One-bit compressive sensing with norm estimation

Consider the recovery of an unknown signal ${x}$ from quantized linear measurements. In the one-bit compressive sensing setting, one typically assumes that ${x}$ is sparse, and that the measurements are of the form $\operatorname{sign}(\langle {a}_i, {x} \rangle) \in \{\pm1\}$. Since such measurements give no information on the norm of ${x}$, recovery methods from such measurements typically assume that $\| {x} \|_2=1$. We show that if one allows more generally for quantized affine measurements of the form $\operatorname{sign}(\langle {a}_i, {x} \rangle + b_i)$, and if the vectors ${a}_i$ are random, an appropriate choice of the affine shifts $b_i$ allows norm recovery to be easily incorporated into existing methods for one-bit compressive sensing. Additionally, we show that for arbitrary fixed ${x}$ in the annulus $r \leq \| {x} \|_2 \leq R$, one may estimate the norm $\| {x} \|_2$ up to additive error $\delta$ from $m \gtrsim R^4 r^{-2} \delta^{-2}$ such binary measurements through a single evaluation of the inverse Gaussian error function. Finally, all of our recovery guarantees can be made universal over sparse vectors, in the sense that with high probability, one set of measurements and thresholds can successfully estimate all sparse vectors ${x}$ within a Euclidean ball of known radius.Comment: 20 pages, 2 figure

Role of T cell receptor signaling in CD8 T cell memory

The generation of immunological memory is the basis for vaccination. The development of memory CD8 T cells is required for long-term protection against intracellular pathogens, such as viruses, and tumors. While the importance of memory generation has been recognized for over 30 years, the mechanism by which memory CD8 T cells arise during immune responses is still not fully understood. T cell receptor (TCR) interaction with antigen (immunogenic peptide)-bound MHC is necessary for activation and differentiation of CD8 T cells. Yet, how the resulting TCR signal regulates T cell memory is unknown. In this dissertation, we investigated the role that the TCR signal plays in memory differentiation. First, we explain how the strength of pMHC-TCR interaction affects memory generation. We also demonstrate that the signals for the development of memory are different depending on TCR ligand strength. Finally, we define a mechanism by which TCR signaling programs memory differentiation. All vaccines utilize pathogen-specific antigens to induce immunological memory. By understanding how antigenic signals program memory differentiation, it will be possible to specifically manipulate this process. We can then produce more effective and longer lasting memory cells

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Recovery of continuous quantities from discrete and binary data with applications to neural data

textWe consider three problems, motivated by questions in computational neuroscience, related to recovering continuous quantities from binary or discrete data or measurements in the context of sparse structure. First, we show that it is possible to recover the norms of sparse vectors given one-bit compressive measurements, and provide associated guarantees. Second, we present a novel algorithm for spike-sorting in neural data, which involves recovering continuous times and amplitudes of events using discrete bases. This method, Continuous Orthogonal Matching Pursuit, builds on algorithms used in compressive sensing. It exploits the sparsity of the signal and proceeds greedily, achieving gains in speed and accuracy over previous methods. Lastly, we present a Bayesian method making use of hierarchical priors for entropy rate estimation from binary sequences.Mathematic

Assessing Cerebellar Disorders with Wearable Inertial Sensor Data Using Time-Frequency and Autoregressive Hidden Markov Model Approaches

Wearable sensor data is relatively easily collected and provides direct measurements of movement that can be used to develop useful behavioral biomarkers. Sensitive and specific behavioral biomarkers for neurodegenerative diseases are critical to supporting early detection, drug development efforts, and targeted treatments. In this paper, we use autoregressive hidden Markov models and a time-frequency approach to create meaningful quantitative descriptions of behavioral characteristics of cerebellar ataxias from wearable inertial sensor data gathered during movement. We create a flexible and descriptive set of features derived from accelerometer and gyroscope data collected from wearable sensors worn while participants perform clinical assessment tasks, and use these data to estimate disease status and severity. A short period of data collection (&lt;5 min) yields enough information to effectively separate patients with ataxia from healthy controls with very high accuracy, to separate ataxia from other neurodegenerative diseases such as Parkinson&rsquo;s disease, and to provide estimates of disease severity

Assessing Cerebellar Disorders with Wearable Inertial Sensor Data Using Time-Frequency and Autoregressive Hidden Markov Model Approaches

Wearable sensor data is relatively easily collected and provides direct measurements of movement that can be used to develop useful behavioral biomarkers. Sensitive and specific behavioral biomarkers for neurodegenerative diseases are critical to supporting early detection, drug development efforts, and targeted treatments. In this paper, we use autoregressive hidden Markov models and a time-frequency approach to create meaningful quantitative descriptions of behavioral characteristics of cerebellar ataxias from wearable inertial sensor data gathered during movement. We create a flexible and descriptive set of features derived from accelerometer and gyroscope data collected from wearable sensors worn while participants perform clinical assessment tasks, and use these data to estimate disease status and severity. A short period of data collection (<5 min) yields enough information to effectively separate patients with ataxia from healthy controls with very high accuracy, to separate ataxia from other neurodegenerative diseases such as Parkinson’s disease, and to provide estimates of disease severity

Functional and mechanistic advantage of the use of a bifunctional anti-PD-L1/IL-15 superagonist

BackgroundAnti(α)-programmed cell death-1 (PD-1)/programmed death-ligand 1 (PD-L1) monotherapy fails to provide durable clinical benefit for most patients with carcinoma. Recent studies suggested that strategies to reduce immunosuppressive cells, promote systemic T-cell responses and lymphocyte trafficking to the tumor microenvironment (TME) may improve efficacy. N-809 is a first-in-class bifunctional agent comprising the interleukin (IL)-15 superagonist N-803 fused to two αPD-L1 domains. Thus, N-809 can potentially stimulate effector immune cells through IL-15 and block immunosuppressive PD-L1. Here, we examined the antitumor efficacy and immunomodulatory effects of N-809 versus N-803+αPD-L1 combination.MethodsThe ability of N-809 to block PD-L1 and induce IL-15-dependent immune effects was examined in vitro and in vivo. Antitumor efficacy of N-809 or N-803+αPD-L1 was evaluated in two murine carcinoma models and an extensive analysis of immune correlates was performed in the tumor and tumor-draining lymph node (dLN).ResultsWe demonstrate that N-809 blocks PD-L1 and induces IL-15-dependent immune effects. N-809 was well-tolerated and reduced 4T1 lung metastasis, decreased MC38 tumor burden and increased survival versus N-803+αPD-L1. Compared with N-803+αPD-L1, N-809 enhanced natural killer (NK) and CD8+ T-cell activation and function in the dLN and TME, relating to increased gene expression associated with interferon and cytokine signaling, lymphoid compartment, costimulation and cytotoxicity. The higher number of TME CD8+ T cells was attributed to enhanced infiltration, not in situ expansion. Increased TME NK and CD8+ T-cell numbers correlated with augmented chemokine ligands and receptors. Moreover, in contrast to N-803+αPD-L1, N-809 reduced immunosuppressive regulatory T cells (Treg), monocytic myeloid-derived suppressor cells (M-MDSC) and M2-like macrophages in the TME.ConclusionsOur results suggest that N-809 functions by a novel immune mechanism to promote antitumor efficacy. Foremost, N-809 enhances intratumoral lymphocyte numbers by increasing trafficking via altered chemokine levels in the TME and chemokine receptor expression on CD8+ T cells and NK cells. In addition, N-809 reduces immunosuppressive and pro-tumorigenic immune cells in the TME, including Treg, M2-like macrophages and M-MDSC. Overall, these novel effects of N-809 promote an inflamed TME, leading to lower tumor burden and increased survival. These results provide mechanistic insight and rationale supporting the potential clinical study of N-809 in patients with carcinoma