What Qualities Are Most Important to Making a Point of Care Test Desirable for Clinicians and Others Offering Sexually Transmitted Infection Testing?

To investigate the possible effects of different levels of attributes of a point-of-care test (POCT) on sexually transmitted infection (STI) professionals' decisions regarding an ideal POCT for STI(s).An online survey was designed based on a large-scale in-depth focus discussion study among STI experts and professionals. The last section of the survey "build your own POCT" was designed by employing the discrete choice experiment approach. Practicing clinicians from two venues, STI-related international conference attendees and U.S. STD clinic clinicians were invited to participate in the survey. Conditional logistical regression modeling was used for data analysis.Overall, 256 subjects took the online survey with 218 (85%) completing it. Most of the participants were STD clinic clinicians who already used some POCTs in their practice. "The time frame required" was identified as a major barrier that currently made it difficult to use STI POCTs. Chlamydia trachomatis was the organism chosen as the top priority for a new POCT, followed by a test that would diagnose early seroconversion for HIV, and a syphilis POCT. Without regard to organism type selected, sensitivity of 90-99% was always the most important attribute to be considered, followed by a cost of $20. However, when the test platform was prioritized for early HIV seroconversion or syphilis, sensitivity was still ranked as most important, but specificity was rated second most important.STI professionals preferred C. trachomatis as the top priority for a new POCT with sensitivity over 90%, low cost, and a very short completion time

Information Transfer in the Brain: Insights from a Unified Approach

Measuring directed interactions in the brain in terms of information flow is a promising approach, mathematically treatable and amenable to encompass several methods. In this chapter we propose some approaches rooted in this framework for the analysis of neuroimaging data. First we will explore how the transfer of information depends on the network structure, showing how for hierarchical networks the information flow pattern is characterized by exponential distribution of the incoming information and a fat-tailed distribution of the outgoing information, as a signature of the law of diminishing marginal returns. This was reported to be true also for effective connectivity networks from human EEG data. Then we address the problem of partial conditioning to a limited subset of variables, chosen as the most informative ones for the driver node.We will then propose a formal expansion of the transfer entropy to put in evidence irreducible sets of variables which provide information for the future state of each assigned target. Multiplets characterized by a large contribution to the expansion are associated to informational circuits present in the system, with an informational character (synergetic or redundant) which can be associated to the sign of the contribution. Applications are reported for EEG and fMRI data

A general protocol for the crystallization of membrane proteins for X-ray structural investigation

Protein crystallography is used to generate atomic resolution structures of protein molecules. These structures provide information about biological function, mechanism and interaction of a protein with substrates or effectors including DNA, RNA, cofactors or other small molecules, ions and other proteins. This technique can be applied to membrane proteins resident in the membranes of cells. To accomplish this, membrane proteins first need to be either heterologously expressed or purified from a native source. The protein has to be extracted from the lipid membrane with a mild detergent and purified to a stable, homogeneous population that may then be crystallized. Protein crystals are then used for X-ray diffraction to yield atomic resolution structures of the desired membrane protein target. Below, we present a general protocol for the growth of diffraction quality membrane protein crystals. The process of protein crystallization is highly variable, and obtaining diffraction quality crystals can require weeks to months or even years in some cases