INFLAMMATORY IMMUNOPATHOLOGY OF COVID-19 AND ITS CORRELATION WITH THE SEVERITY OF THE DISEASE / IMUNOPATOLOGIA INFLAMATÓRIA DA COVID-19 E SUA CORRELAÇÃO COM A GRAVIDADE DA DOENÇA

SARS-CoV-2, which caused the coronavirus pandemic in 2019 (COVID-19), is a beta-coronavirus, and its infection in host cells can activate innate and adaptive immune responses through the activation of several pro-inflammatory cytokines. Thus, in this study we established the relationship between the severity and immunopathology of COVID-19 through the main inflammatory cytokines. Results show that tumor necrosis factor alpha (TNF-α), interferon-gamma (IFN-γ) and interleukins (IL), such as IL-6, are stimulated by the activation of T cell subsets, which results in immune-mediated cellular destruction. Several cytokines reduce the immune response and predispose to a pro-inflammatory and auto-reactive state, including IL-1ß, IL-1RA, IL-7, IL-8, IL-9, IL-10, and associated inflammatory markers (LDH, GM-CSF and VEGF). These higher cytokine levels end up favoring tissue damage in multiple systems, including lungs, heart, gastrointestinal, brain, kidneys and other organs. Increasingly, a greater impact of the markers IL-6, ferritin, pro-calcitonin, lactic dehydrogenase, D-dimer and hypoalbuminemia was observed in patients with severe infection of the disease. In general, the data analyzed confirmed that COVID-19 severity is not caused simply by the viral infection, but rather by immune response and aberrant inflammation. In this way, this study allows a contribution to clinical practice, and it shows that it is essential to carry out in-depth studies about the immunopathology of COVID-19, in order to determine the severity markers involved in the pathogenesis of the viral infection.

O SARS-CoV-2, causador da doença coronavírus 2019 (COVID-19), é um beta-coronavírus, e sua infecção nas células do hospedeiro pode ativar respostas imunes inata e adaptativa, por meio da secreção de várias citocinas pró-inflamatórias. Assim, estabelecemos neste estudo a correlação da gravidade e imunopatologia da COVID-19 com as principais citocinas inflamatórias. Resultados mostram que o fator de necrose tumoral alfa (TNF-α), interferon-gama (IFN-γ) e interleucinas (IL), como a IL-6, são estimulados pela ativação de subconjuntos de células T, o que resulta em destruição celular imunomediada. Sendo que, diversas citocinas deprimem a resposta imune sadia, e predispõem a um estado pró-inflamatório e auto-reativo, dentre elas, IL-1ß, IL-1RA, IL-7, IL-8, IL-9, IL-10, e os marcadores inflamatórios associados (LDH, GM-CSF e VEGF). Isso acaba por favorecer danos teciduais em múltiplos sistemas, como no pulmonar, cardíaco, gastrointestinal, cerebral, renal, dentre outros. Acrescenta-se que foi observado um impacto maior dos marcadores IL-6, ferritina, pró-calcitonina, desidrogenase láctica, D-dímero e hipoalbuminemia em pacientes com infecção grave da doença. De forma geral, pela análise de dados, verificou-se que a gravidade da doença COVID-19 parece ser modulada não apenas pela infecção viral, mas também por respostas imunes e inflamatórias aberrantes no hospedeiro. Dessa forma, este estudo permite contribuir para o auxílio da prática clínica, sendo imprescindível a realização de estudos aprofundados acerca da imunopatologia da COVID-19, a fim de que se determine os marcadores de gravidade envolvidos na patogênese da infecção viral.

Xylooligosaccharides: A Bibliometric Analysis and Current Advances of This Bioactive Food Chemical as a Potential Product in Biorefineries' Portfolios.

Xylooligosaccharides (XOS) are nondigestible compounds of great interest for food and pharmaceutical industries due to their beneficial prebiotic, antibacterial, antioxidant, and antitumor properties. The market size of XOS is increasing significantly, which makes its production from lignocellulosic biomass an interesting approach to the valorization of the hemicellulose fraction of biomass, which is currently underused. This review comprehensively discusses XOS production from lignocellulosic biomass, aiming at its application in integrated biorefineries. A bibliometric analysis is carried out highlighting the main players in the field. XOS production yields after different biomass pretreatment methods are critically discussed using Microsoft PowerBI® (2.92.706.0) software, which involves screening important trends for decision-making. Enzymatic hydrolysis and the major XOS purification strategies are also explored. Finally, the integration of XOS production into biorefineries, with special attention to economic and environmental aspects, is assessed, providing important information for the implementation of biorefineries containing XOS in their portfolio.

A comprehensive method for modeling and simulating ion exchange chromatography of complex mixtures.

In recent years, many biological-based products have been developed, representing a significant fraction of income in the pharmaceutical market. Ion exchange chromatography is an important downstream step for the purification of target recombinant proteins present in clarified cell extracts, together with many other unknown impurities. This work develops a robust approach to model and simulate the purification of untagged heterologous proteins, so that the improved conditions to carry out an ion exchange chromatography are identified in a rational basis prior to the real purification run itself. Purification of the pneumococcal surface protein A (PspA4Pro) was used as a case study. This protein is produced by recombinant Escherichia coli and is a candidate for the manufacture of improved pneumococcal vaccines. The developed method combined experimental and computational procedures. Different anion exchange operating conditions were mapped in order to gather a broad range of representative experimental data. The equilibrium dispersive and the steric mass action equations were used to model and simulate the process. A training strategy to fit the model and separately describe the elution profiles of PspA4Pro and other proteins of the cell extract was applied. Based on the simulation results, a reduced ionic strength was applied for PspA4Pro elution, leading to increases of 14.9% and 11.5% for PspA4Pro recovery and purity, respectively, compared to the original elution profile. These results showed the potential of this method, which could be further applied to improve the performance of ion exchange chromatography in the purification of other target proteins under real process conditions.

A comprehensive method for modeling and simulating ion exchange chromatography of complex mixtures

In recent years, many biological-based products have been developed, representing a significant fraction of income in the pharmaceutical market. Ion exchange chromatography is an important downstream step for the purification of target recombinant proteins present in clarified cell extracts, together with many other unknown impurities. This work develops a robust approach to model and simulate the purification of untagged heterologous proteins, so that the improved conditions to carry out an ion exchange chromatography are identified in a rational basis prior to the real purification run itself. Purification of the pneumococcal surface protein A (PspA4Pro) was used as a case study. This protein is produced by recombinant Escherichia coli and is a candidate for the manufacture of improved pneumococcal vaccines. The developed method combined experimental and computational procedures. Different anion exchange operating conditions were mapped in order to gather a broad range of representative experimental data. The equilibrium dispersive and the steric mass action equations were used to model and simulate the process. A training strategy to fit the model and separately describe the elution profiles of PspA4Pro and other proteins of the cell extract was applied. Based on the simulation results, a reduced ionic strength was applied for PspA4Pro elution, leading to increases of 14.9% and 11.5% for PspA4Pro recovery and purity, respectively, compared to the original elution profile. These results showed the potential of this method, which could be further applied to improve the performance of ion exchange chromatography in the purification of other target proteins under real process conditions.

Performance targets defined by retro-techno-economic analysis for the use of soybean protein as saccharification additive in an integrated biorefinery.

The use of additives in the enzymatic saccharification of lignocellulosic biomass can have positive effects, decreasing the unproductive adsorption of cellulases on lignin and reducing the loss of enzyme activity. Soybean protein stands out as a potential lignin-blocking additive, but the economic impact of its use has not previously been investigated. Here, a systematic evaluation was performed of the process conditions, together with a techno-economic analysis, for the use of soybean protein in the saccharification of hydrothermally pretreated sugarcane bagasse in the context of an integrated 1G-2G ethanol biorefinery. Statistical experimental design methodology was firstly applied as a tool to select the process variable solids loading at 15% (w/w) and soybean protein concentration at 12% (w/w), followed by determination of enzyme dosage at 10 FPU/g and hydrolysis time of 24 h. The saccharification of sugarcane bagasse under these conditions enabled an increase of 26% in the amount of glucose released, compared to the control without additive. The retro-techno-economic analysis (RTEA) technique showed that to make the biorefinery economically feasible, some performance targets should be reached experimentally such as increasing biomass conversion to ideally 80% and reducing enzyme loading to 5.6 FPU/g in the presence of low-cost soybean protein.

Aluminum-induced toxicity in Urochloa brizantha genotypes: A first glance into root Al-apoplastic and -symplastic compartmentation, Al-translocation and antioxidant performance.

Previous studies have unraveled contrasting Al genotypic differences between Urochloa brizantha cv. Marandu (moderately tolerant) and Urochloa brizantha cv. Xaraés (more tolerant). Our objective was to evaluate differences in the response to Al-induced stress between these genotypes, focusing on Al compartmentation in the root apoplast and symplast, and antioxidant enzyme activities after Al exposure. Al-accumulation was 25% higher in the roots of cv. Xaraés than cv. Marandu, while in the shoot Al accumulation was 150% higher in cv. Marandu than cv. Xaraés. U. brizantha cv. Marandu accumulated 73% of the Al absorbed in the root symplast and 27% in the root apoplast, while cv. Xaraés accumulated 61% of the Al absorbed in symplast and 39% in apoplast. Furthermore, Al exposure leaded to physiological and developmental changes in root morphology, such as disorganization of vascular system, the collapse of cortical cells and absence of root hairs from the root tip, with more drastic effects detectable in cv. Marandu. Catalase (CAT) and guaiacol peroxidase (GPOX) activities in the roots of cv. Marandu were lower compared to cv. Xaraés. Our results pointed out that higher Al compartmentalization rates in the root apoplast, altogether with up-regulated metabolic activities of CAT and GPOX and also lower long distance transport of Al are seemingly at the base of the Al tolerance in cv. Xaraés. In conclusion, biochemical analysis of roots suggested that understanding of metabolic pathways is one of pressing approach to elucidate stress tolerance mechanisms in this genus.

Modeling and simulation of anion exchange chromatography for purification of proteins in complex mixtures.

Ion exchange chromatography is extensively used in the purification of biological compounds. Reliable mathematical models describing this chromatographic technique are available and can be used to improve the performance of this separation step. However, the use of synthetic mixtures for model development hampers the application of this approach with real cell extracts processed in downstream operations. This work presents an original approach for handling non-synthetic genuine mixtures of proteins, which was applied in the purification of an untagged recombinant pneumococcal surface protein A (PspA4Pro). First, evaluation was made of the efficiency of steric mass action (SMA) and modified Langmuir isotherms, which were separately used together with the equilibrium dispersive model (EDM). The data used for parameter estimation and model validation were obtained from anion exchange chromatography runs (employing Q-Sepharose FF), applied to real cell extracts produced by different cultivation strategies. Simulations showed that the models were able to describe the complex mixtures of unknown proteins. Next, the EDM and SMA approaches were used to separately describe the profile of PspA4Pro and the pool of protein impurities eluted together. The simulations showed that PspA4Pro tended to elute at the beginning of the peak, enabling the establishment of an alternative elution schedule that provided a 34% increase in the purity achieved using the anion exchange chromatography.

Modeling and simulation of anion exchange chromatography for purification of proteins in complex mixtures

Ion exchange chromatography is extensively used in the purification of biological compounds. Reliable mathematical models describing this chromatographic technique are available and can be used to improve the performance of this separation step. However, the use of synthetic mixtures for model development hampers the application of this approach with real cell extracts processed in downstream operations. This work presents an original approach for handling non-synthetic genuine mixtures of proteins, which was applied in the purification of an untagged recombinant pneumococcal surface protein A (PspA4Pro). First, evaluation was made of the efficiency of steric mass action (SMA) and modified Langmuir isotherms, which were separately used together with the equilibrium dispersive model (EDM). The data used for parameter estimation and model validation were obtained from anion exchange chromatography runs (employing Q-Sepharose FF), applied to real cell extracts produced by different cultivation strategies. Simulations showed that the models were able to describe the complex mixtures of unknown proteins. Next, the EDM and SMA approaches were used to separately describe the profile of PspA4Pro and the pool of protein impurities eluted together. The simulations showed that PspA4Pro tended to elute at the beginning of the peak, enabling the establishment of an alternative elution schedule that provided a 34% increase in the purity achieved using the anion exchange chromatography.

Modeling and simulation of anion exchange chromatography for purification of proteins in complex mixtures

Ion exchange chromatography is extensively used in the purification of biological compounds. Reliable mathematical models describing this chromatographic technique are available and can be used to improve the performance of this separation step. However, the use of synthetic mixtures for model development hampers the application of this approach with real cell extracts processed in downstream operations. This work presents an original approach for handling non-synthetic genuine mixtures of proteins, which was applied in the purification of an untagged recombinant pneumococcal surface protein A (PspA4Pro). First, evaluation was made of the efficiency of steric mass action (SMA) and modified Langmuir isotherms, which were separately used together with the equilibrium dispersive model (EDM). The data used for parameter estimation and model validation were obtained from anion exchange chromatography runs (employing Q-Sepharose FF), applied to real cell extracts produced by different cultivation strategies. Simulations showed that the models were able to describe the complex mixtures of unknown proteins. Next, the EDM and SMA approaches were used to separately describe the profile of PspA4Pro and the pool of protein impurities eluted together. The simulations showed that PspA4Pro tended to elute at the beginning of the peak, enabling the establishment of an alternative elution schedule that provided a 34% increase in the purity achieved using the anion exchange chromatography.

Defining research & development process targets through retro-techno-economic analysis: The sugarcane biorefinery case.

A new approach is reported for techno-economic analysis of lignocellulosic ethanol production. With this methodology, general targets for key process variables can be draw, a valuable feedback for Research & Development teams. An integrated first- and second-generation ethanol from sugarcane biorefinery is presented as a case study for the methodology, with the biomass pretreated by liquid hot water, followed by enzymatic hydrolysis of the cellulose fraction. The hemicellulose fraction may be either fermented or biodigested. The methodology was able to identify the main variables that affect the process global economic performance: enzyme load in the cellulose hydrolysis reactor, cellulose-to-glucose, and xylose-to-ethanol yields. Windows of feasible operation are the graphical output of the methodology, outlining regions to be further explored experimentally. One example of quantitative result is that the maximum feasible enzyme load was 11.3 FPU/gcellulose when xylose is fermented to ethanol and 7.7 FPU/gcellulose when xylose is biodigested.

Nickel Availability in Soil as Influenced by Liming and Its Role in Soybean Nitrogen Metabolism.

Nickel (Ni) availability in soil varies as a function of pH. Plants require Ni in small quantities for normal development, especially in legumes due its role in nitrogen (N) metabolism. This study investigated the effect of soil base saturation, and Ni amendments on Ni uptake, N accumulation in the leaves and grains, as well as to evaluate organic acids changes in soybean. In addition, two N assimilation enzymes were assayed: nitrate reductase (NR) and Ni-dependent urease. Soybean plants inoculated with Bradyrhizobium japonicum were cultivated in soil-filled pots under two base-cation saturation (BCS) ratios (50 and 70%) and five Ni rates - 0.0; 0.1; 0.5; 1.0; and 10.0 mg dm(-3) Ni. At flowering (R1 developmental stage), plants for each condition were evaluated for organic acids (oxalic, malonic, succinic, malic, tartaric, fumaric, oxaloacetic, citric and lactic) levels as well as the activities of urease and NR. At the end of the growth period (R7 developmental stage - grain maturity), grain N and Ni accumulations were determined. The available soil-Ni in rhizosphere extracted by DTPA increased with Ni rates, notably in BCS50. The highest concentrations of organic acid and N occurred in BCS70 and 0.5 mg dm(-3) of Ni. There were no significant differences for urease activity taken on plants grown at BSC50 for Ni rates, except for the control treatment, while plants cultivated at soil BCS70 increased the urease activity up to 0.5 mg dm(-3) of Ni. In addition, the highest values for urease activities were reached from the 0.5 mg dm(-3) of Ni rate for both BCS treatments. The NR activity was not affected by any treatment indicating good biological nitrogen fixation (BNF) for all plants. The reddish color of the nodules increased with Ni rates in both BCS50 and 70, also confirms the good BNF due to Ni availability. The optimal development of soybean occurs in BCS70, but requires an extra Ni supply for the production of organic acids and for increased N-shoot and grain accumulation.

Gluconic acid production from sucrose in an airlift reactor using a multi-enzyme system.

Sucrose from sugarcane is produced in abundance in Brazil, which provides an opportunity to manufacture other high-value products. Gluconic acid (GA) can be produced by multi-enzyme conversion of sucrose using the enzymes invertase, glucose oxidase, and catalase. In this process, one of the byproducts is fructose, which has many commercial applications. This work concerns the batch mode production of GA in an airlift reactor fed with sucrose as substrate. Evaluation was made of the influence of temperature and pH, as well as the thermal stability of the enzymes. Operational conditions of 40 °C and pH 6.0 were selected, based on the enzymatic activity profiles and the thermal stabilities. Under these conditions, the experimental data could be accurately described by kinetic models. The maximum yield of GA was achieved within 3.8 h, with total conversion of sucrose and glucose and a volumetric productivity of around 7.0 g L(-1) h(-1).

Modeling the kinetics of complex systems: enzymatic hydrolysis of lignocellulosic substrates.

Lignocellulosic biomass is mainly composed of cellulose, hemicellulose, and lignin. Fuzzy logic, in turn, is a branch of many-valued logic based on the paradigm of inference under vagueness. This paper presents a methodology, based on computational intelligence, for modeling the kinetics of a complex reactional system. The design of a fuzzy interpolator to model cellulose hydrolysis is reported, within the perspective of applying kinetic models in bioreactor engineering. Experimental data for various types of lignocellulosic materials were used to develop the interpolator. New experimental data from the enzymatic hydrolysis of a synthetic substrate, on the other hand, were used to validate the methodology. The accuracy of the results indicates that this is a promising approach to extend the application of models fitted for specific situations to different cases, thus enhancing their generality.

Bioelectricity versus bioethanol from sugarcane bagasse: is it worth being flexible?

BACKGROUND: Sugarcane is the most efficient crop for production of (1G) ethanol. Additionally, sugarcane bagasse can be used to produce (2G) ethanol. However, the manufacture of 2G ethanol in large scale is not a consolidated process yet. Thus, a detailed economic analysis, based on consistent simulations of the process, is worthwhile. Moreover, both ethanol and electric energy markets have been extremely volatile in Brazil, which suggests that a flexible biorefinery, able to switch between 2G ethanol and electric energy production, could be an option to absorb fluctuations in relative prices. Simulations of three cases were run using the software EMSO: production of 1G ethanol + electric energy, of 1G + 2G ethanol and a flexible biorefinery. Bagasse for 2G ethanol was pretreated with a weak acid solution, followed by enzymatic hydrolysis, while 50% of sugarcane trash (mostly leaves) was used as surplus fuel. RESULTS: With maximum diversion of bagasse to 2G ethanol (74% of the total), an increase of 25.8% in ethanol production (reaching 115.2 L/tonne of sugarcane) was achieved. An increase of 21.1% in the current ethanol price would be enough to make all three biorefineries economically viable (11.5% for the 1G + 2G dedicated biorefinery). For 2012 prices, the flexible biorefinery presented a lower Internal Rate of Return (IRR) than the 1G + 2G dedicated biorefinery. The impact of electric energy prices (auction and spot market) and of enzyme costs on the IRR was not as significant as it would be expected. CONCLUSIONS: For current market prices in Brazil, not even production of 1G bioethanol is economically feasible. However, the 1G + 2G dedicated biorefinery is closer to feasibility than the conventional 1G + electric energy industrial plant. Besides, the IRR of the 1G + 2G biorefinery is more sensitive with respect to the price of ethanol, and an increase of 11.5% in this value would be enough to achieve feasibility. The ability of the flexible biorefinery to take advantage of seasonal fluctuations does not make up for its higher investment cost, in the present scenario.