Statistical Communication Theory

Contains reports on six research projects.National Science Foundation (Grant GP-2495)National Institutes of Health (Grant MH-04737-04)National Aeronautics and Space Administration (Grant NsG-496

Tumor interactions with soluble factors and the nervous system

In the genomic era of cancer research, the development of metastases has been attributed to mutations in the tumor that enable the cells to migrate. However, gene analyses revealed that primary tumors and metastases were in some cases genetically identical and the question was raised whether metastasis formation might be an inherent feature of certain tumor cells. In contradiction to this view, the last decade of cancer research has brought to light, that tumor cell migration, similar to leukocyte and fibroblast migration, is a highly regulated process. The nervous system plays an important role in this regulation, at least in two respects: firstly, neurotransmitters are known to regulate the migratory activity of tumor cells, and secondly, nerve fibers are used as routes for perineural invasion. We also summarize here the current knowledge on the innervation of tumors. Such a process might establish a neuro-neoplastic synapse, with the close interaction of tumor cells and nerve cells supporting metastasis formation

Phase 1/2 study of epacadostat in combination with durvalumab in patients with metastatic solid tumors

BackgroundTargeting programmed cell death protein 1 (PD-1) and indoleamine 2,3-dioxygenase (IDO1) pathways is an appealing option for cancer treatment.MethodsThe open-label, phase 1/2 ECHO-203 study evaluated the safety, tolerability, and efficacy of the IDO1 inhibitor epacadostat in combination with durvalumab, a human anti-PD-L1 monoclonal antibody in adult patients with advanced solid tumors.ResultsThe most common treatment-related adverse events were fatigue (30.7%), nausea (21.0%), decreased appetite (13.1%), pruritus (12.5%), maculopapular rash (10.8%), and diarrhea (10.2%). Objective response rate (ORR) in the overall phase 2 population was 12.0%. Higher ORR was observed in immune checkpoint inhibitor (CPI)-naïve patients (16.1%) compared with patients who had received previous CPI (4.1%). Epacadostat pharmacodynamics were evaluated by comparing baseline kynurenine levels with those on therapy at various time points. Only the 300-mg epacadostat dose showed evidence of kynurenine modulation, albeit unsustained.ConclusionsEpacadostat plus durvalumab was generally well tolerated in patients with advanced solid tumors. ORR was low, and evaluation of kynurenine concentration from baseline to cycle 2, day 1, and cycle 5, day 1, suggested >300 mg epacadostat twice daily is needed to ensure sufficient drug effect.Clinical trial informationA study of epacadostat (INCB024360) in combination with durvalumab (MEDI4736) in subjects with selected advanced solid tumors (ECHO-203) (NCT02318277)

Accelerating Multi-Channel Filtering of Audio Signal on ARM Processors

Tablets and smart phones are nowadays equipped with low-power processor architectures such as the ARMv7 and the ARMv8 series. These processors integrate powerful SIMD units to exploit the intrinsic data-parallelism of most media and signal processing applications. In audio signal processing, there exist multiple problems that require filtering operations such as equalizations or signal synthesizers, among others. Most of these applications can be efficiently executed today on mobile devices by leveraging the processor SIMD unit. In this paper, we target the implementation of multi-channel filtering of audio signals on ARM architectures. To this end, we consider two common audio filter structures: FIR and IIR. The latter is analyzed in two different forms: direct form I and parallel form. Our results show that the SIMD-accelerated implementation increases the processing speed by a factor of 4 × with respect to the original code, and our hand-tuned SIMD implementation outperforms the auto- vectorized code by a factor of 2× . These results allow us to deal in real time with multi-channel systems composed of 260 FIR filters with 256 coefficients, or 125 IIR filters with 256 coefficients, of INT16 data type.The researchers from Universitat Jaume I are supported by the CICYT projects TIN2014-53495-R and TIN2011-23283 of the Ministerio de Economia y Competitividad and FEDER. The authors from the Universitat Politecnica de Valencia are supported by projects TEC2015-67387-C4-1-R and PROMETEOII/2014/003. This work was also supported from the European Union FEDER (CAPAP-H5 network TIN2014-53522-REDT).Belloch Rodríguez, JA.; Alventosa, FJ.; Alonso-Jordá, P.; Quintana Ortí, ES.; Vidal Maciá, AM. (2017). Accelerating Multi-Channel Filtering of Audio Signal on ARM Processors. Journal of Supercomputing. 73(1):203-214. https://doi.org/10.1007/s11227-016-1689-8S203214731ARM NEON. http://www.arm.com/ . Accessed 23 Feb 2015Rämo J, Välimäki V, Bank B (2014) High-precision parallel graphic equalizer. IEEE Trans Audio Speech Lang Process 22:1894–1904Mathews MV, Miller JE, Moore FR, Pierce JR, Risset JC (1969) The technology of computer music. MIT Press, Cambridge, MassRisset JC (1985) Computer music experiments 185. Comput Music J 22:11–18Puckette M (2007) The theory and technique of electronic music, World Scientific Publishing ISBN-13: 978–9812700773Savioja L, Välimäki V, Smith JO (2011) Audio signal processing using graphics processing units. J Audio Eng Soc 59:3–19Belloch JA, Bank B, Savioja L, Gonzalez A, Välimäki V (2014) Multi-channel IIR filtering of audio signals using a GPU. In: Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing (ICASSP-14), pp 6692–6696Belloch JA, Gonzalez A, Martnez-Zaldívar FJ, Vidal AM (2013) Multichannel massive audio processing for a generalized crosstalk cancellation and equalization application using GPUs. Integr Comput Aided Eng 20:169–182Algazi V, Duda R (2011) Headphone-based spatial sound. IEEE Signal Process Mag 28:33–42Belloch JA, Ferrer M, Gonzalez A, Martinez-Zaldívar FJ, Vidal AM (2013) Headphone-based virtual spatialization of sound with a GPU accelerator. J Audio Eng Soc 61:546–556Huang Y, Chen J, Benesty J (2011) Immerse audio schemes. IEEE Signal Process Mag 28:20–32Oppenheim AV, Willsky AS, Hamid S (1997) Signals and systems, processing series, 2nd edn. Prentice Hall, Upper Saddle RiverBank B (2008) Perceptually motivated audio equalization using fixed-pole parallel second-order filters. IEEE Signal Process Lett 15:477–480Mitra G, Johnston B, Rendell AP, McCreath E, Zhou J (2013) Use of SIMD vector operations to accelerate application code performance on low-powered ARM and Intel Platforms. In: IEEE 27th International Parallel and Distributed Processing Symposium Workshops PhD Forum (IPDPSW), pp 1107–1116Welch E, Patru D, Saber E, Bengtson K (2012) A study of the use of SIMD instructions for two image processing algorithms. Western New York Image Processing Workshop (WNYIPW), pp 21–24Wang R, Wan J, Wang W, Wang Z, Dong S, Gao W (2013) High definition IEEE AVS decoder on ARM NEON platform. In: 20th IEEE International Conference on Image Processing (ICIP), pp 1524–1527Holgersson SB (2012) Optimising IIR filters using ARM NEON, Master Thesis of University of DenmarkRabiner LR, Gold B (1975) Theory and application of digital signal processing. Prentice-Hall, Englewood CliffsARM NEON intrinsics. http://gcc.gnu.org/onlinedocs/gcc-4.4.1/gcc/ARM-NEON-Intrinsics.html . Accessed 12 July 2015ARM NEON auto-vectorization. http://gcc.gnu.org/onlinedocs/gcc/ARM-Options.html . Accessed 22 July 201