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Intestinal microbiota is related to obesity and serum lipid levels, both risk factors for chronic diseases constituting a challenge for public health. We investigated how a diet rich in whole grain (WG) products and red meat (RM) influences microbiota. During a 10-week crossover intervention study, 20 healthy adults consumed two isocaloric diets, one rich in WG products and one high in RM. Repeatedly data on microbiota were assessed by 16S rRNA based denaturing gradient gel electrophoresis (DGGE). A blood sample and anthropometric data were collected. Mixed models and logistic regression were used to investigate effects. Microbiota showed interindividual variability. However, dietary interventions modified microbiota appearance: 8 bands changed in at least 4 participants during the interventions. One of the bands appearing after WG and one increasing after RM remained significant in regression models and were identified as Collinsella aerofaciens and Clostridium sp. The WG intervention lowered obesity parameters, while the RM diet increased serum levels of uric acid and creatinine. The study showed that diet is a component of major relevance regarding its influence on intestinal microbiota and that WG has an important role for health. The results could guide investigations of diet and microbiota in observational prospective cohort studies. Trial registration: ClinicalTrials.gov NCT01449383.

Red meat is stigmatized as an unhealthy protein choice; however, its impacts on vascular function have not been evaluated. We aimed to measure the vascular impact of adding either low-fat (~5% fat) ground beef (LFB) or high-fat (~25% fat) ground beef (HFB) to a habitual diet in free-living men. Twenty-three males (39.9 ± 10.8 years, 177.5 ± 6.7 cm, 97.3 ± 25.0 kg) participated in this double-blind crossover study. Assessment of vascular function and aerobic capacity were measured at entry and in the last week of each intervention and washout period. Participants then completed two 5-week dietary interventions (LFB or HFB; 5 patties/week) in a randomized order with a 4-week washout. Data were analyzed via 2 × 2 repeated-measures ANOVA (p < 0.05). The HFB intervention improved FMD relative to all other time points, while lowering systolic (SBP) and diastolic blood pressure (DBP) relative to entry. Neither the HFB nor the LFB altered pulse wave velocity. The addition of either low- or high-fat ground beef did not negatively alter vascular function. In fact, consuming HFB improved FMD and BP values, which may be mediated by lowering LDL-C concentrations.

Adulteration of high-quality meat products using lower-priced meats, such as pork, is a crucial issue that could harm consumers. The consumption of pork is strictly forbidden in certain religions, such as Islam and Judaism. Therefore, the objective of this research was to develop untargeted metabolomics using liquid chromatography-high resolution mass spectrometry (LC-HRMS) combined with chemometrics for analysis of pork in beef meatballs for halal authentication. We investigated the use of non-targeted LC-HRMS as a method to detect such food adulteration. As a proof of concept using six technical replicates of pooled samples from beef and pork meat, we could show that metabolomics using LC-HRMS could be used for high-throughput screening of metabolites in meatballs made from beef and pork. Chemometrics of principal component analysis (PCA) was successfully used to differentiate beef meatballs and pork meatball samples. Partial least square-discriminant analysis (PLS-DA) clearly discriminated between halal and non-halal beef meatball samples with 100% accuracy. Orthogonal projection to latent structures-discriminant analysis (OPLS-DA) perfectly discriminated and classified meatballs made from beef, pork, and a mixture of beef-pork with a good level of fitness (R2X = 0.88, R2Y = 0.71) and good predictivity (Q2 = 0.55). Partial least square (PLS) and orthogonal PLS (OPLS) were successfully applied to predict the concentration of pork present in beef meatballs with high accuracy (R2 = 0.99) and high precision. Thirty-five potential metabolite markers were identified through VIP (variable important for projections) analysis. Metabolites of 1-(1Z-hexadecenyl)-sn-glycero-3-phosphocholine, acetyl-l-carnitine, dl-carnitine, anserine, hypoxanthine, linoleic acid, and prolylleucine had important roles for predicting pork in beef meatballs through S-line plot analysis. It can be concluded that a combination of untargeted metabolomics using LC-HRMS and chemometrics is promising to be developed as a standard analytical method for halal authentication of highly processed meat products.

A new generation of plant-based meat alternatives—formulated to mimic the taste and nutritional composition of red meat—have attracted considerable consumer interest, research attention, and media coverage. This has raised questions of whether plant-based meat alternatives represent proper nutritional replacements to animal meat. The goal of our study was to use untargeted metabolomics to provide an in-depth comparison of the metabolite profiles a popular plant-based meat alternative (n = 18) and grass-fed ground beef (n = 18) matched for serving size (113 g) and fat content (14 g). Despite apparent similarities based on Nutrition Facts panels, our metabolomics analysis found that metabolite abundances between the plant-based meat alternative and grass-fed ground beef differed by 90% (171 out of 190 profiled metabolites; false discovery rate adjusted p < 0.05). Several metabolites were found either exclusively (22 metabolites) or in greater quantities in beef (51 metabolites) (all, p < 0.05). Nutrients such as docosahexaenoic acid (ω-3), niacinamide (vitamin B3), glucosamine, hydroxyproline and the anti-oxidants allantoin, anserine, cysteamine, spermine, and squalene were amongst those only found in beef. Several other metabolites were found exclusively (31 metabolites) or in greater quantities (67 metabolites) in the plant-based meat alternative (all, p < 0.05). Ascorbate (vitamin C), phytosterols, and several phenolic anti-oxidants such as loganin, sulfurol, syringic acid, tyrosol, and vanillic acid were amongst those only found in the plant-based meat alternative. Large differences in metabolites within various nutrient classes (e.g., amino acids, dipeptides, vitamins, phenols, tocopherols, and fatty acids) with physiological, anti-inflammatory, and/or immunomodulatory roles indicate that these products should not be viewed as truly nutritionally interchangeable, but could be viewed as complementary in terms of provided nutrients. The new information we provide is important for making informed decisions by consumers and health professionals. It cannot be determined from our data if either source is healthier to consume.

This study aimed to fabricate and characterize a novel colorimetric indicator designed to detect ammonia (NH3) and monitor meat freshness. The sensing platform was constructed using electrospun nanofibers made from polylactic acid (PLA), which were then impregnated with anthocyanins as a natural pH-sensitive dye, extracted from red cabbage. This research involved investigating the relationship between the various concentrations of anthocyanins and the colorimetric platform’s efficiency when exposed to ammonia vapor. Scanning electron microscope (SEM) results were used to examine the morphology and structure of the nanofiber mats before and after the dip-coating process. The study also delved into the selectivity of the indicator when exposed to various volatile organic compounds (VOCs) and their stability under extreme humidity levels. Furthermore, the platform’s sensitivity was evaluated as it encountered ammonia (NH3) in concentrations ranging from 1 to 100 ppm, with varying dye concentrations. The developed indicator demonstrated an exceptional detection limit of 1 ppm of MH3 within just 30 min, making it highly sensitive to subtle changes in gas concentration. The indicator proved effective in assessing meat freshness by detecting spoilage levels in beef over time. It reliably identified spoilage after 10 h and 7 days, corresponding to bacterial growth thresholds (107 CFU/mL), both at room temperature and in refrigerated environments, respectively. With its simple visual detection mechanism, the platform offered a straightforward and user-friendly solution for consumers and industry professionals alike to monitor packaged beef freshness, enhancing food safety and quality assurance.

This work aimed to evaluate the use of Visible and Near-infrared Spectroscopy (Vis-NIRS) as a tool in the classification of bovine carcasses. A total of 133 animals (77 females, 29 males surgically castrated and 27 males immunologically castrated) were used. Vis-NIRS spectra were collected in a chilling room 24 h postmortem directly on the hanging carcasses over the longissimus thoracis between the surface of the 5th and 6th ribs. The data were evaluated by principal component analysis (PCA) and the partial least squares regression (PLSR) method. For the prediction of sex, the best model was the Standard Normal Variate (SNV) because it presented a relatively high coefficient of determination for prediction, presenting a percentage of correctness of 75.51% and an error of 24.49%. Regarding age, none of the models were able to differentiate the samples through Vis-NIRS. The findings confirm that Vis-NIRS prediction models are a valuable tool for differentiating carcasses based on sex. To further enhance the precision of these predictions, we recommend using Vis-NIRS equipment with the full infrared wavelength range to collect and predict sex and age in intact beef samples.

The aim of the study was to determine the effect of sonication with different levels of total acoustic power (250 W and 500 W) on the physicochemical and biochemical properties of beef and red deer meat. The parameters related to meat colour, surface myoglobin forms, antioxidant properties and the level of fat and protein oxidation were analysed. The results showed that the sonication significantly affected meat colour, myoglobin forms, antioxidant capacity, and oxidative markers, particularly in beef. Beef treated with 500 W sonication exhibited a significant decrease in redness ( a * value reduced by 20%) and increase in yellowness ( b * value increased by 21.5%), resulting in a total colour difference ( ΔE *) increase of 3.42 ± 0.35 units compared to controls. Red deer meat changes were less evident, with a notable rise in oxymyoglobin content (%OMb increased by 7.85%) at 500 W. Protein carbonyl content decreased by 12.4% and 6.9% after sonication at 250 W and 500 W respectively. TBARS values were lower in beef than in deer meat; 250 W sonication reduced TBARS by 29.5% in case of beef and 13.58% in red deer meat, whereas 500 W increased lipid oxidation by 6.5% and 4% respectively. The antioxidant activity of the studied meat extracts increased after the application of 500 W sonication. In conclusion regardless of the type of meat, the highest oxidative stability is demonstrated by samples that were exposed to sonication at a total acoustic power level of 250 W. In addition, red deer meat is less susceptible to sonication process than beef. This study advances understanding of sonication effects on meat quality, providing insights that can improve processing techniques and extend product shelf life.

Development of specific IgE antibodies to the oligosaccharide galactose-α-1, 3-galactose (α-gal) following tick bites has been shown to be the source of red meat allergy. In this study, we investigated the presence of α-gal in four tick species: the lone-star tick ( ), the Gulf-Coast tick ( ), the American dog tick ( ), and the black-legged tick ( ) by using a combination of immunoproteomic approach and, carbohydrate analysis. Anti-α-gal antibodies identified α-gal in the salivary glands of both and , while and appeared to lack the carbohydrate. PNGase F treatment confirmed the deglycosylation of N-linked α-gal-containing proteins in tick salivary glands. Immunolocalization of α-gal moieties to the salivary secretory vesicles of the salivary acini also confirmed the secretory nature of α-gal-containing antigens in ticks. ticks were fed on human blood (lacks α-gal) using a silicone membrane system to determine the source of the α-gal. N-linked glycan analysis revealed that and have α-gal in their saliva and salivary glands, but contains no detectable quantity. Consistent with the glycan analysis, salivary samples from and stimulated activation of basophils primed with plasma from α-gal allergic subjects. Together, these data support the idea that bites from certain tick species may specifically create a risk for the development of α-gal-specific IgE and hypersensitivity reactions in humans. Alpha-Gal syndrome challenges the current food allergy paradigm and broadens opportunities for future research.

This study aimed to determine how quality grade and degree of doneness (DOD) influence the development of volatile compounds among beef whole muscle and ground patties. Volatile compounds were quantified via head space solid phase microextraction from samples tempered in refrigerated temperatures (3 to 5 °C), room temperature (24 to 26 °C), or cooked on an electric clamshell-style grill to an endpoint temperature of 55, 60, 71, or 77 °C. Collected samples were subsequently determined by gas chromatography mass spectrometry. Prominent compounds known to be the result of the Maillard reaction or lipid degradation were retained for comparison. Four Strecker aldehydes, 4 pyrazines, and one ester had a 3-way interaction between quality grade, DOD, and product type (each P < 0.001). Pyrazine concentrations did not differ (P > 0.05) in ground patties and was comparably greater (P < 0.05) in steaks; in Prime and Low Choice steaks, pyrazine concentration increased (P < 0.05) as DOD increased. A 2-way interaction between quality grade and product type was observed for acetaldehyde, dimethyl disulfide, 1-penten-3-ol, butanoic acid, hexanal, octanal, nonanal, and 2-heptanone. Among which, octanal and nonanal were greater (P < 0.05) in Prime steaks compared with ground patties. Another 2-way interaction, quality grade and DOD, was observed in 2 ketones, an alcohol, 2 esters, and 2 aldehydes. For example, 2,3-butanedione was greater (P < 0.05) in concentration in Prime 4 °C samples compared with Low Choice and Standard. The final 2-way interaction of DOD and product type was observed in 3 ketones, 2 sulfur compounds, 2 esters, 5 aldehydes, 2 carboxylic acids, and a ketone. For example, 2-heptanone was greater (P < 0.05) in concentration in ground patties compared to steaks in all degrees of doneness except 4 °C. Overall, these results indicate that the volatile flavor profile of beef is greatly influenced by product type and DOD. Generally, consumers select beef based on product type and determine their cookery approach. Therefore, consumers may greatly influence final beef flavor profile.

The aims of this study were to predict carcass and meat traits, as well as the chemical composition of the 9th to 11th rib sections of beef cattle from portable NIR spectra. The 9th to 11th rib section was obtained from 60 Nellore bulls and cull cows. NIR spectra were acquired at: P1 –center of Longissimus muscle; and P2 –subcutaneous fat cap. The models accurately estimated (P ≥ 0.083) all carcass and meat quality traits, except those for predicting red ( a* ) and yellow ( b* ) intensity from P1, and 12th-rib fat from P2. However, precision was highly variable among the models; those for the prediction of carcass pHu, 12 th rib fat, toughness from P1, and those for 12 th rib fat, a* and b* from P2 presented high precision (R2 ≥ 0.65 or CCC ≥ 0.63), whereas all other models evaluated presented moderate to low precision (R2 ≤ 0.39). Models built from P1 and P2 accurately estimated (P ≥ 0.066) the chemical composition of the meat plus fat, bones and, meat plus fat plus bones, except those for predicting the ether extract (EE) and crude protein (CP) of bones and the EE of Meat plus bones fraction from P2. However, precision was highly variable among the models (–0.08 ≤ R2 ≤ 0.86) of the 9th and 11th rib section. Those models for the prediction of dry matter (DM) and EE of the bones from P1; of EE from P1; and of EE, mineral matter (MM), CP from P2 of meat plus fat plus bones presented high precision (R2 ≥ 0.76 or CCC ≥ 0.62), whereas all other models evaluated presented moderate to low precision (R2 ≤ 0.45). Thus, models built from portable NIR spectra acquired at different points of the 9th to 11th rib section were recommended for predicting carcass and muscle quality traits as well as for predicting the chemical composition of this section of beef cattle. However, it is noteworthy, that the small sample size was one of the limitations of this study.