Production and characterization of new fibrinolytic protease from Mucor subtillissimus UCP 1262 in solid-state fermentation

Fibrinolytic enzymes have received attention regarding their medicinal potential for thrombolytic diseases, a leading cause of morbidity and mortality worldwide. Various natural enzymes purified from animal, plant and microbial sources have been extensively studied. The aim of this work was to produce fibrinolytic protease by solid state fermentation using agro industrial substrates. Rhizopus arrhizus var. arrhizus UCP 1295 and Mucor subtillissimus UCP 1262 filamentous fungi species isolated from soil of Caatinga-PE, Brasil, were used as producer microorganisms. Wheat bran was shown to be the best substrate for the production of the enzyme and by using a 23 full factorial design the main effects and interactions of the quantity of the substrate wheat bran, moisture and temperature on the fibrinolytic enzyme production and protease were evaluated. The best results for fibrinolytic and protease activities, 144.58 U/mL and 48.33 U/mL, respectively, were obtained with Mucor subtillissimus UCP 1262 using as culture medium 3 g wheat bran, 50% moisture at a temperature of 25˚C for 72 hours. The optimum temperature for the produced enzyme was 45˚C and most of its original activity was retained after being subjected to 80˚C for 120 min. The protease activity was enhanced by K+, Ca+ and Mn+; but with Cu+ there was an inhibition. The specificity to chromogenic substrate and the inhibition by PMSF indicates that it is a chymotrypsin-like serine protease. Presented results suggest that this enzyme produced by solid-state fermentation is an interesting alternative as a candidate for thrombolytic therapy

Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil

Cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in Manaus, Brazil, resurged in late 2020 despite previously high levels of infection. Genome sequencing of viruses sampled in Manaus between November 2020 and January 2021 revealed the emergence and circulation of a novel SARS-CoV-2 variant of concern. Lineage P.1 acquired 17 mutations, including a trio in the spike protein (K417T, E484K, and N501Y) associated with increased binding to the human ACE2 (angiotensin-converting enzyme 2) receptor. Molecular clock analysis shows that P.1 emergence occurred around mid-November 2020 and was preceded by a period of faster molecular evolution. Using a two-category dynamical model that integrates genomic and mortality data, we estimate that P.1 may be 1.7- to 2.4-fold more transmissible and that previous (non-P.1) infection provides 54 to 79% of the protection against infection with P.1 that it provides against non-P.1 lineages. Enhanced global genomic surveillance of variants of concern, which may exhibit increased transmissibility and/or immune evasion, is critical to accelerate pandemic responsiveness

Long-term outcomes of the global tuberculosis and COVID-19 co-infection cohort

Background: Longitudinal cohort data of patients with tuberculosis (TB) and coronavirus disease 2019 (COVID-19) are lacking. In our global study, we describe long-term outcomes of patients affected by TB and COVID-19. Methods: We collected data from 174 centres in 31 countries on all patients affected by COVID-19 and TB between 1 March 2020 and 30 September 2022. Patients were followed-up until cure, death or end of cohort time. All patients had TB and COVID-19; for analysis purposes, deaths were attributed to TB, COVID-19 or both. Survival analysis was performed using Cox proportional risk-regression models, and the log-rank test was used to compare survival and mortality attributed to TB, COVID-19 or both. Results: Overall, 788 patients with COVID-19 and TB (active or sequelae) were recruited from 31 countries, and 10.8% (n=85) died during the observation period. Survival was significantly lower among patients whose death was attributed to TB and COVID-19 versus those dying because of either TB or COVID-19 alone (p<0.001). Significant adjusted risk factors for TB mortality were higher age (hazard ratio (HR) 1.05, 95% CI 1.03-1.07), HIV infection (HR 2.29, 95% CI 1.02-5.16) and invasive ventilation (HR 4.28, 95% CI 2.34-7.83). For COVID-19 mortality, the adjusted risks were higher age (HR 1.03, 95% CI 1.02-1.04), male sex (HR 2.21, 95% CI 1.24-3.91), oxygen requirement (HR 7.93, 95% CI 3.44-18.26) and invasive ventilation (HR 2.19, 95% CI 1.36-3.53). Conclusions: In our global cohort, death was the outcome in >10% of patients with TB and COVID-19. A range of demographic and clinical predictors are associated with adverse outcomes

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio