bluuebunny/crossref_metadata_2025_split huggingface dataset:
Acupuncture combined with Tongxieyaofang for diarrhea-type irritable bowel syndrome
Authors: Li Yi-Lin , Yao Cheng-Jiao , Lei Rong , Xie Fengjiao , Xiong Qin , Luo Li-Hong , Feng Pei-Min 
Published: November 2020

Abstract

Background:
As a traditional Chinese medicine external treatment method, acupuncture is characterized by simple operation, significant treatment effect and few side effects. Tong-Xie-Yao-Fang (TXYF), a Chinese patent medicine, combined with acupuncture has been widely used on treating Diarrhea Predominant Irritable Bowel Syndrome (IBS-D). However, the efficacy and safety of TXYF combined with acupuncture for the treatment of IBS-D are unclear. This study aims to investigate verify the efficacy and safety of TXYF combined with acupuncture for IBS-D.

Methods and analysis:
Randomized controlled trials of TXYF combined with acupuncture for all IBS-D will be searched in PubMed, the Cochrane Library, Embase, Web of Science, the China National Knowledge Infrastructure, Wanfang Database, Chinese Science and Technology Periodical Database, and Chinese Biomedical Literature Database from inception to October 20, 2020. And Baidu Scholar, Google Scholar, International Clinical Trials Registry Platform, and Chinese Clinical Trials Registry will be searched to obtain more relevant studies comprehensively. The methodological qualities, including the risk of bias, will be evaluated using the Cochrane risk of bias assessment tool, while confidence in the cumulative evidence will be evaluated using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Two researchers will perform data extraction and risk of bias assessment independently. Statistical analysis will be conducted in RevMan 5.3.

Results:
Based on the current evidence, the potential rank of the efficacy and safety of TXYF plus acupuncture for IBS-D will be assessed.

Conclusion:
The findings of the study will provide helpful evidence for the efficacy and safety of TXYF combined with acupuncture in the treatment of IBS-D, facilitating clinical practice and further scientific studies.
Is the Moon the future of infrared astronomy?
Authors: Maillard Jean-Pierre 
Published: November 2020

Infrared astronomy, particularly in spectroscopy, could benefit in a decisive way from an implementation of telescopes on the Moon since the largest telescopes on Earth are practically limited to 40 m and in space to 10 m. On the Moon, a collector larger than on Earth becomes conceivable, thanks to the low gravity and the absence of wind, in having the advantages of space. Passively cooled in the bottom of a permanently shadowed crater at the northern or the southern pole, it could reach unprecedented spectral sensitivity on a large part of the infrared domain, making possible spectral analysis of the most primitive galaxies and of the terrestrial exoplanet atmospheres. A project aiming at the detection of the weak cosmic microwave background spectral distortions is also presented. Several identical 1.5 m cryo-cooled telescopes at 2.5 K to fit in a launcher, with an imaging Fourier transform spectrometer in each unit, deposited in a cold crater and pointing in the same direction in lunar survey mode, would build for this fundamental goal the equivalent of a large telescope at an extremely low temperature. Last, the feasibility of these projects is discussed.
This article is part of a discussion meeting issue ‘Astronomy from the Moon: the next decades (part 1)'.
EMBEDR: Distinguishing Signal from Noise in Single-Cell Omics Data
Authors: Johnson Eric , Kath William , Mani Madhav 
Published: November 2020

AbstractWhile single-cell “omics” based measurements hold the promise of unparalleled biological insight they remain a challenge to analyze owing to their high-dimensional nature. As a result, Dimensionality Reduction (DR) algorithms are necessary for data visualization and for downstream quantitative analysis. The lack of a principled methodology for separating signal from noise in DR algorithmic outputs has limited the confident application of these methods in unsupervised analyses of single-cell data, greatly hampering researchers’ ability to make data-driven discoveries. In this work we present an approach to quality assessment,EMBEDR, that works in conjunction with any DR algorithm to distinguish signal from noise in dimensionally-reduced representations of high-dimensional data. We apply EMBEDR to t-SNE- and UMAP-generated representations of published scRNA-seq data, revealing where lower-dimensional representations of the data are faithful renditions of biological signal in the data, and where they are more consistent with noise. EMBEDR produces easily interpreted p-values for each cell in a data set, facilitating the comparison of different DR methods and allowing optimization of their global hyperparameters. Most compellingly, EMBEDR allows for the analysis of single-cell data at a single-cell resolution, allowing DR methods to be used in a cell-wise optimal manner. Applying this technique to real data results in a biologically interpretable view of the data with no user supervision. We demonstrate the utility of EMBEDR in the context of several data sets and DR algorithms, illustrating its robustness and flexibility as well as its potential for making rigorous, quantitative analyses of single-cell omics data. EMBEDR is available as a Python package for immediate use.
Community Transmission of SARS-CoV-2 by Fomites: Risks and Risk Reduction Strategies
Authors: Pitol Ana K. , Julian Timothy R. 
Published: November 2020

AbstractSARS-CoV-2, the virus responsible for the COVID-19 pandemic, is perceived to be primarily transmitted via person-to-person contact, through droplets produced while talking, coughing, and sneezing. Transmission may also occur through other routes, including contaminated surfaces; nevertheless, the role that surfaces have on the spread of the disease remains contested. Here we use the Quantitative Microbial Risk Assessment framework to examine the risks of community transmission of SARS-CoV-2 through contaminated surfaces and to evaluate the effectiveness of hand and surface disinfection as potential interventions. The risks posed by contacting surfaces in communities are low (average of the median risks 1.6×10−4- 5.6×10−9) for community infection prevalence rates ranging from 0.2-5%. Hand disinfection substantially reduces relative risks of transmission independently of the disease’s prevalence and the frequency of contact, even with low (25% of people) or moderate (50% of people) compliance. In contrast, the effectiveness of surface disinfection is highly dependent on the prevalence and the frequency of contacts. The work supports the current perception that contaminated surfaces are not a primary mode of transmission of SARS-CoV-2 and affirms the benefits of making hand disinfectants widely available.
Single cell profiling of COVID-19 patients: an international data resource from multiple tissues
Authors:   Chan Zuckerberg Initiative Single-Cell COVID-19 Consortia, Ballestar Esteban , Farber Donna L. , Glover Sarah , Horwitz Bruce , Meyer Kerstin , Nikolić Marko , Ordovas-Montanes Jose , Sims Peter , Shalek Alex , Vandamme Niels , Vandekerckhove Linos , Vento-Tormo Roser , Villani Alexandra Chloe 
Published: November 2020

[Abstract]In late 2019 and through 2020, the COVID-19 pandemic swept the world, presenting both scientific and medical challenges associated with understanding and treating a previously unknown disease. To help address the need for great understanding of COVID-19, the scientific community mobilized and banded together rapidly to characterize SARS-CoV-2 infection, pathogenesis and its distinct disease trajectories. The urgency of COVID-19 provided a pressing use-case for leveraging relatively new tools, technologies, and nascent collaborative networks. Single-cell biology is one such example that has emerged over the last decade as a powerful approach that provides unprecedented resolution to the cellular and molecular underpinnings of biological processes. Early foundational work within the single-cell community, including the Human Cell Atlas, utilized published and unpublished data to characterize the putative target cells of SARS-CoV-2 sampled from diverse organs based on expression of the viral receptor ACE2 and associated entry factors TMPRSS2 and CTSL (Muus et al., 2020; Sungnak et al., 2020; Ziegler et al., 2020). This initial characterization of reference data provided an important foundation for framing infection and pathology in the airway as well as other organs. However, initial community analysis was limited to samples derived from uninfected donors and other previously-sampled disease indications. This report provides an overview of a single-cell data resource derived from samples from COVID-19 patients along with initial observations and guidance on data reuse and exploration.
Antibody response patterns in COVID-19 patients with different levels of disease severity—Japan
Authors: Imai Kazuo , Kitagawa Yutaro , Tabata Sakiko , Kubota Katsumi , Nagura-Ikeda Mayu , Matsuoka Masaru , Miyoshi Kazuyasu , Sakai Jun , Ishibashi Noriomi , Tarumoto Norihito , Takeuchi Shinichi , Ito Toshimitsu , Maesaki Shigefumi , Tamura Kaku , Maeda Takuya 
Published: November 2020

AbstractBackgroundWe analyzed antibody response patterns according to level of disease severity in patients with novel coronavirus disease 2019 (COVID-19) in Japan.MethodsWe analyzed 611 serum specimens from 231 patients with COVID-19 (mild, 170; severe, 31; critical, 30). IgM and IgG antibodies against nucleocapsid protein (N) and spike 1 protein (S1) were detected by enzyme-linked immunosorbent assays.FindingsThe peaks of fitting curves for the OD values of IgM and IgG antibodies against N appeared simultaneously, while those against S1 were delayed compared with N. The OD values of IgM against N and IgG against both N and S1 were significantly higher in the severe and critical cases than in the mild cases at 11 days after symptom onset. The seroconversion rates of IgG were higher than those of IgM against both N and S1 during the clinical course based on the optimal cut-off values defined in this study. The seroconversion rates of IgG and IgM against N and S1 were higher in the severe and critical cases than in the mild cases.ConclusionOur findings show that a stronger antibody response occurred in COVID-19 patients with greater disease severity and there were low seroconversion rates of antibodies against N and S1 in the mild cases. The antibody response patterns in our population suggest a second infection pattern, leading us to hypothesize that cross-reactivity occurs between SARS-CoV-2 and past infection with other human coronaviruses.
A Data Driven Change-point Epidemic Model for Assessing the Impact of Large Gathering and Subsequent Movement Control Order on COVID-19 Spread in Malaysia
Authors: Dass Sarat C. , Kwok Wai M. , Gibson Gavin J. , Gill Balvinder S. , Sundram Bala M. , Singh Sarbhan 
Published: November 2020

AbstractThe second wave of COVID-19 in Malaysia is largely attributed to a mass gathering held in Sri Petaling between February 27, 2020 and March 1, 2020, which contributed to an exponential rise of COVID-19 cases in the country. Starting March 18, 2020, the Malaysian government introduced four consecutive phases of a Movement Control Order (MCO) to stem the spread of COVID-19. The MCO was implemented through various non-pharmaceutical interventions (NPIs). The reported number of cases reached its peak by the first week of April and then started to reduce, hence proving the effectiveness of the MCO. To gain a quantitative understanding of the effect of MCO on the dynamics of COVID-19, this paper develops a class of mathematical models to capture the disease spread before and after MCO implementation in Malaysia. A heterogeneous variant of the Susceptible-Exposed-Infected-Recovered (SEIR) model is developed with additional compartments for asymptomatic transmission. Further, a change-point is incorporated to model the before and after disease dynamics, and is inferred based on data. Related statistical analyses for inference are developed in a Bayesian framework and are able to provide quantitative assessments of (1) the impact of the Sri Petaling gathering, and (2) the extent of decreasing transmission during the MCO period. The analysis here also quantitatively demonstrates how quickly transmission rates fall under effective NPI implemention within a short time period.
Clinical judgement of General Practitioners for the diagnosis of dementia: a diagnostic test accuracy study
Authors: Creavin Samuel Thomas , Haworth Judy , Fish Mark , Cullum Sarah , Bayer Antony , Purdy Sarah , Ben-Shlomo Yoav 
Published: November 2020

BackgroundThe accuracy of General Practitioners’ (GPs’) clinical judgement for dementia is uncertain.AimInvestigate the accuracy of GPs’ clinical judgement for the diagnosis of dementia.Design and SettingDiagnostic test accuracy study, recruiting from 21 practices around Bristol.MethodThe clinical judgement of the treating GP (index test) was based on the information immediately available at their initial consultation with a person aged over 70 years who had cognitive symptoms. The reference standard was an assessment by a specialist clinician, based on a standardised clinical examination and made according to ICD-10 criteria for dementia.Results240 people were recruited, with a median age of 80 years (IQR 75 to 84 years), of whom 126 (53%) were men and 132 (55%) had dementia. The median duration of symptoms was 24 months (IQR 12 to 36 months) and the median ACE-III score was 75 (IQR 65 to 87). GP clinical judgement had sensitivity 56% (95% CI 47% to 65%) and specificity 89% (95% CI 81% to 94%). Positive likelihood ratio was higher in people aged 70-79 years (6.5, 95% CI 2.9 to 15) compared to people aged ≥ 80 years (3.6, 95% CI 1.7 to 7.6), and in women (10.4, 95% CI 3.4 to 31.7) compared to men (3.2, 95% CI 1.7 to 6.2), whereas the negative likelihood ratio was similar in all groups.ConclusionA GP clinical judgement of dementia is specific, but confirmatory testing is needed for symptomatic people who GPs judge as not having dementia.How this fits inPrevious studies in this area have investigated the accuracy of GP clinical judgement as a screening test for dementia in unselected people attending a primary care clinic; or as a retrospective test based on their knowledge of their patient; or derived the accuracy of judgement from the medical records, which may not reflect the judgement of the clinician. The role of the GP in supporting a more effective route to diagnosis for people with dementia is a research priority for patients, carers and clinicians. This study shows that, in a symptomatic older adult, prospective clinical judgement may be useful for helping to confirm a diagnosis of dementia, whereas GP judgement should not by itself be used to exclude dementia.
ANTIBODY RESPONSE TO COVID-19 INFECTION- CLINICAL VARIABLES AT PLAY
Authors: Parkash Anuj , Singla Parul , Bhatia Meenu 
Published: November 2020

ABSTRACTBackgroundThe current COVID19 pandemic began in December 2019 and rapidly expanded to become a global pandemic. The COVID 19 presents multitude of clinical disorders, ranges from asymptomatic infection to severe disease, which can accompanied by multisystem failure leading to death. The immune response to SARS CoV 2 is understood to involve all the components of the system that together causes viral elimination and recovery from the infection. However, such immune responses implicated in the disease has varied presentation ranging from mild to a severe form, which appears to hinge on the loss of the immune regulation between protective and altered responses. In this study, we want to unravel this association of immune responses to various clinical variables, which might have a major role to play, while generating the immune response. The objective was to test this hypothesis in our settings and comparing the results of serologic tests from a group of COVID 19 patients and will analyzed the disease severity in comparison.MethodsTesting for SARS COV2 IgG Antibody was done with chemiluminescent assay on the Ortho Clinical Diagnostic’s (OCD) Vitros 5600 platform.ResultsA total of 106 COVID 19 patients were included in this study, of whom 61 were male and 45 were female. Their mean age was 43.7 years (range 17–83) and the median interval between initial symptom onset and sample collection was 12.33 days. Eighty patients (82%) had mild or moderate symptoms and twenty-six patients (18%) had severe symptoms. The antibody titers were positive in 99 patients (93%) and were found negative in 7 patients (7%). When comparing patients with mild/moderate symptoms and patients with severe/critical diseases, no statistically significant difference was observed between their gender ratios (P = 0.373) and age composition (P = 0.224).ConclusionsThe data presented in this research study did not find any statistical significance between SARS CoV 2 IgG antibody levels with COVID 19 disease severity, duration of symptoms, age, gender, and length of convalescence.
Quantifying the potential value of antigen-detection rapid diagnostic tests for COVID-19: a modelling analysis
Authors: Ricks Saskia , Kendall Emily A. , Dowdy David W. , Sacks Jilian A. , Schumacher Samuel G. , Arinaminpathy Nimalan 
Published: November 2020

AbstractBackgroundTesting plays a critical role in treatment and prevention responses to the COVID-19 pandemic. Compared to nucleic acid tests (NATs), antigen-detection rapid diagnostic tests (Ag-RDTs) can be more accessible, but typically have lower sensitivity and specificity. By quantifying these trade-offs, we aimed to inform decisions about when an Ag-RDT would offer greater public health value than reliance on NAT.MethodsFollowing an expert consultation, we selected two use cases for analysis: rapid identification of people with COVID-19 amongst patients admitted with respiratory symptoms in a ‘hospital’ setting; and early identification and isolation of people with mildly symptomatic COVID-19 in a ‘community’ setting. Using decision analysis, we evaluated the cost and impact (deaths averted and infectious days isolated) of an Ag-RDT-led strategy, compared to a strategy based on NAT and clinical judgment. We performed a multivariate sensitivity analysis to identify key parameters.ResultsIn a hospital setting, an Ag-RDT-led strategy would avert more deaths than a NAT-based strategy, and at lower cost per death averted, when the sensitivity of clinical judgement is less than 85%, and when NAT results are available in time to inform clinical decision-making for less than 90% of patients. The use of an Ag-RDT is robustly supported in community settings, where it would avert more transmission at lower cost than relying on NAT alone, under a wide range of assumptions.ConclusionsDespite their imperfect sensitivity and specificity, Ag-RDTs have the potential to be simultaneously more impactful, and cost-effective, than current approaches to COVID-19 diagnostic testing.
Increased Systemic HSP70B Levels in Spinal Muscular Atrophy Infants
Authors: Eichelberger Eric J. , Alves Christiano R. R. , Zhang Ren , Petrillo Marco , Cullen Patrick , Farwell Wildon , Hurt Jessica A , Staropoli John F. , Swoboda Kathryn J. 
Published: November 2020

AbstractDespite newly available treatments for spinal muscular atrophy (SMA), novel circulating biomarkers are still critically necessary to track SMA progression and therapeutic response. To identify potential biomarkers, we performed whole-blood RNA sequencing analysis in SMA type 1 subjects under 1 year old and age-matched healthy controls. Our analysis revealed the Heat Shock Protein Family A Member 7 (HSPA7) as a novel candidate biomarker to track SMA progression early in life. Changes in circulating HSPA7 protein levels were associated with changes in circulating neurofilaments levels in SMA newborns and infants. Future studies will determine whether HSPA7 levels respond to molecular therapies.
Acute Day Units for mental health crises: A qualitative study of service user and staff views and experiences
Authors: Morant Nicola , Davidson Michael , Wackett Jane , Lamb Danielle , Pinfold Vanessa , Smith Deb , Johnson Sonia , Lloyd-Evans Brynmor , Osborn David P J 
Published: November 2020

AbstractBackgroundAcute Day Units (ADUs) provide intensive, non-residential, short-term treatment for adults in mental health crisis. They currently exist in approximately 30% of health localities in England, but there is little research into their functioning or effectiveness, and how this form of crisis care is experienced by service users. This qualitative study explores the views and experiences of stakeholders who use and work in ADUs.MethodsWe conducted 36 semi-structured interviews with service users, staff and carers at four ADUs in England. Data were analysed using thematic analysis.ResultsBoth service users and staff provided generally positive accounts of using or working in ADUs. Valued features were structured programmes that provide routine, meaningful group activities, and opportunities for peer contact and emotional, practical and peer support, within a ‘safe’ environment. Aspects of ADU care were often described as enabling personal and social connections that contribute to shifting from crisis to recovery. ADUs were compared favourably to other forms of home- and hospital-based acute care, particularly in providing more therapeutic input and social contact. Some service users and staff thought ADU lengths of stay should be extended slightly, and staff described some ADUs being under-utilised or poorly-understood by referrers in local acute care systems.ConclusionsMulti-site qualitative data suggests that ADUs provide a distinctive and valued contribution to acute care systems, and can avoid known problems associated with other forms of acute care, such as low user satisfaction, stressful ward environments, and little therapeutic input or positive peer contact. Findings suggest there may be grounds for recommending further development and more widespread implementation of ADUs to increase choice within local acute care systems.
Comparing Machine Learning Algorithms for Predicting ICU Admission and Mortality in COVID-19
Authors: Subudhi Sonu , Verma Ashish , Patel Ankit B. , Hardin C. Corey , Khandekar Melin J. , Lee Hang , Stylianopoulos Triantafyllos , Munn Lance L. , Dutta Sayon , Jain Rakesh K. 
Published: November 2020

AbstractAs predicting the trajectory of COVID-19 disease is challenging, machine learning models could assist physicians determine high-risk individuals. This study compares the performance of 18 machine learning algorithms for predicting ICU admission and mortality among COVID-19 patients. Using COVID-19 patient data from the Mass General Brigham (MGB) healthcare database, we developed and internally validated models using patients presenting to Emergency Department (ED) between March-April 2020 (n = 1144) and externally validated them using those individuals who encountered ED between May-August 2020 (n = 334). We show that ensemble-based models perform better than other model types at predicting both 5-day ICU admission and 28-day mortality from COVID-19. CRP, LDH, and procalcitonin levels were important for ICU admission models whereas eGFR <60 ml/min/1.73m2, ventilator use, and potassium levels were the most important variables for predicting mortality. Implementing such models would help in clinical decision-making for future COVID-19 and other infectious disease outbreaks.