Multivariate Discriminant Analysis Research Articles

Baseline metabolites could predict responders with hepatitis B virus-related liver fibrosis for entecavir or combined with FuzhengHuayu tablet.

After receiving entecavir or combined with FuzhengHuayu tablet (FZHY) treatment, some sufferers with hepatitis B virus (HBV)-related liver fibrosis could achieve a histological improvement while the others may fail to improve even worsen. Serum metabolomics at baseline in these patients who were effective in treatment remain unclear. To explore baseline serum metabolites characteristics in responders. A total of 132 patients with HBV-related liver fibrosis and 18 volunteers as healthy controls were recruited. First, all subjects were divided into training set and validation set. Second, the included patients were subdivided into entecavir responders (E-R), entecavir no-responders (E-N), FZHY + entecavir responders (F-R), and FZHY + entecavir no-responders (F-N) following the pathological histological changes after 48 wk' treatments. Then, Serum samples of all subjects before treatment were tested by high performance liquid chromatography-tandem mass spectrometry (LC-MS) high-performance LC-MS. Data processing was conducted using multivariate principal component analysis and orthogonal partial least squares discriminant analysis. Diagnostic tests of selected differential metabolites were used for Boruta analyses and logistic regression. As for the intersection about differential metabolic pathways between the groups E-R vs E-N and F-R vs F-N, results showed that 4 pathways including linoleic acid metabolism, aminoacyl-tRNA biosynthesis, cyanoamino acid metabolism, alanine, aspartate and glutamate metabolism were screened out. As for the differential metabolites, these 7 intersected metabolites including hydroxypropionic acid, tyrosine, citric acid, taurochenodeoxycholic acid, benzoic acid, 2-Furoic acid, and propionic acid were selected. Our findings showed that 4 metabolic pathways and 7 differential metabolites had potential usefulness in clinical prediction of the response of entecavir or combined with FZHY on HBV fibrotic liver.

Business bankruptcy prediction: the multisectorial models’ efficiency in the Old Blue Economy Iberian companies’

In the risk evaluation by the stakeholders it’s crucial to understand the causes of bankruptcy or breach in corporate sustainability, as well as more efficient ways of predicting it. These techniques, mainly supported by financial analysis, over time, have given rise to a diversity of approaches in particular to the Multivariate Discriminant Analysis. We selected, 54 iberian companies from that sector, divided them in two samples, one of the bankrupt companies and another of the healthy ones, matched by size and business' volume. Were applied 21 multisectoral models from a diversity of countries abd time horizons, with greater presence in the literature. As conclusions, continuing Peres and Antão (2019) the work, were identified the best bankruptcy or sustainability predictors, to the Old Blue Economy Iberian industries’, up to 5 years in advance.

Serum-Based Lipid Panels for Diagnosis of Idiopathic Parkinson's Disease.

Parkinson's disease (PD) is a highly prevalent neurodegenerative movement disorder with an unclear etiology and a lack of definite diagnostic tests and effective treatments. About 95% of PD cases are idiopathic, in which none of the well-known genes underlying familial parkinsonism are mutated. We used untargeted liquid chromatography-mass spectrometry (LC-MS/MS) to profile the serum lipidome of 50 patients with different stages of idiopathic PD (early, mid, or advanced) and 45 age-matched controls. When comparing the PD patients to the control subjects, 169 lipids were significantly altered in both a univariate analysis and a multivariate partial least-squares discriminant analysis (PLS-DA). Compared to the controls, the patients with PD had higher levels of unsaturated triacylglycerides (e.g., TG O-56:9 and TG 52:3), saturated lysophosphatidylcholines (LPC 17:0, 16:0, and 15:0), and hydroxyeicosatetraenoic acid (12-HETE), while lower levels of phosphatidylserines (e.g., PS 40:4 and PS 16:0_22:4), sphingomyelins (SM 42:1), and ceramides (e.g., Cer 40:0 and 42:0) were found between the PD patients and the controls. A panel of 10 significantly altered lipids (PS 40:0, Cer 40:0, Cer 42:0, LPC 17:0, LPC 15:0, PC 37:7, PE O-40:8, PC O-42:4, FA 23:0, and SM 42:1) resulted in a strong receiver operating characteristic curve with an AUC = 0.974. This panel may, therefore, be useful for diagnosing PD. In addition, lipid panels may prove useful for distinguishing among the progression stages of PD. Using one-way ANOVA, 155 lipid species were significantly altered among the PD stages. Parkinson's disease progressed from the early to advanced stages with decreasing levels of PC 31:1, PC 38:4, and LPE 22:5. Conversely, LPC-O 20:0, PC O-42:3, FA 19:0, and FA 22:2 showed an increase in their levels with disease progression. Overall, this study shows an intriguing number of robust changes in specific serum lipids that may become useful for diagnosing PD and its progression, once panels have been validated in larger clinical trials and prospective studies.

Gastric cancer: Neural networks, complex system analysis, statistics and computer modeling for best management.

37 Background: We examined factors of alive supersystems – gastric cancer (GC) patients (GCP) and cell ratio factors (CRF) significantly affecting GCP survival. CRF - ratio between cancer cells (CC) and blood cells subpopulations. Methods: 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 1975-2023 (m=558, f=241; total gastrectomies (G)=173, distal G=461; proximal G=165; combined G=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. 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. Results: 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 GCP – more than 10 years (LS=5919.5±2020 days). 290 GCP died because of GC (LS=651±347.2 days). Cox modeling displayed that GCP 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). Conclusions: 5-year survival of GCP after radical procedures significantly depended on: PT “early-invasive cancer”; PT N0--N12; CRF; blood cell circuit; biochemical factors; hemostasis system; AT; GC characteristics; GC cell dynamics; tumor localization; anthropometric data; surgery type. Best diagnosis and treatment strategies for GC are: 1) screening and early detection of GC; 2) availability of experienced abdominal surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunotherapy for GCP with unfavorable prognosis.

Effect of Conventional Spinal Cord Stimulation on Serum Protein Profile in Patients With Persistent Spinal Pain Syndrome: A Case-Control Study

Spinal cord stimulation (SCS) provides pain relief for most patients with persistent spinal pain syndrome type 2 (PSPS 2). Evidence is mounting on molecular changes induced by SCS as one of the mechanisms to explain pain improvement. We report the SCS effect on serum protein expression invivo in patients with PSPS2. Serum proteins were identified and quantified using mass spectrometry. Proteins with significantly different expression among patients with PSPS 2 relative to controls, responders, and nonresponders to SCS, or significantly modulated by SCS relative to baseline, were identified. Those most correlated with the presence and time course of pain were selected using multivariate discriminant analysis. Bioinformatic tools were used to identify related biological processes. Thirty patients with PSPS 2, of whom 23 responded to SCS, were evaluated, together with 14 controls with no pain who also had undergone lumbar spinal surgery. A significant improvement in pain intensity, disability, and quality of life was recorded among responders. Five proteins differed significantly at baseline between patients with PSPS 2 and controls, with three proteins, mostly involved in immune processes and inflammation, being downregulated and two, mostly involved in vitamin metabolism, synaptic transmission, and restorative processes, being upregulated. In addition, four proteins, mostly related to immune processes and inflammation, decreased significantly, and three, mostly related to iron metabolism and containment of synaptic sprouting, increased significantly during SCS. This study identifies various biological processes that may underlie PSPS 2 pain and SCS therapeutic effects, including the modulation of neuroimmune response and inflammation, synaptic sprouting, vitamin and iron metabolism, and restorative processes.

Application of ATR-FTIR Incorporated with Multivariate Data Analysis for Discrimination and Quantification of Urea as an Adulterant in UHT Milk.

Urea is naturally present in milk, yet urea is added intentionally to increase milk's nitrogen content and shelf life. In this study, a total of 50 Ultra heat treatment (UHT) milk samples were spiked with known urea concentrations (0-5 w/v%). Attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy with principal component analysis (PCA), discriminant analysis (DA), and multiple linear regression (MLR) were used for the discrimination and quantification of urea. The PCA was built using 387 variables with higher FL > 0.75 from the first PCA with cumulative variability (90.036%). Subsequently, the DA model was built using the same variables from PCA and demonstrated the good distinction between unadulterated and adulterated milk, with a correct classification rate of 98% for cross-validation. The MLR model used 48 variables with p-value < 0.05 from the DA model and gave R2 values greater than 0.90, with RMSE and MSE below 1 for cross-validation and prediction. The DA and MLR models were then validated externally using a test dataset, which shows 100% correct classification, and the t-test result (p > 0.05) indicated that the MLR could determine the percentage of urea in UHT milk within the permission limit (70 mg/mL). In short, the wavenumbers 1626.63, 1601.98, and 1585.5534 cm-1 are suitable as fingerprint regions for detecting urea in UHT milk.

Cranio-facial bones evaluation based on clinical CT data for sex determination in Northwest Indian population

The skull and pelvis have been the first choice of bones for determination of unknown human remains. The goal of the present study was to derive discriminant function equations by using clinical CT scan data of cranio-facial bones for sex determination in Northwest Indian population. This study was conducted at Department of Radiology, by collecting the retrospective data of CT scan of 217 samples. In the data, 106 were males and 111 were females in the age group between 20 and 80 years. The total number of parameters under investigation were 10. All the selected variables were sexually dimorphic and showed significant values. 91.7% of original grouped cases were correctly classified to their sex category. The TEM, rTEM and R were under the acceptable limits. The univariate, multivariate and stepwise discriminant function analysis recorded an accuracy of 88.9%, 91.7% and 93.6% respectively. Multivariate direct discriminant function analysis stepwise method yielded the highest level of accuracy in differentiating males and females. All the variables reflected statistically significant difference between males and females (p less than 0.001). The best single parameter with highest level of sexual dimorphic trait was length of cranial base. This study aims to provide sex assessment using clinical data of CT scan in Northwest Indian population by incorporating the BIOFB cranio-facial parameter. The morphometric measurements taken on CT scan images can be utilized by forensic experts in identification process.

Discriminant Analysis Approach in Morphometric Differentiation and Characterization of Serbian Autochthonous Goats.

This study investigated the possibility of using morphometric measurements to differentiate the autochthonous Serbian White goat breed from Saanen and Balkan goats, which were used as sire and dam breeds in its creation. For this purpose, a multivariate discriminant analysis was used. A total of 11 morphometric traits were measured in 98 does of 3 breeds: Saanen (n = 28), Balkan (n = 28), and Serbian White (n = 42), aged 2 to 7 years, in 4 different locations. Univariate analysis of variance revealed a significant difference in body measurements of all three breeds, with Saanen goat being the largest in format and Balkan the smallest. Discriminant analysis extracted six out of eleven tested morphometric traits with the strongest discriminatory power: heart girth, head length, chest depth, head width, pelvic width, and body length. Mahalanobis distances were significant between all three genetic groups. The discriminant function correctly classified 95.24% of the Domestic White goats investigated to their source group. The classification accuracy of the function was cross-validated and indicated an overall success rate of 91.84%. The results of this research showed that there was a clear separation between Serbian White, Saanen, and Balkan goats. The present findings could help a more rapid field assessment of Serbian White goats.

Development and validation of nonalcoholic fatty liver disease test: a simple sensitive and specific marker for early diagnosis of nonalcoholic fatty liver disease.

This study aimed to develop a noninvasive test for identifying patients with nonalcoholic fatty liver disease (NAFLD) based on clinical and routine laboratory data. The developed model 'NAFLD test' was compared to the most commonly used NAFLD scores and then validated in three groups of NAFLD patients from five centers in Egypt, China, and Chile. Patients were divided into the discovery cohort (n = 212) and the validation study (n = 859). The ROC curve and stepwise multivariate discriminant analysis were used to develop and validate the NAFLD test and evaluate its diagnostic performance, which was then compared to other NAFLD scores. Elevated C-reactive protein (CRP), cholesterol, BMI, and alanine aminotransferase (ALT) levels were significantly associated with NAFLD (P < 0.0001). NAFLD test is depicted as (-0.695 + 0.031 × BMI + 0.003 × cholesterol + 0.014 × ALT + 0.025 × CRP) to discriminate patients with NAFLD from healthy individuals. The area under the ROC curve (AUC) of the NAFLD test was 0.92 [95% confidence interval (CI): 0.88-0.96]. The NAFLD test was the most accurate diagnostic indicator of NAFLD when compared to widely used NAFLD indices. Upon validating the NAFLD test, its AUC (95% CI) for distinguishing patients with NAFLD from healthy individuals was 0.95 (0.94-0.97), 0.90 (0.87-0.93), and 0.94 (0.91-0.97) in Egyptian, Chinese, and Chilean patients with NAFLD respectively. The NAFLD test is a new validated diagnostic biomarker that can be utilized for the early diagnosis of NAFLD with high diagnostic performance.

Fatty Acid Profiles of Some Siberian Bryophytes and Prospects of Their Use in Chemotaxonomy.

The composition of fatty acids (FAs) in gametophyte samples of 20 Siberian bryophyte species from four orders of mosses and four orders of liverworts collected in relatively cold months (April and/or October) was examined. FA profiles were obtained using gas chromatography. Thirty-seven FAs were found, from 12:0 to 26:0; they included mono-, polyunsaturated (PUFAs) and rare FAs, such as 22:5n-3 and two acetylenic FAs, 6a,9,12-18:3 and 6a,9,12,15-18:4 (dicranin). Acetylenic FAs were found in all examined species of the Bryales and Dicranales orders, dicranin being the predominant FA. The role of particular PUFAs in mosses and liverworts is discussed. Multivariate discriminant analysis (MDA) was performed to determine whether FAs can be used in the chemotaxonomy of bryophytes. Based on the MDA results, FA composition is related to the taxonomic status of species. Thus, several individual FAs were identified as chemotaxonomic markers at the level of bryophyte orders. These were 18:3n-3; 18:4n-3; 6a,9,12-18:3; 6a,9,12,15-18:4; 20:4n-3 and EPA in mosses and 16:3n-3; 16:2n-6; 18:2n-6; 18:3n-3 and EPA in liverworts. These findings indicate that further research into bryophyte FA profiles can shed light on phylogenetic relationships within this group of plants and the evolution of their metabolic pathways.

Determining the shelf life and quality changes of potatoes (Solanum tuberosum) during storage using electronic nose and machine learning.

The activities of alpha-amylase, beta-amylase, sucrose synthase, and invertase enzymes are under the influence of storage conditions and can affect the structure of starch, as well as the sugar content of potatoes, hence altering their quality. Storage in a warehouse is one of the most common and effective methods of storage to maintain the quality of potatoes after their harvest, while preserving their freshness and sweetness. Smart monitoring and evaluation of the quality of potatoes during the storage period could be an effective approach to improve their freshness. This study is aimed at assessing the changes in the potato quality by an electronic nose (e-nose) in terms of the sugar and carbohydrate contents. Three potato cultivars (Agria, Santé, and Sprite) were analyzed and their quality variations were separately assessed. Quality parameters (i.e. sugar and carbohydrate contents) were evaluated in six 15-day periods. The e-nose data were analyzed by means of chemometric methods, including principal component analysis (PCA), linear data analysis (LDA), support vector machine (SVM), and artificial neural network (ANN). Quadratic discriminant analysis (QDA) and multivariate discrimination analysis (MDA) offer the highest accuracy and sensitivity in the classification of data. The accuracy of all methods was higher than 90%. These results could be applied to present a new approach for the assessment of the quality of stored potatoes.

Milk and plasma proteomes from cows facing diet-induced milk fat depression are related to immunity, lipid metabolism and inflammation

Milk proteins are a source of bioactive molecules for calves and humans that may also reflect the physiology and metabolism of dairy cows. Dietary lipid supplements are classically used to modulate the lipid content and composition of bovine milk, with potential impacts on the nutrient’s homeostasis and the systemic inflammation of cows that remains to be more explored. This study aimed at identifying discriminant proteins and their associated pathways in twelve Holstein cows (87 ± 7 days in milk), multiparous and non-pregnant, fed for 28 d a diet either, supplemented with 5% DM intake of corn oil and with 50% additional starch from wheat in the concentrate (COS, n = 6) chosen to induce a milk fat depression, or with 3% DM intake of hydrogenated palm oil (HPO, n = 6) known to increase milk fat content. Intake, milk yield and milk composition were measured. On d 27 of the experimental periods, milk and blood samples were collected and label-free quantitative proteomics was performed on proteins extracted from plasma, milk fat globule membrane (MFGM) and skimmed milk (SM). The proteomes from COS and HPO samples were composed of 98, 158 and 70 unique proteins, respectively, in plasma, MFGM and SM. Of these, the combination of a univariate and a multivariate partial least square discriminant analyses reveals that 15 proteins in plasma, 24 in MFGM and 14 in SM signed the differences between COS and HPO diets. The 15 plasma proteins were related to the immune system, acute-phase response, regulation of lipid transport and insulin sensitivity. The 24 MFGM proteins were related to the lipid biosynthetic process and secretion. The 14 SM proteins were linked mainly to immune response, inflammation and lipid transport. This study proposes discriminant milk and plasma proteomes, depending on diet-induced divergence in milk fat secretion, that are related to nutrient homeostasis, inflammation, immunity and lipid metabolism. The present results also suggest a higher state of inflammation with the COS diet.

Features of damage to the conductive structures of the nervous system in patients with vibration disease, burdened with diabetes mellitus and metabolic syndrome

Introduction. Of interest are the processes developing in vibration disease (VD) in combination with metabolic syndrome (MS) or diabetes mellitus (DM), combined forms of diseases worsen their course and prognosis.&#x0D; The study aims to assess the features of the state of central afferent conductive structures and peripheral nerves in patients with vibration disease, burdened with diabetes mellitus or metabolic syndrome.&#x0D; Materials and methods. The scientists have examined 155 workers with VD — group one with an established diagnosis of VD (86 people); group two — with VD combined with DM (30 people); group three — with VD burdened with MS (39 people). The authors have conducted the electroneuromyographic examination and registration of somatosensory evoked potentials, with stimulation of the median nerve in the wrist. Abduction points — Erb point, cervical spinal cord, from the scalp of the projection area of the precentral gyrus. The researchers have applied multivariate discriminant analysis from the STATISTICA — version 6 application software package of StatSoft Inc (USA).&#x0D; Results. With VD complicated by MS, changes were in the distal part of the motor axons, with VD burdened with DM, the amplitude of the motor component of the median and tibial nerves decreased, the speed of the pulse in the proximal part of the median nerve. Somatosensory evoked potentials in VD in combination with MS revealed an increase in latency of N13 and N20. The duration of N13-N18, N13-N20, latency N18, N20, N30 increased in the case of WB, burdened with DM.&#x0D; Limitations. The limitation of the study is the use of unrelated samples for statistical analysis. The study of the state of central and peripheral conductive structures in connected samples should be considered evidence-based: metabolic syndrome and further — diabetes mellitus.&#x0D; Conclusion. The patterns of peripheral nerve damage in VD associated with exposure to general and local vibration, burdened with DM or MS, were disorders of afferent axons of the upper and lower extremities, as well as changes in the distal parts of the motor component of the tibial and median nerves. The features of the peripheral nerve states in VD, burdened with DM, were the complex involvement of the motor component in the pathological process, characterized by changes in the amplitude, pulse transit time at the level of the terminal unmyelinated fibers of the median and tibial nerves and changes in the proximal part of the median nerve. In VD complicated by MS, pathological changes were characteristic of the distal part of the motor axons. The patterns of afferent conductive structures lesion in VD, burdened with DM or MS, consisted in a violation of the activity of neurons of the cervical spinal cord and the somatosensory cortex. The peculiarity of the state of the central afferent conducting structures in VD, burdened with DM, was the slowing down of the afferent excitation wave in the area of thalamic structures to the somatosensory zone of the cortex, a violation of the conduction from the trunk to the cortical projections of the somatosensory zone. In case of VD, complicated by MS — the time of the afferent excitation wave at the level of the cervical spine and the somatosensory cortex.&#x0D; Ethics. Conclusion of the MEC of the Federal State Budgetary Scientific Institution "East Siberian Institute of Medical and Environmental Research" No. 32 dated 09.10.2019.

NMR-Metabolomics Reveals a Metabolic Shift after Surgical Resection of Non-Small Cell Lung Cancer

Lung cancer can be detected by measuring the patient's plasma metabolomic profile using nuclear magnetic resonance (NMR) spectroscopy. This NMR-based plasma metabolomic profile is patient-specific and represents a snapshot of the patient's metabolite concentrations. The onset of non-small cell lung cancer (NSCLC) causes a change in the metabolite profile. However, the level of metabolic changes after complete NSCLC removal is currently unknown. Fasted pre- and postoperative plasma samples of 74 patients diagnosed with resectable stage I-IIIA NSCLC were analyzed using 1H-NMR spectroscopy. NMR spectra (s = 222) representing two preoperative and one postoperative plasma metabolite profile at three months after surgical resection were obtained for all patients. In total, 228 predictors, i.e., 228 variables representing plasma metabolite concentrations, were extracted from each NMR spectrum. Two types of supervised multivariate discriminant analyses were used to train classifiers presenting a strong differentiation between the pre- and postoperative plasma metabolite profiles. The validation of these trained classification models was obtained by using an independent dataset. A trained multivariate discriminant classification model shows a strong differentiation between the pre- and postoperative NSCLC profiles with a specificity of 96% (95% CI [86-100]) and a sensitivity of 92% (95% CI [81-98]). Validation of this model results in an excellent predictive accuracy of 90% (95% CI [77-97]) and an AUC value of 0.97 (95% CI [0.93-1]). The validation of a second trained model using an additional preoperative control sample dataset confirms the separation of the pre- and postoperative profiles with a predictive accuracy of 93% (95% CI [82-99]) and an AUC value of 0.97 (95% CI [0.93-1]). Metabolite analysis reveals significantly increased lactate, cysteine, asparagine and decreased acetate levels in the postoperative plasma metabolite profile. The results of this paper demonstrate that surgical removal of NSCLC generates a detectable metabolic shift in blood plasma. The observed metabolic shift indicates that the NSCLC metabolite profile is determined by the tumor's presence rather than donor-specific features. Furthermore, the ability to detect the metabolic difference before and after surgical tumor resection strongly supports the prospect that NMR-generated metabolite profiles via blood samples advance towards early detection of NSCLC recurrence.

Virulence Phenotyping and Molecular Genotyping Reveal High Diversity Within and Strong Gene Flow Between the Puccinia striiformis f. sp. tritici Populations Collected from Barberry and Wheat in Shaanxi Province of China.

Emergence of new Puccinia striiformis f. sp. tritici races that overcome resistance of wheat cultivars is a challenging issue for wheat production. Although sexual reproduction of the fungus on barberry plants under field conditions in the spring in China has been reported, the diversity of the pathogen on barberry plants and the relationship to the population in wheat fields have not been determined. In the present study, two P. striiformis f. sp. tritici populations collected in western Shaanxi Province in May 2016, one from barberry plants (103 isolates) and the other from nearby wheat crops (107 isolates), were phenotyped for virulence and genotyped with simple sequence repeat (SSR) markers. The phenotypic and genotypic data of the two populations were compared to determine their relationships. A total of 120 races, including 29 previously known races (seven were shared by the two populations) and 91 new races (35 from barberry and 56 from wheat), were identified. Similarly, a total of 132 multilocus genotypes, including 51 only from barberry, 77 only from wheat, and four from both, were detected using the SSR markers. Analyses of molecular variance identified high (93%) genetic variance within populations and low but still significant variance (7%) between the populations. Nonparametric multivariate discriminant analysis of principal components and STRUCTURE analysis showed that the two populations had a close relationship with little genetic differentiation (FST = 0.038) and strong gene flow (Nm = 6.34, P = 0.001) between them. Although the analysis of linkage disequilibrium indicated clonal populations, the isolation of P. striiformis f. sp. tritici from barberry plants and the high genetic diversities in the barberry and wheat populations suggest that barberry plants provide aeciospores to infect wheat crops in the area. The information is useful for understanding stripe rust epidemiology and management of the disease.

Análise discriminante baseada nos escores de conformação e acabamento de carcaça de ovinos

ABSTRACT Carcass classification consists of grouping animals with similar carcass characteristics. When the groups are defined a priori, as in the case of conformation and finishing scores, the interest is to identify the contribution of each variable used in separating the groups. Therefore, discriminant analysis was used to discriminate Santa Inês animals according to the conformation and carcass finishing scores (score 2 = regular, score 3 = good) and to identify the variables that most contribute to the differentiation. The conformation and carcass finishing scores vary from 1 to 5. This study used scores 2 and 3, considering that the evaluated animals ranged between these two respective scales. The database consisted of information from 122 uncastrated Santa Inês sheep submitted to the confinement regime, of which 24 variables related to the carcass of the animals were recorded. Data were submitted to the Mardia test to verify multivariate normality, followed by the nonparametric k-nearest neighbor (k-NN) test. The stepwise procedure selected a particular subset of variables, and the Mahalanobis Distance (D2) was used to assess the separation of groups (p-value ˂ 0.05). The variables with the highest discriminatory power for the carcass conformation scores were cold carcass weight (CCW), external carcass length (ECL), and neck (NEC), for carcass finishing were live weight at slaughter (LWS), ECL, and thoracic perimeter (TP). The multivariate discriminant analysis proved efficient in allocating the animals in their groups of origin.

HPTLC PROFILING AND FTIR FINGERPRINTING COUPLED WITH CHEMOMETRIC ANALYSIS OF MALAYSIAN STINGLESS BEE PROPOLIS

Propolis is a natural substance produced by the bees to protect their hive. The present work reports the utilization of chemical profiling and fingerprinting combined with multivariate analysis for discrimination of the geographical origin of Malaysian stingless bee propolis. High Performance Thin Layer Chromatography (HPTLC) has been performed to profile the chemical composition of Geniotrigona thoracica propolis from different localities in East Coast of Peninsular Malaysia namely Besut, Terengganu (BST), Dungun, Terengganu (DGN), Lundang, Kelantan (LDG), Tanah Merah, Kelantan (TM) and Gua Musang, Kelantan (GM). The obtained HPTLC profiles showed the presence of flavonoids, phenolics and terpenoids in propolis. The chemical fingerprinting was obtained through Fourier Transform Infrared (FTIR) spectroscopy. Chemometric analysis on FTIR dataset using principal component analysis (PCA) and hierarchical cluster analysis (HCA) have classified the propolis into three major groups according to their sampling locations. Chemical fingerprinting analysis on the functional group via FTIR and chemometric revealed that the locations of propolis have direct correlation with the chemical composition, thus affecting the biological activities of propolis. Both chemical marker and chemical fingerprinting analysis are important tools in propolis standardization.

Comparison of Diagnostic Models to Estimate the Risk of Metabolic Syndrome in a Chilean Pediatric Population: A Cross-Sectional Study.

The pediatric population has various criteria for measuring metabolic syndrome (MetS). The diversity of consensus for diagnosis has led to different non-comparable reported prevalence. Given the increase in its prevalence in pediatric ages, it is necessary to develop efficient methods to encourage early detection. Consequently, early screening for the risk of MetS could favor timely action in preventing associated comorbidities in adulthood. This study aimed to establish the diagnostic capacity of models that use non-invasive (anthropometric) and invasive (serum biomarkers) variables for the early detection of MetS in Chilean children. A cross-sectional study was carried out on 220 children aged 6 to 11. Multivariate logistic regressions and discriminant analyses were applied to determine the diagnostic capacity of invasive and non-invasive variables. Based on these results, four diagnostic models were created and compared: (i) anthropometric, (ii) hormonal (insulin, leptin, and adiponectin), (iii) Lipid A (high-density cholesterol lipoprotein [HDL-c] and triglycerides [TG]) and (iv) Lipid B (TG/HDL-c). The prevalence of MetS was 26.8%. Lipid biomarkers (HDL-c and TG) and their ratio (TG/HDL-c) presented higher diagnostic capacity, above 80%, followed by body mass index (BMI, 0.71-0.88) and waist-to-height ratio (WHtR, 0.70-0.87). The lipid model A was the most accurate (sensitivity [S] = 62.7%, specificity [E] = 96.9%, validity index 87.7%), followed by the anthropometric model (S = 69.5%, E = 88.8% and validity index = 83.6%). In conclusion, detecting MetS was possible through invasive and non-invasive methods tested in overweight and obese children. The proposed models based on anthropometric variables, or serum biomarkers of the lipid model A, presented acceptable validity indices. Moreover, they were higher than those that measured adipokines, leptin, and adiponectin. The anthropometric model was the most cost-effective and easy to apply in different environments.

Microbiome in paired root apices and periapical lesions and its association with clinical signs in persistent apical periodontitis using next-generation sequencing.

To assess and compare the microbiome of paired root apices and periapical lesions from cases with failed endodontic treatment and to associate the microbiome and bacterial metabolic pathways in both sites with asymptomatic apical periodontitis (AAP) and symptomatic apical periodontitis (SAP), using next-generation sequencing (NGS). Matched root apices and periapical lesions of patients with failed root canal treatments were surgically extracted. Specimens were cryopulverized, bacterial DNA was extracted and the V3-V4 hypervariable regions of the 16 S rRNA gene were amplified and sequenced using the Illumina Miseq platform. Diversity and community composition were studied in the paired samples, as well as in AAP and SAP cases. Diversity indices were compared in each case by means of the Wilcoxon matched-pairs signed rank and Mann-Whitney U tests. Differences in the community composition were explored with multivariate statistical analysis and Linear discriminant analysis Effect Size (LEfSe). Bacterial functional study was performed through the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) analysis. Twenty-one paired apices and lesions were successfully sequenced and analysed, identifying a total of 21 phyla and 600 genera. A higher alpha-diversity was observed in the periapical lesions, although no global differences in the community composition between the two sites were found (p=.87), the most prevalent genera being Fusobacterium, Porphyromonas and Streptococcus. Prevotella, Clostridiales_vadinBB60_group, Bosea, Phreatobacter, Afipia and Xanthobacteriaceae_unclassified were enriched in SAP samples, while Pseudopropionibacterium, Campylobacter and Peptoniphilus were significantly more abundant in AAP cases (p < .05). Metabolic pathways involved in the amino acid metabolism or degradation and flagellum assembly were more abundant in SAP samples, whereas glucose metabolism-related pathways were associated with AAP. The bacterial community composition was similar in the apices and periapical lesions. The microbiome was different in AAP and SAP samples, gram-negative bacteria showing higher relative abundances in SAP cases. An association was observed between amino acid degradation and flagellum assembly pathways, and the development of tenderness to percussion or palpation.

An RF Fingerprint Extraction Method based on Time-frequency Domain Feature Fusion

Identification and authentication of communication radiation sources using RF fingerprint feature extraction technology is widely used in civilian and military applications and has become a research hotspot. In this paper, an RF fingerprint extraction method based on time-frequency domain feature fusion is proposed. The frequency domain features of WVD and the time domain statistical features (variance, skewness, kurtosis) of the signal are first extracted, and then fused and downscaled using multivariate discriminant analysis to obtain new time-frequency fusion features, which are finally input to the support vector machine for classification and recognition. This method is used to analyze signals of walkie-talkies and signals of cell phones with and without noise, and the experimental results show that this method effectively improves the recognition rate and has good noise immunity compared with using frequency domain features or time domain features alone, and the accuracy is improved by about 5% under the condition of low SNR. When the SNR is -10dB, the recognition accuracy of walkie-talkies can reach 81.6% and that of cell phones can reach 86.1%.