Combination therapy with anti-HIV-1 antibodies maintains viral suppression.

Individuals infected with HIV-1 require lifelong antiretroviral therapy, because interruption of treatment leads to rapid rebound viraemia. Here we report on a phase 1b clinical trial in which a combination of 3BNC117 and 10-1074, two potent monoclonal anti-HIV-1 broadly neutralizing antibodies that target independent sites on the HIV-1 envelope spike, was administered during analytical treatment interruption. Participants received three infusions of 30 mg kg-1 of each antibody at 0, 3 and 6 weeks. Infusions of the two antibodies were generally well-tolerated. The nine enrolled individuals with antibody-sensitive latent viral reservoirs maintained suppression for between 15 and more than 30 weeks (median of 21 weeks), and none developed viruses that were resistant to both antibodies. We conclude that the combination of the anti-HIV-1 monoclonal antibodies 3BNC117 and 10-1074 can maintain long-term suppression in the absence of antiretroviral therapy in individuals with antibody-sensitive viral reservoirs.

Weighted elastic net for unsupervised domain adaptation with application to age prediction from DNA methylation data.

MOTIVATION: Predictive models are a powerful tool for solving complex problems in computational biology. They are typically designed to predict or classify data coming from the same unknown distribution as the training data. In many real-world settings, however, uncontrolled biological or technical factors can lead to a distribution mismatch between datasets acquired at different times, causing model performance to deteriorate on new data. A common additional obstacle in computational biology is scarce data with many more features than samples. To address these problems, we propose a method for unsupervised domain adaptation that is based on a weighted elastic net. The key idea of our approach is to compare dependencies between inputs in training and test data and to increase the cost of differently behaving features in the elastic net regularization term. In doing so, we encourage the model to assign a higher importance to features that are robust and behave similarly across domains. RESULTS: We evaluate our method both on simulated data with varying degrees of distribution mismatch and on real data, considering the problem of age prediction based on DNA methylation data across multiple tissues. Compared with a non-adaptive standard model, our approach substantially reduces errors on samples with a mismatched distribution. On real data, we achieve far lower errors on cerebellum samples, a tissue which is not part of the training data and poorly predicted by standard models. Our results demonstrate that unsupervised domain adaptation is possible for applications in computational biology, even with many more features than samples. AVAILABILITY AND IMPLEMENTATION: Source code is available at https://github.com/PfeiferLabTue/wenda. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Electron tomography reveals the fibril structure and lipid interactions in amyloid deposits.

Electron tomography is an increasingly powerful method to study the detailed architecture of macromolecular complexes or cellular structures. Applied to amyloid deposits formed in a cell culture model of systemic amyloid A amyloidosis, we could determine the structural morphology of the fibrils directly in the deposit. The deposited fibrils are arranged in different networks, and depending on the relative fibril orientation, we can distinguish between fibril meshworks, fibril bundles, and amyloid stars. These networks are frequently infiltrated by vesicular lipid inclusions that may originate from the death of the amyloid-forming cells. Our data support the role of nonfibril components for constructing fibril deposits and provide structural views of different types of lipid-fibril interactions.

XplOit: An Ontology-Based Data Integration Platform Supporting the Development of Predictive Models for Personalized Medicine.

Predictive models can support physicians to tailor interventions and treatments to their individual patients based on their predicted response and risk of disease and help in this way to put personalized medicine into practice. In allogeneic stem cell transplantation risk assessment is to be enhanced in order to respond to emerging viral infections and transplantation reactions. However, to develop predictive models it is necessary to harmonize and integrate high amounts of heterogeneous medical data that is stored in different health information systems. Driven by the demand for predictive instruments in allogeneic stem cell transplantation we present in this paper an ontology-based platform that supports data owners and model developers to share and harmonize their data for model development respecting data privacy.

Safety and antiviral activity of combination HIV-1 broadly neutralizing antibodies in viremic individuals.

Monotherapy of HIV-1 infection with single antiretroviral agents is ineffective because error-prone HIV-1 replication leads to the production of drug-resistant viral variants1,2. Combinations of drugs can establish long-term control, however, antiretroviral therapy (ART) requires daily dosing, can cause side effects and does not eradicate the infection3,4. Although anti-HIV-1 antibodies constitute a potential alternative to ART5,6, treatment of viremic individuals with a single antibody also results in emergence of resistant viral variants7-9. Moreover, combinations of first-generation anti-HIV-1 broadly neutralizing antibodies (bNAbs) had little measurable effect on the infection10-12. Here we report on a phase 1b clinical trial ( NCT02825797 ) in which two potent bNAbs, 3BNC11713 and 10-107414, were administered in combination to seven HIV-1 viremic individuals. Infusions of 30 mg kg-1 of each of the antibodies were well-tolerated. In the four individuals with dual antibody-sensitive viruses, immunotherapy resulted in an average reduction in HIV-1 viral load of 2.05 log10 copies per ml that remained significantly reduced for three months following the first of up to three infusions. In addition, none of these individuals developed resistance to both antibodies. Larger studies will be necessary to confirm the efficacy of antibody combinations in reducing HIV-1 viremia and limiting the emergence of resistant viral variants.