New drug targets in atopic dermatitis

Atopic dermatitis (AD) is a chronic inflammatory skin disorder characterized by eczematous skin lesions, pruritus and typical histopathological features. T cells are thought to play a key role, but B cells might also participate in the pathogenesis of AD. In two investigator-initiated pilot studies, we studied the effects of B cell depletion by monoclonal anti-CD20 antibody therapy or a reduction of activated T cells by LFA3-IgG fusion protein on moderate-to-severe AD. All patients treated with either rituximab or alefacept showed an improvement of their skin symptoms with a sustained effect after treatment. In both studies, histological alterations, such as spongiosis, acanthosis and dermal infiltrate, including T and B cell numbers, dramatically improved and the expression of IL-5 and IL-13 was reduced after therapy. Upon rituximab therapy, allergen-specific IgE levels were not altered and total serum IgE levels only slightly decreased. According to recent studies, neutralizing B and T cells products such as IgE or IL-5 might be effective in subgroups of patients with AD.

Multivariate modelling of responses to conditional items: New possibilities for latent class analysis

Questionnaire data may contain missing values because certain questions do not apply to all respondents. For instance, questions addressing particular attributes of a symptom, such as frequency, triggers or seasonality, are only applicable to those who have experienced the symptom, while for those who have not, responses to these items will be missing. This missing information does not fall into the category 'missing by design', rather the features of interest do not exist and cannot be measured regardless of survey design. Analysis of responses to such conditional items is therefore typically restricted to the subpopulation in which they apply. This article is concerned with joint multivariate modelling of responses to both unconditional and conditional items without restricting the analysis to this subpopulation. Such an approach is of interest when the distributions of both types of responses are thought to be determined by common parameters affecting the whole population. By integrating the conditional item structure into the model, inference can be based both on unconditional data from the entire population and on conditional data from subjects for whom they exist. This approach opens new possibilities for multivariate analysis of such data. We apply this approach to latent class modelling and provide an example using data on respiratory symptoms (wheeze and cough) in children. Conditional data structures such as that considered here are common in medical research settings and, although our focus is on latent class models, the approach can be applied to other multivariate models.

How can computer simulations produce new knowledge?

It is often claimed that scientists can obtain new knowledge about nature by running computer simulations. How is this possible? I answer this question by arguing that computer simulations are arguments. This view parallels Norton’s argument view about thought experiments. I show that computer simulations can be reconstructed as arguments that fully capture the epistemic power of the simulations. Assuming the extended mind hypothesis, I furthermore argue that running the computer simulation is to execute the reconstructing argument. I discuss some objections and reject the view that computer simulations produce knowledge because they are experiments. I conclude by comparing thought experiments and computer simulations, assuming that both are arguments.

Localized Upregulation of a New Expansin Gene Predicts the Site of Leaf Formation in the Tomato Meristem

Expansins are extracellular proteins that increase plant cell wall extensibility in vitro and are thought to be involved in cell expansion. We showed in a previous study that administration of an exogenous expansin protein can trigger the initiation of leaflike structures on the shoot apical meristem of tomato. Here, we studied the expression patterns of two tomato expansin genes, LeExp2 and LeExp18. LeExp2 is preferentially expressed in expanding tissues, whereas LeExp18 is expressed preferentially in tissues with meristematic activity. In situ hybridization experiments showed that LeExp18 expression is elevated in a group of cells, called I1, which is the site of incipient leaf primordium initiation. Thus, LeExp18 expression is a molecular marker for leaf initiation, predicting the site of primordium formation at a time before histological changes can be detected. We propose a model for the regulation of phyllotaxis that postulates a crucial role for expansin in leaf primordium initiation.