Multivariate Discriminant Analysis Research Articles

Insights into the pathophysiology and response of persistent spinal pain syndrome type 2 to spinal cord stimulation: a human genome-wide association study

BackgroundSpinal cord stimulation (SCS) provides pain relief for some patients with persistent spinal pain syndrome type 2 (PSPS 2), but the precise mechanisms of action and prognostic factors for a...

Spatial colocalization and combined survival benefit of natural killer and CD8 T cells despite profound MHC class I loss in non-small cell lung cancer.

MHC class I (MHC-I) loss is frequent in non-small cell lung cancer (NSCLC) rendering tumor cells resistant to T cell lysis. NK cells kill MHC-I-deficient tumor cells, and although previous work indicated their presence at NSCLC margins, they were functionally impaired. Within, we evaluated whether NK cell and CD8 T cell infiltration and activation vary with MHC-I expression. We used single-stain immunohistochemistry (IHC) and Kaplan-Meier analysis to test the effect of NK cell and CD8 T cell infiltration on overall and disease-free survival. To delineate immune covariates of MHC-I-disparate lung cancers, we used multiplexed immunofluorescence (mIF) imaging followed by multivariate statistical modeling. To identify differences in infiltration and intercellular communication between IFNγ-activated and non-activated lymphocytes, we developed a computational pipeline to enumerate single cell neighborhoods from mIF images followed by multivariate discriminant analysis. Spatial quantitation of tumor cell MHC-I expression revealed intra- and inter-tumoral heterogeneity, which was associated with the local lymphocyte landscape. IHC analysis revealed that high CD56+ cell numbers in patient tumors were positively associated with disease-free survival (DFS) (HR=0.58, p=0.064) and overall survival (OS) (HR=0.496, p=0.041). The OS association strengthened with high counts of both CD56+ and CD8+ cells (HR=0.199, p<1×10-3). mIF imaging and multivariate discriminant analysis revealed enrichment of both CD3+CD8+ T cells and CD3-CD56+ NK cells in MHC-I-bearing tumors (p<0.05). To infer associations of functional cell states and local cell-cell communication, we analyzed spatial single cell neighborhood profiles to delineate the cellular environments of IFNγ+/- NK cells and T cells. We discovered that both IFNγ+ NK and CD8 T cells were more frequently associated with other IFNγ+ lymphocytes in comparison to IFNγ- NK cells and CD8 T cells (p<1×10-30). Moreover, IFNγ+ lymphocytes were most often found clustered near MHC-I+ tumor cells. Tumor-infiltrating NK cells and CD8 T cells jointly affected control of NSCLC tumor progression. Co-association of NK and CD8 T cells was most evident in MHC-I-bearing tumors, especially in the presence of IFNγ. Frequent co-localization of IFNγ+ NK cells with other IFNγ+ lymphocytes in near-neighbor analysis suggests NSCLC lymphocyte activation is coordinately regulated.

Distribution of Elements in Durum Wheat Seed and Milling Products: Discrimination between Cultivation Methods through Multivariate Data Analysis.

Many staple foods originate from durum wheat and its milling products; because of this, it is very important to know their characteristics. This study investigates elemental contents in these products and if differences exist because of organic farming. The concentrations of 28 elements in the whole seed and in milling products, that is, bran, semolina and flour, of durum wheat, were determined through ICP-OES. The wheats were grown under conventional or organic agronomic practices to verify the possibility of discriminating, using the elemental content, between products coming from one or the other practice. The elements were more abundant in the outer layer of the seed, the bran, but most of them were also present in the others. Traces of Sb were present only in 3% of the samples, while traces of Tl were detected in approximately half of the seed and bran samples but not in other samples. The absence of an element was more characteristic of specific products, e.g., most semolina and flour lacked Co, while other elements showed small differences between products from organic and conventional cultivation or between different milling products, which was the case, for example, for traces of Ag, B, and V. The concentrations of these elements were coupled with multivariate discriminant analysis, specifically PLS-DA, to identify the cultivation provenance of the milled products. A few elements, although different for each product, are sufficient to attain precision and accuracy of classification close to 1; small differences exist for different products. The worst is flour, where the predicted precision and accuracy are 0.92, although using only three elements: B, K, and Se. Semolina attains perfect prediction when also adding to the three previous elements, Ag, Cd, and Cu. Further elements are necessary for bran, while Fe and Mg replace K and Ag to classify seeds. In conclusion, five elements, B, Cd, Cu, K, and Se, are the most important in distinguishing between organic and conventional agriculture; these elements also permit some differentiation among products. The method could help in fraud prevention.

Revealing the effects of amino acid, organic acid, and phytohormones on the germination of tomato seeds under salinity stress.

Salinity accumulation poses a threat to the production and productivity of economically important crops such as tomatoes (Solanum lycopersicum L.). Currently, salt tolerance breeding programs have been limited by insufficient genetic and physiological knowledge of tolerance-related traits and a lack of an efficient selection domain. For that purpose, we aimed to determine the ability of tomato cultivars to tolerate salt based on seed traits by multiple biochemical pathways. First, we tested three tomato cultivars according to their response to different sodium chloride (NaCl) concentrations (0, 6.3, 9.8, 13.0, and 15.8 dS m-1) and then we analysed their amino acids, organic acids, and phytohormones. Considering the results of germination traits, it is possible to conclude that cultivar H-2274 was more tolerant to salt stress than others. As a result, multivariate discriminant analysis including principal component analysis and two-way hierarchical clustering analyses were constructed and demonstrated that tomato cultivars were separated from each other by the amino acid, organic acid, and phytohormone contents. Considering germination traits of tomato seeds, cv. 'H-2274' was more tolerant to salinity than others depending on high proline (29 pmol µl-1) and citric acid (568 ng µl-1) assays. Biochemical variability offers a valuable tool for investigating salt tolerance mechanisms in tomatoes, and it will be appreciated to find high-tolerant tomato cultivar(s) to saline conditions. Also, the findings of this study have significant potential for practical applications in agriculture, particularly in developing salt-tolerant tomato cultivars to enhance productivity in saline environments and address socio-economic challenges.

Assessing the reliability and accuracy of sex estimation models utilizing sternal morphometry derived from computed tomography in the Ghanaian population

Sex estimation models are specific to populations and cannot be generalized due to genetic and environmental variabilities. This retrospective cross-sectional study, conducted between January and September 2023 at the Tamale Teaching Hospital, included 119 (50.9 %) females and 115 (49.1 %) males aged 23–82 years. Measurements, including manubrium length (M), manubrium width (MW), sternal body length (B), combined manubrium and sternal body lengths (CL), corpus sterni width at first sternebrae (CSWS1), and corpus sterni width at third sternebrae (CSWS3), were obtained from Computerized Tomographic (CT) images of the sternum using DICOM Viewer, accurate to 0.1 cm. Subsequently, sternal area (SA) and sternal index (SI) were calculated. Univariable and stepwise multivariable discriminant function analysis (DFA) and logistic regression (LR) models were developed using a training sample (70 %), and cross-validation was performed on a holdout sample (30 %). Results showed that the linear measurements, excluding M, and sternal area were higher in males than females (P<0.001), while the sternal index was <50 % in males but >50 % in females (P<0.001). Univariable sex estimation accuracies, in cross-validation, ranged from 43.7 % to 92.9 % in DFA and 50.0–92.9 % in LR. For multivariable models, the accuracy ranges were 92.9–94.3 % in DFA and 91.6–93.0 % in LR. The sternal body length was the most accurate at 90.1 % in DFA and 90.2 % in LR, with lower sex bias (male-female) in LR than in DFA (-0.1 vs. 8.7). The sternum proves valuable for sex estimation, with sternal body length as the most accurate linear measurement. However, multivariable models, particularly LR, demonstrate higher accuracy compared to DFA.

Osteological profiling of femoral diaphysis and neck in aquatic, semiaquatic, and terrestrial carnivores and rodents: effects of body size and locomotor habits.

The increased limb bone density documented previously for aquatic tetrapods has been proposed to be an adaptation to overcome buoyancy during swimming and diving. It can be achieved by increasing the amount of bone deposition or by reducing the amount of bone resorption, leading to cortical thickening, loss of medullary cavity, and compaction of trabecular bone. The present study examined the effects of locomotor habit, body size, and phylogeny on the densitometric, cross-sectional, and biomechanical traits of femoral diaphysis and neck in terrestrial, semiaquatic, and aquatic carnivores, and in terrestrial and semiaquatic rodents (12 species) by using peripheral quantitative computed tomography, three-point bending, and femoral neck loading tests. Groupwise differences were analyzed with the univariate generalized linear model and the multivariate linear discriminant analysis supplemented with hierarchical clustering. While none of the individual features could separate the lifestyles or species adequately, the combinations of multiple features produced very good or excellent classifications and clusterings. In the phocid seals, the aquatic niche allowed for lower femoral bone mineral densities than expected based on the body mass alone. The semiaquatic mammals mostly had high bone mineral densities compared to the terrestrial species, which could be considered an adaptation to overcome buoyancy during swimming and shallow diving. Generally, it seems that different osteological properties at the levels of mineral density and biomechanics could be compatible with the adaptation to aquatic, semiaquatic, or terrestrial niches.

Kidney and Liver Predictors of Adults Hospitalized with COVID-19 Infection

SARS-CoV-2 damages not only the lungs, but also the liver and kidney. Most critically ill COVID-19 patients have liver and kidney dysfunctions. The early identification of patients with COVID-19 who will develop severe or critical disease symptoms is important for delivering proper and early treatment. This research studies the correlation of liver and kidney function indexes and COVID-19 outcomes. Electronic medical record data from 391 patients diagnosed with COVID-19 in the COVID-19 Department, Galilee Medical Center, Nahariya, Israel were collected. Epidemiological, clinical, laboratory, and imaging variables were analyzed. The liver and kidney enzyme indexes were measured upon admission and discharge. A correlation between laboratory levels and severity and mortality of COVID-19 patients was undertaken. This study included 391 COVID-19 patients, 258 mild patients and 133 severe patients. Multivariate stepwise regression analyses and discriminant analyses were used to identify and validate powerful predictors. The main outcome was death or invasive ventilation. Three factors, namely higher urea nitrogen (BUN) and IL-6, and lower albumin levels, were the most powerful predictors of mortality, and classified the results (survival vs. death) correctly in 85% of cases (diagnostic accuracy) with a sensitivity of 88% and a specificity 55%. Compared with mild patients, severe patients had lower albumin (ALB), higher alanine aminotransferase (ALT), aspartate aminotransferase (AST) and BUN (all p &lt; 0.001). COVID-19 patients, especially severe patients, have damage to liver and kidney function. BUN, IL-6 and albumin are factors predicting mortality while fibrinogen and AST could be independent factors for predicting the severity of COVID-19.

Examining incubated and nonincubated startups from fear of failure and entrepreneurial well-being during crises

PurposeThis research aimed to examine entrepreneurial fear of failure and entrepreneurial well-being from the perspectives of incubated and nonincubated startups during crises.Design/methodology/approachData were collected by distributing online questionnaires to 152 respondents comprising 43 incubated and 109 nonincubated startups in Indonesia. A multivariate discriminant analysis procedure was used to examine the interrelationships between both groups at the discovery, validation, customer creation and construction stages.FindingsThe result showed a significant difference between these startups at various stages, which was analyzed to provide insights into the relevant dimensions of fear of failure for startups. The essence of entrepreneurial well-being during crises is in accordance with the role of business incubators in an emerging market economy.Practical implicationsStartups need to innovate in order to grow while considering other factors such as work-life balance and financial resource availability. This is important to ensure they have sufficient motivating dosage of fear of failure.Originality/valueThe present study evaluates incubated and nonincubated startups in an emerging market economy by using both the entrepreneurial fear of failure and well-being to capture possible differences between groups. The context of pandemic crises helps us formulate appropriate approaches taken by incubators and startups in the future crises.

EFFECTIVENESS OF THE BUSINESS FAILURE PREDICTION MODELS IN THE IBERIAN TRANSPORT COMPANIES

Purpose: validate, in the existing models, its effectiveness and ability to provide useful information for decision-making, allowing the choice of one that presented as the best alternative for predicting bankruptcy for companies in the transport economic sector (NACE H) up to 6 years before it occurs. Theoretical Framework: in the last decades, since Beaver's (1966) preliminary work in bankruptcy prediction, followed by Altman (1968) models, numerous authors developed different techniques and models to this purpose. Of all the techniques used and developed in almost 60 years of bankruptcy prediction study, Multivariate Discriminant Analysis (MDA) stands out. Despite its limitations, it best combines management and usage simplicity offering stable levels of efficiency. Design/Methodology/Approach: we selected, Portuguese and Spanish companies, from the transport and storage economic sector, subject to statutory auditing, in a sample of 22 companies, considered healthy, according to the most common criterion in the literature: Equity above zero, during six and that in the seventh were considered bankrupt (Equity below zero) and another, paired with the previous one, by Total Assets and Revenues, with 36 companies that presented Equity above zero throughout all the analyzed period, granting the analyzed models full forecasting potential. Were used 21 multi-sectorial models, for different timelines and geographies, with a greater presence in the literature, or developed by Edward Altman, a unique researcher on this subject, between 1979 and 2014. Findings: As a main conclusion, in addition to the description of models and techniques, the formulations developed by Carvalho das Neves (1998), Lizarraga (1998) and Monelos et al. (2011) were the best predictors of bankruptcy, up to 6 years before it occurs, for Portuguese and Spanish companies in the transport economic sector (NACE H). Research, Practical &amp; Social Implications: This information can be used by any interested entity to improve current conditions, optimize and enhance the usage the bankruptcy forecast models. Originality/Value: The global financial crisis and the growing number of company closures make it crucial to understand the causes of corporate failure, with emphasis on forecasting and anticipating it.

Quantitative Assessment of Sourness Intensity in purpleback squid (Symlectoteuthis oualaniensis) from Indian Ocean based on PCA and MVDA models

The occurrence of sour taste with off-flavor in Symlectoteuthis oualaniensis during storage and transportation is a common issue. This current study aimed to quantitatively identify the intensity of sour taste in freeze-stored S. oualaniensis by employing partial least squares regression (PLSR) and Bayesian discriminant model for the relationship between chemically analyzed sourness-related substances and sour taste perception. Principal component analysis was used to classify all tested S. oualaniensis into three groups, accounting for over 90% of the overall variance. It was found that opines, specifically β-alanopine, tauropine, and meso-alanopine, were the main contributors to the sour taste of S. oualaniensis. Discriminant models were successfully developed for the quantification of sour taste with the explanation of 85.0%−103% to the sour taste in squid. The recognition accuracies of self and cross validation results were 100% and 81.0%, respectively. The overall recognition accuracy of the training sample set was 83.3%. These findings suggest that the discriminant approach, combining principal component analysis and multivariate discriminant analysis, can serve as a valuable tool for both qualitative and quantitative analysis of the sour taste intensity in S. oualaniensis from Indian Ocean.

A non-invasive 25-Gene PLNM-Score urine test for detection of prostate cancer pelvic lymph node metastasis.

Prostate cancer patients with pelvic lymph node metastasis (PLNM) have poor prognosis. Based on EAU guidelines, patients with >5% risk of PLNM by nomograms often receive pelvic lymph node dissection (PLND) during prostatectomy. However, nomograms have limited accuracy, so large numbers of false positive patients receive unnecessary surgery with potentially serious side effects. It is important to accurately identify PLNM, yet current tests, including imaging tools are inaccurate. Therefore, we intended to develop a gene expression-based algorithm for detecting PLNM. An advanced random forest machine learning algorithm screening was conducted to develop a classifier for identifying PLNM using urine samples collected from a multi-center retrospective cohort (n = 413) as training set and validated in an independent multi-center prospective cohort (n = 243). Univariate and multivariate discriminant analyses were performed to measure the ability of the algorithm classifier to detect PLNM and compare it with the Memorial Sloan Kettering Cancer Center (MSKCC) nomogram score. An algorithm named 25 G PLNM-Score was developed and found to accurately distinguish PLNM and non-PLNM with AUC of 0.93 (95% CI: 0.85-1.01) and 0.93 (95% CI: 0.87-0.99) in the retrospective and prospective urine cohorts respectively. Kaplan-Meier plots showed large and significant difference in biochemical recurrence-free survival and distant metastasis-free survival in the patients stratified by the 25 G PLNM-Score (log rank P < 0.001 and P < 0.0001, respectively). It spared 96% and 80% of unnecessary PLND with only 0.51% and 1% of PLNM missing in the retrospective and prospective cohorts respectively. In contrast, the MSKCC score only spared 15% of PLND with 0% of PLNM missing. The novel 25 G PLNM-Score is the first highly accurate and non-invasive machine learning algorithm-based urine test to identify PLNM before PLND, with potential clinical benefits of avoiding unnecessary PLND and improving treatment decision-making.

The latest steps of human evolution: What the hard evidence has to say about it?

The latest periods of human evolution are a heated topic of debate and have been at the center of paleoanthropological discussions since the beginning of the field. In the last twenty years, new excavations increased the geographic range of paleoanthropological data, new fossil hominins of the last third of the Pleistocene were found, and old key fossils were redated by modern and more accurate methods. The new picture emerging from this research changed the discussion about the neandertal-sapiens interaction, the finding of their common ancestor, and the understanding of how our lineage evolved. To integrate these new discoveries and to better contextualize how they fit in the hominin framework of the Chibanian, we compared the cranial morphology of 86 well-preserved fossils from Europe, Africa, and Asia of the last 500 thousand years. 25 linear measurements were used to describe the cranial morphology of the fossils, and their biological affinities were explored though multivariate discriminant function analyses. These analyses allow us to assess affinities and possible phylogenetic relationships of Archaic Homo species, including the expressive morphological variability of the specimens included under the umbrella-term “Homo heidelbergensis” from Africa, Asia, and Europe. Our results support that cannot be accommodated in one same species. Additionally, we contribute to the disputable discussion about the origin of H. sapiens, adding support to an African origin for our species.

Abstract TMP25: Common Molecular Biomarkers in Different Types of Acute Brain Injuries Predicting Outcome

Background: Acute brain injuries, including aneurysmal subarachnoid hemorrhage (aSAH), ischemic stroke (IS), and traumatic brain injury (TBI), entail complex recovery processes involving brain plasticity and synaptic regeneration mechanisms. Exploring lipidomic profiles, microRNA expression, and metabolomic changes can yield insights into recovery mechanisms, unveil conserved molecular associations, and identify potential biomarkers. Hypotheses: We hypothesized that regardless of injury type, variations in lipidomic and metabolomic profiles, along with differentially expressed microRNAs, share common characteristics. These changes likely mirror essential biological mechanisms and may correlate with outcomes. Methods: We studied a prospective cohort of patients with IS, aSAH, and TBI (N=71). Serum samples were collected once, followed by comprehensive profiling: lipidomics (Lipidyzer™ Platform), metabolomics (Orbitrap Profiling), and microRNA sequencing (DESeq2). Results: Univariate analysis unveiled candidate molecules predictive of outcomes. Multivariate combinatory linear discriminant analysis (LDA) demonstrated significant prognostic potential for favorable outcomes. The LDA equation combining eight biomarkers was: -0.239[LPC17:0] - 1.125[TAG51:2:FA15:0] + [TAG51:2:FA18:1] + [D-glucuronic Acid] + 0.416[hsa-miR-146b-3p] + 0.082[hsa-miR-485-3p] + 0.433[hsa-miR-5010-5p] + 0.727[hsa-miR-485-5p], effectively predicting favorable outcomes. The AUC was 95.8%, 95% CI (0.88 - 1.00), p-value 0.023, indicating strong discriminatory power of the combinatory biomarker (OR 8.7, 95% CI 1.35-56.9). Conclusion: Findings reveal a shared pattern of lipidomic, metabolomic, and microRNA changes across distinct acute brain injuries. This warrants further investigation and validation, offering prospects for biomarker development, mechanistic validation, and therapeutic interventions in brain recovery. These shared features underscore the importance of interdisciplinary research for targeted, personalized interventions in diverse acute brain injuries.

MicroRNA blood signature for localized radiation injury

A radiological accident, whether from industrial, medical, or malicious origin, may result in localized exposure to high doses of ionizing radiations, leading to the development of local radiation injury (LRI), that may evolve toward deep ulceration and necrosis of the skin and underlying tissues. Early diagnosis is therefore crucial to facilitate identification and management of LRI victims. Circulating microRNAs (miRNA) have been studied as potential diagnostic biomarkers of several diseases including hematological defects following whole-body irradiation (WBI). This study aims to identify a blood miRNA signature associated with LRI in a preclinical C57BL/6J mouse model of hindlimb irradiation using different 10-MV X-ray doses that lead to injuries of different severities. To this end, we first performed broad-spectrum plasma miRNA profiling, followed by a targeted validation step, on two independent animal cohorts. Using a multivariate sparse partial least square discriminant analysis, we identified a panel of eight circulating miRNAs able to segregate mice according to LRI severity. Interestingly, these miRNAs were previously associated with WBI (miR-150-5p, miR-342-3p, miR-146a-5p), inflammation (miR-18a-5p, miR-148b-3p, miR-532-5p) and skin diseases (miR-139-5p, miR-195-5p). Our results suggest the use of circulating miRNAs as suitable molecular biomarkers for LRI prognosis and diagnosis.

Comparison of the distraction index and Norberg angle with radiographic grading of canine hip dysplasia.

The Orthopedic Foundation for Animals (OFA) radiographic grading system stands as a well-established benchmark for categorizing hip dysplasia in canines. Although more objective techniques to quantify early hip laxity in young dogs, such as the Norberg angle (NA) and distraction index (DI), have been documented, there is a scarcity of published studies that directly compare these radiographic measures. The primary objectives of this prospective, analytical study were to assess and compare the NA and DI measures with OFA grades within a cohort of dogs. Thirty dogs (57 hip joints) were evaluated, with a mean age of 5.4±2.9 years and a mean body weight of 34.3±7.1kg. The discriminative power of hip dysplasia for DI and NA used OFA as a reference were compared by multivariate discriminant analysis test. Using the DI (≤0.3) 12 joints were classified as normal, using NA (≥105°) 24 joints and using OFA (≤3) 29. When comparing the discriminant power of NA with OFA resulting similar (P=.8324) with correct classifications of 81% using cross validation, however, the discriminant power of dysplasia of the DI resulted significantly greater (P=.0034) than OFA with correct classifications of only 59% using cross-validation, consequently it was possible determined that of 29 patients with OFA ≤ 3, 20 had DI>0.3. These findings demonstrated that phenotypic healthy dogs according to OFA grading can present passive hip joint laxity, as demonstrated by radiographic evaluation with distraction. Furthermore, DI can contribute to the screening of CHD when evaluated in conjunction with OFA grading.

Multivariate Discriminant Analysis on Differentiating Sheep Breeds Based on Live Body and Carcass Measurements

Multivariate Discriminant Analysis on Differentiating Sheep Breeds Based on Live Body and Carcass Measurements

Laser-induced breakdown spectroscopy combined with multivariate linear discriminant analysis for discriminating different growth phases of bacteria

Laser induced breakdown spectroscopy combined multivariate analysis was used to investigate structure and discrimination of bacteria growth phases.

MATHEMATICAL MODELING OF ASSESSMENT OF THE PROBABILITY OF THE DEVELOPMENT AND PROGRESSING OF DIABETIC MACULAR EDEMA IN PATIENTS WITH TYPE 2 DIABETES

Background. The participation of fractalkine, clusterin and sICAM in the pathogenesis of diabetic complications of the fundus was established. The development of methods of mathematical assessment of the prognosis of the development and course of diabetic macular edema (DME) with the participation of these cytokines is an actual problem of modern ophthalmology and endocrinology.&#x0D; Aim: To develop the prognostic mathematical models for assessing the probability of development and progression of DME in patients with diabetes mellitus (DM) type 2 based on the study of the content of blood serum fractalkine, clusterin and sICAM-1.&#x0D; Material and methods. A single-center selective one-moment open observational study of 82 patients (145 eyes) with DME in type 2 diabetes, divided into 4 groups according to the severity of DME, was conducted. The average age of the patients was 65.25±10.85 years, the average duration of diabetes was 14.0±7.05 years (±SD). The concentration of blood serum fractalkine (Frl), clusterin (Cls) and sICAM-1 was determined by the ELISA, and an instrumental examination of the fundus was performed. Multivariate discriminant analysis was used with the “SPSS 9.0” program. Differences at p&lt;0.05 were considered statistically significant. 3 models with linear combinations of the investigated indicators were developed and corresponding formulas of classification functions (FC) were obtained.&#x0D; Results. Models for assessing the risk of DME development and progression in patients with type 2 DM characterize by the fact that, at the first stage, fix the duration of diabetes mellitus (DD), and measure the concentration of blood serum fractalkine, clusterin, and sICAM-1. Further, with the helpness of ophthalmoscopy, determine the presence and severity of DMN, assigning the code 1 - the presence of concomitant diabetic retinopathy (DRP), the code 2 - the absence of DRP. At the final stage, calculate the classification functions FK1 and FK2 or FK2 and FK3 (depending on the model), compare FK1 with FK2 or FK2 with FK3, and determine which of them is larger according to the appropriate formulas. Moreover, the prognostic decision takes as the choice of the FC that is more important. So, if FK1&gt;FK2, the prognosis is possible the stabilization of the pathological process, and if FK2&gt;FK1 or FK3&gt;FK2, then the prognosis is the probability of progression of the DME.&#x0D; The main model is presented below:&#x0D; FK1DME(0) = -111,278 + 8,57411*Frl + 0,562616*Cls + 0,257994*sICAM -0,139202*DD +7,72433*DRP&#x0D; FK2DME(1) = -101,108 + 8,5887* Frl + 0,544401* Cls + 0,235155*sICAM + +0,0261057*DD + 10,1873*DRP&#x0D; FK3DME(2+3) = -105,68 + 9,06663* Frl + 0,552074* Cls + 0,241348*sICAM -0,102963*DD + 11,8493*DRP&#x0D; Conclusion. The informativeness of mathematical models for assessing the prognostic significance of serum cytokines fractalkine, clusterin and sICAM-1 in the development and progression of DME in patients with type 2 diabetes is 62.5-77.5%, depending on the type of model.

Strategic Financial Management for Housing Finance Companies in India: A Multivariate Approach

Housing Finance Companies (HFCs) have traditionally played a significant role in India's formal housing finance sector. However, their prominence has waned since the fiscal year 2003 when Commercial Banks (CBs) surpassed them in market share, holding over 70 percent of the market compared to HFCs' 28 percent. Cooperative sector institutions occupy a much smaller share, approximately 0.5 percent. Despite their specialization in housing finance, HFCs face increasing challenges to their market share and profitability, particularly the smaller ones. Many smaller HFCs have already succumbed to competitive pressures. The introduction of the 'Base Rate' by the Reserve Bank of India compelled commercial banks to charge higher lending rates to HFCs, placing additional cost pressures on these institutions. Given this evolving landscape, the financial performance of HFCs has become crucial for their survival and growth. In this context, this paper aims to achieve the following objectives: (i) provide an overview of the institutional housing finance system in India, (ii) conduct a comprehensive examination of the role of HFCs in the changing housing finance market, including their principal challenges, (iii) analyze the determinants of superior financial performance in HFCs using Multivariate Discriminant Analysis (MDA) methodology, and (iv) propose effective strategies to enhance the financial performance of HFCs in the context of financial management.

Geographic variation in simple contact calls of Canadian beluga whales (Delphinapterus leucas)

AbstractBeluga whales, Delphinapterus leucas, are a highly social species with a complex and diverse vocal repertoire. Although extensively studied and classified, to date few attempts have been made to examine geographic variation in their calls. In this study, we examined geographic variation in simple contact calls (SCCs), specifically those that consist only of broadband pulsed trains, among four Canadian beluga populations from the Eastern Beaufort Sea (EBS), the Eastern High Arctic‐Baffin Bay, St. Lawrence Estuary (SLE), and the Western Hudson Bay. Five acoustic parameters were measured for each call and compared among populations using multivariate discriminant analysis. Results of our study indicate that there is a degree of variation in SCCs among these four populations, with the most geographically distant populations of the SLE and EBS displaying the greatest degrees of dissimilarity in SCC structure relative to geographically closer populations. Further, these results align with genetic variation of Canadian beluga populations previously described in the literature. This study is the first descriptive population comparison of SCCs for beluga and establishes a baseline for continued work into this developing area of research.