bluuebunny/crossref_metadata_2025_split huggingface dataset:
Interplay between superconductivity and itinerant magnetism in underdoped Ba1−xKxFe2As2 (x = 0.2) probed by the response to controlled point-like disorder
Authors: Prozorov Ruslan , Kończykowski Marcin , Tanatar Makariy A. , Wen Hai-Hu , Fernandes Rafael M. , Canfield Paul C. 
Published: July 2019

AbstractThe response of superconductors to controlled introduction of point-like disorder is an important tool to probe their microscopic electronic collective behavior. In the case of iron-based superconductors, magnetic fluctuations presumably play an important role in inducing high-temperature superconductivity. In some cases, these two seemingly incompatible orders coexist microscopically. Therefore, understanding how this unique coexistence state is affected by disorder can provide important information about the microscopic mechanisms involved. In one of the most studied pnictide family, hole-doped Ba1−xKxFe2As2 (BaK122), this coexistence occurs over a wide range of doping levels, 0.16 ≲ x ≲ 0.25. We used relativistic 2.5 MeV electrons to induce vacancy-interstitial (Frenkel) pairs that act as efficient point-like scattering centers. Upon increasing dose of irradiation, the superconducting transition temperature Tc decreases dramatically. In the absence of nodes in the order parameter this provides a strong support for a sign-changing s± pairing. Simultaneously, in the normal state, there is a strong violation of the Matthiessen’s rule and a decrease (surprisingly, at the same rate as Tc) of the magnetic transition temperature Tsm, which indicates the itinerant nature of the long-range magnetic order. Comparison of the hole-doped BaK122 with electron-doped Ba(FexCo1−x)2As2 (FeCo122) with similar Tsm ~ 110 K, x = 0.02, reveals significant differences in the normal states, with no apparent Matthiessen’s rule violation above Tsm on the electron-doped side. We interpret these results in terms of the distinct impact of impurity scattering on the competing itinerant antiferromagnetic and s± superconducting orders.
High-throughput analysis of the human thymic Vδ1+ T cell receptor repertoire
Authors: Di Lorenzo Biagio , Ravens Sarina , Silva-Santos Bruno 
Published: July 2019

Abstractγδ T cells are a relatively rare subset of lymphocytes in the human peripheral blood, but they play important roles at the interface between the innate and the adaptive immune systems. The γδ T cell lineage is characterized by a signature γδ T cell receptor (γδTCR) that displays extensive sequence variability originated by DNA rearrangement of the corresponding V(D)J loci. Human γδ T cells comprise Vγ9Vδ2 T cells, the major subset in the peripheral blood; and Vδ1+ T cells, the predominant subpopulation in the post-natal thymus and in peripheral tissues. While less studied, Vδ1+ T cells recently gathered significant attention due to their anti-cancer and anti-viral activities. In this study we applied next-generation sequencing (NGS) to analyse the γδTCR repertoire of highly (FACS-)purified Vδ1+ T cells from human thymic biopsies. Our analysis reveals unsuspected aspects of thymically rearranged and expressed (at the mRNA level) TRG and TRD genes, thus constituting a data resource that qualifies previous conclusions on the TCR repertoire of γδ T cells developing in the human thymus.
A DNA barcode reference library of French Polynesian shore fishes
Authors: Delrieu-Trottin Erwan , Williams Jeffrey T. , Pitassy Diane , Driskell Amy , Hubert Nicolas , Viviani Jérémie , Cribb Thomas H. , Espiau Benoit , Galzin René , Kulbicki Michel , Lison de Loma Thierry , Meyer Christopher , Mourier Johann , Mou-Tham Gérard , Parravicini Valeriano , Plantard Patrick , Sasal Pierre , Siu Gilles , Tolou Nathalie , Veuille Michel , Weigt Lee , Planes Serge 
Published: July 2019

AbstractThe emergence of DNA barcoding and metabarcoding opened new ways to study biological diversity, however, the completion of DNA barcode libraries is fundamental for such approaches to succeed. This dataset is a DNA barcode reference library (fragment of Cytochrome Oxydase I gene) for 2,190 specimens representing at least 540 species of shore fishes collected over 10 years at 154 sites across the four volcanic archipelagos of French Polynesia; the Austral, Gambier, Marquesas and Society Islands, a 5,000,000 km2 area. At present, 65% of the known shore fish species of these archipelagoes possess a DNA barcode associated with preserved, photographed, tissue sampled and cataloged specimens, and extensive collection locality data. This dataset represents one of the most comprehensive DNA barcoding efforts for a vertebrate fauna to date. Considering the challenges associated with the conservation of coral reef fishes and the difficulties of accurately identifying species using morphological characters, this publicly available library is expected to be helpful for both authorities and academics in various fields.
Bone growth as the main determinant of mouse digit tip regeneration after amputation
Authors: Sensiate L. A. , Marques-Souza H. 
Published: July 2019

AbstractRegeneration is classically demonstrated in mammals using mice digit tip. In this study, we compared different amputation plans and show that distally amputated digits regrow with morphology close to normal but fail to regrow the fat pad. Proximally amputated digits do not regrow the phalangeal bone, but the remaining structures (nail, skin and connective tissue), all with intrinsic regenerative capacity, re-establishing integrity indistinguishably in distally and proximally amputated digits. Thus, we suggest that the bone growth promoted by signals and progenitor cells not removed by distal amputations is responsible for the re-establishment of a drastically different final morphology after distal or proximal digit tip amputations. Despite challenging the use of mouse digit tip as a model system for limb regeneration in mammals, these findings evidence a main role of bone growth in digit tip regeneration and suggest that mechanisms that promote joint structures formation should be the main goal of regenerative medicine for limb and digit regrowth.
Fractionated mitochondrial magnetic separation for isolation of synaptic mitochondria from brain tissue
Authors: Hubbard W. Brad , Harwood Christopher L. , Prajapati Paresh , Springer Joe E. , Saatman Kathryn E. , Sullivan Patrick G. 
Published: July 2019

AbstractWhile mitochondria maintain essential cellular functions, such as energy production, calcium homeostasis, and regulating programmed cellular death, they also play a major role in pathophysiology of many neurological disorders. Furthermore, several neurodegenerative diseases are closely linked with synaptic damage and synaptic mitochondrial dysfunction. Unfortunately, the ability to assess mitochondrial dysfunction and the efficacy of mitochondrial-targeted therapies in experimental models of neurodegenerative disease and CNS injury is limited by current mitochondrial isolation techniques. Density gradient ultracentrifugation (UC) is currently the only technique that can separate synaptic and non-synaptic mitochondrial sub-populations, though small brain regions cannot be assayed due to low mitochondrial yield. To address this limitation, we used fractionated mitochondrial magnetic separation (FMMS), employing magnetic anti-Tom22 antibodies, to develop a novel strategy for isolation of functional synaptic and non-synaptic mitochondria from mouse cortex and hippocampus without the usage of UC. We compared the yield and functionality of mitochondria derived using FMMS to those derived by UC. FMMS produced 3x more synaptic mitochondrial protein yield compared to UC from the same amount of tissue, a mouse hippocampus. FMMS also has increased sensitivity, compared to UC separation, to measure decreased mitochondrial respiration, demonstrated in a paradigm of mild closed head injury. Taken together, FMMS enables improved brain-derived mitochondrial yield for mitochondrial assessments and better detection of mitochondrial impairment in CNS injury and neurodegenerative disease.
A repository of protein abundance data of drug metabolizing enzymes and transporters for applications in physiologically based pharmacokinetic (PBPK) modelling and simulation
Authors: Ladumor Mayur K. , Thakur Aarzoo , Sharma Sheena , Rachapally Aravind , Mishra Sarang , Bobe Priyanka , Rao V. Kameswara , Pammi Praneetha , Kangne Hari , Levi David , Balhara Ankit , Ghandikota Sriram , Joshi Anupama , Nautiyal Vivek , Prasad Bhagwat , Singh Saranjit 
Published: July 2019

AbstractPopulation factors such as age, gender, ethnicity, genotype and disease state can cause inter-individual variability in pharmacokinetic (PK) profile of drugs. Primarily, this variability arises from differences in abundance of drug metabolizing enzymes and transporters (DMET) among individuals and/or groups. Hence, availability of compiled data on abundance of DMET proteins in different populations can be useful for developing physiologically based pharmacokinetic (PBPK) models. The latter are routinely employed for prediction of PK profiles and drug interactions during drug development and in case of special populations, where clinical studies either are not feasible or have ethical concerns. Therefore, the main aim of this work was to develop a repository of literature-reported DMET abundance data in various human tissues, which included compilation of information on sample size, technique(s) involved, and the demographic factors. The collation of literature reported data revealed high inter-laboratory variability in abundance of DMET proteins. We carried out unbiased meta-analysis to obtain weighted mean and percent coefficient of variation (%CV) values. The obtained %CV values were then integrated into a PBPK model to highlight the variability in drug PK in healthy adults, taking lamotrigine as a model drug. The validated PBPK model was extrapolated to predict PK of lamotrigine in paediatric and hepatic impaired populations. This study thus exemplifies importance of the DMET protein abundance database, and use of determined values of weighted mean and %CV after meta-analysis in PBPK modelling for the prediction of PK of drugs in healthy and special populations.
Spatio-temporal temperature variations in MarkSim multimodel data and their impact on voltinism of fruit fly, Bactrocera species on mango
Authors: Choudhary Jaipal Singh , Mali Santosh S. , Mukherjee Debu , Kumari Anjali , Moanaro L. , Rao M. Srinivasa , Das Bikash , Singh A. K. , Bhatt B. P. 
Published: July 2019

AbstractFruit flies are the most serious economic insect pests of mango in India and other parts of the world. Under future climate change, shifts in temperature will be a key driver of ecosystem function especially in terms of insect pest dynamics. In this study, we predicted the voltinism of the three economically important fruit fly species viz.,Bactrocera dorsalis(Hendel),Bactrocera correcta(Bezzi) andBactrocera zonata(Saunders) of mango from 10 geographical locations in India using well established degree day approaches. Daily minimum and maximum temperature data were generated by using seven General Circulation Models (GCMs) along with their ensemble, in conjunction with the four representative concentration pathways (RCPs) scenarios (RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5) and three time periods (2020, 2050 and 2080) generated from MarkSim® DSSAT weather file generator. Historical data from 1969–2005 of these 10 locations were considered as baseline period. Under future predicted climates, model outputs indicates that all three fruit fly species will produce higher number of generations (1–2 additional generations) with 15–24% reduced generation time over the baseline period. The increased voltinism of fruit fly species due to increased temperature may lead to ≃5% higher infestation of mango fruits in India by the year 2050. Analysis of variance revealed that ‘geographical locations’ explained 77% of the total variation in voltinism followed by ‘time periods’ (11%). Such increase in the voltinism of fruit flies and the consequent increases in the infestation of mango fruits are likely to have significant negative impacts on mango protection and production.
Whole-genome re-sequencing association study for direct genetic effects and social genetic effects of six growth traits in Large White pigs
Authors: Wu Pingxian , Wang Kai , Yang Qiang , Zhou Jie , Chen Dejuan , Liu Yihui , Ma Jideng , Tang Qianzi , Jin Long , Xiao Weihang , Lou Pinger , Jiang Anan , Jiang Yanzhi , Zhu Li , Li Mingzhou , Li Xuewei , Tang Guoqing 
Published: July 2019

AbstractSocially affected traits are affected by direct genetic effects (DGE) and social genetic effects (SGE). DGE and SGE of an individual directly quantify the genetic influence of its own phenotypes and the phenotypes of other individuals, respectively. In the current study, a total of 3,276 Large White pigs from different pens were used, and each pen contained 10 piglets. DGE and SGE were estimated for six socially affected traits, and then a GWAS was conducted to identify SNPs associated with DGE and SGE. Based on the whole-genome re-sequencing, 40 Large White pigs were genotyped and 10,501,384 high quality SNPs were retained for single-locus and multi-locus GWAS. For single-locus GWAS, a total of 54 SNPs associated with DGE and 33 SNPs with SGE exceeded the threshold (P < 5.00E-07) were detected for six growth traits. Of these, 22 SNPs with pleiotropic effects were shared by DGE and SGE. For multi-locus GWAS, a total of 72 and 110 putative QTNs were detected for DGE and SGE, respectively. Of these, 5 SNPs with pleiotropic effects were shared by DGE and SGE. It is noteworthy that 2 SNPs (SSC8: 16438396 for DGE and SSC17: 9697454 for SGE) were detected in single-locus and multi-locus GWAS. Furthermore, 15 positional candidate genes shared by SGE and DGE were identified because of their roles in behaviour, health and disease. Identification of genetic variants and candidate genes for DGE and SGE for socially affected traits will provide a new insight to understand the genetic architecture of socially affected traits in pigs.
Vasopressin enhances human preemptive strike in both males and females
Authors: Kawada Atsushi , Nagasawa Miho , Murata Aiko , Mogi Kazutaka , Watanabe Katsumi , Kikusui Takefumi , Kameda Tatsuya 
Published: July 2019

AbstractThe neuropeptide arginine vasopressin (AVP), which is known to modulate a wide range of social behaviors in animals, has been identified as a modulator of various negative responses to social stimuli in humans. However, behavioral evidence directly supporting its involvement in human defensive aggression has been rare. We investigated the effect of intranasal AVP on defensive aggression in a laboratory experiment, using an incentivized economic game called the “preemptive strike game” (PSG). Participants played PSG individually (1 on 1) as well as in pairs (2 on 2) under either AVP or saline. We observed that exogenous but not basal AVP modulated the attack rate in PSG for both male and female participants. A model-based analysis of the aggregation of individual attack preferences into pair decisions revealed that the AVP effect on defensive aggression occurred mainly at the individual level and was not amplified at the pair level. Overall, these results present the first evidence that intranasal AVP promotes human defensive aggression for both males and females in a bilateral situation where each party can potentially damage the resources of the other party. These findings also parallel accumulating evidence from non-human animals concerning AVP’s involvement in territorial defense against potential intruders.
Anthropogenic pollutant-driven geographical distribution of mesozooplankton communities in estuarine areas of the Bohai Sea, China
Authors: Gao Yangchun , Yang Qing , Li Hongjun , Wang Xiaocheng , Zhan Aibin 
Published: July 2019

AbstractMesozooplankton communities in marine ecosystems are mainly influenced by both anthropogenic pollutants (e.g. nutrients and heavy metals) and natural variables (e.g. temperature, salinity and geographic distance). To achieve a deeper understanding of the effects of anthropogenic pollutants on mesozooplankton communities, we analyzed the community structure of mesozooplankton from 91 stations representing five typical estuarine regions in the Bohai Sea and assessed the relative importance of anthropogenic pollutants and natural variables by using multiple statistical approaches. Cd was identified as the leading pollutant for observed community variation among the five regions, followed by NH4-N and COD. Redundancy analysis (RDA) model demonstrated that mesozooplankton communities were largely determined by both anthropogenic pollutants and natural variables, and the indicator species of mesozooplankton also varied when responding to different factors. Variance partitioning analysis showed both anthropogenic pollutants and natural variables posed significant influences (ANOVA,P < 0.05) on the mesozooplankton community structure, but the explanatory power of anthropogenic pollutants overrode the natural variables. These observations highlighted the importance of anthropogenic pollutants in the shifts of zooplankton structures among different regions. Our results obtained in this study provided new insights into the mechanism of the influence of anthropogenic pollutants on mesozooplankton communities in estuarine areas.
Establishing a many-cytokine signature via multivariate anomaly detection
Authors: Dingle K. , Zimek A. , Azizieh F. , Ansari A. R. 
Published: July 2019

AbstractEstablishing a cytokine signature associated to some medical condition is an important task in immunology. Increasingly, large numbers of cytokines are used for signatures, via lists of reference ranges for each individual cytokine or ratios of cytokines. Here we argue that this common approach has weaknesses, especially when many different cytokines are analysed. Instead, we propose that establishing signatures can be framed as a multivariate anomaly detection problem, and hence exploit the many statistical methods available for this. In this framework, whether or not a given subject’s profile matches the cytokine signature of some condition is determined by whether or not the profile is typical of reference samples of that condition, as judged by an anomaly detection algorithm. We examine previously published cytokine data sets associated to pregnancy complications, brain tumours, and rheumatoid arthritis, as well as normal healthy control samples, and test the performance of a range of anomaly detection algorithms on these data, identifying the best performing methods. Finally, we suggest that this anomaly detection approach could be adopted more widely for general multi-biomarker signatures.
Dual usage of a stage-specific fluorescent reporter system based on a helper-dependent adenoviral vector to visualize osteogenic differentiation
Authors: Sone Takefumi , Shin Masashi , Ouchi Takehito , Sasanuma Hiroki , Miyamoto Arei , Ohte Satoshi , Tsukamoto Sho , Nakanishi Mahito , Okano Hideyuki , Katagiri Takenobu , Mitani Kohnosuke 
Published: July 2019

AbstractWe developed a reporter system that can be used in a dual manner in visualizing mature osteoblast formation. The system is based on a helper-dependent adenoviral vector (HDAdV), in which a fluorescent protein, Venus, is expressed under the control of the 19-kb human osteocalcin (OC) genomic locus. By infecting human and murine primary osteoblast (POB) cultures with this reporter vector, the cells forming bone-like nodules were specifically visualized by the reporter. In addition, the same vector was utilized to efficiently knock-in the reporter into the endogenous OC gene of human induced pluripotent stem cells (iPSCs), by homologous recombination. Neural crest-like cells (NCLCs) derived from the knock-in reporter iPSCs were differentiated into osteoblasts forming bone-like nodules and could be visualized by the expression of the fluorescent reporter. Living mature osteoblasts were then isolated from the murine mixed POB culture by fluorescence-activated cell sorting (FACS), and their mRNA expression profile was analyzed. Our study presents unique utility of reporter HDAdVs in stem cell biology and related applications.
Discovery of food identity markers by metabolomics and machine learning technology
Authors: Erban Alexander , Fehrle Ines , Martinez-Seidel Federico , Brigante Federico , Más Agustín Lucini , Baroni Veronica , Wunderlin Daniel , Kopka Joachim 
Published: July 2019

AbstractVerification of food authenticity establishes consumer trust in food ingredients and components of processed food. Next to genetic or protein markers, chemicals are unique identifiers of food components. Non-targeted metabolomics is ideally suited to screen food markers when coupled to efficient data analysis. This study explored feasibility of random forest (RF) machine learning, specifically its inherent feature extraction for non-targeted metabolic marker discovery. The distinction of chia, linseed, and sesame that have gained attention as “superfoods” served as test case. Chemical fractions of non-processed seeds and of wheat cookies with seed ingredients were profiled. RF technology classified original seeds unambiguously but appeared overdesigned for material with unique secondary metabolites, like sesamol or rosmarinic acid in the Lamiaceae, chia. Most unique metabolites were diluted or lost during cookie production but RF technology classified the presence of the seed ingredients in cookies with 6.7% overall error and revealed food processing markers, like 4-hydroxybenzaldehyde for chia and succinic acid monomethylester for linseed additions. RF based feature extraction was adequate for difficult classifications but marker selection should not be without human supervision. Combination with alternative data analysis technologies is advised and further testing of a wide range of seeds and food processing methods.
Engineering a humanized telomerase reverse transcriptase gene in mouse embryonic stem cells
Authors: Cheng De , Zhao Yuanjun , Zhang Fan , Zhang Jinglong , Wang Shuwen , Zhu Jiyue 
Published: July 2019

AbstractTelomerase is expressed in adult mouse, but not in most human, tissues and mouse telomeres are much longer than those in humans. This interspecies difference of telomere homeostasis poses a challenge in modeling human diseases using laboratory mice. Using chromatinized bacterial artificial chromosome reporters, we discovered that the 5′ intergenic region, introns 2 and 6 of human telomerase gene (hTERT) were critical for regulating its promoter in somatic cells. Accordingly, we engineered a humanized gene, hmTert, by knocking-in a 47-kilobase hybrid fragment containing these human non-coding sequences into the mTert locus in mouse embryonic stem cells (mESCs). The hmTert gene, encoding the wildtype mTert protein, was fully functional, as a mESC line with homozygous hmTert alleles proliferated for over 400 population doublings without exhibiting chromosomal abnormalities. Like human ESCs, the engineered mESCs contained high telomerase activity, which was repressed upon their differentiation into fibroblast-like cells in a histone deacetylase-dependent manner. Fibroblast-like cells differentiated from these mESCs contained little telomerase activity. Thus, telomerase in mESCs with the hmTert alleles was subjected to human-like regulation. Our study revealed a novel approach to engineer a humanized telomerase gene in mice, achieving a milestone in creating a mouse model with humanized telomere homeostasis.