Prenatal Exome Sequencing Analysis in Fetuses with Various Ultrasound Findings.

Objectives: To evaluate the use of Exome Sequencing (ES) for the detection of genome-wide Copy Number Variants (CNVs) and the frequency of SNVs-InDels in selected genes related to developmental disorders in a cohort of consecutive pregnancies undergoing invasive diagnostic procedures for minor or simple ultrasound findings with no indication of ES.

Methods: Women undergoing invasive diagnostic testing (chorionic villus sampling or amniocentesis) for QF-PCR and chromosomal microarray analysis (CMA) due to prenatal ultrasound findings without an indication for ES were selected over a five-month period (May-September 2021). ES was performed to compare the efficiency of genome-wide CNV detection against CMA analysis and to detect monogenic disorders.

Towards an Aspect-Oriented Design and Modelling Framework for Synthetic Biology.

Work on synthetic biology has largely used a component-based metaphor for system construction. While this paradigm has been successful for the construction of numerous systems, the incorporation of contextual design issues-either compositional, host or environmental-will be key to realising more complex applications. Here, we present a design framework that radically steps away from a purely parts-based paradigm by using aspect-oriented software engineering concepts.

Immune response and histology of humoral rejection in kidney transplantation.

The adaptive immune response forms the basis of allograft rejection. Its weapons are direct cellular cytotoxicity, identified from the beginning of organ transplantation, and/or antibodies, limited to hyperacute rejection by preformed antibodies and not as an allogenic response. This resulted in allogenic response being thought for decades to have just a cellular origin.

A Statistical Approach Reveals Designs for the Most Robust Stochastic Gene Oscillators.

The engineering of transcriptional networks presents many challenges due to the inherent uncertainty in the system structure, changing cellular context, and stochasticity in the governing dynamics. One approach to address these problems is to design and build systems that can function across a range of conditions; that is they are robust to uncertainty in their constituent components. Here we examine the parametric robustness landscape of transcriptional oscillators, which underlie many important processes such as circadian rhythms and the cell cycle, plus also serve as a model for the engineering of complex and emergent phenomena.