bluuebunny/crossref_metadata_2025_split huggingface dataset:
RESEARCH PROTOCOL: Large-scale evidence generation and evaluation across a network of databases for type 2 diabetes mellitus
Authors: Khera Rohan , Scheumie Martijn J , Lu Yuan , Ostropolets Anna , Chen Ruijun , Hripcsak George , Ryan Patrick B , Krumholz Harlan M , Suchard Marc A 
Published: September 2021

AbstractBackgroundTherapeutic options for type 2 diabetes mellitus (T2DM) have expanded over the last decade with the emergence of sodium-glucose co-transporter-2 (SGLT2) inhibitors and glucagon-like peptide-1 (GLP1) receptor agonists, which reduced the risk of major cardiovascular events in randomized controlled trials (RCTs). Cardiovascular evidence for older second-line agents, such as sulfonylureas, and direct head-to-head comparisons, including with dipeptidyl peptidase 4 (DPP4) inhibitors, are lacking, leaving a critical gap in our understanding of the relative effects of T2DM agents on cardiovascular risk and on patient-centered safety outcomes.Methods and AnalysisThe Large-Scale Evidence Generations Across a Network of Databases for T2DM (LEGEND-T2DM) initiative is a series of systematic, large-scale, multinational, real-world comparative cardiovascular effectiveness and safety studies of all 4 major second-line anti-hyperglycemic agents including SGLT2 inhibitor, GLP1 receptor agonist, DPP4 inhibitor and sulfonylureas. LEGEND-T2DM will leverage the Observational Health Data Science and Informatics (OHDSI) community that provides access to a global network of administrative claims and electronic health record (EHR) data sources. Committed data partners represent 190 million patients in the US and about 50 million internationally. LEGEND-T2DM will identify all adult, T2DM patients who newly initiate a traditionally second-line T2DM agent, including individuals with and without established cardiovascular disease. Using an active comparator, new-user cohort design, LEGEND-T2DM will execute all pairwise class-vs-class and drug-vs-drug comparisons in each data source that meet a minimum patient count of 1,000 per arm and extensive study diagnostics that assess reliability and generalizability through cohort balance and equipoise to examine the relative risk of cardiovascular and safety outcomes. The primary cardiovascular outcomes include a 3-point and a 4-point composite of major adverse cardiovascular events, and series of safety outcomes. The study will pursue data-driven, large-scale propensity adjustment for measured confounding, a large set of negative control outcome experiments to address unmeasured and systematic bias.Ethics and DisseminationThe study ensures data safety through a federated analytic approach and follows research best practices, including prespecification and full disclosure of hypotheses tested and their results. LEGEND-T2DM is dedicated to open science and transparency and will publicly share all our analytic code from reproducible cohort definitions through turn-key software, enabling other research groups to leverage our methods, data, and results in order to verify and extend our findings.
Understanding the evidence for climate concerns, negative emotions and climate-related mental ill-health in young people: a scoping review
Authors: Ramadan Reem , Randell Alicia , Lavoie Suzie , Gao Caroline X , Manrique Paula Cruz , Anderson Rebekah , Zbukvic Isabel 
Published: September 2021

ABSTRACTBackgroundHuman-induced climate change represents a serious threat to human health, including mental health, due to both the traumatising effects of extreme climate events and the psychological effect of worry about climate change. The present scoping review aims to systematically search and synthesise original research related to mental health and climate related concerns, negative emotions and mental ill-health in young people. Findings will help to understand the current landscape, gaps in the literature, and to provide recommendations for future youth mental health research and practice.MethodsA systematic search and narrative synthesis of the literature published prior to October 2020 examining negative emotions associated with climate change in young people was undertaken. Studies were included if they examined mental ill-health (e.g. symptoms of depression or anxiety) or negative emotions (e.g. distress, worry, concern) associated with the threat of climate change.FindingsOf the 3329 peer-reviewed articles screened, 12 met the inclusion criteria. Together, included studies show that young people are worried about climate change. Studies also explored the coping strategies young people use to manage their distress caused by climate change.InterpretationsThe limited literature in this area indicates a key gap in youth mental health research. Available evidence suggests that young people are concerned about climate change, which may increase risk of mental ill-health. Thus, clinicians should assess for and address climate anxiety in young people. Mental health leaders are urged to advocate for urgent climate action to mitigate the effects of climate anxiety in young people.Fundingthis project was not funded.
A Novel Retinal Vascular Feature and Machine Learning-based Brain White Matter Lesion Prediction Model
Authors: Bhuiyan Alauddin , Roy Pallab Kanti , Bhuiyan Tasin , Storey Elsdon , Abhayaratna Walter P , Dhamoon Mandip , Smith R. Theodore , Ramamohanarao Kotagiri 
Published: September 2021

AbstractWhite matter lesion (WML) is one of the common cerebral abnormalities, it indicates changes in the white matter of human brain and have shown significant association with stroke, dementia and deaths. Magnetic resonance imaging (MRI) of the brain is frequently used to diagnose white matter lesion (WML) volume. Regular screening can detect WML in early stage and save from severe consequences. Current option of MRI based diagnosis is impractical for regular screening because of its high expense and unavailability. Thus, earlier screening and prediction of the WML volume/load specially in the rural and remote areas becomes extremely difficult. Research has shown that changes in the retinal micro vascular system reflect changes in the cerebral micro vascular system. Using this information, we have proposed a retinal image based WML volume and severity prediction model which is very convenient and easy to operate.Our proposed model can help the physicians to detect the patients who need immediate and further MRI based detail diagnosis of WML. Our model uses quantified measurement of retinal micro-vascular signs (such as arteriovenular nicking (AVN), Opacity (OP) and focal arteriolar narrowing (FAN)) as input and estimate the WML volume/load and classify its severity. We evaluate our proposed model on a dataset of 111 patients taken from the ENVISion study which have retinal and MRI images for each patient. Our model shows high accuracy in estimating the WML volume, mean square error (MSE) between our predicted WML load and manually annotated WML load is 0.15. The proposed model achieves an F1 score of 0.92 in classifying the patients having mild and severe WML load.The preliminary results of our study indicate that quantified measurement of retinal micro-vascular features (AVN, OP and FAN) can more accurately identify the patients who have high risk of cardio-vascular diseases and dementia.
Calibrating an SIR model for South Korea COVID-19 infections and predicting vaccination impact
Authors: Pae Brandon 
Published: September 2021

AbstractIn the span of 1.5 years, COVID-19 has caused more than 4 million deaths worldwide. To prevent such a catastrophe from reoccurring, it is necessary to test and refine current epidemiological models that impact policy decisions. Thus, we developed a deterministic SIR model to examine the long-term transmission dynamics of COVID-19 in South Korea. Using this model, we analyzed how vaccines would affect the number of cases. We found that a 70% vaccination coverage with a 100% effective vaccine would effectively eliminate the number of cases and herd immunity would have been obtained approximately 85 days after February 15 had there not been a reintroduction of cases.
Mental Health Concerns Related to the COVID-19 Pandemic on Twitter in the UK
Authors: Zhang Daiwei , Liu Yue , Zhang Senqi , Sun Li , Li Pin , Anand Ajay , Xie Zidian , Li Dongmei 
Published: September 2021

AbstractBackgroundAmid the COVID-19 pandemic, mental health-related symptoms (such as depression and anxiety) have been actively mentioned on social media.ObjectiveIn this study, we aimed to monitor mental health concerns on Twitter during the COVID-19 pandemic in the United Kingdom (UK), and assess the potential impact of the COVID-19 pandemic on mental health concerns of Twitter users.MethodsWe collected COVID-19 and mental health-related tweets from the UK between March 5, 2020 and January 31, 2021 through the Twitter Streaming API. We conducted topic modeling using Latent Dirichlet Allocation model to examine discussions about mental health concerns. Deep learning algorithms including Face++ were used to infer the demographic characteristics (age and gender) of Twitter users who expressed mental health concerns related to the COVID-19 pandemic.ResultsWe showed a positive correlation between COVID-19-related mental health concerns on Twitter and the severity of the COVID-19 pandemic in the UK. Geographic analysis showed that populated urban areas have a higher proportion of Twitter users with mental health concerns compared to England as a whole. Topic modeling showed that general concerns, COVID-19 skeptics, and Death toll were the top topics discussed in mental health-related tweets. Demographic analysis showed that middle-aged and older adults might be more likely to suffer from mental health issues or express their mental health concerns on Twitter during the COVID-19 pandemic.ConclusionsThe COVID-19 pandemic has noticeable effects on mental health concerns on Twitter in the UK, which varied among demographic and geographic groups.
Preoperative optimisation in fast-track and enhanced recovery after surgery (ERAS) programs for total hip and knee joint replacement: a systematic review protocol
Authors: Chang Wei-Ju , Naylor Justine , Liu Victor , Monuja Masiath , Adie Sam 
Published: September 2021

ABSTRACTIntroductionEmerging evidence suggests that fast-track and enhanced recovery after surgery (ERAS) targeting modifiable risk factors reduce complications after total hip (THR) and knee replacement (TKR). However, what constitutes an effective preoperative optimisation protocol for THR and TKR remains unclear. The aims are to: (1) describe pre-operative optimisation protocols for THR and TKR; (2) evaluate the effects of pre-operative optimisation protocols for THR and TKR on morbidity, and patient-reported outcomes.Methods and analysisSystematic review and meta-analysis. Electronic databases will be searched using pre-determined search terms to identify relevant studies and evaluate the study eligibility and risks of bias. Two independent reviewers will select the eligible studies and any disagreement will be resolved through a third reviewer. We will include studies investigated pre-operative optimisation protocols administered prior to participants receiving primary THR or TKR to improve post-operative outcomes. Primary outcomes are hospital readmission, complications and patient-reported pain and function. Risk of bias will be assessed using the Cochrane RoB 1 tool and strength of evidence will be examined using the GRADE approach. Pre-operative optimisation protocols will be summarised qualitatively. Meta-analyses on the effects of included protocols will be conducted if appropriate.Ethics and disseminationThis systematic review does not require ethics approval. The findings will be disseminated in a peer-reviewed journal and presented at relevant conferences.RegistrationThis protocol has been submitted to the International Prospective Register of Systematic Reviews on 30 August 2021.ARTICLE SUMMARYStrength and LimitationsThis systematic review aims to describe pre-operative optimisation protocols for total hip and knee replacement and to synthesise evidence for the effects of pre-operative optimisation protocols on hospital readmission, complications and patient-reported outcomes.Two independent reviewers will conduct study selection, data extraction and risk of bias assessment.Meta-analyses, sub-group and sensitivity analyses will be performed where appropriate.
SARS-Cov-2 Infection versus Vaccine-Induced Immunity among Veterans
Authors: Young-Xu Yinong , Smith Jeremy , Korves Caroline 
Published: September 2021

AbstractBackgroundWith over 40 million cases of SARS-CoV-2 infection reported in the US and discussion of both vaccine mandates as well as boosters ongoing, we aim to examine protection conferred by previous infection compared with vaccination so that citizens and policy makers can make informed decisions.ObjectivesTo compare mRNA COVID-19 vaccine-induced immunity against immunity induced by previous infection with SARS-CoV-2 between June and August 2021 when the Delta variant became dominant in the US.We conducted a retrospective observational study comparing two groups whose incident vaccination or infection occurred within the first two months of 2021: (1) SARS-CoV-2-naive individuals who received a full mRNA vaccination - 2 doses of either Pfizer or Moderna vaccine, (2) newly infected individuals who were subdivided into those have not been vaccinated and those have been vaccinated after their infection. Matched multivariable Cox proportional hazards model was applied. We evaluated laboratory (RT-PCR) confirmed SARS-CoV-2 infection during follow-up, COVID-related hospitalization, and deaths.SettingVeterans Health Administration (VHA).Main outcomesPositive SARS-CoV-2 PCR test, COVID-related hospitalization, and deaths. Protection was estimated from hazard ratios with 95% confidence intervals (CI).ResultsA total of 9,539 patients with SARS-CoV-2 infection during the first two months of 2021 were matched to 14,458 and 23,105 patients fully vaccinated with Moderna and Pfizer mRNA vaccines, during the same two months. 3,917 (41%) of patients with SARS-CoV-2 infection were subsequently vaccinated. We plan to study this group separately. Consequently, protections were estimated among those with infection but were not subsequently vaccinated and those vaccinated with a mRNA vaccine. Among seniors, Moderna and Pfizer mRNA vaccines offered stronger protection against infection, lowering the risk by an additional 66% [HR: 0.34 (95% CI, 0.14-0.78)] and 68% [HR: 0.32 (95% CI, 0.14-0.70)]; stronger protection against hospitalization, lowering the risk by an additional 61% [HR: 0.34 (95% CI, 0.14-0.78)] and 45% [HR: 0.34 (95% CI, 0.14-0.78)]; and stronger protection against deaths lowering the risk by an additional 95% [HR: 0.05 (95% CI, 0.004-0.62)] and 99% [HR: 0.01 (95% CI, 0.001-0.44)]. Among young adults (age < 65), the protections offered by vaccines were statistically equivalent to that provided by previous infection, especially in terms of absolute incidence rate.ConclusionsAmong the elderly (age 65 or older), two-dose mRNA vaccines provided stronger protection against infection, hospitalization, and death, compared to natural immunity. Among young adults (age < 65), the protections offered between natural immunity and vaccine-induced immunity were similar.
The effects of communicating uncertainty around statistics on public trust: an international study
Authors: Kerr John R. , van der Bles Anne Marthe , Schneider Claudia , Dryhurst Sarah , Chopurian Vivien , Freeman Alexandra L.J. , van der Linden Sander 
Published: September 2021

AbstractA growing body of research indicates that transparent communication of statistical uncertainty around facts and figures does not undermine credibility. However, the extent to which these findings apply in the context of the COVID-19 pandemic—rife with uncertainties—is unclear. In a large international survey experiment, (Study 1;N= 10,519) we report that communicating uncertainty around COVID-19 statistics in the form of a numeric range (vs. no uncertainty) may lead to slightly lower trust in the number presented but has no impact on trust in the source of the information. We also report the minimal impact of numeric uncertainty on trust is consistent across estimates of current or future COVID-19 statistics (Study 2) and figures relating to environmental or economic research, rather than the pandemic (Study 3). Conversely, we find imprecise statements about the mere existence of uncertainty without quantification can undermine both trust in the numbers and their source – though effects vary across countries and contexts. Communicators can be transparent about statistical uncertainty without concerns about undermining perceptions of their trustworthiness, but ideally should aim to use numerical ranges rather than verbal statements.
Comammox Nitrospira bacteria outnumber canonical nitrifiers irrespective of nitrogen source and availability
Authors: Vilardi Katherine J. , Cotto Irmarie , Rivera Maria Sevillano , Dai Zihan , Anderson Christopher L. , Pinto Ameet 
Published: September 2021

AbstractComplete ammonia oxidizing bacteria coexist with canonical ammonia and nitrite oxidizing bacteria in a wide range of environments. Whether this is due to competitive or cooperative interactions, or a result of niche separation is not yet clear. Understanding the factors driving coexistence of nitrifiers is critical to manage nitrification processes occurring in engineered and natural ecosystems. In this study, microcosm-based experiments were used to investigate the impact of nitrogen source and loading on the population dynamics of nitrifiers in drinking water biofilter media. Shotgun sequencing of DNA followed by co-assembly and reconstruction of metagenome assembled genomes revealed clade A2 comammox bacteria were likely the primary nitrifiers within microcosms and increased in abundance over Nitrsomonas-like ammonia and Nitrospira-like nitrite oxidizing bacteria irrespective of nitrogen source type or loading. Changes in comammox bacterial abundance did not correlate with either ammonia or nitrite oxidizing bacterial abundance in urea amended systems where metabolic reconstruction indicated potential for cross feeding between ammonia and nitrite oxidizing bacteria. In contrast, comammox bacterial abundance demonstrated a negative correlation with nitrite oxidizers in ammonia amended systems. This suggests potentially weaker synergistic relationships between ammonia and nitrite oxidizers might enable comammox bacteria to displace nitrite oxidizers from complex nitrifying communities.
MNPmApp: An image analysis tool to quantify mononuclear phagocyte distribution in mucosal tissuesa, b
Authors: Potts Catherine , Schearer Julia , Bair Dominic , Ayler Becky , Love Jordan , Dankoff Jennifer , Harris Paul R. , Zosso Dominique , Bimczok Diane 
Published: September 2021

AbstractMononuclear phagocytes (MNPs) such as dendritic cells and macrophages perform key sentinel functions in mucosal tissues and are responsible for inducing and maintaining adaptive immune responses to mucosal pathogens. Positioning of MNPs at the mucosal epithelial interface facilitates their access to luminally-derived antigens and may regulate MNP function through soluble mediators or surface receptor interactions. Therefore, accurately quantifying the distribution of MNPs within mucosal tissues as well as their spatial relationship with other cells is important to infer functional cellular interactions in health and disease. In this study, we developed and validated a MATLAB-based tissue cytometry platform, termed “MNP mapping application” (MNPmApp), that performs high throughput analyses of MNP density and distribution in the gastrointestinal mucosa based on digital multicolor fluorescence microscopy images and that integrates a Monte Carlo modeling feature to assess randomness of MNP distribution. MNPmApp identified MNPs in tissue sections of the human gastric mucosa with a specificity of 98.3 ± 1.6% and a sensitivity of 76.4 ± 15.1%. Monte Carlo modeling revealed that mean MNP-MNP distances were significantly lower than anticipated based on random cell placement, whereas MNP-epithelial distances did not significantly differ from those of randomly placed cells. Interestingly, H. pylori infection had no significant impact on MNP density or distribution with regards to MNP-epithelial distances or MNP-MNP distances in gastric tissue. Overall, our analysis demonstrates that MNPmApp is a useful tool for unbiased quantitation of MNPs and their distribution at mucosal sites.
Milk casein prevents inactivation effect of black tea galloylated theaflavins on SARS-CoV-2 in vitro
Authors: Ohgitani Eriko , Shin-Ya Masaharu , Ichitani Masaki , Kobayashi Makoto , Takihara Takanobu , Saito Motoki , Kinugasa Hitoshi , Mazda Osam 
Published: September 2021

AbstractRepeated emergence of highly contagious and potentially immune-evading variant SARS-CoV-2 is posing global health and socioeconomical threats. For suppression of the spread of the virus infection among people, a procedure to inactivate virus in saliva may be useful, because saliva of infected persons is the major origin of droplets and aerosols that mediate viral transmission to nearby persons. We previously reported that SARS-CoV-2 is rapidly and remarkably inactivated by treatment in vitro with tea including green tea, roasted green tea, oolong tea and black tea. Tea catechin-derived compounds including theaflavins (TFs) with (a) galloyl moiety(ies) showed this activity. Although black tea is popularly consumed worldwide, a lot of people consume it with sugar, milk, lemon juice, and so on. But it has not been determined whether these ingredients may influence the inactivation effect of black tea against SARS-CoV-2. Moreover, it has not been revealed whether black tea is capable of inactivating variant viruses such as delta variant. Here we examined the effect of black tea on some variants in the presence or absence of sugar, milk, and lemon juice in vitro. Black tea and galloylated TFs remarkably inactivated alpha, gamma, delta and kappa variants. Intriguingly, an addition of milk but not sugar and lemon juice totally prevented black tea from inactivating alpha and delta variant viruses. The suppressive effect was also exerted by milk casein. These results suggest the possibility that intake of black tea without milk by infected persons may result in inactivation of the virus in saliva and attenuation of spread of SARS-CoV-2 to nearby persons through droplets. Clinical studies are required to investigate this possibility.