bluuebunny/crossref_metadata_2025_split huggingface dataset:
Differences in Cardiac Magnetic Resonance Imaging Markers Between Patients With COVID-19-associated Myocardial Injury and Patients With Clinically Suspected Myocarditis
Authors: Maurus Stephan , Weckbach Ludwig T. , Marschner Constantin , Kunz Wolfgang G. , Ricke Jens , Kazmierczak Philip M. , Bieber Stephanie , Brado Johannes , Kraechan Angelina , Hellmuth Johannes C. , Hausleiter Joerg , Massberg Steffen , Grabmaier Ulrich , Curta Adrian 
Published: June 2021

Purpose:
Coronavirus 2019 disease (COVID-19) has been shown to affect the myocardium, resulting in a worse clinical outcome. In this registry study, we aimed to identify differences in cardiac magnetic resonance imaging (CMRI) between COVID-19 and all-cause myocarditis.

Materials and Methods:
We examined CMRI of patients with COVID-19 and elevated high-sensitivity serum troponin levels performed between March 31st and May 5th and compared them to CMRI of patients without SARS-CoV-2 infection with suspected myocarditis in the same time period. For this purpose, we evaluated Lake-Louise Criteria for myocarditis by determining nonischemic myocardial injury via T1-mapping, extracellular volume, late gadolinium enhancement, and myocardial edema (ME) by T2-mapping and fat-saturated T2w imaging (T2Q).

Results:
A total of 15 of 18 (89%) patients with COVID-19 had abnormal findings. The control group consisted of 18 individuals. There were significantly fewer individuals with COVID-19 who had increased T2 (5 vs. 10; P=0.038) and all-cause ME (7 vs. 15; P=0.015); thus, significantly fewer patients with COVID-19 fulfilled Lake-Louise Criteria (6 vs. 17; P<0.001). In contrast, nonischemic myocardial injury was not significantly different. In the COVID-19 group, indexed end-diastolic volume of the left ventricle showed a significant correlation to the extent of abnormal T1 (R
2=0.571; P=0.017) and extracellular volume (R
2=0.605; P=0.013) and absolute T1, T2, and T2Q (R
2=0.644; P=0.005, R
2=0.513; P=0.035 and R
2=0.629; P=0.038, respectively); in the control group, only extracellular volume showed a weak correlation (R
2=0.490; P=0.046).

Conclusions:
Cardiac involvement in COVID-19 seems to show less ME than all-cause myocarditis. Abnormal CMRI markers correlated to left ventricle dilation only in the COVID-19 group. Larger comparative studies are needed to verify our findings.
Rapid Metabolic Recovery of Donor Circulatory Death Liver Graft Using Whole Blood Perfusion: A Pig Study
Authors: Yoshimoto Syuhei , Ohara Masayuki , Torai Shinji , Kasamatsu Hiroo , Ishikawa Jun , Kimura Takahiro , Nadahara Soichi , Kobayashi Eiji 
Published: June 2021

Background.
Ex vivo perfusion technology has been actively developed to solve the problem of severe donor shortage. In this study, the ex vivo metabolic characteristics of porcine donation after circulatory death (DCD) liver in short-term perfusion using whole or diluted blood were compared with those of the in vivo transplanted state to evaluate their initial response to resuscitation.

Methods.
The porcine DCD model was constructed by clamping the thoracic aorta. After 60 min of blood flow cessation, retrieved livers were flushed with 500 mL of heparin saline (20 000 IU/L) followed by perfusion with 500 mL of cold histidine-tryptophan-ketoglutarate solution. The liver grafts were immersed in cold histidine-tryptophan-ketoglutarate solution for 60 min. Subsequently, normothermic ex vivo perfusion was performed with 20 000 IU/L of heparin added to the collected blood (whole blood group) or medium mixed with 10% whole blood (dilution group) for 3 h. Blood from the portal vein, the hepatic artery, and infra hepatica inferior vena cava was collected hourly and metabolomic analyses were performed. The other liver graft was heterotopically transplanted as a control (in vivo group). Each experiment was conducted once.

Results.
The guanosine levels demonstrated similar fluctuating trends in the whole blood and in vivo groups. In contrast, the levels increased during the perfusion in the diluted blood group. Fluctuations in choline metabolism demonstrated similar trends in the whole blood and in vivo groups.

Conclusions.
Ex vivo machine perfusion with whole blood over a short time resulted in a metabolic trend similar to that in the in vivo model. Further studies in this regard are warranted to progress in the utilization of DCD organs.
Modelling the effect of an improved trace and isolate system in the wake of a highly transmissible Covid-19 variant with potential vaccine escape
Authors: Bowie Cam 
Published: June 2021

AbstractObjectiveHow helpful would a properly functioning find, test, trace, isolate and support (FTTIS) system be now in the UK with new Covid-19 infections at a low level and half the adult population immunised but with a highly transmissible variant becoming predominant?Designa dynamic causal model of Covid-19 supplied with the latest available empirical data is used to assess the impact of a new highly transmissible variant.Settingthe United Kingdom.Participantsa population based study.Interventionsscenarios are used to explore a Covid-19 transmission rate 50% more and twice the current rate with or without a more effective FTTIS system.Main outcome measuresincidence, death rate and reproductive ratioResultsa small short third wave of infections occurs which does not occur if FTTIS effectiveness is improved from 25% to 30%.Conclusiona modest improvement in FTTIS would prevent a third wave caused by a highly transmissible virus.
TaxoNERD: deep neural models for the recognition of taxonomic entities in the ecological and evolutionary literature
Authors: Le Guillarme Nicolas , Thuiller Wilfried 
Published: June 2021

Given the biodiversity crisis, we more than ever need to access information on multiple taxa (e.g. distribution, traits, diet) in the scientific literature to understand, map and predict all-inclusive biodiversity. Tools are needed to automatically extract useful information from the ever-growing corpus of ecological texts and feed this information to open data repositories. A prerequisite is the ability to recognise mentions of taxa in text, a special case of named entity recognition (NER). In recent years, deep learning-based NER systems have become ubiquitous, yielding state-of-the-art results in the general and biomedical domains. However, no such tool is available to ecologists wishing to extract information from the biodiversity literature.We propose a new tool called TaxoNERD that provides two deep neural network (DNN) models to recognise taxon mentions in ecological documents. To achieve high performance, DNN-based NER models usually need to be trained on a large corpus of manually annotated text. Creating such a gold standard corpus (GSC) is a laborious and costly process, with the result that GSCs in the ecological domain tend to be too small to learn an accurate DNN model from scratch. To address this issue, we leverage existing DNN models pretrained on large biomedical corpora using transfer learning. The performance of our models is evaluated on four GSCs and compared to the most popular taxonomic NER tools.Our experiments suggest that existing taxonomic NER tools are not suited to the extraction of ecological information from text as they performed poorly on ecologically-oriented corpora, either because they do not take account of the variability of taxon naming practices, or because they do not generalise well to the ecological domain. Conversely, a domain-specific DNN-based tool like TaxoNERD outperformed the other approaches on an ecological information extraction task.Efforts are needed in order to raise ecological information extraction to the same level of performance as its biomedical counterpart. One promising direction is to leverage the huge corpus of unlabelled ecological texts to learn a language representation model that could benefit downstream tasks. These efforts could be highly beneficial to ecologists on the long term.
Biologging of emperor penguins – attachment techniques and associated deployment performance
Authors: Houstin Aymeric , Zitterbart Daniel P. , Winterl Alexander , Richter Sebastian , Planas-Bielsa Víctor , Chevallier Damien , Ancel André , Fournier Jérôme , Fabry Ben , Le Bohec Céline 
Published: June 2021

AbstractAn increasing number of marine animals are equipped with biologgers, to study their physiology, behaviour and ecology, often for conservation purposes. To minimise the impacts of biologgers on the animals’ welfare, theRefinementprinciple from the Three Rs framework (Replacement, Reduction, Refinement) urges to continuously test and evaluate new and updated biologging protocols.Here, we propose alternative and promising techniques for emperor penguin (Aptenodytes forsteri) capture and on-site logger deployment that aim to mitigate the potential negative impacts of logger deployment on these birds. We equipped adult emperor penguins for short-term (GPS, Time-Depth Recorder (TDR)) and long-term (i.e. planned for one year) deployments (ARGOS platforms, TDR), as well as juvenile emperor penguins for long-term deployments (ARGOS platforms) in the Weddell Sea area where they had not yet been studied.We describe and qualitatively evaluate our protocols for the attachment of biologgers on-site at the colony, the capture of the animals and the recovery of the devices after deployment. We report unprecedented recaptures of long-term equipped adult emperor penguins (50% of equipped individuals recaptured after 290 days). Our data demonstrate that the traditional technique of long-term attachment by gluing the biologgers directly to the back feathers is detrimental to the birds. It causes excessive feather breakage and the loss of the devices at an early stage. We therefore propose an alternative method of attachment for back-mounted devices. This technique led to successful year-round deployments on 37.5% of the equipped juveniles. Finally, we also disclose the first deployments of leg-bracelet mounted TDRs on emperor penguins.Our findings highlight the importance of monitoring potential impacts of biologger deployments on the animals and the need to remain critical towards established and new protocols.
The interactome of site-specifically acetylated linker histone H1
Authors: Höllmüller Eva , Greiner Katharina , Kienle Simon M. , Scheffner Martin , Marx Andreas , Stengel Florian 
Published: June 2021

ABSTRACTLinker histone H1 plays a key role in chromatin organization and maintenance, yet our knowledge of the regulation of H1 functions by posttranslational modifications (PTMs) is rather limited. In this study, we report on the generation of site-specifically mono- and di-acetylated linker histone H1.2 by genetic code expansion. We used these modified histones to identify and characterize the acetylation-dependent cellular interactome of H1.2 by affinity purification-mass spectrometry (AP-MS) and show that site-specific acetylation results in overlapping, but distinct groups of interacting partners. Among these, we find multiple translational initiation factors and transcriptional regulators such as the NAD+-dependent deacetylase SIRT1, which we demonstrate to act on acetylated H1.2. Taken together our data suggests that site-specific acetylation of H1.2 plays a role in modulating protein-protein interactions.
Cuticular Wax Composition is Essential for Plant Recovery Following Drought with Little Effect under Optimal Conditions
Authors: Negin Boaz , Hen-Avivi Shelly , Almekias-Siegl Efrat , Shachar Lior , Aharoni Asaph 
Published: June 2021

AbstractDespite decades of extensive study, the role of cuticular lipids in sustaining plant fitness is far from being understood. To answer this fundamental question, we employed genome editing in tree tobacco (Nicotiana glauca) plants and generated mutations in 16 different cuticular lipids-related genes. We chose tree tobacco due to the abundant, yet simply composed epicuticular waxes deposited on its surface. Five out of 9 different mutants that displayed a cuticular lipids-related phenotype were selected for in depth analysis. They had either reduced total wax load or complete deficiency in certain wax components. This led to substantial modification in surface wax crystal structure and to elevated cuticular water loss. Remarkably, under non-stressed conditions, mutant plants with altered wax composition did not display elevated transpiration or reduced growth. However, once exposed to drought, plants lacking alkanes were not able to strongly reduce their transpiration, leading to leaf death and impaired recovery upon resuscitation, and even to stem cracking, a phenomenon typically found in trees experiencing drought stress. In contrast, plants deficient in fatty alcohols exhibited an opposite response, having reduced cuticular water loss and rapid recovery following drought. This differential response was part of a larger trend, of no common phenotype connecting plants with a glossy appearance. We conclude that alkanes are essential under drought response and much less under normal non-stressed conditions, enabling plants to seal their cuticle upon stomatal closure, reducing leaf death and facilitating a speedy recovery.
Modelling interference between vectors of non-persistently transmitted plant viruses to identify effective control strategies
Authors: Zaffaroni Marta , Rimbaud Loup , Mailleret Ludovic , Cunniffe Nik J. , Bevacqua Daniele 
Published: June 2021

AbstractAphids are the primary vector of plant viruses. Transient aphids, which probe several plants per day, are considered to be the principal vectors of non-persistently transmitted (NPT) viruses. However, resident aphids, which can complete their life cycle on a single host and are affected by agronomic practices, can transmit NPT viruses as well. Moreover, they can interfere both directly and indirectly with transient aphids, eventually shaping plant disease dynamics. By mean of an epidemiological model, originally accounting for ecological principles and agronomic practices, we explore the consequences of fertilization and irrigation, pesticide deployment and roguing of infected plants on the spread of viral diseases in crops. Our results indicate that the spread of NPT viruses can be i) both reduced or increased by fertilization and irrigation, depending on whether the interference is direct or indirect; ii) counter-intuitively increased by pesticide application and iii) reduced by roguing infected plants. We show that a better understanding of vectors’ interactions would enhance our understanding of disease transmission, supporting the development of disease management strategies.Author summaryA range of both experimental and theoretical studies show that the behaviour and population dynamics of insects depend strongly upon interactions with other insect species. These interactions have the potential to greatly affect the dynamics of insect-vectored plant disease, as transmission of viruses is intimately dependent on the local density of vectors, as well as how they select and move between potential host plants. Surprisingly, the effects of interaction between vector species on epidemics remains little studied and even worse understood, probably because experimentation is costly and difficult. Here, we present a model which permits to investigate the effect of interaction between a virus, two vector species, and the host plant on the spread of viral disease in crops. In this study, our model is used to explore the consequences of common agronomic practices on epidemics. Our study highlights the importance of exploring vectors’ interactions to enhance the understanding of disease transmission, supporting the development of disease management strategies.
The rapid developmental rise of somatic inhibition disengages hippocampal dynamics from self-motion
Authors: Dard Robin F. , Leprince Erwan , Denis Julien , Rao-Balappa Shrisha , Suchkov Dmitrii , Boyce Richard , Lopez Catherine , Giorgi-Kurz Marie , Szwagier Tom , Dumont Theo , Rouault Hervé , Minlebaev Marat , Baude Agnes , Cossart Rosa , Picardo Michel A. 
Published: June 2021

ABSTRACTEarly electrophysiological brain oscillations recorded in preterm babies and newborn rodents are initially mostly ignited by bottom-up sensorimotor activity and only later can detach from external inputs. This is a hallmark of most developing brain areas including the hippocampus, which in the adult brain, functions in integrating external inputs onto internal dynamics. Such developmental disengagement from external inputs is likely a fundamental step for the proper development of cognitive internal models. Despite its importance, the developmental timeline and circuit basis for this disengagement remain unknown. To address this issue, we have investigated the daily evolution of CA1 dynamics and underlying circuits during the first two postnatal weeks of mouse development using two-photon calcium imaging in non-anesthetized pups. We show that the first postnatal week ends with an abrupt shift in the representation of self-motion in CA1. Indeed, most CA1 pyramidal cells switch from activated to inhibited by self-generated movements at the end of the first postnatal week whereas the majority of GABAergic neurons remain positively modulated throughout this period. This rapid switch occurs within two days and follows the rapid anatomical and functional surge of local somatic GABAergic innervation. The observed change in dynamics is consistent with a two-population model undergoing a strengthening of inhibition. We propose that this abrupt developmental transition inaugurates the emergence of internal cognitive models.
Distinguishing between models of mammalian gene expression: telegraph-like models versus mechanistic models
Authors: Braichenko Svitlana , Holehouse James , Grima Ramon 
Published: June 2021

AbstractTwo-state models (telegraph-like models) have a successful history of predicting distributions of cellular and nascent mRNA numbers that can well fit experimental data. These models exclude key rate limiting steps, and hence it is unclear why they are able to accurately predict the number distributions. To answer this question, here we compare these models to a novel stochastic mechanistic model of transcription in mammalian cells that presents a unified description of transcriptional factor, polymerase and mature mRNA dynamics. We show that there is a large region of parameter space where the first, second and third moments of the distributions of the waiting times between two consecutively produced transcripts (nascent or mature) of two-state and mechanistic models exactly match. In this region, (i) one can uniquely express the two-state model parameters in terms of those of the mechanistic model, (ii) the models are practically indistinguishable by comparison of their transcript numbers distributions, and (iii) they are distinguishable from the shape of their waiting time distributions. Our results clarify the relationship between different gene expression models and identify a means to select between them from experimental data.
Deep learning-based brain transcriptomic signatures associated with the neuropathological and clinical severity of Alzheimer’s disease
Authors: Wang Qi , Chen Kewei , Su Yi , Reiman Eric M. , Dudley Joel T. , Readhead Benjamin 
Published: June 2021

AbstractBrain tissue gene expression from donors with and without Alzheimer’s disease (AD) have been used to help inform the molecular changes associated with the development and potential treatment of this disorder. Here, we use a deep learning method to analyze RNA-seq data from 1,114 brain donors from the AMP-AD consortium to characterize post-mortem brain transcriptome signatures associated with amyloid-β plaque, tau neurofibrillary tangles, and clinical severity in multiple AD dementia populations. Starting from the cross-sectional data in the ROSMAP cohort (n = 634), a deep learning framework was built to obtain a trajectory that mirrors AD progression. A severity index (SI) was defined to quantitatively measure the progression based on the trajectory. Network analysis was then carried out to identify key gene (index gene) modules present in the model underlying the progression. Within this dataset, SIs were found to be very closely correlated with all AD neuropathology biomarkers (R ∼ 0.5, p < 1e-11) and global cognitive function (R = -0.68, p < 2.2e-16). We then applied the model to additional transcriptomic datasets from different brain regions (MAYO, n = 266; MSBB, n = 214), and observed that the model remained significantly predictive (p < 1e-3) of neuropathology and clinical severity. The index genes that significantly contributed to the model were integrated with AD co-expression regulatory networks, resolving four discrete gene modules that are implicated in vascular and metabolic dysfunction in different cell types respectively. Our work demonstrates the generalizability of this signature to frontal and temporal cortex measurements and additional brain donors with AD, other age-related neurological disorders and controls; and revealed the transcriptomic network modules contribute to neuropathological and clinical disease severity. This study illustrates the promise of using deep learning methods to analyze heterogeneous omics data and discover potentially targetable molecular networks that can inform the development, treatment and prevention of neurodegenerative diseases like AD.
Sequential delay and probability discounting tasks in mice reveal anchoring effects partially attributable to decision noise
Authors: Rojas Gerardo R. , Curry-Pochy Lisa S. , Chen Cathy S. , Heller Abigail T. , Grissom Nicola M. 
Published: June 2021

AbstractDelay discounting and probability discounting decision making tasks in rodent models have high translational potential. However, it is unclear whether the discounted value of the large reward option is the main contributor to variability in animals’ choices in either task, which may limit translatability to human discounting data. Male and female mice underwent sessions of delay and probability discounting in sequence to assess how choice behavior adapts over experience with each task. To control for “anchoring” (persistent choices based on the initial delay or probability), mice experienced “Worsening” schedules where the large reward was offered under initially favorable delay or probability conditions that became less favorable during testing, followed by “Improving” schedules where the large reward was offered under initially unfavorable conditions that improved over a session. During delay discounting, both male and female mice showed elimination of anchoring effects over training. In probability discounting, both sexes of mice continued to show some anchoring even after months of training. One possibility is that noisy action selection could contribute to these anchoring effects, rather than persistent fluctuations in value discounting. We fit choice behavior in individual animals using models that included both a value-based discounting parameter and a decision noise parameter that captured variability in choices deviating from value maximization. Changes in anchoring behavior over time were tracked by changes in our decision noise parameter, not the value parameter. Thus, changes in discounting behavior in mice can result from changes in exploration of the environment rather than changes in reward valuation.