Purpose: We aim to characterize VTX-2337, a novel Toll-like receptor (TLR) 8 agonist in clinical development, and investigate its potential to improve monoclonal antibody-based immunotherapy that includes the activation of natural killer (NK) cells.Experimental Design: HEK-TLR transfectants were used to compare the selectivity and potency of VTX-2337, imiquimod, CpG ODN2006, and CL075. The ability of VTX-2337 to induce cytokine and chemokine production from human peripheral blood mononuclear cells (PBMC) and activation of specific immune cell subsets was examined. The potential for VTX-2337 to activate NK cell activity through direct and indirect mechanisms was also investigated. Finally, we tested the potential for VTX-2337 to augment antibodydependent cell-mediated cytotoxicity (ADCC), especially in individuals with low-affinity FcgR3A singlenucleotide polymorphism (SNP).Results: VTX-2337 selectively activates TLR8 with an EC 50 of about 100 nmol/L and stimulates production of TNFa and interleukin (IL)-12 from monocytes and myeloid dendritic cells (mDC). VTX-2337 stimulates IFNg production from NK cells and increases the cytotoxicity of NK cells against K562 and ADCC by rituximab and trastuzumab. Effects of VTX-2337 on NK cells were, in part, from direct activation as increased IFNg production and cytotoxic activity were seen with purified NK cells. Finally, VTX-2337 augments ADCC by rituximab in PBMCs with different FcgR3A genotypes (V

Efficiently and accurately analyzing big protein tandem mass spectrometry data sets requires robust software that incorporates state-of-the-art computational, machine learning, and statistical methods. The Crux mass spectrometry analysis software toolkit () is an open source project that aims to provide users with a cross-platform suite of analysis tools for interpreting protein mass spectrometry data.

Seizure forecasting has the potential to create new therapeutic strategies for epilepsy, such as providing patient warnings and delivering preemptive therapy. Progress on seizure forecasting, however, has been hindered by lack of sufficient data to rigorously evaluate the hypothesis that seizures are preceded by physiological changes, and are not simply random events. We investigated seizure forecasting in three dogs with naturally occurring focal epilepsy implanted with a device recording continuous intracranial EEG (iEEG). The iEEG spectral power in six frequency bands: delta (0.1–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), beta (12–30 Hz), low-gamma (30–70 Hz), and high-gamma (70–180 Hz), were used as features. Logistic regression classifiers were trained to discriminate labeled pre-ictal and inter-ictal data segments using combinations of the band spectral power features. Performance was assessed on separate test data sets via 10-fold cross-validation. A total of 125 spontaneous seizures were detected in continuous iEEG recordings spanning 6.5 to 15 months from 3 dogs. When considering all seizures, the seizure forecasting algorithm performed significantly better than a Poisson-model chance predictor constrained to have the same time in warning for all 3 dogs over a range of total warning times. Seizure clusters were observed in all 3 dogs, and when the effect of seizure clusters was decreased by considering the subset of seizures separated by at least 4 hours, the forecasting performance remained better than chance for a subset of algorithm parameters. These results demonstrate that seizures in canine epilepsy are not randomly occurring events, and highlight the feasibility of long-term seizure forecasting using iEEG monitoring.

The core of every protein mass spectrometry analysis pipeline is a function that assesses the quality of a match between an observed spectrum and a candidate peptide. We describe a procedure for computing exact p-values for the oldest and still widely used score function, SEQUEST XCorr. The procedure uses dynamic programming to enumerate efficiently the full distribution of scores for all possible peptides whose masses are close to that of the spectrum precursor mass. Ranking identified spectra by p-value rather than XCorr significantly reduces variance because of spectrum-specific effects on the score. In combination with the Percolator postprocessor, the XCorr p-value yields more spectrum and peptide identifications at a fixed false discovery rate than Mascot, X!Tandem, Comet, and MS-GF؉ across a variety of data sets. Molecular & Cellular