Automated identification and quantification of myocardial inflammatory infiltration in digital histological images to diagnose myocarditis

This study aims to develop a new computational pathology approach that automates the identification and quantification of myocardial inflammatory infiltration in digital HE-stained images to provide a quantitative histological diagnosis of myocarditis.898 HE-stained whole slide images (WSIs) of myocardium from 154 heart transplant patients diagnosed with myocarditis or dilated cardiomyopathy (DCM) were included in this study. An automated DL-based computational pathology approach was developed to identify nuclei and detect myocardial inflammatory infiltration, enabling the quantification of the lymphocyte nuclear density (LND) on myocardial WSIs. A cutoff value based on the quantification of LND was proposed to determine if the myocardial inflammatory infiltration was present. The performance of our approach was evaluated with a five-fold cross-validation experiment, tested with an internal test set from the myocarditis group, and confirmed by an external test from a double-blind trial group. An LND of 1.02/mm2 could distinguish WSIs with myocarditis from those without. The accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) in the five-fold cross-validation experiment were 0.899 plus or minus 0.035, 0.971 plus or minus 0.017, 0.728 plus or minus 0.073 and 0.849 plus or minus 0.044, respectively. For the internal test set, the accuracy, sensitivity, specificity, and AUC were 0.887, 0.971, 0.737, and 0.854, respectively. The accuracy, sensitivity, specificity, and AUC for the external test set reached 0.853, 0.846, 0.858, and 0.852, respectively. Our new approach provides accurate and reliable quantification of the LND of myocardial WSIs, facilitating automated quantitative diagnosis of myocarditis with HE-stained images.Comment: 21 pages,5 figures,6 Tables, 25 reference

Mesenchymal stem cells alleviate bacteria‐induced liver injury in mice by inducing regulatory dendritic cells

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/102718/1/hep26670.pd

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

Dual Feature Fusion Tracking With Combined Cross-Correlation and Transformer

Siamese networks have found applications in various fields, notably object tracking, due to their remarkable speed and accuracy. Siamese tracking networks rely on cross-correlation to obtain the similarity score between the target template and the search region. However, since cross-correlation is a local matching operation, it cannot effectively capture the global context information. While the Transformer for feature fusion can better capture long-range dependencies and obtain more semantic information, more localized edge information is needed to distinguish the target from the background. Cross-correlation fusion and Transformer fusion have their advantages. They can complement each other, so we combine them and propose a dual feature fusion tracker (SiamCT) to obtain the local correlations and global dependencies between the target and the search region. Specifically, we construct two parallel feature fusion paths based on cross-correlation and Transformer. Among them, for cross-correlation fusion, we adopt the more efficient two-dimension pixel-wise cross-correlation (TDPC), which performs correlation operations from both spatial and channel dimensions, and the interaction of multidimensional information helps to realize more accurate feature fusion. Subsequently, the fused features are augmented by coordinate attention (CA) for orientation-dependent positional information. For Transformer fusion, we introduce cos-based linear attention(ClA) to improve Transformer&#x2019;s ability to acquire global context information. Our SiamCT outperforms existing leading methods in GOT-10k, LaSOT, TrackingNet, and OTB100 benchmarks based on extensive experiments. In particular, the AO score on the GOT-10k benchmark is 70.6&#x0025;, and the ${SR_{0.5}}$ and ${SR_{0.75}}$ scores are 80.5&#x0025;, 65.9&#x0025;, respectively, achieving state-of-the-art performance

catalyticconversionofcellulosebasedbiomassandglyceroltolacticacid

Catalytic transformation of cellulose into value-added chemicals is of great importance for utilization of renewable and abundant biomass. Due to the high oxygen content, cellulose serves as an ideal candidate for the production of oxygenates, in particular lactic acid which is a versatile building block in chemical industry. The efficient conversion of cellulose to lactic acid generally requires selective activation of specific C-O and C-C bonds, and therefore multifunctional catalysts that combine several key reactions including hydrolysis, isomerization and retro-aldol fragmentation are highly desirable. This review article highlights the recently developed catalytic systems and catalysts for the selective transformation of cellulose and cellulose-derived carbohydrates into lactic acid, lactates and/or its esters. Emphases will be put on the reaction mechanism and key factors that exert effects on the catalytic performances. In addition, the catalytic transformation of glycerol, a C3 compound over-supplied from biodiesel industry, will also be surveyed. Recent advances in the development of new catalysts or strategies are analyzed and discussed to gain insight into the transformation of C3 compound to lactic acid

Interactive relighting with dynamic BRDFs

We present a technique for interactive relighting in which source radiance, viewing direction, and BRDFs can all be changed on the fly. In handling dynamic BRDFs, our method efficiently accounts for the effects of BRDF modification on the reflectance and incident radiance at a surface point. For reflectance, we develop a BRDF tensor representation that can be factorized into adjustable terms for lighting, viewing, and BRDF parameters. For incident radiance, there exists a non-linear relationship between indirect lighting and BRDFs in a scene, which makes linear light transport frameworks such as PRT unsuitable. To overcome this problem, we introduce precomputed transfer tensors (PTTs) which decompose indirect lighting into precomputable components that are each a function of BRDFs in the scene, and can be rapidly combined at run time to correctly determine incident radiance. We additionally describe a method for efficient handling of high-frequency specular reflections by separating them from the BRDF tensor representation and processing them using precomputed visibility information. With relighting based on PTTs, interactive performance with indirect lighting is demonstrated in applications to BRDF animation and material tuning

catalyticconversionofcellulosebasedbiomassandglyceroltolacticacid

Catalytic transformation of cellulose into value-added chemicals is of great importance for utilization of renewable and abundant biomass. Due to the high oxygen content, cellulose serves as an ideal candidate for the production of oxygenates, in particular lactic acid which is a versatile building block in chemical industry. The efficient conversion of cellulose to lactic acid generally requires selective activation of specific C-O and C-C bonds, and therefore multifunctional catalysts that combine several key reactions including hydrolysis, isomerization and retro-aldol fragmentation are highly desirable. This review article highlights the recently developed catalytic systems and catalysts for the selective transformation of cellulose and cellulose-derived carbohydrates into lactic acid, lactates and/or its esters. Emphases will be put on the reaction mechanism and key factors that exert effects on the catalytic performances. In addition, the catalytic transformation of glycerol, a C3 compound over-supplied from biodiesel industry, will also be surveyed. Recent advances in the development of new catalysts or strategies are analyzed and discussed to gain insight into the transformation of C3 compound to lactic acid

Left ventricular systolic and diastolic dyssynchrony to improve cardiac resynchronization therapy response in heart failure patients with dilated cardiomyopathy.

BACKGROUND: The systolic and diastolic dyssynchrony is physiologically related, but measure different left ventricular mechanisms. Left ventricular systolic mechanical dyssynchrony (systolic LVMD) has shown significant clinical values in improving cardiac resynchronization therapy (CRT) response in the heart failure patients with dilated cardiomyopathy (DCM). Our recent study demonstrated that LV diastolic dyssynchrony (diastolic LVMD) parameters have important prognostic values for DCM patients. However, there are a limited number of studies about the clinical value of diastolic LVMD for CRT. This study aims to explore the predictive values of both systolic LVMD and diastolic LVMD for CRT in DCM patients. METHODS: Eighty-four consecutive CRT patients with both DCM and complete left bundle branch block (CLBBB) who received gated resting SPECT MPI at baseline were included in the present study. The phase analysis technique was applied on resting gated short-axis SPECT MPI images to measure systolic LVMD and diastolic LVMD, characterized by phase standard deviation (PSD) and phase histogram bandwidth (PBW). CRT response was defined as ≥ 5% improvement of LVEF at 6-month follow-up. Variables with P \u3c 0.10 in the univariate analysis were included in the multivariate cox analysis. RESULTS: During the follow-up period, 59.5% (50 of 84) patients were CRT responders. The univariate cox regression analysis showed that at baseline QRS duration, non-sustained ventricular tachycardia (NS-VT), systolic PSD, systolic PBW, diastolic PSD, diastolic PBW, scar burden and LV lead in the scarred myocardium were statistically significantly associated with CRT response. The multivariate cox regression analysis showed that QRS duration, NS-VT, systolic PSD, systolic PBW, diastolic PSD, and diastolic PBW were independent predictive factors for CRT response. Furthermore, the rate of CRT response was 94.4% (17 of 18) in patients whose LV lead was in the segments with both the first three late contraction and the first three late relaxation; by contrast, the rate of CRT response was only 6.7% (1 of 15, P \u3c 0.000) in patients whose LV lead was in the segments with neither the first three late contraction nor the first three late relaxation. CONCLUSION: Both systolic LVMD and diastolic LVMD from gated SPECT MPI have important predictive values for CRT response in DCM patients. Pacing at LV segments with both late contraction and late relaxation has potential to increase the CRT response