Validated ligand binding sites in CCK receptors. Next step: Computer aided design of novel CCK ligands

Computer-aided drug design becomes an important part of G-protein coupled receptors (GPCR) drug discovery process that is applied for improving the efficiency of derivation and optimization of novel ligands. It represents the combination of methods that-use-structural information of a receptor binding site of known ligands to design new ligands. In this report, we give a brief description of ligand binding sites in cholecystokinin and gastrin receptors (CK1R and CCK2R) which were delineated using experimental and computational methods, and then, we show how the validated ligand binding sites can be used to design and improve novel ligands. The translation of the knowledge of ligand-binding sites of different GPCRs to computer-aided design of novel ligands is summarized.

A Sensitivity Approach for Eliminating Clashes from Computer Aided Design Model Assemblies

Clashes occur when components in an assembly unintentionally violate others. If clashes are not identified and designed out before manufacture, product function will be reduced or substantial cost will be incurred in rework. This paper introduces a novel approach for eliminating clashes by identifying which parameters defining the part features in a computer aided design (CAD) assembly need to change and by how much. Sensitivities are calculated for each parameter defining the part and the assembly as the change in clash volume due to a change in each parameter value. These sensitivities give an indication of important parameters and are used to predict the optimum combination of changes in each parameter to eliminate the clash. Consideration is given to the fact that it is sometimes preferable to modify some components in an assembly rather than others and that some components in an assembly cannot be modified as the designer does not have control over their shape. Successful elimination of clashes has been demonstrated in a number of example assemblies.

Time Efficient Assessment and Feedback Methods for Large Computer-Aided-Design Cohorts

Timely and individualized feedback on coursework is desirable from a student perspective as it facilitates formative development and encourages reflective learning practice. Faculty however are faced with a significant and potentially time consuming challenge when teaching larger cohorts if they are to provide feedback which is timely, individualized and detailed. Additionally, for subjects which assess non-traditional submissions, such as Computer-Aided-Design (CAD), the methods for assessment and feedback tend not to be so well developed or optimized. Issues can also arise over the consistency of the feedback provided. Evaluations of Computer-Assisted feedback in other disciplines (Denton et al, 2008), (Croft et al, 2001) have shown students prefer this method of feedback to traditional “red pen” marking and also that such methods can be more time efficient for faculty.
Herein, approaches are described which make use of technology and additional software tools to speed up, simplify and automate assessment and the provision of feedback for large cohorts of first and second year engineering students studying modules where CAD files are submitted electronically. A range of automated methods are described and compared with more “manual” approaches. Specifically one method uses an application programming interface (API) to interrogate SolidWorks models and extract information into an Excel spreadsheet, which is then used to automatically send feedback emails. Another method describes the use of audio recordings made during model interrogation which reduces the amount of time while increasing the level of detail provided as feedback.
Limitations found with these methods and problems encountered are discussed along with a quantified assessment of time saving efficiencies made.

Field investigation of contactless displacement measurement using computer vision systems for civil engineering applications

Much of the bridge stock on major transport links in North America and Europe was constructed in the 1950s and 1960s and has since deteriorated or is carrying loads far in excess of the original design loads. Structural Health Monitoring Systems (SHM) can provide valuable information on the bridge capacity but the application of such systems is currently limited by access and bridge type. This paper investigates the use of computer vision systems for SHM. A series of field tests have been carried out to test the accuracy of displacement measurements using contactless methods. A video image of each test was processed using a modified version of the optical flow tracking method to track displacement. These results have been validated with an established measurement method using linear variable differential transformers (LVDTs). The results obtained from the algorithm provided an accurate comparison with the validation measurements. The calculated displacements agree within 2% of the verified LVDT measurements, a number of post processing methods were then applied to attempt to reduce this error.

The use of morphological characteristics and texture analysis in the identification of tissue composition in prostatic neoplasia

Quantitative examination of prostate histology offers clues in the diagnostic classification of lesions and in the prediction of response to treatment and prognosis. To facilitate the collection of quantitative data, the development of machine vision systems is necessary. This study explored the use of imaging for identifying tissue abnormalities in prostate histology. Medium-power histological scenes were recorded from whole-mount radical prostatectomy sections at × 40 objective magnification and assessed by a pathologist as exhibiting stroma, normal tissue (nonneoplastic epithelial component), or prostatic carcinoma (PCa). A machine vision system was developed that divided the scenes into subregions of 100 × 100 pixels and subjected each to image-processing techniques. Analysis of morphological characteristics allowed the identification of normal tissue. Analysis of image texture demonstrated that Haralick feature 4 was the most suitable for discriminating stroma from PCa. Using these morphological and texture measurements, it was possible to define a classification scheme for each subregion. The machine vision system is designed to integrate these classification rules and generate digital maps of tissue composition from the classification of subregions; 79.3% of subregions were correctly classified. Established classification rates have demonstrated the validity of the methodology on small scenes; a logical extension was to apply the methodology to whole slide images via scanning technology. The machine vision system is capable of classifying these images. The machine vision system developed in this project facilitates the exploration of morphological and texture characteristics in quantifying tissue composition. It also illustrates the potential of quantitative methods to provide highly discriminatory information in the automated identification of prostatic lesions using computer vision.