Development of cordycepin formulations for preclinical and clinical studies

There is extensive literature on in vivo studies with cordycepin but these studies were generally conducted without validation of the various formulations, especially in terms of the solubility of cordycepin in the dosing vehicles used. Cordycepin is a promising drug candidate in multiple therapeutic areas and there is a growing interest in studies aimed at assessing the pharmacological activity of this compound in relevant animal disease models. It is likely that many reported in vivo studies used formulations in which cordycepin was incompletely soluble. This can potentially confound the interpretation of pharmacokinetics and efficacy results. Furthermore, the presence of particles in intravenously administered suspension can cause adverse effects and should be avoided. Here we present the results from our development of simple and readily applicable formulations of cordycepin based on quantitative solubility assessment. Homogeneous solutions of cordycepin were prepared in phosphate-buffered saline (PBS) at different pH levels, suitable as formulations for both intravenously and oral administration. For the purpose of high-dose oral administration we also developed propylene glycol (PPG)-based vehicles in which cordycepin is completely soluble. The stability of the newly developed formulations was also assessed, as well the feasibility of their sterilisation by filtration. Additionally, an HPLC-UV method for the determination of cordycepin in the formulations, which may also be useful for other purposes, was developed and validated. Our study could provide useful information for improvement of future preclinical and clinical studies involving cordycepin

A feasibility study incorporating a pilot randomised controlled trial of oral feeding plus pre-treatment gastrostomy tube versus oral feeding plus as-needed nasogastric tube feeding in patients undergoing chemoradiation for head and neck cancer (TUBE trial): study protocol

Background There are 7000 new cases of head and neck squamous cell cancers (HNSCC) treated by the NHS each year. Stage III and IV HNSCC can be treated non-surgically by radio therapy (RT) or chemoradiation therapy (CRT). CRT can affect eating and drinking through a range of side effects with 90 % of patients undergoing this treatment requiring nutritional support via gastrostomy (G) or nasogastric (NG) tube feeding. Long-term dysphagia following CRT is a primary concern for patients. The effect of enteral feeding routes on swallowing function is not well understood, and the two feeding methods have, to date, not been compared to assess which leads to a better patient outcome. The purpose of this study is to explore the feasibility of conducting a randomised controlled trial (RCT) comparing these two options with particular emphasis on patient willingness to be randomised and clinician willingness to approach eligible patients. Methods/design This is a mixed methods multicentre study to establish the feasibility of a randomised controlled trial comparing oral feeding plus pre-treatment gastrostomy versus oral feeding plus as required nasogastric tube feeding in patients with HNSCC. A total of 60 participants will be randomised to the two arms of the study (1:1 ratio). The primary outcome of feasibility is a composite of recruitment (willingness to randomise and be randomised) and retention. A qualitative process evaluation investigating patient, family and friends and staff experiences of trial participation will also be conducted alongside an economic modelling exercise to synthesise available evidence and provide estimates of cost-effectiveness and value of information. Participants will be assessed at baseline (pre-randomisation), during CRT weekly, 3 months and 6 months. Discussion Clinicians are in equipoise over the enteral feeding options for patients being treated with CRT. Swallowing outcomes have been identified as a top priority for patients following treatment and this trial would inform a future larger scale RCT in this area to inform best practice

Candidate gene prioritization by network analysis of differential expression using machine learning approaches

<p>Abstract</p> <p>Background</p> <p>Discovering novel disease genes is still challenging for diseases for which no prior knowledge - such as known disease genes or disease-related pathways - is available. Performing genetic studies frequently results in large lists of candidate genes of which only few can be followed up for further investigation. We have recently developed a computational method for constitutional genetic disorders that identifies the most promising candidate genes by replacing prior knowledge by experimental data of differential gene expression between affected and healthy individuals.</p> <p>To improve the performance of our prioritization strategy, we have extended our previous work by applying different machine learning approaches that identify promising candidate genes by determining whether a gene is surrounded by highly differentially expressed genes in a functional association or protein-protein interaction network.</p> <p>Results</p> <p>We have proposed three strategies scoring disease candidate genes relying on network-based machine learning approaches, such as kernel ridge regression, heat kernel, and Arnoldi kernel approximation. For comparison purposes, a local measure based on the expression of the direct neighbors is also computed. We have benchmarked these strategies on 40 publicly available knockout experiments in mice, and performance was assessed against results obtained using a standard procedure in genetics that ranks candidate genes based solely on their differential expression levels (<it>Simple Expression Ranking</it>). Our results showed that our four strategies could outperform this standard procedure and that the best results were obtained using the <it>Heat Kernel Diffusion Ranking </it>leading to an average ranking position of 8 out of 100 genes, an AUC value of 92.3% and an error reduction of 52.8% relative to the standard procedure approach which ranked the knockout gene on average at position 17 with an AUC value of 83.7%.</p> <p>Conclusion</p> <p>In this study we could identify promising candidate genes using network based machine learning approaches even if no knowledge is available about the disease or phenotype.</p

Gender gaps in education

This chapter reviews the growing body of research in economics which concentrates on the education gender gap and its evolution, over time and across countries. The survey first focuses on gender differentials in the historical period that roughly goes from 1850 to the 1940s and documents the deep determinants of the early phase of female education expansion, including preindustrial conditions, religion, and family and kinship patterns. Next, the survey describes the stylized facts of contemporaneous gender gaps in education, from the 1950s to the present day, accounting for several alternative measures of attainment and achievement and for geographic and temporal differentiations. The determinants of the gaps are then summarized, while keeping a strong emphasis on an historical perspective and disentangling factors related to the labor market, family formation, psychological elements, and societal cultural norms. A discussion follows of the implications of the education gender gap for multiple realms, from economic growth to family life, taking into account the potential for reverse causation. Special attention is devoted to the persistency of gender gaps in the STEM and economics fields

Gender Gaps in Education

This chapter reviews the growing body of research in economics which concentrates on the education gender gap and its evolution, over time and across countries. The survey first focuses on gender differentials in the historical period that roughly goes from 1850 to the 1940s and documents the deep determinants of the early phase of female education expansion, including preindustrial conditions, religion, and family and kinship patterns. Next, the survey describes the stylized facts of contemporaneous gender gaps in education, from the 1950s to the present day, accounting for several alternative measures of attainment and achievement and for geographic and temporal differentiations. The determinants of the gaps are then summarized, while keeping a strong emphasis on an historical perspective and disentangling factors related to the labor market, family formation, psychological elements, and societal cultural norms. A discussion follows of the implications of the education gender gap for multiple realms, from economic growth to family life, taking into account the potential for reverse causation. Special attention is devoted to the persistency of gender gaps in the STEM and economics fields

Hydrothermal alteration of andesitic lava domes can lead to explosive volcanic behaviour

Dome-forming volcanoes are among the most hazardous volcanoes on Earth. Magmatic outgassing can be hindered if the permeability of a lava dome is reduced, promoting pore pressure augmentation and explosive behaviour. Laboratory data show that acid-sulphate alteration, common to volcanoes worldwide, can reduce the permeability on the sample lengthscale by up to four orders of magnitude and is the result of pore- and microfracture-filling mineral precipitation. Calculations using these data demonstrate that intense alteration can reduce the equivalent permeability of a dome by two orders of magnitude, which we show using numerical modelling to be sufficient to increase pore pressure. The fragmentation criterion shows that the predicted pore pressure increase is capable of fragmenting the majority of dome-forming materials, thus promoting explosive volcanism. It is crucial that hydrothermal alteration, which develops over months to years, is monitored at dome-forming volcanoes and is incorporated into real-time hazard assessments

Luminosity determination using Z boson production at the CMS experiment

Data Availability Statement - This manuscript has no associated data or the data will not be deposited. [Authors’ comment: Release and preser vation of data used by the CMS Collaboration as the basis for publi cations is guidedbytheCMSpolicyasstatedinhttps://cms-docdb.cern. ch/cgibin/PublicDocDB/RetrieveFile?docid=6032&filename=CMSD ataPolicyV1.2.pdf&version=2. CMS data preservation,re-use and open access policy.]The measurement of Z boson production is presented as a method to determine the integrated luminosity of CMS data sets. The analysis uses proton–proton collision data, recorded by the CMS experiment at the CERN LHC in 2017 at a center-of-mass energy of 13 TeV . Events with Z bosons decaying into a pair of muons are selected. The total number of Z bosons produced in a fiducial volume is determined, together with the identification efficiencies and correlations from the same data set, in small intervals of 20 pb-1 of integrated luminosity, thus facilitating the efficiency and rate measurement as a function of time and instantaneous luminosity. Using the ratio of the efficiency-corrected numbers of Z bosons, the precisely measured integrated luminosity of one data set is used to determine the luminosity of another. For the first time, a full quantitative uncertainty analysis of the use of Z bosons for the integrated luminosity measurement is performed. The uncertainty in the extrapolation between two data sets, recorded in 2017 at low and high instantaneous luminosity, is less than 0.5%. We show that the Z boson rate measurement constitutes a precise method, complementary to traditional methods, with the potential to improve the measurement of the integrated luminosity.SCOAP