SOUTHERN JOURNAL OF SCIENCES

Background: Ketogenic diets have a long history of therapeutic use and have recently attracted significant attention due to their promising effects on a variety of disorders. However, no definitive links have been identified. This review aims to highlight the possible impacts of ketogenic diets as well as the mechanisms involved in metabolic processes and related non-communicable metabolic diseases. Methods: For our analysis, a bibliographic review of articles about ketogenic diets and their therapeutic effect on chronic pathologies was carried out, retrieved from the scientific literature. Results and discussion: These studies found both positive and negative outcomes for the effects and implications of ketogenic diets on metabolism. Significant differences in metabolic markers such as weight, glycemia, serum lipids and lipoproteins, anthropometric measures, and hormones such as insulin, leptin, and adiponectin have been reported. In addition to changes in the microbiome that have modest to moderate concurrent effects, changes in metabolism indicate the significance of dietary changes in treating and preventing chronic non-communicable diseases. Conclusions: In this review, we present the available scientific evidence on the effects of the ketogenic diet, and thus ketone bodies, on metabolism and related chronic diseases.

Introduction: The detection of methanol in alcoholic beverages represents a critical public health issue, particularly in light of the recent outbreak of poisonings in Brazil, which registered 58 confirmed cases and 15 deaths through October 2025. Methanol's toxicity, with an estimated lethal dose ranging from 0.5 to 1.5 g/kg, requires reliable analytical methods for health surveillance. Brazilian legislation establishes a maximum limit of 20 mg/100 mL of anhydrous alcohol; however, the need for accessible screening methods in field settings remains an important challenge. Objective: To critically compare three analytical methods for methanol determination: classical qualitative methods (Lucas Test and dichromate/Schiff), Brazilian colorimetric method, and gas chromatography with flame ionization detector (GC-FID), evaluating their performance and applicability in resource-limited contexts. Methods: Theoretical-comparative approach through critical analysis of specialized literature and normative technical documentation. Methods were evaluated according to: operational principle, sensitivity (LOD/LOQ), selectivity, operational complexity, analysis time, and practical applicability. Results: The Lucas Test is not applicable for methanol detection. Colorimetric methods showed moderate sensitivity (LOD ~20-160 mg/100 mL), a 10-30-minute execution time, low operational complexity, and excellent portability. The Brazilian method presented chemical equivalence with international standards, differing only in the type of reading performed. GC-FID has shown superior sensitivity (LOD ≤ 1 mg/100 mL) and high specificity, but it requires extended time (~45-60 minutes), complex laboratory infrastructure, and specialized operators. Sugars interfere with colorimetric methods. Conclusions: The methods are complementary within a hierarchical system. Colorimetric methods enable rapid field screening, while GC-FID serves as the confirmatory method for forensic analyses. We recommend implementing integrated protocols that combine in situ colorimetric screening with GC-FID confirmation in accredited laboratories for effective health surveillance.

Background: in the last decades, colocalization analysis of fluorescently tagged biomolecules has proven to be a powerful approach to studying functional relationships between these biomolecules. However, in many cases, to give this analysis a biological meaning, colocalization coefficients must be tested statistically, comparing them with the colocalization expected by chance. Aim: It addressed the statistical significance of triple colocalization to distinguish real triple colocalization and classify different triple signal scenarios. Methods: we use biological and generated images of triple signal scenarios to contrast seven independent statistical facts with independent statistical tests. Three of these tests correspond to pairwise relationships (double scrambling tests), and the others correspond to triple relationships: single scrambling tests (red, green, and blue scrambling) and the triple scrambling test. The analysis and methodology proposed can be reproduced using the application developed in our laboratory. Results: In the study approach, we found true triple relationships ignored by using traditional methods of computing the statistical significance, while we could reinterpret cases of not significant triple colocalization wrongly considered as significant by traditional methods. Discussion: single scrambling tests can reveal significant triple colocalization for low levels of triple co-occurrence, even when all pairwise relationships were exclusion relationships. Moreover, on the other hand, single scrambling tests can reveal the absence of a significant triple colocalization for high levels of triple co-occurrence, even when all pairwise relationships were significant colocalization. Conclusion: all scrambling tests are useful to classify a specific scenario of a triple relationship. Dynamics like mitosis can be distinguished into their phases by triple signal relationships using these 7 independent statistical tests.