ALBERT

Description: Background: Waardenburg syndrome type I (WS1), an auditory-pigmentary genetic disorder, is caused by heterozygous loss-of-function mutations in PAX3. Abnormal physical signs such as dystopia canthorum, patchy hypopigmentation and sensorineural hearing loss are common, but short stature is not associated with WS1.Case presentationWe reported a 4-year and 6 month-old boy with a rare combination of WS1 and severe short stature (83.5 cm (−5.8SD)). His facial features include dystopia canthorum, mild synophrys, slightly up-slanted palpebral fissure, posteriorly rotated ears, alae nasi hypoplasia and micrognathia. No heterochromia was noticed. He had a normal intelligence quotient and hearing. Insulin-like growth factor-1 (IGF-1) was 52.7 ng/ml, lower than the normal range (55 ~ 452 ng/ml) and the peak growth hormone level was 7.57 ng/ml at 90 minutes after taking moderate levodopa and pyridostigmine bromide. The patient exhibited a good response to human growth hormone (rhGH) replacement therapy, showing a 9.2 cm/year growth rate and an improvement of 1 standard deviation (SD) of height after one year treatment. CMA test of patient’s DNA revealed a 4.46 Mb de novo deletion at 2q35-q36.2 (hg19; chr2:221,234,146-225,697,363). Conclusions: PAX3 haploinsufficiency is known to cause Waardenburg syndrome. Examining overlapping deletions in patients led to the conclusion that EPHA4 is a novel short stature gene. The finding is supported by the splotch-retarded and epha4 knockout mouse models which both showed growth retardation. We believe this rare condition is caused by the haploinsufficiency of both PAX3 and EPH4 genes. We further reported a growth response to recombinant human growth hormone treatment in this patient.

Description: Background: Accurate modeling of electrostatic potential and corresponding energies becomesincreasingly important for understanding properties of biological macromolecules and theircomplexes. However, this is not an easy task due to the irregular shape of biological entitiesand the presence of water and mobile ions. Results: Here we report a comprehensive suite for the well-known Poisson-Boltzmann solver, DelPhi,enriched with additional features to facilitate DelPhi usage. The suite allows for easydownload of both DelPhi executable files and source code along with a makefile for localinstallations. The users can obtain the DelPhi manual and parameter files required for thecorresponding investigation. Non-experienced researchers can download examples containingall necessary data to carry out DelPhi runs on a set of selected examples illustrating variousDelPhi features and demonstrating DelPhi's accuracy against analytical solutions. Conclusions: DelPhi suite offers not only the DelPhi executable and sources files, examples and parameterfiles, but also provides links to third party developed resources either utilizing DelPhi orproviding plugins for DelPhi. In addition, the users and developers are offered a forum toshare ideas, resolve issues, report bugs and seek help with respect to the DelPhi package. Theresource is available free of charge for academic users from URL:http://compbio.clemson.edu/delphi.php

Description: Background: Medication adherence is critical for patient treatment. This study involved evaluating how implementing Short Message Service (SMS) reminders affected patient medication adherence and related factors. Methods: We used a structured questionnaire to survey outpatients at three medical centers. Patients aged 20 years and older who were prescribed more than 7 days of a prescription medication were randomized into SMS intervention or control groups. The intervention group received daily messages reminding them of aspects regarding taking their medication; the control group received no messages. A phone follow-up was performed to assess outcomes after 8 days. Data were collected from 763 participants in the intervention group and 435 participants in the control group. Results: After participants in the intervention group received SMS reminders to take medication or those in the control group received no messages, incidences of delayed doses were decreased by 46.4 and 78.8% for those in the control and intervention groups, respectively. The rate of missed doses was decreased by 90.1% for participants in the intervention group and 61.1% for those in the control group. We applied logistic regression analysis and determined that participants in the intervention group had a 3.2-fold higher probability of having a decrease in delayed doses compared with participants in the control group. Participants in the intervention group also showed a 2.2-fold higher probability of having a decrease in missed doses compared with participants in the control group. Conclusions: Use of SMS significantly affected the rates of taking medicine on schedule. Therefore, daily SMS could be useful for reminding patients to take their medicine on schedule.

Description: Background: With the progress of nanotechnology, one frequently has to model biological macromolecules simultaneously with nano-objects. However, the atomic structures of the nano objects are typically not available or they are solid state entities. Because of that, the researchers have to investigate such nano systems by generating models of the nano objects in a manner that the existing software be able to carry the simulations. In addition, it should allow generating composite objects with complex shape by combining basic geometrical figures and embedding biological macromolecules within the system. Results: Here we report the Protein Nano-Object Integrator (ProNOI) which allows for generating atomic-style geometrical objects with user desired shape and dimensions. Unlimited number of objects can be created and combined with biological macromolecules in Protein Data Bank (PDB) format file. Once the objects are generated, the users can use sliders to manipulate their shape, dimension and absolute position. In addition, the software offers the option to charge the objects with either specified surface or volumetric charge density and to model them with user-desired dielectric constants. According to the user preference, the biological macromolecule atoms can be assigned charges and radii according to four different force fields: Amber, Charmm, OPLS and PARSE. The biological macromolecules and the atomic-style objects are exported as a position, charge and radius (PQR) file, or if a default dielectric constant distribution is not selected, it is exported as a position, charge, radius and epsilon (PQRE) file. As illustration of the capabilities of the ProNOI, we created a composite object in a shape of a robot, aptly named the Clemson Robot, whose parts are charged with various volumetric charge densities and holds the barnase-barstar protein complex in its hand. Conclusions: The Protein Nano-Object Integrator (ProNOI) is a convenient tool for generating atomic-style nano shapes in conjunction with biological macromolecule(s). Charges and radii on the macromolecule atoms and the atoms in the shapes are assigned according to the user's preferences allowing various scenarios of modeling. The default output file is in PQR (PQRE) format which is readable by almost any software available in biophysical field. It can be downloaded from: http://compbio.clemson.edu/downloadDir/ProNO_integrator.tar.gz

Description: Background: Electronic medical records (EMRs) contain vast amounts of data that is of great interest to physicians, clinical researchers, and medial policy makers. As the size, complexity, and accessibility of EMRs grow, the ability to extract meaningful information from them has become an increasingly important problem to solve. Methods: We develop a standardized data analysis process to support cohort study with a focus on a particular disease. We use an interactive divide-and-conquer approach to classify patients into relatively uniform within each group. It is a repetitive process enabling the user to divide the data into homogeneous subsets that can be visually examined, compared, and refined. The final visualization was driven by the transformed data, and user feedback direct to the corresponding operators which completed the repetitive process. The output results are shown in a Sankey diagram-style timeline, which is a particular kind of flow diagram for showing factors’ states and transitions over time. Results: This paper presented a visually rich, interactive web-based application, which could enable researchers to study any cohorts over time by using EMR data. The resulting visualizations help uncover hidden information in the data, compare differences between patient groups, determine critical factors that influence a particular disease, and help direct further analyses. We introduced and demonstrated this tool by using EMRs of 14,567 Chronic Kidney Disease (CKD) patients. Conclusions: We developed a visual mining system to support exploratory data analysis of multi-dimensional categorical EMR data. By using CKD as a model of disease, it was assembled by automated correlational analysis and human-curated visual evaluation. The visualization methods such as Sankey diagram can reveal useful knowledge about the particular disease cohort and the trajectories of the disease over time.