119 research outputs found
Immunohistochemical characteristics of muscular tissue during surgical treatment of patients with ĐĐĐ degree chronic ischemia of lower limb
Background. Of particular note is the analysis of immunohistochemical features of compensatory repair capabilities in terms of muscle ischemic injury developing in several ways: 1) direct induction of angiogenesis; 2) increased survival of muscle fibers; 3) mediated stimulation of muscle-typical differentiation; 4) resistance to apoptotic mechanisms. Objective. The purpose of research was the immunohistochemical analysis of anterior tibial muscle in patients with ĐĐĐ degree chronic ischemia of lower limb after direct, indirect and composite revascularization in near-term and long-term postoperative periods. Methods. Patients have been divided into three groups: 1) 37 patients after femoral-tibial reconstruction; 2) 57 patients after indirect revascularization with autotransplantation of bone marrow; 3) 50 patients after composite revascularization of distal part of lower limb. The observation was carried out in the near-term postoperative period and in 2 years. Immunohistochemical study of tissue samplings of anterior tibial muscle taken between superior and middle one thirds was carried out. Results. It have been determined that direct revascularization causes the significant improvement immunohistochemical characteristics of muscle fibers of anterior tibial muscle in all age groups during 6 months after operation, however does not provide the stabilization of positive changes in long-term postoperative period. Indirect revascularization does not change significally structurally-functional condition of components of muscle in near-term postoperative period, however causes the stable normalization of parameters of tissue components due to initiation of neovasculogenesis at patients till 75 years. Conclusion. Composite revascularization allows to receive near-term normalizing effect concerning the studied immunohistochemical criteria and to provide its stabilization in the long-term postoperative period.
Citation:
Shkuropat VM, Tverdokhleb IV, Baranov IV, Safronkov NA. [Immunohistochemical characteristics of muscular tissue during surgical treatment of patients with ĐĐĐ degree chronic ischemia of lower limb]. Morphologia. 2015;9(1):71-7. Ukrainian
Wave function multifractality and dephasing at metal-insulator and quantum Hall transitions
We analyze the critical behavior of the dephasing rate induced by short-range
electron-electron interaction near an Anderson transition of metal-insulator or
quantum Hall type. The corresponding exponent characterizes the scaling of the
transition width with temperature. Assuming no spin degeneracy, the critical
behavior can be studied by performing the scaling analysis in the vicinity of
the non-interacting fixed point, since the latter is stable with respect to the
interaction. We combine an analytical treatment (that includes the
identification of operators responsible for dephasing in the formalism of the
non-linear sigma-model and the corresponding renormalization-group analysis in
dimensions) with numerical simulations on the Chalker-Coddington
network model of the quantum Hall transition. Finally, we discuss the current
understanding of the Coulomb interaction case and the available experimental
data.Comment: 33 pages, 7 figures, elsart styl
ĐąĐ”Ń ĐœĐŸĐ»ĐŸĐłĐžĐž ĐșĐŸĐŒĐżĐ»Đ”ĐșŃĐœĐŸĐłĐŸ ĐžĐœŃДллДĐșŃŃĐ°Đ»ŃĐœĐŸĐłĐŸ Đ°ĐœĐ°Đ»ĐžĐ·Đ° ĐșĐ»ĐžĐœĐžŃĐ”ŃĐșĐžŃ ĐŽĐ°ĐœĐœŃŃ
The paper presents the system for intelligent analysis of clinical information. Authors describe methods implemented in the system for clinical information retrieval, intelligent diagnostics of chronic diseases, patientâs features importance and for detection of hidden dependencies between features. Results of the experimental evaluation of these methods are also presented.Background: Healthcare facilities generate a large flow of both structured and unstructured data which contain important information about patients. Test results are usually retained as structured data but some data is retained in the form of natural language texts (medical history, the results of physical examination, and the results of other examinations, such as ultrasound, ECG or X-ray studies). Many tasks arising in clinical practice can be automated applying methods for intelligent analysis of accumulated structured array and unstructured data that leads to improvement of the healthcare quality.Aims: the creation of the complex system for intelligent data analysis in the multi-disciplinary pediatric center.Materials and methods: Authors propose methods for information extraction from clinical texts in Russian. The methods are carried out on the basis of deep linguistic analysis. They retrieve terms of diseases, symptoms, areas of the body and drugs. The methods can recognize additional attributes such as «negation» (indicates that the disease is absent), «no patient» (indicates that the disease refers to the patientâs family member, but not to the patient), «severity of illness», «disease course», «body region to which the disease refers». Authors use a set of hand-drawn templates and various techniques based on machine learning to retrieve information using a medical thesaurus. The extracted information is used to solve the problem of automatic diagnosis of chronic diseases. A machine learning method for classification of patients with similar nosology and the method for determining the most informative patientsâ features are also proposed.Results: Authors have processed anonymized health records from the pediatric center to estimate the proposed methods. The results show the applicability of the information extracted from the texts for solving practical problems. The records of patients with allergic, glomerular and rheumatic diseases were used for experimental assessment of the method of automatic diagnostic. Authors have also determined the most appropriate machine learning methods for classification of patients for each group of diseases, as well as the most informative disease signs. It has been found that using additional information extracted from clinical texts, together with structured data helps to improve the quality of diagnosis of chronic diseases. Authors have also obtained pattern combinations of signs of diseases.Conclusions: The proposed methods have been implemented in the intelligent data processing system for a multidisciplinary pediatric center. The experimental results show the availability of the system to improve the quality of pediatric healthcare. ĐĐ±ĐŸŃĐœĐŸĐČĐ°ĐœĐžĐ”. ĐДЎОŃĐžĐœŃĐșОД ŃŃŃĐ”Đ¶ĐŽĐ”ĐœĐžŃ ĐłĐ”ĐœĐ”ŃĐžŃŃŃŃ Đ±ĐŸĐ»ŃŃĐŸĐč ĐżĐŸŃĐŸĐș ĐșĐ°Đș ŃŃŃŃĐșŃŃŃĐžŃĐŸĐČĐ°ĐœĐœŃŃ
, ŃĐ°Đș Đž ĐœĐ”ŃŃŃŃĐșŃŃŃĐžŃĐŸĐČĐ°ĐœĐœŃŃ
ĐŽĐ°ĐœĐœŃŃ
, ŃĐŸĐŽĐ”ŃжаŃĐžŃ
ĐČĐ°Đ¶ĐœŃŃ ĐžĐœŃĐŸŃĐŒĐ°ŃĐžŃ ĐŸ паŃĐžĐ”ĐœŃĐ°Ń
. Đ ŃŃŃŃĐșŃŃŃĐžŃĐŸĐČĐ°ĐœĐœĐŸĐŒ ĐČОЎД, ĐșĐ°Đș ĐżŃĐ°ĐČĐžĐ»ĐŸ, Ń
ŃĐ°ĐœŃŃŃŃ ŃДзŃĐ»ŃŃĐ°ŃŃ Đ°ĐœĐ°Đ»ĐžĐ·ĐŸĐČ, ĐŸĐŽĐœĐ°ĐșĐŸ ĐżĐŸĐŽĐ°ĐČĐ»ŃŃŃДД ĐșĐŸĐ»ĐžŃĐ”ŃŃĐČĐŸ ĐŽĐ°ĐœĐœŃŃ
Ń
ŃĐ°ĐœĐžŃŃŃ ĐČ ĐœĐ”ŃŃŃŃĐșŃŃŃĐžŃĐŸĐČĐ°ĐœĐœĐŸĐč ŃĐŸŃĐŒĐ” ĐČ ĐČОЎД ŃĐ”ĐșŃŃĐŸĐČ ĐœĐ° Đ”ŃŃĐ”ŃŃĐČĐ”ĐœĐœĐŸĐŒ ŃĐ·ŃĐșĐ” (Đ°ĐœĐ°ĐŒĐœĐ”Đ·Ń, ŃДзŃĐ»ŃŃĐ°ŃŃ ĐŸŃĐŒĐŸŃŃĐŸĐČ, ĐŸĐżĐžŃĐ°ĐœĐžŃ ŃДзŃĐ»ŃŃĐ°ŃĐŸĐČ ĐŸĐ±ŃĐ»Đ”ĐŽĐŸĐČĐ°ĐœĐžĐč, ŃĐ°ĐșĐžŃ
ĐșĐ°Đș ĐŁĐĐ, ĐĐĐ, ŃĐ”ĐœŃĐłĐ”ĐœĐŸĐČŃĐșĐžŃ
ĐžŃŃĐ»Đ”ĐŽĐŸĐČĐ°ĐœĐžĐč Đž ĐŽŃ.). ĐŃĐżĐŸĐ»ŃĐ·ŃŃ ĐŒĐ”ŃĐŸĐŽŃ ĐžĐœŃДллДĐșŃŃĐ°Đ»ŃĐœĐŸĐč ĐŸĐ±ŃĐ°Đ±ĐŸŃĐșĐž ĐœĐ°ĐșĐŸĐżĐ»Đ”ĐœĐœŃŃ
ĐŒĐ°ŃŃĐžĐČĐŸĐČ ŃŃŃŃĐșŃŃŃĐžŃĐŸĐČĐ°ĐœĐœŃŃ
Đž ĐœĐ”ŃŃŃŃĐșŃŃŃĐžŃĐŸĐČĐ°ĐœĐœŃŃ
ĐŽĐ°ĐœĐœŃŃ
, ĐŒĐŸĐ¶ĐœĐŸ Đ°ĐČŃĐŸĐŒĐ°ŃОзОŃĐŸĐČĐ°ŃŃ ŃĐ”ŃĐ”ĐœĐžĐ” ĐŒĐœĐŸĐłĐžŃ
Đ·Đ°ĐŽĐ°Ń, ĐČĐŸĐ·ĐœĐžĐșĐ°ŃŃĐžŃ
ĐČ ĐșĐ»ĐžĐœĐžŃĐ”ŃĐșĐŸĐč ĐżŃĐ°ĐșŃĐžĐșĐ” Đž ĐżĐŸĐČŃŃĐžŃŃ ĐșĐ°ŃĐ”ŃŃĐČĐŸ ĐŒĐ”ĐŽĐžŃĐžĐœŃĐșĐŸĐč ĐżĐŸĐŒĐŸŃĐž.ĐŠĐ”Đ»Ń ĐžŃŃĐ»Đ”ĐŽĐŸĐČĐ°ĐœĐžŃ: ŃĐŸĐ·ĐŽĐ°ĐœĐžĐ” ĐșĐŸĐŒĐżĐ»Đ”ĐșŃĐœĐŸĐč ŃĐžŃŃĐ”ĐŒŃ ĐžĐœŃДллДĐșŃŃĐ°Đ»ŃĐœĐŸĐč ĐŸĐ±ŃĐ°Đ±ĐŸŃĐșĐž ĐŽĐ°ĐœĐœŃŃ
ĐČ ĐŒĐœĐŸĐłĐŸĐżŃĐŸŃОлŃĐœĐŸĐŒ пДЎОаŃŃĐžŃĐ”ŃĐșĐŸĐŒ ŃĐ”ĐœŃŃĐ”.ĐĐ”ŃĐŸĐŽŃ. ĐĐ·ĐČлДŃĐ”ĐœĐžĐ” ĐžĐœŃĐŸŃĐŒĐ°ŃОО Оз ĐșĐ»ĐžĐœĐžŃĐ”ŃĐșĐžŃ
ŃĐ”ĐșŃŃĐŸĐČ ĐœĐ° ŃŃŃŃĐșĐŸĐŒ ŃĐ·ŃĐșĐ” ĐŸŃŃŃĐ”ŃŃĐČĐ»ŃĐ”ŃŃŃ ĐœĐ° ĐŸŃĐœĐŸĐČĐ” ĐżĐŸĐ»ĐœĐŸĐłĐŸ Đ»ĐžĐœĐłĐČĐžŃŃĐžŃĐ”ŃĐșĐŸĐłĐŸ Đ°ĐœĐ°Đ»ĐžĐ·Đ°. ĐĐ·ĐČлДĐșĐ°ŃŃŃŃ ŃĐżĐŸĐŒĐžĐœĐ°ĐœĐžŃ Đ·Đ°Đ±ĐŸĐ»Đ”ĐČĐ°ĐœĐžĐč, ŃĐžĐŒĐżŃĐŸĐŒĐŸĐČ, ĐŸĐ±Đ»Đ°ŃŃĐ”Đč ŃДла, лДĐșĐ°ŃŃŃĐČĐ”ĐœĐœŃŃ
ĐżŃДпаŃĐ°ŃĐŸĐČ. Đ ŃĐ”ĐșŃŃĐ” ŃĐ°ĐșжД ŃĐ°ŃĐżĐŸĐ·ĐœĐ°ŃŃŃŃ Đ°ŃŃОбŃŃŃ Đ·Đ°Đ±ĐŸĐ»Đ”ĐČĐ°ĐœĐžĐč: Â«ĐŸŃŃĐžŃĐ°ĐœĐžĐ”Â» (ŃĐșĐ°Đ·ŃĐČĐ°Đ”Ń ĐœĐ° ŃĐŸ, ŃŃĐŸ Đ·Đ°Đ±ĐŸĐ»Đ”ĐČĐ°ĐœĐžĐ” ĐŸŃŃŃŃŃŃĐČŃĐ”Ń), Â«ĐœĐ” паŃĐžĐ”ĐœŃ» (ŃĐșĐ°Đ·ŃĐČĐ°Đ”Ń ĐœĐ° ŃĐŸ, ŃŃĐŸ Đ·Đ°Đ±ĐŸĐ»Đ”ĐČĐ°ĐœĐžĐ” ĐŸŃĐœĐŸŃĐžŃŃŃ ĐœĐ” Đș паŃĐžĐ”ĐœŃŃ, Đ° Đș Đ”ĐłĐŸ ŃĐŸĐŽŃŃĐČĐ”ĐœĐœĐžĐșŃ), «ŃŃжДŃŃŃ Đ·Đ°Đ±ĐŸĐ»Đ”ĐČĐ°ĐœĐžŃ», «ŃĐ”ŃĐ”ĐœĐžĐ” Đ·Đ°Đ±ĐŸĐ»Đ”ĐČĐ°ĐœĐžŃ», Â«ĐŸĐ±Đ»Đ°ŃŃŃ ŃДла, Đș ĐșĐŸŃĐŸŃĐŸĐč ĐŸŃĐœĐŸŃĐžŃŃŃ Đ·Đ°Đ±ĐŸĐ»Đ”ĐČĐ°ĐœĐžĐ”Â». ĐĐ»Ń ĐžĐ·ĐČлДŃĐ”ĐœĐžŃ ĐžĐœŃĐŸŃĐŒĐ°ŃОО ĐžŃĐżĐŸĐ»ŃĐ·ŃŃŃŃŃ ĐŒĐ”ĐŽĐžŃĐžĐœŃĐșОД ŃДзаŃŃŃŃŃ, ĐœĐ°Đ±ĐŸŃ ĐČŃŃŃĐœŃŃ ŃĐŸŃŃĐ°ĐČĐ»Đ”ĐœĐœŃŃ
ŃĐ°Đ±Đ»ĐŸĐœĐŸĐČ, Đ° ŃĐ°ĐșжД ŃазлОŃĐœŃĐ” ĐŒĐ”ŃĐŸĐŽŃ ĐœĐ° ĐŸŃĐœĐŸĐČĐ” ĐŒĐ°ŃĐžĐœĐœĐŸĐłĐŸ ĐŸĐ±ŃŃĐ”ĐœĐžŃ. ĐĐŸĐ»ŃŃĐ”ĐœĐœŃĐ” Оз ŃĐ”ĐșŃŃĐŸĐČ ĐŽĐ°ĐœĐœŃĐ” ĐžŃĐżĐŸĐ»ŃĐ·ŃŃŃŃŃ ĐŽĐ»Ń ŃĐ”ŃĐ”ĐœĐžŃ Đ·Đ°ĐŽĐ°ŃĐž Đ°ĐČŃĐŸĐŒĐ°ŃĐžŃĐ”ŃĐșĐŸĐč ĐŽĐžĐ°ĐłĐœĐŸŃŃĐžĐșĐž Ń
ŃĐŸĐœĐžŃĐ”ŃĐșĐžŃ
Đ·Đ°Đ±ĐŸĐ»Đ”ĐČĐ°ĐœĐžĐč. ĐŃĐ”ĐŽĐ»ĐŸĐ¶Đ”Đœ ĐŒĐ”ŃĐŸĐŽ ĐœĐ° ĐŸŃĐœĐŸĐČĐ” ĐŒĐ°ŃĐžĐœĐœĐŸĐłĐŸ ĐŸĐ±ŃŃĐ”ĐœĐžŃ ĐŽĐ»Ń ĐșлаŃŃĐžŃĐžĐșĐ°ŃОО паŃĐžĐ”ĐœŃĐŸĐČ ŃĐŸ ŃŃ
ĐŸĐ¶ĐžĐŒĐž ĐœĐŸĐ·ĐŸĐ»ĐŸĐłĐžŃĐŒĐž, Đ° ŃĐ°ĐșжД ĐŒĐ”ŃĐŸĐŽ ĐŽĐ»Ń ĐŸĐżŃĐ”ĐŽĐ”Đ»Đ”ĐœĐžŃ ĐœĐ°ĐžĐ±ĐŸĐ»Đ”Đ” ĐžĐœŃĐŸŃĐŒĐ°ŃĐžĐČĐœŃŃ
ĐżŃĐžĐ·ĐœĐ°ĐșĐŸĐČ.РДзŃĐ»ŃŃĐ°ŃŃ. ĐĐșŃпДŃĐžĐŒĐ”ĐœŃĐ°Đ»ŃĐœĐŸĐ” ĐžŃŃĐ»Đ”ĐŽĐŸĐČĐ°ĐœĐžĐ” ŃĐ°Đ·ŃĐ°Đ±ĐŸŃĐ°ĐœĐœŃŃ
ĐŒĐ”ŃĐŸĐŽĐŸĐČ ĐżŃĐŸĐČĐŸĐŽĐžĐ»ĐŸŃŃ ĐœĐ° ĐŸĐ±Đ”Đ·Đ»ĐžŃĐ”ĐœĐœŃŃ
ĐžŃŃĐŸŃĐžŃŃ
Đ±ĐŸĐ»Đ”Đ·ĐœĐž паŃĐžĐ”ĐœŃĐŸĐČ ĐżĐ”ĐŽĐžĐ°ŃŃĐžŃĐ”ŃĐșĐŸĐłĐŸ ŃĐ”ĐœŃŃĐ°. ĐŃĐŸĐČĐ”ĐŽĐ”ĐœĐ° ĐŸŃĐ”ĐœĐșĐ° ĐșĐ°ŃĐ”ŃŃĐČĐ° ŃĐ°Đ·ŃĐ°Đ±ĐŸŃĐ°ĐœĐœŃŃ
ĐŒĐ”ŃĐŸĐŽĐŸĐČ ĐžĐ·ĐČлДŃĐ”ĐœĐžŃ ĐžĐœŃĐŸŃĐŒĐ°ŃОО Оз ĐșĐ»ĐžĐœĐžŃĐ”ŃĐșĐžŃ
ŃĐ”ĐșŃŃĐŸĐČ ĐœĐ° ŃŃŃŃĐșĐŸĐŒ ŃĐ·ŃĐșĐ”. ĐŃĐŸĐČĐ”ĐŽĐ”ĐœĐ° ŃĐșŃпДŃĐžĐŒĐ”ĐœŃĐ°Đ»ŃĐœĐ°Ń ĐŸŃĐ”ĐœĐșĐ° ĐŒĐ”ŃĐŸĐŽĐ° Đ°ĐČŃĐŸĐŒĐ°ŃĐžŃĐ”ŃĐșĐŸĐč ĐŽĐžĐ°ĐłĐœĐŸŃŃĐžĐșĐž ĐœĐ° ĐŽĐ°ĐœĐœŃŃ
паŃĐžĐ”ĐœŃĐŸĐČ Ń Đ°Đ»Đ»Đ”ŃгОŃĐ”ŃĐșĐžĐŒĐž Đ·Đ°Đ±ĐŸĐ»Đ”ĐČĐ°ĐœĐžŃĐŒĐž Đž Đ±ĐŸĐ»Đ”Đ·ĐœŃĐŒĐž ĐŸŃĐłĐ°ĐœĐŸĐČ ĐŽŃŃ
Đ°ĐœĐžŃ, ĐœĐ”ŃŃĐŸĐ»ĐŸĐłĐžŃĐ”ŃĐșĐžĐŒĐž Đž ŃĐ”ĐČĐŒĐ°ŃĐžŃĐ”ŃĐșĐžĐŒĐž Đ·Đ°Đ±ĐŸĐ»Đ”ĐČĐ°ĐœĐžŃĐŒĐž. ĐĐżŃĐ”ĐŽĐ”Đ»Đ”ĐœŃ ĐœĐ°ĐžĐ±ĐŸĐ»Đ”Đ” ĐżĐŸĐŽŃ
ĐŸĐŽŃŃОД ĐŒĐ”ŃĐŸĐŽŃ ĐŒĐ°ŃĐžĐœĐœĐŸĐłĐŸ ĐŸĐ±ŃŃĐ”ĐœĐžŃ ĐŽĐ»Ń ĐșлаŃŃĐžŃĐžĐșĐ°ŃОО паŃĐžĐ”ĐœŃĐŸĐČ ĐŽĐ»Ń ĐșĐ°Đ¶ĐŽĐŸĐč ĐłŃŃĐżĐżŃ Đ·Đ°Đ±ĐŸĐ»Đ”ĐČĐ°ĐœĐžĐč, Đ° ŃĐ°ĐșжД ĐœĐ°ĐžĐ±ĐŸĐ»Đ”Đ” ĐžĐœŃĐŸŃĐŒĐ°ŃĐžĐČĐœŃĐ” ĐżŃĐžĐ·ĐœĐ°ĐșĐž. ĐŃĐżĐŸĐ»ŃĐ·ĐŸĐČĐ°ĐœĐžĐ” ĐŽĐ°ĐœĐœŃŃ
, ОзĐČлДŃĐ”ĐœĐœŃŃ
Оз ĐșĐ»ĐžĐœĐžŃĐ”ŃĐșĐžŃ
ŃĐ”ĐșŃŃĐŸĐČ ŃĐŸĐČĐŒĐ”ŃŃĐœĐŸ ŃĐŸ ŃŃŃŃĐșŃŃŃĐžŃĐŸĐČĐ°ĐœĐœŃĐŒĐž ĐŽĐ°ĐœĐœŃĐŒĐž, ĐżĐŸĐ·ĐČĐŸĐ»ĐžĐ»ĐŸ ĐżĐŸĐČŃŃĐžŃŃ ĐșĐ°ŃĐ”ŃŃĐČĐŸ ĐŽĐžĐ°ĐłĐœĐŸŃŃĐžĐșĐž Ń
ŃĐŸĐœĐžŃĐ”ŃĐșĐžŃ
Đ·Đ°Đ±ĐŸĐ»Đ”ĐČĐ°ĐœĐžĐč ĐżĐŸ ŃŃĐ°ĐČĐœĐ”ĐœĐžŃ Ń ĐžŃĐżĐŸĐ»ŃĐ·ĐŸĐČĐ°ĐœĐžĐ”ĐŒ лОŃŃ ĐŽĐŸŃŃŃĐżĐœŃŃ
ŃŃŃŃĐșŃŃŃĐžŃĐŸĐČĐ°ĐœĐœŃŃ
ĐŽĐ°ĐœĐœŃŃ
. ĐĐŸĐ»ŃŃĐ”ĐœŃ ŃĐ°ĐșжД ŃĐ°Đ±Đ»ĐŸĐœĐœŃĐ” ĐșĐŸĐŒĐ±ĐžĐœĐ°ŃОО ĐżŃĐžĐ·ĐœĐ°ĐșĐŸĐČ Đ·Đ°Đ±ĐŸĐ»Đ”ĐČĐ°ĐœĐžĐč.ĐĐ°ĐșĐ»ŃŃĐ”ĐœĐžĐ”. Đ Đ°Đ·ŃĐ°Đ±ĐŸŃĐ°ĐœĐœŃĐ” ĐŒĐ”ŃĐŸĐŽŃ Đ±ŃлО ŃĐ”Đ°Đ»ĐžĐ·ĐŸĐČĐ°ĐœŃ ĐČ ŃĐžŃŃĐ”ĐŒĐ” ĐžĐœŃДллДĐșŃŃĐ°Đ»ŃĐœĐŸĐč ĐŸĐ±ŃĐ°Đ±ĐŸŃĐșĐž ĐŽĐ°ĐœĐœŃŃ
ĐČ ĐŒĐœĐŸĐłĐŸĐżŃĐŸŃОлŃĐœĐŸĐŒ пДЎОаŃŃĐžŃĐ”ŃĐșĐŸĐŒ ŃĐ”ĐœŃŃĐ”. ĐŃĐŸĐČĐ”ĐŽĐ”ĐœĐœŃĐ” ĐžŃŃĐ»Đ”ĐŽĐŸĐČĐ°ĐœĐžŃ ŃĐČОЎДŃДлŃŃŃĐČŃŃŃ ĐŸ пДŃŃпДĐșŃĐžĐČĐœĐŸŃŃĐž ĐžŃĐżĐŸĐ»ŃĐ·ĐŸĐČĐ°ĐœĐžŃ ŃĐžŃŃĐ”ĐŒŃ ĐŽĐ»Ń ĐżĐŸĐČŃŃĐ”ĐœĐžŃ ĐșĐ°ŃĐ”ŃŃĐČĐ° ĐŒĐ”ĐŽĐžŃĐžĐœŃĐșĐŸĐč ĐżĐŸĐŒĐŸŃĐž паŃĐžĐ”ĐœŃĐ°ĐŒ ĐŽĐ”ŃŃĐșĐŸĐč ĐČĐŸĐ·ŃĐ°ŃŃĐœĐŸĐč ĐșĐ°ŃĐ”ĐłĐŸŃОО
Biologic Therapy in Patients with Juvenile Idiopathic Arthritis â A Unique Single Centre Experience at the Scientific-Research Pediatric Centre in the Russian Federation
Mean-field Phase Diagram of Two-Dimensional Electrons with Disorder in a Weak Magnetic Field
We study two-dimensional interacting electrons in a weak perpendicular
magnetic field with the filling factor and in the presence of a
quenched disorder. In the framework of the Hartree-Fock approximation, we
obtain the mean-field phase diagram for the partially filled highest Landau
level. We find that the CDW state can exist if the Landau level broadening
does not exceed the critical value .
Our analysis of weak crystallization corrections to the mean-field results
shows that these corrections are of the order of and
therefore can be neglected
BCS-BEC Crossover and Chiral Anomaly in p-Wave Superfluids with the Symmetry of A1-Phase
Measurement of CP observables in B± â D(â)K± and B± â D(â)ϱ decays
Measurements of CP observables in B ± âD (â) K ± and B ± âD (â) Ï Â± decays are presented, where D (â) indicates a neutral D or D â meson that is an admixture of D (â)0 and DÂŻ (â)0 states. Decays of the D â meson to the DÏ 0 and DÎł final states are partially reconstructed without inclusion of the neutral pion or photon, resulting in distinctive shapes in the B candidate invariant mass distribution. Decays of the D meson are fully reconstructed in the K ± Ï â , K + K â and Ï + Ï â final states. The analysis uses a sample of charged B mesons produced in pp collisions collected by the LHCb experiment, corresponding to an integrated luminosity of 2.0, 1.0 and 2.0 fb â1 taken at centre-of-mass energies of s=7, 8 and 13 TeV, respectively. The study of B ± âD â K ± and B ± âD â Ï Â± decays using a partial reconstruction method is the first of its kind, while the measurement of B ± âDK ± and B ± âDÏ Â± decays is an update of previous LHCb measurements. The B ± âDK ± results are the most precise to date
First observation of forward production in collisions at TeV
The decay ZâbbÂŻ is reconstructed in pp collision data, corresponding to 2 fb â1 of integrated luminosity, collected by the LHCb experiment at a centre-of-mass energy of s=8 TeV. The product of the Z production cross-section and the ZâbbÂŻ branching fraction is measured for candidates in the fiducial region defined by two particle-level b -quark jets with pseudorapidities in the range 2.220 GeV and dijet invariant mass in the range 452045 < m_{jj} < 1655462 \pm 763Z \rightarrow b \bar{b}332 \pm 46 \pm 59Z \rightarrow b \bar{b}pp$ collisions
Comparative morphological evaluation of lungs of died patients after pneumonectomy with intraoperational use of perftoran and refortan
The goal of the research was to estimate the morphological features of lungs, which develop under influence of intraoperational infusion of refortan and perftoran in oncological patients. It was used the material from 24 patients, died in early postoperative period after pneumonectomy for the reason of lung cancer. During intraoperational infusion therapy in 12 died patients refortan in dosage 5 ml/kg has been used, in other 12 cases perftoran in dosage 3 ml/kg has been used. Morphological analyze was performed with the help of electron microscopy, morphometricaland standard statistical methods. In cases with perftoran use it was observed both damages of aerohematic barrier structures and increased emission of osmiophilic substance by alveolocytes into the alveolar cavity. The last phenomenon has been estimated by us as a compensatory reaction directed on maintenance of respiratory function. In patientswith refortan treatment changes in respiratory tract condition were realized in complex of âdystrophicâ and destructive processes with less compensatory reaction
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