bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mini-XT, a miniaturized tagmentation-based protocol for efficient sequencing of SARS-CoV-2
Authors: Fuchs Marc , Radulescu Clara , Tang Miao , Mahesh Arun , Lavin Deborah , Umbreen Syed , McKenna James , Smyth Mark , McColgan Eilís , Molnar Zoltan , Baxter Chris , Skvortsov Timofey , Singh Aditi , Rogan Fiona , Miskelly Julia , Bridgett Stephen , Fairley Derek , Simpson David A. 
Published: October 2021

AbstractIntroductionThe COVID-19 pandemic has highlighted the importance of whole genome sequencing (WGS) of SARS-CoV-2 to inform public health policy. By enabling definition of lineages it facilitates tracking of the global spread of the virus. The evolution of new variants can be monitored and knowledge of specific mutations provides insights into the mechanisms through which the virus increases transmissibility or evades immunity. To date almost one million SARS-CoV-2 genomes have been sequenced by members of the COVID-19 Genomics UK (COG-UK) Consortium. To achieve similar feats in a more cost-effective and sustainable manner in future, improved high throughput virus sequencing protocols are required. We have therefore developed a miniaturized library preparation protocol with drastically reduced consumable use and costs.MethodsSARS-CoV-2 RNA was amplified using the ARTIC nCov-2019 multiplex RT-PCR protocol and purified using a conventional liquid handling system. Acoustic liquid transfer (Echo 525) was employed to reduce reaction volumes and the number of tips required for a Nextera XT library preparation. Sequencing was performed on an Illumina MiSeq.ResultsWe present the ‘Mini-XT’ miniaturized tagmentation-based library preparation protocol available on protocols.io (https://dx.doi.org/10.17504/protocols.io.bvntn5en). The final version of Mini-XT has been used to sequence 4,384 SARS-CoV-2 samples from N. Ireland with a COG-UK QC pass rate of 97.4%. Sequencing quality was comparable and lineage calling consistent for replicate samples processed with full volume Nextera DNA Flex (333 samples) or using nanopore technology (20 samples). SNP calling between Mini-XT and these technologies was consistent and sequences from replicate samples paired together in maximum likelihood phylogenetic trees.ConclusionThe Mini-XT protocol maintains sequence quality while reducing library preparation reagent volumes 8-fold and halving overall tip usage from sample to sequence to provide concomitant cost savings relative to standard protocols. This will enable more efficient high-throughput sequencing of SARS-CoV-2 isolates and future pathogen WGS.
Neonatal outcomes of preterm infants born during COVID-19 community lockdowns in Melbourne, Australia
Authors: Mulcahy Brendan , Rolnik Daniel L. , Matheson Alexia , Liu Yizhen , Palmer Kirsten R. , Mol Ben W. , Malhotra Atul 
Published: October 2021

AbstractBackgroundCommunity lockdowns during the COVID-19 pandemic may influence preterm birth rates, but mechanisms are unclear.MethodsWe compared neonatal outcomes of preterm infants born to mothers exposed to community lockdowns in 2020 (exposed group) to those born in 2019 (control group). Main outcome studied was composite of significant neonatal morbidity or death.ResultsMedian gestational age was 35+4 weeks (295 infants, exposed group) vs. 35+0 weeks (347 infants, control group) (p = 0.108). The main outcome occurred in 36/295 (12.2%) infants in exposed group vs. 46/347 (13.3%) in control group (p = 0.69). Continuous positive airway pressure (CPAP) use, jaundice requiring phototherapy, hypoglycaemia requiring treatment, early neonatal white cell and neutrophil counts were significantly reduced in the exposed group.ConclusionsCOVID-19 community lockdowns did not alter composite neonatal outcomes in preterm infants, but reduced rates of some common outcomes, and early white cell and neutrophil counts.
CAMION: a catchment area maximization algorithm, with application to oncology accessibility in metropolitan France
Authors: Daoud Eric , Hamy Anne-Sophie , Dumas Elise , Delrieu Lidia , Rejo Beatriz Grandal , Bihan-Benjamin Christine Le , Houzard Sophie , Bousquet Philippe-Jean , Hotton Judicaël , Savoye Aude-Marie , Jouannaud Christelle , Azencott Chloé-Agathe , Lelarge Marc , Reyal Fabien 
Published: October 2021

AbstractBackgroundAccess to health services plays a key role in cancer survival. Uneven distributions of populations and health facilities lead to geographical disparities. Location-allocation algorithms can address these disparities by finding new locations and capacities for health facilities. However, in oncology, opening new hospitals or moving them is difficult in practice, and should be handled carefully.MethodsWe propose a method to measure the spatial accessibility to oncology care and identify the hospitals to grow to reduce disparities. We first ran a clustering algorithm to automatically label the hospitals in terms of oncology specialization. Then, we computed an accessibility score to these hospitals for every population location. Finally, we introducedCAMION, an optimization algorithm based on Linear Programming that reduces disparities in oncology accessibility by identifying health facilities that should increase their capacities.ResultsWe demonstrate our algorithm in metropolitan France. The clustering step let us identify different oncology specialization levels for hospitals. Most of the population in metropolitan France lived in good accessibility areas, especially in large cities. Lower accessibility zones are often rural or suburban municipalities. The optimization algorithm effectively manages to identify hospitals to grow, based on current oncology specialization and accessibility scores.DiscussionThere is a tradeoff to be found by patients, between care center proximity and care center expertise, which is less likely to happen for patients living in good accessibility areas. The accessibility score is deliberately non-specific to cancer type but can be adapted to more precise pathologies. Our method is replicable in any country, given hospitals and population locations data. We developed a web application intended for healthcare professionals to let them to run the optimization algorithm with the desired parameters and visualize the results.
Progressive changes in descriptive discourse in First Episode of Schizophrenia: A longitudinal computational semantics study
Authors: Alonso-Sánchez Maria Francisca , Ford Sabrina D. , MacKinley Michael , Silva Angélica , Limongi Roberto , Palaniyappan Lena 
Published: October 2021

AbstractComputational semantics, a branch of computational linguistics, involves automated meaning analysis that relies on how words occur together in natural language. This offers a promising tool to study schizophrenia. At present, we do not know if these word level choices in speech are sensitive to illness stage (i.e. acute untreated vs. stable established state), track cognitive deficits in major domains (e.g. cognitive control, processing speed) and relate to established dimensions of formal thought disorder. Here we study samples of descriptive discourse in patients with untreated first episode of schizophrenia (x□ 2.8 days of lifetime daily dose exposure) and healthy subjects (246 samples of 1-minute speech; n=82, FES=46, HC=36) using a co-occurrence based vector embedding of words. We obtained six-month follow-up data in a subsample (99 speech samples, n=33, FES=20, HC=13). At baseline, the evidence for higher semantic similarity during descriptive discourse in FES was substantial, compared to null difference (Bayes Factor =6 for full description; 32 for 10-words window). Moreover, the was a linear increase in semantic similarity with time in FES compared to HC (Bayes Factor= 6). Higher semantic similarity related to lower Stroop performance (accuracy and interference, response time), and was present irrespective of the severity of clinically ascertained thought disorder. Automated analysis of non-intrusive 1-minute speech samples provides a window on cognitive control deficits, role functioning and tracks latent progression in schizophrenia.
Adaptive data-driven age and patch mixing in contact networks with recurrent mobility
Authors: Knight Jesse , Ma Huiting , Ghasemi Amir , Hamilton Mackenzie , Brown Kevin , Mishra Sharmistha 
Published: October 2021

AbstractInfectious disease transmission models often stratify populations by age and geographic patches. Contact patterns between age groups and patches are key parameters in such models. Arenas et al. (2020) develop an approach to simulate contact patterns associated with recurrent mobility between patches, such as due to work, school, and other regular travel. Using their approach, mixing between patches is greater than mobility data alone would suggest, because individuals from patches A and B can form a contact if they meet in patch C. We build upon their approach to address three potential gaps that remain. First, our approach includes a distribution of contacts by age that is responsive to underlying age distribution of the mixing pool. Second, different age distributions by contact type are also maintained in our approach, such that changes to the numbers of different types of contacts are appropriately reflected in changes to the overall age mixing patterns. Finally, we introduce and distinguish between two mixing pools associated with each patch, with possible implications for the overall connectivity of the population: the home pool, in which contacts can only be formed with other individuals residing in the same patch; and the travel pool, in which contacts can be formed with some residents of, and any other visitors to the patch. We describe in detail the steps required to implement our approach, and present results of an example application.Graphical Abstract
Importation Risk Stratification for COVID19 using Quantitative Serology
Authors: Williams David E 
Published: October 2021

AbstractRecent work (Khoury et al.,Nature Medicine2021, 27 (7), 1205-1211) has shown that measurement of IgG antibody concentration in blood correlates well with vaccine efficacy. The present communication builds on this work and considers the probability of infection given immunity, taking into account the distribution across the population of antibody concentration in vaccinated or convalescent people. The model is consistent with the observed rates of breakthrough infection following vaccination or previous infection. The model is then developed to consider the use of quantitative measurement of antibody concentration on arrival as an aid to risk stratification of travellers. The model indicates that such a measurement could significantly decrease the quarantine time required to achieve a given level of importation risk.
Patient Attitudes About Light Therapy and Negative Ion Therapy for Nonseasonal Depression: An Online Survey Study
Authors: Lahouaoula Iman , Li Victor W. , Scott Aidan , Do André , Michalak Erin E. , Murphy Jill K. , Huang Samantha , Lam Raymond W. 
Published: October 2021

ABSTRACTObjectiveNo studies have yet evaluated whether light therapy or negative ion therapy can be used as maintenance treatment after acute treatment with antidepressants in patients with major depressive disorder. To address the importance of this question, we surveyed participants with depression to determine their knowledge and attitudes about light therapy and negative ion therapy, and their willingness to participate in a randomized clinical trial with these therapies substituting for antidepressants for maintenance treatment.MethodsParticipants with a self-reported diagnosis of depression were recruited by email, newsletters, and social media to complete an online survey with questions about awareness and effectiveness of light therapy and negative ion therapy for depression. Vignettes describing the use of these therapies for maintenance treatment were presented with follow up questions about the ease of use and reasons for wanting (and not wanting) to use the therapies instead of antidepressants. Another vignette described a randomized study with these therapies followed by questions on whether participants would likely volunteer for the study. Chi-square tests were used to examine differences in responses between therapies.ResultsA total of 221 participants completed the survey. Most of them were aware of both therapies, but more participants had heard of light therapy (95% compared to 62% for negative ion therapy, p<0.0001), had used light therapy (28% versus 16%, p<0.003), and regarded light therapy as effective (54% versus 37%, p<0.001). Both therapies were considered easy to use. The majority of participants (78%) thought that it was important to find non-medication therapies for maintenance treatment, and 77% responded that they would likely volunteer for a randomized study to determine efficacy of the two therapies for maintenance treatment.ConclusionPeople with depression are generally aware of light therapy and negative ion therapy and believe they would be good therapies to substitute for antidepressants in maintenance treatment. These findings support the importance and feasibility for a randomized relapse prevention trial with light therapy and negative ion therapy in patients with depression.
Assessing the Burden of COVID-19 in Developing Countries: Systematic Review, Meta-Analysis, and Public Policy Implications
Authors: Levin Andrew , Owusu-Boaitey Nana , Pugh Sierra , Fosdick Bailey K. , Zwi Anthony B. , Malani Anup , Soman Satej , Besançon Lonni , Kashnitsky Ilya , Ganesh Sachin , McLaughlin Aloysius , Song Gayeong , Uhm Rine , Herrera-Esposito Daniel , de los Campos Gustavo , Pecanha Antiono Ana Carolina , Tadese Enyew Birru , Meyerowitz-Katz Gideon 
Published: October 2021

AbstractIntroductionThe infection-fatality rate (IFR) of COVID-19 has been carefully measured and analyzed in high-income countries, whereas there has been no systematic analysis of age-specific seroprevalence or IFR for developing countries.MethodsWe systematically reviewed the literature to identify all COVID-19 serology studies in developing countries that were conducted using population representative samples collected by early 2021. For each of the antibody assays used in these serology studies, we identified data on assay characteristics, including the extent of seroreversion over time. We analyzed the serology data using a Bayesian model that incorporates conventional sampling uncertainty as well as uncertainties about assay sensitivity and specificity. We then calculated IFRs using individual case reports or aggregated public health updates, including age-specific estimates whenever feasible.ResultsSeroprevalence in many developing country locations was markedly higher than in high-income countries. In most locations, seroprevalence among older adults was similar to that of younger age cohorts, underscoring the limited capacity that these nations have to protect older age groups. Age-specific IFRs were roughly 2x higher than in high-income countries. The median value of the population IFR was about 0.5%, similar to that of high-income countries, because disparities in healthcare access were roughly offset by differences in population age structure.ConclusionThe burden of COVID-19 is far higher in developing countries than in high-income countries, reflecting a combination of elevated transmission to middle-aged and older adults as well as limited access to adequate healthcare. These results underscore the critical need to accelerate the provision of vaccine doses to populations in developing countries.Key Points-Age-stratified infection fatality rates (IFRs) of COVID-19 in developing countries are about twice those of high-income countries.-Seroprevalence (as measured by antibodies against SARS-CoV-2) is broadly similar across age cohorts, underscoring the challenges of protecting older age groups in developing countries.-Population IFR in developing countries is similar to that of high-income countries, because differences in population age structure are roughly offset by disparities in healthcare access as well as elevated infection rates among older age cohorts.-These results underscore the urgency of disseminating vaccines throughout the developing world.
Endemic Seasonal Coronavirus Neutralisation and COVID-19 severity
Authors: Wells David A. , Cantoni Diego , Mayora-Neto Martin , Di Genova Cecilia , Sampson Alexander , Ferrari Matteo , Carnell George , Nadesalingam Angalee , Smith Peter , Chan Andrew , Raddi Gianmarco , Castillo-Olivares Javier , Baxendale Helen , Temperton Nigel , Heeney Jonathan L. 
Published: October 2021

AbstractThe virus SARS-CoV-2, responsible for the global COVID-19 pandemic, spread rapidly around the world causing high morbidity and mortality because humans have no pre-existing immunity. However, there are four known, endemic seasonal coronaviruses in humans (HCoVs) and whether antibodies for these HCoVs play a role in severity of COVID-19 disease has generated a lot of interest. Of these seasonal viruses NL63 is of particular interest as it uses the same cell entry receptor as SARS-CoV-2.We use functional, neutralising assays to investigate cross reactive antibodies and their relationship with COVID-19 severity. We analysed neutralisation of SARS-CoV-2, NL63, HKU1, and 229E in 38 COVID-19 patients and 62 healthcare workers, and a further 182 samples to specifically study the relationship between SARS-CoV-2 and NL63.We found that although HCoV neutralisation was very common there was little evidence that these antibodies neutralised SARS-CoV-2. Despite no evidence in cross neutralisation, levels of NL63 neutralisating antibodies become elevated after exposure to SARS-CoV-2 through infection or following vaccination.
LOTVS: a global collection of permanent vegetation plots
Authors: Sperandii Marta Gaia , de Bello Francesco , Valencia Enrique , Götzenberger Lars , Bazzichetto Manuele , Galland Thomas , E-Vojtkó Anna , Conti Luisa , Adler Peter B. , Buckley Hannah , Danihelka Jiří , Day Nicola J. , Dengler Jürgen , Eldridge David J. , Estiarte Marc , García-González Ricardo , Garnier Eric , Gómez-García Daniel , Hallett Lauren , Harrison Susan , Herben Tomas , Ibáñez Ricardo , Jentsch Anke , Juergens Norbert , Kertész Miklós , Kimuyu Duncan M. , Klumpp Katja , Le Duc Mike , Louault Frédérique , Marrs Rob H. , Ónodi Gábor , Pakeman Robin J. , Pärtel Meelis , Peco Begoña , Peñuelas Josep , Rueda Marta , Schmidt Wolfgang , Schmiedel Ute , Schuetz Martin , Skalova Hana , Šmilauer Petr , Šmilauerová Marie , Smit Christian , Song Ming-Hua , Stock Martin , Val James , Vandvik Vigdis , Wesche Karsten , Wiser Susan K. , Woodcock Ben A. , Young Truman P. , Yu Fei-Hai , Zobel Martin , Lepš Jan 
Published: October 2021

AbstractAnalysing temporal patterns in plant communities is extremely important to quantify the extent and the consequences of ecological changes, especially considering the current biodiversity crisis. Long-term data collected through the regular sampling of permanent plots represent the most accurate resource to study ecological succession, analyse the stability of a community over time and understand the mechanisms driving vegetation change. We hereby present the LOng-Term Vegetation Sampling (LOTVS) initiative, a global collection of vegetation time-series derived from the regular monitoring of vascular plants in permanent plots. With 79 datasets from five continents and 7789 vegetation time-series monitored for at least six years and mostly on an annual basis, LOTVS possibly represents the largest collection of temporally fine-grained vegetation time-series derived from permanent plots and made accessible to the research community. As such, it has an outstanding potential to support innovative research in the fields of vegetation science, plant ecology and temporal ecology.
“Epidemiological profile of patients with stage 5 chronic kidney disease on dialysis with Covid 19 infection in a Public Hospital-Perú”
Authors: Venegas-Justiniano Yanissa , Loza-Munarriz César , Hurtado-Aréstegui Abdías 
Published: October 2021

ABSTRACTIntroductionChronic kidney disease (CKD) in Covid 19 is relevant, however, there are few descriptions and fewer in Peru. Our goal was to describe the epidemiological profile and the factors related to mortality and survival of patients with stage 5 (CKD) on chronic dialysis hospitalized for Covid-19 in a public hospital.MethodsRetrospective case series. Patients with stage 5 CKD, older than 18 years, hospitalized for Covid-19 infection were included. The primary data source was medical records. The clinical and epidemiological profile of the study sample and the factors related to mortality and survival are described.Results105 medical records of patients with CKD 5 were evaluated. 57 (54,29%) were male, with a mean age of 58,59 ± 14,3 years. 84 (80%) patients survived and 21 (20%) died. The main cause of admission to hospitalization was respiratory failure in (80) 76,2%. The hospital stay was 11,76 ± 7,8 days. In the bivariate analysis: the increase in leukocytes, D dimer, ferritin, CRP, LDH and the decrease in lymphocytes, pH, bicarbonate and PaO2/FiO2 were related to mortality. In the multivariate analysis, only CRP> 10 mg/dl [HR: 10.72 (95% CI 1,4-81,58)] and a PaO2/FiO2 ≤ 150 mmHg [HR: 44,40 (95% CI 5,86-336,06)] they were factors related to poor survival.ConclusionsCRP levels> 10mg/dl and PaO2/FiO2 ≤ 150 mmHg are the main factors related to mortality and poor survival in patients with stage 5 CKD hospitalized for Covid-19.
Genome-wide cell-free DNA termini in patients with cancer
Authors: Moldovan Norbert , van der Pol Ymke , van den Ende Tom , Boers Dries , Verkuijlen Sandra , Creemers Aafke , Ramaker Jip , Vu Trang , Fransen Marieke F. , Pegtel Michiel , Bahce Idris , van Laarhoven Hanneke , Mouliere Florent 
Published: October 2021

AbstractThe structure, fragmentation pattern, length and terminal sequence of cell-free DNA (cfDNA) is under the influence of nucleases present in the blood. We hypothesized that differences in the diversity of bases at the end of cfDNA fragments can be leveraged on a genome-wide scale to enhance the sensitivity for detecting the presence of tumor signals in plasma. We surveyed the cfDNA termini in 572 plasma samples from 319 patients with 18 different cancer types using low-coverage whole genome sequencing. The fragment-end sequence and diversity were altered in all cancer types in comparison to 76 healthy controls. We converted the fragment end sequences into a quantitative metric and observed that this correlates with circulating tumor DNA tumor fraction (R = 0.58, p < 0.001, Spearman). Using these metrics, we were able to classify cancer samples from control at a low tumor content (AUROC of 91% at 1% tumor fraction) and shallow sequencing coverage (mean AUROC = 0.99 at >1M fragments). Combining fragment-end sequences and diversity using machine learning, we classified cancer from healthy controls (mean AUROC = 0.99, SD = 0.01). Using unsupervised clustering we showed that early-stage lung cancer can be classified from control or later stages based on fragment-end sequences. We observed that fragment-end sequences can be used for prognostication (hazard ratio: 0.49) and residual disease detection in resectable esophageal adenocarcinoma patients, moving fragmentomics toward a greater clinical implementation.One sentence summarycell-free DNA fragment end sequence analysis enhances cancer detection, monitoring and prognosis.