17 research outputs found
Seed size and cold stratification affect Acer negundo and Acer ginnala seeds germination
The aim of this work is to determine how the germination of seeds of the invasive tree
Acer negundo depends on the period of cold stratification under the snow and the duration of
stratification in the air on the branches of the trees. For comparison with A. negundo, we used
seeds of Acer ginnala, introduced but not invasive tree in the Middle Urals. The period of
stratification in the air modeled by collecting seeds in October and December. The duration of
cold stratification under the snow was 0, 1, 2, 3 and 4 months. We hypothesized that the duration
of stratification in the air did not affect the germination of A. negundo and A. ginnala seeds. Cold
stratification under the snow had a positive effect on seed germination of both species. The best
seed germination of A. negundo and A. ginnala was after 4 months of cold stratification under the
snow, the germination rate differs: in A. negundo 12 Β± 4% (small seeds) and 79 Β± 7% (large
seeds), in A. ginnala β 1 Β± 2% (small seeds) and 18 Β± 4% (large seeds). In both species, large
seeds germinated at 7 to 18 times more intensively than small ones. In A. ginnala case, even after
cold stratification under snow for 4 months, no more than 22% of the seeds germinated. The
germination of A. ginnala seeds was 4β5 times lower than that of A. negundo seeds
Π£ΡΡΡ-ΠΈΡΠΈΠΌΡΠΊΠ°Ρ ΠΊΠΎΡΡΡ: ΠΌΠΈΠ½Π΅ΡΠ°Π»ΠΎΠ³ΠΎΠ³Π΅ΠΎΡ ΠΈΠΌΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΡΠ²ΠΎΠΉΡΡΠ²Π° ΠΊΠ°ΠΊ ΠΈΡΡΠΎΡΠ½ΠΈΠΊ ΠΏΠ°Π»Π΅ΠΎΠ½ΡΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠΉ, ΠΏΠ°Π»Π΅ΠΎΠ°Π½ΡΡΠΎΠΏΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΈ ΠΏΠ°Π»Π΅ΠΎΡΠΊΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ
Ust-Ishim man was the representative of one of the ancestral groups of the Homo sapiens, Neanderthals and Denisovans. The first results of a comprehensive mineralogical and geochemical study of fossil bones using a wide range of physical, chemical and physico-chemical methods: thermal analysis, optical microscopy, scanning electron microscopy, atomic-force microscopy, nitrogen capillary condensation method, X-ray fluorescence analysis, ISP-MS, gas chromatography method, amino acid chromatography analysisβs, X-ray microprobe method, X-ray diffraction method, Raman and infrared spectroscopy, isotope spectrometry are presented in this article. The studied fragment of the skeleton is of higher preservation rate than the common bone detritus of this age and even the fossils of younger Pleistocene animals that allowed determining almost all its primary properties. The unique preservation presumably was provided by the favorable environment and a special way the Ust-Ishim man originally was buried. Results of study of the chemical and mineral composition of the bone fossils allowed a reconstruction of the Ust-Ishim man life history.ΠΠΏΠ΅ΡΠ²ΡΠ΅ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΎ ΠΌΠΈΠ½Π΅ΡΠ°Π»ΠΎΠ³ΠΎ-Π³Π΅ΠΎΡ
ΠΈΠΌΠΈΡΠ΅ΡΠΊΠΎΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΈΡΠΊΠΎΠΏΠ°Π΅ΠΌΠΎΠΉ ΠΊΠΎΡΡΠΈ Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΡΠΈΡΠΎΠΊΠΎΠ³ΠΎ ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠ° ΡΠΈΠ·ΠΈΡΠ΅ΡΠΊΠΈΡ
, ΡΠΈΠ·ΠΈΠΊΠΎ-Ρ
ΠΈΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈ Ρ
ΠΈΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ²: ΡΠ΅ΡΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π°, ΠΎΠΏΡΠΈΡΠ΅ΡΠΊΠΎΠΉ, ΡΠΊΠ°Π½ΠΈΡΡΡΡΠ΅ΠΉ ΡΠ»Π΅ΠΊΡΡΠΎΠ½Π½ΠΎΠΉ, ΡΠΊΠ°Π½ΠΈΡΡΡΡΠ΅ΠΉ Π·ΠΎΠ½Π΄ΠΎΠ²ΠΎΠΉ ΠΌΠΈΠΊΡΠΎΡΠΊΠΎΠΏΠΈΠΈ, ΠΊΠ°ΠΏΠΈΠ»Π»ΡΡΠ½ΠΎΠΉ ΠΊΠΎΠ½Π΄Π΅Π½ΡΠ°ΡΠΈΠΈ Π°Π·ΠΎΡΠ°, ΡΠ΅Π½ΡΠ³Π΅Π½ΡΠ»ΡΠΎΡΠ΅ΡΡΠ΅Π½ΡΠ½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π°, ΠΠ‘Π-ΠΠ‘, Π³Π°Π·ΠΎΠ²ΠΎΠΉ Ρ
ΡΠΎΠΌΠ°ΡΠΎΠ³ΡΠ°ΡΠΈΠΈ, ΡΠ΅Π½ΡΠ³Π΅Π½ΠΎΡΠΏΠ΅ΠΊΡΡΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΠΌΠΈΠΊΡΠΎΠ·ΠΎΠ½Π΄ΠΎΠ²ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π°, ΡΠ΅Π½ΡΠ³Π΅Π½ΠΎΠ²ΡΠΊΠΎΠΉ Π΄ΠΈΡΡΠ°ΠΊΡΠΈΠΈ, ΠΈΠ½ΡΡΠ°ΠΊΡΠ°ΡΠ½ΠΎΠΉ ΠΈ ΠΠ ΡΠΏΠ΅ΠΊΡΡΠΎΡΠΊΠΎΠΏΠΈΠΈ, ΠΈΠ·ΠΎΡΠΎΠΏΠ½ΠΎΠΉ ΡΠΏΠ΅ΠΊΡΡΠΎΠΌΠ΅ΡΡΠΈΠΈ. ΠΠ·ΡΡΠ΅Π½Π½ΡΠΉ Π½Π°ΠΌΠΈ ΡΡΠ°Π³ΠΌΠ΅Π½Ρ ΠΊΠΎΡΡΠΈ ΡΡΡΡΠΈΡΠΈΠΌΡΠΊΠΎΠ³ΠΎ ΡΠ΅Π»ΠΎΠ²Π΅ΠΊΠ° Π½Π° ΡΠΎΠ½Π΅ ΠΊΠΎΡΡΠ½ΠΎΠ³ΠΎ Π΄Π΅ΡΡΠΈΡΠ° ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
Π΅ΠΌΡ ΠΈ Π΄Π°ΠΆΠ΅ Π·Π½Π°ΡΠΈΡΠ΅Π»ΡΠ½ΠΎ Π±ΠΎΠ»Π΅Π΅ ΠΌΠΎΠ»ΠΎΠ΄ΡΡ
ΠΏΠ»Π΅ΠΉΡΡΠΎΡΠ΅Π½ΠΎΠ²ΡΡ
ΠΏΡΠΎΠΌΡΡΠ»ΠΎΠ²ΡΡ
ΠΆΠΈΠ²ΠΎΡΠ½ΡΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΡΠ΅ΡΡΡ Π°Π½ΠΎΠΌΠ°Π»ΡΠ½ΠΎ Π²ΡΡΠΎΠΊΠΎΠΉ ΡΡΠ΅ΠΏΠ΅Π½ΡΡ ΡΠΎΡ
ΡΠ°Π½Π½ΠΎΡΡΠΈ ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΈ ΠΏΠΎ Π²ΡΠ΅ΠΌ ΡΠ²ΠΎΠΈΠΌ ΡΠ²ΠΎΠΉΡΡΠ²Π°ΠΌ. Π€Π΅Π½ΠΎΠΌΠ΅Π½ ΡΡΠΎΠ»Ρ Π°Π½ΠΎΠΌΠ°Π»ΡΠ½ΠΎΠΉ ΡΠΎΡ
ΡΠ°Π½Π½ΠΎΡΡΠΈ ΠΌΠΎΠΆΠ½ΠΎ ΠΎΠ±ΡΡΡΠ½ΠΈΡΡ ΡΠ΅ΠΌ, ΡΡΠΎ ΡΡΡΡΠΈΡΠΈΠΌΡΠΊΠΈΠΉ ΡΠ΅Π»ΠΎΠ²Π΅ΠΊ ΠΏΠ΅ΡΠ²ΠΎΠ½Π°ΡΠ°Π»ΡΠ½ΠΎ Π±ΡΠ» Π·Π°Ρ
ΠΎΡΠΎΠ½Π΅Π½ Π»ΠΈΠ±ΠΎ Π² ΠΎΡΠΎΠ±ΠΎΠΌ ΠΌΠ΅ΡΡΠ΅, Π»ΠΈΠ±ΠΎ ΠΎΡΠΎΠ±Π΅Π½Π½ΡΠΌ ΡΠΏΠΎΡΠΎΠ±ΠΎΠΌ
ΠΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠΈ ΠΊΠΎΠ½ΡΠ°ΠΊΡΠ° Ρ Π»Π΅ΡΠ°ΡΠΈΠΌ Π²ΡΠ°ΡΠΎΠΌ ΠΈ ΡΠ΄ΠΎΠ²Π»Π΅ΡΠ²ΠΎΡΠ΅Π½Π½ΠΎΡΡΡ ΠΏΠΎΠ»ΡΡΠ°Π΅ΠΌΠΎΠΉ ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΎΠΉ ΠΏΠΎΠΌΠΎΡΡΡ Ρ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ², Π³ΠΎΡΠΏΠΈΡΠ°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Π½ΡΡ Π² ΡΠ²ΡΠ·ΠΈ Ρ ΠΏΠΎΠ΄ΡΠ²Π΅ΡΠΆΠ΄Π΅Π½Π½ΡΠΌ COVID-19
Background. The number of hospitalized patients diagnosed with coronavirus infection in MarchMay 2020 increased in almost all countries. Of course, such a pandemic has become a challenge for the entire health care system. In the current conditions, maintaining high standards of quality of medical care, establishing contact between specialists and the patient is a separate difficult task; at the same time, it is precisely the contact with specialists and the subjectively perceived quality of care that plays an important role in establishing compliance, and, therefore, in the success of patient treatment. Our research is devoted to the search for ways to solve this problem.
Aims to study the features of the emotional state of patients hospitalized for COVID-19 and describe the contribution of these features to interaction in the doctor-patient dyad and satisfaction with the medical care received.
Methods. The study involved 127 people hospitalized with a confirmed diagnosis of COVID-19. The research methods used: 1) a questionnaire developed by the authors, which included socio-demographic data and a block of questions about interaction with a doctor and medical personnel; 2) the Russian-language version of the Beck Depression Inventory; 3) Russian-language version of the GAD-7 anxiety questionnaire.
Results. 25.4% of participants have pronounced signs of anxiety, 24.13% signs of depression; 54% of patients indicate that the help they receive in the framework of hospitalization is sufficient; 7% speak of the need for support from a psychologist. Formulated information about what is happening with the patient is the key factor in contact with a doctor (for 62.9%), and a visible improvement in well-being is important only for 43.4%. The presence of anxious and depressive symptoms makes a qualitative difference in establishing contact with a doctor and assessing the severity of ones own condition.
Conclusions. Based on the results of the study, in the future, it is possible to formulate various strategies for working with patients showing high rates of depressive and anxious experiences: such strategies should take into account the importance of close contact with the doctor and detailed information for patients. It is also important when building further work to take into account age characteristics (for example, a greater focus on working with a psychologist among the young population group), the time of hospitalization (whether they coincide with the dates traditionally significant in culture) and the gender of patients. It is also important to take into account that in a COVID-19 situation, it is decisive in contact with a doctor to obtain clear and accessible information about the patients condition and prescriptions made on time, and not a significant improvement in well-being.ΠΠ±ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΠ΅. Π§ΠΈΡΠ»Π΅Π½Π½ΠΎΡΡΡ Π³ΠΎΡΠΏΠΈΡΠ°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ ΠΊΠΎΡΠΎΠ½Π°Π²ΠΈΡΡΡΠ½ΠΎΠΉ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠ΅ΠΉ Π² ΠΌΠ°ΡΡΠ΅ΠΌΠ°Π΅ 2020 Π³. ΡΠΎΡΠ»Π° ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΈ Π²ΠΎ Π²ΡΠ΅Ρ
ΡΡΡΠ°Π½Π°Ρ
. ΠΠ΅Π·ΡΡΠ»ΠΎΠ²Π½ΠΎ, ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΡ ΡΡΠ°Π»Π° Π²ΡΠ·ΠΎΠ²ΠΎΠΌ Π΄Π»Ρ Π²ΡΠ΅ΠΉ ΡΠΈΡΡΠ΅ΠΌΡ Π·Π΄ΡΠ°Π²ΠΎΠΎΡ
ΡΠ°Π½Π΅Π½ΠΈΡ. Π ΡΠ»ΠΎΠΆΠΈΠ²ΡΠΈΡ
ΡΡ ΡΡΠ»ΠΎΠ²ΠΈΡΡ
ΡΠΎΠ±Π»ΡΠ΄Π΅Π½ΠΈΠ΅ Π²ΡΡΠΎΠΊΠΈΡ
ΡΡΠ°Π½Π΄Π°ΡΡΠΎΠ² ΠΊΠ°ΡΠ΅ΡΡΠ²Π° ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΎΠΉ ΠΏΠΎΠΌΠΎΡΠΈ, ΡΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½ΠΈΠ΅ ΠΊΠΎΠ½ΡΠ°ΠΊΡΠ° ΠΌΠ΅ΠΆΠ΄Ρ ΡΠΏΠ΅ΡΠΈΠ°Π»ΠΈΡΡΠ°ΠΌΠΈ ΠΈ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠΌ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»ΡΡΡ ΠΎΡΠ΄Π΅Π»ΡΠ½ΡΡ ΡΠ»ΠΎΠΆΠ½ΡΡ Π·Π°Π΄Π°ΡΡ. ΠΡΠΈ ΡΡΠΎΠΌ ΠΈΠΌΠ΅Π½Π½ΠΎ ΠΊΠΎΠ½ΡΠ°ΠΊΡ ΡΠΎ ΡΠΏΠ΅ΡΠΈΠ°Π»ΠΈΡΡΠΎΠΌ ΠΈ ΡΡΠ±ΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎ Π²ΠΎΡΠΏΡΠΈΠ½ΠΈΠΌΠ°Π΅ΠΌΠΎΠ΅ ΠΊΠ°ΡΠ΅ΡΡΠ²ΠΎ ΠΏΠΎΠΌΠΎΡΠΈ ΠΈΠ³ΡΠ°ΡΡ Π±ΠΎΠ»ΡΡΡΡ ΡΠΎΠ»Ρ Π² ΡΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½ΠΈΠΈ ΠΊΠΎΠΌΠΏΠ»Π°Π΅Π½ΡΠ°, Π° Π·Π½Π°ΡΠΈΡ, ΠΈ Π² ΡΡΠΏΠ΅ΡΠ½ΠΎΡΡΠΈ Π»Π΅ΡΠ΅Π½ΠΈΡ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ². ΠΠΎΠΈΡΠΊΠ°ΠΌ ΠΏΡΡΠ΅ΠΉ ΡΠ΅ΡΠ΅Π½ΠΈΡ ΡΡΠΎΠΉ Π·Π°Π΄Π°ΡΠΈ ΠΏΠΎΡΠ²ΡΡΠ΅Π½ΠΎ Π½Π°ΡΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅.
Π¦Π΅Π»Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΈΠ·ΡΡΠΈΡΡ ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠΈ ΡΠΌΠΎΡΠΈΠΎΠ½Π°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΠΎΡΡΠΎΡΠ½ΠΈΡ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ², Π³ΠΎΡΠΏΠΈΡΠ°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
Π² ΡΠ²ΡΠ·ΠΈ Ρ COVID-19, ΠΈ ΠΎΠΏΠΈΡΠ°ΡΡ Π²ΠΊΠ»Π°Π΄ ΡΡΠΈΡ
ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠ΅ΠΉ Π²ΠΎ Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΠ΅ Π² Π΄ΠΈΠ°Π΄Π΅ Π²ΡΠ°ΡΠΏΠ°ΡΠΈΠ΅Π½Ρ ΠΈ ΡΠ΄ΠΎΠ²Π»Π΅ΡΠ²ΠΎΡΠ΅Π½Π½ΠΎΡΡΡ ΠΏΠΎΠ»ΡΡΠ°Π΅ΠΌΠΎΠΉ ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΎΠΉ ΠΏΠΎΠΌΠΎΡΡΡ.
ΠΠ΅ΡΠΎΠ΄Ρ. Π ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΈ ΠΏΡΠΈΠ½ΡΠ»ΠΈ ΡΡΠ°ΡΡΠΈΠ΅ 127 ΡΠ΅Π»ΠΎΠ²Π΅ΠΊ, Π³ΠΎΡΠΏΠΈΡΠ°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
Π² ΠΊΠ»ΠΈΠ½ΠΈΠΊΡ Π² ΡΠ²ΡΠ·ΠΈ Ρ ΠΏΠΎΠ΄ΡΠ²Π΅ΡΠΆΠ΄Π΅Π½Π½ΡΠΌ Π΄ΠΈΠ°Π³Π½ΠΎΠ·ΠΎΠΌ COVID-19. Π ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π»ΠΈΡΡ: 1) ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½Π½Π°Ρ Π°Π²ΡΠΎΡΠ°ΠΌΠΈ Π°Π½ΠΊΠ΅ΡΠ°, Π²ΠΊΠ»ΡΡΠ°Π²ΡΠ°Ρ ΡΠΎΡΠΈΠΎΠ΄Π΅ΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ Π΄Π°Π½Π½ΡΠ΅ ΠΈ Π±Π»ΠΎΠΊ Π²ΠΎΠΏΡΠΎΡΠΎΠ² ΠΎ Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΠΈ Ρ Π»Π΅ΡΠ°ΡΠΈΠΌ Π²ΡΠ°ΡΠΎΠΌ ΠΈ ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΈΠΌ ΠΏΠ΅ΡΡΠΎΠ½Π°Π»ΠΎΠΌ; 2) ΡΡΡΡΠΊΠΎΡΠ·ΡΡΠ½Π°Ρ Π²Π΅ΡΡΠΈΡ ΠΎΠΏΡΠΎΡΠ½ΠΈΠΊΠ° Π΄Π΅ΠΏΡΠ΅ΡΡΠΈΠΈ ΠΠ΅ΠΊΠ°; 3) ΡΡΡΡΠΊΠΎΡΠ·ΡΡΠ½Π°Ρ Π²Π΅ΡΡΠΈΡ ΠΎΠΏΡΠΎΡΠ½ΠΈΠΊΠ° ΡΡΠ΅Π²ΠΎΠ³ΠΈ GAD-7.
Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. 25,4% ΡΡΠ°ΡΡΠ½ΠΈΠΊΠΎΠ² ΠΈΠΌΠ΅ΡΡ Π²ΡΡΠ°ΠΆΠ΅Π½Π½ΡΠ΅ ΠΏΡΠΈΠ·Π½Π°ΠΊΠΈ ΡΡΠ΅Π²ΠΎΠΆΠ½ΠΎΡΡΠΈ; 24,13% ΠΏΡΠΈΠ·Π½Π°ΠΊΠΈ Π΄Π΅ΠΏΡΠ΅ΡΡΠΈΠΈ; 54% ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² ΡΠΊΠ°Π·ΡΠ²Π°ΡΡ, ΡΡΠΎ ΠΏΠΎΠ»ΡΡΠ°Π΅ΠΌΠ°Ρ ΠΈΠΌΠΈ Π² ΡΠ°ΠΌΠΊΠ°Ρ
Π³ΠΎΡΠΏΠΈΡΠ°Π»ΠΈΠ·Π°ΡΠΈΠΈ ΠΏΠΎΠΌΠΎΡΡ Π΄ΠΎΡΡΠ°ΡΠΎΡΠ½Π°; 7% Π³ΠΎΠ²ΠΎΡΡΡ ΠΎ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎΡΡΠΈ ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΠΈ ΠΏΡΠΈΡ
ΠΎΠ»ΠΎΠ³Π°. ΠΠ»ΡΡΠ΅Π²ΡΠΌ ΡΠ°ΠΊΡΠΎΡΠΎΠΌ Π² ΠΊΠΎΠ½ΡΠ°ΠΊΡΠ΅ Ρ Π²ΡΠ°ΡΠΎΠΌ ΠΎΠΊΠ°Π·ΡΠ²Π°Π΅ΡΡΡ Π΄ΠΎΡΡΡΠΏΠ½ΠΎ ΡΡΠΎΡΠΌΡΠ»ΠΈΡΠΎΠ²Π°Π½Π½Π°Ρ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΡ ΠΎ ΠΏΡΠΎΠΈΡΡ
ΠΎΠ΄ΡΡΠ΅ΠΌ Ρ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠΌ (Π΄Π»Ρ 62,9%), Π° Π²ΠΈΠ΄ΠΈΠΌΠΎΠ΅ ΡΠ»ΡΡΡΠ΅Π½ΠΈΠ΅ ΡΠ°ΠΌΠΎΡΡΠ²ΡΡΠ²ΠΈΡ Π²Π°ΠΆΠ½ΠΎ Π»ΠΈΡΡ Π΄Π»Ρ 43,4%. ΠΠ°Π»ΠΈΡΠΈΠ΅ ΡΡΠ΅Π²ΠΎΠΆΠ½ΠΎΠΉ ΠΈ Π΄Π΅ΠΏΡΠ΅ΡΡΠΈΠ²Π½ΠΎΠΉ ΡΠΈΠΌΠΏΡΠΎΠΌΠ°ΡΠΈΠΊΠΈ Π²Π½ΠΎΡΠΈΡ ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠ΅ ΠΎΡΠ»ΠΈΡΠΈΠ΅ Π² ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΠ΅ ΠΊΠΎΠ½ΡΠ°ΠΊΡΠ° Ρ Π²ΡΠ°ΡΠΎΠΌ ΠΈ ΠΎΡΠ΅Π½ΠΊΡ ΡΡΠΆΠ΅ΡΡΠΈ ΡΠΎΠ±ΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ ΡΠΎΡΡΠΎΡΠ½ΠΈΡ.
ΠΠ°ΠΊΠ»ΡΡΠ΅Π½ΠΈΠ΅. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡ ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°ΡΡ ΡΠ°Π·Π»ΠΈΡΠ½ΡΠ΅ Π²Π°ΡΠΈΠ°Π½ΡΡ ΡΠ°Π±ΠΎΡΡ Ρ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠ°ΠΌΠΈ, Π΄Π΅ΠΌΠΎΠ½ΡΡΡΠΈΡΡΡΡΠΈΠΌΠΈ Π²ΡΡΠΎΠΊΠΈΠ΅ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΠΈ Π΄Π΅ΠΏΡΠ΅ΡΡΠΈΠ²Π½ΡΡ
ΠΈ ΡΡΠ΅Π²ΠΎΠΆΠ½ΡΡ
ΠΏΠ΅ΡΠ΅ΠΆΠΈΠ²Π°Π½ΠΈΠΉ: ΠΏΠΎΠ΄ΠΎΠ±Π½ΡΠ΅ Π²Π°ΡΠΈΠ°Π½ΡΡ Π΄ΠΎΠ»ΠΆΠ½Ρ ΡΡΠΈΡΡΠ²Π°ΡΡ Π·Π½Π°ΡΠΈΠΌΠΎΡΡΡ Π±Π»ΠΈΠ·ΠΊΠΎΠ³ΠΎ ΠΊΠΎΠ½ΡΠ°ΠΊΡΠ° Ρ Π²ΡΠ°ΡΠΎΠΌ ΠΈ ΠΏΠΎΠ΄ΡΠΎΠ±Π½ΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ Π΄Π»Ρ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ². Π’Π°ΠΊΠΆΠ΅ Π²Π°ΠΆΠ½ΠΎ ΠΏΡΠΈ Π²ΡΡΡΡΠ°ΠΈΠ²Π°Π½ΠΈΠΈ Π΄Π°Π»ΡΠ½Π΅ΠΉΡΠ΅ΠΉ ΡΠ°Π±ΠΎΡΡ ΠΏΡΠΈΠ½ΠΈΠΌΠ°ΡΡ Π²ΠΎ Π²Π½ΠΈΠΌΠ°Π½ΠΈΠ΅ Π²ΠΎΠ·ΡΠ°ΡΡΠ½ΡΠ΅ ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠΈ, Π²ΡΠ΅ΠΌΡ Π³ΠΎΡΠΏΠΈΡΠ°Π»ΠΈΠ·Π°ΡΠΈΠΈ ΠΈ ΠΏΠΎΠ» ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ². Π‘Π»Π΅Π΄ΡΠ΅Ρ ΡΡΠΈΡΡΠ²Π°ΡΡ, ΡΡΠΎ Π² ΡΠΈΡΡΠ°ΡΠΈΠΈ COVID-19 ΡΠ΅ΡΠ°ΡΡΠΈΠΌΠΈ Π² ΠΊΠΎΠ½ΡΠ°ΠΊΡΠ΅ Ρ Π²ΡΠ°ΡΠΎΠΌ ΠΎΠΊΠ°Π·ΡΠ²Π°ΡΡΡΡ ΠΏΠΎΠ»ΡΡΠ΅Π½ΠΈΠ΅ ΠΏΠΎΠ½ΡΡΠ½ΠΎΠΉ ΠΈ Π΄ΠΎΡΡΡΠΏΠ½ΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ ΠΎ ΡΠΎΡΡΠΎΡΠ½ΠΈΠΈ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠ° ΠΈ Π²ΠΎΠ²ΡΠ΅ΠΌΡ ΡΠ΄Π΅Π»Π°Π½Π½ΡΠ΅ ΠΏΡΠ΅Π΄ΠΏΠΈΡΠ°Π½ΠΈΡ, Π° Π½Π΅ Π·Π½Π°ΡΠΈΠΌΠΎΠ΅ ΡΠ»ΡΡΡΠ΅Π½ΠΈΠ΅ ΡΠ°ΠΌΠΎΡΡΠ²ΡΡΠ²ΠΈΡ
On the status and selectivity of the infant burials of the Yamnaya Archaeological Culture of the Southern Urals (based on the excavation materials of the burial mound No. 1 of the Boldyrevo-4 group)
Bioarchaeology is an important field of interdisciplinary research based upon the contextual study of anthropological materials. In particular, bioarchaeology of childhood appears to be the most specialised area of research, addressing quality of life and social patterns of ancient groups. In this paper, we continue the study of the infant remains from the burial mound No. 1 of the Boldyrevo-4 burial ground β one of the elite and largest burial mounds of the Yamnaya (Pit Grave) Culture in the northern part of the Volga-Urals. It was located on the left bank of the Irtek River, a tributary of the Ural, and had a diameter of 62 m and a reconstructed height of 8 m. The earliest horizon was represented by mounds Nos. 1 and 2 with close parameters. They contained one burial each (burials Nos. 3 and 4, respectively), located in the centers of the mound platforms, which belonged to children. Based on the results of our preliminary study, the child from burial No. 3 died of metastatic cancer (the most probable diagnosis is lymphocytic leukaemia). Burial No. 4 contained remains of two children. Child No. 1 from burial No. 4, represented only by the cranium, had possibly suffered from scurvy. Here we publish the results of the analysis of ancient DNA aimed at identifying the sex of the interred, as well as the results of the Sr isotope analysis, which allows determination of their βlocalβ or βdistantβ origin. The quality of the ancient DNA was evaluated by targeted sequencing carried out using a specially designed panel of probes that allowed the selection of target sections of the genome for subsequent enrichment using the method of hybridisation, followed by the target NGS. The genetic data confirm that all three individuals belonged to the female sex. On the basis of Sr isotope ratios, the girls from burials Nos. 3 and 4 (No. 2) were born in the territories with different geochemical signals. Unfortunately, for the child No. 1 from burial No. 4 such observations could not be obtained. The biological age (around 6 years old), female sex attributes, and the presence of serious health conditions allows one to pose the question on the selective nature of the children burials in this mound of the Yamnaya Culture. Moreover, they could have received a special hereditary social status, which influenced the further erection of the burial mound for members of the elite
ΠΠ½Π°Π»ΠΈΠ· ΠΌΡΡΠ°ΡΠΈΠΉ Π² Π³Π΅Π½Π°Ρ CDC27, CTBP2, HYDIN ΠΈ KMT5A ΠΏΡΠΈ ΠΊΠ°ΡΠΎΡΠΈΠ΄Π½ΡΡ ΠΏΠ°ΡΠ°Π³Π°Π½Π³Π»ΠΈΠΎΠΌΠ°Ρ
Carotid paragangliomas (CPGLs) are rare neuroendocrine tumors that arise from paraganglionic tissue of the carotid body localizing at the bifurcation of carotid artery. These tumors are slowly growing, but occasionally they become aggressive and metastatic. Surgical treatment remains high-risk and extremely challenging; radiation and chemotherapy are poorly effective. The study of molecular pathogenesis of CPGLs will allow developing novel therapeutic approaches and revealing biomarkers. Previously, we performed the exome sequencing of 52 CPGLs and estimated mutational load (ML). Paired histologically normal tissues or blood were unavailable, so potentially germline mutations were excluded from the analysis with strong filtering conditions using 1000 Genomes Project and ExAC databases. In this work, ten genes (ZNF717, CDC27, FRG2C, FAM104B, CTBP2, HLA-DRB1, HYDIN, KMT5A, MUC3A, and PRSS3) characterized by the highest level of mutational load were analyzed. Using several prediction algorithms (SIFT, PolyPhen-2, MutationTaster, and LRT), potentially pathogenic mutations were identified in four genes (CDC27, CTBP2, HYDIN, and KMT5A). Many of these mutations occurred in the majority of cases, and their mutation type was checked using exome sequencing data of blood prepared with the same exome enrichment kit that was used for preparation of exome libraries from CPGLs. The majority of the mutations were germline that can apparently be associated with annotation errors in 1000 Genomes Project and ExAC. However, part of the mutations identified in CDC27, CTBP2, HYDIN, and KMT5A remain potentially pathogenic, and there is a large body of data on the involvement of these genes in the formation and progression of other tumors. This allows considering CDC27, CTBP2, HYDIN, and KMT5A genes as potentially associated with CPGL pathogenesis and requires taking them into account in further investigations. Thus, there is a necessity to improve the methods for identification of cancer-associated genes as well as pathogenic mutations.ΠΠ°ΡΠΎΡΠΈΠ΄Π½ΡΠ΅ ΠΏΠ°ΡΠ°Π³Π°Π½Π³Π»ΠΈΠΎΠΌΡ (ΠΠΠ) - ΡΠ΅Π΄ΠΊΠΈΠ΅ Π½Π΅ΠΉΡΠΎΡΠ½Π΄ΠΎΠΊΡΠΈΠ½Π½ΡΠ΅ ΠΎΠΏΡΡ
ΠΎΠ»ΠΈ, ΠΊΠΎΡΠΎΡΡΠ΅ ΡΠ°Π·Π²ΠΈΠ²Π°ΡΡΡΡ ΠΈΠ· ΠΏΠ°ΡΠ°Π³Π°Π½Π³Π»ΠΈΠΎΠ½Π°ΡΠ½ΠΎΠΉ ΡΠΊΠ°Π½ΠΈ ΠΊΠ°ΡΠΎΡΠΈΠ΄Π½ΠΎΠ³ΠΎ ΡΠ΅Π»ΡΡΠ° ΠΈ ΡΠ°ΡΠΏΠΎΠ»Π°Π³Π°ΡΡΡΡ Π² ΠΎΠ±Π»Π°ΡΡΠΈ Π±ΠΈΡΡΡΠΊΠ°ΡΠΈΠΈ ΡΠΎΠ½Π½ΠΎΠΉ Π°ΡΡΠ΅ΡΠΈΠΈ. ΠΡΠΈ ΠΎΠΏΡΡ
ΠΎΠ»ΠΈ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΡΡΡΡΡ ΠΌΠ΅Π΄Π»Π΅Π½Π½ΡΠΌ ΡΠΎΡΡΠΎΠΌ, ΠΎΠ΄Π½Π°ΠΊΠΎ Π² ΡΡΠ΄Π΅ ΡΠ»ΡΡΠ°Π΅Π² Π½Π°Π±Π»ΡΠ΄Π°Π΅ΡΡΡ Π°Π³ΡΠ΅ΡΡΠΈΠ²Π½ΠΎΠ΅ ΡΠ΅ΡΠ΅Π½ΠΈΠ΅ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΡ ΠΈ ΠΌΠ΅ΡΠ°ΡΡΠ°Π·ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅. ΠΠΏΠ΅ΡΠ°ΡΠΈΠΈ ΠΏΠΎ ΡΠ΄Π°Π»Π΅Π½ΠΈΡ ΠΊΠ°ΡΠΎΡΠΈΠ΄Π½ΡΡ
ΠΏΠ°ΡΠ°Π³Π°Π½Π³Π»ΠΈΠΎΠΌ ΡΠΎΠΏΡΡΠΆΠ΅Π½Ρ Ρ Π²ΡΡΠΎΠΊΠΈΠΌ ΡΠΈΡΠΊΠΎΠΌ ΠΎΡΠ»ΠΎΠΆΠ½Π΅Π½ΠΈΠΉ, Π² ΡΠΎ Π²ΡΠ΅ΠΌΡ ΠΊΠ°ΠΊ Π»ΡΡΠ΅Π²Π°Ρ ΠΈ Ρ
ΠΈΠΌΠΈΠΎΡΠ΅ΡΠ°ΠΏΠΈΡ ΠΌΠ°Π»ΠΎΡΡΡΠ΅ΠΊΡΠΈΠ²Π½Ρ. ΠΠ·ΡΡΠ΅Π½ΠΈΠ΅ ΠΌΠΎΠ»Π΅ΠΊΡΠ»ΡΡΠ½ΠΎΠ³ΠΎ ΠΏΠ°ΡΠΎΠ³Π΅Π½Π΅Π·Π° ΠΠΠ ΠΌΠΎΠΆΠ΅Ρ ΡΠΏΠΎΡΠΎΠ±ΡΡΠ²ΠΎΠ²Π°ΡΡ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ΅ Π½ΠΎΠ²ΡΡ
ΠΏΠΎΠ΄Ρ
ΠΎΠ΄ΠΎΠ² ΠΊ ΡΠ΅ΡΠ°ΠΏΠΈΠΈ ΠΈ ΠΎΡΠΊΡΡΡΠΈΡ Π±ΠΈΠΎΠΌΠ°ΡΠΊΠ΅ΡΠΎΠ². Π Π°Π½Π΅Π΅ Π½Π°ΠΌΠΈ Π²ΡΠΏΠΎΠ»Π½Π΅Π½ΠΎ Π²ΡΡΠΎΠΊΠΎΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΡΠ΅Π»ΡΠ½ΠΎΠ΅ ΡΠ΅ΠΊΠ²Π΅Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΡΠΊΠ·ΠΎΠΌΠ° 52 Π°ΡΡ
ΠΈΠ²Π½ΡΡ
ΠΎΠ±ΡΠ°Π·ΡΠΎΠ² ΠΠΠ, ΠΎΠ΄Π½ΠΎΠΉ ΠΈΠ· Π·Π°Π΄Π°Ρ ΠΊΠΎΡΠΎΡΠΎΠ³ΠΎ Π±ΡΠ»Π° ΠΎΡΠ΅Π½ΠΊΠ° ΠΌΡΡΠ°ΡΠΈΠΎΠ½Π½ΠΎΠΉ Π½Π°Π³ΡΡΠ·ΠΊΠΈ. ΠΠ·-Π·Π° ΠΎΡΡΡΡΡΡΠ²ΠΈΡ ΠΏΠ°ΡΠ½ΡΡ
ΠΎΠ±ΡΠ°Π·ΡΠΎΠ² Π³ΠΈΡΡΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈ Π½ΠΎΡΠΌΠ°Π»ΡΠ½ΡΡ
ΡΠΊΠ°Π½Π΅ΠΉ ΠΈΠ»ΠΈ ΠΊΡΠΎΠ²ΠΈ ΠΏΠΎΡΠ΅Π½ΡΠΈΠ°Π»ΡΠ½ΠΎ Π³Π΅ΡΠΌΠΈΠ½Π°Π»ΡΠ½ΡΠ΅ ΠΌΡΡΠ°ΡΠΈΠΈ Π±ΡΠ»ΠΈ ΠΈΡΠΊΠ»ΡΡΠ΅Π½Ρ ΠΈΠ· Π²ΡΠ±ΠΎΡΠΊΠΈ Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ Π±Π°Π· Π΄Π°Π½Π½ΡΡ
1000 Genomes Project ΠΈ ExAC ΠΏΡΠΈ ΡΡΡΠΎΠ³ΠΈΡ
ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠ°Ρ
ΡΠΈΠ»ΡΡΡΠ°ΡΠΈΠΈ. Π Π½Π°ΡΡΠΎΡΡΠ΅ΠΌ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΈ ΠΏΡΠΎΠ°Π½Π°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Ρ Π΄Π΅ΡΡΡΡ Π³Π΅Π½ΠΎΠ² (ZNF717, CDC27, FRG2C, FAM104B, CTBP2, HLA-DRB1, HYDIN, KMT5A, MUC3A ΠΈ PRSS3), Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΡΡΡΠΈΡ
ΡΡ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ Π²ΡΡΠΎΠΊΠΎΠΉ ΠΌΡΡΠ°ΡΠΈΠΎΠ½Π½ΠΎΠΉ Π½Π°Π³ΡΡΠ·ΠΊΠΎΠΉ. Π ΡΠ΅ΡΡΡΠ΅Ρ
Π³Π΅Π½Π°Ρ
(CDC27, CTBP2, HYDIN ΠΈ KMT5A) ΠΈΠ΄Π΅Π½ΡΠΈΡΠΈΡΠΈΡΠΎΠ²Π°Π½Ρ ΠΏΠΎΡΠ΅Π½ΡΠΈΠ°Π»ΡΠ½ΠΎ ΠΏΠ°ΡΠΎΠ³Π΅Π½Π½ΡΠ΅ ΠΌΡΡΠ°ΡΠΈΠΈ, ΡΠΎΠ³Π»Π°ΡΠ½ΠΎ Π½Π΅ΡΠΊΠΎΠ»ΡΠΊΠΈΠΌ ΠΏΡΠ΅Π΄ΡΠΊΠ°Π·Π°ΡΠ΅Π»ΡΠ½ΡΠΌ Π°Π»Π³ΠΎΡΠΈΡΠΌΠ°ΠΌ (SIFT, PolyPhen-2, MutationTaster ΠΈ LRT). ΠΠ½ΠΎΠ³ΠΈΠ΅ Π²ΡΡΠ²Π»Π΅Π½Π½ΡΠ΅ ΠΌΡΡΠ°ΡΠΈΠΈ ΠΎΠΊΠ°Π·Π°Π»ΠΈΡΡ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Π½ΡΠΌΠΈ Π² Π±ΠΎΠ»ΡΡΠΎΠΌ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅ ΠΎΠ±ΡΠ°Π·ΡΠΎΠ² Π²ΡΠ±ΠΎΡΠΊΠΈ, ΡΡΠΎ Π·Π°ΡΡΠ°Π²ΠΈΠ»ΠΎ ΠΏΡΠΎΠ²Π΅ΡΠΈΡΡ ΠΈΡ
ΡΠΎΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠΉ ΡΡΠ°ΡΡΡ Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ Π΄ΠΎΠΏΠΎΠ»Π½ΠΈΡΠ΅Π»ΡΠ½ΡΡ
Π΄Π°Π½Π½ΡΡ
ΡΠ΅ΠΊΠ²Π΅Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠΊΠ·ΠΎΠΌΠ° ΠΊΡΠΎΠ²ΠΈ, Π²ΡΠΏΠΎΠ»Π½Π΅Π½Π½ΠΎΠ³ΠΎ Ρ ΡΠ°ΠΊΠΈΠΌ ΠΆΠ΅ Π½Π°Π±ΠΎΡΠΎΠΌ Π΄Π»Ρ ΡΠΊΠ·ΠΎΠΌΠ½ΠΎΠ³ΠΎ ΠΎΠ±ΠΎΠ³Π°ΡΠ΅Π½ΠΈΡ, ΠΊΠ°ΠΊ ΠΈ ΠΏΡΠΈ Π°Π½Π°Π»ΠΈΠ·Π΅ ΠΎΠΏΡΡ
ΠΎΠ»Π΅ΠΉ ΠΠΠ. ΠΠ±Π½Π°ΡΡΠΆΠ΅Π½ΠΎ, ΡΡΠΎ Π·Π½Π°ΡΠΈΡΠ΅Π»ΡΠ½ΠΎΠ΅ ΡΠΈΡΠ»ΠΎ Π²ΡΡΠ²Π»Π΅Π½Π½ΡΡ
ΠΏΠΎΡΠ΅Π½ΡΠΈΠ°Π»ΡΠ½ΠΎ ΠΏΠ°ΡΠΎΠ³Π΅Π½Π½ΡΡ
ΠΌΡΡΠ°ΡΠΈΠΉ ΡΠ²Π»ΡΡΡΡΡ Π³Π΅ΡΠΌΠΈΠ½Π°Π»ΡΠ½ΡΠΌΠΈ, ΡΡΠΎ, ΠΏΠΎ-Π²ΠΈΠ΄ΠΈΠΌΠΎΠΌΡ, ΡΠ²ΡΠ·Π°Π½ΠΎ Ρ Π½Π°Π»ΠΈΡΠΈΠ΅ΠΌ ΠΎΡΠΈΠ±ΠΎΠΊ Π°Π½Π½ΠΎΡΠ°ΡΠΈΠΈ Π² Π±Π°Π·Π°Ρ
Π΄Π°Π½Π½ΡΡ
1000 Genomes Project ΠΈ ExAC. ΠΠ΄Π½Π°ΠΊΠΎ ΡΠ°ΡΡΡ ΠΈΠ΄Π΅Π½ΡΠΈΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
ΠΌΡΡΠ°ΡΠΈΠΉ Π² Π³Π΅Π½Π°Ρ
CDC27, CTBP2, HYDIN ΠΈ KMT5A ΠΎΡΡΠ°ΡΡΡΡ ΠΏΡΠ΅Π΄ΠΏΠΎΠ»ΠΎΠΆΠΈΡΠ΅Π»ΡΠ½ΠΎ ΠΏΠ°ΡΠΎΠ³Π΅Π½Π½ΡΠΌΠΈ, ΠΊΡΠΎΠΌΠ΅ ΡΠΎΠ³ΠΎ, ΠΈΠΌΠ΅ΡΡΡΡ ΠΌΠ½ΠΎΠ³ΠΎΡΠΈΡΠ»Π΅Π½Π½ΡΠ΅ Π΄Π°Π½Π½ΡΠ΅ ΠΎ Π²ΠΎΠ²Π»Π΅ΡΠ΅Π½Π½ΠΎΡΡΠΈ ΡΡΠΈΡ
Π³Π΅Π½ΠΎΠ² Π² ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΠΈ ΠΏΡΠΎΠ³ΡΠ΅ΡΡΠΈΡ Π΄ΡΡΠ³ΠΈΡ
Π²ΠΈΠ΄ΠΎΠ² ΠΎΠΏΡΡ
ΠΎΠ»Π΅ΠΉ. ΠΡΠΎ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ ΡΡΠΈΡΠ°ΡΡ Π³Π΅Π½Ρ CDC27, CTBP2, HYDIN ΠΈ KMT5A ΠΏΠΎΡΠ΅Π½ΡΠΈΠ°Π»ΡΠ½ΠΎ ΡΠ²ΡΠ·Π°Π½Π½ΡΠΌΠΈ Ρ ΠΏΠ°ΡΠΎΠ³Π΅Π½Π΅Π·ΠΎΠΌ ΠΠΠ ΠΈ ΡΡΠ΅Π±ΡΠ΅Ρ ΠΎΠ±ΡΠ°ΡΠΈΡΡ Π½Π° Π½ΠΈΡ
ΠΎΡΠΎΠ±ΠΎΠ΅ Π²Π½ΠΈΠΌΠ°Π½ΠΈΠ΅ Π² Π΄Π°Π»ΡΠ½Π΅ΠΉΡΠΈΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡΡ
. Π’Π°ΠΊΠΈΠΌ ΠΎΠ±ΡΠ°Π·ΠΎΠΌ, Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎ ΡΠΎΠ²Π΅ΡΡΠ΅Π½ΡΡΠ²ΠΎΠ²Π°ΡΡ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠΈ Π΄Π»Ρ Π²ΡΡΠ²Π»Π΅Π½ΠΈΡ ΠΎΠ½ΠΊΠΎ-Π°ΡΡΠΎΡΠΈΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
Π³Π΅Π½ΠΎΠ² ΠΈ ΠΏΠ°ΡΠΎΠ³Π΅Π½Π½ΡΡ
ΠΌΡΡΠ°ΡΠΈΠΉ
ΠΠ½Π°Π»ΠΈΠ· ΠΌΡΡΠ°ΡΠΈΠΉ Π² Π³Π΅Π½Π°Ρ CDC27, CTBP2, HYDIN ΠΈ KMT5A ΠΏΡΠΈ ΠΊΠ°ΡΠΎΡΠΈΠ΄Π½ΡΡ ΠΏΠ°ΡΠ°Π³Π°Π½Π³Π»ΠΈΠΎΠΌΠ°Ρ
Carotid paragangliomas (CPGLs) are rare neuroendocrine tumors that arise from paraganglionic tissue of the carotid body localizing at the bifurcation of carotid artery. These tumors are slowly growing, but occasionally they become aggressive and metastatic. Surgical treatment remains high-risk and extremely challenging; radiation and chemotherapy are poorly effective. The study of molecular pathogenesis of CPGLs will allow developing novel therapeutic approaches and revealing biomarkers. Previously, we performed the exome sequencing of 52 CPGLs and estimated mutational load (ML). Paired histologically normal tissues or blood were unavailable, so potentially germline mutations were excluded from the analysis with strong filtering conditions using 1000 Genomes Project and ExAC databases. In this work, ten genes (ZNF717, CDC27, FRG2C, FAM104B, CTBP2, HLA-DRB1, HYDIN, KMT5A, MUC3A, and PRSS3) characterized by the highest level of mutational load were analyzed. Using several prediction algorithms (SIFT, PolyPhen-2, MutationTaster, and LRT), potentially pathogenic mutations were identified in four genes (CDC27, CTBP2, HYDIN, and KMT5A). Many of these mutations occurred in the majority of cases, and their mutation type was checked using exome sequencing data of blood prepared with the same exome enrichment kit that was used for preparation of exome libraries from CPGLs. The majority of the mutations were germline that can apparently be associated with annotation errors in 1000 Genomes Project and ExAC. However, part of the mutations identified in CDC27, CTBP2, HYDIN, and KMT5A remain potentially pathogenic, and there is a large body of data on the involvement of these genes in the formation and progression of other tumors. This allows considering CDC27, CTBP2, HYDIN, and KMT5A genes as potentially associated with CPGL pathogenesis and requires taking them into account in further investigations. Thus, there is a necessity to improve the methods for identification of cancer-associated genes as well as pathogenic mutations.ΠΠ°ΡΠΎΡΠΈΠ΄Π½ΡΠ΅ ΠΏΠ°ΡΠ°Π³Π°Π½Π³Π»ΠΈΠΎΠΌΡ (ΠΠΠ) - ΡΠ΅Π΄ΠΊΠΈΠ΅ Π½Π΅ΠΉΡΠΎΡΠ½Π΄ΠΎΠΊΡΠΈΠ½Π½ΡΠ΅ ΠΎΠΏΡΡ
ΠΎΠ»ΠΈ, ΠΊΠΎΡΠΎΡΡΠ΅ ΡΠ°Π·Π²ΠΈΠ²Π°ΡΡΡΡ ΠΈΠ· ΠΏΠ°ΡΠ°Π³Π°Π½Π³Π»ΠΈΠΎΠ½Π°ΡΠ½ΠΎΠΉ ΡΠΊΠ°Π½ΠΈ ΠΊΠ°ΡΠΎΡΠΈΠ΄Π½ΠΎΠ³ΠΎ ΡΠ΅Π»ΡΡΠ° ΠΈ ΡΠ°ΡΠΏΠΎΠ»Π°Π³Π°ΡΡΡΡ Π² ΠΎΠ±Π»Π°ΡΡΠΈ Π±ΠΈΡΡΡΠΊΠ°ΡΠΈΠΈ ΡΠΎΠ½Π½ΠΎΠΉ Π°ΡΡΠ΅ΡΠΈΠΈ. ΠΡΠΈ ΠΎΠΏΡΡ
ΠΎΠ»ΠΈ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΡΡΡΡΡ ΠΌΠ΅Π΄Π»Π΅Π½Π½ΡΠΌ ΡΠΎΡΡΠΎΠΌ, ΠΎΠ΄Π½Π°ΠΊΠΎ Π² ΡΡΠ΄Π΅ ΡΠ»ΡΡΠ°Π΅Π² Π½Π°Π±Π»ΡΠ΄Π°Π΅ΡΡΡ Π°Π³ΡΠ΅ΡΡΠΈΠ²Π½ΠΎΠ΅ ΡΠ΅ΡΠ΅Π½ΠΈΠ΅ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΡ ΠΈ ΠΌΠ΅ΡΠ°ΡΡΠ°Π·ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅. ΠΠΏΠ΅ΡΠ°ΡΠΈΠΈ ΠΏΠΎ ΡΠ΄Π°Π»Π΅Π½ΠΈΡ ΠΊΠ°ΡΠΎΡΠΈΠ΄Π½ΡΡ
ΠΏΠ°ΡΠ°Π³Π°Π½Π³Π»ΠΈΠΎΠΌ ΡΠΎΠΏΡΡΠΆΠ΅Π½Ρ Ρ Π²ΡΡΠΎΠΊΠΈΠΌ ΡΠΈΡΠΊΠΎΠΌ ΠΎΡΠ»ΠΎΠΆΠ½Π΅Π½ΠΈΠΉ, Π² ΡΠΎ Π²ΡΠ΅ΠΌΡ ΠΊΠ°ΠΊ Π»ΡΡΠ΅Π²Π°Ρ ΠΈ Ρ
ΠΈΠΌΠΈΠΎΡΠ΅ΡΠ°ΠΏΠΈΡ ΠΌΠ°Π»ΠΎΡΡΡΠ΅ΠΊΡΠΈΠ²Π½Ρ. ΠΠ·ΡΡΠ΅Π½ΠΈΠ΅ ΠΌΠΎΠ»Π΅ΠΊΡΠ»ΡΡΠ½ΠΎΠ³ΠΎ ΠΏΠ°ΡΠΎΠ³Π΅Π½Π΅Π·Π° ΠΠΠ ΠΌΠΎΠΆΠ΅Ρ ΡΠΏΠΎΡΠΎΠ±ΡΡΠ²ΠΎΠ²Π°ΡΡ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ΅ Π½ΠΎΠ²ΡΡ
ΠΏΠΎΠ΄Ρ
ΠΎΠ΄ΠΎΠ² ΠΊ ΡΠ΅ΡΠ°ΠΏΠΈΠΈ ΠΈ ΠΎΡΠΊΡΡΡΠΈΡ Π±ΠΈΠΎΠΌΠ°ΡΠΊΠ΅ΡΠΎΠ². Π Π°Π½Π΅Π΅ Π½Π°ΠΌΠΈ Π²ΡΠΏΠΎΠ»Π½Π΅Π½ΠΎ Π²ΡΡΠΎΠΊΠΎΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΡΠ΅Π»ΡΠ½ΠΎΠ΅ ΡΠ΅ΠΊΠ²Π΅Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΡΠΊΠ·ΠΎΠΌΠ° 52 Π°ΡΡ
ΠΈΠ²Π½ΡΡ
ΠΎΠ±ΡΠ°Π·ΡΠΎΠ² ΠΠΠ, ΠΎΠ΄Π½ΠΎΠΉ ΠΈΠ· Π·Π°Π΄Π°Ρ ΠΊΠΎΡΠΎΡΠΎΠ³ΠΎ Π±ΡΠ»Π° ΠΎΡΠ΅Π½ΠΊΠ° ΠΌΡΡΠ°ΡΠΈΠΎΠ½Π½ΠΎΠΉ Π½Π°Π³ΡΡΠ·ΠΊΠΈ. ΠΠ·-Π·Π° ΠΎΡΡΡΡΡΡΠ²ΠΈΡ ΠΏΠ°ΡΠ½ΡΡ
ΠΎΠ±ΡΠ°Π·ΡΠΎΠ² Π³ΠΈΡΡΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈ Π½ΠΎΡΠΌΠ°Π»ΡΠ½ΡΡ
ΡΠΊΠ°Π½Π΅ΠΉ ΠΈΠ»ΠΈ ΠΊΡΠΎΠ²ΠΈ ΠΏΠΎΡΠ΅Π½ΡΠΈΠ°Π»ΡΠ½ΠΎ Π³Π΅ΡΠΌΠΈΠ½Π°Π»ΡΠ½ΡΠ΅ ΠΌΡΡΠ°ΡΠΈΠΈ Π±ΡΠ»ΠΈ ΠΈΡΠΊΠ»ΡΡΠ΅Π½Ρ ΠΈΠ· Π²ΡΠ±ΠΎΡΠΊΠΈ Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ Π±Π°Π· Π΄Π°Π½Π½ΡΡ
1000 Genomes Project ΠΈ ExAC ΠΏΡΠΈ ΡΡΡΠΎΠ³ΠΈΡ
ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠ°Ρ
ΡΠΈΠ»ΡΡΡΠ°ΡΠΈΠΈ. Π Π½Π°ΡΡΠΎΡΡΠ΅ΠΌ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΈ ΠΏΡΠΎΠ°Π½Π°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Ρ Π΄Π΅ΡΡΡΡ Π³Π΅Π½ΠΎΠ² (ZNF717, CDC27, FRG2C, FAM104B, CTBP2, HLA-DRB1, HYDIN, KMT5A, MUC3A ΠΈ PRSS3), Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΡΡΡΠΈΡ
ΡΡ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ Π²ΡΡΠΎΠΊΠΎΠΉ ΠΌΡΡΠ°ΡΠΈΠΎΠ½Π½ΠΎΠΉ Π½Π°Π³ΡΡΠ·ΠΊΠΎΠΉ. Π ΡΠ΅ΡΡΡΠ΅Ρ
Π³Π΅Π½Π°Ρ
(CDC27, CTBP2, HYDIN ΠΈ KMT5A) ΠΈΠ΄Π΅Π½ΡΠΈΡΠΈΡΠΈΡΠΎΠ²Π°Π½Ρ ΠΏΠΎΡΠ΅Π½ΡΠΈΠ°Π»ΡΠ½ΠΎ ΠΏΠ°ΡΠΎΠ³Π΅Π½Π½ΡΠ΅ ΠΌΡΡΠ°ΡΠΈΠΈ, ΡΠΎΠ³Π»Π°ΡΠ½ΠΎ Π½Π΅ΡΠΊΠΎΠ»ΡΠΊΠΈΠΌ ΠΏΡΠ΅Π΄ΡΠΊΠ°Π·Π°ΡΠ΅Π»ΡΠ½ΡΠΌ Π°Π»Π³ΠΎΡΠΈΡΠΌΠ°ΠΌ (SIFT, PolyPhen-2, MutationTaster ΠΈ LRT). ΠΠ½ΠΎΠ³ΠΈΠ΅ Π²ΡΡΠ²Π»Π΅Π½Π½ΡΠ΅ ΠΌΡΡΠ°ΡΠΈΠΈ ΠΎΠΊΠ°Π·Π°Π»ΠΈΡΡ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Π½ΡΠΌΠΈ Π² Π±ΠΎΠ»ΡΡΠΎΠΌ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅ ΠΎΠ±ΡΠ°Π·ΡΠΎΠ² Π²ΡΠ±ΠΎΡΠΊΠΈ, ΡΡΠΎ Π·Π°ΡΡΠ°Π²ΠΈΠ»ΠΎ ΠΏΡΠΎΠ²Π΅ΡΠΈΡΡ ΠΈΡ
ΡΠΎΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠΉ ΡΡΠ°ΡΡΡ Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ Π΄ΠΎΠΏΠΎΠ»Π½ΠΈΡΠ΅Π»ΡΠ½ΡΡ
Π΄Π°Π½Π½ΡΡ
ΡΠ΅ΠΊΠ²Π΅Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠΊΠ·ΠΎΠΌΠ° ΠΊΡΠΎΠ²ΠΈ, Π²ΡΠΏΠΎΠ»Π½Π΅Π½Π½ΠΎΠ³ΠΎ Ρ ΡΠ°ΠΊΠΈΠΌ ΠΆΠ΅ Π½Π°Π±ΠΎΡΠΎΠΌ Π΄Π»Ρ ΡΠΊΠ·ΠΎΠΌΠ½ΠΎΠ³ΠΎ ΠΎΠ±ΠΎΠ³Π°ΡΠ΅Π½ΠΈΡ, ΠΊΠ°ΠΊ ΠΈ ΠΏΡΠΈ Π°Π½Π°Π»ΠΈΠ·Π΅ ΠΎΠΏΡΡ
ΠΎΠ»Π΅ΠΉ ΠΠΠ. ΠΠ±Π½Π°ΡΡΠΆΠ΅Π½ΠΎ, ΡΡΠΎ Π·Π½Π°ΡΠΈΡΠ΅Π»ΡΠ½ΠΎΠ΅ ΡΠΈΡΠ»ΠΎ Π²ΡΡΠ²Π»Π΅Π½Π½ΡΡ
ΠΏΠΎΡΠ΅Π½ΡΠΈΠ°Π»ΡΠ½ΠΎ ΠΏΠ°ΡΠΎΠ³Π΅Π½Π½ΡΡ
ΠΌΡΡΠ°ΡΠΈΠΉ ΡΠ²Π»ΡΡΡΡΡ Π³Π΅ΡΠΌΠΈΠ½Π°Π»ΡΠ½ΡΠΌΠΈ, ΡΡΠΎ, ΠΏΠΎ-Π²ΠΈΠ΄ΠΈΠΌΠΎΠΌΡ, ΡΠ²ΡΠ·Π°Π½ΠΎ Ρ Π½Π°Π»ΠΈΡΠΈΠ΅ΠΌ ΠΎΡΠΈΠ±ΠΎΠΊ Π°Π½Π½ΠΎΡΠ°ΡΠΈΠΈ Π² Π±Π°Π·Π°Ρ
Π΄Π°Π½Π½ΡΡ
1000 Genomes Project ΠΈ ExAC. ΠΠ΄Π½Π°ΠΊΠΎ ΡΠ°ΡΡΡ ΠΈΠ΄Π΅Π½ΡΠΈΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
ΠΌΡΡΠ°ΡΠΈΠΉ Π² Π³Π΅Π½Π°Ρ
CDC27, CTBP2, HYDIN ΠΈ KMT5A ΠΎΡΡΠ°ΡΡΡΡ ΠΏΡΠ΅Π΄ΠΏΠΎΠ»ΠΎΠΆΠΈΡΠ΅Π»ΡΠ½ΠΎ ΠΏΠ°ΡΠΎΠ³Π΅Π½Π½ΡΠΌΠΈ, ΠΊΡΠΎΠΌΠ΅ ΡΠΎΠ³ΠΎ, ΠΈΠΌΠ΅ΡΡΡΡ ΠΌΠ½ΠΎΠ³ΠΎΡΠΈΡΠ»Π΅Π½Π½ΡΠ΅ Π΄Π°Π½Π½ΡΠ΅ ΠΎ Π²ΠΎΠ²Π»Π΅ΡΠ΅Π½Π½ΠΎΡΡΠΈ ΡΡΠΈΡ
Π³Π΅Π½ΠΎΠ² Π² ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΠΈ ΠΏΡΠΎΠ³ΡΠ΅ΡΡΠΈΡ Π΄ΡΡΠ³ΠΈΡ
Π²ΠΈΠ΄ΠΎΠ² ΠΎΠΏΡΡ
ΠΎΠ»Π΅ΠΉ. ΠΡΠΎ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ ΡΡΠΈΡΠ°ΡΡ Π³Π΅Π½Ρ CDC27, CTBP2, HYDIN ΠΈ KMT5A ΠΏΠΎΡΠ΅Π½ΡΠΈΠ°Π»ΡΠ½ΠΎ ΡΠ²ΡΠ·Π°Π½Π½ΡΠΌΠΈ Ρ ΠΏΠ°ΡΠΎΠ³Π΅Π½Π΅Π·ΠΎΠΌ ΠΠΠ ΠΈ ΡΡΠ΅Π±ΡΠ΅Ρ ΠΎΠ±ΡΠ°ΡΠΈΡΡ Π½Π° Π½ΠΈΡ
ΠΎΡΠΎΠ±ΠΎΠ΅ Π²Π½ΠΈΠΌΠ°Π½ΠΈΠ΅ Π² Π΄Π°Π»ΡΠ½Π΅ΠΉΡΠΈΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡΡ
. Π’Π°ΠΊΠΈΠΌ ΠΎΠ±ΡΠ°Π·ΠΎΠΌ, Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎ ΡΠΎΠ²Π΅ΡΡΠ΅Π½ΡΡΠ²ΠΎΠ²Π°ΡΡ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠΈ Π΄Π»Ρ Π²ΡΡΠ²Π»Π΅Π½ΠΈΡ ΠΎΠ½ΠΊΠΎ-Π°ΡΡΠΎΡΠΈΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
Π³Π΅Π½ΠΎΠ² ΠΈ ΠΏΠ°ΡΠΎΠ³Π΅Π½Π½ΡΡ
ΠΌΡΡΠ°ΡΠΈΠΉ