Modification of β-Sheet Forming Peptide Hydrophobic Face: Effect on Self-Assembly and Gelation

β-Sheet forming peptides have attracted significant interest for the design of hydrogels for biomedical applications. One of the main challenges is the control and understanding of the correlations between peptide molecular structure, the morphology, and topology of the fiber and network formed as well as the macroscopic properties of the hydrogel obtained. In this work, we have investigated the effect that functionalizing these peptides through their hydrophobic face has on their self-assembly and gelation. Our results show that the modification of the hydrophobic face results in a partial loss of the extended β-sheet conformation of the peptide and a significant change in fiber morphology from straight to kinked. As a consequence, the ability of these fibers to associate along their length and form large bundles is reduced. These structural changes (fiber structure and network topology) significantly affect the mechanical properties of the hydrogels (shear modulus and elasticity)

Mathematical modelling long-term effects of replacing Prevnar7 with Prevnar13 on invasive pneumococcal diseases in England and Wales

England and Wales recently replaced the 7-valent pneumococcal conjugate vaccine (PCV7) with its 13-valent equivalent (PCV13), partly based on projections from mathematical models of the long-term impact of such a switch compared to ceasing pneumococcal conjugate vaccination altogether. A compartmental deterministic model was used to estimate parameters governing transmission of infection and competition between different groups of pneumococcal serotypes prior to the introduction of PCV13. The best-fitting parameters were used in an individual based model to describe pneumococcal transmission dynamics and effects of various options for the vaccination programme change in England and Wales. A number of scenarios were conducted using (i) different assumptions about the number of invasive pneumococcal disease cases adjusted for the increasing trend in disease incidence prior to PCV7 introduction in England and Wales, and (ii) a range of values representing serotype replacement induced by vaccination of the additional six serotypes in PCV13. Most of the scenarios considered suggest that ceasing pneumococcal conjugate vaccine use would cause an increase in invasive pneumococcal disease incidence, while replacing PCV7 with PCV13 would cause an overall decrease. However, the size of this reduction largely depends on the level of competition induced by the additional serotypes in PCV13. The model estimates that over 20 years of PCV13 vaccination, around 5000–62000 IPD cases could be prevented compared to stopping pneumococcal conjugate vaccination altogether. Despite inevitable uncertainty around serotype replacement effects following introduction of PCV13, the model suggests a reduction in overall invasive pneumococcal disease incidence in all cases. Our results provide useful evidence on the benefits of PCV13 to countries replacing or considering replacing PCV7 with PCV13, as well as data that can be used to evaluate the cost-effectiveness of such a switch

Cellulosomics, a gene-centric approach to investigating the intraspecific diversity and adaptation of Ruminococcus flavefaciens within the rumen

Peer reviewedPublisher PD

Value of information methods to design a clinical trial in a small population to optimise a health economic utility function

Background: Most confirmatory randomised controlled clinical trials (RCTs) are designed with specified power, usually 80% or 90%, for a hypothesis test conducted at a given significance level, usually 2.5% for a one-sided test. Approval of the experimental treatment by regulatory agencies is then based on the result of such a significance test with other information to balance the risk of adverse events against the benefit of the treatment to future patients. In the setting of a rare disease, recruiting sufficient patients to achieve conventional error rates for clinically reasonable effect sizes may be infeasible, suggesting that the decision-making process should reflect the size of the target population. Methods: We considered the use of a decision-theoretic value of information (VOI) method to obtain the optimal sample size and significance level for confirmatory RCTs in a range of settings. We assume the decision maker represents society. For simplicity we assume the primary endpoint to be normally distributed with unknown mean following some normal prior distribution representing information on the anticipated effectiveness of the therapy available before the trial. The method is illustrated by an application in an RCT in haemophilia A. We explicitly specify the utility in terms of improvement in primary outcome and compare this with the costs of treating patients, both financial and in terms of potential harm, during the trial and in the future. Results: The optimal sample size for the clinical trial decreases as the size of the population decreases. For non-zero cost of treating future patients, either monetary or in terms of potential harmful effects, stronger evidence is required for approval as the population size increases, though this is not the case if the costs of treating future patients are ignored. Conclusions: Decision-theoretic VOI methods offer a flexible approach with both type I error rate and power (or equivalently trial sample size) depending on the size of the future population for whom the treatment under investigation is intended. This might be particularly suitable for small populations when there is considerable information about the patient population

Immune Modulation by Schistosoma mansoni Antigens in NOD Mice: Effects on Both Innate and Adaptive Immune Systems

We have shown that Schistosoma mansoni egg soluble antigen (SEA) prevents diabetes in the nonobese diabetic (NOD) mouse inducing functional changes in antigen presenting cells (APCs) and expanding T helper (Th) 2 and regulatory T cell (Treg) responses. A Th2 response to S. mansoni infection or its antigens is key to both the establishment of tolerance and successfully reproduction in the host. More recently we demonstrated that SEA treatment upregulates bioactive TGFβ on T cells with consequent expansion of Foxp3+ Tregs, and these cells might be important in SEA-mediated diabetes prevention together with Th2 cells. In this study we profile further the phenotypic changes that SEA induces on APCs, with particular attention to cytokine expression and markers of macrophage alternative activation. Our studies suggest that TGFβ from T cells is important not just for Treg expansion but also for the successful Th2 response to SEA, and therefore, for diabetes prevention in the NOD mouse

Approaches to sample size calculation for clinical trials in rare diseases

We discuss 3 alternative approaches to sample size calculation: traditional sample size calculation based on power to show a statistically significant effect, sample size calculation based on assurance, and sample size based on a decision-theoretic approach. These approaches are compared head-to-head for clinical trial situations in rare diseases. Specifically, we consider 3 case studies of rare diseases (Lyell disease, adult-onset Still disease, and cystic fibrosis) with the aim to plan the sample size for an upcoming clinical trial. We outline in detail the reasonable choice of parameters for these approaches for each of the 3 case studies and calculate sample sizes. We stress that the influence of the input parameters needs to be investigated in all approaches and recommend investigating different sample size approaches before deciding finally on the trial size. Highly influencing for the sample size are choice of treatment effect parameter in all approaches and the parameter for the additional cost of the new treatment in the decision-theoretic approach. These should therefore be discussed extensively

Does the low prevalence affect the sample size of interventional clinical trials of rare diseases? An analysis of data from the aggregate analysis of clinicaltrials.gov

Background Clinical trials are typically designed using the classical frequentist framework to constrain type I and II error rates. Sample sizes required in such designs typically range from hundreds to thousands of patients which can be challenging for rare diseases. It has been shown that rare disease trials have smaller sample sizes than non-rare disease trials. Indeed some orphan drugs were approved by the European Medicines Agency based on studies with as few as 12 patients. However, some studies supporting marketing authorisation included several hundred patients. In this work, we explore the relationship between disease prevalence and other factors and the size of interventional phase 2 and 3 rare disease trials conducted in the US and/or EU. We downloaded all clinical trials from Aggregate Analysis of ClinialTrials.gov (AACT) and identified rare disease trials by cross-referencing MeSH terms in AACT with the list from Orphadata. We examined the effects of prevalence and phase of study in a multiple linear regression model adjusting for other statistically significant trial characteristics. Results Of 186941 ClinicalTrials.gov trials only 1567 (0.8%) studied a single rare condition with prevalence information from Orphadata. There were 19 (1.2%) trials studying disease with prevalence <1/1,000,000, 126 (8.0%) trials with 1–9/1,000,000, 791 (50.5%) trials with 1–9/100,000 and 631 (40.3%) trials with 1–5/10,000. Of the 1567 trials, 1160 (74%) were phase 2 trials. The fitted mean sample size for the rarest disease (prevalence <1/1,000,000) in phase 2 trials was the lowest (mean, 15.7; 95% CI, 8.7–28.1) but were similar across all the other prevalence classes; mean, 26.2 (16.1–42.6), 33.8 (22.1–51.7) and 35.6 (23.3–54.3) for prevalence 1–9/1,000,000, 1–9/100,000 and 1–5/10,000, respectively. Fitted mean size of phase 3 trials of rarer diseases, <1/1,000,000 (19.2, 6.9–53.2) and 1–9/1,000,000 (33.1, 18.6–58.9), were similar to those in phase 2 but were statistically significant lower than the slightly less rare diseases, 1–9/100,000 (75.3, 48.2–117.6) and 1-5/10,000 (77.7, 49.6–121.8), trials. Conclusions We found that prevalence was associated with the size of phase 3 trials with trials of rarer diseases noticeably smaller than the less rare diseases trials where phase 3 rarer disease (prevalence <1/100,000) trials were more similar in size to those for phase 2 but were larger than those for phase 2 in the less rare disease (prevalence ≥1/100,000) trials

Using mentoring to improve the foundation placement in psychiatry: review of literature and a practical example

In the past few years, mentoring in clinical settings has attracted the attention of medical educators, clinicians, managers, and policy makers. Most of the Royal Colleges of medical and surgical specialities have some form of mentoring schemes and various regional divisions of Health Education England support mentoring and coaching in the workplace. Despite the importance of this topic and the great need to provide more support to doctors in recent times, there is a paucity of literature on examples of mentoring schemes in clinical settings and practicalities of setting up such schemes in hospitals. This paper describes the implementation of a mentoring scheme in a large mental health trust in the UK to support junior doctors and the issues involved in creating such scheme. We hope that this article will be useful to clinicians who would like to start similar schemes in their workplace