Local Toxicity of Topically Administrated Thermoresponsive Systems: In Vitro Studies with In Vivo Correlation.

Thermoresponsive materials have the ability to respond to a small change in temperature-a property that makes them useful in a wide range of applications and medical devices. Although very promising, there is only little conclusive data about the cytotoxicity and tissue toxicity of these materials. This work studied the biocompatibility of three Food and Drug Administration approved thermoresponsive polymers: poly( N-isopropyl acrylamide), poly(ethylene glycol)-poly(propylene glycol)-poly(ethylene glycol) tri-block copolymer, and poly(lactic acid-co-glycolic acid) and poly(ethylene glycol) tri-block copolymer. Fibroblast NIH 3T3 and HaCaT keratinocyte cells were used for the cytotoxicity testing and a mouse model for the in vivo evaluation. In vivo results generally showed similar trends as the results seen in vitro, with all tested materials presenting a satisfactory biocompatibility in vivo. pNIPAM, however, showed the highest toxicity both in vitro and in vivo, which was explained by the release of harmful monomers and impurities. More data focusing on the biocompatibility of novel thermoresponsive biomaterials will facilitate the use of existing and future medical devices.

StemSearch: RNA search tool based on stem identification and indexing.

The discovery and functional analysis of noncoding RNA (ncRNA) systems in different organisms motivates the development of tools for aiding ncRNA research. Several tools exist that search for occurrences of a given RNA structural profile in genomic sequences. Yet, there is a need for an "RNA BLAST" tool, i.e., a tool that takes a putative functional RNA sequence as input, and efficiently searches for similar sequences in genomic databases, taking into consideration potential secondary structure features of the input query sequence. This work aims at providing such a tool. Our tool, denoted StemSearch, is based on a structural representation of an RNA sequence by its potential stems. Potential stems in genomic sequences are identified in a preprocessing stage, and indexed. A user-provided query sequence is likewise processed, and stems from the target genomes that are similar to the query stems are retrieved from the index. Then, relevant genomic regions are identified and ranked according to their similarity to the query stem-set while enforcing conservation of cross-stem topology. Experiments using RFAM families show significantly improved recall for StemSearch over BLAST, with small loss of precision. We further demonstrate our system's capability to handle eukaryotic genomes by successfully searching for members of the 7SK family in chromosome 2 of the human genome. StemSearch is freely available on the web at: http://www.cs.bgu.ac.il/∼negevcb/StemSearch.

On the support of flexible patient privacy policies in social-medical discovery.

Many new socially flavored medical services have recently emerged, utilizing the data openness and sharing through social channels. The adoption of such services by patients is still very limited, mainly due to privacy issues. Existing social-medical discovery services support only strict patient privacy policies and are not flexible enough to accommodate a wider range of privacy policy definitions. In this paper we present the IBM Medical Information and Care System (Medics) privacy-aware social-medical discovery solution that provides a highly flexible support for both fine-grained and dynamic patient privacy policies.

A unified approach for social-medical discovery.

In this paper we describe a novel social-medical discovery solution, based on an idea of social and medical data unification. Built on foundations of exploratory search technologies, the proposed discovery solution is better tailored for the social-medical discovery task. We then describe its implementation within the IBM Medics system and discuss a sample usecase which demonstrates several new social-medical discovery opportunities.

Two-component cross-linkable gels for fabrication of solid oral dosage forms.

Current three-dimensional (3D) printing techniques involve the solidification of the injected materials by means of UV irradiation, evaporation of organic solvents, or harsh heating and cooling processes. These methods limit the printing of many sensitive bio-active molecules such as proteins. We describe a novel 3D printing technique based on two complementary liquid copolymers, PEG4-PCL-SC and PEG4-PCL-NH2, that are injected in a coordinated fashion and react with each other to form a pre-designed 3D pill. Printed pills swelled about 400% over 3 h, followed by moderate disintegration. Both prednisone and bovine serum albumin were incorporated into the printed pill, but while most of the prednisone was released depending on the ratio between the two complementary pre-polymers, only 40% of the bovine serum albumin was released from the pill. This unique 3D printing apparatus can be used to produce pills at home when the required medication does not handle current production techniques well and may have other possible biomedical applications. However, before this system can be considered for pharmaceutical applications, the low printing resolution, attributable to the slow gelation kinetics and the viscosity of the pre-polymers, should be addressed.

Discovering motifs in ranked lists of DNA sequences.

Computational methods for discovery of sequence elements that are enriched in a target set compared with a background set are fundamental in molecular biology research. One example is the discovery of transcription factor binding motifs that are inferred from ChIP-chip (chromatin immuno-precipitation on a microarray) measurements. Several major challenges in sequence motif discovery still require consideration: (i) the need for a principled approach to partitioning the data into target and background sets; (ii) the lack of rigorous models and of an exact p-value for measuring motif enrichment; (iii) the need for an appropriate framework for accounting for motif multiplicity; (iv) the tendency, in many of the existing methods, to report presumably significant motifs even when applied to randomly generated data. In this paper we present a statistical framework for discovering enriched sequence elements in ranked lists that resolves these four issues. We demonstrate the implementation of this framework in a software application, termed DRIM (discovery of rank imbalanced motifs), which identifies sequence motifs in lists of ranked DNA sequences. We applied DRIM to ChIP-chip and CpG methylation data and obtained the following results. (i) Identification of 50 novel putative transcription factor (TF) binding sites in yeast ChIP-chip data. The biological function of some of them was further investigated to gain new insights on transcription regulation networks in yeast. For example, our discoveries enable the elucidation of the network of the TF ARO80. Another finding concerns a systematic TF binding enhancement to sequences containing CA repeats. (ii) Discovery of novel motifs in human cancer CpG methylation data. Remarkably, most of these motifs are similar to DNA sequence elements bound by the Polycomb complex that promotes histone methylation. Our findings thus support a model in which histone methylation and CpG methylation are mechanistically linked. Overall, we demonstrate that the statistical framework embodied in the DRIM software tool is highly effective for identifying regulatory sequence elements in a variety of applications ranging from expression and ChIP-chip to CpG methylation data. DRIM is publicly available at http://bioinfo.cs.technion.ac.il/drim.

Parallel biomolecular computation on surfaces with advanced finite automata.

A biomolecular, programmable 3-symbol-3-state finite automaton is reported. This automaton computes autonomously with all of its components, including hardware, software, input, and output being biomolecules mixed together in solution. The hardware consisted of two enzymes: an endonuclease, BbvI, and T4 DNA ligase. The software (transition rules represented by transition molecules) and the input were double-stranded (ds) DNA oligomers. Computation was carried out by autonomous processing of the input molecules via repetitive cycles of restriction, hybridization, and ligation reactions to produce a final-state output in the form of a dsDNA molecule. The 3-symbol-3-state deterministic automaton is an extension of the 2-symbol-2-state automaton previously reported, and theoretically it can be further expanded to a 37-symbol-3-state automaton. The applicability of this design was further amplified by employing surface-anchored input molecules, using the surface plasmon resonance technology to monitor the computation steps in real time. Computation was performed by alternating the feed solutions between endonuclease and a solution containing the ligase, ATP, and appropriate transition molecules. The output detection involved final ligation with one of three soluble detection molecules. Parallel computation and stepwise detection were carried out automatically with a Biacore chip that was loaded with four different inputs.

Domain analysis of the chloroplast polynucleotide phosphorylase reveals discrete functions in RNA degradation, polyadenylation, and sequence homology with exosome proteins.

The molecular mechanism of mRNA degradation in the chloroplast consists of sequential events, including endonucleolytic cleavage, the addition of poly(A)-rich sequences to the endonucleolytic cleavage products, and exonucleolytic degradation. In spinach chloroplasts, the latter two steps of polyadenylation and exonucleolytic degradation are performed by the same phosphorolytic and processive enzyme, polynucleotide phosphorylase (PNPase). An analysis of its amino acid sequence shows that the protein is composed of two core domains related to RNase PH, two RNA binding domains (KH and S1), and an alpha-helical domain. The amino acid sequence and domain structure is largely conserved between bacteria and organelles. To define the molecular mechanism that controls the two opposite activities of this protein in the chloroplast, the ribonuclease, polymerase, and RNA binding properties of each domain were analyzed. The first core domain, which was predicted to be inactive in the bacterial enzymes, was active in RNA degradation but not in polymerization. Surprisingly, the second core domain was found to be active in degrading polyadenylated RNA only, suggesting that nonpolyadenylated molecules can be degraded only if tails are added, apparently by the same protein. The poly(A) high-binding-affinity site was localized to the S1 domain. The complete spinach chloroplast PNPase, as well as versions containing the core domains, complemented the cold sensitivity of an Escherichia coli PNPase-less mutant. Phylogenetic analyses of the two core domains showed that the two domains separated very early, resulting in the evolution of the bacterial and organelle PNPases and the exosome proteins found in eukaryotes and some archaea.