bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integration of serial self-testing for COVID-19 as part of contact tracing in the Brazilian public health system: A pragmatic trial protocol
Authors: Green Rebecca K. , Manchola Camilo , Gerth-Guyette Emily , Silva Michelle Oliveira , Stephanie Raissa , Santos Soares Tainá dos , Gottin Luiza Bastos , Coelho Milena , Green Kimberly E. , Costa Alexandre Dias Tavares , Pereira Dhélio Batista 
Published: April 2023

AbstractBackgroundThe coronavirus disease (COVID-19) pandemic has led to an unprecedented public health crisis. Insufficient testing continues to limit the effectiveness of the global response to the COVID-19 pandemic. Molecular testing methods such as reverse transcriptase polymerase chain reaction (RT-PCR) continue to be highly centralized and are a sub-optimal option for population surveillance. Rapid antigen tests (Ag-RDTs) offer multiple benefits including low costs, high flexibility to conduct tests in a wide variety of settings, and faster return of results. Recently, self-test Ag-RDTs (STs) have gained approval in several markets and offer the possibility to expand testing, reaching at-risk populations. While STs have the potential to assist the COVID-19 response, test result integrity, reporting, and appropriate linkage to care continue to hinder the widespread implementation of self-testing programs.MethodsThis protocol presents a mixed-methods pragmatic trial (ISRCTN91602092) to better understand the feasibility of self-testing as part of a contact tracing strategy within the Brazilian public health system. Approximately 604 close contacts of 150 index cases testing positive for COVID-19 will be enrolled. Close contacts will be randomized to either serial (daily) self-testing over a 10-day follow-up period or a more traditional approach to contact tracing with a professional Ag-RDT at one time point post-exposure. Usability workshops and focus group discussions will also be conducted.DiscussionThis study protocol presents a comprehensive plan to assess the effectiveness, operational feasibility, and stakeholder preferences of a serial self-testing strategy for contact tracing within the Brazilian public health system. Our results will contribute to better understanding of the feasibility of a self-testing strategy within the public sector. Potential risks and limitations are discussed. Our findings will have important implications as governments continue working to mitigate the impact of COVID-19, particularly in the context of where to direct limited resources for testing and healthcare infrastructure.
Predictors of acute ischemic cerebral lesions in immune-mediated thrombotic thrombocytopenic purpura and hemolytic uremic syndrome
Authors: Neuman Lisa , Joseph Adrien , Bouzid Raïda , Lescroart Mickael , Mariotte Eric , Ederhy Stéphane , Tuffet Sophie , Baudel Jean-Luc , Benhamou Ygal , Galicier Lionel , Grangé Steven , Provôt François , Neel Antoine , Pène Frédéric , Delmas Yahsou , Presne Claire , Poullin Pascale , Wynckel Alain , Perez Pierre , Barbet Christelle , Halimi Jean-Michel , Chatelet Valérie , Rebibou Jean-Michel , Ojeda-Uribe Mario , Vigneau Cécile , Mesnard Laurent , Veyradier Agnès , Azoulay Elie , Coppo Paul , Chabriat Hugues 
Published: April 2023

AbstractBackgroundThe immune form of thrombotic thrombocytopenic purpura (iTTP) and the hemolytic and uremic syndrome (HUS) are two major forms of thrombotic microangiopathy (TMA). Their treatment has been recently greatly improved. In this new era, both the prevalence and predictors of cerebral lesions occurring during the acute phase of these severe conditions remain poorly known.AimThe prevalence and predictors of cerebral lesions appearing during the acute phase of iTTP and shigatoxin-producingEscherichia coli-HUS or atypical HUS were evaluated in a prospective multicenter study.MethodsUnivariate analysis was performed to report the main differences between patients with iTTP and those with HUS or between patients with acute cerebral lesions and the others. Multivariable logistic regression analysis was used to identify the potential predictors of these lesions.ResultsAmong 73 TMA cases (mean age 46.89 ± 15.99 years (range: 21-87 years) with iTTP (n = 57) or HUS (n= 16), one third presented with acute ischemic cerebral lesions on magnetic resonance imagery (MRI); two individuals also had hemorrhagic lesions. One in ten patients had acute ischemic lesions without any neurological symptom. The neurological manifestations did not differ between iTTP and HUS. In multivariable analysis, 3 factors predicted the occurrence of acute ischemic lesions on cerebral MRI: 1) the presence of old infarcts on cerebral MRI, 2) the level of blood pulse pressure, 3) the diagnosis of iTTP.ConclusionCerebral MRI is crucial to detect both symptomatic and covert ischemic lesions at the acute phase of iTTP and HUS and helps identify patients with old infarcts, at the highest risk of neurological worsening. The diagnosis of iTTP further increases the risk of ischemic lesions but also an increased level of blood pressure that may represent a potential target to further improve the therapeutic management of these conditions.Key points-One third of patients with immune-mediated thrombotic thrombocytopenic purpura (iTTP) or the hemolytic uremic syndrome (HUS) present with acute ischemic cerebral lesions on magnetic resonance imagery (MRI);-The cerebral manifestations on MRI did not differ between iTTP and HUS;-The presence of old infarcts on cerebral MRI, the level of blood pulse pressure and a diagnosis of iTTP predict the occurrence of acute ischemic lesions on cerebral MRI.
SaLSa: a combinatory approach of semi-automatic labeling and long short-term memory to classify behavioral syllables
Authors: Sakata Shuzo 
Published: April 2023

AbstractAccurately and quantitatively describing mouse behavior is an important area. Although advances in machine learning have made it possible to track their behaviors accurately, reliable classification of behavioral sequences or syllables remains a challenge. In this study, we present a novel machine learning approach, called SaLSa (a combination of semi-automatic labeling and long short-term memory-based classification), to classify behavioral syllables of mice exploring an open field. This approach consists of two major steps: first, after tracking multiple body parts, spatial and temporal features of their egocentric coordinates are extracted. A fully automated unsupervised process identifies candidates for behavioral syllables, followed by manual labeling of behavioral syllables using a graphical user interface. Second, a long short-term memory (LSTM) classifier is trained with the labeled data. We found that the classification performance was marked over 97%. It provides a performance equivalent to a state-of-the-art model while classifying some of the syllables. We applied this approach to examine how hyperactivity in a mouse model of Alzheimer’s disease (AD) develops with age. When the proportion of each behavioral syllable was compared between genotypes and sexes, we found that the characteristic hyper-locomotion of female AD mice emerges between 4 and 8 months. In contrast, age-related reduction in rearing is common regardless of genotype and sex. Overall, SaLSa enables detailed characterization of mouse behavior.Significance StatementDescribing complex animal behavior is a challenge. Here, we developed an open-source, combinatory approach to behavioral syllable classification, called SaLSa (a combination ofsemi-automatic labeling andlongshort-term memory-based classification). In order to classify behavioral syllables, this approach combines multiple machine learning methods to label video frames semi- automatically and train a deep learning model. To demonstrate SaLSa’s versatility, we monitored the exploratory behavior of an Alzheimer’s disease mouse model and delineated their complex behaviors. We found that female Alzheimer’s mice become hyperactive in the sense that their locomotion behavior, but not other active behaviors, appear more frequently than controls and even male Alzheimer’s mice as they age. SaLSa offers a toolkit to analyze complex behaviors.
Missense variants inPLA2G6contribute to a spectrum of clinical syndromes and provide pharmacogenomic correlates
Authors: Janardhanan Meghana , Anbhazagan Padmanabhan , Viswanath Biju , Balasundaram Padmanabhan , Jain Sanjeev , Purushottam Meera 
Published: April 2023

AbstractBackgroundRisk alleles in a gene for a genetic disorder can often cause a spectrum of syndromes. The number of copies, deleteriousness and position in the sequence could influence phenotype manifestation.MethodsWhole exome sequencing in 310 individuals from 100 families with severe mental illness revealed 851 instances of variants in thePLA2G6gene. We assessed the population frequency and deleteriousness of the nonsynonymous variants usingin-silicoprediction methods. Molecular docking analyses with antipsychotics was performed to investigate possible pharmacogenomic implications of thePLA2G6mutations identified.ResultsWe found six nonsynonymous variants predicted to be deleterious by VarSome. The frequency of non-synonymous variants was found to vary across populations. The preliminary molecular docking analysis suggests that chlorpromazine and risperidone are predicted to bind at three drug-binding sites however, risperidone has a greater binding affinity to PLA2G6. The occurrence of variants close to these drug-binding sites suggests a possible mechanism for the mediation of parkinsonian side effects on drug intake in patients harboring these variants.ConclusionVariants in thePLA2G6, a gene previously known to be associated with Parkinson’s disease may thus contribute to the risk of psychiatric phenotypes, as observed in these 9 individuals from 6 families with severe mental illness.
Integrating multiple single-cell multi-omics samples with Smmit
Authors: Wan Changxin , Ji Zhicheng 
Published: April 2023

ABSTRACTMulti-sample single-cell multi-omics datasets, which simultaneously measure multiple data modalities in the same cells across multiple samples, facilitate the study of gene expression, gene regulatory activities, and protein abundances on a population scale. We developed Smmit, a computational method for integrating data both across samples and modalities. Compared to existing methods, Smmit more effectively removes batch effects while preserving relevant biological information, resulting in superior integration outcomes. Additionally, Smmit is more computationally efficient and builds upon existing computational pipelines, requiring minimal effort for implementation. Smmit is an R software package that is freely available on Github:https://github.com/zji90/Smmit.
BetaBuddy: An end-to-end computer vision pipeline for the automated analysis of insulin secreting β-cells
Authors: Alsup Anne M. , Fowlds Kelli , Cho Michael , Luber Jacob M. 
Published: April 2023

AbstractInsulin secretion from pancreatic β-cells is integral in maintaining the delicate equilibrium of blood glucose levels. Calcium is known to be a key regulator and triggers the release of insulin. This sub-cellular process can be monitored and tracked through live-cell imaging and subsequent cell segmentation, registration, tracking, and analysis of the calcium level in each cell. Current methods of analysis typically require the manual outlining of β-cells, involve multiple software packages, and necessitate multiple researchers - all of which tend to introduce biases. Utilizing deep learning algorithms, we have therefore created a pipeline to automatically segment and track thousands of cells, which greatly reduces the time required to gather and analyze a large number of sub-cellular images and improve accuracy. Tracking cells over a time-series image stack also allows researchers to isolate specific calcium spiking patterns and spatially identify those of interest, creating an efficient and user-friendly analysis tool. Using our automated pipeline, a previous dataset used to evaluate changes in calcium spiking activity in β-cells post-electric field stimulation was reanalyzed. Changes in spiking activity were found to be underestimated previously with manual segmentation. Moreover, the machine learning pipeline provides a powerful and rapid computational approach to examine, for example, how calcium signaling is regulated by intracellular interactions in a cluster of β-cells.
Structured memory representations develop at multiple time scales in hippocampal-cortical networks
Authors: Tambini Arielle , Miller Jacob , Ehlert Luke , Kiyonaga Anastasia , D’Esposito Mark 
Published: April 2023

AbstractInfluential views of systems memory consolidation posit that the hippocampus rapidly forms representations of specific events, while neocortical networks extract regularities across events, forming the basis of schemas and semantic knowledge. Neocortical extraction of schematic memory representations is thought to occur on a protracted timescale of months, especially for information that is unrelated to prior knowledge. However, this theorized evolution of memory representations across extended timescales, and differences in the temporal dynamics of consolidation across brain regions, lack reliable empirical support. To examine the temporal dynamics of memory representations, we repeatedly exposed human participants to structured information via sequences of fractals, while undergoing longitudinal fMRI for three months. Sequence-specific activation patterns emerged in the hippocampus during the first 1-2 weeks of learning, followed one week later by high-level visual cortex, and subsequently the medial prefrontal and parietal cortices. Schematic, sequence-general representations emerged in the prefrontal cortex after 3 weeks of learning, followed by the medial temporal lobe and anterior temporal cortex. Moreover, hippocampal and most neocortical representations showed sustained rather than time-limited dynamics, suggesting that representations tend to persist across learning. These results show that specific hippocampal representations emerge early, followed by both specific and schematic representations at a gradient of timescales across hippocampal-cortical networks as learning unfolds. Thus, memory representations do not exist only in specific brain regions at a given point in time, but are simultaneously present at multiple levels of abstraction across hippocampal-cortical networks.
The Effect of E-Cigarettes on the Human Heart Studied using Cardiomyocytes Generated from Induced Pluripotent Stem Cells
Authors: Bhowmik Ava T. , Zhao Shane R. , Wu Joseph C. 
Published: April 2023

AbstractAlthough many dangerous effects of smoking e-cigarettes on lungs have come to light, limited and only qualitative efforts have been made to analyze the impact of e-cigarettes on the human heart directly. In this study, we experimentally determined e-liquid cardiotoxicity in both healthy cells and cells with long QT syndrome by treating healthy and diseased human cardiomyocytes with e-liquids with varying nicotine concentrations. These cardiomyocytes were generated from human induced pluripotent stem cells. The cardiomyocytes were divided into 5 groups, a control group and 4 test groups, each treated with e-liquid containing varying amounts of nicotine between 0% and 70%. The cells’ biological indicators such as heart rate, pulse pressure, essential protein concentration, and metabolic activity, were measured and characterized using three different functional assays: contractility, Western blot, and viability, and tracked over 4 days. The results demonstrated that acute exposure to e-liquid led to tachycardia, hypertension, decreased protein levels, and cell death. The rate of cardiotoxicity increases with higher nicotine concentrations. The basal fluid also showed non-negligible toxicity. Under identical conditions, the functionality of the diseased heart cells declined at a faster rate compared to healthy cells. Overall, this work establishes the harmful physiological effects of e-cigarettes on the human heart quantitatively.
Overactivated epithelial NF-κB disrupts lung development in human and nitrofen CDH
Authors: Dylong Florentine , Riedel Jan , Amonkar Gaurang M. , Peukert Nicole , Lieckfeldt Paula , Sturm Katinka , Höxter Benedikt , Tse Wai Hei , Miyake Yuichiro , Mayer Steffi , Keijzer Richard , Lacher Martin , Ai Xingbin , Gosemann Jan-Hendrik , Wagner Richard 
Published: April 2023

AbstractBackground & ObjectiveAbnormal lung development is the main cause of morbidity and mortality in neonates with congenital diaphragmatic hernia (CDH), a common birth defect (1:2500) of largely unknown pathobiology. Recent studies discovered that inflammatory processes, and specifically NF-κB associated pathways are enriched in human and experimental CDH. However, the molecular signaling of NF-κB in abnormal CDH lung development and its potential as a therapeutic target requires further investigation.Methods & ResultsUsing sections and hypoplastic lung explant cultures from the nitrofen rat model of CDH and human fetal CDH lungs, we demonstrate that NF-κB and its downstream transcriptional targets are hyperactive during abnormal lung formation in CDH. NF-κB activity was especially elevated in the airway epithelium of nitrofen and human CDH lungs at different developmental stages. Fetal rat lung explants had impaired pseudoglandular airway branching after exposure to nitrofen, together with increased phosphorylation and transcriptional activity of NF-κB. Dexamethasone, the broad and clinically applicable anti-inflammatory NF-κB antagonist, rescued lung branching and normalized NF-κB signaling in hypoplastic lung explants. Moreover, specific NF-κB inhibition with curcumenol similarly rescuedex vivolung hypoplasia and restored NF-κB signaling. Lastly, we showed that prenatal intraperitoneal dexamethasone administration to pregnant rat dams carrying fetuses with hypoplastic lungs, significantly improves lung branching and normalizes NF-κBin vivo. Conclusions: Our results indicate that NF-κB is aberrantly activated in human and nitrofen CDH lungs. Anti-inflammatory treatment with dexamethasone and/ or specific NF-κB inhibition should be investigated further as a therapeutic avenue to target lung hypoplasia in CDH.
Bullying, mental health and absenteeism: A moderated mediation approach
Authors: Léné Alexandre 
Published: April 2023

PurposeThis study aims to examine the role of mental health disorders (anxiety and depression) underlying the relationship between bullying and absenteeism. Moreover, the author tested the potentially moderating role that job autonomy, supervisor and colleagues’ support may play in the relationship between bullying and mental health disorders.Design/methodology/approachA moderated mediation analysis was conducted with a sample of French workers, controlling for their individual characteristics and their working conditions. The sample comprised 22,661 employees. This sample is representative of the French working population.FindingsThe results showed that the positive relationship between workplace bullying and absenteeism was partially mediated by anxiety and depression. In addition, job autonomy and supervisor support appear to be moderators of bullying effects. Regarding the moderating role of colleagues support, the study’s results are more nuanced.Originality/valueMany studies show that exposure to workplace bullying increases the risk of developing mental health problems and sickness absence. This study extends previous studies by proposing a more comprehensive understanding of how and when bullying results in absenteeism. In particular, this study identified some moderators that can mitigate the harmful effects of workplace bullying on mental health and absenteeism. This study contributes to the literature on this subject by showing that organizations can reduce the potentially negative effects of workplace bullying. Organizational resources can help make individuals capable of coping with aggression. They thus contribute to their resilience.
From Austrian theory of capital to dissent: Nicholas Kaldor, Friedrich A. Hayek and the way to disequilibrium
Authors: Telles Keanu 
Published: April 2023

PurposeIn the early 1930s, Nicholas Kaldor could be classified as an Austrian economist. The author reconstructs the intertwined paths of Kaldor and Friedrich A. Hayek to disequilibrium economics through the theoretical deficiencies exposed by the Austrian theory of capital and its consequences on equilibrium analysis.Design/methodology/approachThe author approaches the discussion using a theoretical and historical reconstruction based on published and unpublished materials.FindingsThe integration of capital theory into a business cycle theory by the Austrians and its shortcomings – e.g. criticized by Piero Sraffa and Gunnar Myrdal – called attention to the limitation of the theoretical apparatus of equilibrium analysis in dynamic contexts. This was a central element to Kaldor’s emancipation in 1934 and his subsequent conversion to John Maynard Keynes’ The General Theory of Employment, Interest, and Money (1936). In addition, it was pivotal to Hayek’s reformulation of equilibrium as a social coordination problem in “Economics and Knowledge” (1937). It also had implications for Kaldor’s mature developments, such as the construction of the post-Keynesian models of growth and distribution, the Cambridge capital controversy, and his critique of neoclassical equilibrium economics.Originality/valueThe close encounter between Kaldor and Hayek in the early 1930s, the developments during that decade and its mature consequences are unexplored in the secondary literature. The author attempts to construct a coherent historical narrative that integrates many intertwined elements and personas (e.g. the reception of Knut Wicksell in the English-speaking world; Piero Sraffa’s critique of Hayek; Gunnar Myrdal’s critique of Wicksell, Hayek, and Keynes; the Hayek-Knight-Kaldor debate; the Kaldor-Hayek debate, etc.) that were not connected until now by previous commentators.
Precursors and outcomes of satisfaction of fair trade coffee consumers
Authors: Mili Samira , Ferro-Soto Carlos 
Published: April 2023

PurposeThis paper aims to identify the antecedents and postcedents of customer satisfaction, including utilitarian, social and emotional factors, in a fair trade (FT) coffee consumption context.Design/methodology/approachThis paper is based on a broad range of 177 consumers of FT coffee in Spain, the data analysis used structural equation modeling (SEM) with SPSS/AMOS 26.0 software.FindingsThis paper supports that both customer social value and quality affect perceived value (PV). PV in turn has effects on customer satisfaction and the latter influences loyalty. Conversely, both customer emotional value and customer expectations were not confirmed as antecedents of PV.Research limitations/implicationsThe consumer satisfaction analysis conducted differs substantially from those of conventionally traded coffee, as social and emotional factors were considered along with utilitarian factors.Practical implicationsPractitioners, retailers and relevant institutions should design strategies to manage efficiently channel efforts to improve the consumer satisfaction and its loyalty.Originality/valueThis paper contributes to a substantial improvement in the understanding of consumer satisfaction and its consequences, in FT coffee consumption contexts. A new integrated theoretical model on customer satisfaction has been provided, which includes social and emotional perception factors, along with cognitive perception (quality and expectations) factors.