Generative Modeling in Sinogram Domain for Sparse-view CT Reconstruction

The radiation dose in computed tomography (CT) examinations is harmful for patients but can be significantly reduced by intuitively decreasing the number of projection views. Reducing projection views usually leads to severe aliasing artifacts in reconstructed images. Previous deep learning (DL) techniques with sparse-view data require sparse-view/full-view CT image pairs to train the network with supervised manners. When the number of projection view changes, the DL network should be retrained with updated sparse-view/full-view CT image pairs. To relieve this limitation, we present a fully unsupervised score-based generative model in sinogram domain for sparse-view CT reconstruction. Specifically, we first train a score-based generative model on full-view sinogram data and use multi-channel strategy to form highdimensional tensor as the network input to capture their prior distribution. Then, at the inference stage, the stochastic differential equation (SDE) solver and data-consistency step were performed iteratively to achieve fullview projection. Filtered back-projection (FBP) algorithm was used to achieve the final image reconstruction. Qualitative and quantitative studies were implemented to evaluate the presented method with several CT data. Experimental results demonstrated that our method achieved comparable or better performance than the supervised learning counterparts.Comment: 11 pages, 12 figure

Characterization of cellulase production by carbon sources in two Bacillus species

The induction of cellulase production in two Bacillus spp. was studied by means of measuring cellulase activities under the condition of different carbon sources. The results indicate that cellulase could not be induced by cellulose material as a sole carbon source. Instead, they could be induced by monosaccharide or disaccharide with reducing group. Moreover, the expression of cellulase components was synergistic. When cell wall/envelope enzyme and endoenzyme from two Bacillus spp. acted on these inducers, analysis of reaction products by high performance liquid chromatography (HPLC) revealed that cell wall/envelope enzyme and endoenzyme from two Bacillus spp. were inactive on these inducers. It also indicated that these inducers entered cells directly and served function of induction.Keywords: Bacillus, cellulase, induction, carbon source

Agonist Anti-GITR Monoclonal Antibody Induces Melanoma Tumor Immunity in Mice by Altering Regulatory T Cell Stability and Intra-Tumor Accumulation

In vivo GITR ligation has previously been shown to augment T-cell-mediated anti-tumor immunity, yet the underlying mechanisms of this activity, particularly its in vivo effects on CD4+ foxp3+ regulatory T cells (Tregs), have not been fully elucidated. In order to translate this immunotherapeutic approach to the clinic it is important gain better understanding of its mechanism(s) of action. Utilizing the agonist anti-GITR monoclonal antibody DTA-1, we found that in vivo GITR ligation modulates regulatory T cells (Tregs) directly during induction of melanoma tumor immunity. As a monotherapy, DTA-1 induced regression of small established B16 melanoma tumors. Although DTA-1 did not alter systemic Treg frequencies nor abrogate the intrinsic suppressive activity of Tregs within the tumor-draining lymph node, intra-tumor Treg accumulation was significantly impaired. This resulted in a greater Teff:Treg ratio and enhanced tumor-specific CD8+ T-cell activity. The decreased intra-tumor Treg accumulation was due both to impaired infiltration, coupled with DTA-1-induced loss of foxp3 expression in intra-tumor Tregs. Histological analysis of B16 tumors grown in Foxp3-GFP mice showed that the majority of GFP+ cells had lost Foxp3 expression. These “unstable” Tregs were absent in IgG-treated tumors and in DTA-1 treated TDLN, demonstrating a tumor-specific effect. Impairment of Treg infiltration was lost if Tregs were GITR−/−, and the protective effects of DTA-1 were reduced in reconstituted RAG1−/− mice if either the Treg or Teff subset were GITR-negative and absent if both were negative. Our results demonstrate that DTA-1 modulates both Teffs and Tregs during effective tumor treatment. The data suggest that DTA-1 prevents intra-tumor Treg accumulation by altering their stability, and as a result of the loss of foxp3 expression, may modify their intra-tumor suppressive capacity. These findings provide further support for the continued development of agonist anti-GITR mAbs as an immunotherapeutic strategy for cancer

Self-antigen–specific CD8+ T cell precursor frequency determines the quality of the antitumor immune response

A primary goal of cancer immunotherapy is to improve the naturally occurring, but weak, immune response to tumors. Ineffective responses to cancer vaccines may be caused, in part, by low numbers of self-reactive lymphocytes surviving negative selection. Here, we estimated the frequency of CD8+ T cells recognizing a self-antigen to be <0.0001% (∼1 in 1 million CD8+ T cells), which is so low as to preclude a strong immune response in some mice. Supplementing this repertoire with naive antigen-specific cells increased vaccine-elicited tumor immunity and autoimmunity, but a threshold was reached whereby the transfer of increased numbers of antigen-specific cells impaired functional benefit, most likely because of intraclonal competition in the irradiated host. We show that cells primed at precursor frequencies below this competitive threshold proliferate more, acquire polyfunctionality, and eradicate tumors more effectively. This work demonstrates the functional relevance of CD8+ T cell precursor frequency to tumor immunity and autoimmunity. Transferring optimized numbers of naive tumor-specific T cells, followed by in vivo activation, is a new approach that can be applied to human cancer immunotherapy. Further, precursor frequency as an isolated variable can be exploited to augment efficacy of clinical vaccine strategies designed to activate any antigen-specific CD8+ T cells

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

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

Regularized Multioutput Gaussian Convolution Process for Chemical Contents Data Imputation in Sintering Raw Materials

Chemical contents, the important quality indicators are crucial for the modeling of sintering process. However, the lack of these data can result in the biasedness of state estimation in sintering process. It, thus, greatly reduces the accuracy of modeling. Although there are some general imputation methods to tackle the data lackness, they rarely consider the interoutputs correlation and the negative impacts caused by incorrect prefilling. In this article, a novel sparse multioutput Gaussian convolution process (MGCP) modeling framework is proposed for data imputation. MGCP can flexibly mine the relationships between the outputs by a convolution of a sharing latent function and different Gaussian kernels. Moreover, the penalization terms are designed to weaken the false relationship between these outputs. To generalize the MGCP to a long-period case, dynamic time warping term is introduced to keep the global similarity between the original and estimated time series. Compared with several existing methods, the proposed method shows great superiority in sintering raw material contents estimation with real-world data