This study aimed to develop chitosan films incorporating natural antioxidants from peanut skin (EPS) and pink pepper residue (EPP) extracts, as well as to evaluate their effects on lipid oxidation, ...pH, color, and microbial counts of a restructured chicken product. EPS had higher phenolic content and antioxidant activity compared to EPP. When both extracts were applied to chicken meat and the chitosan films, there were no differences for color, pH and total mesophilic counts compared to control at the end of the storage period. For lipid oxidation (peroxide value and thiobarbituric acid reactive substances), both extracts proved to be as effective as butylated hydroxytoluene to maintain the oxidative stability of the chicken product. The microbial counts of psychrotrophic microorganisms were significantly lower for treatments with active films. Chitosan active films with residue extracts may maintain the quality of chicken products due to their antioxidant and antimicrobial potential.
•Chitosan films with residue extracts were studied as active packaging in chicken product.•Extract of peanut skin had higher DPPH and ABTS values than that of pink pepper residue.•Both extracts, either added to the product or to the films, were as effective as BHT.•Chitosan films with natural extracts showed lower psychrotrophic counts.•Active films with residue extracts may maintain the quality of chicken products.
Vegetables are widely consumed in Brazil and exported to several countries. This study was performed to evaluate the phenolic content and antioxidant activity of vegetables commonly consumed in ...Brazil using five different methods, namely DPPH and ABTS free radical, β-carotene bleaching, reduction of Fe(3+) (FRAP), oxidative stability in Rancimat, and the chemical composition using gas chromatography-mass spectrometry (GC-MS). The content of phenolic compounds ranged from 1.2 mg GA/g (carrot) to 16.9 mg GA/g (lettuce). Vegetables presenting the highest antioxidant activity were lettuce (77.2 μmol Trolox/g DPPH(•); 447.1 μmol F(2+)/g FRAP), turmeric (118.6 μmol Trolox/g ABTS(•+); 92.8% β-carotene), watercress and broccoli (protective factor 1.29-Rancimat method). Artichoke, spinach, broccoli, and asparagus also showed considerable antioxidant activity. The most frequent phenolic compounds identified by GC-MS were ferulic, caffeic, p-coumaric, 2-dihydroxybenzoic, 2,5-dihydroxybenzoic acids, and quercetin. We observed antioxidant activity in several vegetables and our results point out their importance in the diet.
Agro-industrial activities generate millions of tons of residues all over the world. Although many of them contain bioactive compounds, they are underexplored. Ethanolic extracts of beetroot stems ...(EEB) and guava pomace (peels, seeds) (EEG) were analyzed to assess their chemical composition (phenolic compounds and chemical profile by GC-MS) and antioxidant activity (EC
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and ABTS). Posteriorly, EEB and EEG were added to processed chicken meat, which was cooked and stored in vacuum and aerobic packages at 4 ± 1 °C for 14 days, to assess their oxidative stability and color. EEB presented higher content of phenolic compounds and antioxidant activity compared to EEG. Using GC-MS, we identified 11 phenolic compounds in EEB and EEG. When added to chicken meat, EEG and EEB retarded lipid oxidation compared to the control after 14 days of storage in aerobic packages. In general, in both packages the natural extracts proved to be as effective as BHT to maintain oxidative stability of chicken meat.
Guava pomace is an example of the processing waste generated after the manufacturing process from the juice industry that could be a source of bioactives. Thus, the present investigation was carried ...out in order to evaluate the anti-inflammatory and antinociceptive potential and determinate the main phenolic compounds of a guava pomace extract (GPE).
The anti-inflammatory activity was evaluated by carrageenan, dextran, serotonin, histamine-induced paw edema and neutrophils migration in the peritoneal cavity models. Acetic acid-induced abdominal writhing and formalin test were performed to investigate the antinociceptive effects. In addition, the content of total phenolic and of individual phenolic compounds was determined by GC/MS.
GPE showed anti-inflammatory activity by carrageenan, dextran, serotonin, histamine-induced paw edema and neutrophils migration in the peritoneal cavity models (p < 0.05). GPE also demonstrated antinociceptive activity by acetic acid-induced abdominal writhing and formalin test (p < 0.05). The total phenolic value was 3.40 ± 0.09 mg GAE/g and epicatechin, quercetin, myricetin, isovanilic and gallic acids were identified by GC/MS analysis.
The presence of bioactive phenolic compounds as well as important effects demonstrated in animal models suggest that guava pomace could be an interesting source of anti-inflammatory and analgesic substances.
Identifying patients at increased risk of loss to follow-up (LTFU) is key to developing strategies to optimize the clinical management of tuberculosis (TB). The use of national registry data in ...prediction models may be a useful tool to inform healthcare workers about risk of LTFU. Here we developed a score to predict the risk of LTFU during anti-TB treatment (ATT) in a nationwide cohort of cases using clinical data reported to the Brazilian Notifiable Disease Information System (SINAN).
We performed a retrospective study of all TB cases reported to SINAN between 2015 and 2022; excluding children (< 18 years-old), vulnerable groups or drug-resistant TB. For the score, data before treatment initiation were used. We trained and internally validated three different prediction scoring systems, based on Logistic Regression, Random Forest, and Light Gradient Boosting. Before applying our models we splitted our data into training (~ 80% data) and test (~ 20%) sets, and then compared the model metrics using the test data set.
Of the 243,726 cases included, 41,373 experienced LTFU whereas 202,353 were successfully treated. The groups were different with regards to several clinical and sociodemographic characteristics. The directly observed treatment (DOT) was unbalanced between the groups with lower prevalence in those who were LTFU. Three models were developed to predict LTFU using 8 features (prior TB, drug use, age, sex, HIV infection and schooling level) with different score composition approaches. Those prediction scoring systems exhibited an area under the curve (AUC) ranging between 0.71 and 0.72. The Light Gradient Boosting technique resulted in the best prediction performance, weighting specificity and sensitivity. A user-friendly web calculator app was developed ( https://tbprediction.herokuapp.com/ ) to facilitate implementation.
Our nationwide risk score predicts the risk of LTFU during ATT in Brazilian adults prior to treatment commencement utilizing schooling level, sex, age, prior TB status, and substance use (drug, alcohol, and/or tobacco). This is a potential tool to assist in decision-making strategies to guide resource allocation, DOT indications, and improve TB treatment adherence.
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