Differences In Peak Area Research Articles

Infrared spectroscopic evaluation for catalytic hydrogenation of biomass and coal using unsupervised and supervised algorithms

Three biomass (rice straw, rice husk and wheat straw) and three coal samples (lignite, subbituminous coal and bituminous coal) were extracted via a thermal dissolution (TD) process, and the TD extracts were treated by catalytic hydrogenation to obtain reaction products. To reveal the similarity in molecular information among the samples and elucidate their chemical reactivity, four machine learning algorithms were applied to analyze the Fourier transform infrared spectra of both TD extracts and catalytic hydrogenation products. Functional groups were used as variables and the difference in peak area can be treated as the basis for sample classification. Aromatic CH, COC, aliphatic CH2 or CH3 and aromatic CO or CC bonds were the main characteristic variables in principal component analysis algorithm to classify biomass- and coal-derivated samples. These samples were also grouped into four clusters by hierarchical clustering analysis algorithm according to the similarity and difference in the distribution of functional groups. For artificial neural network algorithm, aliphatic CH and OH bonds are the most important variables to classify these samples into four groups, and aromatic CH, OH, and COC groups are the main variables contributed to the classification trees in random forest algorithm. Machine learning algorithms will provide methodological guidance for the data mining of the spectra of complex organic systems.

Insights into the Effects of Violating Statistical Assumptions for Dimensionality Reduction for Chemical "-omics" Data with Multiple Explanatory Variables.

Biological volatilome analysis is inherently complex due to the considerable number of compounds (i.e., dimensions) and differences in peak areas by orders of magnitude, between and within compounds found within datasets. Traditional volatilome analysis relies on dimensionality reduction techniques which aid in the selection of compounds that are considered relevant to respective research questions prior to further analysis. Currently, compounds of interest are identified using either supervised or unsupervised statistical methods which assume the data residuals are normally distributed and exhibit linearity. However, biological data often violate the statistical assumptions of these models related to normality and the presence of multiple explanatory variables which are innate to biological samples. In an attempt to address deviations from normality, volatilome data can be log transformed. However, whether the effects of each assessed variable are additive or multiplicative should be considered prior to transformation, as this will impact the effect of each variable on the data. If assumptions of normality and variable effects are not investigated prior to dimensionality reduction, ineffective or erroneous compound dimensionality reduction can impact downstream analyses. It is the aim of this manuscript to assess the impact of single and multivariable statistical models with and without the log transformation to volatilome dimensionality reduction prior to any supervised or unsupervised classification analysis. As a proof of concept, Shingleback lizard (Tiliqua rugosa) volatilomes were collected across their species distribution and from captivity and were assessed. Shingleback volatilomes are suspected to be influenced by multiple explanatory variables related to habitat (Bioregion), sex, parasite presence, total body volume, and captive status. This work determined that the exclusion of relevant multiple explanatory variables from analysis overestimates the effect of Bioregion and the identification of significant compounds. The log transformation increased the number of compounds that were identified as significant, as did analyses that assumed that residuals were normally distributed. Among the methods considered in this work, the most conservative form of dimensionality reduction was achieved through analyzing untransformed data using Monte Carlo tests with multiple explanatory variables.

Quantitative LC-MS/MS. 1. Impact of Points across a Peak on the Accuracy and Precision of Peak Area Measurements.

The number of points across a chromatographic peak has long been recognized as a key determinant of the accuracy and precision of the measured peak area. In LC-MS-based quantitation experiments in drug discovery and development, the "rule-of-thumb" has been to use 15 or more points. This "rule" is based on the literature describing chromatographic methods where the goal was to achieve the lowest possible imprecision in the measurements, especially when unknown analytes are being detected. Restricting methods to the requirement of at least 15 points across a peak can be detrimental to the development methods that fully optimize the signal-to-noise ratio for the assay using longer dwell times and/or transition summing. This study aims to show that 7 points across the peak for peaks that are 9 s or less wide provide more than sufficient accuracy and precision for drug quantitation studies. Data from simulated Gaussian curves using a sampling interval of 7 points across the peak gave peak area calculations within 1% of the expected total peak area using the Trapezoidal and Riemann rules and 0.6% for the Simpson rule. Low and high concentration samples (n = 5) were assayed using three different LC methods on three different days on two different instruments (API5000 and API5500). The difference in peak area (%ΔPA) and relative standard deviation of the peak areas (%RSD) was less than ∼5%. No significant difference was observed from the data that were obtained from different sampling intervals, different peak widths, different days, different peak sizes, and different instruments. Three core analytical runs were performed on three different days. In each core run, the lower limit of quantitation (LLOQ, n = 5), low quality control (LQC, n = 5), middle quality control (MQC, n = 5), and high-quality control samples (HQC, n = 5) were processed and run simultaneously with a standard curve. The range of the intra- and interday accuracy and precision for 3 core runs was 98.0-105% and 0.9-3.0% for 7 data points and 97.5-105% and 0.8-4.3% for 17 data points, respectively. No significant difference was observed for the different sampling intervals. The results show a sampling interval of 7 points for peaks up to 9 s wide is sufficient to define a peak accurately and precisely for drug quantitation studies in drug discovery and development.

Increasing accuracy of field-scale studies to investigate plant uptake and soil dissipation of pharmaceuticals.

Pharmaceuticals and personal care products (PPCPs) can enter agricultural fields through wastewater irrigation, biosolid amendments, or urine fertilization. Numerous studies have assessed the risk of PPCP contamination, however there are no standardized methodologies for sample treatment, making the interpretation of results challenging. Various time periods between sampling and analysis have been reported (shipping, storage, etc.), but literature is lacking in the evaluation of PPCP degradation amidst this process. This study assessed the stability of 20 pharmaceuticals (200 μg L-1) in soil and crops stored at -40 °C for 7, 30, and 310 days. After 310 days, caffeine, meprobamate, trimethoprim, primidone, carbamazepine, anhydro-erythromycin and dilantin were found to be stable (≥75% recovery) in all matrices. On the other hand, acetaminophen, amitriptyline, bupropion, lamotrigine, sulfamethoxazole, naproxen, ibuprofen, and paroxetine were unstable after 30 days in at least one of the matrices investigated. Due to variations in analyte stability, fortification with isotopically-labelled surrogates at the point of sample collection was evaluated in comparison to fortification after shipment and storage, immediately prior to extraction. Chromatographic peak areas of stable analytes were found to be reproducible (±15%) in field-fortified samples, indicating that no additional error occurred during sample handling under field conditions despite having a less controlled environment. Unstable analytes revealed notable differences in peak areas between fortification times, suggesting that fortification immediately after sample collection is crucial to account for analyte losses during shipping and storage, resulting in accurate quantification of PPCPs.

Extraction, Analysis, and Antioxidant Activity Evaluation of Phenolic Compounds in Different Italian Extra-Virgin Olive Oils.

The analysis of phenolic compounds in extra virgin olive oils was carried out by high-performance liquid chromatography utilizing photodiode array and mass spectrometry detectors. The chromatographic profile of thirty samples from four Italian Regions highlighted the presence of secoiridoids, phenolic alcohols, flavonoids, and phenolic acid classes. A similar qualitative profile was observed with some differences in peak area and fifteen compounds were tentatively identified. Quantitative analysis was performed by UV detection considering eight standard phenolic compounds. The chromatographic method, after optimization, was validated studying some parameters, e.g., intra-day and inter-day retention time precision, limit of detection, limit of quantification, and linearity. Recovery of the method was performed achieving good results (10 and 50 g·g−1 with recovery of 72.9–92.1% (w/w) and 79.1–102.8% (w/w), respectively). In all samples secoiridoids were the main compounds ranging from 85 to more than 99% (w/w) of the total concentration of detected phenolic compounds while phenolic acids accounted for the lowest percentage (0.1–0.6%, w/w). Finally, total concentration of phenolic compounds and antioxidant activity were determined with different chemical assays. A good and significant correlation among total phenolic compound concentration and antioxidant activity was observed. A significant different phenolic compound concentration and antioxidant activity was determined between samples from Puglia and Sicily. This was studied performing statistical analysis by one-way analysis of variance (ANOVA) followed by Bonferroni post-hoc test.

A Suspect Screening Method for Characterizing Multiple Chemical Exposures among a Demographically Diverse Population of Pregnant Women in San Francisco.

Background:In utero exposure to environmental chemicals can adversely impact pregnancy outcomes and childhood health, but minimal biomonitoring data exist on the majority of chemicals used in commerce.Objectives:We aimed to profile exposure to multiple environmental organic acids (EOAs) and identify novel chemicals that have not been previously biomonitored in a diverse population of pregnant women.Methods:We used liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF/MS) to perform a suspect screen for 696 EOAs, (e.g., phenols and phthalate metabolites) on the maternal serum collected at delivery from 75 pregnant women delivering at two large San Francisco Hospitals. We examined demographic differences in peak areas and detection frequency (DF) of suspect EOAs using a Kruskal-Wallis Rank Sum test or Fisher’s exact test. We confirmed selected suspects by comparison with their respective reference standards.Results:We detected, on average, 56 [standard deviation (SD)]: 8) suspect EOAs in each sample (range: 32–73). Twelve suspect EOAs with were matched to 21 candidate compounds in our EOA database, two-thirds of which are novel chemicals. We found demographic differences in DF for 13 suspect EOAs and confirmed the presence of 6 priority novel chemicals: 2,4-Di-tert-butylphenol, Pyrocatechol, 2,4-Dinitrophenol, 3,5-Di-tert-butylsalicylic acid, 4-Hydroxycoumarin, and 2′-Hydroxyacetophenone (or 3′-Hydroxyacetophenone). The first two are high-production-volume chemicals in the United States.Conclusion:Suspect screening in human biomonitoring provides a viable method to characterize a broad spectrum of environmental chemicals to prioritize for targeted method development and quantification. https://doi.org/10.1289/EHP2920

Adsorption/Desorption of Pesticidal Carboxylate Esters by Switching Liquid Phases on Humic‐Fraction‐Modified Silica Gel Matrix

AbstractA humic‐fraction‐modified silica gel is prepared and used as the adsorbent for various pesticidal carboxylate esters in hexane. The percentage of adsorption, calculated on the basis of the difference in peak areas for most carboxylate esters in hexane, reaches more than 90% in 1 h. The FTIR (Fourier Transform Infrared) Spectroscopy results show that the interaction force leading to the adsorption observed in hexane is dipole‐dipole oriented and is affected negatively both by the steric hindrance created due to the presence of the group near the carbonyl center of esters and the bulky alkyl group attached to an ether linkage. The hydrogen bonding (i.e. strong dipole‐dipole interaction) and π‐π stacking complexation are either absent or the minor force responsible for the adsorption of carboxylate esters in hexane in most cases. Other factors that cause the variation in the percentage of adsorption include the type of liquid phase (e.g. ethyl ether or acetonitrile vs. hexane) and the additive of acidic or basic origin present in the matrix, which renders the desorption approach for analyte adsorbed.

Metabolite profiling on wheat grain to enable a distinction of samples from organic and conventional farming systems

Identification of biomarkers capable of distinguishing organic and conventional products would be highly welcome to improve the strength of food quality assurance. Metabolite profiling was used for biomarker search in organic and conventional wheat grain (Triticum aestivum L.) of 11 different old and new bread wheat cultivars grown in the DOK system comparison trial. Metabolites were extracted using methanol and analysed by gas chromatography-mass spectrometry. Altogether 48 metabolites and 245 non-identified metabolites (TAGs) were detected in the cultivar Runal. Principal component analysis showed a sample clustering according to farming systems and significant differences in peak areas between the farming systems for 10 Runal metabolites. Results obtained from all 11 cultivars indicated a greater influence of the cultivar than the farming system on metabolite concentrations. Nevertheless, a t-test on data of all cultivars still detected 5 metabolites and 11 TAGs with significant differences between the farming systems. Based on individual cultivars, metabolite profiling showed promising results for the categorization of organic and conventional wheat. Further investigations are necessary with wheat from more growing seasons and locations before definite conclusions can be drawn concerning the feasibility to evolve a combined set of biomarkers for organically grown wheat using metabolite profiles.

Rapid screening of natural free radical scavengers in two Polygonum herbs by fast HPLC-DAD-ESI-MSn with precolumn incubation method

A simple and efficient method, i.e. 1,1-diphenyl-2-picrylhydrazyl radical (DPPH) incubation followed by fast HPLC-DAD-ESI-MSn based on novel core–shell particle technology, was proposed for the rapid and high-throughput screening of natural free radical scavengers directly from the crude extract of two Polygonum herbs, P. multiflorum and P. cuspidatum. All of the components in P. multiflorum or P. cuspidatum were well separated within 9 min using the core–shell column, which was much superior to previously reported HPLC methods. After incubation with DPPH, 7 compounds were demonstrated to possess potential free radical scavenging activity. They were identified as gallic acid, cis-2,3,5,4′-tetrahydroxy stilbene-2-O-glucoside and trans-2,3,5,4′-tetrahydroxystilbene-2-O-glucoside from P. multiflorum, together with resveratroloside, piceid, 3,5,4′-trihydroxystilbene-3-O-(6′′-galloyl)-glucoside, and resveratrol in P. cuspidatum. Meanwhile, 3,5,4′-trihydroxystilbene-3-O-(6′′-galloyl)-glucoside showed the strongest scavenging capability, while resveratroloside was the weakest one according to the quantitative difference in peak areas before and after incubation with DPPH. Furthermore, the free radical scavenging activity of five of the pure compounds was further evaluated by a classical DPPH colorimetric assay on a microwell plate for method validation. Collectively, the current work provides a powerful tool for the rapid discovery of natural radical scavengers directly from complex matrices like herbal medicines, and the results could also help to elucidate which components are responsible for the antioxidant activity of two Polygonum herbs.

Adsorption and Desorption of Plasticizers with Humic-Fraction-Immobilized Silica Gel in Hexane: A Facile Approach to Pre-concentration

Humic fraction (HF) collected under acidic conditions and used as an adsorbent for various phosphate-based plasticizers in hexane is immobilized on silica gel. Most plasticizer analytes examined in this study under the same conditions achieved adsorption percentages above 90% in 1 h based on the difference in peak area. The Fourier transform infrared (FTIR) spectroscopy results indicate that the interaction leading to the adsorptions between the functional moieties of the analyte and HF (e.g., the carboxylate group of analyte against the carboxyl group of HF) is specific, reversible, and dipole-dipole-oriented. Moreover, it is significantly enhanced by hexane. However, the π−π interaction (even hydrogen bonding in all cases) was either not as significant or absent in hexane and, therefore, contributed little or nothing to the percentage of adsorption. The interaction is highly affected by the acidic or basic origin of the additive introduced to the liquid phase of the matrix, and it is subject to the steric hindrance effect caused by the bulky alkyl groups attached to ether linkages and the relative position of the two ether bonds on the aromatic moiety of the analyte. The pre-concentration of the analyte and, thus, the recycle of the adsorbent can be achieved by adsorbing and, subsequently, desorbing it in a different solvent, such as acetonitrile. Furthermore, the adsorption process is surface-oriented because of its dependence upon both time and the amount of adsorbent.

Study on fingerprints of chemical constituents of Cinnamomi Ramulus and Cinnamomi Cortex

To compare the difference of chemical constituents of Cinnamomi Ramulus and Cinnamomi Cortex,and study the characteristics of their chemical constituents, in order to provide basis for clinical application and quality control. HPLC fingerprint method was used to analyze chemical constituents of Cinnamomi Ramulus and Cinnamomi Cortex compare the difference between. Cinnamomi Ramulus and Cinnamomi Cortex had similar HPLC fingerprint profiles, but with difference in peak areas of their chemical constituents. Specifically, the average peak areas of cinnamyl alcohol, cinnamic acid and 2-methoxy cinnamic acid were higher than that of Cinnamomi Cortex, whereas the average peak areas of 2-hydroxyl cinnamaldehyde, coumarin, cinnamaldehyde and 2-methoxy cinnamaldehyde in Cinnamomi Cortex were higher than that of Cinnamomi Ramulus. This method can be used for evaluating quality of Cinnamomi Ramulus and Cinnamomi Cortex. The ratio between the peak areas of cinnamaldehyd and cinnamic acid can be used to discriminate most Cinnamomi Ramulus samples (<23) and Cinnamomi Cortex samples (>23). Cinnamomi Ramulus and Cinnamomi Cortex have the similar types of chemical constituents but with difference in content. This study provides reference for the pharmacodynamic difference of Cinnamomi Ramulus and Cinnamomi Cortex.

Determination of polygalacturonic acid content in pectin extracts by diffuse reflectance Fourier transform infrared spectroscopy

Abstract A simple, rapid diffuse reflectance Fourier transform infrared spectroscopy (DRIFTS) method was developed for pectin measurement. Pectin calibration standards were prepared by blending polygalacturonic acid with potassium bromide to cover a range of polygalacturonic acid concentrations (10–98%). A linear relationship between pectin content and total carbonyl absorption band area was found ( R 2 =0.982). Linearity was up to 80% pectin, since there was no significant difference in peak areas of 80% and greater. Pectin contents of various commercial pectin samples were calculated from the linear fit equation. Accuracy of the DRIFTS method was determined by comparing the pectin contents to the values obtained by colorimetric and HPLC methods. For four different sources of samples, the pectin contents by FTIR method were 78.2, 89.4, 65.9 and 67.1%, which were comparable to values obtained by colorimetric analysis (79.1, 87.9, 64.7 and 57.7%) and HPLC (84.1, 91.4, 69.5 and 67.9%).

Identification of gerbera cultivars based on differences in phenolic compounds in ray florets

SummaryA method is described for the identification of gerbera cultivars using HPLC-analysis of phenolic compounds from ray florets. Anthocyanins and flavonoid copigments were analyzed in 65 genotypes. Different criteria for minimum peak area (pamin = 50, 100 or 1000 mVs) and peak matching (maximum difference in peak area, pdmax = factor 2 or 10) were used. The discrimination capacity for anthocyanins ranged from 92.3% of all 2080 pairwise comparisons, using pamin = 50 and pdmax = 2, to 70.5%, using pamin = 1000, pdmax = 10. For flavonoid copigments, the discrimination capacity ranged from 98.9% (pamin = 100, pdmax = 2) to 89.9% (pamin = 100, pdmax = 10). By combining the anthocyanin data (with pamin = 50) and the copigment data (with pamin = 100), using pdmax = 2, a discrimination capacity of 99.5% was obtained. No relation was found between copigment composition and floret colour. For anthocyanins, the yellow and white genotypes formed one cluster. Generally, the reddish and pinkish/purplish genotypes w...

Flavor, Color and Texture of Peanuts Treated with Hydrogen Peroxide1

Abstract Treatment of aflatoxin-contaminated peanut kernels in 0.075% hydrogen peroxide for 1 min has been proposed to reduce aflatoxin contamination by 90%. The effect of hydrogen peroxide treatment on the flavor quality, texture and color was, therefore, investigated. Two hundred grams of peanuts were submerged in a solution containing 0, 0.075 or 0.225% hydrogen peroxide for 1 and 3 min. Treated peanuts were dried to 8-9% moisture, blanched and stored in plastic bags for 0, 1, 2 and 3 weeks at 39 C. Peak areas identified as hexanal increased with increasing hydrogen peroxide concentration, regardless of the treatment and storage time. No significant differences in peak areas identified as ethanol were observed after a 3-week storage time, regardless of the concentration of hydrogen peroxide and treatment time. Hydrogen peroxide treatment and storage of treated peanuts did not significantly affect the lightness (L), chroma (C) and texture of the treated peanuts. Furthermore, sensory analysis conducted on peanut brittle prepared from raw peanuts and peanuts treated with 0.075% hydrogen peroxide for 1 min showed no significant difference between the two samples evaluated.

1] One-dimensional nuclear Overhauser effects and peak intensity measurements

Publisher Summary The nuclear overhauser effect (NOE) can be regarded as a phenomenon in nuclear magnetic resonance (NMR) measurements allowing an experimenter to derive estimates of internuclear distances in molecules as well as information about rotational correlation times. The NOE factor, which was originally determined by the saturation of a neighboring spin with an rf field, is defined as a measure of change in the steady-state description of a nuclear spin system resulting from an external perturbation. There are a number of alternative techniques available for the measurement of NOE factors. The classical one-dimensional technique uses the difference in peak areas as, in which the reference spectrum is measured in the absence of saturating irradiation, or is measured in a region in which there are no resonances. The aim of any experiment is to measure parameters as accurately as possible within a reasonable amount of time. From an experimental point of view, one must pay careful attention to the effects of the rf field on intensity measurements, because it is possible to overload the spectrometer preamplifier and detection system, and because it is possible to partially saturate the resonances giving rise to the peaks. It is impossible to suggest an algorithm for minimizing the effects of systematic errors in peak intensity measurements.

Intra-uterine pressure in dysmenorrhea.

Intra-uterine pressure recordings in normal and dysmenorrheic women during the menstrual period were analysed regarding amplitude, duration, frequency and peak area of contractions and the resting pressure. The activity of the myometrium showed large between subject variability and no significant difference was found, between the two groups in amplitude and duration of contractions or their frequency. However, there was a consistent difference in peak area at the onset of the menses (p less than 0.01) and there was also a significant decrease in peak area during the menses in the group with dysmenorrhea, with maximum uterine work being performed on the day when the pain was at its worst. The contribution of the pattern of contractility to the etiology of dysmenorrhea is discussed. Abnormal uterine activity as a cause of primary dysmenorrhea was first suggested in the 1930s and 1940s on the basis of intra-uterine pressure recordings (Moir, 1936; Woodbury et al., 1947). Since then, intra-uterine pressure has been measured in a number of studies using a micro-balloon (Lundström et al., 1976; Bygdeman et al., 1979). With the introduction of the highly sensitive micro-transducer catheter it has been possible to make accurate quantitative estimations (Akerlund et al., 1978; Ulmsten & Andersson, 1979) but, to our knowledge, no detailed analysis and quantification of intrauterine pressure recordings in primary dysmenorrhea has been reported. In this paper we publish the results of a study in which daily recordings obtained from women suffering from primary dysmenorrhea were compared with those from a group of women with very similar menstrual patterns but with minimal or no symptoms.

Detection and identification of bacteria by gas chromatography.

Ether extracts of cultures of 29 strains representing 6 species of Bacillus, and of individual strains of Escherichia coli, Aerobacter aerogenes, and Pseudomonas aeruginosa were examined in a gas chromatograph by use of flame ionization and electron capture detectors. Among the products detected were compounds with the chromatographic characteristics of acetic, propionic, and butyric acids, ethyl alcohol, diacetyl, acetoin, and 2,3-butanediol. The differences in peak areas of the various products formed by the bacteria were determined statistically for the chromatograms obtained with the two detectors, and the peaks were arranged in order of decreasing areas to yield a signature for each bacterial strain. Different signatures were obtained for the various genera and species and for strains of the same species. B. licheniformis, B. subtilis, and A. aerogenes formed significant quantities of a number of volatile compounds, and qualitative and quantitative differences between strains were noted. The electron capture detector was particularly sensitive to diacetyl and acetoin as well as to unknown compounds. By use of this detector, the presence of 5 pg of diacetyl and 20 pg of acetoin could be demonstrated. The quantity of acetoin detected in B. subtilis and B. licheniformis cultures was present in as little as 6.3 x 10(-3) muliters of medium.

Detection and Identification of Bacteria by Gas Chromatography1

Ether extracts of cultures of 29 strains representing 6 species of Bacillus, and of individual strains of Escherichia coli, Aerobacter aerogenes, and Pseudomonas aeruginosa were examined in a gas chromatograph by use of flame ionization and electron capture detectors. Among the products detected were compounds with the chromatographic characteristics of acetic, propionic, and butyric acids, ethyl alcohol, diacetyl, acetoin, and 2,3-butanediol. The differences in peak areas of the various products formed by the bacteria were determined statistically for the chromatograms obtained with the two detectors, and the peaks were arranged in order of decreasing areas to yield a signature for each bacterial strain. Different signatures were obtained for the various genera and species and for strains of the same species. B. licheniformis, B. subtilis, and A. aerogenes formed significant quantities of a number of volatile compounds, and qualitative and quantitative differences between strains were noted. The electron capture detector was particularly sensitive to diacetyl and acetoin as well as to unknown compounds. By use of this detector, the presence of 5 pg of diacetyl and 20 pg of acetoin could be demonstrated. The quantity of acetoin detected in B. subtilis and B. licheniformis cultures was present in as little as 6.3 x 10(-3) muliters of medium.