The IIASA-LUC Project Georeferenced Database of the Former U.S.S.R., Volume 4: Vegetation

The IIASA/LUC georeferenced database for the former U.S.S.R. was created within the framework of the project "Modeling Land Use and Land Cover Changes in Europe and Northern Asia" (LUC). For Russia, essential information on relief, soil, vegetation, land cover and use, etc., for routine environmental analysis was lacking when the LUC project started developing the database. In addition, the environmental data on the former U.S.S.R. which were available, occurred in formats (papers, tables, etc.) that in general could not be used with modern information technology, and in particular in model building. In creating the LUC project database, we have established a threefold task: (1) to obtain the relevant information for the LUC project modeling exercises; (2) to develop data which is applicable to modem information technology; (3) to contribute a series of digital databases which could be applied for a number of other specific analyses by the national and international scientific community. In defining the tasks it was agreed to create a set of digital databases which could be handled by geographic information systems (GIS). The full set of georeferenced digital databases was combined into the LUC project's GIS, using ARC/INFO. However, each individual item (physiography, soil, vegetation, etc.) was created as a separate digital database, allowing each item to be used independently, according to users' needs. The complete series of the unique georeferenced digital databases for the territory of the former U.S.S.R. is described in the IIASA/LUC volumes: Volume 1: Physiography (landforms, slope conditions, elevations); Volume 2: Soil; Volume 3: Soil degradation status (Russia); Volume 4: Vegetation; Volume 5: Land categories

The IIASA-LUC Project Georeferenced Database of the former USSR. Volume 3: Soil Degradation Status in Russia

The IIASA/LUC georeferenced database for the former USSR (in part only for Russia), was created within the framework of the project "Modeling of Land Use and Land Cover Changes in Europe and Northern Asia" (LUC). For Russia, essential information on relief, soil, vegetation, land cover and use, etc. for routine environmental analysis was lacking when the LUC project first started developing the database. In addition, the environmental data on the former USSR which was available occurred in formats (papers, tables, etc.) that in general could not be used with modern information technology, and in particular in model building. In creating the LUC project database, we have established a threefold task: (1) to obtain the relevant information for the LUC project modeling exercises; (2) to develop data which is applicable to modern information technology; (3) to contribute a series of digital databases which could be applied for a number of other specific analysis by the national and international scientific community. In defining the tasks it was agreed to create a set of digital databases which could be handled by a geographic information systems (GIS). This required that the data had to be georeferenced. The complete set of georeferenced digital databases was combined into the LUC project's GIS, using ARC/INFO. However, each individual item (physiography, soil, vegetation, etc.) was created as an unique specific digital database, allowing to be used separately, depending on user's needs. The complete series of the unique georeferenced digital databases is described in several IIASA/LUC volumes: Volume 1 -- Physiography (land forms, slope conditions, elevations); Volume 2 -- Soil; Volume 3 -- Soil degradation status (Russia); Volume 4 -- Vegetation; Volume 5 -- Land categories; Volume 6 -- Agricultural regionalization

ГАЗОХРОМАТОГРАФИЧЕСКОЕ ОПРЕДЕЛЕНИЕ АСКАРИДОЛА – ПРОДУКТА ВЗАИМОДЕЙСТВИЯ СИНГЛЕТНОГО КИСЛОРОДА С α-ТЕРПИНЕНОМ

The reaction product of singlet oxygen with α-terpinene, ascaridole, can be used in an indirect gas chromatographic determination of the singlet oxygen mass concentration in the air. However, ascaridole is a thermally unstable compound, which can isomerize due to high temperature exposure during the analysis.Thermal decomposition products of ascaridole were identified by gas chromatography-mass spectrometry: isoascaridole, 1,2-ethoxy-p-menthane-3-one and 3,4-ethoxy-p-menthane-2-one. The discrepancy between obtained mass spectrum of ascaridole and mass spectra shown in NIST databases was found. The dependence of ascaridole signal intensity from temperature of injector and detector and from column conditioning was established. These conditions were investigated and optimized.Key words: ascaridole, singlet oxygen, gas chromatography, gas chromatography-mass spectrometry(Russian)DOI: http://dx.doi.org/10.15826/analitika.2013.17.4.009A.S. Ovechkin1,2, M.D. Reyngeverts2, L.A. Kartsova11St. Petersburg State University, Petergof, St. Petersburg, Russian Federation2FSUE «RSC «Applied Chemistry», St. Petersburg, Russian FederationПродукт взаимодействия синглетного кислорода с α-терпиненом, аскаридол, может быть использован при косвенном газохроматографическом определении массовой концентрации синглетного кислорода в воздухе. Однако аскаридол – термически нестабильное соединение, способное изомеризоваться под действием температуры в ходе анализа.Методом хромато-масс-спектрометрии идентифицированы продукты термического разложения аскаридола: изоаскаридол, 1,2-этокси-п-ментан-3-он и 3,4-этокси-п-ментан-2-он. Установлено несоответствие масс-спектра аскаридола, полученного в настоящей работе, масс-спектрам, приведенным в базах данных NIST. Исследованы и оптимизированы условия газохроматографического определения аскаридола: температуры испарителя и детектора, необходимость кондиционирования хроматографической колонки и параметры его проведения.Ключевые слова:аскаридол, синглетный кислород, газовая хроматография, хромато-масс-спектрометрияDOI: http://dx.doi.org/10.15826/analitika.2013.17.4.00

Prolonged repolarization in the early phase of ischemia is associated with ventricular fibrillation development in a porcine model

Background: Repolarization prolongation can be the earliest electrophysiological change in ischemia, but its role in arrhythmogenesis is unclear. The aim of the present study was to evaluate the early ischemic action potential duration (APD) prolongation concerning its causes, expression in ECG and association with early ischemic ventricular fibrillation (phase 1A VF).Methods: Coronary occlusion was induced in 18 anesthetized pigs, and standard 12 lead ECG along with epicardial electrograms were recorded. Local activation time (AT), end of repolarization time (RT), and activation-repolarization interval (ARIc) were determined as dV/dt minimum during QRS-complex, dV/dt maximum during T-wave, and rate-corrected RT–AT differences, respectively. Patch-clamp studies were done in enzymatically isolated porcine cardiomyocytes. IK(ATP) activation and Ito1 inhibition were tested as possible causes of the APD change.Results: During the initial period of ischemia, a total of 11 pigs demonstrated maximal ARIc prolongation >10 ms at 1 and/or 2.5 min of occlusion (8 and 6 cases at 1 and 2.5 min, respectively) followed by typical ischemic ARIc shortening. The maximal ARIc across all leads was associated with VF development (OR 1.024 95% CI 1.003–1.046, p = 0.025) and maximal rate-corrected QT interval (QTc) (B 0.562 95% CI 0.346–0.775, p < 0.001) in logistic and linear regression analyses, respectively. Phase 1A VF incidence was associated with maximal QTc at the 2.5 min of occlusion in ROC curve analysis (AUC 0.867, p = 0.028) with optimal cut-off 456 ms (sensitivity 1.00, specificity 0.778). The pigs having maximal QTc at 2.5 min more and less than 450 ms significantly differed in phase 1A VF incidence in Kaplan-Meier analysis (log-rank p = 0.007). In the patch-clamp experiments, 4-aminopyridine did not produce any effects on the APD; however, pinacidil activated IK(ATP) and caused a biphasic change in the APD with initial prolongation and subsequent shortening.Conclusion: The transiently prolonged repolarization during the initial period of acute ischemia was expressed in the prolongation of the maximal QTc interval in the body surface ECG and was associated with phase 1A VF. IK(ATP) activation in the isolated cardiomyocytes reproduced the biphasic repolarization dynamics observed in vivo, which suggests the probable role of IK(ATP) in early ischemic arrhythmogenesis

Опредеение дальности распознавания объектов тепловизором с микроболометрической матрицей

Запропоновано нову методику визначення максимальної дальності розпізнавання (MRR), заснована на NIIRS. Проведено розрахунок за викладеною методикою та зпівставлено з результатами, отриманими за іншими найбільш розповсюдженими методиками.The new method of determining of the maximal range of recognition (MRR) based on the NIIRS is proposed. The calculation of MRR by the proposed method have been done and was compared with the MRR which were calculated by other most overspread methods.Предложена новая методика определения максимальной дальности распознавания (MRR), основанная на NIIRS. Проведен расчет по представленной методике и результат сопоставлен с результатами, полученными по другим наиболее распространенным методикам

Risk Factors of Severe Disease and Methods for Clinical Outcome Prediction in Patients with COVID-19 (Review)

Large population studies using statistical analysis and mathematical computer modeling could be an effective tool in studying COVID-19. The use of prognostic scales developed using correlation of changes in clinical and laboratory parameters and morphological data, can help in early prediction of disease progression and identification of patients with high risk of unfavorable outcome.Aim of the review. To assess the risk factors for severe course and unfavorable outcome of COVID-19 and to evaluate the existing tools for predicting the course and outcome of the novel coronavirus infection. PubMed, Medline, and Google Scholar were searched for the relevant sources. This review contains information on existing tools for assessing the prognosis and outcome of the disease, along with the brief data on the etiology, pathogenesis of the novel coronavirus infection and the known epidemiological, clinical and laboratory factors affecting its course.Conclusion. It is essential to develop predictive models tailored to specific settings and capable of continuous monitoring of the situation and making the necessary adjustments. The discovery of new and more sensitive early markers and developing marker-based predictive assessment tools could significantly impact improving the outcomes of COVID-19

Факторы риска и методы прогнозирования клинического исхода COVID-19 (обзор)

Large population studies using statistical analysis and mathematical computer modeling could be an effective tool in studying COVID-19. The use of prognostic scales developed using correlation of changes in clinical and laboratory parameters and morphological data, can help in early prediction of disease progression and identification of patients with high risk of unfavorable outcome.Aim of the review. To assess the risk factors for severe course and unfavorable outcome of COVID-19 and to evaluate the existing tools for predicting the course and outcome of the novel coronavirus infection. PubMed, Medline, and Google Scholar were searched for the relevant sources. This review contains information on existing tools for assessing the prognosis and outcome of the disease, along with the brief data on the etiology, pathogenesis of the novel coronavirus infection and the known epidemiological, clinical and laboratory factors affecting its course.Conclusion. It is essential to develop predictive models tailored to specific settings and capable of continuous monitoring of the situation and making the necessary adjustments. The discovery of new and more sensitive early markers and developing marker-based predictive assessment tools could significantly impact improving the outcomes of COVID-19.Одним из эффективных инструментов изучения COVID-19 является исследование больших популяций пациентов и выделение факторов, влияющих на течение и прогноз, с помощью различных методов статистического анализа и математического компьютерного моделирования. Применение прогностических шкал, разработанных на основании сопоставления динамики клинических и лабораторных показателей с морфологическими данными, может помочь в своевременной оценке возможных вариантов течения заболевания и выделении больных группы высокого риска неблагоприятного исхода.Цель обзора. Оценить факторы риска тяжелого течения и неблагоприятного исхода COVID-19, существующие инструменты прогнозирования течения и исхода новой короновирусной инфекции. Поиск источников осуществляли в базах данных PubMed, Medline, Google Scholar. Данный литературный обзор наряду с краткими данными об этиологии, патогенезе COVID-19 и об известных эпидемиологических, клинических и лабораторных факторах, влияющих на ее течение, содержит информацию о существующих инструментах оценки прогноза течения и исхода заболевания.Заключение. Необходима разработка прогностических моделей, созданных под конкретные условия с возможностью постоянного мониторинга ситуации и внесения корректировок при необходимости. Обнаружение новых более чувствительных на ранних этапах заболевания маркеров и разработка на их основе инструментов оценки прогноза могло бы значительно улучшить исходы COVID-19

Addressing Neurosurgery Research and Data Access Gaps in War-Inflicted Nations

For decades, neurosurgical research in war-torn countries has been subpar, owing to a plethora of factors that limit data accessibility and quality research. These countries are frequently affected by ongoing conflicts, which divert resources away from effective health care and research outcomes. Furthermore, they lack adequate institutes of higher education, where clinical and research excellence paves the epicenter of research institutions, trained personnel, and infrastructure, making high-quality research difficult