Prostaglandin H synthase kinetics in the two-phase aqueous-micellar system

AbstractReaction mixture for PGHS (prostaglandin-H-synthase) is a two-phase system including micellar hydrophobic phase and hydrophilic aqueous phase. Reagents added to the mixture are distributed between phases, thus concentrations of reagents dissolved in phases can differ significantly from their overall contents.Using dynamic light scattering we found that the hydrophobic phase produced by tween-20 consists of micelles, which radius (4–5nm) does not depend on either tween-20 overall content (0.1%–1% v/v) or arachidonic acid (AA) addition (10–1000μM) or PGHS addition (1μM).Tween-20 overall content changing from 0.1% to 2% v/v dramatically affected COX kinetic, but accounting AA distribution between phases allowed us to estimate “true” parameters, independent of the tween-20 overall content and the concentration of another substrate: KMOx equals 9.8μM O2 in the aqueous phase or 0.0074bar in the gaseous phase, KMAA equals 5400μM AA in the phase of tween-20 micelles and 5400/PμM AA in the aqueous phase (P is the distribution ratio for the AA between the aqueous phase and the hydrophobic phase (P≫1000)). This approach allowed to evaluate PS, the distribution ratio for the AA between the hydrophobic phase and the PGHS active center (PS ~310). This coefficient indicates the AA selectivity toward the cyclooxygenase active center

Environmental problems of sustainable development of oil-producing regions of the North

There is a relationship between the economic requirements for the development of oil and gas facilities in the oil-producing regions of the North and the environmental problems of sustainable development. One of the ways to solve this problem is the wider use of underground gas storage facilities both for reducing peak loads in the Unified Gas Supply System by collecting and storing previously flared associated petroleum gas, and for burying a large volume of industrial emissions that are harmful to the environment. We have considered a mathematical model of an automated control system for the creation and operation of underground gas storage in the horizons of a depleted oil and gas condensate field with its subsequent use for disposal of industrial emissions. To ensure the stability of the functioning of objects of accumulation and consumption, it is necessary to calculate the depth of feedback for each component of the component: proportional, integral, differential

Control of a Wind Power Plant with a Synchronous Permanent Magnet Generator and a Magnetic Variator

В настоящее время в мировой литературе начинает получать развитие применение ветроэнергетических установок с магнитной редукцией скорости. Особенности применения данных систем в сочетании с ветроэнергетической установкой позволяет решить вопрос ее сопряжения с электроэнергетической системой. Управляемая гибкая связь между турбиной и генератором дает возможность согласовать управление углом нагрузки синхронного генератора. В данной работе рассматривается разработанный контроллер, обеспечивающий комплексное управление ветровой турбиной с магнитным вариатором с переменным шагом угла заклинения лопасти и переменной скоростью вращения турбины ВЭУ. Перспективным направлением построения ветроэнергетических систем в настоящее время является применение электромагнитных вариаторов в составе ветроэнергетических установок. Исследованию электроэнергетических систем, в составе которых имеются ветроустановки с электромагнитными вариаторами, посвящена данная работа. Вариатор встраивается между ветровой турбиной и генератором вместо механического редуктора. Быстродействующее изменение вращающего момента электромагнитного вариатора позволяет удерживать частоту вращения генератора. Из-за присущей нелинейности ветровой турбины и вариатора был определен набор эксплуатационных и аварийных режимов, затем контроллер проектировался для каждой рабочей точки. Кроме того, аэродинамический момент и эффективная скорость ветра оцениваются онлайн и получается планируемый график переменной для реализации контроллера. Потенциал метода был проверен путем моделирования с помощью MATLAB/SimulinkCurrently, the use of wind power plants with magnetic speed reduction is beginning to develop in the world literature. Features of the application of these systems in combination with a wind power plant allows you to solve the issue of its interface with the electric power system. The controlled flexible connection between the turbine and the generator makes it possible to coordinate the control of the load angle of the synchronous generator. In this paper, we consider a developed controller that provides integrated control of a wind turbine with a magnetic variator with a variable pitch of the blade angle and a variable speed of rotation of the wind turbine. A promising direction for the construction of wind power systems is currently the use of electromagnetic variators as part of wind power plants. This work is devoted to the study of electric power systems that include wind turbines with electromagnetic variators. The variator is built between the wind turbine and the generator, instead of a mechanical gearbox. The high-speed change in the torque of the electromagnetic variator allows you to keep the speed of the generator. Due to the inherent non-linearity of the wind turbine and CVT, a set of operational and emergency modes was defined and then the controller was designed for each operating point. In addition, the aerodynamic torque and effective wind speed are estimated online and a planned variable schedule for the controller implementation is obtained. Was tested by simulating with MATLAB/Simulin

Polymorphisms associated with resistance to infectious diseases in different breeds of pigs of the Belgorod Region of Russia

Using the PCR-RFLP method, we genotyped pigs for the genes GBP1 (mutation c. [10A>G; 11A>G]), FUT1 (mutation G307A) and MUC4(A243G) associated with resistance to infectious diseases. A total of 188 boars of four breeds (Duroc, Large White, Landrace and Yorkshire) from the Belgorod Region of Russian Federation were studied. The highest frequency of favorable genotype AG for the polymorphism GBP1E2, which is resistant to pig respiratory syndrome, was characterized by the Duroc breed (0.38). The highest frequency of Eischerichia coli F18-resistant AA genotype was observed in the Landrace population (0.19). And in terms of resistance to E. coli with fibrium type F4 (K 88), the highest frequency of favorable genotype GG is characterized by the breed Large White (0,23). In general, it can be noted that genetic resistance in the studied boars is observed predominantly only to one infectious disease

A pilot study of implication of machine learning for relapse prediction after allogeneic stem cell transplantation in adults with Ph-positive acute lymphoblastic leukemia

Abstract The posttransplant relapse in Ph-positive ALL increases the risk of death. There is an unmet need for instruments to predict the risk of relapse and plan prophylaxis. In this study, we analyzed posttransplant data by machine learning algorithms. Seventy-four Ph-positive ALL patients with a median age of 30 (range 18–55) years who previously underwent allo-HSCT, were retrospectively enrolled. Ninety-three percent of patients received prophylactic/preemptive TKIs after allo-HSCT. The values of the BCR::ABL1 level at serial assessments and over variables were collected in specified intervals after allo-HSCT. They were used to model relapse risk with several machine-learning approaches. GBM proved superior to the other algorithms and provided a maximal AUC score of 0.91. BCR::ABL1 level before and after allo-HSCT, prediction moment, and chronic GvHD had the highest value in the model. It was shown that after Day + 100, both error rates do not exceed 22%, while before D + 100, the model fails to make accurate predictions. As a result, we determined BCR::ABL1 levels at which the relapse risk remains low. Thus, the current BCR::ABL1 level less than 0.06% in patients with chronic GvHD predicts low risk of relapse. At the same time, patients without chronic GVHD after allo-HSCT should be classified as high risk with any level of BCR::ABL1. GBM model with posttransplant laboratory values of BCR::ABL1 provides a high prediction of relapse after allo-HSCT in the era of TKIs prophylaxis. Validation of this approach is warranted

SARS-CoV-2 vaccination modelling for safe surgery to save lives: Data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population