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Tuna and billfish are widely distributed in oceans worldwide. Their survival is relied on a decent share of essential and non-essential elements. We conducted a comprehensive evaluation of essential and non-essential elements in livers of tuna and billfish collected from global oceans. The individual element consistently shown similar orders of magnitude in both tuna and billfish, with essential elements generally being 1–3 orders of magnitude higher than non-essential elements. Various physicochemical properties and behaviors contributed to four distinct clusters of these elements. Also, element distribution pattern indicated the presence of four sample groups based on regions and categories. Nine elements served as characteristic indicators. Among them, fish category was the most important influencing factor. Hg, Fe, Tl, Co, and Se were influenced by body size, trophic level, and feeding habits. Ni was influenced by sampling regions, while Mg, Mn and As were influenced by body size and local primary production. [Display omitted] • Essential and non-essential elements showed different bioaccumulation characteristics. • Element distribution pattern showed four sample groups by regions and categories. • Elements' presence depends on environmental and biological processes. [ABSTRACT FROM AUTHOR]

Energy storage systems play a major role in the energy transition. Among them, vanadium redox flow batteries are a promising alternative to conventional batteries, which due to their design can be scaled, and it is possible to decouple power and energy density. However, the transport of electroactive species through the membrane (cross-contamination) reduces the capacity and useful life of these batteries. In this work, computational simulation was performed using the finite element method coupled to chemometric analysis to develop a mitigation strategy to decrease the vanadium redox flow batteries capacity loss by cross-contamination. This study can be divided into two stages. Initially, a 23 full factorial design was performed to evaluate and determine the effect of different variables: current density, active species concentration, and volumetric flow on the loss of capacity of vanadium redox flow batteries. In the second stage, a Doehlert design was performed with current density, the concentration of active species, and the volumetric flow between electrolyte tanks as variables to obtain the optimum conditions that minimize capacity loss. The results show that the current density and the concentration of active species are the main variables that affect capacity loss in vanadium redox flow batteries. The proposed approach successfully mitigated the cross-contamination in different combinations of current density and concentration of active species providing an optimal flow between electrolyte tanks for different operating conditions. [Display omitted] • Computational approach to mitigate the VRFB capacity loss by cross-contamination. • Current density and active species concentration majorly impact VRFB capacity loss. • Mitigation strategy reduces VRFB capacity loss across diverse operational conditions. [ABSTRACT FROM AUTHOR]

Rana chensinensis ovum (RCO), similar to fish roe, is a part of the gonads of Rana chensinensis and has become a premium delicacy due to its unique flavor and high nutritional value. The impact of breeding environments on the fatty acid content of RCO from various locations, primarily produced in Changbai Mountain, was explored in this study. RCO samples were collected from nine distinct regions that covered the primary production areas. Environmental factors such as altitude, longitude, latitude, average annual temperature, average annual ground temperature, annual precipitation, sunshine hours, soil top/substrate pH (T/S-pH-H 2 O), and soil top/substrate organic carbon content (T/S-OC) were evaluated. A UPLC-Q/TOF-MS-based method was used to determine the composition and distribution of fatty acids in RCO samples collected from different locations. Twenty-three fatty acid components, including DHA, EPA, DPA, ALA, C20:2, C20:3, C18:4, LA, C20:1, AA, C7:0, C10:1, C11:1, C16:2, C16:1, C16:0, OA, C18:0 C19:0, C23:1, C24:1, C22:0, and C17:1, were identified in RCO samples. Gray relational analysis (GRA) and Pearson correlation were employed to evaluate the influence of each environmental factor on fatty acid composition. Hierarchical cluster analysis (HCA), principal component analyses (PCA), and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to classify RCO samples from different origins and analyze their similarities and differences. The results indicated that the habitat of Rana chensinensis can influence their nutritional value, as differences in fatty acid components were observed in RCO samples collected from different environments. [Display omitted] • Fatty acids in Rana chensinensis ovum were characterized through UPLC-Q-TOF-MS. • Breeding environmental parameters were collected from the meteorological stations. • Fatty acids exhibited correlations with the breeding environmental parameters. • Temperature, humidity, and sunshine hours significantly impacted fatty acid content. • Altitude and soil pH showed minimal effect on the fatty acid content. [ABSTRACT FROM AUTHOR]

The aim of the study was to estimate the dietary exposure of the main macro and micro elements from meals typically consumed by the Mediterranean population, in particular Sicilian by samples prepared and cooked prior to analysis. A total of 57 typical Mediterranean meals samples were analysed for 4 macro elements: Calcium (Ca), Potassium (K), Magnesium (Mg) and Sodium (Na) and 13 micro elements: Aluminium (Al), Arsenic (As), Cadmium (Cd), Cobalt (Co), Chromium (Cr), Copper (Cu), Iron (Fe), Mercury (Hg), Manganese (Mn), Nickel (Ni), Lead (Pb), Zinc (Zn) and Vanadium (V) by inductively coupled plasma - mass spectrometry and atomic absorption spectrometry. Mercury concentration was quantified directly on the food samples by using the DMA-80 (Direct for Mercury Analysis). Daily Estimated Element Intake was calculated for essential element and assessment of health risk associated with intake of investigated elements was performed. In particular, analysed samples supply from 3.7% to 62% of sodium, 0.05–19% of potassium, 0.1–3.2% of calcium, 1.6–16% of magnesium, 2.1–37% of iron, 0.7–48% of zinc and 0.98–339% of chromium. some of the foods prepared are lacking in all macroelements (Na, K, Ca, Mg). The quantity of macroelements taken from a single portion of 100 g of several food, compared to the recommended quantities, is low, but it should be considered that on average in one day (breakfast, lunch and dinner), undoubtedly, the inhabitants of the Mediterranean area consume much higher quantities for a total of 500–1000 g, therefore, this study confirmation for the populations concerned, the low probability of nutritional or health risks due to the consumption of foods, indeed, the consumption of Mediterranean dietary foods, has not shown particular risk assessments from heavy metals. • In literature no data are reported on elements in Mediterranean meals. • 57 typical Mediterranean ready-to-eat meals were analyzed. • 17 micro and macro elements were quantified. • Mercury was quantified directly on the food samples by using the DMA-80. • Most of the dishes analyzed contain hazardous metals under the limits tolerated. [ABSTRACT FROM AUTHOR]

The aim of this pilot study was to apply a novel combined metabolomic and proteomic approach in analysis of gestational diabetes mellitus. The investigation was performed with plasma samples derived from pregnant women with diagnosed gestational diabetes mellitus (n = 18) and a matched control group (n = 13). The mass spectrometry-based analyses allowed to determine 42 free amino acids and low molecular-weight peptide profiles. Different expressions of several peptides and altered amino acid profiles were observed in the analyzed groups. The combination of proteomic and metabolomic data allowed obtaining the model with a high discriminatory power, where amino acids ethanolamine, l-citrulline, l-asparagine, and peptide ions with m/z 1488.59; 4111.89 and 2913.15 had the highest contribution to the model. The sensitivity (94.44%) and specificity (84.62%), as well as the total group membership classification value (90.32%) calculated from the post hoc classification matrix of a joint model were the highest when compared with a single analysis of either amino acid levels or peptide ion intensities. The obtained results indicated a high potential of integration of proteomic and metabolomics analysis regardless the sample size. This promising approach together with clinical evaluation of the subjects can also be used in the study of other diseases.

It is thought that the therapeutic efficacy of Morus alba L. is determined by its biological compounds. We investigated the chemical differences in the medicinal parts of M. alba by analyzing a total of 57 samples (15 root barks, 11 twigs, 12 fruits, and 19 leaves). Twelve marker compounds, including seven flavonoids, two stilbenoids, two phenolic acids, and a coumarin, were quantitatively analyzed using a high-performance liquid chromatography-diode array detector and chemometric analyses (principal component and heatmap analysis). The results demonstrated that the levels and compositions of the marker compounds varied in each medicinal part. The leaves contained higher levels of six compounds, the root barks contained higher levels of four compounds, and the twigs contained higher levels of two compounds. The results of chemometric analysis showed clustering of the samples according to the medicinal part, with the marker compounds strongly associated with each part: mulberroside A, taxifolin, kuwanon G, and morusin for the root barks; 4-hydroxycinnamic acid and oxyresveratrol for the twigs and skimmin; chlorogenic acid, rutin, isoquercitrin, astragalin, and quercitrin for the leaves. Our approach plays a fundamental role in the quality evaluation and further understanding of biological actions of herbal medicines derived from various medicinal plant parts.

Amomi Fructus is widely used to treat digestive disorders, and Amomum villosum, A. villosum var. xanthioides, and A. longiligulare are permitted medicinally in national pharmacopeias. However, there are a variety of adulterants present in herbal markets owing to their morphological similarities to the genuine Amomum species. Forty-two Amomi Fructus samples from various origins were identified using internal transcribed spacer and chloroplast barcoding analyses, and then their chromatographic profiles were compared using chemometric analysis for chemotaxonomic monitoring. Among the Amomi Fructus samples, A. villosum, A. longiligulare, A. ghaticum, and A. microcarpum were confirmed as single Amomum species, whereas a mixture of either these Amomum species or with another Amomum species was observed in 15 samples. Chemotaxonomic monitoring results demonstrated that two medicinal Amomum samples, A. villosum and A. longiligulare, were not clearly distinguished from each other, but were apparently separated from other non-medicinal Amomum adulterants. A. ghaticum and A. microcarpum samples were also chemically different from other samples and formed their own species groups. Amomum species mixtures showed diverse variations of chemical correlations according to constituent Amomum species. Genetic authentication-based chemotaxonomic monitoring methods are helpful in classifying Amomi Fructus samples by their original species and to distinguish genuine Amomum species from the adulterants.

Berberis laurina (Berberidaceae) is a well-known medicinal plant used in traditional medicine since ancient times; however, it is scarcely studied to a large-scale fingerprint. This work presents a broad-range fingerprints determination through high-resolution magical angle spinning (HR-MAS) nuclear magnetic resonance (NMR) spectroscopy, a well-established flexible analytical method and one of most powerful “omics” platforms. It had been intended to describe a large range of chemical compositions in all plant parts. Beyond that, HR-MAS NMR allowed the direct investigation of botanical material (leaves, stems, and roots) in their natural, unaltered states, preventing molecular changes. The study revealed 17 metabolites, including caffeic acid, and berberine, a remarkable alkaloid from the genus Berberis L. The metabolic pattern changes of the leaves in the course of time were found to be seasonally dependent, probably due to the variability of seasonal and environmental trends. This metabolites overview is of great importance in understanding plant (bio)chemistry and mediating plant survival and is influenceable by interacting environmental means. Moreover, the study will be helpful in medicinal purposes, health sciences, crop evaluations, and genetic and biotechnological research.

Beer is the most common alcoholic beverage worldwide, and is an excellent source of macro- and microelements, as well as phenolic compounds. In this study, a fast method for the determination of Na, K, Mg, Ca, Fe, Mn, and Cu in beer was developed using flame atomic absorption spectrometry. The precision of this method was between 0.8 and 8.0% (as the relative standard deviation (RSD)), and limits of detections were in the range of 0.45 (Mn)–94 µg/L (Na). Among the macroelements tested in the beer samples, K was found at the highest concentration, whereas Na was found at the lowest concentration level. Beer also turned out to be a good source of Mg and K. The total phenolic content (TPC) was determined by the Folin–Ciocalteu method, while the antioxidant activity was estimated by the ABTS method. The results show remarkable variations in the mineral content, TPC, and antioxidant activity across the beer types and brands. Moreover, the relations between the type, color, refraction index, antioxidant activity, extract, alcohol, mineral, and the total phenolic contents were investigated using the factor analysis of mixed data (FAMD) combined with hierarchical clustering on principal components (HCPC).

Chromatographic profiles of primary essential oils (EO) deliver valuable authentic information about composition and compound pattern. Primary EOs obtained from Pinus sylvestris L. (PS) from different global origins were analyzed using gas chromatography coupled to a flame ionization detector (GC-FID) and identified by GC hyphenated to mass spectrometer (GC-MS). A primary EO of PS was characterized by a distinct sesquiterpene pattern followed by a diterpene profile containing diterpenoids of the labdane, pimarane or abietane type. Based on their sesquiterpene compound patterns, primary EOs of PS were separated into their geographical origin using component analysis. Furthermore, differentiation of closely related pine EOs by partial least square discriminant analysis proved the existence of a primary EO of PS. The developed and validated PLS-DA model is suitable as a screening tool to assess the correct chemotaxonomic identification of a primary pine EOs as it classified all pine EOs correctly.

Fluorinated benzosiloxaboroles–silicon congeners of benzoxaboroles, were synthesized and tested as molecular receptors for mono- and disaccharides. The receptors differed in the Lewis acidity of the boron center as well as in the number of potential binding sites. The calculated stability constants indicated different binding affinity of benzosiloxaborole derivatives towards selected saccharides, enabling their classification using a receptor array-based sensing. Unique fluorescence fingerprints were created on the basis of competitive interactions of the studied receptors with both Alizarin Red S (ARS) and tested saccharide molecules. Detailed chemometric analysis of the obtained fluorescence data (based on partial least squares-discriminant analysis and hierarchical clustering analysis) provided the differential sensing of common saccharides, in particular the differentiation between glucose and fructose. In addition, DFT calculations were carried out to shed light on the binding mechanism under different pH conditions.

Sensory evaluation, carried out by panel tests, is essential for quality classification of virgin olive oils (VOOs), but is time consuming and costly when many samples need to be assessed; sensory evaluation could be assisted by the application of screening methods. Rapid instrumental methods based on the analysis of volatile molecules might be considered interesting to assist the panel test through fast pre-classification of samples with a known level of probability, thus increasing the efficiency of quality control. With this objective, a headspace gas chromatography-ion mobility spectrometer (HS-GC-IMS) was used to analyze 198 commercial VOOs (extra virgin, virgin and lampante) by a semi-targeted approach. Different partial least squares-discriminant analysis (PLS-DA) chemometric models were then built by data matrices composed of 15 volatile compounds, which were previously selected as markers: a first approach was proposed to classify samples according to their quality grade and a second based on the presence of sensory defects. The performance (intra-day and inter-day repeatability, linearity) of the method was evaluated. The average percentages of correctly classified samples obtained from the two models were satisfactory, namely 77% (prediction of the quality grades) and 64% (prediction of the presence of three defects) in external validation, thus demonstrating that this easy-to-use screening instrumental approach is promising to support the work carried out by panel tests.

Establishing the metabolism pathway of the drug undergoing the hepatic biotransformation pathway is one of the most important aspects in the preclinical discovery process since the presence of toxic or reactive metabolites may result in drug withdrawal from the market. In this study, we present the structural elucidation of six, not described yet, metabolites of an antipsychotic molecule: molindone. The elucidation of metabolites was supported with a novel photocatalytical approach with the use of WO3 and WS2 assisted photochemical reactions. An UHPLC-ESI-Q-TOF combined system was used for the registration of all obtained metabolite profiles as well as to record the high resolution fragmentation spectra of the observed transformation products. As a reference in the in vitro metabolism simulation method, the incubation with human liver microsomes was used. Chemometric comparison of the obtained profiles pointed out the use of the WO3 approach as being more convenient in the field of drug metabolism studies. Moreover, the photocatalysis was used in the direction of the main drug metabolite synthesis in order to further isolation and characterization.

This is the first study of mineral content and basic physicochemical parameters of honeys of Montenegro. We examined honey samples from eight different micro-regions of Montenegro, and the results confirm that, with the exception of cadmium in samples from two regions exposed to industrial pollution, none of the 12 elements analyzed exceeded the maximum allowable level. The samples from areas exposed to industrial pollution were clearly distinguished from samples from other regions of Montenegro in the detectable contents of Pb, Cd, and Sr. This study showed that chemometric techniques might enhance the classification of Montenegrin honeys according to their micro-regional origin using the mineral content. Linear discriminant analysis revealed that the classification rate was 79.2% using the cross-validation method.

The development of transgenic glyphosate-tolerant crops has revolutionized weed control in crops in many regions of the world. The early, non-destructive identification of superior plant phenotypes is an important stage in plant breeding programs. Here, glyphosate-tolerant transgenic maize and its parental wild-type control were studied at 2, 4, 6, and 8 days after glyphosate treatment. Visible and near-infrared hyperspectral imaging and chlorophyll fluorescence imaging techniques were applied to monitor the performance of plants. In our research, transgenic maize, which was highly tolerant to glyphosate, was phenotyped using these high-throughput non-destructive methods to validate low levels of shikimic acid accumulation and high photochemical efficiency of photosystem II as reflected by maximum quantum yield and non-photochemical quenching in response to glyphosate. For hyperspectral imaging analysis, the combination of spectroscopy and chemometric methods was used to predict shikimic acid concentration. Our results indicated that a partial least-squares regression model, built on optimal wavelengths, effectively predicted shikimic acid concentrations, with a coefficient of determination value of 0.79 for the calibration set, and 0.82 for the prediction set. Moreover, shikimic acid concentration estimates from hyperspectral images were visualized on the prediction maps by spectral features, which could help in developing a simple multispectral imaging instrument for non-destructive phenotyping. Specific physiological effects of glyphosate affected the photochemical processes of maize, which induced substantial changes in chlorophyll fluorescence characteristics. A new data-driven method, combining mean fluorescence parameters and featuring a screening approach, provided a satisfactory relationship between fluorescence parameters and shikimic acid content. The glyphosate-tolerant transgenic plants can be identified with the developed discrimination model established on important wavelengths or sensitive fluorescence parameters 6 days after glyphosate treatment. The overall results indicated that both hyperspectral imaging and chlorophyll fluorescence imaging techniques could provide useful tools for stress phenotyping in maize breeding programs and could enable the detection and evaluation of superior genotypes, such as glyphosate tolerance, with a non-destructive high-throughput technique.

Background: The growing demand for rosé sparkling wine has led to an increase in its production. Traditional or Charmat wine-making influence the aromatic profiles in wine. An analysis such as gas chromatography makes an accurate assessment of wines based on volatile detection but is resource intensive. On the other hand, the electronic nose (E-nose) has emerged as a versatile tool, offering rapid, cost-effective discrimination of wines, and contributing insights into quality and production processes because of its aptitude to perform a global aromatic pattern evaluation. In the present study, rosé sparkling wines were produced using both methods and major volatile compounds and polyols were measured. Wines were tested by E-nose and predictive modelling was performed to distinguish them., Results: Volatile profiles showed differences between Charmat and traditional methods, especially at 5 months of aging. A partial least square discriminant analysis (PLS-DA) was carried out on E-nose detections, obtaining a model that describes 94% of the variability, separating samples in different clusters and correctly identifying different classes. The differences derived from PLS-DA clustering agree with the results obtained by gas-chromatography. Moreover, a principal components regression model was built to verify the ability of the E-nose to non-destructively predict the amount of different volatiles analyzed., Conclusion: Production methods of Rosé sparkling wine affect the final wine aroma profiles as a result of the differences in terms of volatiles. The PLS-DA of the data obtained with E-nose reveals that distinguishing between Charmat and traditional methods is possible. Moreover, predictive models using gas chromatography-flame ionization detection analysis and E-nose highlight the possibility of fast and efficient prediction of volatiles from the E-nose. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry., (© 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.)

Astringency is an essential sensory attribute of red wine closely related to the saliva precipitation upon contact with the wine. In this study a data matrix of 52 physico-chemical parameters was used to predict the Saliva Precipitation Index (SPI) in 110 Italian mono-varietal red wines using partial least squares regression (PLSr) with variable selection by Variable Importance for Projection (VIP) and the significance of regression coefficients. The final PLSr model, evaluated using a test data set, had 3 components and yielded an R 2 test of 0.630 and an RMSE test of 0.994, with 19 independent variables whose regression coefficients were all significant at p  < 0.05. Variables selected in the final model according to the decreasing magnitude of their absolute regression coefficient include the following: Procyanidin B1, Epicatechin terminal unit, Total aldehydes, Protein content, Vanillin assay, 520 nm, Polysaccharide content, Epigallocatechin PHL, Tartaric acid, Volatile acidity, Titratable acidity, Catechin terminal unit, Proanthocyanidin assay, pH, Tannin-Fe/Anthocyanin, Buffer capacity, Epigallocatechin PHL gallate, Catechin + epicatechin PHL, and Tannin-Fe. These results can be used to better understand the physico-chemical relationship underlying astringency in red wine., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

Bee pollen is one of the most valuable apitherapeutic products with high nutritional value. To obtain a higher diversity of compounds, higher bioactivity, and improve the release of nutrients from bee pollen, additional processing of the raw material may be applied: fermentation using microorganisms or hydrolysis using selective enzymes. This research aimed to determine the impact of enzymatic hydrolysis on the antioxidant and antibacterial activities of bee pollen. Bee pollen samples from Sweden, Spain, Netherlands, Italy, Poland, Denmark, Slovakia, Malta, and Lithuania were hydrolyzed using pure enzymes, including lipase, cellulase, protease, and amyloglucosidase, as well as enzyme mixtures such as Viscozyme ® L and Clara-diastase . Total phenolic content, total flavonoid content, and antioxidant activity were analyzed spectrophotometrically. Antibacterial activity against Staphylococcus aureus , Listeria monocytogenes , Staphylococcus enteritidis , and Salmonella typhimurium was evaluated using the agar well diffusion assay. Obtained results revealed a positive effect of enzymatic hydrolysis on biologically active compound content and activity: total phenolic content increased by 1.1 to 2.5 times, total flavonoid content by 1.1 to 3.0 times, radical scavenging activity by 1.1-3.5 times, and antibacterial activity by 1.1 to 3.3 times. K-means clustering analysis grouped samples into 5-9 clusters and was dependent on the measured characteristic used as an input-total phenolic compounds content, total flavonoid content, antioxidant activity, and antibacterial activity against four different bacteria. Chemometrics showed, that the enzyme used for the hydrolysis had a higher impact on clustering results than the geographical origin of the samples.

Hassawi rice is an Indica variety cultivated in Saudi Arabia with a higher nutritional value than the commercial Basmati rice varieties. The present study has investigated the feasibility of combining Hassawi rice flour (HRF) or husk (HRHF), an abundant byproduct, with wheat flour to produce nutritious economical pan bread. To achieve this aim, the physicochemical properties of HRF and HRHF were assessed using techniques such as UPLC-tandem MS, ICP-OES, and colorimeter. The proximate composition (moisture, crude fiber, and ash) and mineral contents of HRHF are significantly ( p  < 0.05) higher than HRF. On the other hand, the compounds p -coumaric acid, vanillic acid, γ - and δ -tocotrienols, and γ -oryzanol were unique to HRF. We further determined the changes in sensory, technological, and physicochemical properties of wheat flour bread substituted with 5%, 10%, and 15% of HRF or HRHF. The rheological tests showed that the addition of HRF and HRHF increased dough development and stability time. Further, substituting wheat flour for HRF and HRHF at levels higher than 10% affected sensory attributes, such as color, taste, odor, flavor, and appearance. These changes, however, were not always at a significant level. The causes of the differences in properties between control and fortified bread samples were investigated by chemometric methods. Samples of bread + HRF at 5 and 10% had comparable overall profiles to the control. On the other hand, bread + HRHF samples proved to retain higher concentrations of bioactive molecules compared to the control bread. Our findings shed light on the possible use of rice husk fibers in baking goods, notably pan bread. Furthermore, by integrating rice husk fibers into baked goods, we may boost their health benefits while also contributing to the long-term use of agricultural waste., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Elkatry, El-Beltagi, Ahmed, Mohamed, Al-Otaibi, Ramadan and Mahmoud.)

Geographical indications (GI) are used to protect the brand value of agricultural products, foodstuffs, and wine and promote the sustainable development of the agricultural and food industries. Despite the necessity for the traceability and recognition of GI product characteristics, no rapid, non-destructive approaches currently exist to identify, classify, and predict these properties. The application of gas chromatography-ion mobility spectrometry (GC-IMS) has increased exponentially due to instrument robustness and simplicity. This paper provided a detailed overview of recent GC-IMS applications in China for the quality evaluation of GI products and food, including agricultural products, as well as traditional Chinese food and liquor. The general workflow of GC-IMS coupled with chemometric analysis is presented, including sample collection, model construction and interpretation, and data acquisition, processing, and fusion. Several conclusions are drawn to increase partial least squares-discriminant analysis (PLS-DA) model precision, a chemometric technique frequently combined with GC-IMS., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Zhu, Zhu and Sun.)

The objectives of the present study are to compare the phenolic profiles and biological activities of 15 citrus honey samples from three different locations in Turkey using a chemometric approach. The HPLC-DAD analysis was used to determine phenolic profiles. Nineteen phenolic compounds were identified. Gallic acid (107.14-717.04 μg/g) was recorded as the predominant compound. AF (Antalya-Finike) had the highest antioxidant activity in ABTS⋅ + (IC 50 : 18.01±0.69 mg/mL), metal chelating (IC 50 : 6.20±0.19 mg/mL) and CUPRAC (A 0.50 : 12.05±0.68 mg/mL) assays, while it revealed the best anti-inflammatory activity against COX-2 (17.28±0.22 %) and COX-1 (43.28±0.91 %). AM (Antalya-Manavgat) was the most active in β-carotene-linoleic acid (IC 50 : 10.05±0.19 mg/mL), anti-urease (38.90±0.69 %), anti-quorum sensing and antimicrobial activities. AKO1 (Adana-Kozan-1) in DPPH⋅ (IC 50 : 34.25±0.81 mg/mL) assay, AKU1 (Antalya-Kumluca-1) in tyrosinase inhibition activity (37.73±0.38 %) assay, AKU2 (Antalya-Kumluca-2) in AChE (10.55±0.63 %) and BChE (9.18±0.45 %) inhibition activity assays showed the best activity. Chemometric tools were applied to the phenolic compositions and biological properties. PCA and HCA ensured that 15 citrus honey samples were grouped into 3 clusters. The results showed that myricetin, kaempferol, vanillin, protocatechuic acid, rosmarinic acid, rutin, vanillic acid, gallic acid, catechin and p-hydroxyphenyl acetic acid are phenolic compounds that can be used in the classification of citrus honeys., (© 2023 Wiley-VHCA AG, Zurich, Switzerland.)

Cheese whey (CW) and wheat straw hydrolysate (WSH) were used to produce biohydrogen by anaerobic co-digestion of multiple substrates. In this work, the influence of pH, temperature, substrates concentrations on the biohydrogen production was explored with the application of the principal component analysis (PCA) and the hierarchical clustering analysis (HCA), allowing the identification of the main clusters and the uniqueness of some experiments. Response surface methodology (RSM) was used to evaluate the individual and interactive effects of pH, temperature, CW concentration and WSH concentration in the fermentation. Optimal operational conditions obtained by RMS were 5 g L −1 WSH, 25 g L −1  CW, 26.6 °C and pH 7.25. With these conditions was expected 5724.5 mL H 2 L −1 . When optimal conditions were tested using 0.11-L anaerobic serological bottles, 1-L and 4-L bioreactors the results obtained for biohydrogen production were 4554.5 ± 105, 3685 ± 305 and 4132.3 ± 151 mL H 2 L −1 , respectively; on the other hand, the biohydrogen production rate was improved from 66.6 to 89.5 mL H 2 L −1 h −1 . Results demonstrate that it is possible to use WSH and CW, both individually and in combination, as a substrate for the production of biohydrogen. [ABSTRACT FROM AUTHOR]

The correlations between the retention parameters of forty ampholytic, biologically active and/or pharmaceutically relevant substances (obtained for three non-polar HPLC columns at various compositions of mobile phases and pH conditions: 2.5, 7.0, 11.5) and their thirty-two physicochemical (calculated/spectral) characteristics were investigated by applying chemometric methods of analysis. In three cases (among seven cases considered), Quantitative Property-Retention Relation (QPRR) models meeting the predictive capability criteria were developed (the values of R 2 , Q 2 CV , Q 2 Ext were higher than 0.76, 0.66 and 0.67, respectively, while values of RMSE C , RMSE CV and RMSE Ext were lower than 0.51, 0.65 and 0.65 in each developed model). These models create a useful platform for predicting retention parameters of untested chemicals and, to some extent, gaining pharmaceutically valuable information on the biologically active ampholytic substances based on their properties and the conditions of chromatographic separation. [ABSTRACT FROM AUTHOR]

The potential of ultra-fast gas chromatography (GC) combined with chemometric analysis for classification of wine originating from Poland according to the variety of grape used for production was investigated. A total of 44 Polish wine samples differing in the type of grape (and grape growth region) used for the production as well as parameters of the fermentation process, alcohol content, sweetness, and others which characterize wine samples were analysed. The selected features coming from ultra-fast GC analysis were subsequently used as inputs for both principal component analysis (PCA) and supervised machine learning. Using the proposed classification algorithm, it was possible to classify white and red wines according to the variety of grape used for production with a 98.7 and 98.2% accuracy, respectively. The model was characterized by good recall and area under receiver operating characteristic which was 1.000 for white wines and 0.992 for red wines. Cuveé wines (made from various types of grapes) were also successfully classified which leads to the conclusion that the proposed classification method can be used not only to differentiate between wines made from different grapes but also to detect possible adulterations, provided known; non-adulterated samples are available as a reference. The model was also used to classify wine samples based on other features, such as the geographic region in which the vineyard is situated, type of yeast used, the temperature of fermentation, sweetness, etc. In all cases, a high classification accuracy (in most cases > 90%) was achieved. The obtained results could be applied in the wine industry. [ABSTRACT FROM AUTHOR]

Abstract: Antibiotic‐resistant bacterial infection (ARBI) is one of the most serious global public health threats. Antiinfective peptides (AIPs) have been recognized as a promising alternative to traditional antibiotics, which can effectively combat the ARBI in a distinct mechanism. In the current study, we attempt to discover new and potent AIPs from the natural antibacterial protein repertoire. Hundreds of antibacterial proteins with sequence length > 50 amino acids are manually curated from literatures and databases, which are then broken into a large pool of 12‐mer peptide fragments. In the procedure, a high‐throughput statistical screening strategy that integrates machine learning, chemometic prediction, and molecular modeling is employed to computationally identify 8 promising AIP hits from the fragment pool, of which 5 are determined by susceptibility test to possess a moderate or high potency against human pathogenic bacteria (20 μg/mL < minimum inhibitory concentration < 90 μg/mL), while the other 3 have only a low or no antibacterial activity (minimum inhibitory concentration > 100 μg/mL). Conformational analysis characterizes that the active AIPs are almost α‐helical (helical rate > 50%), carry many positive charges (net charge > +3), and exhibit an amphipathic profile. Dynamic simulation of a representative membrane‐AIP interaction reveals that the peptide can fluctuate nearby the membrane surface and use its cationic side chains to directly interact with and tightly bind to the anionic hydrophilic layer of bacterial outer membrane. [ABSTRACT FROM AUTHOR]

High performance liquid chromatography (HPLC) method was optimized using Design of Experiment (DOE) process and validated for quantitative analysis of caffeic acid and rosmarinic acid contents in extracts from Thunbergia laurifolia leaves collected from 10 different locations in Thailand. Antioxidant qualities of all extracts were evaluated by various chemometric analysis methods from the results of HPLC analysis both fingerprints and active component contents, in vitro antioxidant activities determined by 2,2-diphenyl-1-picrylhydrazyl scavenging assay and total phenolic and total flavonoid contents determined by Folin-Ciocaltue and aluminium chloride methods, respectively. It was found that HPLC fingerprints of T. laurifolia leaf extracts analyzed by similarity analysis and chemical pattern recognition had moderate similarity (r = 0.76) with the same 11 major peaks. Total phenolic contents calculated as both caffeic acid equivalent (CAE) and rosmarinic acid equivalent (RAE) showed the highest correlation to antioxidant effects of T. laurifolia leaf extracts (R2 > 0.9). This study is the first demonstration of the analytical method for simultaneous quantitative analysis of 2 active component contents in leaf decoction extract from T. laurifolia and the uses of chemometric methods to evaluate and compare the quality, especially the chemical and biological qualities of raw materials collected from different locations. [ABSTRACT FROM AUTHOR]

The aim of this study was to evaluate the potential compositional differences among different populations of H. officinalis subsp. aristatus (Godr.) Nyman. The plant specimens were collected in different locations in Western Balkans (Kosovo and Albania) and subjected to phytochemical profiling (GC-MS for their essential oils and HPLC-UV-DAD for fingerprinting of their solvent extractable phytochemicals). Antioxidant capacity, total flavonoid and phenol contents were measured using different assays. Out of the five location considered, the specimen from one location displayed significant differences both in terms of essential oil composition and of polyphenolic total content. The electronic nose measurements used to characterize their aromatic profile, was able to clearly discriminate the accessions, indicating a good correlation, in particular, with the marked chemotypic difference established by essential oil profiling (1,8-cineol vs. isopinocamphone/camphone). H. officinalis subspp. aristatus (Godr.) Nyman may constitute an interesting subject for further studies on the effect of genetic and environmental factors, or of their combinations, on its chemotypic expression and sensorial properties. [ABSTRACT FROM AUTHOR]

Efficacy directed-fingerprint analysis of high-performance thin layer chromatography is proposed to set up fingerprint activity relationship modeling for precise discrimination of chemical and effective consistency of Nigella sativa oils from different geographical origins. A whole of 27 samples of N. sativa oils from three geographical area (Egypt, Ethiopia and Syria) were collected and their antimicrobial, cytotoxic, anti-inflammatory and analgesic activities were measured. The results revealed that there was significant difference in the biological activities of the oils collected. The fingerprints of the samples had been established by high performance thin layer chromatography, subsequently the data had been utilized for the discrimination of the samples geographical origin. The loading plots of HPTLC-Principal Component Analysis (PCA) had been used to discover the crucial marker ingredients for classification. Furthermore, targeted chemical fingerprints had been established by HPTLC, and discriminant analyses were calculated depending on five common characteristic peaks. The chosen markers were quantified by validated HPTLC methods, and then the quantitative data as well as the oils bioactive properties were subjected to partial least squares regression (PLSR) analyses. Thymoquinone and free fatty acids (FFA) were revealed as potential markers to distinguish the chemical consistency and efficacy of the oils from the three different geographical origins. The suggested technique provides an applicable integrated strategy to screen for efficacy-associated markers for discrimination of N. sativa oils from distinctive geographical origins exploiting HPTLC fingerprint activity relationship modeling. [ABSTRACT FROM AUTHOR]

Chemometric tools were applied to investigate the biological behaviour of ampholytic substances in relation to their physicochemical and spectral properties. Results of the Principal Component Analysis suggest that size of molecules and their electronic and spectral characteristics are the key properties required to predict therapeutic relevance of the compounds examined. These properties were used for developing the structure-activity classification model. The classification model allows assessing the therapeutic behaviour of ampholytic substances on the basis of solely values of descriptors that can be obtained computationally. Thus, the prediction is possible without necessity of carrying out time-consuming and expensive laboratory tests, which is its main advantage. [ABSTRACT FROM AUTHOR]

The intermolecular interaction among the calcium sensor, calmodulin (CaM), and the C-terminal domain of its cognate partner, transient receptor potential vanilloid 1 (TRPV1), plays a potential role in bone absorption and loss, which has been recognized as a new druggable target for osteoporosis therapy. Here, a synthetic strategy that integrates molecular modeling and chemometric analysis is used to statistically model and quantitatively predict the binding behavior of TRPV1 to CaM. The atomic-level complex structures of CaM protein with the congeneric sequences of TRPV1 C-terminus are modeled by virtual mutagenesis and structural refinement. Inter-residue nonbonded interactions in the computationally modeled complex structures are analyzed, characterized, and correlated with experimentally measured affinity of CaM binding to a series of TRPV1 C-terminal derivatives via both linear and nonlinear regression approaches. The built statistical predictors are then used to systematically investigate the independent residue-pair interactions across CaM-TRPV1 complex interface. Consequently, few TRPV1 C-terminal residues are identified as potential hot spots that are primarily responsible for the CaM-TRPV1 binding. Visual examination of CaM-TRPV1 complex architecture reveals that these hot spot residues are evenly distributed through the core helical region of TRPV1 Cterminus and involved in short-range nonbonded interactions such as hydrogen bonds and salt bridges, which confer specificity to the complex recognition and association. [ABSTRACT FROM AUTHOR]

The determination of the botanical/geographical origin of honey provides assurance of the product’s quality. In the present work, honeys from different ecoregions of Argentina were analysed, and the possible link between the complete pollen profile of honey samples and their volatile composition was evaluated by multivariate statistical tools. A total of 110 volatile compounds were found and semiquantified in honey samples. Redundancy analysis showed significant correlations between the volatile profile of honeys and their production region (P = .0002). According to the present results, 3,8- p -menthatriene; cyclopropylidenemethylbenzene; 1,1,6-trimethyl-1,2-dihydronaphthalene; 1,2,4-trimethylbenzene; α-pinene; isopropyl 2-methylbutanoate; cymene; 2,6-dimethyl-1,6-octadiene; 3-methyloctane; 1-(1,4-dimethyl-3-cyclohexen-1-yl)ethanone; terpinolene; ethyl 2-phenylacetate; naphthalene and 7 unknown compounds could be used to classify Argentinean honeys according to their geographical origin with a prediction success of 96%. Moreover, it could be concluded that honeys with Eucalyptus sp., Aristotelia chilensis and T. Baccharis pollen types presented some characteristic volatile compounds which could be used as floral markers. [ABSTRACT FROM AUTHOR]

The development of transgenic glyphosate-tolerant crops has revolutionized weed control in crops in many regions of the world. The early, non-destructive identification of superior plant phenotypes is an important stage in plant breeding programs. Here, glyphosate-tolerant transgenic maize and its parental wild-type control were studied at 2, 4, 6, and 8 days after glyphosate treatment. Visible and near-infrared hyperspectral imaging and chlorophyll fluorescence imaging techniques were applied to monitor the performance of plants. In our research, transgenic maize, which was highly tolerant to glyphosate, was phenotyped using these high-throughput nondestructive methods to validate low levels of shikimic acid accumulation and high photochemical efficiency of photosystem II as reflected by maximum quantum yield and non-photochemical quenching in response to glyphosate. For hyperspectral imaging analysis, the combination of spectroscopy and chemometric methods was used to predict shikimic acid concentration. Our results indicated that a partial least-squares regression model, built on optimal wavelengths, effectively predicted shikimic acid concentrations, with a coefficient of determination value of 0.79 for the calibration set, and 0.82 for the prediction set. Moreover, shikimic acid concentration estimates from hyperspectral images were visualized on the prediction maps by spectral features, which could help in developing a simple multispectral imaging instrument for nondestructive phenotyping. Specific physiological effects of glyphosate affected the photochemical processes of maize, which induced substantial changes in chlorophyll fluorescence characteristics. A new data-driven method, combining mean fluorescence parameters and featuring a screening approach, provided a satisfactory relationship between fluorescence parameters and shikimic acid content. The glyphosate-tolerant transgenic plants can be identified with the developed discrimination model established on important wavelengths or sensitive fluorescence parameters 6 days after glyphosate treatment. The overall results indicated that both hyperspectral imaging and chlorophyll fluorescence imaging techniques could provide useful tools for stress phenotyping in maize breeding programs and could enable the detection and evaluation of superior genotypes, such as glyphosate tolerance, with a non-destructive high-throughput technique. [ABSTRACT FROM AUTHOR]

Dye molecular aggregation and other interactions on clay mineral surfaces cause phenomena such as methachromasy (change in color), fluorescence enhancement, or quenching, which represent significant changes in the spectral properties of the dye. These phenomena can be used to control the photophysical properties of hybrid systems based on cationic organic dyes. In the present study, the aggregation of two structurally similar cyanine dyes, 3,3'-diethyl-oxocyanine iodide (OxCy) and 3,3'-diethyl-2,2'-thiacyanine iodide (ThCy), in colloidal dispersions of three smectites (saponite, hectorite, and montmorillonite) was studied by absorption and fluorescence spectroscopy for a broad range of dye/smectite loadings. Spectral data were analysed by chemometric methods (principal component analysis, PCA, and multivariate curve resolution, MCR). Detailed analysis of the OxCy absorption spectra by the chemometric methods revealed the formation of two types of oblique aggregates exhibiting light absorption in both H- and J-bands. The existence of such similar aggregates, with similar splitting of excitation energies, appears to be related to the existence of two stable conformational isomers of this dye. On increasing the smectite CEC and dye/smectite loading, fluorescence quenching occurred. The ThCy dye exhibited a stronger tendency for molecular aggregation than OxCy. On increasing the smectite CEC, the formation of oblique aggregates with dominant H-bands also increased. On aging of the hybrid dispersions, equilibria of ThCy aggregates were shifted to the species with dominant J-bands. This behavior had a significant impact on the shape and intensity of the fluorescence emission of the hybrid dispersions. Using different smectites enables control of the dye aggregation and significant change to the photophysical properties of the hybrid systems. These systems can be used for the detailed study of the photophysical properties of cyanine dyes in various states. The colloidal systems with cyanine dyes can be used as precursors for the preparation of novel hybrid materials. In addition, the sensitive response of the photophysical properties of cyanine dyes to the clay mineral surface can be applied to the characterization of clay minerals. [ABSTRACT FROM AUTHOR]

The molecular aggregation of organic dyes onto clay mineral particles is a very complex phenomenon including dye adsorption, the migration of dye molecules, rearrangement of initially formed aggregates, etc. Some details of this complex process are not yet fully understood. The objective of the present study was to understand the influence of dye surface concentration on the dynamic processes in dye molecular aggregation. A stopped-flow rapid mixing device was used for accurate measurements of the molecular aggregation of the cationic dye rhodamine 123 (R123) in montmorillonite (MntK) colloidal dispersions. The influence of dye surface concentration, which was changed by altering the ratio of the amount of R123 to the mass of MntK (nR123/mMntK), was examined in detail. Chemometric analysis was used to reconstruct the spectral matrix to obtain linearly uncorrelated spectral profiles of the major components and their concentrations at the respective reaction times. The conversion of isolated R123 cations into oblique J-aggregates (head-to-tail molecular assemblies) was observed over time and the existence of a J-dimers intermediate was hypothesized. The reaction kinetics followed a biphasic exponential function. An unexpected effect of dye surface concentration on R123 aggregation was observed: the initial formation of the molecular aggregates increased significantly with dye surface concentration, but an inverse trend was observed after longer reaction times. While dye aggregates were formed slowly at low dye loadings, systems with high R123/MntK ratios (nR123/mMntK) reached spectral stability after the first few seconds of the reaction. After longer reaction times, the greatest degree of dye aggregation was achieved in the dispersion of the lowest dye loading. Such a phenomenon is described for the first time. The results presented here are important for understanding the complex processes occurring in systems based on organic cations and clay minerals, and should be considered in the development of functional hybrid materials of dyes and nanoparticles with a layered structure. [ABSTRACT FROM AUTHOR]

The imitation of phase I metabolism of moclobemide and toloxatone, two monoamine oxidase type A (MAO-A) inhibitors, was performed with the use of titanium dioxide photocatalytic process. Ultra high pressure liquid chromatography system coupled with an accurate hybrid ESI-Q-TOF mass spectrometer was used for the evaluation of metabolic profiles, structural elucidation of the identified transformation products and quantitative analysis of the process. Based on high resolution MS and MS/MS data, eleven transformation products were characterized in photocatalytic experiments for moclobemide and seven products for toloxatone. A significant number of these products were found as hepatic metabolites under the incubation of the selected MAO-A inhibitors with human liver microsomes (HLM). What is important, some of these HLM metabolites are not yet described in the literature. It was also found that the multivariate chemometric analysis allowed an effortless characterization of the registered metabolic profiles which can be a useful method for a fast preliminary drug metabolism study. Additionally, principal component analysis (PCA) of the registered TOF (MS) photocatalytic and HLM profiles of moclobemide and toloxatone shows that shorter irradiation time is preferred for photocatalytic metabolism experiments. A heterogeneous photocatalysis with the use of titanium dioxide was found to be a powerful tool for mimicking phase I metabolic reactions, as a fast, sensitive and inexpensive method. [ABSTRACT FROM AUTHOR]

Farmed European sea bass (Dicentrarchus labrax, Linnaeus, 1758) were collected during 2016 from one Sicilian fish farm that uses two different rearing systems – sea cage and concrete tank – for determination of polychlorinated biphenyls (PCB), organochlorine pesticides (OCP) and polycyclic aromatic hydrocarbons (PAH) residues by HRGC-MS/MS. Moreover, commercial feed was analysed. This study aimed to determine whether the different rearing systems affect the concentration of these compounds, and to assess the safety of cultured fish. PCBs represent the pollutants with the highest concentration; in particular, PCB138 and 153 have the highest concentration in almost all samples. Among OCPs, only 4,4′-DDE, 4,4′-DDD and 4,4′-DDT residues have been detected. Concerning PAHs, only fluorene and phenanthrene were detected, in both rearing systems. Although some residues of organic pollutants were found in the analysed samples, they were always below the MRLs, so the results suggest that farmed sea bass are safe for human consumption. [ABSTRACT FROM PUBLISHER]

The objective of this study was to develop a method for authenticating organic milk samples in North Spain on the basis of its trace mineral composition. Fourteen elements in 98 samples were determined by inductively coupled plasma mass spectrometry. Although concentrations of Co, Cr, Cu, I, Se and Zn where statistically higher in conventional milk and As in organic, none of these elements by itself was able to discriminate between organic and conventional milk. The chemical data was examined by principal component analysis and cluster analysis, revealing a natural separation between organic and conventional milk. In a second step, several supervised pattern recognition techniques were used to construct mathematical models for predicting the type of milk (organic or conventional) based on the metal content. The results proved that the model constructed using the artificial neural network is capable of correctly identifying the type of milk in almost 95% of cases. [ABSTRACT FROM AUTHOR]

The paper focussed on the analysis of the environmental status of a natural wetland and the assessment of potential solutions to preserve the area, the related ecosystem services and natural equilibria. Data on water quality parameters and on climatic conditions were derived from a yearly monitoring campaign and web sources respectively. Chemometric techniques and a water quality index (WQI) were applied in order to assemble the obtained information and define an exhaustive overview of the wetland status. Data processing allowed to estimate the system water balance and to evaluate spatial and temporal variations of water quality. A water deficit as well as a major wetland sensitivity respect to pollution loads was verified during the warmer season (June-September). Local criticalities and environmental pressure were assessed and possible solutions to properly manage and restore the natural system were evaluated. The use of the wetland as a free water system (FWS) receiving treated wastewater from a local UWWTP was considered in the view of using local resources and restoring the water balance, avoiding environmental impacts and excessive management costs. Wetland auto-depurative capacity was assessed through common empirical plug flow models which revealed the ammonia nitrogen loads during the winter season as the limiting conditions. By deriving the maximum capacity of the system to receive pollutants, the study showed how water balance restorations as well as environmental and economic savings are achievable. Additional benefits have to be associated to ecosystem services and the possibility for recreational, cultural and educational activities. [ABSTRACT FROM AUTHOR]

Background: Citri Reticulatae Pericarpium is the dried mature pericarp of Citrus reticulata Blanco which can be divided into "Chenpi" and "Guangchenpi." "Guangchenpi" is the genuine Chinese medicinal material in Xinhui, Guangdong province; based on the greatest quality and least amount, it is most expensive among others. Hesperidin is used as the marker to identify Citri Reticulatae Pericarpium described in the Chinese Pharmacopoeia 2010. However, both "Chenpi" and "Guangchenpi" contain hesperidin so that it is impossible to differentiate them by measuring hesperidin. Objective: Our study aims to develop an efficient and accurate method to separate and identify "Guangchenpi" from other Citri Reticulatae Pericarpium. Materials and Methods: The genomic deoxyribonucleic acid (DNA) of all the materials was extracted and then the internal transcribed spacer 2 was amplified, sequenced, aligned, and analyzed. The secondary structures were created in terms of the database and website established by Jörg Schultz et al. High-performance liquid chromatography-diode array detection-electrospray Ionization/mass spectrometry (HPLC-DAD-ESI-MS)/MS coupled with chemometric analysis was applied to compare the differences in chemical profiles of the three kinds of Citri Reticulatae Pericarpium. Results: A total of 22 samples were classified into three groups. The results of DNA barcoding were in accordance with principal component analysis and hierarchical cluster analysis. Eight compounds were deduced from HPLC-DAD-ESI-MS/MS. Conclusions: This method is a reliable and effective tool to differentiate the three Citri Reticulatae Pericarpium. [ABSTRACT FROM AUTHOR]

Phage and antibiotic in raw milk poses significant risks for starter culture activity in fermented products. Therefore, rapid detection of phage and antibiotic contaminations in raw milk is a crucial process in dairy science. For this purpose, a preliminary novel method for detection of phage and antibiotic was developed by using Raman spectroscopy. Streptococcus thermophilus phages and ampicillin which are quite important elements in dairy industry were used as model. The phage and antibiotic samples were added to raw milk separately, and Raman measurements were carried out. The obtained spectra were processed with a chemometric method. In this study, it has been demonstrated that the presence of phage has a titer sufficient to stop the fermentation (10 pfu/ml), and antibiotic in a concentration which inhibits the growth of starter cultures (0.5 µg/ml) in raw milk could be discriminated through Raman spectroscopy with a short analysis time (30 min). [ABSTRACT FROM AUTHOR]

Hypericin (HY) is an excellent photoactive compound that has been investigated for the photodynamic treatment of cancer as well as for microorganism inactivation. In this study, chemometric analysis was applied for the first time on photodynamic assays to investigate the cytotoxicity of HY in tumor (HEp-2) and non-tumor (Vero and HUVEC) cell lines. The experimental planning was based on eight assays using the 2 3 full factorial design combining three important variables for PDT: photosensitizer concentrations, incubation time of cells in HY solutions and employed light dose (λ = 590 ± 10 nm). The statistical data analysis evidenced the relative significance of such variables and the correlations among them on the cell death. The chemometric results suggested that long incubation time and a low HY concentration and/or light dose allow killing selectively tumor cells. The chemometric analysis could be a new useful empiric method to a previous prediction of the IC 50 . In this study, the estimated values were in agreement with the experimental IC 50 values. [ABSTRACT FROM AUTHOR]

Acute leukaemia (AL) is a critical neoplasm of white blood cells. Diagnosing AL requires bone marrow puncture procedure, which many patients do not consent to for it is invasive. Hence sensitive and specific early diagnostic biomarkers are essential for non-invasive diagnosis, new therapeutics and improving the disease prognosis. To differentiate the metabolic alterations associated with acute lymphoblastic leukaemia (ALL) and acute myeloid leukaemia (AML), we investigated serum of ALL and AML patients in comparison with two controls using gas chromatography coupled with triple quadrupole tandem mass spectrometry and multivariate statistical analysis. Twenty seven out of 1425 metabolites were found differentiative among ALL, AML, aplastic anaemia (APA) patients and healthy control using p-value ≤ 0.001. ALL is the most dissimilar group from other three groups as in hierarchical clustering showed 72.1% dissimilarity. Model generation using PLSDA gave an overall accuracy of 91.9%. This study helps in metabolic fingerprinting of control and disease serum at high significance levels and could be used for early diagnosing of AL. Based on pathways analysis, fatty acid metabolism is deregulated in patients with AL and may represent an underlying metabolic pathway associated with disease progression. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Sesame oil is popular in China and many other Asian countries due to its pleasant flavor and high nutritional value. Sesame oil essence is often illegally added to other vegetable oils to counterfeit sesame oil. This study aimed to propose a rapid and cost-effective method, which could help to identify the sesame oil and counterfeit sesame oil. For this purpose, the counterfeit samples were prepared by adding essence to inferior oils (soybean oil, sunflower oil, canola oil, corn oil), all oil samples were examined and their Raman spectra served as data for the construction of the soft independent modeling of class analogy (SIMCA) models and the important variables for distinguishing between authentic and counterfeit sesame oil were selected by orthogonal partial least squares discriminant analysis. The results showed that SIMCA is a strong chemometric technique for classification of authentic sesame oils and the types of counterfeit sesame oil samples based on Raman spectra, and a total 100% correct classification rate of sesame oil could be achieved. The methods allowed the identified counterfeit sesame oil in commercial sesame oil samples, opening the door to further research into the counterfeit detection of other liquid foods. • A rapid detection method for counterfeit sesame oil based on Raman spectra was developed. • OPLS-DA was successfully applied for the selection of important variables from Raman spectra. • The model based on the selected variables by SIMCA yielded the perfect results. [ABSTRACT FROM AUTHOR]