Comparison of two MR grading systems for correlation between grade of cervical neural foraminal stenosis and clinical manifestations.

OBJECTIVE: To compare the reliability of two recently reported MR grading systems of cervical neural foraminal stenosis (CNFS) and their correlation with clinical manifestations. METHODS: We evaluated 188 patients (male : female = 80 : 108; mean age of 41 years) who visited our institution and underwent oblique sagittal MRI of the cervical spine. Two radiologists evaluated the MRI findings for the presence and grade of CNFS at the narrowest point, with the grading systems (Park, Kim and mKim systems) suggested by Park et al and Kim et al. More than one positive neurologic sign and more than one neurologic clinical symptom was considered a positive neurologic manifestation of each foraminal stenosis. Interobserver agreement between the two readers was analyzed using kappa statistics. Non-parametric correlation analysis (Spearman's correlation) was used to evaluate the correlation coefficients (R) to assess the relationship between CNFS grade and clinical manifestations. RESULTS: Both the Park and mKim systems demonstrated a relatively high correlation (R = 0.714-0.764) between the CNFS grade and clinical manifestation, while the Kim system yielded a moderate correlation (by Reader 2). The Park and mKim systems demonstrated higher correlation values at the level of C6-7 than C4-5, while the Kim system showed no difference in correlation at the cervical spine level. CONCLUSION: Both the Park and mKim systems provide a reliable, reproducible CNFS diagnosis, while the Kim system has a slightly inferior reliability. The Park and mKim systems had a similar, relatively high clinical correlation. ADVANCES IN KNOWLEDGE: Grades 2 and 3 of the Park system and Grade 2 in the Kim and mKim systems exhibited a similar clinical significance. Patients with a grade of 0 (using each system) consistently exhibit negative neurologic manifestation.

All-atom de novo protein folding with a scalable evolutionary algorithm.

The search for efficient and predictive methods to describe the protein folding process at the all-atom level remains an important grand-computational challenge. The development of multi-teraflop architectures, such as the IBM BlueGene used in this study, has been motivated in part by the large computational requirements of such studies. Here we report the predictive all-atom folding of the forty-amino acid HIV accessory protein using an evolutionary stochastic optimization technique. We implemented the optimization method as a master-client model on an IBM BlueGene, where the algorithm scales near perfectly from 64 to 4096 processors in virtual processor mode. Starting from a completely extended conformation, we optimize a population of 64 conformations of the protein in our all-atom free-energy model PFF01. Using 2048 processors the algorithm predictively folds the protein to a near-native conformation with an RMS deviation of 3.43 A in < 24 h.