SCAPHOID AND LUNATE CARPAL MECHANICS OVER THE SPECTRUM OF HEALTHY FUNCTION

When ligaments within the wrist are damaged, the resulting loss in range of motion and grip strength can lead to reduced earning potential and restricted ability to perform important activities of daily living. Left untreated, ligament injuries ultimately lead to arthritis and chronic pain. Surgical repair can mitigate these issues but current procedures are often non-anatomic and unable to completely restore the wrist’s complex network of ligaments. An inability to quantitatively assess wrist function clinically, both before and after surgery, limits the ability to assess the response to clinical intervention. Previous work has shown that bones within the wrist move in a similar pattern across people, but these patterns remain challenging to predict and model. In an effort to quantify and further develop the understanding of normal carpal mechanics, we performed two studies using 3D in vivo carpal bone motion analysis techniques. For the first study, we measured wrist laxity and performed CT scans of the wrist to evaluate 3D carpal bone positions. We found that through mid-range radial-ulnar deviation range of motion the scaphoid and lunate primarily flexed and extended; however, there was a significant relationship between wrist laxity and row-column behaviour. We also found that there was a significant relationship between scaphoid flexion and active radial deviation range of motion. For the second study, an analysis was performed on a publicly available database. We evaluated scapholunate relative motion over a full range of wrist positions, and found that there was a significant amount of variation in the location and orientation of the rotation axis between the two bones. Together the findings from the two studies illustrate the complexity and subject specificity of normal carpal mechanics, and should provide insights that can guide the development of anatomical wrist ligament repair surgeries that restore normal function.

Improving drug discovery using a neural networks based parallel scoring function

Virtual Screening (VS) methods can considerably aid clinical research, predicting how ligands interact with drug targets. Most VS methods suppose a unique binding site for the target, but it has been demonstrated that diverse ligands interact with unrelated parts of the target and many VS methods do not take into account this relevant fact. This problem is circumvented by a novel VS methodology named BINDSURF that scans the whole protein surface to find new hotspots, where ligands might potentially interact with, and which is implemented in massively parallel Graphics Processing Units, allowing fast processing of large ligand databases. BINDSURF can thus be used in drug discovery, drug design, drug repurposing and therefore helps considerably in clinical research. However, the accuracy of most VS methods is constrained by limitations in the scoring function that describes biomolecular interactions, and even nowadays these uncertainties are not completely understood. In order to solve this problem, we propose a novel approach where neural networks are trained with databases of known active (drugs) and inactive compounds, and later used to improve VS predictions.

Smoothing a Discrete Hazard Function for the Number of Patients Colonized with Methicillin-Resistance Staphylococcus Aureus in an Intensive Care Unit

A new method for estimating the time to colonization of Methicillin-resistant Staphylococcus Aureus (MRSA) patients is developed in this paper. The time to colonization of MRSA is modelled using a Bayesian smoothing approach for the hazard function. There are two prior models discussed in this paper: the first difference prior and the second difference prior. The second difference prior model gives smoother estimates of the hazard functions and, when applied to data from an intensive care unit (ICU), clearly shows increasing hazard up to day 13, then a decreasing hazard. The results clearly demonstrate that the hazard is not constant and provide a useful quantification of the effect of length of stay on the risk of MRSA colonization which provides useful insight.