bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development and validation of an enzyme immunoassay for detection and quantification of SARS-CoV-2 salivary IgA and IgG
Authors: Costantini Veronica P. , Nguyen Kenny , Lyski Zoe , Novosad Shannon , Bardossy Ana C. , Lyons Amanda K. , Gable Paige , Kutty Preeta K. , Lutgring Joseph D. , Brunton Amanda , Thornburg Natalie , Brown Allison C. , McDonald L. Clifford , Messer William , Vinjé Jan 
Published: September 2021

ABSTRACTOral fluids offer a non-invasive sampling method for the detection of antibodies. Quantification of IgA and IgG antibodies in saliva allows studies of the mucosal and systemic immune response after natural infection or vaccination. We developed and validated an enzyme immunoassay (EIA) to detect and quantify salivary IgA and IgG antibodies against the prefusion-stabilized form of the SARS-CoV-2 spike protein. Normalization against total antibody isotype was performed to account for specimen differences, such as collection time and sample volume. Saliva samples collected from 187 SARS-CoV-2 confirmed cases enrolled in 2 cohorts and 373 pre-pandemic saliva samples were tested. The sensitivity of both EIAs was high (IgA: 95.5%; IgG: 89.7%) without compromising specificity (IgA: 99%; IgG: 97%). No cross reactivity with seasonal coronaviruses was observed. The limit of detection for SARS-CoV-2 salivary IgA and IgG assays were 1.98 ng/mL and 0.30 ng/mL, respectively. Salivary IgA and IgG antibodies were detected earlier in patients with mild COVID-19 symptoms than in severe cases. However, severe cases showed higher salivary antibody titers than those with a mild infection. Salivary IgA titers quickly decreased after 6 weeks in mild cases but remained detectable until at least week 10 in severe cases. Salivary IgG titers remained high for all patients, regardless of disease severity. In conclusion, EIAs for both IgA and IgG had high specificity and sensitivity for the confirmation of current or recent SARS-CoV-2 infections and evaluation of the IgA and IgG immune response.
Suicide and self-harm in low- and middle- income countries during the COVID-19 pandemic: A systematic review
Authors: Knipe Duleeka , John Ann , Padmanathan Prianka , Eyles Emily , Dekel Dana , Higgins Julian PT , Bantjes Jason , Dandona Rakhi , Macleod-Hall Catherine , McGuinness Luke A , Schmidt Lena , Webb Roger T , Gunnell David 
Published: September 2021

AbstractThere is widespread concern over the potential impact of the COVID-19 pandemic on suicide and self-harm globally, particularly in low- and middle-income countries (LMIC) where the burden of these behaviours is greatest. We synthesised the evidence from the published literature on the impact of the pandemic on suicide and self-harm in LMIC.This review is nested within a living systematic review that continuously identifies published evidence (all languages) through a comprehensive automated search of multiple databases (PubMed; Scopus; medRxiv, PsyArXiv; SocArXiv; bioRxiv; the WHO COVID-19 database; and the COVID-19 Open Research Dataset by Semantic Scholar (up to 11/2020), including data from Microsoft Academic, Elsevier, arXiv and PubMed Central.) All articles identified by the 4th August 2021 were screened. Papers reporting on data from a LMIC and presenting evidence on the impact of the pandemic on suicide or self-harm were included.A total of 22 studies from LMIC were identified representing data from 12 countries. There was an absence of data from Africa. The reviewed studies mostly report on the early months of COVID-19 and were generally methodologically poor. Few studies directly assessed the impact of the pandemic. The most robust evidence, from time-series studies, indicate either a reduction or no change in suicide and self-harm behaviour.As LMIC continue to experience repeated waves of the virus and increased associated mortality, against a backdrop of vaccine inaccessibility and limited welfare support, continued efforts are needed to track the indirect impact of the pandemic on suicide and self-harm in these countries.
SARS-CoV-2 circulation in the school setting: A systematic review and meta-analysis
Authors: Martinoli Chiara , La Vecchia Carlo , Raimondi Sara , Bellerba Federica , Sasso Clementina , Basso Alessandra , Cammarata Giulio , Gandini Sara 
Published: September 2021

ABSTRACTBackgroundThe contribution of children to viral spread in schools is still under debate.We conducted a systematic review and meta-analysis of studies to investigate SARS-CoV-2 transmission in the school setting.MethodsLiterature searches from April, 2021 and repeated on May, 15th 2021 yielded a total of 1088 publications: screening, contact tracing and seroprevalence studies.MOOSE guidelines were followed and data analyzed using random-effects models.ResultsFrom screening studies involving more than 120,000 subjects, we estimated 0.31% (95% Confidence Interval [CI] 0.05-0.81%) SARS-CoV-2 point prevalence in schools. Contact tracing studies, involving a total of 112,622 contacts of children and adults, showed that onward viral transmission was limited (2.54%; 95%CI 0.76-5.31). Young index cases were found to be 74% significantly less likely than adults to favor viral spread (Odds Ratio [OR]=0.26; 95%CI 0.11-0.63) and were less susceptible to infection (OR=0.60; 95% CI 0.25-1.47). Finally, from seroprevalence studies, with a total of 17,879 subjects involved, we estimated that children are 43% significantly less likely than adults to test positive for antibodies (OR=0.57; 95%CI: 0.49-0.68).In conclusion, testing all subjects in schools, independently of symptoms, students less likely than adults favor viral spread and SARS-CoV-2 circulation in schools was found to be limited.KEY POINTSQuestionWhat is the infectivity and susceptibility of students and staff exposed to SARS-CoV-2 in the school setting?FindingsThis systematic review and meta-analysis of all available data shows that SARS-CoV-2 viral spread is limited and child-to-adult transmission in the school setting scarce.Summary estimates indicate that young index cases were 74% significantly less likely than adults to favor viral spread and children are 43% less susceptible than adults.MeaningOverall, SARS-CoV-2 circulation in schools was limited and could be reasonably controlled with appropriate mitigation measures.
PIPENN: Protein Interface Prediction with an Ensemble of Neural Nets
Authors: Stringer Bas , de Ferrante Hans , Abeln Sanne , Heringa Jaap , Feenstra K. Anton , Haydarlou Reza 
Published: September 2021

AbstractMotivationProtein interactions play an essential role in many biological and cellular processes, such as protein–protein interaction (PPI) in signaling pathways, binding to DNA in transcription, and binding to small molecules in receptor activation or enzymatic activity. Experimental identification of protein binding interface residues is a time-consuming, costly, and challenging task. Several machine learning and other computational approaches exist which predict such interface residues. Here we explore if Deep Learning (DL) can be used effectively for this prediction task, and which learning strategies and architectures may be most efficient. We introduce seven DL architectures that are applied to eleven independent test sets, focused on the residues involved in PPI interfaces and in binding RNA/DNA and small molecule ligands.ResultsWe constructed a large data set dubbed BioDL, comprising protein-protein interaction data from the PDB and protein-ligand interactions (DNA, RNA and small molecules) from the BioLip database. Additionally, we reused our existing curated homo- and heteromeric PPI data sets. We performed several experiments to assess the impact of different data features, spatial forms, encoding schemes, network initializations, loss functions, regularization mechanisms, and activation functions on the performance of the predictors. Benchmarking the resulting DL models with an independent test set (ZK448) shows no single DL architecture performs best on all instances, but that an ensemble of DL architectures consistently achieves peak prediction performance. Our PIPENN’s ensemble predictor outperforms current state-of-the-art sequence-based protein interface predictors on all interaction types, achieving AUCs of 0.718 (protein–protein), 0.823 (protein–nucleotide) and 0.842 (protein– small molecule) respectively.AvailabilitySource code and data sets at https://github.com/ibivu/pipenn/Contactr.haydarlou@vu.nl
Optimization of closed-loop electrical stimulation enables robust cerebellar-directed seizure control
Authors: Stieve Bethany J. , Richner Thomas J. , Krook-Magnuson Chris , Netoff Theoden I. , Krook-Magnuson Esther 
Published: September 2021

AbstractAdditional treatment options for temporal lobe epilepsy are needed, and potential interventions targeting the cerebellum are of interest. Previous animal work has shown strong inhibition of hippocampal seizures through on-demand optogenetic manipulation of the cerebellum. However, decades of work examining electrical stimulation – a more immediately translatable approach – targeting the cerebellum has produced very mixed results. We were therefore interested in exploring the impact that stimulation parameters may have on seizure outcomes. Using a mouse model of temporal lobe epilepsy, we conducted on-demand electrical stimulation of the cerebellar cortex, and varied stimulation charge, frequency, and pulse width, resulting in over a thousand different potential combinations of settings. To explore this parameter space in an efficient, data-driven, manner, we utilized Bayesian optimization with Gaussian process regression, implemented in Matlab with an Expected Improvement Plus acquisition function. We examined two different fitting conditions and two different electrode orientations. Following the optimization process, we conducted additional on-demand experiments to test the effectiveness of selected settings. Across all animals, we found that Bayesian optimization allowed identification of effective intervention settings. Additionally, generally similar optimal settings were identified across animals, suggesting that personalized optimization may not always be necessary. While optimal settings were consistently effective, stimulation with settings predicted from the Gaussian process regression to be ineffective failed to provide seizure control. Taken together, our results provide a blueprint for exploration of a large parameter space for seizure control, and illustrate that robust inhibition of seizures can be achieved with electrical stimulation of the cerebellum, but only if the correct stimulation parameters are used.
Durability analysis of the highly effective BNT162b2 vaccine against COVID-19
Authors: Puranik Arjun , Lenehan Patrick J. , O’Horo John C. , Niesen Michiel J.M. , Virk Abinash , Swift Melanie D. , Kremers Walter , Venkatakrishnan A.J. , Gordon Joel E. , Geyer Holly L. , Speicher Leigh Lewis , Soundararajan Venky , Badley Andrew D. 
Published: September 2021

AbstractSARS-CoV-2 breakthrough infections have been increasingly reported in fully vaccinated individuals. We conducted a test-negative case-control study to assess the durability of protection after full vaccination with BNT162b2, defined as 14 days after the second dose, against polymerase chain reaction (PCR)-confirmed symptomatic SARS-CoV-2 infection, in a national medical practice between February 1, 2021 and August 22, 2021. We fit conditional logistic regression (CLR) models stratified on residential county and calendar time of testing to assess the association between time elapsed since vaccination and the odds of symptomatic infection or non-COVID-19 hospitalization (negative control), adjusted for several covariates. The primary population included 652 individuals who had a positive symptomatic test after full vaccination with BNT162b2 (cases) and 5,946 individuals with at least one negative symptomatic test after full vaccination (controls). The adjusted odds of symptomatic infection were higher 120 days after full vaccination versus at the date of full vaccination (Odds Ratio [OR]: 3.21, 95% confidence interval [CI]: 1.33-7.74). Importantly, the odds of infection were still lower 150 days after the first BNT162b2 dose as compared to 4 days after the first dose (OR: 0.3, 95% CI: 0.19-0.45), when immune protection approximates the unvaccinated status. Low rates of COVID-19 associated hospitalization or death in this cohort precluded analyses of these severe outcomes. The odds of experiencing a non-COVID-19 hospitalization decreased with time since vaccination, suggesting a possible underestimation of waning protection by this approach due to confounding factors. Taken together, these data constitute an early signal for waning protection against symptomatic illness while also providing reassurance that BNT162b2 continues to protect against symptomatic SARS-CoV-2 infection several months after full vaccination. Continued surveillance of COVID-19 vaccine durability, particularly against severe disease, is critical to guide effective and equitable strategies to respond to the pandemic, including distribution of booster doses, development of new vaccines, and implementation of both pharmaceutical and nonpharmaceutical interventions.
A comparison between time-constrained counts and line transects as methods to estimate butterfly diversity and monitor populations in tropical habitats
Authors: Suman Attiwilli , Ravikanthachari Nitin , Kunte Krushnamegh 
Published: September 2021

AbstractLong-term species monitoring programmes have revealed catastrophic insect population declines and disruption of biological communities that are contributing to biodiversity loss. Such discoveries have been possible because of standardised methods, such as line transects, of counting butterflies and other insects. However, line transects are not feasible in many tropical and mountainous habitats, so alternative methods must be explored. To tackle this issue, we devised time-constrained (30-min) counts and compared butterfly diversity as estimated through this method with that estimated through line transects in three tropical habitats in India (evergreen forest, dry deciduous forest and an urban woodland). We tested the efficacy of the two methods to sample species richness and abundance, as well as numbers of rare, endemic and specialist butterflies. We observed greater species richness, and more species of habitat specialists and endemics per sample in time-constrained counts in evergreen forest, but not in the other two habitats. Thus, time-constrained counts were more efficient at detecting species in the species-rich evergreen habitat. Apart from this difference, the two sampling methods captured similar levels of species richness and other measures of diversity. Our study thus shows that time-constrained counts is a suitable if not a superior alternative to line transects to conduct butterfly diversity surveys and population monitoring in complex tropical landscapes. Due to methodological flexibility and simplicity, this method may be particularly useful to study the impacts of climate change, habitat fragmentation and land use practices on butterfly conservation in populous and tech-ready tropical countries using citizen science frameworks.
Exploring Intuitive Approaches to Protein Conformation Clustering Using Regions of High Structural Variance
Authors: Tan Yi Yao 
Published: September 2021

AbstractThis paper presents a method to find structurally high variance segments of the different conformations of a single protein and uses clusters them using different distance metrics and interpretation of coordinate and angle data presented by three different methods: root mean squared derivation RMSD, t-distributed Stochastic Neighbor Embedding (t-SNE) based map, and dihedral-based clustering. The methods were applied on the human cylin-dependent kinase 2 (CDK2) protein, code P24941 uniprot using a series of python scripts and clustering packages. We test our methods on the data of the CDK2 protein as it is a highly researched protein, with practical applications of clustering in cancer research, crucial in the regulation of the cell-cycle, and has a sizeable amount of experimental data collected on the confirmation structures.While using the distance based root mean squared deviation RMSD provides data of structure to structure dissimilarity between different conformations, a simple RMSD matrix lacks to ability to describe the subsequence-wise in shape and absolute position which could be the main identifying elements for a protein’s conformation and state. To make up for this loss we explore an intuitive and more flexible method, able to accept multiple high structural variance segments, which takes coordinate based data, through a series of maps and with the help of t-SNE, and maps each segment as a feature in the clustering matrix. This method, however, would require additional testing on other proteins and modifications to verify its consistency and test its robustness.In the end we explore the pros and cons of the three methods applied on the high structural variance regions. Despite the randomness factor by the t-SNE used in mapping the coordinates to lower dimensions, the coordinate-based approach consistently performed better than the RSMD and dihedral based methods in clustering the three groups of the CDK2 protein kinase. We also found that analyzing only the substructures identified by the high variance detection algorithm consistently provided more distinct clusters with higher multi-class F1 scores.
Gut Reaction: The Impact of a Film on Public Understanding of Gastrointestinal Conditions
Authors: Gomes Diogo , Loth Alina , Hockley James R.F. , John Smith Ewan St. 
Published: September 2021

AbstractChronic gastrointestinal (GI) tract conditions, such as inflammatory bowel disease (IBD) and irritable bowel syndrome (IBS) are common conditions associated with disordered bowel movements and significant pain. However, discussion of bowel habits is often regarded as taboo and public understanding of what exactly IBD, IBS and related conditions are, and how they impact the lives of those individuals with such conditions is poorly understood. To provide a platform for enhancing public engagement of chronic bowel conditions, a short film was made (Gut Reaction) examining the lives of four individuals with different bowel conditions and what scientists and clinicians are doing to help alleviate the pain experienced by such individuals. This film was then screened at a science festival where a pre- and post-film survey was conducted alongside follow up semi-structured interviews with a small subset of those who had expressed willingness to engage in such an interview. Although films have been used for public engagement and health campaigns, there is a lack of a robust evaluation of such methods. As such, there is no knowledge of impacts and outcomes, jeopardising funding of such projects. Overall, the pre- and post-film surveys demonstrated that the film had increased the attendees’ understanding of chronic bowel conditions, how they are treated, what research is on-going and the likelihood of discussing bowel conditions with friends and family. The follow-up interviews were analysed through the constant comparative coding process. The analysis revealed that participants have a strong belief that bowel conditions need to be part of normal conversations, and the understanding of such conditions, and the people who experience them, needs to be improved by society. Our participants hold that this is crucial for people who experience from such conditions, not least to be able to access help sooner and suffer less. Finally, our participants discussed two strategies to achieve this societal openness and tackle the sense of shame around these issues: one involving role models and the other the media. In summary, Gut Reaction appeared to have met its objectives of improving the viewers’ awareness and understanding of chronic bowel conditions, as well as removing some of the stigma and taboo that surround discussions about these conditions.
Missing the forest for the trees: Do seaweed ecosystems mitigate atmospheric CO2 emissions?
Authors: Gallagher John Barry , Shelamoff Victor , Layton Cayne 
Published: September 2021

AbstractGlobal seaweed carbon sequestration estimates are currently taken as the fraction of the net primary production (NPP) exported to the deep ocean. However, this perspective does not account for CO2 from the consumption of external subsidies. Here we clarify: i) the role of export relative to seaweed net ecosystem production (NEP) for a closed system and one more likely open to subsidies; ii) the importance of subsidies by compiling published estimates of NEP from seaweed-dominated ecosystems; and iii) discuss their impact on the global seaweed net carbon balance and other sequestration constraints as a mitigation service. Examples of seaweed NEP (n = 18) were sparse and variable. Nevertheless, the average NEP (−9.2mmol C m−2 day−1 SE ± 11.6) suggested that seaweed ecosystems are a C source, becoming increasingly heterotrophic as their export is consumed. Critically, mitigation of greenhouse gas emissions was mixed relative to their replacement or baseline states, and where CO2 is supplied independently of organic metabolism and atmospheric exchange we caution a sole reliance on NEP or NPP. This will ensure a more accurate seaweed mitigation assessment, one that does exceed their capacity and is effective within a compliance and carbon trading scheme.
Aversive memory formation in humans is determined by an amygdala-hippocampus phase code
Authors: Costa Manuela , Lozano-Soldevilla Diego , Gil-Nagel Antonio , Toledano Rafael , Oehrn Carina , Kunz Lukas , Yebra Mar , Mendez-Bertolo Costantino , Stieglitz Lennart , Sarnthein Johannes , Axmacher Nikolai , Moratti Stephan , Strange Bryan A. 
Published: September 2021

AbstractMemory for aversive events is central to survival, but can also become maladaptive in psychiatric disorders. Emotional memory relies on the amygdala and hippocampus, but the neural dynamics of their communication during emotional memory encoding remain unknown. Using simultaneous intracranial recordings from both structures in human patients, we show that in response to emotionally aversive, but not neutral, visual stimuli, the amygdala transmits unidirectional influence on the hippocampus through theta oscillations. Critically, successful emotional memory encoding depends on the precise amygdala theta phase to which hippocampal gamma activity and neuronal firing couple. The phase difference between subsequently remembered vs. not-remembered emotional stimuli translates to ∼25-45 milliseconds, a time period that enables lagged coherence between amygdala and downstream hippocampal gamma activity. These results reveal a mechanism whereby amygdala theta phase coordinates transient coherence between amygdala and hippocampal gamma activity to facilitate the encoding of aversive memories in humans.