Towards a global EDGAR‐inventory of particulate matter with focus on elemental carbon

The Emissions Database for Global Atmospheric Research (EDGAR) provides technology based global anthropogenic emissions data of greenhouse gases and air pollutants by country and sector on a 0.1° x 0.1° spatial grid, on a timeline that ranges from 1970 to present days. As part of the constantly ongoing amendment and improvement of the database, a review of the available literature and emission inventory data has been conducted focusing on particulate emissions, with the aim of acquiring a comprehensive array of primary particle matter and carbonaceous particle emission factors (EF). It was found, that emission factor data from different studies show large variation for a given fuel and technology. Furthermore it is plausible that a certain literature or measurement describes emission factors better in the region where it is originating from. With this in mind, a comparison has been made between the available emission factor datasets in a number of different regions, focusing on the power generation sector. The aim of this experiment is to select the most appropriate EF dataset for a given region.JRC.H.2-Air and Climat

Convex Constraint Decomposition of Circular Dichroism Curves of Proteins

A new algorithm, called convex analysis, has been developed to deduce the chiral contribution of the common secondary structures directly from experimental circular dichroism (CD) curves of a large number of proteins. The analysis is based on CD data reported by Yang et aU Test runs were performed on sets of artificial protein spectra created by the Monte Carlo technique using poly-u-Iysine based component spectra. Application of the decomposition algorithm for the created sets of spectra resulted in component spectra [B (2, i)] and weights [C (i, k)] with excellent Pearson correlation coefficients (r).2 The algori thm, independent of X-ray data, revealed that the CD spectrum of a given protein is composed of at least four independent sources of chirality. Three of the computed component curves show remarkable resemblance to the CD spectra of known protein secondary structures. This approach yields a significant improvement compared to the eigenvector analysis of Hennessey and Johnson." The new method is a useful tool not only in analyzing CD spectra but also in treating other decomposition problems where an additivity constraint is valid

Deep Learning-Based Super-Resolution Applied to Dental Computed Tomography

The resolution of dental computed tomography (CT) images is limited by detector geometry, sensitivity, patient movement, the reconstruction technique and the need to minimize radiation dose. Recently, the use of convolutional neural network (CNN) architectures has shown promise as a resolution enhancement method. In the current work, two CNN architectures—a subpixel network and the so called U-net—have been considered for the resolution enhancement of 2-D cone-beam CT image slices of ex vivo teeth. To do so, a training set of 5680 cross-sectional slices of 13 teeth and a test set of 1824 slices of 4 structurally different teeth were used. Two existing reconstruction-based super-resolution methods using l2-norm and total variation regularization were used for comparison. The results were evaluated with different metrics (peak signal-to-noise ratio, structure similarity index, and other objective measures estimating human perception) and subsequent image-segmentation-based analysis. In the evaluation, micro-CT images were used as ground truth.The results suggest the superiority of the proposed CNN-based approaches over reconstruction-based methods in the case of dental CT images, allowing better detection of medically salient features, such as the size, shape, or curvature of the root canal

Association of symptoms of insomnia and sleep parameters among kidney transplant recipients

Objective: Insomnia complaints are frequent among kidney transplant (kTx) recipients and are associated with fatigue, depression, lower quality of life and increased morbidity. However, it is not known if subjective insomnia symptoms are associated with objective parameters of sleep architecture. Thus, we analyze the association between sleep macrostructure and EEG activity versus insomnia symptoms among kTx recipients. Methods: Participants (n1 = 100) were selected from prevalent adult transplant recipients (n0 = 1214) followed at a single institution. Insomnia symptoms were assessed by the Athens Insomnia Scale (AIS) and standard overnight polysomnography was performed. In a subgroup of patients (n2 = 56) sleep microstructure was also analyzed with power spectral analysis. Results: In univariable analysis AIS score was not associated with sleep macrostructure parameters (sleep latency, total sleep time, slow wave sleep, wake after sleep onset), nor with NREM and REM beta or delta activity in sleep microstructure. In multivariable analysis after controlling for covariables AIS score was independently associated with the proportion of slow wave sleep (β = 0.263; CI: 0.026–0.500) and REM beta activity (β = 0.323; CI = 0.041–0.606) (p < 0.05 for both associations). Conclusions: Among kTx recipients the severity of insomnia symptoms is independently associated with higher proportion of slow wave sleep and increased beta activity during REM sleep but not with other parameters sleep architecture. The results suggest a potential compensatory sleep protective mechanism and a sign of REM sleep instability associated with insomnia symptoms among this population

Tumor-Associated Disialylated Glycosphingolipid Antigen-Revealing Antibodies Found in Melanoma Patients' Immunoglobulin Repertoire Suggest a Two-Direction Regulation Mechanism Between Immune B Cells and the Tumor

There is far less information available about the tumor infiltrating B (TIL-B) cells, than about the tumor infiltrating T cells. We focused on discovering the features and potential role of B lymphocytes in solid tumors. Our project aimed to develop innovative strategies to define cancer membrane structures. We chose two solid tumor types, with variable to considerable B cell infiltration. The strategy we set up with invasive breast carcinoma, showing medullary features, has been introduced and standardized in metastatic melanoma. After detecting B lymphocytes by immunohistochemistry, VH-JH, Vκ-Jκ immunoglobulin rearranged V region genes were amplified by RT-PCR, from TIL-B cDNA. Immunoglobulin variable-region genes of interest were cloned, sequenced, and subjected to a comparative DNA analysis. Single-chain variable (scFv) antibody construction was performed in selected cases to generate a scFv library and to test tumor binding capacity. DNA sequence analysis revealed an overrepresented VH3-1 cluster, represented both in the breast cancer and the melanoma TIL-B immunoglobulin repertoire. We observed that our previously defined anti GD3 ganglioside-binder antibody-variable region genes were present in melanoma as well. Our antibody fragments showed binding potential to disialylated glycosphingolipids (GD3 ganglioside) and their O acetylated forms on melanoma cancer cells. We conclude that our results have a considerable tumor immunological impact, as they reveal the power of TIL-B cells to recognize strong tumor-associated glycosphingolipid structures on melanomas and other solid tumors. As tumor-derived gangliosides affect immune cell functions and reduce the B lymphocytes' antibody production, we suspect an important B lymphocyte and cancer cell crosstalk mechanism. We not only described the isolation and specificity testing of the tumor infiltrating B cells, but also showed the TIL-B cells' highly tumor-associated GD3 ganglioside-revealing potential in melanomas. The present data help to identify new cancer-associated biomarkers that may serve for novel cancer diagnostics. The two-direction regulation mechanism between immune B cells and the tumor could eventually be developed into an innovative cancer treatment strategy