Robust Face Recognition With Kernelized Locality-Sensitive Group Sparsity Representation

In this paper, a novel joint sparse representation method is proposed for robust face recognition. We embed both group sparsity and kernelized locality-sensitive constraints into the framework of sparse representation. The group sparsity constraint is designed to utilize the grouped structure information in the training data. The local similarity between test and training data is measured in the kernel space instead of the Euclidian space. As a result, the embedded nonlinear information can be effectively captured, leading to a more discriminative representation. We show that, by integrating the kernelized local-sensitivity constraint and the group sparsity constraint, the embedded structure information can be better explored, and significant performance improvement can be achieved. On the one hand, experiments on the ORL, AR, extended Yale B, and LFW data sets verify the superiority of our method. On the other hand, experiments on two unconstrained data sets, the LFW and the IJB-A, show that the utilization of sparsity can improve recognition performance, especially on the data sets with large pose variation

Transcript and protein profiling analysis of OTA-induced cell death reveals the regulation of the toxicity response process in Arabidopsis thaliana

Ochratoxin A (OTA) is a toxic isocoumarin derivative produced by various species of mould which mainly grow on grain, coffee, and nuts. Recent studies have suggested that OTA induces cell death in plants. To investigate possible mechanisms of OTA phytotoxicity, both digital gene expression (DGE) transcriptomic and two-dimensional electrophoresis proteomic analyses were used, through which 3118 genes and 23 proteins were identified as being up- or down-regulated at least 2-fold in Arabidopsis leaf in response to OTA treatment. First, exposure of excised Arabidopsis thaliana leaves to OTA rapidly causes the hypersensitive reponse, significantly accelerates the increase of reactive oxygen species and malondialdehyde, and enhances antioxidant enzyme defence responses and xenobiotic detoxification. Secondly, OTA stimulation causes dynamic changes in transcription factors and activates the membrane transport system dramatically. Thirdly, a concomitant persistence of compromised photosynthesis and photorespiration is indicative of a metabolic shift from a highly active to a weak state. Finally, the data revealed that ethylene, salicylic acid, jasmonic acid, and mitogen-activated protein kinase signalling molecules mediate the process of toxicity caused by OTA. Profiling analyses on Arabidopsis in response to OTA will provide new insights into signalling transduction that modulates the OTA phytotoxicity mechanism, facilitate mapping of regulatory networks, and extend the ability to improve OTA tolerance in Arabidopsis

Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer

Abstract: Stromal tumor-infiltrating lymphocytes (sTILs) are important prognostic and predictive biomarkers in triple-negative (TNBC) and HER2-positive breast cancer. Incorporating sTILs into clinical practice necessitates reproducible assessment. Previously developed standardized scoring guidelines have been widely embraced by the clinical and research communities. We evaluated sources of variability in sTIL assessment by pathologists in three previous sTIL ring studies. We identify common challenges and evaluate impact of discrepancies on outcome estimates in early TNBC using a newly-developed prognostic tool. Discordant sTIL assessment is driven by heterogeneity in lymphocyte distribution. Additional factors include: technical slide-related issues; scoring outside the tumor boundary; tumors with minimal assessable stroma; including lymphocytes associated with other structures; and including other inflammatory cells. Small variations in sTIL assessment modestly alter risk estimation in early TNBC but have the potential to affect treatment selection if cutpoints are employed. Scoring and averaging multiple areas, as well as use of reference images, improve consistency of sTIL evaluation. Moreover, to assist in avoiding the pitfalls identified in this analysis, we developed an educational resource available at www.tilsinbreastcancer.org/pitfalls

Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group

Funder: U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)Funder: National Center for Research Resources under award number 1 C06 RR12463-01, VA Merit Review Award IBX004121A from the United States Department of Veterans Affairs Biomedical Laboratory Research and Development Service, the DOD Prostate Cancer Idea Development Award (W81XWH-15-1-0558), the DOD Lung Cancer Investigator-Initiated Translational Research Award (W81XWH-18-1-0440), the DOD Peer Reviewed Cancer Research Program (W81XWH-16-1-0329), the Ohio Third Frontier Technology Validation Fund, the Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering and the Clinical and Translational Science Award Program (CTSA) at Case Western Reserve University.Funder: Susan G Komen Foundation (CCR CCR18547966) and a Young Investigator Grant from the Breast Cancer Alliance.Funder: The Canadian Cancer SocietyFunder: Breast Cancer Research Foundation (BCRF), Grant No. 17-194Abstract: Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer, as well as many other solid tumors. This recognition has come about thanks to standardized visual reporting guidelines, which helped to reduce inter-reader variability. Now, there are ripe opportunities to employ computational methods that extract spatio-morphologic predictive features, enabling computer-aided diagnostics. We detail the benefits of computational TILs assessment, the readiness of TILs scoring for computational assessment, and outline considerations for overcoming key barriers to clinical translation in this arena. Specifically, we discuss: 1. ensuring computational workflows closely capture visual guidelines and standards; 2. challenges and thoughts standards for assessment of algorithms including training, preanalytical, analytical, and clinical validation; 3. perspectives on how to realize the potential of machine learning models and to overcome the perceptual and practical limits of visual scoring

Application of a risk-management framework for integration of stromal tumor-infiltrating lymphocytes in clinical trials

Funder: Breast Cancer Research Foundation (BCRF); doi: https://doi.org/10.13039/100001006Abstract: Stromal tumor-infiltrating lymphocytes (sTILs) are a potential predictive biomarker for immunotherapy response in metastatic triple-negative breast cancer (TNBC). To incorporate sTILs into clinical trials and diagnostics, reliable assessment is essential. In this review, we propose a new concept, namely the implementation of a risk-management framework that enables the use of sTILs as a stratification factor in clinical trials. We present the design of a biomarker risk-mitigation workflow that can be applied to any biomarker incorporation in clinical trials. We demonstrate the implementation of this concept using sTILs as an integral biomarker in a single-center phase II immunotherapy trial for metastatic TNBC (TONIC trial, NCT02499367), using this workflow to mitigate risks of suboptimal inclusion of sTILs in this specific trial. In this review, we demonstrate that a web-based scoring platform can mitigate potential risk factors when including sTILs in clinical trials, and we argue that this framework can be applied for any future biomarker-driven clinical trial setting

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

A modified fixed current-mode controller for improved performance in quadratic boost converters

A modified fixed current-mode (CM) control for the quadratic boost converter in the presence of an uncertain load resistance is presented. Specifically, the existing CM control law is modified to include an additional proportional action and using a normalized output error in order to achieve improved performance. The extra proportional action helps to improve the relative stability. An approximate stability analysis was carried out to gain some useful insight into the proposed CM controlled system. Also, experimental results comparing the performance of the proposed controller with that of the traditional CM controllers under different operating conditions are presented

Comparative study of adaptive current-mode controllers for a hybrid-type high-order boost converter

A comparative study of two adaptive current-mode controllers for a high-order hybrid-type dc-dc boost converter is presented. The implementation of the traditional current-mode controller for this converter requires the knowledge of the nominal value of the load resistance to compute the control signal. As such, it is unable to handle systems with uncertain loads well. To address this, an adaptive law is used to estimate the load conductance in order to generate the reference current input. In this adaptive law, the derivative of the estimator is optimised as well as bounded. Moreover, the converter has two inductor currents which can be used for feedback purposes. Considering this, two adaptive current-mode controllers using the input and output inductor currents of the converter are separately designed to find the most appropriate inductor current for the implementation of the proposed controller. Finally, some simulation and experimental results comparing the performance of the adaptive controller using the output inductor current with that of the traditional current-mode controller are also presented.Published versio

Modified voltage-mode controller for the quadratic boost converter with improved output performance

The control of the quadratic boost converter with unknown load resistance and where only the output voltage is used for feedback purposes is addressed. In the existing voltage-mode controlled converter system, there exists a performance `trade-off' between the transient responses after the onset of a reference input and a load disturbance due to the usage of the traditional proportional-integral control scheme. To overcome these problems, a modified voltage-mode controller is proposed. The proposed controller uses a normalised integral action in which the derivative of the integrand is bounded by a user-defined constant. The approximate stability analysis of the resultant voltage-mode controlled quadratic boost converter system is carried out to gain some insight into its closed-loop behaviour. Some simulation and experimental results comparing the performance of the proposed controller with that of the existing controller are also provided to show the improvements obtained using the proposed controller.Accepted versio

A simplified output feedback controller for the DC-DC boost power converter

Boost-type dc-dc converters present non-minimum phase dynamic system characteristics. Therefore, controller design using only the output voltage for feedback purposes is not a very straightforward task. Even though output voltage control can be achieved using inductor current control, the implementation of such current-mode controllers may require prior knowledge of the load resistance and also demand more states such as one or more currents in feedback. In this paper, the development of a new output feedback controller for boost-type dc-dc converters is presented. The controller form is such that it avoids the possibility of saturation in the control signal due to division by zero. The basic structure of the proposed controller is firstly obtained from the expression of the open-loop control signal, and the complete controller structure is then derived to satisfy the closed-loop stability conditions. Simulation and experimental results clearly verify the ability of the control law to provide robust regulation against parameter variations.Published versio