Multivariate Discriminant Analysis Research Articles

Blood T-cell profiling in metastatic melanoma patients as a marker for response to immune checkpoint inhibitors combined with radiotherapy

BackgroundThe addition of stereotactic ablative radiotherapy (SABR) to immune checkpoint inhibitors (ICIs) has the potential to significantly improve outcomes in the treatment of metastatic melanoma. We analysed peripheral blood immune cells of patients receiving combination SABR and ICI to detect the effect of treatment and identify potential biomarkers that predict outcome. Methods24 polymetastatic melanoma patients participated in the SABR IMPACT trial, receiving standard dose immunotherapy with anti-PD-1 and/or anti-CTLA-4 and stereotactic ablative radiotherapy to one site. Comprehensive immunophenotyping of T-cells was performed with flow cytometry on blood samples from 13 patients at baseline and following the first 4 cycles of treatment. ResultsFollowing four cycles of immunotherapy and SABR, the proportion of naïve subsets were reduced within both the CD4 and CD8 T-cell lineages. Independently, SABR resulted in increased expression of PD-1 (p = 0.019) and ICOS (p = 0.046) on the CD8+ T-cells, accompanied by a reduction in regulatory T-cell frequencies (p = 0.048). A multivariate discriminant analysis revealed a baseline signature of lower levels of CD8+ naive T-cells and higher expression of TIM-3 on regulatory T-cells and memory T-cells better predicted response. ConclusionThe combination of immunotherapy and SABR changed the immunophenotype of blood T cells, with some shifts attributable to SABR. Importantly, we identified a T-cell signature at baseline that best predicted response. Validation of these findings in an independent cohort could confirm these as biomarkers at baseline or early during treatment, and whether these can be utilised to stratify patients for high or low intensity treatment to reduce toxicity.

Groundwater contamination in public water supply wells: risk assessment, evaluation of trends and impact of rainfall on groundwater quality

This study investigates the risk to contamination of groundwater in public water supply wells in the Koprivnica-Križevci county (northwest Croatia). Five physicochemical parameters were monitored in all groundwater samples from 2008 to 2017 to identify major differences between the wells, assess temporal variations and understand the capacity for rainfall to alter groundwater pollution loadings. Multivariate discriminant analysis showed statistically significant differences between the six sampled wells based on the analyzed parameters (Wilks' lambda: 0.001; F = 26.2; p < 0.0000). Principal component analysis revealed two significant factors, including factor 1 which explained 32.8% of the variance (suggesting that the quality of the groundwater was mainly controlled by nitrate) and factor 2, accounting for 16.2% of the total variance (which corresponded to KMnO4/oxidizability and to a lesser extent, pH). The time series data showed disparate trends, with nitrate concentrations increasing, whereas pH and KMnO4 decreased, while electrical conductivity and chloride levels remained stable. Although rainfall can impact groundwater pollution loadings through dilution processes in aquifers, the resulting fluctuations in physicochemical parameters are complicated by variations in rainfall events and local topography, as well as from climate change. Therefore, it is important to predict the contamination of groundwater quality in the future using machine learning algorithms using artificial neural network or similar methods. Multivariate statistical techniques are useful in verifying temporal and spatial variations caused by anthropogenic factors and natural processes linked to rainfall. The resulting identified risks to groundwater quality would provide the basis for further groundwater protection, particularly for decisions regarding permitted land use in recharge zones.

Mapping Gully Erosion Variability and Susceptibility Using Remote Sensing, Multivariate Statistical Analysis, and Machine Learning in South Mato Grosso, Brazil

In Brazil, the development of gullies constitutes widespread land degradation, especially in the state of South Mato Grosso, where fighting against this degradation has become a priority for policy makers. However, the environmental and anthropogenic factors that promote gully development are multiple, interact, and present a complexity that can vary by locality, making their prediction difficult. In this framework, a database was constructed for the Rio Ivinhema basin in the southern part of the state, including 400 georeferenced gullies and 13 geo-environmental descriptors. Multivariate statistical analysis was performed using principal component analysis (PCA) to identify the processes controlling the variability in gully development. Susceptibility maps were created through four machine learning models: multivariate discriminant analysis (MDA), logistic regression (LR), classification and regression tree (CART), and random forest (RF). The predictive performance of the models was analyzed by five evaluation indices: accuracy (ACC), sensitivity (SST), specificity (SPF), precision (PRC), and Receiver Operating Characteristic curve (ROC curve). The results show the existence of two major processes controlling gully erosion. The first is the surface runoff process, which is related to conditions of slightly higher relief and higher rainfall. The second also reflects high surface runoff conditions, but rather related to high drainage density and downslope, close to the river network. Human activity represented by peri-urban areas, construction of small earthen dams, and extensive rotational farming contribute significantly to gully formation. The four machine learning models yielded fairly similar results and validated susceptibility maps (ROC curve &gt; 0.8). However, we noted a better performance of the random forest (RF) model (86% and 89.8% for training and test, respectively, with an ROC curve value of 0.931). The evaluation of the contribution of the parameters shows that susceptibility to gully erosion is not governed primarily by a single factor, but rather by the interconnection between different factors, mainly elevation, geology, precipitation, and land use.

P-3 Gastric cancer prognosis and cell ratio factors

We examined cell ratio factors (CRF) significantly affecting gastric cancer (EC) patients GCP) survival. CRF - ratio between cancer cells (CC) and blood cells subpopulations. We analyzed data of 799 consecutive GCP (T1-4N0-2M0) (age=57.1±9.4 years; tumor size=5.4±3.1 cm) radically operated (R0) and monitored in 1975-2022 (m=558, f=241; total gastrectomies=173, distal gastrectomies=461; proximal gastrectomies=165; combined gastrectomies=247 with resection of esophagus, pancreas, liver, duodenum, diaphragm, colon transversum, splenectomy, etc; only surgery-S=624, adjuvant chemoimmunotherapy-AT=175 (5-FU + thymalin/taktivin); T1=238, T2=220, T3=184, T4=157; N0=437, N1=109, N2=253, M0=799; G1=222, G2=164, G3=413. Variables selected for prognosis study were input levels of 45 blood parameters, sex, age, TNMG, cell type, tumor size. Survival curves were estimated by the Kaplan-Meier method. Differences in curves between groups of GCP were evaluated using a log-rank test. Multivariate Cox modeling, discriminant analysis, clustering, SEPATH, Monte Carlo, bootstrap and neural networks computing were used to determine any significant dependence. Overall life span (LS) was 2128.9±2300.3 days and cumulative 5-year survival (5YS) reached 58.4%, 10 years – 51.9%, 20 years – 39%, 30 years – 27.2%. 318 GCP lived more than 5 years (LS=4304.5±2290.6 days), 169 ECP – more than 10 years (LS=5919.5±2020 days). 290 GCP died because of GC (LS=651±347.2 days). Cox modeling displayed that ECP survival significantly depended on CRF: healthy cells/CC, erythrocytes/CC, monocytes/CC, phase transition (PT) in terms of synergetics early-invasive cancer; PT N0--N12, age, G1-3, hemorrhage time, ESS, sex, AT, prothrombin index, residual nitrogen. Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive cancer (rank=1); PT N0--N12 (2); healthy cells/CC (3), erythrocytes/CC (4), thrombocytes/CC (5), monocytes/CC (6), segmented neutrophils/CC (7), leucocytes/CC (8), lymphocytes/CC (9), stick neutrophils/CC (10), eosinophils/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0). GCP survival after radical procedures significantly depended on CRF.

A multivariate regression and discriminant canonical analysis of Isometric Mid-Thigh Pull performance in cadet inline speed skaters

A multivariate regression and discriminant canonical analysis of Isometric Mid-Thigh Pull performance in cadet inline speed skaters

Advanced machine learning algorithms for flood susceptibility modeling - performance comparison: Red Sea, Egypt.

Floods are among the most devastating environmental hazards that directly and indirectly affect people's lives and activities. In many countries, sustainable environmental management requires the assessment of floods and the likely flood-prone areas to avoid potential hazards. In this study, the performance and capabilities of seven machine learning algorithms (MLAs) for flood susceptibility mapping were tested, evaluated, and compared. These MLAs, including support vector machine (SVM), random forest (RF), multivariate adaptive regression spline (MARS), boosted regression tree (BRT), functional data analysis (FDA), general linear model (GLM), and multivariate discriminant analysis (MDA), were tested for the area between Safaga and Ras Gharib cities, Red Sea, Egypt. A geospatial database was developed with eleven flood-related factors, namely altitude, slope aspect, lithology, land use/land cover (LULC), slope length (LS), topographic wetness index (TWI), slope angle, profile curvature, plan curvature, stream power index (SPI), and hydrolithology units. In addition, 420 actual flooded areas were recorded from the study area to create a flood inventory map. The inventory data were randomly divided into training group with 70% and validation group with 30%. The flood-related factors were tested with a multicollinearity test, the variance inflation factor (VIF) was less than 2.135, the tolerance (TOL) was more than 0.468, and their importance was evaluated with a partial least squares (PLS) method. The results show that RF performed the best with the highest AUC (area under curve) value of 0.813, followed by GLM with 0.802, MARS with 0.801, BRT with 0.777, MDA with 0.768%, FDA with 0.763, and SVM with 0.733. The results of this study and the flood susceptibility maps could be useful for environmental mitigation, future development activities in the area, and flood control areas.

Socio-Economic and Cultural Context in the Development of Early Mathematical Competencies: A Comparative Study of Specific Educational Contexts in Chile and Spain.

This research presents the findings of a comparative study of mathematical competence among 130 students (M = 54.08months; SD = 2.57) from vulnerable school contexts in Chile and the Spanish public school system. The study analyses a set of general and specific domain precursors for which evidence of socioeconomic background exists. Using multivariate regression and discriminant analysis techniques, we calculated similarities and differences between groups by comparing these precursors. Significant differences were found between the Spanish and Chilean groups (p < .05); however, no differences were observed in non-symbolic comparison and receptive vocabulary. Possible reasons for the existence and extent of these differences are discussed in terms of socio-cultural and educational contexts.

Determination of Terpenes in Traditional Chinese Medicine (TCM) by Comprehensive Two-Dimensional Gas Chromatography – Mass Spectrometry (GC × GC) Coupled to High-Resolution Quadrupole Time-of-Flight Mass Spectrometry (QTOFMS) with Orthogonal Partial Least Squares – Discrimination Analysis (OPLS-DA)

With a variety of pharmacological effects, the genus Elsholtzia and Mosla of Lamiaceae contain volatile components, including monoterpenes, sesquiterpenes, and their oxygenated derivatives that are widely used in traditional Chinese medicine (TCM). In this work, the volatile terpenes were studied by a more efficient technique based on headspace solid-phase micro-extraction (HS-SPME) combined with comprehensive two-dimensional gas chromatography and quadrupole time-of-flight mass spectrometry (GC × GC-QTOFMS). A total of 91 terpenes consisting of 7 monoterpenes, 34 monoterpene oxides, 39 sesquiterpenes, and 11 sesquiterpene oxides were identified. From the retention time, 4,8,8-trimethyl-2-methylene-4-vinylbicyclo[5.2.0] nonane was identified to be the dominant volatile component in E. blanda, M. chinensis for the first time with 8% prevalence, but further verification is needed. 10 volatile terpenes, including 2-isopropyl-5-methyl-3- cyclohexen-1-one, isoegomaketone, α-muurolene, linalool oxide, ethyl2-(5-methyl- 5-vinyltetrahydrofuran-2-yl)propan-2-ylcarbonate, perilla ketone, elsholtzia ketone, alloaromadendrene oxide, artemisia ketone, longifolene-(V4) were identified by multivariate orthogonal partial least-squares discrimination analysis (OPLS-DA). Because these terpenes have significant pharmacological effects, such as anti-anxiety, anti-oxidation, anti-bacteria, and anti-virus properties, the identification of these terpenes may result in new information related to their pharmacological activities.

Organic hempseed oil from the retail market: chemical profiling and multivariate analysis for label information assessment

PurposeHempseed oil is a valuable emerging food product with recognized health positivity due to its composition. The paper aims to propose a multi-methodological chemical profiling of nine organic hempseed oil samples (different brands and prices) from the retail market, followed by multivariate data analysis.Design/methodology/approachFatty acids, tocopherols, squalene, total carotenoids content, phenolic compounds, total phenolic content and anti-radical activity (DPPH• and ABTS•+ assays) were determined through chromatographic and spectrophotometric techniques. Multivariate (explorative and discriminant) analyses were applied to the profiling results to classify samples according to information claimed on the label, i.e. geographical origin (EU vs. non-EU), extraction procedure (cold-pressed vs. not cold-pressed) and price (lower or higher than 10 € per 250 mL).FindingsThe chemical analysis confirmed the 3 to 1 ?-6:?-3 ratio and the excellent content in antioxidant species. However, no specific trend of results can be stressed. PCA (after variables selection) highlighted a natural grouping of samples, so three discriminant analyses were performed: kNN, Naïve Bayes and LDA. The best classification efficiency was reached for the extraction procedure verification (93–100% correct classification), followed by geographical origin (83–94%) and prices (81.6–90%).Originality/valueThe integrated approach of chemical profiling coupled with multivariate analyses allowed the assessment of label information of the analyzed organic hempseed oil samples, despite the wide heterogeneity of the selected samples.

Determination of the Carbohydrate Profile and Invertase Activity of Adulterated Honeys after Bee Feeding

The higher demand for honey from consumers, combined with its limited availability, has led to different types of honey adulteration, causing substantial economic as well as negative impacts on consumers’ nutrition and health. Therefore, a need has emerged for reliable and cost-effective quality control methods to detect honey adulteration to ensure both the safety and quality of honey. To simulate the process with those applied by beekeepers in real-time, bee colonies were fed with different types of bee feeding (sugar syrup, candy paste and commercial syrup). The produced samples were analyzed for their carbohydrate profile and their invertase activity with the aim to find the effects of bee feeding on the quality of the final product. Honey samples produced after feeding with commercial syrup presented low fructose (22.9 %) and glucose (31.7 %) concentrations and high content of maltose (20.1%), while the samples that came from bee feeding with sugar syrup and candy paste had high concentrations of sucrose (6.2 % and 3.2 %, respectively), exceeding in some cases the legislative limits. Moreover, the samples coming from sugar feeding had lower values of invertase activity, while the group with inverted syrup was clearly discriminated through multi-discriminant analysis. The invertase activity of control samples was found at 153.7 U/kg, which was significantly higher compared to the other groups. The results showed that bee feeding during honey production might lead to adulteration, which can be detected through routine analyses, including the carbohydrate profile and the invertase activity.

Profile of circulating extracellular vesicles microRNA correlates with the disease activity in granulomatosis with polyangiitis.

Granulomatosis with polyangiitis is a chronic systemic inflammation of small vessels characterized by circulating anti-proteinase 3 antibodies. MicroRNAs are short transcripts specifically inhibiting protein translation. Neutrophils can release extracellular vesicles (EVs). In this study, we characterized profile of microRNA trafficked by EVs in GPA. Fifty patients with GPA were enrolled in the study, 25 at acute phase and 25 in remission. EVs were isolated from the blood serum, characterized by their number, size distribution. Following unbiased screening for microRNA expression, differentially expressed candidates were measured by quantitative real-time PCR. Circulating DNA-myeloperoxidase complexes and apoptosis-related transcripts in peripheral blood neutrophils were quantified. We identified four differentially expressed microRNAs from EVs in granulomatosis with polyangiitis (GPA). MirRs-223-3p, 664a-3p, and 200b-3p were overexpressed and miR-769-5p suppressed in the disease. A distinction between GPA and healthy controls was the best for miR-223-3p, whereas miR-664a-3p discriminated between active vs. remission of GPA. Correct classification of the disease based on multivariate discriminant analysis was between 92% for acute phase and 85% for all study participants. Bioinformatics tools identified genes transcripts potentially targeted by the microRNAs belonging to pathways of focal adhesion, mTOR signaling and neutrophil extracellular traps formation. Two microRNAs positively correlating with the disease activity were involved in neutrophil extracellular traps formation and apoptosis inhibition. A comprehensive characteristics of microRNAs trafficked in bloodstream inside EVs correlates well with our understanding of the mechanisms of GPA and suggests the importance of EVs in progression of the disease.

Low genetic variation of foliar traits among Prosopis chilensis (Leguminosae) provenances.

Prosopis chilensis (Molina) Stuntz (Leguminosae) is a valuable native species in Argentina that has been proposed to be used in reforestation, afforestation and restoration programmes. Natural provenances show important differentiation in height, shape, spine size, fruits and foliar traits throughout their distribution in the semiarid Monte ecoregion. The goal of this work was to characterize the genetic basis of the leaf variation in P. chilensis aiming to contribute to the improvement management program. We analyzed morphological variation and estimate narrow sense heritability for ten quantitative traits from a provenance-progeny trial founded from open pollinated families. We assessed the variance components by a generalized linear mixed model. Differences among provenances were quantified through univariate QST statistics and multivariate discriminant analysis of principal components. Finally, univariate and multivariate neutrality test were conducted to unveil the evolutionary forces that shape the variation. Univariate and multivariate analysis showed low genetic variation in foliar traits among provenances grown in the common garden. Consistently, the QST estimates for each trait were low. Both, the univariate (QST-FST comparison) and the multivariate neutrality test suggest that the leaf variation among provenances may be shaped by genetic drift rather than selective forces. Heritability estimates were significant only for leaflet apex and leaflet apex/leaflet area. Since genetic variation for most foliar traits among provenances estimated under controlled environmental conditions were very low or absent, the variation described in the wild would be explained merely by plastic response to varying environments. These results are discussed in terms of adaptive strategies and the use of different provenances as seed sources within the framework of the improvement program. It is expected that P. chilensis seeds or seedlings from trees selected under economical criteria will be able to develop in different areas thanks to the phenotypic plasticity of leaf traits.

Multivariate modeling application to determine the behavior of picloram in soils: a laboratory trial

ABSTRACT Knowledge about herbicide-soil interactions is essential for the safe use of these products. The objective of this study was to evaluate the potential of multivariate discriminant analysis to predict the picloram sorption and desorption capacity of soils and to determine soil groups based on the risk of environmental contamination. Physicochemical properties of 17 soils were subjected to principal component analysis (PCA). Thereafter, the soils were grouped by cluster analysis (CA). Discriminant analysis (DA) was used to determine the efficiency of the clusters. The CA generated three groups of soils, and the coefficients of sorption (Kfs) and desorption (Kfd) were 2.85 and 4.29 for G1, 0.93 and 11.71 for G2, and for G3, 0.36 and 30.76 mg1−1/n L1/n kg−1, respectively. The similarity of soil physicochemical properties in each group resulted in similar picloram sorption and desorption coefficients. Clay, organic matter, pH, and sum of bases showed the greatest influence on the sorption and desorption of picloram. Grouping soils by PCA and CA based on soil physicochemical properties is an alternative approach to determine the risk of environmental contamination by picloram in agricultural areas.

Autonomic Measures in Differentiating Depressive Disorders: A Potential AID.

ObjectiveThe present study aimed at exploring the potential utility of autonomic regulation as a useful marker in the diagnostic differentiation between unipolar and bipolar depression.MethodRespiratory sinus arrhythmia (RSA), low-frequency (LF) of heart rate variability, and systolic blood pressure (SBP) were assessed in patients with bipolar depression (31) and major depressive disorder (MDD=32), and in healthy controls (HCs=32). Since bipolar depressed subjects were maintained on specific medications to manage manic/hypomanic symptoms, we explored whether mood stabilizers (atypical antipsychotics and anticonvulsants or their combinations) could independently affect the physiological parameters.ResultsWhen the autonomic measures were analyzed by a multivariate analysis of variance (MANCOVA), after controlling for BMI, the combination of variables (RSA, LF, SBP) discriminated patients with bipolar depression and MDD from HC (F(6, 178)=3.036, p=0.007, Λ=0.823, partial η2=0.093). In any case, we cannot exclude that mood stabilizers might have affected SBP values in the bipolar group. To deconstruct this multivariate effect, pairwise ANOVAs and discriminant analyses contrasted groups and documented that RSA was the primary variable distinguishing the groups. Discriminant function analyses showed that RSA had a significant discriminating weight between bipolar depressed patients and HC subjects (p<0.0005). By contrast, RSA showed a trend towards the statistical significance in discriminating between bipolar depression and MDD patients (p=0.06).ConclusionsThe assessment of RSA and SBP in outpatient settings might be helpful in the differential diagnosis of affective disorders.

Long-Term Follow-Up of Newborns with 22q11 Deletion Syndrome and Low TRECs

BackgroundPopulation-based neonatal screening using T-cell receptor excision circles (TRECs) identifies infants with profound T lymphopenia, as seen in cases of severe combined immunodeficiency, and in a subgroup of infants with 22q11 deletion syndrome (22q11DS).PurposeTo investigate the long-term prognostic value of low levels of TRECs in newborns with 22q11DS.MethodsSubjects with 22q11DS and low TRECs at birth (22q11Low, N=10), matched subjects with 22q11DS and normal TRECs (22q11Normal, N=10), and matched healthy controls (HC, N=10) were identified. At follow-up (median age 16 years), clinical and immunological characterizations, covering lymphocyte subsets, immunoglobulins, TRECs, T-cell receptor repertoires, and relative telomere length (RTL) measurements were performed.ResultsAt follow-up, the 22q11Low group had lower numbers of naïve T-helper cells, naïve T-regulatory cells, naïve cytotoxic T cells, and persistently lower TRECs compared to healthy controls. Receptor repertoires showed skewed V-gene usage for naïve T-helper cells, whereas for naïve cytotoxic T cells, shorter RTL and a trend towards higher clonality were found. Multivariate discriminant analysis revealed a clear distinction between the three groups and a skewing towards Th17 differentiation of T-helper cells, particularly in the 22q11Low individuals. Perturbations of B-cell subsets were found in both the 22q11Low and 22q11Normal group compared to the HC group, with larger proportions of naïve B cells and lower levels of memory B cells, including switched memory B cells.ConclusionsThis long-term follow-up study shows that 22q11Low individuals have persistent immunologic aberrations and increased risk for immune dysregulation, indicating the necessity of lifelong monitoring.Clinical ImplicationsThis study elucidates the natural history of childhood immune function in newborns with 22q11DS and low TRECs, which may facilitate the development of programs for long-term monitoring and therapeutic choices.

Metabolomics of Synovial Fluid and Infrapatellar Fat Pad in Patients with Osteoarthritis or Rheumatoid Arthritis

Osteoarthritis (OA) and autoimmune-driven rheumatoid arthritis (RA) are inflammatory joint diseases with complex and insufficiently understood pathogeneses. Our objective was to characterize the metabolic fingerprints of synovial fluid (SF) and its adjacent infrapatellar fat pad (IFP) obtained during the same surgical operation from OA and RA knees. Non-targeted metabolite profiling was performed for 5 non-inflammatory trauma controls, 10 primary OA (pOA) patients, and 10 seropositive RA patients with high-resolution mass spectrometry-based techniques, and metabolites were matched with known metabolite identities. Groupwise differences in metabolic features were analyzed with the univariate Welch’s t-test and the multivariate linear discriminant analysis (LDA) and principal component analysis (PCA). Significant discrimination of metabolite profiles was discovered by LDA for both SF and IFP and by PCA for SF based on diagnosis. In addition to a few drug-derived substances, there were 16 and 13 identified metabolites with significant differences between the diagnoses in SF and IFP, respectively. The pathways downregulated in RA included androgen, bile acid, amino acid, and histamine metabolism, and those upregulated included biotin metabolism in pOA and purine metabolism in RA and pOA. The RA-induced downregulation of androgen and bile acid metabolism was observed for both SF and IFP. The levels of 11 lipid metabolites, mostly glycerophospholipids and fatty acid amides, were also altered by these inflammatory conditions. The identified metabolic pathways could be utilized in the future to deepen our understanding of the pathogeneses of OA and RA and to develop not only biomarkers for their early diagnosis but also therapeutic targets.

AN INTEGRATED APPROACH TO THE MORPHOLOGICAL DIAGNOSIS OF DIFFERENT TYPES OF PLEOMORPHIC ADENOMAS OF THE SALIVARY GLAND: LONG-TERM RESEARCH RESULTS.

The aim: To describe an integrated approach to the morphological diagnosis of different types of pleomorphic adenomas of the salivary gland. Materials and methods: Surgical and biopsy material from 30 patients with pleomorphic adenomas of epithelial, mixed and mesenchymal variants was studied using histological, immunohistochemical, genetic, morphometric and statistical methods. Results: The results of research allowed us to identify methods for determination the pleomorphic adenomas types. The first method requires an immunohistochemical reaction with a monoclonal antibody to human papillomavirus type 16, followed by counting the percentage of positively stained cells in the tumor. Thus, the mesenchymal variant of the tumor is diagnosed when the percentage of positively stained cells is < 40%. In the mixed variant, this indicator is ≥ 40%, but ≤ 70%, and in epithelial variant - > 70%. The second method was based on the multivariate discriminant analysis. Three formulae were derived to determine the tumor types (Fmesenchymal = - 41.03 + 4.96Х1 + 1.11Х2, Fepithelial = - 22.27 + 3.46Х1 + 0.85Х2, Fmixed = - 122.25 + 5.63Х1 + 3.2Х2, here Х1 - number of vessels, Х2 - specific volume of parenchyma). Conclusions: The authors identified several methods for determining the histological variants of pleomorphic adenomas. These methods will improve the morphological diagnosis of pleomorphic adenomas variants in the preoperative and postoperative periods.

Rastreability of bovine meat and bone meal using the stable isotope technique in egg production

The present study aimed to verify whether the inclusion of other ingredients in the diet of laying hens could interfere with the traceability of bovine meat and bone meal (BMBM) in eggs through stable carbon and nitrogen isotope analysis. Two hundred and fifty-six white laying hens were used and randomly distributed into eight treatments composed of: CONTROL: control diet; GLUTEN: control diet + corn gluten; YEAST: control diet + yeast; GLUTEN + YEAST: control diet + corn gluten + yeast; BMBM: control diet + 4.5 % BMBM; BMBM + GLUTEN: control diet + corn gluten + 4.5 % BMBM; BMBM + YEAST: control diet + yeast + 4.5 % BMBM; BMBM + GLUTEN + YEAST: control diet + corn gluten + yeast + 4.5 % BMBM. The isotopic results were subjected to multivariate analysis of variance (MANOVA) and LDA multivariate linear discriminant analysis. At 28 days, the eggs of the birds given diets without the addition of BMBM differed from the CONTROL group. The yolks showed that all treatments were significantly different from the CONTROL, and at 56 days, all eggs and egg yolks were different from the CONTROL. At 28 days, albumen was significantly different for all CONTROL experimental treatments; however, at 56 days, the YEAST treatment showed no difference from the control. Thus, it was concluded that even with the addition of other ingredients, the isotope technique is still able to detect the BMBM in eggs.

The impact of board of directors’ characteristics on financial distress: Empirical evidence from Egypt using logit and discriminant analysis models.

Purpose: This paper aims at investigating financial distress and explore the nature of the relationship between board of director’s characteristics and financial distress in the Egyptian economy from 2015-2018. Design /methodology / approach: To determine the best suitable model to express data, two models were employed in this research. The first model is multivariate discriminant analysis model introduced by Altman and Hotchkiss (2010) and logit model. Findings: Our results suggest that the proportion of independent directors and CEO duality are found to be significant determinants for financial distress. However, board size is not a significant variable in predicting financial distress. These results have been confirmed using logistic model. On the other hand, discriminant model reveals that all the explanatory variables are significant in explaining financial distress. Increasing board size increases the probability of financial distress while CEO duality and board independence have a positive impact on financial distress probability. Depending on different criteria (R2, classification table, ROC curve) to compare between logit model and discriminant model, it has been revealed that logit model is better in explaining financial distress. Originality/ value: This article is one of the first to investigate whether board of directors’ attributes contribute to explain of the occurrence of financial distress in the context of Egypt’s economy.

Morphological characterisation and volatile analysis of Turkish garlic genotypes

Garlic is one of the most important vegetables and used for nutrient and medicinal purposes since ancient times. Deficiency in the detection of high-quality garlic genotypes with a rich biochemical profile is one of the main constraints in limiting the production. Currently, the selection and identification of promising garlic genotypes is a popular target, and to reach the best results it is necessary to clarify discrimination. This study aims to discriminate the garlic genotypes obtained from different cultivation locations in Turkey. For that purpose, firstly, morphological characters including biometric parameters were measured based on 18 morphological traits. Particular correlations related to the biometric parameters were calculated. Secondly, a total of 41 main volatiles in the bulbs of garlic genotypes were identi?ed by using headspace-gas chromatography/mass spectrometry. Multivariate discriminant analyses including two-way hierarchical clustering analyses (HCA) and canonical discriminant analysis (CDA) were used to identify dependencies between garlic genotypes and to distinguish the differences based on volatiles among genotypes. There proved to be significant variability in the Turkish genotypes for the morphologic descriptors and the results suggest that besides cultivation area, environmental conditions affect the formation of differentiation in garlic genotypes. Multivariate analysis revealed two main groups, and variation in volatiles within genotypes was important. The closest relationship was determined in the genotypes collected from Araban (district of Gaziantep), Kahramanmaraş, and Yavuzeli (district of Gaziantep) region of Turkey based on the volatiles. The results of volatiles also indicate that the genotypes collected from Kilis, Kastamonu, and Tokat provinces of Turkey could be potential for a promising source related to volatile compounds. The current study established a foundation for the assessment of Turkish garlic genotypes for using in a breeding program and promoting commercialization.