Opicapone Efficacy and Tolerability in Parkinson's Disease Patients Reporting Insufficient Benefit/Failure of Entacapone

Background: Opicapone, a recently introduced catechol‐o‐methyl transferase (COMT) inhibitor has the advantage of being administered once daily, and has pharmacokinetic data to indicate it offers a greater degree of COMT inhibition than entacapone. Although trial data indicate it is non‐inferior to entacapone, there are no data to indicate whether it offers any clinical advantages. / Methods: In this audit, we present data from 57 individuals prescribed opicapone at the National Hospital for Neurology and Neurosurgery, Queen Square who had either not tolerated or reported insufficient benefit following previous prescription of entacapone. / Results: A total of 20 of 57 patients switched directly from entacapone to opicapone (“entacapone switchers”) whereas 37 of 57 patients had previously discontinued entacapone because of lack of benefit or adverse events (“entacapone failures”). A total of 21 of 57 (37%) patients stopped opicapone prior to 6 months. A total of 7 of 20 (35%) “entacapone switchers” experienced adverse events with opicapone of which 5 stopped the drug prior to the 6 month evaluation of efficacy. A total of 23 of 37 (62%) “entacapone failures” reported adverse events of which 16 stopped the drug. Among 36 of 57 (63%) patients who continued to use opicapone at 6 months, there was an improvement in OFF time of ~2 hours per day as measured by interview. / Conclusions: We conclude that opicapone can be an effective additional treatment for wearing off in Parkinson's disease (PD) in a subgroup of patients. The use of opicapone in our cohort with prior entacapone exposure, however, was associated with higher rates of adverse effects and treatment discontinuation than reported in published trial data of COMT inhibitor naïve patients

Effect of Iron Overload and Iron Deficiency on Liver Hemojuvelin Protein

INTRODUCTION: Hemojuvelin (Hjv) is a key component of the signaling cascade that regulates liver hepcidin (Hamp) expression. The purpose of this study was to determine Hjv protein levels in mice and rats subjected to iron overload and iron deficiency. METHODS: C57BL/6 mice were injected with iron (200 mg/kg); iron deficiency was induced by feeding of an iron-deficient diet, or by repeated phlebotomies. Erythropoietin (EPO)-treated mice were administered recombinant EPO at 50 U/mouse. Wistar rats were injected with iron (1200 mg/kg), or fed an iron-deficient diet. Hjv protein was determined by immunoblotting, liver samples from Hjv-/- mice were used as negative controls. Mouse plasma Hjv content was determined by a commercial ELISA kit. RESULTS: Liver crude membrane fraction from both mice and rats displayed a major Hjv-specific band at 35 kDa, and a weaker band of 20 kDa. In mice, the intensity of these bands was not changed following iron injection, repeated bleeding, low iron diet or EPO administration. No change in liver crude membrane Hjv protein was observed in iron-treated or iron-deficient rats. ELISA assay for mouse plasma Hjv did not show significant difference between Hjv+/+ and Hjv-/- mice. Liver Hamp mRNA, Bmp6 mRNA and Id1 mRNA displayed the expected response to iron overload and iron deficiency. EPO treatment decreased Id1 mRNA, suggesting possible participation of the bone morphogenetic protein pathway in EPO-mediated downregulation of Hamp mRNA. DISCUSSION: Since no differences between Hjv protein levels were found following various experimental manipulations of body iron status, the results indicate that, in vivo, substantial changes in Hamp mRNA can occur without noticeable changes of membrane hemojuvelin content. Therefore, modulation of hemojuvelin protein content apparently does not represent the limiting step in the control of Hamp gene expression

Rule-Based Forecasting: Using Judgment in Time-Series Extrapolation

Rule-Based Forecasting (RBF) is an expert system that uses judgment to develop and apply rules for combining extrapolations. The judgment comes from two sources, forecasting expertise and domain knowledge. Forecasting expertise is based on more than a half century of research. Domain knowledge is obtained in a structured way; one example of domain knowledge is managers= expectations about trends, which we call “causal forces.” Time series are described in terms of 28 conditions, which are used to assign weights to extrapolations. Empirical results on multiple sets of time series show that RBF produces more accurate forecasts than those from traditional extrapolation methods or equal-weights combined extrapolations. RBF is most useful when it is based on good domain knowledge, the domain knowledge is important, the series is well behaved (such that patterns can be identified), there is a strong trend in the data, and the forecast horizon is long. Under ideal conditions, the error for RBF’s forecasts were one-third less than those for equal-weights combining. When these conditions are absent, RBF neither improves nor harms forecast accuracy. Some of RBF’s rules can be used with traditional extrapolation procedures. In a series of studies, rules based on causal forces improved the selection of forecasting methods, the structuring of time series, and the assessment of prediction intervals

Golden Rule of Forecasting: Be Conservative

This article proposes a unifying theory, or the Golden Rule, or forecasting. The Golden Rule of Forecasting is to be conservative. A conservative forecast is consistent with cumulative knowledge about the present and the past. To be conservative, forecasters must seek out and use all knowledge relevant to the problem, including knowledge of methods validated for the situation. Twenty-eight guidelines are logically deduced from the Golden Rule. A review of evidence identified 105 papers with experimental comparisons; 102 support the guidelines. Ignoring a single guideline increased forecast error by more than two-fifths on average. Ignoring the Golden Rule is likely to harm accuracy most when the situation is uncertain and complex, and when bias is likely. Non-experts who use the Golden Rule can identify dubious forecasts quickly and inexpensively. To date, ignorance of research findings, bias, sophisticated statistical procedures, and the proliferation of big data, have led forecasters to violate the Golden Rule. As a result, despite major advances in evidence-based forecasting methods, forecasting practice in many fields has failed to improve over the past half-century

Phase structure of ceramics Al[2]O[3]-ZrW[2]O[8]

In the course of work the phase composition of the ceramic composite material Al[2]O[3] - 50 % ZrW[2]O[8] was studied. On the polished surface of the Al[2]O[3]-ZrW[2]O[8] sintered composite can be allocated three areas: dark gray matrix, white inclusions of an irregular form and spherical inclusions. The average size of spherical inclusions was equal to 15 [mu]m. The phase structure of ceramic composite was presented by trigonal modification of aluminum oxide, cubic zirconium tungstate, monoclinic modification of zirconium oxide and tungsten oxide

Physical and mechanical properties and deformation behavior of porous ceramics based on plasma chemical powders Al[2]O[3], ZrO[2](MgO)

This work investigates the behavior of porous alumina and zirconia stabilized with magnesium oxide (within the porosity range of 18% to 70%) ceramics when subjected to deformation by compression and shearing. The analysis of strain-deformation curves showed that there was a transition from a typically brittle state for relatively dense ceramics, to a pseudo-plastic one with a high rate of porosity. The values of the effective elasticity modulus, effective shear modulus and Poisson's ratio decrease with an increase in volume in the pore space of ceramics, which correlates with the appearance of plural cracking during the deformation of ceramics with a high level of porosity. There was made analysis of the nature of the destruction of ceramics with the same level of porosity. The difference in the deformation behavior of the ZrO[2]-MgO compared to the Al[2]O[3] ceramic was the fact that the transition from a typically brittle to tively dense ceramics to the pseudo -plastic at a high level of porosity is implemented with a lower level of porosity

SSR-Based Analysis of Genetic Diversity and Structure of Sweet Cherry (Prunus avium L.) from 19 Countries in Europe

Sweet cherry (Prunus avium L.) is a temperate fruit species whose production might be highly impacted by climate change in the near future. Diversity of plant material could be an option to mitigate these climate risks by enabling producers to have new cultivars well adapted to new environmental conditions. In this study, subsets of sweet cherry collections of 19 European countries were genotyped using 14 SSR. The objectives of this study were (i) to assess genetic diversity parameters, (ii) to estimate the levels of population structure, and (iii) to identify germplasm redundancies. A total of 314 accessions, including landraces, early selections, and modern cultivars, were monitored, and 220 unique SSR genotypes were identified. All 14 loci were confirmed to be polymorphic, and a total of 137 alleles were detected with a mean of 9.8 alleles per locus. The average number of alleles (N = 9.8), PIC value (0.658), observed heterozygosity (Ho = 0.71), and expected heterozygosity (He = 0.70) were higher in this study compared to values reported so far. Four ancestral populations were detected using STRUCTURE software and confirmed by Principal Coordinate Analysis (PCoA), and two of them (K1 and K4) could be attributed to the geographical origin of the accessions. A N-J tree grouped the 220 sweet cherry accessions within three main clusters and six subgroups. Accessions belonging to the four STRUCTURE populations roughly clustered together. Clustering confirmed known genealogical data for several accessions. The large genetic diversity of the collection was demonstrated, in particular within the landrace pool, justifying the efforts made over decades for their conservation. New sources of diversity will allow producers to face challenges, such as climate change and the need to develop more sustainable production systems