Genomic Comparative of Pseudomonas aeruginosa Small Colony Variant, Mucoid and Non-mucoid Phenotypes Obtained from a Patient with Cystic Fibrosis During Respiratory Exacerbations.

Pseudomonas aeruginosa, the most prevalent opportunistic pathogen in chronic obstructive pulmonary disease, associated with high morbidity and mortality in patients with cystic fibrosis (CF), is practically impossible to be eradicated from the airways in chronicity. Its extraordinary genomic plasticity is possibly associated with high antimicrobial resistance, virulence factors, and its phenotypic diversity. The occurrence of P. aeruginosa isolates promoting airway infection, showing mucoid, non-mucoid, and small colony variant (SCV) phenotypes, was observed simultaneously, in the present study, in sputum cultures obtained from a male CF young patient with chronic pulmonary infection for over a decade. The isolates belonged to a new ST (2744) were obtained in two moments of exacerbation of the respiratory disease, in which he was hospitalized. Genetic background and phenotypic analysis indicated that the isolates exhibited multi- and pan-antimicrobial resistant profiles, as well as non-susceptible to polymyxin and predominantly hypermutable (HPM) phenotypes. Whole genome sequencing showed variations in genome sizes, coding sequences and their determinants of resistance and virulence. The annotated genomes were compared for antimicrobial resistance, hypermutability, and SCV characteristics. We highlight the lack of reported genetic determinants of SCV emergence and HPM phenotypes, which can be explained in part due to the very short time between collections of isolates. To the best of our knowledge, this is the first report of genome sequencing of P. aeruginosa SCV from a CF patient in Brazil.

Impact of the first year of COVID-19 vaccination strategy in Brazil: an ecological study.

OBJECTIVES: No consensus exists about the best COVID-19 vaccination strategy to be adopted by low-income and middle-income countries. Brazil adopted an age-based calendar strategy to reduce mortality and the burden on the healthcare system. This study evaluates the impact of the vaccination campaign in Brazil on the progression of the reported COVID-19 deaths. METHODS: This ecological study analyses the dynamic of vaccination coverage and COVID-19 deaths in hospitalised adults (≥20 years) during the first year of the COVID-19 vaccination roll-out (January to December 2021) using nationwide data (DATASUS). We stratified the adult population into 20-49, 50-59, 60-69 and 70+ years. The dynamic effect of the vaccination campaign on mortality rates was estimated by applying a negative binomial regression. The prevented and possible preventable deaths (observed deaths higher than expected) and potential years of life lost (PYLL) for each age group were obtained in a counterfactual analysis. RESULTS: During the first year of COVID-19 vaccination, 266 153 517 doses were administered, achieving 91% first-dose coverage. A total of 380 594 deaths were reported, 154 091 (40%) in 70+ years and 136 804 (36%) from 50-59 or 20-49 years. The mortality rates of 70+ decreased by 52% (rate ratio [95% CI]: 0.48 [0.43-0.53]) in 6 months, whereas rates for 20-49 were still increasing due to low coverage (52%). The vaccination roll-out strategy prevented 59 618 deaths, 53 088 (89%) from those aged 70+ years. However, the strategy did not prevent 54 797 deaths, 85% from those under 60 years, being 26 344 (45%) only in 20-49, corresponding to 1 589 271 PYLL, being 1 080 104 PYLL (68%) from those aged 20-49 years. CONCLUSION: The adopted aged-based calendar vaccination strategy initially reduced mortality in the oldest but did not prevent the deaths of the youngest as effectively as compared with the older age group. Countries with a high burden, limited vaccine supply and young populations should consider other factors beyond the age to prioritise who should be vaccinated first.

Evaluation of behavioral and neurochemical changes induced by carbofuran in zebrafish (Danio rerio).

Carbofuran (CF) is a carbamate class pesticide, widely used in agriculture for pest control in crops. This pesticide has high toxicity in non-target organisms, and its presence in the environment poses a threat to the ecosystem. Research has revealed that this pesticide acts as an inhibitor of acetylcholinesterase (AChE), inducing an accumulation of acetylcholine in the brain. Nonetheless, our understanding of CF impact on the central nervous system remains elusive. Therefore, this study explored how CF influences behavioral and neurochemical outcomes in adult zebrafish. The animals underwent a 96-hour exposure protocol to different concentrations of CF (5, 50, and 500 µg/L) and were subjected to the novel tank (NTT) and social preference tests (SPT). Subsequently, they were euthanized, and their brains were extracted to evaluate neurochemical markers associated with oxidative stress and AChE levels. In the NTT and SPT, CF did not alter the evaluated behavioral parameters. Furthermore, CF did not affect the levels of AChE, non-protein sulfhydryl groups, and thiobarbituric acid reactive species in the zebrafish brain. Nevertheless, further investigation is required to explore the effects of environmental exposure to this compound on non-target organisms.

Racial inequalities in the development of multimorbidity of chronic conditions: results from a Brazilian prospective cohort.

BACKGROUND: The occurrence of multimorbidity and its impacts have differentially affected population subgroups. Evidence on its incidence has mainly come from high-income regions, with limited exploration of racial disparities. This study investigated the association between racial groups and the development of multimorbidity and chronic conditions in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). METHODS: Data from self-reported white, brown (pardos or mixed-race), and black participants at baseline of ELSA-Brasil (2008-2010) who were at risk for multimorbidity were analysed. The development of chronic conditions was assessed through in-person visits and self-reported diagnosis via telephone until the third follow-up visit (2017-2019). Multimorbidity was defined when, at the follow-up visit, the participant had two or more morbidities. Cumulative incidences, incidence rates, and adjusted incidence rate ratios (IRRs) were estimated using Poisson models. RESULTS: Over an 8.3-year follow-up, compared to white participants: browns had a 27% greater incidence of hypertension and obesity; and blacks had a 62% and 45% greater incidence, respectively. Blacks also had 58% more diabetes. The cancer incidence was greater among whites. Multimorbidity affected 41% of the participants, with a crude incidence rate of 57.5 cases per 1000 person-years (ranging from 56.3 for whites to 63.9 for blacks). Adjusted estimates showed a 20% higher incidence of multimorbidity in black participants compared to white participants (IRR: 1.20; 95% CI: 1.05-1.38). CONCLUSIONS: Significant racial disparities in the risk of chronic conditions and multimorbidity were observed. Many associations revealed a gradient increase in illness risk according to darker skin tones. Addressing fundamental causes such as racism and racial discrimination, alongside considering social determinants of health, is vital for comprehensive multimorbidity care. Intersectoral, equitable policies are essential for ensuring health rights for historically marginalized groups.

Persistent high mortality rates for Diabetes Mellitus and Hypertension after excluding deaths associated with COVID-19 in Brazil, 2020-2022.

INTRODUCTION: The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) posed a significant public health challenge globally, with Brazil being no exception. Excess mortality during this period reached alarming levels. Cardiovascular diseases (CVD), Systemic Hypertension (HTN), and Diabetes Mellitus (DM) were associated with increased mortality. However, the specific impact of DM and HTN on mortality during the pandemic remains poorly understood. METHODS: This study analyzed mortality data from Brazil's mortality system, covering the period from 2015 to 2022. Data included all causes of death as listed on death certificates, categorized by International Classification of Diseases 10th edition (ICD-10) codes. Population data were obtained from the Brazilian Census. Mortality ratios (MRs) were calculated by comparing death rates in 2020, 2021, and 2022 to the average rates from 2015 to 2019. Adjusted MRs were calculated using Poisson models. RESULTS: Between 2015 and 2022, Brazil recorded a total of 11,423,288 deaths. Death rates remained relatively stable until 2019 but experienced a sharp increase in 2020 and 2021. In 2022, although a decrease was observed, it did not return to pre-pandemic levels. This trend persisted even when analyzing records mentioning DM, HTN, or CVD. Excluding death certificates mentioning COVID-19 codes, the trends still showed increases from 2020 through 2022, though less pronounced. CONCLUSION: This study highlights the persistent high mortality rates for DM and HTN in Brazil during the years 2020-2022, even after excluding deaths associated with COVID-19. These findings emphasize the need for continued attention to managing and preventing DM and HTN as part of public health strategies, both during and beyond the COVID-19 pandemic. There are complex interactions between these conditions and the pandemic's impact on mortality rates.

Was the COVID-19 epidemic synchronous in space? An analysis in the health regions of the Rio de Janeiro state, 2020-2022.

OBJECTIVE: To analyze the spatio-temporal dynamics of COVID-19 in the Rio de Janeiro state within the nine health regions, between March 2020 and December 2022. METHODS: The Poisson model with random effects was used to smooth and estimate the incidence of COVID-19 hospitalizations reported in the Influenza Epidemiological Surveillance Information System (SIVEP-Gripe) to verify the synchronicity of the epidemic in the state. RESULTS: The COVID-19 epidemic in the state is characterized by the presence of seven peaks during the analyzed period corresponding to seven found. An asynchrony in hospitalizations was identified, varying according to the different virus variants in the nine health regions of the state. The incidence peaks of hospitalizations ranged from 1 to 12 cases per 100,000 inhabitants during the pandemic. CONCLUSION: This spatio-temporal analysis is applicable to other scenarios, enabling monitoring and decision-making for the control of epidemic diseases in different areas.

Integrated environmental assessment of iron ore tailings in floodplain soils and plants after the Fundão Dam disaster in Brazil.

Previous studies of the Doce River basin (Brazil) seem to be contradictory regarding the contamination of soils with potentially harmful elements (PHE). This research aimed to perform an integrated assessment of PHE in the soil-plant-tailing system from the area most affected by the iron waste after the Fundão Dam disaster in 2015. Different fractions of PHE (exchangeable, nonexchangeable, reducible, and pseudo-total) were determined on deposited iron waste (DIW), soil waste mixture (SWM), and control soil (CS) samples. Total contents of PHE in Poaceae were also determined, and Allium cepa bioassays were performed to determine DIW and CS cytotoxicity and/or genotoxicity to plants. The Fe and Mn contaminations were the only ones related to the deposition of DIW on floodplains, and other harmful element content (such as As, Hg, Ni, Cd, Cr, and Pb) was not found above baseline values for soils. In addition, a significant part of the Fe and Mn in DIW is readily available or subject to acidification and prolonged flood reduction processes. The high available content of Fe favored its excessive accumulation by Brachiaria. The DIW chemical conditions reduced biological functions of A. cepa under a controlled environment. However, more drastic effects, such as genetic damage, were not seen. The postdisaster action of covering DIW with CS resulted in undesirable enrichment of Pb on the floodplain soils. The integrated results allow the conclusion that the iron waste is not a time bomb for PHE contamination of soils between the Fundão and Risoleta Neves Hydroelectric Dam (~100 km away from Fundão). Integr Environ Assess Manag 2024;20:117-132. © 2023 SETAC.

Development and validation of a machine learning model to predict the use of renal replacement therapy in 14,374 patients with COVID-19.

PURPOSE: To develop a model to predict the use of renal replacement therapy (RRT) in COVID-19 patients. MATERIALS AND METHODS: Retrospective analysis of multicenter cohort of intensive care unit (ICU) admissions of Brazil involving COVID-19 critically adult patients, requiring ventilatory support, admitted to 126 Brazilian ICUs, from February 2020 to December 2021 (development) and January to May 2022 (validation). No interventions were performed. RESULTS: Eight machine learning models' classifications were evaluated. Models were developed using an 80/20 testing/train split ratio and cross-validation. Thirteen candidate predictors were selected using the Recursive Feature Elimination (RFE) algorithm. Discrimination and calibration were assessed. Temporal validation was performed using data from 2022. Of 14,374 COVID-19 patients with initial respiratory support, 1924 (13%) required RRT. RRT patients were older (65 [53-75] vs. 55 [42-68]), had more comorbidities (Charlson's Comorbidity Index 1.0 [0.00-2.00] vs 0.0 [0.00-1.00]), had higher severity (SAPS-3 median: 61 [51-74] vs 48 [41-58]), and had higher in-hospital mortality (71% vs 22%) compared to non-RRT. Risk factors for RRT, such as Creatinine, Glasgow Coma Scale, Urea, Invasive Mechanical Ventilation, Age, Chronic Kidney Disease, Platelets count, Vasopressors, Noninvasive Ventilation, Hypertension, Diabetes, modified frailty index (mFI) and Gender, were identified. The best discrimination and calibration were found in the Random Forest (AUC [95%CI]: 0.78 [0.75-0.81] and Brier's Score: 0.09 [95%CI: 0.08-0.10]). The final model (Random Forest) showed comparable performance in the temporal validation (AUC [95%CI]: 0.79 [0.75-0.84] and Brier's Score, 0.08 [95%CI: 0.08-0.1]). CONCLUSIONS: An early ML model using easily available clinical and laboratory data accurately predicted the use of RRT in critically ill patients with COVID-19. Our study demonstrates that using ML techniques is feasible to provide early prediction of use of RRT in COVID-19 patients.

The Association Between Prepandemic ICU Performance and Mortality Variation in COVID-19: A Multicenter Cohort Study of 35,619 Critically Ill Patients.

BACKGROUND: During the COVID-19 pandemic, ICUs remained under stress and observed elevated mortality rates and high variations of outcomes. A knowledge gap exists regarding whether an ICU performing best during nonpandemic times would still perform better when under high pressure compared with the least performing ICUs. RESEARCH QUESTION: Does prepandemic ICU performance explain the risk-adjusted mortality variability for critically ill patients with COVID-19? STUDY DESIGN AND METHODS: This study examined a cohort of adults with real-time polymerase chain reaction-confirmed COVID-19 admitted to 156 ICUs in 35 hospitals from February 16, 2020, through December 31, 2021, in Brazil. We evaluated crude and adjusted in-hospital mortality variability of patients with COVID-19 in the ICU during the pandemic. Association of baseline (prepandemic) ICU performance and in-hospital mortality was examined using a variable life-adjusted display (VLAD) during the pandemic and a multivariable mixed regression model adjusted by clinical characteristics, interaction of performance with the year of admission, and mechanical ventilation at admission. RESULTS: Thirty-five thousand six hundred nineteen patients with confirmed COVID-19 were evaluated. The median age was 52 years, median Simplified Acute Physiology Score 3 was 42, and 18% underwent invasive mechanical ventilation. In-hospital mortality was 13% and 54% for those receiving invasive mechanical ventilation. Adjusted in-hospital mortality ranged from 3.6% to 63.2%. VLAD in the most efficient ICUs was higher than the overall median in 18% of weeks, whereas VLAD was 62% and 84% in the underachieving and least efficient groups, respectively. The least efficient baseline ICU performance group was associated independently with increased mortality (OR, 2.30; 95% CI, 1.45-3.62) after adjusting for patient characteristics, disease severity, and pandemic surge. INTERPRETATION: ICUs caring for patients with COVID-19 presented substantial variation in risk-adjusted mortality. ICUs with better baseline (prepandemic) performance showed reduced mortality and less variability. Our findings suggest that achieving ICU efficiency by targeting improvement in organizational aspects of ICUs may impact outcomes, and therefore should be a part of the preparedness for future pandemics.

Was the COVID-19 epidemic synchronous in space? An analysis in the health regions of the Rio de Janeiro state, 2020-2022 / A epidemia de COVID-19 foi síncrona no espaço? Uma análise nas regiões de saúde do estado do Rio de Janeiro, 2020-2022

ABSTRACT Objective: To analyze the spatio-temporal dynamics of COVID-19 in the Rio de Janeiro state within the nine health regions, between March 2020 and December 2022. Methods: The Poisson model with random effects was used to smooth and estimate the incidence of COVID-19 hospitalizations reported in the Influenza Epidemiological Surveillance Information System (SIVEP-Gripe) to verify the synchronicity of the epidemic in the state. Results: The COVID-19 epidemic in the state is characterized by the presence of seven peaks during the analyzed period corresponding to seven found. An asynchrony in hospitalizations was identified, varying according to the different virus variants in the nine health regions of the state. The incidence peaks of hospitalizations ranged from 1 to 12 cases per 100,000 inhabitants during the pandemic. Conclusion: This spatio-temporal analysis is applicable to other scenarios, enabling monitoring and decision-making for the control of epidemic diseases in different areas.

RESUMO Objetivo: Analisar a dinâmica espaço-temporal de COVID-19 no estado do Rio de Janeiro nas nove regiões de saúde, entre março de 2020 e dezembro de 2022. Métodos: Utilizou-se o modelo de Poisson com efeitos aleatórios para suavizar a curva de incidência de hospitalizações por COVID-19 notificadas no Sistema de Informação da Vigilância Epidemiológica da Gripe (Sivep-Gripe) para verificar a sincronicidade da epidemia no estado. Resultados: A epidemia de COVID-19 no estado é caracterizada pela presença de sete picos no período analisado correspondentes a sete variantes encontradas. Identificou-se uma assincronicidade nas hospitalizações, variando de acordo com as diferentes variantes do vírus nas nove regiões de saúde do estado. Os picos de incidência das hospitalizações variaram de 1 a 12 casos por 100 mil habitantes no decorrer da pandemia. Conclusão: Essa análise espaço-temporal é extensível em outros cenários, sendo possível o monitoramento e a tomada de decisões de controle de doenças epidêmicas em várias áreas.

Joint spatial modeling of the risks of co-circulating mosquito-borne diseases in Ceará, Brazil.

Mosquito-borne diseases such as dengue and chikungunya have been co-circulating in the Americas, causing great damage to the population. In 2021, for instance, almost 1.5 million cases were reported on the continent, being Brazil the responsible for most of them. Even though they are transmitted by the same mosquito, it remains unclear whether there exists a relationship between both diseases. In this paper, we model the geographic distributions of dengue and chikungunya over the years 2016 to 2021 in the Brazilian state of Ceará. We use a Bayesian hierarchical spatial model for the joint analysis of two arboviruses that includes spatial covariates as well as specific and shared spatial effects that take into account the potential autocorrelation between the two diseases. Our findings allow us to identify areas with high risk of one or both diseases. Only 7% of the areas present high relative risk for both diseases, which suggests a competition between viruses. This study advances the understanding of the geographic patterns and the identification of risk factors of dengue and chikungunya being able to help health decision-making.

Neurobehavioral effects of fungicides in zebrafish: a systematic review and meta-analysis.

Pesticides are widely used in global agriculture to achieve high productivity levels. Among them, fungicides are specifically designed to inhibit fungal growth in crops and seeds. However, their application often results in environmental contamination, as these chemicals can persistently be detected in surface waters. This poses a potential threat to non-target organisms, including humans, that inhabit the affected ecosystems. In toxicologic research, the zebrafish (Danio rerio) is the most commonly used fish species to assess the potential effects of fungicide exposure, and numerous and sometimes conflicting findings have been reported. To address this, we conducted a systematic review and meta-analysis focusing on the neurobehavioral effects of fungicides in zebrafish. Our search encompassed three databases (PubMed, Scopus, and Web of Science), and the screening process followed predefined inclusion/exclusion criteria. We extracted qualitative and quantitative data, as well as assessed reporting quality, from 60 included studies. Meta-analyses were performed for the outcomes of distance traveled in larvae and adults and spontaneous movements in embryos. The results revealed a significant overall effect of fungicide exposure on distance, with a lower distance traveled in the exposed versus control group. No significant effect was observed for spontaneous movements. The overall heterogeneity was high for distance and moderate for spontaneous movements. The poor reporting practices in the field hindered a critical evaluation of the studies. Nevertheless, a sensitivity analysis did not identify any studies skewing the meta-analyses. This review underscores the necessity for better-designed and reported experiments in this field.

Registration with Primary Health Care and COVID-19 mortality: cohort of diabetics from five administrative health regions in the city of Rio de Janeiro, Brazil, 2020-2021. / Cadastro na Atenção Primária e mortalidade por COVID-19: coorte de diabéticos de cinco regiões administrativas de saúde do município do Rio de Janeiro, 2020­2021.

OBJECTIVE: The present study carried out an analysis of survival according to the status of registration with Primary Health Care (PHC) and of factors associated with death from COVID-19, in cases residing in Programmatic Area 3.1 (PA3.1) with a diagnosis of diabetes (in the notification form or in the electronic medical record), of the Municipality of Rio de Janeiro (RJ), Brazil, in 2020-2021. METHODS: A probabilistic linkage of databases was performed based on information on cases notified as COVID-19 and data from the electronic medical records of people living with diabetes. A survival analysis was carried out, using the Cox regression model stratified by age group and adjusted for confounding variables. RESULTS: Individuals registered with the PHC of PA3.1 had almost twice the risk of death from COVID-19 (adjusted hazard ratio [HRadj]=1.91) when compared to those unregistered. This association was stronger in individuals aged 18 to 59 years registered with the PHC (HRadj=2.82) than in individuals aged 60 years or over (HRadj=1.56). CONCLUSION: Surveillance strategies for identifying and adequately monitoring higher-risk groups, among individuals living with diabetes, within the scope of Primary Health Care, can contribute to reducing mortality from COVID-19.

OBJETIVO: O presente estudo realizou uma análise de sobrevivência segundo situação de cadastro na Atenção Primária à Saúde (APS) e de fatores associados ao óbito por COVID-19, nos casos residentes da Área Programática 3.1 (AP3.1) com diagnóstico de diabetes (na ficha de notificação ou no prontuário eletrônico) do município do Rio de Janeiro, em 2020­2021. MÉTODOS: Foi realizado relacionamento probabilístico de bases de dados com base nas informações dos casos notificados por COVID-19 e dos dados de prontuário eletrônico de pessoas que vivem com diabetes. Conduziu-se uma análise de sobrevivência, utilizando-se o modelo de regressão de Cox estratificado por faixa etária e ajustando-se por variáveis confundidoras. RESULTADOS: Verificou-se que indivíduos cadastrados na APS da AP3.1 possuíam risco quase duas vezes maior de óbito por COVID-19 (hazard ratio ajustada ­ HRaj=1,91) quando comparados aos não cadastrados na APS da AP3.1. Essa associação foi mais forte naqueles com 18 a 59 anos, cadastrados na APS (HRaj=2,82), do que nos de 60 anos ou mais (HRaj=1,56). CONCLUSÃO: Estratégias de vigilância para a identificação e acompanhamento adequado de grupos de maior risco de mortalidade, dentre indivíduos que vivem com DM, no âmbito da APS podem contribuir para a redução da mortalidade em decorrência da COVID-19.

Systematic review and meta-analysis of 10 years of unpredictable chronic stress in zebrafish.

The zebrafish (Danio rerio) is a model animal that is being increasingly used in neuroscience research. A decade ago, the first study on unpredictable chronic stress (UCS) in zebrafish was published, inspired by protocols established for rodents in the early 1980s. Since then, several studies have been published by different groups, in some cases with conflicting results. Here we conducted a systematic review to identify studies evaluating the effects of UCS in zebrafish and meta-analytically synthetized the data of neurobehavioral outcomes and relevant biomarkers. Literature searches were performed in three databases (PubMed, Scopus and Web of Science) with a two-step screening process based on inclusion/exclusion criteria. The included studies underwent extraction of qualitative and quantitative data, as well as risk-of-bias assessment. Outcomes of included studies (n = 38) were grouped into anxiety/fear-related behavior, locomotor function, social behavior or cortisol level domains. UCS increased anxiety/fear-related behavior and cortisol levels while decreasing locomotor function, but a significant summary effect was not observed for social behavior. Despite including a substantial number of studies, the high heterogeneity and the methodological and reporting problems evidenced in the risk-of-bias analysis made it difficult to assess the internal validity of most studies and the overall validity of the model. Our review thus evidences the need to conduct well-designed experiments to better evaluate the effects of UCS on diverse behavioral patterns displayed by zebrafish.