Transverse Spin Structure of the Nucleon through Target Single Spin Asymmetry in Semi-Inclusive Deep-Inelastic (e,e′π±)(e,e^\prime \pi^\pm) Reaction at Jefferson Lab

Jefferson Lab (JLab) 12 GeV energy upgrade provides a golden opportunity to perform precision studies of the transverse spin and transverse-momentum-dependent structure in the valence quark region for both the proton and the neutron. In this paper, we focus our discussion on a recently approved experiment on the neutron as an example of the precision studies planned at JLab. The new experiment will perform precision measurements of target Single Spin Asymmetries (SSA) from semi-inclusive electro-production of charged pions from a 40-cm long transversely polarized $^3$He target in Deep-Inelastic-Scattering kinematics using 11 and 8.8 GeV electron beams. This new coincidence experiment in Hall A will employ a newly proposed solenoid spectrometer (SoLID). The large acceptance spectrometer and the high polarized luminosity will provide precise 4-D ($x$, $z$, $P_T$ and $Q^2$) data on the Collins, Sivers, and pretzelocity asymmetries for the neutron through the azimuthal angular dependence. The full 2$\pi$ azimuthal angular coverage in the lab is essential in controlling the systematic uncertainties. The results from this experiment, when combined with the proton Collins asymmetry measurement and the Collins fragmentation function determined from the e$^+$e$^-$ collision data, will allow for a quark flavor separation in order to achieve a determination of the tensor charge of the d quark to a 10% accuracy. The extracted Sivers and pretzelocity asymmetries will provide important information to understand the correlations between the quark orbital angular momentum and the nucleon spin and between the quark spin and nucleon spin.Comment: 23 pages, 13 figures, minor corrections, matches published versio

Perspectives on the use of transcriptomics to advance biofuels

As a field within the energy research sector, bioenergy is continuously expanding. Although much has been achieved and the yields of both ethanol and butanol have been improved, many avenues of research to further increase these yields still remain. This review covers current research related with transcriptomics and the application of this high-throughput analytical tool to engineer both microbes and plants with the penultimate goal being better biofuel production and yields. The initial focus is given to the responses of fermentative microbes during the fermentative production of acids, such as butyric acid, and solvents, including ethanol and butanol. As plants offer the greatest natural renewable source of fermentable sugars within the form of lignocellulose, the second focus area is the transcriptional responses of microbes when exposed to plant hydrolysates and lignin-related compounds. This is of particular importance as the acid/base hydrolysis methods commonly employed to make the plant-based cellulose available for enzymatic hydrolysis to sugars also generates significant amounts of lignin-derivatives that are inhibitory to fermentative bacteria and microbes. The article then transitions to transcriptional analyses of lignin-degrading organisms, such as Phanerochaete chrysosporium, as an alternative to acid/base hydrolysis. The final portion of this article will discuss recent transcriptome analyses of plants and, in particular, the genes involved in lignin production. The rationale behind these studies is to eventually reduce the lignin content present within these plants and, consequently, the amount of inhibitors generated during the acid/base hydrolysis of the lignocelluloses. All four of these topics represent key areas where transcriptomic research is currently being conducted to identify microbial genes and their responses to products and inhibitors as well as those related with lignin degradation/formation.clos

Steatosis drives monocyte-derived macrophage accumulation in human metabolic dysfunction-associated fatty liver disease

BACKGROUND & AIMS: Metabolic dysfunction-associated fatty liver disease (MAFLD) is a common complication of obesity with a hallmark feature of hepatic steatosis. Recent data from animal models of MAFLD have demonstrated substantial changes in macrophage composition in the fatty liver. In humans, the relationship between liver macrophage heterogeneity and liver steatosis is less clear. METHODS: Liver tissue from 21 participants was collected at time of bariatric surgery and analysed using flow cytometry, immunofluorescence, and H&E microscopy. Single-cell RNA sequencing was also conducted on a subset of samples (n = 3). Intrahepatic triglyceride content was assessed via MRI and tissue histology. Mouse models of hepatic steatosis were used to investigate observations made from human liver tissue. RESULTS: We observed variable degrees of liver steatosis with minimal fibrosis in our participants. Single-cell RNA sequencing revealed four macrophage clusters that exist in the human fatty liver encompassing Kupffer cells and monocyte-derived macrophages (MdMs). The genes expressed in these macrophage subsets were similar to those observed in mouse models of MAFLD. Hepatic CD14 CONCLUSIONS: The human liver in MAFLD contains macrophage subsets that align well with those that appear in mouse models of fatty liver disease. Recruited myeloid cells correlate well with the degree of liver steatosis in humans. MdMs appear to participate in lipid uptake during early stages of MALFD. IMPACT AND IMPLICATIONS: Metabolic dysfunction associated fatty liver disease (MAFLD) is extremely common; however, the early inflammatory responses that occur in human disease are not well understood. In this study, we investigated macrophage heterogeneity in human livers during early MAFLD and demonstrated that similar shifts in macrophage subsets occur in human disease that are similar to those seen in preclinical models. These findings are important as they establish a translational link between mouse and human models of disease, which is important for the development and testing of new therapeutic approaches for MAFLD

Coexistence of the spin-density-wave and superconductivity in the (Ba,K)Fe2As2

The relation between the spin-density-wave (SDW) and superconducting order is a central topic in current research on the FeAs-based high Tc superconductors. Conflicting results exist in the LaFeAs(O,F)-class of materials, for which whether the SDW and superconductivity are mutually exclusive or they can coexist has not been settled. Here we show that for the (Ba,K)Fe2As2 system, the SDW and superconductivity can coexist in an extended range of compositions. The availability of single crystalline samples and high value of the energy gaps would make the materials a model system to investigate the high Tc ferropnictide superconductivity.Comment: 4 pages, 5 figure

Combining vitamin C and carotenoid biomarkers better predicts fruit and vegetable intake than individual biomarkers in dietary intervention studies.

The aim of this study was to determine whether combining potential biomarkers of fruit and vegetables is better at predicting FV intake within FV intervention studies than single biomarkers

Variation among 532 genomes unveils the origin and evolutionary history of a global insect herbivore

The diamondback moth, Plutella xylostella is a cosmopolitan pest that has evolved resistance to all classes of insecticide, and costs the world economy an estimated US $4-5 billion annually. We analyse patterns of variation among 532 P. xylostella genomes, representing a worldwide sample of 114 populations. We find evidence that suggests South America is the geographical area of origin of this species, challenging earlier hypotheses of an Old-World origin. Our analysis indicates that Plutella xylostella has experienced three major expansions across the world, mainly facilitated by European colonization and global trade. We identify genomic signatures of selection in genes related to metabolic and signaling pathways that could be evidence of environmental adaptation. This evolutionary history of P. xylostella provides insights into transoceanic movements that have enabled it to become a worldwide pest.Minsheng You … Simon W. Baxter … Christopher M. Ward … et al

Efficient Physical Embedding of Topologically Complex Information Processing Networks in Brains and Computer Circuits

Nervous systems are information processing networks that evolved by natural selection, whereas very large scale integrated (VLSI) computer circuits have evolved by commercially driven technology development. Here we follow historic intuition that all physical information processing systems will share key organizational properties, such as modularity, that generally confer adaptivity of function. It has long been observed that modular VLSI circuits demonstrate an isometric scaling relationship between the number of processing elements and the number of connections, known as Rent's rule, which is related to the dimensionality of the circuit's interconnect topology and its logical capacity. We show that human brain structural networks, and the nervous system of the nematode C. elegans, also obey Rent's rule, and exhibit some degree of hierarchical modularity. We further show that the estimated Rent exponent of human brain networks, derived from MRI data, can explain the allometric scaling relations between gray and white matter volumes across a wide range of mammalian species, again suggesting that these principles of nervous system design are highly conserved. For each of these fractal modular networks, the dimensionality of the interconnect topology was greater than the 2 or 3 Euclidean dimensions of the space in which it was embedded. This relatively high complexity entailed extra cost in physical wiring: although all networks were economically or cost-efficiently wired they did not strictly minimize wiring costs. Artificial and biological information processing systems both may evolve to optimize a trade-off between physical cost and topological complexity, resulting in the emergence of homologous principles of economical, fractal and modular design across many different kinds of nervous and computational networks

Expert perspectives on global biodiversity loss and its drivers and impacts on people

Despite substantial progress in understanding global biodiversity loss, major taxonomic and geographic knowledge gaps remain. Decision makers often rely on expert judgement to fill knowledge gaps, but are rarely able to engage with sufficiently large and diverse groups of specialists. To improve understanding of the perspectives of thousands of biodiversity experts worldwide, we conducted a survey and asked experts to focus on the taxa and freshwater, terrestrial, or marine ecosystem with which they are most familiar. We found several points of overwhelming consensus (for instance, multiple drivers of biodiversity loss interact synergistically) and important demographic and geographic differences in specialists’ perspectives and estimates. Experts from groups that are underrepresented in biodiversity science, including women and those from the Global South, recommended different priorities for conservation solutions, with less emphasis on acquiring new protected areas, and provided higher estimates of biodiversity loss and its impacts. This may in part be because they disproportionately study the most highly threatened taxa and habitats

Neuroanatomical heterogeneity and homogeneity in individuals at clinical high risk for psychosis

Individuals at Clinical High Risk for Psychosis (CHR-P) demonstrate heterogeneity in clinical profiles and outcome features. However, the extent of neuroanatomical heterogeneity in the CHR-P state is largely undetermined. We aimed to quantify the neuroanatomical heterogeneity in structural magnetic resonance imaging measures of cortical surface area (SA), cortical thickness (CT), subcortical volume (SV), and intracranial volume (ICV) in CHR-P individuals compared with healthy controls (HC), and in relation to subsequent transition to a first episode of psychosis. The ENIGMA CHR-P consortium applied a harmonised analysis to neuroimaging data across 29 international sites, including 1579 CHR-P individuals and 1243 HC, offering the largest pooled CHR-P neuroimaging dataset to date. Regional heterogeneity was indexed with the Variability Ratio (VR) and Coefficient of Variation (CV) ratio applied at the group level. Personalised estimates of heterogeneity of SA, CT and SV brain profiles were indexed with the novel Person-Based Similarity Index (PBSI), with two complementary applications. First, to assess the extent of within-diagnosis similarity or divergence of neuroanatomical profiles between individuals. Second, using a normative modelling approach, to assess the ‘normativeness’ of neuroanatomical profiles in individuals at CHR-P. CHR-P individuals demonstrated no greater regional heterogeneity after applying FDR corrections. However, PBSI scores indicated significantly greater neuroanatomical divergence in global SA, CT and SV profiles in CHR-P individuals compared with HC. Normative PBSI analysis identified 11 CHR-P individuals (0.70%) with marked deviation (>1.5 SD) in SA, 118 (7.47%) in CT and 161 (10.20%) in SV. Psychosis transition was not significantly associated with any measure of heterogeneity. Overall, our examination of neuroanatomical heterogeneity within the CHR-P state indicated greater divergence in neuroanatomical profiles at an individual level, irrespective of psychosis conversion. Further large-scale investigations are required of those who demonstrate marked deviation

Mycorrhizal feedbacks influence global forest structure and diversity

One mechanism proposed to explain high species diversity in tropical systems is strong negative conspecific density dependence (CDD), which reduces recruitment of juveniles in proximity to conspecific adult plants. Although evidence shows that plant-specific soil pathogens can drive negative CDD, trees also form key mutualisms with mycorrhizal fungi, which may counteract these effects. Across 43 large-scale forest plots worldwide, we tested whether ectomycorrhizal tree species exhibit weaker negative CDD than arbuscular mycorrhizal tree species. We further tested for conmycorrhizal density dependence (CMDD) to test for benefit from shared mutualists. We found that the strength of CDD varies systematically with mycorrhizal type, with ectomycorrhizal tree species exhibiting higher sapling densities with increasing adult densities than arbuscular mycorrhizal tree species. Moreover, we found evidence of positive CMDD for tree species of both mycorrhizal types. Collectively, these findings indicate that mycorrhizal interactions likely play a foundational role in global forest diversity patterns and structure