Continuous Automated Model EvaluatiOn (CAMEO)-Perspectives on the future of fully automated evaluation of structure prediction methods.

The Continuous Automated Model EvaluatiOn (CAMEO) platform complements the biennial CASP experiment by conducting fully automated blind evaluations of three-dimensional protein prediction servers based on the weekly prerelease of sequences of those structures, which are going to be published in the upcoming release of the Protein Data Bank. While in CASP14, significant success was observed in predicting the structures of individual protein chains with high accuracy, significant challenges remain in correctly predicting the structures of complexes. By implementing fully automated evaluation of predictions for protein-protein complexes, as well as for proteins in complex with ligands, peptides, nucleic acids, or proteins containing noncanonical amino acid residues, CAMEO will assist new developments in those challenging areas of active research.

Laminar analysis of the cerebellar cortex shows widespread damage in early MS patients: A pilot study at 7T MRI.

BACKGROUND: To date, little is known about the presence and extent of cerebellar cortical pathology in early stages of MS. OBJECTIVE: The aims of this study were to (i) investigate microstructural changes in the normal-appearing cerebellar cortex of early MS patients by using 7 T MRI and (ii) evaluate the influence of those changes on clinical performance. METHODS: Eighteen RRMS patients and nine healthy controls underwent quantitative T1 and T2* measurement at 7 T MRI using high-resolution MP2RAGE and multi-echo gradient-echo imaging. After subtracting lesion masks, average T1 and T2* maps were computed for three layers in the cerebellar cortex and compared between groups using mixed effects models. RESULTS: The volume of the cerebellar cortex and its layers did not differ between patients and controls. In MS patients, significantly longer T1 values were observed in all vermis cortical layers and in the middle and external cortical layer of the cerebellar hemispheres. No between-group differences in T2* values were found. T1 values correlated with EDSS, SDMT and PASAT. CONCLUSIONS: We found MRI evidence of damage in the normal-appearing cerebellar cortex at early MS stages and before volumetric changes. This microstructural alteration appears to be related to EDSS and cognitive performance.

Introducing "best single template" models as reference baseline for the Continuous Automated Model Evaluation (CAMEO).

Critical blind assessment of structure prediction techniques is crucial for the scientific community to establish the state of the art, identify bottlenecks, and guide future developments. In Critical Assessment of Techniques in Structure Prediction (CASP), human experts assess the performance of participating methods in relation to the difficulty of the prediction task in a biennial experiment on approximately 100 targets. Yet, the development of automated computational modeling methods requires more frequent evaluation cycles and larger sets of data. The "Continuous Automated Model EvaluatiOn (CAMEO)" platform complements CASP by conducting fully automated blind prediction evaluations based on the weekly pre-release of sequences of those structures, which are going to be published in the next release of the Protein Data Bank (PDB). Each week, CAMEO publishes benchmarking results for predictions corresponding to a set of about 20 targets collected during a 4-day prediction window. CAMEO benchmarking data are generated consistently for all methods at the same point in time, enabling developers to cross-validate their method's performance, and referring to their results in publications. Many successful participants of CASP have used CAMEO-either by directly benchmarking their methods within the system or by comparing their own performance to CAMEO reference data. CAMEO offers a variety of scores reflecting different aspects of structure modeling, for example, binding site accuracy, homo-oligomer interface quality, or accuracy of local model confidence estimates. By introducing the "bestSingleTemplate" method based on structure superpositions as a reference for the accuracy of 3D modeling predictions, CAMEO facilitates objective comparison of techniques and fosters the development of advanced methods.