Raman spectroscopy-based metabolic fingerprinting of seminal plasma reveals distinct profiles among fertile men.

Fourier Transform Mid-Infrared (FT-MIR) spectroscopy and multivariate statistical analysis were used to differentiate mezcales elaborated with four agave species. The FT-MIR data matrix was subjected to spectral transformations using first and second derivatives. The Partial Least Squares (PLS)-Discriminant Analysis (DA) with the matrix transformed by the first and second derivative allowed the differentiation of mezcales. While Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) was more robust when it was analyzed with second-derivative data. Pairwise comparisons by OPLS-DA allowed mezcales to be correctly discriminated, mainly between Agave karwinskii and Agave potatorum (Q2 = 0.654 and p – value < 0.01; R2Y = 0.985 and p-value < 0.01) and between Agave angustifolia and Agave karwinskii (Q2 = 0.563 and p-value = 0.01; R2Y = 0.989 and p-value = 0.01). FT-MIR spectrophotometry and the PLS-Regression (PLS-R) were applied to predict the ethanol percentage (% v/v) of mezcales collected in 2022 based on the PLS-R model previously run on samples evaluated in 2021.

Background: A set of logical criteria that can accurately identify and verify the cultivation region of raw materials is a critical tool for the scientific management of traditional herbal medicine. Methods and Results: Volatile compounds were obtained from 19 and 32 samples of Angelica gigas Nakai cultivated in Korea and China, respectively, by using steam distillation extraction. The metabolites were identified using GC/MS by querying against the NIST reference library. Data binning was performed to normalize the number of variables used in statistical analysis. Multivariate statistical analyses, such as Principal Component Analysis (PCA), Partial Least Squares-Discriminant Analysis (PLS-DA), and Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) were performed using the SIMCA-P software. Significant variables with a Variable Importance in the Projection (VIP) score higher than 1.0 as obtained through OPLS-DA and those that resulted in p-values less than 0.05 through one-way ANOVA were selected to verify the marker compounds. Among the 19 variables extracted, styrene, α-pinene, and β-terpinene were selected as markers to indicate the origin of A. gigas. Conclusions: The statistical model developed was suitable for determination of the geographical origin of A. gigas. The cultivation regions of six Korean and eight Chinese A. gigas. samples were predicted using the established OPLS-DA model and it was confirmed that 13 of the 14 samples were accurately classified.

Comparative analysis of targeted metabolomics: Dominance-based rough set approach versus orthogonal partial least square-discriminant analysis

MotivationDNA microarray analysis is characterized by obtaining a large number of gene variables from a small number of observations. Cluster analysis is widely used to analyze DNA microarray data to make classification and diagnosis of disease. Because there are so many irrelevant and insignificant genes in a dataset, a feature selection approach must be employed in data analysis. The performance of cluster analysis of this high-throughput data depends on whether the feature selection approach chooses the most relevant genes associated with disease classes.ResultsHere we proposed a new method using multiple Orthogonal Partial Least Squares-Discriminant Analysis (mOPLS-DA) models and S-plots to select the most relevant genes to conduct three-class disease classification and prediction. We tested our method using Golub’s leukemia microarray data. For three classes with subtypes, we proposed hierarchical orthogonal partial least squares-discriminant analysis (OPLS-DA) models and S-plots to select features for two main classes and their subtypes. For three classes in parallel, we employed three OPLS-DA models and S-plots to choose marker genes for each class. The power of feature selection to classify and predict three-class disease was evaluated using cluster analysis. Further, the general performance of our method was tested using four public datasets and compared with those of four other feature selection methods. The results revealed that our method effectively selected the most relevant features for disease classification and prediction, and its performance was better than that of the other methods.

Abstract: Aim: The purpose of this study is to develop a method to explore the difference between the rhizomes and tuberous roots of Curcuma longa, and screen out the difference markers. Materials and Methods: The quantitative analysis and fingerprints of rhizomes and tuberous roots were established by HPLC, rhizomes and tuberous roots of Curcuma longa were clearly discriminated by Hierarchical Cluster Analysis (HCA), Similarity Analysis (SA) and Principal Component Analysis (PCA). The difference markers were screened out by Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA). Results: The contents of curcumin, bisdemethoxycurcumin and demethoxycurcumin in all rhizomes were higher than those in tuberous roots. Multivariate statistical analysis shown that the samples of rhizomes were grouped into the same categories and samples of tuberous root were grouped another group in each analysis mode. And the OPLS-DA model had a good productivity and good fit indicated by the value of R2Y=0.981, Q2=0.946and R2X=0.816. The important markers for discrimination samples were the peak 14, peak 10 (demethoxycurcumin) and peak 11 (curcumin). Conclusion: The fingerprinting combination of multivariate statistical analysis can be applied to distinguish the rhizomes and tuberous roots of Curcuma longa. Keywords: Curcuma longa, Discrimination, HPLC fingerprints, Multivariate statistical analysis, Rhizomes and tuberous root.

Freezing is employed to preserve the quality of pomegranate juice (PJ) for producing nutritious ready-to-drink beverages. However, the aroma compounds of PJ undergo significant alterations post-freezing. This study aimed to examine the impacts of different freezing temperatures (-20 °C, -40 °C, and -80 °C) on the flavor profiles of PJ, using fresh PJ as a control. The quantitative descriptive sensory analysis (QDA) results showed that grassy, woody, and fruity attributes of PJ were notably diminished following the freezing treatment. In total, 34 volatiles were identified by gas chromatography-mass spectrometry (GC-MS), of which 14 were perceived by GC-olfactometry (GC-O). Together with orthogonal partial least squares-discriminant analysis (OPLS-DA) and OAV tests, five volatiles were determined as key differential markers, and three (hexanol, (Z)-3-hexen-1-ol and β-myrcene) were selected for further odorant addition experiments. The results verified that (Z)-3-hexen-1-ol was the primary odorant for enhancing the grassy and fruity notes of PJ, while hexanol and β-myrcene were crucial for enhancing grassy and woody attributes, respectively.

1H-NMR spectroscopy coupled with multivariate statistical analysis was used for the first time to compare the urinary NMR metabolic profiles of neonates with intrauterine growth retardation (IUGR) and large for gestational age (LGA). For the sake of comparison, infants who were adequate for gestational age (AGA) were also analyzed. Pattern recognition methods, including Principal Component Analyses (PCA), Partial Least Squares Discriminant Analysis (PLS-DA) and Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA), were used to analyze NMR data. Clear differences among the metabolic profiles of AGA, IUGR and LGA were observed. The main metabolites responsible for these differentiations were identified as myo-inositol, creatinine, creatine, citrate, urea and glycine. In particular, among these, myo-inositol may be a potential biomarker of an altered glucose metabolism during fetal development both in IUGR and LGA. This study highlights the applicability of NMR-based metabolomics for improving the understanding of the relations among nutrition, integrated metabolism and health in neonatology.

Male infertility occurs approximately in about 50% of all infertility cases and represents a serious concern worldwide. Traditional semen analysis alone is insufficient to diagnose male infertility. Over the past two decades, advances in omics technologies have led to the widespread application of metabolomics profiling as a valuable diagnostic tool for various diseases and disorders. Seminal plasma represents a rich and easily accessible source of metabolites surrounding spermatozoa, a milieu that provides several indispensable nutrients to sustain sperm motility and fertilization. Changes of metabolic profiles in seminal plasma reflect male reproductive tract disorders. Here, we performed seminal plasma metabolomics and lipidomics profiling to identify a new pattern of biomarkers of male infertility. Seminal plasma samples from unfertile subjects (n = 31) and fertile controls (n = 19) were analyzed using an untargeted metabolomics/lipidomics integrated approach, based on Ultra-High-Pressure Liquid Chromatography-tandem Mass Spectrometry. Partial Least Squares-Discriminant Analysis showed a distinct separation between healthy fertile men and infertile subjects. Among the 15 selected candidate biomarkers based on Variable Importance in Projection scores, phosphatidylethanolamine (PE) (18:1; 18:1) resulted with the highest score. In total, 40 molecular species showed statistically significant variations between fertile and infertile men. Heat-map and volcano plot analysis indicated that acylcarnitines, phosphatidylserine (PS) (40:2) and lactate were decreased, while PE (18:1; 18:1), Phosphatidic acid (PA) (O-19:2; 18:1), Lysophosphatidylethanolamine (LPE) (O-16:1) and Phosphatidylcholine (PC) (O-16:2; 18:1)-CH3 were increased in the infertile group. The present study is the first one to analyze the metabolomics/lipidomics dysregulation in seminal plasma between fertile and infertile individuals regardless of sub-infertility condition. Association of several metabolites/lipids dysregulation with male infertility reinforced data of previous studies performed with different approaches. In particular, we confirmed significantly decreased levels of PS and carnitines in infertile patients as well as the positive correlation with sperm motility and morphology. If validated on a larger prospective cohort, the metabolite biomarkers of infertility in seminal plasma we identified in the present study might inform novel strategies for diagnosis and interventions to overcome male infertility.

Male infertility is a pressing global issue, prompting the need for biomarkers correlating with seminal parameters for diagnosis. Our study investigated 10 biochemical and energetic parameters in the seminal plasma and blood sera of fertile (25 subjects) and infertile (88 subjects) Polish men, correlations between their levels in seminal plasma and semen quality, and correlations between blood sera and seminal plasma levels of examined parameters. Infertile men displayed elevated seminal plasma glucose and fructose but reduced HDL levels compared to fertile men. We observed also weak negative correlations between seminal plasma triglycerides and sperm concentration in both groups. Moreover, infertile men exhibited positive correlations between seminal plasma HDL/LDL concentrations and sperm concentration. Fertile men showed moderate negative correlations between glucose/triglycerides concentrations and sperm count and between seminal plasma triglycerides levels and sperm vitality. Semen volume correlated with triglycerides (negative) and fructose (positive) concentrations in infertile men. Sperm motility correlated negatively with total cholesterol, LDL, and triglycerides concentrations in fertile men, and weakly with AMP-activated protein kinase in infertile men. Weak negative correlations between seminal plasma fructose/AMP-activated protein kinase concentrations and sperm progressive motility were observed in infertile men, whereas in fertile men seminal plasma AMP-activated protein kinase levels were positively correlated with progressive motility. Correlation analysis between blood serum and seminal plasma parameters revealed intriguing connections, notably regarding LDL, AMP-activated protein kinase, and carnitine, suggesting systemic influences on seminal plasma composition. These findings emphasize the complex interplay between metabolic factors and sperm parameters, offering promising directions for future research in male infertility diagnostics and therapeutics.

Teratozoospermia, a qualitative sperm disorder characterized by abnormal sperm morphology, represents one of the causes of male infertility worldwide. The metabolic analysis of human seminal plasma (SP), can provide insights into the underlying molecular mechanisms of this condition, identifying novel biomarkers and facilitating the development of diagnostic tests. In this study, an untargeted High-Performance Liquid Chromatography-Mass Spectrometry (HPLC-MS) approach was performed to explore SP metabolic alterations associated with teratozoospermia. SP samples from 15 teratozoospermic (TZ) vs. 20 normozoospermic (NZ) subjects were analyzed to identify metabolic pathways linked to sperm morphology dysfunction. Multivariate statistical analysis, including Partial Least Squares Discriminant Analysis (PLS-DA) and Orthogonal PLS-DA, revealed a distinct separation between TZ and NZ, highlighting 14 significantly altered metabolites. Based on Variable Importance in Projection scores, O-acetyl-L-serine showed the highest score. Main findings include alterations in Creatine, Histidine, Adenine, Allantoin and Deoxyuridine levels, suggesting perturbations in inflammation, oxidative stress and sperm DNA damage in teratozoospermia. Correlation and Receiver Operating Characteristic (ROC) analyses identified potential biomarkers, including O-acetyl-L-serine, Creatine, and Histidine, with robust discriminatory power (AUC >0.7). These findings highlight potential metabolic pathways implicated in the pathophysiology of teratozoospermia and provide a foundation for enabling personalized patient management with precision treatment.

Objective: To establish the characteristic spectrum of Sanghuang standard decoction and the content determination method of index components; To study the change of the characteristic spectrum of Sanghuang and standard decoction, and to analyse the transfer rule of the quantity value of the index component content between Sanghuang and its standard decoction. Methods: Analysis was performed on an Shimadzu WondaSil C18 column (4.6 mm×250 mm, 5 μm) with acetonitrile-0.1% phosphoric acid for gradient elution. The characteristic spectrum method were established. The paste-formi rate, content and transfer rate of polysaccharide and total phenol, and the number of common peaks in the characteristic spectrum were used as the main evaluation indexes to analyze the quantitative transmission law of the standard decoction of Sanghuang . Results: The findings demonstrated that the similarity of characteristic chromatographic both Sanghuang and its standard decoction was all at a rane of 0.992 to 1.000. The ability of both Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) and Hierarchical Cluster Analysis (HCA) to distinguish between them confirmed that peaks 1 (ergothioneine), 4 (protocatechuic aldehyde), and 6 are the distinctive elements of Sanghuang and its typical decoctions. Polysaccharides and total phenols from Sanghuang were transferred to standard decoctions at average rates of 31.98% and 25.38%, respectively, while the average extraction rate of 15 batches of standard decoctions was 4.85%. Conclusion: Sanghuang ’s chemical components and those of its normal decoctions are nearly the same, with main chemical components and stable components showing good transfer throughout the procedure. This lays the foundation for the development of quality standards for Sanghuang formula particles by demonstrating the well-controlled quality of Sanghuang standard decoctions and a methodical and scientific preparation methodology.

This study investigated the effect of high pressure processing (HPP) on the fatty acids and amino acids content in New Zealand Diamond Shell (Spisula aequilatera), Storm Shell (Mactra murchisoni), and Tua Tua (Paphies donacina) clams. The clam samples were subjected to HPP with varying levels of pressure (100, 200, 300, 400, 500, and 600 MPa) and holding times (5 and 600 s) at 20 °C. Partial Least Squares Discriminant Analysis (PLS-DA) and Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) were deployed to fingerprint the discriminating amino and fatty acids post-HPP processing while considering their inherent biological variation. Aspartic acid (ASP), isoleucine (ILE), leucine (LEU), lysine (LYS), methionine (MET), serine (SER), threonine (THR), and valine (VAL) were identified as discriminating amino acids, while C18:0, C22:1n9, C24:0, and C25:5n3 were identified as discriminating fatty acids. These amino and fatty acids were then subjected to mixed model ANOVA. Mixed model ANOVA was employed to investigate the influence of HPP pressure and holding times on amino acids and fatty acids in New Zealand clams. A significant effect of pressure levels was reported for all three clam species for both amino and fatty acids composition. Additionally, holding time was a significant factor that mainly influenced amino acid content. butnot fatty acids, suggesting that hydrostatic pressure hardly causes hydrolysis of triglycerides. This study demonstrates the applicability of OPLS-DA in identifying the key discriminating chemical components prior to traditional ANOVA analysis. Results from this research indicate that lower pressure and shorter holding time (100 MPa and 5 s) resulted in the least changes in amino and fatty acids content of clams.

Semen profile, testicular volume, and hormonal levels in infertile patients with varicoceles compared with fertile men with and without varicoceles

Background: Despite Zinc (Zn) deficiency being prevalent in humans, less emphasis has been given on the understanding of its impact on male reproduction. Spermatogenesis has a strict requirement for zinc. The relationship of seminal plasma zinc level and semen parameter until now is controversial.Objective : The study was done to find out the impact of seminal plasma zinc and serum zinc level on semen parameter of fertile and infertile males.Subjects and methods: The study was done in Center for Assisted Reproduction, a tertiary Infertility center in Dhaka and in the Biochemistry Department of Bangabandhu Sheik Mujib Medical University (BSMMU), Dhaka. Sixteen fertile males were taken as control and sixty nine infertile males were taken as cases. Semen analysis was done according to WHO criteria (2004). Serum zinc and seminal plasma zinc levels were measured in the Biochemistry Department of BSMMU by Graphite Furnace Atomic Absorption Spectrophotometer.Result: Seminal parameters between fertile and infertile men showed significantly high sperm count, sperm motility, rapid linear motility, and morphology in fertile group. In fertile men, serum zinc level was lower than the infertile group, whereas the seminal plasma zinc level was higher in the fertile than the infertile group which was not statistically significant. In fertile men except for serum zinc, all parameters showed positive relationship; and in infertile men, except sperm morphology, all other parameters showed negative relationship. Seminal plasma zinc shows positive correlation with all semen parameters in fertile group and negative correlation in infertile group except for sperm morphology. There is negative correlation of serum zinc and seminal zinc-in both groups. Regarding other parameters, semen zinc shows positive correlation with all parameter except sperm morphology in fertile men and negative correlation with all parameter except sperm count in infertile men.Conclusion: Seminal zinc levels in fertile men are higher than those in the infertile patients although the serum zinc level is lower. Zinc levels in seminal plasma has a direct relationship with semen parameters. Zinc deficiency may be an important risk factor for low semen parameters and idiopathic male infertility.J Bangladesh Coll Phys Surg 2017; 35(1): 15-19

The aim of the study was to explore the impact of oxidative stress on frozen seminal plasma in fertile and infertile men by examining the total antioxidant capacity. Patients: Infertile patients from male infertility clinic with various diagnoses and fertile men. Design: Seminal plasma from proven fertile men [n=50] and infertile patients [n=50] were examined for total antioxidant capacity (TAC) level, semen parameters such as morphology, motility and concentration, and DNA integrity test. Interventions: Seminal plasma TAC measurement by luminometric assay using the TAC assay kit, semen analysis parameters, DNA integrity test. Fertile men showed higher TAC values (median and SD): 1201µM (SD±548), as compared with the infertile patients: 831μM (SD±343). The result from sperm morphology of fertile patients showed a mean percentage of 4.8 % (SD±1.68) whereas the percentage in the infertile group was 2.68% (SD ±1.68). The same group of samples, analyzed for DNA damage showed a mean of DFI 10.38% (SD±5.17%) in fertile men and a mean of DFI 17.22% (SD±7.22%) in infertile men. Total antioxidant capacity of the seminal plasma as measured by the luminоmetric assay is a reliable and simple test for diagnosing and management of male infertility.