Duke University

Los Alamos National Security, LLC

Beth Israel Deaconess Medical Center, Inc.

University of Alabama

Dana-farber-cancer Institute Inc.

Los Alamos Security, LLC

U. of Alabama at Birmingham Research Foundation

Simon J Perkins

James Theiler

Barton F Haynes

Bette T Korber

Beatrice H Hahn

William M Fischer

Norman L Letvin

Karina Yusim

Carla L Kuiken

Tanmoy Bhattacharya

Joseph G Sodroski

Bette T M Korber

S Gnanakaran

Disclosed herein are mosaic HIV envelope (Env) polypeptides that can elicit an immune response to HIV (such as cytotoxic T cell (CTL), helper T cell, and/or humoral responses). Also disclosed are sets of the disclosed mosaic Env polypeptides, which include two or more (for example, three) of the polypeptides. Also disclosed herein are methods for treating or inhibiting HIV in a subject including administering one or more of the disclosed immunogenic polypeptides or compositions to a subject infected with HIV or at risk of HIV infection. In some embodiments, the methods include inducing an immune response to HIV in a subject comprising administering to the subject at least one (such as two, three, or more) of the immunogenic polypeptides or at least one (such as two, three, or more) nucleic acids encoding at least one of the immunogenic polypeptides disclosed herein.

Mosaic HIV envelope immunogenic polypeptides

The disclosure generally relates to an immunogenic composition (e.g., a vaccine) and, in particular, to a polyvalent immunogenic composition, such as a polyvalent HIV vaccine, and to methods of using same.

Nucleic acids encoding mosaic HIV-1 gag proteins

The present invention relates to mosaic HIV-1 group M Gag sequences and to a composition comprising same.

Human immunodeficiency virus type 1 clade M mosaic gag polypeptides

The present invention relates to mosaic clade M HIV-1 Nef polypeptides and to compositions comprising same. The polypeptides of the invention are suitable for use in inducing an immune response to HIV-1 in a human.

Immunogenic compositions comprising human immunodeficiency virus (HIV) mosaic Nef proteins

A distribution-based anomaly detection platform is described that identifies a non-flat background that is specified in terms of the distribution of the data. A resampling approach is also disclosed employing scrambled resampling of the original data with one class specified by the data and the other by the explicit distribution, and solving using binary classification.

Anomalous change detection in imagery

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Santa Fe, NM, United States of America

Simon J Perkins