Color Cherenkov imaging of clinical radiation therapy

Color vision is used throughout medicine to interpret the health and status of tissue. Ionizing radiation used in radiation therapy produces broadband white lig...     

A cluster-DEE-based strategy to empower protein design

The Medical and Pharmaceutical industries have shown high interest in the precise engineering of protein hormones and enzymes that perform existing functions under a wide range of conditions. Proteins are responsible for the execution of different functions in the cell: catalysis in chemical reactions, transport and storage, regulation and recognition control. Computational Protein Design (CPD) investigates the relationship between 3-D structures of proteins and amino acid sequences and looks for all sequences that will fold into such 3-D structure. Many computational methods and algorithms have been proposed over the last years, but the problem still remains a challenge for Mathematicians, Computer Scientists, Bioinformaticians and Structural Biologists. In this article we present a new method for the protein design problem. Clustering techniques and a Dead-End-Elimination algorithm are combined with a SAT problem representation of the CPD problem in order to design the amino acid sequences. The obtained results illustrate the accuracy of the proposed method, suggesting that integrated Artificial Intelligence techniques are useful tools to solve such an intricate problem.     

External tools for collaborative medication scheduling

Medication adherence—taking medication as prescribed—is critical for successful self-care, especially among older adults. Adherence depends on developing and implementing plans for taking medications. Age-related cognitive declines that affect adherence may be mitigated using external tools that support patient-provider collaboration needed to develop these adherence plans. We tested the effectiveness of structured collaborative medication tools to support better medication planning and adherence practices. Evidence for benefits of collaborative tools has been mixed in terms of their usefulness for medication-scheduling tasks, perhaps because the tools have not been explicitly designed to support patient-provider collaboration. A total of 144 community-dwelling older adults participated in pairs and performed the role of a patient or provider in a simulated patient-provider medication-scheduling task. Each pair worked with a structured (MedTable^? and e-MedTable) or unstructured (Medcard) scheduling tool and completed four problems (2 simple and 2 complex). Performance was measured using the following: problem-solving (medication schedule) accuracy, problem-solving time, solution (schedule) optimality, tool usability, collaborative effectiveness, and subjective workload involved in creating the medication schedules. Participants using structured tools produced more accurate and optimal schedules. They also rated subjective workload as lower and thought that the structured tools were easier to use, reduced subjective workload associated with creating the schedules. There was also suggestive evidence that participants using the structured tools rated more highly the quality of their collaboration. Structured medication-scheduling tools have the potential to improve medication adherence among older adults because they support collaborative planning and reduce the cognitive load involved in creating these adherence plans.     

Measurement of periodic micro flows using micro-particle image velocimetry with phase sampling

A phase-sampling method has been developed to measure periodic flows at a high temporal resolution using conventional micro-particle image velocimetry (PIV). In this technique, the sampling is set such that each velocimetry dataset represents a unique point in phase of a periodic flow. The flow characteristics over a single cycle are reconstructed from measurements over a number of cycles, thus allowing measurement at a higher temporal resolution than the PIV system. The flow measurements were performed for AC electroosmotic flows and verified with results from the phase-locking technique. The temporal resolution is limited by the shortest camera exposure time and the time separation between laser pulses. The theoretical sampling resolution can be as low as 20 μs for 100 Hz periodic flows. A resolution of 200 μs was obtained in the experiment using 40 velocimetry datasets.     

Improved cytotoxicity testing of magnesium materials

Metallic magnesium (Mg) and its alloys are highly suitable for medical applications as biocompatible and biodegradable implant materials. Magnesium has mechanical properties similar to bone, stimulates bone regeneration, is an essential non-toxic element for the human body and degrades completely within the body environment. In consequence, magnesium is a promising candidate as implant material for orthopaedic applications. Protocols using the guideline of current ISO standards should be carefully evaluated when applying them for the characterization of the cytotoxic potential of degradable magnesium materials. For as-cast material we recommend using 10 times more extraction medium than recommended by the ISO standards to obtain reasonable results for reliable cytotoxicity rankings of degradable materials in vitro. In addition primary isolated human osteoblasts or mesenchymal stem cells should be used to test magnesium materials.