Machine learning algorithms using national registry data to predict loss to follow-up during tuberculosis treatment.

Background: 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).

The impact of ZIKV infection on gene expression in neural cells over time.

Zika virus (ZIKV) outbreak caused one of the most significant medical emergencies in the Americas due to associated microcephaly in newborns. To evaluate the impact of ZIKV infection on neuronal cells over time, we retrieved gene expression data from several ZIKV-infected samples obtained at different time point post-infection (pi). Differential gene expression analysis was applied at each time point, with more differentially expressed genes (DEG) identified at 72h pi.

Machine learning algorithms using national registry data to predict loss to follow- up during tuberculosis treatment.

Background: 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).

Chitosan active films containing agro-industrial residue extracts for shelf life extension of chicken restructured product.

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.

Guava pomace: a new source of anti-inflammatory and analgesic bioactives.

Background: 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).

Methods: The anti-inflammatory activity was evaluated by carrageenan, dextran, serotonin, histamine-induced paw edema and neutrophils migration in the peritoneal cavity models.

Antioxidant activity of Brazilian vegetables and its relation with phenolic composition.

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.