Patency and Clinico-Haematological Pathologies Sequel to Trypanosoma brucei and Trypanosoma evansi Induced Infections in Yankasa Sheep I

Trypanosomosis remains one of the most deadly protozoan diseases that pose a significant impact on livestock health in the tropics. Sixteen (16) rams aged between 24 to 30 months and weighed between 22-25kg were acclimatized under standard animal housing  conditions. Twelve (12) of the sheep deemed fit and healthy were randomly divided into four groups (I, II, III, and IV) of three sheep each. Each sheep in groups I and II was inoculated intravenously with 2 mL containing 2 X 106 trypomastigote forms of Trypanosoma brucei and Trypanosoma evansi, respectively. While group III, each sheep received 2 mL containing 2 X 106 mixed inoculums of T. brucei and T. evansi (50% each by volume of the infective inoculums). Sheep in group IV served as the non-infected control. Post-infection animals were monitored for 14 weeks for parasitaemia, clinical signs, and haematological pathologies. The patent infection became evident in groups I, II, and III between 5-21 days post-infection with average patency of 7, 20, and 8.5 days respectively. The infection was characterized by intermittent pyrexia with a significant decrease (p< 0.001) in mean weekly packed cell volume (PCV),  haemoglobin concentration (Hb), live weight gain, plasma protein, which significantly decreased (p< 0.001) in all the infected groups. Pearson’s correlation (r) indicates a strong positive correlation (r= 0.991) between parasitaemia and pyrexia, and principal component analysis (PCA) biplot increased the predictabilities of these two indices as the major precursors in the progression of the trypanosomes pathogenesis in sheep. Keywords: Trypanosomosis; Patency; Clinico-haematological pathologies; Trypanosoma brucei; Trypanosoma evansi; Yankasa shee

Road-side roasted plantain and maize in Zaria and environs: nutritional composition and heavy metal evaluation

This study aimed to assess the nutritional quality and heavy metal contamination of roasted and raw corn and plantain marketed in Zaria and its vicinity. Raw and roasted plantain and maize were obtained from three distinct areas of Zaria. The samples were air-dried and ground into powdered flour for analysis. Moisture content was lowest in roasted plantain (4.67±0.54%) and highest in raw maize (9.58±0.60%). Crude protein and crude fibre were most elevated in roasted maize samples (10.56±0.26, 3.22±0.13%, respectively) and lowest in raw plantain samples (8.62±0.37, 1.70±0.20%, respectively). Ash content was highest in raw plantain (3.28±0.16%) and lowest in roasted maize samples (2.00±0.26%). Nitrogen-free extract (NFE) was significantly higher (P <0.05) in both raw (78.42±0.64%) and roasted plantain (78.63±1.14%). The mineral composition of roasted road-side plantain (Ca, 0.22±0.04; Ph, 0.11±0.03) and maize (Ca, 0.23±0.02; Ph, 0.22±0.00) reveal that calcium and phosphorus were found within the moderate limit adequate for human consumption. Based on the current study, raw and roasted plantain and maize across all the study locations were highly contaminated with Pb, Cr, and Cd, which may pose a public health concern

Increasing coverage of vaccination by pharmacists in Nigeria; an urgent need

Pharmacists have a key role to play to advance public health through immunization. Pharmacists are well trained and play a huge role in vaccine production, research and development, safety, pharmacovigilance, storage, logistics and distribution. There is a need for a revised national policy and strategy in Nigeria on vaccination and immunization programs with the involvement of community pharmacies and/or pharmacists. This will help accelerate getting a wider vaccination access coverage, establishing a greater healthcare delivery workforce for societal benefits and demonstrate the full potential of the community pharmacies and the pharmacists’ role in immunization programs

Measurement of the Bottom contribution to non-photonic electron production in p+pp+p collisions at s\sqrt{s} =200 GeV

The contribution of $B$ meson decays to non-photonic electrons, which are mainly produced by the semi-leptonic decays of heavy flavor mesons, in $p+p$ collisions at $\sqrt{s} =$ 200 GeV has been measured using azimuthal correlations between non-photonic electrons and hadrons. The extracted $B$ decay contribution is approximately 50% at a transverse momentum of $p_{T} \geq 5$ GeV/$c$. These measurements constrain the nuclear modification factor for electrons from $B$ and $D$ meson decays. The result indicates that $B$ meson production in heavy ion collisions is also suppressed at high $p_{T}$.Comment: 6 pages, 4 figures, accepted by PR

Mapping geographical inequalities in childhood diarrhoeal morbidity and mortality in low-income and middle-income countries, 2000–17 : analysis for the Global Burden of Disease Study 2017

Background Across low-income and middle-income countries (LMICs), one in ten deaths in children younger than 5 years is attributable to diarrhoea. The substantial between-country variation in both diarrhoea incidence and mortality is attributable to interventions that protect children, prevent infection, and treat disease. Identifying subnational regions with the highest burden and mapping associated risk factors can aid in reducing preventable childhood diarrhoea. Methods We used Bayesian model-based geostatistics and a geolocated dataset comprising 15 072 746 children younger than 5 years from 466 surveys in 94 LMICs, in combination with findings of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017, to estimate posterior distributions of diarrhoea prevalence, incidence, and mortality from 2000 to 2017. From these data, we estimated the burden of diarrhoea at varying subnational levels (termed units) by spatially aggregating draws, and we investigated the drivers of subnational patterns by creating aggregated risk factor estimates. Findings The greatest declines in diarrhoeal mortality were seen in south and southeast Asia and South America, where 54·0% (95% uncertainty interval [UI] 38·1–65·8), 17·4% (7·7–28·4), and 59·5% (34·2–86·9) of units, respectively, recorded decreases in deaths from diarrhoea greater than 10%. Although children in much of Africa remain at high risk of death due to diarrhoea, regions with the most deaths were outside Africa, with the highest mortality units located in Pakistan. Indonesia showed the greatest within-country geographical inequality; some regions had mortality rates nearly four times the average country rate. Reductions in mortality were correlated to improvements in water, sanitation, and hygiene (WASH) or reductions in child growth failure (CGF). Similarly, most high-risk areas had poor WASH, high CGF, or low oral rehydration therapy coverage. Interpretation By co-analysing geospatial trends in diarrhoeal burden and its key risk factors, we could assess candidate drivers of subnational death reduction. Further, by doing a counterfactual analysis of the remaining disease burden using key risk factors, we identified potential intervention strategies for vulnerable populations. In view of the demands for limited resources in LMICs, accurately quantifying the burden of diarrhoea and its drivers is important for precision public health

Event-plane-dependent Dihadron Correlations With Harmonic Vn Subtraction In Au + Au Collisions At S Nn =200 Gev

STAR measurements of dihadron azimuthal correlations (Δφ) are reported in midcentral (20-60%) Au+Au collisions at sNN=200 GeV as a function of the trigger particle's azimuthal angle relative to the event plane, φs=|φt-ψEP|. The elliptic (v2), triangular (v3), and quadratic (v4) flow harmonic backgrounds are subtracted using the zero yield at minimum (ZYAM) method. The results are compared to minimum-bias d+Au collisions. It is found that a finite near-side (|Δφ|π/2) correlation shows a modification from d+Au data, varying with φs. The modification may be a consequence of path-length-dependent jet quenching and may lead to a better understanding of high-density QCD. © 2014 American Physical Society.894DOE; U.S. Department of EnergyArsene, I., (2005) Nucl. Phys. A, 757, p. 1. , (BRAHMS Collaboration), () NUPABL 0375-9474 10.1016/j.nuclphysa.2005.02. 130;Back, B.B., (2005) Nucl. Phys. A, 757, p. 28. , (PHOBOS Collaboration), () NUPABL 0375-9474 10.1016/j.nuclphysa.2005.03. 084;Adams, J., (2005) Nucl. Phys. A, 757, p. 102. , (STAR Collaboration), () NUPABL 0375-9474 10.1016/j.nuclphysa.2005.03. 085;Adcox, K., (2005) Nucl. Phys. A, 757, p. 184. , (PHENIX Collaboration),. NUPABL 0375-9474 10.1016/j.nuclphysa.2005.03.086Heinz, U., Kolb, P.F., (2002) Nucl. Phys. A, 702, p. 269. , NUPABL 0375-9474 10.1016/S0375-9474(02)00714-5Wang, X.-N., Gyulassy, M., (1992) Phys. Rev. Lett., 68, p. 1480. , PRLTAO 0031-9007 10.1103/PhysRevLett.68.1480Adler, S., (2003) Phys. Rev. Lett., 91, p. 072301. , (PHENIX Collaboration), () PRLTAO 0031-9007 10.1103/PhysRevLett.91. 072301;Adams, J., (2003) Phys. Rev. Lett., 91, p. 072304. , (STAR Collaboration), () PRLTAO 0031-9007 10.1103/PhysRevLett.91.072304;Adler, C., (2003) Phys. Rev. Lett., 90, p. 082302. , (STAR Collaboration),. PRLTAO 0031-9007 10.1103/PhysRevLett.90.082302Adams, J., (2005) Phys. Rev. Lett., 95, p. 152301. , (STAR Collaboration), () PRLTAO 0031-9007 10.1103/PhysRevLett.95.152301;Aggarwal, M.M., (2010) Phys. Rev. C, 82, p. 024912. , (STAR Collaboration),. PRVCAN 0556-2813 10.1103/PhysRevC.82.024912Adams, J., (2004) Phys. Rev. Lett., 93, p. 252301. , (STAR Collaboration),. PRLTAO 0031-9007 10.1103/PhysRevLett.93.252301Poskanzer, A.M., Voloshin, S.A., (1998) Phys. Rev. C, 58, p. 1671. , PRVCAN 0556-2813 10.1103/PhysRevC.58.1671Alver, B., (2008) Phys. Rev. C, 77, p. 014906. , PRVCAN 0556-2813 10.1103/PhysRevC.77.014906Feng, A., (2008), Ph.D. thesis, Institute of Particle Physics, CCNU, (unpublished);Konzer, J., (2013), Ph.D. thesis, Purdue University, (unpublished)Agakishiev, H., (STAR Collaboration), arXiv:1010.0690Ackermann, K.H., (2003) Nucl. Instrum. Meth., A499, p. 624. , (STAR Collaboration),. NIMAER 0168-9002 10.1016/S0168-9002(02)01960-5Ackermann, K.H., (1999) Nucl. Phys. A, 661, p. 681. , (STAR Collaboration),. NUPABL 0375-9474 10.1016/S0375-9474(99)85117-3Adams, J., (2004) Phys. Rev. Lett., 92, p. 112301. , (STAR Collaboration),. PRLTAO 0031-9007 10.1103/PhysRevLett.92.112301Borghini, N., Dinh, P.M., Ollitrault, J.Y., (2000) Phys. Rev. C, 62, p. 034902. , PRVCAN 0556-2813 10.1103/PhysRevC.62.034902Adams, J., (2005) Phys. Rev. C, 72, p. 014904. , (STAR Collaboration),. PRVCAN 0556-2813 10.1103/PhysRevC.72.014904Abelev, B.I., (2009) Phys. Rev. C, 79, p. 034909. , (STAR Collaboration),. PRVCAN 0556-2813 10.1103/PhysRevC.79.034909Bielcikova, J., (2004) Phys. Rev C, 69, p. 021901. , (R) () PRVCAN 0556-2813 10.1103/PhysRevC.69.021901;Konzer, J., Wang, F., (2009) Nucl. Instrum. Meth., A606, p. 713. , NIMAER 0168-9002 10.1016/j.nima.2009.05.011Mishra, A.P., (2008) Phys. Rev. C, 77, p. 064902. , PRVCAN 0556-2813 10.1103/PhysRevC.77.064902;Alver, B., Roland, G., (2010) Phys. Rev. C, 81, p. 054905. , PRVCAN 0556-2813 10.1103/PhysRevC.81.054905Alver, B., Roland, G., (2010) Phys. Rev. C, 82, p. 039903. , 0556-2813 10.1103/PhysRevC.82.039903Xu, J., Ko, C.M., (2011) Phys. Rev. C, 84, p. 014903. , PRVCAN 0556-2813 10.1103/PhysRevC.84.014903Petersen, H., (2010) Phys. Rev. C, 82, p. 041901. , PRVCAN 0556-2813 10.1103/PhysRevC.82.041901Takahashi, J., (2009) Phys. Rev. Lett., 103, p. 242301. , PRLTAO 0031-9007 10.1103/PhysRevLett.103.242301;Andrade, R.P.G., (2012) Phys. Lett. B, 712, p. 226. , PYLBAJ 0370-2693 10.1016/j.physletb.2012.04.044;Qian, W.L., (2013) Phys. Rev. C, 87, p. 014904. , PRVCAN 0556-2813 10.1103/PhysRevC.87.014904Schenke, B., Jeon, S., Gale, C., (2011) Phys. Rev. Lett., 106, p. 042301. , PRLTAO 0031-9007 10.1103/PhysRevLett.106.042301;Qiu, Z., Heinz, U.W., (2011) Phys. Rev. C, 84, p. 024911. , PRVCAN 0556-2813 10.1103/PhysRevC.84.024911;Song, H., (2011) Phys. Rev. Lett., 106, p. 192301. , PRLTAO 0031-9007 10.1103/PhysRevLett.106.192301;Schenke, B., Jeon, S., Gale, C., (2012) Phys. Rev. C, 85, p. 024901. , PRVCAN 0556-2813 10.1103/PhysRevC.85.024901;Schenke, B., Tribedy, P., Venugopalan, R., (2012) Phys. Rev. Lett., 108, p. 252301. , PRLTAO 0031-9007 10.1103/PhysRevLett.108.252301Adare, A., (2011) Phys. Rev. Lett., 107, p. 252301. , (PHENIX Collaboration),. PRLTAO 0031-9007 10.1103/PhysRevLett.107.252301Adamczyk, L., (2013) Phys. Rev. C, 88, p. 014904. , (STAR Collaboration),. PRVCAN 0556-2813 10.1103/PhysRevC.88.014904Abelev, B.I., (2008) Phys. Rev. Lett., 101, p. 252301. , (STAR Collaboration),. PRLTAO 0031-9007 10.1103/PhysRevLett.101.252301Teaney, D., Yan, L., (2011) Phys. Rev. C, 83, p. 064904. , PRVCAN 0556-2813 10.1103/PhysRevC.83.064904Pandit, Y., (2013) J. Phys. Conf. Ser., 446, p. 012012. , (STAR Collaboration),. 1742-6596 10.1088/1742-6596/446/1/012012Ajitanand, N.N., (2005) Phys. Rev. C, 72, p. 011902. , PRVCAN 0556-2813 10.1103/PhysRevC.72.011902Agakishiev, G., (2012) Phys. Rev. C, 86, p. 064902. , (STAR Collaboration),. PRVCAN 0556-2813 10.1103/PhysRevC.86.064902Adler, C., (2002) Phys. Rev. C, 66, p. 034904. , (STAR Collaboration),. PRVCAN 0556-2813 10.1103/PhysRevC.66.034904Abelev, B.I., (2009) Phys. Rev. C, 80, p. 064912. , (STAR Collaboration), () PRVCAN 0556-2813 10.1103/PhysRevC.80.064912;Abelev, B.I., (2010) Phys. Rev. Lett., 105, p. 022301. , PRLTAO 0031-9007 10.1103/PhysRevLett.105.022301Adler, S.S., (2006) Phys. Rev. Lett., 97, p. 052301. , (PHENIX Collaboration), () PRLTAO 0031-9007 10.1103/PhysRevLett.97. 052301;Adare, A., (2008) Phys. Rev. C, 78, p. 014901. , (PHENIX Collaboration),. PRVCAN 0556-2813 10.1103/PhysRevC.78.014901Stoecker, H., (2005) Nucl. Phys. A, 750, p. 121. , NUPABL 0375-9474 10.1016/j.nuclphysa.2004.12.074;Casalderrey-Solana, J., Shuryak, E.V., Teaney, D., (2005) J. Phys. Conf. Ser., 27, p. 22. , 1742-6588 10.1088/1742-6596/27/1/003;Ruppert, J., Müller, B., (2005) Phys. Lett. B, 618, p. 123. , PYLBAJ 0370-2693 10.1016/j.physletb.2005.04.075Betz, B., (2010) Phys. Rev. Lett., 105, p. 222301. , PRLTAO 0031-9007 10.1103/PhysRevLett.105.222301;Ma, G.L., Wang, X.N., (2011) Phys. Rev. Lett., 106, p. 162301. , PRLTAO 0031-9007 10.1103/PhysRevLett.106.162301Abelev, B.I., (2009) Phys. Rev. Lett., 102, p. 052302. , (STAR Collaboration),. PRLTAO 0031-9007 10.1103/PhysRevLett.102.052302Adamczyk, L., (2014) Phys. Rev. Lett., 112, p. 122301. , (STAR Collaboration),. 10.1103/PhysRevLett.112.12230

Study of Z → llγ decays at √s = 8 TeV with the ATLAS detector

This paper presents a study of Z → llγ decays with the ATLAS detector at the Large Hadron Collider. The analysis uses a proton–proton data sample corresponding to an integrated luminosity of 20.2 fb−1 collected at a centre-ofmass energy √s = 8 TeV. Integrated fiducial cross-sections together with normalised differential fiducial cross-sections, sensitive to the kinematics of final-state QED radiation, are obtained. The results are found to be in agreement with stateof-the-art predictions for final-state QED radiation. First measurements of Z → llγ γ decays are also reported

Search for leptoquark pair production decaying into te−te¯ + or tμ−t¯μ+ in multi-lepton final states in pp collisions at √s = 13 TeV with the ATLAS detector

A search for leptoquark pair production decaying into te−te¯ + or tμ−t¯μ+ in final states with multiple leptons is presented. The search is based on a dataset of pp collisions at √s = 13 TeV recorded with the ATLAS detector during Run 2 of the Large Hadron Collider, corresponding to an integrated luminosity of 139 fb−1. Four signal regions, with the requirement of at least three light leptons (electron or muon) and at least two jets out of which at least one jet is identified as coming from a b-hadron, are considered based on the number of leptons of a given flavour. The main background processes are estimated using dedicated control regions in a simultaneous fit with the signal regions to data. No excess above the Standard Model background prediction is observed and 95% confidence level limits on the production cross section times branching ratio are derived as a function of the leptoquark mass. Under the assumption of exclusive decays into te− (tμ−), the corresponding lower limit on the scalar mixed-generation leptoquark mass mLQd mix is at 1.58 (1.59) TeV and on the vector leptoquark mass mU˜1 at 1.67 (1.67) TeV in the minimal coupling scenario and at 1.95 (1.95) TeV in the Yang–Mills scenario

Constraints on spin-0 dark matter mediators and invisible Higgs decays using ATLAS 13 TeV pp collision data with two top quarks and missing transverse momentum in the final state

This paper presents a statistical combination of searches targeting final states with two top quarks and invisible particles, characterised by the presence of zero, one or two leptons, at least one jet originating from a b-quark and missing transverse momentum. The analyses are searches for phenomena beyond the Standard Model consistent with the direct production of dark matter in pp collisions at the LHC, using 139 fb−1 of data collected with the ATLAS detector at a centre-of-mass energy of 13 TeV. The results are interpreted in terms of simplified dark matter models with a spin-0 scalar or pseudoscalar mediator particle. In addition, the results are interpreted in terms of upper limits on the Higgs boson invisible branching ratio, where the Higgs boson is produced according to the Standard Model in association with a pair of top quarks. For scalar (pseudoscalar) dark matter models, with all couplings set to unity, the statistical combination extends the mass range excluded by the best of the individual channels by 50 (25) GeV, excluding mediator masses up to 370 GeV. In addition, the statistical combination improves the expected coupling exclusion reach by 14% (24%), assuming a scalar (pseudoscalar) mediator mass of 10 GeV. An upper limit on the Higgs boson invisible branching ratio of 0.38 (0.30+0.13−0.09) is observed (expected) at 95% confidence level

Software performance of the ATLAS track reconstruction for LHC run 3

Charged particle reconstruction in the presence of many simultaneous proton–proton (pp) collisions in the LHC is a challenging task for the ATLAS experiment’s reconstruction software due to the combinatorial complexity. This paper describes the major changes made to adapt the software to reconstruct high-activity collisions with an average of 50 or more simultaneous pp interactions per bunch crossing (pileup) promptly using the available computing resources. The performance of the key components of the track reconstruction chain and its dependence on pile-up are evaluated, and the improvement achieved compared to the previous software version is quantified. For events with an average of 60 pp collisions per bunch crossing, the updated track reconstruction is twice as fast as the previous version, without significant reduction in reconstruction efficiency and while reducing the rate of combinatorial fake tracks by more than a factor two