506 research outputs found
36 Months Survivability And Its Predictors In Patients With Chronic Heart Failure And Decreased Fraction Of Left Ventricular Ejection Depending On Sex
Aim of the work: to compare survivability parameters during 36 months and their predictors among men and women with chronic heart failure and decreased fraction of left ventricular ejection.Materials and methods: the research included 356 patients with CHF (NYHA ΠΠ βΠV) with decreased LVEF<40 %, 18β75 years old. Using Kaplan-Meier method, there was analyzed the survivability in men and women during 36 months, then there were analyzed independent factors that influenced survivability terms depending on sex using the multiple logistic regression.Results. Our analysis of the survivability of patients with CHF with decreased LVEF demonstrated that the cumulative survival after 3 years of observation was 49 and 51 % for men and women, respectively. The curves of 36 months survivability didn\u27t reliably differ. At the analysis of factors, associated with the bad prognosis, there were observed differences between groups of men and women with CHF. Thus, in men the predictors of 36 month survival were: the thickness of the right ventricle wall, size of the right atrium, end-diastolic volume and end-systolic volume of LV, indices of EDV and ESV of LV, urinary acid level, value of LVEF. In women the predictors of survivability during 3 years were the following parameters: BMI, DM type 2 in an anamnesis, end-diastolic size of LV, end-systolic size of LV, blood glucose level, LVEF.Conclusion. The survivability of men and women with CHF with decreased LVEF during 36 months didn\u27t reliably differ and was 49 and 51 % respectively. But predictors of the lethal outcome in men and women essentially differed during 36 months, and their number is essentially higher in men
Climate variation influences host specificity in avian malaria parasites
Parasites with low host specificity (e.g. infecting a large diversity of host species) are of special
interest in disease ecology, as they are likely more capable of circumventing ecological or
evolutionary barriers to infect new hosts than are specialist parasites. Yet for many parasites,
host specificity is not fixed and can vary in response to environmental conditions. Using data on
host associations for avian malaria parasites (Apicomplexa: Haemosporida), we develop a
hierarchical model that quantifies this environmental dependency by partitioning host specificity
variation into region- and parasite-level effects. Parasites were generally phylogenetic host
specialists, infecting phylogenetically clustered subsets of available avian hosts. However, the
magnitude of this specialization varied biogeographically, with parasites exhibiting higher host
specificity in regions with more pronounced rainfall seasonality and wetter dry seasons.
Recognizing the environmental dependency of parasite specialization can provide useful
leverage for improving predictions of infection risk in response to global climate change
Comparing the mitochondrial genomes of Wolbachia-dependent and independent filarial nematode species
BACKGROUND: Many species of filarial nematodes depend on Wolbachia endobacteria to carry out their life cycle. Other species are naturally Wolbachia-free. The biological mechanisms underpinning Wolbachia-dependence and independence in filarial nematodes are not known. Previous studies have indicated that Wolbachia have an impact on mitochondrial gene expression, which may suggest a role in energy metabolism. If Wolbachia can supplement host energy metabolism, reduced mitochondrial function in infected filarial species may account for Wolbachia-dependence. Wolbachia also have a strong influence on mitochondrial evolution due to vertical co-transmission. This could drive alterations in mitochondrial genome sequence in infected species. Comparisons between the mitochondrial genome sequences of Wolbachia-dependent and independent filarial worms may reveal differences indicative of altered mitochondrial function. RESULTS: The mitochondrial genomes of 5 species of filarial nematodes, Acanthocheilonema viteae, Chandlerella quiscali, Loa loa, Onchocerca flexuosa, and Wuchereria bancrofti, were sequenced, annotated and compared with available mitochondrial genome sequences from Brugia malayi, Dirofilaria immitis, Onchocerca volvulus and Setaria digitata. B. malayi, D. immitis, O. volvulus and W. bancrofti are Wolbachia-dependent while A. viteae, C. quiscali, L. loa, O. flexuosa and S. digitata are Wolbachia-free. The 9 mitochondrial genomes were similar in size and AT content and encoded the same 12 protein-coding genes, 22 tRNAs and 2 rRNAs. Synteny was perfectly preserved in all species except C. quiscali, which had a different order for 5 tRNA genes. Protein-coding genes were expressed at the RNA level in all examined species. In phylogenetic trees based on mitochondrial protein-coding sequences, species did not cluster according to Wolbachia dependence. CONCLUSIONS: Thus far, no discernable differences were detected between the mitochondrial genome sequences of Wolbachia-dependent and independent species. Additional research will be needed to determine whether mitochondria from Wolbachia-dependent filarial species show reduced function in comparison to the mitochondria of Wolbachia-independent species despite their sequence-level similarities
Treatment and prevention of arresive bleeding in patients with pancreonecrosis.
The article is devoted to the study of acute necrotizing pancreatitis, which leads to the development of various fluid pathologies different in pathogenesis and time, which in turn can lead to an arrosive bleeding. Diagnostic-treatment ispresented algorithm with the active use of modern methods of hemostasis in patients with arrosive bleeding developed against the background of pancreatonecrosis
Treatment and prevention of arresive bleeding in patients with pancreonecrosis.
The article is devoted to the study of acute necrotizing pancreatitis, which leads to the development of various fluid pathologies different in pathogenesis and time, which in turn can lead to an arrosive bleeding. Diagnostic-treatment ispresented algorithm with the active use of modern methods of hemostasis in patients with arrosive bleeding developed against the background of pancreatonecrosis
ΠΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ Π΄Π²ΠΈΠΆΠ΅Π½ΠΈΡ Π°Π½ΡΡΠΎΠΏΠΎΠΌΠΎΡΡΠ½ΠΎΠ³ΠΎ ΡΠ°Π³Π°ΡΡΠ΅Π³ΠΎ Π°ΠΏΠΏΠ°ΡΠ°ΡΠ° Π½Π° ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ»ΡΠ½ΠΎΠΉ ΡΠ²Π΅ΡΠ΄ΠΎΠΉ ΠΏΠΎΠ²Π΅ΡΡ Π½ΠΎΡΡΠΈ
Π£ ΡΠΎΠ±ΠΎΡΡ ΠΎΡΠ½ΠΎΠ²Π½Ρ ΡΠ²Π°Π³Ρ ΠΏΡΠΈΠ΄ΡΠ»Π΅Π½ΠΎ ΠΌΠΎΠ΄Π΅Π»ΡΠ²Π°Π½Π½Ρ Ρ
ΠΎΠ΄ΠΈ ΠΠΠ Π±Π΅Π· Π·ΡΡΠΊΠ½Π΅Π½Π½Ρ Π· ΠΏΠΎΠ²Π΅ΡΡ
Π½Π΅Ρ ΠΏΡΠ΄ ΡΠ°Ρ ΠΏΠ΅ΡΠ΅ΠΌΡΡΠ΅Π½Π½Ρ ΡΡ
ΠΈΠ»ΠΎΠΌ ΡΠΈ ΠΏΡΠ΄ΠΉΠΎΠΌΠΎΠΌ, ΡΠΎ Π°ΠΊΡΡΠ°Π»ΡΠ½ΠΎ Π΄Π»Ρ Π·Π°Π΄Π°ΡΡ ΠΏΠΎΠ±ΡΠ΄ΠΎΠ²ΠΈ ΠΊΡΠΎΠΊΡΡΡΠΈΡ
ΡΠΈΡΡΠ΅ΠΌΠΈ Π½Π° ΠΎΡΠ½ΠΎΠ²Ρ Π°Π½ΡΡΠΎΠΏΠ½ΠΎΠ³ΠΎ ΠΏΡΠΈΠ½ΡΠΈΠΏΡ. ΠΠ»Ρ ΡΠ΅Π°Π»ΡΠ·Π°ΡΡΡ Π°Π½ΡΡΠΎΠΏΠΎΠΌΠΎΡΡΠ½ΠΎΠ³ΠΎ ΠΏΠ΅ΡΠ΅ΠΌΡΡΠ΅Π½Π½Ρ, Ρ Π΄ΠΎΡΠ»ΡΠ΄ΠΆΠ΅Π½Π½Ρ Π·Π°ΡΡΠΎΡΠΎΠ²ΡΠ²Π°Π»ΠΈΡΡ ΠΏΡΠΈΠ½ΡΠΈΠΏΠΈ Π·Π²ΠΎΡΠΎΡΠ½ΡΠΎΡ Π΄ΠΈΠ½Π°ΠΌΡΠΊΠΈ ΡΠ° ΠΊΡΠ½Π΅ΠΌΠ°ΡΠΈΠΊΠΈ ΡΡΡ
Ρ Π±Π°Π³Π°ΡΠΎΠ»Π°Π½ΠΊΠΎΠ²ΠΎΡ ΡΠΈΡΡΠ΅ΠΌΠΈ. Π ΠΎΠ·Π³Π»ΡΠ΄ Π΅Π½Π΅ΡΠ³ΠΎΠ΅ΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ Π·Π΄ΡΠΉΡΠ½ΡΠ²Π°Π²ΡΡ ΠΏΠΎΡΡΠ²Π½ΡΠ½Π½ΡΠΌ Π΅Π½Π΅ΡΠ³ΠΎΠ·Π°ΡΡΠ°ΡΠ½ΠΎΡΡΡ Π΄ΠΎ ΠΏΡΠΎΠ΄ΡΠΊΡΠΈΠ²Π½ΠΎΡΡΡ ΠΏΠ΅ΡΠ΅ΠΌΡΡΠ΅Π½Π½Ρ.This paper focuses on the modeling approaches AKA without contact with the surface when moving or lifting the hill, which is important for the task of building a walking system based on the anthropic principle. To implement an anthropomorphic moving, the study applied the principles of inverse dynamics and kinematics multi-tier system. Consideration of energy efficiency are compared to the performance of energy-consuming travel.Π ΡΠ°Π±ΠΎΡΠ΅ ΠΎΡΠ½ΠΎΠ²Π½ΠΎΠ΅ Π²Π½ΠΈΠΌΠ°Π½ΠΈΠ΅ ΡΠ΄Π΅Π»Π΅Π½ΠΎ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ Ρ
ΠΎΠ΄Ρ ΠΠΠ Π±Π΅Π· ΡΠΎΠΏΡΠΈΠΊΠΎΡΠ½ΠΎΠ²Π΅Π½ΠΈΡ Ρ ΠΏΠΎΠ²Π΅ΡΡ
Π½ΠΎΡΡΡΡ ΠΏΡΠΈ ΠΏΠ΅ΡΠ΅ΠΌΠ΅ΡΠ΅Π½ΠΈΠΈ ΠΏΠΎ ΡΠΊΠ»ΠΎΠ½Ρ ΠΈΠ»ΠΈ ΠΏΠΎΠ΄ΡΠ΅ΠΌΠΎΠΌ, ΡΡΠΎ Π°ΠΊΡΡΠ°Π»ΡΠ½ΠΎ Π΄Π»Ρ Π·Π°Π΄Π°ΡΠΈ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΡ ΡΠ°Π³Π°ΡΡΠΈΡ
ΡΠΈΡΡΠ΅ΠΌΡ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ Π°Π½ΡΡΠΎΠΏΠ½ΠΎΠ³ΠΎ ΠΏΡΠΈΠ½ΡΠΈΠΏΠ°. ΠΠ»Ρ ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΠΈ Π°Π½ΡΡΠΎΠΏΠΎΠΌΠΎΡΡΠ½ΠΎΠ³ΠΎ ΠΏΠ΅ΡΠ΅ΠΌΠ΅ΡΠ΅Π½ΠΈΡ, Π² ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΈ ΠΏΡΠΈΠΌΠ΅Π½ΡΠ»ΠΈΡΡ ΠΏΡΠΈΠ½ΡΠΈΠΏΡ ΠΎΠ±ΡΠ°ΡΠ½ΠΎΠΉ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠΈ ΠΈ ΠΊΠΈΠ½Π΅ΠΌΠ°ΡΠΈΠΊΠΈ Π΄Π²ΠΈΠΆΠ΅Π½ΠΈΡ ΠΌΠ½ΠΎΠ³ΠΎΠ·Π²Π΅Π½Π½ΠΎΠΉ ΡΠΈΡΡΠ΅ΠΌΡ. Π Π°ΡΡΠΌΠΎΡΡΠ΅Π½ΠΈΠ΅ ΡΠ½Π΅ΡΠ³ΠΎΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ ΠΎΡΡΡΠ΅ΡΡΠ²Π»ΡΠ»ΡΡ ΡΡΠ°Π²Π½Π΅Π½ΠΈΠ΅ΠΌ ΡΠ½Π΅ΡΠ³ΠΎΠ·Π°ΡΡΠ°ΡΠ½ΠΎΡΡΠΈ ΠΊ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ ΠΏΠ΅ΡΠ΅ΠΌΠ΅ΡΠ΅Π½ΠΈΡ
Contribution of chromosomal abnormalities and genes of the major histocompatibility complex to early pregnancy losses
Aim. The determination of chromosomal abnormalities in samples from early pregnancy losses and allelic polymorphism of HLAβDRB1 and DQA1 genes in couples with recurrent miscarriage. Methods. Banding cytogenetic and interphase mFISH analysis, DNA extraction by salting method, PCR, agarose gel electrophoresis. Results. Cytogenetic and molecular-cytogenetic investigations of SA material identified karyotype anomalies in 32.4 % of cases with prevalence of autosomal trisomy β 42.65 %, triploidy β 30.38 % and monosomy X β 19.11 %. Complex analysis of frequency and distribution of allelic variants of genes HLA-DRB1 and HLA-DQA1 allowed establishing the alleles DRB1*0301, DRB1*1101-1104 and DQA1*0501 to be aggressor alleles in women with recurrent pregnancy loss (RPL). The cumulative homology of allelic polymorphism of more than 50 % of HLA-DRB1 and HLA-DQA1 loci between partners increases the risk of RPL by almost four times. Conclusion. The detected chromosome aneuploidies in the samples from products of conception and the changes in the major histocompatibility complex genes can cause the failure of a couples reproductive function and can lead to an early fetal loss.ΠΠ΅ΡΠ°. ΠΡΡΠ°Π½ΠΎΠ²ΠΈΡΠΈ Ρ
ΡΠΎΠΌΠΎΡΠΎΠΌΠ½Ρ Π°Π½ΠΎΠΌΠ°Π»ΡΡ Ρ ΠΌΠ°ΡΠ΅ΡΡΠ°Π»Ρ ΡΠ°Π½Π½ΡΡ
ΡΠ΅ΠΏΡΠΎΠ΄ΡΠΊΡΠΈΠ²Π½ΠΈΡ
Π²ΡΡΠ°Ρ Ρ Π°Π»Π΅Π»ΡΠ½ΠΈΠΉ ΠΏΠΎΠ»ΡΠΌΠΎΡΡΡΠ·ΠΌ Π³Π΅Π½ΡΠ² HLA β DRB1 Ρ DQA1 Ρ ΠΏΠΎΠ΄ΡΡΠΆΠ½ΡΡ
ΠΏΠ°Ρ ΡΠ· Π½Π°Π²ΠΈΠΊΠΎΠ²ΠΈΠΌ Π½Π΅Π²ΠΈΠ½ΠΎΡΡΠ²Π°Π½Π½ΡΠΌ Π²Π°Π³ΡΡΠ½ΠΎΡΡΡ. ΠΠ΅ΡΠΎΠ΄ΠΈ. Π‘ΡΠ°Π½Π΄Π°ΡΡΠ½ΠΈΠΉ ΡΠΈΡΠΎΠ³Π΅Π½Π΅ΡΠΈΡΠ½ΠΈΠΉ ΡΠ° ΡΠ½ΡΠ΅ΡΡΠ°Π·Π½ΠΈΠΉ mFISH ΠΌΠ΅ΡΠΎΠ΄ΠΈ, Π²ΠΈΠ΄ΡΠ»Π΅Π½Π½Ρ ΠΠΠ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ Π²ΠΈΡΠΎΠ»ΡΠ²Π°Π½Π½Ρ, ΠΠΠ , Π΅Π»Π΅ΠΊΡΡΠΎΡΠΎΡΠ΅Π· Π² Π°Π³Π°ΡΠΎΠ·Π½ΠΎΠΌΡ Π³Π΅Π»Ρ. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΠΈ. Π¦ΠΈΡΠΎΠ³Π΅Π½Π΅ΡΠΈΡΠ½Ρ ΡΠ° ΠΌΠΎΠ»Π΅ΠΊΡΒΠ»ΡΡΠ½ΠΎ-ΡΠΈΡΠΎΠ³Π΅Π½Π΅ΡΠΈΡΠ½Ρ Π΄ΠΎΡΠ»ΡΠ΄ΠΆΠ΅Π½Ρ ΠΌΠ°ΡΠ΅ΡΡΠ°Π»Ρ Π²ΡΡΠ°ΡΠ΅Π½ΠΈΡ
Π²Π°Π³ΡΡΠ½ΠΎΡΡΠ΅ΠΉ ΠΏΠΎΠΊΠ°Π·Π°Π»ΠΈ Π°Π½ΠΎΠΌΠ°Π»ΡΡ ΠΊΠ°ΡΡΠΎΡΠΈΠΏΡ Π² 32.4 % Π²ΠΈΠΏΠ°Π΄ΠΊΠ°Ρ
Π· ΠΏΠ΅ΡΠ΅Π²Π°ΠΆΠ°Π½Π½ΡΠΌ Π°ΡΡΠΎΡΠΎΠΌΠ½ΠΈΡ
ΡΡΠΈΡΠΎΠΌΡΠΉ β 42.65 %, ΡΡΠΈΠΏΠ»ΠΎΡΠ΄ΡΠΉ β 30.38 % Ρ ΠΌΠΎΠ½ΠΎΡΠΎΠΌΡΡ X β 19.11 %. ΠΠΎΠΌΠΏΠ»Π΅ΠΊΡΠ½ΠΈΠΉ Π°Π½Π°Π»ΡΠ· ΡΠ°ΡΡΠΎΡΠΈ Ρ ΡΠΎΠ·ΠΏΠΎΠ΄ΡΠ»Ρ Π°Π»Π΅Π»ΡΠ½ΠΈΡ
Π²Π°ΡΡΠ°Π½ΡΡΠ² Π³Π΅Π½ΡΠ² HLA-DRB1 Ρ HLA-DQA1 Π΄ΠΎΠ·Π²ΠΎΠ»ΠΈΠ² Π²ΡΡΠ°Π½ΠΎΠ²ΠΈΡΠΈ, ΡΠΎ DRB1*0301, DRB1*1101-1104 Ρ DQA1*0501 Ρ Π°Π»Π΅Π»ΡΠΌΠΈ-Π°Π³ΡΠ΅ΡΠΎΡΠ°ΠΌΠΈ Ρ ΠΆΡΠ½ΠΎΠΊ ΡΠ· ΡΠ°Π½Π½ΡΠΌΠΈ ΡΠ΅ΠΏΡΠΎΠ΄ΡΠΊΡΠΈΠ²Π½ΠΈΠΌΠΈ Π²ΡΡΠ°ΡΠ°ΠΌΠΈ (Π Π Π). Π‘ΡΠΊΡΠΏΠ½Π° Π³ΠΎΠΌΠΎΠ»ΠΎΠ³ΡΡ Π°Π»Π΅Π»ΡΠ½ΠΎΠ³ΠΎ ΠΏΠΎΠ»ΡΠΌΠΎΡΡΡΠ·ΠΌΡ Π»ΠΎΠΊΡΡΡΠ² HLA-DRB1 Ρ HLA-DQA1 Π±ΡΠ»ΡΡΠ΅ 50 % ΠΌΡΠΆ ΠΏΠ°ΡΡΠ½Π΅ΡΠ°ΠΌΠΈ Π·Π±ΡΠ»ΡΡΡΡ ΡΠΈΠ·ΠΈΠΊ Π Π Π ΠΌΠ°ΠΉΠΆΠ΅ Π² ΡΠΎΡΠΈΡΠΈ ΡΠ°Π·ΠΈ. ΠΠΈΡΠ½ΠΎΠ²ΠΊΠΈ. ΠΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½Ρ Ρ
ΡΠΎΠΌΠΎΡΠΎΠΌΠ½Ρ Π°Π½Π΅ΡΠΏΠ»ΠΎΡΠ΄ΡΡ Π² ΠΌΠ°ΡΠ΅ΡΡΠ°Π»Ρ Π²ΡΡΠ°ΡΠ΅Π½ΠΈΡ
Π²Π°Π³ΡΡΠ½ΠΎΡΡΠ΅ΠΉ ΡΠ° Π·ΠΌΡΠ½ΠΈ Π² Π³Π΅Π½Π°Ρ
Π³ΠΎΠ»ΠΎΠ²Π½ΠΎΠ³ΠΎ ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠ° Π³ΡΡΡΠΎΡΡΠΌΡΡΡΠ½ΠΎΡΡΡ Ρ ΠΏΠΎΠ΄ΡΡΠΆΠ½ΡΡ
ΠΏΠ°Ρ ΠΌΠΎΠΆΡΡΡ Π²ΠΈΠΊΠ»ΠΈΠΊΠ°ΡΠΈ ΠΏΠΎΡΡΡΠ΅Π½Π½Ρ ΡΠ΅ΠΏΡΠΎΠ΄ΡΠΊΡΠΈΠ²Π½ΠΎΡ ΡΡΠ½ΠΊΡΡΡ ΡΠ° ΡΠ°Π½Π½Ρ Π΅Π»ΡΠΌΡΠ½Π°ΡΡΡ ΠΏΠ»ΠΎΠ΄Π°.Π¦Π΅Π»Ρ. ΠΈΠ·ΡΡΠΈΡΡ Ρ
ΡΠΎΠΌΠΎΡΠΎΠΌΠ½ΡΠ΅ Π°Π½ΠΎΠΌΠ°Π»ΠΈΠΈ Π² Π±ΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠΌ ΠΌΠ°ΡΠ΅ΡΠΈΠ°Π»Π΅ ΡΠ°Π½Π½ΠΈΡ
ΡΠ΅ΠΏΡΠΎΠ΄ΡΠΊΡΠΈΠ²Π½ΡΡ
ΠΏΠΎΡΠ΅ΡΡ ΠΈ Π°Π»Π»Π΅Π»ΡΠ½ΡΠΉ ΠΏΠΎΠ»ΠΈΠΌΠΎΡΡΠΈΠ·ΠΌ Π³Π΅Π½ΠΎΠ² HLA β DRB1 ΠΈ DQA1 Ρ ΡΡΠΏΡΡΠΆΠ΅ΡΠΊΠΈΡ
ΠΏΠ°Ρ Ρ ΠΏΡΠΈΠ²ΡΡΠ½ΡΠΌ Π½Π΅Π²ΡΠ½Π°ΡΠΈΠ²Π°Π½ΠΈΠ΅ΠΌ Π±Π΅ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΡΡΠΈ. ΠΠ΅ΡΠΎΠ΄Ρ. ΡΡΠ°Π½ΒΠ΄Π°ΡΡΠ½ΡΠΉ ΡΠΈΡΠΎΠ³Π΅Π½Π΅ΡΠΈΡΠ΅ΡΠΊΠΈΠΉ ΠΈ ΠΈΠ½ΡΠ΅ΡΡΠ°Π·Π½ΡΠΉ mFISH ΠΌΠ΅ΡΠΎΠ΄Ρ, Π²ΡΠ΄Π΅Π»Π΅Π½ΠΈΠ΅ ΠΠΠ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ Π²ΡΡΠ°Π»ΠΈΠ²Π°Π½ΠΈΡ, ΠΠ¦Π , ΡΠ»Π΅ΠΊΡΡΠΎΡΠΎΡΠ΅Π· Π² Π°Π³Π°ΡΠΎΠ·Π½ΠΎΠΌ Π³Π΅Π»Π΅. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. ΠΡΠΎΠ²Π΅Π΄Π΅Π½Π½ΡΠ΅ ΡΠΈΡΠΎΠ³Π΅Π½Π΅ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΈ ΠΌΠΎΠ»Π΅ΠΊΡΠ»ΡΡΠ½ΠΎ-ΡΠΈΡΠΎΠ³Π΅Π½Π΅ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ ΠΌΠ°ΡΠ΅ΡΠΈΠ°Π»Π° ΡΠ°Π½Π½ΠΈΡ
ΡΠ΅ΠΏΡΠΎΠ΄ΡΠΊΡΠΈΠ²Π½ΡΡ
ΠΏΠΎΡΠ΅ΡΡ ΠΏΠΎΠΊΠ°Π·Π°Π»ΠΈ Π°Π½ΠΎΠΌΠ°Π»ΠΈΠΈ ΠΊΠ°ΡΠΈΠΎΡΠΈΠΏΠ° Π² 32.4 % ΡΠ»ΡΡΠ°Π΅Π² Ρ ΠΏΡΠ΅ΠΎΠ±Π»Π°ΒΠ΄Π°Π½ΠΈΠ΅ΠΌ Π°ΡΡΠΎΡΠΎΠΌΠ½ΡΡ
ΡΡΠΈΡΠΎΠΌΠΈΠΉ β 42.65 %, ΡΡΠΈΠΏΠ»ΠΎΠΈΠ΄ΠΈΠΉ β 30.38 % ΠΈ ΠΌΠΎΠ½ΠΎΡΠΎΠΌΠΈΠΈ Π₯ β 19.11 %. ΠΠΎΠΌΠΏΠ»Π΅ΠΊΡΠ½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· ΡΠ°ΡΡΠΎΡΡ ΠΈ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ Π°Π»Π»Π΅Π»ΡΠ½ΡΡ
Π²Π°ΡΠΈΠ°Π½ΡΠΎΠ² Π³Π΅Π½ΠΎΠ² HLA-DRB1 ΠΈ HLA-DQA1ΠΏΠΎΠΊΠ°Π·Π°Π», ΡΡΠΎ DRB1*0301, DRB1*1101-1104 ΠΈ DQA1*0501 ΡΠ²Π»ΡΡΡΡΡ Π°Π»Π»Π΅Π»ΡΠΌΠΈ-Π°Π³ΡΠ΅ΡΡΠΎΡΠ°ΠΌΠΈ Ρ ΠΆΠ΅Π½ΡΠΈΠ½ Ρ ΡΠ°Π½Π½ΠΈΠΌΠΈ ΡΠ΅ΠΏΡΠΎΠ΄ΡΠΊΡΠΈΠ²Π½ΡΠΌΠΈ ΠΏΠΎΡΠ΅ΡΡΠΌΠΈ (Π Π Π). Π‘ΠΎΠ²ΠΎΠΊΡΠΏΠ½Π°Ρ Π³ΠΎΠΌΠΎΠ»ΠΎΠ³ΠΈΡ Π°Π»Π»Π΅Π»ΡΠ½ΠΎΠ³ΠΎ ΠΏΠΎΠ»ΠΈΠΌΠΎΡΡΠΈΠ·ΠΌΠ° Π»ΠΎΠΊΡΡΠΎΠ² HLA-DRB1 ΠΈ HLA-DQA1 Π±ΠΎΠ»Π΅Π΅ 50 % ΠΌΠ΅ΠΆΠ΄Ρ ΠΏΠ°ΡΡΠ½Π΅ΡΠ°ΠΌΠΈ ΡΠ²Π΅Π»ΠΈΡΠΈΠ²Π°Π΅Ρ ΡΠΈΡΠΊ Π Π Π ΠΏΠΎΡΡΠΈ Π² ΡΠ΅ΡΡΡΠ΅ ΡΠ°Π·Π°. ΠΡΠ²ΠΎΠ΄Ρ. ΠΡΡΠ²Π»Π΅Π½Π½ΡΠ΅ Ρ
ΡΠΎΠΌΠΎΡΠΎΠΌΠ½ΡΠ΅ Π°Π½Π΅ΡΠΏΠ»ΠΎΠΈΠ΄ΠΈΠΈ Π² ΠΌΠ°ΡΠ΅ΡΠΈΠ°Π»Π΅ ΡΠ°ΠΌΠΎΠΏΡΠΎΠΈΠ·Π²ΠΎΠ»ΡΠ½ΡΡ
Π²ΡΠΊΠΈΠ΄ΡΡΠ΅ΠΉ ΠΈ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡ Π² Π³Π΅Π½Π°Ρ
Π³Π»Π°Π²Π½ΠΎΠ³ΠΎ ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠ° Π³ΠΈΡΡΠΎΡΠΎΠ²ΠΌΠ΅ΡΡΠΈΠΌΠΎΡΡΠΈ Ρ ΡΡΠΏΡΡΠΆΠ΅ΡΠΊΠΈΡ
ΠΏΠ°Ρ ΠΌΠΎΠ³ΡΡ Π²ΡΠ·ΡΠ²Π°ΡΡ Π½Π°ΡΡΡΠ΅Π½ΠΈΡ ΡΠ΅ΠΏΡΠΎΠ΄ΡΠΊΡΠΈΠ²Π½ΠΎΠΉ ΡΡΠ½ΠΊΡΠΈΠΈ ΠΈ ΡΠ»ΠΈΠΌΠΈΠ½Π°ΡΠΈΡ ΠΏΠ»ΠΎΠ΄Π° Π² ΡΠ°Π½Π½Π΅ΠΌ ΠΏΠ΅ΡΠΈΠΎΠ΄Π΅ Π±Π΅ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΡΡΠΈ
- β¦