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by Catarina Simões, Diana S. Vasconcelos, Raquel Xavier, Xavier Santos, Catarina Rato, D. James Harris
Fire has long been recognized as an important ecological and evolutionary force in plant communities, but its influence on vertebrate community ecology, particularly regarding predator-prey interactions, remains understudied. This study reveals the impact of wildfires on the diet of Podarcis lusitanicus, a lizard species inhabiting a fire-prone region in the Iberian Peninsula. In order to explore diet variability associated with different local burn histories, we evaluated P. lusitanicus diet across three types of sites in Northern Portugal: those had not burned since 2016, those burned in 2016, and those more recently burned in 2022. Podarcis lusitanicus is a generalist arthropod predator with dietary flexibility. Given the turnover of arthropod species after fire, it is expected to find variations in diet caused by different fire histories, especially between unburned and recently burned sites. From DNA metabarcoding of faecal samples, our study revealed that while prey richness remained unaffected by wildfire regime, significant shifts occurred in diet composition between more recently burned and unburned areas. Specifically, we found that differences in diet composition between these two fire regimes were due to the presence of Tapinoma ants and jumping spiders (Salticus scenicus). These prey were present in the diets of lizards occupying unburned areas, while these were absent in areas burned in 2022. Interestingly, diets in unburned areas and areas burned in 2016 showed no significant differences, highlighting the lizards’ ecological flexibility and the habitat’s resilience over time. The ant species T. topitotum was found in dominance in both burned areas, suggesting that this species may be fire tolerant. In addition, families such as Cicadellidae and Noctuidae were found to be more associated with more recently burned areas. The use of DNA metabarcoding in this study was essential to provide a more detailed and accurate view of predator-prey interactions in ecosystems susceptible to fire, and therefore a better understanding of changes in prey consumption in this fire-adapted ecosystem.by Denis Sereno, Tahar Kernif, Renato Leon, Kholoud Kahime, Souad Guernaoui, Chaymaa Harkat, Mario J. Grijalva, Omar Hamarsheh, Anita G. Villacis, Bachir Medrouh, Thiago Vasconcelos Dos Santos, Razika Beniklef, Naouel Eddaikra, Phlippe Holzmuller
IntroductionLeishmaniases are a vector-borne parasitic diseases with diverse clinical manifestations involving multiple Leishmania species and animal hosts. While most leishmaniasis cases are caused by a few well characterized Leishmania species, reports describe infections by unconventional or emerging Leishmania taxa, atypical clinical presentations from classical species, and occurrences of atypical Leishmania in animal hosts. These underrecognized infections present diagnostic and therapeutic challenges and are rarely reflected in surveillance systems or clinical guidelines. A systematic mapping of this evolving landscape is needed to guide future diagnostics, policy, and research priorities.
Methods and analysisFollowing the Joanna Briggs Institute (JBI) methodology and PRISMA-ScR guidelines, we will search PubMed, Embase, Cochrane Library (CENTRAL), PROSPERO, Web of Science, and Global Index Medicus, as well as relevant grey literature. Eligible studies will include human cases with clinical presentations that diverge from those typically associated with well-characterized Leishmania species, reports involving unconventional or emerging Leishmania species, and animal cases of veterinary relevance caused by non-classical species, regardless of study design. Dual independent screening of records and data extraction using a standardized charting form will be conducted. Discrepancies between reviewers will be resolved by consensus. Data will be summarized descriptively through tables, figures, and thematic synthesis. Research gaps will be identified to inform future studies and public health strategies.
DisseminationThis review will use data from published sources and findings will be disseminated through publication in a peer-reviewed journal, presentations at scientific conferences, and sharing with relevant stakeholders. The results are intended to inform clinicians, researchers, and policymakers about the evolving landscape of leishmaniasis and to highlight priorities for future research and surveillance.
by Juliana Rodrigues Tovar Garbin, Franciéle Marabotti Costa Leite, Ana Paula Brioschi dos Santos, Larissa Soares Dell’Antonio, Cristiano Soares da Silva Dell’Antonio, Luís Carlos Lopes-Júnior
A comprehensive understanding of the factors influencing the epidemiological dynamics of COVID-19 across the pandemic waves—particularly in terms of disease severity and mortality—is critical for optimizing healthcare services and prioritizing high-risk populations. Here we aim to analyze the factors associated with short-term and prolonged hospitalization for COVID-19 during the first three pandemic waves. We conducted a retrospective observational study using data from individuals reported in the e-SUS-VS system who were hospitalized for COVID-19 in a state in a southeast state of Brazil. Hospitalization duration was classified as short or prolonged based on a 7-day cutoff, corresponding to the median length of hospital stay during the second pandemic wave. Bivariate analyses were performed using the chi-square test for heterogeneity. Logistic regression models were used to estimate odds ratios (ORs) and their respective 95% confidence intervals (CIs), with statistical significance set at 5%. When analyzing hospitalization duration across the three waves, we found that 51.1% (95%CI: 49.3–53) of hospitalizations in the first wave were prolonged. In contrast, short-duration hospitalizations predominated in the second (54.7%; 95% CI: 52.4–57.0) and third (51.7%; 95% CI: 50.2–53.2) waves. Factors associated with prolonged hospitalization varied by wave. During the first wave, older adults (≥60 years) (OR=1.67; 95%CI: 1.35–2.06), individuals with ≥10 symptoms (OR=2.03; 95%CI: 1.04–3.94), obese individuals (OR=2.0; 95%CI: 1.53–2.74), and those with ≥2 comorbidities (OR=2.22; 95%CI: 1.71–2.89) were more likely to experience prolonged hospitalization. In the second wave, he likelihood of extended hospital stays was higher among individuals aged ≥60 years (OR=2.04; 95%CI: 1.58–2.62) and those with ≥2 comorbidities (OR=1.77; 95%CI: 1.29–2.41). In the third wave, prolonged hospitalization was more frequent among older adults (OR=1.89; 95%CI: 1.65–2.17,), individuals with 5–9 symptoms (OR=1.52; 95%CI: 1.20–1.92), obese individuals (OR=2.2; 95%CI: 1.78–2.73), and those with comorbidities (OR=1.45; 95%CI: 1.22–1.72 and OR=2.0; 95%CI: 1.69–2.45). In conclusion, we identified variations in hospitalization patterns across the pandemic waves, although the differences were relatively subtle. These variations likely reflect gradual shifts in the risk factors associated with prolonged hospital stays. Our findings highlight t the importance of implementing targeted public health interventions, particularly those designed to reduce disease severity and improve clinical outcomes among vulnerable populations at greater risk of extended hospitalization.by Ana Paula Cândido Oliveira, Daniela Alencar Vieira, Cristiane Wanderley Cardoso, Tereza Magalhães, Rosangela Oliveira Anjos, Eduardo José Farias Borges Reis, Kionna Oliveira Bernardes Santos, Guilherme Sousa Ribeiro
Work ability is a subjective concept that reflects the balance between an individual’s perception of the physical, mental, and social demands of work and their competence and resources to meet those demands. The COVID-19 crisis significantly impacted health, work, and socioeconomic conditions worldwide. However, few studies have examined work ability in disadvantaged urban communities during this period. To analyze factors associated with work ability within the context of social vulnerability during the COVID-19 pandemic, we conducted a cross-sectional study in a low-income neighborhood in Salvador, Brazil, between February and June 2022. Sociodemographic, health, and labor data were collected, and work ability was assessed using the Work Ability Index (WAI), a widely used tool for evaluating work ability. Multivariable analyses based on a hierarchical model were run to investigate factors associated with low WAI scores. The study included 292 workers aged ≥16 years (59.6% women; median age 41 years). Most workers (84.6%) were classified as having adequate work ability based on their WAI scores. Multivariable analyses found that inadequate work ability was more frequent among women (prevalence ratio [PR]: 1.89, 95% confidence interval [CI]: 1.02-3.48), individuals who self-rated their health as moderate/good (PR: 5.91; 95% CI: 1.45-24.05) or poor/very poor (PR: 21.62; 95% CI: 5.14-90.91) compared to those with excellent/very good health, and those reporting diabetes (PR: 2.1; 95% CI: 1.13-3.9). Working >40 hours per week (PR: 0.47; 95% CI: 0.28-0.96) was negatively associated with inadequate work ability, suggesting that individuals with adequate work ability may be selected for longer working hours. A history of COVID-19 was not associated with inadequate work ability. These findings suggest that targeted interventions to improve work ability in low-income communities should prioritize women and workers with chronic health conditions, such as diabetes.by Isabela Bittencourt Basso, Pedro Felipe de Jesus Freitas, Aline Xavier Ferraz, Ana Julia Borkovski, Ana Laura Borkovski, Rosane Sampaio Santos, Rodrigo Nunes Rached, Erika Calvano Küchler, Angela Graciela Deliga Schroder, Cristiano Miranda de Araujo, Odilon Guariza-Filho
Characteristics of the mandible structures have been relevant in anthropological and forensic studies for sex prediction. This study aims to evaluate the coronoid process, condyle, and sigmoid notch patterns in sex prediction through supervised machine learning algorithms. Cephalometric radiographs from 410 dental records of patients were screened to investigate the morphology of the coronoid process, condyle, and sigmoid notch and the Co-Gn distance. The following machine learning algorithms were used to build the predictive models: Decision Tree, Gradient Boosting Classifier, K-Nearest Neighbors (KNN), Logistic Regression, Multilayer Perceptron Classifier, Random Forest Classifier, and Support Vector Machine (SVM). A 5-fold cross-validation approach was adopted to validate each model. Metrics such as area under the curve (AUC), accuracy, recall, precision, and F1 Score were calculated for each model, and ROC curves were constructed. All tested variables demonstrated statistical significance (pby Gustavo Ferlini Agne, Kellie Adamson, Leah McGlinchey, Olena Kravchuk, Luiz Santos, John Schumacher
Accuracy of a median nerve block is normally assessed by testing skin sensitivity on the medial and dorsal aspects of fetlock and pastern. The present study evaluated subjective and objective analysis of skin surface temperature obtained with two different infrared (IR) thermography cameras (a high-end [FLIR P640] and a smartphone IR thermography device [FLIR One®]) before and after anaesthesia of the median nerve. Thermographic images were obtained at 0, 30, 60 and 90 minutes after performing a median nerve block with 2% mepivacaine hydrochloride. The subjective analysis of thermographic images using the FLIR P640 camera found assessors had >50% agreement for the presence of a nerve block (p
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