Lucas Alves da Mota Santana

EXCLI Journal - Experimental and Clinical Sciences, International Online Journal for Advances in Sciences

The COVID-19 pandemic necessitated rigorous infection control protocols across hospital environments, particularly in nutrition services. UV-C light emerged as a viable option due to its shortest wavelength, conferring the greatest capacity for nucleic acid (DNA/RNA) penetration in both microorganisms and human cells. We aim to develop and validate an alternative method for decontaminating food carts using UV-C light. A prototype box was created to cover the meal transport carts, with UV-C lamps strategically positioned for irradiation and decontamination. To validate this technology, four different hygiene protocols were compared: Group 1, positive control, with no sanitization procedure; Group 2, cleaned using the standard protocol of the University Hospital of UFS (HU/UFS) with 70% ethanol solution; Group 3, negative control, cleaned using the standard HU/UFS protocol with 70% ethanol and neutral detergent; and Group 4, exposed to UV-C light irradiation for 10 min after food transport. Microbiological samples were collected from 15 distinct points on the carts. Samples were collected using sterile swabs moistened with 0.85% saline solution and incubated in BHI broth at 37 °C for 24 h for presence/absence testing. Positive samples were plated on selective media (CLED, SS, MacConkey and Blood agar), incubated at 37 °C for 24–48 h, and evaluated for colony-forming unit (CFU) count. A statistically significant association was found between the hygiene method and the presence of microbial contamination (p < 0.001), based on both bacterial plate counts and BHI broth growth. Carts sanitized with 70% alcohol showed a lower probability of contamination compared to the control group (alcohol + detergent), while unsanitized carts showed a higher risk. UV-C light treatment resulted in complete absence of bacterial growth. UV-C disinfection demonstrated superior effectiveness in eliminating microorganisms, indicating a promising alternative to traditional methods.

Artificial intelligence (AI) has been widely used in the health sector for diagnostic, assistance and guidance purposes. However, its expansion has come up against applicability barriers in underdeveloped countries due to structural, financial and technological limitations encountered within a specific context. With this letter, we draw attention to the challenges of implementing AI in developing countries, suggesting strategies for scientific studies to optimise this.

Objective: To assess the prevalence of dental caries experience, developmental defects of enamel (DDE),and visible plaque in children from two traditional communities in Brazil, and examine associatedsociodemographic, dietary, and clinical factors. Method: A cross-sectional study was conducted with 40children (≤18 years) from two traditional communities in Sergipe, Brazil. Oral examinations were performedby calibrated examiners using World Health Organization (WHO) standard protocols. Sociodemographic,dietary, and clinical data were obtained through structured interviews with caregivers. A composite outcomewas defined as the presence of dental caries experience, DDE, and/or visible plaque. Poisson regression with robust variance was used to identify associated factors. Result: Overall, 65% of children presented dentalcaries experience, DDE, and/or visible plaque. Significant predictors included clinical comorbidities(adjusted Prevalence Ratio [aPR]: 1.77; 95% CI: 1.30–2.42), breastfeeding >12 months (aPR: 1.64; 95% CI:1.10–2.44), <3 daily meals (aPR: 1.73; 95% CI: 1.04–2.87), and cassava flour consumption (aPR: 1.83; 95%CI: 1.04–3.25). Conclusion: Children from traditional communities showed a high burden of oralconditions, reflecting social vulnerability and food insecurity. These findings highlight the need for early,culturally appropriate preventive strategies focused on oral hygiene and nutrition.