Immunohistochemical characteristics of muscular tissue during surgical treatment of patients with ІІІ 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 ІІІ 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 ІІІ 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 $2+\epsilon$ 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

Технологии комплексного интеллектуального анализа клинических данных

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, patient’s 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 patient’s 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 patients’ 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. Обоснование. Медицинские учреждения генерируют большой поток как структурированных, так и неструктурированных данных, содержащих важную информацию о пациентах. В структурированном виде, как правило, хранятся результаты анализов, однако подавляющее количество данных хранится в неструктурированной форме в виде текстов на естественном языке (анамнезы, результаты осмотров, описания результатов обследований, таких как УЗИ, ЭКГ, рентгеновских исследований и др.). Используя методы интеллектуальной обработки накопленных массивов структурированных и неструктурированных данных, можно автоматизировать решение многих задач, возникающих в клинической практике и повысить качество медицинской помощи.Цель исследования: создание комплексной системы интеллектуальной обработки данных в многопрофильном педиатрическом центре.Методы. Извлечение информации из клинических текстов на русском языке осуществляется на основе полного лингвистического анализа. Извлекаются упоминания заболеваний, симптомов, областей тела, лекарственных препаратов. В тексте также распознаются атрибуты заболеваний: «отрицание» (указывает на то, что заболевание отсутствует), «не пациент» (указывает на то, что заболевание относится не к пациенту, а к его родственнику), «тяжесть заболевания», «течение заболевания», «область тела, к которой относится заболевание». Для извлечения информации используются медицинские тезаурусы, набор вручную составленных шаблонов, а также различные методы на основе машинного обучения. Полученные из текстов данные используются для решения задачи автоматической диагностики хронических заболеваний. Предложен метод на основе машинного обучения для классификации пациентов со схожими нозологиями, а также метод для определения наиболее информативных признаков.Результаты. Экспериментальное исследование разработанных методов проводилось на обезличенных историях болезни пациентов педиатрического центра. Проведена оценка качества разработанных методов извлечения информации из клинических текстов на русском языке. Проведена экспериментальная оценка метода автоматической диагностики на данных пациентов с аллергическими заболеваниями и болезными органов дыхания, нефрологическими и ревматическими заболеваниями. Определены наиболее подходящие методы машинного обучения для классификации пациентов для каждой группы заболеваний, а также наиболее информативные признаки. Использование данных, извлеченных из клинических текстов совместно со структурированными данными, позволило повысить качество диагностики хронических заболеваний по сравнению с использованием лишь доступных структурированных данных. Получены также шаблонные комбинации признаков заболеваний.Заключение. Разработанные методы были реализованы в системе интеллектуальной обработки данных в многопрофильном педиатрическом центре. Проведенные исследования свидетельствуют о перспективности использования системы для повышения качества медицинской помощи пациентам детской возрастной категории

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 $\nu \gg 1$ 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 $1/2\tau$ does not exceed the critical value $1/2\tau_{c}=0.038\omega_{H}$. Our analysis of weak crystallization corrections to the mean-field results shows that these corrections are of the order of $(1/\nu)^{2/3}\ll 1$ and therefore can be neglected

Measurement of CP observables in B± → D(⁎)K± and B± → D(⁎)π± decays

Measurements of CP observables in B ± →D (⁎) K ± and B ± →D (⁎) π ± decays are presented, where D (⁎) indicates a neutral D or D ⁎ meson that is an admixture of D (⁎)0 and D¯ (⁎)0 states. Decays of the D ⁎ meson to the Dπ 0 and Dγ 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 ± π ∓ , K + K − and π + π − 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 −1 taken at centre-of-mass energies of s=7, 8 and 13 TeV, respectively. The study of B ± →D ⁎ K ± and B ± →D ⁎ π ± decays using a partial reconstruction method is the first of its kind, while the measurement of B ± →DK ± and B ± →Dπ ± decays is an update of previous LHCb measurements. The B ± →DK ± results are the most precise to date

First observation of forward Z→bbˉZ \rightarrow b \bar{b} production in pppp collisions at s=8\sqrt{s}=8 TeV

The decay Z→bb¯ is reconstructed in pp collision data, corresponding to 2 fb −1 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 Z→bb¯ 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 4520$GeV and dijet invariant mass in the range$45 < m_{jj} < 165$GeV. From a signal yield of$5462 \pm 763$$Z \rightarrow b \bar{b}$events, where the uncertainty is statistical, a production cross-section times branching fraction of$332 \pm 46 \pm 59$pb is obtained, where the first uncertainty is statistical and the second systematic. The measured significance of the signal yield is 6.0 standard deviations. This measurement represents the first observation of the$Z \rightarrow b \bar{b}$production in the forward region of$pp$ 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 ‘dystrophic’ and destructive processes with less compensatory reaction