Association of polymorphisms in long pentraxin 3 and its plasma levels with COVID-19 severity.

COVID-19 is an infectious respiratory disease caused by SARS-CoV-2. Pentraxin 3 (PTX3) is involved in the activation and regulation of the complement system, demonstrating an important role in the pathogenesis of COVID-19. The aim was to evaluate the association of single nucleotide polymorphisms in PTX3 and its plasma levels with the severity of COVID-19. This is a retrospective cohort study, carried out between August 2020 and July 2021, including patients with confirmed COVID-19 hospitalized in 2 hospitals in the Northeast Region of Brazil. Polymorphisms in PTX3 (rs1840680 and rs2305619) were determined by real-time PCR. PTX3 plasma levels were measured by ELISA. Serum levels of interleukin (IL)-6, IL-8, and IL-10 were determined by flow cytometry. A multivariate logistic regression model was used to identify parameters independently associated with COVID-19 severity. P values < 0.05 were considered significant. The study included 496 patients, classified as moderate (n = 267) and severe (n = 229) cases. The PTX3 AA genotype (rs1840680) was independently associated with protection against severe COVID-19 (P = 0.037; odds ratio = 0.555). PTX3 plasma levels were significantly associated with COVID-19 severity and mortality (P < 0.05). PTX3 levels were significantly correlated with IL-6, IL-8, IL-10, C-reactive protein, total leukocytes, neutrophil-to-lymphocyte ratio, urea, creatinine, ferritin, length of hospital stay, and higher respiratory rate (P < 0.05). Our results revealed a protective effect of the PTX3 AA genotype (rs1840680) on the development of severe forms of COVID-19. Additionally, PTX3 plasma levels were associated with the severity of COVID-19. The results of this study provide evidence of an important role of PTX3 in the immunopathology of COVID-19.

Clinical characteristics and laboratory parameters associated with the risk of severe COVID-19 in patients from two hospitals in Northeast Brazil.

BACKGROUND: Although most coronavirus disease 2019 (COVID-19) infections are mild, some patients have severe clinical conditions requiring hospitalization. Data on the severity of COVID-19 in Brazil are scarce and are limited to public databases. This study aimed to investigate the clinical and laboratory factors associated with the severity of COVID-19 in a cohort of hospitalized adults from two hospitals in Northeast Brazil. METHODS: Patients over 18 years of age who were hospitalized between August 2020 and July 2021 with a confirmed diagnosis of COVID-19 were included. The patients were classified into two groups: moderate and severe. Clinical, laboratory and imaging parameters were collected and compared between the groups. A multivariate logistic regression model was used to determine the predictors of COVID-19 severity. RESULTS: This study included 495 patients (253 moderate and 242 severe). A total of 372 patients (75.2%) were between 18 and 65 years of age, and the majority were male (60.6%; n = 300). Patients with severe disease had higher levels of leukocytes, neutrophils, platelets, neutrophil-to-lymphocyte ratio, monocyte-to-lymphocyte ratio, blood glucose, C-reactive protein, ferritin, D-dimer, aspartate aminotransferase, creatinine, and urea (p < 0.05). In multivariate logistic regression, the following variables were significant predictors of COVID-19 severity: leukocytes (odds ratio [OR] 3.27; 95% confidence interval [CI] 2.12-5.06), international normalized ratio (INR) (OR 0.22, 95% CI 0.14-0.33), and urea (OR 4.03; 95% CI 2.21-7.35). CONCLUSIONS: The present study identified the clinical and laboratory factors associated with the severity of COVID-19 in hospitalized Brazilian individuals.

In-Hospital Mortality from Cardiovascular Diseases in Brazil during the First Year of The COVID-19 Pandemic. / Excesso de Mortalidade Hospitalar por Doenças Cardiovasculares no Brasil Durante o Primeiro Ano da Pandemia de COVID-19.

BACKGROUND: The COVID-19 pandemic has had an impact on mortality from several diseases worldwide, especially cardiovascular diseases (CVD). Brazil is a continent-sized country with significant differences in the health care structure between its federative units. OBJECTIVE: Analyze in-hospital mortality from CVDs in the Brazilian public health system during the first year of the COVID-19 pandemic (2020). METHODS: This is an ecological study analyzing the absolute number of in-hospital deaths and the rate of in-hospital mortality in Brazil, its macro-regions, and federative units. Data were obtained from the Hospital Information System of the Brazilian Ministry of Health. To analyze excess mortality, the P-score was used. It compares the events observed with those expected for a given place and period. The P-score was corrected by the joinpoint regression model, with a 95% confidence interval and 5% significance level. RESULTS: There were 93,104 in-hospital deaths due to CVD in Brazil in 2020, representing 1,495 fewer deaths (P score: -1.58) than expected. The central-west region had a positive P-score, with a 15.1% increase in the number of deaths. Ten federative units showed a greater number of deaths in 2020. There was also a 13.3% excess in-hospital mortality at the country level, and an excess in-hospital mortality in all macro-regions. CONCLUSIONS: There was a decrease in the absolute number of in-hospital deaths, as well as an increase in in-hospital mortality from CVD in Brazil, in 2020, after the COVID-19 pandemic onset.

FUNDAMENTO: A pandemia da COVID-19 tem causado um impacto sobre a mortalidade por várias doenças em todo o mundo, especialmente por doenças cardiovasculares (DCVs). O Brasil é um país de dimensões continentais com diferenças significativas na estrutura de saúde entre seus estados. OBJETIVO: Analisar a mortalidade hospitalar por DCV no sistema público de saúde durante o primeiro ano da pandemia por COVID-19 (2020) no Brasil. MÉTODOS: Este é um estudo ecológico analisando o número absoluto de mortes hospitalares e a taxa de mortalidade hospitalar no Brasil, suas macrorregiões, e unidades federativas. Os dados foram obtidos do Sistema de Informações Hospitalares (SIH) do Ministério da Saúde. O P-escore foi usado para analisar o excesso de mortalidade. O escore compara os eventos observados com os eventos esperados para um dado local e período. O escore-P foi corrigido por um modelo de regressão joinpoint, com um intervalo de confiança de 95% e nível de significância de 5%. RESULTADOS: Houve 93.104 óbitos hospitalares por DCV no Brasil em 2020, o que representa 1495 menos óbitos (escore-P: -1,58) que o esperado. A região centro-oeste apresentou um escore-P positivo, com um aumento de 15,1% no número de mortes. Dez estados apresentaram um maior número de óbitos em 2020. Ainda, observou-se um excesso de 13,3% de mortalidade hospitalar no país como um todo, e um excesso de mortalidade hospitalar em todas as macrorregiões. CONCLUSÕES: Houve uma diminuição no número absoluto de óbitos hospitalares, bem como um aumento na taxa de mortalidade por DCV no Brasil em 2020, após o início da pandemia por COVID-19.

Excesso de Mortalidade Hospitalar por Doenças Cardiovasculares no Brasil Durante o Primeiro Ano da Pandemia de COVID-19 / In-Hospital Mortality from Cardiovascular Diseases in Brazil during the First Year of The COVID-19 Pandemic

Resumo Fundamento: A pandemia da COVID-19 tem causado um impacto sobre a mortalidade por várias doenças em todo o mundo, especialmente por doenças cardiovasculares (DCVs). O Brasil é um país de dimensões continentais com diferenças significativas na estrutura de saúde entre seus estados. Objetivo: Analisar a mortalidade hospitalar por DCV no sistema público de saúde durante o primeiro ano da pandemia por COVID-19 (2020) no Brasil. Métodos: Este é um estudo ecológico analisando o número absoluto de mortes hospitalares e a taxa de mortalidade hospitalar no Brasil, suas macrorregiões, e unidades federativas. Os dados foram obtidos do Sistema de Informações Hospitalares (SIH) do Ministério da Saúde. O P-escore foi usado para analisar o excesso de mortalidade. O escore compara os eventos observados com os eventos esperados para um dado local e período. O escore-P foi corrigido por um modelo de regressão joinpoint, com um intervalo de confiança de 95% e nível de significância de 5%. Resultados: Houve 93.104 óbitos hospitalares por DCV no Brasil em 2020, o que representa 1495 menos óbitos (escore-P: -1,58) que o esperado. A região centro-oeste apresentou um escore-P positivo, com um aumento de 15,1% no número de mortes. Dez estados apresentaram um maior número de óbitos em 2020. Ainda, observou-se um excesso de 13,3% de mortalidade hospitalar no país como um todo, e um excesso de mortalidade hospitalar em todas as macrorregiões. Conclusões: Houve uma diminuição no número absoluto de óbitos hospitalares, bem como um aumento na taxa de mortalidade por DCV no Brasil em 2020, após o início da pandemia por COVID-19.

Abstract Background: The COVID-19 pandemic has had an impact on mortality from several diseases worldwide, especially cardiovascular diseases (CVD). Brazil is a continent-sized country with significant differences in the health care structure between its federative units. Objective: Analyze in-hospital mortality from CVDs in the Brazilian public health system during the first year of the COVID-19 pandemic (2020). Methods: This is an ecological study analyzing the absolute number of in-hospital deaths and the rate of in-hospital mortality in Brazil, its macro-regions, and federative units. Data were obtained from the Hospital Information System of the Brazilian Ministry of Health. To analyze excess mortality, the P-score was used. It compares the events observed with those expected for a given place and period. The P-score was corrected by the joinpoint regression model, with a 95% confidence interval and 5% significance level. Results: There were 93,104 in-hospital deaths due to CVD in Brazil in 2020, representing 1,495 fewer deaths (P score: −1.58) than expected. The central-west region had a positive P-score, with a 15.1% increase in the number of deaths. Ten federative units showed a greater number of deaths in 2020. There was also a 13.3% excess in-hospital mortality at the country level, and an excess in-hospital mortality in all macro-regions. Conclusions: There was a decrease in the absolute number of in-hospital deaths, as well as an increase in in-hospital mortality from CVD in Brazil, in 2020, after the COVID-19 pandemic onset.

Clinical characteristics and laboratory parameters associated with the risk of severe COVID-19 in patients from two hospitals in Northeast Brazil

ABSTRACT Background: Although most coronavirus disease 2019 (COVID-19) infections are mild, some patients have severe clinical conditions requiring hospitalization. Data on the severity of COVID-19 in Brazil are scarce and are limited to public databases. This study aimed to investigate the clinical and laboratory factors associated with the severity of COVID-19 in a cohort of hospitalized adults from two hospitals in Northeast Brazil. Methods: Patients over 18 years of age who were hospitalized between August 2020 and July 2021 with a confirmed diagnosis of COVID-19 were included. The patients were classified into two groups: moderate and severe. Clinical, laboratory and imaging parameters were collected and compared between the groups. A multivariate logistic regression model was used to determine the predictors of COVID-19 severity. Results: This study included 495 patients (253 moderate and 242 severe). A total of 372 patients (75.2%) were between 18 and 65 years of age, and the majority were male (60.6%; n = 300). Patients with severe disease had higher levels of leukocytes, neutrophils, platelets, neutrophil-to-lymphocyte ratio, monocyte-to-lymphocyte ratio, blood glucose, C-reactive protein, ferritin, D-dimer, aspartate aminotransferase, creatinine, and urea (p < 0.05). In multivariate logistic regression, the following variables were significant predictors of COVID-19 severity: leukocytes (odds ratio [OR] 3.27; 95% confidence interval [CI] 2.12-5.06), international normalized ratio (INR) (OR 0.22, 95% CI 0.14-0.33), and urea (OR 4.03; 95% CI 2.21-7.35). Conclusions: The present study identified the clinical and laboratory factors associated with the severity of COVID-19 in hospitalized Brazilian individuals.

Antinociceptive and anti-inflammatory effects of hydrazone derivatives and their possible mechanism of action in mice.

Pain and inflammation are unpleasant experiences that usually occur as a result of tissue damage. Despite the number of existing analgesic drugs, side effects limit their use, stimulating the search for new therapeutic agents. In this sense, five hydrazone derivatives (H1, H2, H3, H4, and H5), with general structure R1R2C = NNR3R4, were synthesized with molecular modification strategies. In this paper, we describe the ability of hydrazone derivatives to attenuate nociceptive behavior and the inflammatory response in mice. Antinociceptive activity was evaluated through acetic acid-induced writhing and formalin-induced nociception tests. In both experimental models, the hydrazone with the greatest potency (H5) significantly (p < 0.05) reduced nociceptive behavior. Additionally, methods of acute and chronic inflammation induced by different chemicals (carrageenan and histamine) were performed to evaluate the anti-inflammatory effect of H5. Moreover, molecular docking analysis revealed that H5 can block the COX-2 enzyme, reducing arachidonic acid metabolism and consequently decreasing the production of prostaglandins, which are important inflammatory mediators. H5 also changes locomotor activity. In summary, H5 exhibited relevant antinociceptive and anti-inflammatory potential and acted on several targets, making it a candidate for a new multi-target oral anti-inflammatory drug.

Influence of light intensity, fertilizing and season on the cirsiliol content, a chemical marker of Leonotis nepetifolia (Lamiaceae).

BACKGROUND: Leonotis nepetifolia (Family Lamiaceae) is a medicinal plant from which the flavonoid cirsiliol with sedative, hypnotic, anti-inflammatory and cytotoxic activity has been extracted. METHODS: Seedlings were cultivated under different levels of shade in native or fertilized modes. The content of cirsiliol was measured monthly by high-performance liquid chromatography and the total phenolic content by the Folin-Ciocalteu method. Monitoring of growth was carried out with the weekly measurement of height until the stabilization of growth. RESULTS: The application of fertilizing and/or shading does not alter significantly the cirsiliol content. However, this content varies throughout the year, reaching the peak production in the summer, independently of the treatment applied. This same profile, with production in the summer, was also verified for phenolic compounds, reaching 58.15 ± 9.35 mg of equivalents of gallic acid per g of extract in the summer, content 1.84 times greater than the content verified in winter (31.56 ± 4.09 mg of gallic acid/g of extract). Although shading and fertilizing had no effect on cirsiliol content, the results also showed a positive influence on the height and biomass of the plant, which can causes a higher yield of extractable material. DISCUSSION: Biotic and abiotic stresses are able to increase or decrease the production of secondary metabolites, including phenolic compounds in medicinal plants and, as the stress response is peculiar to each species, cultivation studies become necessary. The present study reports by the first time the influence of shading, fertilizing and seasons in cirsiliol content in L. nepetifolia. Among analyzed variables, the seasons showed a larger influence in expression of cirsiliol and among seasons, our results showed that the summer is the ideal season for collections. In summer, the photoperiod is larger than in other seasons of the year and due to that, the plants need greater protection against the long photoperiod. For this, the plants increase the production of phenolic compounds as observed in this study. Although they do not influence the production of cirsiliol, the shading and nutrients in soil favor growth and leaf area of several plants, explaining, thus, the higher height and biomass obtained.