bluuebunny/crossref_metadata_2025_split huggingface dataset:
Angiotensin-(1–7) decreases the expression of collagen I via TGF-β1/Smad2/3 and subsequently inhibits fibroblast–myofibroblast transition
Authors: Zhou Jian Ping , Tang Wei , Feng Yun , Li Ning , Gu Chen Juan , Li Qing Yun , Wan Huan Ying 
Published: August 2016

Previous studies have shown that the RAS (renin–angiotensin system) might participate in airway remodelling in asthma. As a main component of the RAS, Ang-(1–7) [angiotensin-(1–7)] has been reported in few studies regarding its protective effect on asthma. However, the functional roles and relevant signalling pathways of Ang-(1–7) have not been well illustrated. In the present study, we analysed the effect of Ang-(1–7) on AngII (angiotensin II)-induced HLF (human lung fibroblast)–MF (myofibroblast) transition by detecting Col-I (collagen type I), TGF-β1 (transforming growth factor-β1) and α-SMA (α-smooth muscle actin) expression. We explored further the possible signalling pathways involved in HLF–MF transition. Our results showed that Ang-(1–7) could down-regulate the expression of Col-I, α-SMA and TGF-β1/Smad2/3 (all P&lt;0.05). A significant decrease was found in phosphorylation of PI3K (phosphoinositide 3-kinase), Akt, p38-MAPK (mitogen-activated protein kinase) and JNK (c-Jun N-terminal kinase) signalling pathways during HLF–MF transition (all P&lt;0.05). Our data suggests that Ang-(1–7) decreases the expression of Col-I via TGF-β1/Smad2/3 and subsequently inhibits HLF–MF transition.
Prevalence, Awareness, Treatment, and Control of Hypertension in the Southern Cone of Latin America
Authors: Rubinstein Adolfo L. , Irazola Vilma E. , Calandrelli Matias , Chen Chung-Shiuan , Gutierrez Laura , Lanas Fernando , Manfredi Jose A. , Mores Nora , Poggio Rosana , Ponzo Jacqueline , Seron Pamela , Bazzano Lydia A. , He Jiang 
Published: August 2016

BACKGROUND
Hypertension is the leading global preventable risk factor for premature death. While hypertension prevalence has been declining in high-income countries, it has increased continuously in low- and middle-income countries.

METHODS
We conducted a cross-sectional survey in 7,524 women and men aged 35–74 years from randomly selected samples in 4 cities (Bariloche and Marcos Paz, Argentina; Temuco, Chile; and Pando-Barros Blancos, Uruguay) in 2010–2011. Three blood pressure (BP) measurements were obtained by trained observers using a standard mercury sphygmomanometer. Hypertension was defined as a mean systolic BP ≥140mm Hg and/or diastolic BP ≥90mm Hg and/or use of antihypertensive medications.

RESULTS
An estimated 42.5% of the study population (46.6% of men and 38.7% of women) had hypertension and an estimated 32.5% (36.0% of men and 29.4% of women) had prehypertension. Approximately 63.0% of adults with hypertension (52.5% of men and 74.3% of women) were aware of their disease condition, 48.7% (36.1% of men and 62.1% of women) were taking prescribed medications to lower their BP, and only 21.1% of all hypertensive patients (13.8% of men and 28.9% of women) and 43.3% of treated hypertensive patients (38.1% of men and 46.5% of women) achieved BP control.

CONCLUSIONS
This study indicates that the prevalence of hypertension is high while awareness, treatment, and control are low in the general population in the Southern Cone of Latin America. These data call for bold actions at regional and national levels to implement effective, practical, and sustainable intervention programs aimed to improve hypertension prevention, detection, and control.
STAMS: STRING-assisted module search for genome wide association studies and application to autism
Authors: Hillenmeyer Sara , Davis Lea K. , Gamazon Eric R. , Cook Edwin H. , Cox Nancy J. , Altman Russ B. 
Published: August 2016

Motivation: Analyzing genome wide association data in the context of biological pathways helps us understand how genetic variation influences phenotype and increases power to find associations. However, the utility of pathway-based analysis tools is hampered by undercuration and reliance on a distribution of signal across all of the genes in a pathway. Methods that combine genome wide association results with genetic networks to infer the key phenotype-modulating subnetworks combat these issues, but have primarily been limited to network definitions with yes/no labels for gene-gene interactions. A recent method (EW_dmGWAS) incorporates a biological network with weighted edge probability by requiring a secondary phenotype-specific expression dataset. In this article, we combine an algorithm for weighted-edge module searching and a probabilistic interaction network in order to develop a method, STAMS, for recovering modules of genes with strong associations to the phenotype and probable biologic coherence. Our method builds on EW_dmGWAS but does not require a secondary expression dataset and performs better in six test cases.
Results: We show that our algorithm improves over EW_dmGWAS and standard gene-based analysis by measuring precision and recall of each method on separately identified associations. In the Wellcome Trust Rheumatoid Arthritis study, STAMS-identified modules were more enriched for separately identified associations than EW_dmGWAS (STAMS P-value 3.0 × 10−4; EW_dmGWAS- P-value = 0.8). We demonstrate that the area under the Precision-Recall curve is 5.9 times higher with STAMS than EW_dmGWAS run on the Wellcome Trust Type 1 Diabetes data.
Availability and Implementation: STAMS is implemented as an R package and is freely available at https://simtk.org/projects/stams.
Contact: rbaltman@stanford.edu
Supplementary information: Supplementary data are available at Bioinformatics online.
DEsubs: an R package for flexible identification of differentially expressed subpathways using RNA-seq experiments
Authors: Vrahatis Aristidis G. , Balomenos Panos , Tsakalidis Athanasios K. , Bezerianos Anastasios 
Published: August 2016

Summary: DEsubs is a network-based systems biology R package that extracts disease-perturbed subpathways within a pathway network as recorded by RNA-seq experiments. It contains an extensive and customized framework with a broad range of operation modes at all stages of the subpathway analysis, enabling so a case-specific approach. The operation modes include pathway network construction and processing, subpathway extraction, visualization and enrichment analysis with regard to various biological and pharmacological features. Its capabilities render DEsubs a tool-guide for both the modeler and experimentalist for the identification of more robust systems-level drug targets and biomarkers for complex diseases.
Availability and Implementation: DEsubs is implemented as an R package following Bioconductor guidelines: http://bioconductor.org/packages/DEsubs/.
Contact: tassos.bezerianos@nus.edu.sg
Supplementary information: Supplementary data are available at Bioinformatics online.
Switching to Raltegravir From a Virologically Effective Boosted Protease Inhibitor Regimen: A Comparative Effectiveness Analysis From the French Hospital Database on HIV (FHDH-ANRS CO4)
Authors: Potard Valérie , Simon Anne , Lacombe Jean-Marc , Parienti Jean-Jacques , Costagliola Dominique 
Published: August 2016

Abstract
Background.  In individuals with viral load (VL) suppression on a boosted protease inhibitor (PI) regimen, a switch to raltegravir (RAL) can be an option in case of comorbidities, but the SWITCHMRK trials challenged this strategy. Here, among individuals with VL suppression on a boosted PI, we compared outcomes between those who continued on the same regimen and those who switched to RAL.
Methods.  In this cohort study from the French Hospital Database on HIV, each individual who switched to RAL was matched with up to 3 individuals who continued PI, were being followed up during the calendar period of the switch, and had the same duration of VL suppression (both ±6 months). The primary endpoint was a composite endpoint of hospitalization, or AIDS event or death, and secondary endpoints the immunovirologic responses. To control for measured confounders, the inverse probability treatment weighting (IPTW) method was applied to estimate hazards ratios between the 2 groups.
Results.  We matched 282 RAL switchers with 838 nonswitchers. Although several variables differed significantly between the groups, including a higher prevalence of comorbidities in the RAL group, the IPTW method yielded standardized differences &lt;10% for all variables. After IPTW, there was no difference in the risk of hospitalization or AIDS event or death between the 2 groups (13.6% and 10.5%, respectively; hazard ratio, 1.16 [95% confidence interval, .74–1.83]) and no difference in the likelihood of virologic failure or CD4 cell gain.
Conclusions.  In individuals with controlled VL on a boosted PI regimen who switched to RAL, none of the endpoints differed with nonswitchers after IPTW.
Cell cycle arrest caused by MEK/ERK signaling is a mechanism for suppressing growth of antigen-hyperstimulated effector T cells
Authors: Ohtsuka Shizuka , Ogawa Shuhei , Wakamatsu Ei , Abe Ryo 
Published: August 2016

AbstractSuppression of T-cell growth is an important mechanism for establishment of self-tolerance and prevention of unwanted prolonged immune responses that may cause tissue damage. Although negative selection of potentially self-reactive T cells in the thymus as well as in peripheral tissues has been extensively investigated and well documented, regulatory mechanisms to dampen proliferation of antigen-specific effector T cells in response to antigen stimulation remain largely unknown. Thus, in this work, we focus on the identification of growth suppression mechanisms of antigen-specific effector T cells. In order to address this issue, we investigated the cellular and molecular events in growth suppression of an ovalbumin (OVA)-specific T-cell clone after stimulation with a wide range of OVA-peptide concentrations. We observed that while an optimal dose of peptide leads to cell cycle progression and proliferation, higher doses of peptide reduced cell growth, a phenomenon that was previously termed high-dose suppression. Our analysis of this phenomenon indicated that high-dose suppression is a consequence of cell cycle arrest, but not Fas–Fas ligand-dependent apoptosis or T-cell anergy, and that this growth arrest occurs in S phase, accompanied by reduced expression of CDK2 and cyclin A. Importantly, inhibition of MEK/ERK activation eliminated this growth suppression and cell cycle arrest, while it reduced the proliferative response to optimal antigenic stimulation. These results suggest that cell cycle arrest is the major mechanism regulating antigen-specific effector T-cell expansion, and that the MEK/ERK signaling pathway has both positive and negative effects, depending on the strength of antigenic stimulation.
The intrinsic line width of the Fe K α line of AGN
Authors: Liu Jiren 
Published: August 2016

Abstract
X-ray fluorescent lines are unique features of the reflection spectrum of the cold torus when irradiated by the central AGN. Their intrinsic line widths can be used to probe the line-emitting region. The line widths of the Fe K α line measured from the first-order Chandra High Energy Grating (HEG) spectra are 3–5 times larger than those measured with the Si K α line for Circinus, Mrk 3, and NGC 1068. Because the observed Si K α and Fe K α lines are not necessarily coming from the same physical region, it is uncertain whether the line widths of the Fe K α line are overestimated or not. We measured the intrinsic line widths of the Fe K α line of several nearby bright AGN using the second- and third-order Chandra HEG spectra, whose spectral resolutions are better than the first-order data. We found the measured widths are all smaller than those from the first-order data. The results clearly show that the widths of the Fe K α line measured from the first-order HEG data are overestimated. It indicates that the Fe K α lines of the studied sources are originating from regions around the cold dusty torus.
The problematic growth of dust in high-redshift galaxies
Authors: Ferrara A. , Viti S. , Ceccarelli C. 
Published: August 2016

Abstract
Dust growth via accretion of gas species has been proposed as the dominant process to increase the amount of dust in galaxies. We show here that this hypothesis encounters severe difficulties that make it unfit to explain the observed UV and IR properties of such systems, particularly at high redshifts. Dust growth in the diffuse ISM phases is hampered by (a) too slow accretion rates, (b) too high dust temperatures, and (c) the Coulomb barrier that effectively blocks accretion. In molecular clouds these problems are largely alleviated. Grains are cold (but not colder than the CMB temperature, TCMB ≈ 20 K at redshift z = 6). However, in dense environments accreted materials form icy water mantles, perhaps with impurities. Mantles are immediately (≲1 yr) photo-desorbed as grains return to the diffuse ISM at the end of the cloud lifetime, thus erasing any memory of the growth. We conclude that dust attenuating stellar light at high-z must be ready-made stardust largely produced in supernova ejecta.
SXDF-ALMA 2 arcmin2 deep survey: Resolving and characterizing the infrared extragalactic background light down to 0.5 mJy
Authors: Yamaguchi Yuki , Tamura Yoichi , Kohno Kotaro , Aretxaga Itziar , Dunlop James S. , Hatsukade Bunyo , Hughes David , Ikarashi Soh , Ishii Shun , Ivison Rob J. , Izumi Takuma , Kawabe Ryohei , Kodama Tadayuki , Lee Minju , Makiya Ryu , Matsuda Yuichi , Nakanishi Kouichiro , Ohta Kouji , Rujopakarn Wiphu , Tadaki Ken-ichi , Umehata Hideki , Wang Wei-Hao , Wilson Grant W. , Yabe Kiyoto , Yun Min S. 
Published: August 2016

Abstract
We present a multiwavelength analysis of five submillimeter sources (S1.1mm = 0.54–2.02 mJy) that were detected during our 1.1 mm deep continuum survey in the Subaru/XMM-Newton Deep Survey Field (SXDF)-UDS-CANDELS field (2 arcmin2, 1σ = 0.055 mJy beam−1) using the Atacama Large Millimeter/submillimeter Array (ALMA). The two brightest sources correspond to a known single-dish (AzTEC) selected bright submillimeter galaxy (SMG), whereas the remaining three are faint SMGs newly uncovered by ALMA. If we exclude the two brightest sources, the contribution of the ALMA-detected faint SMGs to the infrared extragalactic background light is estimated to be $\sim 4.1^{+5.4}_{-3.0}\:$Jy deg−2, which corresponds to $\sim 16^{+22}_{-12}\%$ of the infrared extragalactic background light. This suggests that their contribution to the infrared extragalactic background light is as large as that of bright SMGs. We identified multiwavelength counterparts of the five ALMA sources. One of the sources (SXDF-ALMA3) is extremely faint in the optical to near-infrared region despite its infrared luminosity ($L_\mathrm{IR}\simeq 1\times 10^{12}\,L_{\odot}$ or SFR ≃ 100 M⊙ yr−1). By fitting the spectral energy distributions at the optical-to-near-infrared wavelengths of the remaining four ALMA sources, we obtained the photometric redshifts (zphoto) and stellar masses (M*): zphoto ≃ 1.3–2.5, M* ≃ (3.5–9.5) × 1010 M⊙. We also derived their star formation rates (SFRs) and specific SFRs as ≃30–200 M⊙ yr−1 and ≃0.8–2 Gyr−1, respectively. These values imply that they are main sequence star-forming galaxies.
Altered Morphology and Immunohistochemical Characteristics in Metastatic Malignant Melanoma After Therapy With Vemurafenib
Authors: Powell Matthew R. , Sheehan Daniel J. , Kleven Daniel T. 
Published: August 2016

Abstract:
Metastatic melanoma is traditionally diagnosed using classic morphologic features in addition to immunohistochemical studies. The authors report a case of metastatic malignant melanoma where both morphology and immunohistochemistry were altered after treatment. This 51-year-old patient presented with metastatic melanoma to the brain and axilla. Initially, both metastases showed classic morphology and diffuse staining with the pan-melanoma antibody cocktail. This cocktail is a combination of 3 antibodies commonly used to diagnose melanocytic neoplasms: Melan-A (MART-1), tyrosinase, and HMB-45. In combination, the cocktail is highly sensitive for detecting melanocytic neoplasms and is commonly used to diagnose metastatic melanoma. Her tumor was positive for the BRAF 1799T>A (V600E) mutation, and she was treated with BRAF inhibitor therapy (vemurafenib). However, the axillary tumor recurred after treatment with vemurafenib. The recurrent tumor showed a markedly different morphology and complete loss of staining with the pan-melanoma antibody cocktail. This loss of staining accompanied by the change in morphology was an observation not previously documented after therapy with vemurafenib. This case demonstrates a potential pitfall in the diagnosis of metastatic or recurrent malignant melanoma.
Endodermal Cyst of the Third Nerve in a Child
Authors: Jiramongkolchai Kim , Bhatti Muhammed T. , Fuchs Herbert E. , Cummings Thomas E. , Jiramongkolchai Pawina , El-Dairi Mays A. 
Published: August 2016

Abstract:
Endodermal cysts, also known as neurogenic, neuroenteric, foregut, bronchogenic, respiratory, epithelial, teratomatous, or gastrocytoma cysts, can be found in the central nervous system, predominantly in the subarachnoid space of the cervical and thoracic spinal cord. We describe a child with an endodermal cyst of the third nerve and highlight neuroimaging findings, pathological correlation, clinical course, and patient management.
Reward-based training of recurrent neural networks for cognitive and value-based tasks
Authors: Song H. Francis , Yang Guangyu R. , Wang Xiao-Jing 
Published: August 2016

AbstractTrained neural network models, which exhibit many features observed in neural recordings from behaving animals and whose activity and connectivity can be fully analyzed, may provide insights into neural mechanisms. In contrast to commonly used methods for supervised learning from graded error signals, however, animals learn from reward feedback on definite actions through reinforcement learning. Reward maximization is particularly relevant when the optimal behavior depends on an animal’s internal judgment of confidence or subjective preferences. Here, we describe reward-based training of recurrent neural networks in which a value network guides learning by using the selected actions and activity of the policy network to predict future reward. We show that such models capture both behavioral and electrophysiological findings from well-known experimental paradigms. Our results provide a unified framework for investigating diverse cognitive and value-based computations, including a role for value representation that is essential for learning, but not executing, a task.
Assembly of Radically Recoded E. coli Genome Segments
Authors: Norville Julie E. , Gardner Cameron L. , Aponte Eduardo , Camplisson Conor K. , Gonzales Alexandra , Barclay David K. , Turner Katerina A. , Longe Victoria , Mincheva Maria , Teramoto Jun , Tominaga Kento , Sugimoto Ryota , DiCarlo James E. , Guell Marc , Hysolli Eriona , Aach John , Gregg Christopher J. , Wanner Barry L. , Church George M. 
Published: August 2016

AbstractThe large potential of radically recoded organisms (RROs) in medicine and industry depends on improved technologies for efficient assembly and testing of recoded genomes for biosafety and functionality. Here we describe a next generation platform for conjugative assembly genome engineering, termed CAGE 2.0, that enables the scarless integration of large synthetically recoded E. coli segments at isogenic and adjacent genomic loci. A stable tdk dual selective marker is employed to facilitate cyclical assembly and removal of attachment sites used for targeted segment delivery by sitespecific recombination. Bypassing the need for vector transformation harnesses the multi Mb capacity of CAGE, while minimizing artifacts associated with RecA-mediated homologous recombination. Our method expands the genome engineering toolkit for radical modification across many organisms and recombinase-mediated cassette exchange (RMCE).
Direct determination of diploid genome sequences
Authors: Weisenfeld Neil I. , Kumar Vijay , Shah Preyas , Church Deanna M. , Jaffe David B. 
Published: August 2016

ABSTRACTDetermining the genome sequence of an organism is challenging, yet fundamental to understanding its biology. Over the past decade, thousands of human genomes have been sequenced, contributing deeply to biomedical research. In the vast majority of cases, these have been analyzed by aligning sequence reads to a single reference genome, biasing the resulting analyses and, in general, failing to capture sequences novel to a given genome.Somede novoassemblies have been constructed, free of reference bias, but nearly all were constructed by merging homologous loci into single ‘consensus’ sequences, generally absent from nature. These assemblies do not correctly represent the diploid biology of an individual. In exactly two cases, true diploidde novoassemblies have been made, at great expense. One was generated using Sanger sequencing and one using thousands of clone pools.Here we demonstrate a straightforward and low-cost method for creating true diploidde novoassemblies. We make a single library from ~1 ng of high molecular weight DNA, using the 10x Genomics microfluidic platform to partition the genome. We applied this technique to seven human samples, generating low-cost HiSeq X data, then assembled these using a new ‘pushbutton’ algorithm, Supernova. Each computation took two days on a single server. Each yielded contigs longer than 100 kb, phase blocks longer than 2.5 Mb, and scaffolds longer than 15 Mb. Our method provides a scalable capability for determining the actual diploid genome sequence in a sample, opening the door to new approaches in genomic biology and medicine.
Deep Learning and Association Rule Mining for Predicting Drug Response in Cancer. A Personalised Medicine Approach
Authors: Vougas Konstantinos , Krochmal Magdalena , Jackson Thomas , Polyzos Alexander , Aggelopoulos Archimides , Pateras Ioannis S. , Liontos Michael , Varvarigou Anastasia , Johnson Elizabeth O. , Georgoulias Vassilis , Vlahou Antonia , Townsend Paul , Thanos Dimitris , Bartek Jiri , Gorgoulis Vassilis G. 
Published: August 2016

ABSTRACTA major challenge in cancer treatment is predicting the clinical response to anti-cancer drugs for each individual patient. For complex diseases such as cancer, characterized by high inter-patient variance, the implementation of precision medicine approaches is dependent upon understanding the pathological processes at the molecular level. While the “omics” era provides unique opportunities to dissect the molecular features of diseases, the ability to utilize it in targeted therapeutic efforts is hindered by both the massive size and diverse nature of the “omics” data. Recent advances with Deep Learning Neural Networks (DLNNs), suggests that DLNN could be trained on large data sets to efficiently predict therapeutic responses in cancer treatment. We present the application of Association Rule Mining combined with DLNNs for the analysis of high-throughput molecular profiles of 1001 cancer cell lines, in order to extract cancer-specific signatures in the form of easily interpretable rules and use these rules as input to predict pharmacological responses to a large number of anti-cancer drugs. The proposed algorithm outperformed Random Forests (RF) and Bayesian Multitask Multiple Kernel Learning (BMMKL) classification which currently represent the state-of-the-art in drug-response prediction. Moreover, thein silicopipeline presented, introduces a novel strategy for identifying potential therapeutic targets, as well as possible drug combinations with high therapeutic potential. For the first time, we demonstrate that DLNNs trained on a large pharmacogenomics data-set can effectively predict the therapeutic response of specific drugs in different cancer types. These findings serve as a proof of concept for the application of DLNNs to predict therapeutic responsiveness, a milestone in precision medicine.