Despite the ease of inhibiting immune responses by blockade of T-cell costimulation in naive rodent models, it is difficult to suppress those responses in animals with memory cells 1,2 . Studies demonstrating the importance of alloreactive T-cell deletion during tolerance induction have promoted use of peritransplant T-cell-depleting therapies in clinical trials [3][4][5][6] . But potentially complicating wide-scale, nonspecific T-cell depletion is the finding that extensive T-cell proliferation can occur under conditions of lymphopenia. This process, termed homeostatic proliferation 7,8 , may induce acquisition of functional memory T cells 9-13 . Here, using clinically relevant mouse models of peripheral T-cell depletion, we show that residual nondepleted T cells undergo substantial homeostatic expansion. In this setting, costimulatory blockade neither significantly suppresses homeostatic proliferation nor prevents allograft rejection. In addition, T cells that have completed homeostatic proliferation show dominant resistance to tolerance when adoptively transferred into wild-type recipients, consistent with known properties of memory cells in vivo. These findings establish the importance of homeostatic proliferation in clinically relevant settings, demonstrate the barrier that homeostatic proliferation can present to the induction of transplantation tolerance, and have important implications for transplantation protocols that use partial or complete peripheral T-cell depletion.T cells undergo homeostatic proliferation when transferred into severe combined immunodeficiency (scid), recombination-activating gene-deficient or irradiated recipients7 ,8 . In many clinical transplantation protocols, T-cell depletion is less profound. We therefore asked whether residual nondepleted cells could undergo homeostatic proliferation. We treated mice with two doses (100 μg/dose) of depleting monoclonal antibodies directed at CD4 and CD8 (days 0 and 5). This induced 80-90% T-cell depletion, which was maintained for >10 d after the last dose (data not shown).

The source of the optical signal responsible for the proton dose measurement using bare optical fibers is not Čerenkov radiation. It is fluorescence of the plastic material of the fiber.

Acoustic-based proton range verification (protoacoustics) is a potential in vivo technique for determining the Bragg peak position. Previous measurements and simulations have been restricted to homogeneous water tanks. Here, a CT-based simulation method is proposed and applied to a liver and prostate case to model the effects of tissue heterogeneity on the protoacoustic amplitude and time-of-flight range verification accuracy. For the liver case, posterior irradiation with a single proton pencil beam was simulated for detectors placed on the skin. In the prostate case, a transrectal probe measured the protoacoustic pressure generated by irradiation with five separate anterior proton beams. After calculating the proton beam dose deposition, each CT voxel's material properties were mapped based on Hounsfield Unit values, and thermoacoustically-generated acoustic wave propagation was simulated with the k-Wave MATLAB toolbox. By comparing the simulation results for the original liver CT to homogenized variants, the effects of heterogeneity were assessed. For the liver case, 1.4 cGy of dose at the Bragg peak generated 50 mPa of pressure (13 cm distal), a 2×  lower amplitude than simulated in a homogeneous water tank. Protoacoustic triangulation of the Bragg peak based on multiple detector measurements resulted in 0.4 mm accuracy for a δ-function proton pulse irradiation of the liver. For the prostate case, higher amplitudes are simulated (92-1004 mPa) for closer detectors (<8 cm). For four of the prostate beams, the protoacoustic range triangulation was accurate to  ⩽1.6 mm (δ-function proton pulse). Based on the results, application of protoacoustic range verification to heterogeneous tissue will result in decreased signal amplitudes relative to homogeneous water tank measurements, but accurate range verification is still expected to be possible.

No abstract

To match corresponding seed images in different radiographs so that the 3D seed locations can be triangulated automatically and without ambiguity requires (at least) three radiographs taken from different perspectives, and an algorithm that finds the proper permutations of the seed-image indices. Matching corresponding images in only two radiographs introduces inherent ambiguities which can be resolved only with the use of non-positional information obtained with intensive human effort. Matching images in three or more radiographs is an 'NP (Non-determinant in Polynomial time)-complete' problem. Although the matching problem is fundamental, current methods for three-radiograph seed-image matching use 'local' (seed-by-seed) methods that may lead to incorrect matchings. We describe a permutation-sampling method which not only gives good 'global' (full permutation) matches for the NP-complete three-radiograph seed-matching problem, but also determines the reliability of the radiographic data themselves, namely, whether the patient moved in the interval between radiographic perspectives.