Metalloids - Crossref

Stable Isotope Fractionation of Metals and Metalloids in Plants: A Review

Ca and Mg fractionate via root apoplast adsorption, Si through diffusion during membrane passage, Fe and Cu by diffusion during membrane migration, Fe and Cu by reduction prior to membrane transport in strategy I plants, and Zn, Cu, and Cd by membrane transport during uptake. Plant fractionation is influenced by biotic factors, such as phenological stages and plant genetics, as well as abiotic factors. Mg, Cu, and Zn were all shown shifts in isotope fractionation patterns, suggesting that isotope process tracing can be used as a way to identify and quantify various uptake pathways in reaction to abiotic stresses. However, the determination of isotope fractionation in plants is difficult, because many isotope fractionation factors associated with particular procedures are unknown, and experiments are often exploratory. To fully exploit the potential of isotope process tracing in plants, the interdisciplinary expertise of plant and isotope geochemistry scientists is required.

Source link: https://doi.org/10.3389/fpls.2022.840941

Criticality of metals and metalloids

Significance Irmation Significance In the ten years, periodic metals and metalloids that have been integral to modern technology for over a decade have spawned attempts to determine the relative "criticality" of various materials as a guide to materials scientists and product designers. We design a comprehensive, adaptable, and transparent strategy that we use to 62 metals and metalloids in the present research.

Source link: https://doi.org/10.1073/pnas.1500415112

Association of Metals and Metalloids With Urinary Albumin/Creatinine Ratio: Evidence From a Cross-Sectional Study Among Elderly in Beijing

Few studies are focused on the correlation of urinary metals and metalloids concentrations with the urinary albumin/creatinine ratio among elderly people, particularly in areas and seasons of heavy air pollution. Method We conducted a cross-sectional survey in Beijing, which has seen China's most severe air pollution from November to December 2016. Using GLM, we discovered that among the 275 elderly people included in the study, elevated urinary Cu concentration was positively correlated with UACR use. The change in UACR from 25th to 75th percentile value in urinary Cu concentrations remained stable at their 25th, 50th, or 75th percentile values, according to the BKMR algorithm. Urinary Cu concentrations had the most notable positive effect on the qgcomp model, according to the most notable positive change in the qgcomp model.

Source link: https://doi.org/10.3389/fpubh.2022.832079

Heavy metals and metalloids accumulation in organs of some representatives of the genus Paeonia L. under technogenic pollution conditions

The paper investigates the physical and metalloid deposits produced by decorative flower crops on the example of the generic complex Paeonia L. in Ufa's urbanized urban environment. According to the method Determination of As, Pb, Cd, Sn, Cr, Cu, Fe, Mn, and Ni in samples of food raw materials by atomic absorption technique with electrothermal atomization, the determination of the elemental composition of the aboveground and underground parts was carried out. Mathematical data processing was carried out using generally accepted variation estimation methods using the AgCStat software package as a Excel add-in. The absolute values of the investigated elements in the proposed taxon of paeonies correlate with each other in a moderate and robust manner, according to the results of the correlation analysis.

Source link: https://doi.org/10.17816/snv2021104115

Features of heavy metals and metalloids accumulation in soils of Samara and Syzran large recreational zones

The paper discusses the findings of soil geochemical and geochemical investigations in the Sokoli Mountains, located near Samara, and in a special protected natural area Monastyrskaya Mountain, which is located within the boundaries of Samara Region's boundaries. The Sokoli Mountains' study areas are natural forests, while Monastyrskaya Mountain is an artificially planted forest stand. Heavy metals and metalloids accumulate more in the soils of the upper layer of Kuznetsov Mountain's vicinity than in the Monastyrskaya Mountain's sandy and loamy soils, which are characterized by greater geochemical heterogeneity. The soils of the Monastyrskaya Mountains dispersal processes are more apparent, while soils of the Kuznetsov Mountain surroundings accumulation processes are more visible.

Source link: https://doi.org/10.17816/snv202104

Role of Intestinal Microbiota in Transformation of Bismuth and Other Metals and Metalloids into Volatile Methyl and Hydride Derivatives in Humans and Mice

paramol h 1 kg 1 to 2,100 pmol h 1 kg p1 1 in human feces samples and from approximately 5 pmol h 1 to 120 pmol h 1 in mouse gut samples, respectively. The finding that the gut microbiota plays a key role in these transformation steps, as shown by the manufacture of volatile derivatives of various elements in feces samples, is backed up by the fact that germfree mice's gut segments are unable to convert administered bismuth to 3 Bi.

Source link: https://doi.org/10.1128/aem.02933-07

Contamination Assessment and Source Apportionment of Metals and Metalloids Pollution in Agricultural Soil: A Comparison of the APCA-MLR and APCA-GWR Models

Metals and metalloids accumulate in soil, causing not only soil erosion and crop yield reduction reduction, but also poses risks to human health. Generally, source apportionment methods produce a general relationship between sources and elements, which means that they do not have the ability to capture significant geographic variations of pollution sources. The present study uses a database from extensive sampling in the Shanghai study area and suggests a synthetic route to source attribution in the case of spatial heterogeneity by the integration of absolute principal component scores with geographically weighted regression. This review, in summary, highlights the use of a synthetic APCA-GWR model to effectively address source apportionment issues with spatial heterogeneity, providing more accurate and detailed pollution source data as well as safer references for pollution prevention and human health protection.

Source link: https://doi.org/10.3390/su14020783

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