The case for allele‐specific recognition by the TCR

There is a sharp difference in how one views TCR structure–function–behaviour dependent on whether its recognition of major histocompatibility complex‐encoded restriction elements (R) is germline selected or somatically generated. The generally accepted or Standard model is built on the assumption that recognition of R is by the V regions of the αβ TCR, which is not driven by allele specificity, whereas the competing model posits that recognition of R is allele‐specific. The establishing of allele‐specific recognition of R by the TCR would rule out the Standard model and clear the road to a consideration of a competing construct, the Tritope model. Here, the case for allele‐specific recognition (germline selected) is detailed making it obvious that the Standard model is untenable.     

Generalized,severe epidermolysis bullosa simplex caused by a Keratin 5 p.E477K mutation

Epidermolysis bullosa simplex (EBS) is a skin fragility disorder resulting from mutations of structural proteins in the epidermis. We provide a brief report of long‐term survival and reproduction in a mother with EBS due to keratin 5 (KRT5) c.1429G > A (p.E477K) mutation, which causes a particularly severe form of the disease.     

Sample size re-estimation for clinical trials with longitudinal negative binomial counts including time trends

In some diseases, such as multiple sclerosis, lesion counts obtained from magnetic resonance imaging (MRI) are used as markers of disease progression. This leads to longitudinal, and typically overdispersed, count data outcomes in clinical trials. Models for such data invariably include a number of nuisance parameters, which can be difficult to specify at the planning stage, leading to considerable uncertainty in sample size specification. Consequently, blinded sample size re-estimation procedures are used, allowing for an adjustment of the sample size within an ongoing trial by estimating relevant nuisance parameters at an interim point, without compromising trial integrity. To date, the methods available for re-estimation have required an assumption that the mean count is time-constant within patients. We propose a new modeling approach that maintains the advantages of established procedures but allows for general underlying and treatment-specific time trends in the mean response. A simulation study is conducted to assess the effectiveness of blinded sample size re-estimation methods over fixed designs. Sample sizes attained through blinded sample size re-estimation procedures are shown to maintain the desired study power without inflating the Type I error rate and the procedure is demonstrated on MRI data from a recent study in multiple sclerosis.