CATH--a hierarchic classification of protein domain structures

BACKGROUND: Protein evolution gives rise to families of structurally related proteins, within which sequence identities can be extremely low. As a result, structure-based classifications can be effective at identifying unanticipated relationships in known structures and in optimal cases function can also be assigned. The ever increasing number of known protein structures is too large to classify all proteins manually, therefore, automatic methods are needed for fast evaluation of protein structures. RESULTS: We present a semi-automatic procedure for deriving a novel hierarchical classification of protein domain structures (CATH). The four main levels of our classification are protein class (C), architecture (A), topology (T) and homologous superfamily (H). Class is the simplest level, and it essentially describes the secondary structure composition of each domain. In contrast, architecture summarises the shape revealed by the orientations of the secondary structure units, such as barrels and sandwiches. At the topology level, sequential connectivity is considered, such that members of the same architecture might have quite different topologies. When structures belonging to the same T-level have suitably high similarities combined with similar functions, the proteins are assumed to be evolutionarily related and put into the same homologous superfamily. CONCLUSIONS: Analysis of the structural families generated by CATH reveals the prominent features of protein structure space. We find that nearly a third of the homologous superfamilies (H-levels) belong to ten major T-levels, which we call superfolds, and furthermore that nearly two-thirds of these H-levels cluster into nine simple architectures. A database of well-characterised protein structure families, such as CATH, will facilitate the assignment of structure-function/evolution relationships to both known and newly determined protein structures.     

Inhibitory control over no-longer-relevant information: adult age differences

Hartmann and Hasher (1991) used a garden-path task in which younger and older adults generated the final word for each of a series of high-cloze sentences. Under instructions to remember the final word, the experiment included critical sentences for which the generated word was replaced by a new, to-be-remembered target. Using an implicit priming task, the first experiment replicated a basic finding: Younger adults showed priming only for the target words, whereas older adults showed priming for both the generated and target words. Two experiments explored the boundary conditions. One showed that an additional sentence that interpreted the new target word enabled older adults to narrow access to only the target word. The provision of additional time following the introduction of the new target word did not. Specific information, not more time, is required for inefficient inhibitory mechanisms to clear the recent past from memory.     

Evaluation of low density spine software for the assessment of bone mineral density in children

Pediatric dual-energy X-ray absorptiometry spine scans often cannot be analyzed with standard software due to a failure to identify the bone edges of low density vertebrae. Low density spine (LDS) software improves bone detection compared with standard software. The objective of this study was to compare bone mineral density (BMD) measurements obtained with the standard and LDS software in 27 healthy nonobese, 32 obese, and 41 chronically ill children, ages 2-18 years. Lumbar spine (L1-L4) BMD, measured by standard analysis, ranged from 0.531-1.244 gm/cm2. Reanalysis with the LDS software resulted in a systematic increase (mean +/- SD) in estimated bone area of 17.0+/-5.0%, an increase in bone mineral content of 6.1+/-6.3%, and a mean decrease in BMD of 8.7+/-1.7% (all p < 0.001). This resulted in a mean decrease in BMD Z score of 0.7+/-0.2. Linear regression models, predicting standard BMD from LDS BMD, were fit for the three subject groups (R2 = 0.993-0.995). Small differences in slopes were detected across groups (p = 0.07); LDS BMD predicted higher standard BMD in obese subjects. In conclusion, LDS analysis resulted in a clinically significant decrease in measured BMD. The association between analysis methods was exceptionally high (R2 > 0.99), indicating that LDS BMD accurately predicts standard BMD. Although LDS BMD in obese subjects predicts higher standard BMD results than in nonobese subjects, the small difference is of questionable clinical significance. LDS software is a useful tool for the assessment of BMD in children.