Analysis and recognition of touching cell images based on morphological structures

Automated analysis and recognition of cell-nuclear phases using fluorescence microscopy images play an important role for high-content screening. A major task of automated imaging based high-content screening is to segment and reconstruct each cell from the touching cell images. In this paper we present new useful method for recognizing morphological structural models of touching cells, detecting segmentation points, determining the number of segmented cells in touching cell image, finding the related data of segmented cell arcs and reconstructing segmented cells. The conceptual frameworks are based on the morphological structures where a series of structural points and their morphological relationships are established. Experiment results have shown the efficient application of the new method for analysis and recognition of touching cell images of high-content screening.     

Ensembled support vector machines for human papillomavirus risk type prediction from protein secondary structures

Infection by the human papillomavirus (HPV) is regarded as the major risk factor in the development of cervical cancer. Detection of high-risk HPV is important for understanding its oncogenic mechanisms and for developing novel clinical tools for its diagnosis, treatment, and prevention. Several methods are available to predict the risk types for HPV protein sequences. Nevertheless, no tools can achieve a universally good performance for all domains, including HPV and nor do they provide confidence levels for their decisions. Here, we describe ensembled support vector machines (SVMs) to classify HPV risk types, which assign given proteins into high-, possibly high-, or low-risk type based on their confidence level. Our approach uses protein secondary structures to obtain the differential contribution of subsequences for the risk type, and SVM classifiers are combined with a simple but efficient string kernel to handle HPV protein sequences. In the experiments, we compare our approach with previous methods in accuracy and F1-score, and present the predictions for unknown HPV types, which provides promising results.     

Medical Student Dermatology Interest Groups

The Dermatology Interest Group (DIG) at the University of Texas Medical Branch (UTMB) blog (digutmb.blogspot.com) was created in 2004 with the aims of increasing communication and collaboration among students, faculty, residents, and alumni, promoting educational opportunities, and fostering the missions for which DIG was created. This blog is unique, because its frequent activity is directed toward the educational and professional needs of medical students and residents. We assessed the use of this blog by evaluating the number of blog views and audience members with relationship to the number of posts and post content over time via a tracking system. We found that there has been an increase in blog posts, views, and subscribers, as well as in areas of post content including dermatology resources/news/articles, residency applications, and resident-related information. Usefulness of such posts expands beyond UTMB students, which increases blog views and widens viewer audience. An international viewer population also was evaluated. Recorded blog viewing time was 1 minute, 57 seconds, which is more time than needed to read a post, suggesting use of additional blog information. This review of the DIG at the UTMB blog demonstrates how the use of web-based tools, in addition to the inherent benefits of medical student interests groups, are valuable resources for students, residents, and faculty.     

Analysis of unpredictable components within QRS complex using a finite-impulse-response prediction model for the diagnosis of patients with ventricular tachycardia

This study proposes a finite-impulse-response (FIR) prediction model to analyze the unpredictable intra-QRS potentials (UIQP) for identifying ventricular tachycardia patients with high-risk ventricular arrhythmias. The simulation study shows that a QRS complex including abnormal intra-QRS potentials (AIQP) has a higher UIQP and UIQP-to-QRS ratio in comparison with one without AIQP. The clinical results demonstrate that the mean UIQP-to-QRS ratios of VT patients in leads X, Y and Z were significantly larger than those of the normal subjects, and the linear and logical combination of UIQP-to-QRS ratios and ventricular late potential parameters can enhance diagnosis performance for VT patients.     

Prediction of protein functions based on function-function correlation relations

A protein function pair approach, based on protein-protein interaction (PPI) data, is proposed to predict protein functions. Randomization tests are performed on the PPI dataset, which resulted in a protein function correlation scoring value which is used to rank the relative importance of a function pair. It has been found that certain classes of protein functions tend to be correlated together. Scoring values of these correlation pairs allow us to predict the functionality of a protein given that it interacts with proteins having well-defined function annotations.The jackknife test is used to validate the function pair method. The protein function pair approach achieves a prediction sensitivity comparable to an approach using more sophisticated method. The main advantages of this approach are as follows: (i) a set of function-function correlation relations are derived and intuitive biological interpretation can be achieved, and (ii) its simplicity, only two parameters are needed.     

GaitaBase: Web-based repository system for gait analysis

The need to share gait analysis data to improve clinical decision support has been recognised since the early 1990s. GaitaBase has been established to provide a web-accessible repository system of gait analysis data to improve the sharing of data across local and international clinical and research community. It is used by several clinical and research groups across the world providing cross-group access permissions to retrieve and analyse the data. The system is useful for bench-marking and quality assurance, clinical consultation, and collaborative research. It has the capacity to increase the population sample size and improve the quality of ‘normative’ gait data. In addition the accumulated stored data may facilitate clinicians in comparing their own gait data with others, and give a valuable insight into how effective specific interventions have been for others.