bluuebunny/crossref_metadata_2025_split huggingface dataset:
The relation between short- and long-term deformation in actively deforming plate boundary zones
Authors: Lamb Simon 
Published: February 2021

Satellite-based measuring systems are making it possible to monitor deformation of the Earth's surface at a high spatial resolution over periods of several decades and a significant fraction of the seismic cycle. It is widely assumed that this short-term deformation directly reflects the long-term pattern of crustal deformation, although modified in detail by local elastic effects related to locking on individual faults. This way, short-term deformation is often jointly inverted with long-term estimates of fault slip rates, or even stress, over periods of 10 s to 100 s kyrs. Here, I examine the relation between these two timescales of deformation for subduction, continental shortening and rifting tectonic settings, with examples from the active New Zealand and Central Andean plate boundary zone. I show that the relation is inherently non-unique, and simple models of locking on a deep-seated megathrust or decollement, or mantle flow, provide excellent fits to the short-term observations without requiring any information about the geometry and rate of surface faulting. The short-term deformation, in these settings at least, cannot be used to determine the behaviour of individual faults, but instead places constraints on the forces that drive deformation. Thus, there is a fundamental difference between the stress loading and stress relief parts of the earthquake cycle, with failure determined by dynamical rather than kinematic constraints; the same stress loading can give rise to widely different modes of long-term deformation, depending on the strength and rheology of the deforming zone, and the role of gravitational stresses. The process of slip on networks of active faults may have an intermediate timescale of kyrs to 10 s kyrs, where individual faults fail piecemeal without any characteristic behaviour. Physics-based dynamical models of short-term deformation may be the best way to make full use of the increasing quality of this type of data in the future.This article is part of a discussion meeting issue ‘Understanding earthquakes using the geological record’.
Caspase-6-cleaved tau is relevant in Alzheimer’s disease but not in other tauopathies: diagnostic and therapeutic implications
Authors: Theofilas Panos , Piergies Antonia M.H. , Li Song Hua , Petersen Cathrine , Ehrenberg Alexander J. , Eser Rana A. , Chin Brian , Yang Teddy , Khan Shireen , Ng Raymond , Spina Salvatore , Seeley Willian W. , Miller Bruce L. , Arkin Michelle R. , Grinberg Lea T. 
Published: February 2021

AbstractAimTau truncation (tr-tau) by active caspase-6 (aCasp-6) generates toxic tau fragments prone to self-aggregation. Yet, the relationship between aCasp-6, different forms of tr-tau, and hyperphosphorylated tau (p-tau) accumulation in human brains with Alzheimer’s disease (AD) and other tauopathies remains unclear.MethodsWe generated two neoepitope monoclonal antibodies against tr-tau sites (D402 and D13) targeted by aCasp-6. Then, we used 5-plex immunofluorescence to quantify the neuronal and astroglial burden of aCasp-6, tr-tau, p-tau, and their co-occurrence in healthy controls, AD, and primary tauopathies.ResultsCasp-6 activation was strongest in AD, followed by Pick’s disease (PiD), but almost absent in 4-repeat (4R) tauopathies. In neurons, the tr-tau burden was much more abundant in AD than in 4R tauopathies, and disproportionally higher when normalizing by p-tau pathology. Tr-tau astrogliopathy was detected in low numbers in 4R tauopathies. Unexpectedly, about half of tr-tau positive neurons in AD lacked p-tau aggregates.ConclusionsEarly modulation of aCasp-6 to reduce tr-tau pathology is a promising therapeutic strategy for AD, and possibly PiD, but is unlikely to benefit 4R tauopathies. The large percentage of tr-tau-positive neurons lacking p-tau suggests that not all neurons that are vulnerable to tau pathology are detected by a conventional p-tau Ser 202 antibody and that AD has distinct mechanisms of tangle formation. Therapeutic strategies against tr-tau pathology could be necessary to modulate tau abnormalities in AD. The disproportionally higher burden of tr-tau in AD supports the investigation of biofluid biomarkers against N-terminus tr-tau, which could detect AD and differentiate it from 4R tauopathies at a single patient level.3 - sentence summaryTau truncation (tr-tau) by active caspase-6 (aCasp-6) generates toxic tau fragments prone to self-aggregation, but the relationship between aCasp-6, tr-tau, and hyperphosphorylated tau (p-tau) accumulation in Alzheimer’s disease (AD) and other tauopathies remains unclear. We generated two neoepitope monoclonal antibodies against tr-tau sites (D402 and D13) targeted by aCasp-6 and used 5-plex immunofluorescence to quantify the neuronal and astroglial burden of aCasp-6, tr-tau, p-tau, and their co-occurrence in brains from healthy controls, AD, and primary tauopathies. We detected relatively high Casp-6 activation in AD, followed by Pick’s disease (PiD). aCasp-6 was almost absent in 4-repeat (4R) tauopathies, suggesting that early modulation of aCasp-6 to reduce tr-tau pathology is a promising therapeutic strategy in AD, and possibly PiD, but is unlikely to benefit 4R tauopathies.
Discrimination of SARS-Cov 2 and arboviruses (DENV, ZIKV and CHIKV) clinical features using machine learning techniques: a fast and inexpensive clinical screening for countries simultaneously affected by both diseases
Authors: Castro João Daniel S. 
Published: February 2021

AbstractSARS-Cov-2 (Covid-19) has spread rapidly throughout the world, and especially in tropical countries already affected by outbreaks of arboviruses, such as Dengue, Zika and Chikungunya, and may lead these locations to a collapse of health systems. Thus, the present work aims to develop a methodology using a machine learning algorithm (Support Vector Machine) for the prediction and discrimination of patients affected by Covid-19 and arboviruses (DENV, ZIKV and CHIKV). Clinical data from 204 patients with both Covid-19 and arboviruses obtained from 23 scientific articles and 1 dataset were used. The developed model was able to predict 93.1% of Covid-19 cases and 82.1% of arbovirus cases, with an accuracy of 89.1% and Area under Roc Curve of 95.6%, proving to be effective in prediction and possible screening of these patients, especially those affected by Covid-19, allowing early isolation.
Predicting Prognosis in COVID-19 Patients using Machine Learning and Readily Available Clinical Data
Authors: Campbell Thomas W. , Wilson Melissa P. , Roder Heinrich , MaWhinney Samantha , Georgantas Robert W. , Maguire Laura K. , Roder Joanna , Erlandson Kristine M. 
Published: February 2021

AbstractRationalePrognostic tools for aiding in the treatment of hospitalized COVID-19 patients could help improve outcome by identifying patients at higher or lower risk of severe disease.ObjectivesThe study objective was to develop models to stratify patients by risk of severe outcomes during COVID-19 hospitalization using readily available information at hospital admission.MethodsHierarchical ensemble classification models were trained on a set of 229 patients hospitalized with COVID-19 to predict severe outcomes, including ICU admission, development of ARDS, or intubation, using easily attainable attributes including basic patient characteristics, vital signs at admission, and basic lab results collected at time of presentation. Each test stratifies patients into groups of increasing risk. An additional cohort of 330 patients was used for blinded, independent validation. Shapley value analysis evaluated which attributes contributed most to the models’ predictions of risk.Measurements and Main ResultsTest performance was assessed using precision (positive predictive value) and recall (sensitivity) of the final risk groups. All test cut-offs were fixed prior to blinded validation. In both development and validation, the tests achieved precision in the lowest risk groups near or above 0.9. The proportion of patients with severe outcomes significantly increased across increasing risk groups. While the importance of attributes varied by test and patient, CRP, LDH, and D-dimer were often found to be important in the assignment of risk label.ConclusionsRisk of severe outcomes for patients hospitalized with COVID-19 infection can be assessed using machine learning-based models based on attributes routinely collected at hospital admission.
DeepRank: A deep learning framework for data mining 3D protein-protein interfaces
Authors: Renaud Nicolas , Geng Cunliang , Georgievska Sonja , Ambrosetti Francesco , Ridder Lars , Marzella Dario , Bonvin Alexandre M.J.J. , Xue Li C 
Published: February 2021

AbstractThree-dimensional (3D) structures of protein complexes provide fundamental information to decipher biological processes at the molecular scale. The vast amount of experimentally and computationally resolved protein-protein interfaces (PPIs) offers the possibility of training deep learning models to aid the predictions of their biological relevance.We present here DeepRank, a general, configurable deep learning framework for data mining PPIs using 3D convolutional neural networks (CNNs). DeepRank maps features of PPIs onto 3D grids and trains a user-specified CNN on these 3D grids. DeepRank allows for efficient training of 3D CNNs with data sets containing millions of PPIs and supports both classification and regression.We demonstrate the performance of DeepRank on two distinct challenges: The classification of biological versus crystallographic PPIs, and the ranking of docking models. For both problems DeepRank is competitive or outperforms state-of-the-art methods, demonstrating the versatility of the framework for research in structural biology.
HashSeq: A Simple, Scalable, and ConservativeDe NovoVariant Caller for 16S rRNA Gene Datasets
Authors: Fouladi Farnaz , Young Jacqueline B. , Fodor Anthony A. 
Published: February 2021

Abstract16S rRNA gene sequencing is a common and cost-effective technique for characterization of microbial communities. Recent bioinformatics methods enable high-resolution detection of sequence variants of only one nucleotide difference. In this manuscript, we utilize a very fast HashMap-based approach to detect sequence variants in six publicly available 16S rRNA gene datasets. We then use the normal distribution combined with LOESS regression to estimate background error rates as a function of sequencing depth for individual clusters of sequences. This method is computationally efficient and produces inference that yields sets of variants that are conservative and well supported by reference databases. We argue that this approach to inference is fast, simple, scalable to large datasets, and provides a high-resolution set of sequence variants which are less likely to be the result of sequencing error.
Multi-Tissue Multi-Compartment models of diffusion MRI
Authors: Frigo Matteo , Fick Rutger H.J. , Zucchelli Mauro , Deslauriers-Gauthier Samuel , Deriche Rachid 
Published: February 2021

AbstractState-of-the-art multi-compartment microstructural models of diffusion MRI (dMRI) in the human brain have limited capability to model multiple tissues at the same time. In particular, the available techniques that allow this multi-tissue modelling are based on multi-TE acquisitions. In this work we propose a novel multi-tissue formulation of classical multi-compartment models that relies on more common single-TE acquisitions and can be employed in the analysis of previously acquired datasets. We show how modelling multiple tissues provides a new interpretation of the concepts of signal fraction and volume fraction in the context of multi-compartment modelling. The software that allows to inspect single-TE diffusion MRI data with multi-tissue multi-compartment models is included in the publicly available Dmipy Python package.
Metformin protects against insulin resistance induced by high uric acid in cardiomyocytes via AMPK signaling pathways in vitro and in vivo
Authors: Jiao Zhenyu , Chen Yingqun , Xie Yang , Li Yanbing , Li Zhi 
Published: February 2021

AbstractHigh uric acid (HUA) is associated with insulin resistance and abnormal glucose metabolism in cardiomyocytes. Metformin is a recognized agonist of AMP-activated protein kinase (AMPK) and an antidiabetic drug widely used for type 2 diabetes. It can play a cardioprotective role in many pathways. We investigated whether metformin protects against HUA-induced insulin resistance and abnormal glucose metabolism in cardiomyocytes. We exposed primary cardiomyocytes to HUA, and cellular glucose uptake was quantified by measuring the uptake of 2-NBDG, a fluorescent glucose analog, after insulin excitation. Treatment with metformin (10 μmol/L) protected against HUA-inhibited glucose uptake induced by insulin in primary cardiomyocytes, as shown by fluorescence microscopy and flow cytometry analysis. HUA directly inhibited the phosphorylation of Akt and the translocation of glucose transporter type 4 (GLUT4) induced by insulin, which was blocked by metformin. Metformin promoted phosphorylation of AMPK, renewed HUA-inhibited glucose uptake induced by insulin and protected against insulin resistance in cardiomyocytes. As a result of these effects, in a mouse model of acute hyperuricemia, metformin improved insulin tolerance and glucose tolerance, accompanied by increased AMPK phosphorylation, Akt phosphorylation and translocation of GLUT4 in myocardial tissues. As expected, AICAR, another AMPK activator, had equivalent effects to metformin, demonstrating the important role of AMPK activation in protecting against insulin resistance induced by HUA in cardiomyocytes. Metformin protects against insulin resistance induced by HUA in cardiomyocytes and improves insulin tolerance and glucose tolerance in an acute hyperuricemic mouse model, along with the activation of AMPK. Consequently, metformin may be an important potential new treatment strategy for hyperuricemia-related cardiovascular disease.
Nrg1/ErbB Signaling-Mediated Regulation of Fibrosis After Myocardial Infarction
Authors: Shiraishi Manabu , Yamaguchi Atsushi , Suzuki Ken 
Published: February 2021

AbstractRATIONALEAppropriate fibrotic tissue formation after myocardial infarction (MI) is crucial to maintenance of the heart’s structure. Reparative or M2-like macrophages play a vital role in post-MI fibrosis by activating cardiac fibroblasts. However, the mechanism by which post-MI cardiac fibrosis is regulated is not fully understood.OBJECTIVEWe investigated the cellular and molecular mechanisms of post-MI fibrotic tissue formation, especially those related to regulation of cellular senescence and apoptosis.METHODS AND RESULTSIn vivoandin vitroexperiments were used to investigate the molecular and cellular mechanisms through which post-MI fibrosis occurs, with a focus on the role of M2-like macrophages. Microarray analysis revealed that CD206+F4/80+CD11b+M2-like macrophages collected from mouse hearts on post-MI day 7 showed increased expression of neuregulin 1 (Nrg1). Nrg1 receptor epidermal growth factor receptor ErbB was expressed on cardiac fibroblasts in the infarct area. In cardiac fibroblasts in which hydrogen peroxide-induced senescence, M2-like macrophage-derived Nrg1 suppressed both senescence and apoptosis of the fibroblasts, whereas blockade of ErbB function significantly accelerated. M2-like macrophage-derived Nrg1/ErbB/PI3K/Akt signaling, which was shown to be related to anti-senescence, was activated in damaged cardiac fibroblasts. Interestingly, systemic blockade of ErbB function in MI model mice enhanced senescence and apoptosis of cardiac fibroblasts and exacerbated inflammation. Further, increased accumulation of M2-like macrophages resulted in excessive progression of fibrosis in post-MI murine hearts. The molecular mechanism underlying regulation of fibrotic tissue formation in the infarcted myocardium was shown in part to be attenuation of apoptosis and senescence of cardiac fibroblasts by activation of Nrg1/ErbB/PI3K/Akt signaling.CONCLUSIONSM2-like macrophage-mediated regulation of Nrg1/ErbB signaling, have a substantial effect on fibrotic tissue formation in the infarcted adult mouse heart, is critical for suppressing the progression of senescence and apoptosis of cardiac fibroblasts.
Impact of COVID-19 restrictions on the postpartum experience of women living in Eastern Canada: A mixed method cohort study
Authors: Dol Justine , Richardson Brianna , Aston Megan , Mcmillan Douglas , Tomblin murphy Gail , Campbell-yeo Marsha 
Published: February 2021

AbstractObjectivesTo (1) compare changes in self-efficacy, social support, postpartum anxiety and postpartum depression in Canadian women collected before (Cohort 1) and during the COVID-19 pandemic (Cohort 2); (2) explore the women felt related to having a newborn during the pandemic; and (3) explore ways that women coped.MethodsPrior to the pandemic (October 1, 2019-January 1, 2020), an online survey was conducted with women had given birth within the past six months in one of the three Eastern Canadian Maritime provinces (Cohort 1). A second, similar survey was conducted between August 1, 2020 and October 31, 2020 (Cohort 2) during a period of provincial pandemic response to COVID-19.ResultsFor Cohort 1, 561 women completed the survey and 331 women in Cohort 2. Cohorts were similar in terms of age of women, parity, and age of newborn. There were no significant differences for self-efficacy, social support, postpartum anxiety, and depression between the cohorts. Difficulties that women reported as a result of COVID-19 restrictions included lack of support from family and friends, fear of COVID-19 exposure, feeling isolated and uncertain, negative impact on perinatal care experience, and hospital restrictions. Having support from partners and families, in-person/virtual support, as well as self-care and the low prevalence of COVID-19 during the summer of 2020 helped women cope.ConclusionWhile there was no significant difference in pre-pandemic and during pandemic psychosocial outcomes, there were still challenges and negative impacts that women identified. Consideration of vulnerable populations is important when making public health recommendations.What is already known on this subject?Previous work has shown the importance of social support in the postpartum transition in developing parenting self-efficacy and decreasing postpartum anxiety and depression. However, during the COVID-19 pandemic, women’s mental health, particularly during the perinatal period, has seen an increases in rates of postpartum anxiety and depression.What this study adds?This study is able to compare self-efficacy, social support, postpartum anxiety and depression between two cohorts of postpartum women living in Eastern Canada – pre-COVID-19 pandemic and during. While there was no significant difference in pre-pandemic and during pandemic psychosocial outcomes, there were still challenges and negative impacts that women identified.
Separated and overlapping neural coding of face and body identity
Authors: Foster Celia , Zhao Mintao , Bolkart Timo , Black Michael J. , Bartels Andreas , Bülthoff Isabelle 
Published: February 2021

AbstractRecognising a person’s identity often relies on face and body information, and is tolerant to changes in low-level visual input (e.g. viewpoint changes). Previous studies have suggested that face identity is disentangled from low-level visual input in the anterior face-responsive regions. It remains unclear which regions disentangle body identity from variations in viewpoint, and whether face and body identity are encoded separately or combined into a coherent person identity representation. We trained participants to recognize three identities, and then recorded their brain activity using fMRI while they viewed face and body images of the three identities from different viewpoints. Participants’ task was to respond to either the stimulus identity or viewpoint. We found consistent decoding of body identity across viewpoint in the fusiform body area, right anterior temporal cortex, middle frontal gyrus and right insula. This finding demonstrates a similar function of fusiform and anterior temporal cortex for bodies as has previously been shown for faces, suggesting these regions may play a general role in extracting high-level identity information. Moreover, we could decode identity across neural activity evoked by faces and bodies in the early visual cortex, right inferior occipital cortex, right parahippocampal cortex and right superior parietal cortex, revealing a distributed network that encodes person identity abstractly. Lastly, identity decoding was consistently better when participants attended to identity, indicating that attention to identity enhances its neural representation. These results offer new insights into how the brain develops an abstract neural coding of person identity, shared by faces and bodies.
Disrupted Surfaces of Porous Membranes Reduce Nuclear YAP Localization and Enhance Adipogenesis through Morphological Changes
Authors: Allahyari Zahra , Casillo Stephanie M. , Perry Spencer J. , Peredo Ana P. , Gholizadeh Shayan , Gaborski Thomas R. 
Published: February 2021

ABSTRACTThe disrupted surface of porous membranes, commonly used in tissue-chip and cellular co-culture systems, is known to weaken cell-substrate interactions. Here, we investigated whether disrupted surfaces of membranes with micron and sub-micron scale pores affect YAP localization and differentiation of adipose-derived stem cells (ADSCs). We found that these substrates reduce YAP nuclear localization through decreased cell spreading, consistent with reduced cell-substrate interactions, and in turn enhance adipogenesis, while decreasing osteogenesis.Abstract Figure
Diffuse cutaneous mastocytosis: Identification of KIT mutation and long‐term follow‐up with serum tryptase level
Authors: Shibata Yuka , Hirota Seiichi , Saito Ikuo , Asahina Akihiko 
Published: February 2021

AbstractDiffuse cutaneous mastocytosis (DCM) is the least common subtype of cutaneous mastocytotis and is generally more severe than other subtypes. We herein report a case of DCM with the consequence of a long‐term follow‐up. A 4‐month‐old boy visited with a 3‐month history of diffuse erythema that gradually worsened. Darier's sign was positive. The plasma histamine level was 4.95 ng/mL, and the serum tryptase and c‐Kit (CD117) levels were 33.3 and 27.4 ng/mL, respectively. Histopathology of the biopsied specimen showed dermal papillary edema and infiltration of mast cells identified by c‐Kit and toluidine blue staining. Amplification and direct sequencing of genomic DNA extracted from the skin biopsy specimen revealed the presence of a deletion of codon 419 in exon 8 (c.1255_1257delGAC [p. Asp419del]). There was no evidence of systemic infiltration of mast cells in this case, and we started topical corticosteroid and oral antihistamine with the diagnosis of DCM. Diffuse erythema subsided constantly with age in parallel with chronological decline of serum tryptase level, and it is no longer apparent presently at the age of 7 years, leaving only faint brown spots. Blister formation did not occur throughout the course. Our case indicates that spontaneous resolution can be expected even in DCM after a long period of time, and that serum tryptase level serves as a good surrogate marker to monitor the clinical course.