Cell circuits between B cell progenitors and IL-7+ mesenchymal progenitor cells control B cell development

B cell progenitors require paracrine signals such as interleukin-7 (IL-7) provided by bone marrow stromal cells for proliferation and survival. Yet, how B cells regulate access to these signals in vivo remains unclear. Here we show that proB and IL-

Integrated signaling in developing lymphocytes: The role of DNA damage responses

Lymphocyte development occurs in a stepwise progression through distinct developmental stages. This ordered maturation ensures that cells express a single, non-autoreactive antigen receptor, which is the cornerstone of a diverse adaptive immune response. Expression of a mature antigen receptor requires assembly of the antigen receptor genes by the process of V(D)J recombination, a reaction that joins distant gene segments through DNA double-strand break (DSB) intermediates. These physiologic DSBs are generated by the recombinase-activating gene (RAG) -1 and -2 proteins, and their generation is regulated by lymphocyte and developmental stage-specific signals from cytokine receptors and antigen receptor chains. Collectively, these signals ensure that V(D)J recombination of specific antigen receptor genes occurs at discrete developmental stages. Once generated, RAG-induced DSBs activate the ataxia-telangiectasia mutated (ATM) kinase to orchestrate a multifaceted DNA damage response that ensures proper DSB repair. In response to RAG DSBs, ATM also regulates a cell type-specific transcriptional response, and here we discuss how this genetic program integrates with other cellular cues to regulate lymphocyte development

System Response Kernel Calculation for List-mode Reconstruction in Strip PET Detector

Reconstruction of the image in Positron Emission Tomographs (PET) requires the knowledge of the system response kernel which describes the contribution of each pixel (voxel) to each tube of response (TOR). This is especially important in list-mode reconstruction systems, where an efficient analytical approximation of such function is required. In this contribution, we present a derivation of the system response kernel for a novel 2D strip PET.Comment: 10 pages, 2 figures; Presented at Symposium on applied nuclear physics and innovative technologies, Cracow, 03-06 June 201

Application of Compressive Sensing Theory for the Reconstruction of Signals in Plastic Scintillators

Compressive Sensing theory says that it is possible to reconstruct a measured signal if an enough sparse representation of this signal exists in comparison to the number of random measurements. This theory was applied to reconstruct signals from measurements of plastic scintillators. Sparse representation of obtained signals was found using SVD transform.Comment: 7 pages, 3 figures; Presented at Symposium on applied nuclear physics and innovative technologies, Cracow, 03-06 June 201

A novel method for calibration and monitoring of time synchronization of TOF-PET scanners by means of cosmic rays

All of the present methods for calibration and monitoring of TOF-PET scanner detectors utilize radioactive isotopes such as e.g. $^{22}$Na or $^{68}$Ge, which are placed or rotate inside the scanner. In this article we describe a novel method based on the cosmic rays application to the PET calibration and monitoring methods. The concept allows to overcome many of the drawbacks of the present methods and it is well suited for newly developed TOF-PET scanners with a large longitudinal field of view. The method enables also monitoring of the quality of the scintillator materials and in general allows for the continuous quality assurance of the PET detector performance.Comment: 10 pages, 7 figure

Compressive Sensing of Signals Generated in Plastic Scintillators in a Novel J-PET Instrument

The J-PET scanner, which allows for single bed imaging of the whole human body, is currently under development at the Jagiellonian University. The dis- cussed detector offers improvement of the Time of Flight (TOF) resolution due to the use of fast plastic scintillators and dedicated electronics allowing for sam- pling in the voltage domain of signals with durations of few nanoseconds. In this paper we show that recovery of the whole signal, based on only a few samples, is possible. In order to do that, we incorporate the training signals into the Tikhonov regularization framework and we perform the Principal Component Analysis decomposition, which is well known for its compaction properties. The method yields a simple closed form analytical solution that does not require iter- ative processing. Moreover, from the Bayes theory the properties of regularized solution, especially its covariance matrix, may be easily derived. This is the key to introduce and prove the formula for calculations of the signal recovery error. In this paper we show that an average recovery error is approximately inversely proportional to the number of acquired samples