Principal Component Cluster Analysis Research Articles

Pollution and health risk assessments related to heavy metals on three prominent beaches in Makkah Province, Kingdom of Saudi Arabia: Concerning levels of cadmium pollution.

Beach pollution can impact the health of people living in or visiting coastal areas. The primary goal of this research was to investigate the presence of heavy metal pollutants and associated health risks in three distinct coastal cities, Jeddah, Al-Lith, and Al-Qunfudhah, located along Saudi Arabia's Red Sea coast. Forty-three soil samples were collected from different locations, heavy metals including Fe, Zn, Mn, Cu, Cd, and Pb were isolated, and analyzed using inductively coupled plasma optical emission spectroscopy. Various metrics such as pollution indices (PI), integrated pollution indices (IPI), enrichment factors (EF), daily dose averages (ADD), hazard quotients (HQ), and hazard indices (HI), as well as principal component analysis (PCA) and cluster analysis were employed to evaluate the environmental impacts and health risks posed by these heavy metals. The results revealed that Fe, Pb, Cu, Mn, and Zn concentrations in beach zones were below their respective background levels, while concentrations of Cd exceeded corresponding background levels. PCA revealed the highest levels of Pb, Fe, and Mn on Al-Qundudah beach, while Cd and Cu were highest on Al-Lith beach, and Zn was highest on Jeddah beach. PI values highlighted extremely high levels of Cd pollution on all designated beaches. The findings provide a foundational basis for further investigations into health problems potentially related to Cd contamination, such as chronic kidney disease (CKD), osteomalacia, and osteoporosis.

Exploring disparities and similarities in daily travel mode choices between electric vehicle owners and internal combustion engine vehicle owners

ABSTRACT This study proposes a novel instrument for measuring private car owners’ travel-related lifestyle (PCTRL) based on a survey (N = 2045) conducted in China’s four first-tier cities and ten quasi first-tier cities. By employing principal component analysis (PCA) and cluster analysis, the study classifies electric vhehicle (EV) owners and internal combustion engine vehicle (ICEV) owners into five distinct PCTRL segments, respectively. The findings reveal that only 66% of EV owners have similar PCTRLs to 67% of ICEV owners, with the most notable disparity being the higher likelihood of EV owners choosing private cars for their daily commutes. Furthermore, a random forest model was developed to predict the daily activity-based travel mode choices behavior of both EV and ICEV owners. The findings offer valuable insights into understanding the behavior of EV and ICEV owners in their daily travel mode choices and help formulating more effective traffic management strategies.

Marine macroalgae Chaetomorpha aerea as a dietary supplement: Optimizing immunity and resistance to Edwardsiella tarda in tilapia (Oreochromis mossambicus)

The intensification of aquaculture has led to a rise in fish infections, necessitating the search for alternative antibiotics. In this context, our study investigated the effects of dietary supplementation with Chaetomorpha aerea, a filamentous green algae, on the immune health and resistance to infections in tilapia (Oreochromis mossambicus). Diets containing varying concentrations of C. aerea (0, 1, 2, 5, and 10 g/kg) were prepared and administered to the fish for 30 days, followed by a challenge with Edwardsiella tarda to evaluate survival rates. The results were significant. The diet containing 5 g/kg of C. aerea (group T3) brought about substantial improvements in hematological parameters, including increases in red blood cell count (RBC), hematocrit (Hct), and hemoglobin (Hb). The T3 group exhibited a robust immune response, with higher lysozyme and ceruloplasmin activity in immunological assays. LBP gene expression was significantly elevated in the spleen and thymus of fish in the T3 group, which correlated with higher survival after bacterial challenge compared to the control group. Principal Component Analysis (PCA) and cluster analysis confirmed that the 5 g/kg concentration stood out for maximizing immunological benefits without compromising the overall health of the fish. These findings highlight the robust immune response in the T3 group, a key finding of our study. We conclude that supplementation with C. aerea represents a promising and sustainable alternative in the formulation of diets for tilapia, contributing to improved health and resistance to diseases. Future studies are recommended to explore its application in other species and development stages, in addition to evaluating other health biomarkers.

Characterization of Pasture Production Systems in Makueni County of Kenya

Livestock feed is a key factor influencing animal production and productivity as evidenced by the increased demand for animal source foods (ASFs) to feed a growing human population in Kenya. However, there exists untapped potential of pasture commercialization and hence the need to harness the social, economic and environmental benefits in the ASALs for overall rural development. A study was conducted to characterize the existing pasture production systems in Makueni County. A purposive random sampling of 300 respondents drawn from 3 Sub-counties and 12 wards was conducted in Makueni County in January, 2021. The study aimed to characterize existing pasture production systems using a structured questionnaire. Data were analyzed using descriptive and inferential statistics. Multivariate statistical techniques; principal Component Analysis (PCA) and Cluster Analysis (CA) were used to determine whether or not there were significant differences in the pasture production systems in Makueni County. Results of the study showed that majority (97%) of the farmers were small scale farmers (SSFs) who dedicated less than 5 acres of their land to pasture production. The mean age of small- scale farmers was 52 years compared to 55 years for the large-scale farmers (LSFs). Most of the households were male headed (83%). Most of the SSFs household heads had primary level of education level or lower while most of the large-scale household heads had secondary education and above. Majority (35%) of SSFs owned the land under pasture without a title while most of the LSFs had a title. The land under pasture for SSFs was about 2 acres with an average of 102 bales per season while LSFs had about 23 acres under pasture and produced about 1,762 bales per season. Majority (92%) grew local grass varieties and sold their pasture in form of a bale. 58% of SSFs sited NGOs as their main source of grass seeds while LSFs mainly sourced from agrovets Results of PCA revealed that 6 of the 17 components had eigen values greater than 1 and accounted for 58% of the total variance. Based on Euclidian distance, six clusters were determined using the agglomeration schedule. ANOVA analysis of the six profiles were estimated to have p-values of 0.000, suggesting the existence of significance difference between cluster 1 to 6 in relation to the 6 profiles and hence concluding the existence of variations in pasture production systems in Makueni County. Development strategies should focus on knowledge of and improved access to grass seeds to farmers as well as development of standards of the mode of sale of pasture.

Screening of Ecotypes and Construction of Evaluation System for Drought Resistance during Seed Germination in Kudouzi (Sophora alopecuroides)

Drought is a major limiting factor in the cultivation of Sophora alopecuroides in China’s arid and semi-arid regions. This study aimed to identify drought-resistant S. alopecuroides ecotypes and explore key drought tolerance indicators during germination by simulating drought conditions with a 10% PEG-6000 solution, using pure water as a control. Determination of seven germination indicators for S. alopecuroides, including germination rate (GR), germination energy (GE), germination index (GI), vigor index (VI), promptness index (PI), fresh weight (FW), and dry weight (DW), was conducted. Principal component analysis (PCA), membership function, cluster analysis, and linear regression were employed to comprehensively evaluate the drought resistance of thirty-five S. alopecuroides ecotypes. The results showed that drought stress caused reductions in six of the seven indicators across all ecotypes, except for DW, compared to the control. Correlation analysis revealed varying relationships among the indicators, with most showing significant or highly significant correlations. PCA reduced the seven indicators to two independent comprehensive factors, with a cumulative contribution rate of 83.99%. Based on the D-value and cluster analysis, the thirty-five ecotypes were ranked for drought resistance and classified into four categories. The top five drought-tolerant genotypes during the germination stage were identified as Yutian, Alar, Jinghe, Baoding, and Guyuan. Moreover, the stepwise regression model was established and demonstrated that GR, GE, PI, FW, and DW are key indicators for screening and identifying drought-resistant S. alopecuroides ecotypes. This study offers a comprehensive and reliable method for evaluating drought resistance in S. alopecuroides ecotypes and provides a reference for selecting ecotypes for artificial cultivation in Northwestern China.

Analysis of free amino acids and evaluation of the quality of gallnut honeys from different geographical areas

AbstractGallnut honey, a typical Chinese medicinal commodity, is produced from the nectar of Rhus chinensis Mill. Gallnut honey is very popular with consumers because of its health effects and nutritional value, but its specific nutritional composition and medicinal components are not clear. Free amino acids are important nutritional components of honey, and can provide relevant information about the honey, such as geographical and botanical origin, as well as adulterations. The aim of this paper was to explore the free amino acid characteristics of gallnut honeys in different areas. 18 free amino acids from 17 places in China were determined by automatic amino acid analyser analysis, and the geographical characteristics were studied by principal component analysis and cluster analysis. Results showed that gallnut honey is rich in free amino acids. A total of 12 types of free amino acids were detected in all honey-producing areas, and the total amino acid content was 0.132–0.292 g/100 g. Due to its free amino acid content gallnut honey has high nutritional supplement potential, and exhibits good pharmacodynamic activity and special taste characteristics. Flavour-related free amino acids were primarily aromatic free amino acids and umami free amino acids. Pharmacodynamic free amino acids accounted for 61.22–83.85%. Results also showed that free amino acids contribute to the geographical tracing of honey, and samples of gallnut honey at different altitudes can be distinguished by cluster analysis.

Exploring critical quality indicators and developing a non-destructive detection method using near-infrared spectroscopy for sea bass (Lateolabrax japonicus) quality evaluation

In this study, chemometrics were employed to explore the relationship between sensory evaluation and physicochemical indicators of sea bass (Lateolabrax japonicus). Through principal component analysis, cluster analysis, and Pearson correlation analysis, three pivotal indicators were identified: protein content, b* value, and condition factor. Leveraging the grey relational analysis, weights were assigned to these three core quality indicators, resulting in a comprehensive sea bass quality evaluation model: Y = 0.911 × protein (g/100 g) + 0.742 × b* + 0.747 × condition factor. Moreover, near-infrared spectroscopy combined with chemometrics were employed to evaluate the quality of sea bass. The different origins of sea bass were accurately distinguished using orthogonal partial least squares discriminant analysis. The partial least squares regression model was constructed for predicting the critical quality indicator, protein content, with R2P of 0.926. This study offers new insights for developing rapid, economical, and reliable methods for assessing aquatic product quality.

Metabolomic analysis of the impact of red ginseng on equine physiology.

Red ginseng (RG), a traditional herbal remedy, has garnered attention owing to its diverse health benefits resulting from its complex composition. However, extensive research is needed to substantiate the efficacy of RG and understand the underlying mechanisms supporting these benefits. This study aimed to identify potential biomarkers and investigate the impact of RG on related metabolic pathways in horse plasma using liquid chromatography-mass spectrometry (LC-MS)-based metabolomics. Ten horses were divided into control and RG groups, with the latter administered RG at a dose of 600 mg⋅kg-1⋅day-1 for 3 weeks. Subsequently, the plasma samples were collected and analyzed using LC-MS. Multivariate statistical analysis, volcano plots, and feature-based molecular networking were employed. The analysis identified 16 metabolites that substantially decreased and 21 metabolites that substantially increased following RG consumption. Among the identified metabolites were oleanolic acid, ursolic acid, and ginsenoside Rb1, which are known for their antioxidant and anti-inflammatory properties, as well as lipid species that influence sphingolipid and glycerophospholipid metabolism. Additionally, potential biomarkers, including major RG components, demonstrated distinct group clustering in principal component analysis and partial least squares-discriminant analysis, indicating their utility in assessing the physiological effects of RG consumption. This study contributes to a comprehensive understanding of the effects of RG on health.

Morphological variation of endemic Gymnocypris chilianensis (Cyprinidae) collected from three inland water systems in Qilian Mountains, China

To explore the morphological differences among different geographic populations of Gymnocypris chilianensis, 29 measurable traits and 13 landmarks on 191 individuals of 10 geographic populations were collected from three different inland water systems, i.e., Shiyang River, Heihe River, and Shule River, in Qilian Mountains, China. Multivariate statistical methods were used to compare morphological differences among the populations, such as principal component analysis, cluster analysis, discriminant analysis, and visual analysis of landmark data. The results showed that: (1) There were significant morphological differences between groups of G. chilianensis. The Shiyang River basin differs significantly from populations in the other two basins. (2) The inter-population differences were mainly reflected in the length of the trunk and tail, and the difference between trunk and caudal fin had the most obvious characteristics, proving the tail being the main direction of variation. This research provides an effective theoretical basis for the fine management and accurate protection of G. chilianensis germplasm resources.

Assessment of pesticide residues: a comprehensive analysis of seasonal trends and health implications

This study assessed the presence of eight pesticide residues in the Indus River, Mianwali, Pakistan, focusing on three sampling sites (S1, S2, and S3) in water, sediment, and the fish species Cyprinus carpio during both dry and wet seasons. Analysis was conducted using gas chromatography with an electron capture detector. Results indicated elevated pesticide concentrations in both seasons, with levels of 0.84 and 0.62 μg/L in water, 12.47 and 9.21 μg/g/dw in sediment, and 17.33 and 12.17 μg/g/ww in fish, with higher concentrations observed during the dry season. Cypermethrin and carbofuran were the primary pesticides detected in water, while endosulfan and cypermethrin were dominant in sediment and fish tissue, often exceeding standard safety thresholds. Principal Component Analysis (PCA) and cluster analysis revealed stronger correlations between sediment and fish muscle, with varying associations among pesticides across seasons. The Hazard Index (HI) surpassed 1 in both seasons, signaling potential health risks to humans. These findings underscore the substantial risk agricultural pesticides pose to the aquatic ecosystem and food chain, highlighting the urgent need for sustainable agricultural practices and stricter regulations to minimize pesticide use and encourage eco-friendly pest management strategies.

Establishment of near-infrared rapid prediction model and comprehensive evaluation model for foxtail millet quality

Foxtail millet (Setaria italica) is one of the earliest cereal crops in the world and is still an important food crop in Asia, Europe and Africa. However, there are few reports on rapid and comprehensive evaluations of foxtail millet quality. In this study, color, nutrient content, cooking quality and sensory quality of 45 varieties of foxtail millet from the main production areas of the country were determined. Near infrared spectroscopy (NIRS) combined with partial least squares regression (PLSR) was developed for rapid and nondestructive detection of foxtail millet quality, where NIRS models for ash, amylopectin, protein, and VB1 and VB2 were desirable. In addition, correlation analysis, principal component analysis and cluster analysis were used for comprehensive evaluation of millet quality. The results showed that foxtail millet with low ash, protein, fat and fiber content and high amylopectin and carotenoid content has good cooking quality and was more preferred. This research will contribute to the quality evaluation and further processing of foxtail millet.

Color, proximate composition, bioactive compounds and antinutrient profiling of rose

Rose (Rosa sp.) is one of the most important ornamentals which is commercialize for its aesthetic values, essential oils, cosmetic, perfume, pharmaceuticals and food industries in the world. It has wide range of variations that is mostly distinguished by petal color differences which is interlinked with the phytochemicals, secondary metabolites and antinutrient properties. Here, we explored the color, bioactive compounds and antinutritional profiling and their association to sort out the most promising rose genotypes. For this purpose, we employed both quantitative and qualitative evaluation by colorimetric, spectrophotometric and visual analyses following standard protocols. The experiment was laid out in randomized complete block design (RCBD) with three replications where ten rose genotypes labelled R1, R2, R3, R4, R5, R6, R7, R8, R9 and R10 were used as plant materials. Results revealed in quantitative assessment, the maximum value of lightness, and the luminosity indicating a brightening of rose petals close to a yellow color from rose accessions R4, and R10, respectively which is further confirmed with the visually observed color of the respective rose petals. Proximate composition analyses showed that the highest amount of carotenoid and β-carotene was found in R10 rose genotype, anthocyanin and betacyanin in R7. Among the bioactive compounds, maximum tocopherol, phenolic and flavonoid content was recorded in R8, R6 and R3 while R1 showed the highest free radical scavenging potentiality with the lowest IC50 (82.60 µg/mL FW) compared to the others. Meanwhile, the enormous variation was observed among the studied rose genotypes regarding the antinutrient contents of tannin, alkaloid, saponin and phytate whereas some other antinutrient like steroids, coumarines, quinones, anthraquinone and phlobatanin were also figured out with their presence or absence following qualitative visualization strategies. Furthermore, according to the Principal Component Analysis (PCA), correlation matrix and cluster analysis, the ten rose genotypes were grouped into three clusters where, cluster-I composed of R3, R4, R5, R8, cluster-II: R9, R10 and cluster-III: R1, R2, R6, R7 where the rose genotypes under cluster III and cluster II were mostly contributed in the total variations by the studied variables. Therefore, the rose genotypes R9, R10 and R1, R2, R6, R7 might be potential valuable resources of bioactive compounds for utilization in cosmetics, food coloration, and drugs synthesis which have considerable health impact.

Understanding eco-innovation in the Hungarian wine sector

PurposeA growing body of literature analyzes eco-innovation in the wine industry, specifically focusing on the internal and external factors that contribute to sustainable innovation in wineries. The purpose of this study is to classify wineries according to their eco-innovation strategy and investigate variations in innovation groups concerning networking and socio-demographic characteristics.Design/methodology/approachThe authors use an original firm-level survey conducted between June 2022 and January 2023 to study eco-innovation practices of 234 Hungarian winemakers using four groups of indicators: marketing, organizational, process and product innovations. The authors apply principal component analysis and cluster analysis to identify eco-innovation dimensions and group wineries. The authors also investigate the relationship between eco-innovation strategies, determinants and firm-specific characteristics.FindingsThe estimations identify two innovation modes: with Cluster 1 (characterized by innovative wineries) surpassing Cluster 2 (comprising less innovative wineries) in all aspects. Marketing and process innovations were more widespread than product and organizational innovations. The results confirm the importance of firm and manager characteristics, corporate organization and size, age and education of management influence innovation activity.Research limitations/implicationsThe cross-sectional nature of the survey provides a snapshot of the wine industry. To identify changing trends, it is beneficial to conduct follow-up research and ongoing monitoring for a more comprehensive understanding of the dynamics of eco-innovation over time. The study offers valuable information about the Hungarian wine sector, but generalization of results to other geographic areas or wine-producing regions should be careful. The unique characteristics of particular regions might have a different effect on the dynamics of eco-innovation. Comparative studies across different wine regions or countries may reveal regional variations in eco-innovation strategies and the impact of local contexts.Practical implicationsThe study highlights the priority of human elements, such as the commitment of owners and managers to sustainability in driving force for innovation. The ability of businesses to absorb new knowledge and the exchange of information within organizations is crucial in promoting innovation. Considering the results of the survey, managers should proactively strive to improve knowledge transfer and information sharing within their organizations and establish cooperative alliances with universities, research institutes, suppliers, industry bodies and associations and global consultancy firms. Such knowledge-based cooperation can counterweight the innovative inertia of the micro and small enterprises representing the Hungarian wine sector.Social implicationsTo address the issue of “innovative inertia” faced by micro and small businesses in the wine sector, policymakers may implement focused supports, such as educational initiatives and grants, to augment their understanding and promote sustainable innovation. They should initiate intra- and inter-cluster connections and cooperations. Incentives, such as tax reduction or financial support, may stimulate wineries to introduce eco-innovation practices. Policymakers could also streamline the process of obtaining funding or grants for wineries interested in investing in cutting-edge solutions, such as renewable energy or advanced cultivation technologies to accelerate the adoption of sustainable practices.Originality/valueThis study contributes to the eco-innovation literature by providing insights into the drivers and practices of wineries in Hungary. The results emphasize the significance of networking, sharing of knowledge and firm/manager-specific characteristics in influencing eco-innovation in the wine industry.

Leftover love: Exploring the behavioural heterogeneity of household meal wasters

Meal leftovers are a major component of household food waste. However, there is a limited understanding of leftover food management behaviours, which can assist in reducing food waste in household settings. This study segments households with distinctive behaviours associated with meal leftover management. Principal component analysis and cluster analysis were used for consumer segmentation. Data on meal leftovers and food management behaviours were collected using a national-level survey of 1728 Australian households. We identified two heterogenous groups of households regarding leftover meal management, ‘Self-sufficient savers’ (59% of the sample) and ‘Naïve discarders’ (41% of the sample). The findings indicate that inefficient cooking and storing behaviours lead to cooked meals being discarded. ‘Naïve discarders’ dispose of leftover meals either immediately or after storing them because they do not have sufficient cooking skills to repurpose leftovers or judge the safety of the food after storing them. They also lack meal-planning skills. In contrast, the ‘Self-sufficient savers’ demonstrated efficient cooking skills and storing behaviours. They read and followed the storage and meal portioning instructions. Results highlight the need for customised interventions targeting consumers with low cooking and storing knowledge to contribute towards overall food waste minimisation.

Interplay of natural and anthropogenic factors in sediment dynamics and trace element distribution in Güllük Gulf, western Türkiye: A comprehensive geochemical and hydrodynamic analysis

Güllük Gulf, located in the southeastern Aegean Sea, is significantly impacted by diverse human activities, including urban development, tourism, and intensive aquaculture. This study aims to assess the spatial distribution of trace metals in the Gulf's sediments, identify their sources, and evaluate their environmental impacts to inform effective management strategies. It also examines sediment transport patterns, which are crucial in influencing the distribution and concentration of pollutants. Establishing background concentration levels for various elements provides a baseline to assess pollution levels and identify deviations due to anthropogenic impact. Sediment samples were collected from 45 stations and analyzed for grain size, organic carbon, carbonate content, and concentrations of 26 elements. Contamination was assessed using indices such as Enrichment Factor (EF), Geoaccumulation Index (Igeo), Contamination Factor (Cf), Degree of Contamination (Cdeg), Pollution Load Index (PLI), Modified Pollution Index (MPI), and Toxic Risk Index (TRI). Statistical analyses, including Principal Component Analysis (PCA) and Cluster Analysis (CA), were used to identify pollution sources. Results indicated that Güllük Gulf's sediments are predominantly sandy, with significant silt and clay fractions in sheltered bays. Organic carbon content averaged 1.68%, with higher values near urban and aquaculture areas. Trace metal concentrations exhibited notable spatial variability, with elevated levels of Pb, Cu and Zn in specific areas, indicating both natural and anthropogenic sources. PCA identified five significant factors contributing to metal presence, linking them to lithogenic origins, aquaculture activities, and industrial inputs. TRI results showed moderate toxic risk in Asin Bay, primarily due to Ni, As and Cr. The sediment transport model of Güllük Gulf, crucial in understanding regional pollution dynamics, revealed a complex interplay of hydrodynamic forces. The study underscores the significant environmental impact of human activities on sediment quality in Güllük Gulf. Elevated trace metal levels near aquaculture sites emphasize the need for stringent environmental management practices. Effective strategies should include regular monitoring, sustainable aquaculture practices, and stakeholder engagement to mitigate environmental impacts and preserve the Gulf's ecological integrity. This comprehensive approach provides crucial insights for future research and environmental management policies aimed at addressing the complex challenges facing Güllük Gulf.

A Comparison Analysis of Four Different Drying Treatments on the Volatile Organic Compounds of Gardenia Flowers.

The gardenia flower not only has extremely high ornamental value but also is an important source of natural food and spices, with a wide range of uses. To support the development of gardenia flower products, this study used headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) technology to compare and analyze the volatile organic compounds (VOCs) of fresh gardenia flower and those after using four different drying methods (vacuum freeze-drying (VFD), microwave drying (MD), hot-air drying (HAD), and vacuum drying (VD)). The results show that, in terms of shape, the VFD sample is almost identical to fresh gardenia flower, while the HAD, MD, and VD samples show significant changes in appearance with clear wrinkling; a total of 59 volatile organic compounds were detected in the gardenia flower, including 13 terpenes, 18 aldehydes, 4 esters, 8 ketones, 15 alcohols, and 1 sulfide. Principal component analysis (PCA), cluster analysis (CA), and partial least-squares regression analysis (PLS-DA) were performed on the obtained data, and the research found that different drying methods impact the VOCs of the gardenia flower. VFD or MD may be the most effective alternative to traditional sun-drying methods. Considering its drying efficiency and production cost, MD has the widest market prospects.

A Multivariate Investigation of Groundwater Chemistry Data in Barak River Valley, South Assam, India

ABSTRACTThe present study investigated seven physico‐chemical parameters (depth, pH, chloride, and hardness) and trace elements (arsenic [As], copper [Cu], and iron [Fe]) in the shallow aquifers of Barak River valley in Assam, India. All the physico‐chemical parameters were within the guideline value except pH; approximately 37.5% of the samples were below the guideline value (6.5–8.5). As ranged from 0 to 270 µg/L, Fe ranged from 1.43 to 61.03 mg/L, and Cu concentration ranged from 0 to 0.25 mg/L. All the samples for Fe, 83.33% for Cu and 70.84% for As were above the guideline value as prescribed by WHO or BIS. Further, the data were subjected to multivariate statistical analysis (MSA), including principal component analysis (PCA) and cluster analysis (CA), to investigate pollution sources. PCA identified three components, accounting for 72.42% of the total variance. The R‐mode CA identified two clusters, while the Q‐mode identified six clusters. The MSA results signified that human activities were more responsible than natural or geogenic processes for the deterioration of groundwater quality in the study area.

Baseline status of the levels and distribution of rare, noble, and fissionable elements from the Northern Nile Delta black sand deposits

This study examined the composition, distribution, and origins of rare, Noble, and fissionable elements for the first time in black sand deposits from the Northern Delta coastal region. The findings showed that among the elements under investigation, Fe, Ti, Mn, and Sn had the greatest mean levels, while Hf, Cd, and As had the lowest mean amounts. According to the study's elemental composition, black sand is thought to have economic worth for Ti, Zr, Hf, Sn, Ag, and W. The Zr, Co, Cd, Cu, Hf, V, W, and Zn correlation points to the same source origin. It is clear that the accessory mineral composition in the sediments under study especially the heavy ones controls the geochemical patterns of trace elements. The trace element concentrations of interest show a pattern of element variability related to the mineralogy of the sands, as indicated by the principal component analysis and cluster analysis. To explore and exploit heavy minerals in the research region, the study's findings are important.

Sex-specific dietary patterns and their association with metabolic syndrome: Insights from a cross-sectional analysis

AimsThis study aims to identify a posteriori dietary patterns with a sex approach and to evaluate their association with metabolic syndrome criteria. MethodsCross-sectional study conducted in 6821 men and women between 55 and 75 years of age. Forty-two food groups were analyzed from dietary information collected with food frequency questionnaires, using principal component analysis and cluster analysis and then information from both statistical methods was compared. Prevalences were calculated foreach cluster group, based on the number and types of metabolic syndrome criteria they met. ResultsFollowing principal component analysis, two dietary patterns labeled “healthy” and “unhealthy” were identified in both men and women, due to the presence of foods that are considered more or less healthy. These same dietary patterns were found in cluster analysis plus an “intermediate” cluster consisting of both healthy and unhealthy foods. The presence of metabolic syndrome is related to the “healthy” dietary pattern in women and to the “unhealthy” dietary pattern in men. Comparison of the two statistical approaches showed a high level of correlation between them (weighted Kappa = 0.703 in women and weighted Kappa = 0.691 in men). ConclusionsAdherence to both healthy and unhealthy dietary pattern appears to be related to the development of MS. The differences found by sex make it necessary to develop interventions with a sex-specific approach.

Heavy metals and metalloid contamination and risk evaluation in the surface sediment of the Bakkhali River estuary in Bangladesh

Current state of contamination and subsequent risk of contaminated sediment of a tidal river of Bangladesh was evaluated in the present study. Sediment samples were collected from five locations in the tributary of Bakkhali River estuary during summer (April) and winter (December) season, 2020. Collected samples were processed using standard protocol and the content of heavy metals (Cd, Cr, Cu, Pb and Zn) and metalloid (As), were analyzed by the Flame Atomic Absorption Spectrometer. Sediment contamination was evaluated by pollution load index (PLI), contamination factor (CF), degree of contamination (Cd), potential ecological risk index (PERI), non-carcinogenic and carcinogenic risk (CR) due to the dermal contact of the sediment. Multivariate statistical analysis such as principal component analysis (PCA) and cluster analysis (CA) were also applied to find out the possible sources of the contaminant in the sediment. Results showed the average concentration of As, Cd, Cr, Pb, Cu and Zn was 9.74 ± 3.57, 2.00 ± 0.85, 48.75 ± 8.92, 29.78 ± 8.39, 5.44 ± 2.03 and 56.94 ± 8.57 mg/kg, respectively. Concentration of Cu, Pb and Zn were within the recommended level whereas the concentration of As, Cd and Cr were suppressed the recommended level of WHO and FAO/WHO standards. PLI, CF and Cd revealed considerably low degree of contamination of the sediment. Geo-accumulation index indicated uncontaminated to moderately contaminated condition of the sediment. Although the values of enrichment factor revealed no potential enrichment for most of the metals, Cd showed a minor enrichment during the winter season. Based on the ecological risk assessment, the sediment from all of the sample locations was found to be of moderate to low risk. PCA and CA analysis revealed the origin of contaminants mainly from anthropogenic sources. Although different metals showed non-carcinogenic risk to the inhabitants, cancer risk values for dermal contact (CRderm) were much lower than 10−6 indicating no cancer risk for adult and child. However, the findings also revealed that children were more susceptible to CRderm compared to adults. The present study concluded that long term dermal contact of the sediment of Bakkhali River estuary will be contagious to the people. Therefore, regular monitoring of the estuarine environment is necessary so that contamination does not get worse.