bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessment of Bone Formation After Secondary Alveolar Bone Grafting With and Without Platelet-Rich Plasma Using Computer-Aided Engineering Techniques
Authors: Chen Shuxiu , Liu Bing , Yin Ningbei , Wang Yongqian , Li Haidong 
Published: January 2020

Abstract
The aim of this study was to analyze the newly formed bone volume (FV), 6 months after secondary alveoloplasty using iliac cancellous bone graft, with and without platelet-rich plasma (PRP). Forty patients with unilateral alveolar cleft were involved in this randomized, prospective, comparative study, with 20 patients each forming the control (group A) and PRP (group B) groups, respectively. The preoperative alveolar defect volume (DV) and the postoperative FV were automatically calculated by the computer-aided engineering software using the patients’ pre and postsurgical computed tomography data. The volume of the actual bone graft (AV) was identical to the DV calculated before surgery. The bone formation ratio (BF%) was calculated as follows: BF% = (FV/AV) × 100%. The mean BF% was 42.54 ± 9.32% in group A and 46.97 ± 18.49% in group B. There was no statistically significant difference between the 2 groups for BF% (P > 0.05). The study presents a fast and accurate method for assessing the effect of PRP in alveolar grafting. However, the study found no conclusive evidence on the effect of PRP on bone growth.
Diverse genetic origins of medieval steppe nomad conquerors – a response to Mikheyev et al. (2019)
Authors: Elhaik Eran 
Published: January 2020

AbstractRecently, Mikheyev et al. (2019) have produced a preprint study describing the genomes of nine Khazars archeologically dated from the 7thto the 9thcenturies found in the Rostov county in modern-day Russia. Skull morphology indicated a mix of “Caucasoid” and “Mongoloid” shapes. The authors compared the samples to ancient and contemporary samples to study the genetic makeup of the Khazars and their genetic legacy and addressed the question of the relationships between the Khazar and Ashkenazic Jews. A careful examination reveals grave concerns regarding all the aspects of the study from the identification of the “Khazar” samples, the choice of environment for ancient DNA sequencing, and the analyses. The authors did not disclose the data used in their study, and their methodology is incoherent. We demonstrate that their analyses yield nonsensical results and argue that none of the claims made in this study are supported by the data unequivocally. Provided the destruction of the bone samples and the irreproducibility of the analyses, even by the forgivable standards of the field, this study is irreplicable, wasteful, and misleading.
Analysis of Plant-derived Phytochemicals as Anti-cancer Agents Targeting Cyclin Dependent Kinase-2, Human Topoisomerase IIa and Vascular Endothelial Growth Factor Receptor-2
Authors: Sarkar Bishajit , Ullah Md. Asad , Islam Syed Sajidul , Rahman Md. Hasanur 
Published: January 2020

AbstractCancer is caused by a variety of pathways, involving numerous types of enzymes, among them three enzymes: Cyclin dependent kinase-2 (CDK-2), Human topoisomerase IIα and Vascular Endothelial Growth Factor Receptor-2 (VEGFR-2) are three most common enzymes that are involved in the cancer development. Although many chemical drugs are available in the market, plant sources are known to contain a wide variety of agents that are known to possess anticancer activity. In this experiment, total thirty compounds were analysed against the mentioned enzymes using different tools of bioinformatics andin silicobiology like molecular docking study, druglikeness property experiment, ADME/T test, PASS prediction and P450 site of metabolism prediction as well as DFT calculations to determine three best ligands that have the capability to inhibit the mentioned enzymes. Form the experiment, Epigallocatechin gallate was found to be the best ligand to inhibit CDK-2, Daidzein showed best inhibitory activities towards Human topoisomerase IIα and Quercetin was predicted to be the best agent against VEGFR-2. They were also predicted to be quite safe and effective agents to treat cancer. However, morein vivoandin vitroanalysis are required to confirm their safety and efficacy in this regard.
simplePHENOTYPES: SIMulation of Pleiotropic, Linked and Epistatic PHENOTYPES
Authors: Fernandes Samuel B. , Lipka Alexander E. 
Published: January 2020

AbstractMotivationAdvances in genotyping and phenotyping techniques have enabled the acquisition of a great amount of data. Consequently, there is an interest in multivariate statistical analyses that identify genomic regions likely to contain causal mutations affecting multiple traits (i.e., pleiotropy). As the demand for multivariate analyses increases, it is imperative that optimal tools are available to compare different implementations of these analyses. To facilitate the testing and validation of these multivariate approaches, we developed simplePHENOTYPES, an R package that simulates pleiotropy, partial pleiotropy, and spurious pleiotropy in a wide range of genetic architectures, including additive, dominance and epistatic models.ResultsWe illustrate simplePHENOTYPES’ ability to simulate thousands of phenotypes in less than one minute. We then provide a vignette illustrating how to simulate a set of correlated traits in simplePHENOTYPES. Finally, we demonstrate the use of results from simplePHENOTYPES in a standard GWAS software, as well as the numerical equivalence of simulated phenotypes from simplePHENOTYPES and other packages with similar capabilities.ConclusionssimplePHENOTYPES is a CRAN package that makes it possible to simulate multiple traits controlled by loci with varying degrees of pleiotropy. Its ability to interface with both commonly-used marker data formats and downstream quantitative genetics software and packages should facilitate a rigorous assessment of both existing and emerging statistical GWAS and GS approaches. simplePHENOTYPES is also available athttps://github.coin/sainuelbfernandes/siinplePHENOTYPES.
“Online” modulation of brain hemodynamics despite stereotyped running
Authors: Bergel Antoine , Tiran Elodie , Deffieux Thomas , Demené Charlie , Tanter Mickaël , Cohen Ivan 
Published: January 2020

AbstractTheta and gamma rhythms coordinate large cell assemblies during locomotion. Their spread across temporal and spatial scales makes them challenging to observe. Additionally, the metabolic cost of these oscillations and their contribution to neuroimaging signals remains elusive. To finely characterize neurovascular interactions in running rats, we monitored brain hemodynamics with functional ultrasound and hippocampal local field potentials in running rats. Theta rhythm and running speed were strongly coupled to brain hemodynamics in multiple structures, with delays ranging from 0.8 seconds to 1.8 seconds. Surprisingly, hemodynamics was also strongly modulated across trials within the same recording session: cortical hemodynamics sharply decreased after 5-10 runs, while hippocampal hemodynamics strongly and linearly potentiated, particularly in the CA regions. This effect occurred while running speed and theta activity remained constant, and was accompanied by increased power in hippocampal high-frequency oscillations (100-150 Hz). Our findings reveal distinct vascular subnetworks modulated across fast and slow timescales and suggest strong adaptation processes despite stereotyped behavior.
Recognition of cellular RNAs by the S9.6 antibody creates pervasive artefacts when imaging RNA:DNA hybrids
Authors: Smolka John A. , Sanz Lionel A. , Hartono Stella R. , Chédin Frédéric 
Published: January 2020

ABSTRACTThe contribution of RNA:DNA hybrid metabolism to cellular processes and disease states has become a prominent topic of study. The S9.6 antibody recognizes RNA:DNA hybrids with a subnanomolar affinity, making it a broadly used tool to detect and study RNA:DNA hybrids. However, S9.6 also binds double-stranded RNAin vitrowith significant affinity. Though frequently used in immunofluorescence microscopy, the possible reactivity of S9.6 with non-RNA:DNA hybrid substratesin situ, particularly RNA, has not been comprehensively addressed. Furthermore, S9.6 immunofluorescence microscopy has been methodologically variable and generated discordant imaging datasets. In this study, we find that the majority of the S9.6 immunofluorescence signal observed in fixed human cells arises from RNA, not RNA:DNA hybrids. S9.6 staining was quantitatively unchanged by pre-treatment with the human RNA:DNA hybrid-specific nuclease, RNase H1, despite experimental verificationin situthat S9.6 could recognize RNA:DNA hybrids and that RNase H1 was active. S9.6 staining was, however, significantly sensitive to pre-treatments with RNase T1, and in some cases RNase III, two ribonucleases that specifically degrade single-stranded and double-stranded RNA, respectively. In contrast, genome-wide maps obtained by high-throughput DNA sequencing after S9.6-mediated DNA:RNA Immunoprecipitation (DRIP) are RNase H1-sensitive and RNase T1- and RNase III-insensitive. Altogether, these data demonstrate that the S9.6 antibody, though capable of recognizing RNA:DNA hybridsin situandin vitro, suffers from a lack of specificity that precludes reliable imaging of RNA:DNA hybrids and renders associated imaging data inconclusive in the absence of controls for its promiscuous recognition of cellular RNAs.
CRISPR-mediated activation of biosynthetic gene clusters for bioactive molecule discovery in filamentous fungi
Authors: Roux Indra , Woodcraft Clara , Hu Jinyu , Wolters Rebecca , Gilchrist Cameron L.M. , Chooi Yit-Heng 
Published: January 2020

AbstractAccessing the full biosynthetic potential encoded in the genomes of fungi is limited by the low expression of most biosynthetic gene clusters (BGCs) under common laboratory culture conditions. CRISPR-mediated transcriptional activation (CRISPRa) of fungal BGC could accelerate genomics-driven bioactive secondary metabolite discovery. In this work, we established the first CRISPRa system for filamentous fungi. First, we constructed a CRISPR/dLbCas12a-VPR-based system and demonstrated the activation of a fluorescent reporter inAspergillus nidulans. Then, we targeted the native nonribosomal peptide synthetase-like (NRPS-like) genemicAin both chromosomal and episomal contexts, achieving increased production of the compound microperfuranone. Finally, multi-gene CRISPRa led to the discovery of themiccluster product as dehydromicroperfuranone. Additionally, we demonstrated the utility of the variant dLbCas12aD156R-VPR for CRISPRa at room temperature culture conditions. Different aspects that influence the efficiency of CRISPRa in fungi were investigated, providing a framework for the further development of fungal artificial transcription factors based on CRISPR/Cas.
Single-cell transcriptome analysis reveals cell-cell communication and thyrocyte diversity in the zebrafish thyroid gland
Authors: Gillotay Pierre , Shankar Meghna , Haerlingen Benoit , Eski Sema Elif , Pozo-Morales Macarena , Suñer Inés Garteizgogeascoa , Reinhardt Susanne , Kränkel Annekathrin , Bläsche Juliane , Petzold Andreas , Ninov Nikolay , Kesavan Gokul , Lange Christian , Brand Michael , Detours Vincent , Costagliola Sabine , Singh Sumeet Pal 
Published: January 2020

AbstractThe thyroid gland regulates growth and metabolism via production of thyroid hormone in follicles composed of thyrocytes. So far, thyrocytes have been assumed to be a homogenous population. To uncover genetic heterogeneity in the thyrocyte population, and molecularly characterize the non-thyrocyte cells surrounding the follicle, we developed a single-cell transcriptome atlas of the zebrafish thyroid gland. The 6249-cell atlas includes profiles of thyrocytes, blood vessels, lymphatic vessels, immune cells and fibroblasts. Further, the thyrocytes could be split into two sub-populations with unique transcriptional signature, including differential expression of the transcription factorpax2a. To validate thyrocyte heterogeneity, we generated a CRISPR/Cas9-basedpax2aknock-in line, which demonstrated specificpax2aexpression in the thyrocytes. However, a population ofpax2a-low mature thyrocytes interspersed within individual follicles could be distinguished, corroborating heterogeneity within the thyrocyte population. Our results identify and validate transcriptional differences within the nominally homogenous thyrocyte population.One-line summarySingle-cell analysis uncovers latent heterogeneity in thyroid follicular cells.Graphical Abstract
Systems level profiling of arginine starvation reveals MYC and ERK adaptive metabolic reprogramming
Authors: Brashears Caitlyn B. , Rathore Richa , Schultze Matthew , Ehrhardt William R. , Tzeng Shin-Chen , Van Tine Brian A. , Held Jason M. 
Published: January 2020

AbstractArginine auxotrophy due to the silencing of argininosuccinate synthetase 1 (ASS1) occurs in many cancers, especially sarcomas. Arginine deiminase (ADI-PEG20) therapy exploits this metabolic vulnerability by depleting extracellular arginine, causing arginine starvation. ASS1-negative cells develop resistance to ADI-PEG20 through a metabolic adaptation that includes re-expressing ASS1. As arginine-based multiagent therapies are being developed, further characterization of the changes induced by arginine starvation is needed. In order to develop a systems-level understanding of these changes, activity-based proteomic profiling (ABPP) and phosphoproteomic profiling were performed before and after ADI-PEG20 treatment in ADI-PEG20-sensitive and resistant sarcoma cells. When integrated with previous metabolomic profiling (Kremeret al, 2017a), this multi-omic analysis reveals that cellular response to arginine starvation is mediated by adaptive ERK signaling, driving a Myc-Max transcriptional network. Concomitantly, these data elucidate proteomic changes that facilitate oxaloacetate production by enhancing glutamine and pyruvate anaplerosis, and altering lipid metabolism to recycle citrate for oxidative glutaminolysis. Based on the complexity of metabolic and cellular signaling interactions, these multi-omic approaches could provide valuable tools for evaluating response to metabolically targeted therapies.
Disease mutation study identifies essential residues for phosphatidylserine flippase ATP11A
Authors: Sun Kuanxiang , Tian Wanli , Liu Wenjing , Yang Yeming , Zhu Xianjun 
Published: January 2020

AbstractPS flippase (P4-ATPase) transports PS from the outer to the inner leaflet of the lipid bilayer in the membrane to maintain PS asymmetry, which is important for biological activity of the cell. ATP11A is expressed in multiple tissues and plays a role in myotube formation. However, detailed cellular function of ATP11A remains elusive. Mutation analysis revealed that I91, L308 and E897 residues in ATP8A2 are important for flippase activity. In order to investigate the roles of these corresponding amino acid residues in ATP11A, we assessed the expression and flippase activity of the respective ATP11A mutant proteins. ATP11A mainly localizes to the Golgi when co-expressed with TMEM30A, the β-subunit of the complex. Y300F and D913K mutations affect correct Golgi localization and PS stimulated flippase activity. In addition, Y300F mutation causes reduced ATP11A expression. Our data provides insight into essential residues for expression and flippase activity of ATP11A.
Function and evolution of B-Raf loop dynamics relevant to cancer recurrence under drug inhibition
Authors: Babbitt Gregory A. , Lynch Miranda L. , McCoy Matthew , Fokoue Ernest P. , Hudson André O. 
Published: January 2020

AbstractOncogenic mutations in the kinase domain of the B-Raf protein have long been associated with cancers involving the MAPK pathway. One constitutive MAPK activating mutation in B-Raf, the V600E (valine to glutamate) replacement occurring adjacent to a site of threonine phosphorylation (T599) occurs in many types of cancer, and in a large percentage of certain cancers, such as melanoma. Because ATP binding activity and the V600E mutation are both known to alter the physical behavior of the activation loop in the B-Raf ATP binding domain, this system is especially amenable to comparative analyses of molecular dynamics simulations modeling various genetic and drug class variants. Here, we employ machine learning enabled identification of functionally conserved protein dynamics to compare how the binding interactions of four B-Raf inhibitors impact the functional loop dynamics controlling ATP activation. We demonstrate that drug development targeting B-Raf has progressively moved towards ATP competitive inhibitors that demonstrate less tendency to mimic the functionally conserved dynamic changes associated with ATP activation and leading to the side effect of hyperactivation (i.e. inducing MAPK activation in non-tumorous cells in the absence of secondary mutation). We compare the functional dynamic impacts of V600E and other sensitizing and drug resistance causing mutations in the regulatory loops of B-Raf, confirming sites of low mutational tolerance in these regions. Lastly, we investigate V600E sensitivity of B-Raf loop dynamics in an evolutionary context, demonstrating that while sensitivity has an ancient origin with primitive eukaryotes, it was also secondarily increased during early jawed vertebrate evolution.
A unifying model for the propagation of prion proteins in yeast brings insight into the [PSI+] prion
Authors: Paul Lemarre , Suzanne Sindi S. , Laurent Pujo-Menjouet 
Published: January 2020

AbstractThe use of yeast systems to study the propagation of prions and amyloids has emerged as a crucial aspect of the global endeavor to understand those mechanisms. Yeast prion systems are intrinsically multi-scale: the molecular chemical processes are indeed coupled to the cellular processes of cell growth and division to influence phenotypical traits, observable at the scale of colonies. We introduce a novel modeling framework to tackle this difficulty using impulsive differential equations. We apply this approach to the [PSI+] yeast prion, which associated with the misconformation and aggregation of Sup35. We build a model that reproduces and unifies previously conflicting experimental observations on [PSI+] and thus sheds light onto characteristics of the intracellular molecular processes driving aggregate replication. In particular our model uncovers a kinetic barrier for aggregate replication at low densities, meaning the change between prion or prion-free phenotype is a bi-stable transition. This result is based on the study of prion curing experiments, as well as the phenomenon of colony sectoring, a phenotype which is often ignored in experimental assays and has never been modeled. Furthermore, our results provide further insight into the effect of guanidine hydrochloride (GdnHCl) on Sup35 aggregates. To qualitatively reproduce the GdnHCl curing experiment, aggregate replication must not be completely inhibited, which suggests the existence of a mechanism different than Hsp104-mediated fragmentation. Those results are promising for further development of the [PSI+] model, but also for extending the use of this novel framework to other yeast prion or amyloid systems.Author summaryIn the study of yeast prions, mathematical modeling is a powerful tool, in particular when it comes to facing the difficulties of multi-scale systems. In this study, we introduce a mathematical framework for investigating this problem in a unifying way. We focus on the yeast prion [PSI+] and present a simple molecular scheme for prion replication and a model of yeast budding. In order to qualitatively reproduce experiments, we need to introduce a non-linear mechanism in the molecular rates. This transforms the intracellular system into a bi-stable switch and allows for curing to occur, which is a crucial phenomenon for the study of yeast prions. To the best of our knowledge, no model in the literature includes such a mechanism, at least not explicitly. We also describe the GdnHCl curing experiment, and the propagon counting procedure. Reproducing this result requires challenging hypotheses that are commonly accepted, and our interpretation gives a new perspective on the concept of propagon. This study may be considered as a good example of how mathematical modeling can bring valuable insight into biological concepts and observations.
Influence of the ecological opportunity of interaction on the structure of host-parasite networks
Authors: D’Bastiani Elvira , Campião Karla Magalhães , Boeger Walter Antonio , Araújo Sabrina Borges Lino 
Published: January 2020

AbstractDespite the great interest to quantify the structure of ecological networks, the influence of morphological, ecological and evolutionary characteristics of the species still remains poorly understood. One of the challenging issues in ecology is how the interaction opportunity influences and provides changes to the associations between species, and which effects these changes have on ecological systems. To explore topological patterns in host-parasite networks, we sampled endoparasites-anurans interactions in South America in order to determine whether the effect of the ecological opportunity affects our understanding of the topological structure of the interaction networks. To identify the effect of the ecological opportunity for interaction, we investigated interactions in environments with and without flood pulse, where presence would promote higher ecological opportunity of interaction. Moreover, we created three theoretical models with filters to test the influence of the ecological opportunity for interaction: random, phylogeny and host body size. We then calculated commonly used binary network metrics (connectance, nestedness and modularity) for the networks generated by the theoretical models. We demonstrated that the interaction ecological opportunity changes the structure of host-parasite networks, and was influenced mainly by phylogeny and body size of the host. Our results indicate that environments that offer greater opportunities for interaction between species present networks with the most connectance/nestedness and less modularity. Networks in environments that do not have such opportunities for interaction depict the opposite pattern. Our results indicate that the ecological opportunity of interaction is reflected in an increase in interaction associations between species and affect/change the organization of these interactive assemblages. From an epidemiological point of view, changes in the composition of parasitic species are associated with risks of invasions and emerging diseases. In part, emerging diseases are the result of processes such as those occurring during the flood pulse, in which climate change, travel, and global trade create opportunities for new species associations. Our results provide insight into the dynamics of incorporating a new resource, considering an evolutionary factor responsible for these changes in species composition.