Assessment of the Atmospheric Deposition of Potentially Toxic Elements Using Moss Pleurozium schreberi in an Urban Area: The Perm (Perm Region, Russia) Case Study.

Assessment of air quality in urban areas is very important because pollutants affect both the environment and human health. In Perm (Russia), a moss biomonitoring method was used to assess the level of air pollution. The concentrations of 15 elements in 87 samples of moss Pleurozium schreberi in the city territory were determined using a direct mercury analyzer and an inductively coupled plasma atomic emission spectroscopy. Using factor and correlation analyses, the grouping of elements and their relationship with emission sources were established. The main sources of emissions of potentially toxic elements are the transportation (road and rail), metallurgical, and chemical industries. The level of atmospheric air pollution was assessed by calculating the environmental risk index, pollutant load index, and pollution coefficient. Based on the values of the pollution index, the level of atmospheric air pollution in Perm varies from unpolluted to highly polluted, with moderate environmental risk.

A comparative thermo-chemical characterization of oilseed, millet and pulse stem biomass for bioethanol production.

Various thermochemical and biochemical processes are resorted to transform agri-wastes into diverse green fuels. Current investigation encompassed three different types of biomass viz., gingelly, kodo millet and horse grams, whose desirability as biofuel feedstock have been largely unexplored till date. The existence of significant amount of cellulose (38.07 %), volatiles (75.19 %), calorific value (avg. 16.98 MJ/kg) in the gingelly biomass, demonstrates the effectiveness of the concerned biomass for utilization as feedstock in diverse industrial applications. The mean estimates of Eα were lower for kodo millet (approx. 150 kJ/mole), followed by gingelly (approx. 178 kJ/mole) and horse gram (approx. 180 kJ/mole). The mean estimates of ΔHα were 174.81 (FWO), 170.22 (KAS), 169.17 (S) and 170.40 (T) kJ/mol for the gingelly biomass. The mean estimates of ΔHα were 147.83 (FWO), 148.81 (KAS), 147.93 (S) and 149.04 (T) kJ/mol for kodo millet biomass, while for horse gram biomass, mean estimates of ΔHα were 178.91 (FWO), 169.61 (KAS), 168.56 (S) and 168.81 (T) kJ/mol. The minor difference of 3-4 kJ/mole between Aα and Hα, signifies the viability of the thermal disintegration process. From master plot, it's evident that the experimental curve intersects multiple theoretical curves, highlighting the intricate characteristics of the thermal disintegration process. The overall ethanol recovery was highest in gingelly as compared to both the biomasses. Gingelly biomass yielded an ethanol titer of 24.8 g/L after 24 h, resulting in a volumetric ethanol productivity of 1.03 g/L/h and an ethanol yield of 0.36 g/g.

Assessment of physicochemical properties and radioactivity in groundwater at households living in bac Lieu province, vietnam.

This paper presents findings on groundwater physiochemical composition and radioactivity levels in households in Bac Lieu province, Vietnam. Through discriminant analysis, it was observed that groundwater quality exhibits spatial variations corresponding to saline intrusion zones. The paired-samples T-tests revealed significantly different ratios of Ra-224, Ra-226, and Ra-228 isotopes between Na-Cl and Ca-Na-HCO3 water types. All three water types had a ratio of Ra-226/Ra-228 of approximately one, indicating the presence of groundwater aquifers beneath the crust and fluvial marine sediment. Furthermore, strong associations between sulfate and calcium suggest that CO2 enrichment in groundwater aquifers indicates anoxic aquatic environments. Twenty-five of the thirty-three evaluated samples exceeded the national technical regulations for domestic water quality with parameters such as chloride, sulfate, sodium, gross alpha, or total dissolved solids. Fifteen samples exceeded gross alpha's allowable contamination threshold of 0.1 Bq/L. The combination of Ra-226 and Ra-228 did not surpass the U.S. Environmental Protection Agency's recommended limit of 0.185 Bq/L. However, nineteen samples exhibited annual committed effective doses of radium isotopes for infants that exceeded the WHO recommendation of 0.1 mSv/year.

Quantitative analysis and health risk assessment of selected heavy metals in pet food samples using ultrasound assisted hydrogen peroxide extraction followed by ICP-OES analysis.

There is a lack of information regarding the presence of heavy metals in feed ingredients for animals. Therefore, this study examines 10 feed samples collected from commercial pet food in South African market. The optimal working parameters for ultrasound assisted hydrogen peroxide extraction (UA-HPE) confirmed by multivariate optimization were sonication temperature at 80 °C for 60 min, sample mass of 0.1 g, and H2O2 concentration of 5 mol/L. The UA-HPE results demonstrated high accuracy of (>95%), reproducibility (≤1.9%), low method of detection limits (0.3498 and 0.49 µg/g), and strong linearity as confirmed by regression analysis. The environmental friendliness of the UA-HPE method was assessed using AGREEPrep metric tool that resulted with a score of 0.74. The concentration levels of Cd, Pb and As, ranged between 0.86 and 11.34, 4.50-11.45, and 2.61-12.5 µg/g, respectively greater than the standardized limits, whilst Cr, and Sn were below the limits of detection in all pet food. The health index calculations (HI > 1) revealed that the cat, dog, and horse feed pose health risk for animal consumption. Consequently, this study demonstrated a green, efficient, and cost-effective method for the analysis of animal feed with high accuracy.

Determination of trace elements content of fruits from Tehran's market using ICP- OES method: a risk assessment study.

For the first time in Iran, in this study, the amount of 19 trace elements in some types of commonly consumed Iranian fruits (in their peel and pulp) was evaluated by ICP-OES (Inductively coupled plasma-optical emission spectrometry) method. Based on the outcomes, the highest and lowest average detected elements in all fruits samples were related to (Al) aluminum (1842.18) and (V) vanadium (0.28) ppm, respectively. Mercury (Hg) and antimony (Sb) were not detected (ND) in any samples. Also, the maximum mean of elements in quince, lemon, grapefruit, kiwi, orange south, orange north and tangerine samples was related to(Fe) iron (2048.32 ppm), (Zn)zinc(753.45 ppm), Fe (1056.33 ppm), Al (9794.41 ppm), Zn (717.78 ppm), Fe (1334.87 ppm) and Fe (974.93 ppm), respectively. Furthermore, our outcomes revealed, the highest mean of elements in kiwi peel, kiwi pulp, orange North peel, orange North pulp, orange South peel, orange South pulp, quince peel, quince pulp, grapefruit peel, grapefruit pulp, lemon peel, lemon pulp, tangerine peel and tangerine pulp was related to Al (17967.79 ppm), Al (1621.03 ppm), Fe (1350.01 ppm), Al (1457.66 ppm), Zn (934.71 ppm), Fe (728.06 ppm), Fe (2768.11 ppm), Fe (1328.54 ppm), Zn (1008.54 ppm), Fe (1198.00 ppm), Zn (683.35 ppm), Zn (823.55 ppm), Fe (1182.59 ppm), and Fe (767.27 ppm), respectively. Based on the Monte Carlo simulation results, the THQ (target hazard quotient) and ILCR (Incremental Lifetime Cancer Risk) related to exposure to heavy metals via fruits for adults and children showed that there is no significant non-carcinogenic risk (THQ < 1) and carcinogenic risk (ILCR < 1E-4) for adults and children.

Source Identification of Potentially Toxic Metals in Plants of Alpine Ecosystems of Mt. Madra by Positive Matrix Factorization.

In this study, the concentrations of cadmium (Cd), iron (Fe), manganese (Mn), nickel (Ni), lead (Pb) and zinc (Zn) in plants sampled from Mt. Madra were investigated. Furthermore, the distribution characteristics and source identification of potentially toxic metals were investigated with the application of Positive Matrix Factorization (PMF) modelling. Samples of 26 different plant species were taken from Mt. Madra at elevations ranging from 177 to 1347 m using the multi-point sampling approach. The metal quantities measured by ICP-OES are the following sequences (mean ± SD) (mg/kg): Fe (974.96 ± 29.6) > Mn (111.81 ± 2.6) > Zn (27.28 ± 0.2) > Ni (2.17 ± 0.03) > Pb (0.77 ± 0.01) > Cd (0.12 ± 0.01). According to the plant samples in which the highest values were determined, the metals are as follows: Cd (Lathyrus laxiflorus, 0.401 mg/kg), Fe (Ajuga orientalis, 7621.207 mg/kg), Mn (Castanea sativa, 724.927 mg/kg), Ni (Prunella laciniata, 6.947 mg/kg), Pb (Crataegus stevenii, 3.955 mg/kg) and Zn (Prunella laciniata, 50.802 mg/kg). The results of the PMF model showed that Cd had an atmospheric transport factor originated and transported from industrial activites, Ni had a substrate factor, Fe, Mn, Pb and Zn were influenced by different anthropogenic factors.

Tracking the Mandorla di Avola Almond Variety by Means of ICP Analysis.

The Mandorla di Avola is recognized all over the world as one of the best almond varieties. It is cultivated in a small area inside the provinces of Siracusa and Ragusa (Sicily, southern Italy). It is used in traditional Sicilian cuisine for both salty and sweet foods and of course in artisan pastry, apart from being consumed as a fruit. Due to its extraordinary organoleptic and beneficial features, the Mandorla di Avola is frequently counterfeit with almond varieties of lower quality coming from other countries. While its nutraceutical features have been studied, the possibility of authenticating it with respect to other varieties has not been explored. In this work, we used microelements determined with ICP-OES and ICP-MS as chemical descriptors to distinguish samples of Mandorla di Avola almonds from almonds coming from California and Spain, which are usually employed as substitutes in pastry. Among the different elements determined, Mn and P were found to be the best descriptors for authentication.

Investigating Trace and Macro-element Composition of Herbal and Nutraceutical Dietary Supplements Marketed in Oman: Insights into Safety and Labeling.

With the global increase in the use of dietary supplements to provide nutrients in one's regular diet, these supplements' potential health risks and benefits have become a topic of significant interest. Interestingly, as dietary supplements, the Food and Drug Administration (FDA) in the United States (USA), Europe, and most countries do not require manufacturers and distributors to obtain approval or provide safety assessments before marketing those products. This research explores for the first time 16 heavy, trace and macro-elemental contents, namely, As, Ni, Cd, Pb, Cu, Co, Mn, Cr, Zn, V, Fe, Al, K, Na, Mg, and Ca, within 24 nutraceutical and herbal supplements marketed in Oman. The research is focusing on ensuring their compositions, concentrations, and freedom of toxic elements. ICP-OES was utilized, preceded by a microwave digestion technique to digest the samples in concentrated HNO3 and HCl (3:1, v/v). The method was validated within linear ranges of 0.03-5.00 ppm and 1.0-200.0 ppm for micro- and macro-elements, respectively, with %recoveries ranging from 90 to 104%. The limits of detection ranged from 0.01 to 0.09 and 0.14 to 0.30 ppm, while the limits of quantification ranged from 0.03 to 0.28 and 0.46 to 0.91 ppm for micro- and macro-elements, respectively. The detected levels were compared to online databases for risk assessment. Although As and Cd were not detected in all samples, Pb was found in nine samples, with some exceeding regulated limits of exposure. About 80% of the samples contained Al, of which two samples were susceptible to serious health risks of exceeding exposure limits in their compiled doses. The locally harvested Omani herbal supplements revealed significant amounts of Zn, Mg, Mn, and Cu. The results highlighted the potential risks associated with both dosage compliance and labeling discrepancies.

Adsorption Dynamics of Disodium Octaborate Tetrahydrate on Clay Minerals: Implications for Construction Wood Protection.

The wood preservative disodium octaborate tetrahydrate (DOT) migration is studied in clay. Using boron analysis by inductively coupled plasma optical emission spectroscopy (ICP-OES), DOT spatial and temporal dynamics are surveyed to show how DOT permeates into the wood and the clay using concentration profiles as a function of depth, initial wood moisture, and direction of filling. Atomic force microscopy and chemical imaging using photoinduced force microscopy are used to show the morphology of the wood samples and the distribution of DOT on their surface. ICP-OES results show that the average DOT concentration in the wood samples is originally 0.8 and 1.5 wt% in the bulk and at the surface, respectively. Conditioning of the wood to a moisture content of 19% in a climatic chamber reduces DOT concentration by 8% for the fir and 17% for the spruce. After one week of contact with the clays, the results showed a rapid decrease of 25-40% in DOT concentration in wood. On longer periods (5 months), the spruce shows a tendency to reabsorb the DOT from the clay and the DOT migration stabilizes at 20%. These results contribute to defining the dosage of DOT when the wood is exposed to clay.

Infrared spectroscopy coupled with machine learning algorithms for predicting the detailed milk mineral profile in dairy cattle.

Milk minerals are not only essential components for human health, but they can be informative for milk quality and cow's health. Herein, we investigated the feasibility of Fourier Transformed mid Infrared (FTIR) spectroscopy for the prediction of a detailed panel of 17 macro, trace, and environmental elements in bovine milk, using partial least squares regression (PLS) and machine learning approaches. The automatic machine learning significantly outperformed the PLS regression in terms of prediction performances of the mineral elements. For macrominerals, the R2 ranged from 0.59 to 0.78. Promising predictability was achieved for Cu and B (R2 = 0.66 and 0.74, respectively) and more moderate ones for Fe, Mn, Zn, and Al (R2 from 0.48 to 0.58). These results provide a reliable basis for a rapid and cost-effective quantification of these traits, serving as a resource for dairy farmers seeking to enhance the quality of milk production and optimize cheese properties.

Employing a switching valve to automate external standard calibration in inductively coupled plasma optical emission spectrometry.

The traditional external standard calibration method (EC) is automated and simplified using a four-port switching valve (SV4) and a multi-signal approach that enables the generation of several calibration points from a single calibration solution. The SV4-EC method is applied to inductively coupled plasma optical emission spectrometry (ICP-OES) and is based on gradient dilution taking place within the instrument's sample introduction tubing. Both the calibration solution and the samples are diluted by a blank solution containing an internal standard species. Forty-five dilution points are collected over time while the solutions are mixed. Instrument responses from the calibration solution are then plotted against those from the samples, and the slope of the calibration curve is used to determine the unknown analyte concentrations in the samples. The method is used to determine Ba, Co, Cr, Cu, Fe, Mn, Ni, V and Zn in coconut water, creek water, green tea, mouthwash, soft drink, vinegar, and vodka. Limits of detection are in the 0.0002-0.009 mg L-1 (n = 10) range, with precision on the order of 0.4 %-3 % RSD. Analyte percent recoveries from a 0.5 mg L-1 spike are in the ranges of 88.4 %-111 %, 88.9 %-111 %, and 88.0 %-111 % for EC, SV4-EC, and the internal-standard-corrected method (SV4-EC/Sc), respectively. No statistically significant difference is observed between EC and SV4-EC recoveries for any of the sample matrices evaluated. Comparable results between EC and SV4-EC were also found for the analysis of two certified reference materials, Bovine Liver and Oyster Tissue. Based on a single calibration solution, the SV4-EC method requires caution when preparing the calibration standard to minimize measurement bias.

Investigation of mercury contamination in lipstick sold in the Saudi market and the potential health risk.

Background: Environmental contamination is a significant global health issue, with cosmetics and pharmaceuticals being major polluters. High concentrations of heavy metals, such as Hg, have been found to have toxic effects and may pose a threat to human health. This study aimed to determine the concentration of mercury (Hg) in lipsticks available in the Saudi Arabia market.Methods: In this study, 12 lipstick samples from three colors were analyzed using inductively coupled plasma optical emission spectrometry (ICP-OES) to measure the content of Hg.Results: The concentration range of Hg was 0.004-0.296 ppm. Moreover, the systemic exposure dosage of mercury in the lipstick samples examined in this study ranged from 5.01 × 10-8 to 1.43 × 10-6 µg/kg bw/day, while the range of the margin of safety was from 7.3 × 109 to 2.2 × 108.Discussion: The Hg concentration in all analyzed samples was less than 0.50 and 1 ppm, which indicated that the Hg level was within acceptable limits according to Saudi Standards, Metrology and Quality Organisation (SASO) and the United States Food and Drug Administration (US FDA), respectively. On the other hand, the calculated margin of safety values for mercury exceeded the safe standard established by the WHO. The results derived from using hazard quotient (HQ) indices depict the potential carcinogenic health risk posed to consumers who employ red-colored lipsticks.

Machine Learning-Based Classification of Soil Parent Materials Using Elemental Concentration and Vis-NIR Data.

In soil science, the allocation of soil samples to their respective origins holds paramount significance, as it serves as a crucial investigative tool. In recent times, with the increasing use of proximal sensing and advancements in machine-learning techniques, new approaches have accompanied these developments, enhancing the effectiveness of soil utilization in soil science. This study investigates soil classification based on four parent materials. For this purpose, a total of 59 soil samples were collected from 12 profiles and the vicinity of each profile at a depth of 0-30 cm. Surface soil samples were analyzed for elemental concentrations using X-Ray fluorescence (XRF) and inductively coupled plasma-optical emission spectrometry (ICP-OES) and soil spectra using a visible near-infrared (Vis-NIR) spectrometer. Soil samples collected from soil profiles (12 soil samples) and surface (47 soil samples) were used to classify parent materials using machine learning-based algorithms such as Support Vector Machine (SVM), Ensemble Subspace k-Near Neighbor (ESKNN), and Ensemble Bagged Trees (EBTs). Additionally, as a validation of the classification techniques, the dataset was subjected to five-fold cross-validation and independent sample set splitting (80% calibration and 20% validation). Evaluation metrics such as accuracy, F score, and G mean were used to evaluate prediction performance. Depending on the dataset and algorithm used, the classification success rates varied between 70% and 100%. Overall, the ESKNN (99%) produced better results than other classification methods. Additionally, Relief algorithms were employed to identify key variables for each dataset (ICP-OES: CaO, Fe2O3, Al2O3, MgO, and MnO; XRF: SiO2, CaO, Fe2O3, Al2O, and MnO; Vis-NIR: 567, 571, 572, 573, and 574 nm). Subsequent soil reclassification using these reduced variables revealed reduced accuracies using Vis-NIR data, with ESKNN still yielding the best results.

Correlation Between Severity of Schizophrenia with Certain Trace Elements and TNF-α Gene Expression and Its Circulatory Level in the Population of Western India.

This cross-sectional study aimed to assess serum trace element (TE) concentrations, TNF-α gene expression, protein levels in schizophrenia (SZ) patients, and their correlation with disease severity measured by Positive and Negative Syndrome Scale (PANSS) scores. Forty SZ cases and 40 healthy controls aged 18-60 were recruited. Forty (n = 40) cases who meet ICD-10 criteria for SZ and 40 (n = 40) healthy individuals (controls) between 18 and 60 years of age were recruited in the study. Sandwich enzyme-linked immunosorbent assay (ELISA) and RT-qPCR (quantitative real-time PCR) were used to estimate pro-inflammatory cytokine TNF-α protein and gene expression. Inductively coupled plasma-optical emission spectroscopy (ICP-OES) and graphite furnace atomic absorption spectroscopy (GFAAS) were used to assess serum levels of trace elements (TEs): Fe, Zn, Cu, Mg, and Se. Compared to healthy controls, cases had significantly higher levels of TNF-α protein, as well as Fe, Cu, and Se (p < 0.05). Cu correlated positively with TNF-α protein level (rho = 0.234; p = 0.048) and gene expression (rho = 0.333; p = 0.041) and with PANSS negative (rho = 0.531), general (rho = 0.643), and total (rho = 0.541) scores. Additionally, Zn negatively correlated with serum Mg (rho = - 0.426, p < 0.01) and positively with serum Se (rho = 0.343, p < 0.05). In conclusion, elevated Cu levels could potentially contribute to the development of SZ. Elevated Cu levels in cases and their correlation with the TNF-α gene and protein and PANSS score indicate Cu's potential role in exacerbating SZ severity through inflammatory cytokines. This suggests the involvement of metals and cytokines in the pathophysiology of SZ.

Recent Advances in the Determination of Major and Trace Elements in Plants Using Inductively Coupled Plasma Optical Emission Spectrometry.

Interest in measuring major and trace elements in plants has increased in recent years because of growing concerns about the elements' contribution to daily intakes or the health risks posed by ingesting vegetables contaminated by potentially toxic elements. The recent advances in using inductively coupled plasma atomic emission spectrometry (ICP-OES) to measure major and trace elements in plant samples are reviewed in the present work. The sample preparation before instrumental determination and the main advantages and limitations of ICP-OES are described. New trends in element extraction in liquid solutions using fewer toxic solvents and microextractions are observed in recently published literature. Even though ICP-OES is a well-established and routine technique, recent innovations to increase its performance have been found. Validated methods are needed to ensure the obtaining of reliable results. Much research has focused on assessing principal figures of merit, such as limits of detection, quantification, selectivity, working ranges, precision in terms of repeatability and reproducibility, and accuracy through spiked samples or certified reference materials analysis. According to the published literature, the ICP-OES technique, 50 years after the release of the first commercially available equipment, remains a powerful and highly recommended tool for element determination on a wide range of concentrations.

Size-dependent renal filtration model explains human pharmacokinetics of a functional nanoparticle: The SPAGOPIX-01 clinical trial.

The pharmacokinetics in patients dosed with the nanoparticle-based MRI contrast agent SN132D is explained by a size dependent clearance mechanism and this behavior was modeled numerically. Blood samples from 14 patients were analyzed for silicon (a component of the nanoparticle) by ICP-OES. The pharmacokinetic model has only one free parameter and relies on a measured size distribution of the contrast agent and well-established properties of the renal and cardiovascular systems. The model fits well (R2 = 0.9910) with experimental data from samples taken from ten minutes to two weeks after start of infusion. These results support that the cut-off diameter for human renal filtration is 5.5 nm. The agreement between experiment and model implies that there is little or no plasma protein binding to the nanoparticles.

Advances in assessing Ca, K, and Mn translocation in oak tree stems (Quercus spp.).

As a part of the biogeochemical cycle, nutrient translocation plays an important role in enhancing the capacity of perennial plants to grow in nutrient-poor soils. Although leaf translocation has been extensively studied, nutrient translocation between wood rings has received considerably less attention, primarily because of methodological constraints. This study aimed to (i) evaluate the effects of different drying techniques on Ca, K, and Mn concentrations, (ii) calibrate a semi-quantitative method for obtaining ring-to-ring nutrient concentrations along wood cores, and (iii) develop a complete calculation chain for nutrient translocation. Three pairs of cores per tree were extracted from nine oaks, and three drying methods-103 °C, 65 °C, and freeze-drying-were applied to each core pair. For each core pair, the first core was analyzed using ITRAX. The second core was analyzed using ICP-OES following the mineralization of a 20 mg wood sample. Ca, K, and Mn concentrations and wood density were not affected by the drying methods (p > 0.05 for Ca, K, and Mn). After upscaling at the stand level, the total translocation was 10.8 ± 5.5 kg ha-1, 14.8 ± 11.4 kg ha-1, and 2.6 ± 0.9 kg ha-1 for Ca, K, and Mn, respectively, after 45 growing years. The total Ca, K, and Mn translocation showed a strong tree effect, partly explained by tree diameter. The study findings suggest that similar measurements can be performed on all wood cores sampled in previous studies and stored after air-drying. These results provide a reference for future analyses of Ca, K, and Mn translocations in different species from wide geographic areas.

Elemental Profiling of Common Anti-diabetic Medicinal Plants of Swat and Peshawar Districts of Khyber Pakhtunkhwa (KPK) Province of Pakistan: An Investigation Using PIXE and ICP-OES.

The use of medicinal plants is integral to addressing liver, heart, lung, and other metabolic issues. These plants are rich in vitamins, minerals, flavonoids, and alkaloids, which collectively help in lowering intestinal glucose absorption and increasing insulin secretion by pancreatic tissues. Elemental analysis, encompassing major, minor, and trace elements, was performed on various parts (leaves, roots, and seeds) of 16 anti-diabetic medicinal plants collected from different regions of Swat and Peshawar in Khyber Pakhtunkhwa (KPK), Pakistan. This analysis utilized proton-induced X-ray emission (PIXE) and inductively coupled plasma optical emission spectroscopy (ICP-OES) techniques. Our PIXE and ICP-OES analysis revealed the presence of major (Ca, K, S, P), minor (Si, Cl), and trace (Al, Mn, Fe, Ni, Cu, Zn, Se, Cr, and Sc) elements in various parts (leaves, roots, and seeds) of the 16 anti-diabetic medicinal plants studied. Specifically, elements such as Ca, K, Cr, Cu, Mn, Zn, and Se were detected, all of which are known to contribute in maintaining normal glucose metabolism. Notably, Zn and Se are crucial trace elements for the synthesis, secretion, and action of insulin. Significant Zn concentrations were observed in ten anti-diabetic medicinal plants: Albizia lebbeck (AL), Atropa acuminata (AA), Avena fatua (AF), Citrus medica (CM), Commiphora wightii (CW), Cymbopogon citratus (CC), Daucus carota (DC), Ziziphus mauritiana (FM), Hyoscyamus niger (HN), and Martynia annua (MA), and significant Se concentrations were observed in twelve medicinal plants, i.e., Albizia lebbeck (AL), Allium sativum (AS), Atropa acuminata (AA), Avena fatua (AF), Cannabis sativa (CS), Capparis spinosa (CaS), Commiphora wightii (CW), Cymbopogon citratus (CC), Datura alba (DA), Daucus carota (DC), Ziziphus mauritiana (FM), and Hyoscyamus niger (HN). Our study's elemental analysis using PIXE and ICP-OES on various parts of 16 medicinal plants identified a significant number of useful elements. Elements such as Ca, K, S, P, Al, Si, Cl, Mn, Fe, Ni, Cu, Zn, Se, and Cr were identified and quantified. These findings support the potential use of these plants in managing diabetes and highlight the importance of elemental profiling in understanding their therapeutic properties.

The levels of essential nutrients and nonessential metals in different varieties of teff produced in Hidabu Abote Woreda, Oromia, Ethiopia.

Ethiopia is the world's largest producer of teff (Eragrostis tef Zucc). This research was intended to determine the levels of mineral nutrients (metals and nonmetals) and nonessential metals in the grains of teff. Following the optimization of the method, the samples were wet-digested using reagents (5-mL HNO3 and 1-mL HClO4) at a temperature of 230°C for two and a half hours and analyzed using inductively coupled plasma-optical emission spectrometry. Under the optimum procedure, the coefficients of determination (R 2) ranged between .9980 and .9999. The limits of detection and limits of quantification were in the range of 0.036-14.49 and 0.111-43.93 mg/kg, respectively. The recovery ranged from 80.72% to 107.79%, indicating that the method was accurate. The optimized and validated method was applied to quantify the levels of analytes in the teff samples. The overall mean concentrations of the analytes in the three varieties of teff samples were determined (mg/kg) to be in the order P (3890-4853) > K (3040-3784) > Ca (1906-1959) > Mg (1402-1698) > Fe (128-305) > Mn (64-127.8) > Na (50-136.5) > Zn (19.8-27.3) > B (1.8-21.9) > Cu (4.17-6.9) > Ni (2.6-4.05) > Hg (1.8-4.0) > Pb (0.048-3.7) > Cd (0.012-2.09) > As (0.02-0.24), with a % RSD ranging between 0.017 and 11.1. The results revealed that teff grains are a good source of minerals and contain a significant amount of toxic elements, such as Cd, Hg, Pb, and As.

Environmental Factors Influencing Metal Concentrations in Scomber colias Along the Canary Islands.

A total of 140 specimens of Scomber colias were collected from the Canary archipelago waters during the first semester of 2021, with 20 samples from each of the seven main islands. After analyzing the concentrations of metals (Al, Zn, Cd, Pb, Fe, and Cu) with ICP-OES, significant variations were observed among islands, with specimens from Tenerife and Gran Canaria containing higher levels of Al, Cd, and Pb, while those from Lanzarote and Fuerteventura had elevated levels of Zn, Fe, and Cu. These differences are probably related to greater anthropogenic activity around Tenerife and Gran Canaria coasts, leading to higher pollution levels, and the influence of Saharan dust and African upwelling on Lanzarote and Fuerteventura, enriching the waters with nutrients. Specific management strategies to mitigate marine pollution and continuous monitoring are crucial to safeguard marine ecosystems and to ensure food security.