Two-trace two-dimensional correlation spectra (2T2D-COS) analysis using FTIR spectra to monitor the immune response by COVID-19.

There is a growing trend in using saliva for SARS-CoV-2 detection with reasonable accuracy. We have studied the responses of IgA, IgG, and IgM in human saliva by directly comparing disease with control analyzing two-trace two-dimensional correlation spectra (2T2D-COS) employing Fourier transform infrared (FTIR) spectra. It explores the molecular-level variation between control and COVID-19 saliva samples. The advantage of 2T2D spectra is that it helps in discriminating remarkably subtle features between two simple pairs of spectra. It gives spectral information from highly overlapped bands associated with different systems. The clinical findings from 2T2D show the decrease of IgG and IgM salivary antibodies in the 50, 60, 65, and 75-years COVID-19 samples. Among the various COVID-19 populations studied the female 30-years group reveals defense mechanisms exhibited by IgM and IgA. Lipids and fatty acids decrease, resulting in lipid oxidation due to the SARS-CoV-2 in the samples studied. Study shows salivary thiocyanate plays defense against SARS-CoV-2 in the male population in 25 and 35 age groups. The receiver operation characteristics statistical method shows a sensitivity of 98% and a specificity of 94% for the samples studied. The measure of accuracy computed as F score and G score has a high value, supporting our study's validation. Thus, 2T2D-COS analysis can potentially monitor the progression of immunoglobulin's response function to COVID-19 with reasonable accuracy, which could help diagnose clinical trials. KEY MESSAGES: The molecular profile of salivary antibodies is well resolved and identified from 2T2D-COS FTIR spectra. The IgG antibody plays a significant role in the defense mechanism against SARS-CoV-2 in 25-40 years. 2T2D-COS reveals the absence of salivary thiocyanate in the 40-75 years COVID-19 population. The receiver operation characteristic (ROC) analysis validates our study with high sensitivity and specificity.

A Study of the Interactions of Heavy Metals in Dairy Matrices Using Fourier Transform Infrared Spectroscopy, Chemometric, and In Silico Analysis.

Heavy metals are among the toxic substances longest recognized by man. Today, due to the myriad sources of exposure, such as contaminated water, food, or air, they have become a major public health problem. This work presents the effects manifested in the infrared spectrum behavior caused by the presence of Cd2+, Cr6+, and Pb2+ at different concentrations in three different matrices: water, casein, and milk; observing that the spectral modifications in the regions of different vibrational modes of nucleophilic groups such as -OH, COO- and NH2 depending on the nature of the metal and its concentration. These findings were correlated in-silico using optimized models in Gabedit software and structural optimization was performed with MOPAC 2016 showing stable structures between the metals and Gln, Hys, Glu, and Phe of casein. By applying chemometrics (Principal Component Analysis), it was possible to observe a good correlation between the experimental data and to discriminate between the type of metal, the matrix that contains it, and the concentration could be represented through linear models that showed adjustments with a value of r2 ≥ 0.95.

ATR-FTIR spectrum analysis of saliva samples from COVID-19 positive patients.

The coronavirus disease 2019 (COVID-19) is the latest biological hazard for the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Even though numerous diagnostic tests for SARS-CoV-2 have been proposed, new diagnosis strategies are being developed, looking for less expensive methods to be used as screening. This study aimed to establish salivary vibrational modes analyzed by attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy to detect COVID-19 biological fingerprints that allow the discrimination between COVID-19 and healthy patients. Clinical dates, laboratories, and saliva samples of COVID-19 patients (N = 255) and healthy persons (N = 1209) were obtained and analyzed through ATR-FTIR spectroscopy. Then, a multivariate linear regression model (MLRM) was developed. The COVID-19 patients showed low SaO2, cough, dyspnea, headache, and fever principally. C-reactive protein, lactate dehydrogenase, fibrinogen, D-dimer, and ferritin were the most important altered laboratory blood tests, which were increased. In addition, changes in amide I and immunoglobulin regions were evidenced in the FTIR spectra analysis, and the MLRM showed clear discrimination between both groups. Specific salivary vibrational modes employing ATR-FTIR spectroscopy were established; moreover, the COVID-19 biological fingerprint in saliva was characterized, allowing the COVID-19 detection using an MLRM, which could be helpful for the development of new diagnostic devices.

Thermosonicated whey protein concentrate blends on quality attributes of reduced fat Panela cheese.

Aiming at producing a reduced fat cheese (RFC) as an alternative to full-fat Panela cheese, a highly consumed fresh Mexican dairy product, thermosonication (TS) processes (24 kHz, 400 W nominal power, 2, 4 and 6 min; 50, 55 and 60 °C) were evaluated to treat WPC (80% protein) blended with reduced-fat milk (1 and 2% fat), which were later LTLT pasteurized. TS blends were compared in terms of their technological properties (water holding capacity-WPC, gel firmness- GF, color, pH and titratable acidity) with those of a regular full fat (3%) LTLT pasteurized milk used as a control. Afterwards, a regression analysis was carried out with the obtained data in order to select the most appropriate conditions for cheesemaking purposes (similar GF, higher WHC with respect to the control), minimize both fat content and TS treatment duration to minimize energy expenses. According to these restrictions, the selected conditions were 1.5% fat milk-WPC blend, TS treated at 60 °C for 120 s; 1% fat milk-WPC blend, TS treated at 50 °C for 120 s and 1% fat milk-WPC blend, 50 °C for 144 s, which allowed preparing low fat cheeses (LFCs). These TS treatments were applied in a larger scale to elaborate Panela-type LFCs comparing different technological properties (cheese yield, syneresis, water content, texture profile analysis, color and titratable acidity) with those of a full fat variety, at day 1 and during 14 days of refrigerated storage. Results showed similar texture profiles of LFC cheeses and full fat milk cheeses throughout their storage period with significant changes in composition parameters (higher moisture, protein and salt contents, with low fat percentages), syneresis, selected color parameters (hue, b*), with no observed changes in cheese yield, TA and pH during cheese storage. These promising results are encouraging to develop LFCs with no physicochemical or technological defects using novel processing techniques that may help reducing calorie consumption without compromising sensory acceptability.

Bacterial Succession through the Artisanal Process and Seasonal Effects Defining Bacterial Communities of Raw-Milk Adobera Cheese Revealed by High Throughput DNA Sequencing.

The bacterial community of the artisanal Adobera cheese from Los Altos de Jalisco was described through high-throughput sequencing of 16S rRNA gene libraries. Samples were collected in two different seasons (dry and rainy) during four key steps of the manufacturing process (raw milk, fresh curd, matured curd, and cheese). Bacterial diversity was higher in early steps in comparison with the final elaboration stages. Firmicutes and Proteobacteria were the most abundant phyla, strongly represented by the Streptococcaceae, Enterobacteriaceae and Lactobacillaceae families, and core bacteria genera such as Streptococcus spp., Lactococcus spp., and Lactobacillus spp. Undesirable bacteria, including Pseudomonas spp. and Acinetobacter spp., were also detected in raw milk but almost undetectable at the end of the cheese manufacturing process, and seemed to be displaced by lactic-acid bacteria-related genera. Seasonal effects were observed on the community structure but did not define the core microbiota composition. Predictive metabolism was related to membrane transport, and amino-acid, lipid, and carbohydrate metabolism pathways. Our results contribute to deduce the role of bacteria involved in Adobera cheese manufacturing in terms of the metabolism involved, cheese microbial safety, and how undesirable bacterial populations could be regulated by process standardization as a potential tool to improve safety.

Ligninolytic activity patterns of Pleurotus ostreatus obtained by submerged fermentation in presence of 2,6-dimethoxyphenol and remazol brilliant blue R dye.

The degradation of 2,6-dimethoxyphenol (DMP) and decolorization of Remazol brilliant blue R dye (RBB), added to culture media of Pleurotus ostreatus developed in submerged fermentation, and the laccase, manganese peroxidase and veratryl alcohol oxidase activities produced in these systems were evaluated. Both compounds were removed from the culture medium mainly by enzymatic action. These compounds decreased the specific growth rate and the effect on the maximal biomass values was not important. The enzymatic activities were increased by DMP and/or RBB; however, the DMP showed a higher inducer effect on all enzymes than RBB. On the other hand, the RBB showed a larger inducer effect on manganese peroxidase activity than on the laccases and veratryl alcohol oxidase activities. These results show that DMP was a better inducer of ligninolytic enzymes than dye, and the process of dye decolorization and degradation of DMP requires the action of all enzymes of the ligninolytic complex.