bluuebunny/crossref_metadata_2025_split huggingface dataset:
Behaviour of smokers and their influencers in the UK during COVID-19 pandemic
Authors: Patwardhan Sudhanshu , Trainer Claudia 
Published: May 2021

AbstractPurposeThe COVID-19 pandemic has resulted in unprecedented circumstances and changes in behaviour. This research sought to better understand the impact of the COVID-19 pandemic, and lockdown, on smoking behaviour in the UK from the perspectives of consumers (current and former smokers) and some of their smoking-related behaviour-influencers.Design/methodology/approachThis research project encompassed two surveys, one for current and former smokers (Consumers) and one for those individuals in professions with the potential to influence smoking behaviours (Influencers). Both surveys were conducted online and were infield for approximately two weeks during UK’s first COVID-19 lockdown. Because of the unprecedented times the society was experiencing, several questions relating directly to COVID-19 were added to the survey and this paper is based only on findings only from those questions and not the whole project. The results were analysed descriptively.FindingsA total of 954 consumers and 1027 influencers participated in the surveys. Increased smoking was reported by 67% of the consumers mainly due to stress and boredom arising out of COVID-19 lockdown. Consumers under 45 years of age, those in professional and managerial occupations, and among dual users reported increased smoking in lockdown. The COVID-19 situation changed the plans to quit smoking in 36% of consumers, with only 6% deciding to quit. Only 40% of healthcare professionals (HCPs) documented patient smoking status in over half their interactions.Originality/ valueThis research among current and former smokers and their influencers highlights important changes in behaviour during the COVID-19 times and underscores urgent measures to be taken by HCPs and policymakers for staying on course of achieving smokefree goals despite challenges posed by COVID-19.
Immune determinants of the association between tumor mutational burden and immunotherapy response across cancer types
Authors: Sinha Neelam , Sinha Sanju , Valero Cristina , Schäffer Alejandro A. , Aldape Kenneth , Litchfield Kevin , Chan Timothy A , Morris Luc G T , Ruppin Eytan 
Published: May 2021

AbstractThe FDA has recently approved high tumor mutational burden (TMB), defined by ≥10 mutations/Mb, as a biomarker for the treatment of solid tumors with pembrolizumab, an immune checkpoint inhibitor (ICI) that targets PD1. However, recent studies testify that high TMB levels are only able to stratify ICI responders in a subset of cancer types, where the mechanisms underlying this observation have remained unknown. We hypothesized that the tumor immune microenvironment (TME) may modulate the stratification power of TMB (termed TMB power) in a cancer type, leading to this observation. To systematically study this hypothesis, we analyzed TCGA expression data to infer the levels of 31 immune-related factors characteristic of the TME of different cancer types. We integrated this information with TMB and response data of 2,277 patients treated with anti-PD1 or anti-PD-L1 ICI to identify the key immune factors that can determine TMB power across 14 different cancer types. We find that high levels of M1 macrophages and low resting dendritic cells in the TME characterize cancer types with high TMB power. A model based on these two immune factors is strongly predictive of the TMB power in a given cancer type (Spearman Rho=0.76, P<3.6×10−04). Using this model, we provide predictions of the TMB power in nine additional cancer types, including rare cancers, for which TMB and ICI response data are not yet publicly available on a large scale. Our analysis indicates that TMB-High may be highly predictive of ICI response in cervical squamous cell carcinoma, suggesting that such a study should be prioritized.
Dynamics of Functional Network Organization Through Graph Mixture Learning
Authors: Ricchi Ilaria , Tarun Anjali , Maretic Hermina Petric , Frossard Pascal , Van De Ville Dimitri 
Published: May 2021

AbstractUnderstanding the organizational principles of human brain activity at the systems level remains a major challenge in network neuroscience. Here, we introduce a fully data-driven approach based on graph learning to extract meaningful repeating network patterns from regionally-averaged time-courses. We use the Graph Laplacian Mixture Model (GLMM), a generative model that treats functional data as a collection of signals expressed on multiple underlying graphs. By exploiting covariance between activity of brain regions, these graphs can be learned without resorting to structural information. To validate the proposed technique, we first apply it to task fMRI with a known experimental paradigm. The probability of each graph to occur at each time-point is found to be consistent with the task timing, while the spatial patterns associated to each epoch of the task are in line with previously established activation patterns using classical regression analysis. We further on apply the technique to resting state data, which leads to extracted graphs that correspond to well-known brain functional activation patterns. The GLMM allows to learn graphs entirely from the functional activity that, in practice, turn out to reveal high degrees of similarity to the structural connectome. We compared similarity of the default mode network estimated from different task data and comparing them to each other and to structure. Using different metrics, a similar distinction between high- and low-level cognitive tasks arises.Overall, this method allows us to infer relevant functional brain networks without the need of structural connectome information. Moreover, we find that these networks correspond better to structure compared to traditional methods.
Feasibility of FreeSurfer processing for T1-weighted brain images of 5-year-olds: semiautomated protocol of FinnBrain Neuroimaging Lab
Authors: Pulli Elmo P. , Silver Eero , Kumpulainen Venla , Copeland Anni , Merisaari Harri , Saunavaara Jani , Parkkola Riitta , Lähdesmäki Tuire , Saukko Ekaterina , Nolvi Saara , Kataja Eeva-Leena , Korja Riikka , Karlsson Linnea , Karlsson Hasse , Tuulari Jetro J. 
Published: May 2021

AbstractPediatric neuroimaging is a quickly developing field that still faces important methodological challenges. One key challenge is the use of many different atlases, automated segmentation tools, manual edits in semiautomated protocols, and quality control protocols, which complicates comparisons between studies. In this article, we present our semiautomated segmentation protocol using FreeSurfer v6.0, ENIGMA consortium software, and the quality control protocol that was used in FinnBrain Birth Cohort Study. We used a dichotomous quality rating scale for inclusion and exclusion of images, and then explored the quality on a region of interest level to exclude all regions with major segmentation errors. The effects of manual edits on cortical thickness values were minor: less than 2% in all regions. Supplementary materials cover registration and additional edit options in FreeSurfer and comparison to the computational anatomy toolbox (CAT12). Overall, we conclude that despite minor imperfections FreeSurfer can be reliably used to segment cortical metrics from T1-weighted images of 5-year-old children with appropriate quality assessment in place. However, custom templates may be needed to optimize the results for the subcortical areas. Our semiautomated segmentation protocol provides high quality pediatric neuroimaging data and could help investigators working with similar data sets.
TRPA1 block protects against loss of white matter function during ischaemia in the mouse optic nerve
Authors: Lajoso Wendy , Flower Grace , Giacco Vincenzo , Kaul Anjuli , La Mache Circe , Brăban Andra , Roxas Angela , Hamilton Nicola 
Published: May 2021

AbstractOligodendrocytes produce myelin which provides insulation to axons and speeds up neuronal transmission. In ischaemic conditions myelin is damaged, resulting in mental and physical disabilities. Therefore, it is important to understand how the function of oligodendrocytes and myelin is affected by ischaemia. Recent evidence suggests that oligodendrocyte damage during ischaemia is mediated by TRPA1, whose activation raises intracellular Ca2+ concentrations and damages compact myelin. Here, we show that TRPA1 is constitutively active in oligodendrocytes and the optic nerve, as the specific TRPA1 antagonist, A-967079, decreases basal oligodendrocyte Ca2+ concentrations and increases the size of the compound action potential. Conversely, TRPA1 agonists reduce the size of the optic nerve compound action potential, and this effect is significantly reduced by the TRPA1 antagonist. These results indicate that glial TRPA1 regulates neuronal excitability in the white matter under physiological as well as pathological conditions. Importantly, we find that inhibition of TRPA1 prevents loss of compound action potentials during oxygen and glucose deprivation (OGD) and improves the recovery. TRPA1 block was effective when applied before, during or after OGD, indicating that the damage is occurring during ischaemia and during the recovery, but importantly, that therapeutic intervention is possible after the ischaemic insult. These results indicate that TRPA1 has an important role in the brain, and that its block may be effective in treating oligodendrocyte loss and damage in many white matter diseases.
Alpha phase-amplitude tradeoffs predict visual perception
Authors: Fakche Camille , VanRullen Rufin , Marque Philippe , Dugué Laura 
Published: May 2021

AbstractSpontaneous alpha oscillations (~10 Hz) have been associated with various cognitive functions, including perception. Their phase and amplitude independently predict cortical excitability and subsequent perceptual performance. Yet, the causal role of alpha phase-amplitude tradeoffs on visual perception remains ill-defined. We aimed to fill this gap and tested two clear predictions from the Pulsed Inhibition theory according to which alpha oscillations are associated with periodic functional inhibition. (1) High alpha amplitude induces cortical inhibition at specific phases, associated with low perceptual performance, while at opposite phases, inhibition decreases (potentially increasing excitation) and perceptual performance increases. (2) Low alpha amplitude is less susceptible to these phasic (periodic) pulses of inhibition, leading to overall higher perceptual performance. Here, cortical excitability was assessed in humans using phosphene (illusory) perception induced by single pulses of transcranial magnetic stimulation (TMS) applied over visual cortex at perceptual threshold, and its post-pulse evoked activity recorded with simultaneous electroencephalography (EEG). We observed that pre-pulse alpha phase modulates the probability to perceive a phosphene, predominantly for high alpha amplitude, with a non-optimal phase for phosphene perception between −π/2 and −π/4. The pre-pulse non-optimal phase further leads to an increase in post-pulse evoked activity (ERP), in phosphene-perceived trials specifically. Together, these results show that alpha oscillations create periodic inhibitory moments when alpha amplitude is high, leading to periodic decrease of perceptual performance. This study provides strong causal evidence in favor of the Pulsed Inhibition theory.Visual AbstractSignificance StatementThe Pulsed Inhibition theory predicts that the functional inhibition induced by high alpha oscillations’ amplitude is periodic, with specific phases decreasing neural firing and perceptual performance. In turn, low alpha oscillations’ amplitude is less susceptible to phasic moments of pulsed inhibition leading to overall higher perceptual performance. Using TMS with simultaneous EEG recordings in humans, we found that specific phases of spontaneous alpha oscillations (~10 Hz) decrease cortical excitability and the subsequent perceptual outcomes predominantly when alpha amplitude is high. Our results provide strong causal evidence in favor of the Pulsed Inhibition theory.
PERK Activation by SB202190 Attenuates Amyloidogenesis via TFEB-induced Autophagy-Lysosomal Pathway
Authors: Do Mihyang , Park Jeongmin , Chen Yubing , Rah So-Young , Nghiem Thu-Hang Thi , Gong Jeong Heon , Kim Byung-Sam , Park Jeong Woo , Ryter Stefan W. , Surh Young-Joon , Kim Uh-Hyun , Joe Yeonsoo , Chung Hun Taeg 
Published: May 2021

AbstractThe protein kinase R (PKR)-like endoplasmic reticulum (ER) kinase (PERK), a key ER stress sensor of the unfolded protein response (UPR), can confer beneficial effects by facilitating the removal of cytosolic aggregates through the autophagy-lysosome pathway (ALP). In neurodegenerative diseases, the ALP ameliorates the accumulation of intracellular protein aggregates in the brain. Transcription factor-EB (TFEB), a master regulator of the ALP, positively regulates key genes involved in the cellular degradative pathway. However, in neurons, the role of PERK activation in mitigating amyloidogenesis by ALP remains unclear. In this study, we found that SB202190 selectively activates PERK independently of its inhibition of p38 mitogen-activated protein kinase, but not inositol-requiring transmembrane kinase/endoribonuclease-1α (IRE1α) or activating transcription factor 6 (ATF6), in human neuroblastoma cells. PERK activation by SB202190 was dependent on mitochondrial ROS production and promoted Ca2+-calcineurin activation. The activation of the PERK-Ca2+-calcineurin axis by SB202190 positively affects TFEB activity to increase ALP in neuroblastoma cells. Collectively, our study reveals a novel physiological mechanism underlying ALP activation, dependent on PERK activation, for ameliorating amyloidogenesis in neurodegenerative diseases.
Parthenogenesis and the Evolution of Anisogamy
Authors: Constable George W.A. , Kokko Hanna 
Published: May 2021

AbstractRecently, it was pointed out [1] that classic models for the evolution of anisogamy do not take into account the possibility of parthenogenetic reproduction, even though sex is facultative in many relevant taxa (e.g. algae) that harbour both anisogamous and isogamous species. Here we complement the analysis of [1] with an approach where we assume that the relationship between progeny size and its survival may differ between parthenogenetically and sexually produced progeny, favouring either the former or the latter. We show that the findings of [1], that parthenogenesis can stabilise isogamy relative to the obligate sex case, extend to our scenarios. We additionally investigate two different ways for one mating type to take over the entire population. First, parthenogenesis can lead to biased sex ratios that are sufficiently extreme that one type can displace the other, leading to de facto asexuality for the remaining type that now lacks partners to fuse with. This process involves positive feedback: microgametes, being numerous, lack opportunities for syngamy, and should they proliferate parthenogenetically, the next generation makes this asexual route even more prominent for microgametes. Second, we consider mutations to strict asexuality in producers of micro- or macrogametes, and show that the prospects of asexual invasion depend strongly on the mating type in which the mutation arises. Perhaps most interestingly, we also find scenarios in which parthenogens have an intrinsic survival advantage yet facultatively sexual isogamous populations are robust to the invasion of asexuals, despite us assuming no genetic benefits of recombination. Here equal contribution from both mating types to zygotes that are sufficiently well provisioned can outweigh the additional costs associated with syngamy.
Orthogonal translation initiation using the non-canonical initiator tRNA(AAC) alters protein sequence and stability in vivo
Authors: Hutvagner Andras , Scopelliti Dominic , Whelan Fiona , Jaschke Paul R. 
Published: May 2021

AbstractBiological engineers seek to have better control and a more complete understanding of the process of translation initiation within cells so that they may produce proteins more efficiently, as well as to create orthogonal translation systems. Previously, initiator tRNA variants have been created that initiate translation from non-AUG start codons, but their orthogonality has never been measured and the detailed characteristics of proteins produced from them have not been well defined. In this study we created an initiator tRNA mutant with anticodon altered to AAC to be complementary to GUU start codons. We deploy this i-tRNA(AAC) into E. coli cells and measure translation initiation efficiency against all possible start codons. Using parallel reaction monitoring targeted mass spectrometry we identify the N-terminal amino acids of i-tRNA(AAC)-initiated reporter proteins and show these proteins have altered stability within cells. We also use structural modeling of the peptide deformylase enzyme interaction with position 1 valine peptides to interrogate a potential mechanism for accumulation of formylated-valine proteins observed by mass spectrometry. Our results demonstrate that mutant initiator tRNAs have potential to initiate translation more orthogonally than the native initiator tRNA but their interactions with cellular formyltransferases and peptide deformylases can be inefficient because of the amino acid they are charged with. Additionally, engineered initiator tRNAs may enable tuning of in vivo protein stability through initiation with non-methionine amino acids that alter their interaction with cellular proteases.
Internal and external features of wild birds after collisions without apparent trauma in Japan
Authors: Ushine Nana , Tanaka Aki , Sato Tatsuo , Nonagase Masaki , Hayama Shin-ichi 
Published: May 2021

AbstractWild birds often require rehabilitation after collisions, even with no apparent injury. Information about aftermath of collisions is still scares. Here, we investigated external characteristics and clinical features of the internal organs of wild birds that experienced collision and compared them with birds admitted to rehabilitation center for other reasons. Necropsy was performed on 55 bird carcasses from Passeriformes and Coraciiform. Five external characteristics were recorded before necropsy including; cause of admission, keel score, life stage, fat score, and number of days before death. The median survival time was calculated by Kaplan-Meier estimates. Data on external and internal features were compared using univariate and multivariate multinomial regressions. There was no significant difference in the median survival time among the causes of admission: 1 day for collision, 2 days for trauma, and 2 days for malnutrition. Kidney discoloration was more significantly associated with collision than with other trauma (p = 0.01). Although no apparent kidney abnormality (including enlargement) were observed, anterior lobe was significantly larger than posterior lobe with collision compared with malnutrition (p = 0.045). Birds that experienced collision exhibited a higher fat score than malnourished birds (p = 0.03). Our results suggested that wild birds with abundant fat were more likely to be admitted due to collision. The gross characteristics of collision included kidney discoloration and anterior lobe extension, which was possibly due to rupture of renal blood vessels by blunt external force. From these findings, it was considered that collision caused major axis of anterior lobe significantly larger than posterior lobe, even though no abnormal finding in renal size such as hypertrophy was recognized. This was the first study to evaluate the cause of admission, necropsy results, and external characteristics in wild birds admitted to rehabilitation centers. Absolute cage rest should be adhered to restore renal function for those birds admitted due to collision, and handling and treatment should be minimized to avoid excess movement of the birds.
CoRe: A robustly benchmarked R package for identifying core-fitness genes in genome-wide pooled CRISPR-Cas9 screens
Authors: Vinceti Alessandro , Karakoc Emre , Pacini Clare , Perron Umberto , De Lucia Riccardo Roberto , Garnett Mathew J. , Iorio Francesco 
Published: May 2021

AbstractCRISPR-Cas9 genome-wide screens are being increasingly performed, allowing systematic explorations of cancer dependencies at unprecedented accuracy and scale. Identifying from these screens the genes that are essential for cell survival invariantly across tissues, conditions, and genomic-contexts (core-fitness genes), is of paramount importance to assess the safety profile of candidate therapeutic targets and for elucidating mechanisms involved in tissue-specific genetic diseases. We present CoRe: An R package implementing novel methods for identifying core-fitness genes from joint analyses of multiple CRISPR-Cas9 screens. We demonstrate that CoRe outperforms state-of-the-art tools, yielding more reliable sets of core-fitness genes than existing and widely used reference sets.
Computational Design Map for Heterogeneous Experimental Studies
Authors: Kulkarni Chhaya , Maisha Nuzhat , Schaub Leasha J , Glaser Jacob , Lavik Erin , Janeja Vandana P. 
Published: May 2021

AbstractThis paper focuses on the discovery of a computational design map of disparate heterogeneous outcomes from bioinformatics experiments in pig (porcine) studies to help identify key variables impacting the experiment outcomes. Specifically we aim to connect discoveries from disparate laboratory experimentation in the area of trauma, blood loss and blood clotting using data science methods in a collaborative ensemble setting. Trauma related grave injuries cause exsanguination and death, constituting up to 50% of deaths especially in the armed forces. Restricting blood loss in such scenarios usually requires the presence of first responders, which is not feasible in certain cases. Moreover, a traumatic event may lead to a cytokine storm, reflected in the cytokine variables. Hemostatic nanoparticles have been developed to tackle these kinds of situations of trauma and blood loss. This paper highlights a collaborative effort of using data science methods in evaluating the outcomes from a lab study to further understand the efficacy of the nanoparticles. An intravenous administration of hemostatic nanoparticles was executed in pigs that had to undergo hemorrhagic shock and blood loss and other immune response variables, cytokine response variables are measured. Thus, through various hemostatic nanoparticles used in the intervention, multiple data outcomes are produced and it becomes critical to understand which nanoparticles are critical and what variables are key to study further variations in the lab. We propose a collaborative data mining framework which combines the results from multiple data mining methods to discover impactful features. We used frequent patterns observed in the data from these experiments. We further validate the connections between these frequent rules by comparing the results with decision trees and feature ranking. Both the frequent patterns and the decision trees help us identify the critical variables that stand out in the lab studies and need further validation and follow up in future studies. The outcomes from the data mining methods help produce a computational design map of the experimental results. Our preliminary results from such a computational design map provided insights in determining which features can help in designing the most effective hemostatic nanoparticles.