bluuebunny/crossref_metadata_2025_split huggingface dataset:
Computed Tomography for 4-Dimensional Angiography and Perfusion Imaging of the Prostate for Embolization Planning of Benign Prostatic Hyperplasia
Authors: Kobe Adrian , Puippe Gilbert , Klotz Ernst , Alkadhi Hatem , Pfammatter Thomas 
Published: June 2019

Objectives
The aim of this study was to evaluate the feasibility of a computed tomography (CT) protocol enabling the visualization of the prostatic artery (PA) before prostatic artery embolization (PAE) in benign prostatic hyperplasia, which provides quantitative perfusion information of the prostate gland.

Materials and Methods
In this institutional review board–approved study, 22 consecutive patients (mean age, 67 ± 7 years) who were planned to undergo PAE underwent a dynamic CT scan of the pelvis (scan range, 22.4 cm; cycle time, 1.5 seconds; scan time, 44 seconds; 25 scan cycles; 70 kVp; 100 mAs) after the administration of 70 mL of iodinated contrast media (flow rate, 6 mL/s; 10 seconds' delay). Image postprocessing consisted of a spatiotemporal, frequency-depending multiband filtering technique with noise reduction, motion correction, resulting in (1) time-resolved, temporal maximum intensity projection (MIP) images from fusion of multiple arterial time points; (2) 4-dimensional (4D) CT angiography images after bone and calcium plaque removal; and (3) parametric perfusion maps of the prostate. Intraprocedural cone-beam CT was performed with a microcatheter in the PA. In both modalities, the contrast-to-noise ratio of the right internal iliac artery or the PA was calculated, respectively. Visibility of the PA was scored using a Likert scale (score 1 = not seen, to score 4 = intraprostatic PA branches seen). Quantitative perfusion analysis of the dynamic pelvic CT included calculation of the blood flow, blood volume, mean transit time, and flow extraction product.

Results
The average volume CT dose index and dose length product of CT was 35.7 ± 6.8 mGy and 737.4 ± 146.3 mGy·cm, respectively. Contrast-to-noise ratio of the pelvic vessels on temporal MIP images and cone-beam CT were 45 ± 19 and 69 ± 27, respectively (P < 0.01). The mean visibility score of the PA was 3.6 ± 0.6 for 4D-CT angiography and 3.97 ± 0.2 for cone-beam CT (P < 0.001). The PA was visualized in 100% of 4D-CT angiography examinations, with one PA being visible only proximally. Prostate CT perfusion analysis showed blood flow, blood volume, mean transit time, and flow extraction product values of 27.9 ± 12.5 mL/100 mL/min, 2.0 ± 0.8 mL/100 mL, 4.5 ± 0.5 second, and 12.6 ± 5.4 mL/100 mL/min, respectively, for the whole prostate gland. About half the patients showed a pronounced difference between the lobes.

Conclusions
We introduced a CT protocol for PAE planning providing excellent visualization of the PA on temporal MIP images and 4D-CT angiography at a reasonable dose and low contrast volume. In addition, quantitative perfusion information is available, which might be useful for outcome prediction after embolization.
Derivation of oligodendrocyte precursor cells from human bone marrow stromal cells and use for re-myelination in the congenitally dysmyelinated brain
Authors: Lam Guy , Shea Graham Ka-Hon , Wu Lap Kei , Sui Maximillian Li Tak , Hei Kwok Chun , Kuen Zora Chan Chui , Cheuk Yin Yvonne Wong , Tsui Alex Yat Ping , Shum Daisy Kwok Yan , Chan Ying Shing 
Published: June 2019

ABSTRACT/ SUMMARYOligodendrocytes (OLs) are the only myelinating glia in the central nervous system (CNS). In congenital myelin disorders, OL dysfunction or death results in loss of myelin. This causes progressive and irreversible impairment to motor and cognitive functions, and is amongst the most disabling neurological disorder.Neonatal engraftment by glial progenitor cells (GPCs) allows the robust myelination of congenitally dysmyelinated brain, thereby preserving brain function and quality of life of patients. However, endogenous sources of glial progenitors are hard to obtain without causing secondary injury, while use of exogenous sources such as embryonic stem cells and induced-pluripotent stem cells face considerable ethical and safety issues.To circumvent such hurdles, we asked whether NG2+cells in the bone marrow could be a potential cell source for GPCs. We successfully generated glial progenitor cells (GPCs) from human bone marrow stromal cells (hBMSCs) from 3 donors using a 14- day induction protocol. The generated hBMSC-GPCs were highly enriched in OPC marker expression, including OLIG2, PDGFRα, NG2, SOX10 and O4, and showed efficient differentiation into myelinogenic oligodendrocytes when transplanted into postnatal day 7 (P7) myelin-deficient shiverer mice. Remyelination of the shiverer mouse brain significantly extended lifespan and improved motor function.The novel induction protocol described here provides a method for fast, simple and effective glial therapy for myelin disorders, overcoming existent hurdles of cell source restriction and time frame requirement.Graphical AbstractHighlights- Human bone marrow stromal cells (BMSCs) can be programmed to myelinating glia (GPCs, glial progenitor cells), via a novel 14-dayin vitroinduction protocol- Transplantation of these hBM-GPCs robustly remyelinated myelin deficient shiverer mice.- hBM-GPC transplant significantly extended lifespan, increased body weight and improved motor function
Bayesian inference of power law distributions
Authors: Grigaityte Kristina , Atwal Gurinder 
Published: June 2019

AbstractObserved data from many research disciplines, ranging from cellular biology to economics, often follow a particular long-tailed distribution known as a power law. Despite the ubiquity of natural power laws, inferring the exact form of the distribution from sampled data remains challenging. The possible presence of multiple generative processes giving rise to an unknown weighted mixture of distinct power law distributions in a single dataset presents additional challenges. We present a probabilistic solution to these issues by developing a Bayesian inference approach, with Markov chain Monte Carlo sampling, to accurately estimate power law exponents, the number of mixtures, and their weights, for both discrete and continuous data. We determine an objective prior distribution that is invariant to reparameterization of parameters, and demonstrate its effectiveness to accurately infer exponents, even in the low sample limit. Finally, we provide a comprehensive and documented software package, written in Python, of our Bayesian inference methodology, freely available at https://github.com/AtwalLab/BayesPowerlaw.
MiR-9-5p protects from kidney fibrosis by metabolic reprogramming
Authors: Fierro-Fernández Marta , Miguel Verónica , Márquez-Expósito Laura , Nuevo-Tapioles Cristina , Herrero J. Ignacio , Blanco-Ruiz Eva , Tituaña Jessica , Castillo Carolina , Cannata Pablo , Monsalve María , Ruiz-Ortega Marta , Ramos Ricardo , Lamas Santiago 
Published: June 2019

AbstractMicroRNAs (miRNAs) regulate gene expression post-transcriptionally and control biological processes, including fibrogenesis. Kidney fibrosis remains a clinical challenge and miRNAs may represent a valid therapeutic avenue. We show that miR-9-5p protected from renal fibrosis in the mouse model of unilateral ureteral obstruction (UUO). This was reflected in reduced expression of pro-fibrotic markers, decreased number of infiltrating monocytes/macrophages and diminished tubular epithelial cell injury and transforming growth factor-beta 1 (TGF-β1)-dependent de-differentiation in human kidney proximal tubular (HKC-8) cells. RNA sequencing (RNA-Seq) studies in the UUO model revealed that this protection was mediated by a global shift in the expression profile of genes related to key metabolic pathways, including mitochondrial dysfunction, oxidative phosphorylation (OXPHOS), fatty acid oxidation (FAO) and glycolysis, preventing their UUO-dependent down-regulation. This effect was mirrored by a prevention in the TGF-β1-induced bioenergetics changes in HKC-8 cells. The expression of the FAO-related axis peroxisome proliferator-activated receptor gamma coactivator 1 alpha (PGC-1α)-peroxisome proliferator-activated receptor alpha (PPARα) was reduced by UUO, although preserved by the administration of miR-9-5p. We found that in mice null for the mitochondrial master regulator PGC-1α, miR-9-5p was unable to promote a protective effect in the UUO model. We propose that miR-9-5p elicits a protective response to chronic kidney injury and renal fibrosis by inducing reprogramming of the metabolic derangement and mitochondrial dysfunction affecting tubular epithelial cells.
Super-resolution imaging reveals the evolution of higher-order chromatin folding in early carcinogenesis
Authors: Xu Jianquan , Ma Hongqiang , Ma Hongbin , Jiang Wei , Duan Meihan , Zhao Shimei , Gao Chenxi , Hahm Eun-Ryeong , Lardo Santana M. , Troy Kris , Sun Ming , Pai Reet , Stolz Donna B , Singh Shivendra , Brand Randall E , Hartman Douglas J. , Hu Jing , Hainer Sarah J. , Liu Yang 
Published: June 2019

SUMMARYAberrant chromatin structure is a hallmark in cancer cells and has long been used for clinical diagnosis of cancer. However, underlying higher-order chromatin folding during malignant transformation remains elusive, due to the lack of molecular scale resolution. Using optimized stochastic optical reconstruction microscopy (STORM) for pathological tissue (PathSTORM), we uncovered a gradual decompaction and fragmented higher-order chromatin folding throughout all stages of carcinogenesis in multiple tumor types, even prior to the tumor formation. Our integrated imaging, genomic, and transcriptomic analyses reveal the functional consequences in enhanced formation of transcription factories, spatial juxtaposition with relaxed nanosized chromatin domains and impaired genomic stability. We also demonstrate the potential of imaging higher-order chromatin decompaction to detect high-risk precursors that cannot be distinguished by conventional pathology. Taken together, our findings reveal the gradual decompaction and fragmentation of higher-order chromatin structure as an enabling characteristic in early carcinogenesis to facilitate malignant transformation, which may improve cancer diagnosis, risk stratification, and prevention.SIGNIFICANCEGenomic DNA is folded into a higher-order structure that regulates transcription and maintains genomic stability. Although much progress has been made on understanding biochemical characteristics of epigenetic modifications in cancer, the higher-order folding of chromatin structure remains largely unknown. Using optimized super-resolution microscopy, we uncover de-compacted and fragmented chromatin folding in tumor initiation and stepwise progression in multiple tumor types, even prior to the presence of tumor cells. This study underlines the significance of unfolding higher-order chromatin structure as an enabling characteristic to promote tumorigenesis, which may facilitate the development and evaluation of new preventive strategies. The potential of imaging higher-order chromatin folding to improve cancer detection and risk stratification is demonstrated by detecting high-risk precursors that cannot be distinguished by conventional pathology.
Trevolver: simulating non-reversible DNA sequence evolution in trinucleotide context on a bifurcating tree
Authors: Nelson Chase W. , Fu Yunxin , Li Wen-Hsiung 
Published: June 2019

AbstractSummaryRecent de novo mutation data allow the estimation of non-reversible mutation rates for trinucleotide sequence contexts. However, existing tools for simulating DNA sequence evolution are limited to time-reversible models or do not consider trinucleotide context-dependent rates. As this ability is critical to testing evolutionary scenarios under neutrality, we created Trevolver. Sequence evolution is simulated on a bifurcating tree using a 64 × 4 trinucleotide mutation model. Runtime is fast and results match theoretical expectation for CpG sites. Simulations with Trevolver will enable neutral hypotheses to be tested at within-species (polymorphism), between-species (divergence), within-host (e.g., viral evolution), and somatic (e.g., cancer) levels of evolutionary change.Availability and ImplementationTrevolver is implemented in Perl and available on GitHub under GNU General Public License (GPL) version 3 at https://github.com/chasewnelson/trevolver.Contactcnelson@amnh.orgSupplementary informationFurther details and example data are available on GitHub.
Coping with Pleistocene climatic fluctuations: demographic responses in remote endemic reef fishes
Authors: Delrieu-Trottin Erwan , Hubert Nicolas , Giles Emily C. , Chifflet-Belle Pascaline , Suwalski Arnaud , Neglia Valentina , Rapu-Edmunds Cristian , Mona Stefano , Saenz-Agudelo Pablo 
Published: June 2019

AbstractElucidating demographic history during the settlement of ecological communities is crucial for properly inferring the mechanisms that shape patterns of species diversity and their persistence through time. Here, we used genomic data and coalescent-based approaches to elucidate for the first time the demographic dynamics associated with the settlement by endemic reef fish fauna of one of the most remote peripheral islands of the Pacific Ocean, Rapa Nui (Easter Island). We compared the demographic history of nine endemic species in order to explore their demographic responses to Pleistocene climatic fluctuations. We found that Rapa Nui endemic species share a common demographic history as signatures of population expansions were retrieved for almost all of the species studied here, and synchronous demographic expansions initiated during the last glacial period were recovered for more than half of the studied species. These results suggest that eustatic fluctuations associated with Milankovitch cycles have played a central role in species demographic histories and in the final stage of the community assembly of many Rapa Nui reef fishes. Specifically, sea level low stands resulted in the maximum reef habitat extension for Rapa Nui endemic species; we discuss the potential role of seamounts in allowing endemic species to cope with Pleistocene climatic fluctuations, and we highlight the importance of local historical processes over regional ones. Overall, our results shed light on the mechanisms by which endemism arises and is maintained in peripheral reef fish fauna.
Exhaustive identification of conserved upstream open reading frames with potential translational regulatory functions from animal genomes
Authors: Takahashi Hiro , Miyaki Shido , Onouchi Hitoshi , Motomura Taichiro , Idesako Nobuo , Takahashi Anna , Murase Masataka , Fukuyoshi Shuichi , Endo Toshinori , Satou Kenji , Naito Satoshi , Itoh Motoyuki 
Published: June 2019

AbstractUpstream open reading frames (uORFs) are present in the 5’-untranslated regions of many eukaryotic mRNAs, and some peptides encoded by these regions play important regulatory roles in controlling main ORF (mORF) translation. We previously developed a novel pipeline, ESUCA, to comprehensively identify plant uORFs encoding functional peptides, based on genome-wide identification of uORFs with conserved peptide sequences (CPuORFs). Here, we applied ESUCA to diverse animal genomes, because animal CPuORFs have been identified only by comparing uORF sequences between a limited number of species, and how many previously identified CPuORFs encode regulatory peptides is unclear. By using ESUCA, 1,517 (1,373 novel and 144 known) CPuORFs were extracted from four evolutionarily divergent animal genomes. We examined the effects of 17 human CPuORFs on mORF translation using transient expression assays. Through these analyses, we identified seven novel regulatory CPuORFs that repressed mORF translation in a sequence-dependent manner, including one conserved only among Eutheria. We discovered a much higher number of animal CPuORFs than previously identified. Since most human CPuORFs identified in this study are conserved across a wide range of Eutheria or a wider taxonomic range, many CPuORFs encoding regulatory peptides are expected to be found in the identified CPuORFs.
Generation of comprehensive ecosystems-specific reference databases with species-level resolution by high-throughput full-length 16S rRNA gene sequencing and automated taxonomy assignment (AutoTax)
Authors: Dueholm Morten Simonsen , Andersen Kasper Skytte , McIlroy Simon Jon , Kristensen Jannie Munk , Yashiro Erika , Karst Søren Michael , Albertsen Mads , Nielsen Per Halkjær 
Published: June 2019

AbstractHigh-throughput 16S rRNA gene amplicon sequencing is an essential method for studying the diversity and dynamics of microbial communities. However, this method is presently hampered by the lack of high-identity reference sequences for many environmental microbes in the public 16S rRNA gene reference databases, and by the absence of a systematic and comprehensive taxonomy for the uncultured majority. Here we demonstrate how high-throughput synthetic long-read sequencing can be applied to create ecosystem-specific full-length 16S rRNA gene amplicon sequence variant (FL-ASV) reference databases that include high-identity references (>98.7% identity) for nearly all abundant bacteria (>0.01% relative abundance) using Danish wastewater treatment systems and anaerobic digesters as an example. In addition, we introduce a novel sequence identity-based approach for automated taxonomy assignment (AutoTax) that provides a complete seven-rank taxonomy for all reference sequences, using the SILVA taxonomy as a backbone, with stable placeholder names for unclassified taxa. The FL-ASVs are perfectly suited for the evaluation of taxonomic resolution and bias associated with primers commonly used for amplicon sequencing, allowing researchers to choose those that are ideal for their ecosystem. The AutoTax taxonomy greatly improves the classification of short-read 16S rRNA gene amplicon sequence variants (ASVs) at the genus- and species-level, compared to the commonly used universal reference databases. Importantly, the placeholder names provide a way to explore the unclassified environmental taxa at different taxonomic ranks, which in combination within situanalyses can be used to uncover their ecological roles.
Working out Classic Examples of Metabolic Networks Structural Analysis with Wolfram Language
Authors: Liang Kuo Kan 
Published: June 2019

AbstractMetabolic reaction networks usually include a large number of enzymatic reaction steps. Nowadays, people desire to work on larger and larger metabolic networks, in the research fields of for example systems or synthetic biology. With the growing sizes of the metabolic networks considered, it is more and more tedious and cumbersome for a human to perform routine processing and analysis of the networks. Computer programs that automate metabolic analysis will be beneficial. In this work, the use of Wolfram Language to automate metabolic analysis is demonstrated. Although there are many different analyses to perform in a metabolic network analysis project, the analysis of metabolic network structure may be the most common first step and one of the most troublesome tasks. Therefore, instead of demonstrating a lot of different analyses, the structures of a few important examples from one chapter in the classic textbook by Professor Gregory Stephanopoulos are analyzed with a program written in Wolfram Language and the models are book-kept in JSON format.
Effects of temperature andpCO2on the respiration, biomineralization and photophysiology of the giant clamTridacna maxima
Authors: Brahmi Chloé , Chapron Leila , Le Moullac Gilles , Soyez Claude , Beliaeff Benoît , Lazareth Claire E. , Gaertner-Mazouni Nabila , Vidal-Dupiol Jeremie 
Published: June 2019

AbstractSuch as many other reef organisms, giant clams are today confronted to global change effects and can suffer mass bleaching or mortality events mainly related to abnormally high seawater temperatures. Despite its strong ecological and socio-economical importance, its responses to the two most alarming threats linked to global change (i.e., ocean warming and acidification) still need to be explored. We investigated physiological responses of 4-years-oldTridacna maximaspecimens to realistic levels of temperature and partial pressure of carbon dioxide (pCO2) (+1.5°C and +800μatm of CO2) predicted for 2100 in French Polynesian lagoons during the warmer season. During a 65-days crossed-factor experiment, individuals were exposed to two temperatures (29.2°C; 30.7°C) and twopCO2(430µatm; 1212µatm) conditions. Impact of each parameter and their potential synergetic effect were evaluated on respiration, biomineralization and photophysiology. Kinetics of thermal and acidification stress were evaluated by performing measurements at different times of exposure (29, 41, 53, 65 days). At 30.7°C, the holobiont O2production, symbiont photosynthetic yield, and density were negatively impacted. HighpCO2had a significant negative effect on shell growth rate, symbiont photosynthetic yield and density. Shell microstructural modifications were observed from 41 days in all temperature andpCO2conditions. No significant synergetic effect was found. Today thermal conditions (29.2°C) appeared to be sufficiently stressful to induce a host acclimatization process. All these observations indicate that temperature andpCO2are both forcing variables affectingT. maximaphysiology and jeopardize its survival under environmental conditions predicted for the end of this century.
Classification-based Inference of Dynamical Models of Gene Regulatory Networks
Authors: Fehr David A. , Manu  , Loh Yen Lee 
Published: June 2019

AbstractCell-fate decisions during development are controlled by densely interconnected gene regulatory networks (GRNs) consisting of many genes. Inferring and predictively modeling these GRNs is crucial for understanding development and other physiological processes. Gene circuits, coupled differential equations that represent gene product synthesis with a switch-like function, provide a biologically realistic framework for modeling the time evolution of gene expression. However, their use has been limited to smaller networks due to the computational expense of inferring model parameters from gene expression data using global non-linear optimization. Here we show that the switch-like nature of gene regulation can be exploited to break the gene circuit inference problem into two simpler optimization problems that are amenable to computationally efficient supervised learning techniques. We present FIGR (Fast Inference of Gene Regulation), a novel classification-based inference approach to determining gene circuit parameters. We demonstrate FIGR’s effectiveness on synthetic data as well as experimental data from the gap gene system ofDrosophila. FIGR is faster than global non-linear optimization by nearly three orders of magnitude and its computational complexity scales much better with GRN size. On a practical level, FIGR can accurately infer the biologically realistic gap gene network in under a minute on desktop-class hardware instead of requiring hours of parallel computing. We anticipate that FIGR would enable the inference of much larger biologically realistic GRNs than was possible before. FIGR Source code is freely available athttp://github.com/mlekkha/FIGR.