Principal Component Analysis Analysis Research Articles

Assessment of trace elements in Iranian kefir samples by using ICP-OES technique

ABSTRACT In this research, levels of 12 trace elements (Al, Zn, Cd, Ni, Hg, Pb, Co, Cr, Se, Fe, As and Mn) were measured in Iranian kefir samples by using ICP-OES (Inductively Coupled Plasma Optical Emission Spectroscopy) method. Based on our findings, the maximum and minimum averages of essential elements were related to Fe (423 ± 146 µg/kg) and Se (not detected or ND), respectively, and the maximum and minimum averages of toxic elements were related to As (13.3 ± 4.68 µg/kg) and Hg (ND), respectively. Based on the amount of fat in the kefir samples, the highest mean values of toxic and essential elements was related to As (15.9 ± 5.25 µg/kg) and Fe (466 ± 177 µg/kg) in high-fat kefir samples, respectively. In addition, the correlation between the amount of fat and elements in the samples was shown with a multivariate principal component analysis (PCA). Based on the obtained results, the amount of trace elements in kefir samples was lower than the existing standards (Cd = 10, Pb = 20, Al = 500, Hg = 20, As = 140, Mn = 100 and Fe = 2700 µg/kg). Also, in reviewing the results by PCA analysis, the differences and similarities between the type and amount of toxic elements and essential elements in kefir samples have been shown. Finally, based on the obtained results, it can be concluded that the consumption of this food item can be safe due to the low level of elements below the acceptable limit.

Lumbopelvic Stability during a Single Leg Step Down Predicts Elbow Varus Torque during Baseball Pitching.

During a baseball pitch, energy is transferred from the lower extremities through the lumbopelvic junction to the upper extremity. Reduced lumbopelvic stability has been associated with elbow injuries, but the mechanisms are unclear. Characterize the predictive ability of lumbopelvic stability on elbow varus torque during a baseball pitch. Cross-Sectional. Facilities at NCAA Division 1 universities. NCAA Division 1 baseball players (N=44; 19.6+1.3yrs). Pitchers completed a warm-up and then threw ten fastballs from a mound to a catcher. During the pitches, elbow varus torque was recorded using an inertial measurement unit and ball velocity was recorded with a radar gun. Participants also completed a single leg step down (SLSD) task with and without a cognitive Stroop, while triplanar pelvic and trunk kinematics were recorded by inertial measurement units. Statistical analysis consisted of a cluster analysis, principal component analysis (PCA), and a multivariate logistic regression model. Cluster analysis revealed 2 clusters: Low Torque-High Velocity and High-Torque-Low Velocity. The PCA analysis revealed 4 patterns of variability (principal components) during the SLSD: 1-sagittal plane, 2-transverse plane, 3-frontal plane trail limb, and 4-frontal plane lead limb. Logistic regression indicated increased transverse plane trunk and pelvis motion predicted higher odds of belonging to the High Torque-Low Velocity cluster; trunk [OR=2.9 (95%CI:1.1,8.0), p=0.036] and pelvis [OR=2.6 (95%CI:1.1,6.0), p=0.031]. Lumbopelvic movement assessed during the SLSD can identify deficits that relate to high elbow torque-low ball velocity during the baseball pitch. Specifically, higher pelvis and trunk transverse plane motion was associated with pitchers in the High Torque-Low Velocity cluster. Our assessment of trunk and pelvis motion during a SLSD provides a method for coaches and clinicians to identify a potential risk factor related to increased elbow varus torque and decreased ball velocity.

Association between urinary phthalate metabolites and renal function in late pregnant women

Evidence about associations of phthalates metabolites with increased serum uric acid (SUA) levels in pregnant women remains unknown. To address this, we conducted a cross-sectional population-based study including 851 pregnant women from Zunyi birth cohort in southwest China. Multiple linear regression models were used to explore single relationships between ten urinary phthalate metabolites with SUA and estimated glomerular filtration rate (eGFR). And then, the overall relationship of phthalate mixture with SUA and eGFR were determined by principal component analysis (PCA) and quantile g-computation (Q-g) analysis. The multivariable linear regression showed that mono-butyl phthalate (MBP), mono-octyl phthalate (MOP) and mono-benzyl phthalate (MBzP) were positively associated with SUA, while mono (2-ethylhexyl) phthalate (MEHP) and mono (2-ethyl-5-hydroxyhexyl) phthalate (MEHHP) were associated with increased eGFR level. Moreover, PCA analysis suggested that phthalate mixture was positively associated with SUA, and MOP, MBzP and MEHP appeared to be the major contributors. Furthermore, Q-g regression showed that each quantile increase in phthalate mixture was associated with 3.27% higher SUA (95% CI 0.21%, 6.41%). Our results imply that phthalate metabolites were associated with higher SUA in late pregnant women, and MBP, MBzP and MOP might be the major drivers. So, a health perinatal duration should be seriously taken to counteract the environment-related dysregulated kidney function.

Childhood obesity accelerates biological ageing: is oxidative stress a link?

Obesity is multifactorial pathophysiological condition with an imbalance in biochemical, immunochemical, redox status and genetic parameters values. We aimed estimate connection between relative leukocyte telomere lengths (rLRL) - biomarker of cellular aging with metabolic and redox status biomarkers values in a group of obese and lean children. The study includes 110 obese and 42 lean children and adolescents, both genders. The results suggested that rLTL are significantly shorter in obese, compared to lean group (p<0,01). Negative correlation of rLTL with total oxidant status, TOS (Spearman's ρ = -0.365, p<0.001) as well as with C reactive protein (Spearman's ρ= -0,363, p<0.001) were observed. Principal component analysis (PCA) extracted three distinct factors (i.e. principal components) entitled as: prooxidant factor with 35% of total variability; antioxidant factor with 30% of total variability and lipid antioxidant - biological ageing factor with 12% of the total variability. The most important predictor of body mass index (BMI) >30kg/m2 according to logistic regression analysis was PCA derived antioxidant factor's score (OR: 1.66, 95th Cl: 1.05-2.6, p=0.029). PCA analysis confirmed oxidative stress importance in biological ageing caused by obesity and its multiple consequences related to prooxidants augmentation and antioxidants exhaustion and gave us clear signs of disturbed cellular homeostasis deepness, even before any overt disease occurrence.

Deciphering crypto interconnections using a multi-analytical approach

Blockchain technology has primarily underpinned cryptocurrencies that are used either as speculative investment vehicles or for transaction facilitation. There has been a keen interest in understanding the dynamics of interconnectedness and conditional correlations among cryptocurrency prices. While most studies have primarily focused on Bitcoin or the top few cryptocurrencies, this study adopts a comprehensive, multi-analytical approach, incorporating other smaller cryptos that appeal to small and medium investors. Pearson correlational analysis explores the interconnectedness among cryptos and investigates co-movement in crypto prices through their returns, volatility, volume traded, and the CCi30 index returns. Principal Component Analysis (PCA) is used to identify highly correlated clusters, summarizing cross-sectional information based on covariance within the predictors. The predictive regression model of Granger Causality test is applied as a vector autoregression (VAR) forecasting method to examine Granger causality of price movements within the clusters identified. The findings from the correlational matrices of returns and volatilities show no difference in behaviours between larger and smaller cap ones, whereas correlations in trading volumes indicate high correlations in large market-caps. Smaller market-cap cryptos exhibit stronger correlations in volatilities than the larger market cap ones. Two highly correlated clusters emerged from the PCA analysis, with Binance Coin (BNB) and Ripple (XRP) exhibiting greater influence than Bitcoin (BTC) and Tether (USDT) in the second cluster. The findings will enable cryptocurrency users and investors to grasp price mechanisms better, offering valuable insights to improve their decision-making abilities.

Multivariate statistical methods for analysis of physicochemical and microbiological parameters of well water from the village M’Pody

The pollution of surface water and groundwater is a real public health problem that is currently receiving particular attention throughout the world. The use of water for food or hygiene purposes requires excellent physicochemical and microbiological quality. Well water is used for many purposes by the inhabitants of M’pody, a village in the Anyama district of Côte d’Ivoire. In this village, an epidemic of diarrhoea was detected in January 2020. This epidemic claimed sixty-nine (69) victims. This study aims to evaluate well water quality controls using the methods of principal component analysis (PCA), correspondence factorial analysis (CFA), analysis of variance (ANOVA) and self-organizing map (SOM) algorithm. The parameters studied were, turbidity (Tur), conductivity (Cond), hydrogen potential (pH), temperature (T), nitrate (NO3-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$NO_{3^{-}}$$\\end{document}), nitrite (NO2-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$NO_{2^{-}}$$\\end{document}), ammonium (NH4+\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$NH_{4^{+}}$$\\end{document}), phosphates (PO43-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$PO_{4}^{3^{-}}$$\\end{document}), chlorides (Cl-)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$(Cl^{-})$$\\end{document}, total hydrotimetric degree (DHT), sulfates (SO42-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$SO_{4}^{2^{-}}$$\\end{document}), bicarbonate (HCO3-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$HCO_{3^{-}}$$\\end{document}), total alkalinity contents (TAC), escherichia coli (E.coli), thermotolerant coliforms (CTH) and enterococcus faecalis (E.faecalis). Data were collected from seventy-two (72) wells in the village during four campaigns in 2020. Physicochemical parameters were determined by electrochemical and spectrophotometric methods. Microbiological analysis was carried out using membrane filtration technique. Descriptive statistics revealed that Tur, Cond, pH and T parameters did not meet world health organization (WHO, 2017) standards. However, the parameters NO3-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$NO_{3^{-}}$$\\end{document}, NO2-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$NO_{2^{-}}$$\\end{document}, NH4+\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$NH_{4^{+}}$$\\end{document}, PO43-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$PO_{4}^{3^{-}}$$\\end{document}, Cl-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$Cl^{-}$$\\end{document}, DHT, TAC, SO42-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$SO_{4}^{2^{-}}$$\\end{document} and HCO3-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$HCO_{3^{-}}$$\\end{document} comply with WHO standards. The results of bacteriological analyzes confirm the presence in very significant numbers of indicators of faecal contamination (CTH, E.coli and E.faecalis) in all wells. The logical explanations for faecal pollution would come from the infiltration of septic tanks located near the wells and the run-off of waste water carrying human and animal faecal matter. The diarrhea epidemic would therefore be caused by the consumption of this polluted water. PCA, FCA and hierarchical cluster analysis (HCA) were jointly employed to identify the structure of wells and deduce the principal factors controlling the parameters of these well waters. ANOVA revealed the effect of human-induced activities as the main factors influencing the physicochemical and microbiological parameters of the studied well waters. Further studies should focus on multivariate statistical techniques for effective forecasting and monitoring of emerging pollution for improved water quality.

VCF2PCACluster: a simple, fast and memory-efficient tool forprincipal component analysis of tens of millions of SNPs.

Principal component analysis (PCA) is an important and widely used unsupervised learning method that determines population structure based on genetic variation. Genome sequencing of thousands of individuals usually generate tens of millions of SNPs, making it challenging for PCA analysis and interpretation. Here we present VCF2PCACluster, a simple, fast and memory-efficient tool for Kinship estimation, PCA and clustering analysis, and visualization based on VCF formatted SNPs. We implemented five Kinship estimation methods and three clustering methods for its users to choose from. Moreover, unlike other PCA tools, VCF2PCACluster possesses a clustering function based on PCA result, which enabling users to automatically and clearly know about population structure. We demonstrated the same accuracy but a higher performance of this tool in performing PCA analysis on tens of millions of SNPs compared to another popular PLINK2 software, especially in peak memory usage that is independent of the number of SNPs in VCF2PCACluster.

Human resources development: Evaluating perceptions against policy

The objective of sustaining smart, sustainable and cohesive inclusive growth, framed by the European strategy, is in line with the global commitments of the Sustainable Development Goals. Thus, an analysis of people’s attitudes towards social policy and perceptions of professional development in Poland against European development policy is crucial. The nationwide representative sample included 1,000 respondents aged 18-64. The study used principal component analysis (PCA), an approach for the multi-response optimisation. The results indicate that respondents’ evaluations are in line with the direction of EU labour policy, where their decisions correspond to the planned priorities oriented towards inclusion and cohesion. The PCA analysis showed that employee competencies and priorities for individual standing can be considered strongly correlated. Competencies were also found to be important for the platform to support systemic development. However, the items included in the analysis that are beyond the scope of the ESF+, although even correlated, are of lesser importance. The research results allow to expand knowledge on the perception of the development policy facets promoted by the EU, supplemented by themes of leadership or immigrants. The study may become a starting point for inclusive and cohesive working climate research.

Multimorbidity disease clusters are associated with venous thromboembolism: an extended cross-sectional national study.

Multimorbidity, i.e., two or more non-communicable diseases (NCDs), is an escalating challenge for society. Venous thromboembolism (VTE) is a common cardiovascular disease and it is unknown which multimorbidity clusters associates with VTE. Our aim was to examine the association between different common disease clusters of multimorbidity and VTE. The study is an extended (1997-2015) cross-sectional Swedish study using the National Patient Register and the Multigeneration Register. A total of 2,694,442 Swedish-born individuals were included in the study. Multimorbidity was defined by 45 NCDs. A principal component analysis (PCA) identified multimorbidity disease clusters. Odds ratios (OR) for VTE were calculated for the different multimorbidity disease clusters. There were 16% (n = 440,742) of multimorbid individuals in the study population. Forty-four of the individual 45 NCDs were associated with VTE. The PCA analysis identified nine multimorbidity disease clusters, F1-F9. Seven of these multimorbidity clusters were associated with VTE. The adjusted OR for VTE in the multimorbid patients was for the first three clusters: F1 (cardiometabolic diseases) 3.44 (95%CI 3.24-3.65), F2 (mental disorders) 2.25 (95%CI 2.14-2.37) and F3 (digestive system diseases) 4.35 (95%CI 3.63-5.22). There was an association between multimorbidity severity and OR for VTE. For instance, the occurrence of at least five diseases was in F1 and F2 associated with ORs for VTE: 8.17 (95%CI 6.32-10.55) and 6.31 (95%CI 4.34-9.17), respectively. In this nationwide study we have shown a strong association between VTE and different multimorbidity disease clusters that might be useful for VTE prediction.

Comparison of Three Different Methods in Investigating the Molecular Epidemiology of Carbapenem-Resistant Acinetobacter baumannii Clinical Isolates

The aim of the study was to evaluate the relationship between carbapenem-resistant Acinetobacter baumannii isolates carrying oxacillinase-type carbapenemase genes with "international high-risk clones" (IC I, II, and III) by different molecular epidemiological methods and to statistically compare the concordance and discrimination power of the methods. Carbapenem-resistant and moderately susceptible A.baumannii isolates from non-repeating blood cultures of 72 patients were included in the study. The presence of "blaOXA-23 , blaOXA-24 , blaOXA-51 ve blaOXA-58 " genes within OXA-type carbapenemases was detected by polymerase chain reaction (PCR) method and confirmed by DNA sequence analysis. Pulsed f ield gel electrophoresis (PFGE), multilocus sequence typing (MLST) and matrix-assisted laser desorption/ ionization time- of-flight mass spectrometry (MALDI-TOF MS) analyses were performed to evaluate the clonal relations of IC I, II and III clones together with clinical isolates. In the statistical comparison of the methods, discrimination power was evaluated by Simpson index of diversity (SID) and concordance by "Wallace coefficient". All of the isolates were found to carry blaOXA-23 and blaOXA-51 genes. As a result of the bioinformatic analysis of the four isolates selected for sequence analysis; blaOXA-23 and blaOXA-51 genes were detected in the selected isolates, and the analysis of two isolates carrying blaOXA-51 gene showed 99% similarity with blaOXA-92 gene. The isolates were clustered into five pulsotypes (A, B, C, D and E) according to ≥ 85% similarity coefficient by PFGE. The isolates and RUH 875, RUH 134, LUH 5875 strains belonging to high-risk clones ICI, ICII and ICIII, respectively, were divided into five main groups [A (n= 58), B (n= 8), C (n= 4), D (n= 4) and E (n= 1)] and 10 subgroups (A1, A2, A4, A5, A6, A9, B1, B4, C3, D1) by PFGE. IC clone III (E1) and seven strains showed singleton PFGE profiles (A3, A7, A8, B2, B3, C1, C2). ICII was found in A5 subtype, ICI in C1 subtype and ICIII in E1 subtype. By PFGE subtype groups, 18 pulsotypes were determined and ST1, ST2, ST81, ST157 and ST604 sequence types were found in 20 isolates randomly selected from pulsotypes according to MLST Pasteur scheme (cpn60, fusA, gltA, pyrG, recA, rplB, rpoB). Principal component analysis (PCA) of the spectra of 72 A. baumannii isolates and ICI, ICII and ICIII clones was performed by MALDI-TOF MS. In PCA analysis, the cluster distance level was defined as 1.5 and the isolates were divided into three clusters. IC clone I, II and III together with 70 clinical isolates were grouped in one cluster, while two clinical isolates (AB083 and AB0115) formed singleton clusters. There was no significant agreement between MALDI-TOF MS; MLST and PFGE data according to Wallace coefficient. It was found that PFGE method gave significant results in terms of discrimination power with SID coefficient, MALDI-TOF MS PCA analysis had the lowest discrimination power value, and the Wallace coefficient result of PFGE and MLST was concordant. In conclusion, MALDI-TOF MS may not function as a gold standard method like PFGE and MLST for epidemiological analysis in A.baumannii species and the epidemiological typing protocols used for MALDI-TOF MS need to be improved and developed.

Genetic Diversity Analysis in Medium Duration Pigeonpea [Cajanus cajan (L) Millsp.] Germplasm for Different Agronomic Traits and Biotic Factors

For the people living in tropical and sub-tropical regions, Pigeon pea [Cajanus cajan (L) Millsp.] is a very essential pulse crop because of its high nutrition along with several important features such as feed and fodder for animal consumption, fuel for household work etc. Despite being a multipurpose and attractive crop, its productivity has remained up to 700-800kg ha-1. Along-with low productivity, Pigeon pea is also affected by a number of biotic stresses such as fusarium wilt, pod borer, pod fly. It is therefore, need of the hour to search for the genetic diversity present in the existing cultivars along with wild relatives and landraces. The present investigation was conducted with forty Pigeon pea germplasm to assess the genetic diversity by principal component analysis (PCA). PCA is an important statistical technique which reduces the dimension of the much large data set into a more concise data set while retaining a significant amount of information from the original data. PCA analysis revealed a significant amount of variability present in the germplasm. PC1 contributed maximum variance towards diversity (22.05%) followed by PC2 (15.87%), PC3 (11.39%), PC4 (10.18%), PC5 (9.10%) and PC6 (8.18%). Scatter plot diagram showed that genotypes number 1 (CRG 82), 5 (GJP 1721), 19 (ICPL 15062), and 31 (BAUPP-18-8) exhibited the highest diversity.

Searching for homogeneous regions in regional flood frequency analysis for Southeast Australia

Study regionSoutheast Australia Study focusThis study examines identification of homogeneous regions for regional flood frequency analysis (RFFA) using 201 gauged catchments and applying principal component analysis (PCA) and cluster analysis. Quantile regression technique (QRT) is applied to develop prediction equations. Leave-one-out (LOO) validation is used to evaluate the accuracy of the developed prediction equations. New hydrologic insights for the regionFor the regions formed based on PCA and cluster analysis, the Hosking and Wallis’ heterogeneity (H1) statistics are found to vary in the range of 11.55–24.52, and 5.11–26.27, respectively. The assumed regions are highly heterogeneous as H1 values are much higher than 1.00. The median of absolute relative error values associated with the developed prediction equations for the assumed regions are found to vary in the range of 17–62 %, which are comparable to similar RFFA studies. PCA and cluster analysis do not deliver sufficiently homogeneous regions in southeast Australia. The degree of heterogeneity of a region has little effect on the relative accuracy of flood quantile estimates. The findings of this study will assist to update RFFA technique in Australian Rainfall and Runoff (national guideline).

Red rice (Oryza sativa L.) composition and its water interaction

Red rice (RR) is renowned for its exceptional nutritional properties and bioactive compounds. Preservation techniques can extend its shelf-life and enhance its market value. Understanding the relationship between the nutritional composition of RR and its water interaction is crucial for improving processing control, product quality and its culinary implications. This study evaluates the influence of RR composition and its water interaction. Nutritional composition was measured. A drying process was conducted to raise the drying critical processing points/periods using an incubator with airflow (1 m/s) at 60 °C. Empirical models were applied to assess the response of the biological material and ensure a good fit. The experiments and statistical analyses were conducted in triplicate. Principal Component Analysis (PCA) was employed to evaluate the correlation between drying periods and the nutritional composition. Results revealed that the nutritional composition influenced the drying critical points/periods. The applied models adjusted well for 'MNA-PB-901', 'MNA-PB-902', and 'MNA-PB-405', while Page's model best fit the experimental data for 'CAQUI' and 'MARANHÃO'. PCA analysis indicated that carbohydrates and amylose impacted superficial water content. A positive correlation was observed between the ash content and "D" point, and crude Fibre and "E" point.

Turkish cultural adaptation, validity, and reliability of the stroke activity scale in individuals with Hemiparesis

ABSTRACT Aim The aim of this study was to make the Turkish cultural adaptation of the the Stroke Activity Scale (SAS). Method This study was designed as a methodological research. The psychometric properties of the SAS scale were evaluated by validity and reliability analyses. Results The average age of 84 stroke patients (mean ± SD) was 59.52 ± 14.03 years. Kaiser-Meyer-Olkin (0.816) and Bartlett’s Test of Sphericity (χ2 = 288.968, df = 10, p < 0.001) showed that the data set can be factored. A one-factor structure was obtained with Principal Component Analysis (PCA). The factor loads of the items obtained with PCA and Confirmatory Factor Analysis (CFA) were found to be statistically significant. The obtained chi-square statistics (χ2 = 2.227, p = 0.694), normalized chi-square/freedom (χ2/sd) value (0 ≤ 0.557 ≤ 2) and other goodness of fit indices showed good compliance. The positive highly significant correlation (r = 0.846, p < 0.001) between the SAS and Rivermead Mobility Index (RMI) scales confirmed the Concurrent validity. Cronbach’s alpha (0.864) value showed high reliability and Intraclass Correlation Coefficient (ICC) value (0.983, p < 0.001) showed excellent agreement. Conclusions In this study, which was conducted for the Turkish adaptation of the SAS scale, the 5-item and 1-factor structure was evaluated as a valid and reliable scale for evaluating the balance abilities of stroke patients living in Turkey.

Integrated application of multiple indicators and geographic information system-based approaches for comprehensive assessment of environmental impacts of toxic metals-contaminated agricultural soils and vegetables

Conventional monitoring and mapping approaches are laborious, expensive, and time-consuming because they need a large number of data and consequently extensive sampling and experimental operations. Therefore, due to the growing concern about the potential of contamination of soils and agricultural products with heavy metals (HMs), a field experiment was conducted on 77 farm lands in an area of 2300 ha in the southeast of Shiraz (Iran) to investigate the source of metal contamination in the soils and vegetables and to model spatial distribution of HMs (iron, Fe; manganese, Mn; copper, Cu; zinc, Zn; cadmium, Cd; nickel, Ni, and lead, Pb) over the region using geographic information system (GIS) and geostatistical (Ordinary Kriging, OK) approaches and compare the results with deterministic approaches (Inverse Distance Weighting, IDW with different weighting power). Furthermore, some ecological and health risks indices including Pollution index (PI), Nemerow integrated pollution index (NIPI), pollution load index (PLI), degree of contamination (Cdeg), modified contamination degree (mCd), PIaverage and PIvector for soil quality, multi-element contamination (MEC), the probability of toxicity (MERMQ), the potential ecological index (RI), total hazard index (THI) and total carcinogenic risk index (TCR) based on ingestion, inhalation, and dermal exposure pathways for adults and children respectively for analyzing the noncarcinogenic and carcinogenic risks were calculated. Experimental semivariogram of the mentioned HMs were calculated and theoretical models (i.e., exponential, spherical, Gaussian, and linear models) were fitted in order to model their spatial structures and to investigate the most representative models. Moreover, principal component analysis (PCA) and cluster analysis (CA) were used to identify sources of HMs in the soils. Results showed that IDW method was more efficient than the OK approach to estimate the properties and HMs contents in the soils and plants. The estimated daily intake of metals (DIM) values of Pb and Ni exceeded their safe limits. In addition, Cd was the main element responsible for ecological risk. The PIave and PIvector indices showed that soil quality in the study area is not suitable. According to mCd values, the soils classified as ultra-high contaminated for Cu and Cd, extremely high for Zn and Pb, very high, high, and very low degree of contamination for Ni, Mn, and Fe, respectively. 36, 60, and 4 % of the sampling sites had high, medium, and low risk levels with 49, 21, and 9 % probability of toxicity, respectively. The maximum health risk index (HRI) value of 20.42 with extremely high risk for children was obtained for Ni and the HI for adults and children were 0.22 and 1.55, respectively. The THI values of Pb and Cd were the highest compared to the other HMs studied, revealing a possible non-cancer risk in children associated with exposure to these metals. The routes of exposure with the greatest influence on the THI and TCR indices were in the order of ingestion > inhalation > dermal. Therefore, ingestion, as the main route of exposure, is the route of greatest contribution to health risks. PCA analysis revealed that Fe, Mn, Cu, and Ni may originate from natural sources, while Fe was appeared to be controlled by fertilizer, and Cu primarily coming from pesticide, while Cd and Pb were mainly associated with the anthropogenic contamination, atmospheric depositions, and terrific in the urban soils. While, Zn mainly originated from fertilization. Findings are vital for developing remediation approaches for controlling the contaminants distribution as well as for monitoring and mapping the quality and health of soil resources.

Honey differentiation with FTIR-ATR spectroscopy – Comparison with physicochemical parameters of a Polish honey sample set

The varietal discrimination of honey is important because its bioactive properties, as well as specific characteristics, depend on the botanical origin. The present study aimed to verify the discriminatory power of Fourier-transform infrared spectroscopy (FT-IR) for differentiating Polish honeys and compare the results with the discrimination power of a model built on the basis of selected physicochemical parameters. For this purpose, buckwheat, rape, acacia, heather, goldenrod, and coniferous honeydew honeys were collected from trustworthy apiaries in different regions of Poland. The samples were further authenticated using pollen analysis and tested by means of FT-IR and the attenuated total reflection (ATR) technique. Basic psychochemical parameters were also assessed. The obtained data were analyzed by means of principal component analysis (PCA) and linear discriminant analysis (LDA). The obtained models were validated with a leave-one-out cross-validation (LOOCV) procedure. PCA analysis confirmed the usefulness of the ATR FT-IR method as a honey differentiation tool. The LDA for the FT-IR model allowed to correctly classify 26 out of 32 samples (81.3% accuracy), which was only slightly lower than for data the model based on the physiochemical characteristics (27 out of 32 samples and 84.4% accuracy), revealing a certain potential of FT-IR as fast evaluation method.

Variability in Crithmum maritimum L. Essential Oils’ Chemical Composition: PCA Analysis, Food Safety, and Sustainability

In this study, four accessions of Crithmum maritimum L., not previously studied, collected in Isola delle Femmine (Italy) (S43), Croatia (S44), Montenegro (S45), and Israel (S46) were investigated. The volatile profile of essential oils was evaluated using GC–MS and 38 compounds were identified. All the analyzed samples show a composition characterized essentially by monoterpene hydrocarbons (94.0–97.6%), with limonene, γ-terpinene, β-phellandrene, α-pinene, and p-cymene as the principal compounds. In addition, a comprehensive review of the composition of C. maritimum essential oils that have been studied thus far was conducted. To evaluate the similarity between samples, principal component analysis (PCA) and Hierarchical Cluster Analysis (HCA) were utilized. To evaluate the possibility of addressing food value to natural species that can strengthen sustainable food policies, it appears necessary to consider the previous safety of the dietary intake of C. maritimum. A matrix plot analysis of the content of dillapiole, a toxic constituent, in the samples was performed. The results of the statistical analysis show the presence of six clusters indicating some differences between C. maritimum accessions from different locations. Regarding dillapiole content, the four accessions discussed in this paper showed dillapiole values of less than 2%, suggesting the healthiness of sea fennel from these locations, while the highest values were found in samples from France, Portugal, and Tunisia.

Revealing distinct DNA methylation patterns in hepatic carcinoma through high-throughput sequencing

Abstract Objectives To study the relationship between DNA methylation and tumour development and provide experimental evidence for the personalized diagnosis and treatment of hepatic carcinoma. Methods The DNA of hepatic carcinoma tissue (Ca group) and adjacent normal tissue (T group) were extracted using the phenol-chloroform method and then treated with bisulfite. Twenty-five genes including 45 subtypes were amplified by PCR. The PCR products were sequenced via the Illumina 450k methylation array assay. The changes of methylated DNA performance were analysed through principal component analysis (PCA). Cluster analysis was used to evaluate the classification of methylated DNA regions. Haplotype abundance variation was tested for methylation differences. Statistical analysis was performed using the chi-square (χ2) test or Fisher’s exact test. Results Sequencing discoveries indicated CG-type methylation pervading all amplicons. However, CHG-type and CHH-type methylations were confined to only four amplicons (or nine subtypes). The methylation ratios of three specific amplicons (DAB2IP, PRDM14-1, Rab31-1) out of 45 amplicon subtypes in the Ca group significantly increased (over 10 %) compared to the T group (p&lt;0.05). Nineteen amplicons demonstrated minor distinction (methylation pattern variations between 1 and 10 %), with the remaining 23 amplicons showing only minimal disparities (under 1 %). PCA and cluster analysis unveiled a marked difference in methylation levels between cancerous and healthy tissues (p&lt;0.05). Conclusions The changes in haplotypes and methylation sites could serve as a biomarker for the clinical diagnosis of hepatic carcinoma. Methylation patterns might play an important role in the occurrence and development of hepatic carcinoma.

Respiratory fit test panel representing population of Malaysia

BackgroundThe existing respiratory fit test panels (RFTPs) are based on Bivariate and Principal Component Analysis (PCA) which utilise American and Chinese head and facial dimensions. As RFTPs based on local facial anthropometric data for Malaysia are not available, this study was conducted with the aim to develop new RFTPs using Malaysian data.MethodologyA cross-sectional study was conducted across Malaysia among 3,324 participants of the study of National Health and Morbidity Survey 2020 aged 18 and above. Ten head and facial dimensions were measured. Face length and face width were used to construct bivariate facial panel, whereas the scores from the first two PCA were used to develop the PCA panel.ResultsThis study showed that Malaysians have the widest upper limit for facial width. It also found that three factors could be reduced from the PCA analysis. However only 2 factors were selected with PCA 1 representing head and facial size and PCA 2 representing facial shape. Our bivariate panel could accommodate 95.0% of population, while our PCA panel accommodated 95.6%.ConclusionThis was the first study to use Malaysian head and facial anthropometry data to create bivariate and PCA panels. Respirators constructed using these panels are likely to fit ≥ 95.0% of Malaysia’s population.

Capturing COPD heterogeneity: anomaly detection and parametric response mapping comparison for phenotyping on chest computed tomography.

Chronic obstructive pulmonary disease (COPD) poses a substantial global health burden, demanding advanced diagnostic tools for early detection and accurate phenotyping. In this line, this study seeks to enhance COPD characterization on chest computed tomography (CT) by comparing the spatial and quantitative relationships between traditional parametric response mapping (PRM) and a novel self-supervised anomaly detection approach, and to unveil potential additional insights into the dynamic transitional stages of COPD. Non-contrast inspiratory and expiratory CT of 1,310 never-smoker and GOLD 0 individuals and COPD patients (GOLD 1-4) from the COPDGene dataset were retrospectively evaluated. A novel self-supervised anomaly detection approach was applied to quantify lung abnormalities associated with COPD, as regional deviations. These regional anomaly scores were qualitatively and quantitatively compared, per GOLD class, to PRM volumes (emphysema: PRMEmph, functional small-airway disease: PRMfSAD) and to a Principal Component Analysis (PCA) and Clustering, applied on the self-supervised latent space. Its relationships to pulmonary function tests (PFTs) were also evaluated. Initial t-Distributed Stochastic Neighbor Embedding (t-SNE) visualization of the self-supervised latent space highlighted distinct spatial patterns, revealing clear separations between regions with and without emphysema and air trapping. Four stable clusters were identified among this latent space by the PCA and Cluster Analysis. As the GOLD stage increased, PRMEmph, PRMfSAD, anomaly score, and Cluster 3 volumes exhibited escalating trends, contrasting with a decline in Cluster 2. The patient-wise anomaly scores significantly differed across GOLD stages (p < 0.01), except for never-smokers and GOLD 0 patients. In contrast, PRMEmph, PRMfSAD, and cluster classes showed fewer significant differences. Pearson correlation coefficients revealed moderate anomaly score correlations to PFTs (0.41-0.68), except for the functional residual capacity and smoking duration. The anomaly score was correlated with PRMEmph (r = 0.66, p < 0.01) and PRMfSAD (r = 0.61, p < 0.01). Anomaly scores significantly improved fitting of PRM-adjusted multivariate models for predicting clinical parameters (p < 0.001). Bland-Altman plots revealed that volume agreement between PRM-derived volumes and clusters was not constant across the range of measurements. Our study highlights the synergistic utility of the anomaly detection approach and traditional PRM in capturing the nuanced heterogeneity of COPD. The observed disparities in spatial patterns, cluster dynamics, and correlations with PFTs underscore the distinct - yet complementary - strengths of these methods. Integrating anomaly detection and PRM offers a promising avenue for understanding of COPD pathophysiology, potentially informing more tailored diagnostic and intervention approaches to improve patient outcomes.