Nursing diagnoses of newborns with sepsis in a Neonatal Intensive Care Unit

OBJECTIVES: to elaborate the Nursing Diagnoses of newborns with sepsis in a neonatal intensive care unit and characterize the profile of the neonates and their mothers.METHOD: a cross-sectional and quantitative study, with a sample of 41 neonates. A physical examination and consultation of the hospital records were undertaken, using an instrument. The elaboration of the Nursing Diagnoses followed a process of diagnostic inference and was based on the North American Nursing Diagnosis Association 2012-2014.RESULTS: the mothers were around 25 years old, had a low average number of pre-natal consultations, and various complications during the pregnancy; and the newborns were predominantly premature and with very low birth weights. Five Nursing Diagnoses predominated, and all the neonates presented Risk of Shock and Risk of fluid volume imbalance.CONCLUSION: the Nursing Diagnoses of the neonates with sepsis can guide the formulating of specific assistential plans. The study contributes to the generation of new knowledge and found various relationships between the Nursing Diagnoses and the variables selected in the characterization of the neonates, which deserve to be elucidated in greater detail based on further research on the issue

Algorithms to predict cerebral malaria in murine models using the SHIRPA protocol

<p>Abstract</p> <p>Background</p> <p><it>Plasmodium berghei </it>ANKA infection in C57Bl/6 mice induces cerebral malaria (CM), which reproduces, to a large extent, the pathological features of human CM. However, experimental CM incidence is variable (50-100%) and the period of incidence may present a range as wide as 6-12 days post-infection. The poor predictability of which and when infected mice will develop CM can make it difficult to determine the causal relationship of early pathological changes and outcome. With the purpose of contributing to solving these problems, algorithms for CM prediction were built.</p> <p>Methods</p> <p>Seventy-eight <it>P. berghei</it>-infected mice were daily evaluated using the primary SHIRPA protocol. Mice were classified as CM+ or CM- according to development of neurological signs on days 6-12 post-infection. Logistic regression was used to build predictive models for CM based on the results of SHIRPA tests and parasitaemia.</p> <p>Results</p> <p>The overall CM incidence was 54% occurring on days 6-10. Some algorithms had a very good performance in predicting CM, with the area under the receiver operator characteristic (_auROC) curve ≥ 80% and positive predictive values (PV+) ≥ 95, and correctly predicted time of death due to CM between 24 and 72 hours before development of the neurological syndrome (_auROC = 77-93%; PV+ = 100% using high cut off values). Inclusion of parasitaemia data slightly improved algorithm performance.</p> <p>Conclusion</p> <p>These algorithms work with data from a simple, inexpensive, reproducible and fast protocol. Most importantly, they can predict CM development very early, estimate time of death, and might be a valuable tool for research using CM murine models.</p

Genetic characterization of morphologically variant strains of Paracoccidioides brasiliensis

Molecular characterization of Paracoccidioides brasiliensis variant strains that had been preserved under mineral oil for decades was carried out by random amplified polymorphic DNA analysis (RAPD). On P. brasiliensis variants in the transitional phase and strains with typical morphology, RAPD produced reproducible polymorphic amplification products that differentiated them. A dendrogram based on the generated RAPD patterns placed the 14 P. brasiliensis strains into five groups with similarity coefficients of 72%. A high correlation between the genotypic and phenotypic characteristics of the strains was observed. A 750 bp-RAPD fragment found only in the wild-type phenotype strains was cloned and sequenced. Genetic similarity analysis using BLASTx suggested that this RAPD marker represents a putative domain of a hypothetical flavin-binding monooxygenase (FMO)-like protein of Neurospora crassa.FiocruzBritish Council Progra

Measurement of the t(t)over-bar production cross section in the dilepton channel in pp collisions at √s=8 TeV

The top-antitop quark (t (t) over bar) production cross section is measured in proton-proton collisions at root s = 8 TeV with the CMS experiment at the LHC, using a data sample corresponding to an integrated luminosity of 5.3 fb(-1). The measurement is performed by analysing events with a pair of electrons or muons, or one electron and one muon, and at least two jets, one of which is identified as originating from hadronisation of a bottom quark. The measured cross section is 239 +/- 2 (stat.) +/- 11 (syst.) +/- 6 (lum.) pb, for an assumed top-quark mass of 172.5 GeV, in agreement with the prediction of the standard model

Limits on WWZ and WW\gamma couplings from p\bar{p}\to e\nu jj X events at \sqrt{s} = 1.8 TeV

We present limits on anomalous WWZ and WW-gamma couplings from a search for WW and WZ production in p-bar p collisions at sqrt(s)=1.8 TeV. We use p-bar p -> e-nu jjX events recorded with the D0 detector at the Fermilab Tevatron Collider during the 1992-1995 run. The data sample corresponds to an integrated luminosity of 96.0+-5.1 pb^(-1). Assuming identical WWZ and WW-gamma coupling parameters, the 95% CL limits on the CP-conserving couplings are -0.33<lambda<0.36 (Delta-kappa=0) and -0.43<Delta-kappa<0.59 (lambda=0), for a form factor scale Lambda = 2.0 TeV. Limits based on other assumptions are also presented.Comment: 11 pages, 2 figures, 2 table