55 research outputs found
The Deformation Stimulated Luminescence in KCl, KBr and KI Crystals
Currently, strengthening of the intensity of luminescence in alkali halide crystals (AHC) at lattice symmetry lowering is discussed as a promising direction for the development of scintillation detectors. In this regard, for the study of anion excitons and radiation defects in the AHC anion sublattice at deformation, the crystals with the same sizes of cations and different sizes of anions were chosen. In the X-ray spectra of KCl at 10 K, the luminescence at 3.88 eV; 3.05 eV and 2.3 eV is clearly visible. The luminescence at 3.05 eV corresponds to the tunneling recharge [F*, H]. Luminescence at 3.88 eV is quenched in the region of thermal destruction of F'-centers and characterizes tunneling recharge of F', VK-centers. In KCl at 90 K, the luminescence of self-trapped excitons (STE) is completely absent. In KBr at deformation not only STE luminescence, but also deformation stimulated luminescence at 3.58 eV were recorded, the last one corresponds to tunneling recharge of F', VK-centers. In KI crystal at 10 K and 90 K at deformation, only STE luminescence is enhanced. There are no deformation luminescence bands in KI compares with KBr and KCl crystals
ΠΠΎΡΡΠΎΠ»ΠΎΠ³ΠΈΡ ΠΌΡΠΊΠΎΡΠΈΠ»ΠΈΠ°ΡΠ½ΠΎΠΉ ΡΡΠ°Π½ΡΠΏΠΎΡΡΠ½ΠΎΠΉ ΡΠΈΡΡΠ΅ΠΌΡ ΠΏΡΠΈ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΌ Ρ ΡΠΎΠ½ΠΈΡΠ΅ΡΠΊΠΎΠΌ Π½Π΅ΠΎΠ±ΡΡΡΡΠΊΡΠΈΠ²Π½ΠΎΠΌ Π±ΡΠΎΠ½Ρ ΠΈΡΠ΅
Π ΠΌΠ΅Ρ
Π°Π½ΠΈΠ·ΠΌΠ°Ρ
ΠΌΠ΅ΡΡΠ½ΠΎΠΉ Π½Π΅ΡΠΏΠ΅ΡΠΈΡΠΈΡΠ΅ΡΠΊΠΎΠΉ Π·Π°ΡΠΈΡΡ Π»Π΅Π³ΠΊΠΈΡ
Π²Π°ΠΆΠ½ΡΡ ΡΠΎΠ»Ρ ΠΎΡΠ²ΠΎΠ΄ΡΡ ΠΌΡΠΊΠΎΡΠΈΠ»ΠΈΠ°ΡΠ½ΠΎΠΉ ΡΡΠ°Π½ΡΠΏΠΎΡΡΠ½ΠΎΠΉ ΡΠΈΡΡΠ΅ΠΌΠ΅, Π΄Π΅ΡΡΠ΅Π»ΡΠ½ΠΎΡΡΡ ΠΊΠΎΡΠΎΡΠΎΠΉ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ΅ΡΡΡ Π³Π»Π°Π²Π½ΡΠΌ ΠΎΠ±ΡΠ°Π·ΠΎΠΌ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΡΡ ΡΠΈΠ»ΠΈΠ°ΡΠ½ΠΎΠ³ΠΎ Π°ΠΏΠΏΠ°ΡΠ°ΡΠ° Π±ΡΠΎΠ½Ρ
ΠΈΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΠΏΠΈΡΠ΅Π»ΠΈΡ ΠΈ ΡΠ΅ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠΌΠΈ ΡΠ²ΠΎΠΉΡΡΠ²Π°ΠΌΠΈ Π±ΡΠΎΠ½Ρ
ΠΈΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΠ΅ΠΊΡΠ΅ΡΠ°
Π‘ΠΊΡΠΈΠ½ΠΈΠ½Π³ Π»Π°ΡΠ΅Π½ΡΠ½ΠΎΠΉ ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·Π½ΠΎΠΉ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΈ Ρ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ΠΌ Π°Π»Π»Π΅ΡΠ³Π΅Π½Π° ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·Π½ΠΎΠ³ΠΎ ΡΠ΅ΠΊΠΎΠΌΠ±ΠΈΠ½Π°Π½ΡΠ½ΠΎΠ³ΠΎ
InΒ recent years theΒ significant deterioration ofΒ health has been observed inΒ schoolchildren. AsΒ perΒ official data only 20% ofΒ children graduating fromΒ school areΒ considered toΒ be completely healthy, andΒ 60% suffer fromΒ chronic diseases, i.e. belong toΒ health groups III, IV andΒ V, among which there areΒ many children belonging toΒ tuberculosis risk groups andΒ suffering fromΒ undetected latent tuberculous infection. TheΒ efficiency ofΒ theΒ new technique aimed toΒ detect active tuberculous infection inΒ children andΒ adolescents ofΒ health groups III, IV andΒ V has been evaluated. Screening proved theΒ reduction inΒ theΒ number ofΒ patients inΒ need ofΒ TB doctor advising byΒ 8.4 fold compared toΒ traditional mass diagnostics withΒ tuberculin. Hyperergic reactions toΒ diaskintest areΒ 6 fold less common compared toΒ Mantoux test. AndΒ 99.2% ofΒ children referred toΒ TB doctor were registered toΒ theΒ dispensary follow-upΒ versus 23.4% ofΒ children referred toΒ TB doctor asΒ perΒ mass tuberculin testing results. (p <Β 0.001). Thus theΒ validity ofΒ referral toΒ TB doctor increased 4.2 fold. TheΒ detection rate ofΒ active forms ofΒ tuberculosis made 0.4 perΒ 1000 examinations versus 0.1 inΒ case ofΒ mass screening withΒ tuberculin testing.Π ΠΏΠΎΡΠ»Π΅Π΄Π½ΠΈΠ΅ Π³ΠΎΠ΄Ρ Π½Π°Π±Π»ΡΠ΄Π°Π΅ΡΡΡ ΡΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠ΅ ΡΡ
ΡΠ΄ΡΠ΅Π½ΠΈΠ΅ ΡΠΎΡΡΠΎΡΠ½ΠΈΡ Π·Π΄ΠΎΡΠΎΠ²ΡΡ ΡΠΊΠΎΠ»ΡΠ½ΠΈΠΊΠΎΠ². ΠΠΎ ΠΎΡΠΈΡΠΈΠ°Π»ΡΠ½ΡΠΌ Π΄Π°Π½Π½ΡΠΌ, Π»ΠΈΡΡ 20% Π΄Π΅ΡΠ΅ΠΉ, Π·Π°ΠΊΠ°Π½ΡΠΈΠ²Π°ΡΡΠΈΡ
ΡΠΊΠΎΠ»Ρ, ΡΡΠΈΡΠ°ΡΡΡΡ ΠΏΠΎΠ»Π½ΠΎΡΡΡΡ Π·Π΄ΠΎΡΠΎΠ²ΡΠΌΠΈ, Π° 60% ΠΈΠΌΠ΅ΡΡ Ρ
ΡΠΎΠ½ΠΈΡΠ΅ΡΠΊΠΈΠ΅ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΡΠΌΠΈ, Ρ. Π΅. III, IV ΠΈΠ»ΠΈ V Π³ΡΡΠΏΠΏΡ Π·Π΄ΠΎΡΠΎΠ²ΡΡ, ΡΡΠ΅Π΄ΠΈ ΠΊΠΎΡΠΎΡΡΡ
Π²Π΅Π»ΠΈΠΊΠ° Π΄ΠΎΠ»Ρ Π΄Π΅ΡΠ΅ΠΉ, ΠΎΡΠ½ΠΎΡΡΡΠΈΡ
ΡΡ ΠΊ Π³ΡΡΠΏΠΏΠ°ΠΌ ΡΠΈΡΠΊΠ° ΠΏΠΎ ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·Ρ ΠΈ ΠΈΠΌΠ΅ΡΡΠΈΡ
Π½Π΅Π²ΡΡΠ²Π»Π΅Π½Π½ΡΡ Π»Π°ΡΠ΅Π½ΡΠ½ΡΡ ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·Π½ΡΡ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΡ. ΠΡΠΎΠ²Π΅Π΄Π΅Π½Π° ΠΎΡΠ΅Π½ΠΊΠ° ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ Π½ΠΎΠ²ΠΎΠ³ΠΎ ΠΌΠ΅ΡΠΎΠ΄Π° Π²ΡΡΠ²Π»Π΅Π½ΠΈΡ Π°ΠΊΡΠΈΠ²Π½ΠΎΠΉ ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·Π½ΠΎΠΉ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΈ Ρ Π΄Π΅ΡΠ΅ΠΉ ΠΈ ΠΏΠΎΠ΄ΡΠΎΡΡΠΊΠΎΠ² III, IV ΠΈ V Π³ΡΡΠΏΠΏ Π·Π΄ΠΎΡΠΎΠ²ΡΡ. Π‘ΠΊΡΠΈΠ½ΠΈΠ½Π³ΠΎΠ²ΠΎΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΠΎΠΊΠ°Π·Π°Π»ΠΎ ΡΠΌΠ΅Π½ΡΡΠ΅Π½ΠΈΠ΅ ΡΠΈΡΠ»Π° ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ², Π½ΡΠΆΠ΄Π°ΡΡΠΈΡ
ΡΡ Π² ΠΊΠΎΠ½ΡΡΠ»ΡΡΠ°ΡΠΈΠΈ ΡΡΠΈΠ·ΠΈΠ°ΡΡΠ°, Π² 8,4 ΡΠ°Π·Π° ΠΏΠΎ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ Ρ ΡΡΠ°Π΄ΠΈΡΠΈΠΎΠ½Π½ΠΎΠΉ ΠΌΠ°ΡΡΠΎΠ²ΠΎΠΉ ΡΡΠ±Π΅ΡΠΊΡΠ»ΠΈΠ½ΠΎΠ΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠΎΠΉ. ΠΠΈΠΏΠ΅ΡΠ΅ΡΠ³ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΡΠ΅Π°ΠΊΡΠΈΠΈ Π½Π° ΠΏΡΠΎΠ±Ρ Ρ Π΄ΠΈΠ°ΡΠΊΠΈΠ½ΡΠ΅ΡΡΠΎΠΌ Π²ΡΡΠ²Π»ΡΡΡΡΡ Π² 6 ΡΠ°Π· ΡΠ΅ΠΆΠ΅ ΠΏΠΎ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ Ρ ΠΏΡΠΎΠ±ΠΎΠΉ ΠΠ°Π½ΡΡ. ΠΡΠΈ ΡΡΠΎΠΌ Π½Π° Π΄ΠΈΡΠΏΠ°Π½ΡΠ΅ΡΠ½ΡΠΉ ΡΡΠ΅Ρ Ρ Π²ΡΠ°ΡΠ°-ΡΡΠΈΠ·ΠΈΠ°ΡΡΠ° Π²Π·ΡΡΠΎ 99,2% Π΄Π΅ΡΠ΅ΠΉ ΠΎΡ Π½Π°ΠΏΡΠ°Π²Π»Π΅Π½Π½ΡΡ
Π½Π° ΠΊΠΎΠ½ΡΡΠ»ΡΡΠ°ΡΠΈΡ ΠΏΡΠΎΡΠΈΠ² 23,4% Π΄Π΅ΡΠ΅ΠΉ, Π½Π°ΠΏΡΠ°Π²Π»Π΅Π½Π½ΡΡ
ΠΏΠΎ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ°ΠΌ ΠΌΠ°ΡΡΠΎΠ²ΠΎΠΉ ΡΡΠ±Π΅ΡΠΊΡΠ»ΠΈΠ½ΠΎΠ΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠΈ (p < 0,001). Π’Π°ΠΊΠΈΠΌ ΠΎΠ±ΡΠ°Π·ΠΎΠΌ, Π² 4,2 ΡΠ°Π·Π° ΡΠ²Π΅Π»ΠΈΡΠΈΠ»Π°ΡΡ ΠΎΠ±ΠΎΡΠ½ΠΎΠ²Π°Π½Π½ΠΎΡΡΡ Π½Π°ΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΡΠ΅Π±Π΅Π½ΠΊΠ° ΠΊ Π²ΡΠ°ΡΡ-ΡΡΠΈΠ·ΠΈΠ°ΡΡΡ. ΠΡΡΠ²Π»ΡΠ΅ΠΌΠΎΡΡΡ Π°ΠΊΡΠΈΠ²Π½ΡΡ
ΡΠΎΡΠΌ ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·Π° Π½ΠΎΠ²ΡΠΌ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ ΡΠΎΡΡΠ°Π²ΠΈΠ»Π° 0,4 Π½Π° 1 000 ΠΎΠ±ΡΠ»Π΅Π΄ΠΎΠ²Π°Π½Π½ΡΡ
ΠΏΡΠΎΡΠΈΠ² 0,1 ΠΏΡΠΈ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΠΈ ΠΌΠ°ΡΡΠΎΠ²ΠΎΠΉ ΡΡΠ°Π΄ΠΈΡΠΈΠΎΠ½Π½ΠΎΠΉ ΡΡΠ±Π΅ΡΠΊΡΠ»ΠΈΠ½ΠΎΠ΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠΈ
Resolved photometry of extragalactic young massive star clusters
We present colour-magnitude diagrams (CMDs) for a sample of seven young
massive clusters in the galaxies NGC 1313, NGC 1569, NGC 1705, NGC 5236 and NGC
7793. The clusters have ages in the range 5-50 million years and masses of 10^5
-10^6 Msun. Although crowding prevents us from obtaining photometry in the
central regions of the clusters, we are still able to measure up to 30-100
supergiant stars in each of the richest clusters, along with the brighter main
sequence stars. The resulting CMDs and luminosity functions are compared with
photometry of artificially generated clusters, designed to reproduce the
photometric errors and completeness as realistically as possible. In agreement
with previous studies, our CMDs show no clear gap between the H-burning main
sequence and the He-burning supergiant stars, contrary to predictions by common
stellar isochrones. In general, the isochrones also fail to match the observed
number ratios of red-to-blue supergiant stars, although the difficulty of
separating blue supergiants from the main sequence complicates this comparison.
In several cases we observe a large spread (1-2 mag) in the luminosities of the
supergiant stars that cannot be accounted for by observational errors. This
spread can be reproduced by including an age spread of 10-30 million years in
the models. However, age spreads cannot fully account for the observed
morphology of the CMDs and other processes, such as the evolution of
interacting binary stars, may also play a role.Comment: 15 pages, 12 figures, accepted for publication in A&
Evolution of Sex-Specific Traits through Changes in HOX-Dependent doublesex Expression
Analysis in Drosophila suggests that evolutionary changes in the spatial regulation of the transcription factor doublesex play a key role in the origin, diversification, and loss of sex-specific structures
ΠΠ ΠΠ’ΠΠ ΠΠ ΠΠ€Π€ΠΠΠ’ΠΠΠΠΠ‘Π’Π ΠΠΠ§ΠΠΠΠ― Π’Π£ΠΠΠ ΠΠ£ΠΠΠΠ Π£Β ΠΠΠ’ΠΠ Π Π‘ΠΠΠ ΠΠΠΠΠΠ«Π₯ Π£Π‘ΠΠΠΠΠ―Π₯
The main objective of a phthisiologist following up and treating children and adolescents with local forms of tuberculosis is to achieve complete clinical cure with minimal remaining post-tuberculosis changes. Evaluation of treatment progress is important since it defines not only the duration of chemotherapy and follow-up but it also serves a prognostic criterion of stable clinical cure and prevention of relapse in the future. New criteria for evaluation of tuberculosis activity and clinical cure in children and adolescents were assessed. It was proved that Mantoux test could not be the criterion of the disease activity. While results of the test with tuberculous recombinant allergen (TRA) performed at the moment of clinical cure did not depend on the volume and severity of changes and allowed assessing the activity of the disease with any intensity of specific changes in chest lymph nodes and lung tissue, and TRA test served as a criterion of activity of mycobacterial population in the host.ΠΡΠ½ΠΎΠ²Π½ΠΎΠΉ ΡΠ΅Π»ΡΡ ΡΠ°Π±ΠΎΡΡ Π²ΡΠ°ΡΠ°-ΡΡΠΈΠ·ΠΈΠ°ΡΡΠ° Π² ΠΏΡΠΎΡΠ΅ΡΡΠ΅ Π΄ΠΈΡΠΏΠ°Π½ΡΠ΅ΡΠ½ΠΎΠ³ΠΎ Π½Π°Π±Π»ΡΠ΄Π΅Π½ΠΈΡ ΠΈ Π»Π΅ΡΠ΅Π½ΠΈΡ Π΄Π΅ΡΠ΅ΠΉ ΠΈ ΠΏΠΎΠ΄ΡΠΎΡΡΠΊΠΎΠ² Ρ Π»ΠΎΠΊΠ°Π»ΡΠ½ΡΠΌΠΈ ΡΠΎΡΠΌΠ°ΠΌΠΈ ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·Π° ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΏΠΎΠ»Π½ΠΎΡΠ΅Π½Π½ΠΎΠ΅ ΠΊΠ»ΠΈΠ½ΠΈΡΠ΅ΡΠΊΠΎΠ΅ ΠΈΠ·Π»Π΅ΡΠ΅Π½ΠΈΠ΅ Ρ ΠΌΠΈΠ½ΠΈΠΌΠ°Π»ΡΠ½ΡΠΌΠΈ ΠΎΡΡΠ°ΡΠΎΡΠ½ΡΠΌΠΈ ΠΏΠΎΡΡΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·Π½ΡΠΌΠΈ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡΠΌΠΈ. ΠΡΠ΅Π½ΠΊΠ° Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠΈ ΠΏΡΠΎΡΠ΅ΡΡΠ° Π½Π° ΡΠΎΠ½Π΅ ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠΌΠΎΠ³ΠΎ Π»Π΅ΡΠ΅Π½ΠΈΡ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»ΡΠ΅ΡΡΡ Π²Π°ΠΆΠ½ΠΎΠΉ, ΡΠ°ΠΊ ΠΊΠ°ΠΊ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ΅Ρ Π½Π΅ ΡΠΎΠ»ΡΠΊΠΎ Π΄Π»ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΡ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎΠ³ΠΎ ΠΊΡΡΡΠ° ΠΏΡΠΎΡΠΈΠ²ΠΎΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·Π½ΠΎΠΉ Ρ
ΠΈΠΌΠΈΠΎΡΠ΅ΡΠ°ΠΏΠΈΠΈ ΠΈ Π΄ΠΈΡΠΏΠ°Π½ΡΠ΅ΡΠ½ΠΎΠ³ΠΎ Π½Π°Π±Π»ΡΠ΄Π΅Π½ΠΈΡ, Π½ΠΎ ΠΈ ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΏΡΠΎΠ³Π½ΠΎΡΡΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΊΡΠΈΡΠ΅ΡΠΈΠ΅ΠΌ Π΄Π»Ρ ΡΡΠΎΠΉΠΊΠΎΠ³ΠΎ ΠΊΠ»ΠΈΠ½ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈΠ·Π»Π΅ΡΠ΅Π½ΠΈΡ ΠΈ ΠΎΡΡΡΡΡΡΠ²ΠΈΡ ΡΠ΅ΡΠΈΠ΄ΠΈΠ²Π° Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΡ Π² Π΄Π°Π»ΡΠ½Π΅ΠΉΡΠ΅ΠΌ. ΠΡΠΎΠ²Π΅Π΄Π΅Π½Π° ΠΎΡΠ΅Π½ΠΊΠ° Π½ΠΎΠ²ΡΡ
ΠΊΡΠΈΡΠ΅ΡΠΈΠ΅Π² Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ ΠΈ ΠΊΠ»ΠΈΠ½ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈΠ·Π»Π΅ΡΠ΅Π½ΠΈΡ ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·Π° Ρ Π΄Π΅ΡΠ΅ΠΉ ΠΈ ΠΏΠΎΠ΄ΡΠΎΡΡΠΊΠΎΠ². ΠΠΎΠΊΠ°Π·Π°Π½ΠΎ, ΡΡΠΎ ΠΏΡΠΎΠ±Π° ΠΠ°Π½ΡΡ Π½Π΅ ΠΌΠΎΠΆΠ΅Ρ ΡΠ²Π»ΡΡΡΡΡ ΠΊΡΠΈΡΠ΅ΡΠΈΠ΅ΠΌ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·Π½ΠΎΠ³ΠΎ ΠΏΡΠΎΡΠ΅ΡΡΠ°. ΠΠ°ΠΏΡΠΎΡΠΈΠ², ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ ΠΏΡΠΎΠ±Ρ Ρ Π°Π»Π»Π΅ΡΠ³Π΅Π½ΠΎΠΌ ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·Π½ΡΠΌ ΡΠ΅ΠΊΠΎΠΌΠ±ΠΈΠ½Π°Π½ΡΠ½ΡΠΌ (ΠΠ’Π ) Π½Π° ΠΌΠΎΠΌΠ΅Π½Ρ ΠΊΠ»ΠΈΠ½ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈΠ·Π»Π΅ΡΠ΅Π½ΠΈΡ ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·Π° Π½Π΅ Π·Π°Π²ΠΈΡΡΡ ΠΎΡ ΠΎΠ±ΡΠ΅ΠΌΠ° ΠΈ ΡΡΠ΅ΠΏΠ΅Π½ΠΈ Π²ΡΡΠ°ΠΆΠ΅Π½Π½ΠΎΡΡΠΈ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ ΠΈ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡΡ ΠΎΡΠ΅Π½ΠΈΠ²Π°ΡΡ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΡ ΠΏΡΠΈ Π»ΡΠ±ΠΎΠΉ Π²ΡΡΠ°ΠΆΠ΅Π½Π½ΠΎΡΡΠΈ ΡΠΏΠ΅ΡΠΈΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ Π²ΠΎ Π²Π½ΡΡΡΠΈΠ³ΡΡΠ΄Π½ΡΡ
Π»ΠΈΠΌΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ·Π»Π°Ρ
ΠΈ Π»Π΅Π³ΠΎΡΠ½ΠΎΠΉ ΡΠΊΠ°Π½ΠΈ, Π° Π·Π½Π°ΡΠΈΡ, ΠΏΡΠΎΠ±Π° Ρ ΠΠ’Π ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΊΡΠΈΡΠ΅ΡΠΈΠ΅ΠΌ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ ΠΌΠΈΠΊΡΠΎΠ±Π½ΠΎΠΉ ΠΏΠΎΠΏΡΠ»ΡΡΠΈΠΈ ΠΌΠΈΠΊΠΎΠ±Π°ΠΊΡΠ΅ΡΠΈΠΉ ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·Π° Π² ΠΎΡΠ³Π°Π½ΠΈΠ·ΠΌΠ΅ ΡΠ΅Π»ΠΎΠ²Π΅ΠΊΠ°
Π‘ΠΎΠ·Π΄Π°Π½ΠΈΠ΅ ΠΊΠΎΠ»Π»Π΅ΠΊΡΠΈΠΈ ΠΠ‘ΠΠ’-ΠΈΠ·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΠΉ ΠΈ ΠΊΠ»ΠΈΠ½ΠΈΡΠ΅ΡΠΊΠΈΡ Π΄Π°Π½Π½ΡΡ ΠΏΡΠΈ ΠΎΡΡΡΡΡ Π½Π°ΡΡΡΠ΅Π½ΠΈΡΡ ΠΌΠΎΠ·Π³ΠΎΠ²ΠΎΠ³ΠΎ ΠΊΡΠΎΠ²ΠΎΠΎΠ±ΡΠ°ΡΠ΅Π½ΠΈΡ
Background The use of neuroimaging methods is an integral part of the process of assisting patients with acute cerebrovascular events (ACVE), and computed tomography (CT) is the Β«gold standardΒ» for examining this category of patients. The capabilities of the analysis of CT images may be significantly expanded with modern methods of machine learning including the application of the principles of radiomics. However, since the use of these methods requires large arrays of DICOM (Digital Imaging and Communications in Medicine)-images, their implementation into clinical practice is limited by the lack of representative sample sets. Inaddition, at present, collections (datasets) of CT images of stroke patients, that are suitable for machine learning, are practically not available in the public domain.Aim of study Regarding the aforesaid, the aim of this work was to create a DICOM images dataset of native CT and CT-angiography of patients with different types of stroke. Material and meth ods The collection was based on the medical cases of patients hospitalized in the Regional Vascular Center of the N.V. Sklifosovsky Research Institute for Emergency Medicine. We used a previously developed specialized platform to enter clinical data on the stroke cases, to attach CT DICOMimages to each case, to contour 3D areas of interest, and to tag (label) them. A dictionary was developed for tagging, where elements describe the type of lesion, location, and vascular territory.Results A dataset of clinical cases and images was formed in the course of the work. It included anonymous information about 220 patients, 130 of them with ischemic stroke, 40 with hemorrhagic stroke, and 50 patients without cerebrovascular disorders. Clinical data included information about type of stroke, presence of concomitant diseases and complications, length of hospital stay, methods of treatment, and outcome. The results of 370 studies of native CT and 102 studies of CT-angiography were entered for all patients. The areas of interest corresponding to direct and indirect signs of stroke were contoured and tagged by radiologists on each series of images.Conclusion The resulting collection of images will enable the use of various methods of data analysis and machine learning in solving the most important practical problems including diagnosis of the stroke type, assessment of lesion volume, and prediction of the degree of neurological deficit.ΠΠΊΡΡΠ°Π»ΡΠ½ΠΎΡΡΡ ΠΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² Π½Π΅ΠΉΡΠΎΠ²ΠΈΠ·ΡΠ°Π»ΠΈΠ·Π°ΡΠΈΠΈ ΡΠ²Π»ΡΠ΅ΡΡΡ Π½Π΅ΠΎΡΡΠ΅ΠΌΠ»Π΅ΠΌΠΎΠΉ ΡΠ°ΡΡΡΡ ΠΏΡΠΎΡΠ΅ΡΡΠ° ΠΎΠΊΠ°Π·Π°Π½ΠΈΡ ΠΏΠΎΠΌΠΎΡΠΈ Π±ΠΎΠ»ΡΠ½ΡΠΌ Ρ ΠΎΡΡΡΡΠΌΠΈ Π½Π°ΡΡΡΠ΅Π½ΠΈΡΠΌΠΈ ΠΌΠΎΠ·Π³ΠΎΠ²ΠΎΠ³ΠΎ ΠΊΡΠΎΠ²ΠΎΠΎΠ±ΡΠ°ΡΠ΅Π½ΠΈΡ (ΠΠΠΠ), ΠΏΡΠΈ ΡΡΠΎΠΌ Π·ΠΎΠ»ΠΎΡΡΠΌ ΡΡΠ°Π½Π΄Π°ΡΡΠΎΠΌ ΠΎΠ±ΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π΄Π°Π½Π½ΠΎΠΉ ΠΊΠ°ΡΠ΅Π³ΠΎΡΠΈΠΈ Π±ΠΎΠ»ΡΠ½ΡΡ
ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΊΠΎΠΌΠΏΡΡΡΠ΅ΡΠ½Π°Ρ ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠΈΡ (ΠΠ’). ΠΠ½Π°ΡΠΈΡΠ΅Π»ΡΠ½ΠΎ ΡΠ°ΡΡΠΈΡΠΈΡΡ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠΈ Π°Π½Π°Π»ΠΈΠ·Π° ΠΠ’-ΠΈΠ·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΠΉ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎ Ρ ΠΏΠΎΠΌΠΎΡΡΡ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² ΠΌΠ°ΡΠΈΠ½Π½ΠΎΠ³ΠΎ ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ, Π² ΡΠΎΠΌ ΡΠΈΡΠ»Π΅ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΠΏΡΠΈΠ½ΡΠΈΠΏΠΎΠ² ΡΠ°Π΄ΠΈΠΎΠΌΠΈΠΊΠΈ. ΠΠ΄Π½Π°ΠΊΠΎ, ΡΠ°ΠΊ ΠΊΠ°ΠΊ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΡΡΠΈΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² ΡΡΠ΅Π±ΡΠ΅Ρ Π½Π°Π»ΠΈΡΠΈΡ Π±ΠΎΠ»ΡΡΠΈΡ
ΠΌΠ°ΡΡΠΈΠ²ΠΎΠ² DICOM (Digital Imaging and Communications in Medicine)-ΠΈΠ·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΠΉ, ΠΈΡ
Π²Π½Π΅Π΄ΡΠ΅Π½ΠΈΠ΅ Π² ΠΊΠ»ΠΈΠ½ΠΈΡΠ΅ΡΠΊΡΡ ΠΏΡΠ°ΠΊΡΠΈΠΊΡ ΠΎΠ³ΡΠ°Π½ΠΈΡΠ΅Π½ΠΎ ΠΏΡΠΎΠ±Π»Π΅ΠΌΠΎΠΉ Π½Π°Π±ΠΎΡΠ° ΡΠ΅ΠΏΡΠ΅Π·Π΅Π½ΡΠ°ΡΠΈΠ²Π½ΡΡ
Π²ΡΠ±ΠΎΡΠΎΠΊ. ΠΡΠΎΠΌΠ΅ ΡΠΎΠ³ΠΎ, Π² Π½Π°ΡΡΠΎΡΡΠ΅Π΅ Π²ΡΠ΅ΠΌΡ Π² ΠΎΡΠΊΡΡΡΠΎΠΌ Π΄ΠΎΡΡΡΠΏΠ΅ ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΈ Π½Π΅ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Ρ ΠΊΠΎΠ»Π»Π΅ΠΊΡΠΈΠΈ, ΡΠΎΠ΄Π΅ΡΠΆΠ°ΡΠΈΠ΅ ΠΠ’-ΠΈΠ·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΡ Π±ΠΎΠ»ΡΠ½ΡΡ
c ΠΠΠΠ, ΠΊΠΎΡΠΎΡΡΠ΅ Π±ΡΠ»ΠΈ Π±Ρ ΠΏΡΠΈΠ³ΠΎΠ΄Π½Ρ Π΄Π»Ρ ΠΌΠ°ΡΠΈΠ½Π½ΠΎΠ³ΠΎ ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ.Π¦Π΅Π»Ρ Π ΡΠ²ΡΠ·ΠΈ Ρ Π²ΡΡΠ΅ΡΠΊΠ°Π·Π°Π½Π½ΡΠΌ, ΡΠ΅Π»ΡΡ Π΄Π°Π½Π½ΠΎΠΉ ΡΠ°Π±ΠΎΡΡ ΡΠ²Π»ΡΠ»ΠΎΡΡ ΡΠΎΠ·Π΄Π°Π½ΠΈΠ΅ ΠΊΠΎΠ»Π»Π΅ΠΊΡΠΈΠΈ DICOM-ΠΈΠ·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΠΉ Π½Π°ΡΠΈΠ²Π½ΠΎΠΉ ΠΠ’ ΠΈ ΠΠ’-Π°Π½Π³ΠΈΠΎΠ³ΡΠ°ΡΠΈΠΈ Ρ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΡΠ°Π·Π»ΠΈΡΠ½ΡΠΌΠΈ ΡΠΈΠΏΠ°ΠΌΠΈ ΠΠΠΠ.ΠΠ°ΡΠ΅ΡΠΈΠ°Π» ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ ΠΡΠ½ΠΎΠ²ΠΎΠΉ Π΄Π»Ρ ΡΠΎΠ·Π΄Π°Π½ΠΈΡ ΠΊΠΎΠ»Π»Π΅ΠΊΡΠΈΠΈ ΡΡΠ°Π»ΠΈ ΠΈΡΡΠΎΡΠΈΠΈ Π±ΠΎΠ»Π΅Π·Π½ΠΈ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ², Π³ΠΎΡΠΏΠΈΡΠ°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
Π² ΡΠ΅Π³ΠΈΠΎΠ½Π°Π»ΡΠ½ΡΠΉ ΡΠΎΡΡΠ΄ΠΈΡΡΡΠΉ ΡΠ΅Π½ΡΡ ΠΠΠ Π‘Π ΠΈΠΌ. Π.Π. Π‘ΠΊΠ»ΠΈΡΠΎΡΠΎΠ²ΡΠΊΠΎΠ³ΠΎ. ΠΠ»Ρ ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΊΠΎΠ»Π»Π΅ΠΊΡΠΈΠΈ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π»Π°ΡΡ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½Π½Π°Ρ Π½Π°ΠΌΠΈ ΡΠ°Π½Π΅Π΅ ΡΠΏΠ΅ΡΠΈΠ°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Π½Π°Ρ ΠΏΠ»Π°ΡΡΠΎΡΠΌΠ°, ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡΡΠ°Ρ Π²Π²ΠΎΠ΄ΠΈΡΡ ΠΊΠ»ΠΈΠ½ΠΈΡΠ΅ΡΠΊΠΈΠ΅ Π΄Π°Π½Π½ΡΠ΅ ΠΎ ΡΠ»ΡΡΠ°ΡΡ
ΠΠΠΠ, ΠΏΡΠΈΠΊΡΠ΅ΠΏΠ»ΡΡΡ ΠΊ ΠΊΠ°ΠΆΠ΄ΠΎΠΌΡ ΡΠ»ΡΡΠ°Ρ DICOM-ΠΈΠ·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΡ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½Π½ΡΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ, Π° ΡΠ°ΠΊΠΆΠ΅ ΠΎΠΊΠΎΠ½ΡΡΡΠΈΠ²Π°ΡΡ ΠΈ ΡΠ΅Π³ΠΈΡΠΎΠ²Π°ΡΡ (ΡΠ°Π·ΠΌΠ΅ΡΠ°ΡΡ) 3D-ΠΎΠ±Π»Π°ΡΡΠΈ ΠΈΠ½ΡΠ΅ΡΠ΅ΡΠ°. ΠΠ»Ρ ΡΠ΅Π³ΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π±ΡΠ» ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½ ΡΠ»ΠΎΠ²Π°ΡΡ, ΡΠ»Π΅ΠΌΠ΅Π½ΡΡ ΠΊΠΎΡΠΎΡΠΎΠ³ΠΎ ΠΎΠΏΠΈΡΡΠ²Π°ΡΡ ΡΠΈΠΏ ΠΏΠ°ΡΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΡ, Π»ΠΎΠΊΠ°Π»ΠΈΠ·Π°ΡΠΈΡ ΠΈ Π±Π°ΡΡΠ΅ΠΉΠ½ ΠΊΡΠΎΠ²ΠΎΡΠ½Π°Π±ΠΆΠ΅Π½ΠΈΡ.Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ Π Ρ
ΠΎΠ΄Π΅ ΡΠ°Π±ΠΎΡΡ Π±ΡΠ»Π° ΡΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½Π° ΠΊΠΎΠ»Π»Π΅ΠΊΡΠΈΡ ΠΊΠ»ΠΈΠ½ΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ»ΡΡΠ°Π΅Π² ΠΈ ΠΈΠ·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΠΉ, Π²ΠΊΠ»ΡΡΠ°ΡΡΠ°Ρ Π°Π½ΠΎΠ½ΠΈΠΌΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Π½ΡΡ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΡ ΠΎ 220 ΠΏΠ°ΡΠΈΠ΅Π½ΡΠ°Ρ
, ΠΈΠ· Π½ΠΈΡ
130 - Ρ ΠΈΡΠ΅ΠΌΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΈΠ½ΡΡΠ»ΡΡΠΎΠΌ, 40 - Ρ Π³Π΅ΠΌΠΎΡΡΠ°Π³ΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΈΠ½ΡΡΠ»ΡΡΠΎΠΌ, Π° ΡΠ°ΠΊΠΆΠ΅ 50 ΡΠ΅Π»ΠΎΠ²Π΅ΠΊ Π±Π΅Π· ΡΠ΅ΡΠ΅Π±ΡΠΎΠ²Π°ΡΠΊΡΠ»ΡΡΠ½ΠΎΠΉ ΠΏΠ°ΡΠΎΠ»ΠΎΠ³ΠΈΠΈ. ΠΠ»ΠΈΠ½ΠΈΡΠ΅ΡΠΊΠΈΠ΅ Π΄Π°Π½Π½ΡΠ΅ Π²ΠΊΠ»ΡΡΠ°Π»ΠΈ ΡΠ²Π΅Π΄Π΅Π½ΠΈΡ ΠΎ ΡΠΈΠΏΠ΅ ΠΠΠΠ, Π½Π°Π»ΠΈΡΠΈΠΈ ΡΠΎΠΏΡΡΡΡΠ²ΡΡΡΠΈΡ
Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΠΉ ΠΈ ΠΎΡΠ»ΠΎΠΆΠ½Π΅Π½ΠΈΠΉ, Π΄Π»ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ Π³ΠΎΡΠΏΠΈΡΠ°Π»ΠΈΠ·Π°ΡΠΈΠΈ, ΡΠΏΠΎΡΠΎΠ±Π΅ Π»Π΅ΡΠ΅Π½ΠΈΡ ΠΈ ΠΈΡΡ
ΠΎΠ΄Π΅. ΠΡΠ΅Π³ΠΎ Π΄Π»Ρ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Π±ΡΠ»ΠΈ Π²Π²Π΅Π΄Π΅Π½Ρ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ 370 ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ Π½Π°ΡΠΈΠ²Π½ΠΎΠΉ ΠΠ’ ΠΈ 102 ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΠ’-Π°Π½Π³ΠΈΠΎΠ³ΡΠ°ΡΠΈΠΈ. ΠΠ° ΠΊΠ°ΠΆΠ΄ΠΎΠΉ ΡΠ΅ΡΠΈΠΈ ΠΈΠ·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΠΉ Π²ΡΠ°ΡΠΎΠΌ-ΡΠΊΡΠΏΠ΅ΡΡΠΎΠΌ Π±ΡΠ»ΠΈ ΠΎΠΊΠΎΠ½ΡΡΡΠ΅Π½Ρ ΠΈ ΠΏΡΠΎΡΠ΅Π³ΠΈΡΠΎΠ²Π°Π½Ρ ΠΎΠ±Π»Π°ΡΡΠΈ ΠΈΠ½ΡΠ΅ΡΠ΅ΡΠ°, ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΡΡΡΠΈΠ΅ ΠΏΡΡΠΌΡΠΌ ΠΈ ΠΊΠΎΡΠ²Π΅Π½Π½ΡΠΌ ΠΏΡΠΈΠ·Π½Π°ΠΊΠ°ΠΌ ΠΠΠΠ.ΠΡΠ²ΠΎΠ΄ Π‘ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½Π½Π°Ρ ΠΊΠΎΠ»Π»Π΅ΠΊΡΠΈΡ ΠΈΠ·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΠΉ ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΡ Π² ΠΏΠΎΡΠ»Π΅Π΄ΡΡΡΠ΅ΠΌ ΠΏΡΠΈΠΌΠ΅Π½ΠΈΡΡ ΡΠ°Π·Π»ΠΈΡΠ½ΡΠ΅ ΠΌΠ΅ΡΠΎΠ΄Ρ Π°Π½Π°Π»ΠΈΠ·Π° Π΄Π°Π½Π½ΡΡ
ΠΈ ΠΌΠ°ΡΠΈΠ½Π½ΠΎΠ³ΠΎ ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ Π² ΡΠ΅ΡΠ΅Π½ΠΈΠΈ Π²Π°ΠΆΠ½Π΅ΠΉΡΠΈΡ
ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΈΡ
Π·Π°Π΄Π°Ρ, Π² ΡΠΎΠΌ ΡΠΈΡΠ»Π΅ Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠΈ ΡΠΈΠΏΠ° ΠΠΠΠ, ΠΎΡΠ΅Π½ΠΊΠΈ ΠΎΠ±ΡΠ΅ΠΌΠ° ΠΏΠΎΡΠ°ΠΆΠ΅Π½ΠΈΡ, ΠΏΡΠΎΠ³Π½ΠΎΠ·Π° ΡΡΠ΅ΠΏΠ΅Π½ΠΈ Π½Π΅Π²ΡΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π΄Π΅ΡΠΈΡΠΈΡΠ°
Bio-nanotechnology application in wastewater treatment
The nanoparticles have received high interest in the ο¬eld of medicine and water puriο¬cation, however, the nanomaterials produced by chemical and physical methods are considered hazardous, expensive, and leave behind harmful substances to the environment. This chapter aimed to focus on green-synthesized nanoparticles and their medical applications. Moreover, the chapter highlighted the applicability of the metallic nanoparticles (MNPs) in the inactivation of microbial cells due to their high surface and small particle size. Modifying nanomaterials produced by green-methods is safe, inexpensive, and easy. Therefore, the control and modiο¬cation of nanoparticles and their properties were also discussed
ΠΠΎΠΌΠΏΡΡΡΠ΅ΡΠ½Π°Ρ ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠΈΡ ΠΏΡΠΈ ΡΠΏΠΎΠ½ΡΠ°Π½Π½ΠΎΠΉ Π³Π΅ΠΌΠ°ΡΠΎΠΌΠ΅ ΠΏΠΈΡΠ΅Π²ΠΎΠ΄Π°: Π½Π°Π΄Π΅ΠΆΠ½ΠΎΠ΅ ΡΠΎΠΏΡΠΎΠ²ΠΎΠΆΠ΄Π΅Π½ΠΈΠ΅ ΠΎΡ Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠΈ Π΄ΠΎ Π²ΡΠ·Π΄ΠΎΡΠΎΠ²Π»Π΅Π½ΠΈΡ
The purpose of the study. To study the possibilities of computed tomography (CT) in the diagnosis of spontaneous hematoma of the esophagus, including in the process of dynamic observation.Materials and methods. A retrospective analysis of CT results in 11 patients with spontaneous esophageal hematoma treated at the N.V. Sklifosovsky Research Institute of SP in the period 2005β2020 is presented. All patients underwent a comprehensive laboratory and instrumental examination, including CT. CT studies were performed with oral and intravenous bolus contrast, primarily at admission and in dynamics.Results. In all cases, according to CT data, acute pathology of the aorta, rupture of the esophagus were excluded and signs of spontaneous hematoma of the esophagus were revealed. CT semiotics of esophageal hematoma was analyzed with quantitative treatment of changes in density, linear dimensions and volume. CT semiotics analysis also revealed the volumetric effect of hematoma on surrounding organs and structures, accumulation of blood in the pleural cavities, and verified signs of infection of hematoma with inflammatory changes in the surrounding paraesophageal tissue. CT data served as the basis for determining the optimal treatment tactics for spontaneous esophageal hematoma. Conservative therapy was the main method of her treatment. CT examination in dynamics allowed timely detection of complications of spontaneous hematoma of the esophagus (hemothorax, perforation of the esophagus, infection of the hematoma) requiring surgical intervention.Conclusion. CT is the method of choice in the diagnosis of spontaneous hematoma of the esophagus, which allows for a clear differential diagnosis with urgent life-threatening conditions. CT data make it possible to justify treatment tactics and assess the dynamics of the pathological process.Π¦Π΅Π»Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ: ΠΈΠ·ΡΡΠΈΡΡ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠΈ ΠΊΠΎΠΌΠΏΡΡΡΠ΅ΡΠ½ΠΎΠΉ ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠΈΠΈ (ΠΠ’) Π² Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠ΅ ΡΠΏΠΎΠ½ΡΠ°Π½Π½ΠΎΠΉ Π³Π΅ΠΌΠ°ΡΠΎΠΌΡ ΠΏΠΈΡΠ΅Π²ΠΎΠ΄Π°, Π² ΡΠΎΠΌ ΡΠΈΡΠ»Π΅ Π² ΠΏΡΠΎΡΠ΅ΡΡΠ΅ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π½Π°Π±Π»ΡΠ΄Π΅Π½ΠΈΡ.ΠΠ°ΡΠ΅ΡΠΈΠ°Π» ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ. ΠΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½ ΡΠ΅ΡΡΠΎΡΠΏΠ΅ΠΊΡΠΈΠ²Π½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ² ΠΠ’ Ρ 11 ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² ΡΠΎ ΡΠΏΠΎΠ½ΡΠ°Π½Π½ΠΎΠΉ Π³Π΅ΠΌΠ°ΡΠΎΠΌΠΎΠΉ ΠΏΠΈΡΠ΅Π²ΠΎΠ΄Π°, Π½Π°Ρ
ΠΎΠ΄ΠΈΠ²ΡΠΈΡ
ΡΡ Π½Π° Π»Π΅ΡΠ΅Π½ΠΈΠΈ Π² ΠΠΠ Π‘Π ΠΈΠΌ. Π.Π. Π‘ΠΊΠ»ΠΈΡΠΎΡΠΎΠ²ΡΠΊΠΎΠ³ΠΎ Π² ΠΏΠ΅ΡΠΈΠΎΠ΄ 2005β2020 Π³Π³. ΠΡΠ΅ΠΌ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠ°ΠΌ Π±ΡΠ»ΠΎ Π²ΡΠΏΠΎΠ»Π½Π΅Π½ΠΎ ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠ½ΠΎΠ΅ Π»Π°Π±ΠΎΡΠ°ΡΠΎΡΠ½ΠΎ-ΠΈΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠ°Π»ΡΠ½ΠΎΠ΅ ΠΎΠ±ΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅, Π²ΠΊΠ»ΡΡΠ°Π²ΡΠ΅Π΅ ΠΠ’ Ρ ΠΏΠ΅ΡΠΎΡΠ°Π»ΡΠ½ΡΠΌ ΠΈ Π²Π½ΡΡΡΠΈΠ²Π΅Π½Π½ΡΠΌ Π±ΠΎΠ»ΡΡΠ½ΡΠΌ ΠΊΠΎΠ½ΡΡΠ°ΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ, ΠΊΠ°ΠΊ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎ ΠΏΡΠΈ ΠΏΠΎΡΡΡΠΏΠ»Π΅Π½ΠΈΠΈ, ΡΠ°ΠΊ ΠΈ Π² Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠ΅.Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. ΠΠΎ Π²ΡΠ΅Ρ
ΡΠ»ΡΡΠ°ΡΡ
ΠΏΠΎ Π΄Π°Π½Π½ΡΠΌ ΠΠ’ Π±ΡΠ»ΠΈ ΠΈΡΠΊΠ»ΡΡΠ΅Π½Ρ ΠΎΡΡΡΠ°Ρ ΠΏΠ°ΡΠΎΠ»ΠΎΠ³ΠΈΡ Π°ΠΎΡΡΡ, ΡΠ°Π·ΡΡΠ² ΠΏΠΈΡΠ΅Π²ΠΎΠ΄Π° ΠΈ Π²ΡΡΠ²Π»Π΅Π½Ρ ΠΏΡΠΈΠ·Π½Π°ΠΊΠΈ ΡΠΏΠΎΠ½ΡΠ°Π½Π½ΠΎΠΉ Π³Π΅ΠΌΠ°ΡΠΎΠΌΡ ΠΏΠΈΡΠ΅Π²ΠΎΠ΄Π°. ΠΡΠΎΠ°Π½Π°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Π° ΠΠ’-ΡΠ΅ΠΌΠΈΠΎΡΠΈΠΊΠ° Π³Π΅ΠΌΠ°ΡΠΎΠΌΡ ΠΏΠΈΡΠ΅Π²ΠΎΠ΄Π° Ρ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΠΎΠΉ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ ΠΏΠΎ ΠΏΠ»ΠΎΡΠ½ΠΎΡΡΠΈ, Π»ΠΈΠ½Π΅ΠΉΠ½ΡΠΌ ΡΠ°Π·ΠΌΠ΅ΡΠ°ΠΌ ΠΈ ΠΎΠ±ΡΠ΅ΠΌΡ. ΠΠ½Π°Π»ΠΈΠ· ΠΠ’-ΡΠ΅ΠΌΠΈΠΎΡΠΈΠΊΠΈ ΡΠ°ΠΊΠΆΠ΅ ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ» Π²ΡΡΠ²ΠΈΡΡ ΠΎΠ±ΡΠ΅ΠΌΠ½ΠΎΠ΅ Π²ΠΎΠ·Π΄Π΅ΠΉΡΡΠ²ΠΈΠ΅ Π³Π΅ΠΌΠ°ΡΠΎΠΌΡ Π½Π° ΠΎΠΊΡΡΠΆΠ°ΡΡΠΈΠ΅ ΠΎΡΠ³Π°Π½Ρ ΠΈ ΡΡΡΡΠΊΡΡΡΡ, ΡΠΊΠΎΠΏΠ»Π΅Π½ΠΈΠ΅ ΠΊΡΠΎΠ²ΠΈ Π² ΠΏΠ»Π΅Π²ΡΠ°Π»ΡΠ½ΡΡ
ΠΏΠΎΠ»ΠΎΡΡΡΡ
, Π²Π΅ΡΠΈΡΠΈΡΠΈΡΠΎΠ²Π°ΡΡ ΠΏΡΠΈΠ·Π½Π°ΠΊΠΈ ΠΈΠ½ΡΠΈΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π³Π΅ΠΌΠ°ΡΠΎΠΌΡ Ρ Π²ΠΎΡΠΏΠ°Π»ΠΈΡΠ΅Π»ΡΠ½ΡΠΌΠΈ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡΠΌΠΈ ΠΎΠΊΡΡΠΆΠ°ΡΡΠ΅ΠΉ ΠΏΠ°ΡΠ°ΡΠ·ΠΎΡΠ°Π³Π΅Π°Π»ΡΠ½ΠΎΠΉ ΠΊΠ»Π΅ΡΡΠ°ΡΠΊΠΈ. ΠΠ°Π½Π½ΡΠ΅ ΠΠ’ ΠΏΠΎΡΠ»ΡΠΆΠΈΠ»ΠΈ ΠΎΡΠ½ΠΎΠ²ΠΎΠΉ Π΄Π»Ρ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΎΠΏΡΠΈΠΌΠ°Π»ΡΠ½ΠΎΠΉ Π»Π΅ΡΠ΅Π±Π½ΠΎΠΉ ΡΠ°ΠΊΡΠΈΠΊΠΈ ΠΏΡΠΈ ΡΠΏΠΎΠ½ΡΠ°Π½Π½ΠΎΠΉ Π³Π΅ΠΌΠ°ΡΠΎΠΌΠ΅ ΠΏΠΈΡΠ΅Π²ΠΎΠ΄Π°. ΠΠΎΠ½ΡΠ΅ΡΠ²Π°ΡΠΈΠ²Π½Π°Ρ ΡΠ΅ΡΠ°ΠΏΠΈΡ ΡΠ²Π»ΡΠ»Π°ΡΡ ΠΎΡΠ½ΠΎΠ²Π½ΡΠΌ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ Π΅Π΅ Π»Π΅ΡΠ΅Π½ΠΈΡ. ΠΠ’-ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ Π² Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠ΅ ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ»ΠΎ ΡΠ²ΠΎΠ΅Π²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎ Π²ΡΡΠ²ΠΈΡΡ ΠΎΡΠ»ΠΎΠΆΠ½Π΅Π½ΠΈΡ ΡΠΏΠΎΠ½ΡΠ°Π½Π½ΠΎΠΉ Π³Π΅ΠΌΠ°ΡΠΎΠΌΡ ΠΏΠΈΡΠ΅Π²ΠΎΠ΄Π° (Π³Π΅ΠΌΠΎΡΠΎΡΠ°ΠΊΡ, ΠΏΠ΅ΡΡΠΎΡΠ°ΡΠΈΡ ΠΏΠΈΡΠ΅Π²ΠΎΠ΄Π°, ΠΈΠ½ΡΠΈΡΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ Π³Π΅ΠΌΠ°ΡΠΎΠΌΡ), ΡΡΠ΅Π±ΡΡΡΠΈΠ΅ Ρ
ΠΈΡΡΡΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π²ΠΌΠ΅ΡΠ°ΡΠ΅Π»ΡΡΡΠ²Π°.ΠΠ°ΠΊΠ»ΡΡΠ΅Π½ΠΈΠ΅. ΠΠ’ ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ Π²ΡΠ±ΠΎΡΠ° ΠΏΡΠΈ Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠ΅ ΡΠΏΠΎΠ½ΡΠ°Π½Π½ΠΎΠΉ Π³Π΅ΠΌΠ°ΡΠΎΠΌΡ ΠΏΠΈΡΠ΅Π²ΠΎΠ΄Π°, ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡΡΠΈΠΌ ΠΏΡΠΎΠ²Π΅ΡΡΠΈ ΡΠ΅ΡΠΊΡΡ Π΄ΠΈΡΡΠ΅ΡΠ΅Π½ΡΠΈΠ°Π»ΡΠ½ΡΡ Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΡ Ρ Π½Π΅ΠΎΡΠ»ΠΎΠΆΠ½ΡΠΌΠΈ ΠΆΠΈΠ·Π½Π΅ΡΠ³ΡΠΎΠΆΠ°ΡΡΠΈΠΌΠΈ ΡΠΎΡΡΠΎΡΠ½ΠΈΡΠΌΠΈ. ΠΠ’-Π΄Π°Π½Π½ΡΠ΅ Π΄Π°ΡΡ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡ ΠΎΠ±ΠΎΡΠ½ΠΎΠ²Π°ΡΡ ΡΠ°ΠΊΡΠΈΠΊΡ Π»Π΅ΡΠ΅Π½ΠΈΡ ΠΈ ΠΎΡΠ΅Π½ΠΈΡΡ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΡ ΠΏΠ°ΡΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΏΡΠΎΡΠ΅ΡΡΠ°
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