R v Dr Priya Ramnath

The recent conviction at Birmingham Crown Court of Dr Priya Ramnath for the manslaughter of a patient under her care at Stafford District General Hospital, occurs no less than a decade after the original inquest into the victim’s death recorded a verdict of death by natural causes. This verdict was later overturned following a second inquest in 2004 and substituted for a verdict of unlawful killing...

Increased expression of phosphorylated forms of RNA-dependent protein kinase and eukaryotic initiation factor 2 alpha may signal skeletal muscle atrophy in weight-losing cancer patients

Previous studies suggest that the activation (autophosphorylation) of dsRNA-dependent protein kinase (PKR) can stimulate protein degradation, and depress protein synthesis in skeletal muscle through phosphorylation of the translation initiation factor 2 (eIF2) on the alpha-subunit. To understand whether these mediators are important in muscle wasting in cancer patients, levels of the phospho forms of PKR and eIF2alpha have been determined in rectus abdominus muscle of weight losing patients with oesophago-gastric cancer, in comparison with healthy controls. Levels of both phospho PKR and phospho eIF2alpha were significantly enhanced in muscle of cancer patients with weight loss irrespective of the amount and there was a linear relationship between phosphorylation of PKR and phosphorylation of eIF2alpha (correlation coefficient 0.76, P=0.005). This suggests that phosphorylation of PKR led to phosphorylation of eIF2alpha. Myosin levels decreased as the weight loss increased, and there was a linear relationship between myosin expression and the extent of phosphorylation of eIF2alpha (correlation coefficient 0.77, P=0.004). These results suggest that phosphorylation of PKR may be an important initiator of muscle wasting in cancer patients.

Statnote 14: the correlation of two variables (Pearson's 'r')

Pearson's correlation coefficient (‘r���) is one of the most widely used of all statistics. Nevertheless, care needs to be used in interpreting the results because with large numbers of observations, quite small values of ‘r��� become significant and the X variable may only account for a small proportion of the variance in Y. Hence, ‘r squared’ should always be calculated and included in a discussion of the significance of ‘r���. The use of ‘r��� also assumes that the data follow a bivariate normal distribution (see Statnote 17) and this assumption should be examined prior to the study. If the data do not conform to such a distribution, the use of a non-parametric correlation coefficient should be considered. A significant correlation should not be interpreted as indicating ‘causation’ especially in observational studies, in which the two variables may be correlated because of their mutual correlations with other confounding variables.

The effect of R-plasmid RP1 on the properties of Proteus mirabilis

A clinical isolate of Proteus mirabilis containing R-plasmid RP1 (R+ cells), grown in both iron- and carbon- limited chemically defined media in mixed culture with plasmid-free (R- cells), did not disappear as expected, due to adherence of R+ cells to the wall of the chemostat vessel. Plasmid RP1 promoted adherence to glass and to medical prostheses. The hydrophobicity and surface charge of R+ cells were different from those of R- cells and both factors may contribute to the adherence of R+ cells to surfaces. The mode of cultivation of the cells, whether batch or continuous culture, were also found to affect the result. Antibodies raised against homologous cells increased the surface hydrophobicity of both R+ and R- cells and eliminated the differences between them. Results for surface hydrophobicity varied with the method used for measuring it. R+ cells were more sensitive than R- cells to tbe bacteridical action of normal serum and whole blood and to phagocytosis as measured by chemiluminescence. No clear differences were revealed in the protein antigens of R+ and R- cells by both SDS PAGE gels and immunoblots reacted with homologous antibodies. However, lectins revealed differences in the sugars exposed on the cell surfaces. Chemical analysis of R&43 and R- cells also revealed differences in the content of 2-keto-3-deoxy-D-manno-2-octulosonate, lipopolysaccharide and total fatty acids, when cells were grown in media containing added iron; however, no qualitative differences in the lipopolysaccharide were found. Removal of iron from the medium was found to have considerable effects on the chemical structure of R+ cells but not of R- ones. Adhesion to prostheses and to leucocytes is discussed in the light of the results and the clinical relevance outlined with respect to the initiation of infection and the association of virulence with antibiotic resistance.

Productivity in China's high technology industry:regional heterogeneity and R&D

This paper analyzes the impact of Research and Development (R&D) on the productivity of China's high technology industry. In order to capture important differences in the effect of R&D on output that arise from geographic and socioeconomic differences across three major regions in China, we use a novel semiparametric approach that allows us to model heterogeneities across provinces and time. Using a unique provincial level panel dataset spanning the period 2000–2007, we find that the impact of R&D on output varies substantially in terms of magnitude and significance across different regions. Results show that the eastern region benefits the most from R&D investments, however it benefits the least from technical progress, while the western region benefits the least from R&D investments, but enjoys the highest benefits from technical progress. The central region benefits from R&D investments more than the western region and benefits from technical progress more than the eastern region. Our results suggest that R&D investments would significantly increase output in both the eastern and central regions, however technical progress in the central region may further compound the effects of R&D on output within the region.

The nitric oxide-donating pravastatin derivative, NCX 6550 [(1S-[1α(βS*, δS*), 2α, 6α, 8β-(R*), 8aα]]-1,2,6,7,8,8a-hexahydro-β, δ, 6-trihydroxy-2-methyl-8-(2-methyl-1-oxobutoxy)-1-naphtalene-heptanoic acid 4-(nitrooxy)butyl ester)], reduces splenocyte adhesion and reactive oxygen species generation in normal and atherosclerotic mice

Statins possess anti-inflammatory effects that may contribute to their ability to slow atherogenesis, whereas nitric oxide (NO) also influences inflammatory cell adhesion. This study aimed to determine whether a novel NO-donating pravastatin derivative, NCX 6550 [(1S-[1∝(ßS*,dS*),2∝,6a∝,8ß-(R*),8a∝]]-1,2,6,7,8,8a-hexahydro-ß,δ,6-trihydroxy-2-methyl-8-(2-methyl-1-oxobutoxy)-1-naphthalene-heptanoic acid 4-(nitrooxy)butyl ester)], has greater anti-inflammatory properties compared with pravastatin in normal and atherosclerotic apolipoprotein E receptor knockout (ApoE-/-) mice. C57BL/6 and ApoE-/- mice were administered pravastatin (40 mg/kg), NCX 6550 (48.5 mg/kg), or vehicle orally for 5 days. Ex vivo studies assessed splenocyte adhesion to arterial segments and splenocyte reactive oxygen species (ROS) generation. NCX 6550 significantly reduced splenocyte adhesion to artery segments in both C57BL/6 (8.8 ± 1.9% versus 16.6 ± 6.7% adhesion; P < 0.05) and ApoE-/- mice (9.3 ± 2.9% versus 23.4 ± 4.6% adhesion; P < 0.05) concomitant with an inhibition of endothelial intercellular adhesion molecule-1 expression. NCX 6550 also significantly reduced phorbol 12-myristate 13-acetate-induced ROS production that was enhanced in isolated ApoE-/- splenocytes. Conversely, pravastatin had no significant effects on adhesion in normal or ApoE-/- mice but reduced the enhanced ROS production from ApoE-/- splenocytes. In separate groups of ApoE-/- mice, NCX 6550 significantly enhanced endothelium-dependent relaxation to carbachol in aortic segments precon-tracted with phenylephrine (-logEC50, 6.37 ± 0.37) compared with both vehicle-treated (-logEC50, 5.81 ± 0.15; P < 0.001) and pravastatin-treated (-logEC50, 5.57 ± 0.45; P < 0.05) mice. NCX 6550 also significantly reduced plasma monocyte chemoattractant protein-1 levels (648.8 pg/ml) compared with both vehicle (1191.1 pg/ml; P < 0.001) and pravastatin (847 ± 71.0 pg/ml; P < 0.05) treatment. These data show that NCX 6550 exerts superior anti-inflammatory actions compared with pravastatin, possibly through NO-related mechanisms.

Public R&D policies and private R&D investment:a survey of the empirical evidence

The importance of R&D investment in explaining economic growth is well documented in the literature. Policies by modern governments increasingly recognise the benefits of supporting R&D investment. Government funding has, however, become an increasingly scarce resource in times of financial crisis and economic austerity. Hence, it is important that available funds are used and targeted effectively. This paper offers the first systematic review and critical discussion of what the R&D literature has to say currently about the effectiveness of major public R&D policies in increasing private R&D investment. Public policies are considered within three categories, R&D tax credits and direct subsidies, support of the university research system and the formation of high-skilled human capital, and support of formal R&D cooperations across a variety of institutions. Crucially, the large body of more recent literature observes a shift away from the earlier findings that public subsidies often crowd-out private R&D to finding that subsidies typically stimulate private R&D. Tax credits are also much more unanimously than previously found to have positive effects. University research, high-skilled human capital, and R&D cooperation also typically increase private R&D. Recent work indicates that accounting for non-linearities is one area of research that may refine existing results. © 2014 John Wiley & Sons Ltd.

A Bayesian neural network algorithm identifies patients in whom post-EVAR surveillance may be unnecessary

Lifelong surveillance is not cost-effective after endovascular aneurysm repair (EVAR), but is required to detect aortic complications which are fatal if untreated (type 1/3 endoleak, sac expansion, device migration). Aneurysm morphology determines the probability of aortic complications and therefore the need for surveillance, but existing analyses have proven incapable of identifying patients at sufficiently low risk to justify abandoning surveillance. This study aimed to improve the prediction of aortic complications, through the application of machine-learning techniques. Patients undergoing EVAR at 2 centres were studied from 2004–2010. Aneurysm morphology had previously been studied to derive the SGVI Score for predicting aortic complications. Bayesian Neural Networks were designed using the same data, to dichotomise patients into groups at low- or high-risk of aortic complications. Network training was performed only on patients treated at centre 1. External validation was performed by assessing network performance independently of network training, on patients treated at centre 2. Discrimination was assessed by Kaplan-Meier analysis to compare aortic complications in predicted low-risk versus predicted high-risk patients. 761 patients aged 75 +/− 7 years underwent EVAR in 2 centres. Mean follow-up was 36+/− 20 months. Neural networks were created incorporating neck angu- lation/length/diameter/volume; AAA diameter/area/volume/length/tortuosity; and common iliac tortuosity/diameter. A 19-feature network predicted aor- tic complications with excellent discrimination and external validation (5-year freedom from aortic complications in predicted low-risk vs predicted high-risk patients: 97.9% vs. 63%; p < 0.0001). A Bayesian Neural-Network algorithm can identify patients in whom it may be safe to abandon surveillance after EVAR. This proposal requires prospective study.

Do R&D strategies in high-tech sectors differ from those in low-tech sectors? An alternative approach to testing the pooling assumption

Most studies investigating the determinants of R&D investment consider pooled estimates. However, if the parameters are heterogeneous, pooled coefficients may not provide reliable estimates of individual industry effects. Hence pooled parameters may conceal valuable information that may help target government tools more efficiently across heterogeneous industries. There is little evidence to date on the decomposition of the determinants of R&D investment by industry. Moreover, the existing work does not distinguish between those R&D determinants for which pooling may be valid and those for which it is not. In this paper, we test the pooling assumption for a panel of manufacturing industries and find that pooling is valid only for output fluctuations, adjustment costs and interest rates. Implementing the test results into our model, we find government funding is significant only for low-tech R&D. Foreign R&D and skilled labour matter only in high-tech sectors. These results suggest important implications for R&D policy.

The determinants of R&D investment: A survey of the empirical research

This paper offers an extensive survey and a critical discussion of the empirical literature on the driving factors of R&D. These factors are subsumed under five broad types. The paper first summarises the key predictions from theory regarding each type's R&D effect. It then examines for which factors differences in the theoretical predictions can also be found in empirical studies, and for which factors the empirical evidence is more unanimous. As the focus is on the empirical literature, methodological issues are also highlighted. The major factor types identified in the literature are, individual firm or industry characteristics, particularly internal finance and sales; competition in product markets; R&D tax credits and subsidies; location and resource related factors, such as spillovers from university research within close geographic proximity, membership of a research joint venture and cooperation with research centres, and the human capital embodied in knowledge workers; and spillovers from foreign R&D. Although on balance there is a consensus regarding the R&D effects of most factors, there is also variation in results. Recent work suggests that accounting for non-linearities is one area of research that may explain and encompass contradictory findings.