406 research outputs found
On-Off Intermittency in Time Series of Spontaneous Paroxysmal Activity in Rats with Genetic Absence Epilepsy
Dynamic behavior of complex neuronal ensembles is a topic comprising a
streamline of current researches worldwide. In this article we study the
behavior manifested by epileptic brain, in the case of spontaneous
non-convulsive paroxysmal activity. For this purpose we analyzed archived
long-term recording of paroxysmal activity in animals genetically susceptible
to absence epilepsy, namely WAG/Rij rats. We first report that the brain
activity alternated between normal states and epilepsy paroxysms is the on-off
intermittency phenomenon which has been observed and studied earlier in the
different nonlinear systems.Comment: 11 pages, 6 figure
Impact of inter-ventricular lead distance on cardiac resynchronization therapy outcomes
Cardiac resynchronization therapy (CRT) has been shown as an essential treatment of patients with heart failure, leading to improvements in symptoms, left ventricular (LV) function, and survival. However, up to 30% of appropriately selected patients remain non-responders to CRT. The aim of our study was to test a hypothesis on the impact of lead positioning in the ventricular walls on CRT response in patients with advanced chronic heart failure with and without pre-operative inter and intra-ventricular myocardial dyssynchrony. We examined 53 guideline-selected CRT candidates. Response to CRT was defined in 6 months after implantation of CRT devices. All patients underwent standard and Doppler echocardiography for assessment of LV function and mechanical dyssynchrony. Individual right ventricular (RV) and LV lead tip position, inter-lead distance, and the horizontal and vertical components were measured on the radiograph images with using an automated custom made software Our results showed that the RLV inter-lead distance is an essential parameter correlated with the CRT outcomes. A logistic model comprising the RLV inter-lead distance with parameters of dyssynchrony demonstrated a high predictive power for odds of CRT success. Β© 2017 IEEE Computer Society. All rights reserved.Research was supported by Act 211 Government of the Russian Federation, agreement β 02.A03.21.0006 and Program of the RAS Presidium #I.33Π
Teaching Quality Assurances in Higher Education Institution: Competence-Based Approach
Use of research methods (analytic and synthetic, modeling, studying of psychology and pedagogical literature and products of activity) allowed researchers of the study to prove relevance of a problem of providing quality assurance of teaching in higher education institution on the basis of competence-based approach to be defined in concept of teaching quality assurance system to develop mechanisms, means, conditions, model of system realization. As the bases for development of teaching quality assurance system realization model the grounds of competence-based approach, the increasing requirements of the state, society, family and personality to education quality, their dissatisfaction with speed and adequacy of the happening changes ac
Thermochemistry of heteroatomic compounds X. The thermochemistry of solution and solvation of substituted alkylphosphonic derivatives
The enthalpies of vaporization of different classes of phosphorylated alcohols and amines were determined from their enthalpies of solution in hexane and carbon tetrachloride. The enthalpies of specific (hydrogen-bond) interaction with the solvents (chloroform and pyridine) of derivatives containing X-H groups (X=O or N) in the Ξ±-position to the P=O group were detemined. The results were explained in terms of the spatial structure of such compounds
Coping Responses During the COVID-19 Pandemic: A Cross-Cultural Comparison of Russia, Kyrgyzstan, and Peru
Background. The COVID-19 pandemic has subjected people around the world to severe stress, evoking a variety of coping responses. Coping responses can be broadly classified into four strategies: 1) problem-focused coping; 2) emotion-focused coping; 3) socially supported coping; and 4) avoidance. While there is a wide variability of individual coping responses, to some extent they are also culturally specific. Objective. This study aimed to compare the differences in the prevalence and factor structure of coping responses during COVID-19 pandemic in three countries: Russia, Kyrgyzstan, and Peru. Design. The sample included 501 participants from Russia, 456 participants from Kyrgyzstan, and 354 participants from Peru. The mean age of participants was 28 years in Russia (SD = 13.5); 24 years in Kyrgyzstan (SD = 10.0); and 30 years in Peru (SD = 12.3). In Russia and Kyrgyzstan, coping strategies were assessed with an abbreviated Russian adaptation of the COPE (Coping Orientations to Problems Experienced) questionnaire. In Peru, coping responses were assessed using the Spanish version of the Brief COPE questionnaire. The average scores from fifteen COPE scales were used as the input data for linear modelling and factor analysis. Results. The coping scores varied substantially within each country. Differences between countries accounted for 17.7% of the total variability in religious coping; 15.8% in acceptance; 13.9% in mental disengagement; and less than 7% in the other coping strategies. No difference in the prevalence of coping responses was found between Russian and Kyrgyz participants after accounting for age and gender. In all three countries the coping responses were associated with the same four coping domains: problem-focused coping, socially supported coping, avoidance, and emotion-focused coping. Four factors explained up to 44% of the total variation in the COPE scores. Religious coping and mental disengagement were classified into different coping domains in the three countries. Conclusion. The results suggest that during the COVID-19 pandemic, people from different countries apply the full range of coping responses within the four universal coping strategies. Religious coping and mental disengagement differed the most across the countries, suggesting that some coping behaviors can take on different roles within the system of coping responses to stressful events. We attribute these differences to differing cultural and socioeconomic characteristics, and the different measures taken by governments in response to COVID-19
ΠΠΊΡΠΏΡΠ΅ΡΡΠΈΡ ΠΏΡΠΎΠ²ΠΎΡΠΏΠ°Π»ΠΈΡΠ΅Π»ΡΠ½ΡΡ ΠΈ ΠΊΠΎΡΡΠΈΠΌΡΠ»ΠΈΡΡΡΡΠΈΡ ΠΌΠΎΠ»Π΅ΠΊΡΠ» Π½Π° ΠΌΠ°ΠΊΡΠΎΡΠ°Π³Π°Ρ in vitro Ρ Π±ΠΎΠ»ΡΠ½ΡΡ ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·ΠΎΠΌ Π»Π΅Π³ΠΊΠΈΡ
The aim of this study was to identify features of the expression of pro-inflammatory and co-stimulatory moleculesΒ on the surface of macrophages in vitro in patients with pulmonary tuberculosis, depending on the clinical form ofΒ the disease and sensitivity of the pathogen to anti-TB drugs.Materials and methods. 40 patients (36 men and 4 women) with pulmonary tuberculosis (TB) were examined:Β 18 patients (16 men and 2 women, average age (44.56 Β± 8.10) years) with disseminated tuberculosis (DTB) andΒ Β 22 patients (20 men and 2 women, average age (46.54 Β± 5.24) years) with infiltrative tuberculosis (ITB). Of those,Β 30 patients secreted Mycobacterium tuberculosis (MBT) sensitive to the basic anti-TB drugs (ATBD), and 10Β patients secreted MBT resistant to first-line anti-TB drugs. Venous blood was the study material. To isolateΒ monocytes from the whole blood in order to transform them into macrophages, ficoll density gradient centrifugationΒ with gradient density of 1.077 g/cm3 was used followed by immunomagnetic separation of CD14+ cells. MonocytesΒ were cultured in a complete culture medium X-VIVO 10 with gentamicin and phenol red with the addition of theΒ macrophage colony-stimulating factor (M-CSF) (5 ng/ml) at a concentration of 1Γ106 cells/ml with the followingΒ stimulators: interleukin (IL) 4 (10 ng/ml) and interferon (IFN) Ξ³ (100 ng/ml). Immunophenotyping of macrophagesΒ was performed using monoclonal antibodies to CD80, CD86, and HLA-DR on a Beckman Coulter CytoFLEX LXΒ flow cytometer (Beckman Coulter, USA). The analysis of the obtained data was carried out using the CytExpert 2.0Β software application. The results were analyzed using statistical methods.Results. The number of intact and cytokine-stimulated (IL-4 and IFNΞ³) CD80-positive macrophages in patientsΒ with ITB and drug-resistant TB (DR TB) exceeded their number not only in healthy donors, but also in patientsΒ with DTB and drug-sensitive TB (DS TB), respectively. In addition, an increase in CD86 expression on the surfaceΒ of macrophages was registered in patients with ITB and DR TB after adding IFNΞ³ (M1-activation inducer) to theΒ suspension culture. In contrast, in patients with DTB and DS TB, the number of macrophages with expression ofΒ B7 family co-stimulating molecules decreased or remained within the normal values in the absence of a reaction toΒ cytokines during cytokine induction. Deficiency of HLA-DR-positive macrophages was found in all TB patients.Β The minimal number of macrophages expressing HLA-DR was found in patients with DTB and DS TB after cellΒ incubation with IL-4 (M2-activation inducer).Conclusion. Evaluation of the expression of B7 (CD80/86) and HLA-DR membrane molecules on macrophages inΒ TB patients allows to conclude that anti-TB immune response is impaired at stages of antigen presentation (in allΒ examined patients with TB) and co-stimulation (in DTB and DS TB). An increase in the expression of macrophageΒ surface molecules CD80 (with M1- and M2-stimulation) and CD86 (with M1-stimulation) in patients with ITB andΒ DR TB indicates an increase in cell reactivity in these forms of TB. In addition, deficit of expression of HLA-DRΒ (a key marker of pro-inflammatory cell activation) on the surface of macrophages in TB can be considered as aΒ general (independent of the clinical form of the disease and drug sensitivity of the pathogen) pathogenetic factor ofΒ immune imbalance in pulmonary tuberculosis.Π¦Π΅Π»Ρ ΡΠ°Π±ΠΎΡΡ β ΡΡΡΠ°Π½ΠΎΠ²ΠΈΡΡ ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠΈ ΡΠΊΡΠΏΡΠ΅ΡΡΠΈΠΈ ΠΏΡΠΎΠ²ΠΎΡΠΏΠ°Π»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΠΈ ΠΊΠΎΡΡΠΈΠΌΡΠ»ΠΈΡΡΡΡΠΈΡ
ΠΌΠΎΠ»Π΅ΠΊΡΠ» Π½Π°Β ΠΌΠ°ΠΊΡΠΎΡΠ°Π³Π°Ρ
in vitro Ρ Π±ΠΎΠ»ΡΠ½ΡΡ
ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·ΠΎΠΌ Π»Π΅Π³ΠΊΠΈΡ
Π² Π·Π°Π²ΠΈΡΠΈΠΌΠΎΡΡΠΈ ΠΎΡ ΠΊΠ»ΠΈΠ½ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠΎΡΠΌΡ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΡ ΠΈΒ ΡΡΠ²ΡΡΠ²ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ Π²ΠΎΠ·Π±ΡΠ΄ΠΈΡΠ΅Π»Ρ ΠΊ ΠΏΡΠΎΡΠΈΠ²ΠΎΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·Π½ΡΠΌ Π»Π΅ΠΊΠ°ΡΡΡΠ²Π΅Π½Π½ΡΠΌ ΡΡΠ΅Π΄ΡΡΠ²Π°ΠΌ.ΠΠ°ΡΠ΅ΡΠΈΠ°Π»Ρ ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ. ΠΠ±ΡΠ»Π΅Π΄ΠΎΠ²Π°Π½Ρ 40 ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² (36 ΠΌΡΠΆΡΠΈΠ½ ΠΈ 4 ΠΆΠ΅Π½ΡΠΈΠ½Ρ): 18Β ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ Π΄ΠΈΡΡΠ΅ΠΌΠΈΠ½ΠΈΡΠΎΠ²Π°Π½Π½ΡΠΌ ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·ΠΎΠΌ Π»Π΅Π³ΠΊΠΈΡ
(ΠΠ’Π) (16 ΠΌΡΠΆΡΠΈΠ½ ΠΈ 2 ΠΆΠ΅Π½ΡΠΈΠ½Ρ,Β ΡΡΠ΅Π΄Π½ΠΈΠΉ Π²ΠΎΠ·ΡΠ°ΡΡ (44,56 Β± 8,10) Π»Π΅Ρ) ΠΈΒ 22 ΠΏΠ°ΡΠΈΠ΅Π½ΡΠ° Ρ ΠΈΠ½ΡΠΈΠ»ΡΡΡΠ°ΡΠΈΠ²Π½ΡΠΌ ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·ΠΎΠΌ Π»Π΅Π³ΠΊΠΈΡ
(ΠΠ’Π) (20 ΠΌΡΠΆΡΠΈΠ½ ΠΈ 2 ΠΆΠ΅Π½ΡΠΈΠ½Ρ, ΡΡΠ΅Π΄Π½ΠΈΠΉ Π²ΠΎΠ·ΡΠ°ΡΡΒ (46,54 Β± 5,24) Π»Π΅Ρ) c ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·ΠΎΠΌ Π»Π΅Π³ΠΊΠΈΡ
(Π’Π). ΠΠ· Π½ΠΈΡ
Π±ΡΠ»ΠΎ 30 ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ², Π²ΡΠ΄Π΅Π»ΡΡΡΠΈΡ
MycobacteriumΒ tuberculosis (MBT), ΡΡΠ²ΡΡΠ²ΠΈΡΠ΅Π»ΡΠ½ΡΠ΅ ΠΊ ΠΎΡΠ½ΠΎΠ²Π½ΡΠΌ ΠΏΡΠΎΡΠΈΠ²ΠΎΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·Π½ΡΠΌ ΡΡΠ΅Π΄ΡΡΠ²Π°ΠΌ (ΠΠ’Π‘), ΠΈ 10 ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ², Π²ΡΠ΄Π΅Π»ΡΡΡΠΈΡ
MBT, ΡΡΡΠΎΠΉΡΠΈΠ²ΡΠ΅ ΠΊ Π»Π΅ΠΊΠ°ΡΡΡΠ²Π΅Π½Π½ΡΠΌΒ ΡΡΠ΅Π΄ΡΡΠ²Π°ΠΌ ΠΎΡΠ½ΠΎΠ²Π½ΠΎΠ³ΠΎ ΡΡΠ΄Π° ΠΏΡΠΎΡΠΈΠ²ΠΎΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·Π½ΠΎΠΉΒ ΡΠ΅ΡΠ°ΠΏΠΈΠΈ. ΠΡΡΠΏΠΏΡ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ ΡΠΎΡΡΠ°Π²ΠΈΠ»ΠΈ 15 Π·Π΄ΠΎΡΠΎΠ²ΡΡ
Π΄ΠΎΠ½ΠΎΡΠΎΠ² Ρ ΡΠΎΠΏΠΎΡΡΠ°Π²ΠΈΠΌΡΠΌΠΈ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ°ΠΌΠΈ ΠΏΠΎ ΠΏΠΎΠ»ΡΒ ΠΈ Π²ΠΎΠ·ΡΠ°ΡΡΡ.ΠΠ°ΡΠ΅ΡΠΈΠ°Π»ΠΎΠΌ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠ²Π»ΡΠ»Π°ΡΡ Π²Π΅Π½ΠΎΠ·Π½Π°Ρ ΠΊΡΠΎΠ²Ρ. ΠΠ»Ρ Π²ΡΠ΄Π΅Π»Π΅Π½ΠΈΡ ΠΌΠΎΠ½ΠΎΡΠΈΡΠΎΠ² ΠΈΠ· ΡΠ΅Π»ΡΠ½ΠΎΠΉ ΠΊΡΠΎΠ²ΠΈ Ρ ΡΠ΅Π»ΡΡΒ ΠΈΡ
ΡΡΠ°Π½ΡΡΠΎΡΠΌΠ°ΡΠΈΠΈ Π² ΠΌΠ°ΠΊΡΠΎΡΠ°Π³ΠΈ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π»ΠΈ ΠΌΠ΅ΡΠΎΠ΄ ΡΠ΅Π½ΡΡΠΈΡΡΠ³ΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π² Π³ΡΠ°Π΄ΠΈΠ΅Π½ΡΠ΅ ΡΠΈΠΊΠΎΠ»Π»Π° ΠΏΠ»ΠΎΡΠ½ΠΎΡΡΡΡΒ 1,077 Π³/ΡΠΌ3 Ρ ΠΏΠΎΡΠ»Π΅Π΄ΡΡΡΠ΅ΠΉ ΠΈΠΌΠΌΡΠ½ΠΎΠΌΠ°Π³Π½ΠΈΡΠ½ΠΎΠΉ ΡΠ΅ΠΏΠ°ΡΠ°ΡΠΈΠ΅ΠΉ CD14+ ΠΊΠ»Π΅ΡΠΎΠΊ. ΠΠΎΠ½ΠΎΡΠΈΡΡ ΠΊΡΠ»ΡΡΠΈΠ²ΠΈΡΠΎΠ²Π°Π»ΠΈ Π²Β ΠΏΠΎΠ»Π½ΠΎΠΉ ΠΏΠΈΡΠ°ΡΠ΅Π»ΡΠ½ΠΎΠΉ ΡΡΠ΅Π΄Π΅ X-VIVO 10 Ρ Π΄ΠΎΠ±Π°Π²Π»Π΅Π½ΠΈΠ΅ΠΌ ΠΊΠΎΠ»ΠΎΠ½ΠΈΠ΅ΡΡΠΈΠΌΡΠ»ΠΈΡΡΡΡΠ΅Π³ΠΎ ΡΠ°ΠΊΡΠΎΡΠ° ΠΌΠ°ΠΊΡΠΎΡΠ°Π³ΠΎΠ² (M-CSF)Β (5 Π½Π³/ΠΌΠ») Π² ΠΊΠΎΠ½ΡΠ΅Π½ΡΡΠ°ΡΠΈΠΈ 1Γ106 ΠΊΠ»Π΅ΡΠΎΠΊ/ΠΌΠ» ΡΠΎ ΡΡΠΈΠΌΡΠ»ΡΡΠΎΡΠ°ΠΌΠΈ: ΠΈΠ½ΡΠ΅ΡΠ»Π΅ΠΉΠΊΠΈΠ½ΠΎΠΌ (IL) 4 (10 Π½Π³/ΠΌΠ») ΠΈ ΠΈΠ½ΡΠ΅ΡΡΠ΅ΡΠΎΠ½ΠΎΠΌΒ (IFN) Ξ³ (100 Π½Π³/ΠΌΠ»).Β ΠΠΌΠΌΡΠ½ΠΎΡΠ΅Π½ΠΎΡΠΈΠΏΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΠΌΠ°ΠΊΡΠΎΡΠ°Π³ΠΎΠ² ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΈ Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΠΌΠΎΠ½ΠΎΠΊΠ»ΠΎΠ½Π°Π»ΡΠ½ΡΡ
Π°Π½ΡΠΈΡΠ΅Π» ΠΊ CD80, CD86, HLA-DR Π½Π° ΠΏΡΠΎΡΠΎΡΠ½ΠΎΠΌ ΡΠΈΡΠΎΠΌΠ΅ΡΡΠ΅ Beckman Coulter CytoFLEX LX (Beckman Coulter,Β Π‘Π¨Π). ΠΠ½Π°Π»ΠΈΠ· ΠΏΠΎΠ»ΡΡΠ΅Π½Π½ΡΡ
Π΄Π°Π½Π½ΡΡ
ΠΎΡΡΡΠ΅ΡΡΠ²Π»ΡΠ»ΠΈ ΠΏΡΠΈ ΠΏΠΎΠΌΠΎΡΠΈ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½ΠΎΠ³ΠΎ ΠΏΡΠΈΠ»ΠΎΠΆΠ΅Π½ΠΈΡ CytExpert 2.0Β (Beckman Coulter, Π‘Π¨Π). ΠΠΎΠ»ΡΡΠ΅Π½Π½ΡΠ΅ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ Π°Π½Π°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π»ΠΈ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΠΌΠΈ ΠΌΠ΅ΡΠΎΠ΄Π°ΠΌΠΈ.Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. ΠΠΎΠ»ΠΈΡΠ΅ΡΡΠ²ΠΎ ΠΈΠ½ΡΠ°ΠΊΡΠ½ΡΡ
ΠΈ ΡΡΠΈΠΌΡΠ»ΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
ΡΠΈΡΠΎΠΊΠΈΠ½Π°ΠΌΠΈ (IL-4 ΠΈ IFNΞ³) CD80- ΠΏΠΎΠ·ΠΈΡΠΈΠ²Π½ΡΡ
ΠΌΠ°ΠΊΡΠΎΡΠ°Π³ΠΎΠ² Ρ Π±ΠΎΠ»ΡΠ½ΡΡ
ΠΠ’Π ΠΈ Ρ Π»Π΅ΠΊΠ°ΡΡΡΠ²Π΅Π½Π½ΠΎ-ΡΡΡΠΎΠΉΡΠΈΠ²ΡΠΌ Π’Π (ΠΠ£ Π’Π)Β ΠΏΡΠ΅Π²ΡΡΠ°Π»ΠΎ ΠΈΡ
ΡΠΈΡΠ»ΠΎ Π½Π΅ ΡΠΎΠ»ΡΠΊΠΎ Ρ Π·Π΄ΠΎΡΠΎΠ²ΡΡ
Β Π΄ΠΎΠ½ΠΎΡΠΎΠ², Π½ΠΎ ΠΈ Ρ Π±ΠΎΠ»ΡΠ½ΡΡ
ΠΠ’Π ΠΈ Ρ Π»Π΅ΠΊΠ°ΡΡΡΠ²Π΅Π½Π½ΠΎ-ΡΡΠ²ΡΡΠ²ΠΈΡΠ΅Π»ΡΠ½ΡΠΌ Π’Π (ΠΠ§ Π’Π) ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²Π΅Π½Π½ΠΎ. ΠΡΠΎΠΌΠ΅ ΡΠΎΠ³ΠΎ, ΡΒ Π±ΠΎΠ»ΡΠ½ΡΡ
ΠΠ’Π ΠΈ ΠΠ£ Π’Π ΡΠ΅Π³ΠΈΡΡΡΠΈΡΠΎΠ²Π°Π»ΠΎΡΡ ΠΏΠΎΠ²ΡΡΠ΅Π½ΠΈΠ΅ ΡΠΊΡΠΏΡΠ΅ΡΡΠΈΠΈ CD86 Π½Π° ΠΌΠ°ΠΊΡΠΎΡΠ°Π³Π°Ρ
ΠΏΠΎΡΠ»Π΅ Π΄ΠΎΠ±Π°Π²Π»Π΅Π½ΠΈΡ Π² ΡΡΡΠΏΠ΅Π½Π·ΠΈΠΎΠ½Π½ΡΡ ΠΊΡΠ»ΡΡΡΡΡ IFNΞ³ (ΠΈΠ½Π΄ΡΠΊΡΠΎΡ Π1-Π°ΠΊΡΠΈΠ²Π°ΡΠΈΠΈ). Π£ Π±ΠΎΠ»ΡΠ½ΡΡ
ΠΠ’Π ΠΈ ΠΠ§ Π’Π ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²ΠΎ ΠΌΠ°ΠΊΡΠΎΡΠ°Π³ΠΎΠ²Β Ρ ΡΠΊΡΠΏΡΠ΅ΡΡΠΈΠ΅ΠΉ ΠΊΠΎΡΡΠΈΠΌΡΠ»ΠΈΡΡΡΡΠΈΡ
ΠΌΠΎΠ»Π΅ΠΊΡΠ» ΡΠ΅ΠΌΠ΅ΠΉΡΡΠ²Π° Π7 ΠΏΡΠΈ ΠΈΠ½Π΄ΡΠΊΡΠΈΠΈ ΡΠΈΡΠΎΠΊΠΈΠ½Π°ΠΌΠΈ, Π½Π°ΠΏΡΠΎΡΠΈΠ², ΡΠ½ΠΈΠΆΠ°Π»ΠΎΡΡΒ ΠΈΠ»ΠΈ ΡΠΎΡ
ΡΠ°Π½ΡΠ»ΠΎΡΡ Π² ΠΏΡΠ΅Π΄Π΅Π»Π°Ρ
Π½ΠΎΡΠΌΡ Π² ΠΎΡΡΡΡΡΡΠ²ΠΈΠ΅ ΡΠ΅Π°ΠΊΡΠΈΠΈ Π½Π° ΡΠΈΡΠΎΠΊΠΈΠ½Ρ. ΠΠ΅ΡΠΈΡΠΈΡ HLA-DR-ΠΏΠΎΠ·ΠΈΡΠΈΠ²Π½ΡΡ
Β ΠΌΠ°ΠΊΡΠΎΡΠ°Π³ΠΎΠ² ΠΎΠ±Π½Π°ΡΡΠΆΠΈΠ²Π°Π»ΡΡ Ρ Π²ΡΠ΅Ρ
Π±ΠΎΠ»ΡΠ½ΡΡ
Π’Π. ΠΠΈΠ½ΠΈΠΌΠ°Π»ΡΠ½ΠΎΠ΅ ΡΠΈΡΠ»ΠΎ ΠΌΠ°ΠΊΡΠΎΡΠ°Π³ΠΎΠ², ΡΠΊΡΠΏΡΠ΅ΡΡΠΈΡΡΡΡΠΈΡ
Β HLADR, ΡΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½ΠΎ Ρ Π±ΠΎΠ»ΡΠ½ΡΡ
ΠΠ’Π ΠΈ ΠΠ§ Π’Π ΠΏΠΎΡΠ»Π΅ ΠΈΠ½ΠΊΡΠ±Π°ΡΠΈΠΈ ΠΊΠ»Π΅ΡΠΎΠΊ Ρ IL-4 (ΠΈΠ½Π΄ΡΠΊΡΠΎΡΒ Π2-Π°ΠΊΡΠΈΠ²Π°ΡΠΈΠΈ).ΠΠ°ΠΊΠ»ΡΡΠ΅Π½ΠΈΠ΅. ΠΡΠ΅Π½ΠΊΠ° ΡΠΊΡΠΏΡΠ΅ΡΡΠΈΠΈ ΠΌΠ΅ΠΌΠ±ΡΠ°Π½Π½ΡΡ
ΠΌΠΎΠ»Π΅ΠΊΡΠ» B7 (CD80/86) ΠΈ HLA-DR Π½Π° ΠΌΠ°ΠΊΡΠΎΡΠ°Π³Π°Ρ
Ρ Π±ΠΎΠ»ΡΠ½ΡΡ
Β Π’Π ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ ΡΠ΄Π΅Π»Π°ΡΡ Π²ΡΠ²ΠΎΠ΄ ΠΎ Π½Π°ΡΡΡΠ΅Π½ΠΈΡΡ
Β ΠΏΡΠΎΡΠΈΠ²ΠΎΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·Π½ΠΎΠ³ΠΎ ΠΈΠΌΠΌΡΠ½Π½ΠΎΠ³ΠΎ ΠΎΡΠ²Π΅ΡΠ° Π½Π° ΡΡΠ°Π΄ΠΈΠΈ ΠΏΡΠ΅Π·Π΅Π½ΡΠ°ΡΠΈΠΈΒ Π°Π½ΡΠΈΠ³Π΅Π½Π° (Ρ Π²ΡΠ΅Ρ
ΠΎΠ±ΡΠ»Π΅Π΄ΠΎΠ²Π°Π½Π½ΡΡ
Π±ΠΎΠ»ΡΠ½ΡΡ
Π’Π) ΠΈ ΠΊΠΎΡΡΠΈΠΌΡΠ»ΡΡΠΈΠΈ (ΠΏΡΠΈ ΠΠ’Π ΠΈ ΠΠ§ Π’Π). Π£Π²Π΅Π»ΠΈΡΠ΅Π½ΠΈΠ΅ ΡΠΊΡΠΏΡΠ΅ΡΡΠΈΠΈΒ ΠΌΠ°ΠΊΡΠΎΡΠ°Π³Π°ΠΌΠΈ ΠΏΠΎΠ²Π΅ΡΡ
Π½ΠΎΡΡΠ½ΡΡ
ΠΌΠΎΠ»Π΅ΠΊΡΠ» CD80 (ΠΏΡΠΈ Π1- ΠΈ Π2-ΡΡΠΈΠΌΡΠ»ΡΡΠΈΠΈ) ΠΈΒ CD86 (ΠΏΡΠΈ Π1-ΡΡΠΈΠΌΡΠ»ΡΡΠΈΠΈ) ΡΒ Π±ΠΎΠ»ΡΠ½ΡΡ
ΠΠ’Π ΠΈ ΠΠ£ Π’Π ΡΠ²ΠΈΠ΄Π΅ΡΠ΅Π»ΡΡΡΠ²ΡΠ΅Ρ ΠΎ ΠΏΠΎΠ²ΡΡΠ΅Π½ΠΈΠΈ ΡΠ΅Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ ΠΊΠ»Π΅ΡΠΎΠΊ ΠΏΡΠΈ Π΄Π°Π½Π½ΡΡ
ΡΠΎΡΠΌΠ°Ρ
ΡΠ΅ΡΠ΅Π½ΠΈΡ Π’Π.Β ΠΠ°ΡΡΠ΄Ρ Ρ ΡΡΠΈΠΌ Π΄Π΅ΡΠΈΡΠΈΡ ΡΠΊΡΠΏΡΠ΅ΡΡΠΈΠΈ Π½Π° ΠΌΠ°ΠΊΡΠΎΡΠ°Π³Π°Ρ
HLA-DR (ΠΊΠ»ΡΡΠ΅Π²ΠΎΠ³ΠΎ ΠΌΠ°ΡΠΊΠ΅ΡΠ° ΠΏΡΠΎΠ²ΠΎΡΠΏΠ°Π»ΠΈΡΠ΅Π»ΡΠ½ΠΎΠΉ Π°ΠΊΡΠΈΠ²Π°ΡΠΈΠΈΒ ΠΊΠ»Π΅ΡΠΎΠΊ) ΠΏΡΠΈ Π’Π ΠΌΠΎΠΆΠ½ΠΎ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°ΡΡ ΠΊΠ°ΠΊ ΠΎΠ±ΡΠΈΠΉ (Π½Π΅ Π·Π°Π²ΠΈΡΡΡΠΈΠΉ ΠΎΡ ΠΊΠ»ΠΈΠ½ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠΎΡΠΌΡ Π±ΠΎΠ»Π΅Π·Π½ΠΈ ΠΈΒ Π»Π΅ΠΊΠ°ΡΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΡΡΠ²ΡΡΠ²ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ Π²ΠΎΠ·Π±ΡΠ΄ΠΈΡΠ΅Π»Ρ) ΠΏΠ°ΡΠΎΠ³Π΅Π½Π΅ΡΠΈΡΠ΅ΡΠΊΠΈΠΉ ΡΠ°ΠΊΡΠΎΡ ΠΈΠΌΠΌΡΠ½Π½ΠΎΠ³ΠΎΒ Π΄ΠΈΡΠ±Π°Π»Π°Π½ΡΠ° ΠΏΡΠΈ ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·Π΅ Π»Π΅Π³ΠΊΠΈΡ
.
Coping Responses During the COVID-19 Pandemic: A Cross-Cultural Comparison of Russia, Kyrgyzstan, and Peru
Background. The COVID-19 pandemic has subjected people around the world to severe stress, evoking a variety of coping responses. Coping responses can be broadly classified into four strategies: 1) problem-focused coping; 2) emotion-focused coping; 3) socially supported coping; and 4) avoidance. While there is a wide variability of individual coping responses, to some extent they are also culturally specific. Objective. This study aimed to compare the differences in the prevalence and factor structure of coping responses during COVID-19 pandemic in three countries: Russia, Kyrgyzstan, and Peru. Design. The sample included 501 participants from Russia, 456 participants from Kyrgyzstan, and 354 participants from Peru. The mean age of participants was 28 years in Russia (SD = 13.5); 24 years in Kyrgyzstan (SD = 10.0); and 30 years in Peru (SD = 12.3). In Russia and Kyrgyzstan, coping strategies were assessed with an abbreviated Russian adaptation of the COPE (Coping Orientations to Problems Experienced) questionnaire. In Peru, coping responses were assessed using the Spanish version of the Brief COPE questionnaire. The average scores from fifteen COPE scales were used as the input data for linear modelling and factor analysis. Results. The coping scores varied substantially within each country. Differences between countries accounted for 17.7% of the total variability in religious coping; 15.8% in acceptance; 13.9% in mental disengagement; and less than 7% in the other coping strategies. No difference in the prevalence of coping responses was found between Russian and Kyrgyz participants after accounting for age and gender. In all three countries the coping responses were associated with the same four coping domains: problem-focused coping, socially supported coping, avoidance, and emotion-focused coping. Four factors explained up to 44% of the total variation in the COPE scores. Religious coping and mental disengagement were classified into different coping domains in the three countries. Conclusion. The results suggest that during the COVID-19 pandemic, people from different countries apply the full range of coping responses within the four universal coping strategies. Religious coping and mental disengagement differed the most across the countries, suggesting that some coping behaviors can take on different roles within the system of coping responses to stressful events. We attribute these differences to differing cultural and socioeconomic characteristics, and the different measures taken by governments in response to COVID-19. Β© 2020. Lomonosov Moscow State University. All Rights Reserved.is study was supported by Russian Foundation for Basic Research (Project No. 20-04-60394)
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