48 research outputs found
Bovine GDF10 gene polymorphism analysis and its association with body measurement traits in Chinese indigenous cattle
The objective of this research was to detect bovine GDF10 gene polymorphism and analyze its association with body measurement traits (BMT) of animals sampled from 6 different Chinese indigenous cattle populations. The populations included Xuelong (Xl), Luxi (Lx), Qinchuan (Qc), Jiaxian red (Jx), Xianang (Xn) and Nanyang (Ny). Blood samples were taken from a total of 417 female animals stratified into age categories of 12–36 months. Polymerase chain reaction–single strand conformation polymorphism (PCR–SSCP) was employed to find out GDF10 single polymorphism nucleotide (SNPs) and explore their possible association with BMT. Sequence analysis of GDF10 gene revealed 3 SNPs in total: 1 in exon1 (G142A) and 2 in exon3 (A11471G, and T12495C). G142A and T12495C SNPs are both synonymous mutation. They showed 2 genotypes namely respectively (GG, GA) and (PP and PB). A11471G SNP is a missense mutation leading to the change of Alanine to Threonine amino acid. It showed three genotypes namely AA, BB and AB. Analysis of association of polymorphism with body measurement traits at the three locus showed that there were significant effects on BMT in Qc, Jx and Ny cattle population. These results suggest that the GDF10 gene might have potential effects on body measurement traits in the above mentioned cattle populations and could be used for marker-assisted selection
Constitutive nuclear factor-kappa B mRNA, protein overexpression and enhanced DNA-binding activity in thymidylate synthase inhibitor-resistant tumour cells
In this study, the gene copy number, mRNA and protein expression levels and nuclear DNA-binding activity of nuclear factor kappa B (NF-kappaB) were compared in a panel of five pairs of thymidylate synthase (TS) inhibitor-resistant and wild-type parent cancer cell lines. High constitutive NF-kappaB DNA-binding activity was detected in all chemoresistant cell lines. The upregulated NF-kappaB activity was composed of NF-kappaB subunits p50 and p65. Four out of five resistant cell lines constitutively overexpressed NF-kappaB p50 and p63 mRNA and protein. One resistant cell line with the highest NF-kappaB DNA-binding activity showed normal p50 and p65 protein expression. No NF-kappaB gene amplification was detected in resistant cell lines. Transient exposure of wild-type RKOWT and H630(WT) cells to 5-FU induced NF-kappaB DNA-binding activity but had no effect on NF-kappaB protein expression in these cells, Our results indicate that high constitutive NF-kappaB activity caused by its gene overexpression is an intrinsic character of TS inhibitor-resistant cells. NF-kappaB can antagonise anticancer drug-induced apoptosis. High NF-kappaB expression and nuclear activity in TS inhibitor-resistant cancer cells may play an important role in the chemoresistance
Individual Differences in Sound-in-Noise Perception Are Related to the Strength of Short-Latency Neural Responses to Noise
Important sounds can be easily missed or misidentified in the presence of extraneous noise. We describe an auditory illusion in which a continuous ongoing tone becomes inaudible during a brief, non-masking noise burst more than one octave away, which is unexpected given the frequency resolution of human hearing. Participants strongly susceptible to this illusory discontinuity did not perceive illusory auditory continuity (in which a sound subjectively continues during a burst of masking noise) when the noises were short, yet did so at longer noise durations. Participants who were not prone to illusory discontinuity showed robust early electroencephalographic responses at 40–66 ms after noise burst onset, whereas those prone to the illusion lacked these early responses. These data suggest that short-latency neural responses to auditory scene components reflect subsequent individual differences in the parsing of auditory scenes
Characterization of an Nmr Homolog That Modulates GATA Factor-Mediated Nitrogen Metabolite Repression in Cryptococcus neoformans
Nitrogen source utilization plays a critical role in fungal development, secondary metabolite production and pathogenesis. In both the Ascomycota and Basidiomycota, GATA transcription factors globally activate the expression of catabolic enzyme-encoding genes required to degrade complex nitrogenous compounds. However, in the presence of preferred nitrogen sources such as ammonium, GATA factor activity is inhibited in some species through interaction with co-repressor Nmr proteins. This regulatory phenomenon, nitrogen metabolite repression, enables preferential utilization of readily assimilated nitrogen sources. In the basidiomycete pathogen Cryptococcus neoformans, the GATA factor Gat1/Are1 has been co-opted into regulating multiple key virulence traits in addition to nitrogen catabolism. Here, we further characterize Gat1/Are1 function and investigate the regulatory role of the predicted Nmr homolog Tar1. While GAT1/ARE1 expression is induced during nitrogen limitation, TAR1 transcription is unaffected by nitrogen availability. Deletion of TAR1 leads to inappropriate derepression of non-preferred nitrogen catabolic pathways in the simultaneous presence of favoured sources. In addition to exhibiting its evolutionary conserved role of inhibiting GATA factor activity under repressing conditions, Tar1 also positively regulates GAT1/ARE1 transcription under non-repressing conditions. The molecular mechanism by which Tar1 modulates nitrogen metabolite repression, however, remains open to speculation. Interaction between Tar1 and Gat1/Are1 was undetectable in a yeast two-hybrid assay, consistent with Tar1 and Gat1/Are1 each lacking the conserved C-terminus regions present in ascomycete Nmr proteins and GATA factors that are known to interact with each other. Importantly, both Tar1 and Gat1/Are1 are suppressors of C. neoformans virulence, reiterating and highlighting the paradigm of nitrogen regulation of pathogenesis
Present and future evolution of advanced breast cancer therapy
Although the introduction of novel therapies and drug combinations has improved the prognosis of metastatic breast cancer, the disease remains incurable. Increased knowledge of the biology and the molecular alterations in breast cancer has facilitated the design of targeted therapies. These agents include receptor and nonreceptor tyrosine kinase inhibitors (epidermal growth factor receptor family), intracellular signaling pathways (phosphatidylinositol-3-kinase, AKT, mammalian target of rapamycin) angiogenesis inhibitors and agents that interfere with DNA repair (poly(ADP-ribose) polymerase inhibitors). In the present review, we present the most promising studies of these new targeted therapies and novel combinations of targeted therapies with cytotoxic agents
Identifying the participant characteristics that predict recruitment and retention of participants to randomised controlled trials involving children : a systematic review
Background
Randomised controlled trials (RCTs) are recommended as the ‘gold standard’ in evaluating health care interventions. The conduct of RCTs is often impacted by difficulties surrounding recruitment and retention of participants in both adult and child populations. Factors influencing recruitment and retention of children to RCTs can be more complex than in adults. There is little synthesised evidence of what influences participation in research involving parents and children.
Aim
To identify predictors of recruitment and retention in RCTs involving children.
Methods
A systematic review of RCTs was conducted to synthesise the available evidence. An electronic search strategy was applied to four databases and restricted to English language publications. Quantitative studies reporting participant predictors of recruitment and retention in RCTs involving children aged 0–12 were identified. Data was extracted and synthesised narratively. Quality assessment of articles was conducted using a structured tool developed from two existing quality evaluation checklists.
Results
Twenty-eight studies were included in the review. Of the 154 participant factors reported, 66 were found to be significant predictors of recruitment and retention in at least one study. These were classified as parent, child, family and neighbourhood characteristics. Parent characteristics (e.g. ethnicity, age, education, socioeconomic status (SES)) were the most commonly reported predictors of participation for both recruitment and retention. Being young, less educated, of an ethnic minority and having low SES appear to be barriers to participation in RCTs although there was little agreement between studies. When analysed according to setting and severity of the child’s illness there appeared to be little variation between groups. The quality of the studies varied. Articles adhered well to reporting guidelines around provision of a scientific rationale for the study and background information as well as displaying good internal consistency of results. However, few studies discussed the external validity of the results or provided recommendations for future research.
Conclusion
Parent characteristics may predict participation of children and their families to RCTs; however, there was a lack of consensus. Whilst sociodemographic variables may be useful in identifying which groups are least likely to participate they do not provide insight into the processes and barriers to participation for children and families. Further studies that explore variables that can be influenced are warranted. Reporting of studies in this field need greater clarity as well as agreed definitions of what is meant by retention
Multi-messenger observations of a binary neutron star merger
On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta
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Design of the ECCE Detector for the Electron Ion Collider
Preprint submitted to Nuclear Instruments and Methods A. The file archived on this institutional repository has not been certified by peer review.32 pages, 29 figures, 9 tablesThe EIC Comprehensive Chromodynamics Experiment (ECCE) detector has been designed to address the full scope of the proposed Electron Ion Collider (EIC) physics program as presented by the National Academy of Science and provide a deeper understanding of the quark-gluon structure of matter. To accomplish this, the ECCE detector offers nearly acceptance and energy coverage along with excellent tracking and particle identification. The ECCE detector was designed to be built within the budget envelope set out by the EIC project while simultaneously managing cost and schedule risks. This detector concept has been selected to be the basis for the EIC project detector.Office of Science in the Department of Energy, the National Science Foundation, and the Los Alamos National
Laboratory Laboratory Directed Research and Development (LDRD) 20200022DR; This research used resources of the Compute and Data Environment for Science (CADES) at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-
00OR22725. The work of AANL group are supported by the Science Committee of RA, in the frames of the research project # 21AG-1C028. And we gratefully acknowledge that support of Brookhaven National Lab and the Thomas Jefferson National Accelerator Facility which are operated under contracts DESC0012704 and DE-AC05-06OR23177 respectivel
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AI-assisted optimization of the ECCE tracking system at the Electron Ion Collider
arXiv preprint [v2] Fri, 20 May 2022 03:23:44 UTC (2,296 KB) made available under a Creative Commons (CC BY) Attribution Licence, now in press, published by Elsevier: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, available online 17 November 2022 at: https://doi.org/10.1016/j.nima.2022.167748The Electron-Ion Collider (EIC) is a cutting-edge accelerator facility that will study the nature of the "glue" that binds the building blocks of the visible matter in the universe. The proposed experiment will be realized at Brookhaven National Laboratory in approximately 10 years from now, with detector design and R&D currently ongoing. Notably, EIC is one of the first large-scale facilities to leverage Artificial Intelligence (AI) already starting from the design and R&D phases. The EIC Comprehensive Chromodynamics Experiment (ECCE) is a consortium that proposed a detector design based on a 1.5T solenoid. The EIC detector proposal review concluded that the ECCE design will serve as the reference design for an EIC detector. Herein we describe a comprehensive optimization of the ECCE tracker using AI. The work required a complex parametrization of the simulated detector system. Our approach dealt with an optimization problem in a multidimensional design space driven by multiple objectives that encode the detector performance, while satisfying several mechanical constraints. We describe our strategy and show results obtained for the ECCE tracking system. The AI-assisted design is agnostic to the simulation framework and can be extended to other sub-detectors or to a system of sub-detectors to further optimize the performance of the EIC detector.Office of Nuclear Physics in the Office of Science in the Department of Energy; National Science Foundation, and the Los Alamos National Laboratory Laboratory Directed Research and Development (LDRD) 20200022DR