Gardiner, Siobhan Gardiner, Caroline Gardiner-Hill, Jonathan Gardner, Mark Garfield, Atul Garg, Nathan Garlick, Lucie Garner, Zoe Garner, Rosaline Garr, Mark Garton, Florence Garty, Rachel Gascoyne, Hyeriju Gashau, Aoife Gatenby, Erin Gaughan, Alok Gaurav, Mariana Gavrila, Jane Gaylard, Emma Gaywood, Catherine Geddie, Sarah Gee, Gemma Genato, Neil Gent, Susan Gent, Natalie Geoghegan, Nithin George, Sam George, Tina George, Simon Georges, Domonique Georgiou, Leigh Gerdes, Louise Germain, Helen Gerrish, Abel Getachew, Hisham Ghanayem, Auns Ghazanfar, Anca Gherman, Alison Ghosh, Arjun Ghosh, Justin Ghosh, Sudhamay Ghosh, Sarra Giannopoulou, Malick Gibani, Ben Gibbison, Kerry Gibbons, Bethan Gibson, Henry Gibson, Kimberley Gibson, Kirsty Gibson, Sian Gibson, Cat Gilbert, Jeanette Gilbert, Kayleigh Gilbert, Benjamin Giles, Mandy Gill, Lynne Gill, Paul Gillen, Annelies Gillesen, Deborah Gilliland, Robert Gillott, Jemma Gilmore, Danielle Gilmour, Kate Gilmour, Theodora Giokanini-Royal, Anna Gipson, Joanna Girling, Rhian Gisby, Angelena Gkioni, Effrossyni Gkrania-Klotsas, Amy Gladwell, James Glanville, Susannah Glasgow, Jon Glass, Lynn Glass, Lisa Gledhill, Ana Glennon, John Glover, Kyle Glover, Jan Glover Bengtsson, Chevanthy Gnanalingam, Julie Goddard, Wendy Goddard, Emily Godden, Jo Godden, Emma Godson, Aiky Goh, Sunita Gohil, Rebeca Goiriz, Sriya Gokaraju, Raphael Goldacre, Arthur Goldsmith, Portia Goldsmith, Darren Gomersall, Lucia Gomez, Raquel Gomez-Marcos, Ali Gondal, Jack Goodall, Bob Goodenough, Camelia Goodwin, Elizabeth Goodwin, Jayne Goodwin, Paula Goodyear, Rajiv Gooentilleke, Michelle Goonasekara, Sheila Gooseman, Shameer Gopal, Sally Gordon, Hugh Gorick, Stuart Gormley, Michelle Gorst, Thomas Gorsuch, Rebecca Gosling, Henry Goss, Naomi Gott, Elizabeth Goudie, Susan Gould, Melonie Gouldbourne, Lysander Gourbault, Abha Govind, Sharon Gowans, Girish Gowda, Rohit Gowda, Hannah Gower, Thomas Gower, Diana Grabowska, Clive Graham, Donald Graham, Jonathan Graham, Justin Graham, Sharon Graham, Matthew Graham-Brown, Julia Grahamslaw, Gianluca Grana, Tracyanne Grandison, Louis Grandjean, Alison Grant, David Grant, Matthew Grant, Pauleen Grant, Rhys Gravell, Jenny Graves, Alasdair Gray, Catherine Gray, Emily Gray, Georgina Gray, Glaxy Gray, Jackie Gray, Karen Gray, Sebastian Gray, Alan Grayson, Fiona Greaves, Paul Greaves, Charlotte Green, Christopher Green, Frederick Green, Joel Green, Marie Green, Stacey Green, Diarra Greene, Lawrence Greenfield, Philippa Greenfield, Alan Greenhalgh, Daniel Greenwood, Sandra Greer, James Gregory, Jane Gregory, Katie Gregory, Tamsin Gregory, Jill Greig, Julia Greig, Rebecca Grenfell, Teena Grenier, Susan Grevatt, Glaxy Grey, Andrew Gribbin, Ben Griffin, Denise Griffin, Mel Griffin, Sian Griffith, Andrew Griffiths, Daniel Griffiths, David Griffiths, Donna Griffiths, Isabel Griffiths, Nicola Griffiths, Oliver Griffiths, Sofia Grigoriadou, Steph Grigsby, Russell Gritton, Evelina Grobovaite, Clarissa Grondin, Rachel Groome, Liliana Grosu, Jenny Grounds, Jayne Groves, Neil Grubb, Julie Grundy, Francesca Guarino, Sharada Gudur, Shivang Gulati, Vikas Gulia, Pumali Gunasekera, Kirun Gunganah, Jessica Gunn, Emma Gunter, Alok Gupta, Atul Gupta, Rajeev Gupta, Richa Gupta, Tarun Gupta, Vineet Gupta, Ankur Gupta-Wright, Sambasivarao Gurram, Ishy Gurung, Shraddha Gurung, Hazel Guth, Ruth Habibi, Pamela Hackney, Christian Hacon, Aiman Haddad, Denise Hadfield, Michalis Hadjiandreou, Anna Haestier, Nauman Hafiz, Rana Hafiz-Ur-Rehman, Samantha Hagan, Jack W Hague, Rosemary Hague, Andrew Haigh, Kate Haigh, Christina Haines, Scott Hainey, Morton Hair, Brigid Hairsine, Juraj Hajnik, Anne Haldeos, Carmel Halevy, William Halford, Alistair Hall, Anthony Hall, Chloe Hall, Claire Hall, Emily Hall, Helen Hall, Jennifer Hall, Kathryn Hall, Toni Hall, Jan Hallas, Kyle Hallas, Charles Hallett, Heather Halls, Maryam Hamdollah-Zadeh, Bilal Hameed, Imran Hamid, Mohamad Hamie, Bethany Hamilton, Fergus Hamilton, Leigh Hamilton, Ruth Hamlin, Eleanor Hamlyn, Shirley Hammersley, Kate Hammerton, Bev Hammond, Leah Hammond, Rachel Hammond-Hall, Fiona Hammonds, Nidal Hammoud, Ibrahim Hamoodi, Karen Hampshire, Jude Hampson, Shi Han Lee, Ozan Hanci, James Hand, Soran Handrean, Georgina Hands, Sheharyar Hanif, Amy Hannington, Merhej Hannun, Aidan Hanrath, Jane Hanson, Kathryn Hanson, Mazhar U Haq, Ala Haqiqi, Monjurul Haque, Zoe Harding, Simon Hardman, Kumar Haresh, Rachel Harford, Beverley Hargadon, Carolyn Hargreaves, James Hargreaves, Alice Harin, Mohammed Haris, Helen Harizaj, Edward Harlock, Paula Harman, Tracy Harman, Mark Harmer, Muhammad A Haroon, Charlie H Harper, Heather Harper, Peter Harper, Rosemary Harper, Sarah Harrhy, Sian Harrington, Yasmin Harrington-Davies, Claire Harris, Jade Harris, Julie Harris, Laura Harris, Marie-Clare Harris, Nichola Harris, David Harrison, Laura Harrison, Melanie Harrison, Rowan Harrison, Susie Harrison, Tom Harrison, Wendy Harrison, Elizabeth Harrod, Ciaran Hart, Dominic Hart, Rosemary Hartley, Ruth Hartley, Tom Hartley, William Hartrey, Hans Hartung, Alice Harvey, Angela Harvey, Max Harvey, Catherine Harwood, Helen Harwood, Neda Hasan, Brigitte Haselden, Mohammed Hashimm, Imranullah Hashmi, Zena Haslam, Abdulhakim Hassan, Adil Hassan, Ali Hassan, Waqar Ul Hassan, Philip Hassell, Alex Hastings, Bethany Hastings, Jonathan Hatton, Jennifer Haugh, May Havinden-Williams, Stefan Havlik, Dan Hawcutt, Liz Hawes, Nicola Hawes, Annie Hawkins, Nancy Hawkins, Daniel Hawley, Edward Haworth, Cathy Hay, Jamal Hayat, Anne Hayes, Melony Hayes, Fiona Hayes, Antara Hayman, Melanie Hayman, Matthew Haynes, Richard Haynes, Rachel Hayre, Patrick Haywood, Tracy Hazelton, Phoebe Hazenberg, Zhengmai He, Elizabeth Headon, Carrie Heal, Brendan Healy, Amy Hearn, Angela Heath, Rowan Heath, Diane Heaton, Kerry Hebbron, Neil Hedger, Katrine Hedges, Cheryl Heeley, Elaine Heeney, Rajdeep Heire, David Helm, Ulla Hemmila, Scott Hemphill, Deborah Hemsley, Alistair Henderson, Jennifer Henderson, Steven Henderson, Joanne Henry, Karol Henry, Lavinia Henry, Margo Henry, David Henshall, Gillian Herdman, Rosaleen Herdmangrant, William Herrington, Emilia Heselden, Peta Heslop, Simon Hester, Emily Hetherington, Joseph Hetherington, Andrew Hetreed, Chamila Hettiarachchi, Gihan Hettiarachchi, Hayley Hewer, John Hewertson, Anna Hewetson, Sue Hewins, Claire Hewitt, Davina Hewitt, Richard Hewitt, Robert S Heyderman, Matthis Heydtmann, Joseph Heys, Jonathan Heywood, Meg Hibbert, Naomi Hickey, Alexander Hicks, Jenny Hicks, Scott R Hicks, Daniel Higbee, Jennifer Higgins, Lucy Higgins, Andrew Higham, Martin Highcock, Judith Highgate, Mondy Hikmat, Amanda Hill, Helen Hill, Joanne Hill, Phoebe Hill, Annette Hilldrith, Catherine Hillman-Cooper, Zoe Hilton, Alice Hindmarsh, Paul Hine, Kim Hinshaw, Clare Hird, Jemma Hives, Benson Ho, David Hobden, Gill Hobden, Maria Hobrok, Simon Hobson, Simon Hodge, Lesley Hodgen, Holly Hodgkins, Sally Hodgkinson, David Hodgson, Helen Hodgson, Luke Hodgson, Sheila Hodgson, Gemma Hodkinson, Kenneth Hodson, Matthew Hogben, Lucy Hogg, Lee Hoggett, Abigail Holborow, Becky Holbrook, Catherine Holbrook, Catherine Holden, Jill Holden, Melinda Holden, Thomas Holder, Hannah Holdsworth, Lisa Holland, Maureen Holland, Nicky Holland, Marie Hollands, Elizabeth Holliday, Nina Holling, Nigel Hollister, Laszlo Hollos, Evelyn Holmes, Megan Holmes, Raphael Holmes, Rebecca Holmes, Kelly Holroyd, Lyndsey Holt, Siobhan Holt, Alexandra Holyome, Marie Home, Kate Hong, Andrew Hood, Clare Hooper, Samantha Hope, Susan Hope, Bridget Hopkins, Peter W Horby, Stephanie Horler, Anil Hormis, Rachel Horn, Nicola Hornby, Sophie Horrocks, Latoya Horsford, Megan Horsford, Valana Horsham, Alex Horsley, Ashley Horsley, Elizabeth Horsley, Sarah Horton, Jane Hosea, Toby Hoskins, Ejaz Hossain, Muhammad S Hossain, Rashed Hossain, Maxine Hough, Sarah Hough, Kathryn Houghton, Rebecca Houlihan, Gordon Houston, Hamish Houston, Eleanor Hoverd, Roseanna Hovvels, Lee How, Laura Howaniec, Laura Howard, Linda Howard, Lucy Howard, Sarah Howard, Richard Howard-Griffin, Serena Howe, Mark Howells, Lyn Howie, Alex Howlett, Sophie Howlett, Josh Hrycaiczuk, Desmond Hsu, Hein Htet, Zaw Htet, Naing Z Htoon, Su Htwe, Ying Hu, Abby Huckle, Shahzya Huda, Alison Hudak, Lisa Hudig, Heather Hudson, Alison Hufton, Conor Huggins, Alistair Hughes, Emma Hughes, Gareth Hughes, Heather Hughes, Luke Hughes, Rachel Hughes, Rhian Hughes, Samantha Hughes, Stephen Hughes, Vikki Hughes, Wesley Hughes, Lukas Huhn, Ching Hui, Ruth Hulbert, Diana Hull, Robert Hull, Amanda Hulme, Peter Hulme, Wendy Hulse, George Hulston, Ryan Hum, Charlotte Humphrey, Alasdair Humphries, Joanne Humphries, David Hunt, Fiona Hunt, Jane Hunt, Kristen Hunt, Luke Hunt, Karl Hunter, Neil Hunter, Elizabeth Hurditch, Cian Hurley, Katrina Hurley, Mohammed A Husain, Syeda Y Husaini, Coralie Huson, Ibraar Hussain, Mohammad Hussain, Muhammad Hussain, Reda Hussain, Sajid Hussain, Samia Hussain, Sanniah Hussain, Yasmin Hussain, Mohammed Hussam El-Din, Rebecca Hussey, Christopher Hutchcroft, Camille Hutchinson, Dorothy Hutchinson, Elizabeth Hutchinson, John Hutchinson, Claire Hutsby, Paula Hutton, Daniella Hydes, Jamie Hyde-Wyatt, Niamh Hynes, Megan Hyslop, Ahmed Ibrahim, Asil Ibrahim, Kamal Ibrahim, Mohamed Ibrahim, Wadah Ibrahim, Muhammad Idrees, Hina Iftikhar, Chukwuemeka Igwe, Mohammad Ijaz, Amaju Ikomi, Clare Iles, Stamatina Iliodromiti, Lorna Ilves, La'ali Imam-Gutierrez, Christopher Imray, Haider Imtiaz, Jack Ingham, Julie Ingham, Rory Ingham, Tejas Ingle, Anne Ingram, Luke Ingram, Peter Inns, Ken Inweregbu, Andreea A Ionescu, Ana 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Sabrina Jansz, Deepa Japp, Catherine Jardine, Ellie Jarvie, Rosina Jarvis, Patrycja Jastrzebska, Hafsa Javed, Lona Jawaheer, Dinakaran Jayachandran, Deepak Jayaram, Geeshath Jayasekera, Lalith Jayasekera, Saman Jeddi, Mohammad S Jeelani, Katie Jeffery, Rachel Jeffrey, Nathan Jeffreys, Benjamin Jeffs, Debbie Jegede, Taylor Jemima, Ifan Jenkin, Alison Jenkins, David Jenkins, Elinor Jenkins, Sarah Jenkins, Sian Jenkins, Stephen Jenkins, Edward Jenner, David Jennings, Jacqui Jennings, Louise Jennings, Virginia Jennings, Ellen Jerome, Douglas Jerry, Ellen Jessup-Dunton, Jorge A Jesus Silva, Kishan Jethwa, Abi Jeyabalan, Akhilesh Jha, Shaman Jhanji, Khoo Jian, Zhixin Jiao, Ana Jimenez Gil, Jithin Jith, Teishel Joefield, Navraj Johal, Karine Johannessen, Aisyah Johari, Annie John, Anu John, Emma Johns, Margaret Johns, Antoinette Johnson, Gillian Johnson, Kathryn Johnson, Luke Johnson, Mark Johnson, Claire Johnston, Janet Johnston, Susan Johnston, Victoria Johnston, Dawn Johnstone, Ed 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Muhammad U Khalid, Amir Khalil, Asma Khalil, Sijjad Khalil, Ali Khan, Al-Imran Khan, Asad Khan, Burhan Khan, Fatimah Khan, Kausik Khan, Lubna Khan, Malik A Khan, Marria Khan, Mohammad Khan, Mohammed R Khan, Nayeem Khan, Omar Khan, Rahila Khan, Shabana Khan, Shahul Khan, Tasaduksultan Khan, Waseem Khan, Usman F Khatana, Jibran Khatri, Jyoti Khatri, Sagira Khatun, Taslima Khatun, Chuen R Khaw, Htet HE Khin, Kiran Khokhar, Najaf Khota, Chloe Khurana, Shruti Khurana, Faith Kibutu, Andrew Kidd, Michelle Kidd, Joe Kidney, Shane Kidney, Will Kieffer, Caroline Kilby, Eliz Kilich, Jee Whang Kim, Sarah Kimber, Andy King, Barbara King, Jennifer King, Kirsten King, Rachel King, Sam King, Victoria King, Emily King-Oakley, Laura Kingsmore, Fiona Kinney, Jeremy Kirk, Amy Kirkby, Emily Kirkham, Gemma Kirkman, Ursula Kirwan, Toby Kitching, Laura Kitto, Lauren Kittridge, Sarah Klaczek, Susan Kmachia, Christopher Knapp, Lucy Knibbs, Alicia Knight, Fraser Knight, Marian Knight, Sarah Knight, Steven 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MacDonald, Sheila MacFadyen, James G MacFarlane, Jill Macfarlane, Laura Macfarlane, Lisa MacInnes, Jill MacIntyre, Kirsten Mack, Callum Mackay, Euan Mackay, Alexander Mackenzie, Matt Mackenzie, Robert MacKenzie Ross, Ami Mackey, Fiona Mackie, Robert Mackie, Carolyn Mackinlay, Claire Mackintosh, Katherine Mackintosh, Colin MacLeod, Mary J MacLeod, Michael Macmahon, Andrew MacNair, Catherine Macphee, Iain Macpherson, Allan MacRaild, Alannah Madden, Mary Madden, Norman Madeja, Paula Madgwick, Madhavi Madhusudhana, Alpha Madu, Lorraine Madziva, Marion Mafham, Emma Magavern, Negar Maghsoodi, Christopher Magier, Marios Magriplis, Natasha Mahabir, Subramanian Mahadevan-Bava, Anjanie Maharajh, Ajit Mahaveer, Bal Mahay, Hibo Mahdi, Thushika Mahendiran, Siva Mahendran, Sarah Maher, Shameera Maheswaran, Parisa Mahjoob-Afag, Ahmed Mahmood, Farhana Mahmood, Hager Mahmoud, Mian Mahmood, Waheed Mahmood, Ewan Mahony, Luke Mair, James Maitland, Rupert Major, Jaydip Majumdar, Mohammad KH Majumder, Stephen Makin, Marius Malanca, Hannah Malcolm, Neeraj Malhan, Gulshan Malik, Mohammed Maljk, Petrina Mallinder, Louise Mallon, Edward Malone, Gracie Maloney, Madhu Mamman, Irene Man, Marco Mancuso-Marcello, Aritri Mandal, Tracy Manders, Lauren Manderson, Justin Mandeville, Roope Manhas, Carmen Maniero, Bobby Mann, Baranitharan Manoharan, Katherine Mansi, Dina Mansour, Isheunesu T Mapfunde, Predeesh Mappa, Hemant Maraj, Gemma Marayan, Clare Marchand, Neil Marcus, Maria Marecka, Gomathi Margabanthu, Jordi Margalef, Lavinia Margarit, Georgios Margaritopoulos, Mike Margarson, Fernandez M Maria del Rocio, Victor Mariano, Ashleigh Maric, Arran Marriott, Nemonie Marriott, Karen Marsden, Paul Marsden, Tracy Marsden, Robyn Marsh, Adam Marshall, Andrew Marshall, Gail Marshall, Henry Marshall, Jaimie Marshall, Jenna Marshall, Nicola Marshall, Emmeline Martin, Hayley Martin, Hope Martin, Jane Martin, Karen Martin, Laila Martin, Michael Martin, Sarah Martin, Winston Martin, Tim Martindale, Marcus 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Rose, Steve Rose, Zoe Rose, Josephine Rosier, Jennifer Rossdale, Sabrina Rossi, Andrew Ross-Parker, Alex Rothman, Joanne Rothwell, Lindsay Roughley, Guy Rousseau, Kathy Rowan, Neil Rowan, Stephen Rowan, Louise Rowe-Leete, Benjamin Rowlands, Aparajita Roy, Subarna Roy, Anna Roynon-Reed, Sam Rozewicz, Antonio Rubino, Anna Rudenko, Senthan Rudrakumar, Banu Rudran, Shannon Ruff, Prita Rughani, Mike Ruiz, Sharon Rundell, Hitasha Rupani, Darren Rusk, Joseph Russell, Peter Russell, Richard Russell, Cristina Russo, Marieke Rutgers, Aidan Ryan, Brendan Ryan, Lucy Ryan, Matthew Ryan, Pat Ryan, Phil Ryan, Declan Ryan-Wakeling, Chloe Saad, M Saad, Javeson Sabale, Suganya Sabaretnam, Gorka Sacher, Noman Sadiq, Ashiq Saffy, Diaeddin Sagar, Beth Sage, Harkiran Sagoo, Rajnish Saha, Nikhil Sahdev, Jagdeep Sahota, Nooria Said, Sreekanth Sakthi, Abdul Salam, Erika Salciute, Jessica Sale, Gina Saleeb, Mumtaz Saleh, Hizni Salih, Laylan Salih, Sarah Salisbury, Rustam Salman, Jenny Salmon, Dario Salutous, Mfon Sam, Sally Sam, Tinashe Samakovna, Razan Saman, Renaldo Samlal, Emily Sammons, David Sammut, Mark Sammut, Sunitha Sampath, Julia Sampson, Anda Samson, Debbie Samuel, Johnson Samuel, Reena Samuel, Thomas DL Samuel, Elsward Samuels, Theo Samuels, Joanna Samways, Manjula Samyraju, Ilves Sana, Aabid Sanaullah, Veronica Sanchez, Amada Sanchez, Tom Sanctuary, Peter Sandercock, Amy Sanderson, Paul Sanderson, Tom Sanderson, Kuljinder Sandhu, Loveleen Sandhu, Victoria Sandrey, Sarah Sands, Mirriam Sangombe, Matthew Sanju, Rojy Santosh, Jayanta Sanyal, Aureo F Sanz-Cepero, Najam Saqib, Sarbjit Sarai, Dinesh Saralaya, Arun Saraswatula, Avishay Sarfatti, Rebecca Sargent, Beatrix Sari, Rahul Sarkar, Sruthi Sarma, Varun Sarodaya, Zainab Sarwar, Thea Sass, Sonia Sathe, Sobitha Sathianandan, Abilash Sathyanarayanan, Thozhukat Sathyapalan, Prakash Satodia, Rachel Saunders, Samantha Saunders, Anne Saunderson, Heather Savill, Karishma Savlani, Matthew Saxton, Amrinder Sayan, Diane Scaletta, Lyndsay Scarratt, Sean Scattergood, Alvin Schadenberg, Alex Schoolmeesters, Natasha Schumacher, Nicola Schunke, Martin Schuster Bruce, Karin Schwarz, Tim Scorrer, Fiona Scothern, A Scott, Anne Scott, Christine Scott, Emily Scott, Kerrie Scott, Stephen Scott, Timothy Scott, Sarah Scourfield, Wendy Scrase, Angela Scullion, Emily Seager, Cathy Seagrave, Eleanor Sear, Isabella Seaton, Anna Seckington, Joanna Sedano, Gabrielle Seddon, Muhammad A Seelarbokus, Christopher Sefton, Matias Segovia, Gillian Sekadde, Georgina Selby, Katharine Sellers, Joseph Selley, Victoria Sellick, Gobika Selvadurai, Brintha Selvarajah, Haresh Selvaskandan, Gary Semple, Nandini Sen, Seema Sen, Namrita Sengreen, Aditya Sengupta, Niladri Sengupta, HoJan Senya, Jaskaran Sethi, Niranjan Setty, Abigail Seward, Teswaree Sewdin, Jack Seymour, Tariq Shafi, Aashni Shah, Ahmar Shah, Anand Shah, Anjnee Shah, Bhavni Shah, Neil Shah, Pallav Shah, Priyank Shah, Qasim Shah, Sarfaraz H Shah, Snehal Shah, Suraj Shah, Syed Shah, Sousan Shahi, Sipan Shahnazari, Ramli Shahrul, Muhammad Shahzeb, Amina Y Shaikh, Rajit Shail, Mariya Shaji, Korah Shalan, Nafe Shami, Nadia Shamim, Kazi Shams, Thomas Shanahan, Paul Shannon, Hamed Sharaf, Asir Sharif, Akhilesh Sharma, Ash Sharma, Mona Sharma, Ojasvi Sharma, Rajeev Sharma, Sanjeev Sharma, Sarkhara Sharma, Alexander Sharp, Charles Sharp, Gemma Sharp, Paula Sharratt, Phoebe Sharratt, Christopher Shaw, David Shaw, Deborah Shaw, Joanne Shaw, Jonathan Shaw, Lisa Shaw, Tomos G Shaw, Anna Shawcross, Jill Shawe, Sophy Shedwell, Jonathan Sheffield, Zak Shehata, Arshiya Sheik, Asif Sheikh, Noorann Sheikh, Benjamin Shelley, Sarah Shelton, Anil Shenoy, Julie Shenton, Amy Shepherd, Lorna Shepherd, Scott Shepherd, Rhian Sheppeard, Helen Sheridan, Ray Sheridan, Samuel Sherridan, Leanne Sherris, Susanna Sherwin, Shaad Shibly, Norma Shields, Chiaki Shioi, Lucy Shipp, Anand Shirgaonkar, Kim Shirley, Adebusola Shonubi, Rohan Shotton, Sarah Shotton, Ervin Shpuza, Nora Shrestha, Karen Shuker, Jack Shurmer, Loria Siamia, Seshnag Siddavaram, Nasir Siddique, Sohail Siddique, Nyma Sikondari, Malcolm Sim, Robert Sime, Oliver Simmons, Richard Simms, Angela Simpson, Anna Simpson, Danny Simpson, Georgina Simpson, Kathryn Simpson, Kerry Simpson, Phillip Simpson, Thomas Simpson, Janet Sinclair, Ankita Singh, Claire Singh, Jayaprakash Singh, Jyoti Singh, Manjeet Singh, Nadira Singh, Pankaj Singh, Prabhsimran Singh, Salil Singh, Parag Singhal, Surendra Singham, Bryan Singizi, Manas Sinha, Sharad Sinha, Utkarsh Sinha, Guy Sisson, Karthikadevi Sivakumar, Shanmugasundaram Sivakumar, Darshi Sivakumaran, Sivanthi Sivanadarajah, Nicole Skehan, Robert Skelly, Jill Skelton, Orlagh Skelton, Imogen Skene, Denise Skinner, Tabitha Skinner, Victoria Skinner, Agnieszka Skorko, Iwona Skorupinska, Mariola Skorupinska, Amy Slack, Katie Slack, Heather Slade, Mark Slade, Holly Slater, Lynda Slater, Nicola Slawson, Andrew Sloan, Brendan Sloan, Derek Sloan, Grace Sluga, Ellen Small, Samuel Small, Karen D 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Temple, Helen Tench, Yi He Teoh, Lynne Terrett, Louise Terry, Dariusz Tetla, Daniel Tewkesbury, Manish Thakker, Mini Thankachen, Dushen Tharmaratnam, Hilary Thatcher, Andrew Thayanandan, Krishna Thazhatheyil, Eaint Thein, Byron Theron, Phyu Thet, Kapeendran Thevarajah, Brinda Thillainathan, Yvette Thirlwall, Muthu Thirumaran, Alice Thomas, Amy Thomas, Andrew Thomas, Emma Thomas, Enson Thomas, Esther Thomas, Helen Thomas, James Thomas, Karen Thomas, Koshy Thomas, Lucy Thomas, Megan Thomas, Rachel Thomas, Rebecca Thomas, Rhys Thomas, Ruth Thomas, Sarah Thomas, Sherine Thomas, Tessy Thomas, Vicky Thomas, Rhian Thomas-Turner, Catherine Thompson, Christopher Thompson, Clara Thompson, Fiona Thompson, Katharine Thompson, Laura Thompson, Liz Thompson, Orla Thompson, Roger Thompson, Jason Thomson, Nicola Thomson, Natasha Thorn, Charlotte Thorne, Nicola Thorne, Jim Thornton, Richard Thornton, Sarah Thornton, Susan Thornton, Thomas Thornton, Christopher Thorpe, Sarah Thorpe, Paradeep Thozthumparambil, Laura Thrasyvoulou, Hannah Thraves, Guy Thwaites, Simon Tiberi, Serena Tieger, Carey Tierney, Caroline Tierney, Mark Tighe, Sorrell Tilbey, Amanda Tiller, Elizabeth Timlick, Hayley Timms, Anne-Marie Timoroksa, Samakomva Tinashe, Heather Tinkler, Marianne Tinkler, Jacqui Tipper, Sophie Tisi, Helen Tivenan, Suzy Tluk, Helen T-Michael, Anne Todd, Jackie Todd, Stacy Todd, Mohamed Tohfa, Melanie Tolson, Ana L Tomas, Natalia Tomasova, Sharon Tomlin, Simon Tomlins, Ivan Tonna, Kirsty Topham, Mathew Topping, Parisa Torabi, M Estee Torok, Mark Toshner, Ruhaif Tousis, Peter Tovey, Gareth Towersey, Jill Townley, Richard Tozer, Myat T Trafford, Helen Tranter, Christopher Travill, Sarah Traynor, Ascanio Tridente, Sanchia Triggs, Fiona Trim, Alex Trimmings, Tom Trinick, Maria Tripouki, Ashifa Trivedi, Dawn Trodd, Amy Trotter, Madeleine Trowsdale Stannard, Nigel Trudgill, Daniel Trushell-Pottinger, Maria Truslove, Shaun Trussell, Tariq Trussell, Kyriaki Tsakiridou, Christine Tsang, Peter Tsang, Kyriaki K Tsilimpari, Georgios Tsinaslanidis, Simon Tso, Sally Tucker, Aisha Tufail, Redmond Tully, Killian Turbitt, Rezon Turel, Tolga Turgut, Claudia Turley, Alison Turnbull, Aine Turner, Ash Turner, Charlotte Turner, Gail Turner, Kate Turner, Kelly Turner, Lucy Turner, Mark Turner, Patricia Turner, Sally Turner, Samantha Turner, Victoria Turner, Sharon Turney, Jon Turvey, Emma Twohey, Bhavya Tyagi, Vedang Tyagi, Abigail Tyer, Jayne Tyler, Jennifer Tyler, Alison Tyzack, Petros Tzavaras, Mohammad S Uddin, Ruhama Uddin, Salamat Ullah, Sanda Ullah, Athavan Umaipalan, Judith Umeadi, Akudo Umeh, Wilfred Umeojiako, Lizzie Undrell, Adam Unsworth, Veerpal SU Uppal, Gerry Upson, Alison Uriel, Sebastian Urruela, Hiromi Uru, Miranda Usher, Rebecca Usher, Andrew Ustianowski, Linda C Vaccari, Abhay Vaidya, Erika Vainieri, Bernardas Valecka, Jennifer Valentine, Balan Valeria, Luke Vamplew, Ekaterini Vamvakiti, Joannis Vamvakopoulos, Maud van de Venne, Alex van der Meer, Nora van der Stelt, Lynne Van Koutrik, Joseph Vance-Daniel, Rama Vancheeswaran, Samuel I Vandeyoon, Padma Vankayalapati, Chloe Vansomeren, William Van't Hoff, Sejal Vara, Anu Varghese, Maria Varghese, Teena Varghese, William Varney, Giulia Varnier, Valeria Vasadi, Vimal Vasu, Vasanthi Vasudevan, Ramu Vathenen, Manu Vatish, Heloyes Vayalaman, Christopher Vaz, Niki Veale, Bar Velan, Swati Velankar, Luxmi Velauthar, Neyme Veli, Nicola Vella, Anitha Velusamy, Ian Venables, Mavi Venditti, Ramya Venkataramakrishnan, Richard Venn, Robert Venn, Lyn Ventilacion, Mark Veres, Stefania Vergnano, Will Verling, Amit Verma, Britney Vernon, Nathan Vernon, Mark Vertue, Natalie Vethanayagam, Lucy Veys, Jennifer Vidler, Denise Vigni, Vinod W Vijayaraghavan Nalini, Enric Vilar, Neringa Vilimiene, Joseph Villiers, Sylvia Vinay, Latha Vinayakarao, Rachel Vincent, Rosie Vincent, Lisa Vincent Smith, Emma Virgilio, Abdullah M Virk, Elisa Visentin, Karunakaran Vithian, Alain Vuylsteke, Eleftheria Vyras, Richard Wach, Beverley Wadams, Susan Wadd, Natalia Waddington, Kirsten Wadsworth, Syed EI Wafa, Daniel Wagstaff, Lynda Wagstaff, Dalia Wahab, Zaroug Wahbi, Khalilullah Wahdati, Sawan Waidyanatha, Rachel Wake, Alice Wakefield, Emma Wakefield, Harry Wakefield, William Wakeford, Fiona Wakinshaw, Andrew Walden, Lorna Walding, Claire Walker, Ian Walker, Kevin Walker, Kim Walker, Linda Walker, Marie Walker, Rachel Walker, Susan Walker, Elaine Wall, Rebecca Wallbutton, Jessica Wallen, Karl Wallendszus, Arabella Waller, Michael Waller, Rosemary Waller, Gabriel Wallis, Louise Wallis, Donna Walsh, Elizabeth Walsh, Lani Walshaw, Daniel Walter, Holt Walters, Jocelyn Walters, Eileen Walton, Maggie Walton, Michael Walton, Olivia Walton, Susan Walton, Mandy Wan, Thin Wan, Mary Wands, Rachel Wane, Frank Wang, Nick Wang, Ran Wang, Deborah Warbrick, Samantha Warburton, Deborah Ward, Emma Ward, Katie Ward, Luke Ward, Rachael Ward, Thomas Ward, Scott A Warden, Steve Wardle, Hassan Wardy, Tobias Wareham, Scott Waring, Jenny Warmington, Ben Warner, Christian Warner, Lewis Warnock, Sarah Warran, Lisa Warren, Yolanda Warren, Hannah Warren-Miell, Hazel J Watchorn, Holly Waterfall, Abby Waters, Donald Waters, Mark Waterstone, Catherine Watkins, Catrin Watkins, Eleanor Watkins, Karen Watkins, Lynn Watkins, Adam JR Watson, Ekaterina Watson, Eleanor Watson, Paul Watson, Robert Watson, Malcolm Watters, Donna Watterson, Daniel Watts, John Watts, Merlin Watts, Victoria Waugh, Emma Wayman, Akhlaq Wazir, Nick Weatherly, Hayley Webb, Kathryn Webb, Stephen Webb, Ian Webster, Tim Webster, Ling Wee, Thanuja Weerasinghe, Janaka Weeratunga, Maria Weetman, Shuying Wei, Freshtah Weidi, Hugh Welch, James Welch, Leanne Welch, Steven Welch, Samantha Weller, Claire Wells, Susan Wellstead, Berni Welsh, RIchard Welsh, Ingeborg Welters, Rachael Welton, Lauren Wentworth, Kate Wesseldine, Magdelena West, Raha West, Ruth West, Sophie West, Heather Weston, Alice Westwood, Bill Wetherall, Helen Wheeler, Matthew Whelband, Amanda Whileman, Jenny Whitbread, Benjamin White, Catherine White, Christopher White, Duncan White, James White, Jonathan White, Katie White, Marie White, Nick White, Sarah White, Sonia White, Tracey White, Catherine Whitehead, Anne Whitehouse, Claire Whitehouse, Tony Whitehouse, Sophie Whiteley, Gabriel Whitlingum, Elizabeth Whittaker, Lindsay Whittam, Ashley Whittington, Helen Whittle, Eunice Wiafe, Lou Wiblin, John Widdrington, Jason Wieboldt, Hannah Wieringa, Cornelia Wiesender, Laura Wiffen, Andrew Wight, Christopher Wignall, Danielle Wilcock, Emma Wilcock, Louise Wilcox, Karen Wild, Laura Wild, Stephen Wild, Michael Wilde, Peter Wilding, Tracey Wildsmith, Joe Wileman, Joy Wiles, Kate Wiles, Elva Wilhelmsen, Thomas Wiliams, David Wilkin, Hannah Wilkins, Joy Wilkins, Suzanne Wilkins, Iain Wilkinson, Lesley Wilkinson, Nicola Wilkinson, Sophia Wilkinson, Susan Wilkinson, Tim Wilkinson, Sylvia Willetts, Alexandra Williams, Alison Williams, Angharad Williams, Ava Williams, Carl Williams, Caroline V Williams, Claire Williams, Dewi Williams, Felicity Williams, Gail Williams, Hannah Williams, James Williams, Jennie Williams, John Williams, Joseph JR Williams, Karen Williams, Kathryn Williams, Marie Williams, Matthew Williams, Patricia Williams, Penny Williams, Samson Williams, Sarah Williams, Sophie Williams, Tamanna Williams, Annie Williamson, Cath Williamson, Catherine Williamson, Dawn Williamson, James D Williamson, Elizabeth Willis, Emily Willis, Heather Willis, Herika Willis, Joanna Willis, Louise Wills, Lucy Willsher, Francesca Willson, Alison Wilson, Andrea Wilson, Antoinette Wilson, Debbie Wilson, James Wilson, Kate Wilson, Lucinda Wilson, Mark Wilson, Toni Wilson, Tim Wilson, Marlar Win, Tin T Win, Lucinda Winckworth, Laura Winder, Piers Winder, Nicola Window, Simon Winn, Carmen Winpenny, Helen Winslow, Martin Winstanley, Helen Winter, Jonathan Winter, Barbara Winter-Goodwin, Stephen Wisdom, Martin Wiselka, Sophie Wiseman, Steven Wishart, Eric Witele, Nicholas Withers, Janet Wittes, Donna Wixted, Nicola Wolff, Kirsten Wolffsohn, Rebecca Wolf-Roberts, Elena Wolodimeroff, Chi-Hung Wong, Edwin Wong, Jessica SY Wong, Kit Y Wong, Nick Wong, Sam Wong, Caroline Wood, Dianne Wood, Fiona Wood, Hannah Wood, Jennifer Wood, Joe Wood, Lisa Wood, Louise Wood, Michelle Wood, Stephen Wood, Tracy Wood, Katharine Woodall, Rebecca Woodfield, Christopher Woodford, Jill Woodford, Louise Woodhead, Timothy Woodhead, Philip Woodland, Marc Woodman, Jane Woods, Katherine Woods, Sarah Woods, Elizabeth Woodward, Zoe Woodward, Megan Woolcock, Gemma Wooldridge, Rebecca Woolf, Chris Woollard, Louisa Woollen, Emma Woolley, Jade Woolley, Daniel Woosey, Dan Wootton, Joanne Wootton, Stephy Worton, Jonathan Wraight, Lynn Wren, Caroline Wrey Brown, Demi Wright, Francesca Wright, Imogen Wright, Lianne Wright, Rachel Wright, Caroline Wroe, Henry Wu, Peishan Wu, Pensee Wu, Johnathan Wubetu, Retno Wulandari, Kim Wyness, Frederick Wyn-Griffiths, Inez Wynter, Bindhu Xavier, Zhongyang Xia, Masseh Yakubi, May Yan, Michael Yanney, Salima Yasmin, Bryan Yates, David Yates, Edward Yates, Helen Yates, Mark Yates, Charlotte Yearwood Martin, Khin Yein, Robert Yellon, Fiona Yelnoorkar, Peter Yew, Kawai Yip, Laura Ylquimiche Melly, Inez Ynter, Cissy Yong, Jemma Yorke, Abdel Younes Ibrahim, Gail Young, Louise Young, Sajeda Youssouf, Ahmed Yousuf, Chrissie Yu, Bernard Yung, Daniel Yusef, Anna-Sophia Zafar, Silvia Zagalo, Su Zaher, Kareem Zaki, Nabhan Zakir, Kasia Zalewska, Ane Zamalloa, Mohsin Zaman, Shakir Zaman, Julie Zamikula, Louise Zammit, Marie Zammit-Mangion, Ausra Zdanaviciene, Esther Zebracki, Daniel Zehnder, Lisa Zeidan, Xiaobei Zhao, Dongling Zheng, Jane Zhixin, Doreen Zhu, Madiha Zia, Omar Zibdeh, Rabia Zill-E-Huma, Ei T Zin, Vivian Zinyemba, Christos Zipitis, Arkadiusz Zmierczak, Azam Zubir, Naz Zuhra, Rasha Zulaikha, Carol Zullo, Ana Zuriaga-Alvaro, National Institute for Health Research, UK Research and Innovation, University of St Andrews. School of Medicine, Horby, PW, Roddick, A, Spata, E, Staplin, N, Emberson, JR, Pessoa-Amorim, G, Peto, L, Day, J, Thwaites, G, Mafham, M, Haynes, R, and Landray, MJ
Subjects: Male, medicine.medical_treatment, 030204 cardiovascular system & hematology, Azithromycin, ResearchInstitutes_Networks_Beacons/humanitarian_conflict_response_institute, Rate ratio, chemistry.chemical_compound, 0302 clinical medicine, RA0421, Oxygen therapy, RA0421 Public health. Hygiene. Preventive Medicine, 030212 general & internal medicine, Hospital Mortality, 11 Medical and Health Sciences, azithromycin, education.field_of_study, Covid19, clinical trial, General Medicine, 3rd-DAS, Middle Aged, Hospitalization, Survival Rate, Treatment Outcome, Humanitarian and Conflict Response Institute, Female, Life Sciences & Biomedicine, medicine.medical_specialty, RM, Population, COVID-19/drug therapy, Azithromycin/therapeutic use, 03 medical and health sciences, Pharmacotherapy, Tocilizumab, Medicine, General & Internal, SDG 3 - Good Health and Well-being, Internal medicine, General & Internal Medicine, medicine, Humans, education, Survival rate, Mechanical ventilation, Science & Technology, business.industry, COVID-19, NIS, Length of Stay, R1, United Kingdom, COVID-19 Drug Treatment, RM Therapeutics. Pharmacology, RECOVERY Collaborative Group, chemistry, Relative risk, business, RA, Anaesthesia Pain and Critical Care
Abstract: The RECOVERY trial is supported by a grant to the University of Oxford from UK Research and Innovation (Medical Research Council) and NIHR (MC_PC_19056) and by core funding provided by NIHR Oxford Biomedical Research Centre, Wellcome, the Bill & Melinda Gates Foundation, the Department for International Development, Health Data Research UK, the Medical Research Council Population Health Research Unit, the NIHR Health Protection Unit in Emerging and Zoonotic Infections, and NIHR Clinical Trials Unit Support Funding. TJ is supported by a grant from UK Medical Research Council (MC_UU_0002/14) and an NIHR Senior Research Fellowship (NIHR-SRF-2015-08-001). WSL is supported by core funding provided by NIHR Nottingham Biomedical Research Centre. Background: Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatory actions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19. Methods: In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospital with COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients were randomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once per day by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatment groups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment and were twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants and local study staff were not masked to the allocated treatment, but all others involved in the trial were masked to the outcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treat population. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936. Findings: Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) were eligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was 65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomly allocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall, 561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days (rate ratio 0·97, 95% CI 0·87-1·07; p=0·50). No significant difference was seen in duration of hospital stay (median 10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days (rate ratio 1·04, 95% CI 0·98-1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, no significant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilation or death (risk ratio 0·95, 95% CI 0·87-1·03; p=0·24). Interpretation: In patients admitted to hospital with COVID-19, azithromycin did not improve survival or other prespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restricted to patients in whom there is a clear antimicrobial indication. Publisher PDF
Published: 2021
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38. Adaptive Robust Local Online Density Estimation for Streaming Data

Author: Andrea Edwards, Zhide Fang, Zhong Chen, Kun Zhang, Victor S. Sheng, Jiabin Zhao, and Wei Fan
Subjects: Concept drift, Data stream mining, Computer science, Kernel density estimation, 02 engineering and technology, Density estimation, Ensemble learning, Article, Noise, Artificial Intelligence, Robustness (computer science), 020204 information systems, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Computer Vision and Pattern Recognition, Algorithm, Software, Statistical hypothesis testing
Abstract: Accurate online density estimation is crucial to numerous applications that are prevalent with streaming data. Existing online approaches for density estimation somewhat lack prompt adaptability and robustness when facing concept-drifting and noisy streaming data, resulting in delayed or even deteriorated approximations. To alleviate this issue, in this work, we first propose an adaptive local online kernel density estimator (ALoKDE) for real-time density estimation on data streams. ALoKDE consists of two tightly integrated strategies: (1) a statistical test for concept drift detection and (2) an adaptive weighted local online density estimation when a drift does occur. Specifically, using a weighted form, ALoKDE seeks to provide an unbiased estimation by factoring in the statistical hallmarks of the latest learned distribution and any potential distributional changes that could be introduced by each incoming instance. A robust variant of ALoKDE, i.e., R-ALoKDE, is further developed to effectively handle data streams with varied types/levels of noise. Moreover, we analyze the asymptotic properties of ALoKDE and R-ALoKDE, and also derive their theoretical error bounds regarding bias, variance, MSE and MISE. Extensive comparative studies on various artificial and real-world (noisy) streaming data demonstrate the efficacies of ALoKDE and R-ALoKDE in online density estimation and real-time classification (with noise).
Published: 2021

39. Primary acute lymphoblastic leukemia cells are susceptible to microtubule depolymerization in G1 and M phases through distinct cell death pathways

Author: Magdalena Delgado, Randall R. Rainwater, Billie Heflin, Alicja Urbaniak, Kaitlynn Butler, Mari Davidson, Reine M. Protacio, Giulia Baldini, Andrea Edwards, Megan R. Reed, Kevin D. Raney, and Timothy C. Chambers
Subjects: Enzyme Activation, Caspase 3, Vincristine, Cell Cycle, Humans, Mitosis, Apoptosis, Cell Biology, Precursor Cell Lymphoblastic Leukemia-Lymphoma, Microtubules, Molecular Biology, Biochemistry, bcl-2-Associated X Protein
Abstract: Microtubule targeting agents (MTAs) are widely used cancer chemotherapeutics which conventionally exert their effects during mitosis, leading to mitotic or postmitotic death. However, accumulating evidence suggests that MTAs can also generate death signals during interphase, which may represent a key mechanism in the clinical setting. We reported previously that vincristine and other microtubule destabilizers induce death not only in M phase but also in G1 phase in primary acute lymphoblastic leukemia cells. Here, we sought to investigate and compare the pathways responsible for phase-specific cell death. Primary acute lymphoblastic leukemia cells were subjected to centrifugal elutriation, and cell populations enriched in G1 phase (97%) or G2/M phases (80%) were obtained and treated with vincristine. We found death of M phase cells was associated with established features of mitochondrial-mediated apoptosis, including Bax activation, loss of mitochondrial transmembrane potential, caspase-3 activation, and nucleosomal DNA fragmentation. In contrast, death of G1 phase cells was not associated with pronounced Bax or caspase-3 activation but was associated with loss of mitochondrial transmembrane potential, parylation, nuclear translocation of apoptosis-inducing factor and endonuclease G, and supra-nucleosomal DNA fragmentation, which was enhanced by inhibition of autophagy. The results indicate that microtubule depolymerization induces distinct cell death pathways depending on during which phase of the cell cycle microtubule perturbation occurs. The observation that a specific type of drug can enter a single cell type and induce two different modes of death is novel and intriguing. These findings provide a basis for advancing knowledge of clinical mechanisms of MTAs.
Published: 2022
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40. Changes in the host transcriptome and microbial metatranscriptome of the ileum of dairy calves subjected to artificial dosing of exogenous rumen contents

Author: Anna Larsen, Madison S. Cox, Andrew J. Steinberger, Wenli Li, Andrea Edwards, Garret Suen, S.M. Raabis, Joseph H. Skarlupka, and Brianna Murphy
Subjects: 0301 basic medicine, Male, Rumen, Physiology, 030106 microbiology, Ileum, Weaning, Biology, Microbiology, Transcriptome, 03 medical and health sciences, Immune system, Genetics, medicine, Animals, RNA-Seq, Dairy cattle, Gastrointestinal tract, Host Microbial Interactions, Animal Feed, Small intestine, Immunity, Innate, Body Fluids, Gastrointestinal Microbiome, 030104 developmental biology, medicine.anatomical_structure, Gene Ontology, Animals, Newborn, Genes, RNA, Ribosomal, Cattle, Female
Abstract: Development of a properly functioning gastrointestinal tract (GIT) at an early age is critical for the wellbeing and lifetime productivity of dairy cattle. The role of early microbial colonization on GIT development in neonatal cattle and the associated molecular changes remain largely unknown, particularly for the small intestine. In this study, we performed artificial dosing of exogenous rumen fluid during the early life of the calf, starting at birth through the weaning transition at 8 wk. Six calves were included in this study. At 8 wk of age, tissue from the ileum was collected and subjected to host transcriptome and microbial metatranscriptome analysis using RNA sequencing. A total of 333 genes showed significant differential expression (DE) (fold-change ≥2; adjusted P < 0.1, mean read-count ≥10) between the treated and control calves. Gene ontology analysis indicated that these DE genes are predominantly associated with processes related to the host immune response ( P < 0.0001). Association analysis between the host gene expression and the microbial genus abundance identified 57 genes as having significant correlation with the ileum microbial genera ( P < 0.0001). Of these, three genes showed significant association with six microbial genera: lysozyme 2 ( LYZ2), fatty acid binding protein 5 ( FABP5), and fucosyltransferase (FUT1). Specifically, the profound increase in expression of LYZ2 in treated calves suggests the initiation of antibacterial activity and innate response from the host. Despite the limitation of a relatively small sample size, this study sheds light on the potential impact of early introduction of microbes on the small intestine of calves.
Published: 2020

41. Assessment of Sexual Reproductive Health Knowledge Amongst Patients with Cystic Fibrosis

Author: D. Lau, Lorraine Speight, Andrea Edwards, R.I. Ketchell, Jamie Duckers, and C. Wilson
Subjects: medicine.medical_specialty, business.industry, Genetic counseling, media_common.quotation_subject, Rehabilitation, Physical Therapy, Sports Therapy and Rehabilitation, Fertility, Carrier testing, Quality of life (healthcare), Family medicine, Life expectancy, Medicine, Anxiety, Thematic analysis, medicine.symptom, business, Reproductive health, media_common
Abstract: This study is concerned with evaluating cystic fibrosis (CF) annual review practice. More precisely, we wanted to know if we are utilizing genetic counseling services and identifying poor knowledge of sexual reproductive health at annual review. We conducted short interviews with 21 CF patients at annual review regarding genetic counseling knowledge and perception. Patient responses were documented, analyzed and coded using a simple thematic analysis to precis the content. Immediately post-interview, patients were asked to complete a CF questionnaire comprised of nine questions, testing knowledge of the science of Mendelian genetics, contraceptive needs and fertility. Knowledge was then compared to responses documented at annual review. Emerging themes from interviews included: poor knowledge and a need for more information regarding what genetic counseling involves, a positive perception and experience of genetic counseling for those who had attended, and partner anxiety related to carrier testing. The percentage of patients who reported they were aware of the CF fertility and genetic issues was 95%, however, questionnaire scores ranged from 0 to 9/9 (mean 4.8 SD [2.2]). 57% of patients had received genetic counseling. These patients had a statistically significantly higher score 6.2 (1.5) versus those who had not 2.9 (1.3) p
Published: 2019
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42. Changes in meta-transcriptome of rumen epimural microbial community and liver transcriptome in young calves with feed induced acidosis

Author: Wenli Li, Sonia Gelsinger, Christina Riehle, Andrea Edwards, and Daniel J. Koch
Subjects: Rumen, Pyruvate metabolic process, lcsh:Medicine, Physiology, Biology, Article, Transcriptome, medicine, Animals, Weaning, lcsh:Science, Dairy cattle, Acidosis, Multidisciplinary, lcsh:R, Lipid metabolism, Genomics, Animal Feed, Gastrointestinal Microbiome, Disease Models, Animal, Cellular component organization, Liver, Cattle, lcsh:Q, Gene expression, medicine.symptom
Abstract: The common management practices of dairy calves leads to increased starch concentration in feed, which subsequently may cause rumen acidosis while on milk and during weaning. Until recently, few attempts were undertaken to understand the health risks of prolonged ruminal acidosis in post weaning calves. Resultantly, the molecular changes in the digestive tracts in post-weaning calves with ruminal acidosis remain largely unexplored. In this study, we investigated the liver transcriptome changes along with its correlation with the rumen microbial rRNA expression changes in young calves using our model of feed induced ruminal acidosis. In this model, new born calves were fed a highly processed, starch-rich diet starting from one week of age through 16 weeks. A total of eight calves were involved in this study. Four of them were fed the acidosis-inducing diet (Treated) and the rest of the four were fed a standard starter diet (Control). Liver and rumen epithelial tissues were collected at necropsy at 17 weeks of age. Transcriptome analyses were carried out in the liver tissues and rRNA meta-transcriptome analysis were done using the rumen epithelial tissues. The correlation analysis was performed by comparing the liver mRNA expression with the rumen epithelial rRNA abundance at genus level. Calves with induced ruminal acidosis had significantly lower ruminal pH in comparison to the control group, in addition to significantly less weight-gain over the course of the experiment. In liver tissues, a total of 428 differentially expressed genes (DEGs) (fold-change, FC ≥ 1.5; adjusted P ≤ 0.1) were identified in treated group in comparison to control. Biological pathways enriched by these DEGs included cellular component organization, indicating the impact of ruminal acidosis on liver development in young calves. Specifically, the up-regulated genes were enriched in acute phase response (P P P ≪ 0.001), indicating the liver’s response to feed induced acidosis at the transcriptome level. Twelve transferase activity related genes had significant correlation with rumen microbial rRNA expression changes. Among these genes, two up-regulated genes were reported with involvement in lipid metabolism in the liver, implying the direct effect of feed-induced acidosis on both the rumen microbial community and liver metabolism. Our study provides insight into the physiological remodeling in the liver resultant from the prolonged acidosis in post weaning calves, which may facilitate future RNA-seq based diagnosis and precision management of rumen acidosis in dairy calves.
Published: 2019
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43. Identification of Single Nucleotide Polymorphism in Red Clover (Trifolium pratense L.) Using Targeted Genomic Amplicon Sequencing and RNA-seq

Author: Randy D. Dinkins, Andrea Edwards, Heathcliffe Riday, Christina Riehle, and Wenli Li
Subjects: 0106 biological sciences, 0301 basic medicine, Genomics, Single-nucleotide polymorphism, RNA-Seq, Plant Science, Biology, lcsh:Plant culture, 01 natural sciences, Genome, self-incompatibility, DNA sequencing, 03 medical and health sciences, lcsh:SB1-1110, Original Research, Genetics, food and beverages, targeted amplicon sequencing, single-nucleotide polymorphism, biology.organism_classification, Medicago truncatula, Red Clover, 030104 developmental biology, red clover, Pentatricopeptide repeat, RNA-seq, 010606 plant biology & botany
Abstract: Red clover (Trifolium pratense L.) is a diploid, naturally cross-pollinated, cool-season species. As a perennial forage legume, red clover is mostly cultivated in temperate regions worldwide. Being a non-model crop species, genomic resources for red clover have been underdeveloped. Thus far, genomic analysis used in red clover has mainly relied on simple sequence repeat (SSR) markers. However, SSR markers are sparse in the genome and it is often difficult to unambiguously map them using short reads generated by next generation sequencing technology. Single nucleotide polymorphisms (SNPs) have been successfully applied in genomics assisted breeding in several agriculturally important species. Due to increasing importance of legumes in forage production, there is a clear need to develop SNP based markers for red clover that can be applied in breeding applications. In this study, we first developed an analytical pipeline that can confidently identify SNPs in a set of 72 different red clover genotypes using sequences generated by targeted amplicon sequencing. Then, with the same filtering stringency used in this pipeline, we used sequences from publicly available RNA-seq data to identify confident SNPs in different red clover varieties. Using this strategy, we have identified a total of 67,975 SNPs across red clover varieties. Among these, 28% (19,116) of them are missense mutations. Using Medicago truncatula as the reference, we annotated the regions affected by these missense mutations. We identified 2,909 protein coding regions with missense mutations. Pathway analysis of these coding regions indicated several biological processes impacted by these mutations. Specifically, three domains (homeobox domain, pentatricopeptide repeat containing plant-like, and regulator of Vps4 activity) were identified with five or more missense SNPs. These domain might also be a functional contributor in the molecular mechanisms of self-incompatibility in red clover. Future in-depth sequence diversity analysis of these three genes may yield valuable insights into the molecular mechanism involved in self-incompatibility in red clover.
Published: 2019
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44. Transcriptome analysis of rumen epithelium and meta-transcriptome analysis of rumen epimural microbial community in young calves with feed induced acidosis

Author: Sonia Gelsinger, Wenli Li, Andrea Edwards, Daniel J. Koch, and Christina Riehle
Subjects: 0301 basic medicine, Rumen, animal structures, lcsh:Medicine, Weaning, Biology, Weight Gain, Article, Epithelium, Transcriptome, 03 medical and health sciences, 0302 clinical medicine, Animal science, medicine, Animals, lcsh:Science, Dairy cattle, Acidosis, Multidisciplinary, Gene Expression Profiling, Microbiota, lcsh:R, Age Factors, Hydrogen-Ion Concentration, Animal Feed, 030104 developmental biology, medicine.anatomical_structure, Microbial population biology, lcsh:Q, Cattle, medicine.symptom, Weight gain, 030217 neurology & neurosurgery
Abstract: Many common management practices used to raise dairy calves while on milk and during weaning can cause rumen acidosis. Ruminal pH has long been used to identify ruminal acidosis. However, few attempts were undertaken to understand the role of prolonged ruminal acidosis on rumen microbial community or host health in young calves long after weaning. Thus, the molecular changes associated with prolonged rumen acidosis in post weaning young calves are largely unknown. In this study, we induced ruminal acidosis by feeding a highly processed, starch-rich diet to calves starting from one week of age through 16 weeks. Rumen epithelial tissues were collected at necropsy at 17 weeks of age. Transcriptome analyses on the rumen epithelium and meta-transcriptome analysis of rumen epimural microbial communities were carried out. Calves with induced ruminal acidosis showed significantly less weight gain over the course of the experiment, in addition to substantially lower ruminal pH in comparison to the control group. For rumen epithelial transcriptome, a total of 672 genes (fold-change, FC ≥ 1.5; adjusted-p ≤ 0.05) showed significant differential expression in comparison to control. Biological pathways impacted by these differentially expressed genes included cell signaling and morphogenesis, indicating the impact of ruminal acidosis on rumen epithelium development. rRNA read-based microbial classification indicated significant increase in abundance of several genera in calves with induced acidosis. Our study provides insight into host rumen transcriptome changes associated with prolonged acidosis in post weaning calves. Shifts in microbial species abundance are promising for microbial species-based biomarker development and artificial manipulation. Such knowledge provides a foundation for future more precise diagnosis and preventative management of rumen acidosis in dairy calves.
Published: 2019
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45. svdPPCS: an effective singular value decomposition-based method for conserved and divergent co-expression gene module identification.

Author: Wensheng Zhang 0005, Andrea Edwards, Wei Fan 0001, Dongxiao Zhu, and Kun Zhang 0012
Published: 2010
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46. Transcriptomics analysis of host liver and meta-transcriptome analysis of rumen epimural microbial community in young calves treated with artificial dosing of rumen content from adult donor cow

Author: Madison S. Cox, Andrew J. Steinberger, Andrea Edwards, Joseph H. Skarlupka, Derek M. Bickhart, Jason G. Walling, Christina Riehle, S.M. Raabis, Wenli Li, and Garret Suen
Subjects: 0301 basic medicine, Rumen, lcsh:Medicine, Biology, Article, Bacterial genetics, Microbiology, Transcriptome, 03 medical and health sciences, 0302 clinical medicine, Animals, Colonization, Microbiome, Author Correction, lcsh:Science, Bacterial phyla, Phylogeny, Aldehyde-Lyases, Multidisciplinary, Bacteria, Whole Genome Sequencing, Sequence Analysis, RNA, Host (biology), Gene Expression Profiling, lcsh:R, Animal Feed, Up-Regulation, RNA, Bacterial, 030104 developmental biology, Liver, Microbial population biology, RNA, Ribosomal, Cattle, lcsh:Q, Metagenomics, 030217 neurology & neurosurgery
Abstract: In mammals, microbial colonization of the digestive tract (GIT) occurs right after birth by several bacterial phyla. Numerous human and mouse studies have reported the importance of early gut microbial inhabitants on host health. However, few attempts have been undertaken to directly interrogate the role of early gut/rumen microbial colonization on GIT development or host health in neonatal ruminants through artificial manipulation of the rumen microbiome. Thus, the molecular changes associated with bacterial colonization are largely unknown in cattle. In this study, we dosed young calves with exogenous rumen fluid obtained from an adult donor cow, starting at birth, and repeated every other week until six weeks of age. Eight Holstein bull calves were included in this study and were separated into two groups of four: the first group was treated with rumen content freshly extracted from an adult cow, and the second group was treated with sterilized rumen content. Using whole-transcriptome RNA-sequencing, we investigated the transcriptional changes in the host liver, which is a major metabolic organ and vital to the calf’s growth performance. Additionally, the comparison of rumen epimural microbial communities between the treatment groups was performed using the rRNA reads generated by sequencing. Liver transcriptome changes were enriched with genes involved in cell signaling and protein phosphorylation. Specifically, up-regulation of SGPL1 suggests a potential increase in the metabolism of sphingolipids, an essential molecular signal for bacterial survival in digestive tracts. Notably, eight genera, belonging to four phyla, had significant increases in abundance in treated calves. Our study provides insight into host liver transcriptome changes associated with early colonization of the microbial communities in neonatal calves. Such knowledge provides a foundation for future probiotics-based research in microbial organism mediated rumen development and nutrition in ruminants.
Published: 2019
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47. CSTG: An Effective Framework for Cost-sensitive Sparse Online Learning

Author: Zhong Chen, Kun Zhang, Zhide Fang, Andrea Edwards, and Wei Fan
Subjects: Computer science, Data stream mining, business.industry, Online learning, Cost sensitive, Regret, Extension (predicate logic), Machine learning, computer.software_genre, Article, Sparse learning, Convex optimization, Artificial intelligence, Baseline (configuration management), business, computer
Abstract: Sparse online learning and cost-sensitive learning are two important areas of machine learning and data mining research. Each has been well studied with many interesting algorithms developed. However, very limited published work addresses the joint study of these two fields. In this paper, to tackle the high-dimensional data streams with skewed distributions, we introduce a framework of cost-sensitive sparse online learning. Our proposed framework is a substantial extension of the influential Truncated Gradient (TG) method by formulating a new convex optimization problem, where the two mutual restraint factors, misclassification cost and sparsity, can be simultaneously and favorably balanced. We theoretically analyze the regret and cost bounds of the proposed algorithm, and pinpoint its theoretical merit compared to the existing related approaches. Large-scale empirical comparisons to five baseline methods on eight real-world streaming datasets demonstrate the encouraging performance of the developed method. Algorithm implementation and datasets are available upon request.
Published: 2018

48. Author Correction: Transcriptomics analysis of host liver and meta-transcriptome analysis of rumen epimural microbial community in young calves treated with artificial dosing of rumen content from adult donor cow

Author: Wenli Li, Andrea Edwards, Christina Riehle, Madison S. Cox, Sarah Raabis, Joseph H. Skarlupka, Andrew J. Steinberger, Jason Walling, Derek Bickhart, and Garret Suen
Subjects: Multidisciplinary, lcsh:R, ComputingMethodologies_DOCUMENTANDTEXTPROCESSING, lcsh:Medicine, lcsh:Q, lcsh:Science
Abstract: A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.
Published: 2019
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49. A Fan-tastic Alternative to Bulbs: Learning Circuits with Fans

Author: Robert Ekey, Andrea Edwards, Roy McCullough, William Reitz, and Brandon Mitchell
Subjects: 0103 physical sciences, 05 social sciences, 050301 education, General Physics and Astronomy, 010306 general physics, 0503 education, 01 natural sciences, Education
Published: 2017
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50. Racial disparities in patient survival and tumor mutation burden, and the association between tumor mutation burden and cancer incidence rate

Author: Erik K. Flemington, Wensheng Zhang, Andrea Edwards, and Kun Zhang
Subjects: 0301 basic medicine, Oncology, medicine.medical_specialty, Pathology, Tumor incidence, lcsh:Medicine, Article, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, Neoplasms, Epidemiology, medicine, Humans, In patient, lcsh:Science, Socioeconomic status, Survival analysis, Genetic Association Studies, Multidisciplinary, business.industry, Incidence, lcsh:R, Racial Groups, medicine.disease, Head and neck squamous-cell carcinoma, Obesity, Survival Analysis, 3. Good health, 030104 developmental biology, 030220 oncology & carcinogenesis, Mutation, Adenocarcinoma, lcsh:Q, business, SEER Program
Abstract: The causes underlying racial disparities in cancer are multifactorial. In addition to socioeconomic issues, biological factors may contribute to these inequities, especially in disease incidence and patient survival. To date, there have been few studies that relate the disparities in these aspects to genetic aberrations. In this work, we studied the impacts of race on the patient survival and tumor mutation burden using the data released by the Cancer Genome Atlas (TCGA). The potential relationship between mutation burden and disease incidence is further inferred by an integrative analysis of TCGA data and the data from the Surveillance, Epidemiology, and End Results (SEER) Program. The results show that disparities are present (p r = 0.46, p r = 0.88, p
Published: 2017

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