Вычисление истинного уровня значимости предикторов при проведении процедуры спецификации уравнения регрессии

The paper is devoted to a new randomization method that yields unbiased adjustments of p-values for linear regression models predictors by incorporating the number of potential explanatory variables, their variance-covariance matrix and its uncertainty, based on the number of observations. This adjustment helps to control type I errors in scientific studies, significantly decreasing the number of publications that report false relations to be authentic ones. Comparative analysis with such existing methods as Bonferroni correction and Shehata and White adjustments explicitly shows their imperfections, especially in case when the number of observations and the number of potential explanatory variables are approximately equal. Also during the comparative analysis it was shown that when the variance-covariance matrix of a set of potential predictors is diagonal, i.e. the data are independent, the proposed simple correction is the best and easiest way to implement the method to obtain unbiased corrections of traditional p-values. However, in the case of the presence of strongly correlated data, a simple correction overestimates the true pvalues, which can lead to type II errors. It was also found that the corrected p-values depend on the number of observations, the number of potential explanatory variables and the sample variance-covariance matrix. For example, if there are only two potential explanatory variables competing for one position in the regression model, then if they are weakly correlated, the corrected p-value will be lower than when the number of observations is smaller and vice versa; if the data are highly correlated, the case with a larger number of observations will show a lower corrected p-value. With increasing correlation, all corrections, regardless of the number of observations, tend to the original p-value. This phenomenon is easy to explain: as correlation coefficient tends to one, two variables almost linearly depend on each other, and in case if one of them is significant, the other will almost certainly show the same significance. On the other hand, if the sample variance-covariance matrix tends to be diagonal and the number of observations tends to infinity, the proposed numerical method will return corrections close to the simple correction. In the case when the number of observations is much greater than the number of potential predictors, then the Shehata and White corrections give approximately the same corrections with the proposed numerical method. However, in much more common cases, when the number of observations is comparable to the number of potential predictors, the existing methods demonstrate significant inaccuracies. When the number of potential predictors is greater than the available number of observations, it seems impossible to calculate the true p-values. Therefore, it is recommended not to consider such datasets when constructing regression models, since only the fulfillment of the above condition ensures calculation of unbiased p-value corrections. The proposed method is easy to program and can be integrated into any statistical software package.Данная научная работа посвящена новому численному методу, вычисляющему несмещенные оценки p-значений для предикторов линейных регрессионных моделей с учетом числа потенциальных объясняющих переменных, их дисперсионно-ковариационной матрицы и степени ее неопределенности, основанной на числе рассматриваемых наблюдений. Такая поправка помогает ограничивать число ошибок 1-ого рода в научных исследованиях, значительно понижая число публикаций, декларирующих ложные зависимости в качестве истинных. Сравнительный анализ с такими существующими методами как поправка Бонферрони и поправка Шехата и Уайта явным образом демонстрирует их недостатки, особенно в случае, когда число потенциальных предикторов сравнимо с числом наблюдений. Также в процессе проведения сравнительного анализа было показано, что когда дисперсионно-ковариационная матрица набора потенциальных предикторов является диагональной, т.е. данные независимы, предложенная простая поправка является лучшим и самым легким в реализации методом для получения несмещенных корректировок традиционных p-значений. Однако, в случае присутствия сильно коррелированных данных простая поправка переоценивает истинные p-значения, что может приводить к ошибкам 2-ого рода. Также было выявлено, что исправленные p-значения зависят от числа наблюдений, числа потенциальных объясняющих переменных и выборочной дисперсионно-ковариационной матрицы. Например, если имеется только две потенциальных объясняющих переменных, конкурирующие за одну позицию в регрессионной модели, тогда, если они слабо коррелированы, исправленное p-значение будет ниже, чем в случае когда число наблюдений меньше и наоборот; если данные сильно коррелированы, случай с большим числом наблюдений будет показывать более низкое исправленное p-значение. С увеличением корреляции все поправки независимо от числа наблюдений стремятся к исходному p-значению. Данный феномен легко объяснить: с приближением коэффициента корреляции к единице две переменных практически линейно зависят друг от друга и в случае, если одна из них является значимой, то и другая почти наверняка будет демонстрировать такую же значимость. С другой стороны, если выборочная дисперсионно-ковариационная матрица стремится к диагональной и число наблюдений стремится к бесконечности, то предложенный численный метод будет возвращать поправки, близкие к простой поправке. В случае, когда число наблюдений много больше числа потенциальных предикторов, тогда поправка Шехата и Уайта дают примерно одинаковые поправки с предложенным численным методом. Однако, в намного более распространенных случаях, когда число наблюдений сравнимо с числом потенциальных предикторов, существующие методы демонстрируют достаточно значительные неточности. Когда число потенциальных предикторов больше доступного числа наблюдений, представляется невозможным рассчитать истинные p-значения. Вследствие этого рекомендуется не рассматривать такие наборы данных при построении регрессионных моделей, поскольку только выполнение вышеупомянутого условия обеспечивает расчет несмещенных корректировок p-значения. Предлагаемый метод полностью алгоритмизирован и может быть внедрен в любой пакет статистического анализа данных

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km² resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e., offset) between in-situ soil temperature measurements, based on time series from over 1200 1-km² pixels (summarized from 8500 unique temperature sensors) across all the world’s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in-situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world\u27s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Albiglutide and cardiovascular outcomes in patients with type 2 diabetes and cardiovascular disease (Harmony Outcomes): a double-blind, randomised placebo-controlled trial

Background: Glucagon-like peptide 1 receptor agonists differ in chemical structure, duration of action, and in their effects on clinical outcomes. The cardiovascular effects of once-weekly albiglutide in type 2 diabetes are unknown. We aimed to determine the safety and efficacy of albiglutide in preventing cardiovascular death, myocardial infarction, or stroke. Methods: We did a double-blind, randomised, placebo-controlled trial in 610 sites across 28 countries. We randomly assigned patients aged 40 years and older with type 2 diabetes and cardiovascular disease (at a 1:1 ratio) to groups that either received a subcutaneous injection of albiglutide (30–50 mg, based on glycaemic response and tolerability) or of a matched volume of placebo once a week, in addition to their standard care. Investigators used an interactive voice or web response system to obtain treatment assignment, and patients and all study investigators were masked to their treatment allocation. We hypothesised that albiglutide would be non-inferior to placebo for the primary outcome of the first occurrence of cardiovascular death, myocardial infarction, or stroke, which was assessed in the intention-to-treat population. If non-inferiority was confirmed by an upper limit of the 95% CI for a hazard ratio of less than 1·30, closed testing for superiority was prespecified. This study is registered with ClinicalTrials.gov, number NCT02465515. Findings: Patients were screened between July 1, 2015, and Nov 24, 2016. 10 793 patients were screened and 9463 participants were enrolled and randomly assigned to groups: 4731 patients were assigned to receive albiglutide and 4732 patients to receive placebo. On Nov 8, 2017, it was determined that 611 primary endpoints and a median follow-up of at least 1·5 years had accrued, and participants returned for a final visit and discontinuation from study treatment; the last patient visit was on March 12, 2018. These 9463 patients, the intention-to-treat population, were evaluated for a median duration of 1·6 years and were assessed for the primary outcome. The primary composite outcome occurred in 338 (7%) of 4731 patients at an incidence rate of 4·6 events per 100 person-years in the albiglutide group and in 428 (9%) of 4732 patients at an incidence rate of 5·9 events per 100 person-years in the placebo group (hazard ratio 0·78, 95% CI 0·68–0·90), which indicated that albiglutide was superior to placebo (p<0·0001 for non-inferiority; p=0·0006 for superiority). The incidence of acute pancreatitis (ten patients in the albiglutide group and seven patients in the placebo group), pancreatic cancer (six patients in the albiglutide group and five patients in the placebo group), medullary thyroid carcinoma (zero patients in both groups), and other serious adverse events did not differ between the two groups. There were three (<1%) deaths in the placebo group that were assessed by investigators, who were masked to study drug assignment, to be treatment-related and two (<1%) deaths in the albiglutide group. Interpretation: In patients with type 2 diabetes and cardiovascular disease, albiglutide was superior to placebo with respect to major adverse cardiovascular events. Evidence-based glucagon-like peptide 1 receptor agonists should therefore be considered as part of a comprehensive strategy to reduce the risk of cardiovascular events in patients with type 2 diabetes. Funding: GlaxoSmithKline

Global maps of soil temperature.

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

ION-FAST as the NIRFI’s Ionospheric Diagnostic Platform

In December 2021, we presented a prototype of a fast ionosonde for vertical sounding based on the usage of publicly available radio-electronic components. This approach led to a major reduction in the cost of the created device. We called our development ION-FAST, which characterizes the key feature of the ionosonde: the possibility of continuous operation at a speed of one ionogram per second, which is required to study the rapid processes of redistribution of the electron concentration during heating experiments. In May 2022, an ionosonde for vertical sounding of the ionosphere, developed at the Radiophysical Research Institute of Nizhni Novgorod (NIRFI), was put into continuous operation at the SURA facility. This report provides a description of the improvements made to the prototype over the last year and the path to be passed from idea to implementation. The results of the first months of the prototype’s operation (especially the results of the supporting optic experiment in August 2022), as well as prospects for further use and modernization, are provided. In addition, the realization of the oblique chirp-sounding receiver prototype as an extension of the proposed diagnostic platform’s functionality, including the first results, is presented

Light Emitting Devices Based on Quantum Well-Dots

We review epitaxial formation, basic properties, and device applications of a novel type of nanostructures of mixed (0D/2D) dimensionality that we refer to as quantum well-dots (QWDs). QWDs are formed by metalorganic vapor phase epitaxial deposition of 4–16 monolayers of InxGa1−xAs of moderate indium composition (0.3 < x < 0.5) on GaAs substrates and represent dense arrays of carrier localizing indium-rich regions inside In-depleted residual quantum wells. QWDs are intermediate in properties between 2D quantum wells and 0D quantum dots and show some advantages of both of those. In particular, they offer high optical gain/absorption coefficients as well as reduced carrier diffusion in the plane of the active region. Edge-emitting QWD lasers demonstrate low internal loss of 0.7 cm−1 and high internal quantum efficiency of 87%. as well as a reasonably high level of continuous wave (CW) power at room temperature. Due to the high optical gain and suppressed non-radiative recombination at processed sidewalls, QWDs are especially advantageous for microlasers. Thirty-one μm in diameter microdisk lasers show a high record for this type of devices output power of 18 mW. The CW lasing is observed up to 110 °C. A maximum 3-dB modulation bandwidth of 6.7 GHz is measured in the 23 μm in diameter microdisks operating uncooled without a heatsink. The open eye diagram is observed up to 12.5 Gbit/s, and error-free 10 Gbit/s data transmission at 30 °C without using an external optical amplifier, and temperature stabilization is demonstrated

Time-Dependent Shifts in Intestinal Bacteriome, <i>Klebsiella</i> Colonization and Incidence of Antibiotic-Resistance Genes after Allogeneic Hematopoietic Stem Cell Transplantation

Dose-intensive cytostatic therapy and antibiotic treatment in allogeneic hematopoietic stem cell transplantation (allo-HSCT) cause severe abnormalities in a composition of gut microbiota as well as the emergence of antibiotic resistance. The data on the longitudinal recovery of major bacterial phyla and the expansion of genes associated with antibiotic resistance are limited. We collected regular stool samples during the first year after allo-HSCT from 12 adult patients with oncohematological disorders after allo-HSCT and performed 16SrRNA sequencing, multiplex PCR, conventional bacteriology and CHROMagar testing. We observed a decline in Shannon microbiota diversity index as early as day 0 of allo-HSCT (p = 0.034) before any administration of antibiotics, which persisted up to 1 year after transplantation, when the Shannon index returned to pre-transplant levels (p = 0.91). The study confirmed the previously shown decline in Bacillota (Firmicutes) genera and the expansion of E. coli/Shigella, Klebsiella and Enterococci. The recovery of Firmicutes was slower than that of other phyla and occurred only a year post-transplant. A positive correlation was observed between the expansion of E. coli/Shigella genera and blaKPC, blaCTX-M-1 and blaTEM (p Klebsiella spp. and blaOXA-48-like, blaNDM, blaCTX-M-1, blaTEM, and blaSHV (p Pseudomonas spp. and blaNDM (p = 0.002), Enterococcus spp. and blaOXA-48-like, blaNDM, blaCTX-M-1, blaSHV (p p K. pneumoniae strains in fecal samples proved to be resistant to the main antibiotic groups (carbapenems, aminoglycosides, fluoroquinolones, third-generation cephalosporins). One year after HSCT, we documented the spontaneous decolonization of K. pneumoniae. The sensitivity of molecular biology techniques in the search for total and antibiotic-resistant Klebsiella seems to be superior to common bacteriological cultures. Future studies should be focused on searching for novel approaches to the efficient reconstitution and/or maintenance of strictly anaerobic microbiota in oncological patients