Spontaneous Discharge Patterns in Cochlear Spiral Ganglion Cells Prior to the Onset of Hearing in Cats

Spontaneous neural activity has been recorded in the auditory nerve of cats as early as 2 days postnatal (P2 ), yet individual auditory neurons do not respond to ambient sound levels below 90–100 dB SPL until about P10. Significant refinement of the central projections from the spiral ganglion to the cochlear nucleus occurs during this neonatal period. This refinement may be dependent on peripheral spontaneous discharge activity. We recorded from single spiral ganglion cells in kittens aged P3 to P9. The spiral ganglion was accessed via the round window through the spiral lamina. A total of 112 ganglion cells were isolated for study in 9 animals. Spike rates in neonates were very low, ranging from 0.06 to 56 sp/s with a mean of 3.09 +/- 8.24 sp/s. Ganglion cells in neonatal kittens exhibited remarkable repetitive spontaneous bursting discharge patterns. The unusual patterns were evident in the large mean interval coefficient of variation (CVi = 2.9 +/-1.6) and burst index of 5.2 +/- 3.5 across ganglion cells. Spontaneous bursting patterns in these neonatal mammals were similar to those reported for cochlear ganglion cells of the embryonic chicken suggesting this may be a general phenomenon that is common across animal classes. Rhythmic spontaneous discharge of retinal ganglion cells has been shown to be important in the development of central retinotopic projections and normal binocular vision (Shatz, 1996, Proc Natl Acad Sci 93). Bursting rhythms in cochlear ganglion cells may play a similar role in the auditory system during pre-hearing periods. Originally published in Journal of Neurophysiology Vol. 98, No. 4 200

Dynamics of Stroke Incidence and Mortality Indicators over Eight-Year Period in the Territories Included into the Federal Program of Reorganization of Care for Patients with Stroke

Background. Stroke is a severe medical, social and economic burden for all countries of the world. The leading indicators characterizing the “epidemiological picture” of stroke are the incidence and mortality rates from stroke.Aims. Analyze the dynamics of stroke incidence and mortality rates in the regions of Russia that were included in the federal program for reorganizing care for patients with stroke for the period from 2009 to 2016.Material and methods. The study was based on the data of the territorial-population register for seven study areas in the regions of Russia that were included in the federal program for reorganizing care for patients with stroke (Republic of Bashkortostan, Sverdlovsk region, Republic of Tatarstan, Sakhalin region, Stavropol Territory, Ivanovo Region and Irkutsk Region). The age of the examined persons was 25 years and older.Results. In the period from 2009 to 2016, in the studied territories, there was a consistent stable decrease in the value of the stroke incidence rate. Stroke mortality rates fluctuated with a single increase in 2012. When comparing the average incidence of stroke and mortality from it between 2009 and 2016, we discovered a statistically significant decrease in the incidence of stroke – by 1.4 times and in the rate of mortality from stroke – by 2.3 times. According to the results of the cluster analysis, we revealed a significant conformity (similarity) of mortality rates between regions by 2016 and the absence of monotony (stability) of the rate of stroke incidence.Conclusion. In all the regions under study, an almost systematic annual decrease in the incidence and mortality rates from stroke among the adult population was revealed in seven studied territories. The results of cluster analysis of the “picture” of stroke incidence and mortality from it also demonstrate a positive trend by 2016 in all studied territories. Only one of the studied territories – the Republic of Tatarstan – despite the presence of a positive dynamics of stroke incidence over an eight-year period, in 2016 belonged to the rank with a high integral incidence rate

Hyperexpression of TLR2 and TLR4 in patients with ischemic stroke in acute period of the disease

Pathogenesis of ischemic stroke  is actively  involved  in the  system  of innate immunity. Under conditions of cerebral  ischemia, a number of biologically  active  substances are  released  that  interact with innate immunity receptors, in particular TLR2  and  TLR4, which  exacerbate inflammation in brain  tissue. Identification of predictor markers  at the level of the innate immunity system may foresee the clinical course of ischemic stroke and ensure timely treatment. Our objective was to study expression of TLR2 and TLR4 receptors in peripheral blood leukocytes  in patients with ischemic stroke in the dynamics of the disease. 27 people  were included in the study. The main  group consisted of patients with ischemic stroke of varying severity (n = 19). Patients of the main  group were divided into two subgroups:  with an NIHSS index value of < 10 (n = 10) and > 10 (n = 9). The control group included healthy  donors  with no history  of acute  and chronic inflammatory diseases (n = 8). Peripheral blood  leukocytes  were used as the  test material. To determine expression  of the TLR2  and TLR4  genes, RT-PCR in real time was used. Surface  expression  of TLRs was determined by flow cytometry. A study of the TLR2 and TLR4 gene expression showed that on the 1st, 3rd  and 7th  day post-stroke, the TLR4 gene expression  in patients was significantly  increased, when compared to the control group (p < 0.01), whereas TLR2 gene expression on the 3rd  day of the disease was not statistically different from the control group. A study of surface expression  of receptors showed that the average TLR2 fluorescence intensity on the patients’ peripheral blood monocytes was significantly  increased on the 1st  and 3rd  day of disease when compared to the control group.  The  surface  expression  of TLR4  on monocytes has a statistically significant  increase  only on day 7. Assessment  of surface expression  of TLRs in subgroups  with different  severity values by NIHSS showed that  patients with a NIHSS index > 10 had a significantly  higher  level of surface of TLR2  expression  over the observation period, while the largest difference in TLR4  expression  in the subgroups  was observed  on the 1st day of the disease (p < 0.05). Patients with ischemic stroke showed an increase  in TLR2 and TLR4 expression at the gene and protein level, compared to healthy  donors. These indices can be considered possible predictors for clinical  prognosis  of ischemic stroke

The effect of morphine on tumor cells growth

This article examines the effect of morphine on tumor growth, angiogenesis, metastasis, inflammation, and immunomodulation. The review of the research data revealed that morphine plays a dual role in tumor regulationВ данной статье рассмотрено влияние морфина на рост опухоли, ангиогенез, метастазирование, воспаление и иммуномодуляцию. Изучая данные исследований, было показано, что морфин играет двойную роль в регуляции опухоле

Анализ 19,9 млн публикаций базы данных PubMed/MEDLINE методами искусственного интеллекта: подходы к обобщению накопленных данных и феномен “fake news”

Introduction. The English-language databases PubMed/MEDLINE and Embase are valuable information resources for finding original publications in basic and clinical medicine. Currently, there are no artificial intelligence systems to evaluate the quality of these publications.Aim. Development and testing of a system for sentiment analysis (i.e. analysis of emotional modality) of biomedical publications.Materials and methods. The technique of analysis of the “Big data” of biomedical publications was formulated on the basis of the topological theory of sentiment analysis. Algorithms have been developed that allow for the classification of texts from 16 sentiment classes with 90% accuracy (manipulative speech, research without positive results, propaganda, falsification of results, negative personal attitude, aggressive text, negative emotional background, etc.). Based on the algorithms, a scale for assessing the sentiment quality of research (β-score) is proposed.Results. Abstracts of 19.9 million publications registered in PubMed/MEDLINE over the past 50 years (1970–2019) were analyzed. It was shown that publications with low sentiment quality (the value of the β-score of the text is less than zero, which corresponds to the prevalence of manipulative and negative sentiments in the text) comprise only 18.5% (3.68 out of 19.9 million). The greatest values of the β-score were characterized by publications on sports medicine, systems biology, nutrition, on the use of applied mathematics and data mining in medicine. The rubrication of the entire array of publications by 27,840 headings (MESH-system of PubMed/MEDLINE) indicated an increase in the β-score by years (i.e., the positive dynamics of sentiment quality of the texts of publications) for 27,090 of the studied headings. The most intense positive dynamics was found for research in genetics, physiology, pharmacology, and gerontology. 249 headings with sharply negative dynamics of sentiment quality and with a pronounced increase in the manipulative sentiments characteristic of the tabloid press were highlighted. Separate assessments of international experts are presented that confirm the patterns identified.Conclusion. The proposed artificial intelligence system allows a researcher to make an effective assessment of the sentiment quality of biomedical research papers, filtering out potentially inappropriate publications disguised as “evidence-based”.  Введение. Англоязычные базы данных PubMed/MEDLINE и Embase являются ценными информационными ресурсами для нахождения оригинальных публикаций по фундаментальной и клинической медицине. В настоящее время не существует систем искусственного интеллекта, позволяющих оценивать качество этих публикаций.Цель. Разработка и апробация системы для проведения сентимент-анализа (то есть анализа эмоциональной модальности) публикаций по биомедицине.Материалы и методы. Сформулирована методика анализа «больших данных» биомедицинских публикаций, основанная на топологической теории сентимент-анализа медицинских текстов. Разработаны алгоритмы, позволяющие с 90%-й точностью классифицировать тексты по 16 классам сентиментов (манипулятивные обороты речи, исследования без положительных результатов, пропаганда, подделка результатов, негативное личное отношение, агрессивность текста, негативный эмоциональный фон и др.). На основе алгоритмов предложена балльная шкала оценки сентимент-качества исследований (β-балл).Результаты. Проведен анализ текстов абстрактов 19,9 млн публикаций, зарегистрированных в PubMed/MEDLINE за последние 50 лет (1970–2019). Показано, что публикации с низким сентимент-качеством (значение β-балла текста меньше нуля, что соответствует преобладанию манипулятивных и негативных сентиментов в тексте) составляют всего 18,5% (3,68 из 19,9 млн).  Наибольшими значениями β-балла характеризовались публикации по спортивной медицине,  системной биологии, нутрициологии, по использованию методов прикладной математики и интеллектуального анализа данных в медицине. Рубрикация всего массива публикаций по 27840 рубрикам (MESH-система PubMed/MEDLINE) указала на повышение β-балла по годам (то есть на положительную динамику сентимент-качества текстов публикаций) для 27090 исследованных рубрик. Наиболее интенсивная положительная динамика найдена для исследований по генетике, физиологии, фармакологии и геронтологии. Выделены 249 рубрик с резко отрицательной  динамикой сентимент-качества и с выраженным нарастанием манипулятивных сентиментов,  характерных для «желтой» англоязычной прессы. Приведены отдельные оценки международных экспертов, которые подтверждают выявленные закономерности. Заключение. Разработанная система искусственного интеллекта позволяет проводить  эффективную оценку сентимент-качества биомедицинских исследований, отфильтровывая  потенциально неадекватные публикации, публикуемые под маской «доказательных». 

Компьютерный анализ эмоциональной модальности 20 млн публикаций в базе данных PUBMED указывает на пути повышения эффективности фармакотерапии посредством идентификации псевдонаучных публикаций, направленных на негативную эмоциональную «накачку» врачей

The search for original publications on fundamental and clinical medicine that would produce results of the highest scientific quality represents an urgent need for every medical researcher. Such publications are essential, in particular, for the development of reliable treatment standards. The Englishlanguage resources PUBMED and EMBASE are essential to help in solving this problem. However, there is an obvious problem in assessing the quality of the studies found. The paper formulates a method for analyzing the texts of biomedical publications, which is based on an algorithmic assessment of the emotional modality of medical texts (so-called sentiment analysis). The use of the topological theory of data analysis made it possible to develop a set of high-precision algorithms for identifying 16 types of sentiments (manipulative turns of speech, research without positive results, propaganda, falsification of results, negative personal attitude, aggressiveness of the text, negative emotional background, etc.). On the basis of the developed algorithms, a point scale for assessing the sentiment quality of research was obtained, which we called the "β-score": the higher the β-score, the less the evaluated text contains manipulative language constructions. As a result, the ANTIFAKE system (http://antifake-news.ru) was developed to analyze the sentiment-quality of Englishlanguage scientific texts. An analysis of ~ 20 million abstracts from PUBMED showed that publications with low sentiment quality (β-score <0, that is, that the prevalence of manipulative constructions over meaningful ones) is only 19 %. In the overwhelming majority of thematic headings (27,090 out of 27,840 headings of the MESH system PUBMED), a positive dynamics of sentiment quality of the texts of publications is shown by years). At the same time, as a result of the study, 249 headings were identified with sharply negative dynamics of sentiment quality and with a pronounced increase in manipulative sentiments characteristic of the "yellow" English-language press. These headings include tens of thousands of publications in peer-reviewed journals, which are aimed at (1) legalizing ethically unacceptable practices (euthanasia, perversions, so-called "population control", etc.), (2) discrediting psychiatry as a science, (3) media the war against micronutrients and (4) discrediting evidence-based medicine under the guise of developing the so-called "international standards of evidence-based medicine". In general, the developed system of artificial intelligence allows researchers to filter out pseudoscientific publications, the text of which is overloaded with emotional manipulation and which are published under the guise of "evidence-based standards".Поиск оригинальных публикаций по фундаментальной и клинической медицине наивысшего научного качества – насущная необходимость для каждого врача-исследователя. Такие публикации принципиально необходимы, в частности, для разработки надёжных стандартов лечения. Существенной подмогой в решении этой задачи являются англоязычные ресурсы PUBMED и EMBASE. Однако существует очевидная проблема оценки качества находимых исследований. В работе сформулирована методика анализа текстов биомедицинских публикаций, в основе которой лежит алгоритмическая оценка эмоциональной модальности медицинских текстов (т. н. сентимент-анализа). Применение топологической теории анализа данных позволило разработать комплекс высокоточных алгоритмов для выявления 16 типов сентиментов (манипулятивные обороты речи, исследования без положительных результатов, пропаганда, подделка результатов, негативное личное отношение, агрессивность текста, негативный эмоциональный фон и др.). На основе разработанных алгоритмов получена балльная шкала оценки сентимент-качества исследований, которую мы назвали «β-баллом»: чем выше β-балл, тем в меньшей степени оцениваемый текст содержит манипулятивные языковые конструкции. В результате разработана и апробирована система ANTIFAKE (http://antifake-news.ru), предназначенная для анализа сентимент-качества англоязычных научных текстов. Анализ ~20 млн абстрактов из PUBMED показал, что публикации с низким сентимент-качеством (β-балл которые направлены на (1) легализацию этически порочных практик (эвтаназия, т. н. «контроль популяций» и т. п.), (2) дискредитацию психиатрии как науки, (3) медийную войну против микронутриентов и (4) дискредитацию доказательной медицины под видом разработки т. н. «международных стандартов доказательной медицины». В целом, разработанная система искусственного интеллекта позволяет отфильтровывать псевдонаучные публикации, текст которых перегружен эмоциональной манипуляцией и которые публикуются под маской «доказательных стандартов»

Risk factors for ischemic stroke among the rural population of the Stavropol territory

The paper presents the results of a study of risk factors for ischemic stroke (IS) in the rural versus urban population of the Stavropol Territory. The rural dwellers have been found to have a higher rate of alcohol abuse, atherogenic diet, unawareness of arterial hypertension and, accordingly, its treatment and atrial fibrillation. How to improve the prevention of IS in the rural area is discussed

PREDICTION OF PROBABILITY OF THE LONG TERM FATAL OUTCOME OF STROKE BY THE DATA OF TERRITORY AND POPULATIONAL REGISTRY

Aim. To develop a prediction model of individual probability of long term (within first 28 days from the onset) outcome of stroke.Material and methods. By the method of territory-populational registry, in 2009-2016 in 16 regions of Russia, an analysis performed, of significant predictors of fatal stroke outcome. Overall, 50902 strokes registered in persons older 25 y. In 1553 there were no data on long term mortality. By the results of revealed significant predictors of the fatal outcome of stroke by LOTUS method, a tree-branching was done for development of probability of long term fatal outcome during the first 28 days from disease presentation.Results. The significant predictors were acquired, of the fatal outcome of stroke, and graded by odds ratio. Based on the definition of significant predictors of fatal outcome, first time a prediction model developed of probability of long term stroke fatal outcome taken heterogeneity and multifactorial nature of the disease. Clinical guidelines proposed.Conclusion. The developed prediction model of individual probability of long term stroke fatal outcome shows high level of sensitivity and specificity. Application of such model and of proposed clinical guidelines at various stages of patients management will facilitate diagnostical search, management strategy selection and improvement of prevention