Studying the Underlying Event in Drell-Yan and High Transverse Momentum Jet Production at the Tevatron

We study the underlying event in proton-antiproton collisions by examining the behavior of charged particles (transverse momentum pT > 0.5 GeV/c, pseudorapidity |\eta| < 1) produced in association with large transverse momentum jets (~2.2 fb-1) or with Drell-Yan lepton-pairs (~2.7 fb-1) in the Z-boson mass region (70 < M(pair) < 110 GeV/c2) as measured by CDF at 1.96 TeV center-of-mass energy. We use the direction of the lepton-pair (in Drell-Yan production) or the leading jet (in high-pT jet production) in each event to define three regions of \eta-\phi space; toward, away, and transverse, where \phi is the azimuthal scattering angle. For Drell-Yan production (excluding the leptons) both the toward and transverse regions are very sensitive to the underlying event. In high-pT jet production the transverse region is very sensitive to the underlying event and is separated into a MAX and MIN transverse region, which helps separate the hard component (initial and final-state radiation) from the beam-beam remnant and multiple parton interaction components of the scattering. The data are corrected to the particle level to remove detector effects and are then compared with several QCD Monte-Carlo models. The goal of this analysis is to provide data that can be used to test and improve the QCD Monte-Carlo models of the underlying event that are used to simulate hadron-hadron collisions.Comment: Submitted to Phys.Rev.

Measurement of the W+W−W^+W^- Production Cross Section and Search for Anomalous WWγWW\gamma and WWZWWZ Couplings in ppˉp \bar p Collisions at s=1.96\sqrt{s} = 1.96 TeV

This Letter describes the current most precise measurement of the $W$ boson pair production cross section and most sensitive test of anomalous $WW\gamma$ and $WWZ$ couplings in $p \bar p$ collisions at a center-of-mass energy of 1.96 TeV. The $WW$ candidates are reconstructed from decays containing two charged leptons and two neutrinos, where the charged leptons are either electrons or muons. Using data collected by the CDF II detector from 3.6 fb$^{-1}$ of integrated luminosity, a total of 654 candidate events are observed with an expected background contribution of $320 \pm 47$ events. The measured total cross section is $\sigma (p \bar p \to W^+ W^- + X) = 12.1 \pm 0.9 \textrm{(stat)} ^{+1.6}_{-1.4} \textrm{(syst)}$ pb, which is in good agreement with the standard model prediction. The same data sample is used to place constraints on anomalous $WW\gamma$ and $WWZ$ couplings.Comment: submitted to Phys. Rev. Let

Compressed representation of a partially defined integer function over multiple arguments

In OLAP (OnLine Analitical Processing) data are analysed in an n-dimensional cube. The cube may be represented as a partially defined function over n arguments. Considering that often the function is not defined everywhere, we ask: is there a known way of representing the function or the points in which it is defined, in a more compact manner than the trivial one

Phospholipase D Family Member 4, a Transmembrane Glycoprotein with No Phospholipase D Activity, Expression in Spleen and Early Postnatal Microglia

BACKGROUND: Phospholipase D (PLD) catalyzes conversion of phosphatidylcholine into choline and phosphatidic acid, leading to a variety of intracellular signal transduction events. Two classical PLDs, PLD1 and PLD2, contain phosphatidylinositide-binding PX and PH domains and two conserved His-x-Lys-(x)(4)-Asp (HKD) motifs, which are critical for PLD activity. PLD4 officially belongs to the PLD family, because it possesses two HKD motifs. However, it lacks PX and PH domains and has a putative transmembrane domain instead. Nevertheless, little is known regarding expression, structure, and function of PLD4. METHODOLOGY/PRINCIPAL FINDINGS: PLD4 was analyzed in terms of expression, structure, and function. Expression was analyzed in developing mouse brains and non-neuronal tissues using microarray, in situ hybridization, immunohistochemistry, and immunocytochemistry. Structure was evaluated using bioinformatics analysis of protein domains, biochemical analyses of transmembrane property, and enzymatic deglycosylation. PLD activity was examined by choline release and transphosphatidylation assays. Results demonstrated low to modest, but characteristic, PLD4 mRNA expression in a subset of cells preferentially localized around white matter regions, including the corpus callosum and cerebellar white matter, during the first postnatal week. These PLD4 mRNA-expressing cells were identified as Iba1-positive microglia. In non-neuronal tissues, PLD4 mRNA expression was widespread, but predominantly distributed in the spleen. Intense PLD4 expression was detected around the marginal zone of the splenic red pulp, and splenic PLD4 protein recovered from subcellular membrane fractions was highly N-glycosylated. PLD4 was heterologously expressed in cell lines and localized in the endoplasmic reticulum and Golgi apparatus. Moreover, heterologously expressed PLD4 proteins did not exhibit PLD enzymatic activity. CONCLUSIONS/SIGNIFICANCE: Results showed that PLD4 is a non-PLD, HKD motif-carrying, transmembrane glycoprotein localized in the endoplasmic reticulum and Golgi apparatus. The spatiotemporally restricted expression patterns suggested that PLD4 might play a role in common function(s) among microglia during early postnatal brain development and splenic marginal zone cells

Natural Form of Noncytolytic Flexible Human Fc as a Long-Acting Carrier of Agonistic Ligand, Erythropoietin

Human IgG1 Fc has been widely used as a bioconjugate, but exhibits shortcomings, such as antibody- and complement-mediated cytotoxicity as well as decreased bioactivity, when applied to agonistic proteins. Here, we constructed a nonimmunogenic, noncytolytic and flexible hybrid Fc (hyFc) consisting of IgD and IgG4, and tested its function using erythropoietin (EPO) conjugate, EPO-hyFc. Despite low amino acid homology (20.5%) between IgD Fc and IgG4 Fc, EPO-hyFc retained “Y-shaped” structure and repeated intravenous administrations of EPO-hyFc into monkeys did not generate EPO-hyFc-specific antibody responses. Furthermore, EPO-hyFc could not bind to FcγR I and C1q in contrast to EPO-IgG1 Fc. In addition, EPO-hyFc exhibited better in vitro bioactivity and in vivo bioactivity in rats than EPO-IgG1 Fc, presumably due to the high flexibility of IgD. Moreover, the mean serum half-life of EPO-hyFc(H), a high sialic acid content form of EPO-hyFc, was approximately 2-fold longer than that of the heavily glycosylated EPO, darbepoetin alfa, in rats. More importantly, subcutaneous injection of EPO-hyFc(H) not only induced a significantly greater elevation of serum hemoglobin levels than darbepoetin alfa in both normal rats and cisplatin-induced anemic rats, but also displayed a delayed time to maximal serum level and twice final area-under-the-curve (AUClast). Taken together, hyFc might be a more attractive Fc conjugate for agonistic proteins/peptides than IgG1 Fc due to its capability to elongate their half-lives without inducing host effector functions and hindering bioactivity of fused molecules. Additionally, a head-to-head comparison demonstrated that hyFc-fusion strategy more effectively improved the in vivo bioactivity of EPO than the hyperglycosylation approach

Altered Small-World Brain Networks in Schizophrenia Patients during Working Memory Performance

Impairment of working memory (WM) performance in schizophrenia patients (SZ) is well-established. Compared to healthy controls (HC), SZ patients show aberrant blood oxygen level dependent (BOLD) activations and disrupted functional connectivity during WM performance. In this study, we examined the small-world network metrics computed from functional magnetic resonance imaging (fMRI) data collected as 35 HC and 35 SZ performed a Sternberg Item Recognition Paradigm (SIRP) at three WM load levels. Functional connectivity networks were built by calculating the partial correlation on preprocessed time courses of BOLD signal between task-related brain regions of interest (ROIs) defined by group independent component analysis (ICA). The networks were then thresholded within the small-world regime, resulting in undirected binarized small-world networks at different working memory loads. Our results showed: 1) at the medium WM load level, the networks in SZ showed a lower clustering coefficient and less local efficiency compared with HC; 2) in SZ, most network measures altered significantly as the WM load level increased from low to medium and from medium to high, while the network metrics were relatively stable in HC at different WM loads; and 3) the altered structure at medium WM load in SZ was related to their performance during the task, with longer reaction time related to lower clustering coefficient and lower local efficiency. These findings suggest brain connectivity in patients with SZ was more diffuse and less strongly linked locally in functional network at intermediate level of WM when compared to HC. SZ show distinctly inefficient and variable network structures in response to WM load increase, comparing to stable highly clustered network topologies in HC

Biased-corrected richness estimates for the Amazonian tree flora

Amazonian forests are extraordinarily diverse, but the estimated species richness is very much debated. Here, we apply an ensemble of parametric estimators and a novel technique that includes conspecific spatial aggregation to an extended database of forest plots with up-to-date taxonomy. We show that the species abundance distribution of Amazonia is best approximated by a logseries with aggregated individuals, where aggregation increases with rarity. By averaging several methods to estimate total richness, we confirm that over 15,000 tree species are expected to occur in Amazonia. We also show that using ten times the number of plots would result in an increase to just ~50% of those 15,000 estimated species. To get a more complete sample of all tree species, rigorous field campaigns may be needed but the number of trees in Amazonia will remain an estimate for years to come

The Human Phenotype Ontology in 2024: phenotypes around the world

\ua9 The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research. The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs

Building connectomes using diffusion MRI: why, how and but

Why has diffusion MRI become a principal modality for mapping connectomes in vivo? How do different image acquisition parameters, fiber tracking algorithms and other methodological choices affect connectome estimation? What are the main factors that dictate the success and failure of connectome reconstruction? These are some of the key questions that we aim to address in this review. We provide an overview of the key methods that can be used to estimate the nodes and edges of macroscale connectomes, and we discuss open problems and inherent limitations. We argue that diffusion MRI-based connectome mapping methods are still in their infancy and caution against blind application of deep white matter tractography due to the challenges inherent to connectome reconstruction. We review a number of studies that provide evidence of useful microstructural and network properties that can be extracted in various independent and biologically-relevant contexts. Finally, we highlight some of the key deficiencies of current macroscale connectome mapping methodologies and motivate future developments

Mapping inequalities in exclusive breastfeeding in low- and middle-income countries, 2000–2018

Exclusive breastfeeding (EBF)-giving infants only breast-milk for the first 6 months of life-is a component of optimal breastfeeding practices effective in preventing child morbidity and mortality. EBF practices are known to vary by population and comparable subnational estimates of prevalence and progress across low- and middle-income countries (LMICs) are required for planning policy and interventions. Here we present a geospatial analysis of EBF prevalence estimates from 2000 to 2018 across 94 LMICs mapped to policy-relevant administrative units (for example, districts), quantify subnational inequalities and their changes over time, and estimate probabilities of meeting the World Health Organization's Global Nutrition Target (WHO GNT) of ≥70% EBF prevalence by 2030. While six LMICs are projected to meet the WHO GNT of ≥70% EBF prevalence at a national scale, only three are predicted to meet the target in all their district-level units by 2030.This work was primarily supported by grant no. OPP1132415 from the Bill & Melinda Gates Foundation. Co-authors used by the Bill & Melinda Gates Foundation (E.G.P. and R.R.3) provided feedback on initial maps and drafts of this manuscript. L.G.A. has received support from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Brasil (CAPES), Código de Financiamento 001 and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) (grant nos. 404710/2018-2 and 310797/2019-5). O.O.Adetokunboh acknowledges the National Research Foundation, Department of Science and Innovation and South African Centre for Epidemiological Modelling and Analysis. M.Ausloos, A.Pana and C.H. are partially supported by a grant from the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project no. PN-III-P4-ID-PCCF-2016-0084. P.C.B. would like to acknowledge the support of F. Alam and A. Hussain. T.W.B. was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, funded by the German Federal Ministry of Education and Research. K.Deribe is supported by the Wellcome Trust (grant no. 201900/Z/16/Z) as part of his international intermediate fellowship. C.H. and A.Pana are partially supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project no. PN-III-P2-2.1-SOL-2020-2-0351. B.Hwang is partially supported by China Medical University (CMU109-MF-63), Taichung, Taiwan. M.Khan acknowledges Jatiya Kabi Kazi Nazrul Islam University for their support. A.M.K. acknowledges the other collaborators and the corresponding author. Y.K. was supported by the Research Management Centre, Xiamen University Malaysia (grant no. XMUMRF/2020-C6/ITM/0004). K.Krishan is supported by a DST PURSE grant and UGC Centre of Advanced Study (CAS II) awarded to the Department of Anthropology, Panjab University, Chandigarh, India. M.Kumar would like to acknowledge FIC/NIH K43 TW010716-03. I.L. is a member of the Sistema Nacional de Investigación (SNI), which is supported by the Secretaría Nacional de Ciencia, Tecnología e Innovación (SENACYT), Panamá. M.L. was supported by China Medical University, Taiwan (CMU109-N-22 and CMU109-MF-118). W.M. is currently a programme analyst in Population and Development at the United Nations Population Fund (UNFPA) Country Office in Peru, which does not necessarily endorses this study. D.E.N. acknowledges Cochrane South Africa, South African Medical Research Council. G.C.P. is supported by an NHMRC research fellowship. P.Rathi acknowledges support from Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, India. Ramu Rawat acknowledges the support of the GBD Secretariat for supporting the reviewing and collaboration of this paper. B.R. acknowledges support from Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal. A.Ribeiro was supported by National Funds through FCT, under the programme of ‘Stimulus of Scientific Employment—Individual Support’ within the contract no. info:eu-repo/grantAgreement/FCT/CEEC IND 2018/CEECIND/02386/2018/CP1538/CT0001/PT. S.Sajadi acknowledges colleagues at Global Burden of Diseases and Local Burden of Disease. A.M.S. acknowledges the support from the Egyptian Fulbright Mission Program. F.S. was supported by the Shenzhen Science and Technology Program (grant no. KQTD20190929172835662). A.Sheikh is supported by Health Data Research UK. B.K.S. acknowledges Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal for all the academic support. B.U. acknowledges support from Manipal Academy of Higher Education, Manipal. C.S.W. is supported by the South African Medical Research Council. Y.Z. was supported by Science and Technology Research Project of Hubei Provincial Department of Education (grant no. Q20201104) and Outstanding Young and Middle-aged Technology Innovation Team Project of Hubei Provincial Department of Education (grant no. T2020003). The funders of the study had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication. All maps presented in this study are generated by the authors and no permissions are required to publish them