Discrimination and authentication of lard blending with palm oil in cosmetic soap formulations.

BACKGROUND: The employment of Fourier transforms infrared (FT-IR) spectroscopy combined with chemometrics for determination and quantification of lard in a binary blend with palm oil in a cosmetic soap formulations. OBJECTIVE: To determine and quantify lard as an adulterant in a binary blend with palm oil in a cosmetic soap formulations by FT-IR and multivariate analysis. METHODS: Fatty acids in lard, palm oil and binary blends were extracted via liquid-liquid extraction and were subjected to FTIR spectrometry, combined with principal component analysis (PCA) and discriminant analysis (DA) for the classification of lard in cosmetic soap formulations via two DA models: Model A (percentage of lard in cosmetic soap) and Model B (porcine and non-porcine cosmetic soap). Linear regression (MLR), partial least square regression (PLS-R) and principal components regression (PCR) were used to assess the degree of adulteration of lard in the cosmetic soap. FINDINGS: The FTIR spectrum of palm oil slightly differed from that of lard at the wavenumber range of 1453 cm -1 and 1415 cm -1 in palm oil and lard, respectively, indicating the bending vibrations of CH2 and CH3 aliphatic groups and OH carboxyl group respectively. Both of the DA models could accurately classify 100% of cosmetic soap formulations. Nevertheless, less than 100% of verification value was obtained when it was further used to predict the unknown cosmetic soap sample suspected of containing lard or a different percentage of lard. The PCA for Model A and Model B explained a similar cumulative variability (CV) of 92.86% for the whole dataset. MLR and PCR showed the highest determination coefficient (R2) of 0.996, and the lowest relative standard error (RSE) and mean square error (MSE), indicating that both regression models were effective in quantifying the lard adulterant in cosmetic soap. CONCLUSION: FTIR spectroscopy coupled with chemometrics with DA, PCA and MLR or PCR can be used to analyse the presence of lard and quantify its percentage in cosmetic soap formulations.

CONTEXTE: Combinée à la chimiométrie, la spectroscopie infrarouge à transformée de Fourier (SI-TF) permet de déterminer et de quantifier la présence du saindoux dans un mélange binaire avec de l'huile de palme parmi des formulations de savon cosmétique. OBJECTIF: Déterminer et quantifier le saindoux comme adultérant dans un mélange binaire avec de l'huile de palme parmi des formulations de savon cosmétique par SI-TF et analyse multivariée. MÉTHODES: Les acides gras dans le saindoux, l'huile de palme et les mélanges binaires ont été extraits par extraction liquide-liquide, puis ont été soumis à une SI-TF. Ils ont également fait l'objet d'une analyse en composantes principales (ACP) et d'une analyse discriminante (AD) pour la classification du saindoux dans les formulations de savons cosmétiques via deux modèles d'AD : le modèle A (pourcentage de saindoux dans le savon cosmétique) et le modèle B (savon cosmétique de porc et non de porc). Le degré d'altération du saindoux dans le savon cosmétique a été évalué selon une régression linéaire (régression L), une régression des moindres carrés partiels (régression PLS) et une régression sur composantes principales (régression CP). RÉSULTATS: Le spectre SI-TF de l'huile de palme différait légèrement de celui du saindoux sur la plage de nombre d'ondes de 1 453 cm −1 et 1 415 cm −1 dans l'huile de palme et le saindoux, respectivement, et indiquait les vibrations de flexion des groupes aliphatiques CH2 et CH3, et du groupe carboxyle OH, respectivement. Les deux modèles d'AD ont permis de classer avec précision 100 % des formulations de savon cosmétique. Néanmoins, la valeur de vérification obtenue s'est avérée inférieure à 100 % une fois les modèles utilisés pour prédire l'échantillon de savon cosmétique inconnu suspecté de contenir du saindoux ou un pourcentage de saindoux différent. L'ACP du modèle A et du modèle B expliquait une variabilité cumulée (VC) similaire de 92,86 % pour l'ensemble de l'ensemble des données. La régression L et la régression PLS ont montré le coefficient de détermination le plus élevé (R2), soit 0,996, ainsi que l'erreur type relative (ETR) et l'erreur carrée moyenne (EMM) les plus faibles, indiquant que les deux modèles de régression ont été efficaces pour quantifier le saindoux adultérant dans le savon cosmétique. CONCLUSION: Couplée à la chimiométrie avec une AD, une ACP et une régression L ou une régression PLS, la SI-TF permet d'analyser la présence de saindoux et de quantifier son pourcentage dans les formulations de savon cosmétique.

Impact of harvesting seasons on physicochemical properties and volatile compound profiles of Malaysian stingless bee honey analysed using chemometrics and support vector machine.

Stingless bee honey's nutritional value is gaining attention, but the impact of harvesting seasons, specifically the rainy (September 2018) and dry (February 2019) seasons in Malaysia on the honey's physicochemical properties and volatile compounds remains insufficiently explored. This research revealed marginal differences in the physicochemical properties between seasons. However, through individual bee species and cumulative data analysis, honey samples were effectively differentiated based on harvesting seasons. A set of seventeen volatile compounds were identified as potential chemical markers for distinguishing H. bakeri, G. thoracica, and T. binghami honey between rainy and dry seasons. For cumulative data, four significant markers were proposed. These discrimination methods and chemical markers can serve as valuable references in distinguishing stingless bee honey, whether its entomological origin is specified or not between rainy and dry seasons.

Application of ATR-FTIR Incorporated with Multivariate Data Analysis for Discrimination and Quantification of Urea as an Adulterant in UHT Milk.

Urea is naturally present in milk, yet urea is added intentionally to increase milk's nitrogen content and shelf life. In this study, a total of 50 Ultra heat treatment (UHT) milk samples were spiked with known urea concentrations (0-5 w/v%). Attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy with principal component analysis (PCA), discriminant analysis (DA), and multiple linear regression (MLR) were used for the discrimination and quantification of urea. The PCA was built using 387 variables with higher FL > 0.75 from the first PCA with cumulative variability (90.036%). Subsequently, the DA model was built using the same variables from PCA and demonstrated the good distinction between unadulterated and adulterated milk, with a correct classification rate of 98% for cross-validation. The MLR model used 48 variables with p-value < 0.05 from the DA model and gave R2 values greater than 0.90, with RMSE and MSE below 1 for cross-validation and prediction. The DA and MLR models were then validated externally using a test dataset, which shows 100% correct classification, and the t-test result (p > 0.05) indicated that the MLR could determine the percentage of urea in UHT milk within the permission limit (70 mg/mL). In short, the wavenumbers 1626.63, 1601.98, and 1585.5534 cm-1 are suitable as fingerprint regions for detecting urea in UHT milk.

Bacterial Metabolomics: Sample Preparation Methods.

Metabolomics is a comprehensive analysis of metabolites existing in biological systems. As one of the important "omics" tools, the approach has been widely employed in various fields in helping to better understand the complex cellular metabolic states and changes. Bacterial metabolomics has gained a significant interest as bacteria serve to provide a better subject or model at systems level. The approach in metabolomics is categorized into untargeted and targeted which serves different paradigms of interest. Nevertheless, the bottleneck in metabolomics has been the sample or metabolite preparation method. A custom-made method and design for a particular species or strain of bacteria might be necessary as most studies generally refer to other bacteria or even yeast and fungi that may lead to unreliable analysis. The paramount aspect of metabolomics design comprises sample harvesting, quenching, and metabolite extraction procedures. Depending on the type of samples and research objective, each step must be at optimal conditions which are significantly important in determining the final output. To date, there are no standardized nor single designated protocols that have been established for a specific bacteria strain for untargeted and targeted approaches. In this paper, the existing and current developments of sample preparation methods of bacterial metabolomics used in both approaches are reviewed. The review also highlights previous literature of optimized conditions used to propose the most ideal methods for metabolite preparation, particularly for bacterial cells. Advantages and limitations of methods are discussed for future improvement of bacterial metabolomics.

Isotopic Tracer for Absolute Quantification of Metabolites of the Pentose Phosphate Pathway in Bacteria.

The pentose phosphate pathway (PPP) plays a key role in many metabolic functions, including the generation of NADPH, biosynthesis of nucleotides, and carbon homeostasis. In particular, the intermediates of PPP have been found to be significantly perturbed in bacterial metabolomic studies. Nonetheless, detailed analysis to gain mechanistic information of PPP metabolism remains limited as most studies are unable to report on the absolute levels of the metabolites. Absolute quantification of metabolites is a prerequisite to study the details of fluxes and its regulations. Isotope tracer or labeling studies are conducted in vivo and in vitro and have significantly improved the analysis and understanding of PPP. Due to the laborious procedure and limitations in the in vivo method, an in vitro approach known as Group Specific Internal Standard Technology (GSIST) has been successfully developed to measure the absolute levels of central carbon metabolism, including PPP. The technique adopts derivatization of an experimental sample and a corresponding internal standard with isotope-coded reagents to provide better precision for accurate identification and absolute quantification. In this review, we highlight bacterial studies that employed isotopic tracers as the tagging agents used for the absolute quantification analysis of PPP metabolites.

Evaluation of metabolomics behavior of human colon cancer HT29 cell lines treated with ionic liquid graviola fruit pulp extract.

ETHNOPHARMACOLOGICAL RELEVANCE: Medicinal plants have been used by indigenous people across the world for centuries to help individuals preserve their wellbeing and cure diseases. Annona muricata L. (Graviola) which is belonging to the Annonaceae family has been traditionally used due to its medicinal abilities including antimicrobial, anti-inflammatory, antioxidant and cancer cell growth inhibition. Graviola is claimed to be a potential antitumor due to its selective cytotoxicity against several cancer cell lines. However, the metabolic mechanism information underlying the anticancer activity remains limited. AIM OF THE STUDY: This study aimed to investigate the effect of ionic liquid-Graviola fruit pulp extract (IL-GPE) on the metabolomics behavior of colon cancer (HT29) by using an untargeted GC-TOFMS-based metabolic profiling. MATERIALS AND METHODS: Multivariate data analysis was used to determine the metabolic profiling, and the ingenuity pathway analysis (IPA) was used to predict the altered canonical pathways after treating the HT29 cells with crude IL-GPE and Taxol (positive control). RESULTS: The principal components analysis (PCA) identified 44 metabolites with the most reliable factor loading, and the cluster analysis (CA) separated three groups of metabolites: metabolites specific to the non-treated HT29 cells, metabolites specific to the treated HT29 cells with the crude IL-GPE and metabolites specific to Taxol treatment. Pathway analysis of metabolomic profiles revealed an alteration of many metabolic pathways, including amino acid metabolism, aerobic glycolysis, urea cycle and ketone bodies metabolism that contribute to energy metabolism and cancer cell proliferation. CONCLUSION: The crude IL-GPE can be one of the promising anticancer agents due to its selective inhibition of energy metabolism and cancer cell proliferation.

Evaluation of microplastics ingested by sea cucumber Stichopus horrens in Pulau Pangkor, Perak, Malaysia.

The widespread presence of microplastics has caused significant concerns on their potential effects on marine ecosystems. Microplastics are classified as plastic products of less than 5 mm in size and are known to be one of the most dangerous aquatic debris to marine species. Sea cucumbers are deposit feeders living in sediment regions and benthic zone that may collect microplastics in low-energy environments. This research aims to evaluate the types of microplastic isolated from the intestine of Stichopus horrens in Malaysia. This species is selected because it is mainly found in this island. Pulau Pangkor is one of the leading tourism destinations on the small islands is facing increasing numbers of tourists and development and it is useful for sustainable study. A total of 20 S. horrens samples collected from Pulau Pangkor, Malaysia were dissected, and their intestines were collected for digestion. Microplastics were extracted using NaOH and filtered using filter paper. Microplastic identification was conducted on the based of the physical characteristics (colour, shape, size) and chemical characterisation was evaluated using FTIR for polymer functional groups. A total of 1446 unit of microplastics were found in S. horrens. Among various types and colours, fibre (90%) and black (59%) were dominant amongst the various particles identified. The majority of microplastics sizes were 0.51 µm and 1-2 µm. Two polymer materials were identified, namely polyethylene and poly(methyl methacrylate). As a conclusion, the findings of the study will serve as primary data for pollution indicators in respective islands. The microplastics could impact the immune system and upset gut's balance of human.

The characteristics and roles of antimicrobial peptides as potential treatment for antibiotic-resistant pathogens: a review.

The emergence of antibiotic-resistant bacteria has become a significant and ever-increasing threat to global public health, increasing both morbidity and mortality rates, and the financial burden on health services. Infection by drug-resistant bacteria is anticipated to contribute to the demise of almost 10 million people by the year 2050 unless a competent and effective response is devised to engage with this issue. The emergence and spread of resistance are commonly caused by the excessive or inappropriate use of antibiotics and substandard pharmaceuticals. It arises when pathogens adapt to different conditions and develop self-defence mechanisms. Currently, novel antimicrobial peptides (AMPs) have been reported to be the sole cure for some clinical cases of infectious diseases such as sepsis and skin infections, although these agents may, on occasion, require administration together with an adjunctive low-dose antibiotic. Although AMPs are a promising alternative form of anti-microbial therapy and easily applied in the medical sector, they still have limitations that should not be taken lightly. Hence, this review explores the characteristics, advantages and disadvantages of AMPs for their potential in treating antibiotic-resistant pathogens.