bluuebunny/crossref_metadata_2025_split huggingface dataset:
AnthropoAge, a novel approach to integrate body composition into the estimation of biological age
Authors: Fermín-Martínez Carlos A. , Márquez-Salinas Alejandro , Guerra Enrique C. , Zavala-Romero Lilian , Antonio-Villa Neftali Eduardo , Fernández-Chirino Luisa , Sandoval-Colin Eduardo , Barquera-Guevara Daphne Abigail , Muñoz Alejandro Campos , Vargas-Vázquez Arsenio , Paz-Cabrera César Daniel , Ramírez-García Daniel , Gutiérrez-Robledo Luis Miguel , Bello-Chavolla Omar Yaxmehen 
Published: September 2021

ABSTRACTAging is believed to occur across multiple domains, one of which is body composition; however, attempts to integrate it into biological age (BA) have been limited. Here, we consider the sex-dependent role of anthropometry for prediction of 10-year all-cause mortality using data from 18,794 NHANES participants to generate and validate a new BA metric. Our data-driven approach pointed to sex-specific contributors for BA estimation: WHtR, arm and thigh circumferences for men; weight, WHtR, thigh circumference, subscapular and triceps skinfolds for women. We used these measurements to generate AnthropoAge, which predicted all-cause mortality (AUROC 0.876, 95%CI 0.864-0.887) and cause-specific mortality independently of race, sex, and comorbidities; AnthropoAge was a better predictor than PhenoAge for cerebrovascular, Alzheimer and COPD mortality. A metric of age acceleration was also derived and used to assess sexual dimorphisms linked to accelerated aging, where women had an increase in overall body mass plus an important subcutaneous to visceral fat redistribution, and men displayed a marked decrease in fat and muscle mass. Finally, we showed that consideration of multiple BA metrics may identify unique aging trajectories with increased mortality (HR for multidomain acceleration 2.43, 95%CI 2.25-2.62) and comorbidity profiles. A simplified version of AnthropoAge (S-AnthropoAge) was generated using only BMI and WHtR, all results were preserved using this metric. In conclusion, AnthropoAge is a useful proxy of BA that captures cause-specific mortality and sex dimorphisms in body composition, and it could be used for future multidomain assessments of aging to better characterize the heterogeneity of this phenomenon.GRAPHICAL ABSTRACT
Revisiting the Use of Structural Similarity Index in Hi-C
Authors: Lee Hanjun , Blumberg Bruce , Lawrence Michael S. , Shioda Toshi 
Published: September 2021

AbstractIdentification of dynamic changes in chromatin conformation is a fundamental task in genetics. In 2020, Galan et al.1 presented CHESS (Comparison of Hi-C Experiments using Structural Similarity), a novel computational algorithm designed for systematic identification of structural differences in chromatin-contact maps. Using CHESS, the same group recently reported that chromatin organization is largely maintained across tissues during dorsoventral patterning of fruit fly embryos despite tissue-specific chromatin states and gene expression2. However, here we show that the primary outputs of CHESS–namely, the structural similarity index (SSIM) profiles–are nearly identical regardless of the input matrices, even when query and reference reads were shuffled to destroy any significant differences. This issue stems from the dominance of the regional counting noise arising from stochastic sampling in chromatin-contact maps, reflecting a fundamentally incorrect assumption of the CHESS algorithm. Therefore, biological interpretation of SSIM profiles generated by CHESS requires considerable caution.
Fluctuations in Neural Complexity During Wakefulness Relate To Conscious Level and Cognition
Authors: Mediano Pedro A.M. , Ikkala Aleksi , Kievit Rogier A. , Jagannathan Sridhar R. , Varley Thomas F. , Stamatakis Emmanuel A. , Bekinschtein Tristan A. , Bor Daniel 
Published: September 2021

ABSTRACTThere has been considerable recent progress in measuring conscious level using neural complexity measures. For instance, such measures can reliably distinguish healthy awake from asleep subjects and vegetative state patients. However, this line of research has never explored the dynamics of conscious level during normal wakefulness. Being able to capture meaningful differences in conscious level during wakefulness may provide a vital new insight into the nature of consciousness, by demonstrating what biological, behavioural and cognitive factors relate to such differences. Here we take advantage of a large MEG and fMRI dataset of healthy adults, to examine within-subject conscious level fluctuations during resting state and tasks, by using a range of complexity measures. We first establish the validity of this approach in both neuroimaging domains by relating neural complexity measures to pre-existing techniques for capturing transitions of consciousness from full wakefulness into drowsiness and the earliest stages of sleep, finding decreased complexity as participants become increasingly drowsy. We further demonstrate that neural complexity measures in both MEG and fMRI change both within and between tasks, and relate to performance on an executive task, with higher complexity associated with better performance and faster reaction times. This approach provides a powerful new route to further explore the cognitive and neural underpinnings of consciousness.
Characterization of Cervical-Cranial Muscle Network in Correlation with Vocal Features
Authors: O’Keeffe Rory , Shirazi Seyed Yahya , Mehrdad Sarmad , Crosby Tyler , Johnson Aaron M. , Atashzar S. Farokh 
Published: September 2021

AbstractObjective evaluation of physiological responses using non-invasive methods has attracted great interest regarding the assessment of vocal performance and disorders. This paper, for the first time, demonstrates that the topographical features of the cervical-cranial intermuscular coherence network generated using surface electromyography (sEMG) have a strong potential for detecting subtle changes in vocal performance. For this purpose, in this paper, 12 sEMG signals were collected from six cervical and cranial muscles bilaterally. Data were collected from four subjects without a history of a voice disorder performing a series of vocal tasks. The vocal tasks were varied phonation (an /a/ sustained for the maximal duration with combinations of two levels of loudness and two levels of pitch), a pitch glide from low to high, singing a familiar song, spontaneous speech, and reading with different loudness levels. The varied phonation tasks showed the median degree, and weighted clustering coefficient of the coherence-based intermuscular network ascends monotonically, with a high effect size (|rrb| = 0.52). The set of tasks, including pitch glide, singing, and speech, was significantly distinguishable using the network features as both degree and weighted clustering coefficient had a very high effect size (|rrb| > 0.83) across these tasks. Also, pitch glide has the highest degree and weighted clustering coefficient among all tasks (degree > 0.6, weighted clustering coefficient > 0.6). Spectrotemporal features performed far less effective than the proposed functional muscle network metrics to differentiate the vocal tasks. The highest effect size for spectrotemporal features was only |rrb| = 0.19. In this paper, for the first time, the power of a cervical-cranial muscle network has been demonstrated as a neurophysiological window to vocal performance. The results also shed light on the tasks with the highest network involvement, which may be potentially used in monitoring vocal disorders and tracking rehabilitation progress.
Traumatic Brain Injury Exacerbates Alzheimer’s Disease Pathology in the Retinas of TgF344-AD Rats
Authors: Secora Conner , Vielle Anne , Wang Athena Ching-Jung , Lenhart Patricia , Salcedo Ernesto , Johnson Noah R. , Ahmed Md. Mahuiddin , Chial Heidi J. , Boyd Timothy D. , Potter Huntington , Natalia Vergara M. 
Published: September 2021

AbstractAlzheimer’s disease (AD) is a neurodegenerative condition that affects 6.2 million people age 65 and older in the U.S. alone, and is the leading cause of dementia. Moreover, AD can lead to visual impairment, and AD histopathology also manifests in the retina. However, the factors that modulate AD pathophysiology and lead to varied susceptibility and presentation in the population are not well understood. In this context, traumatic brain injury (TBI), which can arise from sport concussions, military combat, and other causes, is associated with a 2.3-fold higher risk of developing AD and AD-related dementias (ADRD). Thus, we set out to evaluate the effects of TBI, AD, and their combination, on retinal histopathology.Several animal models have been developed to investigate the mechanisms underlying AD, but many have been limited by imperfect recapitulation of human pathology, and no model of TBI-associated AD (AD-TBI) has been characterized. To address this gap, we generated an innovative model of AD-TBI by taking advantage of a transgenic rat model (Tg-F344-AD) shown to recapitulate the main features of human AD pathology, and combining it with a twotime unilateral controlled cortical impact paradigm to mimic repetitive mild TBI (rmTBI). Histopathological analyses at four months post-impact confirm the presence of AD markers in transgenic retinas, and an increased severity of AD pathology due to TBI. Together, these results contribute to our understanding of the effects of TBI on AD retinopathy, with implications for patient care and therapeutic development.
Genetic effect modification of cis-acting C-reactive protein variants in cardiometabolic disease status
Authors: Zheng Jie , Tang Haotian , Lyon Matthew , Davies Neil M. , Walker Venexia , Floyd James S. , Austin Thomas R. , Shojaie Ali , Psaty Bruce M. , Gaunt Tom R. , Smith George Davey 
Published: September 2021

SummaryMendelian randomization (MR) studies carried out among patients with a particular health condition should establish the genetic instrument influences the exposure in that subgroup, however this is normally investigated in the general population. Here, we investigated whether the genetic associations of four cis-acting C-reactive protein (CRP) variants differed between participants with and without three cardiometabolic conditions: obesity, type 2 diabetes, and cardiovascular disease. Associations of cis-genetic variants with CRP differed between obese and non-obese individuals. A multivariable analysis suggested strong independent associations of the gene-by-body mass index (BMI) interaction on CRP (P<1.18×10−8 for the CRP variants). Applying MR, we observed strong causal effect of BMI on CRP (P=2.14×10−65). In summary, our study indicates that genetic associations with CRP differ across disease sub-groups, with evidence to suggest that BMI is an effect modifier. MR studies of disease progression should report on the genetic instrument-exposure association in the disease subgroup under investigation.
Biclique extension as an effective approach to predict novel interaction partners in metabolic compound-protein interaction networks
Authors: Thieme Sandra , Walther Dirk 
Published: September 2021

AbstractMotivationMetabolic networks are complex systems of connected chemical reactions with physical interactions between metabolites and proteins playing a critical role for both metabolic conversion and regulation. In this study, we aimed to predict previously unknown compound-protein interactions (CPI) by transferring the concept of biclique extension, which was developed in the context of drug-target interaction prediction and that is based on the rationale that interactions that readily extend an existing biclique are real, to metabolic CPI networks.ResultsWe developed and tested a workflow to predict CPIs based on the concept of extending existing bicliques and applied it toE. coliand human using their respective known CPI network as input. Depending on the chosen biclique size, for theE. colinetwork we reached a sensitivity of 39% with an associated precision of 59%. For the larger human CPI network, a sensitivity of 78% with a false-positive rate of less than 5% and an associated precision of 75% was obtained. At more stringent settings, a precision as high as 95% was attainable at the expense of a lowered recall. Prediction performance significantly exceeded that obtained using randomized networks as input. Predicted novel interactions were tested for biomolecular function involvement, with TCA-cycle and ribosomal processes found associated with particularly pronounced statistical significance. As we demonstrate, our approach holds great potential to increase efficiency of experimental testing of CPIs and can readily be transferred to other species of interest.Availability and implementationThe R code and datasets are available athttps://github.com/SandraThieme/BiPredict.
An innovative optical context to make honeybees crash repeatedly
Authors: Serres Julien R. , Morice Antoine H.P. , Blary Constance , Miot Romain , Montagne Gilles , Ruffier Franck 
Published: September 2021

AbstractTo investigate altitude control in honeybees, an optical context was designed to make honeybees crash. It has been widely accepted that honeybees rely on the optic flow generated by the ground to control their altitude. However, identifying an optical context capable of uncorrelating forward speed from altitude in honeybees’ flight was the first step towards enhancing the optical context to better understand altitude control in honeybees. This optical context aims to put honeybees in the same flight conditions as an open sky flight above mirror-smooth water. An optical manipulation, based on a pair of opposed horizontal mirrors, was designed to remove any visual information coming from the floor and ceiling. Such an optical manipulation reproduced quantitatively the seminal experiment of Heran & Lindauer (1963), and revealed that honeybees control their altitude by detecting the optic flow with a visual field that extends to approximately 165°.
Models as games: a novel approach for ‘gamesourcing’ parameter data and communicating complex models
Authors: Minderman Jeroen , Duthie A. Bradley , Jones Isabel L. , Thomas-Walters Laura , Bach Adrian , Nuttall Matthew , Bunnefeld Nils 
Published: September 2021

1SummaryModels have become indispensable tools in conservation science in the face of increasingly rapid loss of biodiversity through anthropogenic habitat loss and natural resource exploitation. In addition to their ecological components, accurately representing human decision-making processes in such models is vital to maximise their utility. This can be problematic as modelling complexity increases, making them challenging to communicate and parameterise.Games have a long history of being used as science communication tools, but are less widely used as data collection tools, particularly in videogame form. We propose a novel approach to (1) aid communication of complex social-ecological models, and (2) “gamesource” human decision-making data, by explicitly casting an existing modelling framework as an interactive videogame.We present players with a natural resource management game as a front-end to a social-ecological modelling framework (Generalised Management Strategy Evaluation, GMSE). Players’ actions replace a model algorithm making management decisions about a population of wild animals, which graze on crops and can thus lower agricultural yield. A number of non-player agents (farmers) respond through modelled algorithms to the player’s management, taking actions that may affect their crop yield as well as the animal population. Players are asked to set their own management goal (e.g. maintain the animal population at a certain level or improve yield) and make decisions accordingly. Trial players were also asked to provide any feedback on both gameplay and purpose.We demonstrate the utility of this approach by collecting and analysing game play data from a sample of trial plays, in which we systematically vary two model parameters, and allowing trial players to interact with the model through the game interface. As an illustration, we show how variations in land ownership and the number of farmers in the system affects decision-making patterns as well as population trajectories (extinction probabilities).We discuss the potential and limitations of this model-game approach in the light of trial player feedback received. In particular, we highlight how a common concern about the game framework (perceived lack of “realism” or relevance to a specific context) are actually criticisms of the underlying model, as opposed to the game itself. This further highlights both the parallels between games and models, as well as the utility of model-games to aid in communicating complex models. We conclude that videogames may be an effective tool for conservation and natural resource management, and that although they provide a promising means to collect data on human decision-making, it is vital to carefully consider both external validity and potential biases when doing so.
Not all that is gold glitters: PV-IRES-Cre mouse line shows low efficiency of labeling of parvalbumin interneurons in the perirhinal cortex
Authors: Nigro Maximiliano José , Kirikae Hinako , Kjelsberg Kasper , Nair Rajeevkumar Raveendran , Witter Menno P. 
Published: September 2021

AbstractThe wide diversity of cortical inhibitory neuron types populating the cortex allows the assembly of diverse microcircuits and endows these circuits with different computational properties. Thus, characterizing neuronal diversity is fundamental to describe the building blocks of cortical microcircuits and probe their function. To this purpose, the mouse has emerged as a powerful tool to genetically label and manipulate specific inhibitory cell-types in the mammalian brain. Among these cell-types, the parvalbumin-expressing interneuron type (PV-INs) is perhaps the most characterized. Several mouse lines have been generated to target PV-INs. Among these mouse lines, the PV-IRES-Cre lines is the most widely used and demonstrated a high specificity and efficiency in targeting PV-INs in different cortical areas. However, a characterization of the performance across cortical regions is still missing. Here we show that the PV-IRES-Cre mouse line labels only a fraction of parvalbumin immunoreactive neurons in perirhinal cortex and other association areas. Our results point to a yet uncharacterized diversity within the PV-INs and emphasize the need to characterize these tools in specific cortical areas.
A network model of glymphatic flow under different experimentally-motivated parametric scenarios
Authors: Tithof Jeffrey , Boster Kimberly A. S. , Bork Peter A. R. , Nedergaard Maiken , Thomas John H. , Kelley Douglas H. 
Published: September 2021

AbstractRapidly growing evidence demonstrates that flow of cerebrospinal fluid (CSF) through perivascular spaces (PVSs) – annular channels surrounding vasculature in the brain – is a critically-important component of neurophysiology. CSF inflow contributes during physiological conditions to clearance of metabolic waste and in pathological situations to edema formation. However, brain-wide imaging methods cannot resolve PVSs, and high-resolution methods cannot access deep tissue or be applied to human subjects, so theoretical models provide essential insight. We model this CSF pathway as a network of hydraulic resistances, built from published parameters. A few parameters have very wide uncertainties, so we focus on the estimated limits of their feasible ranges by analyzing different parametric scenarios. We identify low-resistance PVSs and high-resistance parenchyma (brain tissue) as the scenario that best explains experimental observations. Our results point to the most important parameters that should be measured in future experiments. Extensions of our modeling may help predict stroke severity or lead to neurological disease treatments and drug delivery methods.
Rescuing Biologically Relevant Consensus Regions Across Replicated Samples
Authors: Jalili Vahid , Cremona Marzia Angela , Palluzzi Fernando 
Published: September 2021

AbstractMotivationProtein-DNA binding sites of ChIP-seq experiments are identified where the binding affinity is significant based on a given threshold. The choice of the threshold is a trade-off between conservative region identification and discarding weak, but true binding sites.ResultsWe argue the biological relevance of weak binding sites and the information they add when rescued. The sites are rescued using MSPC, which exploits replicates to lower the threshold required to identify a binding site while keeping a low false-positive rate. We extend MSPC to call consensus regions across any number of replicated samples, accounting for differences between biological and technical replicates. We observed several master transcription regulators (e.g., SP1 and GATA3) and HDAC2-GATA1 regulatory networks on rescued regions.Availability and implementationAn implementation of the proposed method and the scripts to reproduce the performed analysis are freely available at https://genometric.github.io/MSPC/, MSPC is distributed as a command-line application, an R package available from Bioconductor (https://doi.org/doi:10.18129/B9.bioc.rmspc), and a C# library.
Domain General Processes for Interactive Touch
Authors: Buck Tao , DiCocco Courtney , Cuzzocreo Jennifer L. , Noah J. Adam , Zhang Xian , Hirsch Joy 
Published: September 2021

AbstractThe nexus model of social processing proposes that the right temporal parietal junction (rTPJ) serves as a neural hub for cognitive social functions. We test the hypothesis that the rTPJ is a domain general region including somatosensory social functions. Neuroimaging findings and cross-brain coherence for right- and left-hand handclasps with real vs. simulated hands were consistent with the domain general model.
Compositional phylogenomic modelling resolves the ‘Zoraptera problem’: Zoraptera are sister to all other polyneopteran insects
Authors: Tihelka Erik , Engel Michael S. , Lozano-Fernandez Jesus , Giacomelli Mattia , Yin Ziwei , Rota-Stabelli Omar , Huang Diying , Pisani Davide , Donoghue Philip C.J. , Cai Chenyang 
Published: September 2021

AbstractThe evolution of wings propelled insects to their present mega-diversity. However, interordinal relationships of early-diverging winged insects and the timescale of their evolution are difficult to resolve, in part due to uncertainties in the placement of the enigmatic and species-poor order Zoraptera. The ‘Zoraptera problem’ has remained a contentious issue in insect evolution since its discovery more than a century ago. This is a key issue because different placements of Zoraptera imply dramatically different scenarios of diversification and character evolution among polyneopteran. Here, we investigate the systematic placement of Zoraptera using the largest protein-coding gene dataset available to date, deploying methods to mitigate common sources of error in phylogenomic inference, and testing historically proposed hypotheses of zorapteran evolution. We recover Zoraptera as the earliest-diverging polyneopteran order, while earwigs (Dermaptera) and stoneflies (Plecoptera) form a monophyletic clade (Dermoplectopterida) sister to the remainder of Polyneoptera. The morphology and palaeobiology of stem-zorapterans are informed by Mesozoic fossils. The gut content and mouthparts of a male specimen ofZorotypus nascimbeneifrom Kachin amber (Cretaceous) reveal a fungivorous diet of Mesozoic zorapterans, akin to extant species. Based on a set of 42 justified fossil and stratigraphic calibrations, we recover a Devonian origin of winged insects and Polyneoptera, suggesting that these groups coincided with the rise of arborescence during the diversification of early terrestrial plants, fungi, and animals. Our results provide a robust framework for understanding the pattern and timescale of early winged insect diversification.