bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effectiveness of BNT162b2 and ChAdOx1 vaccines against symptomatic COVID-19 among Healthcare Workers in Kuwait: A retrospective cohort study
Authors: Alali Walid Q. , Ali Lamiaa A. , AlSeaidan Mohammad , Al-Rashidi Mohammad 
Published: July 2021

AbstractBackgroundThe COVID-19 BNT162b2 vaccination roll-out in Kuwait started on 24 December 2020 followed by ChAdOx1 on 3 February 2021. The study objectives were to assess the factors associated with vaccine coverage and determine vaccine effectiveness (VE) against SARS-CoV-2 infection in a healthcare worker (HCW) population.MethodsThis retrospective cohort study was conducted among HCW working at a public secondary hospital in Kuwait. The follow-up period was from 24 December 2020 to 15 June 2021. The primary outcomes were vaccine coverage and PCR-confirmed SARS-CoV-2 infection for the VE analysis. Data on new SARS-CoV-2 infections (with or without symptoms) during study period in addition to HCWs characteristics (sex, age, nationality, and occupation) were extracted from the hospital records. The vaccine coverage and PCR-confirmed SARS-CoV-2 infections were cross-tabulated by the HCWs characteristics. Furthermore, we used Cox regression to estimate time-to-infection hazard ratios in vaccinated (first and second dose) compared to unvaccinated HCWs. Only one ChAdOx1 dose was given during the study period.ResultsThere were 3246 HCWs included in the analysis. The median age was 38 years (IQR = 33 - 44), 63.4% were females, 46.8% aged 31-40, and 82.3% were non-Kuwaitis. Overall, 82.1% of HCWs received at least one vaccine dose (50.4% received only one dose of ChAdOx1, 3.3% received one dose of BNT162b2, and 28.3% received two doses of BNT162b2). 17.9% of HCWs remained unvaccinated by the end of the study. A significantly lower vaccination coverage percentage was amongst female HCWs, younger age group (20 – 30 years old), and administrative/executive staff. Symptomatic SARS-CoV-2 PCR-confirmed infection prevalence was 7.3%. No asymptomatic infections were reported. The SARS-CoV-2 infection incidence rate was 126 per 100,000 person-days in the unvaccinated group; whereas, the incidence rates in the partially vaccinated groups (≥ 28 days after ChAdOx1 first dose) and (≥ 14 days after receiving BNT162b2 through receipt of second dose) were 31.4 and 10.9 per 100,000 person-days, respectively. In the fully vaccinated group (≥ 14 days after BNT162b2 second dose), the incidence rate was 6.3 per 100,000 person-days. The estimated adjusted vaccine effectiveness of fully vaccinated was 94.5% (95% confidence interval [CI] = 89.4%–97.2%). The VE of partially vaccinated for ChAdOx1 and BNT162b2 was 75.4% (95% CI = 67.2%–81.6%) and 91.4% (95% CI = 65.1%–97.9%), respectively.ConclusionsBoth BNT162b2 and ChAdOx1 vaccines prevented most symptomatic infections in this population across age groups, nationalities, and occupations. A significant proportion (17.9%) of HCWs were unvaccinated despite the vaccine accessibility. The findings complement other VE studies and demonstrate the vaccine benefit among HCWs.
Parent attitudes about childhood vaccines: a vaccine hesitancy point prevalence study
Authors: Marshall Sarah , Moore Anne C , Sahm Laura J , Fleming Aoife 
Published: July 2021

AbstractObjectivesThe aim of this study was to measure the prevalence of vaccine hesitancy using Parent Attitudes about Childhood Vaccines (PACV) survey regarding paediatric vaccines for their children, in a population of parents attending a STEM (Science, Technology, Engineering and Mathematics) outreach event in Cork, Ireland.Study designCross-sectional survey study.MethodsThis study was conducted in November 2018 at the “Community Festival of Science” STEM event. Eligible attendees were invited to read the participant information leaflet, provide written informed consent, and complete the validated Parent Attitudes about Childhood Vaccines (PACV) survey. Each of the 15 PACV survey items was scored. A score ≥50 identified vaccine hesitant parents.ResultsA total of 105 parents participated in the study. A small number of participants (6.7%, n = 7) were identified as vaccine hesitant. There were no statistically significant differences between the vaccine hesitant and non-hesitant groups based on age, education, or number of children. Parents had concerns around vaccine side effects (36.2%, n=38) and vaccine safety (20%, n=21). Parents trusted the information they received on vaccines (85.6%, n=90) and 81.9% (n=86) believed that the vaccine schedule was good for their child.ConclusionsThe findings of this research indicate the presence of vaccine hesitancy in parents in Ireland regarding paediatric vaccines. Parents had concerns regarding vaccine side effects and the number of vaccines on the paediatric immunisation schedule. Further research is necessary to understand how these issues may contribute to vaccine hesitancy, and to develop evidence-based interventions to build on parents existing trust in the vaccination schedule.Key pointsA low level of vaccine hesitancy regarding childhood vaccinations was reported in a sample of parents at a science outreach event in Ireland using the PACV survey.Areas of parents’ concerns were around vaccine side effects and number of vaccines.Most parents trusted their doctors regarding vaccines, trusted vaccines information and followed the vaccine schedule.The PACV survey could be used as a screening tool to identify vaccine hesitant parents by healthcare providers and provide them with additional information and support, to support public health vaccination campaigns.
Tracking Cryptic SARS-CoV-2 Lineages Detected in NYC Wastewater
Authors: Smyth Davida S. , Trujillo Monica , Gregory Devon A. , Cheung Kristen , Gao Anna , Graham Maddie , Guan Yue , Guldenpfennig Caitlyn , Hoxie Irene , Kannoly Sherin , Kubota Nanami , Lyddon Terri D. , Markman Michelle , Rushford Clayton , San Kaung Myat , Sompanya Geena , Spagnolo Fabrizio , Suarez Reinier , Teixeiro Emma , Daniels Mark , Johnson Marc C. , Dennehy John J. 
Published: July 2021

AbstractTracking SARS-CoV-2 genetic diversity is strongly indicated because diversifying selection may lead to the emergence of novel variants resistant to naturally acquired or vaccine-induced immunity. To monitor New York City (NYC) for the presence of novel variants, we amplified regions of the SARS-CoV-2 Spike protein gene from RNA acquired from all 14 NYC wastewater treatment plants (WWTPs) and ascertained the diversity of lineages from these samples using high throughput sequencing. Here we report the detection and increasing frequencies of novel SARS-CoV-2 lineages not recognized in GISAID’s EpiCoV database. These lineages contain mutations rarely observed in clinical samples, including Q493K, Q498Y, H519N and T572N. Many of these mutations were found to expand the tropism of SARS-CoV-2 pseudoviruses by allowing infection of cells expressing the human, mouse, or rat ACE2 receptor. In addition, pseudoviruses containing the Spike amino acid sequence of these lineages were found to be resistant to many different classes of receptor binding domain (RBD) binding neutralizing monoclonal antibodies. We offer several hypotheses for the anomalous presence of these mutations, including the possibility of a non-human animal reservoir. Although wastewater sampling cannot provide direct inference of SARS-CoV-2 clinical sequences, our research revealed several lineages that could be relevant to public health and they would not have been discovered if not for wastewater surveillance.
Wastewater surveillance for infectious disease: a systematic review
Authors: Kilaru Pruthvi , Hill Dustin , Anderson Kathryn , Collins Mary B. , Green Hyatt , Kmush Brittany L. , Larsen David A. 
Published: July 2021

AbstractWastewater surveillance of SARS-CoV-2 has shown to be a valuable source of information regarding SARS-CoV-2 transmission and COVID-19 cases. Though the method has been used for several decades to track other infectious diseases, there has not been a comprehensive review outlining all of the pathogens surveilled through wastewater. The aim of this study is to identify what infectious diseases have been previously studied via wastewater surveillance prior to the COVID-19 Pandemic and identify common characteristics between the studies, as well as identify current gaps in knowledge. Peer-reviewed articles published as of August 1, 2020 that examined wastewater for communicable and infectious human pathogens on 2 or more occasions were included in the study. Excluded from this list were all reviews and methods papers, single collection studies, and non-human pathogens. Infectious diseases and pathogens were identified in studies of wastewater surveillance, as well as themes of how wastewater surveillance and other measures of disease transmission were linked. This review did not include any numerical data from individual studies and thus no statistical analysis was done. 1005 articles were identified but only 100 were included in this review after applying the inclusion criteria. These studies came from 38 countries with concentration in certain countries including Italy, Israel, Brazil, Japan, and China. Twenty-five separate pathogen families were identified in the included studies, with the majority of studies examining pathogens from the family Picornaviridae, including polio and non-polio enteroviruses. Most studies of wastewater surveillance did not link what was found in the wastewater to other measures of disease transmission. Among those studies that did compare wastewater surveillance to other measures of disease transmission the value observed was dependent upon pathogen and varied by study. Wastewater surveillance has historically been used to assess water-borne and fecal-orally transmitted pathogens causing diarrheal disease. However, numerous other types of pathogens have been surveilled using wastewater and wastewater surveillance should be considered as a potential tool for many infectious diseases. Wastewater surveillance studies can be improved by incorporating other measures of disease transmission at the population-level including disease incidence and hospitalizations.
Small Patient Datasets Reveal Genetic Drivers of Non-Small Cell Lung Cancer Subtypes Using a Novel Machine Learning Approach
Authors: Moses Cook , Bessi Qorri , Amruth Baskar , Jalal Ziauddin , Luca Pani , Shashibushan Yenkanchi , Geraci Joseph 
Published: July 2021

AbstractBackgroundThere are many small datasets of significant value in the medical space that are being underutilized. Due to the heterogeneity of complex disorders found in oncology, systems capable of discovering patient subpopulations while elucidating etiologies is of great value as it can indicate leads for innovative drug discovery and development.Materials and MethodsHere, we report on a machine intelligence-based study that utilized a combination of two small non-small cell lung cancer (NSCLC) datasets consisting of 58 samples of adenocarcinoma (ADC) and squamous cell carcinoma (SCC) and 45 samples (GSE18842). Utilizing a set of standard machine learning (ML) methods which are described in this paper, we were able to uncover subpopulations of ADC and SCC while simultaneously extracting which genes, in combination, were significantly involved in defining the subpopulations. We also utilized a proprietary interactive hypothesis-generating method designed to work with machine learning methods, which provided us with an alternative way of pinpointing the most important combination of variables. The discovered gene expression variables were used to train ML models. This allowed us to create methods using standard methods and to also validate our in-house methods for heterogeneous patient populations, as is often found in oncology.ResultsUsing these methods, we were able to uncover genes implicated by other methods and accurately discover known subpopulations without being asked, such as different levels of aggressiveness within the SCC and ADC subtypes. Furthermore, PIGX was a novel gene implicated in this study that warrants further study due to its role in breast cancer proliferation.ConclusionHere we demonstrate the ability to learn from small datasets and reveal well-established properties of NSCLC. This demonstrates the utility for machine learning techniques to reveal potential genes of interest, even from small data sets, and thus the driving factors behind subpopulations of patients.
Short Report –Consumption of multiple sources of protein is associated with gestational diabetes mellitus in the Chinese population
Authors: Wang Wei-Qin , Chiang Vic Shao-Chih , Wen Jing-Yuan , Hu Ji-Fen , Xu Rong-Xian 
Published: July 2021

AbstractBackgroundGestational diabetes mellitus (GDM) is a hyperglycemic state during pregnancy that results in disruptions of insulin sensitivity and secretion. It affects 7% of all pregnancies and lead to adverse maternal and offspring outcomes. GDM has many risk factors, such as ethnicity special, hereditary. However Nutritional factors offer key strategies against GDM, but this is less characterized for the Chinese population.MethodsA case control study of GDM pregnant women (n=49, 29.88±3.92 years of age) and healthy pregnant women (n=77, 27.63±4.83 years of age) from 1st Affiliated Hospital of Fujian Medical University were studied. Diagnosis was made using oral glucose tolerance test. Dietary data were collected using food frequency questionnaires. Data for use of dietary supplements, occupation, education, income, meal expenditure and smoking history were also recorded.ResultsNo differences were found between GDM and control subjects for their age, education, occupation, monthly income, grocery expenditure and smoking (p>0.05). GDM subjects were associated with higher quantities of dairy products (p<0.05) and seafood (p<0.01) intake. There were also higher number of GDM subjects using protein powder supplementation (p<0.05).ConclusionsDietary recommendation guidelines for pregnant Chinese women should consider possible risks with excessive consumption of dairy products, seafood and protein powder. They should also assess the quality of the nutrition factor, other dietary interactions and their nutritional status further to minimize adverse outcomes caused by GDM.
Genetic and neurophysiological biomarkers of neuroplasticity inform post-stroke language recovery
Authors: Dresang Haley C. , Harvey Denise Y. , Shah-Basak Priyanka P. , DeLoretta Laura , Wurzman Rachel , Parchure Shreya Y. , Sacchetti Daniela , Faseyitan Olufunsho , Lohoff Falk W. , Hamilton Roy H. 
Published: July 2021

AbstractBackgroundThere is high variability in post-stroke aphasia severity and predicting recovery remains imprecise. Standard prognostics do not include neurophysiological indicators or genetic biomarkers of neuroplasticity, which may be critical sources of variability.ObjectiveTo evaluate whether a common polymorphism (Val66Met) in the gene for brain-derived neurotrophic factor (BDNF) contributes to variability in post-stroke language recovery, and to assess whether BDNF polymorphism interacts with neurophysiological indicators of neuroplasticity to improve estimates of aphasia severity.MethodsSaliva samples and motor-evoked potentials (MEPs) were collected from participants with chronic aphasia subsequent to left-hemisphere stroke. MEPs were collected prior to continuous theta burst stimulation (cTBS; index for cortical excitability) and 10 minutes following cTBS (index for stimulation-induced neuroplasticity) to the left primary motor cortex. Analyses assessed the extent to which BDNF polymorphism interacted with cortical excitability and stimulation-induced neuroplasticity to predict aphasia severity beyond established predictors.ResultsVal66Val carriers showed less aphasia severity than Met allele carriers, after controlling for lesion volume and time post-stroke. Furthermore, Val66Val carriers showed expected effects of age on aphasia severity, and positive associations between both cortical excitability and stimulation-induced neuroplasticity and severity. In contrast, Met allele carriers showed weaker effects of age and negative associations between cortical excitability, stimulation-induced neuroplasticity and aphasia severity.ConclusionsNeurophysiological indicators and genetic biomarkers of neuroplasticity improved ability to predict aphasia severity. Furthermore, BDNF polymorphism interacted with cortical excitability and stimulation-induced neuroplasticity to improve predictions. These findings provide novel insights into mechanisms of variability in stroke recovery and may improve aphasia prognostics.
The Vaccination Threshold for SARS-CoV-2 Depends on the Indoor Setting and Room Ventilation
Authors: Mikszewski A. , Stabile L. , Buonanno G. , Morawska L. 
Published: July 2021

AbstractBackgroundEffective vaccines are now available for SARS-CoV-2 in the second year of the COVID-19 pandemic, but there remains significant uncertainty surrounding the necessary vaccination rate to safely lift occupancy controls in public buildings and return to pre-pandemic norms. The aim of this paper is to estimate setting-specific vaccination thresholds for SARS-CoV-2 to prevent sustained community transmission using classical principles of airborne contagion modeling. We calculated the airborne infection risk in three settings, a classroom, prison cell block, and restaurant, at typical ventilation rates, and then the expected number of infections resulting from this risk at varying levels of occupant susceptibility to infection.ResultsWe estimate the vaccination threshold for control of SARS-CoV-2 to range from a low of 40% for a mechanically ventilation classroom to a high of 85% for a naturally ventilated restaurant.ConclusionsIf vaccination rates are limited to a theoretical minimum of approximately two-thirds of the population, enhanced ventilation above minimum standards for acceptable air quality is needed to reduce the frequency and severity of SARS-CoV-2 superspreading events in high-risk indoor environments.
Uncovering the Bromodomain Interactome using Site-Specific Azide-Acetyllysine Photochemistry, Proteomic Profiling and Structural Characterization
Authors: Wagner Shana , Fedorov Elena , Sudhamalla Babu , Jnawali Hum Nath , Debiec Ronald , Ghosh Agnidipta , Islam Kabirul 
Published: July 2021

AbstractProtein-protein interactions mediated by acetyllysines and bromodomains are essential for the regulation of eukaryotic gene expression. Diagramming the bromodomain interactome network and molecular characterization of these interactions are key to unraveling context-dependent signaling pathways. Herein, we employ a chemoproteomic platform, called interaction-based protein profiling (IBPP), to map the acetylome of the bromodomain and extra terminal domain (BET) family of bromodomains. We developed photo-responsive bromodomain analogues to carry out UV light-induced azide-acetyllysine crosslinking within the recognition cavity of the domain to capture transient interacting partners present in human cells. Subsequent proteomic and biochemical analyses lead to the identification of an array of acetylated interacting factors, which extend the potential function of BET family proteins beyond transcription. We present here eight high-resolution crystal structures of interactome-bound bromodomains that underscore the atypical binding modes and sequence motifs by which BET members recognize an expanded repertoire of acetylated proteins. In addition, we report an acetyllysine-dependent interaction between BRD4 and interleukin enhancer binding factor 3 (ILF3) in human cells, and uncover its role in recruiting transcriptional regulators to the promoter of the Survivin gene, an anti-apoptotic factor overexpressed in a wide range of human neoplasia. Collectively, our work provides a blueprint for engineering bromodomains, establishes IBPP as a robust chemoproteomic tool to characterize bromodomain interactome, and reveals distinctive recognition modes by which such associations may take place in order to modulate signaling pathways. Furthermore, these structural snapshots offer clues to design specific small-molecule inhibitors against the novel BET interactions and paves the path for exploring the biological significance of this newly identified signaling network.
Early Life Adversity in Male Mice Sculpts Reward Circuits
Authors: Wendel Kara M. , Short Annabel K. , Noarbe Brenda P. , Haddad Elizabeth , Palma Anton M. , Yassa Michael A. , Baram Tallie Z. , Obenaus Andre 
Published: July 2021

AbstractEarly life adversity (ELA) comprises a wide variety of negative experiences during early life and has been linked to cognitive impairments, reduced experiences of pleasure (anhedonia), and other long-term consequences implying that ELA impacts the reward circuitry. In this study, we focused on the projections from the dorsal raphe (DR) to the ventral tegmental area (VTA) and on to the nucleus accumbens (NAcc), an important pathway within the reward circuit. We hypothesized that ELA alters connectivity within the DR-VTA- NAcc pathway, manifested behaviorally as anhedonia in adulthood. We used the limited bedding and nesting model to induce ELA in mice and measured reward-related behaviors in adulthood using the three-chamber social interaction and sucrose preference tests. High resolution ex vivo diffusion tensor imaging (DTI) was acquired and processed for regional DTI metrics, including tractography to assess circuit organization. We found brain-wide changes in radial diffusivity (RD) and altered connectivity of the reward circuit in the ELA group. DR-VTA-NAcc circuit tractography and axial diffusivity (AD) along this tract exhibited dispersed organization where AD was increased in the VTA segment. Behaviorally, ELA elicited an anhedonic phenotype in adulthood with decreased direct social approach and time spent with peer but no overt differences in sucrose preference test. Our findings suggest that reward circuits, assessed using DTI, are altered following ELA and that these changes may drive enduring reward deficits.
Estimating dispersal using close kin dyads: The kindisperse R package
Authors: Jasper Moshe E , Hoffmann Ary A , Schmidt Thomas L 
Published: July 2021

AbstractInvestigating dispersal in animal populations can be difficult, particularly for taxa that are hard to directly observe such as those that are small or rare. A promising solution may come from new approaches that use genome-wide sequence data to detect close kin dyads and estimate dispersal parameters from the distribution of these dyads. These methods have so far only been applied to mosquito populations. However, they should have broad applicability to a range of taxa, although no assessment has yet been made on their performance under different dispersal conditions and study designs. Here we develop an R package and Shiny app, kindisperse, that can be used to estimate dispersal parameters from the spatial distribution of close kin. Kindisperse can handle study designs that target different life stages and allows for a range of dispersal kernel shapes and organismal life histories; we provide implementation examples for a vertebrate (Antechinus) and an invertebrate (Aedes). We use simulations run in kindisperse to compare the performance of two published close kin methodologies, showing that one method produces unbiased estimates whereas the other produces downward-biased estimates. We also use kindisperse simulations to investigate how study design affects dispersal estimates, and we provide guidelines for the size and shape of sample sites as well as the number of close kin needed for accurate estimates. kindisperse is easily adaptable for application to a variety of research contexts ranging from invasive pests to threatened species where non-invasive DNA sampling can be used to detect close kin.