Elemental analysis of particulate matter by X-ray fluorescence methods: A green approach to air quality monitoring

This review explores X-ray fluorescence (XRF) spectrometry for elemental analysis of particulate matter (PM) for air quality monitoring. The introduction presents PM classification based on size and composition, covering various elemental analysis methods while highlighting the increasing interest in XRF due to its non-destructive, rapid, and green features. The fundamental concepts of XRF and the experimental configurations commonly used are discussed, focusing on Energy Dispersive X-Ray Fluorescence (EDXRF) and Total Reflection X-Ray Fluorescence (TXRF). PM sampling devices and substrate are described, with a specific emphasis on filtering membranes for EDXRF and reflecting substrates for TXRF. Sample preparation strategies and procedures are presented. Qualitative and quantitative analysis is described, with a particular focus on the calibration approaches implemented for PM. Finally, the challenges faced by XRF in becoming a recognized reliable analytical technique for PM analysis, comparable to other standardized techniques for PM filters analysis, while capitalizing on its green advantages

Application of benchtop total-reflection X-ray fluorescence spectrometry and chemometrics in classification of origin and type of Croatian wines

The contents of selected metals (K, Ca, Fe, Cu, Zn, Mn, Sr, Rb, Ba, Pb, Ni, Cr and V) in 70 wine samples from Continental and Adriatic part of Croatia and different types of wine (red and white) were determined by TXRF. The aim of this study was to compare the elemental composition of wines from two different regions and to determine the discriminant ability of each variable and to indicate which variables discriminate between the four categories considered. Principal component analysis and cluster analysis showed that K, Mn, Ba and Ni can be considered as the most important characteristics to distinguish between Continental red and white wines, Rb, Ni and Ba for Continental red and Adriatic red wines while Sr is the only metal that completely distinguishes the samples of each category. Finally, linear discriminant analysis showed good recognition (100%) and prediction abilities (96.43%) using these selected elements

waste silica sources as heavy metal stabilizers for municipal solid waste incineration fly ash

Abstract The present work discusses a new method, based on the use of silica fume, for heavy metal stabilization. The inertization procedure is reported and compared with other technologies, involving the employ of amorphous silica as stabilizing agent for municipal solid waste incinerator fly ash treatment (i.e. colloidal silica and rice husk ash). The obtained final materials are characterized in terms of chemical composition and phase analysis. The reported method, realized at room temperature, employs all waste or by-product materials. As a consequence it appears to be economically and environmentally sustainable

Formation of stacked ER cisternae by low affinity protein interactions

The endoplasmic reticulum (ER) can transform from a network of branching tubules into stacked membrane arrays (termed organized smooth ER [OSER]) in response to elevated levels of specific resident proteins, such as cytochrome b(5). Here, we have tagged OSER-inducing proteins with green fluorescent protein (GFP) to study OSER biogenesis and dynamics in living cells. Overexpression of these proteins induced formation of karmellae, whorls, and crystalloid OSER structures. Photobleaching experiments revealed that OSER-inducing proteins were highly mobile within OSER structures and could exchange between OSER structures and surrounding reticular ER. This indicated that binding interactions between proteins on apposing stacked membranes of OSER structures were not of high affinity. Addition of GFP, which undergoes low affinity, antiparallel dimerization, to the cytoplasmic domains of non–OSER-inducing resident ER proteins was sufficient to induce OSER structures when overexpressed, but addition of a nondimerizing GFP variant was not. These results point to a molecular mechanism for OSER biogenesis that involves weak homotypic interactions between cytoplasmic domains of proteins. This mechanism may underlie the formation of other stacked membrane structures within cells

Targeting and Function of the Mitochondrial Fission Factor GDAP1 Are Dependent on Its Tail-Anchor

Proteins controlling mitochondrial dynamics are often targeted to and anchored into the mitochondrial outer membrane (MOM) by their carboxyl-terminal tail-anchor domain (TA). However, it is not known whether the TA modulates protein function. GDAP1 is a mitochondrial fission factor with two neighboring hydrophobic domains each flanked by basic amino acids (aa). Here we define GDAP1 as TA MOM protein. GDAP1 carries a single transmembrane domain (TMD) that is, together with the adjacent basic aa, critical for MOM targeting. The flanking N-terminal region containing the other hydrophobic domain is located in the cytoplasm. TMD sequence, length, and high hydrophobicity do not influence GDAP1 fission function if MOM targeting is maintained. The basic aa bordering the TMD in the cytoplasm, however, are required for both targeting of GDAP1 as part of the TA and GDAP1-mediated fission. Thus, this GDAP1 region contains critical overlapping motifs defining intracellular targeting by the TA concomitant with functional aspects

Strategies to develop radiomics and machine learning models for lung cancer stage and histology prediction using small data samples

Predictive models based on radiomics and machine-learning (ML) need large and annotated datasets for training, often difficult to collect. We designed an operative pipeline for model training to exploit data already available to the scientific community. The aim of this work was to explore the capability of radiomic features in predicting tumor histology and stage in patients with non-small cell lung cancer (NSCLC). We analyzed the radiotherapy planning thoracic CT scans of a proprietary sample of 47 subjects (L-RT) and integrated this dataset with a publicly available set of 130 patients from the MAASTRO NSCLC collection (Lung1). We implemented intra- and inter-sample cross-validation strategies (CV) for evaluating the ML predictive model performances with not so large datasets. We carried out two classification tasks: histology classification (3 classes) and overall stage classification (two classes: stage I and II). In the first task, the best performance was obtained by a Random Forest classifier, once the analysis has been restricted to stage I and II tumors of the Lung1 and L-RT merged dataset (AUC = 0.72 ± 0.11). For the overall stage classification, the best results were obtained when training on Lung1 and testing of L-RT dataset (AUC = 0.72 ± 0.04 for Random Forest and AUC = 0.84 ± 0.03 for linear-kernel Support Vector Machine). According to the classification task to be accomplished and to the heterogeneity of the available dataset(s), different CV strategies have to be explored and compared to make a robust assessment of the potential of a predictive model based on radiomics and ML

Bacterial Transmembrane Proteins that Lack N-Terminal Signal Sequences

Tail-anchored membrane proteins (TAMPs), a class of proteins characterized by their lack of N-terminal signal sequence and Sec-independent membrane targeting, play critical roles in apoptosis, vesicle trafficking and other vital processes in eukaryotic organisms. Until recently, this class of membrane proteins has been unknown in bacteria. Here we present the results of bioinformatic analysis revealing proteins that are superficially similar to eukaryotic TAMPs in the bacterium Streptomyces coelicolor. We demonstrate that at least four of these proteins are bona fide membrane-spanning proteins capable of targeting to the membrane in the absence of their N-terminus and the C-terminal membrane-spanning domain is sufficient for membrane targeting. Several of these proteins, including a serine/threonine kinase and the SecE component of the Sec translocon, are widely conserved in bacteria

Integrated management of ash from industrial and domestic combustion : a new sustainable approach for reducing greenhouse gas emissions from energy conversion

This work supports, for the first time, the integrated management of waste materials arising from industrial processes (fly ash from municipal solid waste incineration and coal fly ash), agriculture (rice husk ash), and domestic activities (ash from wood biomass burning in domestic stoves). The main novelty of the paper is the reuse of wood pellet ash, an underestimated environmental problem, by the application of a new technology (COSMOS-RICE) that already involves the reuse of fly ashes from industrial and agricultural origins. The reaction mechanism involves carbonation: this occurs at room temperature and promotes permanent carbon dioxide sequestration. The obtained samples were characterized using XRD and TGA (coupled with mass spectroscopy). This allowed quantification of the mass loss attributed to different calcium carbonate phases. In particular, samples stabilized using wood pellet ash show a weight loss, attributed to the decomposition of carbonates greater than 20%. In view of these results, it is possible to conclude that there are several environmental benefits from wood pellet ash reuse in this way. In particular, using this technology, it is shown that for wood pellet biomass the carbon dioxide conversion can be considered negative