Multivariate Principal Component Analysis Research Articles

Variability of Silver Fir Needle (Abies alba Mill.) Anatomical Features in the Southeast Europe Natural Populations

The survival of marginal/peripheral silver fir (Abies alba Mill.) populations in the broader region of Southeast Europe is endangered due to climate change and population decline. This study aimed to determine the level and pattern of variability for the anatomical traits of needles and the possibility of linking the pattern of phenotypic variability with environmental factors. In most of the analyzed needle traits, the statistically significant variability between populations was determined. According to the results of the multivariate principal component analysis, it is evident that the populations are distinct from each other, in three groups. The climatic factors Hargreaves reference evaporation, mean annual temperature, and growing degree-days, were statistically significantly correlated. The altitude and heating degree-days are statistically significantly correlated with the following three environmental factors: Hargreaves reference evaporation, mean annual temperature and growing degree-days, but negatively with others. The paper’s findings indicate significant moderate and high correlations between the anatomical traits of the needles’ central bundle diameter with the resin duct diameter, the distance between the vascular bundle and the resin duct and the epidermis thickness with cuticle, the resin duct diameter with the distance between the vascular bundle and the resin duct and the epidermis thickness with cuticle, as well as the distance between the vascular bundle and the resin duct with the hypodermis height and the epidermis thickness with cuticle. The results of agglomerative hierarchical clustering analysis, performed for anatomical and climatic traits, confirmed the existence of three groups of tested populations according to the altitude gradient. Research results provide knowledge on the diversity and structure of Abies alba populations of Southeast Europe, important for further research and guidelines for the species’ conservation and genetic variability preservation in the southern marginal distribution area and keeping in line with climate change projections.

Hydrogeological trends in an alluvial valley in the Brazilian semiarid: Impacts of observed climate variables change and exploitation on groundwater availability and salinity

Study regionMimoso Alluvial Valley, Semiarid Brazil. Study focusThis study aims to assess the influence of climate variability and exploitation on groundwater accessibility, quantity and quality, based on a spatiotemporal data analysis from long-term monitoring field campaigns, conducted monthly from 2000 to 2019. This study successfully identified representative stable monitoring points, piezometers and wells, for piezometric and salinity levels employing the technique of relative differences, taking into account aquifer hydraulic properties. Trend analysis was then carried out adopting the Mann-Kendall Method, Sen's Slope test, Pettitt test, and the Seasonal Trend decomposition through the Loess (STL) method. Principal Component Multivariate Analysis (PCA) was also employed to validate long-term analysis of annual groundwater levels, rainfall, evapotranspiration, and pumping rates. New hydrological insights for the regionThe spatial-temporal variability of salinity is closely linked to the salt balance in regions with low hydraulic permeability and groundwater use for irrigation. Groundwater salinity presented a strong link between rainfall and groundwater levels. A temporal rise in evapotranspiration alongside declines in rainfall and groundwater levels was observed, potentially exacerbating groundwater scarcity alongside intensified aquifer exploitation. Furthermore, groundwater salinity presented a decreasing trend for the pumping wells and no trends for piezometers. This could potentially disrupt future irrigation plans and cause long-term water shortages in a region already under severe water scarcity. Hence, groundwater pumping constitutes a positive management alternative for controlling groundwater salinity in the domain.

Risk Assessment and Sources Apportionment of Toxic Metals in Two Commonly Consumed Fishes from a Subtropical Estuarine Wetland System.

The widespread occurrence of heavy metals in aquatic environments, resulting in their bioaccumulation within aquatic organisms like fish, presents potential hazards to human health. This study investigates the concentrations of five toxic heavy metals (Pb, Hg, Zn, Cu, and Cr) and their potential health implications in two economically important fish species (Otolithoides pama and Labeo bata) from a subtropical estuarine wetland system (Feni estuary, Bangladesh). Muscle and gill samples from 36 individual fish were analyzed using energy dispersive X-ray fluorescence (EDXRF). The results revealed that the average quantities of heavy metals in both fishes' muscle followed the declining order of Zn (109.41-119.93 mg/kg) > Cu (45.52-65.43 mg/kg) > Hg (1.25-1.39 mg/kg) > Pb (0.68-1.12 mg/kg) > Cr (0.31-5.82 mg/kg). Furthermore, Zn was found to be present in the highest concentration within the gills of both species. While the levels of Cu, Zn, and Cr in the fish muscle were deemed acceptable for human consumption, the concentrations of Pb and Hg exceeded the permissible limits (>0.5 mg/kg) for human consumption. Different risk indices, including estimated daily intake (EDI), target hazard quotient (THQ), hazard index (HI), and carcinogenic or target risk (TR), revealed mixed and varying degrees of potential threat to human health. According to the EDI values, individuals consuming these fish may face health risks as the levels of Zn, Cu, and Cr in the muscle are either very close to or exceed the maximum tolerable daily intake (MTDI) threshold. Nevertheless, the THQ and HI values suggested that both species remained suitable for human consumption, as indicated by THQ (<1) and HI (<1) values. Carcinogenic risk values for Pb, Cr, and Zn all remained within permissible limits, with TR values falling below the range of (10-6 to 10-4), except for Zn, which exceeded it (>10-4). The correlation matrix and multivariate principal component analysis (PCA) findings revealed that Pb and Cr primarily stemmed from natural geological backgrounds, whereas Zn, Cu, and Hg were attributed to human-induced sources such as agricultural chemicals, silver nanoparticles, antimicrobial substances, and metallic plating. Given the significance of fish as a crucial and nutritious element of a balanced diet, it is essential to maintain consistent monitoring and regulation of the levels and origins of heavy metals found within it.

Evaluation Study of Ammonium Removal from Groundwater by Electrodialysis: Case Study of Real Groundwater from the City of Kenitra in Morocco.

In this work, we investigated the feasibility of ammonium removal by electrodialysis (ED), a well-known electro-membrane process, based on the selective migration of anions and cations through anion exchange membranes (AEMs) and cation exchange membranes (CEMs). ED experiments are performed using a laboratory pilot. The ion exchange membranes (IEMs) pair used is AXE/CMX, AXE as an AEMs and CMX as a CEMs. The first tests are performed with real groundwater solutions from Kenitra city (Morocco), spiked with an initial concentration of 3 mg/L NH4Cl. The results gave a specific demineralization (SD) to NH4 + ions of 84.60 %; for a demineralization rate (DR) of 80 % and a time of 60 min. The multivariate principal component analysis (PCA) presents a total inertia of 99.23 %, the majority of the variables of which are positively correlated on the C1 axis with a variance of 95.5 % than that of C2 of 3.78 %. The quality of the diluted water determined by the Legrand-Poirier method showed that the water was aggressive and that the addition of 4.54 mg/L Ca2+ was necessary to balance the water and make it fit for human consumption.

A multisensor approach coupled with multivariate statistics and geostatistics for assessing the status of land degradation: The case of soils contaminated in a former outdoor shooting range

Soil contamination in outdoor shooting ranges (OSRs) is a major threat for human health, particularly when, after the end of activities, the land is used for recreational areas or agricultural production. The status of land degradation of an OSR in southern Italy was assessed using a multisensor approach. It was based on: i) proximal sensors, including electromagnetic induction (EMI) for measuring soil electrical conductivity (ECa) and magnetic susceptibility (MSa), γ-ray spectrometry for K, eU and eTh analyses and ultrasonic penetrometry detecting cone index (CI) data representative of soil's strength, ii) field surveys on soil thickness (ST), and iii) laboratory analyses of potentially-toxic-elements (PTEs) by portable X-ray fluorescence spectrometry and polycyclic aromatic hydrocarbons (PAHs) by gas-chromatography. Spatial variability of measurements was modelled and mapped using geostatistical methods. The most densely measured covariate (i.e., the ECa of the topsoil) was used within kriging with external drift to improve the PTEs predictions. The PTEs maps were complemented by maps of spatial uncertainty. A robust multivariate principal component analysis (rPCA) was applied to proximal sensor and laboratory data and allowed to identify associations of PAHs, lead, CI with the topsoil ECa along the first component (PC1), highlighting the correlation between land anthropogenic effects and EMI measures; while the association between the ST (estimating the depth of underground travertine hard-layers) and the bottom soil ECa and MSa along the second component (PC2) evidenced the influence of soil stratigraphy on the EMI measures. This study demonstrates that the simultaneous use of different proximal sensors associated with laboratory analysis can allow to assess and model the spatial variability of the land degradation status of an OSR, including soil compaction, organic and inorganic contamination. The correlation between EMI data with the PTEs content highlights the potential of this technique in the field of soil contamination.

Evaluation and Selection of Multi-Spectral Indices to Classify Vegetation Using Multivariate Functional Principal Component Analysis

The identification, classification and mapping of different plant communities and habitats is of fundamental importance for defining biodiversity monitoring and conservation strategies. Today, the availability of high temporal, spatial and spectral data from remote sensing platforms provides dense time series over different spectral bands. In the case of supervised mapping, time series based on classical vegetation indices (e.g., NDVI, GNDVI, …) are usually input characteristics, but the selection of the best index or set of indices (which guarantees the best performance) is still based on human experience and is also influenced by the study area. In this work, several different time series, based on Sentinel-2 images, were created exploring new combinations of bands that extend the classic basic formulas as the normalized difference index. Multivariate Functional Principal Component Analysis (MFPCA) was used to contemporarily decompose the multiple time series. The principal multivariate seasonal spectral variations identified (MFPCA scores) were classified by using a Random Forest (RF) model. The MFPCA and RF classifications were nested into a forward selection strategy to identify the proper and minimum set of indices’ (dense) time series that produced the most accurate supervised classification of plant communities and habitat. The results we obtained can be summarized as follows: (i) the selection of the best set of time series is specific to the study area and the habitats involved; (ii) well-known and widely used indices such as the NDVI are not selected as the indices with the best performance; instead, time series based on original indices (in terms of formula or combination of bands) or underused indices (such as those derivable with the visible bands) are selected; (iii) MFPCA efficiently reduces the dimensionality of the data (multiple dense time series) providing ecologically interpretable results representing an important tool for habitat modelling outperforming conventional approaches that consider only discrete time series.

Voice self-assessment in individuals with Parkinson's Disease as compared to general voice disorders

BackgroundIndividuals with Parkinson's Disease (IwPD) often fail to adjust their voice in different situations, without awareness of this limitation. Clinicians use self-report questionnaires that are typically designed for individuals with General Voice Disorders (GVD) in the vocal assessment of IwPD. However, these instruments may not consider that IwPD have a reduced self-perception of their vocal deficits. This study aimed to compare self-reported vocal symptoms and voice loudness between IwPD and GVD. Methods28 IwPD and 26 with GVD completed the Voice Symptom Scale (VoiSS) questionnaire to evaluate their voice self-perception. Vocal loudness (dB) was also assessed. Univariate and multivariate analyses were used to compare the outcomes from these measures between the two groups. Principal Component Analysis and Hierarchical Clustering Analysis were applied to explore data patterns related to voice symptoms. ResultsIwPD reported significantly fewer vocal symptoms than those with GVD in all VoiSS questionnaire domains. Multivariate principal component analysis found no significant correlations between VoiSS scores and participant similarities in voice measures. Despite experiencing hypophonia, IwPD scored lower in all VoiSS domains but still fell in the healthy voice range. Hierarchical Clustering Analysis grouped participants into three distinct categories, primarily based on age, vocal loudness, and VoiSS domain scores, distinguishing between PD and GVD individuals. ConclusionsIwPD reported fewer vocal symptoms than GVD. The voice self-assessment seems to be unreliable to assess vocal symptoms in IwPD, at least regarding loudness. New self-report instruments tailored to PD individuals are needed due to their particular voice characteristics.

Air pollution exposure may impact the composition of human milk oligosaccharides

Human milk oligosaccharides (HMOs) impact neonate immunity and health outcomes. However, the environmental factors influencing HMO composition remain understudied. This study examined the associations between ambient air pollutant (AAP) exposure and HMOs at 1-month postpartum. Human milk samples were collected at 1-month postpartum (n = 185). AAP (PM2.5, PM10, NO2) exposure included the 9-month pregnancy period through 1-month postpartum. Associations between AAP with (1) HMO diversity, (2) the sum of sialylated and fucosylated HMOs, (3) 6 a priori HMOs linked with infant health, and (4) all HMOs were examined using multivariable linear regression and principal component analysis (PCA). Exposure to AAP was associated with lower HMO diversity. PM2.5 and PM10 exposure was positively associated with the HMO 3-fucosyllactose (3FL); PM2.5 exposure was positively associated with the sum of total HMOs, sum of fucosylated HMOs, and the HMO 2′-fucosyllactose (2′FL). PCA indicated the PM2.5, PM10, and NO2 exposures were associated with HMO profiles. Individual models indicated that AAP exposure was associated with five additional HMOs (LNFP I, LNFP II, DFLNT, LNH). This is the first study to demonstrate associations between AAP and breast milk HMOs. Future longitudinal studies will help determine the long-term impact of AAP on human milk composition.

Regio-specific lipid fingerprinting of edible sea cucumbers using LC/MS

Sea cucumbers are a rich source of bioactive compounds and are gaining popularity as nutrient-rich seafood. They are consumed as a whole organism in Pacific regions. However, limited data are available on the comparison of their lipid composition and nutritional value. In this study, untargeted liquid chromatography/mass spectrometry was applied to comprehensively profile lipids in the skin, meat, and intestinal contents of three color-distinct edible sea cucumbers. Multivariate principal component analysis revealed that the lipid composition of the intestinal contents of red, black, and blue sea cucumbers differs from that of skin, and meats. Polyunsaturated fatty acids (PUFAs) are abundant in the intestinal contents, followed by meats of sea cucumber. Lipid nutritional quality assessments based on fatty acid composition revealed a high P:S ratio, low index of atherogenicity, and high health promotion indices for the intestinal contents of red sea cucumber, suggesting its potential health benefits. In addition, hierarchical cluster analysis revealed that the intestinal contents of sea cucumbers were relatively high in PUFA-enriched phospholipids and lysophospholipids. Ceramides are abundant in black skin, blue meat, and red intestinal content samples. Overall, this study provides the first insights into a comprehensive regio-specific profile of the lipid content of sea cucumbers and their potential use as a source of lipid nutrients in food and nutraceuticals.

Characterization and childhood exposure assessment of toxic heavy metals in household dust under true living conditions from 10 China cities

Health hazards caused by metal exposure in household dust are concerning environmental health problems. Exposure to toxic metals in household dust imposes unclear but solid health risks, especially for children. In this multicenter cross-sectional study, a total of 250 household dust samples were collected from ten stratified cities in China (Panjin, Shijiazhuang, Qingdao, Lanzhou, Luoyang, Ningbo, Xi'an, Wuxi, Mianyang, Shenzhen) between April 2018 and March 2019. Questionnaire was conducted to gather information on individuals' living environment and health status in real-life situations. Multivariate logistic regression and principal component analysis were conducted to identify risk factors and determine the sources of metals in household dust. The median concentration of five metals in household dust from 10 cities ranged from 0.03 to 73.18 μg/g. Among the five heavy metals, only chromium in household dust of Mianyang was observed significantly both higher in the cold season and from the downwind households. Mercury, cadmium, and chromium were higher in the third-tier cities, with levels of 0.08, 0.30 and 97.28 μg/g, respectively. There were two sources with a contribution rate of 38.3 % and 25.8 %, respectively. Potential risk factors for increased metal concentration include long residence time, close to the motorway, decoration within five years, and purchase of new furniture within one year. Under both moderate and high exposure scenarios, chromium showed the highest level of exposure with 6.77 × 10−4 and 2.28 × 10−3 mg·kg−1·d−1, and arsenic imposed the highest lifetime carcinogenic risk at 1.67 × 10−4 and 3.17 × 10−4, respectively. The finding highlighted the priority to minimize childhood exposure of arsenic from household dust.

Effects of investment opportunities on firms' financial performance: a fresh look through a dynamic panel approach and multivariate analysis

The aim of this study is to investigate the macroeconomic component Investment Opportunities influence, extracted by the multivariate PCA method, on firms' financial performance. The analysis was conducted in two stages: i) Principal Component Analysis (PCA) to circumvent the multicollinearity problem and identification of the Investment Opportunities variable; and ii) Application of the Systemic Generalized Method of Moments (GMM) both to analyze the relationship between Investment Opportunities and firms' financial performance (measured by current and future ROE), and to correct for data endogeneity. The sample comprises 160 non-financial companies, with quarterly data from 2010 to 2020. We use the PCA method exploratively to identify the first principal component as the predictor variable in the econometric model. It was extracted from macroeconomic variables, which include GDP variation and activity indexes, confidence, and agents’ expectations in Brazilian economy. Finally, we applied the GMM panel data modeling.  The results showed that the Investment Opportunities variable has a positive and significant effect on companies’ financial performance, with persistent effects in future quarters. Furthermore, we demonstrate that financial performance is highly responsive to these opportunities with significant results in all estimated models. This study makes a practical and theoretical contribution by demonstrating, through multivariate analysis, how economic conditions are important exogenous drivers of firm performance and competitive advantage.

Demonstrating the relevance of spatial-functional statistical analysis in marine ecological studies: The case of environmental variations in micronektonic layers

In this study, we conducted an analysis of a multifrequency acoustics dataset acquired from scientific echosounders in the West African water. Our objective was to explore the spatial arrangement of marine organism aggregations. We investigated various attributes of these intricate biological entities, such as thickness, relative density, and depth, in relation to their surroundings. These environmental conditions were represented at a fine scale using a towed multiparameter system. This study is closely intertwined with two key domains: Fisheries acoustics techniques and functional data analysis. Fisheries acoustics techniques facilitate the collection of high-resolution spatial and temporal data concerning marine organisms at various depths and spatial scales, all without causing any disturbance. On the other hand, spatial-functional data analysis is a statistical approach for examining data characterised by functional attributes distributed across a spatial domain. This analysis encompasses dimension reduction techniques, as well as supervised and unsupervised methods, which take into consideration spatial dependencies within extensive datasets.We began by applying multivariate statistical techniques and subsequently employed Functional Data Analysis (FDA). In the modeling section, we introduced the spatial dimension with the spatial coordinates as covariates in the General Additive Model (GAM) and Functional Generalized Spectral Additive Model (FGSAM) models, aiming to underscore its relevance in those contexts. In an exploratory phase, Multivariate Functional Principal Component Analysis provided detailed insights into the variations of parameters at different depths, a capability not offered by traditional Principal Component Analysis. When it came to regression tasks, we explored the interactions between descriptors of Sound Scattering Layers and key environmental variables, both with and without considering spatial dimensions. Our findings revealed significant distinctions between northern and southern Sound Scattering Layers, as well as between coastal and high-sea regions. The use of the spatial locations enhanced the performance of GAM and FGSAM, particularly in the case of salinity, reflecting the influence of water mixing and seawater temperature. The multifaceted effects of environmental variations on Sound Scattering Layers underscore the importance of spatial-functional statistical analysis in ecological studies involving complex, spatially functional objects. Beyond the scope of this specific case study, the application of functional data analysis shows promise for a wide array of ecological studies dealing with extensive spatial datasets.

Dissecting new lipids and their composition in herbal tea using untargeted LC/MS

Herbal teas and beverages have gained global attention because they are rich in natural bioactive compounds, which are known to have diverse biological effects, including antioxidant and anticarcinogenic properties. However, the lipidomic profiles of herbal teas remain unclear. In this study, we applied an untargeted lipidomics approach using high-performance liquid chromatography coupled with linear ion trap-Orbitrap mass spectrometry to comprehensively profile, compare, and identify unknown lipids in four herbal teas: dokudami, kumazasa, sugina, and yomogi. A total of 341 molecular species from five major classes of lipids were identified. Multivariate principal component analysis revealed distinct lipid compositions for each of the herbs. The fatty acid α-linolenic acid (FA 18:3) was found to be abundant in kumazasa, whereas arachidonic acid (FA 20:4) was the most abundant in sugina. Interestingly, novel lipids were discovered for the first time in plants; specifically, short-chain fatty acid esters of hydroxy fatty acids (SFAHFAs) with 4-hydroxy phenyl nonanoic acid as the structural core. This study provides insight into the lipidomic diversity and potential bioactive lipid components of herbal teas, offering a foundation for further research into their health-promoting properties and biological significance.

Interspecific niche overlap and climatic associations of native Quercus species in the Zagros forests of Iran

In the arid regions surrounding southwestern Asia, oak trees play an important role in the environment by conserving water and preserving soil and supporting wildlife. There are concerns for the health and continued productivity of these forests, and there is a widespread oak decline. In this study, ecological niche modeling (ENM) and multivariate principal component analysis (PCA) were used to determine the environmental variations among Quercus brantii, Q. infectoria, and Q. libani in the Zagros forests of western Iran. Based on the area under the curve (AUC > 0.9) and the true skill statistic (TSS > 0.8), three algorithms, including random forest (RF), maximum entropy (MaxEnt), and maximum picking neural net (MAXnet), were used in an ensemble approach to explore the most important environmental variables within the projected suitable habitat of each species. Environmental variables related to climate, including annual precipitation (bio12) and annual mean temperature (bio1), were among the most important drivers of habitat suitability for oak species. The results illustrated that suitable areas for Q. infectoria and Q. libani often occur in the northern parts of the Zagros, which are humid and cooler than the southern areas. The results suggested that Q. brantii has a higher tolerance for harsh conditions in Zagros and therefore inhabits almost all areas of Zagros, including the southern parts. The climatic overlap between pairs of species was found to be significant based on equivalency and similarity tests, suggesting that the environmental conditions of the two species compared are more similar than would be expected by chance. The gap analysis for the three oak species revealed that only a few protected areas currently exist within their suitable habitats, with most of the highly suitable habitats located on non-protected lands, particularly for Q. libani and Q. infectoria. In addition, deforestation is known to sometimes occur within the boundaries of protected areas. Improving the level of protection by upgrading the current protected areas to national parks can help with conservation.

Assessment of the Relationship Between Humic Acid Contents and Trace Elements of Some Agricultural Soils in Diyarbakır Region by Multivariate Statistical Methods

There are important relationships between humic acid (HA) and the bioavailability, reactions and mobility of trace elements in the soil. For this reason, soils are tried to be improved chemically, biologically and physically with HA applications. In this study, the relationship of humic acid contents of 118 agricultural soil samples from Diyarbakır region with some trace elements (Al, As, Ba, Be, Cd, Fe, Mn, Pb, Sb, Sn, Se, V and P) was evaluated by multivariate statistical analysis. After the soil samples were solubilized by the microwave wet digestion method, the element contents were determined with the ICP OES (Inductively Coupled Plasma Optical Emission Spectrometer) device. SRM NIST 2586 was used as SRM (Standard Reference Material) for the accuracy of the method. Recovery values were found between 91.6% and 105.9% as a result of the analysis. Humic acid was extracted from soils by the International Society for Humic Substances (IHSS) method and determined using a shaker and centrifuge device. For the accuracy of the method, it was tested with Humic Acid Sodium Salt (HA-Na). Pearson correlation and partial correlation analysis were applied to the obtained data set. In addition, multivariate statistical analyses such as multiple regression HCA (Hierarchical Cluster Analysis) and PCA (Principal Component Analysis) were applied. Multiple regression analysis was performed according to the Step-wise method. Manganese and P (p&lt; 0.01) were significant when HA was taken as the dependent variable. According to the Pearson correlation coefficient, the correlation between HA and As (r = -0.282**) in soil was negative and significant, while Fe (r = 0.185*), Mn (r = 0.273**)), Sn (r = 0.242*), Se (r = 0.325**) and P (r = 0.315**) were determined as positive and significant. In clustering and PCA analysis, HA, P Mn and Fe were found to be in the same group. The analyses have shown that HA has a positive effect on the plant nutrients in the soil.

Projection-based two-sample inference for sparsely observed multivariate functional data.

Modern longitudinal studies collect multiple outcomes as the primary endpoints to understand the complex dynamics of the diseases. Oftentimes, especially in clinical trials, the joint variation among the multidimensional responses plays a significant role in assessing the differential characteristics between two or more groups, rather than drawing inferences based on a single outcome. We develop a projection-based two-sample significance test to identify the population-level difference between the multivariate profiles observed under a sparse longitudinal design. The methodology is built upon widely adopted multivariate functional principal component analysis to reduce the dimension of the infinite-dimensional multi-modal functions while preserving the dynamic correlation between the components. The test applies to a wide class of (non-stationary) covariance structures of the response, and it detects a significant group difference based on a single p-value, thereby overcoming the issue of adjusting for multiple p-values that arise due to comparing the means in each of components separately. Finite-sample numerical studies demonstrate that the test maintains the type-I error, and is powerful to detect significant group differences, compared to the state-of-the-art testing procedures. The test is carried out on two significant longitudinal studies for Alzheimer's disease and Parkinson's disease (PD) patients, namely, TOMMORROW study of individuals at high risk of mild cognitive impairment to detect differences in the cognitive test scores between the pioglitazone and the placebo groups, and Azillect study to assess the efficacy of rasagiline as a potential treatment to slow down the progression of PD.

Analysis of backyard agriculture and livestock production activities in the South Huasteca Region in San Luis Potosí, Mexico

Objective: To carry out a diagnosis and assess the importance of backyard agriculture and livestock production in rural communities of the XV District in the South Huasteca Region of the State of San Luis Potosí, Mexico, on the social, economic and nutritional context of the population. Design/Methodology/Approach: The study was carried out with two blocks of surveys, the first with the local government and the second with peasants, evaluating the socioeconomic status, importance of livestock and agriculture, nutritional status and culture. The method was deductive and descriptive; the information was with multivariate analysis of principal components. Results: Government support does not reduce poverty. Families feel secure with their material goods. The nutritional status of the population is lacking. Raising chickens, turkeys and Creole pigs prioritizes livestock activity. Self-consumption and the commercialization of plant species is a traditional activity. There is a culinary culture. Limitations on study/Implications: The restriction of information by the municipal government; the pandemic problems to generate more information from the surveys. Conclusions: It is necessary to create efficient programs that improve agricultural and livestock production in the region, with the purpose of improving the nutritional status of the population and generating economic resources to reduce poverty.

Multivariate techniques for analyzing morphological characteristics of cactus pear genotypes in semiarid Brazil

The objective of this study was to identify variables with better discriminatory power between treatments and reduce the dimensions of the original data set. Multivariate principal component analysis (PCA) and dendrogram clustering techniques were used on a data set of morphological characteristics of cactus pear genotypes. The palm genotypes of the genera Nopalea and Opuntia were arranged in a completely randomized design, with 30 treatments and six replications. After 180 days of cultivation, morphological characteristics were evaluated, including plant height (PH) and width (PW), total number of plant cladodes (NCP), length (CL), width (CW), perimeter (CP), cladode thickness (CT), cladode area (CA), active photosynthetic area (APA) and cladode area index (CAI). Varimax rotation with Kaiser normalization was used to prevent variables with greater explanatory capacity from affecting the rotation. Measurements were obtained as part of cluster model generation, using a full set of morphological variables for subsequent analysis of principal component and cluster analyses. The main components obtained were efficient in reducing the total variation accumulated in 30 original variables correlated to two linear combinations, which explained 81.04% of the total variation present in the original variables. Grouping using the Ward hierarchical method formed 3 groups, namely, group I consisted of genotypes F27, F48, G1, G14, G15, G20, G3, PC2, PCD, PM, T72, V07 and V20; group II was composed of the genotypes BA, F16, F34, G4, G5, OEA, OEM, POEA, T35, T80 and V19 and; group III was composed of genotypes F24, PC1, PC3, PC4, PC5 and V17. PCA demonstrated that APA, CAI, CA, NCP, PH, PW and CT are morphological variables that determine the best palm characteristics. The association of cactus morphological variables varied according to the genotypes, within each genus Nopalea and Opuntia. The genotypes with the best morphological characteristics were F27, F48, G1, G14, G15, G20, G3, PC2, PCD, PM, T72, V07 and V20.

Characterization and evaluation of the morphological attributes of Ethiopian mustard (Brassica carinata A. Braun) landraces

Ethiopian mustard (Brassica carinata A. Braun) is one of the Brassica leafy vegetables and oilseed crops, which can withstand adverse environmental conditions. This study was conducted to characterize and evaluate the leaf attributes of 313 Ethiopian mustard accessions grown in the greenhouse and field in 2018/19 in Beijing, China. Data on 18 different leaf morphological attributes were collected based on the IBPGR for Brassica and Raphanus descriptor format and Fiji Image J. The collected data were subjected to descriptive statistics using JMP version 14 software. Results indicate that the majority of the accessions had serrated leaf margin, intermediate juvenile development, rounded apex leaf shape, absence of leaf pubescence, number of lobes > 5 and had intermediate number of leaves per plant with frequencies of 101, 213, 223, 244, 183 and 289, respectively. The accessions had also white midrib color, light green leaf color, purple petiole color, purple stem color and purple apex leaf color pigments with frequencies of 168, 165, 104, 113 and 122, respectively. Significant differences were observed among the accessions for leaf size attributes (p < 0.001) indicating their potential as leafy vegetables. Furthermore, there were significant accession × environment effects for the laminal length, total leaf length, leaf area, leaf weight and petiole length. Notably, 71% of the accessions had an average of 81 days flowering time. The multivariate cluster and principal component analyses divided the 313 accessions into eight groups with distinctive information; consisting of 81, 37, 79, 38, 14, 11, 6 and 47 accessions. Thus, this study provides important information about Ethiopian mustard germplasms that is vital for further advancement and genetic improvement of the crop.

Orthopaedic Personal Statement Thematic Review: Does Topic Matter?

In the process of applying into medical residency, the Electronic Residency Application Service (ERAS) requires critical documents including a personal statement. Utility of personal statements are questioned based on suspected congruity of the content within personal statements among those who apply into orthopaedic surgery. The goal of this study was to identify and categorize the thematic elements found within the 2021 to 2022 personal statements of orthopaedic surgery applicants at a single institution and assess a correlation to interview invitation. Deidentified personal statements among 2021 to 2022 ERAS applicants were reviewed by the research staff and categorized into one of the proposed themes. Three hundred ninty-four applications passed initial screening filters, and 49 applicants were granted an interview. Proposed themes that were collected included: family of physician, working with hands, history of injury/disease, prior professional setting, immigration/travel, athlete/sports, reapplication, previous clinical experience, and other. χ2 test was used to analyze categorical themes and additional univariate group-to-group comparisons. Multivariate principal component analysis was performed to determine which themes were associated with interview invitation. There was a significant difference in theme selection for an applicant's personal statement (χ2 = 209.5, p < 0.001), but no statistical difference was observed between each individual categorical themes and interview selection. Univariate group-to-group comparison demonstrated greater interview rates between immigration/travel compared with reapplicant and family of physician compared with working with hands. Multivariate principal component analysis demonstrated immigration/travel as the theme with a positive correlation toward an interview invitation. Despite a significant focus of the application process into orthopaedic surgery residencies, our single-institution study did observe specific themes that were more prevalent. There was an increased interview rate between applicant's themes for immigration/travel and family of physician when comparing groups. Immigration/travel was also identified as the only significant theme associated with interview invitation which may be due to the recent emphasis on promoting diversity within orthopaedic surgery.