bluuebunny/crossref_metadata_2025_split huggingface dataset:
Paraspeckles are constructed as block copolymer micelles through microphase separation
Authors: Yamazaki Tomohiro , Yamamoto Tetsuya , Yoshino Hyura , Souquere Sylvie , Nakagawa Shinichi , Pierron Gerard , Hirose Tetsuro 
Published: November 2020

SummaryParaspeckles are constructed by NEAT1_2 architectural long noncoding RNAs and possess characteristic cylindrical shapes with highly ordered internal organization, distinct from typical liquid–liquid phase-separated condensates. We experimentally and theoretically investigated how the shape and organization of paraspeckles are determined. We identified the NEAT1_2 RNA domains responsible for shell localization of the NEAT1_2 ends, which determine the characteristic internal organization. We then applied a theoretical framework using soft matter physics to understand the principles that determine the NEAT1_2 organization, shape, number, and size of paraspeckles. By treating paraspeckles as amphipathic block copolymer micelles, we could explain and predict the experimentally observed behaviors of paraspeckles upon NEAT1_2 domain deletions or transcriptional modulation. Thus, we propose that paraspeckles are block copolymer micelles assembled through microphase separation. This work provides an experimentally-based theoretical framework for the concept that ribonucleoprotein complexes (RNPs) can act as block copolymers to form RNA-scaffolding microphase-separated condensates in cells.
The mental health of staff working in intensive care during COVID-19
Authors: Greenberg Neil , Weston Dale , Hall Charlotte , Caulfield Tristan , Williamson Victoria , Fong Kevin 
Published: November 2020

AbstractBackgroundIntensive Care Unit (ICU), anaesthetic and theatres staff have faced significant challenges during the COVID-19 pandemic which have the potential to adversely affect their mental healthAimsTo identify the rates of probable mental health disorder in ICU and anaesthetic staff in six English hospitals during June and July 2020MethodsAn anonymised brief web-based survey comprising standardised questionnaires examining depression, anxiety symptoms, symptoms of Post Traumatic Stress Disorder (PTSD), wellbeing and alcohol use was administered to staff.Results709 participants completed the surveys comprising 291 (41%) doctors, 344 (48.5%) nurses, and 74 (10.4%) other healthcare staff. Over half (58.8%) reported good wellbeing, however 45.4% met the threshold for probable clinical significance on at least one of the following measures: severe depression (6.3%), PTSD (39.5%), severe anxiety (11.3%) or problem drinking (7.2%). 13.4% of respondents reported frequent thoughts of being better off dead, or of hurting themselves in the past two weeks. We found that doctors consistently reported better mental health than nurses.ConclusionsWe found substantial rates of probable mental health disorders, and thoughts of self-harm, amongst ICU staff; these difficulties were especially prevalent in nurses. These results indicate the need for a national strategy to protect the mental health, and decrease the risk of functional impairment, of ICU staff whilst they carry out their essential work during COVID-19.Occ Med Statements: article should contain 3 statements (each max of 3 bullets of max 50 words each)What is already known about this subjectIntensive care unit (ICU) staff are regularly exposed to traumatic situations as part of their jobPrevious studies have shown them to be at risk of psychological and moral distressLittle is known about the mental health of ICU staff during the current pandemicWhat this study addsAlmost half of ICU staff report symptoms consistent with a probable diagnosis of post traumatic stress disorder, severe depression or anxiety or problem drinkingAround 1 in 7 ICU staff report recent thoughts of self-harm or of wanting to be better off deadNursing staff are more likely to report higher levels of distress than doctors or other clinical staffWhat impact this may have on practice or policyHealthcare managers need to prioritise staff mental health support and timely access to evidence based treatments for ICU staffSupervisors and managers should be aware that a substantial proportion of ICU staff may perform less well because of their current poor state of mental healthMore work is needed to understand whether the high levels of mental health symptoms identified in this study are truly indicative of high levels of clinical need for mental healthcare
SARS-CoV-2 antibody prevalence and symptoms in a local Austrian population
Authors: Ladage Dennis , Höglinger Yana , Ladage Dorothee , Adler Christoph , Yalcin Israfil , Braun Ralf J. 
Published: November 2020

BackgroundSince December 2019 the novel coronavirus (SARS-CoV-2) is the center of global attention due to its rapid transmission and toll on health care systems and global economy. Population-based serosurveys measuring antibodies for SARS-CoV-2 provide one method for estimating infection rates and monitoring the progression of the epidemic.MethodsIn June 2020 we succeeded in testing almost half of the population of an Austrian township (n=835 of 1359 inhabitants) with a reported higher incidence for COVID-19 infections. We determined the level of prevalence for SARS-CoV-2 in this population, factors affecting, and symptoms correlated with prior infection.ResultsWe found a high prevalence of 9% positive antibodies among the town population in comparison to 6% of the neighboring villages. Only 20% of SARS-CoV-2 cases self-declared being asymptomatic. In contrast, we identified six single major symptoms, including anosmia/ageusia, weight loss, anorexia, general debility, dyspnea, and fever, and especially their combination to be of high prognostic value for predicting SARS-CoV-2 infection in a patient. Our comparison of the gold standard lab-based ELISA test and the on-site antibody test demonstrated a lack of accuracy for the latter test form.ConclusionsThis population study demonstrated a high prevalence of antibodies to SARS-CoV-2 as a marker of both active and past infections in an Austrian township. Several symptoms revealed a diagnostic value especially in combination. Results from self-administered antibody tests should be considered with caution.
A Digital CRISPR-based Method for the Rapid Detection and Absolute Quantification of Viral Nucleic Acids
Authors: Wu Xiaolin , Chan Cheryl , Lee Yie Hou , Springs Stacy L. , Lu Timothy K. , Yu Hanry 
Published: November 2020

AbstractQuantitative real-time PCR and CRISPR-based methods detect SARS-CoV-2 in 1 hour but do not allow for the absolute quantification of virus particles, which could reduce inter-lab variability and accelerate research. The 4-hour reaction time of the existing digital PCR-based method for absolute virus quantification is too long for widespread application. We report a RApid DIgital Crispr Approach (RADICA) for the absolute quantification of SARS-CoV-2 DNA and Epstein–Barr virus DNA in human samples that yields results within 1 hour. For validation, we compared RADICA to digital PCR for quantifying synthetic SARS-CoV-2 DNA and Epstein–Barr viral DNA. RADICA allows absolute quantification of DNA with a dynamic range from 0.6 to 2027 copies/µL (R2 value > 0.98), without cross-reactivity on similar virus or human background DNA. Thus, RADICA can accurately detect and quantify nucleic acid in 1h without thermal cycling, providing a 4-fold faster alternative to digital PCR-based virus detection.
Genomic surveillance of antimicrobial resistant bacterial colonisation and infection in intensive care patients
Authors: Wyres Kelly L. , Hawkey Jane , Mirčeta Mirianne , Judd Louise M. , Wick Ryan R. , Gorrie Claire L. , Pratt Nigel F. , Garlick Jill S. , Watson Kerrie M. , Pilcher David V. , McGloughlin Steve A. , Abbott Iain J. , Macesic Nenad , Spelman Denis W. , Jenney Adam W. J. , Holt Kathryn E. 
Published: November 2020

AbstractBackgroundThird-generation cephalosporin-resistant Gram-negatives (3GCR-GN) and vancomycin-resistant Enterococci (VRE) are common causes of multi-drug resistant healthcare-associated infections, for which gut colonisation is considered a prerequisite. However, there remains a key knowledge gap about colonisation and infection dynamics in high-risk settings such as the intensive care unit (ICU), thus hampering infection prevention efforts.MethodsWe performed a three-month prospective genomic survey of infection and gut-colonisation with 3GCR-GN and VRE among patients admitted to an Australian ICU.ResultsAmong 287 patients screened on admission, 17.4% and 8.4% were colonised by 3GCR-GN and VRE, respectively. Escherichia coli was the most common species (n=36 episodes, 58.1%) and the most common cause of 3GCR-GN infection. Only two VRE infections were identified. The rate of infection among patients colonised with E. coli was low, but higher than those who were not colonised on admission (6% vs 2% E. coli, p=0.3). While few patients were colonised with 3GCR-Klebsiella pneumoniae or Pseudomonas aeruginosa on admission (n=4), all such patients developed infections with the colonising strain. Genomic analyses revealed 10 putative nosocomial transmission clusters: four VRE, six 3GCR-GN, with epidemiologically linked clusters accounting for 21% and 6% of episodes, respectively (OR 4.3, p=0.02).Conclusions3GCR-E. coli and VRE were the most common gut colonisers. E. coli was the most common cause of 3GCR-GN infection, but other 3GCR-GN species showed greater risk for infection in colonised patients. Larger studies are warranted to elucidate the relative risks of different colonisers and guide the use of screening in ICU infection control.Key pointsSurveillance for VRE or ESBL Gram-negative bacteria in ICU showed distinct species-specific clinical risk profiles. VRE and ESBL-Escherichia coli were the most common colonisers, but were associated with lower attack rate and transmission rate, compared with rarer coloniser Klebsiella pneumoniae.
Using convolutional neural network to predict remission of diabetes after gastric bypass surgery: a machine learning study from the Scandinavian Obesity Surgery Register
Authors: Cao Yang , Näslund Ingmar , Näslund Erik , Ottosson Johan , Montgomery Scott , Stenberg Erik 
Published: November 2020

AbstractBackgroundPrediction of diabetes remission is an important topic in the evaluation of patients with type-2 diabetes (T2D) before bariatric surgery. While several high-quality predictive indices are available, artificial intelligence (AI) algorithms offer the potential for higher predictive capability. The objective was to construct and validate an AI prediction model for diabetes remission after Roux-en-Y gastric bypass surgery.MethodsPatients who underwent surgery from 2007 until 2017 were included in the study, with collection of individual data from the Scandinavian Obesity Surgery Registry (SOReg), the Swedish National Patients Register, the Swedish Prescribed Drugs Register, and Statistics Sweden. A 7-layer convolution neural network (CNN) model was developed using 80% of patients randomly selected from SOReg and 20% of patients for external testing. The predictive capability of the CNN model and currently used scores (DiaRem, Ad-DiaRem, DiaBetter and IMS) were compared.ResultsIn total, 8057 patients with T2D were included in the study. At 2 years after surgery 77.1% achieved pharmacological remission, while 62.2% achieved complete remission. The area under the receiver operating curve (AUC) for the CNN-model for pharmacological remission was 0.85 [95% confidence interval (CI): 0.83-0.86] during validation, and 0.83 for the final test, which was 9-12% better than the traditional predictive indices. AUC for complete remission was 0.83 (95% CI: 0.81-0.85) during validation, and 0.82 for the final test, which was 9-11% better than the traditional predictive indices.ConclusionThe CNN method had better predictive capability compared to traditional indices for diabetes remission. However, further validation is needed in other countries to evaluate its external generalizability.
Social innovation research checklist: A crowdsourcing open call and digital hackathon to develop a checklist for research to advance social innovation in health
Authors: Kpokiri Eneyi , Chen Elizabeth , Li Jingjing , Payne Sarah , Shrestha Priyanka , Afsana Kaosar , Amazigo Uche , Awor Phyllis , de Lavison Jean-Francois , Khan Saqif , Mier-Alpaño Jana D. , Ong Alberto , Subhedar Shivani , Wachmuth Isabelle , Mehta Kala M. , Halpaap Beatrice , Tucker Joseph D. 
Published: November 2020

AbstractWhile social innovations in health have shown promise in closing the healthcare delivery gap, especially in low- and middle-income countries (LMICs), more research is needed to evaluate, scale up, and sustain social innovations. Research checklists can standardize and improve reporting of research findings, promote transparency, and increase replicability of study results and findings. This article describes the development of a 17-item social innovation in health research checklist to assess and report social innovation projects and provides examples of good reporting. The checklist is adapted from the TIDieR checklist and will facilitate more complete and transparent reporting and increase end user engagement.Summary pointsWhile many social innovations have been developed and shown promise in closing the healthcare delivery gap, more research is needed to evaluate social innovationThe Social Innovation in Health Research Checklist, the first of its kind, is a 17-item checklist to improve reporting completeness and promote transparency in the development, implementation, and evaluation of social innovations in healthThe research checklist was developed through a three-step process, including a global open call for ideas, a scoping review, and a three-round modified Delphi processUse of this research checklist will enable researchers, innovators and partners to learn more about the process and results of social innovation in health research
Experiences of living with mental health problems during the COVID-19 pandemic in the UK: a coproduced, participatory qualitative interview study
Authors: Gillard Steven , Dare Ceri , Hardy Jackie , Nyikavaranda Patrick , Olive Rachel Rowan , Shah Prisha , Birken Mary , Foye Una , Ocloo Josephine , Pearce Ellie , Stefanidou Theodora , Pitman Alexandra , Simpson Alan , Johnson Sonia , Lloyd-Evans Brynmor 
Published: November 2020

AbstractPurposeResearch is beginning to quantify the impact of COVID-19 on people with pre-existing mental health conditions. Our paper addresses a lack of in-depth qualitative research exploring their experiences and perceptions of how life has changed at this time.MethodsWe used qualitative interviews (N=49) to explore experiences of the pandemic for people with pre-existing mental health conditions. In a participatory, coproduced approach, researchers with lived experiences of mental health conditions conducted interviews and analysed data as part of a multi-disciplinary research team.ResultsExisting mental health difficulties were exacerbated for many people. People experienced specific psychological impacts of the pandemic, struggles with social connectedness, and inadequate access to mental health services, while some found new ways to cope and connect to community. New remote ways to access mental health care, including digital solutions, provided continuity of care for some but presented substantial barriers for others. People from black and ethnic minority (BAME) communities experienced heightened anxiety, stigma and racism associated with the pandemic, further impacting their mental health.ConclusionThere is a need for evidence-based solutions to achieve accessible and effective mental health care in response to the pandemic, especially remote approaches to care. Further research should explore the long-term impacts of COVID-19 on people with pre-existing mental health conditions. Particular attention should be paid to understanding inequalities of impact on mental health, especially for people from BAME communities.
Infection patterns of endemic human coronaviruses in rural households in coastal Kenya
Authors: Nyaguthii Dickson Machira , Otieno Grieven P. , Kombe Ivy K. , Koech Dorothy , Mutunga Martin , Medley Graham F. , Nokes D. James , Munywoki Patrick K. 
Published: November 2020

AbstractIntroductionThe natural history and transmission patterns of endemic human coronaviruses are of increased interest following the emergence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2).MethodsIn rural Kenya 483 individuals from 47 households were followed for six months (2009-10) with nasopharyngeal swabs collected twice weekly regardless of symptoms. A total of 16,918 swabs were tested for human coronavirus (hCoV) OC43, NL63 and 229E and other respiratory viruses using polymerase chain reaction.ResultsFrom 346 (71.6%) household members 629 hCoV infection episodes were defined with 36.3% being symptomatic: varying by hCoV type and decreasing with age. Symptomatic episodes (aHR=0.6 (95% CI:0.5-0.8) or those with elevated peak viral load (medium aHR=0.4 (0.3-0.6); high aHR=0.31 (0.2-0.4)) had longer viral shedding compared to their respective counterparts. Homologous reinfections were observed in 99 (19.9%) of 497 first infections. School-age children (55%) were the most common index cases with those having medium (aOR=5.3 (2.3 – 12.0)) or high (8.1 (2.9 - 22.5)) peak viral load most often generating secondary cases.ConclusionHousehold coronavirus infection was common, frequently asymptomatic and mostly introduced by school-age children. Secondary transmission was influenced by viral load of index cases. Homologous-type reinfection was common. These data may be insightful for SARS-CoV-2.
Metabolic characterization of plasma and cyst fluid from cystic precursors to pancreatic cancer patients reveal metabolic signatures of bacterial infection
Authors: Morgell Ann , Reisz Julie A. , Ateeb Zeeshan , Davanian Haleh , Reinsbach Susanne E. , Halimi Asif , Gaiser Rogier , Valente Roberto , Arnelo Urban , Chiaro Marco Del , Sällberg Chen Margaret , D’Alessandro Angelo 
Published: November 2020

AbstractPancreatic cancer is the seventh leading cause of cancer-related death worldwide, with a 5-year survival rate as low as 9%. One factor complicating the management of pancreatic cancer is the lack of reliable tools for early diagnosis. While up to 50% of the adult population has been shown to develop precancerous pancreatic cysts, limited and insufficient approaches are currently available to determine whether a cyst is going to progress into pancreatic cancer. Recently, we used metabolomics approaches to identify candidate markers of disease progression in patients diagnosed with intraductal papillary mucinous neoplasms (IPMNs) undergoing pancreatic resection. Here we enrolled an independent cohort to verify the candidate markers from our previous study with orthogonal quantitative methods in plasma and cyst fluid from serous cystic neoplasm and IPMN (either low- or high-grade dysplasia or pancreatic ductal adenocarcinoma). We thus validated these markers with absolute quantitative methods through the auxilium of stable isotope-labelled internal standards in a new independent cohort. Finally, we identified novel markers of IPMN status and disease progression – including amino acids, carboxylic acids, conjugated bile acids, free and carnitine-conjugated fatty acids, purine oxidation products and TMAO. We show that the levels of these metabolites of potential bacterial origin correlated with the degree of bacterial enrichment in the cyst, as determined by 16S RNA. Overall, our findings are interesting per se, owing to the validation of previous markers and identification of novel small molecule signatures of IPMN and disease progression. In addition, our findings further fuel the provoking debate as to whether bacterial infections may represent an etiological contributor to the development and severity of the disease in pancreatic cancer, in like fashion to other cancers (e.g.,Helicobacter pyloriand gastric cancer).Key pointsWe identified and quantified novel markers of IPMN cyst status and pancreatic cancer disease progression – including amino acids, carboxylic acids, conjugated bile acids, free and carnitine-conjugated fatty acids, purine oxidation products and TMAO.We show that the levels of these metabolites of potential bacterial origin correlated with the degree of bacterial enrichment in the cyst, as determined by 16S RNA.
Whole-genome sequencing reveals new Alzheimer’s disease-associated rare variants in loci related to synaptic function and neuronal development
Authors: Prokopenko Dmitry , Morgan Sarah L. , Mullin Kristina , Hofmann Oliver , Chapman Brad , Kirchner Rory , Amberkar Sandeep , Wohlers Inken , Lange Christoph , Hide Winston , Bertram Lars , Tanzi Rudolph E. 
Published: November 2020

AbstractINTRODUCTIONGenome-wide association studies have led to numerous genetic loci associated with Alzheimer’s disease (AD). Whole-genome sequencing (WGS) now permit genome-wide analyses to identify rare variants contributing to AD risk.METHODSWe performed single-variant and spatial clustering-based testing on rare variants (minor allele frequency ≤1%) in a family-based WGS-based association study of 2,247 subjects from 605 multiplex AD families, followed by replication in 1,669 unrelated individuals.RESULTSWe identified 13 new AD candidate loci that yielded consistent rare-variant signals in discovery and replication cohorts (4 from single-variant, 9 from spatial-clustering), implicating these genes: FNBP1L, SEL1L, LINC00298, PRKCH, C15ORF41, C2CD3, KIF2A, APC, LHX9, NALCN, CTNNA2, SYTL3, CLSTN2.DISCUSSIONDownstream analyses of these novel loci highlight synaptic function, in contrast to common AD-associated variants, which implicate innate immunity. These loci have not been previously associated with AD, emphasizing the ability of WGS to identify AD-associated rare variants, particularly outside of coding regions.