Willis and the generic turn in nursing

Over the past months a series of articles in the journal have drawn attention to concerns about aspects of the quality of nursing care in the UK (Paley, 2013; Darbyshire, 2013; Rolfe and Gardner, 2014; Roberts and Ion, 2014). Jackson et al.’s (2014) recent review of the whistleblowing literature indicates that these concerns are more widespread. This view is echoed by Ion et al. (2015) who noted that student nurses from across the world encountered poor practice while on placement. In the UK this has led to a good deal of reflection with some arguing that the problem is a function of chronic under funding of health services and a workforce which is understaffed (Randall and Mckeown, 2014). For others, the issue is tied to the way in which nurses are educated. This is the view taken by Lord Willis whose Shape of Caring report was published in March (Willis, 2015)

Remarks on the k-error linear complexity of p(n)-periodic sequences

Recently the first author presented exact formulas for the number of 2ⁿn-periodic binary sequences with given 1-error linear complexity, and an exact formula for the expected 1-error linear complexity and upper and lower bounds for the expected k-error linear complexity, k >2, of a random 2ⁿn-periodic binary sequence. A crucial role for the analysis played the Chan-Games algorithm. We use a more sophisticated generalization of the Chan-Games algorithm by Ding et al. to obtain exact formulas for the counting function and the expected value for the 1-error linear complexity for pⁿn-periodic sequences over Fp, p prime. Additionally we discuss the calculation of lower and upper bounds on the k-error linear complexity of pⁿn-periodic sequences over Fp

How to determine linear complexity and kk-error linear complexity in some classes of linear recurring sequences

Several fast algorithms for the determination of the linear complexity of $d$-periodic sequences over a finite field \F_q, i.e. sequences with characteristic polynomial $f(x) = x^d-1$, have been proposed in the literature. In this contribution fast algorithms for determining the linear complexity of binary sequences with characteristic polynomial $f(x) = (x-1)^d$ for an arbitrary positive integer $d$, and $f(x) = (x^2+x+1)^{2^v}$ are presented. The result is then utilized to establish a fast algorithm for determining the $k$-error linear complexity of binary sequences with characteristic polynomial $(x^2+x+1)^{2^v}$

A survey on knowledge of stroke in Hong Kong Chinese

published_or_final_versio

Ontogeny of synaptophysin and synaptoporin in the central nervous system

The expression of the synaptic vesicle antigens synaptophysin (SY) and synaptoporin (SO) was studied in the rat striatum, which contains a nearly homogeneous population of GABAergic neurons. In situ hybridization revealed high levels of SY transcripts in the striatal anlage from embryonic day (E) 14 until birth. In contrast. SO hybridization signals were low, and no immunoreactive cell bodies were detected at these stages of development. At E 14, SY-immunoreactivity was restricted to perikarya. In later prenatal stages of development SY-immunoreactivity appeared in puncta (identified as terminals containing immunostained synaptic vesicles), fibers, thick fiber bundles and ‘patches’. In postnatal and adult animals, perikarya of striatal neurons exhibited immunoreaction for SO; ultrastructurally SO antigen was found in the Golgi apparatus and in multivesicular bodies. SO-positive boutons were rare in the striatum. In the neuropil, numerous presynaptic terminals positive for SY were observed. Our data indicate that the expression of synaptic vesicle proteins in GABAergic neurons of the striatum is developmentally regulated. Whereas SY is prevalent during embryonic development, SO is the major synaptic vesicle antigen expressed postnatally by striatal neurons which project to the globus pallidus and the substantia nigra. In contrast synapses of striatal afferents (predominantly from cortex, thalamus and substantia nigra) contain SY

Comparison of three creatinine-based equations to predict adverse outcome in a cardiovascular high-risk cohort:an investigation using the SPRINT research materials

Background:Novel creatinine-based equations have recently been proposed but their predictive performance for cardiovascular outcomes in participants at high cardiovascular risk in comparison to the established CKD-EPI 2009 equation is unknown. Method:In 9361 participants from the United States included in the randomized controlled SPRINT trial, we calculated baseline estimated glomerular filtration rate (eGFR) using the CKD-EPI 2009, CKD-EPI 2021, and EKFC equations and compared their predictive value of cardiovascular events. The statistical metric used is the net reclassification improvement (NRI) presented separately for those with and those without events. Results:During a mean follow-up of 3.1 ± 0.9 years, the primary endpoint occurred in 559 participants (6.0%). When using the CKD-EPI 2009, the CKD-EPI 2021, and the EKFC equations, the prevalence of CKD (eGFR &lt;60 ml/min/1.73 m2 or &gt;60 ml/min/1.73 m2 with an ACR ≥30 mg/g) was 37% vs. 35.3% (P = 0.02) vs. 46.4% (P &lt; 0.001), respectively. The corresponding mean eGFR was 72.5 ± 20.1 ml/min/1.73 m2 vs. 73.2 ± 19.4 ml/min/1.73 m2 (P &lt; 0.001) vs. 64.6 ± 17.4 ml/min/1.73 m2 (P &lt; 0.001). Neither reclassification according to the CKD-EPI 2021 equation [CKD-EPI 2021 vs. CKD-EPI 2009: NRIevents: −9.5% (95% confidence interval (CI) −13.0% to −5.9%); NRInonevents: 4.8% (95% CI 3.9% to 5.7%)], nor reclassification according to the EKFC equation allowed better prediction of cardiovascular events compared to the CKD-EPI 2009 equation (EKFC vs. CKD-EPI 2009: NRIevents: 31.2% (95% CI 27.5% to 35.0%); NRInonevents: −31.1% (95% CI −32.1% to −30.1%)). Conclusion. Substituting the CKD-EPI 2009 with the CKD-EPI 2021 or the EKFC equation for calculation of eGFR in participants with high cardiovascular risk without diabetes changed the prevalence of CKD but was not associated with improved risk prediction of cardiovascular events for both those with and without the event.</p

Comparison of three creatinine-based equations to predict adverse outcome in a cardiovascular high-risk cohort:an investigation using the SPRINT research materials

Background:Novel creatinine-based equations have recently been proposed but their predictive performance for cardiovascular outcomes in participants at high cardiovascular risk in comparison to the established CKD-EPI 2009 equation is unknown. Method:In 9361 participants from the United States included in the randomized controlled SPRINT trial, we calculated baseline estimated glomerular filtration rate (eGFR) using the CKD-EPI 2009, CKD-EPI 2021, and EKFC equations and compared their predictive value of cardiovascular events. The statistical metric used is the net reclassification improvement (NRI) presented separately for those with and those without events. Results:During a mean follow-up of 3.1 ± 0.9 years, the primary endpoint occurred in 559 participants (6.0%). When using the CKD-EPI 2009, the CKD-EPI 2021, and the EKFC equations, the prevalence of CKD (eGFR &lt;60 ml/min/1.73 m2 or &gt;60 ml/min/1.73 m2 with an ACR ≥30 mg/g) was 37% vs. 35.3% (P = 0.02) vs. 46.4% (P &lt; 0.001), respectively. The corresponding mean eGFR was 72.5 ± 20.1 ml/min/1.73 m2 vs. 73.2 ± 19.4 ml/min/1.73 m2 (P &lt; 0.001) vs. 64.6 ± 17.4 ml/min/1.73 m2 (P &lt; 0.001). Neither reclassification according to the CKD-EPI 2021 equation [CKD-EPI 2021 vs. CKD-EPI 2009: NRIevents: −9.5% (95% confidence interval (CI) −13.0% to −5.9%); NRInonevents: 4.8% (95% CI 3.9% to 5.7%)], nor reclassification according to the EKFC equation allowed better prediction of cardiovascular events compared to the CKD-EPI 2009 equation (EKFC vs. CKD-EPI 2009: NRIevents: 31.2% (95% CI 27.5% to 35.0%); NRInonevents: −31.1% (95% CI −32.1% to −30.1%)). Conclusion. Substituting the CKD-EPI 2009 with the CKD-EPI 2021 or the EKFC equation for calculation of eGFR in participants with high cardiovascular risk without diabetes changed the prevalence of CKD but was not associated with improved risk prediction of cardiovascular events for both those with and without the event.</p

Insights into GABA receptor signalling in TM3 Leydig cells

gamma-Aminobutyric acid (GABA) is an emerging signalling molecule in endocrine organs, since it is produced by endocrine cells and acts via GABA(A) receptors in a paracrine/autocrine fashion. Testicular Leydig cells are producers and targets for GABA. These cells express GABA(A) receptor subunits and in the murine Leydig cell line TM3 pharmacological activation leads to increased proliferation. The signalling pathway of GABA in these cells is not known in this study. We therefore attempted to elucidate details of GABA(A) signalling in TM3 and adult mouse Leydig cells using several experimental approaches. TM3 cells not only express GABA(A) receptor subunits, but also bind the GABA agonist {[}H-3] muscimol with a binding affinity in the range reported for other endocrine cells (K-d = 2.740 +/- 0.721 nM). However, they exhibit a low B-max value of 28.08 fmol/mg protein. Typical GABA(A) receptor-associated events, including Cl- currents, changes in resting membrane potential, intracellular Ca2+ or cAMP, were not measurable with the methods employed in TM3 cells, or, as studied in part, in primary mouse Leydig cells. GABA or GABA(A) agonist isoguvacine treatment resulted in increased or decreased levels of several mRNAs, including transcription factors (c-fos, hsf-1, egr-1) and cell cycle-associated genes (Cdk2, cyclin D1). In an attempt to verify the cDNA array results and because egr-1 was recently implied in Leydig cell development, we further studied this factor. RT-PCR and Western blotting confirmed a time-dependent regulation of egr-1 in TM3. In the postnatal testis egr-1 was seen in cytoplasmic and nuclear locations of developing Leydig cells, which bear GABA(A) receptors and correspond well to TM3 cells. Thus, GABA acts via an untypical novel signalling pathway in TM3 cells. Further details of this pathway remain to be elucidated. Copyright (c) 2005 S. Karger AG, Base