27 research outputs found

    Hidden attractors in fundamental problems and engineering models

    Full text link
    Recently a concept of self-excited and hidden attractors was suggested: an attractor is called a self-excited attractor if its basin of attraction overlaps with neighborhood of an equilibrium, otherwise it is called a hidden attractor. For example, hidden attractors are attractors in systems with no equilibria or with only one stable equilibrium (a special case of multistability and coexistence of attractors). While coexisting self-excited attractors can be found using the standard computational procedure, there is no standard way of predicting the existence or coexistence of hidden attractors in a system. In this plenary survey lecture the concept of self-excited and hidden attractors is discussed, and various corresponding examples of self-excited and hidden attractors are considered

    Effect of synthetic peptide thrombin receptor agonist encapsulated in microparticles based on lactic and glycolic acid copolymer on healing of experimental skin wounds in mice.

    Full text link
    PAR1 peptide thrombin receptor agonist (PAR1-AP) was encapsulated in microcorpuscles based on lactic and glycolic acid copolymer. The desorption profile of the preparation was studied in vitro and its wound-healing effects were studied on a model of cut skin wound in mice. The study showed that 90% PAR1-AP was desorbed over 6 h, but the peptide was detected in eluates from the microparticle surface after 23 h. The desorbed peptide retained its physiological activity and was capable of activating PAR1 receptors on human platelets. The study of the dynamics of experimental skin wound healing in mice showed lower number of macrophages in the wounds treated with PAR1-AP microparticles compared to the control (open wounds and wounds covered with microparticles) and higher number of fibroblasts on day 3 of tissue reparation. Hence, PAR1-AP desorbed from microparticles shortened the inflammation phase in the wound. On day 7 the best healing parameters were also observed in wounds treated with PAR1-AP microparticles, which attests to shortening of the proliferation phase and acceleration of wound healing

    Infectious and non-infectious pericarditis in children

    No full text
    Pericardial diseases in children are heterogeneous in nature and can be both isolated and part of the systemic pathology. Data on the epidemiology and etiology of pericardial disease are contradictory and depend on the hospital profile, patients' age and study aims. Objective of the research-to study modern structure of pericardial diseases in children, clinical and instrumental features of individual forms and treatment tactics in real clinical practice according to the data of the Moscow multi-profile hospital. Study materials and methods: A complex clinical and laboratory-based examination was conducted in 121 patients aged from 1 month to 18 years, admitted to Morozov Children's City Clinical Hospital in Moscow in 2001-2016 with pericardium diseases. Results: pericardium inflammatory lesions were diagnosed in 86% of children, 57% of patients had infectious pericarditis (bacterial and idiopathic). The most severe course was in cases of bacterial, neoplastic pericarditis and postpericardiotomy syndrome (PPTS). A common feature of the severe course was the accumulation of a large pericardial effusion and the threat of a cardiac tamponade. In patients with idiopathic pericarditis and PPTS, herpesvirus infections markers, Mycoplasma pneumoniae, Chlamydophila pneumoniae, were more often detected with large effusions accumulation (p=0,02). Complications development was noted in 33 (27,3%) children: cardiac tamponade or the threat of its development in 23 (19%), recurrent course in 11 (9,1%). As anti-inflammatory therapy non-steroidal anti-inflammatory drugs were used (73,6% of patients); if they were inefficient-glucocorticosteroids (41,3%) and intravenous immunoglobulins (24,8%). Pericardiocentesis due to threat of cardiac tamponade was performed in 13 (10,74%) children. Conclusion: in pericarditis structure dominated infectious: bacterial and idiopathic (57%). Specific IgM antibodies to herpesviruses, Mycoplasma pneumoniae, Chlamydophila pneumoniae are possible markers of large pericardial effusion accumulation children with idiopathic pericarditis and PPTS. To assess the predictors of pericarditis adverse course incl. use of glucocorticosteroids, it is necessary to analyze long-term disease catamnesis. Β© 2017, Pediatria Ltd. All rights reserved

    Infectious and non-infectious pericarditis in children

    No full text
    Pericardial diseases in children are heterogeneous in nature and can be both isolated and part of the systemic pathology. Data on the epidemiology and etiology of pericardial disease are contradictory and depend on the hospital profile, patients' age and study aims. Objective of the research-to study modern structure of pericardial diseases in children, clinical and instrumental features of individual forms and treatment tactics in real clinical practice according to the data of the Moscow multi-profile hospital. Study materials and methods: A complex clinical and laboratory-based examination was conducted in 121 patients aged from 1 month to 18 years, admitted to Morozov Children's City Clinical Hospital in Moscow in 2001-2016 with pericardium diseases. Results: pericardium inflammatory lesions were diagnosed in 86% of children, 57% of patients had infectious pericarditis (bacterial and idiopathic). The most severe course was in cases of bacterial, neoplastic pericarditis and postpericardiotomy syndrome (PPTS). A common feature of the severe course was the accumulation of a large pericardial effusion and the threat of a cardiac tamponade. In patients with idiopathic pericarditis and PPTS, herpesvirus infections markers, Mycoplasma pneumoniae, Chlamydophila pneumoniae, were more often detected with large effusions accumulation (p=0,02). Complications development was noted in 33 (27,3%) children: cardiac tamponade or the threat of its development in 23 (19%), recurrent course in 11 (9,1%). As anti-inflammatory therapy non-steroidal anti-inflammatory drugs were used (73,6% of patients); if they were inefficient-glucocorticosteroids (41,3%) and intravenous immunoglobulins (24,8%). Pericardiocentesis due to threat of cardiac tamponade was performed in 13 (10,74%) children. Conclusion: in pericarditis structure dominated infectious: bacterial and idiopathic (57%). Specific IgM antibodies to herpesviruses, Mycoplasma pneumoniae, Chlamydophila pneumoniae are possible markers of large pericardial effusion accumulation children with idiopathic pericarditis and PPTS. To assess the predictors of pericarditis adverse course incl. use of glucocorticosteroids, it is necessary to analyze long-term disease catamnesis. Β© 2017, Pediatria Ltd. All rights reserved

    Π“Π΅Π½Ρ‹ «стахановцы» 18 хромосомы Ρ‡Π΅Π»ΠΎΠ²Π΅ΠΊΠ°, ΠΎΡ‚ΡΡƒΡ‚ΡΡ‚Π²ΡƒΡŽΡ‰ΠΈΠ΅ Π±Π΅Π»ΠΊΠΈ ΠΈ Π½Π΅ ΠΎΡ…Π°Ρ€Π°ΠΊΡ‚Π΅Ρ€ΠΈΠ·ΠΎΠ²Π°Π½Π½Ρ‹Π΅ Π±Π΅Π»ΠΊΠΈ Π² Ρ‚ΠΊΠ°Π½ΠΈ ΠΏΠ΅Ρ‡Π΅Π½ΠΈ ΠΈ ΠΊΠ»Π΅Ρ‚ΠΎΡ‡Π½ΠΎΠΉ Π»ΠΈΠ½ΠΈΠΈ HepG2

    No full text
    Missing (MP) and functionally uncharacterized proteins (uPE1) comprise less than 5% of the total number of proteins encoded by human Chr18 genes. Within half a year, since the January 2020 version of NextProt, the number of entries in the MP+uPE1 datasets changed, mainly due to the achievements of antibody-based proteomics. Assuming that the proteome is closely related to the transcriptome scaffold, quantitative PCR, Illumina HiSeq, and Oxford Nanopore Technology were applied to characterize the liver samples of three male donors in comparison with the HepG2 cell line. The data mining of the Expression Atlas (EMBL-EBI) and the profiling of biopsy samples by using orthogonal methods of transcriptome analysis have shown that in HepG2 cells and the liver, the genes encoding functionally uncharacterized proteins (uPE1) are expressed as low as for the missing proteins (less than 1 copy per cell), except the selected cases of HSBP1L1, TMEM241, C18orf21, and KLHL14. The initial expectation that uPE1 genes might be expressed at higher levels than MP genes, was compromised by severe discrepancies in our semi-quantitative gene expression data and in public databanks. Such discrepancy forced us to revisit the transcriptome of Chr18, the target of the Russian C-HPP Consortium. Tanglegram of highly expressed genes and further correlation analysis have shown the severe dependencies on the mRNA extraction method and the analytical platform. Targeted gene expression analysis by quantitative PCR (qPCR) and high-throughput transcriptome profiling (Illumina HiSeq and ONT MinION) for the same set of samples from normal liver tissue and HepG2 cells revealed the detectable expression of 250+ (92%) protein-coding genes of Chr18 (at least one method). The expression of slightly more than 50% protein-coding genes was detected simultaneously by all three methods. Correlation analysis of the gene expression profiles showed that the grouping of the datasets depended almost equally on both the type of biological material and the experimental method, particularly cDNA/mRNA isolation and library preparation.ΠžΡ‚ΡΡƒΡ‚ΡΡ‚Π²ΡƒΡŽΡ‰ΠΈΠ΅ Π±Π΅Π»ΠΊΠΈ ΠΈ Ρ„ΡƒΠ½ΠΊΡ†ΠΈΠΎΠ½Π°Π»ΡŒΠ½ΠΎ Π½Π΅ ΠΎΡ…Π°Ρ€Π°ΠΊΡ‚Π΅Ρ€ΠΈΠ·ΠΎΠ²Π°Π½Π½Ρ‹Π΅ Π±Π΅Π»ΠΊΠΈ (Π² англоязычной Π»ΠΈΡ‚Π΅Ρ€Π°Ρ‚ΡƒΡ€Π΅ ΠΎΠ±ΠΎΠ·Π½Π°Ρ‡Π΅Π½Π½Ρ‹Π΅ ΠΊΠ°ΠΊ missing (MP) ΠΈ functionally uncharacterized proteins (uPE1), соотвСтствСнно) ΡΠΎΡΡ‚Π°Π²Π»ΡΡŽΡ‚ ΠΌΠ΅Π½Π΅Π΅ 5% ΠΎΡ‚ ΠΎΠ±Ρ‰Π΅Π³ΠΎ числа Π±Π΅Π»ΠΊΠΎΠ², ΠΊΠΎΠ΄ΠΈΡ€ΡƒΠ΅ΠΌΡ‹Ρ… Π³Π΅Π½Π°ΠΌΠΈ 18 хромосомы Ρ‡Π΅Π»ΠΎΠ²Π΅ΠΊΠ°. Π’ Ρ‚Π΅Ρ‡Π΅Π½ΠΈΠ΅ ΠΏΠΎΠ»ΡƒΠ³ΠΎΠ΄Π°, начиная с января 2020 Π³ΠΎΠ΄Π°, Π² вСрсии NextProt выросло количСство записСй Π² Π½Π°Π±ΠΎΡ€Π°Ρ… Π΄Π°Π½Π½Ρ‹Ρ… MP+uPE1. ΠŸΠΎΠ΄ΠΎΠ±Π½Ρ‹Π΅ измСнСния обусловлСны прСимущСствСнно достиТСниями ΠΏΡ€ΠΎΡ‚Π΅ΠΎΠΌΠΈΠΊΠΈ Π½Π° основС Π°Π½Ρ‚ΠΈΡ‚Π΅Π». Π’ Π΄Π°Π½Π½ΠΎΠΉ Ρ€Π°Π±ΠΎΡ‚Π΅ количСствСнная ПЦР, Ρ‚Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³ΠΈΠΈ сСквСнирования Illumina HiSeq ΠΈ Oxford Nanopore Technologies Π±Ρ‹Π»ΠΈ ΠΏΡ€ΠΈΠΌΠ΅Π½Π΅Π½Ρ‹ для ΡΡ€Π°Π²Π½ΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° транскриптомного профиля ΠΎΠ±Ρ€Π°Π·Ρ†ΠΎΠ² ΠΏΠ΅Ρ‡Π΅Π½ΠΈ Ρ‚Ρ€Π΅Ρ… Π΄ΠΎΠ½ΠΎΡ€ΠΎΠ² муТского ΠΏΠΎΠ»Π° ΠΈ ΠΊΠ»Π΅Ρ‚ΠΎΡ‡Π½ΠΎΠΉ Π»ΠΈΠ½ΠΈΠΈ HepG2. Анализ Π΄Π°Π½Π½Ρ‹Ρ… атласа экспрСссии (Expression Atlas, EMBL-EBI) ΠΈ ΠΏΠΎΠ»ΡƒΡ‡Π΅Π½Π½Ρ‹Ρ… Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΎΠ² ΠΏΠΎ биологичСским ΠΎΠ±Ρ€Π°Π·Ρ†Π°ΠΌ с использованиСм ΠΎΡ€Ρ‚ΠΎΠ³ΠΎΠ½Π°Π»ΡŒΠ½Ρ‹Ρ… ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠ² Π°Π½Π°Π»ΠΈΠ·Π° транскриптома ΠΏΠΎΠΊΠ°Π·Π°Π», Ρ‡Ρ‚ΠΎ Π² ΠΊΠ»Π΅Ρ‚ΠΊΠ°Ρ… ΠΏΠ΅Ρ‡Π΅Π½ΠΈ ΠΈ HepG2 ΡƒΡ€ΠΎΠ²Π΅Π½ΡŒ экспрСссии Π³Π΅Π½ΠΎΠ², ΠΊΠΎΠ΄ΠΈΡ€ΡƒΡŽΡ‰ΠΈΡ… Ρ„ΡƒΠ½ΠΊΡ†ΠΈΠΎΠ½Π°Π»ΡŒΠ½ΠΎ Π½Π΅ ΠΎΡ…Π°Ρ€Π°ΠΊΡ‚Π΅Ρ€ΠΈΠ·ΠΎΠ²Π°Π½Π½Ρ‹Π΅ Π±Π΅Π»ΠΊΠΈ (uPE1), находится Π½Π° Ρ‚Π°ΠΊΠΎΠΌ ΠΆΠ΅ Π½ΠΈΠ·ΠΊΠΎΠΌ ΡƒΡ€ΠΎΠ²Π½Π΅, ΠΊΠ°ΠΊ ΠΈ Π² случаС Π³Π΅Π½ΠΎΠ² MP (Π² количСствС ΠΌΠ΅Π½Π΅Π΅ 1 ΠΊΠΎΠΏΠΈΠΈ Π½Π° ΠΊΠ»Π΅Ρ‚ΠΊΡƒ). Π˜ΡΠΊΠ»ΡŽΡ‡Π΅Π½ΠΈΠ΅ составили нСсколько Π³Π΅Π½ΠΎΠ²: HSBP1L1, TMEM241, C18orf21 ΠΈ KLHL14. Богласно сущСствСнным расхоТдСниям Π² Ρ€Π°Π½Π΅Π΅ ΠΏΠΎΠ»ΡƒΡ‡Π΅Π½Π½Ρ‹Ρ… полуколичСствСнных Π΄Π°Π½Π½Ρ‹Ρ… ΠΏΠΎ экспрСссии Π³Π΅Π½ΠΎΠ² ΠΈ Π΄Π°Π½Π½Ρ‹ΠΌ Π² ΠΎΡ‚ΠΊΡ€Ρ‹Ρ‚Ρ‹Ρ… Π±Π°Π·Π°Ρ… Π΄Π°Π½Π½Ρ‹Ρ…, ΠΈΠ·Π½Π°Ρ‡Π°Π»ΡŒΠ½ΠΎ ΠΏΡ€Π΅Π΄ΠΏΠΎΠ»Π°Π³Π°Π»ΠΎΡΡŒ, Ρ‡Ρ‚ΠΎ экспрСссия Π³Π΅Π½ΠΎΠ² uPE1 ΠΌΠΎΠΆΠ΅Ρ‚ Π±Ρ‹Ρ‚ΡŒ Π²Ρ‹ΡˆΠ΅, Ρ‡Π΅ΠΌ Π³Π΅Π½ΠΎΠ² MP. ПодобноС расхоТдСниС ΠΏΠΎΠ±ΡƒΠ΄ΠΈΠ»ΠΎ ΠΎΠ±Ρ€Π°Ρ‚ΠΈΡ‚ΡŒΡΡ ΠΊ транскриптому 18 хромосомы Ρ‡Π΅Π»ΠΎΠ²Π΅ΠΊΠ°, ΡΠ²Π»ΡΡŽΡ‰Π΅ΠΉΡΡ Ρ†Π΅Π»Π΅Π²ΠΎΠΉ для России Π² ΠΏΡ€ΠΎΠ΅ΠΊΡ‚Π΅ Β«ΠŸΡ€ΠΎΡ‚Π΅ΠΎΠΌ Ρ‡Π΅Π»ΠΎΠ²Π΅ΠΊΠ°Β». ΠŸΠΎΠ»ΡƒΡ‡Π΅Π½Π½Ρ‹Π΅ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹ ΠΎ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ экспрСссируСмых Π³Π΅Π½Π°Ρ… ΠΈ дальнСйший коррСляционный Π°Π½Π°Π»ΠΈΠ· ΠΏΠΎΠΊΠ°Π·Π°Π» сущСствованиС зависимости ΠΎΡ‚ ΠΌΠ΅Ρ‚ΠΎΠ΄Π° экстракции мРНК ΠΈ аналитичСской ΠΏΠ»Π°Ρ‚Ρ„ΠΎΡ€ΠΌΡ‹. Анализ экспрСссии Ρ†Π΅Π»Π΅Π²Ρ‹Ρ… Π³Π΅Π½ΠΎΠ² 18 хромосомы с ΠΏΡ€ΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ΠΌ количСствСнной ПЦР (qPCR) ΠΈ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠ² Π²Ρ‹ΡΠΎΠΊΠΎΠΏΡ€ΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎΠ³ΠΎ профилирования транскриптома (Illumina HiSeq ΠΈ ONT MinION) для ΠΎΠ΄ΠΈΠ½Π°ΠΊΠΎΠ²Ρ‹Ρ… Π½Π°Π±ΠΎΡ€ΠΎΠ² ΠΎΠ±Ρ€Π°Π·Ρ†ΠΎΠ² Π½ΠΎΡ€ΠΌΠ°Π»ΡŒΠ½ΠΎΠΉ Ρ‚ΠΊΠ°Π½ΠΈ ΠΏΠ΅Ρ‡Π΅Π½ΠΈ ΠΈ ΠΊΠ»Π΅Ρ‚ΠΎΡ‡Π½ΠΎΠΉ Π»ΠΈΠ½ΠΈΠΈ HepG2 выявил Π±ΠΎΠ»Π΅Π΅ 250 (92%) Π±Π΅Π»ΠΎΠΊ-ΠΊΠΎΠ΄ΠΈΡ€ΡƒΡŽΡ‰ΠΈΡ… Π³Π΅Π½ΠΎΠ², Π΄Π΅Ρ‚Π΅ΠΊΡ‚ΠΈΡ€ΡƒΠ΅ΠΌΡ‹Ρ… хотя Π±Ρ‹ ΠΎΠ΄Π½ΠΈΠΌ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠΌ. ЭкспрСссия Π±ΠΎΠ»Π΅Π΅ Ρ‡Π΅ΠΌ 50% Π±Π΅Π»ΠΎΠΊ-ΠΊΠΎΠ΄ΠΈΡ€ΡƒΡŽΡ‰ΠΈΡ… Π³Π΅Π½ΠΎΠ² Π±Ρ‹Π»Π° Π΄Π΅Ρ‚Π΅ΠΊΡ‚ΠΈΡ€ΠΎΠ²Π°Π½Π° всСми трСмя ΠΌΠ΅Ρ‚ΠΎΠ΄Π°ΠΌΠΈ. ΠšΠΎΡ€Ρ€Π΅Π»ΡΡ†ΠΈΠΎΠ½Π½Ρ‹ΠΉ Π°Π½Π°Π»ΠΈΠ· ΠΏΡ€ΠΎΡ„ΠΈΠ»Π΅ΠΉ экспрСссии Π³Π΅Π½ΠΎΠ² ΠΏΠΎΠΊΠ°Π·Π°Π», Ρ‡Ρ‚ΠΎ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹ Β«Π³Ρ€ΡƒΠΏΠΏΠΈΡ€ΡƒΡŽΡ‚ΡΡΒ» Π² зависимости ΠΎΡ‚ Ρ‚ΠΈΠΏΠ° биологичСского ΠΌΠ°Ρ‚Π΅Ρ€ΠΈΠ°Π»Π° ΠΈ ΡΠΊΡΠΏΠ΅Ρ€ΠΈΠΌΠ΅Π½Ρ‚Π°Π»ΡŒΠ½Ρ‹Ρ… ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠ², Π² частности ΠΎΡ‚ способа ΠΏΠΎΠ΄Π³ΠΎΡ‚ΠΎΠ²ΠΊΠΈ Π±ΠΈΠ±Π»ΠΈΠΎΡ‚Π΅ΠΊΠΈ (выдСлСния ΠΊΠ”ΠΠš, мРНК). Π—Π°Π²ΠΈΡΠΈΠΌΠΎΡΡ‚ΡŒ ΠΎΡ‚ Π²Ρ‹Π±ΠΎΡ€Π° способа биоинформатичСской ΠΎΠ±Ρ€Π°Π±ΠΎΡ‚ΠΊΠΈ Π±Ρ‹Π»Π° ΠΎΡ‚ΠΌΠ΅Ρ‡Π΅Π½Π° Π² Π·Π½Π°Ρ‡ΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎ мСньшСй стСпСни
    corecore