scholarly journals Changes in Amino Acid and Acylcarnitine Plasma Profiles for Distinguishing Patients with Multiple Sclerosis from Healthy Controls

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Marat F. Kasakin ◽  
Artem D. Rogachev ◽  
Elena V. Predtechenskaya ◽  
Vladimir J. Zaigraev ◽  
Vladimir V. Koval ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Amino Acid ◽  
Discriminant Analysis ◽  
Clinical Decision ◽  
Partial Least Square ◽  
Least Square ◽  
Control Group ◽  
Healthy Controls ◽  
Linear Discriminant ◽  
Tandem Mass Spectrometric

McDonald criteria and magnetic resonance imaging (MRI) are used for the diagnosis of multiple sclerosis (MS); nevertheless, it takes a considerable amount of time to make a clinical decision. Amino acid and fatty acid metabolic pathways are disturbed in MS, and this information could be useful for diagnosis. The aim of our study was to find changes in amino acid and acylcarnitine plasma profiles for distinguishing patients with multiple sclerosis from healthy controls. We have applied a targeted metabolomics approach based on tandem mass-spectrometric analysis of amino acids and acylcarnitines in dried plasma spots followed by multivariate statistical analysis for discovery of differences between MS (n=16) and control (n=12) groups. It was found that partial least square discriminant analysis yielded better group classification as compared to principal component linear discriminant analysis and the random forest algorithm. All the three models detected noticeable changes in the amino acid and acylcarnitine profiles in the MS group relative to the control group. Our results hold promise for further development of the clinical decision support system.

scholarly journals A fast and low-cost approach to quality control of alcohol-based hand sanitizer using portable near infrared spectrometer and chemometrics

2021 ◽  
pp. 096703352098731
Author(s):  
Adenilton C da Silva ◽  
Lívia PD Ribeiro ◽  
Ruth MB Vidal ◽  
Wladiana O Matos ◽  
Gisele S Lopes
Keyword(s):  
Quality Control ◽  
Discriminant Analysis ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Chemical Components ◽  
Linear Discriminant ◽  
Hand Sanitizer

The use of alcohol-based hand sanitizers is recommended as one of several strategies to minimize contamination and spread of the COVID-19 disease. Current reports suggest that the virucidal potential of ethanol occurs at concentrations close to 70%. Traditional methods of verifying the ethanol concentration in such products invite potential errors due to the viscosity of chemical components or may be prohibitively expensive to undertake in large demand. Near infrared (NIR) spectroscopy and chemometrics have already been used for the determination of ethanol in other matrices and present an alternative fast and reliable approach to quality control of alcohol-based hand sanitizers. In this study, a portable NIR spectrometer combined with classification chemometric tools, i.e., partial least square discriminant analysis (PLS–DA) and linear discriminant analysis with successive algorithm projection (SPA–LDA) were used to construct models to identify conforming and non-conforming commercial and laboratory synthesized hand sanitizer samples. Principal component analysis (PCA) was applied in an exploratory data study. Three principal components accounted for 99% of data variance and demonstrate clustering of conforming and non-conforming samples. The PLS–DA and SPA–LDA classification models presented 77 and 100% of accuracy in cross/internal validation respectively and 100% of accuracy in the classification of test samples. A total of 43% commercial samples evaluated using the PLS–DA and SPA–LDA presented ethanol content non-conforming for hand sanitizer gel. These results indicate that use of NIR spectroscopy and chemometrics is a promising strategy, yielding a method that is fast, portable, and reliable for discrimination of alcohol-based hand sanitizers with respect to conforming and non-conforming ethanol concentrations.

Near-Infrared Spectroscopy for Discrimination of Charcoal from Eucalyptus and Native Cerrado Species—Contribution to a Database for Forestry Supervision

2021 ◽  
Author(s):  
Silvana Nisgoski ◽  
Thaís A P Gonçalves ◽  
Júlia Sonsin-Oliveira ◽  
Adriano W Ballarin ◽  
Graciela I B Muñiz
Keyword(s):  
Infrared Spectroscopy ◽  
Discriminant Analysis ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
New Technologies ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Eucalyptus Species ◽  
Linear Discriminant

Abstract The illegal charcoal trade is an internationally well-known forest crime. In Brazil, government agents try to control it using the document of forest origin (DOF). To confirm a load’s legality, the agents must compare it with the declared content of the DOF. However, to identify charcoal is difficult even for specialists in wood anatomy. Hence, new technologies would facilitate the agents’ work. Near-infrared spectroscopy (NIR) provides a rapid and precise response to differentiate carbonized species. Considering the rich Brazilian flora, NIR studies are still underdeveloped. Our work aimed to differentiate charcoals of seven eucalypts and 10 Cerrado species based on NIR analysis and to add information to a charcoal database. Data were collected with a spectrophotometer in reflectance mode. Partial least square regression with discriminant analysis (PLS-DA) and a linear discriminant analysis (LDA) was applied to confirm the performance and potential of NIR spectra to distinguish native Cerrado species from eucalyptus species. Wavenumbers from 4,000 to 6,000 cm−1 and transversal surface presented the best results. NIR had the potential to distinguish eucalypt charcoals from Cerrado species and in comparison to reference samples. NIR is a potential tool for forestry supervision to guarantee the sustainability of the charcoal supply in Brazil and countries with similar conditions. Study Implications It is a challenge to protect the Cerrado biome against deforestation for charcoal production. The application of new technologies such as near-infrared spectroscopy (NIR) for charcoal identification might improve the work of government agents. In this article, we studied the spectra of Cerrado and eucalypt species. Our results present good separation between the analyzed groups. The main goal is to develop a reliable NIR database that would be useful in the practical work of agents. The database will be available for all control agencies, and future training will be done for a rapid initial evaluation in the field.

scholarly journals Characterization of Esophageal Microbiota in Patients With Esophagitis and Esophageal Squamous Cell Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Zongdan Jiang ◽  
Jun Wang ◽  
Ziyang Shen ◽  
Zhenyu Zhang ◽  
Shukui Wang
Keyword(s):  
Squamous Cell Carcinoma ◽  
Discriminant Analysis ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Control Group ◽  
Rrna Gene ◽  
Healthy Controls ◽  
Linear Discriminant ◽  
Genus Level

Microbial imbalances have been well elucidated in esophageal adenocarcinoma. However, few studies address the microbiota in esophageal squamous cell carcinoma (ESCC) and esophagitis (ES). We aimed to explore the association of esophageal microbiota with these patients. Esophageal tissues were obtained from healthy controls and ES and ESCC patients undergoing upper endoscopy. 16S rRNA gene sequencing was applied to analyze the microbiome. The α and β diversity differences were tested by Tukey test and partial least squares-discriminant analysis (PLS-DA), respectively. Linear discriminant analysis effect size (LEfSe) analysis was performed to assess taxonomic differences between groups. A total of 68 individuals were enrolled (control = 21, ES = 15, ESCC = 32). Microbial diversity was significantly different between the ESCC patients and healthy controls by Chao1 index, Shannon index, and PLS-DA. Firmicutes, Proteobacteria, Bacteroidetes, Actinobacteria, and Fusobacteria were the five dominant bacterial phyla among the three groups. Megamonas, Collinsella, Roseburia, and Ruminococcus_2 showed a significantly continuous decreasing trend from the control group to the ESCC group at the genus level. When compared with the control group, decreased Fusobacteria at phylum level and Faecalibacterium, Bacteroides, Curvibacter, and Blautia at genus level were detected. ESCC samples also displayed a striking reduction of Bacteroidetes, Faecalibacterium, Bacteroides, and Blautia in comparison with the ES patients. LEfSe analysis indicated a greater abundance of Streptococcus, Actinobacillus, Peptostreptococcus, Fusobacterium, and Prevotella in the ESCC group. Our study suggests a potential association between esophageal microbiome dysbiosis and ESCC and provides insights into potential screening markers for esophageal cancer.

scholarly journals Potencial Use of Near Infrared Spectroscopy (NIRS) to Categorise Chorizo Sausages from Iberian Pigs According to Several Quality Standards

2021 ◽  
Vol 11 (23) ◽  
pp. 11379
Author(s):  
Alberto Ortiz ◽  
Lucía León ◽  
Rebeca Contador ◽  
David Tejerina
Keyword(s):  
Infrared Spectroscopy ◽  
Discriminant Analysis ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
External Validation ◽  
Partial Least Square ◽  
Least Square ◽  
Raw Material ◽  
Linear Discriminant ◽  
Discriminant Ability

The ability of Near Infrared Spectroscopy (NIRS) to classify pre-sliced Iberian chorizo modified atmosphere packaged (MAP) according to the animal material used in their production (Black, Red, White) in their production in accordance with the official trade categories (which includes the handling system and the different inter-racial crossbreeds) without opening the package was assayed. Furthermore, various spectra pre-treatments and supervised classification chemometric tools; Partial least square-discriminant analysis (PLS-DA), soft independent modelling of class analogies (SIMCA) and linear discriminant analysis (LDA), were assessed. The highest sensitivity values in both calibration and external validation were achieved with SIMCA followed by PLS-DA approaches, while LDA had more provided values among sensitivity and specificity and between the different commercial categories in both sample sets, thus yielding the highest discriminant ability. These results could be a resource to support the traceability and authentication control of individual pre-sliced MAP Iberian chorizo according to the commercial category of the raw material in a non-destructive way.

scholarly journals Discrimination of Melanoma Using Laser-Induced Breakdown Spectroscopy Conducted on Human Tissue Samples

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Muhammad Nouman Khan ◽  
Qianqian Wang ◽  
Bushra Sana Idrees ◽  
Geer Teng ◽  
Xutai Cui ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Partial Least Square ◽  
Least Square ◽  
Laser Induced Breakdown Spectroscopy ◽  
Chemometric Methods ◽  
Tissue Samples ◽  
Linear Discriminant ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown ◽  
Signal Intensities

Discrimination and identification of melanoma (a kind of skin cancer) by using laser-induced breakdown spectroscopy (LIBS) combined with chemometrics methods are reported. The human melanoma and normal tissues are used in the form of formalin-fixed paraffin-embedded (FFPE) blocks as samples. The results demonstrated higher LIBS signal intensities of phosphorus (P), potassium (K), sodium (Na), magnesium (Mg), and calcium (Ca) in melanoma FFPE samples while lower signal intensities in normal FFPE tissue samples. Chemometric methods, artificial neural network (ANN), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and partial least square discriminant analysis (PLS-DA) are used to build the classification models. Different preprocessing methods, standard normal variate (SNV), mean-centering, normalization by total area, and autoscaling, were compared. A good performance of the model (sensitivity, specificity, and accuracy) for melanoma and normal FFPE tissues has been achieved by the ANN and PLS-DA models (all were 100%). The results revealed that LIBS combined with chemometric methods for detection and discrimination of human malignancies is a reliable, accurate, and precise technique.

A Common Thrombomodulin Amino Acid Dimorphism Is Associated with Myocardial Infarction

1997 ◽  
Vol 77 (02) ◽  
pp. 248-251 ◽  
Author(s):  
Lena Norlund ◽  
Johan Holm ◽  
Bengt Zöller ◽  
Ann-Kristin Öhlin
Keyword(s):  
Myocardial Infarction ◽  
Amino Acid ◽  
Plasma Concentration ◽  
Acute Coronary Syndromes ◽  
Protein C ◽  
Integral Membrane Protein ◽  
Control Group ◽  
Healthy Controls ◽  
Coronary Syndromes ◽  
Premature Myocardial Infarction

SummaryEndothelial dysfunction and haemostatic imbalance are believed to be important aetiological factors in the development of acute coronary syndromes. Thrombomodulin (TM) is an integral membrane protein crucial for normal endothelial function and activation of the protein C anticoagulant pathway. We have investigated the importance of a common C/T dimorphism in the TM gene (nucleotide 1418) for development of premature myocardial infarction (MI). The C/T dimorphism predicts an Ala455 to Val replacement in the sixth EGF-like domain of TM. The dimorphism was investigated in 97 MI survivors and 159 healthy controls. The C allele was significantly more frequent among patients than controls (p = 0.035). The allele frequency for the C allele was 0.82 in the patients and 0.72 in the control group. The plasma concentration of TM was investigated among healthy controls but was not related to the C/T dimorphism. In conclusion, the association of the C allele with premature MI, suggests that the TM gene and the C/T dimorphism may be aetiological factors involved in the pathogenesis of MI. Possibly, the Ala455 to Val replacement may affect the function of the TM molecule and the activation of the protein C anticoagulant pathway.

scholarly journals The inflammatory profile of cerebrospinal fluid, plasma, and saliva from patients with severe neuropathic pain and healthy controls-a pilot study

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Mika Jönsson ◽  
Björn Gerdle ◽  
Bijar Ghafouri ◽  
Emmanuel Bäckryd
Keyword(s):  
Cerebrospinal Fluid ◽  
Neuropathic Pain ◽  
Pain Intensity ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Therapeutic Interventions ◽  
Healthy Controls ◽  
Inflammatory Profile

Abstract Background Neuropathic pain (NeuP) is a complex, debilitating condition of the somatosensory system, where dysregulation between pro- and anti-inflammatory cytokines and chemokines are believed to play a pivotal role. As of date, there is no ubiquitously accepted diagnostic test for NeuP and current therapeutic interventions are lacking in efficacy. The aim of this study was to investigate the ability of three biofluids - saliva, plasma, and cerebrospinal fluid (CSF), to discriminate an inflammatory profile at a central, systemic, and peripheral level in NeuP patients compared to healthy controls. Methods The concentrations of 71 cytokines, chemokines and growth factors in saliva, plasma, and CSF samples from 13 patients with peripheral NeuP and 13 healthy controls were analyzed using a multiplex-immunoassay based on an electrochemiluminescent detection method. The NeuP patients were recruited from a clinical trial of intrathecal bolus injection of ziconotide (ClinicalTrials.gov identifier NCT01373983). Multivariate data analysis (principal component analysis and orthogonal partial least square regression) was used to identify proteins significant for group discrimination and protein correlation to pain intensity. Proteins with variable influence of projection (VIP) value higher than 1 (combined with the jack-knifed confidence intervals in the coefficients plot not including zero) were considered significant. Results We found 17 cytokines/chemokines that were significantly up- or down-regulated in NeuP patients compared to healthy controls. Of these 17 proteins, 8 were from saliva, 7 from plasma, and 2 from CSF samples. The correlation analysis showed that the most important proteins that correlated to pain intensity were found in plasma (VIP > 1). Conclusions Investigation of the inflammatory profile of NeuP showed that most of the significant proteins for group separation were found in the less invasive biofluids of saliva and plasma. Within the NeuP patient group it was also seen that proteins in plasma had the highest correlation to pain intensity. These preliminary results indicate a potential for further biomarker research in the more easily accessible biofluids of saliva and plasma for chronic peripheral neuropathic pain where a combination of YKL-40 and MIP-1α in saliva might be of special interest for future studies that also include other non-neuropathic pain states.

Calculation of Predictive Odds for Possible Carriers of Haemophilia

1975 ◽  
Author(s):  
G. D. Forbes ◽  
A. D. McLaren ◽  
C. R. M. Prentice
Keyword(s):  
Biological Activity ◽  
Discriminant Analysis ◽  
Factor Viii ◽  
Factor Vii ◽  
Control Group ◽  
Posterior Odds ◽  
Linear Discriminant ◽  
Bayesian Calculation ◽  
Using Data ◽  
Betting Odds

The predictive odds for possible carriers of haemophilia have been calculated using data derived from normal and known carrier populations. For each individual the concentration of factor VII-related antigen (A) and factor VIII biological activity (B) was measured. The data has been studied by linear discriminant analysis linked to a Bayesian calculation of posterior odds using the predictive distributions of both the normal and obligatory carrier populations. The proportion of possible carriers assigned to the definite carrier group or control group is dependent on which betting odds are regarded as most suitable for counselling patients. For instance, if betting odds of 5 : 1 were given it was possible to assign 22 of 32 possible carriers (69 per cent) to control or carrier groups. Of this group of 22 possible carriers, 11 were thought to be normal and 11 were thought to be haemophilia carriers.

Association between circulating leptin levels and multiple sclerosis: a systematic review and meta-analysis

2018 ◽  
Vol 94 (1111) ◽  
pp. 278-283 ◽  
Author(s):  
Xue-Feng Xie ◽  
Xiao-Hui Huang ◽  
Ai-Zong Shen ◽  
Jun Li ◽  
Ye-Huan Sun
Keyword(s):  
Multiple Sclerosis ◽  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Control Group ◽  
Sample Type ◽  
Healthy Controls ◽  
Eligibility Criteria ◽  
Effect Model ◽  
Healthy Control

AimLeptin, synthesised by adipocytes, has been identified as a hormone that can influence inflammatory activity. Several studies have investigated leptin levels in patients with multiple sclerosis (MS), but the results are not consistent. This study aims to derive a more precise evaluation on the relationship between circulating leptin levels and MS.DesignA comprehensive literature searched up to July 2017 was conducted to evaluate the association of circulating leptin levels and MS. The random-effect model was applied to calculate pooled standardised mean difference (SMD) and its 95% CI.Main outcome measuresCirculating leptin levels of patients with MS and healthy controls.ResultsOf 2155 studies identified, 33 met eligibility criteria and 9 studies with 645 patients with MS and 586 controls were finally included in the meta-analysis. Meta-analysis revealed that, compared with the healthy control group, the MS group had significantly higher plasma/serum leptin levels, with the SMD of 0.70% and 95% CI (0.24 to 1.15). Subgroup analyses suggested that the leptin levels of patients with MS were associated with region, age, study sample size, measurement type, gender and blood sample type.ConclusionOverall, our study suggests that patients with MS have a significantly higher leptin level than in healthy controls. Further mechanism studies and longitudinal large cohort studies are still needed to further reveal the role of leptin in the pathogenesis of MS.

Identification and Quantification of Metamizole in Traditional Herbal Medicines using Spectroscopy FTIR-ATR combined with Chemometrics

2021 ◽  
pp. 4413-4419
Author(s):  
Dharmastuti Cahya Fatmarahmi ◽  
Ratna Asmah Susidarti ◽  
Respati Tri Swasono ◽  
Abdul Rohman
Keyword(s):  
Discriminant Analysis ◽  
Herbal Medicine ◽  
Ftir Spectroscopy ◽  
Herbal Medicines ◽  
Principal Component ◽  
Attenuated Total Reflection ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Precision Data

The study aims to develop an effective, efficient, and reliable method using Fourier Transform Infrared (FTIR) spectroscopy with Attenuated Total Reflection (ATR) combined with chemometric for identifying the synthetic drug in Indonesian herbal medicine known as Jamu. Jamu powders, Metamizole, and the binary mixture of Jamu and Metamizole were measured using FTIR-ATR at the mid-infrared region (4000-650 cm-1). The obtained spectra profiles were further analyzed by Principal Component Analysis, Partial Least Square Regression, Principal Component Regression, and Discriminant Analysis. Jamu Pegel Linu (JPL), Jamu Encok (JE), Jamu Sakit Pinggang (JSP), Metamizole (M), and adulterated Jamu by Metamizole were discriminated well on PCA score plot. PLSR and PCR showed the accuracy and precision data to quantify JPL, JE, and JSP, and each adulterated by M with R2 value > 0,995 and low value of RMSEC and RMSEP. Discriminant Analysis (DA) was successfully grouping Jamu and Metamizole without any misclassification. A combination of FTIR spectroscopy and chemometrics offered useful tools for detecting Metamizole in traditional herbal medicine.

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