A Stop Codon in Xeroderma Pigmentosum Group C Families in Turkey and Italy: Molecular Genetic Evidence for a Common Ancestor

Xeroderma pigmentosum family G from Van, Turkey had two severely affected children: a son with multiple skin cancers who died at age 10 (XP67TMA), and an 8 y old daughter who began developing skin cancer before 3 y of age (XP68TMA). XP67TMA and XP68TMA cells were hypersensitive to killing by ultraviolet and the post-ultraviolet DNA repair level was 12–16% of normal. Host cell reactivation of an ultraviolet-treated reporter plasmid cotransfected with a vector expressing wild-type XPC cDNA assigned XP67TMA to xeroderma pigmentosum complementation group C. The XPC mRNA level was markedly reduced. Sequencing of the 3.5 kb XPC cDNA from XP67TMA showed a C–T mutation in XPC exon 8 at base pair 1840. This mutation converts the CGA codon of arginine at amino acid 579 to a UGA stop codon resulting in marked truncation of the 940 amino acid xeroderma pigmentosum C protein. Restriction fragment length polymorphism analysis of XPC exon 8 DNA in XP67TMA and XP68TMA showed that both affected children had a homozygous mutation and that both parents had heterozygous normal and mutated sequences at the same position consistent with a history of consanguinity in the family. The mutated allele also contained two XPC single nucleotide polymorphisms. The same mutated XPC allele was reported in an Italian family. Studies of 19 microsatellite markers flanking the XPC gene on chromosome 3 suggest that the XPC allele passed between Italy and Turkey approximately 300–500 y ago. This XPC allele containing a nonsense mutation is associated with severe clinical disease with multiple skin cancers and early death

FlyBase at 25: looking to the future.

Since 1992, FlyBase (flybase.org) has been an essential online resource for the Drosophila research community. Concentrating on the most extensively studied species, Drosophila melanogaster, FlyBase includes information on genes (molecular and genetic), transgenic constructs, phenotypes, genetic and physical interactions, and reagents such as stocks and cDNAs. Access to data is provided through a number of tools, reports, and bulk-data downloads. Looking to the future, FlyBase is expanding its focus to serve a broader scientific community. In this update, we describe new features, datasets, reagent collections, and data presentations that address this goal, including enhanced orthology data, Human Disease Model Reports, protein domain search and visualization, concise gene summaries, a portal for external resources, video tutorials and the FlyBase Community Advisory Group

Effect of Homocysteine-Lowering Nutrients on Blood Lipids: Results from Four Randomised, Placebo-Controlled Studies in Healthy Humans

BACKGROUND: Betaine (trimethylglycine) lowers plasma homocysteine, a possible risk factor for cardiovascular disease. However, studies in renal patients and in obese individuals who are on a weight-loss diet suggest that betaine supplementation raises blood cholesterol; data in healthy individuals are lacking. Such an effect on cholesterol would counteract any favourable effect on homocysteine. We therefore investigated the effect of betaine, of its precursor choline in the form of phosphatidylcholine, and of the classical homocysteine-lowering vitamin folic acid on blood lipid concentrations in healthy humans. METHODS AND FINDINGS: We measured blood lipids in four placebo-controlled, randomised intervention studies that examined the effect of betaine (three studies, n = 151), folic acid (two studies, n = 75), and phosphatidylcholine (one study, n = 26) on plasma homocysteine concentrations. We combined blood lipid data from the individual studies and calculated a weighted mean change in blood lipid concentrations relative to placebo. Betaine supplementation (6 g/d) for 6 wk increased blood LDL cholesterol concentrations by 0.36 mmol/l (95% confidence interval: 0.25–0.46), and triacylglycerol concentrations by 0.14 mmol/l (0.04–0.23) relative to placebo. The ratio of total to HDL cholesterol increased by 0.23 (0.14–0.32). Concentrations of HDL cholesterol were not affected. Doses of betaine lower than 6 g/d also raised LDL cholesterol, but these changes were not statistically significant. Further, the effect of betaine on LDL cholesterol was already evident after 2 wk of intervention. Phosphatidylcholine supplementation (providing approximately 2.6 g/d of choline) for 2 wk increased triacylglycerol concentrations by 0.14 mmol/l (0.06–0.21), but did not affect cholesterol concentrations. Folic acid supplementation (0.8 mg/d) had no effect on lipid concentrations. CONCLUSIONS: Betaine supplementation increased blood LDL cholesterol and triacylglycerol concentrations in healthy humans, which agrees with the limited previous data. The adverse effects on blood lipids may undo the potential benefits for cardiovascular health of betaine supplementation through homocysteine lowering. In our study phosphatidylcholine supplementation slightly increased triacylglycerol concentrations in healthy humans. Previous studies of phosphatidylcholine and blood lipids showed no clear effect. Thus the effect of phosphatidylcholine supplementation on blood lipids remains inconclusive, but is probably not large. Folic acid supplementation does not seem to affect blood lipids and therefore remains the preferred treatment for lowering of blood homocysteine concentrations

Identification of brain transcriptional variation reproduced in peripheral blood: an approach for mapping brain expression traits

Genome-wide gene expression studies may provide substantial insight into gene activities and biological pathways differing between tissues and individuals. We investigated such gene expression variation by analyzing expression profiles in brain tissues derived from eight different brain regions and from blood in 12 monkeys from a biomedically important non-human primate model, the vervet (Chlorocebus aethiops sabaeus). We characterized brain regional differences in gene expression, focusing on transcripts for which inter-individual variation of expression in brain correlates well with variation in blood from the same individuals. Using stringent criteria, we identified 29 transcripts whose expression is measurable, stable, replicable, variable between individuals, relevant to brain function and heritable. Polymorphisms identified in probe regions could, in a minority of transcripts, confound the interpretation of the observed inter-individual variation. The high heritability of levels of these transcripts in a large vervet pedigree validated our approach of focusing on transcripts that showed higher inter-individual compared with intra-individual variation. These selected transcripts are candidate expression Quantitative Trait Loci, differentially regulating transcript levels in the brain among individuals. Given the high degree of conservation of tissue expression profiles between vervets and humans, our findings may facilitate the understanding of regional and individual transcriptional variation and its genetic mechanisms in humans. The approach employed here—utilizing higher quality tissue and more precise dissection of brain regions than is usually possible in humans—may therefore provide a powerful means to investigate variation in gene expression relevant to complex brain related traits, including human neuropsychiatric diseases

Meta-analysis of real-time fMRI neurofeedback studies using individual participant data: How is brain regulation mediated?

An increasing number of studies using real-time fMRI neurofeedback have demonstrated that successful regulation of neural activity is possible in various brain regions. Since these studies focused on the regulated region(s), little is known about the target-independent mechanisms associated with neurofeedback-guided control of brain activation, i.e. the regulating network. While the specificity of the activation during self-regulation is an important factor, no study has effectively determined the network involved in self-regulation in general. In an effort to detect regions that are responsible for the act of brain regulation, we performed a post-hoc analysis of data involving different target regions based on studies from different research groups. We included twelve suitable studies that examined nine different target regions amounting to a total of 175 subjects and 899 neurofeedback runs. Data analysis included a standard first- (single subject, extracting main paradigm) and second-level (single subject, all runs) general linear model (GLM) analysis of all participants taking into account the individual timing. Subsequently, at the third level, a random effects model GLM included all subjects of all studies, resulting in an overall mixed effects model. Since four of the twelve studies had a reduced field of view (FoV), we repeated the same analysis in a subsample of eight studies that had a well-overlapping FoV to obtain a more global picture of self-regulation. The GLM analysis revealed that the anterior insula as well as the basal ganglia, notably the striatum, were consistently active during the regulation of brain activation across the studies. The anterior insula has been implicated in interoceptive awareness of the body and cognitive control. Basal ganglia are involved in procedural learning, visuomotor integration and other higher cognitive processes including motivation. The larger FoV analysis yielded additional activations in the anterior cingulate cortex, the dorsolateral and ventrolateral prefrontal cortex, the temporo-parietal area and the visual association areas including the temporo-occipital junction. In conclusion, we demonstrate that several key regions, such as the anterior insula and the basal ganglia, are consistently activated during self-regulation in real-time fMRI neurofeedback independent of the targeted region-of-interest. Our results imply that if the real-time fMRI neurofeedback studies target regions of this regulation network, such as the anterior insula, care should be given whether activation changes are related to successful regulation, or related to the regulation process per se. Furthermore, future research is needed to determine how activation within this regulation network is related to neurofeedback success

Desert Farming Benefits from Microbial Potential in Arid Soils and Promotes Diversity and Plant Health

BACKGROUND: To convert deserts into arable, green landscapes is a global vision, and desert farming is a strong growing area of agriculture world-wide. However, its effect on diversity of soil microbial communities, which are responsible for important ecosystem services like plant health, is still not known. METHODOLOGY/PRINCIPAL FINDINGS: We studied the impact of long-term agriculture on desert soil in one of the most prominent examples for organic desert farming in Sekem (Egypt). Using a polyphasic methodological approach to analyse microbial communities in soil as well as associated with cultivated plants, drastic effects caused by 30 years of agriculture were detected. Analysing bacterial fingerprints, we found statistically significant differences between agricultural and native desert soil of about 60%. A pyrosequencing-based analysis of the 16S rRNA gene regions showed higher diversity in agricultural than in desert soil (Shannon diversity indices: 11.21/7.90), and displayed structural differences. The proportion of Firmicutes in field soil was significantly higher (37%) than in the desert (11%). Bacillus and Paenibacillus play the key role: they represented 96% of the antagonists towards phytopathogens, and identical 16S rRNA sequences in the amplicon library and for isolates were detected. The proportion of antagonistic strains was doubled in field in comparison to desert soil (21.6%/12.4%); disease-suppressive bacteria were especially enriched in plant roots. On the opposite, several extremophilic bacterial groups, e.g., Acidimicrobium, Rubellimicrobium and Deinococcus-Thermus, disappeared from soil after agricultural use. The N-fixing Herbaspirillum group only occurred in desert soil. Soil bacterial communities were strongly driven by the a-biotic factors water supply and pH. CONCLUSIONS/SIGNIFICANCE: After long-term farming, a drastic shift in the bacterial communities in desert soil was observed. Bacterial communities in agricultural soil showed a higher diversity and a better ecosystem function for plant health but a loss of extremophilic bacteria. Interestingly, we detected that indigenous desert microorganisms promoted plant health in desert agro-ecosystems

Exclusive J/ψ detection and physics with ECCE

The file available on this institutional repository is an arXiv preprint which may not have been certified by peer review. The definitive version of record published by Elsevier is available at https://doi.org/10.48550/arXiv.2207.10356.Copyright © The Authors 2023. The EIC Comprehensive Chromodynamics Experiment (ECCE) detector has been recommended as a reference design for the proposed Electron-Ion Collider (EIC) program. This paper presents simulation studies of exclusive J/ψ detection and selected physics impact results in EIC using the projected ECCE detector concept. Exclusive quarkonium photoproduction is one of the most popular processes in EIC, which has a large cross section and a simple final state. Due to the gluonic nature of the exchange Pomeron, this process can be related to the gluon distributions in the nucleus. Preliminary results estimate the excellent statistics benefited from the large cross section of J/ψ photoproduction and superior performance of ECCE detector concept. The precise measurement of exclusive J/ψ photoproduction at EIC will help us to more deeply understand nuclear gluon distributions, near threshold production mechanism and nucleon mass structure.X. Li and W. Zha are supported by the National Natural Science Foundation of China (12005220, 12175223) and MOST (2018YFE0104900). The authors would like to thank the ECCE Consortium for performing a full simulation of their detector design, for providing up-to-date information on EIC run conditions, and for suggestions and comments on the manuscript. X. Li and W. Zha would like to thank Y. Zhou for useful suggestions and discussions related to this analysis. W. Zha is supported by Anhui Provincial Natural Science Foundation No. 2208085J23 and Youth Innovation Promotion Association of Chinese Academy of Sciences. AANL group are supported by the Science Committee of RA , in the frames of the research project 21AG-1C028

Design and Simulated Performance of Calorimetry Systems for the ECCE Detector at the Electron Ion Collider

We describe the design and performance the calorimeter systems used in the ECCE detector design to achieve the overall performance specifications cost-effectively with careful consideration of appropriate technical and schedule risks. The calorimeter systems consist of three electromagnetic calorimeters, covering the combined pseudorapdity range from -3.7 to 3.8 and two hadronic calorimeters. Key calorimeter performances which include energy and position resolutions, reconstruction efficiency, and particle identification will be presented.Comment: 19 pages, 22 figures, 5 table

AI-assisted Optimization of the ECCE Tracking System at the Electron Ion Collider

The 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.Comment: 16 pages, 18 figures, 2 appendices, 3 table

ECCE Sensitivity Studies for Single Hadron Transverse Single Spin Asymmetry Measurements

We performed feasibility studies for various single transverse spin measurements that are related to the Sivers effect, transversity and the tensor charge, and the Collins fragmentation function. The processes studied include semi-inclusive deep inelastic scattering (SIDIS) where single hadrons (pions and kaons) were detected in addition to the scattered DIS lepton. The data were obtained in {\sc pythia}6 and {\sc geant}4 simulated e+p collisions at 18 GeV on 275 GeV, 18 on 100, 10 on 100, and 5 on 41 that use the ECCE detector configuration. Typical DIS kinematics were selected, most notably $Q^2 > 1$ GeV$^2$, and cover the $x$ range from $10^{-4}$ to $1$. The single spin asymmetries were extracted as a function of $x$ and $Q^2$, as well as the semi-inclusive variables $z$, and $P_T$. They are obtained in azimuthal moments in combinations of the azimuthal angles of the hadron transverse momentum and transverse spin of the nucleon relative to the lepton scattering plane. The initially unpolarized MonteCarlo was re-weighted in the true kinematic variables, hadron types and parton flavors based on global fits of fixed target SIDIS experiments and $e^+e^-$ annihilation data. The expected statistical precision of such measurements is extrapolated to 10 fb$^{-1}$ and potential systematic uncertainties are approximated given the deviations between true and reconstructed yields. The impact on the knowledge of the Sivers functions, transversity and tensor charges, and the Collins function has then been evaluated in the same phenomenological extractions as in the Yellow Report. The impact is found to be comparable to that obtained with the parameterized Yellow Report detector and shows that the ECCE detector configuration can fulfill the physics goals on these quantities.Comment: 22 pages, 22 figures, to be submitted to joint ECCE proposal NIM-A volum