Principal Component Analysis Analysis Research Articles

DETECTION OF WHITE RICE ADULTERANTS IN LAMPUNG ROBUSTA COFFEE EXTRACT USING FT-IR METHOD BY FINGERPRINT ANALYSIS AND PRINCIPAL COMPONENT ANALYSIS

Lampung Province has 3 areas that produce coffee: West Lampung, Tanggamus, and Waykanan, which can produce 51,484 tons of coffee annually. The high demand for coffee and limited harvest are some factors that cause the addition of adulterants to coffee products such as corn, soybeans, rye, coffee beans, and rice. This study aims to detect rice adulterants in Lampung robusta coffee using the FTIR spectrophotometric method combined with chemometric analysis using the PCA (Principal Component Analysis) method. FTIR spectrophotometric method combined with chemometric analysis using PCA (Principal Component Analysis) method. The PCA method was validated using the cross-validation method. Samples were taken from 3 Lampung coffees on the market. The extraction process was carried out on Lampung coffee and Lampung rice from 3 regions using 96% ethanol. After concentrating, the coffee and rice extracts were measured using FTIR and read in the 4000-650 cm-1 wave number range. Different wave number curves were obtained between coffee and rice. A pre-processing chemometric analysis was performed, which resulted in the classification of Robusta coffee and rice using PC1 and PC2 (50% and 24%). The results of PCA analysis showed that PC1 and PC2 in the three Lampung coffee samples, samples A and C, did not contain adulterants, while sample B was suspected of containing white rice. Keywords: Alduteran, FTIR, Chemometrics, PCA, Lampung Robusta Coffee.

The potential of calcium nanoparticles in posthaverst conservation of fresh-cut seedless watermelon (Citrullus lanatus)

In fresh cut (FC) watermelon, texture loss on the flesh leads to tissue softening and greater water soaking, reducing the shelf life. This study was assessed the effect of calcium nanoparticles (NP) [CaO-NP and Ca(OH)2-NP] at three concentrations (100, 150, and 200 mg L−1) compared to control (water) and CaCl2 (1 %, w/v), on FC seedless watermelon. Treatments were applied by 3-min immersion and stored for 12 d at 5 ± 1 °C. Quality, oxidative stress and softening variables were determined every four days. The postharvest quality variables for all treatments were subjected to principal component analysis (PCA), followed by cluster analysis, using the first three dimensions obtained from PCA (explaining 71.68 %). The PCA results showed that visual quality (VQ) was the most influential variable. The treatments with Ca(OH)2-NP positively affected FC watermelon while the treatments with CaO-NP showed a negative correlation. Furthermore, the PCA analysis showed a negative correlation between visual quality and the variables juice leakage (JL) and weight loss (WL). Cluster analysis showed that Ca(OH)2-NP treatments at 8 and 12 d were globally closer to the control at 0 d followed by all treatments applied at 4 d of storage. In general, positive effects were observed in the FC seedless watermelon treated with 100 and 150 mg L−1 Ca(OH)2-NP, compared to the FC seedless watermelon treated with CaO-NP in the same concentrations, in the parameters of water soaking, lipid peroxidation and in the PME activity after 12 d of storage. FC seedless watermelon treated with 100, 150 and 200 mg L−1 Ca(OH)2-NP showed 2.2, 4.4 and 3.2 times less water soaking, respectively, compared to the values observed in the same concentrations of CaO-NP. A similar trend was observed in the values of lipid peroxidation parameters and PME activity, where 2.5, 3.2 and 2.7 times less lipid peroxidation and 1.2, 1.4 and 1.8 times lower PME activity were observed. No differences were detected in CAT and POD activities between CaO-NP and Ca(OH)2-NP treatments. In general, the best quality results were obtained in the FC seedless watermelon fruit treated with the different concentrations of Ca(OH)2-NP.

PHYTOPLANKTON COMMUNITY STRUCTURE IN THE EAST PLAWANGAN OF SEGARA ANAKAN, CILACAP

The East Plawangan waters of Laguna Segara Anakan (LSA), Cilacap are unique waters that are characterized by high biodiversity and are a meeting place for several rivers. It is thought that anthropogenic activities around waters will cause changes in ecological conditions. The organisms that first respond to these changes are phytoplankton. The aim of this research is to determine the structure of the phytoplankton community which includes abundance, diversity index, evenness index and dominance index, as well as to determine physical-chemical factors and the relationship between phytoplankton abundance and physical-chemical factors. The method used is a survey method with Purposive Random Sampling at 5 stations. The f test and Lackey Drop Microtransect Counting method were used to determine the abundance of phytoplankton. Principal Component Analysis (PCA) was used to determine the relationship between phytoplankton abundance and physical-chemical factors. The results showed that the abundance of phytoplankton was in the low and medium categories with values of 840 ± 435 to 3814 ± 939 ind/L; The diversity index ranged from 2.42 - 2.99 (medium); The phytoplankton evenness index ranges between 0.74 - 0.89 (high) and the phytoplankton dominance index ranges from 0.06 - 0.14 (low). Physical-chemical factors in East Plawangan are still at the threshold that can be tolerated by phytoplankton. PCA analysis showed a relationship between phytoplankton abundance and physical-chemical factors as indicated by two main factors (F1 and F2) which produced a variance value of 87.49% with the most influencing factor being orthophosphate.

Zoo Benthic Biodiversity as a Bioindicator in the Bengawan Solo Estuary

Graphical Abstract Highlight Research Salinity is the critical influencing the distribution of macrobenthos species based on habitat (seawater and freshwater species) in estuaries. The brackish water station exhibited the highest macrobenthos abundance, whereas the seawater station showed the highest meiobenthos abundance. Corresponding water quality parameters markedly influenced the abundance of each benthic group. The calculation of abundance and biological indexes classified the Bengawan Solo estuary as relatively stable. Abstract As key aquatic organisms, benthos are a reliable indicator of water quality owing to their relatively fixed habitats, limited mobility, and residence at the bottom of the water. This study aimed to analyze benthos' biodiversity and community structure as bioindicators in the waters of the Bengawan Solo estuary that important for fisheries activities conducted by local fishermen community. A descriptive analysis method was employed, involving identifying and analyzing benthos in abundance, biological indexes, and principal component analysis (PCA). The macrobenthos species composition consisted of Gastropoda, Bivalvia, Maxillopoda, Malacostraca, Polychaeta, and Clitellata while meiobenthos comprised Foraminifera, Bivalvia, Gastropoda, and Polychaeta. Macrobenthos abundance was 288 ind./m2, whereas meiobenthos abundance was 16 ind./10 cm2. Both macrobenthos and meiobenthos exhibited a moderate diversity index and a medium evenness index, although evenness values tended to be higher in macrobenthos. The dominance index for both macrobenthos and meiobenthos showed moderate values. PCA analysis revealed that macrobenthos, Bivalvia, Gastropoda, and Clitellata abundance was influenced by brightness and turbidity, Malacostraca and Maxillopoda abundance by salinity, and Polychaeta abundance by dissolved oxygen. In meiobenthos, Gastropoda and Foraminifera abundance was influenced by salinity, whereas Bivalvia and Polychaeta abundance was affected by brightness and turbidity. Abundance and biological index results indicate that the Bengawan Solo estuary is relatively stable.

FT-IR Characterization and Phylogenetic Analysis of Patchouli Oil from West Aceh and Aceh Jaya using PCA and HCA

This study aims to characterize and compare the chemical composition of patchouli oil from various regions in Aceh, Indonesia, using Fourier-transform Infrared Spectroscopy (FT-IR) combined with Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA). Patchouli oil samples from five distinct locations within West Aceh and Aceh Jaya Regencies were analyzed, focusing on the 1800-500 cm⁻¹ range. The FT-IR spectra revealed significant chemical markers, with notable absorption bands corresponding to aliphatic C-H, C=O, and C=C stretching vibrations. Multivariate analyses showed distinct clustering patterns, with four samples (POSM, POSP, POT, and POW) exhibiting high chemical similarity and clustering together, while one sample (POP) formed a separate cluster, indicating a lower degree of similarity. PCA analysis of the original spectra in the 1800-500 cm⁻¹ range yielded a cumulative PC1 and PC2 value of 89%. The HCA dendrogram highlighted a significant relative distance of 10 between the POP sample and the other four samples, indicating minimal relatedness, with the closest relatedness observed between POSM and POSP, having a relative distance of 1.1. This study demonstrates the effectiveness of FT-IR spectroscopy combined with PCA and HCA in distinguishing chemical profiles of patchouli oil from different regions, providing insights into geographical and varietal influences on oil composition. The findings are crucial for quality control and standardization in the patchouli oil industry, with further molecular studies recommended to corroborate and enhance understanding of genetic diversity among patchouli varieties in Aceh.

Comparing quantitative image parameters between animal and clinical CT-scanners: a translational phantom study analysis.

This study compares phantom-based variability of extracted radiomics features from scans on a photon counting CT (PCCT) and an experimental animal PET/CT-scanner (Albira II) to investigate the potential of radiomics for translation from animal models to human scans. While oncological basic research in animal PET/CT has allowed an intrinsic comparison between PET and CT, but no 1:1 translation to a human CT scanner due to resolution and noise limitations, Radiomics as a statistical and thus scale-independent method can potentially close the critical gap. Two phantoms were scanned on a PCCT and animal PET/CT-scanner with different scan parameters and then the radiomics parameters were extracted. A Principal Component Analysis (PCA) was conducted. To overcome the limitation of a small dataset, a data augmentation technique was applied. A Ridge Classifier was trained and a Feature Importance- and Cluster analysis was performed. PCA and Cluster Analysis shows a clear differentiation between phantom types while emphasizing the comparability of both scanners. The Ridge Classifier exhibited a strong training performance with 93% accuracy, but faced challenges in generalization with a test accuracy of 62%. These results show that radiomics has great potential as a translational tool between animal models and human routine diagnostics, especially using the novel photon counting technique. This is another crucial step towards integration of radiomics analysis into clinical practice.

Hybrid wavelength selection strategy combined with ATR-FTIR spectroscopy for preliminary exploration of vintage labeling traceability of sauce-flavor baijiu

The allure of substantial profits has perpetuated the illicit trade of counterfeit vintage labels for baijiu. While various approaches have been employed to intelligently ascertain the vintage of baijiu, many of them are both cost-intensive and time-consuming. This work pioneered the use of Attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy, coupled with chemometric analysis, offering a non-destructive and economically viable method for discriminating sauce-flavor baijiu across different aging periods (1-, 2-, and 3-year). In this research, principal component analysis (PCA) was first conducted to explore clustering trends among distinct vintage groups. Subsequently, the effect of spectral pre-processing on modeling performance was explored. For wavelength selection, four wavelength selection methods (ReliefF, random forest variable importance (RFVI), variable importance in projection (VIP), and Venn) were first used to identify the subset of candidate features that potentially best mapped the vintage labels. Immediately following this, to explore the possibility of further improving the identification capabilities of the model as well as to reduce the redundant data that may still be present, sequential backward selection (SBS) was utilized for secondary feature reduction within the subset of candidates. The amalgamation of these two techniques is termed a “hybrid wavelength selection strategy.” Additionally, the dimensionality reduction effects of PCA and kernel principal component analysis (KPCA) were compared to demonstrate the robustness of the proposed method. Finally, classification models such as partial least squares discriminant analysis (PLS-DA), random forest (RF), and grasshopper optimization algorithm-based support vector machine (GOA-SVM) were developed. The results show that the spectral data need not be pre-processed, and the proposed hybrid wavelength selection strategy can further improve the identification ability of the model. Among the many models developed, ReliefF-SBS-GOA-SVM emerged as the most proficient classification model, yielding accuracy, sensitivity, and specificity rates of 94.44%, 95.23%, and 94.44%, respectively. This method not only holds promise for the discrimination of baijiu class attributes such as brand, origin, flavor, and vintage but also exhibits potential applicability in other non-targeted identification studies involving spectroscopy methodologies.

Chemotherapy-Induced Peripheral Neuropathy and Falls in Cancer Survivors Relate to Digital Balance and Gait Impairments.

Chemotherapy-induced peripheral neuropathy (CIPN) and falls can be persistent side effects of cancer treatment. Standing postural sway and gait tests with body-worn, inertial sensors provide objective digital balance and gait measures that represent several different domains controlling mobility. Specific domains of balance and gait that related to neuropathy and falls are unknown. The aim of this study was to determine which domains of balance and gait differed between cancer survivors who report (1) CIPN symptoms versus no symptoms, (2) a history of falls in the past 6 months versus no falls, and (3) prospective falls over 12 months versus no falls. Postural sway during 30 seconds of quiet standing and gait characteristics from a 7-m timed up and go test were recorded with six synchronized inertial sensors (Opals by APDM Wearable Technologies, a Clario Company) in 425 older, female cancer survivors (age: 62 ± 6 years). A principal component analysis (PCA) approach was used to identify independent domains of mobility from 15 balance and gait measures. PCA analysis revealed five independent domains (PC1 = sway amplitude, PC2 = gait pace, PC3 = sway frequency, PC4 = gait spatial-temporal, and PC5 = turning) that accounted for 81% of the variance of performance. Cancer survivors who reported CIPN symptoms had significantly higher sway frequency (PC3) than asymptomatic survivors. Past fallers had significantly larger sway area (PC1) and slower gait pace (PC2) than nonfallers. Prospective fallers showed a significantly smaller stride length (PC4) than nonfallers. Digital balance and gait measures using wearable sensors during brief standing and walking tests provide objective metrics of CIPN-related mobility impairment and fall risk that could be useful for oncology clinical trials.

Ecohydrological indicators and environmental flow assessment in the middle and lower reaches of the Huai River, China

The vitality of river ecosystems is vital for the sustainable development of river basins, with the assessment of environmental flow (EF) playing a pivotal role in eco-informatics. This study delves into the middle and lower reaches (MLR) of the Huai River basin (HRB) in China, utilizing hydrological data spanning from 1950 to 2020. Its principal objective lies in the selection of ecohydrological indicators to refine the estimation of EF in the HRB. Employing principal component analysis (PCA), ecologically relevant hydrological indicators (ERHIs) were discerned and scrutinized for their hydrological characteristics. The analysis extended to evaluating hydrological shifts at different stations using ERHIs, determining suitable EF in the MLR, and delineating the trajectories of appropriate intra-annual flows in different hydrological years through HEC-RPT. Based on a variety of mutation test methods, the change point of runoff sequence was determined in 1991. The PCA analysis identified eight ERHIs, reflecting hydrological changes of 49.79 % and 56.26 % at Bengbu and Sanhezha, respectively, which indicate a moderate alteration. Based on ERHIs, the other stations in the HRB exhibited hydrological alterations ranging from 33 % to 47 %, notably highlighting substantial changes in maximal 30d flow and flow fall rate. The optimal flood pulse discharge in the middle reaches is 4150 m3/s, 3140 m3/s and 2150 m3/s in wet, dry and dry years, respectively. Downstream, flood pulse flow in wet, normal and dry years should exceed 4070 m3/s, 3110 m3/s and 1980 m3/s, respectively. The research contributes significantly to the management of rivers and the sustainable conservation of the ecological milieu.

Principal Component Analysis of a Real-World Cohort of Descemet Stripping Automated Endothelial Keratoplasty and Descemet Membrane Endothelial Keratoplasty Cases: Demonstration of a Powerful Data-Mining Technique for Identifying Areas of Research.

Principal component analysis (PCA) is a descriptive exploratory statistical technique that is widely used in complex fields for data mining. However, it is rarely used in ophthalmology. We explored its research potential with a large series of eyes that underwent 3 keratoplasty techniques: Descemet membrane endothelial keratoplasty (DMEK), conventional Descemet stripping automated endothelial keratoplasty (ConDSAEK), or ultrathin-DSAEK (UT-DSAEK). All consecutive DMEK/DSAEK cases conducted in 2016 to 2022 that had ≥24 months of follow-up were included. ConDSAEK and UT-DSAEK were defined as preoperative central graft thickness ≥130 and <130 μm, respectively. Seventy-six patient, disease, surgical practice, and temporal outcome variables were subjected to PCA, including preoperative anterior keratometry, the use of sulfur hexafluoride gas (SF6) versus air for primary tamponade, and postoperative best corrected visual acuity and endothelial cell density. Associations of interest that were revealed by PCA were assessed with the Welch t test or Pearson test. A total of 331 eyes were treated with DMEK (n = 165), ConDSAEK (n = 95), or UT-DSAEK (n = 71). PCA showed that ConDSAEK and UT-DSAEK clustered closely, including regarding postoperative best corrected visual acuity, and were clearly distinct from DMEK. PCA and follow-up univariate analyses suggested that in DMEK, 1) flatter preoperative anterior keratometry (average, K1, and K2) associated with more rebubbling (P = 0.004-0.089) and graft detachment (P = 0.007-0.022); 2) graft marking did not affect postoperative ECD; and 3) lower postoperative endothelial cell density associated with SF6 use (all P > 0.001) and longer surgery (P = 0.005-0.091). All associations are currently under additional investigation in our hospital. PCA is a powerful technique that can rapidly reveal clinically relevant associations in complex ophthalmological datasets.

Application of Principal Component Analysis in Determining the Hydrogeochemistry Characteristics of Karst Water in Bac Kan and Cao Bang

Research on the origin and processes affecting the hydrogeochemical characteristics of karst water provides useful information for the management and exploitation of karst water resources. Principal Component Analysis (PCA) was applied to the karst water physicochemical data, including temperature, pH, Electronic Conductivity (EC), Ca2+, Mg2+, Na+, K+, Cl-, HCO3-, SO42-, and NO3- in Ba Be lake (Bac Kan province) and Ha Quang, Trung Khanh (Cao Bang province). The Piper diagram described the main type of hydrochemical facies in karst water at 24/25 survey points as Ca2+-HCO3-. The combination of eleven physicochemical properties was reduced into four main components (PC1, PC2, PC3, PC4) based on eigenvalues of 4,0; 2,5; 1,3 and 1,2, respectively. A total of 81,53% of the variance was represented by four main components, in which PC1 (36,36%) represented the rock-water interaction, PC2 (22,88%) represented pollution sources related to human activities, PC3 and PC4 (22,29%) represented the dissolution of magnesium minerals. The moderate-strong correlation between parameters of the Mia Le Formation’s sample in Ba Be Lake area and PC1 indicated that the major chemical composition of karst water is strongly influenced by the interaction between carbonate rocks and water. This process also occurs intensely at some survey points in the Bac Son, Song Hien, and Cao Bang formations. Meanwhile, some samples NK.19, NK.23, NK.25 of the Bac Son and Song Hien formations had a moderate positive correlation with PC2 and are affected by human activities. Research results have shown that the combination of principal component analysis PCA and correlation analysis is an effective tool in determining karst water characteristics in the area.

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.

Investigating the Effects of Tube Current and Tube Voltage on Patient Dose in Computed Tomography Examinations with Principial Component Analysis and Cluster Analysis: Phantom Study.

The aim of this study was to investigate the effects of tube current and tube voltage choices on patient dose in adult and pediatric CT protocols by qualitative analysis using Principal Component Analysis (PCA), cluster analysis, and statistical analysis.Dose length product (DLP), Effective mAs (Eff. mAs), and volume-weighted CT dose index (CTDIvol) dose descriptors were obtained from 16 adult and pediatric head phantom CT examinations. Different tube voltage and tube current values were selected in both pediatric head and adult head CT imaging protocols, and PCA and cluster analysis were applied to the data obtained for qualitative analysis of the relationship between CTDIvol, Eff. mAs and Total DLP values. The two principial components (PC) with the highest values among those obtained as a result of the PCA method were used. PC1 was 70.97%, and PC2 was 28.03%. In the cluster analysis, it was observed that the values obtained from pediatric and adult phantom CT scans were classified into two different clusters. The correlation coefficient for adult patients was r = 0.998, and for pediatric patients, the correlation coefficient was r = 0.947. When the obtained clusters were examined, the degree of closeness or distance of the variables could be observed. In the study, as a result of the analysis of CTDIvol, Eff. mAs and Total DLP data based on manufacturer data at different kV and mA values with PCA and cluster analysis, it was shown that pediatric patients could be exposed to more radiation than the adult patients.

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 a multifactorial pathophysiological condition with an imbalance in biochemical, immunochemical, redox status and genetic parameters values. We aimed to estimate the connection between relative leucocyte telomere lengths (rLTL) - biomarker of cellular ageing 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 sexes. The results suggested that rLTL are significantly shorter in obese, compared with 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 BMI > 30 kg/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 that oxidative stress importance in biological ageing is caused by obesity and its multiple consequences related to prooxidants augmentation and antioxidants exhaustion and gave us clear signs of disturbed cellular homoeostasis deepness, even before any overt disease occurrence.

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 1000 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.

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.