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This study introduces a novel method for the quantification of malachite green (MG), a pervasive cationic dye, in surface water by synergizing multiphase electroextraction (MPEE) with digital image analysis (DIA) and partial least square discriminant analysis. Aimed at addressing the limitations of conventional DIA methods in terms of quantitation limits and selectivity, this study achieves a significant breakthrough in the preconcentration of MG using magnesium silicate as a novel sorbent. Demonstrating exceptional processing efficiency, the method allows for the analysis of 10 samples within 20 min, exhibiting remarkable sensitivity and specificity (over 0.95 and 0.90, respectively) across 156 samples in both training and test sets. Notably, the method detects MG at low concentrations (0.2 µg L -1 ) in complex matrices, highlighting its potential for broader application in environmental monitoring. This approach not only underscores the method's cost-effectiveness and simplicity but also its precision, making it a valuable tool for the preliminary testing of MG in surface waters. This study underscores the synergy among MPEE, DIA, and chemometric tools, presenting a cost-efficient and reliable alternative for the sensitive detection of water contaminants., (© 2024 Wiley‐VCH GmbH.)

Since hop secondary metabolites have a direct correlation with the quality of beer and other hop-based beverages, and the volatile fraction of hop has a complex composition, requiring effective separation, here we explore the application of headspace solid-phase microextraction as a sample preparation method, coupled with comprehensive two-dimensional gas chromatography-mass spectrometry (GC×GC-MS) analysis. The methodology involved the use of a DVB/PDMS fibre with 500 mg of hop cone powder, extracted for 40 min at 50 °C, for both GC-MS and GC×GC-MS. The varieties Azacca, Cascade, Enigma, Loral, and Zappa were studied comprehensively. The results demonstrate that GC×GC-MS increases the number of peaks by over 300% compared to classical GC-MS. Overall, 137 compounds were identified or tentatively identified and categorised into 10 classes, representing between 87.6% and 96.9% of the total peak area. The composition revealed the highest concentration of sesquiterpene hydrocarbons for Enigma, whilst Zappa showed a relatively significant concentration of monoterpene hydrocarbons. Principal component analysis for all compounds and classes, along with hierarchical cluster analysis, indicated similarities between Zappa and Cascade, and Azacca and Loral. In conclusion, this method presents an optimistic advancement in hop metabolite studies with a simple and established sample preparation procedure in combination with an effective separation technique.

Gas chromatography-mass spectrometry (GC-MS), physicochemical and microbiological analyses, sensory descriptive evaluation, and multivariate analyses were applied to evaluate the efficiencies of microfiltration and pasteurization processes during the shelf life of beer. Samples of microfiltered and pasteurised beer were divided into fresh and aged groups. A forced ageing process, which consisted of storing fresh samples at 55° C for 6 days in an incubator and then keeping them under ambient conditions prior to analysis, was applied. Physicochemical analysis showed that both microfiltered and pasteurised samples had a slight variation in apparent extract, pH, and bitterness. The samples that underwent heat treatment had lower colour values compared with those that were microfiltered. Chromatographic peak areas of vicinal diketones increased in both fresh and aged samples. The results of the microbiological analysis revealed spoilage lactic acid bacteria ( Lactobacillus ) and yeasts ( Saccharomyces and non-Saccharomyces) in fresh microfiltered samples. In the GC-MS analysis, furfural, considered by many authors as a heat indicator, was detected only in samples that underwent forced ageing and not in samples that were subjected to thermal pasteurisation. Finally, sensory analysis found differences in the organoleptic properties of fresh microfiltered samples compared with the rest of the samples.

A recent case of contamination of some batches of a Brazilian beer brand with diethylene glycol (DEG) had great repercussion, resulting in at least seven deaths. In this article, a direct method was developed for the rapid detection of DEG in beer samples based on portable near-infrared spectroscopy combined with partial least squares discriminant analysis (PLS-DA). The discriminant model was built with 100 uncontaminated beer samples and 100 samples containing DEG in a concentration range between 10 and 1000 mg L -1 , totalizing 200 samples of different brands and styles. The method was validated by estimating figures of merit, such as false positive and false negative rates, sensitivity, specificity, accuracy, accordance, and concordance. The decision limit (CCα) of the method was 52 mg L -1 and the detection capability (CCβ) was 106 mg L -1 . This method does not consume reagents/solvents and can be suitable for the beer industry quality control or forensic investigations., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

The Brazilian cerrado is considered one of the most critical biomes in the world. Araticum (Annona crassiflora Mart.) is a native plant from the Brazilian cerrado, abundant in nutrients and highly energetic. This study aimed to obtain chemical fingerprints of different parts of the araticum fruit, i.e. pulp, peel, and seed. Extracts from these three parts were prepared using different solvents (ethanol, water, and mixtures of ethanol and water) and later analyzed by paper spray ionization mass spectrometry. In general, ethanol extracted more metabolites than the other solvents. The chemical profiles varied according to the fruit part, geographic location, and extractor solvent. Among the metabolites, acetogenins (62.3%) and alkaloids (20.7%) predominated. Principal component analyses revealed that the samples were grouped according to the fruit part, regardless of the extractor solvent used. Araticum shows remarkable potential due to the beneficial properties of the metabolites for human health. The insertion of araticum in the human diet is still underexplored but is a promising alternative., Competing Interests: Declaration of Competing Interest 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., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

The Specialty Coffee Association (SCA) sensory analysis protocol is the methodology that is used to classify specialty coffees. However, because the sensory analysis is sensitive to the taster's training, cognitive psychology, and physiology, among other parameters, the feasibility of instrumental approaches has been recently studied for complementing such analyses. Spectroscopic methods, mainly near infrared (NIR) and mid infrared (FTIR-Fourier Transform Infrared), have been extensively employed for food quality authentication. In view of the aforementioned, we compared NIR and FTIR to distinguish different qualities and sensory characteristics of specialty coffee samples in the present study. Twenty-eight green coffee beans samples were roasted (in duplicate), with roasting conditions following the SCA protocol for sensory analysis. FTIR and NIR were used to analyze the ground and roasted coffee samples, and the data then submitted to statistical analysis to build up PLS models in order to confirm the quality classifications. The PLS models provided good predictability and classification of the samples. The models were able to accurately predict the scores of specialty coffees. In addition, the NIR spectra provided relevant information on chemical bonds that define specialty coffee in association with sensory aspects, such as the cleanliness of the beverage.

Spectrofluorimetry combined with multiway chemometric tools were applied to discriminate pure Aroeira honey samples from samples adulterated with corn syrup, sugar cane molasses and polyfloral honey. Excitation emission spectra were acquired for 232 honey samples by recording excitation from 250 to 500 nm and emission from 270 to 640 nm. Parallel factor analysis (PARAFAC), partial least squares discriminant analysis (PLS-DA), unfolded PLS-DA (UPLS-DA) and multilinear PLS-DA (NPLS-DA) methods were used to decompose the spectral data and build classification models. PLS-DA models presented poor classification rates, demonstrating the limitation of the traditional two-way methods for this dataset, and leading to the development of three-way classification models. Overall, UPLS-DA provided the best classification results with misclassification rates of 4% and 8% for the training and test sets, respectively. These results showed the potential of the proposed method for routine laboratory analysis as a simple, reliable, and affordable tool., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Acute kidney injury (AKI) in hospitalized patients with COVID-19 is associated with higher mortality and a worse prognosis. Nevertheless, most patients with COVID-19 have mild symptoms, and about 5% can develop more severe symptoms and involve hypovolemia and multiple organ dysfunction syndrome. In a pathophysiological perspective, severe SARS-CoV-2 infection is characterized by numerous dependent pathways triggered by hypercytokinemia, especially IL-6 and TNF-alpha, leading to systemic inflammation, hypercoagulability, and multiple organ dysfunction. Systemic endotheliitis and direct viral tropism to proximal renal tubular cells and podocytes are important pathophysiological mechanisms leading to kidney injury in patients with more critical infection, with a clinical presentation ranging from proteinuria and/or glomerular hematuria to fulminant AKI requiring renal replacement therapies. Glomerulonephritis, rhabdomyolysis, and nephrotoxic drugs are also associated with kidney damage in patients with COVID-19. Thus, AKI and proteinuria are independent risk factors for mortality in patients with SARS-CoV-2 infection. We provide a comprehensive review of the literature emphasizing the impact of acute kidney involvement in the evolutive prognosis and mortality of patients with COVID-19.

Kidney impairment in hospitalized patients with SARS-CoV-2 infection is associated with increased in-hospital mortality and worse clinical evolution, raising concerns towards patients with chronic kidney disease (CKD). From a pathophysiological perspective, COVID-19 is characterized by an overproduction of inflammatory cytokines (IL-6, TNF-alpha), causing systemic inflammation and hypercoagulability, and multiple organ dysfunction syndrome. Emerging data postulate that CKD under conservative treatment or renal replacement therapy (RRT) is an important risk factor for disease severity and higher in-hospital mortality amongst patients with COVID-19. Regarding RAAS blockers therapy during the pandemic, the initial assumption of a potential increase and deleterious impact in infectivity, disease severity, and mortality was not evidenced in medical literature. Moreover, the challenge of implementing social distancing in patients requiring dialysis during the pandemic prompted national and international societies to publish recommendations regarding the adoption of safety measures to reduce transmission risk and optimize dialysis treatment during the COVID-19 pandemic. Current data convey that kidney transplant recipients are more vulnerable to more severe infection. Thus, we provide a comprehensive review of the clinical outcomes and prognosis of patients with CKD under conservative treatment and dialysis, and kidney transplant recipients and COVID-19 infection.

In this work, a new large-volume multiphase, multi-sample electroextraction device was developed and applied to selectively extract malachite green (MG) from water samples. This device was easily constructed with ordinary materials and capable of extracting ten samples simultaneously, obtaining MG preconcentrated on a solid support, to fit into a pipette tip. A multi-well plate was applied to extract MG from aquaculture water samples, and the extracts containing the desorbed MG were analysed by LC-DAD and LC-MS/MS. The signals from both detectors were used in two independent validation procedures. Linearity, matrix effect, selectivity, precision, trueness, and limits of detection and quantification were all evaluated. For both detectors, linearity was demonstrated in the range of 0.5-5 μg L -1 (R 2  > 0.98). Matrix effect was insignificant for LC-DAD only, and the average preconcentration factor was about 60 times. Recoveries ranged from 94 to 113% for LC-DAD and 95-115% for LC-MS/MS analysis. ANOVA was applied to estimate the standard deviation under repeatability (6.96-8.61% for LC-DAD and 5.98-7.41% for LC-MS/MS) and within-reproducibility (6.96-8.61% for LC-DAD and 6.56-7.41% for LC-MS/MS) conditions. The limits of detection and quantification for LC-MS/MS analysis were 4.29 and 28.74 ng L -1 , respectively, while, for LC-DAD, these limits were 14.29 and 95.81 ng L -1 , respectively. The results demonstrated that the developed method was suitable for determining MG in water samples, and the large-volume multiphase, multi-sample electroextraction device proved to be a powerful sample preparation technique to obtain high clean-up and large preconcentration levels, which are of paramount importance for environmental applications., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Cardiac injury in patients infected with the novel Coronavirus (COVID-19) seems to be associated with higher morbimortality. We provide a broad review of the clinical evolution of COVID-19, emphasizing its impact and implications on the cardiovascular system. The pathophysiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is characterized by overproduction of inflammatory cytokines (IL-6 and TNF-α) leading to systemic inflammation and multiple organ dysfunction syndrome, acutely affecting the cardiovascular system. Hypertension (56.6%) and diabetes (33.8%) are the most prevalent comorbidities among individuals with COVID-19, who require hospitalization. Furthermore, cardiac injury, defined as elevated us-troponin I, significantly relates to inflammation biomarkers (IL-6 and C-reactive protein (CRP), hyperferritinemia, and leukocytosis), portraying an important correlation between myocardial injury and inflammatory hyperactivity triggered by viral infection. Increased risk for myocardial infarction, fulminant myocarditis rapidly evolving with depressed systolic left ventricle function, arrhythmias, venous thromboembolism, and cardiomyopathies mimicking STEMI presentations are the most prevalent cardiovascular complications described in patients with COVID-19. Moreover, SARS-CoV-2 tropism and interaction with the RAAS system, through ACE2 receptor, possibly enhances inflammation response and cardiac aggression, leading to imperative concerns about the use of ACEi and ARBs in infected patients. Cardiovascular implications result in a worse prognosis in patients with COVID-19, emphasizing the importance of precocious detection and implementation of optimal therapeutic strategies.

In this work, cellulose cone tips were used as a hydrophilic sorbent supporting an aqueous electrolyte solution in a four-phase electric-field-assisted extraction. The wetted tips were immersed in an immiscible organic phase, acting as a filter to extract analytes present in an aqueous sample. Simultaneous four-phase extractions were carried out under the influence of an electric field using a 66-well plate constructed with inexpensive and readily available laboratory materials. Several parameters that control the electric resistivity of the system were evaluated, and the cone tips provided reproducible and stable electric current during application of electric potential difference. In a final application, a cationic dye and its metabolite, crystal and leuco crystal violet, were extracted from spiked fish extracts and quantified by a digital image analysis method. The method presented a linear range of 2-100 ng mL -1 ( r > 0.999), limit of detection of 1.37 ng mL -1 , inter- (3 consecutive days) and intraday precision determined for 4 concentration levels ( n = 6, each) were lower than 29% and mean recoveries for these concentrations ranging from 95% to 115%. The results demonstrated that the 66-well plate provides a stable, reproducible, and simple way to conduct extractions of ionic compounds from complex aqueous matrixes. The effectiveness of the low-cost cellulose cone tips used as a solid fourth phase also confirmed that it can easily overcome many drawbacks of similar liquid-liquid-liquid approaches.

Coffee cup quality, determined by the sensory attributes evaluated by professional tasters, is a decisive factor for evaluating coffee, with the "Specialty Coffee Association of America" (SCAA) classification being nowadays considered the most suitable. Panels of trained coffee tasters are used by the industry to describe and evaluate beverage quality, but those evaluations can be subjective and time demanding. Recent studies have demonstrated the potential of spectroscopy-based methods for establishing parameters of quality in the analysis of food products, including coffee. Thus, the aim of this study was to evaluate the potential of ATR-FTIR and chemometrics to discriminate espresso coffees with different sensory characteristics reported by a panel of coffee tasters. The results showed good consistency among coffee tasters. PLS-DA models based on spectroscopic data were able to classify samples according to sensory attributes, confirming the potential of FTIR and chemometrics in coffee quality evaluation., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Sensory (cup) analysis is a reliable methodology for green coffee quality evaluation, but faces barriers when applied to commercial roasted coffees due to lack of information on roasting conditions. The aim of this study was to examine the potential of mid-infrared spectroscopy for predicting cup quality of arabica coffees of different roasting degrees. PCA analysis showed separation of arabica and robusta. A two-level PLS-DA Hierarchical strategy was employed, with coffee being classified as high or low quality in the first level and then separated according to cup quality in the second level. Validation results showed that the second level models exhibited 100% sensitivity and specificity in the training sets. For the test set, sensitivity ranged from 67% (rio zona) to 100% (soft) while specificity ranged from 71% (rio) to 100% (rioysh, hard). Thus, the proposed method can be used for the quality evaluation of arabica coffees regardless of roasting conditions., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Calibration transfer is commonly used for spectra obtained in different spectrometers or other conditions. This paper proposed the use of calibration transfer between spectra recorded for the same samples in different physical forms. A new method was developed for the direct determination of nevirapine in solid pharmaceutical formulations based on diffuse reflectance near infrared spectroscopy (NIRS) and partial least squares (PLS). This method was developed with 50 powder mixtures and then, successfully extended to the quantification in intact tablets by using calibration transfer with double window piecewise direct standardization (DWPDS). This chemometric strategy provided good results with a small number of tablet transfer samples, only seven, prepared out of the narrow range of active principle ingredients (API) content around the nominal value of the formulation (100%). The method was fully validated in the working range of 83.0-113.9% of nevirapine and the use of DWPDS allowed to significantly decreasing the root mean square error of prediction (RMSEP) from 4.8% (tablets predicted by a model built with only powder samples) to 2.6%. The range of relative errors decreased from -5.1/8.7% to -4.6/3.3%. Considering that the amount of raw materials demanded for preparing tablets is up to ten times higher than for powder mixtures, this type of application is of particular interest in pharmaceutical analysis. In the context of process analytical technology (PAT), the use of the same multivariate model in different steps of the production is very advantageous, saving time and labor., (Copyright © 2015 Elsevier B.V. All rights reserved.)

This paper proposed a new screening method for the simultaneous detection of five common adulterants in raw cow milk by using attenuated total reflectance (ATR) mid infrared spectroscopy and multivariate supervised classification (partial least squares discrimination analysis - PLSDA). The method was able to detect the presence of the adulterants water, starch, sodium citrate, formaldehyde and sucrose in milk samples containing from one up to five of these analytes, in the range of 0.5-10% w/v. A multivariate qualitative validation was performed, estimating specific figures of merit, such as false positive and false negative rates, selectivity, specificity and efficiency rates, accordance and concordance. The proposed method does not need any sample pretreatment, requires a small amount of sample (30 μL), is fast and simple, being suitable for the control of raw milk in a dairy industry or for the quality inspection of commercialized milk., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

This paper proposed a novel methodology for the quantification of an artificial dye, sunset yellow (SY), in soft beverages, using image analysis (RGB histograms) and partial least squares regression. The developed method presented many advantages if compared with alternative methodologies, such as HPLC and UV/VIS spectrophotometry. It was faster, did not require sample pretreatment steps or any kind of solvents and reagents, and used a low cost equipment, a commercial flatbed scanner. This method was able to quantify SY in isotonic drinks and orange sodas, in the range of 7.8-39.7 mg L(-1), with relative prediction errors lower than 10%. A multivariate validation was also performed according to the Brazilian and international guidelines. Linearity, accuracy, sensitivity, bias, prediction uncertainty and a recently proposed tool, the β-expectation tolerance intervals, were estimated. The application of digital images in food analysis is very promising, opening the possibility for automation., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Direct infusion electrospray ionization mass spectrometry in the positive ion mode [ESI(+)-MS] is used to obtain fingerprints of aqueous-methanolic extracts of two types of olive oils, extra virgin (EV) and ordinary (OR), as well as of samples of EV olive oil adulterated by the addition of OR olive oil and other edible oils: corn (CO), sunflower (SF), soybean (SO) and canola (CA). The MS data is treated by the partial least squares discriminant analysis (PLS-DA) protocol aiming at discriminating the above-mentioned classes formed by the genuine olive oils, EV (1) and OR (2), as well as the EV adulterated samples, i.e. EV/SO (3), EV/CO (4), EV/SF (5), EV/CA (6) and EV/OR (7). The PLS-DA model employed is built with 190 and 70 samples for the training and test sets, respectively. For all classes (1-7), EV and OR olive oils as well as the adulterated samples (in a proportion varying from 0.5 to 20.0% w/w) are properly classified. The developed methodology required no ions identification and demonstrated to be fast, as each measurement lasted about 3 min including the extraction step and MS analysis, and reliable, because high sensitivities (rate of true positives) and specificities (rate of true negatives) were achieved. Finally, it can be envisaged that this approach has potential to be applied in quality control of EV olive oils., (Copyright © 2013 John Wiley & Sons, Ltd.)

Brazil is one of the most important countries as a producer and exporter of cattle and poultry. In 2009 cattle accounted for 30% of the export market and 41.4% for poultry meat. The Brazilian National Residues and Contaminants Control Plan (PNCRC) follows the guidelines set by the Codex Alimentarius Commission and checks compliance maximum residue limits (MRLs) to ensure the quality of these commodities. Kidney samples (n = 2978) were analysed between January 2008 and December 2009. Fifteen antibiotics of the macrolide and aminoglycoside groups (clindamycin, eritromycin, lincomycin, tylmicosin, tylosin, amikacin, apramycin, dihydrostreptomycin, gentamycin, higromycin, kanamycin, neomycin, spectinomycin, streptomycin, tobramycin) were determined by a microbiological screening method (FAST) and confirmed/quantified using liquid chromatography (LC-MS/MS and UPLC-MS/MS). In 2008, 1459 samples were analysed by a screening test and liquid chromatography with only one sample (0.07%) exceeded Brazilian legislation limits (>MRL). In 2009, 1519 samples were analysed and none exceeding Brazilian legislation limits (>MRL). The slaughterhouses of 16 states were monitored during the year of 2008, and 18 states were monitored in 2009, being the major producing states most sampled by the PNCRC.

PremiTest, a microbial inhibition test for the screening of antimicrobial residues, was validated according to the criteria established by Decision 2002/657/EC. Sensitivity, detection capability (CCβ), specificity, selectivity, robustness and applicability were evaluated. The methodology involves the technique of solvent extraction, which increases the detection capability of the test for a wider range of antibiotics. The following CCβ values in poultry muscle were found: penicillin G ≤ 12.5 µg kg(-1), total sulfonamides ≤ 75 µg kg(-1), erythromycin 75 µg kg(-1) and lincomycin 50 µg kg(-1). The detection capability of chlortetracycline was equal to its maximum residue limit (100 µg kg(-1)) and the method did not detect gentamicin (1000 µg kg(-1)), for which no MRL is established in poultry muscle. Specificity evaluated in relation to different analytes and matrices did not detect any interferences in the tests results; whilst the robustness showed that the pH neutralisation point of the extract affects the analytical results and the kits' performance. Only the screening of tetracyclines requires the analysis of extracts without pH neutralisation. The results of the validation process showed that this method is acceptable for screening β-lactam, sulfonamide and macrolide antimicrobial groups in the National Residues and Contaminants Control Programme (PNCRC), and that for this it is fit for purpose.