bluuebunny/crossref_metadata_2025_split huggingface dataset:
A generalized kinetic model describes ion-permeation mechanisms in various ion channels
Authors: Wu Di 
Published: May 2021

AbstractIon channels conduct various ions across biological membranes to maintain the membrane potential, to transmit the electrical signals, and to elicit the subsequent cellular responses by the signaling ions. Ion channels differ in their capabilities to select and conduct ions, which can be studied by the patch-clamp recording method that compares the current traces responding to the test voltage elicited at different conditions. In these experiments, the current-voltage curves are usually fitted by a sigmoidal function containing the Boltzmann factor. This equation is quite successful in fitting the experimental data in many cases, but it also fails in several others. Regretfully, some useful information may be lost in these data, which otherwise can reveal the ion-permeation mechanisms. Here we present a generalized kinetic model that captures the essential features of the current-voltage relations and describes the simple mechanism of the ion permeation through different ion channels. We demonstrate that this model is capable to fit various types of the patch-clamp data and explain their ion-permeation mechanisms.
metID:A R package for automatable compound annotation for LC−MS-based data
Authors: Shen Xiaotao , Wu Si , Liang Liang , Chen Songjie , Contrepois Kévin , Zhu Zheng-Jiang , Snyder Michael 
Published: May 2021

AbstractSummaryAccurate and efficient compound annotation is a long-standing challenge for LC−MS-based data (e.g. untargeted metabolomics and exposomics). Substantial efforts have been devoted to overcoming this obstacle, whereas current tools are limited by the sources of spectral information used (in-house and public databases) and are not automated and streamlined. Therefore, we developedmetID, an R package that combines information from all major databases for comprehensive and streamlined compound annotation.metIDis a flexible, simple, and powerful tool that can be installed on all platforms, allowing the compound annotation process to be fully automatic and reproducible. A detailed tutorial and a case study are provided in Supplementary Materials.Availability and implementationhttps://jaspershen.github.io/metID/.Contactjiangzhu@sioc.ac.cnandmpsnyder@stanford.edu
Knowledge production and translation of science between Academia and Industry: assessing the impact of R&D in India
Authors: US Vishal Rao , Ram Jenu Naga Durga , Arakeri Gururaj , Nayar Ravi C , Kumar Jitendra , Mendes Rui Amaral 
Published: May 2021

AbstractIndia is at the 3rdposition worldwide in terms of publication of scientific literature. However, in terms of productivity, it has been consistently failing to transform the research knowledge into industrial output. This study compares India with the leading countries to understand its lacuna in terms of R&D policy and outputs. Although scientific publications are regarded as the output of basic research, patent applications serve as a better indicator of the applied research. This paper assesses the important determinants for patent filings of a nation. It also focuses on the role of academia and industry collaboration in R&D and the productivity of a nation. We found that the higher the GERD (total Gross Domestic Expenditure of R&D) and the R&D personnel in a nation, the higher the patent filings of the nation. Moreover, we show that academia-industrial collaboration plays a key role in transforming basic research into real-world applications, as we illustrate the government’s role in making necessary policies to make the collaboration successful. This paper highlights the significance of investing in R&D to improve the productivity of a nation, as also the need to design policies to strengthen the applied research environment by fostering solution-centric collaborations between academia and industry.
ARTIFICIAL INTELLIGENCE ACCURATELY DETECTS TRAUMATIC THORACOLUMBAR FRACTURES ON SAGITTAL RADIOGRAPHS
Authors: Rosenberg Guillermo Sanchez , Cina Andrea , Schirò Giuseppe Rosario , Giorgi Pietro Domenico , Gueorguiev Boyko , Alini Mauro , Varga Peter , Galbusera Fabio , Gallazzi Enrico 
Published: May 2021

AbstractBackground contextTraumatic thoracolumbar (TL) fractures are frequently encountered in emergency rooms. Sagittal and anteroposterior radiographs are the first step in the trauma routine imaging. Up to 30% of TL fractures are missed in this imaging modality, thus requiring a CT and/or MRI to confirm the diagnosis. A delay in treatment leads to increased morbidity, mortality, exposure to ionizing radiation and financial burden. Fracture detection with Machine Learning models has achieved expert level performance in previous studies. Reliably detecting vertebral fractures in simple radiographic projections would have a significant clinical and financial impact.PurposeTo develop a deep learning model that detects traumatic fractures on sagittal radiographs of the TL spine.Study design/settingRetrospective Cohort study.MethodsWe collected sagittal radiographs, CT and MRI scans of the TL spine of 362 patients exhibiting traumatic vertebral fractures. Cases were excluded when CT and/or MRI where not available. The reference standard was set by an expert group of three spine surgeons who conjointly annotated the sagittal radiographs of 171 cases. CT and/or MRI were reviewed to confirm the presence and type of the fracture in all cases. 302 cropped vertebral images were labelled ‘fracture’ and 328 ‘no fracture’. After augmentation, this dataset was then used to train, validate, and test deep learning classifiers based on ResNet18 and VGG16 architectures. To ensure that the model’s prediction was based on the correct identification of the fracture zone, an Activation Map analysis was conducted.ResultsVertebras T12 to L2 were the most frequently involved, accounting for 48% of the fractures. A4, A3 and A1 were the most frequent AO Spine fracture types. Accuracies of 88% and 84% were obtained with ResNet18 and VGG16 respectively. The sensitivity was 89% with both architectures but ResNet18 showed a higher specificity (88%) compared to VGG16 (79%). The fracture zone was precisely identified in 81% of the heatmaps.ConclusionsOur AI model can accurately identify anomalies suggestive of vertebral fractures in sagittal radiographs by precisely identifying the fracture zone within the vertebral body.Clinical significanceClinical implementation of a diagnosis aid tool specifically trained for TL fracture identification is anticipated to reduce the rate of missed vertebral fractures in emergency rooms.
IMMUND: an Early Stage Diagnostic and Therapeutic Frame for Neurodegenerative Diseases and Multiple Sclerosis based on Immunological Markers
Authors: Sen Sagnik , Dey Ashmita , Sanyal Dwipanjan , Chattopadhyay Krishnananda , Maulik Ujjwal 
Published: May 2021

ABSTRACTFor neurodegenerative diseases, the impact of immunological markers is one of the modern research areas. It has been observed that neuroinflammation increases the cellular precipitation of some of the key proteins associated with neurodegenerative diseases. Therefore, the possibility of functional loss can be enhanced due to neuroinflammation which leads to the initiation of any related diseases. In this regard, autoantibodies, which are known for their autophagy nature, can be considered as key elements for early diagnostic as well as early therapeutics. In this article, we have proposed a comprehensive framework to unveil the diagnostic as well as the therapeutic possibility of the autoantibodies which are largely associated with Mild-Moderate Alzheimer’s Disease, Early-Stage Parkinson’s Disease, and Multiple Sclerosis. Here, we have introduced a new concept of average p-value where multiple p-values of an autoantibody in a singular disease have been considered as a multi-occurrence of that sample in cellular systems. Also, multiple proteins from a single protein family under a differentially expressed range have been prioritized. As a result, the top ten autoantibodies have been selected for further study and also considered as diagnostic markers. Interestingly, most of the selected autoantibodies are either cytokines or immunoglobulins. Subsequently, we have performed an evolutionary sequence-structure space study to identify the druggable structural facet for the selected autoantibodies. To make the therapeutic perspective more robust, we have introduced the concept of protein moonlighting. Hence, it provides more robustness in therapeutic identification. Finally, two autoantibodies i.e., Q9NYV4 and P01602 are identified as a novel marker.
Stress-induced protein disaggregation in the Endoplasmic Reticulum catalysed by BiP
Authors: Melo Eduardo Pinho , Farace Ilaria , Konno Tasuku , Awadelkareem Mosab Ali , Skov Lise R. , Sancho Teresa P. , Paton Adrienne W. , Paton James C. , Fares Matthew , Paulo Pedro M. R. , Zang Xin , Avezov Edward 
Published: May 2021

AbstractProtein synthesis is supported by cellular machineries that ensure polypeptides fold to their native three-dimensional conformation with high fidelity whilst eliminating misfolded, aggregation-prone species. While protein aggregates can contribute to pathologies exemplified by Alzheimer’s and Parkinson’s diseases, their abundance is normally minimised by molecular chaperones such as HSP70/90, which promote native folding and drive the recycling of aberrantly folded species. Cytoplasmic chaperones (e.g. HSP70/40) can resolve insoluble protein aggregates should the preventive mechanisms falter. However, it is unknown whether an analogous disaggregation system is needed and exists in the Endoplasmic Reticulum (ER), where ∼30% of the proteome is synthesised. Here we show that the ER of a variety of mammalian cell types, including neurons, is endowed with the capability to resolve protein aggregates that accumulate upon expression of metastable proteins. Utilising a purpose-developed protein aggregation probing system with a sub-organellar resolution, we observed steady-state aggregate accumulation in the ER. Strikingly, pharmacological induction of ER stress did not augment aggregates but rather stimulated their clearance within hours. We found that this disaggregation activity was catalysed by the stress-responsive ER molecular chaperone – BiP. Its elimination abolished the disaggregation activity in cells. Further, we reconstructed the disaggregation-reactionin-vitroby a minimal system of ATP-fuelled BiP and its J-protein cofactor. These data reveal a hitherto unknown, non-redundant function of the ER stress response. Thus, our findings may facilitate the identification of aggregation-antagonising strategies and rationalising the age-dependent protein misfolding pathology.SummaryER stress induction activates a protein disaggregation machinery, powered by BiP – an abundant ER chaperone, revealed by a FLIM-based protein aggregation monitoring in live cells.
Disrupted microglial iron homeostasis in progressive multiple sclerosis
Authors: Proto Jonathan D. , Zhang Mindy , Ryan Sean , Yao Xinting , Huang Yinyin , Chang Yi-Chien , Dufault Michael R. , Christie Emilie , Chomyka Anthony , Saleh Jackie , Sancho Jose , Hammond Timothy , Trapp Bruce , Ofengeim Dimitry 
Published: May 2021

ABSTRACTMultiple Sclerosis (MS) is a chronic autoimmune disease affecting the central nervous system (CNS). Despite therapies that reduce relapses, many patients eventually develop secondary progressive MS (SPMS), characterized by ongoing and irreversible neurodegeneration and worsening clinical symptoms. Microglia are the resident innate immune cells of the CNS. While the cellular and molecular determinants of disability progression in MS remain incompletely understood, they are thought to include non-resolving microglial activation and chronic oxidative injury. In this study, our aim was to better characterize microglia in SPMS tissues to identify disease-related changes at the single cell level. We performed single nucleus RNA-seq (snRNA-seq) on cryopreserved post-mortem brain cortex and identified disease associated changes in multiple cell types and in particular distinct SPMS-enriched microglia subsets. When compared to the cluster most enriched in healthy controls (i.e. homeostatic microglia), we found a number of SPMS-enriched clusters with transcriptional profiles reflecting increased oxidative stress and perturbed iron homeostasis. Using histology and RNA-scope, we confirmed the presence of iron accumulating, ferritin-light chain (FTL)-expressing microgliain situ. Among disease-enriched clusters, we found evidence for divergent responses to iron accumulation and identified the antioxidant enzyme GPX4 as a key fate determinant. These data help elucidate processes that occur in progressive MS brains, and highlight novel nodes for therapeutic intervention.
iPSC modeling shows uncompensated mitochondrial mediated oxidative stress underlies early heart failure in hypoplastic left heart syndrome
Authors: Xu Xinxiu , Jin Kang , Bais Abha S. , Zhu Wenjuan , Yagi Hisato , Feinstein Timothy N , Nguyen Phong , Criscione Joseph , Liu Xiaoqin , Beutner Gisela , Karunakaran Kalyani B. , Adams Phillip , Kuo Catherine K. , Kostka Dennis , Pryhuber Gloria S. , Shiva Sruti , Ganapathiraju Madhavi K. , Porter George A. , Lin Jiuann-Huey Ivy , Aronow Bruce , Lo Cecilia W. 
Published: May 2021

SummaryHypoplastic left heart syndrome (HLHS) is a severe congenital heart defect with 30% mortality from heart failure (HF) in the first year of life, but why only some patients suffer early-HF and its cause remain unknown. Modeling using induced pluripotent stem cell-derived cardiomyocytes (iPSC-CM) showed early-HF patient iPSC-CM have increased apoptosis, redox stress, and failed antioxidant response. This was associated with mitochondrial permeability transition pore (mPTP) opening, mitochondrial hyperfusion and respiration defects. Whereas iPSC-CM from patients without early-HF had hyper-elevated antioxidant response with increased mitochondrial fission and mitophagy. Single cell transcriptomics showed dichotomization by HF outcome, with mitochondrial dysfunction and endoplasmic reticulum (ER) stress associated with early-HF. Importantly, oxidative stress and apoptosis associated with early HF were rescued by sildenafil inhibition of mPTP opening or TUDCA suppression of ER stress. Together these findings demonstrate a new paradigm for modeling clinical outcome in iPSC-CM, demonstrating uncompensated mitochondrial oxidative stress underlies early HF in HLHS.
xbx-4, a homolog of the Joubert syndrome gene FAM149B1, acts via the CCRK and MAK kinase cascade to regulate cilia morphology
Authors: Maurya Ashish K. , Sengupta Piali 
Published: May 2021

ABSTRACTPrimary cilia are microtubule (MT)-based organelles that mediate sensory functions in multiple cell types. Disruption of cilia structure or function leads to a diverse collection of diseases termed ciliopathies (1–3). Mutations in the DUF3719 domain-containing protein FAM149B1 have recently been shown to elongate cilia via unknown mechanisms and result in the ciliopathy Joubert syndrome (4). The highly conserved CCRK and MAK/RCK kinases negatively regulate cilia length and structure inChlamydomonas, C. elegans, and mammalian cells (5–11). How the activity of this kinase cascade is tuned to precisely regulate cilia architecture is unclear. Here we identify XBX-4, a DUF3719 domain-containing protein related to human FAM149B1, as a novel regulator of the DYF-18 CCRK and DYF-5 MAK kinase pathway inC. elegans.As indyf-18anddyf-5mutants (11), sensory neuron cilia are elongated inxbx-4mutants and exhibit altered axonemal MT stability. XBX-4 promotes DYF-18 CCRK activity to regulate DYF-5 MAK function and localization. We find that Joubert syndrome-associated mutations in the XBX-4 DUF3719 domain also elongate cilia inC. elegans.Our results identify a new metazoan-specific regulator of this highly conserved kinase pathway, and suggest that FAM149B1 may similarly act via the CCRK/MAK kinase pathway to regulate ciliary homeostasis in humans.
Species variations in tenocytes’ response to inflammation require careful selection of animal models for tendon research
Authors: Oreff Gil Lola , Fenu Michele , Vogl Claus , Ribitsch Iris , Jenner Florien 
Published: May 2021

AbstractFor research on tendon injury, many different animal models are utilized; however, the extent to which these species simulate the clinical condition and disease pathophysiology has not yet been critically evaluated. Considering the importance of inflammation in tendon disease, this study compared the cellular and molecular features of inflammation in tenocytes of humans and four common model species (mouse, rat, sheep, and horse). While mouse and rat tenocytes most closely equalled human tenocytes’ low proliferation capacity and the negligible effect of inflammation on proliferation, the wound closure speed of humans was best approximated by rats and horses. The overall gene expression of human tenocytes was most similar to mice under healthy, to horses under transient and to sheep under constant inflammatory conditions. Humans were best matched by mice and horses in their tendon marker and collagen expression, by horses in extracellular matrix remodelling genes, and by rats in inflammatory mediators. As no single animal model perfectly replicates the clinical condition and sufficiently emulates human tenocytes, fit-for-purpose selection of the model species for each specific research question and combination of data from multiple species will be essential to optimize translational predictive validity.
Population Structure of Nation-wide Rice in Thailand
Authors: Vejchasarn Phanchita , Shearman Jeremy R. , Chaiprom Usawadee , Phansenee Yotwarit , Suthanthangjai Arissara , Jairin Jirapong , Chamarerk Varapong , Tulyananda Tatpong , Amornbunchornvej Chainarong 
Published: May 2021

AbstractBackgroundThailand is a country with large diversity in rice varieties due to its rich and diverse ecology. In this paper, 300 rice accessions from all across Thailand were sequenced to identify SNP variants allowing for the population structure to be explored.ResultsThe result of inferred population structure from admixture and clustering analysis illustrated strong evidence of substructure in each geographical region. The results of phylogenetic tree, PCA analysis, and machine learning on population identifying SNPs also supported the inferred population structure.ConclusionThe population structure inferred in this study contains five subpopulations that tend to group individuals based on location. So, each subpopulation has unique genetic patterns, agronomic traits, as well as different environmental conditions. This study can serve as a reference point of the nation-wide population structure for supporting breeders and researchers who are interested in Thai rice.
Insights into the molecular mechanisms of cell fate decision making processes from chromosome structural dynamics
Authors: Chu Xiakun , Wang Jin 
Published: May 2021

AbstractCell state transitions or cell fate decision making processes, such as cell development and cell pathological transformation, are believed to be determined by the regulatory network of genes, which intimately depend on the structures of chromosomes in the cell nucleus. The high temporal resolution picture of how chromosome reorganizes its 3D structure during the cell state transitions is the key to understanding the mechanisms of these fundamental cellular processes. However, this picture is still challenging to acquire at present. Here, we studied the chromosome structural dynamics during the cell state transitions among the pluripotent embryonic stem cell (ESC), the terminally differentiated normal cell and the cancer cell using landscape-switching model implemented in the molecular dynamics simulation. We considered up to 6 transitions, including differentiation, reprogramming, cancer formation and reversion. We found that the pathways can merge at certain stages during the transitions for the two processes having the same destination as the ESC or the normal cell. Before reaching the merging point, the two pathways are cell-type-specific. The chromosomes at the merging points show high structural similarity to the ones at the final cell states in terms of the contact maps, TADs and compartments. The post-merging processes correspond to the adaption of the chromosome global shape geometry through the chromosome compaction without significantly disrupting the contact formation. On the other hand, our detailed analysis showed no merging point for the two cancer formation processes initialized from the ESC and the normal cell, implying that cancer progression is a complex process and may be associated with multiple pathways. Our results draw a complete molecular picture of cell development and cancer at the dynamical chromosome structural level, and help our understanding of the molecular mechanisms of cell fate decision making processes.
Organ-specific metabolic pathways distinguish prediabetes, type 2 diabetes and normal tissues
Authors: Diamanti Klev , Cavalli Marco , Pereira Maria J. , Pan Gang , Castillejo-Lopez Casimiro , Kumar Chanchal , Mundt Filip , Komorowski Jan , Deshmukh Atul Shahaji , Mann Matthias , Korsgren Olle , Eriksson Jan W. , Wadelius Claes 
Published: May 2021

AbstractDefects in pancreatic islets and the progression of multi-tissue insulin resistance in combination with environmental factors are the main causes of type 2 diabetes (T2D). Mass spectrometry-based proteomics of five key-metabolic tissues on a cohort of 42 multi-organ donors provided deep coverage of the proteomes of pancreatic islets, visceral adipose tissue (VAT), liver, skeletal muscle and serum. Enrichment analysis of gene ontology (GO) terms built a tissue-specific map of the chronological order of altered biological processes across healthy controls (CTRL), pre-diabetes (PD) and T2D subjects. This unique dataset allowed us to explore alterations of entire biological pathways and individual proteins in multiple tissues. We confirmed the significant decrease of the citric acid cycle and the respiratory electron transport in VAT and muscle of T2D and we provided a thorough visual representation of the complete set of downregulated proteins. Importantly, we found widespread novel alterations in relevant biological pathways including the increase in hemostasis in pancreatic islets of PD, the increase in the complement cascade in liver and pancreatic islets of PD and the elevation in cholesterol biosynthesis in liver of T2D. Overall, our findings suggest inflammatory, immune and vascular impairments in pancreatic islets as potentially causal factors of insufficient insulin production and increased glucagon levels in the early stages of T2D. In contrast alterations in lipid metabolism and mitochondrial function in the liver and VAT/muscle, respectively, became evident later in manifest T2D. This first multi-tissue proteomic map indicates the temporal order of tissue-specific metabolic dysregulation in T2D development.