Exploiting Robot Hand Compliance and Environmental Constraints for Edge Grasps.

This paper presents a method to grasp objects that cannot be picked directly from a table, using a soft, underactuated hand. These grasps are achieved by dragging the object to the edge of a table, and grasping it from the protruding part, performing so-called grasps. This type of approach, which uses the environment to facilitate the grasp, is named Environmental Constraint Exploitation (ECE), and has been shown to improve the robustness of grasps while reducing the planning effort.

Long-term effects after treatment with platinum compounds, cisplatin and [Pt(O,O'-acac)(γ-acac)(DMS)]: Autophagy activation in rat B50 neuroblastoma cells.

Cisplatin (cisPt), among the best known components of multi-drug front-line therapies used for the treatments of solid tumors, such as the childhood neuroblastoma, acts through DNA linking. Nevertheless, the cisPt effectiveness is compromised by the onset of severe side effects, including neurotoxicity that results in neurodegeneration, cell death, and drug-resistance. In the field of experimental oncology, aimed at overcoming cytotoxicity and chemoresistance, great efforts are devoted to the synthesis of new platinum-based drugs, such as [Pt(O,O'-acac)(γ-acac)(DMS)] (PtAcacDMS), which shows a specific reactivity with sulfur residues of enzymes involved in apoptosis.

Construction of a network describing asparagine metabolism in plants and its application to the identification of genes affecting asparagine metabolism in wheat under drought and nutritional stress.

A detailed network describing asparagine metabolism in plants was constructed using published data from Arabidopsis () maize (), wheat (), pea (), soybean (), lupin (), and other species, including animals. Asparagine synthesis and degradation is a major part of amino acid and nitrogen metabolism in plants. The complexity of its metabolism, including limiting and regulatory factors, was represented in a logical sequence in a pathway diagram built using yED graph editor software.

Sequencing of prostate cancers identifies new cancer genes, routes of progression and drug targets.

Prostate cancer represents a substantial clinical challenge because it is difficult to predict outcome and advanced disease is often fatal. We sequenced the whole genomes of 112 primary and metastatic prostate cancer samples. From joint analysis of these cancers with those from previous studies (930 cancers in total), we found evidence for 22 previously unidentified putative driver genes harboring coding mutations, as well as evidence for NEAT1 and FOXA1 acting as drivers through noncoding mutations.

Identification of cancer biomarkers of prognostic value using specific gene regulatory networks (GRN): a novel role of RAD51AP1 for ovarian and lung cancers.

To date, microarray analyses have led to the discovery of numerous individual 'molecular signatures' associated with specific cancers. However, there are serious limitations for the adoption of these multi-gene signatures in the clinical environment for diagnostic or prognostic testing as studies with more power need to be carried out. This may involve larger richer cohorts and more advanced analyses.

Integrating Gene Regulatory Networks to identify cancer-specific genes.

Consensus approaches have been widely used to identify Gene Regulatory Networks (GRNs) that are common to multiple studies. However, in this research we develop an application that semi-automatically identifies key mechanisms that are specific to a particular set of conditions. We analyse four different types of cancer to identify gene pathways unique to each of them.

Discovering study-specific gene regulatory networks.

Microarrays are commonly used in biology because of their ability to simultaneously measure thousands of genes under different conditions. Due to their structure, typically containing a high amount of variables but far fewer samples, scalable network analysis techniques are often employed. In particular, consensus approaches have been recently used that combine multiple microarray studies in order to find networks that are more robust.