bluuebunny/crossref_metadata_2025_split huggingface dataset:
B1+-correction of MT saturation maps optimized for 7TpostmortemMRI of the brain
Authors: Lipp I. , Kirilina E. , Edwards L.J. , Pine K.J. , Jäger C. , Gräßle T. ,   EBC consortium, Weiskopf N. , Helms G. 
Published: July 2022

AbstractPurposeMagnetization transfer saturation (MTsat) is a useful marker to probe tissue macromolecular content and myelination in the brain. The increased-inhomogeneity at ≥ 7T and significantly larger saturation pulse flip angles which are often used forpostmortemstudies exceed the limits where previous MTsatcorrection methods are applicable. Here, we develop a calibration-based correction model and procedure, and validate and evaluate it inpostmortem7T data of whole chimpanzee brains.TheoryThedependence of MTsat was investigated by varying the off-resonance saturation pulse flip angle. For the range of saturation pulse flip angles applied in typical experiments onpostmortemtissue, the dependence was close to linear. A linear model with a single calibration constantCis proposed to correct bias in MTsat by mapping it to the reference value of the saturation pulse flip angle.MethodsCwas estimated voxel-wise in fivepostmortemchimpanzee brains. “Individual-based global parameters” were obtained by calculating the meanCwithin individual specimen brains and “group-based global parameters” by calculating the means of the individual-based global parameters across the five brains.ResultsThe linear calibration model described the data well, thoughCwas not entirely independent of the underlying tissue and. Individual-based and group-based global correction parameters (C= 1.2) led to visible, quantifiable reductions of-biases in high resolution MTsat maps.ConclusionThe presented model and calibration approach effectively corrects forin-homogeneities inpostmortem7T data.
Mink on the brink: Comparing survey methods for detecting a Critically Endangered carnivore, the European minkMustela lutreola
Authors: Croose Elizabeth , Hanniffy Ruth , Harrington Andrew , Põdra Madis , Gómez Asun , Bolton Polly L. , Lavin Jenna V. , Browett Samuel S. , Ruiz Javier Pinedo , Arnaez David Lacanal , Galdos Iñaki , Ugarte Jon , Torre Aitor , Wright Patrick , MacPherson Jenny , McDevitt Allan D. , Carter Stephen P. , Harrington Lauren A. 
Published: July 2022

ABSTRACTMonitoring rare and elusive species is critical in guiding appropriate conservation management measures. Mammalian carnivores are challenging to monitor directly, due to their generally nocturnal and solitary lifestyle, and relatively large home ranges. The European minkMustela lutreolais a Critically Endangered, small, semi-aquatic carnivore and is one of the most threatened mammal species in Europe. In northern Spain, the European mink population is monitored regionally using different methods and approaches, making assessment of national population status difficult. There is an urgent need to 1) assess the efficacy of survey methods, and 2) identify a standard monitoring methodology that can be deployed rapidly and inexpensively over large areas of the mink’s range. We deployed four methods – camera trapping, hair tubes, live trapping, and environmental DNA (eDNA) from water samples – to compare the probability of detecting European mink when present at 25 sampling sites within five 10×10km squares, and the economic cost and time required for each method. All four methods successfully detected European mink but the probability of detection varied by method. Camera trapping and hair tubes had the highest probability of detection; however, eDNA and live trapping detected mink in one 10×10km square where the latter two methods did not. For future European mink monitoring programmes, we recommend a combination of at least two methods, and suggest that camera traps or hair tubes are combined with live trapping or eDNA (depending on the scale and aims of the study), to gather critical information on distribution, occupancy and conservation status.
Through a Dog’s Eyes: fMRI Decoding of Naturalistic Videos from Dog Cortex
Authors: Phillips Erin M. , Gillette Kirsten D. , Dilks Daniel D. , Berns Gregory S. 
Published: July 2022

AbstractRecent advancements using machine learning and fMRI to decode visual stimuli from human and nonhuman cortex have resulted in new insights into the nature of perception. However, this approach has yet to be applied substantially to animals other than primates, raising questions about the nature of such representations across the animal kingdom. Here, we used awake fMRI in two domestic dogs and two humans, obtained while each watched specially created dog-appropriate naturalistic videos. We then trained a neural net (Ivis) to classify the video content from a total of 90 minutes of recorded brain activity from each. We tested both an object-based classifier, attempting to discriminate categories such as dog, human and car, and an action-based classifier, attempting to discriminate categories such as eating, sniffing and talking. Compared to the two human subjects, for whom both types of classifier performed well above chance, only action-based classifiers were successful in decoding video content from the dogs. These results demonstrate the first known application of machine learning to decode naturalistic videos from the brain of a carnivore and suggest that the dog’s-eye view of the world may be quite different than our own.
Restoring morphology of light sheet microscopy data based on magnetic resonance histology
Authors: Tian Yuqi , Cook James J. , Johnson G. Allan 
Published: July 2022

AbstractThe combination of cellular-resolution whole brain light sheet microscopy (LSM) images with an annotated atlas enables quantitation of cellular features in specific brain regions. However, most existing methods register LSM data with existing canonical atlases, e.g. The Allen Brain Atlas (ABA), which limits the precision of measuring regional volumes and eliminates the individual difference in brain partitions for different strains, ages, and environmental exposures. Thus, these approaches obscure valuable anatomical information. Here, we present a method to combine LSM data with magnetic resonance histology (MRH) of the same brain restoring the morphology of the LSM images to the in-skull morphology. Our pipeline which maps 3D LSM data (terabyte level per dataset) to magnetic resonance histology of the same mouse brain provides accurate registration with low displacement error in 10 hours with limited manual input. Optimization and validation, from initialization of the data, designing the quantitative loss function, optimizing the 20+ image processing variables on multiple resolution scales, and finalizing the application on full resolution data has been integrated through a structured workflow. Excellent agreement has been seen between registered data and reference data both locally and globally. This workflow has been applied to a collection of datasets with varied MRH and LSM contrast providing a routine method for streamlined registration of LSM images to MRH.
On the role of tail in stability and energetic cost of bird flapping flight
Authors: Ducci Gianmarco , Vitucci Gennaro , Chatelain Philippe , Ronsse Renaud 
Published: July 2022

AbstractMigratory birds travel over impressively long distances. Consequently, they have to adopt flight regimes being both efficient - in order to spare their metabolic resources - and robust to perturbations.This paper investigates the relationship between both aspects, i.e. mechanical performance and stability in flapping flight of migratory birds. Relying on a poly-articulated wing morphing model and a tail-like surface, several families of steady flight regime have been identified and analyzed. These families differ by their wing kinematics and tail opening. A systematic parametric search analysis has been carried out, in order to evaluate power consumption and cost of transport. A framework tailored for assessing limit cycles, namely Floquet theory, is used to numerically study flight stability.Our results show that under certain conditions, an inherent passive stability of steady and level flight can be achieved. In particular, we find that progressively opening the tail leads to passively stable flight regimes. Within these passively stable regimes, the tail can produce either upward or downward lift. However, these configurations entail an increase of cost of transport at high velocities penalizing fast forward flight regimes.Our model-based predictions suggest that long range flights require a furled tail configuration, as confirmed by field observations, and consequently need to rely on alternative mechanisms to stabilize the flight.
PanomiR: A systems biology framework for analysis of multi-pathway targeting by miRNAs
Authors: Yeganeh Pourya Naderi , Teo Yue Yang , Karagkouni Dimitra , Pita-Juárez Yered , Morgan Sarah L. , Slack Frank J. , Vlachos Ioannis S. , Hide Winston A. 
Published: July 2022

AbstractCharting microRNA (miRNA) regulation across pathways is central to characterizing their role in disease. Yet, current methods reveal only individual miRNA-pathway interactions. We have developed a systems biology approach,Pathway networks of miRNA Regulation(PanomiR), that overcomes these limitations to identify miRNA targeting of groups of interacting pathways using gene expression. The approach does not depend on statistically significant enrichment of miRNA target genes in individual pathways or significant differentially expressed genes. Rather, it directly captures differential activity of pathways between states, determining their up-or-down regulation while sensitively detecting biologically-meaningful signals. PanomiR analyzes the co-activity of differentially regulated pathways to determine coordinate functional groups and uses these co-activated grouped pathways to uncover miRNAs that target them. Incorporating both experimentally-supported or predicted miRNA-mRNA interactions, PanomiR robustly identifies miRNAs central to the regulation of disease functions. We applied PanomiR to a liver cancer dataset and showed that it can organize liver cancer pathways and their regulating miRNAs into coordinated transcriptional programs, reflecting the pathogenic mechanisms of hepatocellular carcinoma. PanomiR recapitulated known central miRNAs in liver cancer with a biologically meaningful assignment of pathways under their regulation, unbiased by the number of genes targeted by each miRNA. PanomiR is a granular framework for detecting broad-scale multi-pathway programs under miRNA regulation. It is accessible as an open-source R/Bioconductor package: <https://bioconductor.org/packages/PanomiR>.
Mouse microglia express unique miRNA-mRNA networks to facilitate age-specific functions in the developing central nervous system
Authors: Walsh Alexander D. , Stone Sarrabeth , Aprico Andrea , Kilpatrick Trevor J. , Ansell Brendan A. , Binder Michele D. 
Published: July 2022

AbstractMicroglia regulate multiple processes in the central nervous system, exhibiting a significant level of cellular plasticity which is facilitated by an equally dynamic transcriptional environment. While many gene networks that regulate microglial functions have been characterised, the influence of epigenetic regulators such as small non-coding microRNAs (miRNAs) is less well defined. We have sequenced the miRNAome and mRNAome of mouse microglia during brain development and adult homeostasis, identifying unique profiles of known and novel miRNAs. Microglia express both a consistently enriched miRNA signature as well as temporally distinctive subsets of miRNAs. We generated robust miRNA-mRNA networks related to fundamental developmental processes, in addition to networks associated with immune function and dysregulated disease states. There was no apparent influence of sex on miRNA expression. This study reveals a unique developmental trajectory of miRNA expression in microglia during critical stages of CNS development, establishing miRNAs as important modulators of microglial phenotype.
scDREAMER: atlas-level integration of single-cell datasets using deep generative model paired with adversarial classifier
Authors: Shree Ajita , Pavan Musale Krushna , Zafar Hamim 
Published: July 2022

AbstractIntegration of heterogeneous single-cell sequencing datasets generated across multiple tissue locations, time and conditions is essential for a comprehensive understanding of the cellular states and expression programs underlying complex biological systems. Here, we present scDREAMER (https://github.com/Zafar-Lab/scDREAMER), a novel data integration framework that employs a novel adversarial variational autoencoder for learning lower-dimensional cellular embeddings and a batch classifier neural network for the removal of batch effects. Using five real benchmarking datasets, we demonstrated that scDREAMER can overcome critical challenges including the presence of skewed cell types among batches, nested batch effects, large number of batches and conservation of development trajectory across different batches. Moreover, our benchmarking demonstrated that scDREAMER outperformed state-of-the-art methods in batch-correction and conservation of biological variation. Using a 1 million cells dataset, we further showed that scDREAMER is scalable and can perform atlas-level integration across species (e.g., human and mouse) while being faster than other deep-learning-based methods.
Extreme differences in SARS-CoV-2 viral loads among respiratory specimen types during presumed pre-infectious and infectious periods
Authors: Winnett Alexander Viloria , Akana Reid , Shelby Natasha , Davich Hannah , Caldera Saharai , Yamada Taikun , Reyna John Raymond B. , Romano Anna E. , Carter Alyssa M. , Kim Mi Kyung , Thomson Matt , Tognazzini Colten , Feaster Matthew , Goh Ying-Ying , Chew Yap Ching , Ismagilov Rustem F. 
Published: July 2022

ABSTRACTSARS-CoV-2 viral load measurements from a single specimen type are used to establish diagnostic strategies, interpret clinical-trial results for vaccines and therapeutics, model viral transmission, and understand virus-host interactions. However, measurements from a single specimen type are implicitly assumed to be representative of other specimen types. We quantified viral-load timecourses from individuals who began daily self-sampling of saliva, anterior nares (nasal), and oropharyngeal (throat) swabs before or at the incidence of infection with the Omicron variant. Viral loads in different specimen types from the same person at the same timepoint exhibited extreme differences, up to 109copies/mL. These differences were not due to variation in sample self-collection, which was consistent. For most individuals, longitudinal viral-load timecourses in different specimen types did not correlate. Throat-swab and saliva viral loads began to rise up to 7 days earlier than nasal-swab viral loads in most individuals, leading to very low clinical sensitivity of nasal swabs during the first days of infection. Individuals frequently exhibited presumably infectious viral loads in one specimen type while viral loads were low or undetectable in other specimen types. Therefore, defining an individual as infectious based on assessment of a single specimen type underestimates the infectious period, and overestimates the ability of that specimen type to detect infectious individuals. For diagnostic COVID-19 testing, these three single specimen types have low clinical sensitivity, whereas a combined throat-nasal swab, and assays with high analytical sensitivity, were inferred to have significantly better clinical sensitivity to detect presumed pre-infectious and infectious individuals.Significance StatementIn a longitudinal study of SARS-CoV-2 Omicron viral loads in three paired specimen types (saliva, anterior-nares swabs, and oropharyngeal swabs), we found extreme differences among paired specimen types collected from a person at the same timepoint, and that viral loads in different specimen types from the same person often do not correlate throughout infection. Individuals often exhibited high, presumably infectious viral loads in oral specimen types before nasal viral loads remained low or even undetectable. Combination oropharyngeal-nasal swabs were inferred to have superior clinical sensitivity to detect infected and infectious individuals. This demonstrates that single specimen type reference standard tests for SARS-CoV-2, such as in clinical trials or diagnostics evaluations may miss infected and even infectious individuals.
Augmented Pain-Evoked Primary Sensorimotor Cortex Activation in Adolescent Girls with Juvenile Fibromyalgia
Authors: Tong Han , Maloney Thomas C. , Payne Michael F. , Suñol Maria , King Christopher D. , Ting Tracy V. , Kashikar-Zuck Susmita , Coghill Robert C. , López-Solà Marina 
Published: July 2022

ObjectiveJuvenile fibromyalgia (JFM) is a chronic widespread pain condition that primarily affects adolescent girls. Previous studies have found increased sensitivity to noxious pressure in adolescents with JFM. However, the underlying changes in brain systems remain unclear. The aim of this study was to characterize pain-evoked brain responses and identify brain mediators of pain hypersensitivity in adolescent girls with JFM.MethodsThirty-three adolescent girls with JFM and thirty-three healthy adolescent girls underwent functional MRI scans involving noxious pressure applied to the left thumbnail at an intensity of 2.5 or 4 kg/cm2 and rated pain intensity and unpleasantness on a computerized visual analogue scale. We conducted standard general linear model analyses and exploratory whole-brain mediation analyses, and computed pain-evoked brain responses within seven major cortical networks.ResultsThe JFM group reported significantly greater pain intensity and unpleasantness than the control group in response to noxious pressure stimuli at both intensities (p<0.05). The JFM group showed augmented right primary somatosensory cortex (S1) activation to 4 kg/cm2 (Z>3.1, cluster-corrected p<0.05), and the peak S1 activation magnitudes correlated with Widespread Pain Index scores (r=0.35, p=0.048). In the JFM group, we also found augmented activation of the somatomotor network in response to 2.5 kg/cm2, and greater primary sensorimotor cortex activation in response to 4kg/cm2 mediated the between-group differences in pain intensity ratings (p<0.001).ConclusionWe found heightened sensitivity to noxious pressure stimuli and augmented pain-evoked sensorimotor cortex responses in adolescent girls with JFM, which could reflect central sensitization or amplified nociceptive input.
Genome evolution and early introductions of the SARS-CoV-2 Omicron Variant in Mexico
Authors: Castelán-Sánchez Hugo G. , Martínez-Castilla León P. , Sganzerla-Martínez Gustavo , Torres-Flores Jesús , López-Leal Gamaliel 
Published: July 2022

ABSTRACTA new variant of SARS-CoV-2 Omicron (Pango lineage designation B.1.1.529), was first reported to the World Health Organization (WHO) by South African health authorities on November 24, 2021. The Omicron variant possesses numerous mutations associated with increased transmissibility and immune escape properties. In November 2021, Mexican authorities reported Omicron’s presence in the country. In this study, we infer the first introductory events of Omicron and the impact that human mobility can have on the spread of the virus. We also evaluated the adaptive evolutionary processes in Mexican SARS-CoV-2 genomes during the first month of circulation of Omicron.We infer 173 introduction events of Omicron in Mexico in the first two months of detection; subsequently, of the introductions, there was an increase in the prevalence for January.This higher prevalence of the novel variant results in a peak of cases reported, on average, six weeks after a higher mobility trend was reported. The peak of cases reported is due to the BA.1.1 Omicron sub-lineage dominated, followed by BA.1 and BA.15 sub-lineages in the country from January to February 2022.Additionally, we identified the presence of diversifying natural selection in the genomes of Omicron and found mainly five non-synonymous mutations in the RDB domain of the Spike protein, all of them related to evasion of the immune response. In contrast, the other proteins in the genome are highly conserved—however, there are homoplasies mutations in non-structural proteins, indicating a parallel evolution.
Exploring regression dilution bias using repeat measurements of 2858 variables in up to 49 000 UK Biobank participants
Authors: Rutter Charlotte E , Millard Louise AC , Borges Maria Carolina , Lawlor Deborah A 
Published: July 2022

AbstractBackgroundMeasurement error in exposures and confounders can bias exposure-outcome associations but is rarely considered. Our aim was to assess measurement error between repeat measures of all continuous variables in UK Biobank, and explore approaches to mitigate its impact on exposure-outcome associations.MethodsIntraclass correlation coefficients (ICC) were calculated for all continuous variables with repeat measures. Regression calibration was used to correct for measurement error in both exposures and confounders, using the association of C-Reactive Protein (CRP) with mortality as an illustrative example.ResultsThe 2858 continuous variables with repeat measures, varied in sample size from 109 to 49 121. They fell into three groups: (i) baseline visit measures (529 variables; median ICC=0.64, IQR= [0.57, 0.83]); (ii) online dietary measures (22 variables; median ICC=0.35, IQR=[0.30, 0.40]) and (iii) imaging measures (2307 variables; median ICC=0.85, IQR=[0.73, 0.94]). Highest ICC were for anthropometric and medical history measures, and lowest for dietary and heart magnetic resonance imaging.The ICC for CRP was 0.29 (95% CI=[0.27, 0.30]), and for body mass index and smoking pack-years (confounders), were 0.93 (95% CI=[0.92, 0.93]) and 0.85 (95% CI=[0.84, 0.86]) respectively. The association of CRP with all-cause mortality (Hazard Ratio (HR)=1.029 per mg/L, 95% CI=[1.028, 1.031]) increased when correction for RDB was applied to the exposure (HR=1.119, 95% CI=[1.095, 1.143]). Confounder correction did not influence estimates.ConclusionsMeasurement error varies widely and is often non-negligible. For UK Biobank we provide relevant statistics and adaptable code to help other researchers explore and correct for bias due to measurement error.Key MessagesRandom measurement error in the exposure and confounders can bias the association between exposure and outcome towards or away from the null.Some prospective studies, including UK Biobank, provide repeat measures of variables in a sub-sample for exploring bias due to random measurement error; these are rarely used.Our results demonstrate that measurement error is often non-negligible and may bias estimates.Agreement between repeated measures varies by category. In UK Biobank, dietary measures and heart magnetic resonance imaging are least stable while anthropometric and medical history variables are most stable.We have provided intraclass correlation coefficients for 2858 continuous variables from UK Biobank and adaptable code to support researchers to correct for bias due to random error in exposures and confounders.