A randomized, double-blind, placebo-controlled phase II trial to explore the effects of a GABA-α5 NAM (basmisanil) on intellectual disability associated with Down syndrome.

Background: There are currently no pharmacological therapies to address the intellectual disability associated with Down syndrome. Excitatory/inhibitory imbalance has been hypothesized to contribute to impairments in cognitive functioning in Down syndrome. Negative modulation of the GABA-α5 receptor is proposed as a mechanism to attenuate GABAergic function and restore the excitatory/inhibitory balance.

Development of a novel duplex lateral flow test for simultaneous detection of casein and β-lactoglobulin in food.

Milk by-products such as whey and caseinate are widely used as ingredients or processing aids in food industry. However, since they could cause allergic reactions they are included in Allergen Control Plans. β-Lactoglobulin is the major whey protein and caseins are main proteins in milk.

Cysteine Mutational Studies Provide Insight into a Thiol-Based Redox Switch Mechanism of Metal and DNA Binding in FurA from Anabaena sp. PCC 7120.

Aims: The ferric uptake regulator (Fur) is the main transcriptional regulator of genes involved in iron homeostasis in most prokaryotes. FurA from Anabaena sp. PCC 7120 contains five cysteine residues, four of them arranged in two redox-active CXXC motifs.

Site-directed mutagenesis and spectral studies suggest a putative role of FurA from Anabaena sp. PCC 7120 as a heme sensor protein.

The transcriptional repressor Fur (ferric uptake regulator) is one of the most important switches regulating prokaryotic iron metabolism. Cyanobacterial FurA binds heme in the micromolar concentration range and this interaction negatively affects its in vitro DNA binding ability in a concentration-dependent manner. Using site-directed mutagenesis along with difference absorption UV-visible, circular dichroism and electronic paramagnetic resonance spectroscopies, we further analyse the nature of heme binding in FurA.

Using hybrid hierarchical K-means (HHK) clustering algorithm for protein sequence motif super-rule-tree (SRT) structure construction.

Many algorithms or techniques to discover motifs require a predefined fixed window size in advance. Because of the fixed size, these approaches often deliver a number of similar motifs simply shifted by some bases or including mismatches. To confront the mismatched motifs problem, we use the super-rule concept to construct a Super-Rule-Tree (SRT) by a modified Hybrid Hierarchical K-means (HHK) clustering algorithm, which requires no parameter set-up to identify the similarities and dissimilarities between the motifs.