bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pandemic-response adenoviral vector and RNA vaccine manufacturing
Authors: Kis Zoltán , Tak Kyungjae , Ibrahim Dauda , Papathanasiou Maria M , Chachuat Benoît , Shah Nilay , Kontoravdi Cleo 
Published: September 2021

AbstractRapid global COVID-19 pandemic response by mass vaccination is currently limited by the rate of vaccine manufacturing. This study presents a techno-economic feasibility assessment and comparison of three vaccine production platform technologies deployed during the COVID-19 pandemic: (1) adenovirus-vectored (AVV) vaccines, (2) messenger RNA (mRNA) vaccines, and (3) the newer self-amplifying RNA (saRNA) vaccines. Besides assessing the baseline performance of the production process, the impact of key design and operational uncertainties on the productivity and cost performance of these vaccine platforms were also evaluated using variance-based global sensitivity analysis. Cost and resource requirement projections were also computed for manufacturing multi-billion vaccine doses for covering the current global demand shortage and for providing annual booster immunizations. This model-based assessment provides key insights to policymakers and vaccine manufacturers for risk analysis, asset utilisation, directions for future technology improvements and future epidemic/pandemic preparedness, given the disease-agnostic nature of these vaccine production platforms.
Pharmacokinetic /Pharmacodynamic Considerations of Alternate Dosing Strategies of Tocilizumab in COVID-19
Authors: Leung Elizabeth , Jorgensen Sarah C.J. , Crass Ryan L. , Raybardhan Sumit , Langford Bradley , Moore W. Justin , Rhodes Nathaniel J. 
Published: September 2021

AbstractTocilizumab is one of few treatments that have been shown to improve mortality in patients with COVID-19, but increased demand has led to relative global shortages. Recently, it has been suggested that lower doses, or fixed doses, of tocilizumab could be a potential solution to conserve the limited global supply while conferring equivalent therapeutic benefit to the dosing regimens studied in major trials. The relationship between tocilizumab dose, exposure, and response in COVID-19 has not been adequately characterized. There are a number of pharmacokinetic (PK) parameters which likely differ between patients with severe COVID-19 and patients in whom tocilizumab was studied during the FDA approval process. Likewise, it is unclear whether a threshold exposure is necessary for tocilizumab efficacy. The safety and efficacy of fixed versus weight-based dosing of tocilizumab has been evaluated outside of COVID-19, but it is uncertain if these observations are generalizable to severe or critical COVID-19. In the current review, we consider the potential advantages and limitations of alternative tocilizumab dosing strategies. Leveraging PK models and simulation analyses, we demonstrate that a fixed single dose of tocilizumab 400 mg is unlikely to produce PK exposures equivalent to those achieved in the REMAP-CAP trial, though weight-stratified dosing appears to produce more uniform exposure distribution. Data from current and future trials could provide PK/PD insight to better inform dosing strategies at the bedside. Ultimately, rational dosing strategies that balance available limited supply with patient needs are required.
Computational methods for the discovery and annotation of viral integrations
Authors: Palatini Umberto , Pischedda Elisa , Bonizzoni Mariangela 
Published: September 2021

AbstractThe transfer of genetic material between viruses and eukaryotic cells is pervasive. Somatic integrations of DNA viruses and retroviruses have been linked to persistent viral infection and genotoxic effects. Integrations into germline cells, referred to as Endogenous Viral Elements (EVEs), can be co-opted for host functions. Besides DNA viruses and retroviruses, EVEs can also derive from nonretroviral RNA viruses, which have often been observed in piRNA clusters. Here, we describe a bioinformatic framework to annotate EVEs in a genome assembly, study their widespread occurrence and polymorphism and identify sample-specific viral integrations using whole-genome sequencing data.
Longitudinal analysis of SARS-CoV-2 vaccine breakthrough infections reveal limited infectious virus shedding and restricted tissue distribution
Authors: Ke Ruian , Martinez Pamela P. , Smith Rebecca L. , Gibson Laura L. , Achenbach Chad J. , McFall Sally , Qi Chao , Jacob Joshua , Dembele Etienne , Bundy Camille , Simons Lacy M. , Ozer Egon A. , Hultquist Judd F. , Lorenzo-Redondo Ramon , Opdycke Anita K. , Hawkins Claudia , Murphy Robert L. , Mirza Agha , Conte Madison , Gallagher Nicholas , Luo Chun Huai , Jarrett Junko , Conte Abigail , Zhou Ruifeng , Farjo Mireille , Rendon Gloria , Fields Christopher J. , Wang Leyi , Fredrickson Richard , Baughman Melinda E. , Chiu Karen K. , Choi Hannah , Scardina Kevin R. , Owens Alyssa N. , Broach John , Barton Bruce , Lazar Peter , Robinson Matthew L. , Mostafa Heba H. , Manabe Yukari C. , Pekosz Andrew , McManus David D. , Brooke Christopher B. 
Published: September 2021

ABSTRACTThe global effort to vaccinate people against SARS-CoV-2 in the midst of an ongoing pandemic has raised questions about the nature of vaccine breakthrough infections and the potential for vaccinated individuals to transmit the virus. These questions have become even more urgent as new variants of concern with enhanced transmissibility, such as Delta, continue to emerge. To shed light on how vaccine breakthrough infections compare with infections in immunologically naive individuals, we examined viral dynamics and infectious virus shedding through daily longitudinal sampling in a small cohort of adults infected with SARS-CoV-2 at varying stages of vaccination. The durations of both infectious virus shedding and symptoms were significantly reduced in vaccinated individuals compared with unvaccinated individuals. We also observed that breakthrough infections are associated with strong tissue compartmentalization and are only detectable in saliva in some cases. These data indicate that vaccination shortens the duration of time of high transmission potential, minimizes symptom duration, and may restrict tissue dissemination.
Prostate cancer risk stratification via non-destructive 3D pathology with annotation-free gland segmentation and analysis
Authors: Xie W. , Reder N.P. , Koyuncu C. , Leo P. , Hawley S. , Huang H. , Mao C. , Postupna N. , Kang S. , Serafin R. , Gao G. , Han Q. , Bishop K.W. , Barner L.A. , Fu P. , Wright J.L. , Keene C.D. , Vaughan J.C. , Janowczyk A. , Glaser A.K. , Madabhushi A. , True L.D. , Liu J.T.C. 
Published: September 2021

AbstractProstate cancer treatment planning is largely dependent upon examination of core-needle biopsies. In current clinical practice, the microscopic architecture of the prostate glands is what forms the basis for prognostic grading by pathologists. Interpretation of these convoluted 3D glandular structures via visual inspection of a limited number of 2D histology sections is often unreliable, which contributes to the under- and over-treatment of patients. To improve risk assessment and treatment decisions, we have developed a workflow for non-destructive 3D pathology and computational analysis of whole prostate biopsies labeled with a rapid and inexpensive fluorescent analog of standard H&E staining. Our analysis is based on interpretable glandular features, and is facilitated by the development of image-translation-assisted segmentation in 3D (ITAS3D). ITAS3D is a generalizable deep-learning-based strategy that enables tissue microstructures to be volumetrically segmented in an annotation-free and objective (biomarker-based) manner without requiring real immunolabeling. To provide evidence of the translational value of a computational 3D pathology approach, we analyzed ex vivo biopsies (n = 300) extracted from archived radical-prostatectomy specimens (N = 50), and found that 3D glandular features are superior to corresponding 2D features for risk stratification of low-to intermediate-risk PCa patients based on their clinical biochemical recurrence (BCR) outcomes.SignificanceWe present an end-to-end pipeline for computational 3D pathology of whole prostate biopsies, showing that non-destructive pathology has the potential to enable superior prognostic stratification for guiding critical oncology decisions.
Unique plasma metabolite signature for adolescents with Klinefelter syndrome reveals altered fatty acid metabolism
Authors: Davis Shanlee M , Urban Rhianna , D’Alessandro Angelo , Haines Julie , Chan Christine , Kelsey Megan , Howell Susan , Tartaglia Nicole , Zeitler Philip , Baker Peter 
Published: September 2021

AbstractConditions related to cardiometabolic disease, including metabolic syndrome and type 2 diabetes, are common among men with Klinefelter syndrome (KS).The molecular mechanisms underlying this aberrant metabolism in KS are largely unknown, although there is an assumption that chronic testosterone deficiency plays a role. This cross-sectional study compared plasma metabolites in 31 pubertal adolescent males with KS to 32 controls of similar age (14 ± 2 yrs), pubertal stage, and body mass index z-score (0.1 ± 1.2), and then between testosterone treated (n=16) and untreated males with KS. The plasma metabolome in males with KS was distinctly different from controls, with 22% of measured metabolites having a differential abundance and seven metabolites nearly completely separating KS from controls (AUC>0.9, p<0.0001). Multiple saturated free fatty acids were higher in KS while mono- and polyunsaturated fatty acids were lower, and the top significantly enriched pathway was mitochondrial ß-oxidation of long-chain saturated fatty acids (enrichment ratio 16, p<0.0001). In contrast, there were no observed differences in metabolite concentrations between testosterone-treated and untreated individuals with KS. In conclusion, the plasma metabolome profile in adolescent males with KS is distinctly different from males without KS independent of age, obesity, pubertal development, or testosterone treatment status, and is suggestive of differences in mitochondrial ß-oxidation.
Fine analysis of lymphocyte subpopulations in SARS-CoV-2 infected patients: toward a differential profiling of patients with severe outcome
Authors: Clavarino Giovanna , Leroy Corentin , Epaulard Olivier , Raskovalova Tatiana , Vilotitch Antoine , Pernollet Martine , Dumestre-Pérard Chantal , Defendi Federica , Le Marechal Marion , Le Gouellec Audrey , Audoin Pierre , Bosson Jean-Luc , Poignard Pascal , Roustit Matthieu , Jacob Marie-Christine , Cesbron Jean-Yves 
Published: September 2021

AbstractCOVID-19 is caused by the human pathogen severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and has resulted in widespread morbidity and mortality. CD4+ T cells, CD8+ T cells and neutralizing antibodies all contribute to control SARS-CoV-2 infection. However, heterogeneity is a major factor in disease severity and in immune innate and adaptive responses to SARS-CoV-2. We performed a deep analysis by flow cytometry of lymphocyte populations of 125 hospitalized SARS-CoV-2 infected patients on the day of hospital admission. Five clusters of patients were identified using hierarchical classification on the basis of their immunophenotypic profile, with different mortality outcomes. Some characteristics were observed in all the clusters of patients, such as lymphopenia and an elevated level of effector CD8+CCR7- T cells. However, low levels of T cell activation are associated to a better disease outcome; on the other hand, profound CD8+ T-cell lymphopenia, a high level of CD4+ and CD8+ T-cell activation and a high level of CD8+ T-cell senescence are associated with a higher mortality outcome. Furthermore, a cluster of patient was characterized by high B-cell responses with an extremely high level of plasmablasts. Our study points out the prognostic value of lymphocyte parameters such as T-cell activation and senescence and strengthen the interest in treating the patients early in course of the disease with targeted immunomodulatory therapies based on the type of adaptive response of each patient.
How varying intervention, vaccination, mutation and ethnic conditions affect COVID-19 resurgence
Authors: Cao Longbing , Liu Qing 
Published: September 2021

ABSTRACTAfter a year of the unprecedented COVID-19 pandemic in 2020, the world has been overwhelmed by COVID-19 resurgences and virus mutations up to today. Here we develop a dynamic intervention, vaccination and mutation-driven epidemiological model with sequential interventions influencing epidemiological compartments and their state transition. We quantify epidemiological differences between waves under fatal viral mutations, the impacts of control or relaxation interventions and fatal virus mutations on resurgence under vaccinated or unvaccinated conditions, and estimate potential trends under varying interventions and mutations. Comprehensive analyses - between waves, with or without vaccinations, across representative countries with distinct ethnic and cultural backgrounds, what-if scenario simulations on second waves, and future 30-day trend - in two COVID-19 waves in Germany, France, Italy, Israel and Japan over 2020 and 2021 obtain quantitative empirical indication of the influence of strong vs. weak interventions, various combinations of control vs. relaxation strategies, and different transmissibility levels of coronavirus mutants on the behaviors and patterns of different waves and resurgences and future infection trends. The analyses quantify that (1) virus mutations, intervention fatigue, early relaxations, and lagging interventions, etc. may be common reasons for the resurgences observed in many countries; (2) timely strong interventions such as full lockdown will contain resurgence; (3) some resurgences relating to fatal mutants could have been better contained by either carrying forward the effective interventions from their early waves or implementing better controls and timing; (4) insufficient evidence is found on distinguishing the infection between unvaccinated and vaccinated countries while substantial vaccinations ensure much low mortality rate and high recovery rate; (5) resurgences with substantial vaccination have a much lower mortality rate and a higher recovery rate than those without vaccination; and (6) in the absence of sufficient vaccination, herd immunity and effective antiviral pharmaceutical treatments and with more infectious mutations, the widespread early or fast relaxation of interventions including public activity restrictions likely result in a COVID-19 resurgence. We also find the severity, number and timing of control and relaxation interventions determines a protection-deconfinement tradeoff, which can be used to evaluate the containment effect and the opportunity of resurgence and reopening under vaccination and fatal mutations.
Consensus molecular subtype differences linking colon adenocarcinoma and obesity revealed by a cohort transcriptomic analysis
Authors: Greene Michael W. , Abraham Peter T. , Kuhlers Peyton C. , Lipke Elizabeth A. , Heslin Martin J. , Wijaya Stanley T. , Odeniyi Ifeoluwa 
Published: September 2021

AbstractBackgroundColorectal cancer (CRC) is the third-leading cause of cancer-related deaths in the United States and worldwide. Obesity - a worldwide public health concern - is a known risk factor for cancer including CRC. However, the mechanisms underlying the link between CRC and obesity have yet to be fully elucidated in part because of the molecular heterogeneity of CRC. We hypothesized that obesity modulates CRC in a consensus molecular subtype (CMS)-dependent manner.MethodsRNA-seq data and associated tumor and patient characteristics including body weight and height data for 232 patients were obtained from The Cancer Genomic Atlas – Colon Adenocarcinoma (TCGA-COAD) database. Tumor samples were classified into the four CMSs with the CMScaller R package; Body mass index (BMI) was calculated and categorized as normal, overweight, and obese.ResultsWe observed a significant difference in CMS categorization between BMI categories. Differentially expressed genes (DEGs) between obese and overweight samples and normal samples differed across the CMSs, and associated prognostic analyses indicated that the DEGs had differing effects on survival. Using Gene Set Enrichment Analysis, we found differences in Hallmark gene set enrichment between obese and overweight samples and normal samples across the CMSs. We constructed Protein-Protein Interaction networks and observed differences in obesity-regulated hub genes for each CMS. Finally, we analyzed and found differences in predicted drug sensitivity between obese and overweight samples and normal samples across the CMSs.ConclusionsThus, we conclude that obesity has CMS-specific effects on the CRC tumor transcriptome.
Estimation of Vaccine Efficacy for Variants that Emerge After the Placebo Group Is Vaccinated
Authors: Follmann Dean , Fay Michael , Magaret Craig , Gilbert Peter 
Published: September 2021

SummarySARS-CoV-2 continues to evolve and the vaccine efficacy against variants is challenging to estimate. It is now common in phase III vaccine trials to provide vaccine to those randomized to placebo once efficacy has been demonstrated, precluding a direct assessment of placebo controlled vaccine efficacy after placebo vaccination. In this work we extend methods developed for estimating vaccine efficacy post placebo vaccination to allow variant specific time varying vaccine efficacy, where time is measured since vaccination. The key idea is to infer counterfactual strain specific placebo case counts by using surveillance data that provide the proportions of the different strains. This blending of clinical trial and observational data allows estimation of strain-specific time varying vaccine efficacy, or sieve effects, including for strains that emergent after placebo vaccination. The key requirements are that surveillance strain distribution accurately reflect the strain distribution for a placebo group, throughout follow-up after placebo group vaccination and that at least one strain is present before and after placebo vaccination. For illustration, we develop a Poisson approach for an idealized design under a rare disease assumption and then use a proportional hazards modeling to better reflect the complexities of field trials with staggered entry, crossover, and smoothly varying strain specific vaccine efficacy We evaluate these by theoretical work and simulations, and demonstrate that useful estimation of the efficacy profile is possible for strains that emerge after vaccination of the placebo group. An important principle is to incorporate sensitivity analyses to guard against mis-specfication of the strain distribution. We also provide an approach for use when genotyping of the infecting strains of the trial participants has not been done.
The association between influenza vaccination, all-cause mortality and cardiovascular mortality: a protocol for a living systematic review and prospective meta-analysis
Authors: Liu Rong , Patel Anushka , Du Xin , Liu Hueiming , Liu Bette , Wang Chi , Di Tanna Gian Luca 
Published: September 2021

AbstractIntroductionInfluenza virus infection is known to increase the risk of cardiovascular events, especially in populations with pre-existing cardiovascular disease. Considering that influenza is vaccine preventable, international guidelines recommend high-risk populations with CVD receive an influenza vaccine every year, but there are various classifications of recommendations and levels of evidence. Previous systematic reviews concluded uncertain evidence on influenza vaccine efficacy for preventing cardiovascular events in the general population or in populations with pre-existing CVD. Limited safety data of influenza vaccines were reported for populations with pre-existing CVD. Randomized control trials with larger sample sizes relative to previous studies are emerging, the findings of these trials are likely to be highly influential on summary efficacy estimates.Methods and analysisWe aim to perform a living systematic review and a prospective meta-analysis to evaluate the efficacy and safety of influenza vaccines compared to no vaccines or placebo for preventing mortality or cardiovascular disease events in the general population and in populations with pre-existing CVD.Ethics and disseminationFormal ethical review is not required as this study does not need primary data collection. We will publish results of the living systematic review and prospective meta-analysis in a peer-reviewed journal. Findings will also be presented at relevant meetings.PROSPERO registration numberCRD42021222519.Strengths and limitations of this studyThe living systematic review will continually incorporate the latest research findings and keep the synthesized information updated. A prospective meta-analysis will better address this evolving evidence.Safety of influenza vaccines in populations with pre-existing cardiovascular diseases will be studied in particular to complete the current evidence base.Observational studies may affect the overall quality of the study results. We will stratify the analysis by study design and present both randomized and non-randomized results.
Variant abundance estimation for SARS-CoV-2 in wastewater using RNA-Seq quantification
Authors: Baaijens Jasmijn A. , Zulli Alessandro , Ott Isabel M. , Petrone Mary E. , Alpert Tara , Fauver Joseph R. , Kalinich Chaney C. , Vogels Chantal B.F. , Breban Mallery I. , Duvallet Claire , McElroy Kyle , Ghaeli Newsha , Imakaev Maxim , Mckenzie-Bennett Malaika , Robison Keith , Plocik Alex , Schilling Rebecca , Pierson Martha , Littlefield Rebecca , Spencer Michelle , Simen Birgitte B. ,   Yale SARS-CoV-2 Genomic Surveillance Initiative, Hanage William P. , Grubaugh Nathan D. , Peccia Jordan , Baym Michael 
Published: September 2021

AbstractEffectively monitoring the spread of SARS-CoV-2 variants is essential to efforts to counter the ongoing pandemic. Wastewater monitoring of SARS-CoV-2 RNA has proven an effective and efficient technique to approximate COVID-19 case rates in the population. Predicting variant abundances from wastewater, however, is technically challenging. Here we show that by sequencing SARS-CoV-2 RNA in wastewater and applying computational techniques initially used for RNA-Seq quantification, we can estimate the abundance of variants in wastewater samples. We show by sequencing samples from wastewater and clinical isolates in Connecticut U.S.A. between January and April 2021 that the temporal dynamics of variant strains broadly correspond. We further show that this technique can be used with other wastewater sequencing techniques by expanding to samples taken across the United States in a similar timeframe. We find high variability in signal among individual samples, and limited ability to detect the presence of variants with clinical frequencies <10%; nevertheless, the overall trends match what we observed from sequencing clinical samples. Thus, while clinical sequencing remains a more sensitive technique for population surveillance, wastewater sequencing can be used to monitor trends in variant prevalence in situations where clinical sequencing is unavailable or impractical.