Effect of nitrate supplementation on oxygen saturation levels for acute mountain sickness prevention: A systematic review and meta-analysis.

PURPOSE: This study aimed to systematically review the effect of nitrate supplementation on blood oxygen saturation. METHODS: We searched PubMed, Scopus, and Cochrane Library databases from their inception up to October 2022. Two reviewers independently conducted two stages of the screening process to include a randomized controlled trial with nitrate supplementation versus placebo intervention assessing oxygen saturation among lowlanders going to either real or simulated high altitude environments. We used the Cochrane Risk of Bias 2.0 tool to assess the risk of bias in the included studies. Fixed-effect model meta-analyses were conducted for laboratory-based studies. Random-effect meta-analyses were conducted for real-world studies. RESULTS: We found 7 trials that met the eligibility criteria. A meta-analysis of studies with some bias concerns showed an increase of 1.26 % in the SpO2 with 44 % I2 during submaximal exercise at simulated high altitudes (GRADE: low). On the contrary, a meta-analysis of studies without heterogeneity showed that nitrate supplementation aggravated oxygen saturation decline (-2.64 %, p = 0.03, GRADE: high) during rest in real high-altitude environments. A meta-analysis also showed that nitrate supplementation did not affect Acute Mountain Sickness (AMS) symptoms (GRADE: high). CONCLUSION: Our results suggest that nitrate supplementation did not provide benefits for AMS prevention during rest at high altitudes. The low-quality evidence showing small beneficial effects of nitrate supplementation during exercise calls for further studies.

UHPLC-Q-Orbitrap HR-MS-Based Metabolomics for Profiling the Sida rhombifolia Metabolites with Different Plant Organs and Cultivation Ages.

Plant organs and cultivation ages can result in different compositions and concentration levels of plant metabolites. The metabolite profile of plants can be determined using liquid chromatography. This study determined the metabolite profiles of leaves, stems, and roots of Sida rhombifolia at different cultivation ages at 3, 4, and 5 months post-planting (MPP) using liquid chromatography-mass spectrometry/mass spectrometry (LC/MS/MS). The results identified that 41 metabolites in S. rhombifolia extract for all plant organs and cultivation ages. We successfully identified approximately 36 (leaves), 22 (stems), and 18 (roots) compounds in all extract. Using principal component analysis (PCA) with peak area as the variable, we clustered all sample extracts based on plant organs and cultivation ages. As a result of PCA, S. rhombifolia extracts were grouped according to plant organs and cultivation ages. In conclusion, a clear difference in the composition and concentration levels of metabolites was observed in the leaves, stems, and roots of S. rhombifolia harvested at 3-, 4-, and 5-MPP.

Analysis of Pork in Beef Sausages Using LC-Orbitrap HRMS Untargeted Metabolomics Combined with Chemometrics for Halal Authentication Study.

Beef sausage (BS) is one of the most favored meat products due to its nutrition and good taste. However, for economic purposes, BS is often adulterated with pork by unethical players. Pork consumption is strictly prohibited for religions including Islam and Judaism. Therefore, advanced detection methods are highly required to warrant the halal authenticity of BS. This research aimed to develop a liquid chromatography-high-resolution mass spectrometry (LC-HRMS) method to determine the halal authenticity of BS using an untargeted metabolomics approach. LC-HRMS was capable of detecting various metabolites in BS and BS containing pork. The presence of pork in BS could be differentiated using principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) with high accuracy. PLS-DA perfectly classified authentic BS and BS containing pork in all concentration levels of pork with R2X = (0.821), R2Y(= 0.984), and Q2 = (0.795). The level of pork in BS was successfully predicted through partial least squares (PLS) and orthogonal PLS (OPLS) chemometrics. Both models gave high R2 (>0.99) actual and predicted values as well as few errors, indicating good accuracy and precision. Identification of discriminating metabolites' potential as biomarker candidates through variable importance for projections (VIP) value revealed metabolites of 2-arachidonyl-sn-glycero-3-phosphoethanolamine, 3-hydroxyoctanoylcarnitine, 8Z,11Z,14Z-eicosatrienoic acid, D-(+)-galactose, oleamide, 3-hydroxyhexadecanoylcarnitine, arachidonic acid, and α-eleostearic acid as good indicators to detect pork. It can be concluded that LC-HRMS metabolomics combined with PCA, PLS-DA, PLS, and OPLS was successfully used to detect pork adulteration in beef sausages. The results imply that LC-HRMS untargeted metabolomics in combination with chemometrics is a promising alternative as an analytical technique to detect pork in sausage products. Further analysis of larger samples is required to warrant the reproducibility.

Application of Chromatographic and Spectroscopic-Based Methods for Analysis of Omega-3 (ω-3 FAs) and Omega-6 (ω-6 FAs) Fatty Acids in Marine Natural Products.

Omega-3 fatty acids v(ω-3 FAs) such as EPA (eicosapentaenoic acid) and DHA (docosahexaenoic acid) and omega-6 fatty acids (ω-6 FAs) such as linoleic acid and arachidonic acid are important fatty acids responsible for positive effects on human health. The main sources of ω-3 FAs and ω-6 FAs are marine-based products, especially fish oils. Some food, supplements, and pharmaceutical products would include fish oils as a source of ω-3 FAs and ω-6 FAs; therefore, the quality assurance of these products is highly required. Some analytical methods mainly based on spectroscopic and chromatographic techniques have been reported. Molecular spectroscopy such as Infrared and Raman parallel to chemometrics has been successfully applied for quantitative analysis of individual and total ω-3 FAs and ω-6 FAs. This spectroscopic technique is typically applied as the alternative method to official methods applying chromatographic methods. Due to the capability to provide the separation of ω-3 FAs and ω-6 FAs from other components in the products, gas and liquid chromatography along with sophisticated detectors such as mass spectrometers are ideal analytical methods offering sensitive and specific results that are suitable for routine quality control.

Metabolite Fingerprinting Based on 1H-NMR Spectroscopy and Liquid Chromatography for the Authentication of Herbal Products.

Herbal medicines (HMs) are regarded as one of the traditional medicines in health care to prevent and treat some diseases. Some herbal components such as turmeric and ginger are used as HMs, therefore the identification and confirmation of herbal use are very necessary. In addition, the adulteration practice, mainly motivated to gain economical profits, may occur by substituting the high price of HMs with lower-priced ones or by addition of certain chemical constituents known as Bahan Kimia Obat (chemical drug ingredients) in Indonesia. Some analytical methods based on spectroscopic and chromatographic methods are developed for the authenticity and confirmation of the HMs used. Some approaches are explored during HMs authentication including single-component analysis, fingerprinting profiles, and metabolomics studies. The absence of reference standards for certain chemical markers has led to exploring the fingerprinting approach as a tool for the authentication of HMs. During fingerprinting-based spectroscopic and chromatographic methods, the data obtained were big, therefore the use of chemometrics is a must. This review highlights the application of fingerprinting profiles using variables of spectral and chromatogram data for authentication in HMs. Indeed, some chemometrics techniques, mainly pattern recognition either unsupervised or supervised, were applied for this purpose.

Detection of Pork in Beef Meatballs Using LC-HRMS Based Untargeted Metabolomics and Chemometrics for Halal Authentication.

Adulteration of high-quality meat products using lower-priced meats, such as pork, is a crucial issue that could harm consumers. The consumption of pork is strictly forbidden in certain religions, such as Islam and Judaism. Therefore, the objective of this research was to develop untargeted metabolomics using liquid chromatography-high resolution mass spectrometry (LC-HRMS) combined with chemometrics for analysis of pork in beef meatballs for halal authentication. We investigated the use of non-targeted LC-HRMS as a method to detect such food adulteration. As a proof of concept using six technical replicates of pooled samples from beef and pork meat, we could show that metabolomics using LC-HRMS could be used for high-throughput screening of metabolites in meatballs made from beef and pork. Chemometrics of principal component analysis (PCA) was successfully used to differentiate beef meatballs and pork meatball samples. Partial least square-discriminant analysis (PLS-DA) clearly discriminated between halal and non-halal beef meatball samples with 100% accuracy. Orthogonal projection to latent structures-discriminant analysis (OPLS-DA) perfectly discriminated and classified meatballs made from beef, pork, and a mixture of beef-pork with a good level of fitness (R2X = 0.88, R2Y = 0.71) and good predictivity (Q2 = 0.55). Partial least square (PLS) and orthogonal PLS (OPLS) were successfully applied to predict the concentration of pork present in beef meatballs with high accuracy (R2 = 0.99) and high precision. Thirty-five potential metabolite markers were identified through VIP (variable important for projections) analysis. Metabolites of 1-(1Z-hexadecenyl)-sn-glycero-3-phosphocholine, acetyl-l-carnitine, dl-carnitine, anserine, hypoxanthine, linoleic acid, and prolylleucine had important roles for predicting pork in beef meatballs through S-line plot analysis. It can be concluded that a combination of untargeted metabolomics using LC-HRMS and chemometrics is promising to be developed as a standard analytical method for halal authentication of highly processed meat products.

Metabolite Fingerprinting Using 1H-NMR Spectroscopy and Chemometrics for Classification of Three Curcuma Species from Different Origins.

Curcuma longa, Curcuma xanthorrhiza, and Curcuma manga have been widely used for herbal or traditional medicine purposes. It was reported that turmeric plants provided several biological activities such as antioxidant, anti-inflammatory, hepatoprotector, cardioprotector, and anticancer activities. Authentication of the Curcuma species is important to ensure its authenticity and to avoid adulteration practices. Plants from different origins will have different metabolite compositions because metabolites are affected by soil nutrition, climate, temperature, and humidity. 1H-NMR spectroscopy, principal component analysis (PCA), and orthogonal projections to latent structures-discriminant analysis (OPLS-DA) were used for authentication of C. longa, C. xanthorrhiza, and C. manga from seven different origins in Indonesia. From the 1H-NMR analysis it was obtained that 14 metabolites were responsible for generating classification model such as curcumin, demethoxycurcumin, alanine, methionine, threonine, lysine, alpha-glucose, beta-glucose, sucrose, alpha-fructose, beta-fructose, fumaric acid, tyrosine, and formate. Both PCA and OPLS-DA model demonstrated goodness of fit (R2 value more than 0.8) and good predictivity (Q2 value more than 0.45). All OPLS-DA models were validated by assessing the permutation test results with high value of original R2 and Q2. It can be concluded that metabolite fingerprinting using 1H-NMR spectroscopy and chemometrics provide a powerful tool for authentication of herbal and medicinal plants.

Assessment of the effect of polymers combination and effervescent component on the drug release of swellable gastro-floating tablet formulation through compartmental modeling-based approach.

The aim of this research was to assess the effect of polymer blend and effervescent components on the floating and swelling behaviors of swellable gastro-floating formulation as well as the drug release through a compartmental modeling analysis. Swellable gastro-floating formulation of freely water-soluble drug, metformin HCl as a drug model, was formulated and developed using D-optimal design. Polymer combination between interpolymer complex (IPC) (poly-vinyl acetate-copolymer methacrylate) and hydroxy propyl methyl cellulose (HPMC), and effervescent components were studied and optimized in this work. Several factors affecting the drug release behavior were determined e.g. swelling behavior, erosion behavior, and floating behavior were studied as well as the drug release through compartmental modeling analysis. The results revealed that the hydrophilic polymer was responsible for gas entrapment formed from effervescent reaction, meanwhile IPC contributed on maintaining the swollen matrix integrity through intermolecular polymer interaction. In addition, effervescent components played fundamental role in the formation of porous system as well as inducing burst release effect. Compartmental modeling provided different outlook about the drug release. Presence of IPC at a high proportion (10-15%) of the polymer blend modulated the changes of pattern of the drug release kinetics and mechanism. Finally, compartmental modeling-based approach was more adequate to describe the drug release kinetics and mechanism compared to the monophasic equation model correlating with process understanding of the drug release from swellable gastro-floating formulation.

The Application of Molecular Spectroscopy in Combination with Chemometrics for Halal Authentication Analysis: A Review.

Halal is an Arabic term used to describe any components allowed to be used in any products by Muslim communities. Halal food and halal pharmaceuticals are any food and pharmaceuticals which are safe and allowed to be consumed according to Islamic law (Shariah). Currently, in line with halal awareness, some Muslim countries such as Indonesia, Malaysia, and Middle East regions have developed some standards and regulations on halal products and halal certification. Among non-halal components, the presence of pig derivatives (lard, pork, and porcine gelatin) along with other non-halal meats (rat meat, wild boar meat, and dog meat) is typically found in food and pharmaceutical products. This review updates the recent application of molecular spectroscopy, including ultraviolet-visible, infrared, Raman, and nuclear magnetic resonance (NMR) spectroscopies, in combination with chemometrics of multivariate analysis, for analysis of non-halal components in food and pharmaceutical products. The combination of molecular spectroscopic-based techniques and chemometrics offers fast and reliable methods for screening the presence of non-halal components of pig derivatives and non-halal meats in food and pharmaceutical products.

The Authentication of Java Turmeric (Curcuma xanthorrhiza) Using Thin Layer Chromatography and 1H-NMR Based-Metabolite Fingerprinting Coupled with Multivariate Analysis.

The identification of adulteration practices of medicinal plants used as herbal medicine is very important to ensure the quality, safety, and efficacy. In this study, thin layer chromatography (TLC) and proton nuclear magnetic resonance (1H-NMR)-based metabolite fingerprinting coupled with multivariate analysis were used for authentication of Curcuma xanthorrhiza extract from Curcuma aeruginosa. Curcumin contents obtained from C. xanthorrhiza extract from various regions were in the range of 0.74%-1.23%. Meanwhile, curcumin contents obtained from C. xanthorrhiza extract adulterated with 0%, 10%, 25%, 40%, 50%, and 75% of C. aeruginosa were 1.02%, 0.96%, 0.86%, 0.69%, 0.43%, and 0.27%, respectively. The decreasing of curcumin contents in adulterant concentrations of 40% and more in C. xanthorrhiza rhizome could indicate the adulteration with other rhizomes. Multivariate analysis of PCA (principal component analysis) using data set obtained from 1H-NMR spectra clearly discriminated pure and adulterated C. xanthorrhiza with C. aeruginosa. OPLS-DA (orthogonal projections to latent structures-discriminant analysis) successfully classified pure and adulterated C. xanthorrhiza with higher R2X (0.965), R2Y (0.958), and Q2(cum) (0.93). It can be concluded that 1H-NMR-based metabolite fingerprinting coupled with PCA and OPLS-DA offers an adequate method to assess adulteration practice and to evaluate the authentication of C. xanthorrhiza extracts.

Comprehensive Review on Application of FTIR Spectroscopy Coupled with Chemometrics for Authentication Analysis of Fats and Oils in the Food Products.

Currently, the authentication analysis of edible fats and oils is an emerging issue not only by producers but also by food industries, regulators, and consumers. The adulteration of high quality and expensive edible fats and oils as well as food products containing fats and oils with lower ones are typically motivated by economic reasons. Some analytical methods have been used for authentication analysis of food products, but some of them are complex in sampling preparation and involving sophisticated instruments. Therefore, simple and reliable methods are proposed and developed for these authentication purposes. This review highlighted the comprehensive reports on the application of infrared spectroscopy combined with chemometrics for authentication of fats and oils. New findings of this review included (1) FTIR spectroscopy combined with chemometrics, which has been used to authenticate fats and oils; (2) due to as fingerprint analytical tools, FTIR spectra have emerged as the most reported analytical techniques applied for authentication analysis of fats and oils; (3) the use of chemometrics as analytical data treatment is a must to extract the information from FTIR spectra to be understandable data. Next, the combination of FTIR spectroscopy with chemometrics must be proposed, developed, and standardized for authentication and assuring the quality of fats and oils.

Reducing Burst Release Effect of Freely Water-Soluble Drug Incorporated into Gastro-Floating Formulation Below HPMC Threshold Concentration Through Interpolymer Complex.

Undesired-burst release effect is observed in a freely water-soluble drug formulated into a gastro-floating formulation with effervescent (GFFE) delivery system. In order to address this limitation, interpolymer complex (IPC) of two swellable and non-soluble polymers, poly-ammonium methacrylate and poly-vinyl acetate, was incorporated into hydroxypropyl methyl cellulose (HPMC)-based matrix GFFE. This research studied the effect and interaction of the IPC-HPMC blending on the drug release of GFFE using a freely water-soluble drug, metformin HCl, under different threshold concentration levels and curing effect. The interaction between the IPC and HPMC was characterized using vibrational spectroscopy and thermal analyses under curing and swelling conditions. Anti-solvent followed by lyophilization had better physicochemical and physicomechanic properties than spray dying technique. The interaction was observed by a specific shifting of the vibrational peaks and alteration of the thermal behavior pattern. These effects altered the drug release behavior. Thereafter, the IPC reduced burst release effects in the initial time and during testing, and the IPC improved the HPMC matrix robustness under mechanical stress testing below threshold concentration of HPMC matrix formulated in the GFFE.

Identification of Pork Contamination in Meatballs of Indonesia Local Market Using Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) Analysis.

This research applied and evaluated a polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) using cytochrome b gene to detect pork contamination in meatballs from local markets in Surabaya and Yogyakarta regions, Indonesia. To confirm the effectiveness and specificity of this fragment, thirty nine DNA samples from different meatball shops were isolated and amplified, and then the PCR amplicon was digested by BseDI restriction enzyme to detect the presence of pork in meatballs. BseDI restriction enzyme was able to cleave porcine cytochrome b gene into two fragments (131 bp and 228 bp). Testing the meatballs from the local market showed that nine of twenty meatball shops in Yogyakarta region were detected to have pork contamination, but there was no pork contamination in meatball shops in Surabaya region. In conclusion, specific PCR amplification of cytochrome b gen and cleaved by BseDI restriction enzymes seems to be a powerful technique for the identification of pork presence in meatball because of its simplicity, specificity and sensitivity. Furthermore, pork contamination intended for commercial products of sausage, nugget, steak and meat burger can be checked. The procedure is also much cheaper than other methods based on PCR, immunodiffusion and other techniques that need expensive equipment.

Analysis of dog meat adulteration in beef meatballs using non-targeted UHPLC-Orbitrap HRMS metabolomics and chemometrics for halal authentication study.

Due to the different price and high quality, halal meat such as beef can be adulterated with non-halal meat with low price to get an economical price. The objective of this research was to develop an analytical method for halal authentication testing of beef meatballs (BM) from dog meat (DM) using a non-targeted metabolomics approach employing liquid chromatography-high-resolution mass spectrometry (LC-HRMS) and chemometrics. The differentiation of authentic BM from that adulterated with DM was successfully performed using partial least square-discriminant analysis (PLS-DA) with high accuracy (R2X = 0.980, and R2Y = 0.980) and good predictivity (Q2 = 0.517). In addition, partial least square (PLS) and orthogonal PLS (OPLS) were successfully used to predict the DM added (% w/w) in BM with high accuracy (R2 > 0.990). A number of metabolites, potential for biomarker candidates, were identified to differentiate BM and that adulterated with DM. It showed that the combination of a non-targeted LC-HRMS Orbitrap metabolomics and chemometrics could detect up to 0.1% w/w of DM adulteration. The developed method was successfully applied for analysis of commercial meatball samples (n = 28). Moreover, pathway analysis revealed that beta-alanine, histidine, and ether lipid metabolism were significantly affected by dog meat adulteration. In summary, this developed method has great potential to be developed and used as an alternative method for analysis of non-halal meats in halal meat products.

The combination of Fourier-transform infrared spectroscopy with pattern recognition techniques for classification and discrimination of red snapper fish oils.

Fish oils are good sources for essential fatty acids such as omega-3 and omega-6 fatty acids needed to human growth. Indonesia is rich in fish species and among this, red snapper fish (Lutjanus sp.) can be extracted to get red snapper fish oils (RSFOs). The aim of this study was to classify and discriminate RSFO from different origins using Fourier-transform infrared (FTIR) spectra and pattern recognition techniques. All of the RSFO's FTIR spectra were very similar. The FTIR vibrations showed the presence of triglycerides as the main composition in fish oils. Principal component analysis (PCA) could separate the RSFO according to sample origin. Supervised pattern recognition of partial least square-discriminant analysis (PLS-DA) and sparse PLS-DA (sPLS-DA) successfully discriminated and classified different Lutjanus species of fish oils obtained from different origins. The vibration of functional groups at 1711, 1653, 1745, and 3012 per cm were considered for their important contributions in discriminating of Lutjanus species (variable importance in projection, variable importance in the projection score >1). Fish oils obtained from the same species were classified into the same class indicating similar chemical compositions. Among the three pattern recognition techniques used, sPLS-DA offers the best model for the discrimination and classification of Lutjanus fish oils. It can be concluded that FTIR spectroscopy in combination with the pattern recognition technique is the potential to be used for of fish oil authentication to verify the quality of the fish oils. It can be further developed as a rapid and effective method for fish oil authentication.

Untargeted metabolomics using liquid chromatography-high resolution mass spectrometry and chemometrics for analysis of non-halal meats adulteration in beef meat.

OBJECTIVE: The adulteration of raw beef (BMr) with dog meat (DMr) and pork (PMr) becomes a serious problem because it is associated with halal status, quality, and safety of meats. This research aimed to develop an effective authentication method to detect non-halal meats (dog meat and pork) in beef using metabolomics approach. METHODS: Liquid chromatography-high resolution mass spectrometry (LC-HRMS) using untargeted approach combined with chemometrics was applied for analysis non-halal meats in BMr. RESULTS: The untargeted metabolomics approach successfully identified various metabolites in BMr DMr, PMr, and their mixtures. The discrimination and classification between authentic BMr and those adulterated with DMr and PMr were successfully determined using partial least square-discriminant analysis (PLS-DA) with high accuracy. All BMr samples containing non-halal meats could be differentiated from authentic BMr. A number of discriminating metabolites with potential as biomarkers to discriminate BMr in the mixtures with DMr and PMr could be identified from the analysis of variable importance for projection value. Partial least square (PLS) and orthogonal PLS (OPLS) regression using discriminating metabolites showed high accuracy (R2>0.990) and high precision (both RMSEC and RMSEE <5%) in predicting the concentration of DMr and PMr present in beef indicating that the discriminating metabolites were good predictors. The developed untargeted LC-HRMS metabolomics and chemometrics successfully identified non-halal meats adulteration (DMr and PMr) in beef with high sensitivity up to 0.1% (w/w). CONCLUSION: A combination of LC-HRMS untargeted metabolomic and chemometrics promises to be an effective analytical technique for halal authenticity testing of meats. This method could be further standardized and proposed as a method for halal authentication of meats.

Validation and Collaborative Studies of Headspace Gas Chromatography-Mass Spectrometry (HS GC-MS) for Determination of 1,4-Dioxane in Cosmetic Samples.

BACKGROUND: 1,4-Dioxane (1,4-D) is a by-product of the synthesis of surfactants, typically found in some cosmetics products such as shampoo, toothpaste, and soap. The presence of 1,4-D in cosmetics products is limited to certain amount since 1,4-D is classified as a probable human carcinogen. OBJECTIVE: This present study was intended to validate static headspace gas chromatography-mass spectrometry (HS GC-MS) for the determination of 1,4-D in cosmetics products. METHODS: The condition of headspace and GC-MS was optimized to get the best condition for analysis of 1,4-D using 1,4-Dioxane-d8 (1,4-D-d8) as internal standard (IS). The developed method was validated by evaluating the key performance characteristics, including specificity, linearity, limit of detection (LoD), limit of quantification (LoQ), accuracy, and precision. RESULTS: The results showed that HS GC-MS was specific since the peaks of the selected ion monitoring (SIM) mode could be separated and confirmed at m/z 88 and m/z 96 for 1,4-D and 1,4-D-d8, respectively. The method was linear over the concentration range of 0.1287-1.2875 µg/mL, with R2 > 0.999 and RSD residuals < 2.0. A collaborative study were conducted on this method, with ten participating laboratories from four countries. The outcome of this study was found to be accurate and precise, as evidenced by the excellent recoveries ranged from 94.6-102.1% and with good reproducibility with RSD values ranged from 0.2-1.1%. The collaborative studies exhibited that all data reported by ten participating laboratories in four countries were inliers without any extreme values observed either in mean or RSD values. CONCLUSION: This HS GC-MS is found to be fit and suitable for the determination of trace level of 1,4-D in cosmetics products. HIGHLIGHTS: HS GC-MS method could be proposed as a standard method for quantitative analysis of 1,4-D in cosmetics products since the collaborative studies indicated that the developed method meet the requirement in "Guidelines for Collaborative Study Procedures to Validate Characteristics of a Method of Analysis".

Authentication of Nigella sativa seed oil in binary and ternary mixtures with corn oil and soybean oil using FTIR spectroscopy coupled with partial least square.

Fourier transform infrared spectroscopy (FTIR) combined with multivariate calibration of partial least square (PLS) was developed and optimized for the analysis of Nigella seed oil (NSO) in binary and ternary mixtures with corn oil (CO) and soybean oil (SO). Based on PLS modeling performed, quantitative analysis of NSO in binary mixtures with CO carried out using the second derivative FTIR spectra at combined frequencies of 2977-3028, 1666-1739, and 740-1446 cm(-1) revealed the highest value of coefficient of determination (R (2), 0.9984) and the lowest value of root mean square error of calibration (RMSEC, 1.34% v/v). NSO in binary mixtures with SO is successfully determined at the combined frequencies of 2985-3024 and 752-1755 cm(-1) using the first derivative FTIR spectra with R (2) and RMSEC values of 0.9970 and 0.47% v/v, respectively. Meanwhile, the second derivative FTIR spectra at the combined frequencies of 2977-3028 cm(-1), 1666-1739 cm(-1), and 740-1446 cm(-1) were selected for quantitative analysis of NSO in ternary mixture with CO and SO with R (2) and RMSEC values of 0.9993 and 0.86% v/v, respectively. The results showed that FTIR spectrophotometry is an accurate technique for the quantitative analysis of NSO in binary and ternary mixtures with CO and SO.

Cytotoxicity Activity, Metabolite Profiling, and Isolation Compound from Crude Hexane Extract of Cleome rutidospermae.

OBJECTIVE: This study isolated the chemical compounds and evaluated the cytotoxic activity of the crude hexane extract of Cleome rutidospermae herb (CRH). METHODS: The isolate was purified using silica gel, column chromatography, and preparative thin layer chromatography (PTLC). Furthermore, the structure of the compounds was identified by spectroscopic methods using 1D, 2D NMR, and mass spectrometry. The cytotoxic activity of CRH at a concentration of 20 ug/mL was also tested against MCF-7, A549, KB, KB-VIN, and MDA-MB-231 cancer cells using the sulforhodamine B (SRB) method. RESULTS: The CRH contained compounds of unsaturated fatty acid, saturated fatty acid, lipid, glycerol, ω-3 fatty acid, and cholesterol. Two compounds were obtained from the plant, and their structures were identified as (1) Stigmasta-5,22-dien-3-ol (STML) and (2) 1,2-Benzene dicarboxylic acid, 1,2-bis (2-Ethylhexyl) esters (DEHP). These compounds were reported in this plant for the first time. In comparison, CRH had % growth inhibition in the proliferation of MCF-7 cells up to 28.1%, with cancer cells A549, KB, KB-VIN, and MDA-MB-231 by >50% Compared to the negative DMSO of 0.20%, while the positive control could inhibit the growth of all cancer cells (100%). CONCLUSION: Our findings suggested that crude herb from the plant CRH was the potential for breast cancer treatment.

Quantification and classification of corn and sunflower oils as adulterants in olive oil using chemometrics and FTIR spectra.

Commercially, extra virgin olive oil (EVOO) is subjected to be adulterated with low-price oils having similar color to EVOO. Fourier transform infrared (FTIR) spectroscopy combined with chemometrics has been successfully used for classification and quantification of corn (CO) and sunflower oils (SFOs) in EVOO sets. The combined frequency regions of 3027-3000, 1076-860, and 790-698 cm(-1) were used for classification and quantification of CO in EVOO; meanwhile, SFO was analyzed using frequency regions of 3025-3000 and 1400-985 cm(-1). Discriminant analysis can make classification of pure EVOO and EVOO adulterated with CO and SFO with no misclassification reported. The presence of CO in EVOO was determined with the aid of partial least square calibration using FTIR normal spectra. The calibration and validation errors obtained in CO's quantification are 0.404 and 1.13%, respectively. Meanwhile, the first derivative FTIR spectra and PLS calibration model were preferred for quantification of SFO in EVOO with high coefficient of determination (R(2)) and low errors, either in calibration or in validation sample sets.