Bioactivity and volatile compound evaluation in sheep milk processed by ohmic heating.

Ohmic heating may improve bioactive compounds and processing, ensuring food safety of beverages, liquid and pasty food, or liquid with solid pieces. Due to those traits, this study conducted a comparison between ohmic heating technology and conventional heating (CH), with a focus on assessing the impact of both methods on functional compounds (such as angiotensin-converting enzyme inhibition, α-amylase and α-glucosidase inhibition, and antioxidant activity) in both fresh and thawed raw sheep milk, which had been frozen for up to 3 mo. Different ohmic heating conditions were applied and compared to CH (3.33-8.33 V/cm vs. CH [73°C/15 s]). A total of 18 peptides with some functional activities were identified by MALDI-TOF mass spectrometry analysis. Ohmic heating samples presented the highest activities related to health, followed by CH and raw milk samples; antioxidant activity range was from 0.11% to 0.71%, antihypertensive activity ranged from 0.20% to 0.72%, and antidiabetic activity ranged from 0.21% to 0.79%. Of 51 volatile compounds detected, some were degraded by freezing, storing, and heating the sheep milk. This study showed for the first time that ohmic heating processing improved sheep milk bioactive peptides and preserved volatile compounds.

In Vitro Effect of Epigallocatechin Gallate on Heme Synthesis Pathway and Protoporphyrin IX Production.

Photodynamic therapy (PDT) treats nonmelanoma skin cancer. PDT kills cells through reactive oxygen species (ROS), generated by interaction among cellular O2, photosensitizer and specific light. Protoporphyrin IX (PpIX) is a photosensitizer produced from methyl aminolevulinate (MAL) by heme group synthesis (HGS) pathway. In PDT-resistant cells, PDT efficacy has been improved by addition of epigallocatechin gallate (EGCG). Therefore, the aim of this work is to evaluate the effect of EGCG properties over MAL-TFD and PpIX production on A-431 cell line. EGCG's role over cell proliferation (flow cytometry and wound healing assay) and clonogenic capability (clonogenic assay) was evaluated in A-431 cell line, while the effect of EGCG over MAL-PDT was determined by cell viability assay (MTT), PpIX and ROS detection (flow cytometry), intracellular iron quantification and gene expression of HGS enzymes (RT-qPCR). Low concentrations of EGCG (<50 µM) did not have an antiproliferative effect over A-431 cells; however, EGCG inhibited clonogenic cell capability. Furthermore, EGCG (<50 µM) improved MAL-PDT cytotoxicity, increasing PpIX and ROS levels, exerting a positive influence on PpIX synthesis, decreasing intracellular iron concentration and modifying HGS enzyme gene expression such as PGB (upregulated) and FECH (downregulated). EGCG inhibits clonogenic capability and modulates PpIX synthesis, enhancing PDT efficacy in resistant cells.

Prediction of new spin-forbidden transitions in the N2 molecule-the electric dipole A'5Σg + → A3Σu + and magnetic dipole a'1Σu -← A3Σu + transitions.

On the ground of multi-reference configuration interaction calculations with an account of spin-orbit coupling, we have predicted the probability of two unknown spin-forbidden transitions in the spectrum of the N2 molecule: the electric dipole A'5Σg + → A3Σu + emission system and the magnetic dipole a'1Σu - ← A3Σu + transition. The radiative lifetime of the lowest A'5Σg + sublevel is less than a microsecond; the magnetic transition induced by the spin current in the triplet state is predicted with relatively low oscillator strength (f = 10-10), which still could be detectable.

Decoding Electroencephalography Signal Response by Stacking Ensemble Learning and Adaptive Differential Evolution.

Electroencephalography (EEG) is an exam widely adopted to monitor cerebral activities regarding external stimuli, and its signals compose a nonlinear dynamical system. There are many difficulties associated with EEG analysis. For example, noise can originate from different disorders, such as muscle or physiological activity. There are also artifacts that are related to undesirable signals during EEG recordings, and finally, nonlinearities can occur due to brain activity and its relationship with different brain regions. All these characteristics make data modeling a difficult task. Therefore, using a combined approach can be the best solution to obtain an efficient model for identifying neural data and developing reliable predictions. This paper proposes a new hybrid framework combining stacked generalization (STACK) ensemble learning and a differential-evolution-based algorithm called Adaptive Differential Evolution with an Optional External Archive (JADE) to perform nonlinear system identification. In the proposed framework, five base learners, namely, eXtreme Gradient Boosting, a Gaussian Process, Least Absolute Shrinkage and Selection Operator, a Multilayer Perceptron Neural Network, and Support Vector Regression with a radial basis function kernel, are trained. The predictions from all these base learners compose STACK's layer-0 and are adopted as inputs of the Cubist model, whose hyperparameters were obtained by JADE. The model was evaluated for decoding the electroencephalography signal response to wrist joint perturbations. The variance accounted for (VAF), root-mean-squared error (RMSE), and Friedman statistical test were used to validate the performance of the proposed model and compare its results with other methods in the literature, including the base learners. The JADE-STACK model outperforms the other models in terms of accuracy, being able to explain around, as an average of all participants, 94.50% and 67.50% (standard deviations of 1.53 and 7.44, respectively) of the data variability for one step ahead and three steps ahead, which makes it a suitable approach to dealing with nonlinear system identification. Also, the improvement over state-of-the-art methods ranges from 0.6% to 161% and 43.34% for one step ahead and three steps ahead, respectively. Therefore, the developed model can be viewed as an alternative and additional approach to well-established techniques for nonlinear system identification once it can achieve satisfactory results regarding the data variability explanation.

Electrophilic C-H Borylation of Aza[5]helicenes Leading to Bowl-Shaped Quasi-[7]Circulenes with Switchable Dynamics.

The intrinsic relationship between helicenes and circulenes is of fundamental interest and importance in molecular engineering. Herein, electrophilic borylation of phenanthroline-derived aza[5]helicenes is presented, resulting in the incorporation of a boryl unit into two termini of helicenes to afford quasi-[7]circulenes. Their bowl-shaped structures were determined by X-ray diffraction. UV-vis absorption and fluorescence spectroscopy, as well as electrochemical measurements and DFT calculations, gave insight into their electronic properties. Variable-temperature NMR studies and DFT calculations revealed bowl-to-bowl inversion at room temperature and bowl-to-helix equilibria at elevated temperature, highlighting the important role of B ← N bond strength in tuning their dynamic properties.

In vitro activity of N-phenyl-1,10-phenanthroline-2-amines against tachyzoites and bradyzoites of Toxoplasma gondii.

Toxoplasma gondiiis an apicomplexan parasite, the causative agent of toxoplasmosis, a common disease in the world. Toxoplasmosis could be severe, especially in immunocompromised patients. The current therapy is limited, where pyrimethamine and sulfadiazine are the best choices despite being associated with side effects and ineffective against the bradyzoites, the parasitic form present during the chronic phase of the infection. Thus, new therapies against both tachyzoites and bradyzoites from T. gondii are urgent. Herein, we present the anti-T. gondii effect of 1,10-phenanthroline and its N-phenyl-1,10-phenanthroline-2-amine derivatives. The chemical modification of 1,10-phenanthroline tonew derivatives improved the anti-T. gondiiactivity 3.4 fold. The most active derivative presented ED50in the nanomolar range, the smallest value found was for Ph8, 0.1 µM for 96 h of treatment. The host cell viability was maintained after the treatment with the compounds, which were found to be highly selective presenting large selectivity indexes. Treatment with derivatives for 96 h was able to eliminate the T. gondii infection irreversibly. The ultrastructural alterations caused after the treatment with the most effective derivative (Ph8) included signs of cell death, specifically revealed by the Tunel assay for detection of DNA fragmentation. The Phen derivatives were also able to control the growth of the in vitro-derived bradyzoite forms of T. gondii EGS strain, causing its lysis and death. These findings promote the 1,10-phenanthroline derivatives as potential lead compounds for the development of a treatment for acute and chronic phases of toxoplasmosis.

Effect of probiotic Minas Frescal cheese on the volatile compound and metabolic profiles assessed by nuclear magnetic resonance spectroscopy and chemometric tools.

This study aimed to evaluate the effect of Lacticaseibacillus casei 01 as a probiotic culture on the production of volatile organic compounds and metabolic profile of Minas Frescal cheese. Lactose (α-lactose and ß-lactose), fatty acids (unsaturated and saturated), citric acid, tryptophan, and benzoic acid were the main compounds. Compared with the control cheese, probiotic cheese was characterized by the highest concentration of tryptophan and presented a higher number of volatile acids. The control cheese was characterized by the highest concentration of benzoic acid and fatty acids, resulting in a higher number of volatile alcohols and esters. No differences were observed for α-lactose, ß-lactose, and citric acid contents. A clear separation of probiotic and control Minas Frescal cheese was obtained using 1H nuclear magnetic resonance spectra, demonstrating that the addition of probiotic culture altered the metabolic profile of Minas Frescal cheese. Overall, the findings suggested that the addition of probiotic culture promoted the proteolysis in the fresh cheeses, decreased the lipolysis, and altered the volatile compounds. Furthermore, nuclear magnetic resonance spectroscopy coupled to chemometrics tools could be used to differentiate probiotic and conventional cheeses.

Sheep milk kefir sweetened with different sugars: Sensory acceptance and consumer emotion profiling.

The objective of this study was to determine the sensory acceptance and emotional profile of sheep milk kefir sweetened with different sugars (demerara sugar, brown sugar, fructose, coconut sugar, and honey, 100 g/L). Consumers (n = 100) assessed sensory acceptance (appearance, aroma, taste, texture, and overall impression), and expressed their emotions (satisfied, active, loving, calm, comfortable, energetic, happy, healthy, refreshing, disgusted, worried, and upset). The emotions "satisfied," "active," "comfortable," "energetic," "healthy," and "refreshing" were found between moderate and very high levels, indicating that they are important emotions for the characterization and sensory acceptance of kefir samples. The use of different sugars had no influence on the intensity of the emotions "calm," "comfortable," "happy," or "disgusted," and resulted in a greater sense of satisfaction. The use of demerara sugar or fructose did not alter the acceptance of the products or the intensity of emotions. The use of brown sugar decreased acceptance (taste, texture, and overall impression) and the intensity of the emotions "active," "loving," "energetic," "healthy," and "refreshing." The use of coconut sugar decreased acceptance (appearance, aroma, and taste) and the intensity of the emotions "refreshing" and "upset." The use of honey improved acceptance in appearance and aroma but reduced the intensity of the emotions "active," "loving," "energetic," and "healthy." Based on sensory data, it is recommended to use demerara sugar or fructose as a substitute for sucrose. In conclusion, the study of emotions can be used as an additional tool for obtaining data related to the sensory acceptance of products.

Ohmic heating does not influence the biochemical properties of Minas Frescal cheese but decreases uric acid levels in healthy Wistar rats.

The objective of this study was to evaluate the effects of the consumption of Minas Frescal cheese (2 g for 15 d) produced with pasteurized milk or milk subjected to ohmic heating on the health variables (biochemical, hematological, and uric acid levels) of rats, as well as on the identity variables and proteolysis indices of cheese. Three groups of rats (n = 6 per group) were studied, as follows: control group, without cheese consumption (CON), rats fed Minas Frescal cheese produced with milk pasteurized by conventional technology (PC, 72 to 75°C for 15 s), and rats fed Minas Frescal cheese produced with milk subjected to ohmic heating (OHC, 8 V/cm, 72 to 75°C for 15 s). Ohmic heating did not alter the macronutrient levels (moisture, fat, protein) of the cheeses, but an increase in the proteolysis index was observed. For both cheeses, no significant differences were observed for feed intake (139 to 143 g/d), water consumption (196 to 206 mL/d), or final animal weight (236 to 252 g), and no changes were detected in hematological variables (counts of red blood cells, hemoglobin, leukocytes, and platelets) or levels of potassium, calcium, magnesium, urea, creatinine, total cholesterol, high-density lipoprotein cholesterol, blood glucose, and bilirubin (total, direct, and indirect) of rats. In addition, both cheeses led to a reduction of serum triglycerides and an increase in monocyte, eosinophil, and basophil levels. However, consumption of OHC resulted in decreased sodium, uric acid, and lymphocyte levels. The present results suggest that ohmic heating in the processing of Minas Frescal cheese has positive effects on the health of healthy rats.

Traceability: Perception and attitudes of artisanal cheese producers in Brazil.

This study aimed to evaluate the perceptions and attitudes of artisanal cheese producers (n = 40) in Brazil regarding the implementation of traceability. A questionnaire consisting of 16 statements using a 5-point Likert scale was applied, and descriptive statistics and factor analysis were used for data analysis. The implementation of a traceability system can reduce the number of consumer complaints and the loss of products, in addition to increasing supplier control and process safety, thus protecting health and increasing consumer confidence. However, we did not find consensus on the relationship between implementation of a traceability system and rapid recalls in crisis episodes, or on the reduction in recalls and their negative impact on consumers. Because of the costs that drive implementation of this technology, some artisanal cheese producers do not consider a traceability system as a current reality to monitor their production. We concluded that Brazilian artisanal cheese producers have limited awareness of the impact of traceability implementation, which restricts investments in the system.

Food defense: Perceptions and attitudes of Brazilian dairy companies.

This study aimed to evaluate the perception of Brazilian dairy processors (n = 31) concerning food defense. The results showed that respondents consider the implementation of control procedures related to facilities, products, materials, and individuals as important measures in food defense. The higher agreement rates (strongly agreed + slightly agreed) of the companies in relation to the perception of food defense were 84% for external security, followed by personnel security (82%), generalities (81%), and internal security (74%). Thus, protecting facilities and controlling the traffic flow were considered to be the most important actions under the participants' perspectives. Employee satisfaction and identification of end products and raw materials are also considered relevant in the food defense program. Although food defense is not a formal requirement in Brazilian law, the results show that there is adequate awareness of this topic by the Brazilian dairy companies.

Forecasting Brazilian and American COVID-19 cases based on artificial intelligence coupled with climatic exogenous variables.

The novel coronavirus disease (COVID-19) is a public health problem once according to the World Health Organization up to June 24th, 2020, more than 9.1 million people were infected, and more than 470 thousand have died worldwide. In the current scenario, the Brazil and the United States of America present a high daily incidence of new cases and deaths. Therefore, it is important to forecast the number of new cases in a time window of one week, once this can help the public health system developing strategic planning to deals with the COVID-19. The application of the forecasting artificial intelligence (AI) models has the potential of deal with dynamical behavior of time-series like of COVID-19. In this paper, Bayesian regression neural network, cubist regression, k-nearest neighbors, quantile random forest, and support vector regression, are used stand-alone, and coupled with the recent pre-processing variational mode decomposition (VMD) employed to decompose the time series into several intrinsic mode functions. All AI techniques are evaluated in the task of time-series forecasting with one, three, and six-days-ahead the cumulative COVID-19 cases in five Brazilian and American states, with a high number of cases up to April 28th, 2020. Previous cumulative COVID-19 cases and exogenous variables as daily temperature and precipitation were employed as inputs for all forecasting models. The models' effectiveness are evaluated based on the performance criteria. In general, the hybridization of VMD outperformed single forecasting models regarding the accuracy, specifically when the horizon is six-days-ahead, the hybrid VMD-single models achieved better accuracy in 70% of the cases. Regarding the exogenous variables, the importance ranking as predictor variables is, from the upper to the lower, past cases, temperature, and precipitation. Therefore, due to the efficiency of evaluated models to forecasting cumulative COVID-19 cases up to six-days-ahead, the adopted models can be recommended as a promising models for forecasting and be used to assist in the development of public policies to mitigate the effects of COVID-19 outbreak.

Short-term forecasting COVID-19 cumulative confirmed cases: Perspectives for Brazil.

The new Coronavirus (COVID-19) is an emerging disease responsible for infecting millions of people since the first notification until nowadays. Developing efficient short-term forecasting models allow forecasting the number of future cases. In this context, it is possible to develop strategic planning in the public health system to avoid deaths. In this paper, autoregressive integrated moving average (ARIMA), cubist regression (CUBIST), random forest (RF), ridge regression (RIDGE), support vector regression (SVR), and stacking-ensemble learning are evaluated in the task of time series forecasting with one, three, and six-days ahead the COVID-19 cumulative confirmed cases in ten Brazilian states with a high daily incidence. In the stacking-ensemble learning approach, the CUBIST regression, RF, RIDGE, and SVR models are adopted as base-learners and Gaussian process (GP) as meta-learner. The models' effectiveness is evaluated based on the improvement index, mean absolute error, and symmetric mean absolute percentage error criteria. In most of the cases, the SVR and stacking-ensemble learning reach a better performance regarding adopted criteria than compared models. In general, the developed models can generate accurate forecasting, achieving errors in a range of 0.87%-3.51%, 1.02%-5.63%, and 0.95%-6.90% in one, three, and six-days-ahead, respectively. The ranking of models, from the best to the worst regarding accuracy, in all scenarios is SVR, stacking-ensemble learning, ARIMA, CUBIST, RIDGE, and RF models. The use of evaluated models is recommended to forecasting and monitor the ongoing growth of COVID-19 cases, once these models can assist the managers in the decision-making support systems.

Epigallocatechin Gallate Enhances MAL-PDT Cytotoxic Effect on PDT-Resistant Skin Cancer Squamous Cells.

Photodynamic therapy (PDT) has been used to treat certain types of non-melanoma skin cancer with promising results. However, some skin lesions have not fully responded to this treatment, suggesting a potential PDT-resistant phenotype. Therefore, novel therapeutic alternatives must be identified that improve PDT in resistant skin cancer. In this study, we analyzed the cell viability, intracellular protoporphyrin IX (PpIX) content and subcellular localization, proliferation profile, cell death, reactive oxygen species (ROS) detection and relative gene expression in PDT-resistant HSC-1 cells. PDT-resistant HSC-1 cells show a low quantity of protoporphyrin IX and low levels of ROS, and thus a low rate of death cell. Furthermore, the resistant phenotype showed a downregulation of HSPB1, SLC15A2, FECH, SOD2 and an upregulation of HMBS and BIRC5 genes. On the other hand, epigallocatechin gallate catechin enhanced the MAL-PDT effect, increasing levels of protoporphyrin IX and ROS, and killing 100% of resistant cells. The resistant MAL-PDT model of skin cancer squamous cells (HSC-1) is a reliable and useful tool to understand PDT cytotoxicity and cellular response. These resistant cells were successfully sensitized with epigallocatechin gallate catechin. The in vitro epigallocatechin gallate catechin effect as an enhancer of MAL-PDT in resistant cells is promising in the treatment of difficult skin cancer lesions.

A theoretical study of energy transfer in Ar(1S) + SO2( X ̃ 1 A ') collisions: Cross sections and rate coefficients for vibrational transitions.

Vibrational transitions, induced by collisions between rare-gas atoms and molecules, play a key role in many problems of interest in physics and chemistry. A theoretical investigation of the translation-to-vibration (T-V) energy transfer process in argon atom and sulfur dioxide molecule collisions is presented here. For such a purpose, the framework of the quasi-classical trajectory (QCT) methodology was followed over the range of translational energies 2 ≤ Etr/kcal mol-1 ≤ 100. A new realistic potential energy surface (PES) for the ArSO2 system was developed using pairwise addition for the four-body energy term within the double many-body expansion. The topological features of the obtained function are compared with a previous one reported by Hippler et al. [J. Phys. Chem. 90, 6158 (1986)]. To test the accuracy of the PES, additional coupled cluster singles and doubles method with a perturbative contribution of connected triples calculations were carried out for the global minimum configuration. From dynamical calculations, the cross sections for the T-V excitation process indicate a barrier-type mechanism due to strong repulsive interactions between SO2 molecules and the Ar atom. Corrections to zero-point energy leakage in QCT were carried out using vibrational energy quantum mechanical threshold of the complex and variations. Rate coefficients and cross sections are calculated for some vibrational transitions using pseudo-quantization approaches of the vibrational energy of products. Main attributes of the title molecular collision are discussed and compared with available information in the literature.

Copper(ii) catalyzed synthesis of novel helical luminescent benzo[4,5]imidazo[1,2-a][1,10]phenanthrolines via an intramolecular C-H amination reaction.

In the present study a series of N-phenyl-1,10-phenanthroline-2-amine derivatives were obtained by heating 2-chlorophenanthroline with aniline derivatives under solvent free conditions in good to excellent yields. The N-phenyl-1,10-phenanthroline-2-amines were employed as substrates in a copper(ii)-catalyzed C-H amination reaction to give derivatives of the novel heterocyclic system benzo[4,5]imidazo[1,2-a][1,10]phenanthroline. The structure of these compounds was predicted to be helical by DFT calculations and single crystal X-ray diffraction of an example of this system confirmed the non-planar helical structure. The luminescence properties of the parent heterocyclic system were characterized.

Correction: Copper(ii) catalyzed synthesis of novel helical luminescent benzo[4,5]imidazo[1,2-a][1,10]phenanthrolines via an intramolecular C-H amination reaction.

Correction for 'Copper(ii) catalyzed synthesis of novel helical luminescent benzo[4,5]imidazo[1,2-a][1,10]phenanthrolines via an intramolecular C-H amination reaction' by Ramon Borges da Silva, et al., Org. Biomol. Chem., 2017, DOI: 10.1039/c6ob02508k.

A quasi-classical study of energy transfer in collisions of hyperthermal H atoms with SO2 molecules.

A deep understanding of energy transfer processes in molecular collisions is at central attention in physical chemistry. Particularly vibrational excitation of small molecules colliding with hot light atoms, via a metastable complex formation, has shown to be an efficient manner of enhancing reactivity. A quasi-classical trajectory study of translation-to-vibration energy transfer (T-V ET) in collisions of hyperthermal H(2S) atoms with SO2(X̃1A') molecules is presented here. For such a study, a double many-body expansion potential energy surface previously reported for HSO2(2A) is used. This work was motivated by recent experiments by Ma et al. studying collisions of H + SO2 at the translational energy of 59 kcal/mol [J. Ma et al., Phys. Rev. A 93, 040702 (2016)]. Calculations reproduce the experimental evidence that during majority of inelastic non-reactive collision processes, there is a metastable intermediate formation (HOSO or HSO2). Nevertheless, the analysis of the trajectories shows that there are two distinct mechanisms in the T-V ET process: direct and indirect. Direct T-V processes are responsible for the high population of SO2 with relatively low vibrational excitation energy, while indirect ones dominate the conversion from translational energy to high values of the vibrational counterpart.

Manufacture of probiotic Minas Frescal cheese with Lactobacillus casei Zhang.

In this study, the addition of Lactobacillus casei Zhang in the manufacture of Minas Frescal cheese was investigated. Minas Frescal cheeses supplemented with probiotic bacteria (Lactobacillus casei Zhang) were produced by enzymatic coagulation and direct acidification and were subjected to physicochemical (pH, proteolysis, lactic acid, and acetic acid), microbiological (probiotic and lactic bacteria counts), and rheological analyses (uniaxial compression and creep test), instrumental color determination (luminosity, yellow intensity, and red intensity) and sensory acceptance test. The addition of L. casei Zhang resulted in low pH values and high proteolysis indexes during storage (from 5.38 to 4.94 and 0.470 to 0.702, respectively). Additionally, the cheese protocol was not a hurdle for growth of L. casei Zhang, as the population reached 8.16 and 9.02 log cfu/g by means of the direct acidification and enzymatic coagulation protocol, respectively, after 21 d of refrigerated storage. The rheology data showed that all samples presented a more viscous-like behavior, which rigidity tended to decrease during storage and lower luminosity values were also observed. Increased consumer acceptance was observed for the control sample produced by direct acidification (7.8), whereas the cheeses containing L. casei Zhang presented lower values for all sensory attributes, especially flavor and overall liking (5.37 and 4.61 for enzymatic coagulation and 5.57 and 4.72 for direct acidification, respectively). Overall, the addition of L. casei Zhang led to changes in all parameters and affected negatively the sensory acceptance. The optimization of L. casei Zhang dosage during the manufacturing of probiotic Minas Frescal cheese should be performed.

Think and Choose! The Dual Impact of Label Information and Consumer Attitudes on the Choice of a Plant-Based Analog.

This study explored the impact of various label information (extrinsic attributes) and sociodemographic and attitudinal factors (intrinsic attributes) on Brazilian consumer choices, using simulated traditional and plant-based muçarela cheese as the model product. The research was conducted in two phases: the first involved a structured questionnaire assessing attitudinal dimensions such as Health Consciousness, Climate Change, Plant-based Diets, and Food Neophobia, along with sociodemographic data collection. The second phase comprised a discrete choice experiment with (n = 52) and without (n = 509) eye tracking. The term "Cheese" on labels increased choice probability by 7.6% in a general survey and 15.1% in an eye tracking study. A prolonged gaze at "Cheese" did not affect choice, while more views of "Plant-based product" slightly raised choice likelihood by 2.5%. Repeatedly revisiting these terms reduced the choice probability by 3.7% for "Cheese" and 1% for "Plant-based product". Nutritional claims like "Source of Vitamins B6 and B12" and "Source of Proteins and Calcium" boosted choice probabilities by 4.97% and 5.69% in the general and 8.4% and 6.9% in the eye-tracking experiment, respectively. Conversely, front-of-package labeling indicating high undesirable nutrient content decreased choice by 13% for magnifying presentations and 15.6% for text. In a plant-based subsample, higher environmental concerns and openness to plant-based diets increased choice probabilities by 5.31% and 5.1%, respectively. These results highlight the complex dynamics between label information, consumer understanding, and decision-making.