bluuebunny/crossref_metadata_2025_split huggingface dataset:
UKCTOCS Update: Applying insights of delayed effects in cancer screening trials to the long-term follow-up mortality analysis
Authors: Burnell Matthew , Gentry-Maharaj Aleksandra , Skates Steven J , Ryan Andy , Karpinskyj Chloe , Kalsi Jatinderpal , Apostolidou Sophia , Singh Naveena , Dawnay Anne , Woolas Robert , Fallowfield Lesley , Campbell Stuart , McGuire Alistair , Jacobs Ian J , Parmar Mahesh , Menon Usha 
Published: November 2020

AbstractBackgroundDuring trials that span decades, new evidence including progress in statistical methodology, may require revision of original assumptions. An example is the continued use of a constant-effect approach to analyse the mortality reduction which is often delayed in cancer-screening trials. The latter led us to re-examine our approach for the upcoming primary mortality analysis(2020) of long-term follow-up of the United Kingdom Collaborative Trial of Ovarian Cancer Screening (LTFU UKCTOCS), having initially(2014) used the proportional hazards(PH) Cox-model.MethodsWe wrote to 12 experts in statistics/epidemiology/screening-trials, setting out current evidence, importance of pre-specification, previous mortality analysis (2014) and three possible choices for the follow-up analysis (2020) of the mortality outcome - (A)all data(2001-2020) using the Cox-model(2014) (B)new data(2015-2020) only (C)all data(2001-2020) using a test that allows for delayed effects.ResultsOf 11 respondents, eight supported changing the 2014-approach to allow for a potential delayed effect (optionC), suggesting various tests while three favoured retaining the Cox-model (optionA). Consequently, we opted for the Versatile test introduced in 2016 which maintains good power for early, constant or delayed effects. We retained the Royston-Parmar model to estimate absolute differences in disease-specific mortality at 5,10,15 and 18 years.ConclusionsThe decision to alter the follow-up analysis for the primary outcome on the basis of new evidence and using new statistical methodology for long-term follow-up is novel and has implications beyond UKCTOCS. There is an urgent need for consensus building on how best to design, test, estimate and report mortality outcomes from long-term randomised cancer screening trials.Trial registration: (ISRCTN22488978, Registration date: 6/4/2000)
Automated Segmentation of Amyloid-βStained Whole Slide Images of Brain Tissue
Authors: Lai Zhengfeng , Guo Runlin , Xu Wenda , Hu Zin , Mifflin Kelsey , DeCarli Charles , Dugger Brittany N. , Cheung Sen-ching , Chuah Chen-Nee 
Published: November 2020

AbstractNeurodegenerative disease pathologies have been reported in both grey matter (GM) and white matter (WM) with different density distributions, an automated separation of GM/WM would be extremely advantageous for aiding in neuropathologic deep phenotyping. Standard segmentation methods typically involve manual annotations, where a trained researcher traces the delineation of GM/WM in ultra-high-resolution Whole Slide Images (WSIs). This method can be time-consuming and subjective, preventing the analysis of large amounts of WSIs at scale. This paper proposes an automated segmentation pipeline combining a Convolutional Neural Network (CNN) module for segmenting GM/WM regions and a post-processing module to remove artifacts/residues of tissues as well as generate XML annotations that can be visualized via Aperio ImageScope. First, we investigate two baseline models for medical image segmentation: FCN, and U-Net. Then we propose a patch-based approach, ResNet-Patch, to classify the GM/WM/background regions. In addition, we integrate a Neural Conditional Random Field (NCRF) module, ResNet-NCRF, to model and incorporate the spatial correlations among neighboring patches. Although their mechanisms are greatly different, both U-Net and ResNet-Patch/ResNet-NCRF achieve Intersection over Union (IoU) of more than 90% in GM and more than 80% in WM, while ResNet-Patch achieves 1% superior to U-Net with lower variance among various WSIs. ResNet-NCRF further improves the IoU by 3% for WM compared to ResNet-Patch before post-processing. We also apply gradient-weighted class activation mapping (Grad-CAM) to interpret the segmentation masks and provide relevant explanations and insights.
Dissociation Between Individual Differences in Self-Reported Pain Intensity and Underlying Brain Activation
Authors: Hoeppli M.E. , Nahman-Averbuch H. , Hinkle W.A. , Leon E. , Peugh J. , Lopez-Sola M. , King C.D. , Goldschneider K.R. , Coghill R.C. 
Published: November 2020

AbstractPain is a uniquely individual experience. Previous studies have highlighted changes in brain activation and morphology associated with inter- and intra-individual pain perception. In this study we sought to characterize brain mechanisms associated with individual differences in pain in a large sample of healthy participants (N = 101). Pain ratings varied widely across individuals. Moreover, individuals reported changes in pain evoked by small differences in stimulus intensity in a manner congruent with their pain sensitivity, further supporting the utility of subjective reporting as a measure of the true individual experience. However, brain activation related to inter-individual differences in pain was not detected, despite clear sensitivity of the BOLD signal to small differences in noxious stimulus intensities within individuals. These findings raise questions about the utility of fMRI as an objective measure to infer reported pain intensity.
Noradrenergic Regulation of Two-Armed Bandit Performance
Authors: Swanson Kyra , Averbeck Bruno B. , Laubach Mark 
Published: November 2020

AbstractReversal learning depends on cognitive flexibility. Many reversal learning studies assess cognitive flexibility based on the number of reversals that occur over a test session. Reversals occur when an option is repeatedly chosen, e.g. eight times in a row. This design feature encourages win-stay behavior and thus makes it difficult to understand how win-stay decisions influence reversal performance. We used an alternative design, reversals over blocks of trials independent of performance, to study how perturbations of the medial orbital cortex and the noradrenergic system influence reversal learning. We found that choice accuracy varies independently of win-stay behavior and the noradrenergic system controls sensitivity to positive feedback during reversal learning.
Comparing global and regional maps of intactness in the boreal region of North America: Implications for conservation planning in one of the world’s remaining wilderness areas
Authors: Vernier Pierre , Leroux Shawn , Cumming Steve , Lisgo Kim , Esteban Alberto Suarez , Krawchuck Meg , Schmiegelow Fiona 
Published: November 2020

AbstractThough North America’s boreal forest contains some of the largest remaining intact and wild ecosystems in the world, human activities are systematically reducing its extent. Consequently, forest intactness and human influence maps are increasingly used for monitoring and conservation planning in the boreal region. We compare eight forest intactness and human impact maps to provide a multi-model assessment of intactness in the boreal region. All maps are global in extent except for Global Forest Watch Canada’s Human Access (2000) and Intact Forest Landscapes (2000, 2013) maps, although some global maps are restricted to areas that were at least 20% treed. As a function of each map’s spatial coverage in North America, the area identified as intact ranged from 55% to 79% in Canada and from 32% to 96% in Alaska. Likewise, the similarity between pairs of datasets in the Canadian boreal ranged from 0.58 to 0.86 on a scale of 0-1. In total, 45% of the region was identified as intact by the seven most recent datasets. There was also variation in the ability of the datasets to account for anthropogenic disturbances that are increasingly common in the boreal region, such as those associated with resource extraction. In comparison to a recently developed high resolution regional disturbance dataset, the four human influence datasets (Human Footprint, Global Human Modification, Large Intact Areas, and Anthropogenic Biomes), in particular, omitted 59-85% of all linear disturbances and 54-89% of all polygonal disturbances. In contrast, the global IFL, Canadian IFL, and Human Access maps omitted 2-7% of linear disturbances and 0.1-5% of polygonal disturbances. Several differences in map characteristics, including input datasets and methods used to develop the maps may help explain these differences. Ultimately, the decision on which dataset to use will depend on the objectives of each specific conservation planning project, but we recommend using datasets that 1) incorporate regional anthropogenic activities, 2) are updated regularly, 3) provide detailed information of the methods and input data used, and 4) can be replicated and adapted for local use. This is especially important in landscapes that are undergoing rapid change due to development, such as the boreal forest of North America.
Impact of the COVID-19 pandemic on Older Adults Mental Health Services: a mixed methods study
Authors: Bhome Rohan , Huntley Jonathan , Dalton- Locke Christian , Vera San Juan Norha , Oram Sian , Foye Una , Livingston Gill 
Published: November 2020

AbstractPurposeThe Covid-19 pandemic is likely to have a significant impact on older adults mental health care. Our study aimed to explore staff perspectives on key challenges and innovations, to help inform the delivery of older adults mental health care in subsequent waves of the pandemic.MethodsA mixed methods online questionnaire developed by NIHR Mental Health Policy Research Unit (MHPRU) was used to gather staff perspectives on their challenges at work, problems faced by service users and their carers, and sources of help and support. Descriptive statistics were used for quantitative analysis and descriptive content analysis for qualitative analysis.Results158 participants, working in either community or inpatient settings, and from a range of professional disciplines, were included. For inpatient staff, a significant challenge was infection control. In the community, staff identified a lack of access to physical and social care as well as reduced contact with friends and families as being challenges for patients. Remote working was seen as a positive innovation along with Covid-19 related guidance from various sources and peer support.ConclusionOur study, with a focus on staff and patient well-being, helps to inform service development for future waves of the pandemic. We discuss measures to improve infection control in inpatient settings, the role of voluntary organisations in supporting socially isolated community patients, the need for better integration of physical and mental health services at an organisational level, and the importance of training staff to support patients and their families with end of life planning.
Occurrence of cardiovascular complications associated with SARS-CoV-2 infection: a systematic review
Authors: Sardinha Daniele Melo , Lima Karla VB , Ueno Thalyta MRL , Rodrigues Yan Correa , Garcez Juliana CD , Santos Anderson LS , Ferreira Ana LS , Guimaraes Ricardo JPS , Lima Luana NGC 
Published: November 2020

AbstractCardiovascular Diseases represent the main cause of death in the world, and are associated with risk factors that cause serious complications in cases of infections, such as those of the respiratory tract. In March 2020 the World Health Organization declared a pandemic for SARS-CoV-2, a new coronavirus causing severe pneumonia, which emerged in December 2019 in Wuhan, China. The objective is to investigate the occurrence of cardiovascular complications associated with SARS-CoV-2 infection. It is a systematic review, quantitative, in the databases, PubMed and Science direct, including primary studies with hospitalized patients confirmed for COVID-19 and who presented cardiovascular complications, the form used tools for evaluation of quality and evidence, following the PRISMA recommendations. Results: 12 studies were included. The occurrence of cardiovascular complications was: 27.35% of the sample of 3,316 patients. Types: Acute cardiac injury 17.09%; Thromboembolism 4.73%; Heart failure 3.43%; Arrhythmias 1.77%; stroke 0.33%. Mean age 61 years. Conclusions: This study showed that there are several cardiovascular complications associated with SARS-CoV-2, that the main one is acute cardiac injury, which causes several instabilities in the cardiopulmonary system, and that it is associated with mortality.
Detection of the SARS-CoV-2 spike protein in saliva with Shrinky-Dink© electrodes
Authors: Zakashansky Julia A. , Imamura Amanda H. , Salgado Darwin F. , Romero Mercieca Heather C. , Aguas Raphael F.L. , Lao Angelou M. , Pariser Joseph , Arroyo-Currás Netzahualcóyotl , Khine Michelle 
Published: November 2020

AbstractUsing the children’s toy, Shrinky-Dink ©, we present an aptamer-based electrochemical (E-AB) assay that recognizes the spike protein of SARS-CoV-2 in saliva for viral infection detection. The low-cost electrodes are implementable at population scale and demonstrate detection down to 0.1 fg mL−1 of the S1 subunit of the spike protein.
SARS-CoV-2 causes a different cytokine response compared to other cytokine storm-causing respiratory viruses in severely ill patients
Authors: Olbei Marton , Hautefort Isabelle , Modos Dezso , Treveil Agatha , Poletti Martina , Gul Lejla , Shannon-Lowe Claire D , Korcsmaros Tamas 
Published: November 2020

AbstractHyper-induction of pro-inflammatory cytokines, also known as a cytokine storm or cytokine release syndrome (CRS) is one of the key aspects of the currently ongoing SARS-CoV-2 pandemic. This process occurs when a large number of innate and adaptive immune cells are activated, and start producing pro-inflammatory cytokines, establishing an exacerbated feedback loop of inflammation. It is one of the factors contributing to the mortality observed with COVID-19 for a subgroup of patients. CRS is not unique to SARS-CoV-2 infection; it was prevalent in most of the major human coronavirus and influenza A subtype outbreaks of the past two decades (H5N1, SARS-CoV, MERS-CoV, H7N9). Here, we collected changing cytokine levels upon infection with the aforementioned viral pathogens through a comprehensive literature search. We analysed published patient data to highlight the conserved and unique cytokine responses caused by these viruses. A map of such responses could help specialists identify interventions that successfully alleviated CRS in different diseases and evaluate whether they could be used in COVID-19 cases.
Phe2vec: Automated Disease Phenotyping based on Unsupervised Embeddings from Electronic Health Records
Authors: De Freitas Jessica K. , Johnson Kipp W. , Golden Eddye , Nadkarni Girish N. , Dudley Joel T. , Bottinger Erwin P. , Glicksberg Benjamin S. , Miotto Riccardo 
Published: November 2020

AbstractObjectiveRobust phenotyping of patient data from electronic health records (EHRs) at scale is a current challenge in the field of clinical informatics. We introduce Phe2vec, an automated framework for disease phenotyping from EHRs based on unsupervised learning, and we assess its effectiveness against standard rule-based algorithms from the Phenotype KnowledgeBase (PheKB).Materials and MethodsPhe2vec is based on pre-computing embeddings of medical concepts and patients’ longitudinal clinical history. Disease phenotypes are then derived from a seed concept and its neighbors in the embedding space. Patients are similarly linked to a disease if their embedded representation is close to the phenotype. We implemented Phe2vec using 49,234 medical concepts from structured EHRs and clinical notes from 1,908,741 patients in the Mount Sinai Health System. We assessed performance on ten diverse diseases that have a PheKB algorithm.ResultsPhe2vec phenotypes derived using Word2vec, GloVe, and Fasttext embeddings led to promising performance in disease definition and patient cohort identification with respect to phenotypes and cohorts obtained by PheKB. When comparing Phe2vec and PheKB disease patient cohorts head-to-head using chart review, Phe2vec performed on par or better in nine out of ten diseases in terms of positive predictive values.DiscussionPhe2vec offers a solution to improve time-consuming phenotyping pipelines. Differently from other approaches in the literature, it is data-driven and unsupervised, can easily scale to any disease and was validated against widely adopted expert-based standards.ConclusionPhe2vec aims to optimize clinical informatics research by augmenting current frameworks to characterize patients by condition and derive reliable disease cohorts.
Sediment Selection: Range Expanding Fiddler Crabs are Better Burrowers Than Their Historic Range Counterparts
Authors: Wong Richard J , Roy Michael S. , Byrnes Jarrett E. K. 
Published: November 2020

ABSTRACTSpecies ranges are shifting in response to climate change. In New England saltmarshes, the mud fiddler crab,Minuca pugnax, is expanding north of Cape Cod, MA into the Gulf of Maine (GoM) due to warming waters. The burrowing lifestyle ofM. pugnaxmeans sediment compaction in saltmarshes may influence the ability for crabs to dig, with more compact soils being resilient to burrowing. Previous studies indicate that saltmarshes along the GoM have higher soil strength (i.e., compaction) relative to marshes south of Cape Cod. Together, physical characteristics and temperature of this habitat may be influencing the burrowing performance ofM. pugnax, and therefore the continuation of their northward range expansion into the GoM. To determine if compaction affects burrowing activity ofM. pugnaxin historical and range expanded populations, we conducted a controlled laboratory experiment. We manipulated soil compaction in standardized lab assays and measured crab burrowing performance with individuals collected from Nantucket (i.e., historical range) and the Plum Island Estuary (PIE, i.e., expanded range). We determined compaction negatively affected burrowing ability in crabs from both sites; however, crabs from PIE burrowed in higher soil compactions than Nantucket crabs. In addition, PIE crabs were more likely to burrow overall. We conclude that site level differences in compaction are likely altering burrowing behavior in the crab’s expanded range territory by way of phenotypic plasticity or rapid evolution. Our study demonstrates that non-temperature physical habitat traits can be as important as temperature in influencing climate driven range expansions.
Machine learning aided top-down proteomics on a microfluidic platform
Authors: Zhang Yuewen , Wright Maya A. , Saar Kadi L. , Challa Pavankumar , Morgunov Alexey S. , Peter Quentin A. E. , Devenish Sean , Dobson Christopher M. , Knowles Tuomas P.J. 
Published: November 2020

AbstractThe ability to determine the identity of specific proteins is a critical challenge in many areas of cellular and molecular biology, and in medical diagnostics. Here, we present a microfluidic protein characterisation strategy that within a few minutes generates a three-dimensional fingerprint of a protein sample indicative of its amino acid composition and size and, thereby, creates a unique signature for the protein. By acquiring such multidimensional fingerprints for a set of ten proteins and using machine learning approaches to classify the fingerprints, we demonstrate that this strategy allows proteins to be classified at a high accuracy, even though classification using a single dimension is not possible. Moreover, we show that the acquired fingerprints correlate with the amino acid content of the samples, which makes it is possible to identify proteins directly from their sequence without requiring any prior knowledge about the fingerprints. These findings suggest that such a multidimensional profiling strategy can lead to the development of novel method for protein identification in a microfluidic format.
The Network Analysis Profiler (NAP v2.0): A web tool for visual topological comparison between multiple networks
Authors: Koutrouli Mikaela , Theodosiou Theodosios , Iliopoulos Ioannis , Pavlopoulos Georgios A. 
Published: November 2020

ABSTRACTIn this article we present the Network Analysis Profiler (NAP v2.0), a web tool to directly compare the topological features of multiple networks simultaneously. NAP is written in R and Shiny and currently offers both 2D and 3D network visualization as well as simultaneous visual comparisons of node- and edge-based topological features both as bar charts or as a scatterplot matrix. NAP is fully interactive and users can easily export and visualize the intersection between any pair of networks using Venn diagrams or a 2D and a 3D multi-layer graph-based visualization. NAP supports weighted, unweighted, directed, undirected and bipartite graphs and is available at:http://bib.fleming.gr:3838/NAP/. Its code can be found at:https://github.com/PavlopoulosLab/NAP
Data-driven streamflow modelling in ungauged basins: regionalizing random forest (RF) models
Authors: Araza Arnan , Hein Lars , Duku Confidence , Rawlins Maurice Andres , Lomboy Richard 
Published: November 2020

AbstractStreamflow predictions in ungauged basins (PUB) has been geared towards data-driven methods, including the use of machine learning methods such as random forest (RF). Such methods are applied in PUB regionalization or the transfer of a streamflow model from gauged to ungauged (sub) basins or watersheds after grouping watersheds on similarity rules. Regionalized streamflow models are needed for tropical-mountainous regions like Luzon, Philippines - where gauged data is limited - but demands on streamflow modelling for water resources accounting and management are high. In 21 watersheds in Luzon, we “regionalize” RF streamflow models after grouping watersheds based on: a principal components analysis (PCA-clustered), by major river basins (basin-clustered), whole study area scale (one-clustered). Another method without watershed grouping (watershed-level) was also included and inter-compared. Among the four methods, goodness-of-fit evaluations revealed that PCA-clustered method was higher by at most 0.35 coefficient of determinationR2and 0.31 nash-sutcliffe efficiencyNSE, and the least bias in 8 of 12 monthly flows. These are attributed to the added-value of homogeneous watershed grouping, reflected by higher importance (to RF models), of static covariates from open and high-resolution data. Normalized errors from monthly streamflow showed a clear bias (least with the PCA-clustered metohd), linked to season and water management practices in the study area. Ungauged watersheds in the Philippines can effectively use streamflow models from gauged watersheds if they belong to the same cluster.Key PointsUngauged sub-basins (watersheds) can effectively use RF streamflow models from gauged watersheds if both belong to the same cluster.Biophysical data from high-resolution open data are valuable: as basis for watershed clustering and as streamflow predictors to RF models.The predicted streamflow from the RF models reflects seasonal deviations in streamflow caused by natural and man-made water regulation