Symptomatic hypogammaglobulinemia in infancy and childhood – clinical outcome and in vitro immune responses

BACKGROUND: Symptomatic hypogammaglobulinemia in infancy and childhood (SHIC), may be an early manifestation of a primary immunodeficiency or a maturational delay in the normal production of immunoglobulins (Ig). We aimed to evaluate the natural course of SHIC and correlate in vitro lymphoproliferative and secretory responses with recovery of immunoglobulin values and clinical resolution. METHODS: Children, older than 1 year of age, referred to our specialist clinic because of recurrent infections and serum immunoglobulin (Ig) levels 2 SD below the mean for age, were followed for a period of 8 years. Patient with any known familial, clinical or laboratory evidence of cellular immunodeficiency or other immunodeficiency syndromes were excluded from this cohort. Evaluation at 6- to 12-months intervals continued up to 1 year after resolution of symptoms. In a subgroup of patients, in vitro lymphocyte proliferation and Ig secretion in response to mitogens was performed. RESULTS: 32 children, 24 (75%) males, 8 (25%) females, mean age 3.4 years fulfilled the inclusion criteria. Clinical presentation: ENT infections 69%, respiratory 81%, diarrhea 12.5%. During follow-up, 17 (53%) normalized serum Ig levels and were diagnosed as transient hypogammaglobulinemia of infancy (THGI). THGI patients did not differ clinically or demographically from non-transient patients, both having a benign clinical outcome. In vitro Ig secretory responses, were lower in hypogammaglobulinemic, compared to normal children and did not normalize concomitantly with serum Ig's in THGI patients. CONCLUSIONS: The majority of children with SHIC in the first decade of life have THGI. Resolution of symptoms as well as normalization of Ig values may be delayed, but overall the clinical outcome is good and the clinical course benign

Benchmarking of cell type deconvolution pipelines for transcriptomics data

Many computational methods have been developed to infer cell type proportions from bulk transcriptomics data. However, an evaluation of the impact of data transformation, pre-processing, marker selection, cell type composition and choice of methodology on the deconvolution results is still lacking. Using five single-cell RNA-sequencing (scRNA-seq) datasets, we generate pseudo-bulk mixtures to evaluate the combined impact of these factors. Both bulk deconvolution methodologies and those that use scRNA-seq data as reference perform best when applied to data in linear scale and the choice of normalization has a dramatic impact on some, but not all methods. Overall, methods that use scRNA-seq data have comparable performance to the best performing bulk methods whereas semi-supervised approaches show higher error values. Moreover, failure to include cell types in the reference that are present in a mixture leads to substantially worse results, regardless of the previous choices. Altogether, we evaluate the combined impact of factors affecting the deconvolution task across different datasets and propose general guidelines to maximize its performance. Inferring cell type proportions from transcriptomics data is affected by data transformation, normalization, choice of method and the markers used. Here, the authors use single-cell RNAseq datasets to evaluate the impact of these factors and propose guidelines to maximise deconvolution performance

The use of live attenuated bacteria as a delivery system for heterologous antigens

Live attenuated mutants of several pathogenic bacteria have been exploited as potential vaccine vectors for heterologous antigen delivery by the mucosal route. Such live vectors offer the advantage of potential delivery in a single oral, intranasal or inhalational dose, stimulating both systemic and mucosal immune responses. Over the years, a range of strategies have been developed to allow controlled and stable delivery of antigens and improved immunogenicity where required. Most of these approaches have been evaluated in Salmonella vaccine vectors and, as a result, several live attenuated recombinant Salmonella vaccines are now in human clinical trials. In this review, these strategies and their use in the development of a delivery system for the Yersinia pestis V antigen are described

Loss-function learning for digital tissue deconvolution

The gene expression profile of a tissue averages the expression profiles of all cells in this tissue. Digital tissue deconvolution (DTD) addresses the following inverse problem: Given the expression profile $y$ of a tissue, what is the cellular composition $c$ of that tissue? If $X$ is a matrix whose columns are reference profiles of individual cell types, the composition $c$ can be computed by minimizing $\mathcal L(y-Xc)$ for a given loss function $\mathcal L$. Current methods use predefined all-purpose loss functions. They successfully quantify the dominating cells of a tissue, while often falling short in detecting small cell populations. Here we learn the loss function $\mathcal L$ along with the composition $c$. This allows us to adapt to application specific requirements such as focusing on small cell populations or distinguishing phenotypically similar cell populations. Our method quantifies large cell fractions as accurately as existing methods and significantly improves the detection of small cell populations and the distinction of similar cell types

The formation of Staphylococcus aureus enterotoxin in food environments and advances in risk assessment

The recent finding that the formation of staphylococcal enterotoxins in food is very different from that in cultures of pure Staphylococcus aureus sheds new light on, and brings into question, traditional microbial risk assessment methods based on planktonic liquid cultures. In fact, most bacteria in food appear to be associated with surfaces or tissues in various ways, and interaction with other bacteria through molecular signaling is prevalent. Nowadays it is well established that there are significant differences in the behavior of bacteria in the planktonic state and immobilized bacteria found in multicellular communities. Thus, in order to improve the production of high-quality, microbiologically safe food for human consumption, in situ data on enterotoxin formation in food environments are required to complement existing knowledge on the growth and survivability of S. aureus. This review focuses on enterotoxigenic S. aureus and describes recent findings related to enterotoxin formation in food environments, and ways in which risk assessment can take into account virulence behavior. An improved understanding of how environmental factors affect the expression of enterotoxins in foods will enable us to formulate new strategies for improved food safety