bluuebunny/crossref_metadata_2025_split huggingface dataset:
The rise and fall of novel ecological communities
Authors: Pandolfi John M. , Staples Timothy L. , Kiessling Wolfgang 
Published: June 2020

AbstractLocal and global environmental change is transforming ecological assemblages into new configurations, resulting in ecosystems with novel communities. Here we develop a robust methodology for the identification of novel communities, examine patterns in their natural chance of occurrence, and quantify the probability of local extinction, emigration, local origination and immigration in transitions to and from novel communities. Using a global dataset of Cenozoic marine plankton communities, we found the probability of local extinction, origination and emigration during transitions to a novel community increased up to four times that of background community changes, with the probability of species loss about equal to that of species gain. Although rare, once a novel community state emerged, the chance of shifting into another novel community state was five times greater than expected by chance. Thus, for marine planktonic communities at 100K year time scales, novel communities are particularly sensitive to further extinctions and community shift.One Sentence SummaryOnce developed, novel ecological communities face increased susceptibility to further shifts in species composition, with heightened extinction risk.
Are adversities and worries during the COVID-19 pandemic related to sleep quality? Longitudinal analyses of 48,000 UK adults
Authors: Wright Liam , Steptoe Andrew , Fancourt Daisy 
Published: June 2020

AbstractThere are concerns that both the experience of adversities during the COVID-19 pandemic and worries about experiencing adversities will have substantial and lasting effects on mental health. One pathway through which both experience of and worries about adversity may impact health is through effects on sleep. We used data from 48,723 UK adults in the COVID-19 Social Study assessed weekly from 01/04/2020-12/05/2020 to study the association between adversities and sleep quality. We studied six categories of adversity including both worries and experiences of: illness with COVID-19, financial difficulty, loss of paid work, difficulties acquiring medication, difficulties accessing food, and threats to personal safety. We used random-effect within-between models to account for all time-invariant confounders. Both the total number of adversity experiences and total number of adversity worries were associated with lower quality sleep. Each additional experience was associated with a 1.16 (95% CI = 1.10, 1.22) times higher odds of poor quality sleep while each additional worry was associated with a 1.20 (95% CI = 1.17, 1.22) times higher odds of poor quality sleep. When considering specific experiences and worries, all worries and experiences were significantly related to poorer quality sleep except experiences relating to employment and finances. Having a larger social network offered some buffering effects on associations but there was limited further evidence of moderation by social or psychiatric factors. Poor sleep may be a mechanism by which COVID-19 adversities are affecting mental health. This highlights the importance of interventions that support adaptive coping strategies during the pandemic.
Comparative assessment of multiple COVID-19 serological technologies supports continued evaluation of point-of-care lateral flow assays in hospital and community healthcare settings
Authors: Pickering Suzanne , Betancor Gilberto , Galão Rui Pedro , Merrick Blair , Signell Adrian W. , Wilson Harry D. , Ik Mark Tan Kia , Seow Jeffrey , Graham Carl , Acors Sam , Kouphou Neophytos , Steel Kathryn J.A. , Hemmings Oliver , Patel Amita , Nebbia Gaia , Douthwaite Sam , O’Connell Lorcan , Luptak Jakub , McCoy Laura E. , Brouwer Philip , Gils Marit J. van , Sanders Rogier W. , Nunez Rocio Martinez , Bisnauthsing Karen , O’Hara Geraldine , MacMahon Eithne , Batra Rahul , Malim Michael H. , Neil Stuart J.D. , Doores Katie J. , Edgeworth Jonathan D. 
Published: June 2020

AbstractThere is a clear requirement for an accurate SARS-CoV-2 antibody test, both as a complement to existing diagnostic capabilities and for determining community seroprevalence. We therefore evaluated the performance of a variety of antibody testing technologies and their potential as diagnostic tools. A highly specific in-house ELISA was developed for the detection of anti-spike (S), -receptor binding domain (RBD) and -nucleocapsid (N) antibodies and used for the cross-comparison of ten commercial serological assays – a chemiluminescence-based platform, two ELISAs and seven colloidal gold lateral flow immunoassays (LFIAs) – on an identical panel of 110 SARS-CoV-2-positive samples and 50 pre-pandemic negatives. There was a wide variation in the performance of the different platforms, with specificity ranging from 82% to 100%, and overall sensitivity from 60.9% to 87.3%. However, the head-to-head comparison of multiple sero-diagnostic assays on identical sample sets revealed that performance is highly dependent on the time of sampling, with sensitivities of over 95% seen in several tests when assessing samples from more than 20 days post onset of symptoms. Furthermore, these analyses identified clear outlying samples that were negative in all tests, but were later shown to be from individuals with mildest disease presentation. Rigorous comparison of antibody testing platforms will inform the deployment of point-of-care technologies in healthcare settings and their use in the monitoring of SARS-CoV-2 infections.
Testing the effects of the timing of application of preventative procedures against COVID-19: An insight for future measures such as local emergency brakes
Authors: Scullion Francis , Scullion Geraldine 
Published: June 2020

AbstractAs many countries plan to lift lockdown measures aimed at suppression of COVID-19, data from early regional epidemics in Italy were analysed to ascertain the effectiveness of the timing of preventative measures. The cumulative caseload data were extracted from regional epidemics in Italy. Epidemic features in regions where lockdown was applied early were compared to those where lockdown was applied later for statistical differences. There were statistically significant differences in the timing of the peak, the cumulative incidence at peak and the case/km2 at peak between regions where the lockdown had been applied early and those where it was applied late. The peak occurred 7 days earlier with four times less cases/km2 in regions where the lockdown was applied within 10 days of the start of the epidemic. Cumulative caseloads, cases/km2 and/or the number of days into an epidemic can be used to plan future localised suppression measures as part of a national post-lockdown policy. There were 350 (95% confidence interval (CI) 203) cumulative cases and 2.4 (CI 1.1) cases/km2 on day 8 of the regional epidemics.
Serological assessment of SARS-CoV-2 exposure in northern Sweden by the use of at-home sampling to meet geographical challenges in rural regions
Authors: Byström Julia Wigren , Vikström Linnea , Rosendal Ebba , Gröning Remigius , Gwon Yong-Dae , Nilsson Emma , Sharma Atin , Espaillat Akbar , Hanke Leo , McInerney Gerald , Puhar Andrea , Cava Felipe , Karlsson Hedestam Gunilla B , Thunberg Therese , Monsen Tor , Elgh Fredrik , Evander Magnus , Johansson Anders , Överby Anna K , Ahlm Clas , Normark Johan , Forsell Mattias NE 
Published: June 2020

ABSTRACTThe current SARS-CoV-2 pandemic has highlighted a need for easy and safe blood sampling in combination with accurate serological methodology. Venipuncture is usually performed by trained staff at health care centers. Long travel distances may introduce a bias of testing towards relatively large communities with close access to health care centers. Rural regions may thus be overlooked. Here, we demonstrate a sensitive method to measure antibodies to the S-protein of SARS-CoV-2. We adapted and optimized this assay for clinical use together with capillary blood sampling to meet the geographical challenges of serosurveillance. Finally, we tested remote at-home capillary blood sampling together with centralized assessment of S-specific IgG in a rural region of northern Scandinavia that encompasses 55,185 sq kilometers. We conclude that serological assessment from capillary blood sampling gives comparable results as analysis of venous blood. Importantly, at-home sampling enabled citizens living in remote rural areas access to centralized and sensitive laboratory antibody tests.
Consumption of breast milk, formula and other non-human milk by children aged under two years: analysis of 86 low and middle income countries
Authors: Neves Paulo A. R. , Barros Aluisio J.D. , Baker Phillip , Piwoz Ellen , Santos Thiago M. , Gatica-Domínguez Giovanna , Vaz Juliana S. , Rollins Nigel , Victora Cesar G. 
Published: June 2020

AbstractBackgroundConsumption of breast milk substitutes (BMS) by children aged under six months in low and middle income countries (LMICs) is directly driven by country income and family wealth. Multi-country investigations on the consumption of BMS by older children (6–23 months) are lacking.MethodsUsing data from 86 nationally representative surveys carried out in LMICs from 2010 onwards, we analyzed the prevalence of continued breastfeeding at one and two years, and frequency of consumption of formula and other non-human milk by age in months. Indicators were estimated through 24-hour dietary recall. Absolute and relative wealth indicators were used to describe within- and between-country socioeconomic inequalities. Results were stratified by country income groups.FindingsBreastfeeding declined sharply as children became older in all LMICs, especially in upper-middle income countries. Formula consumption peaked at six months of age in low and lower-middle income countries, and at around 12 months in upper-middle income countries. Consumption of formula at any age higher in children from wealthier families in all countries, while breastfeeding was more common among poor children. Multilevel linear regression analysis showed that consumption of formula was positively associated while breastfeeding was negatively associated with absolute national income. Factors at country level explained a substantial proportion of overall variability in formula use and breastfeeding.InterpretationInfant and young child feeding practices vary strongly according to wealth, both within and between countries. Breastfeeding falls sharply as children become older, especially in wealthier families living in upper-middle income countries; this is also the group with highest formula consumption at any age. Country-level factors play an important role in explaining BMS consumption by all family wealth groups in LMICs, suggesting that formula marketing at national level may be partly responsible for the observed differences.FundingThe Bill & Melinda Gates Foundation, through the WHO
Assessing capacity to social distance and neighborhood-level health disparities during the COVID-19 pandemic
Authors: Carrión Daniel , Colicino Elena , Pedretti Nicolo Foppa , Arfer Kodi B. , Rush Johnathan , DeFelice Nicholas , Just Allan C. 
Published: June 2020

AbstractThe COVID-19 pandemic has yielded disproportionate impacts on communities of color in New York City (NYC). Researchers have noted that social disadvantage may result in limited capacity to socially distance, and consequent disparities. Here, we investigate the role of neighborhood social disadvantage on the ability to socially distance, infections, and mortality. We combine Census Bureau and NYC open data with SARS-CoV-2 testing data using supervised dimensionality-reduction with Bayesian Weighted Quantile Sums regression. The result is a ZIP code-level index with relative weights for social factors facilitating infection risk. We find a positive association between neighborhood social disadvantage and infections, adjusting for the number of tests administered. Neighborhood infection risk is also associated with capacity to socially isolate, as measured by NYC subway data. Finally, infection risk is associated with COVID-19-related mortality. These analyses support that differences in capacity to socially isolate is a credible pathway between disadvantage and COVID-19 disparities.
Characterizing the Theory of Mind Network in Schizophrenia Reveals a Sparser Network Structure
Authors: Bitsch Florian , Berger Philipp , Nagels Arne , Falkenberg Irina , Straube Benjamin 
Published: June 2020

AbstractImpaired social functioning is a hallmark of schizophrenia and altered functional integration between distant brain regions are expected to account for signs and symptoms of the disorder. The functional neuroarchitecture of a network relevant for social functioning, the mentalizing network, is however poorly understood. In this study we examined dysfunctions of the mentalizing network in patients with schizophrenia compared to healthy controls via dynamic causal modelling and an interactive social decision-making game. Network characteristics were analyzed on a single subject basis whereas graph theoretic metrics such as in-degree, out-degree and edge-connectivity per network node were compared between the groups. The results point to a sparser network structure in patients with schizophrenia and highlight the dorsomedial prefrontal cortex as a disconnected network hub receiving significantly less input from other brain regions in the network. Further analyses suggest that integrating pathways from the right and the left temporo-parietal junction into the dorsomedial prefrontal cortex were less frequently found in patients with schizophrenia. Brain and behavior analyses further suggest that the connectivity-intactness within the entire network is associated with functional interpersonal behavior during the task. Thus, the neurobiological alterations within the mentalizing network in patients with schizophrenia point to a specific integration deficit between core brain regions underlying the generation of higher-order representations and thereby provide a potential treatment target.
Using a bistable animal opsin for switchable and scalable optogenetic inhibition of neurons
Authors: Rodgers Jessica , Bano-Otalora Beatriz , Belle Mino DC , Paul Sarika , Hughes Rebecca , Wright Phillip , McDowell Richard , Milosavljevic Nina , Orlowska-Feuer Patrycja , Martial Franck , Wynne Jonathan , Ballister Edward R , Storchi Riccardo , Allen Annette E , Brown Timothy , Lucas Robert J 
Published: June 2020

AbstractThere is no consensus on the best optogenetic tool for neuronal inhibition. Lamprey parapinopsin (‘Lamplight’) is a Gi/o-coupled bistable animal opsin that can be activated and deactivated by short and long wavelength light, respectively. Since native mechanisms of neuronal inhibition frequently employ Gi/o signalling, we asked here whether Lamplight could be used for optogenetic silencing. We show that short (405nm) and long (525nm) wavelength pulses repeatedly switch Lamplight between stable signalling active and inactive states, and that combining these wavelengths can be used to achieve intermediate levels of activity. We demonstrate that these properties can be applied to produce switchable and scalable neuronal hyperpolarisation, and suppression of spontaneous spike firing in the mouse hypothalamic suprachiasmatic nucleus. We show that expressing Lamplight in (predominantly) ON bipolar cells can photosensitise retinas following advanced photoreceptor degeneration, and that 405 and 525nm stimuli can produce responses of opposite sign in output neurons of the retina. Lamplight-driven responses to both activating (405nm) and deactivating (525nm) light can occur within 500ms and be elicited by intensities at least 10x below threshold for available inhibitory optogenetic tools. We conclude that Lamplight can co-opt endogenous signalling mechanisms to allow optogenetic inhibition that is scalable, sustained and rapidly reversible.
Enteropathy-induced regulatory T cells inhibit intestinal CD4+ T cell responses against oral vaccines
Authors: Bhattacharjee Amrita , Burr Ansen H.P. , Overacre-Delgoffe Abigail E. , Tometich Justin T. , Yang Deyi , Huckestein Brydie R. , Linehan Jonathan L. , Spencer Sean P. , Hall Jason A. , Harrison Oliver J. , da Fonseca Denise Morais , Norton Elizabeth B. , Belkaid Yasmine , Hand Timothy W. 
Published: June 2020

SummaryEnvironmental Enteric Dysfunction (EED) is an intestinal disease caused by malnutrition and infection that leads to malabsorption and stunting. EED is also associated with a reduced efficacy of oral vaccines. We show in a microbiota and diet-dependent model of EED that oral vaccine-specific CD4+T cell responses fail in the small intestine but responses in the draining lymph node were unaffected. Accordingly, the number of immunosuppressive RORγT+FOXP3+Tregsin the small intestine inversely correlated with the response to oral vaccination. Depletion of RORγT+FOXP3+Tregsindicated that they were necessary for EED-associated inhibition of the vaccine response. Additionally, RORγT+FOXP3+Tregsare important to regulate EED-associated inflammation as their depletion significantly worsened stunting. We have shown that EED-associated intestinal inflammation leads to a localized intestinal blockade of CD4 T cell immunity. These results support a modular model for immunity where tissue responses can be regulated independently of systemic immunity to prevent autoinflammation.
Structural elucidation of the heterodimericcis-prenyltransferase NgBR/DHDDS complex reveals novel insights in regulation of protein glycosylation
Authors: Edani Ban , Grabińska Kariona A. , Zhang Rong , Park Eon Joo , Siciliano Benjamin , Surmacz Liliana , Ha Ya , Sessa William C. 
Published: June 2020

SummaryCis-prenyltransferase (cis-PTase) catalyzes the rate-limiting step in the synthesis of glycosyl carrier lipids required for protein glycosylation in the lumen of endoplasmic reticulum. Here we report the crystal structure of the human NgBR/DHDDS complex, which represents the first atomic resolution structure for any heterodimericcis-PTase. The crystal structure sheds light on how NgBR stabilizes DHDDS through dimerization, participates in the enzyme’s active site through its C-terminal -RXG- motif, and how phospholipids markedly stimulatecis-PTase activity. Comparison of NgBR/DHDDS with homodimericcis-PTase structures leads to a model where the elongating isoprene chain extends beyond the enzyme’s active site tunnel, and an insert within the α3 helix helps to stabilize this energetically unfavorable state to enable long chain synthesis to occur. These data provide unique insights into how heterodimericcis-PTases have evolved from their ancestral, homodimeric forms to fulfill their function in long chain polyprenol synthesis.
Modeling cell turning by mechanics at the cell rear
Authors: Lee Kun Chun , Allen Greg M. , Barnhart Erin L. , Tsuchida Mark A. , Wilson Cyrus A. , Gutierrez Edgar , Groisman Alexander , Theriot Julie A. , Mogilner Alex 
Published: June 2020

AbstractIn this study, we explore a simulation of a mechanical model of the keratocyte lamellipodium as previously tested and calibrated for straight steady-state motility [1] and for the process of polarization and motility initiation [2]. In brief, this model uses the balance of three essential forces (myosin contraction, adhesive drag and actin network viscosity) to determine the cell’s mechanical behavior. Cell shape is set by the balance between the actin polymerization-driven protrusion at the cell boundary and myosin-driven retraction of the actin-myosin network. In the model, myosin acts to generate contractile stress applied to a viscous actin network with viscous resistance to actin flow created by adhesion to the substrate. Previous study [3] demonstrated that similar simple model with uniform constant adhesion predicts a rotating behavior of the cell; however, this behavior is idealized, and does not mimic observed features of the keratocyte’s turning behavior. Our goal is to explore what are the consequences of introducing mechanosensitive adhesions to the model.
A prediction model based on machine learning for diagnosing the early COVID-19 patients
Authors: Sun Nan-Nan , Yang Ya , Tang Ling-Ling , Dai Yi-Ning , Gao Hai-Nv , Pan Hong-Ying , Ju Bin 
Published: June 2020

AbstractWith the dramatically fast spread of COVID-9, real-time reverse transcription polymerase chain reaction (RT-PCR) test has become the gold standard method for confirmation of COVID-19 infection. However, RT-PCR tests are complicated in operation andIt usually takes 5-6 hours or even longer to get the result. Additionally, due to the low virus loads in early COVID-19 patients, RT-PCR tests display false negative results in a number of cases. Analyzing complex medical datasets based on machine learning provides health care workers excellent opportunities for developing a simple and efficient COVID-19 diagnostic system. This paper aims at extracting risk factors from clinical data of early COVID-19 infected patients and utilizing four types of traditional machine learning approaches including logistic regression(LR), support vector machine(SVM), decision tree(DT), random forest(RF) and a deep learning-based method for diagnosis of early COVID-19. The results show that the LR predictive model presents a higher specificity rate of 0.95, an area under the receiver operating curve (AUC) of 0.971 and an improved sensitivity rate of 0.82, which makes it optimal for the screening of early COVID-19 infection. We also perform the verification for generality of the best model (LR predictive model) among Zhejiang population, and analyze the contribution of the factors to the predictive models. Our manuscript describes and highlights the ability of machine learning methods for improving the accuracy and timeliness of early COVID-19 infection diagnosis. The higher AUC of our LR-base predictive model makes it a more conducive method for assisting COVID-19 diagnosis. The optimal model has been encapsulated as a mobile application (APP) and implemented in some hospitals in Zhejiang Province.