bluuebunny/crossref_metadata_2025_split huggingface dataset:
Persistent frustration-induced reconfigurations of brain networks predict individual differences in irritability
Authors: Linke J.O. , Haller S.P. , Xu E. , Nguyen L. , Chue A. , Zapp C. , Revzina O. , Perlstein S. , Ross A.J. , Tseng W.-L. , Shaw P. , Brotman M.A. , Pine D.S. , Gotts S.J. , Leibenluft E. , Kircanski K. 
Published: November 2021

AbstractBackgroundFrustration, the response to blocked goal attainment, is a universal affective experience, but how the brain embodies frustration is not known. Understanding brain network dynamics during frustration may provide insight into pediatric irritability, one of the most frequent reasons for psychiatric consultation in youth and a risk factor for affective disorders and suicidality.MethodsUsing fMRI, we investigated changes in neural network architecture from a baseline resting-state, through a task that included frustrative nonreward (FNR) and anticipation of new feedback following FNR (FNR+1), to a post-task resting-state in a transdiagnostic sample of 66 youth (33 female, mean age 14 years). Using a train/test/held-out procedure, we aimed to predict past-week irritability from the global efficiency (i.e., Eglob, capacity for parallel information processing) of brain networks before, during, and after frustration.ResultsCompared to pre-task resting state, FNR+1 and the post-state resting state were uniquely associated with a more segregated brain network organization. Nodes that were originally affiliated with the default-mode-temporal-limbic and fronto-parietal networks contributed most to this reconfiguration. Solely Eglob of brain networks that emerged after the frustrating task predicted self- and observer-rated irritability in previously unseen data. Self-reported irritability was predicted by Eglob of a fronto-temporal-limbic module, while observer-rated irritability was predicted by Eglob of motor-parietal and ventral-prefrontal-subcortical modules.DiscussionWe characterize frustration as an evolving brain network process and demonstrate the importance of the post-frustration recovery period for the pathophysiology of irritability; an insight that, if replicated, suggests specific intervention targets for irritability.
Computations of State Ventilation and Respiratory Parameters
Authors: Yang Quangang 
Published: November 2021

ABSTRACTBackgroundIn mechanical ventilation, there are still some challenges to turn a modern ventilator into a fully reactive device, such as lack of a comprehensive target variable and the unbridged gap between input parameters and output results. This paper aims to present a state ventilation which can provide a measure of two primary, but heterogenous, ventilation support goals. The paper also tries to develop a method to compute, rather than estimate, respiratory parameters to obtain the underlying causal information.MethodsThis paper presents a state ventilation, which is calculated based on minute ventilation and blood gas partial pressures, to evaluate the efficacy of ventilation support and indicate disease progression. Through mathematical analysis, formulae are derived to compute dead space volume/ventilation, alveolar ventilation, and CO2 production.ResultsMeasurements from a reported clinical study are used to verify the analysis and demonstrate the application of derived formulae. The state ventilation gives the expected trend to show patient status, and the calculated mean values of dead space volume, alveolar ventilation, and CO2 production are 158mL, 8.8L/m, and 0.45L/m respectively for a group of patients.Discussions and ConclusionsState ventilation can be used as a target variable since it reflects patient respiratory effort and gas exchange. The derived formulas provide a means to accurately and continuously compute respiratory parameters using routinely available measurements to characterize the impact of different contributing factors.
A theoretical framework for multi-species range expansion in spatially heterogeneous landscapes
Authors: Eigentler Lukas , Stanley-Wall Nicola R. , Davidson Fordyce A. 
Published: November 2021

AbstractRange expansion is the spatial spread of a population into previously unoccupied regions. Understanding range expansion is important for the study and successful manipulation and management of ecosystems, with applications ranging from controlling bacterial biofilm formation in industrial and medical environments to large scale conservation programmes for species undergoing climate-change induced habitat disruption. During range expansion, species typically encounter competitors. Moreover, the environment into which expansion takes place is almost always heterogeneous when considered at the scale of the individual. Despite the ubiquitous nature of these features, the impact of competition and spatial landscape heterogeneities on range expansion remains understudied. In this paper we present a theoretical framework comprising two competing generic species undergoing range expansion and use it to investigate the impact of spatial landscape heterogeneities on range expansion with a particular focus on its effect on competition dynamics. We reveal that the area covered by range expansion during a fixed time interval is highly variable due to the fixed landscape heterogeneities. Moreover, we report significant variability in competitive outcome (relative abundance of a focal species) but determine that this is induced by low initial population densities, independent of landscape heterogeneities. We further show that both area covered by range expansion and competitive outcome can be accurately predicted by a Voronoi tessellation with respect to an appropriate metric, which only requires information on the spatial landscape and the response of each species to that landscape. Finally, we reveal that if species interact antagonistically during range expansion, the dominant mode of competition depends on the initial population density. Antagonistic actions determine competitive outcome if the initial population density is high, but competition for space is the dominant mode of competition if the initial population density is low.
Neurons from individual early Alzheimer’s disease patients reflect their clinical vulnerability
Authors: Ng Bryan , Rowland Helen A. , Wei Tina , Arunasalam Kanisa , Hayes Emma Mee , Koychev Ivan , Hedegaard Anne , Ribe Elena M. , Chan Dennis , Chessell Tharani , ffytche Dominic , Gunn Roger N. , Kocagoncu Ece , Lawson Jennifer , Malhotra Paresh , Ridha Basil H. , Rowe James B. , Thomas Alan J. , Zamboni Giovanna , Buckley Noel J. , Cader Zameel M. , Lovestone Simon , Wade-Martins Richard 
Published: November 2021

AbstractEstablishing preclinical models of Alzheimer’s disease that predict clinical outcomes remains a critically important, yet to date not fully realised, goal. Models derived from human cells offer considerable advantages over non-human models, including the potential to reflect some of the inter-individual differences that are apparent in patients. Here we report an approach using induced pluripotent stem cell-derived cortical neurons from people with early symptomatic Alzheimer’s disease where we sought a match between individual disease characteristics in cells with analogous characteristics in the people from whom they were derived. We show that the response to amyloid-β burden in life, as measured by cognitive decline and brain activity levels, varies between individuals and this vulnerability rating correlates with the individual cellular vulnerability to extrinsic amyloid-β in vitro as measured by synapse loss and function. Our findings indicate that patient induced pluripotent stem cell-derived cortical neurons not only present key aspects of Alzheimer’s disease pathology, but also reflect key aspects of the clinical phenotypes of the same patients. Cellular models that reflect an individual’s in-life clinical vulnerability thus represent a tractable method of Alzheimer’s disease modelling using clinical data in combination with cellular phenotypes.
Identification of mRNAs that undergo stop codon readthrough inArabidopsis thaliana
Authors: Sahoo Sarthak , Singh Divyoj , Singh Anumeha , Eswarappa Sandeep M 
Published: November 2021

ABSTRACTA stop codon ensures termination of translation at a specific position on an mRNA. Sometimes, termination fails as translation machinery recognizes a stop codon as a sense codon. This leads to stop codon readthrough (SCR) resulting in the continuation of translation beyond the stop codon, generating protein isoforms with C-terminal extension. SCR has been observed in viruses, fungi, and multicellular organisms including mammals. However, SCR is largely unexplored in plants. In this study, we have analyzed ribosome profiling datasets to identify mRNAs that undergo SCR inArabidopsis thaliana. Analyses of the ribosome density, ribosome coverage and three-nucleotide periodicity of the ribosome profiling reads, in the mRNA region downstream of the stop codon, provided strong evidence for SCR in mRNAs of 144 genes. This process generates putative peroxisomal targeting signal, nuclear localization signal, prenylation signal, transmembrane helix and intrinsically disordered regions in the C-terminal extension of several of these proteins. Gene ontology (GO) functional enrichment analysis revealed that these 144 genes belong to three major functional groups - translation, photosynthesis and abiotic stress tolerance. Finally, using a luminescence-based assay, we experimentally demonstrate SCR in representative mRNAs belonging to these functional classes. Based on these observations, we propose that SCR plays an important role in plant physiology by regulating the protein localization and function.AUTHOR SUMMARYProtein synthesis executed by macromolecular complexes, termed ribosomes, starts and stops at specific locations on a messenger RNA (mRNA). This fidelity is critical for the normal functioning of cells. However, sometimes ribosomes don’t stop translation at the stop signal (termed stop codon) on an mRNA resulting in longer proteins with properties different from those of the canonical shorter protein. This process called stop codon readthrough (SCR) has been observed in viruses, fungi, and multicellular organisms including mammals. However, it remains largely unexplored in plants. In this study, we report evidence of SCR in 144 genes ofArabidopsis thaliana, a small flowering weed widely used as a model system to study plant biology. These genes are involved in protein synthesis, photosynthesis and stress tolerance in plants. We have also experimentally demonstrated SCR in a few genes that represent these functional classes. Our analysis shows that SCR can change the localization and functional properties of these proteins. We propose that SCR plays an important role in plant physiology.
Fast anther dehiscence state recognition system establishing by deep learning to screen heat tolerant cotton
Authors: Tan Zhihao , Shi Jiawei , Lv Rongjie , Li Qingyuan , Yang Jing , Ma Yizan , Li Yanlong , Wu Yuanlong , Zhang Rui , Ma Huanhuan , Li Yawei , Zhu Li , Kong Jie , Zhang Xianlong , Yang Wanneng , Min Ling 
Published: November 2021

AbstractCotton is one of the most economically important crops in the world. The fertility of male reproductive organs is a key determinant of cotton yield. The anther dehiscence or indehiscence directly determine the probability of fertilization in cotton. Thus, the rapid and accurate identification of cotton anther dehiscence status is important for judging anther growth status and promoting genetic breeding research. The development of computer vision technology and the advent of big data have prompted the application of deep learning techniques to agricultural phenotype research. Therefore, two deep learning models (Faster R-CNN and YOLOv5) were proposed to detect the number and dehiscence status of anthers. The single-stage model based on YOLOv5 has higher recognition efficiency and the ability to deploy to the mobile end. Breeding researchers can apply this model to terminals to achieve a more intuitive understanding of cotton anther dehiscence status. Moreover, three improvement strategies of Faster R-CNN model were proposed, the improved model has higher detection accuracy than YOLOv5 model. In addition, the percentage of dehiscent anther of randomly selected 30 cotton varieties were observed from cotton population under normal temperature and high temperature (HT) conditions through the integrated Faster R-CNN model and manual observation. The result showed HT varying decreased the percentage of dehiscent anther in different cotton lines, consistent with the manual method. Thus, this system can help us to rapid and accurate identification of HT-tolerant cotton.One sentence summaryThe deep learning technique was applied to identify the anther dehiscence state for the first time to quickly screen heat tolerant cotton varieties and help to explore key genetic improvement genes.
NIfTI-MRS: A standard format for magnetic resonance spectroscopic data
Authors: Clarke William T , Mikkelsen Mark , Oeltzschner Georg , Bell Tiffany K. , Shamaei Amirmohammad , Soher Brian J. , Emir Uzay E , Wilson Martin 
Published: November 2021

AbstractPurposeThe use of multiple data formats in the MRS community currently hinders data sharing and integration. NIfTI-MRS is proposed as a standard MR spectroscopy data format, which is implemented as an extension to the neuroimaging informatics technology initiative (NIfTI) format.Using this standardised format will facilitate data sharing, ease algorithm development, and encourage the integration of MRS analysis with other imaging modalities.MethodsA file format based on the NIfTI header extension framework was designed to incorporate essential spectroscopic metadata and additional encoding dimensions. A detailed description of the specification is provided. An open-source command-line conversion program is implemented to enable conversion of single-voxel and spectroscopic imaging data to NIfTI-MRS. To provide visualisation of data in NIfTI-MRS, a dedicated plugin is implemented for FSLeyes, the FSL image viewer.ResultsAlongside online documentation, ten example datasets are provided in the proposed format. In addition, minimal examples of NIfTI-MRS readers have been implemented. The conversion software, spec2nii, currently converts fourteen formats to NIfTI-MRS, including DICOM and vendor proprietary formats.ConclusionThe proposed format aims to solve the issue of multiple data formats being used in the MRS community. By providing a single conversion point, it aims to simplify the processing and analysis of MRS data, thereby lowering the barrier to use of MRS. Furthermore, it can serve as the basis for open data sharing, collaboration, and interoperability of analysis programs. It also opens possibility of greater standardisation and harmonisation. By aligning with the dominant format in neuroimaging, NIfTI-MRS enables the use of mature tools present in the imaging community, demonstrated in this work by using a dedicated imaging tool, FSLeyes, as a viewer.
Oversized cells activate global proteasome-mediated protein degradation to maintain cell size homeostasis
Authors: Liu Shixuan , Tan Ceryl , Melo-Gavin Chloe , Ginzberg Miriam B. , Blutrich Ron , Patel Nish , Rape Michael , Mark Kevin G. , Kafri Ran 
Published: November 2021

AbstractProliferating animal cells maintain a stable size distribution over generations despite fluctuations in cell growth and division size. This tight control of cell size involves both cell size checkpoints, which delay cell cycle progression in small cells, and size-dependent regulation of mass accumulation rates. While we previously identified the p38 MAPK pathway as a key regulator of the mammalian cell size checkpoint, the mechanism of size-dependent growth rate regulation has remained elusive. Here, we quantified global rates of protein synthesis and degradation in cells of varying sizes, both under unperturbed conditions and in response to perturbations that trigger size-dependent compensatory growth slowdown. We found that protein synthesis rates scale proportionally with cell size across cell cycle stages and experimental conditions. In contrast, oversized cells that undergo compensatory growth slowdown exhibit a superlinear increase in proteasome-mediated protein degradation, with accelerated protein turnover per unit mass, suggesting activation of the proteasomal degradation pathway. Both nascent and long-lived proteins contribute to the elevated protein degradation during compensatory growth slowdown, with long-lived proteins playing a crucial role at the G1/S transition. Notably, large G1/S cells exhibit particularly high efficiency in protein degradation, surpassing that of similarly sized or larger cells in S and G2, coinciding with the timing of the most stringent size control in animal cells. These results collectively suggest that oversized cells reduce their growth efficiency by activating global proteasome-mediated protein degradation to promote cell size homeostasis.
Prehension Kinematics in Humans and Macaques
Authors: Yan Yuke , Sobinov Anton R. , Bensmaia Sliman J. 
Published: November 2021

AbstractNon-human primates, especially rhesus macaques, have been a dominant model to study sensorimotor control of the upper limbs. Indeed, human and macaques have similar hands and homologous neural circuits to mediate manual behavior. However, few studies have systematically and quantitatively compared the manual behaviors of the two species. Such comparison is critical for assessing the validity of using the macaque sensorimotor system as a model of its human counterpart. In this study, we systematically compared the prehensile behaviors of humans and rhesus macaques using an identical experimental setup. We found human and macaque prehension kinematics to be generally similar with a few subtle differences. While the structure of the preshaping postures is similar in humans and macaques, human postures are more object-specific and human joints are less intercorrelated. Conversely, monkeys demonstrate more stereotypical grasping behaviors that are common across all grasp conditions and more variability in their postures across repeated grasps of the same object. Despite these subtle differences in manual behavior between humans and monkeys, our results bolster the use of the macaque model to understand the neural mechanisms of manual dexterity in humans.New and newsworthyMacaques have been a dominant animal model to study the neural mechanisms of human dexterity because they exhibit complex manual behavior. We show that the kinematics of prehension – a critical dexterous behavior – are largely similar in humans and macaques. However, human preshaping postures are more object-specific and the movement of human digits are less correlated with each other. The thumb, index, and wrist are major driver of these interspecies differences.
On-tissue spatial proteomics integrating MALDI-MS imaging with shotgun proteomics reveals soy consumption-induced biomarkers in a fragile X syndrome mouse model
Authors: Ma Min , Yu Qinying , Delafield Daniel G. , Cui Yusi , Li Zihui , Wu Wenxin , Shi Xudong , Gutierrez Alejandra , Westmark Pamela R. , Xu Meng , Westmark Cara J. , Li Lingjun 
Published: November 2021

AbstractSoy-based diets are associated with increased seizures and autism. Thus, there is an acute need for unbiased protein biomarker identification in Fragile X syndrome (FXS) in response to soy consumption. Herein, we present a spatial proteomics approach integrating mass spectrometry imaging (MSI) with label-free proteomics in a mouse model of FXS to map the spatial distribution and quantify the levels of proteins in the hippocampus and hypothalamus brain regions. In total, 1,004 unique peptides were spatially resolved, demonstrating the diverse array of peptidomes present in the tissue slices and the broad coverage of the strategy. A group of proteins that are known to be involved in the GABAergic system, synaptic transmission, and co-expression network analysis indicated that protein in soy group was significantly associated with metabolism and synapse modules in the Fmr1KO brain. Ultimately, this spatial proteomics work laid the ground for identifying novel therapeutic targets and biomarkers for FXS.
In silico Analysis of Nonsynonymous Genomic Variants within CCM2 Gene Reaffirm the Existence of Dual Cores within Typical PTB Domain
Authors: Padarti Akhil , Belkin Ofek , Abou-Fadel Johnathan , Zhang Jun 
Published: November 2021

AbstractPurposeThe objective of this study is to validate the existence of dual cores within the typical phosphotyrosine binding (PTB) domain and to identify potentially damaging and pathogenic nonsynonymous coding single nuclear polymorphisms (nsSNPs) in the canonical PTB domain of the CCM2 gene that causes cerebral cavernous malformations (CCMs).MethodsThe nsSNPs within the coding sequence for PTB domain of human CCM2 gene, retrieved from exclusive database search, were analyzed for their functional and structural impact using a series of bioinformatic tools. The effects of the mutations on tertiary structure of the PTB domain in human CCM2 protein were predicted to examine the effect of the nsSNPs on tertiary structure on PTB Cores.ResultsOur mutation analysis, through alignment of protein structures between wildtype CCM2 and mutant, indicated that the structural impacts of pathogenic nsSNPs is biophysically limited to only the spatially adjacent substituted amino acid site with minimal structural influence on the adjacent core of the PTB domain, suggesting both cores are independently functional and essential for proper CCM2 function.ConclusionUtilizing a combination of protein conservation and structure-based analysis, we analyzed the structural effects of inherited pathogenic mutations within the CCM2 PTB domain. Our results indicated that the pathogenic amino acid substitutions lead to only subtle changes locally confined to the surrounding tertiary structure of the PTB core within which it resides, while no structural disturbance to the neighboring PTB core was observed, reaffirming the presence of dual functional cores in the PTB domain.
Quantitative analysis of transcription start site selection inSaccharomyces cerevisiaereveals control by DNA sequence, RNA Polymerase II activity, and NTP levels
Authors: Zhu Yunye , Vvedenskaya Irina O. , Sze Sing-Hoi , Nickels Bryce E. , Kaplan Craig D. 
Published: November 2021

AbstractTranscription start site (TSS) selection is a key step in gene expression and occurs at many promoter positions over a wide range of efficiencies. Here, we develop a massively parallel reporter assay to quantitatively dissect contributions of promoter sequence, NTP substrate levels, and RNA polymerase II (Pol II) activity to TSS selection by “promoter scanning” inSaccharomyces cerevisiae(Pol II MAssively Systematic Transcript End Readout, “Pol II MASTER”). Using Pol II MASTER, we measure the efficiency of Pol II initiation at 1,000,000 individual TSS sequences in a defined promoter context. Pol II MASTER confirms proposed critical qualities ofS. cerevisiaeTSS -8, -1, and +1 positions quantitatively in a controlled promoter context. Pol II MASTER extends quantitative analysis to surrounding sequences and determines that they tune initiation over a wide range of efficiencies. These results enabled the development of a predictive model for initiation efficiency based on sequence. We show that genetic perturbation of Pol II catalytic activity alters initiation efficiency mostly independently of TSS sequence, but selectively modulates preference for initiating nucleotide. Intriguingly, we find that Pol II initiation efficiency is directly sensitive to GTP levels at the first five transcript positions and to CTP and UTP levels at the second position genome wide. These results suggest individual NTP levels can have transcript-specific effects on initiation, representing a cryptic layer of potential regulation at the level of Pol II biochemical properties. The results establish Pol II MASTER as a method for quantitative dissection of transcription initiation in eukaryotes.