Principal Component Analysis Research Articles

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.

Analysis of the Role of Human Capital on Economic Growth in the Beijing-Tianjin-Hebei

Abstract This paper uses some human capital related data in the Beijing-Tianjin-Hebei region as empirical data to study the impact of human capital on the economic growth of the Beijing-Tianjin-Hebei region; based on the selected data, the principal component analysis method is used to analyze health human capital, education human capital, and comprehensive human capital. Measure and compare the human capital differences of the three places in Beijing, Tianjin and Hebei. Finally, based on the economic growth model, the three places are regression analysis, and the results of different types of human capital on the three places are obtained. The analysis results show that different types of human capital measurement values in the Beijing-Tianjin-Hebei region are indeed different. In general, the human capital in the Beijing-Tianjin-Hebei region contributes more to economic growth than physical capital, and the contribution of health human capital is better than that of education human capital. Keywords: Human capital, Economic growth, Regression analysis, Principal component analysis, Health; Education.

Using principal component analysis to determine which vestibular stimuli provide best biomarkers for separating Alzheimer's from mixed Alzheimer's disease.

Alzheimer's disease (AD) is often mixed with cerebrovascular disease (AD-CVD). Heterogeneity of dementia etiology and the overlapping of neuropathological features of AD and AD-CVD make feature identification of the two challenging. Separation of AD from AD-CVD is important as the optimized treatment for each group may differ. Recent studies using vestibular responses recorded from electrovestibulography (EVestG™) have offered promising results for separating these two pathologies. An EVestG measurement records responses to several different physical stimuli (called tilts). In previous research, the number of EVestG features from different tilts was selected based on physiological intuition to classify AD from AD-CVD. As the number of potential characteristic features from all tilts can be very large, in this study, we used an algorithm based on principal component analysis (PCA) to rank the most effective vestibular stimuli for differentiating AD from AD-CVD. Analyses were performed on the EVestG signals of 28 individuals with AD and 24 with AD-CVD. The results of this study showed that tilts simulating the otolithic organs (utricle and saccule) generated the most characteristic features for separating AD from AD-CVD.

Impact of salt content on Douchi metabolites: biogenic amines, non-volatile compounds and volatile compounds.

The excessive salt intake associated with Douchi has become a topic of controversy. Addressing this concern and enhancing its market competitiveness necessitates the application of salt reduction fermentation in Douchi. Therefore, to promote the application of salt reduction fermentation in Douchi, a comprehensive study was undertaken aiming to investigate the differences in biogenic amines, volatile compounds and non-volatile compounds in Douchi with varying salt content. The findings unequivocally demonstrate that salt hampers the formation of metabolites in Douchi. As the salt content increased, there was a significant decrease (P < 0.05) in the levels of total acid, amino-type nitrogen and free amino acids in Douchi. Notably, when the salt content exceeded 80 g kg-1, there was a substantial reduction (P < 0.05) in putrescine, lactic acid and malic acid levels. Similarly, when the salt content surpassed 40 g kg-1, β-phenethylamine and oxalic acid levels exhibited a significant decline (P < 0.05). Furthermore, the results of E-nose and principal component analysis based on headspace solid phase microextraction gas chromatography-mass spectrometry revealed notable discrepancies in the volatile compound content between Douchi samples with relatively low salt content (40 and 80 g kg-1) and those with relatively high salt content (120, 160 and 200 g kg-1) (P < 0.05). By employing partial least squares discriminant analysis, eight distinct volatile compounds, including o-xylene, benzaldehyde and 1-octen-one, were identified. These compounds exhibited higher concentrations in Douchi samples with relatively low salt content (40 and 80 g kg-1). The sensory results showed that Douchi samples with lower salt content exhibited higher scores in the soy sauce-like and Douchi aroma attributes. In conclusion, this study significantly enhances our understanding of the impact of salt on metabolites in Douchi and provides invaluable insights for the development of salt reduction fermentation in this context. © 2024 Society of Chemical Industry.

Water Quality Assessment Using the Water Quality Index, and Geographic Information Systems in Nador Canal, Morocco

In recent decades, water pollution has emerged as a significant concern, posing a threat to both humans and natural ecosystems. This study aimed to assess the spatial variations in water quality in the Nador Canal, Morocco using the water quality index combined with multivariate statistical techniques and geographic information systems (GIS). The parameters examined were then compared to the maximum permissible limit values recommended by Moroccan surface water standards and the World Health Organization. The results indicated that the WQI of Nador Canal is generally suitable for irrigation and unsuitable for drinking. It indicated that the quality of surface water in the Nador Canal is affected by organic pollutants, and this is evidenced by low levels of dissolved oxygen, the levels of elements were high, especially chlorine and sodium, in addition to a high concentration of ammonia, nitrate, and phosphate in some of the stations studied. Principal component analysis (PCA) results revealed that PC1–PC3 collectively accounted for 73% of the variation in surface water quality within the study area. The cluster analysis also proves that the water quality is relatively polluted. Potential contributing factors to surface water pollution include changes in the hydrological regime, household waste discharges, and agricultural activities. These findings furnish essential insights into water quality, particularly its suitability for irrigation, and contribute to enhancing the water quality management system of the Nador Canal in the Gharb region of Morocco.

Implementation of the International Classification of Diseases 11th revision behavioural indicators for disorders of intellectual development with co-occurring autism spectrum disorder.

The classification of mental, behavioural and neurodevelopmental disorders in the World Health Organization's International Classification of Diseases 11th revision (ICD-11) includes a comprehensive set of behavioural indicators (BIs) within the neurodevelopmental disorders grouping. BIs can be used to assess the severity of disorders of intellectual development in situations in which standardised measures of intellectual functioning and adaptive behaviours are not available or feasible. This international study examines the implementation characteristics of the BIs and compares them to standardised measures for assessing the severity of intellectual impairment and adaptive behaviours in disorders of intellectual development and autism spectrum disorder (ASD). The clinical utility of the ICD-11 and the fidelity of its application in international clinical settings were also assessed. A total of 116 children and adolescents (5-18years old) with a suspected or established diagnosis of disorders of intellectual development were included across four sites [Italy (n=18), Sri Lanka (n=19) and two sites in India (n=79)]. A principal component analysis was conducted to evaluate the application of the ICD-11 guidance for combining severity levels. Assessment using the BIs showed a higher proportion of individuals classified with mild severity, whereas the standardised measures indicated a higher proportion of severe ratings. Additionally, individuals with co-occurring ASD tended to have more severe impairments compared with those without ASD, as indicated by both BIs and standardised measures. Overall, the BIs were considered clinically useful, although more time and consideration were required when applying the guidelines for individuals with a co-occurring disorder of intellectual development and ASD. The principal component analysis revealed one principal component representing overall disorders of intellectual development severity levels. The ICD-11 BIs can be implemented as intended in international clinical settings for a broad range of presentations of individuals with neurodevelopmental disorders. Use of the BIs results in similar severity diagnoses to those made using standardised measures. The BIs are expected to improve the reliability of severity assessments in settings where appropriate standardised measures for intellectual and adaptive behaviours are not available or feasible.

Trends in Water Quality in a Tropical Kenyan River-estuary System: Responses to Anthropogenic Activities

Aims: To determine the spatial variation in physico-chemical water quality attributes in estuarine ecosystems of South Coast Kenya to inform its management. Study Design: We employed diagnostic research design where such factors as anthropogenic activities, hydrology, and accessibility were considered in choosing 12 sampling stations. A mixed sampling design (probability and non-probability) was used to sample. Place and Duration of Study: Four discharging rivers into estuarine system with a reference point were identified. 12 sampling points were earmarked and sampled for 12 months. Methodology: Nine selected water quality parameters were collected in triplicates monthly for 12 months. Temperature, dissolved oxygen, pH, conductivity, salinity and TDS were collected in situ using YSI Multiparameter meter (Professional plus) while nutrients were analyzed in the laboratory calorimetrically. Data was tested for normality and homogeneity of variances using Levene's and Shapiro-Wilk tests. Two-way analysis of variance (ANOVA), and Principal Component Analysis (PCA) were done using the 64-bit R Software version 4.3.0 to test for significant differences and correlate the parameters among the sampling sites respectively. Observed differences were considered statistically significant at P &lt; 0.05. Results: The measured environmental variables differed significantly among the sampling stations (P &lt; 0.05). temperature and salinity exhibited moderate to strong effect on water quality, while pH and nutrients (phosphates, nitrates, and ammonia) exhibited mixed effects with both negative and positive loadings on the Principal Components. It is demonstrated that the south coast estuary, Kenya is affected by two gradients: mineralization from the sea and the organic matter gradient at the upstream stations dominated by the fluvial inflows from the respective rivers. Conclusion: The south coast of Kenya estuary is impacted by natural processes and anthropogenic activities. we recommend for continued regular water quality assessment and monitoring to acquire sufficient data to shape policy frameworks towards its sustainable management.

Functional typology of settlements in the Srem region, Serbia

Abstract The development of the functional settlement typology methodology is of academic and practical importance as it incorporates the social, economic, and demographic dimensions of regional development. Rural settlements are seen as a base for labor; traditional urban centers have become a base for commuters, while at the same time, new economic centers are emerging where capital investment is accumulating. This article presents the research conducted in the Srem region (located in the province of Vojvodina) to determine the functional typology of the settlement, which is of social, economic, and demographic importance for the region itself and for Serbia as a whole. This well-known immigration area in Serbia has been inhabited for centuries for its specific economic and political reasons. The very intensive economic activities of the last two decades have been influenced by development investments and contributed to the functional transformation of the settlements. The census data from 2022 make it possible to determine a functional typology of settlements in the Srem region using the factor method (principal component analysis). The article aims to explain the basic characteristics of functional types of settlements and to determine the mechanisms of their territorial distribution, which would be helpful in the future planning and organization of local and regional development of the Republic of Serbia.

Nutrition addition alleviates negative drought effects on Quercus acutissima seedlings

Changing precipitation patterns have exacerbated severe drought events, causing tree die-off and forest mortality. Nutrition addition, as a critical method for forest management, may alleviate negative drought effects. Therefore, we set up a two-factor orthogonal experiment to study the responses of the leaf structural traits of Quercus acutissima to nutrition addition under drought stress. Leaf structural traits, including leaf morphological traits, leaf mass, and leaf nutrition traits, were measured under nine water and nutrition addition treatments. Two-way analysis of variance was used to detect the main effect and interaction of water and nutrition addition on leaf structural traits, principal component analysis was used to screen key traits. Our results show that drought had a unique and decisive effect on leaf length, leaf width, and leaf center, while leaf thickness only depended on nutrition addition. Conversely, no treatments changed the leaf length-width ratio and leaf nitrogen-phosphorus ratio. Besides, nutrition addition alleviated negative drought effects on leaf area, leaf saturated mass, leaf dry mass, leaf nitrogen content, leaf phosphorus content, leaf volume, specific leaf area, and leaf dry-matter content. According to the principal component 1 (54.83%), we screened seven key traits from leaf structural traits, including leaf area, leaf saturated mass, leaf dry mass, leaf nitrogen content, leaf volume, specific leaf area, and leaf dry-matter content, to effectively capture changes in leaf structural traits. Our results demonstrate that under drought stress, nutrition addition enhanced soil nutrition availability, increased leaf nitrogen and leaf phosphorus content, and finally alleviated negative drought effects. Thus, nutrition addition is crucial for plants to get through drought and for forest ecological restoration under global climate change.

Differentiation of Polygonatum Cyrtonema Hua from Different Geographical Origins by near-Infrared Spectroscopy with Chemometrics.

The identification of the geographical origin of Polygonatum cyrtonema Hua is of particular importance because the quality and market value of Polygonatum cyrtonema Hua from different production areas are highly variable due to differences in the growing environment and climatic conditions. This study utilized near-infrared spectra (NIR) of Polygonatum cyrtonema Hua (n = 400) to develop qualitative models for effective differentiation of Polygonatum cyrtonema Hua from various regions. The models were produced under different conditions to distinguish the origins distinctly. Ten pre-processing methods have been used to pre-process the original spectra (OS) and to select the most optimal spectral pre-processing method. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA) were employed to determine appropriate models. For simplicity, the pretreated full spectrum was calculated by different wavelength selection methods, and the four most significant variables were selected as discriminant indicator variables. The results show that Polygonatum cyrtonema Hua from different regions can be effectively distinguished using spectra from a series of samples analyzed by OPLS-DA. The accuracy of the OPLS-DA model is also satisfactory, with a good differentiation rate. The study findings indicate the feasibility of using spectroscopy in combination with multivariate analysis to identify the geographical origins of Polygonatum cyrtonema Hua. The utilization of near-infrared spectroscopy combined with chemometrics exhibits high efficacy in discerning the provenance of herbal medicines and foods, thereby facilitating quality assurance measures.

Validation of the Cognitive Assessment Instrument for Obsessions and Compulsions (CAIOC-13) in an Indian Sample

Background: Brief self-report measures of cognition are advantageous for flagging significant cognitive dysfunction without extensive neuropsychological assessments. The Cognitive Assessment Instrument for Obsessions and Compulsions (CAIOC-13) is a recently developed self-report that assesses everyday cognitive dysfunction in obsessive-compulsive disorder (OCD), for example, difficulties with reading, slowness, and decision-making. This study was undertaken to validate the CAIOC-13 in an Indian sample of OCD. Material and Methods: 75 subjects with OCD and 81 non-clinical controls completed CAIOC-13, Perceived Deficits Questionnaire (PDQ), and Dysfunctional Attitude Scale-Short Form (DAS-SF1). Convergent and divergent validity with PDQ and DAS-SF1 were established with Pearson’s correlation; the Receiver Operating Characteristic (ROC) curve was used to analyze discriminant validity; and factorial structure was evaluated using the principal component analysis (PCA). Results: CAIOC-13 scores showed a strong significant correlation ( r = 0.56; p &lt; .001) with PDQ and a moderate correlation with DAS-SF1 scores ( r = 0.33; p = .003). CAIOC-13 could accurately discriminate between OCD and controls (area under curve = 0.92). PCA revealed strong loading on a single component. Conclusion: CAIOC-13 is a valid tool for briefly assessing OCD-related cognitive dysfunction in Indian samples. Future studies may examine the correlation of CAIOC-13 with standardized neuropsychological assessments.

Thermal behavior of Sicilian clay-based geopolymers

AbstractGeopolymers have been recently proposed for restoration of built heritage to substitute traditional mortars. Local materials and industrial wastes from the Italian region Sicily showed their potential as low-cost aluminosilicate sources for the preparation of geopolymers. Here, a set of Sicilian clays was studied by Thermogravimetry (TG) and Differential Scanning Calorimetry (DSC), and its mineralogical composition was evaluated by X-ray diffraction (XRD). The raw materials were used to prepare geopolymers by alkaline activation with or without the addition of silicate. The thermal degradation profile of the final materials was studied by TGA and compared with that of the precursors, and the energetics of dehydration were investigated by DSC. Two statistical analyses (made by Principal Component Analysis) were performed on the TG data of raw materials and geopolymers and on the TG data of geopolymers and their mineralogical composition, respectively. The last analysis in particular showed a correlation between the mineralogical composition of the materials and the samples' thermal properties. Additional studies of samples subject to accelerated aging by UV irradiation and exposure to acetic acid vapors highlighted the different effects of these two agents on the samples’ stability. Graphical abstract

Morphological characterisation of ethnomedicinally important Kaempferia L. (Zingiberaceae) and its present distribution status in Manipur, North-East India

Kaempferia L., a member of the Zingiberaceae family, is one of the most potent medicinal plants in India and requires proper attention. Our efforts to collect various species of Kaempferia in their natural habitat led to the collection of 30 accessions, including K. galanga, K. marginata, K. parviflora, K. rotunda, and five other unidentified Kaempferia species that are likely natural hybrids with no distinguishing features. It has been found that rhizomes are the most usable portion of the plant, and people in this region use them the most for medical purposes. The present study aimed to describe and evaluate the morphological structures of the plant, incorporating 52 phenotypic descriptors. Descriptive statistics and multivariate analysis were employed to explore diversity. The majority of the traits tested were highly variable. The elevation range (28704.02%) and plant height (at 648.03 %) had the largest coefficients of variation (CV %), whereas anther length (0.06 %) and corolla shape (0.19 %) had the lowest. Rhizome size has a high positive correlation with the odour of the aerial plant parts, growing, dormant, new shoots sprouting, and flowering seasons. However, it shows negative correlations with elevation, lifespan of the flower, and number of leaves. Principal component analysis (PCA), revealed that the first five components accounted for 89.90 % of the variability, and hierarchical grouping based on accession dissimilarity revealed two significant groupings. It was found that wild K. species populations were genetically diverse, suggesting that this diversity can be used for agronomic and horticultural purposes to isolate and characterise numerous important, well-adapted genotypes with the potential to significantly increase yields. Therefore, it is crucial to conserve the genetic material that is currently available.

Dissolved trace elements and nutrients in the North Sea—a current baseline

Primary production is an important driver of marine carbon storage. Besides the major nutrient elements nitrogen, phosphorus, and silicon, primary production also depends on the availability of nutrient-type metals (e.g., Cu, Fe, Mo) and the absence of toxicologically relevant metals (e.g., Ni, Pb). Especially in coastal oceans, carbon storage and export to the open ocean is highly variable and influenced by anthropogenic eutrophication and pollution. To model future changes in coastal carbon storage processes, a solid baseline of nutrient and metal concentrations is crucial. The North Sea is an important shelf sea, influenced by riverine, atmospheric, Baltic Sea, and North Atlantic inputs. We measured the concentrations of dissolved nutrients (NH4+, NO3−, PO43−, and SiO44−) and 26 metals in 337 water samples from various depths within the entire North Sea and Skagerrak. A principal component analysis enabled us to categorize the analytes into three groups according to their predominant behavior: tracers for seawater (e.g., Mo, U, V), recycling (e.g., NO3−, PO43−, SiO44−), and riverine or anthropogenic input (e.g., Ni, Cu, Gd). The results further indicate an increasing P-limitation and increasing anthropogenic gadolinium input into the German Bight.

Design and psychometric evaluation of the collaborative coping with infertility questionnaire in candidate of assisted reproductive techniques

Evaluating couples’ coping with infertility and its impact on their mental health is valuable in designing supportive programs. Since infertility is a shared problem in married life, coping with it requires collaborative coping strategies. Therefore, the aim of the present study was to design and psychometrically evaluate the collaborative coping with infertility questionnaire (CCIQ) in candidates of assisted reproductive techniques (ART). The exploratory factor analysis of a 27-item questionnaire designed based on the Likert scale in the Persian language was evaluated through the principal component analysis method in a cross-sectional study conducted on 200 couples who volunteered for ART. The cut-off point of factor loadings was considered 0.4. Furthermore, the criterion validity of the questionnaire was evaluated using a 12-item revised Fertility Adjustment Scale (R-FAS) and its relationship with the score of the CCIQ. Moreover, the internal consistency of the questionnaire was evaluated using Cronbach’s alpha correlation coefficient. In the exploratory factor analysis, 20 items with a factor loading above 0.4 were extracted under three factors. The three extracted factors with a value above one explained 43.78% of the variance of CCIQ. The factor loading of the accepted items ranged between 0.402 and 0.691. External reliability was confirmed with Cronbach’s alpha coefficient of 0.98. The relationship between CCIQ and R-FAS score was significant (p < 0.0001). The results of the study showed that the 20-item CCIQ enjoyed acceptable validity and reliability in the three dimensions of ‘dynamic interaction,’ ‘reorganizing married life goals,’ and ‘perception about infertility,’ which can be used to evaluate collaborative coping with infertility questionnaire in ART candidates.

OPN, BSP, and Bone Quality-Structural, Biochemical, and Biomechanical Assessment in OPN-/-, BSP-/-, and DKO Mice.

Osteopontin (OPN) and Bone Sialoprotein (BSP), abundantly expressed by osteoblasts and osteoclasts, appear to have important, partly overlapping functions in bone. In gene-knockout (KO, -/-) models of either protein and their double (D)KO in the same CD1/129sv genetic background, we analyzed the morphology, matrix characteristics, and biomechanical properties of femur bone in 2 and 4month old, male and female mice. OPN-/- mice display inconsistent, perhaps localized hypermineralization, while the BSP-/- are hypomineralized throughout ages and sexes, and the low mineralization of young DKO mice recovers with age. The higher contribution of primary bone remnants in OPN-/- shafts suggests a slow turnover, while their lower percentage in BSP-/- indicates rapid remodeling, despite FTIR-based evidence in this genotype of a high maturity of the mineralized matrix. In 3-point bending assays, OPN-/- bones consistently display higher Maximal Load, Work to Max. Load and in young mice Ultimate Stress, an intrinsic characteristic of the matrix. Young male and old female BSP-/- also display high Work to Max. Load along with low Ultimate Stress. Principal Component Analysis confirms the major role of morphological traits in mechanical competence, and evidences a grouping of the WT phenotype with the OPN-/- and of BSP-/- with DKO, driven by both structural and matrix parameters, suggesting that the presence or absence of BSP has the most profound effects on skeletal properties. Single or double gene KO of OPN and BSP thus have multiple distinct effects on skeletal phenotypes, confirming their importance in bone biology and their interplay in its regulation.

CgSSR marker based trait associations for Sitotroga cerealella (Olivier) resistance in stored paddy rice

Rice is stored for a longer time and many primary and secondary insect pests attack grains, causing both quantitative and qualitative losses. Physicochemical characteristics of grain influence stored grain insect susceptibility and resistance. Identification of gene/Quantitative Trait Loci (QTLs) and introgression in the cultivars would provide the desired solution for varietal resistance against S. cerealella. A group of 80 rice varieties was used for genetic analysis for the identification of candidate genes responsible for Sitotroga cerealella resistance. Heat maps derived from values in the kinship matrix were used to group the varieties into three subpopulations. The largest subpopulation has 34 varieties, while the lowest had 19. The first three principal components (PCs) explained 16, 9, and 6 percent of total variation, respectively, as indicated by the Principal Component Analysis (PCA). The PCA results complemented the heat map results in defining population structure. Genome-wide association mapping can detect marker-trait associations/QTLs in a heterogeneous population of breeding lines, despite population structure and unequal family relatedness. As shown by the Genomic Association and Prediction Integrated Tool (GAPIT) heat map, there are three subpopulations in the association mapping panel. Two cgSSR markers, related to gene SDG725 and FLO2, were linked to the attributes and responsible for conferring resistance against S. cerealella infestation. This is the first report of association and that would help in the development of cultivar with S. cerealella resistance.

Analysis and validation of biomarkers of immune cell-related genes in postmenopausal osteoporosis: An observational study.

Postmenopausal osteoporosis (PMOP) is a common metabolic inflammatory disease. In conditions of estrogen deficiency, chronic activation of the immune system leads to a hypo-inflammatory phenotype and alterations in its cytokine and immune cell profile, although immune cells play an important role in the pathology of osteoporosis, studies on this have been rare. Therefore, it is important to investigate the role of immune cell-related genes in PMOP. PMOP-related datasets were downloaded from the Gene Expression Omnibus database. Immune cells scores between high bone mineral density (BMD) and low BMD samples were assessed based on the single sample gene set enrichment analysis method. Subsequently, weighted gene co-expression network analysis was performed to identify modules highly associated with immune cells and obtain module genes. Differential analysis between high BMD and low BMD was also performed to obtain differentially expressed genes. Module genes are intersected with differentially expressed genes to obtain candidate genes, and functional enrichment analysis was performed. Machine learning methods were used to filter out the signature genes. The receiver operating characteristic (ROC) curves of the signature genes and the nomogram were plotted to determine whether the signature genes can be used as a molecular marker. Gene set enrichment analysis was also performed to explore the potential mechanism of the signature genes. Finally, RNA expression of signature genes was validated in blood samples from PMOP patients and normal control by real-time quantitative polymerase chain reaction. Our study of PMOP patients identified differences in immune cells (activated dendritic cell, CD56 bright natural killer cell, Central memory CD4 T cell, Effector memory CD4 T cell, Mast cell, Natural killer T cell, T follicular helper cell, Type 1 T-helper cell, and Type 17 T-helper cell) between high and low BMD patients. We obtained a total of 73 candidate genes based on modular genes and differential genes, and obtained 5 signature genes by least absolute shrinkage and selection operator and random forest model screening. ROC, principal component analysis, and t-distributed stochastic neighbor embedding down scaling analysis revealed that the 5 signature genes had good discriminatory ability between high and low BMD samples. A logistic regression model was constructed based on 5 signature genes, and both ROC and column line plots indicated that the model accuracy and applicability were good. Five signature genes were found to be associated with proteasome, mitochondria, and lysosome by gene set enrichment analysis. The real-time quantitative polymerase chain reaction results showed that the expression of the signature genes was significantly different between the 2 groups. HIST1H2AG, PYGM, NCKAP1, POMP, and LYPLA1 might play key roles in PMOP and be served as the biomarkers of PMOP.

Efficient and Simplified Modeling for Kerosene Processing Quality Detection Using Partial Least Squares-Discriminant Analysis Regression

Kerosene from various refineries and crudes is used for heating and other purposes in many countries like Iraq; therefore, it is important to identify its source to recognize and tax any adulteration. In this study, a fast classification technique for kerosene marketed in Iraq was developed with the goal of identifying its quality. The samples were categorized using a supervised partial least squares discriminant analysis (PLS-DA) approach. Multivariate analyses using agglomerative hierarchal clustering and principal component analysis were utilized to identify outliers and sample dissimilarities. The dataset was divided into calibration and prediction sets. The prediction set was used to evaluate the model’s separation performance. The Q2 cross-validation was applied. The PLS-DA models achieved significant accuracy, sensitivity, and specificity, showing strong segregation ability, notably for the calibration set (100% accuracy and 1.00 sensitivity). It was found that kerosene processing can be classified rapidly and non-destructively without the need for complicated analyses, demonstrating the best results for classification even when compared with the classification outcomes of other fuels. This PLS-DA approach has never been looked at before for process quality detection, and the results are comparable to direct kerosene classification with soft independent modeling of class analogy and support vector machines.

Ecomorphology of yellowtail lambari (Characiformes: Characidae) in the neotropical semi-arid region, Brazil

The ecomorphological patterns of the Astyanax lacustris in different environments (lotic and lentic) of the semiarid region of Pernambuco were analyzed using 25 linear morphometric measurements on 240 specimens (120 males and 120 females), with standard lengths ranging from 24.25 to 91.50 mm. These data were converted into 16 ecomorphological attributes and correlated with environmental characteristics. The principal component analysis (PCA) explained 81.64% (first and second components) of the data variation, highlighting sexual dimorphism in specimen size and noticeable variation among individuals of the same sex in different environments. Specimens from lotic environments showed higher caudal peduncle compression index (CPCI) values, while the pectoral fin aspect ration (PFAR) was more pronounced in lentic environments. Overall, females exhibited a wide morphometric variation. Analysis of linear morphometry in different water bodies indicated an intrinsic variation related to hydrodynamics linked to sexual dimorphism and water flow speed. Further studies are suggested to investigate whether factors such as macrophytes and different levels of water depth and flow contribute to this morphometric variation of species in the semi-arid region.