The papillomavirus major late protein, L1, forms the pentameric assembly unit of the viral shell. Recombinant HPV16 L1 pentamers assemble in vitro into capsid-like structures, and truncation of ten N-terminal residues leads to a homogeneous preparation of 12-pentamer, icosahedral particles. X-ray crystallographic analysis of these particles at 3.5 A resolution shows that L1 closely resembles VP1 from polyomaviruses. Surface loops contain the sites of sequence variation among HPV types and the locations of dominant neutralizing epitopes. The ease with which small virus-like particles may be obtained from L1 expressed in E. coli makes them attractive candidate components of a papillomavirus vaccine. Their crystal structure also provides a starting point for future vaccine design.

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We describe a multi-purpose image classifier that can be applied to a wide variety of image classification tasks without modifications or fine-tuning, and yet provide classification accuracy comparable to state-of-the-art task-specific image classifiers. The proposed image classifier first extracts a large set of 1025 image features including polynomial decompositions, high contrast features, pixel statistics, and textures. These features are computed on the raw image, transforms of the image, and transforms of transforms of the image. The feature values are then used to classify test images into a set of pre-defined image classes. This classifier was tested on several different problems including biological image classification and face recognition. Although we cannot make a claim of universality, our experimental results show that this classifier performs as well or better than classifiers developed specifically for these image classification tasks. Our classifier's high performance on a variety of classification problems is attributed to (i) a large set of features extracted from images; and (ii) an effective feature selection and weighting algorithm sensitive to specific image classification problems. The algorithms are available for free download from openmicroscopy.org.