Optimization of the Erythrosine-mediated photodynamic therapy against Escherichia coli using response surface methodology.

BACKGROUND: The efficacy of photodynamic therapy (PDT) depends on the combination of light and a photosensitizer for inactivation of microorganisms. However, finding the ideal conditions for the factors involved in this technique is time and cost-consuming. The rotational composite central design (RCCD) is a tool that can be allied with PDT to achieve precise results within a shorter working time. METHODS: This study used the response surface methodology to optimize the parameters of PDT mediated by Erythrosine (ERY) and green light-emitting diodes (LED) in different Escherichia coli strains by applying RCCD. RESULTS: The RCCD predicted optimum values of ERY and light exposure on PDT. According to the experimental results, the light exposure time showed the most significant influence on the inactivation of the evaluated bacteria. The optimized operating conditions were validated in laboratory tests, and no viable cells were recovered with ERY at 116 µmol L-1 and 30 min of light (33.34 J cm2) for E. coli ATCC 25922, 108 µmol L-1 and 40 min (44.38 J cm2) for E. coli ATCC 35218, and 108 µmol L-1 and 29.3 min (32.5 J cm2) for E. coli O157:H7 EDL 933. CONCLUSION: The adjusted polynomial models provided accurate information on the combined effects of ERY and lighting time with green LED on PDT. The application of the RCCD, in addition to reducing the number of experiments, also allows for increased quantity and quality of the results. Therefore, surface response methodology combined with PDT is a promising approach to inactivate E. coli.

Optimization of the extraction of phenolic compounds from the leaves of yerba mate (Ilex paraguariensis) through high hydrostatic pressure system using mixture design with process variables.

In this study, a mixture design with process variables was used to optimize the extraction of total phenolic compounds (TPC) from yerba mate leaves through high hydrostatic pressure extraction. The studied variables were pressure (50, 100, and 150 MPa), extraction time (10, 20, and 30 min), and solvent (water, glycerin, and 50% v/v water/50% v/v glycerin). The multiple linear regression model presented an excellent fit (R2 adjusted of 0.9792) and demonstrated the major influence of glycerin content on the water/glycerin mixture solvent for TPC extraction. Optimal process conditions obtained were 69% v/v water, 31% v/v glycerin, 50 MPa pressure, and 10 min time. PRACTICAL APPLICATION: The paper describes a novel extraction method to obtain phenolic compounds from yerba mate (compounds that can replace synthesized antioxidants in the food industry) using high hydrostatic pressure and environmentally friendly solvents. The extraction process was studied to optimize its performance, obtaining more phenolic compounds from the same amount of yerba mate.

Detection of adulteration in Eragrostis tef (Zucc.) Trotter flour using EDXRF and ComDim-MLR data fusion.

The teff cereal gained worldwide attention because it is gluten-free and rich in iron; thus, its flour is subject to fraud. This study evaluated the ability of Energy Dispersive X-Ray Fluorescence Spectroscopy (EDXRF) to identify teff flours adulterated with rice, whole wheat, oat, and rye flours. The adulteration followed a {5,4} simplex-lattice design. After smoothing and pretreatments, 15 kV and 50 kV spectra were fused by Common Dimension Analysis (ComDim). Multiple Linear Regression (MLR) models using EDXRF-ComDim scores and percentage of teff were adjusted. The best model presented four common dimensions (CD), r2prediction = 0.8534, low RMSEP (0.0564), and absence of overfitting. The obtained model was robust to quantify adulteration in teff flour even with the differences in the intensity of EDXRF spectra of different crops. Therefore, EDXRF, in tandem with ComDim data fusion, was an efficient tool for the adulteration control of teff flours.

Successful combination of benchtop nuclear magnetic resonance spectroscopy and chemometric tools: A review.

Low-field nuclear magnetic resonance (NMR) has three general modalities: spectroscopy, imaging, and relaxometry. In the last twelve years, the modality of spectroscopy, also known as benchtop NMR, compact NMR, or just low-field NMR, has undergone instrumental development due to new permanent magnetic materials and design. As a result, benchtop NMR has emerged as a powerful analytical tool for use in process analytical control (PAC). Nevertheless, the successful application of NMR devices as an analytical tool in several areas is intrinsically linked to its coupling with different chemometric methods. This review focuses on the evolution of benchtop NMR and chemometrics in chemical analysis, including applications in fuels, foods, pharmaceuticals, biochemicals, drugs, metabolomics, and polymers. The review also presents different low-resolution NMR methods for spectrum acquisition and chemometric techniques for calibration, classification, discrimination, data fusion, calibration transfer, multi-block and multi-way.

Can Near-Infrared Spectroscopy Replace a Panel of Tasters in Sensory Analysis of Dry-Cured Bísaro Loin?

This study involved a comprehensive examination of sensory attributes in dry-cured Bísaro loins, including odor, androsterone, scatol, lean color, fat color, hardness, juiciness, chewiness, flavor intensity and flavor persistence. An analysis of 40 samples revealed a wide variation in these attributes, ensuring a robust margin for multivariate calibration purposes. The respective near-infrared (NIR) spectra unveiled distinct peaks associated with significant components, such as proteins, lipids and water. Support vector regression (SVR) models were methodically calibrated for all sensory attributes, with optimal results using multiplicative scattering correction pre-treatment, MinMax normalization and the radial base kernel (non-linear SVR model). This process involved partitioning the data into calibration (67%) and prediction (33%) subsets using the SPXY algorithm. The model parameters were optimized via a hybrid algorithm based on particle swarm optimization (PSO) to effectively minimize the root-mean-square error (RMSECV) derived from five-fold cross-validation and ensure the attainment of optimal model performance and predictive accuracy. The predictive models exhibited acceptable results, characterized by R-squared values close to 1 (0.9616-0.9955) and low RMSE values (0.0400-0.1031). The prediction set's relative standard deviation (RSD) remained under 5%. Comparisons with prior research revealed significant improvements in prediction accuracy, particularly when considering attributes like pig meat aroma, hardness, fat color and flavor intensity. This research underscores the potential of advanced analytical techniques to improve the precision of sensory evaluations in food quality assessment. Such advancements have the potential to benefit both the research community and the meat industry by closely aligning their practices with consumer preferences and expectations.

Semi-Quantitative Discrimination of Honey Adulterated with Cane Sugar Solution by an ETongue.

This study successfully applied a potentiometric E-tongue with 20 cross-selectivity lipidic polymeric membranes in the discrimination of three semi-quantitative groups, that represented the following intervals of honey adulteration percentage with cane sugar: 0 %; [0, 10]%; [10, 20]% of adulteration. We analysed five different types of Portuguese honey; five brands of cane sugar were added to the adulterated samples; a comparative analysis was then performed. Linear discriminant analysis coupled with a tabu search algorithm for feature selection was applied to the ETongue's analytical data to select the best model. A discriminant model with 12 sensors was obtained. This model classified correctly all samples in both in internal (train data, 15 samples) and external validation (test data,10 samples). Also, multiple linear regression with tabu search was applied to verify if ETongue's data would allow quantifying the honey's adulteration level. The results showed that it was possible to obtain a quantitative model but with unsatisfactory predictive performance in the test data group (external validation), giving, in general, values below the expected concentrations. E-tongue is a real-time green, flexible and low-cost analytical tool that requires minimum sample preparation and no special technical skills, being a promising tool for everyday application.

Non-Invasive Method to Predict the Composition of Requeijão Cremoso Directly in Commercial Packages Using Time Domain NMR Relaxometry and Chemometrics.

Low Field Time-Domain Nuclear Magnetic Resonance (TD-NMR) relaxometry was used to determine moisture, fat, and defatted dry matter contents in "requeijão cremoso" (RC) processed cheese directly in commercial packaged (plastic cups or tubes with approximately 200 g). Forty-five samples of commercial RC types (traditional, light, lactose-free, vegan, and fiber) were analyzed using longitudinal (T1) and transverse (T2) relaxation measurements in a wide bore Halbach magnet (0.23 T) with a 100 mm probe. The T1 and T2 analyses were performed using CWFP-T1 (Continuous Wave Free Precession) and CPMG (Carr-Purcell-Meiboom-Gill) single shot pulses. The scores of the principal component analysis (PCA) of CWFP-T1 and CPMG signals did not show clustering related to the RC types. Optimization by variable selection was carried out with ordered predictors selection (OPS), providing simpler and predictive partial least squares (PLS) calibration models. The best results were obtained with CWFP-T1 data, with root-mean-square errors of prediction (RMSEP) of 1.38, 4.71, 3.28, and 3.00% for defatted dry mass, fat in the dry and wet matter, and moisture, respectively. Therefore, CWFP-T1 data modeled with chemometrics can be a fast method to monitor the quality of RC directly in commercial packages.

E-sensing and nanoscale-sensing devices associated with data processing algorithms applied to food quality control: a systematic review.

Devices of human-based senses such as e-noses, e-tongues and e-eyes can be used to analyze different compounds in several food matrices. These sensors allow the detection of one or more compounds present in complex food samples, and the responses obtained can be used for several goals when different chemometric tools are applied. In this systematic review, we used Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines, to address issues such as e-sensing with chemometric methods for food quality control (FQC). A total of 109 eligible articles were selected from PubMed, Scopus and Web of Science. Thus, we predicted that the association between e-sensing and chemometric tools is essential for FQC. Most studies have applied preliminary approaches like exploratory analysis, while the classification/regression methods have been less investigated. It is worth mentioning that non-linear methods based on artificial intelligence/machine learning, in most cases, had classification/regression performances superior to non-liner, although their applications were seen less often. Another approach that has generated promising results is the data fusion between e-sensing devices or in conjunction with other analytical techniques. Furthermore, some future trends in the application of miniaturized devices and nanoscale sensors are also discussed.

Data fusion of middle-resolution NMR spectroscopy and low-field relaxometry using the Common Dimensions Analysis (ComDim) to monitor diesel fuel adulteration.

Medium-resolution (MR-NMR) and time-domain NMR relaxometry (TD-NMR) using benchtop and low-field NMR instruments are powerful tools to tackle fuel adulteration issues. In this work, for the first time, we investigate the possibility of enhancing the low-field NMR capability on fuel analysis using data fusion of MR and TD-NMR. We used the ComDim (Common Dimensions Analysis) multi-block analysis to join the data, which allowed exploration, classification, and quantification of common adulterations of diesel fuel by vegetable oils, biodiesel, and diesel of different sources as well as the sulfur content. After data exploration using ComDim, classification (applying linear discriminant analysis, LDA), and regression (applying multiple linear regression, MLR), models were built using ComDim scores as input variables on the LDA and MLR analyses. This approach enabled 100% of accuracy in classifying diesel fuel source (refinery), sulfur content (S10 or S500), vegetable oil, and biodiesel source. Moreover, in the quantification step, all MLR models showed a root mean square error of prediction (RMSEP) and the residual prediction deviation (RPD) values comparable to the literature for determining diesel, vegetable oil, and biodiesel contents.

Compact low-field NMR spectroscopy and chemometrics applied to the analysis of edible oils.

Compact nuclear magnetic resonance (NMR) spectroscopy combined with chemometric tools opens new perspectives for NMR use. This work compares the potential of 43, 60 and 400 MHz NMR spectroscopy for quality control of edible oils. Partial least squares regression (PLSR) and support vector regression (SVR) models built on the three NMR devices had equivalent performances for fatty acids and iodine value, and the models built with the low field spectra were equivalent to the high field. Moreover, performances for calibration indicated that most of the models built with medium/or high-resolution fields presented reproducibility values lower than the minimum accepted by the American Oil Chemists' Society (AOCS). Compared to classical methods, this new approach allows the application of medium resolution devices as a sample screening tool in analytical laboratories since it allows the spectrum obtention in a few seconds, without the need for sample preparation or the use of deuterated solvents.

Analytical validation of an ultraviolet-visible procedure for determining vitamin D3 in vitamin D3-loaded microparticles and toxigenetic studies for incorporation into food.

Vitamin D is a water-insoluble compound presented in two main forms (D2 and D3), susceptible to environmental conditions. Microencapsulation is an alternative to supplements and preserve vitamin D properties in foods. Entrapment efficiency (EE) is the main property to evaluate the encapsulation effectiveness and therefore it is of interest the study of analytical methods for the identification and quantification of this compound within the particle. This paper describes a low cost UV-Vis methodology validation to the identification and quantification of vitamin D3 in microparticles produced by hot homogenization. The method was validated following the International Conference on Harmonization (ICH) guidelines. To guarantee safe application in foodstuff, microparticles toxigenicity was evaluated with Allium cepa L. in vivo model, showing no cytotoxic nor genotoxic potential. High entrapment efficiency was obtained, the results also demonstrated that the concentration of vitamin D3 in microparticles can be safely accessed by the validated method.

pH interferes in photoinhibitory activity of curcumin nanoencapsulated with pluronic® P123 against Staphylococcus aureus.

Microbial contamination control is a public health concern and challenge for the food industry. Antimicrobial technologies employing natural agents may be useful in the food industry for these purposes. This work aimed to investigate the effect of photodynamic inactivation using curcumin in Pluronic® P123 nanoparticles (Cur/P123) at different pH and blue LED light against Staphylococcus aureus. Bacterial photoinactivation was conducted using different photosensitizer concentrations and exposure times at pH 5.0, 7.2 and 9.0. A mixture design was applied to evaluate the effects of exposure time (dark and light incubation) on the photoinhibitory effect. S. aureus was completely inactivated at pH 5.0 by combining low concentrations of Cur/P123 (7.80-30.25 µmol/L) and light doses (6.50-37.74 J/cm2). According to the mathematical model, dark incubation had low significance in bacterial inactivation at pH 5.0 and 9.0. No effect in bacterial inactivation was observed at pH 7.2. Cur/P123 with blue LED was effective in inactivating S. aureus. The antimicrobial effect of photodynamic inactivation was also pH-dependent.

Endogenous antioxidant properties of curcuminoids from Curcuma longa L. obtained by a single-step extraction/nanoencapsulation approach.

Curcuminoids found in turmeric have attracted attention due to their remarkable biological activity. Nanoencapsulation may improve their technological properties, but extraction and encapsulation procedures could be time-consuming and expensive when carried out separately. This work aimed to combine extraction and nanoencapsulation steps to obtain curcuminoids-polyvinylpyrrolidone (PVP) nanoparticles directly from plant rhizomes. This single-step procedure was evaluated by a Rotatable Central Composite Design (RCCD) and optimized using desirability functions, resulting in the optimal conditions of temperature (29.9°C), ethanol (99%), and PVP (15.38 mg). Nanoencapsulation allowed curcuminoids to exert scavenging activity against superoxide anions donors and hydrogen peroxide in an aqueous medium, despite their poor water solubility. Curcuminoids-PVP nanoparticles could be used to formulate nutraceutical foods as an adjuvant to the endogenous antioxidant defense systems protecting against cellular damage. PRACTICAL APPLICATION: Simultaneous extraction and nanoencapsulation of curcuminoids from turmeric (Curcuma longa L.) was studied in this work. The combination of two processes in one single step reduces production time and costs, enhancing the feasibility of curcuminoids microparticles application into foodstuff. Moreover, since most foodstuff presents water in their composition, increase of curcuminoids water dispersibility could facilitate their incorporation into food matrices and improve the use of their health benefits, as results from this research demonstrated that encapsulated curcuminoids were able to scavenge reactive oxygen species in aqueous medium, even though they are lipophilic compounds.

Calibration Transfer of Partial Least Squares Regression Models between Desktop Nuclear Magnetic Resonance Spectrometers.

Low-field proton nuclear magnetic resonance (LF-1H NMR) devices based on permanent magnets are a promising analytical tool to be extensively applied to the process analytical chemistry scenario. To enhance its analytical applicability in samples where the spectral resolution is compromised, multivariate regression methods are required. However, building a robust calibration model, such as partial least squares (PLS) regression, is a laborious task because (1) the number of measurements required during the calibration process is large and (2) the procedure must be repeated when the instrument is changed or after a certain period due to the long-term stability of the instrument. Thus, the present work describes the application of calibration transfer methodologies (direct standardization (DS), piece-wise direct standardization (PDS), and double-window piece-wise direct standardization (DWPDS)) on LF-1H NMR to exempt the necessity of a recalibration procedure when moving from the original spectrometer to a second one with the same, lower, or higher magnetic field. These calibration transfer methodologies were tested with PLS models built on a 60 MHz (for the proton Larmor frequency) spectrometer to predict the specific gravity (SG), distillation temperature (T50%), and final boiling point (FBP) of commercial gasoline. The results showed that the DWPDS method applying only 2 to 7 transference samples enables the transference of all PLS models built on the primary instrument (60 MHz) to other (43, 60, and 80 MHz) different instruments, reaching the same RMSEP values as the primary instrument: 1.2 kg/m3 for SG, 5.1 °C for FBP, and 1.1 °C for T50%.

Hypericin-mediated photoinactivation of polymeric nanoparticles against Staphylococcus aureus.

Photoinactivation is a promising technique for Staphylococcus aureus control. This microorganism causes foodborne diseases (DTAs) and forms biofilms that are highly resistant and difficult to eradicate. Thus, the aim of this study was to evaluate the photodynamic activity of hypericin (HYP) in polymeric nanoparticles (Pluronic® P123) against S. aureus planktonic and biofilm cells. Planktonic cells and biofilms of S. aureus (ATCC 25923) were subjected to photoinactivation using low-power orange LED (0.3 mW/cm²) with different HYP formulation concentrations in Pluronic® P123. The P123 molar ratios were 2.5 (HYP/P123-2.5) and 10 (HYP/P123-10), respectively. The treatment times for planktonic cells were proposed by a mixture design, and bacterial photoinactivation was observed in concentrations of 12.5 to 3.12 µmol/L for HYP/P123-2.5 and reductions of ∼ 4.0 log CFU/mL in 12.5 to 0.78 µmol/L for HYP/P123-10. For biofilms, 30 min of darkness and 30 min of illumination were used. Maximum reductions were similar for both formulations and corresponded to approximately 0.9 log CFU/cm². It was concluded that photoinactivation with longer lighting times was effective against planktonic cells and could be potentially applied to control S. aureus.

Application of Response Surface Methodology to Evaluate Photodynamic Inactivation Mediated by Eosin Y and 530 nm LED against Staphylococcus aureus.

Photodynamic antimicrobial chemotherapy (PAC) is an efficient tool for inactivating microorganisms. This technique is a good approach to inactivate the foodborne microorganisms, which are responsible for one of the major public health concerns worldwide-the foodborne diseases. In this work, response surface methodology (RSM) was used to evaluate the interaction of Eosin Y (EOS) concentration and irradiation time on Staphylococcus aureus counts and a sequence of designed experiments to model the combined effect of each factor on the response. A second-order polynomial empirical model was developed to describe the relationship between EOS concentration and irradiation time. The results showed that the derived model could predict the combined influences of these factors on S. aureus counts. The agreement between predictions and experimental observations (R2adj = 0.9159, p = 0.000034) was also observed. The significant terms in the model were the linear negative effect of photosensitizer (PS) concentration, followed by the linear negative effect of irradiation time, and the quadratic negative effect of PS concentration. The highest reductions in S. aureus counts were observed when applying a light dose of 9.98 J/cm2 (498 nM of EOS and 10 min. irradiation). The ability of the evaluated model to predict the photoinactivation of S. aureus was successfully validated. Therefore, the use of RSM combined with PAC is a promising approach to inactivate foodborne pathogens.

Tailoring swelling of alginate-gelatin hydrogel microspheres by crosslinking with calcium chloride combined with transglutaminase.

Alginate-based hydrogels can find uses in a wide range of applications, including in the encapsulation field. This type of hydrogels is usually ionically crosslinked using calcium sources giving rise to products with limited internal crosslinking. In this work, it is hypothesized that the combination of alginate crosslinked by calcium chloride (external crosslinking; ionic mechanism) with gelatin crosslinked by transglutaminase (internal crosslinking; enzymatic induced mechanism) can be used to tailor the swelling behavior of alginate-based hydrogel microspheres. A systematic study was conducted by covering process variables such as gelatin content, TGase concentration, and CaCl2 contact time, added by statistic tools as central composite rotatable design (CCRD), principal component analysis (PCA) and multiobjective optimization, to map their effect on the resulting water content after production (expressed as swelling ratio), and swelling properties at pH 3 and 7. Among the studied variables, particle's swelling was mostly affected by the gelatin content and transglutaminase concentration.

The nanoencapsulation of curcuminoids extracted from Curcuma longa L. and an evaluation of their cytotoxic, enzymatic, antioxidant and anti-inflammatory activities.

Curcumin, bisdemethoxycurcumin and demethoxycurcumin are the main curcuminoids present in Curcuma longa L. and are known for their bioactivity. However, their low water solubility results in poor bioavailability and therapeutic efficacy. This work aimed to investigate the in vitro modulation capacity on the enzymes acetylcholinesterase (AChE) and glutathione S-transferase (GST), as well as the in vitro antioxidant (OxHLIA and TBARS) and anti-inflammatory activities (RAW 264.7 test) of nanoencapsulated curcuminoids. Cytotoxicity on tumor and non-tumor cell lines was also investigated. Curcuminoid nanoparticles significantly inhibited the in vitro activity of AChE (12% inhibition at 50 µM) and GST (30% inhibition at 5 µM). They presented antioxidant activity and toxic effects against breast adenocarcinoma, lung, cervical and hepatocellular carcinoma cells when dispersed in water. Encapsulated curcuminoids exhibited bioactive properties in aqueous medium (no hydrophobic solvent added), exerting antioxidant and cytotoxic effects and acting on the cholinergic and endogenous antioxidant systems.

Multi-block analysis for the correlation of physico-chemical and rheological data of 42 fruit pulps.

The common dimension (ComDim) chemometric method for multi-block analysis and hierarchical cluster analysis (HCA) were used to evaluate the data obtained from the physico-chemical and rheological characterization of 42 commercial fruit pulps. The physico-chemical characteristics and the rheological behavior of the pulps were found to be considerably different. The Herschel-Bulkley equation was fit to the steady-state flow curves of the fruit pulps, and it was found to appropriately describe the materials, which showed a wide range of yield stresses. The soluble solids content and the yield stress were the main factors responsible for the sample discrimination in the multivariate statistical analysis. The ComDim model indicates that these parameters may have a direct correlation. Namely, the soluble solids amount can influence the viscosity, as demonstrated by the similar scores of the samples in both common components, and this corroborated with the HCA analysis. PRACTICAL APPLICATIONS: Fruit pulps can be used as raw materials in the food industry to obtain several products, such as nectars, jellies, ice creams, and juices, which can also be sold directly to consumers. To evaluate the technical and economic feasibility of those industrial processes, it is important to know the physico-chemical properties of the products. Therefore, in this study we attempt to correlate the physical-chemical and rheological data using a new statistical approach.

Systematic study on the extraction of antioxidants from pinhão (araucaria angustifolia (bertol.) Kuntze) coat.

Food by-products containing bioactive substances have attracted attention due to the possibility of adding values to residues of the food industry. In this work, the extraction of phenolic compounds from pinhão seed coats (Araucaria angustifolia (Bertol.) Kuntze) using a central composite rotatable design was applied to obtain prediction models for the extract volume yield, total phenolic content, total phenolic acids and total flavonoids. Principal component analysis and hierarchical cluster analysis were implemented showing an evident poor effect of the temperature on phenolic compounds extraction, which is in accordance with the prediction model obtained by the experimental design for total phenolic acids. Volume yield presented a high positive correlation with extraction temperature, followed by solvent composition. Scanning electron microscopy showed that higher temperatures and lower ethanol percentages resulted in highly defibrillated pinhão coats that retained more extract after the extraction process, leading to lower volume yield percentages.