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Respiratory syncytial virus (RSV) is an important cause of respiratory illness. While most attention is paid to childhood infection, the RSV burden in adults ≥60 y should also be considered. In Brazil, this is generally underrecognized, where greater focus is toward other respiratory pathogens. This article presents insights from a multidisciplinary panel gathered to review epidemiologic data and current diagnostic approaches to RSV in Brazil (and their limitations) and develop communication strategies to improve knowledge and awareness. National surveillance data indicate a steady increase in cases of RSV-related severe acute respiratory illness (RSV-SARI) in those aged ≥60 y in recent years, with high fatality rates (>30%). Routine RSV testing in older individuals with respiratory symptoms is relatively low. Educational activities targeted toward health-care professionals and the general public are critical to raising awareness of the importance of RSV in older individuals, particularly as protective vaccines are now available.

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The 2023 Annual Symposium of the Fisheries Society of the British Isles hosted opportunities for researchers, scientists, and policy makers to reflect on the state of art of predicting fish distributions and consider the implications to the marine and aquatic environments of a changing climate. The outcome of one special interest group at the Symposium was a collection of questions, organized under five themes, which begin to capture the state of the field and identify priorities for research and management over the coming years. The five themes were Physiology, Mechanisms, Detect and Measure, Manage, and Wider Ecosystems. The questions, 25 of them, addressed concepts which remain poorly understood, are data deficient, and/or are likely to be impacted in measurable or profound ways by climate change. Moving from the first to the last theme, the questions expanded in the scope of their considerations, from specific processes within the individual to ecosystem-wide impacts, but no one question is bigger than any other: each is important in detecting, understanding, and predicting fish distributions, and each will be impacted by an aspect of climate change. In this way, our questions, particularly those concerning unknown mechanisms and data deficiencies, aimed to offer a guide to other researchers, managers, and policy makers in the prioritization of future work as a changing climate is expected to have complex and disperse impacts on fish populations and distributions that will require a coordinated effort to address.

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Cullin-1-RING ubiquitin ligases (CRL1) or SCF1 (SKP1-CUL1-RBX1) E3 ubiquitin ligases are the largest and most extensively investigated class of E3 ligases in mammals that regulate fundamental processes, such as the cell cycle and proliferation. These enzymes are multiprotein complexes comprising SKP1, CUL1, RBX1, and an F-box protein that acts as a specificity factor by interacting with SKP1 through its F-box domain and recruiting substrates via other domains. E3 ligases are important players in the ubiquitination process, recognizing and transferring ubiquitin to substrates destined for degradation by proteasomes or processing by deubiquitinating enzymes. The ubiquitin-proteasome system (UPS) is the main regulator of intracellular proteolysis in eukaryotes and is required for parasites to alternate hosts in their life cycles, resulting in successful parasitism. Leishmania UPS is poorly investigated, and CRL1 in L. infantum, the causative agent of visceral leishmaniasis in Latin America, is yet to be described. Here, we show that the L. infantum genes LINF_110018100 (SKP1-like protein), LINF_240029100 (cullin-like protein-like protein), and LINF_210005300 (ring-box protein 1 -putative) form a LinfCRL1 complex structurally similar to the H. sapiens CRL1. Mass spectrometry analysis of the LinfSkp1 and LinfCul1 interactomes revealed proteins involved in several intracellular processes, including six F-box proteins known as F-box-like proteins (Flp) (data are available via ProteomeXchange with identifier PXD051961). The interaction of LinfFlp 1-6 with LinfSkp1 was confirmed, and using in vitro ubiquitination assays, we demonstrated the function of the LinfCRL1(Flp1) complex to transfer ubiquitin. We also found that LinfSKP1 and LinfRBX1 knockouts resulted in nonviable L. infantum lineages, whereas LinfCUL1 was involved in parasite growth and rosette formation. Finally, our results suggest that LinfCul1 regulates the S phase progression and possibly the transition between the late S to G2 phase in L. infantum. Thus, a new class of E3 ubiquitin ligases has been described in L. infantum with functions related to various parasitic processes that may serve as prospective targets for leishmaniasis treatment.

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The influenza-like illness (ILI) sentinel surveillance operates in Brazil to identify respiratory viruses of public health relevance circulating in the country and was first implemented in 2000. Recently, the COVID-19 pandemic reinforced the importance of early detection of the circulation of new viruses in Brazil. Therefore, an analysis of the design of the ILI sentinel surveillance is timely. To this end, we simulated a sentinel surveillance network, identifying the municipalities that would be part of the network according to the criteria defined in the design of the ILI sentinel surveillance and, based on data from tested cases of severe acute respiratory illness (SARI) from 2014 to 2019, we drew samples for each sentinel municipality per epidemiological week. The draw was performed 1,000 times, obtaining the median and 95% quantile interval (95%QI) of virus positivity by Federative Unit and epidemiological week. According to the ILI sentinel surveillance design criteria, sentinel units would be in 64 municipalities, distributed mainly in capitals and their metropolitan areas, recommending 690 weekly samples. The design showed good sensitivity (91.65% considering the 95%QI) for qualitatively detecting respiratory viruses, even those with low circulation. However, there was important uncertainty in the quantitative estimate of positivity, reaching at least 20% in 11.34% of estimates. The results presented here aim to assist in evaluating and updating the ILI sentinel surveillance design. Strategies to reduce uncertainty in positivity estimates need to be evaluated, as does the need for greater spatial coverage.

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Meropenem is a potent carbapenem antibiotic frequently used in medical settings. Several studies have confirmed the pervasive presence of these antibiotics in wastewater treatment plants and aquatic environments. However, the effects of these substances on non-target organisms, such as plants, have not been adequately monitored. Thus, this study aimed to assess the short-term impact of meropenem on the growth, photosynthesis, chlorophyll content, and enzyme activity of the macrophyte plant Lemna minor. The methods involved exposing the plant to meropenem under controlled conditions and assessing physiological and biochemical parameters to determine the impact on photosynthetic activity and oxidative stress. These analyses included growth rate, antioxidant enzyme activity, and photosynthetic capacity. The findings suggest that the growth rate of Lemna minor remained unaffected by meropenem at concentrations <200000 µgL-1. However, plants exposed to concentrations >20 µgL-1showed physiological alterations, such as decreased net photosynthesis rate (17%) and chlorophyll concentration (57%), compared to the control group. For acute toxicity assays, the calculated EC50 7-day and EC20 7-day were 1135 µgL-1and 33 µgL-1, respectively. In addition, in most treatments tested, meropenem caused an increase in the superoxide dismutase (SOD), catalase (CAT) and ascorbate peroxidase (APX) activity as a defense mechanism against oxidative stress. Our results suggest that meropenem affects photosynthetic processes and induces oxidative stress in the macrophyte plant Lemna minor. Further studies are needed to assess the physiological and metabolic interactions between antibiotics and primary producers at different long-term trophic levels.

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We compared the ability of one emergent (Sagittaria montevidensis), two floating (Salvinia minima and Lemna gibba), and one heterophyllous species (Myriophyllum aquaticum) to simultaneously remove sulfamethoxazole, sulfadiazine, ciprofloxacin, enrofloxacin, norfloxacin, levofloxacin, oxytetracycline, tetracycline, doxycycline, azithromycin, amoxicillin, and meropenem from wastewater in a mesocosm-scale constructed wetland over 28 days. Antibiotic concentrations in plants and effluent were analyzed using an LC-MS/MS to assess the removal rates and phytoremediation capacities. M. aquaticum did not effectively mitigate contamination due to poor tolerance and survival in effluent conditions. S. minima and L. gibba demonstrated superior efficiency, reducing the antibiotic concentrations to undetectable levels within 14 days, while S. montevidensis achieved this result by day 28. Floating macrophytes emerge as the preferable choice for remediation of antibiotics compared to emergent and heterophyllous species. Antibiotics were detected in plant tissues at concentrations ranging from 0.32 to 29.32 ng g-1 fresh weight, highlighting macrophytes' ability to uptake and accumulate these contaminants. Conversely, non-planted systems exhibited a maximum removal rate of 65%, underscoring the persistence of these molecules in natural environments, even after the entire experimental period. Additionally, macrophytes improved effluent quality regardless of species by reducing total soluble solids and phosphate concentrations and mitigating ecotoxicological effects. This study underscores the potential of using macrophytes in wastewater treatment plants to enhance overall efficiency and prevent environmental contamination by antibiotics, thereby mitigating the harmful impact on biota and antibiotic resistance. Selecting appropriate plant species is crucial for successful phytoremediation in constructed wetlands, and actual implementation is essential to validate their effectiveness and practical applicability.

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The escalating global concern of antimicrobial resistance poses a significant challenge to public health. This study delved into the occurrence of resistant bacteria and antimicrobial resistance genes in the waters and sediments of urban rivers and correlated this emergence and the heightened use of antimicrobials during the COVID-19 pandemic. Isolating 45 antimicrobial-resistant bacteria across 11 different species, the study identifies prevalent resistance patterns, with ceftriaxone resistance observed in 18 isolates and ciprofloxacin resistance observed in 13 isolates. The detection of extended-spectrum ß-lactamases, carbapenemases, and acquired quinolone resistance genes in all samples underscores the gravity of the situation. Comparison with a pre-pandemic study conducted in the same rivers in 2019 reveals the emergence of previously undetected new resistant species, and the noteworthy presence of new resistant species and alterations in resistance profiles among existing species. Notably, antimicrobial concentrations in rivers increased during the pandemic, contributing significantly to the scenario of antimicrobial resistance observed in these rivers. We underscore the substantial impact of heightened antimicrobial usage during epidemics, such as COVID-19, on resistance in urban rivers. It provides valuable insights into the complex dynamics of antimicrobial resistance in environmental settings and calls for comprehensive approaches to combat this pressing global health issue, safeguarding both public and environmental health.

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The benefits of physical exercise (PE) on memory consolidation have been well-documented in both healthy and memory-impaired animals. However, the underlying mechanisms through which PE exerts these effects are still unclear. In this study, we aimed to investigate the role of hippocampal protein synthesis in memory modulation by acute PE in rats. After novel object recognition (NOR) training, rats were subjected to a 30-min moderate-intensity acute PE on the treadmill, while control animals did not undergo any procedures. Using anisomycin (ANI) and rapamycin (RAPA), compounds that inhibit protein synthesis through different mechanisms, we manipulated protein synthesis in the CA1 region of the hippocampus to examine its contribution to memory consolidation. Memory was assessed on days 1, 7, and 14 post-training. Our results showed that inhibiting protein synthesis by ANI or RAPA impaired NOR memory consolidation in control animals. However, acute PE prevented this impairment without affecting memory persistence. We also evaluated brain-derived neurotrophic factor (BDNF) levels after acute PE at 0.5h, 2h, and 12h afterward and found no differences in levels compared to animals that did not engage in acute PE or were only habituated to the treadmill. Therefore, our findings suggest that acute PE could serve as a non-pharmacological intervention to enhance memory consolidation and prevent memory loss in conditions associated with hippocampal protein synthesis inhibition. This mechanism appears not to depend on BDNF synthesis in the early hours after exercise.

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Respiratory Syncytial Virus (RSV) is an important cause of respiratory infection in humans. Severe cases are common in children ≤2 years old, immunocompromised individuals, and the elderly. In 2020, RSV infection reduced in Rio Grande do Sul (RS), southern Brazil; however, in 2021 resurgence of RSV was observed. This study analyzed epidemiological and genetic features of RSV infection cases reported in 2021 in RS. Nasopharyngeal samples collected from individuals with respiratory infection negative for SARS-CoV-2, Influenza A and B viruses were assessed for the presence of RSV by real time RT-qPCR. RSV-A and RSV-B genomic sequencing and phylogenetic reconstructions were performed for genotyping and clade characterization. Among 21,035 respiratory samples analyzed, 2,947 were positive for RSV, 947 of which were hospitalized patients. Positive cases were detected year-round, with the highest number in June-July (winter). Children <1 year comprised 56.28% (n = 533) of the hospitalized patients infected with RSV, whereas 14.46% (n = 137) were individuals >60 years. Of a total of 361 deaths, 14.68% (n = 53) were RSV positive, mostly patients >60 years old (73.58%, n = 39). Chronic kidney disease, cardiopathy, Down syndrome and neurological diseases were associated with RSV infection. RSV-A was identified in 58.5% (n = 117/200) of the patients, and RSV-B in 41.5% (n = 83/200). Of 95 RSV genomes recovered from SARI cases, 66 were RSV-A GA.2.3.5 genotype, while 29 were RSV-B GB.5.0.5a genotype. This study provides epidemiological and molecular data on RSV cases in RS during the COVID-19 pandemic and highlights that investigation of different respiratory viruses is essential for decision-making and disease prevention and control measures.

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The SARS-CoV-2 XBB is a group of highly immune-evasive lineages of the Omicron variant of concern that emerged by recombining BA.2-descendent lineages and spread worldwide during 2023. In this study, we combine SARS-CoV-2 genomic data (n = 11,065 sequences) with epidemiological data of severe acute respiratory infection (SARI) cases collected in Brazil between October 2022 and July 2023 to reconstruct the space-time dynamics and epidemiologic impact of XBB dissemination in the country. Our analyses revealed that the introduction and local emergence of lineages carrying convergent mutations within the Spike protein, especially F486P, F456L, and L455F, propelled the spread of XBB* lineages in Brazil. The average relative instantaneous reproduction numbers of XBB* + F486P, XBB* + F486P + F456L, and XBB* + F486P + F456L + L455F lineages in Brazil were estimated to be 1.24, 1.33, and 1.48 higher than that of other co-circulating lineages (mainly BQ.1*/BE*), respectively. Despite such a growth advantage, the dissemination of these XBB* lineages had a reduced impact on Brazil's epidemiological scenario concerning previous Omicron subvariants. The peak number of SARI cases from SARS-CoV-2 during the XBB wave was approximately 90%, 80%, and 70% lower than that observed during the previous BA.1*, BA.5*, and BQ.1* waves, respectively. These findings revealed the emergence of multiple XBB lineages with progressively increasing growth advantage, yet with relatively limited epidemiological impact in Brazil throughout 2023. The XBB* + F486P + F456L + L455F lineages stand out for their heightened transmissibility, warranting close monitoring in the months ahead. IMPORTANCE: Brazil was one the most affected countries by the SARS-CoV-2 pandemic, with more than 700,000 deaths by mid-2023. This study reconstructs the dissemination of the virus in the country in the first half of 2023, a period characterized by the dissemination of descendants of XBB.1, a recombinant of Omicron BA.2 lineages evolved in late 2022. The analysis supports that XBB dissemination was marked by the continuous emergence of indigenous lineages bearing similar mutations in key sites of their Spike protein, a process followed by continuous increments in transmissibility, and without repercussions in the incidence of severe cases. Thus, the results suggest that the epidemiological impact of the spread of a SARS-CoV-2 variant is influenced by an intricate interplay of factors that extend beyond the virus's transmissibility alone. The study also underlines the need for SARS-CoV-2 genomic surveillance that allows the monitoring of its ever-shifting composition.

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BACKGROUND: In hematologic cancers, including leukemia, cells depend on amino acids for rapid growth. Anti-metabolites that prevent their synthesis or promote their degradation are considered potential cancer treatment agents. Amino acid deprivation triggers proliferation inhibition, autophagy, and programmed cell death. L-lysine, an essential amino acid, is required for tumor growth and has been investigated for its potential as a target for cancer treatment. L-lysine α-oxidase, a flavoenzyme that degrades L-lysine, has been studied for its ability to induce apoptosis and prevent cancer cell proliferation. In this study, we describe the use of L-lysine α-oxidase (LO) from the filamentous fungus Trichoderma harzianum for cancer treatment. RESULTS: The study identified and characterized a novel LO from T. harzianum and demonstrated that the recombinant protein (rLO) has potent and selective cytotoxic effects on leukemic cells by triggering the apoptotic cascade through mitochondrial dysfunction. CONCLUSIONS: The results support future translational studies using the recombinant LO as a potential drug for the treatment of leukemia.

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Severe acute respiratory infection (SARI) outbreaks occur annually, with seasonal peaks varying among geographic regions. Case notification is important to prepare healthcare networks for patient attendance and hospitalization. Thus, health managers need adequate resource planning tools for SARI seasons. This study aims to predict SARI outbreaks based on models generated with machine learning using SARI hospitalization notification data. In this study, data from the reporting of SARI hospitalization cases in Brazil from 2013 to 2020 were used, excluding SARI cases caused by COVID-19. These data were prepared to feed a neural network configured to generate predictive models for time series. The neural network was implemented with a pipeline tool. Models were generated for the five Brazilian regions and validated for different years of SARI outbreaks. By using neural networks, it was possible to generate predictive models for SARI peaks, volume of cases per season, and for the beginning of the pre-epidemic period, with good weekly incidence correlation (R2 = 0.97; 95%CI: 0.95-0.98, for the 2019 season in the Southeastern Brazil). The predictive models achieved a good prediction of the volume of reported cases of SARI; accordingly, 9,936 cases were observed in 2019 in Southern Brazil, and the prediction made by the models showed a median of 9,405 (95%CI: 9,105-9,738). The identification of the period of occurrence of a SARI outbreak is possible using predictive models generated with neural networks and algorithms that employ time series.

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This study aimed to assess the sonographic features of abdominal organs in healthy captive Neotropical otters (Lontra longicaudis). The sonograph showed that the urinary bladder was located in the caudal abdomen and its content was uniformly anechoic. The bladder wall had three layers: outer hyperechoic serosa, hypoechoic muscular layer and hyperechoic mucosa. The mean total wall thickness was 0.10 cm. The splenic parenchyma had a homogeneous echotexture with greater echogenicity than that of the left renal cortex and liver. The borders were regular and tapered. Rugal folds were observed in the stomach when undistended. The mean gastric wall thickness was 0.28 cm and five distinct layers were visible. The liver had smooth contours, and division of the hepatic lobes was not precisely visualized. The hepatic parenchyma had a homogeneous echotexture with greater echogenicity as compared to the right kidney and lesser echogenicity than that of the spleen. The gallbladder appeared as an oval or rounded structure in the transverse plane, filled with homogeneous anechogenic content; the wall was thin, regular and hyperechoic, with a mean thickness of 0.09 cm. The kidneys had a lobulated appearance with renicular subunits. The mean total length of the kidneys in longitudinal plane was 6.18 cm for the left and 6.27 cm for the right. Each reniculus was covered by an echogenic capsule, and the medullary region was more hypoechogenic than the cortical region. In conclusion, sonographic features in most of the abdominal organs in Neotropical otters are similar to the ultrasound patterns observed in healthy dogs and cats, except for kidneys with reniculi.

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Abstract: Severe acute respiratory infection (SARI) outbreaks occur annually, with seasonal peaks varying among geographic regions. Case notification is important to prepare healthcare networks for patient attendance and hospitalization. Thus, health managers need adequate resource planning tools for SARI seasons. This study aims to predict SARI outbreaks based on models generated with machine learning using SARI hospitalization notification data. In this study, data from the reporting of SARI hospitalization cases in Brazil from 2013 to 2020 were used, excluding SARI cases caused by COVID-19. These data were prepared to feed a neural network configured to generate predictive models for time series. The neural network was implemented with a pipeline tool. Models were generated for the five Brazilian regions and validated for different years of SARI outbreaks. By using neural networks, it was possible to generate predictive models for SARI peaks, volume of cases per season, and for the beginning of the pre-epidemic period, with good weekly incidence correlation (R2 = 0.97; 95%CI: 0.95-0.98, for the 2019 season in the Southeastern Brazil). The predictive models achieved a good prediction of the volume of reported cases of SARI; accordingly, 9,936 cases were observed in 2019 in Southern Brazil, and the prediction made by the models showed a median of 9,405 (95%CI: 9,105-9,738). The identification of the period of occurrence of a SARI outbreak is possible using predictive models generated with neural networks and algorithms that employ time series.

Resumo: Surtos de síndrome respiratória aguda grave (SRAG) ocorrem anualmente, com picos sazonais variando entre regiões geográficas. A notificação dos casos é importante para preparar as redes de atenção à saúde para o atendimento e internação dos pacientes. Portanto, os gestores de saúde precisam ter ferramentas adequadas de planejamento de recursos para as temporadas de SRAG. Este estudo tem como objetivo prever surtos de SRAG com base em modelos gerados com aprendizado de máquina usando dados de internação por SRAG. Foram incluídos dados sobre casos de hospitalização por SRAG no Brasil de 2013 a 2020, excluindo os casos causados pela COVID-19. Estes dados foram preparados para alimentar uma rede neural configurada para gerar modelos preditivos para séries temporais. A rede neural foi implementada com uma ferramenta de pipeline. Os modelos foram gerados para as cinco regiões brasileiras e validados para diferentes anos de surtos de SRAG. Com o uso de redes neurais, foi possível gerar modelos preditivos para picos de SRAG, volume de casos por temporada e para o início do período pré-epidêmico, com boa correlação de incidência semanal (R2 = 0,97; IC95%: 0,95-0,98, para a temporada de 2019 na Região Sudeste). Os modelos preditivos obtiveram uma boa previsão do volume de casos notificados de SRAG; dessa forma, foram observados 9.936 casos em 2019 na Região Sul, e a previsão feita pelos modelos mostrou uma mediana de 9.405 (IC95%: 9.105-9.738). A identificação do período de ocorrência de um surto de SRAG é possível por meio de modelos preditivos gerados com o uso de redes neurais e algoritmos que aplicam séries temporais.

Resumen: Brotes de síndrome respiratorio agudo grave (SRAG) ocurren todos los años, con picos estacionales que varían entre regiones geográficas. La notificación de los casos es importante para preparar las redes de atención a la salud para el cuidado y hospitalización de los pacientes. Por lo tanto, los gestores de salud deben tener herramientas adecuadas de planificación de recursos para las temporadas de SRAG. Este estudio tiene el objetivo de predecir brotes de SRAG con base en modelos generados con aprendizaje automático utilizando datos de hospitalización por SRAG. Se incluyeron datos sobre casos de hospitalización por SRAG en Brasil desde 2013 hasta 2020, salvo los casos causados por la COVID-19. Se prepararon estos datos para alimentar una red neural configurada para generar modelos predictivos para series temporales. Se implementó la red neural con una herramienta de canalización. Se generaron los modelos para las cinco regiones brasileñas y se validaron para diferentes años de brotes de SRAG. Con el uso de redes neurales, se pudo generar modelos predictivos para los picos de SRAG, el volumen de casos por temporada y para el inicio del periodo pre-epidémico, con una buena correlación de incidencia semanal (R2 = 0,97; IC95%: 0,95-0,98, para la temporada de 2019 en la Región Sudeste). Los modelos predictivos tuvieron una buena predicción del volumen de casos notificados de SRAG; así, se observaron 9.936 casos en 2019 en la Región Sur, y la predicción de los modelos mostró una mediana de 9.405 (IC95%: 9.105-9.738). La identificación del periodo de ocurrencia de un brote de SRAG es posible a través de modelos predictivos generados con el uso de redes neurales y algoritmos que aplican series temporales.

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Abstract: The influenza-like illness (ILI) sentinel surveillance operates in Brazil to identify respiratory viruses of public health relevance circulating in the country and was first implemented in 2000. Recently, the COVID-19 pandemic reinforced the importance of early detection of the circulation of new viruses in Brazil. Therefore, an analysis of the design of the ILI sentinel surveillance is timely. To this end, we simulated a sentinel surveillance network, identifying the municipalities that would be part of the network according to the criteria defined in the design of the ILI sentinel surveillance and, based on data from tested cases of severe acute respiratory illness (SARI) from 2014 to 2019, we drew samples for each sentinel municipality per epidemiological week. The draw was performed 1,000 times, obtaining the median and 95% quantile interval (95%QI) of virus positivity by Federative Unit and epidemiological week. According to the ILI sentinel surveillance design criteria, sentinel units would be in 64 municipalities, distributed mainly in capitals and their metropolitan areas, recommending 690 weekly samples. The design showed good sensitivity (91.65% considering the 95%QI) for qualitatively detecting respiratory viruses, even those with low circulation. However, there was important uncertainty in the quantitative estimate of positivity, reaching at least 20% in 11.34% of estimates. The results presented here aim to assist in evaluating and updating the ILI sentinel surveillance design. Strategies to reduce uncertainty in positivity estimates need to be evaluated, as does the need for greater spatial coverage.

Resumen: La vigilancia centinela de la enfermedad tipo infuenza (ETI) funciona en Brasil para identificar los virus respiratorios de importancia para la salud pública que circulan en el país y comenzó a ser implementada en 2000. Recientemente, la pandemia de COVID-19 ha reforzado la importancia de la detección temprana de la circulación de nuevos virus en el territorio brasileño. Así, se hace oportuno un análisis del diseño de la vigilancia centinela de la ETI. Para ello, simulamos una red centinela identificando los municipios que formarían parte de la red según los criterios definidos en el diseño de la vigilancia centinela de la ETI y, a partir de los datos de casos testados de infección respiratoria aguda grave (IRAG) de 2014 a 2019, se extrajeron muestras para cada municipio centinela por semana epidemiológica. El sorteo se repitió 1.000 veces y se obtuvo la mediana y el intervalo cuantílico del 95% (IC95%) de la positividad por virus, por Unidad Federativa y semana epidemiológica. Según los criterios del diseño de la vigilancia centinela de la ETI, unidades centinelas estarían en 64 municipios, distribuidas principalmente en capitales y zonas metropolitanas de las capitales, preconizando 690 muestras semanales. El diseño presentó una buena sensibilidad (total de 91,65% considerando el IC95%) para la detección cualitativa de los virus respiratorios, incluso los de baja circulación. Sin embargo, hubo una importante incertidumbre en la estimación cuantitativa de la positividad, alcanzando al menos el 20% en el 11,34% de las estimaciones. Los resultados presentados aquí tienen como objetivo ayudar en la evaluación y actualización del diseño de la red centinela. Es necesario evaluar las estrategias para reducir la incertidumbre en las estimaciones de positividad, al igual que la necesidad de una mayor cobertura espacial.

Resumo: A vigilância sentinela de síndrome gripal atua no Brasil identificando os vírus respiratórios de importância para a saúde pública circulantes no país, e começou a ser implementada em 2000. Recentemente, a pandemia de COVID-19 reforçou a importância da detecção precoce de novos vírus em circulação no território brasileiro. Assim, se faz oportuna uma análise do desenho da vigilância sentinela de síndrome gripal. Para tal, simulamos uma rede sentinela, identificando os municípios que fariam parte da rede segundo os critérios definidos no desenho da vigilância sentinela de síndrome gripal, e, a partir dos dados de casos testados de síndrome respiratória aguda grave (SRAG) de 2014 a 2019, sorteamos amostras para cada município sentinela por semana epidemiológica. O sorteio foi repetido mil vezes, obtendo-se a mediana e intervalo quantílico de 95% (IQ95%) da positividade para cada vírus por Unidade Federativa e semana epidemiológica. Segundo os critérios do desenho da vigilância sentinela de síndrome gripal, unidades sentinelas estariam em 64 municípios, distribuídas principalmente em capitais e suas zonas metropolitanas, o que preconizou 690 amostras semanais. O desenho apresentou boa sensibilidade (total de 91,65%, considerando o IQ95%) para a detecção qualitativa dos vírus respiratórios, mesmo os de baixa circulação. Porém, houve importante incerteza na estimativa quantitativa de positividade, chegando a, pelo menos, 20% em 11,34% das estimativas. Os resultados aqui apresentados visam auxiliar a avaliação e a atualização do desenho da rede sentinela. Estratégias para reduzir a incerteza nas estimativas de positividade precisam ser avaliadas, assim como a necessidade de maior cobertura espacial.

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BACKGROUND: Obesity is a multifactorial disease with epigenetic manifestations that increases the prevalence of associated comorbidities such as metabolic syndrome, cardiovascular dysfunction, and major depression disorder. Given the aforementioned, a search for new pharmacological alternatives for the treatment of this disease is necessary. The current study aimed to evaluate the effects of histone deacetylase-3 (HDAC3) inhibition caused by RGFP966 (a benzamide-type HDAC inhibitor selective for HDAC3) administration, in an animal model of obesity induced by high-fat diet (HFD). METHODS: Adult male mice C57BJ/6 were fed with a normal pellet diet (NPD) or HFD for 120 days. The HDAC3 inhibitor (RGFP966; 10 mg/kg; sc) was administered on the 91st to 120th day of the experiment (per 30 days). After the last inhibitor administration, animals were euthanized, blood was collected, and the hippocampus was removed for biochemical determinations. RESULTS: In an overall manner, the administration of RGFP966 protected against changes in body weight gain, glucose, insulin, lipid profile, adipokines, and increase of hippocampal proinflammatory cytokines levels caused by HFD. CONCLUSION: Therefore, HDAC3 inhibition can represent a promising pharmacological target for the treatment of obesity.

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Social media has profound impact on how we experience the world and interact with others. Rapidly advancing technology has created platforms that have become increasingly image-based and emotionally manipulative. Do the new patterns of communication change patients' mental processes? Is free association becoming more imagistic? Contemporary clinical settings invite new perspectives on the intersections between the social and individual realms, patients' modes of expression, and analysts' interpretations.

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Enrofloxacin (Enro) has been widely encountered in natural water sources, and that water is often used for irrigation in crop production systems. Due to its phytotoxicity and accumulation in plant tissues, the presence of Enro in water used for crop irrigation may represent economical and toxicological concerns. Here, we irrigated two ornamental plant species (Zantedeschia rehmannii Engl. and Spathiphyllum wallisii Regel.) with water artificially contaminated with the antimicrobial enrofloxacin (Enro; 0, 5, 10, 100, and 1000 µg L-1) to evaluate its effects on ornamental plant production, as well as its accumulation and distribution among different plant organs (roots, leaves, bulbs, and flower stems), and examined the economic and environmental safety of commercializing plants produced under conditions of pharmaceutical contamination. The presence of Enro in irrigation water was not found to disrupt plant growth (biomass) or flower production. Both species accumulated Enro, with its internal concentrations distributed as the following: roots > leaves > bulbs > flower stems. In addition to plant tolerance, the content of Enro in plant organs indicated that both Z. rehmannii and S. wallisii could be safety produced under Enro-contaminated conditions and would not significantly contribute to contaminant transfer. The high capacity of those plants to accumulate Enro in their tissues, associated with their tolerance to it, indicates them for use in Enro-phytoremediation programs.

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Aversive memory extinction comprises a novel learning that blocks retrieving a previously formed traumatic memory. In this sense, aversive memory extinction is an excellent tool for decreasing fear responses. However, this tool it's not effective in the long term because of original memory spontaneous recovery. Thus, searching for alternative strategies that strengthen extinction learning is essential. In the current study, we evaluated the effects of a novel context (i.e., novelty) exposure on aversive memory extinction enhancement over days and the dopaminergic system requirement. Given the purpose, experiments were conducted using 3-month-old male Wistar rats. Animals were trained in inhibitory avoidance (IA). Twenty-four hours later, rats were submitted to a weak extinction protocol. Still, 30 min before the first extinction session, animals were submitted to an exploration of a novel context for 5 min. After, memory retention and persistence were evaluated 24 h, 3, 7, 14, and 21 days later. The exposition of a novel context caused a decrease in aversive responses in all days analyzed and an increase in dopamine levels in the hippocampus. The intrahippocampal infusion of dopamine in the CA1 area or the stimulation of the ventral tegmental area (VTA) by a glutamatergic agonist (NMDA) showed similar effects of novelty. In contrast, VTA inhibition by a gabaergic agonist (muscimol) impaired the persistence of extinction learning induced by novelty exposition and caused a decrease in hippocampal dopamine levels. In summary, we show that novel context exposure promotes persistent aversive memory extinction, revealing the significant role of the dopaminergic system.

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Aim: To access the metabolic changes caused by a chalcone derivative (LabMol-75) through a proteomic approach. Methods: Proteomic analysis was performed after 9 h of Paracoccidioides brasiliensis yeast (Pb18) cell incubation with the LabMol-75 at MIC. The proteomic findings were validated through in vitro and in silico assays. Results: Exposure to the compound led to the downregulation of proteins associated with glycolysis and gluconeogenesis, ß-oxidation, the citrate cycle and the electron transport chain. Conclusion: LabMol-75 caused an energetic imbalance in the fungus metabolism and deep oxidative stress. Additionally, the in silico molecular docking approach pointed to this molecule as a putative competitive inhibitor of DHPS.

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