scholarly journals Modeling of RO/NF membrane rejections of PhACs and organic compounds: a statistical analysis

2008 ◽  
Vol 1 (1) ◽  
pp. 7-15 ◽  
Author(s):  
V. Yangali-Quintanilla ◽  
T.-U. Kim ◽  
M. Kennedy ◽  
G. Amy
Keyword(s):  
Dipole Moment ◽  
Molar Volume ◽  
Organic Compounds ◽  
Equivalent Width ◽  
Trichloroacetic Acid ◽  
Statistical Significance ◽  
Principal Component ◽  
Dichloroacetic Acid ◽  
Neutral Compounds ◽  
Molecular Length

Abstract. Rejections of pharmaceutical compounds (Ibuprofen, Diclofenac, Clofibric acid, Naproxen, Primidone, Phenacetin) and organic compounds (Dichloroacetic acid, Trichloroacetic acid, Chloroform, Bromoform, Trichloroethene, Perchloroethene, Carbontetrachloride, Carbontetrabromide) by NF (Filmtec, Saehan) and RO (Filmtec, Saehan, Toray, Koch) membranes were studied. Chloroform presented the lowest rejection due to small molar volume, equivalent width and length. Diclofenac and Primidone showed high rejections related to high molar volume and length. Dichloroacetic acid and Trichloroacetic acid presented good rejections caused by charge exclusion instead of steric hindrance mechanism influencing rejection. Bromoform and Trichloroethene showed low rejections due to small length and equivalent width. Carbontetrabromide, Perchloroethene and Carbontetrachloride with higher equivalent width than BF and TCE presented better rejections. A qualitative analysis of variables using Principal Component Analysis was successfully implemented for reduction of physical-chemical compound properties that influence membrane rejection of PhACs and organic compounds. Properties such as dipole moment, molar volume, hydrophobicity/hydrophilicity, molecular length and equivalent width were found to be important descriptors for simulation of membrane rejection. For membranes used in the experiments, we may conclude that charge repulsion was an important mechanism of rejection for ionic compounds. After analysis with Multiple Linear Regression, we also may conclude that membrane rejection of neutral compounds was well predicted by molar volume, length, equivalent width, hydrophobicity/hydrophilicity and dipole moment. Molecular weight was a poor descriptor variable for rejection modelling. We were able to provide acceptable statistical significance for important results.

scholarly journals Prediction of RO/NF membrane rejections of PhACs and organic compounds: a statistical analysis

2008 ◽  
Vol 1 (1) ◽  
pp. 21-44 ◽  
Author(s):  
V. Yangali-Quintanilla ◽  
T.-U. Kim ◽  
M. Kennedy ◽  
G. Amy
Keyword(s):  
Dipole Moment ◽  
Molar Volume ◽  
Organic Compounds ◽  
Equivalent Width ◽  
Trichloroacetic Acid ◽  
Principal Component ◽  
Dichloroacetic Acid ◽  
Neutral Compounds ◽  
Molecular Length ◽  
Ionic Compounds

Abstract. Rejections of pharmaceutical compounds (Ibuprofen, Diclofenac, Clofibric acid, Naproxen, Primidone, Phenacetin) and organic compounds (Dichloroacetic acid, Trichloroacetic acid, Chloroform, Bromoform, Trichloroethene, Perchloroethene, Carbontetrachloride, Carbontetrabromide) by NF (Filmtec, Saehan) and RO (Filmtec, Saehan, Toray, Koch) membranes were studied. Chloroform presented the lowest rejection due to small molar volume, equivalent width and length. Diclofenac and Primidone showed high rejections related to high molar volume and length. Dichloroacetic acid and Trichloroacetic acid presented good rejections caused by charge exclusion instead of steric hindrance mechanism influencing rejection. Bromoform and Trichloroethene showed low rejections due to small length and equivalent width. Carbontetrabromide, Perchloroethene and Carbontetrachloride with higher equivalent width than BF and TCE presented better rejections. A qualitative analysis of variables using Principal Component Analysis was successfully implemented for reduction of physical-chemical compound properties that influence membrane rejection of PhACs and organic compounds. Properties such as dipole moment, molar volume, hydrophobicity/hydrophilicity, molecular length and equivalent width were found to be important descriptors for prediction of membrane rejection. Ionic and neutral compounds were successfully separated before analysis. For membranes used in the experiments, we may conclude that charge repulsion was an important mechanism of rejection for ionic compounds. Molecular weight was a poor variable for rejection prediction. Membrane rejection of neutral compounds was well predicted by dipole moment, molar volume, length, equivalent width and hydrophobicity/hydrophilicity of compounds after analysis with Multiple Linear Regression.

The Evaluation of Genotoxicity Using DNA Repairing Test for Chemicals Produced in Chlorination and Ozonation Processes

1991 ◽  
Vol 23 (1-3) ◽  
pp. 329-338 ◽  
Author(s):  
Yoshiro Ono ◽  
Isao Somiya ◽  
Masasumi Kawamura
Keyword(s):  
Dna Repair ◽  
Organic Compounds ◽  
Quantitative Evaluation ◽  
Trichloroacetic Acid ◽  
Research Work ◽  
Dichloroacetic Acid ◽  
Umu Test ◽  
Organic Halogenated Compounds ◽  
By Products ◽  
Microsomal Activation

The umu-test which can detect the induction of DNA repair is applied in order to analyze the genotoxicity of by-products of chlorination and ozonation. In this research work, the genotoxicities of 37 comnercial chemicals which are expected to be involved in the by-products of chlorination and ozonation processes are checked and evaluated by the umu-test. The genotoxicities of the following organic halogenated compounds are clearly detected: Without microsomal activation; m-dichlorobenzene, 1,2,4-trichlorobenzene and bromoform: With microsomal activation; m-dichlorobenzene, dichloroacetic acid, trichloroacetic acid and chloral are detected. From the results on some compounds which are expected to be produced by ozonation, formaldehyde and ionone show positive genotoxicities without microsomal activation, and 5 compounds have positive genotoxicities with microsomal activation; formaldehyde, furfrol, carvone, glyoxal and acrolein. The effects of the concentration on genotoxicities of those chemicals are discussed and compared with the results obtained in other bacterial assays. Some of the selected organic compounds, chloroform and so on, are identified positive genotoxic, which were reported not to be mutagenic in other bacterial assays. As the Quantitative evaluation for genotoxicity on chemical dose, the time of DNA repairing on damaged spots by SOS genes and the induction rate of umu gene are experimentally evaluated.

scholarly journals Bioprospecting of Sechium spp. varieties for the selection of characters with pharmacological activity

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
María Isabel Iñiguez-Luna ◽  
Jorge Cadena-Iñiguez ◽  
Ramón Marcos Soto-Hernández ◽  
Francisco Javier Morales-Flores ◽  
Moisés Cortes-Cruz ◽  
...  
Keyword(s):  
Cell Lines ◽  
Proliferative Activity ◽  
Meta Analysis ◽  
Pearson Correlation ◽  
Statistical Significance ◽  
Economic Value ◽  
Principal Component ◽  
Malignant Cell ◽  
Length Polymorphisms ◽  
Relevant Variables

AbstractBioprospecting identifies new sources of compounds with actual or potential economic value that come from biodiversity. An analysis was performed regarding bioprospecting purposes in ten genotypes of Sechium spp., through a meta-analysis of 20 information sources considering different variables: five morphological, 19 biochemical, anti-proliferative activity of extracts on five malignant cell lines, and 188 polymorphic bands of amplified fragment length polymorphisms, were used in order to identify the most relevant variables for the design of genetic interbreeding. Significant relationships between morphological and biochemical characters and anti-proliferative activity in cell lines were obtained, with five principal components for principal component analysis (SAS/ETS); variables were identified with a statistical significance (< 0.7 and Pearson values ≥ 0.7), with 80.81% of the accumulation of genetic variation and 110 genetic bands. Thirty-nine (39) variables were recovered using NTSYSpc software where 30 showed a Pearson correlation (> 0.5) and nine variables (< 0.05), Finally, using a cladistics analysis approach highlighted 65 genetic bands, in addition to color of the fruit, presence of thorns, bitter flavor, piriform and oblong shape, and also content of chlorophylls a and b, presence of cucurbitacins, and the IC50 effect of chayote extracts on the four cell lines.

scholarly journals Influence of age and gender on the profile of exhaled volatile organic compounds analyzed by an electronic nose

2016 ◽  
Vol 42 (2) ◽  
pp. 143-145 ◽  
Author(s):  
Silvano Dragonieri ◽  
Vitaliano Nicola Quaranta ◽  
Pierluigi Carratu ◽  
Teresa Ranieri ◽  
Onofrio Resta
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Electronic Nose ◽  
Principal Component ◽  
Exhaled Breath ◽  
Age And Gender ◽  
Volatile Organic ◽  
Older Subjects ◽  
Never Smokers ◽  
And Gender

We aimed to investigate the effects of age and gender on the profile of exhaled volatile organic compounds. We evaluated 68 healthy adult never-smokers, comparing them by age and by gender. Exhaled breath samples were analyzed by an electronic nose (e-nose), resulting in "breathprints". Principal component analysis and canonical discriminant analysis showed that older subjects (≥ 50 years of age) could not be distinguished from younger subjects on the basis of their breathprints, as well as that the breathprints of males could not distinguished from those of females (cross-validated accuracy, 60.3% and 57.4%, respectively).Therefore, age and gender do not seem to affect the overall profile of exhaled volatile organic compounds measured by an e-nose.

scholarly journals Genetic Analysis of Patients With Sickle Cell Anemia and Stroke Before 4 Years of Age Suggest an Important Role for Apoliprotein E

2020 ◽  
Vol 13 (5) ◽  
pp. 531-540
Author(s):  
John N. Brewin ◽  
Alexander E. Smith ◽  
Riley Cook ◽  
Sanjay Tewari ◽  
Julie Brent ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Sickle Cell ◽  
Sickle Cell Anemia ◽  
Odds Ratio ◽  
Multiple Testing ◽  
Statistical Significance ◽  
Principal Component ◽  
Population Substructure ◽  
Reference Allele ◽  
Primary Finding

Background: Ischemic stroke is a devastating complication affecting children with sickle cell anemia. Genetic factors are likely to be important in determining the risk of stroke but are poorly defined. Methods: We have studied a cohort of 19 children who had an overt ischemic stroke before 4 years of age. We predicted genetic determinants of stroke would be more prominent in this group. We performed whole exome sequencing on this cohort and applied 2 hypotheses to our variant filtering. First, we looked for strong, potentially mono- or oligogenic variants for ischemic stroke, and second, we considered that more common polygenic variants will be enriched in our cohort. Candidate variants emerging from both strategies were validated in a cohort of 283 patients with sickle cell anemia and known pediatric cerebrovascular outcomes. We used principal component analysis in this cohort to control for relatedness and population substructure. Results: Our primary finding was that the Apoliprotein E genotypes ε2/ε4 and ε4/ ε4, defined by the interplay of rs7412 and rs429358 , were associated with increased stroke risk, with an odds ratio of 4.35 ([95% CI, 1.85–10.0] P =0.0011) for ischemic stroke in the validation cohort. We also found that rs2297518 in NOS (NO synthase) 2 (odds ratio, 2.25 [95% CI, 1.21–4.19]; P =0.014) and rs2230123 in signal transducer and activator of transcription (odds ratio, 2.60 [95% CI, 1.30–5.20]; P =0.009) both had increased odds ratios for ischemic stroke, although these two variants were below the threshold for statistical significance after correction for multiple testing. Conclusions: These data identify new loci for future functional investigations into cerebrovascular disease in sickle cell anemia. Based on African population reference allele frequencies, the Apoliprotein E genotypes would be present in about 10% of children with sickle cell anemia and represent a genetic risk factor that is potentially modifiable by both dietary and pharmaceutical manipulation of its dyslipidemic effects.

AUTOMATION OF MR BRAIN IMAGE CLASSIFICATION FOR MALIGNANCY DETECTION

2019 ◽  
Vol 19 (01) ◽  
pp. 1940002 ◽  
Author(s):  
K. V. AHAMMED MUNEER ◽  
K. PAUL JOSEPH
Keyword(s):  
Brain Tumor ◽  
Nearest Neighbor ◽  
Statistical Significance ◽  
Principal Component ◽  
Feature Reduction ◽  
Brain Atlas ◽  
Significant Feature ◽  
Support Vector ◽  
Brain Images ◽  
Mr Brain

Magnetic resonance imaging (MRI) plays an integral role among the advanced techniques for detecting a brain tumor. The early detection of brain tumor with proper automation algorithm results in assisting oncologists to make easy decisions for diagnostic purposes. This paper presents an automatic classification of MR brain images in normal and malignant conditions. The feature extraction is done with gray-level co-occurrence matrix, and we proposed a feature reduction technique based on statistical test which is preceded by principal component analysis (PCA). The main focus of the work is to establish the statistical significance of the features obtained after PCA, thereby selecting significant feature values for subsequent classification. For that, a [Formula: see text]-test is performed which yielded a [Formula: see text]-value of 0.05. Finally, a comparative study using [Formula: see text]-nearest neighbor (kNN), support vector machine and artificial neural network (ANN)-based supervised classifiers is performed. In this work, we could achieve reasonably good sensitivity, specificity and accuracy for all the classifiers. The ANN classifier gives better performance with sensitivity of 97.33%, specificity of 97.42% and accuracy of 98.66% on the whole brain atlas database. The experimental results obtained are comparable to the other recent state-of-the-art.

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