Challenges and Progress in Designing Broad-Spectrum Vaccines Against Rapidly Mutating Viruses.

Viruses evolve to evade prior immunity, causing significant disease burden. Vaccine effectiveness deteriorates as pathogens mutate, requiring redesign. This is a problem that has grown worse due to population increase, global travel, and farming practices.

Hierarchical confounder discovery in the experiment-machine learning cycle.

The promise of machine learning (ML) to extract insights from high-dimensional datasets is tempered by confounding variables. It behooves scientists to determine if a model has extracted the desired information or instead fallen prey to bias. Due to features of natural phenomena and experimental design constraints, bioscience datasets are often organized in nested hierarchies that obfuscate the origins of confounding effects and render confounder amelioration methods ineffective.

Setwise comparison: efficient fine-grained rating of movement videos using algorithmic support - a proof of concept study.

Clinical ordinal rating scales of movements, e.g., the Expanded Disability Status Scale, have poor intra- and interrater reliability, are insensitive to subtle differences and result in coarse-grained ratings compared to relative comparative rating methods.

Bifunctional immune checkpoint-targeted antibody-ligand traps that simultaneously disable TGFβ enhance the efficacy of cancer immunotherapy.

A majority of cancers fail to respond to immunotherapy with antibodies targeting immune checkpoints, such as cytotoxic T-lymphocyte antigen-4 (CTLA-4) or programmed death-1 (PD-1)/PD-1 ligand (PD-L1). Cancers frequently express transforming growth factor-β (TGFβ), which drives immune dysfunction in the tumor microenvironment by inducing regulatory T cells (Tregs) and inhibiting CD8 and T1 cells. To address this therapeutic challenge, we invent bifunctional antibody-ligand traps (Y-traps) comprising an antibody targeting CTLA-4 or PD-L1 fused to a TGFβ receptor II ectodomain sequence that simultaneously disables autocrine/paracrine TGFβ in the target cell microenvironment (a-CTLA4-TGFβRIIecd and a-PDL1-TGFβRIIecd).

Inhibition of TGF-β enhances the in vivo antitumor efficacy of EGF receptor-targeted therapy.

EGF receptor (EGFR)-targeted monoclonal antibodies (mAb), such as cetuximab, execute their antitumor effect in vivo via blockade of receptor-ligand interactions and engagement of Fcγ receptors on immune effector cells that trigger antibody-dependent cell-mediated cytotoxicity (ADCC). We show that tumors counteract the in vivo antitumor activity of anti-EGFR mAbs by increasing tumor cell-autonomous expression of TGF-β. We show that TGF-β suppresses the expression of key molecular effectors of immune cell-mediated cytotoxicity, including Apo2L/TRAIL, CD95L/FasL, granzyme B, and IFN-γ.