An Objective Assessment of Effect of Stimulants on Attention in Individuals With ADHD.

INTRODUCTION: Currently, assessing ADHD treatment response to stimulants relies on rating scales and subjective questionnaires and sometimes a CPT. Such tools fall short of objective, quantifiable measurement of effect, especially in natural settings and can result in inconsistent treatment. METHOD: We report results from two studies using a novel proof-of-concept approach. A preliminary trial of 10 individuals used a high-fidelity eye tracker; a second study of 100 individuals used webcams at the participants' homes. RESULTS: Both studies evaluated stimulant effect using reading behavior analysis, being an ADHD symptom that stimulants affect and a major symptom patients want to improve. Both showed a significant change in reading behavior related to medication state, suggesting a clear, objective measure of stimulant effect. CONCLUSION: Using ubiquitous hardware, investigators created a user-friendly treatment assessment platform where individuals can collect their own objective data within minutes in any setting where they have access to a web camera and computer.

Chirality-induced spin polarization places symmetry constraints on biomolecular interactions.

Noncovalent interactions between molecules are key for many biological processes. Necessarily, when molecules interact, the electronic charge in each of them is redistributed. Here, we show experimentally that, in chiral molecules, charge redistribution is accompanied by spin polarization. We describe how this spin polarization adds an enantioselective term to the forces, so that homochiral interaction energies differ from heterochiral ones. The spin polarization was measured by using a modified Hall effect device. An electric field that is applied along the molecules causes charge redistribution, and for chiral molecules, a Hall voltage is measured that indicates the spin polarization. Based on this observation, we conjecture that the spin polarization enforces symmetry constraints on the biorecognition process between two chiral molecules, and we describe how these constraints can lead to selectivity in the interaction between enantiomers based on their handedness. Model quantum chemistry calculations that rigorously enforce these constraints show that the interaction energy for methyl groups on homochiral molecules differs significantly from that found for heterochiral molecules at van der Waals contact and shorter (i.e., ∼0.5 kcal/mol at 0.26 nm).

hsa-miR-191 is a candidate oncogene target for hepatocellular carcinoma therapy.

Hepatocellular carcinoma (HCC) is generally a fatal disease due to a paucity of effective treatment options. The identification of oncogenic microRNAs that exert pleiotropic effects in HCC cells may offer new therapeutic targets. In this study, we have identified the human microRNA miR-191 as a potential target for HCC therapy. Inhibition of miR-191 decreased cell proliferation and induced apoptosis in vitro and significantly reduced tumor masses in vivo in an orthotopic xenograft mouse model of HCC. Additionally, miR-191 was found to be upregulated by a dioxin, a known liver carcinogen, and was found to be a regulator of a variety of cancer-related pathways. Our findings offer a preclinical proof of concept for miR-191 targeting as a rational strategy to pursue for improving HCC treatment.

Discovery of microRNAs and other small RNAs in solid tumors.

MicroRNAs (miRNAs) are ∼22-nt long, non-coding RNAs that regulate gene silencing. It is known that many human miRNAs are deregulated in numerous types of tumors. Here we report the sequencing of small RNAs (17-25 nt) from 23 breast, bladder, colon and lung tumor samples using high throughput sequencing. We identified 49 novel miRNA and miR-sized small RNAs. We further validated the expression of 10 novel small RNAs in 31 different types of blood, normal and tumor tissue samples using two independent platforms, namely microarray and RT-PCR. Some of the novel sequences show a large difference in expression between tumor and tumor-adjacent tissues, between different tumor stages, or between different tumor types. We also report the identification of novel small RNA classes in human: highly expressed small RNA derived from Y-RNA and endogenous siRNA. Finally, we identified dozens of new miRNA sequence variants that demonstrate the existence of miRNA-related SNP or post-transcriptional modifications. Our work extends the current knowledge of the tumor small RNA transcriptome and provides novel candidates for molecular biomarkers and drug targets.

MiR-92b and miR-9/9* are specifically expressed in brain primary tumors and can be used to differentiate primary from metastatic brain tumors.

A recurring challenge for brain pathologists is to diagnose whether a brain malignancy is a primary tumor or a metastasis from some other tissue. The accurate diagnosis of brain malignancies is essential for selection of proper treatment. MicroRNAs are a class of small non-coding RNA species that regulate gene expression; many exhibit tissue-specific expression and are misregulated in cancer. Using microRNA expression profiling, we found that hsa-miR-92b and hsa-miR-9/hsa-miR-9* are over-expressed, specifically in brain primary tumors, as compared to primary tumors from other tissues and their metastases to the brain. By considering the expression of only these two microRNAs, it is possible to distinguish between primary and metastatic brain tumors with very high accuracy. These microRNAs thus represent excellent biomarkers for brain primary tumors. Previous reports have found that hsa-miR-92b and hsa-miR-9/hsa-miR-9* are expressed more strongly in developing neurons and brain than in adult brain. Thus, their specific over-expression in brain primary tumors supports a functional role for these microRNAs or a link between neuronal stem cells and brain tumorigenesis.

Occurrence of protein structure elements in conserved sequence regions.

BACKGROUND: Conserved protein sequence regions are extremely useful for identifying and studying functionally and structurally important regions. By means of an integrated analysis of large-scale protein structure and sequence data, structural features of conserved protein sequence regions were identified. RESULTS: Helices and turns were found to be underrepresented in conserved regions, while strands were found to be overrepresented. Similar numbers of loops were found in conserved and random regions. CONCLUSION: These results can be understood in light of the structural constraints on different secondary structure elements, and their role in protein structural stabilization and topology. Strands can tolerate fewer sequence changes and nonetheless keep their specific shape and function. They thus tend to be more conserved than helices, which can keep their shape and function with more changes. Loop behavior can be explained by the presence of both constrained and freely changing loops in proteins. Our detailed statistical analysis of diverse proteins links protein evolution to the biophysics of protein thermodynamic stability and folding. The basic structural features of conserved sequence regions are also important determinants of protein structure motifs and their function.

Using an alignment of fragment strings for comparing protein structures.

MOTIVATION: Most methods that are used to compare protein structures use three-dimensional (3D) structural information. At the same time, it has been shown that a 1D string representation of local protein structure retains a degree of structural information. This type of representation can be a powerful tool for protein structure comparison and classification, given the arsenal of sequence comparison tools developed by computational biology. However, in order to do so, there is a need to first understand how much information is contained in various possible 1D representations of protein structure. RESULTS: Here we describe the use of a particular structure fragment library, denoted here as KL-strings, for the 1D representation of protein structure. Using KL-strings, we develop an infrastructure for comparing protein structures with a 1D representation. This study focuses on the added value gained from such a description. We show the new local structure language adds resolution to the traditional three-state (helix, strand and coil) secondary structure description, and provides a high degree of accuracy in recognizing structural similarities when used with a pairwise alignment benchmark. The results of this study have immediate applications towards fast structure recognition, and for fold prediction and classification.

Network analysis of protein structures identifies functional residues.

Identifying active site residues strictly from protein three-dimensional structure is a difficult task, especially for proteins that have few or no homologues. We transformed protein structures into residue interaction graphs (RIGs), where amino acid residues are graph nodes and their interactions with each other are the graph edges. We found that active site, ligand-binding and evolutionary conserved residues, typically have high closeness values. Residues with high closeness values interact directly or by a few intermediates with all other residues of the protein. Combining closeness and surface accessibility identified active site residues in 70% of 178 representative structures. Detailed structural analysis of specific enzymes also located other types of functional residues. These include the substrate binding sites of acetylcholinesterases and subtilisin, and the regions whose structural changes activate MAP kinase and glycogen phosphorylase. Our approach uses single protein structures, and does not rely on sequence conservation, comparison to other similar structures or any prior knowledge. Residue closeness is distinct from various sequence and structure measures and can thus complement them in identifying key protein residues. Closeness integrates the effect of the entire protein on single residues. Such natural structural design may be evolutionary maintained to preserve interaction redundancy and contribute to optimal setting of functional sites.

New types of conserved sequence domains in DNA-binding regions of homing endonucleases.

We have identified four new types of short conserved sequence domains in homing endonucleases and related proteins. These domains are modular, appearing in various combinations. One domain includes a motif known by structure as a novel sequence-specific DNA-binding helix. Sequence similarity shows two other domains to be new types of helix-turn-helix DNA-binding domains. We term the new domains nuclease-associated modular DNA-binding domains (NUMODs).