P13.23 Study of migration characteristics of human glioma cells in vitro

BACKGROUND

Gliomas are still one of the most aggressive human cancers, and even despite modern therapeutic approaches, the prognosis for patients with this disease is not favorable. It is known that glioma cells are capable of local invasiveness, when glioma cells migrate into healthy brain tissue. A lack of any definite markers, characterizing migrating glioma cells and allowing them to be distinguished from healthy brain cells, requires a thorough investigation. In case it would be possible to characterize invasive glioma cells, then a development of targeted therapy could be feasible.

MATERIAL AND METHODS

Cell cultures of human gliomas Gr II, III and IV were developed with 5 cultures for each Grade. MTT, RT-PCR, Western and Nosern blot, transcriptome analysis were applied.

RESULTS

Three cultures of human gliomas had a high degree of migration, within the range of 6% - 14%. These cultures were developed from gliomas of Grade III and Grade IV, and with IDH1- (minus) phenotype. Moreover, cell cultures with IDH1 + (plus) phenotype had a low migration rate within 1%. An intensity of migration correlated with the degree of malignancy, and an average rate decreased with a decrease of the Grade. Moreover, an analysis of the proliferative activity of cell cultures of human gliomas of various degrees of malignancy did not reveal a relationship with a migratory properties of cultures. A number of actively proliferating cultures did not show high migration, while cultures with medium proliferative activity could show a high level of migration. The low level of proliferation of cultures of gliomas of Grade II and I at the beginning of cultivation, in some cases, subsequently increased, but an inherent low migration activity did not change. In actively migrating cultures, a significant decrease in the expression of Sox2 and Nestin is detected. A positive correlation was found between migration abilities of human glioma cell culture cells and the marker Ki67, GFAP, Sox2, and Oct4. The difference was statistically significant by the one-sided Mann-Whitney test.

CONCLUSION

Conclusions: Cell cultures derived from glioma tumor tissue can be used to predict invasive properties of the tumor. High tumor invasiveness is characteristic for Grade III and Grade IV, and with IDH1- (minus) phenotype, and it also correlates with elevated expression of GFAP, Sox2 and Oct4The reported study was funded by RFBR according to the research project № 18-29-01012 and by the Ministry of Science and Higher Education of the Russian Federation, grant number 075-15-2020-809 (13.1902.21.0030).

[PSYCHOTHERAPEUTIC INTERVENTIONS IN PATIENTS WITH AUTO-AGGRESSIVE BEHAVIOR DURING THE FIRST PSYCHOTIC EPISODE]

In this article the formation of psychopathological predictors auto-aggressive behavior in patients with a first psychotic episode were identified, which became "targets" in the framework of a comprehensive emergency suicide assistance to conduct the crisis psychotherapy. The work was done on the basis of the Sumy regional psychoneurologic dispensary, where 100 patients with a first psychotic episode were examined: 52 of them (core group) had suicidal symptoms and 48 (control group) had not. According to the test results of severity of auto-aggressive predictors (pre-suicidal syndrome) to clinicopsychopathological predictors of auto-aggressive behavior include: the narrowing of the cognitive function (p≤0,001), the avoidance of interpersonal contact (r≤0,001), the presence of affective (p≤0,001) and vegetative (p≤0,01) violations, the autoaggression of moderate severity (p≤0,001) and impulsivity (p≤0,001). Patients of the core group with the auto-aggressive behavior (n=58) completed a course of a crisis psychotherapy comprising the stages of crisis support, crisis intervention and increase the adaptation layer. After a psychotherapy course levels of aggression (6,45±0,41), auto-aggression (of 9,68±0,67), disorders in the affective sphere (18,58±0,66) and impulsivity (of 4,23±0,30) decreased, which was manifested in increasing tolerance to emotional stress factors, control over their emotions and reduce their affective valence (p≤0,001). The expansion of interpersonal interaction, the increase of patients social activity, the blood relationships establishment (of 9,23±0,40) was observed.

Quality of end-of-life cancer care in Canada: a retrospective four-province study using administrative health care data

BACKGROUND

The quality of data comparing care at the end of life (eol) in cancer patients across Canada is poor. This project used identical cohorts and definitions to evaluate quality indicators for eol care in British Columbia, Alberta, Ontario, and Nova Scotia.

METHODS

This retrospective cohort study of cancer decedents during fiscal years 2004-2009 used administrative health care data to examine health service quality indicators commonly used and previously identified as important to quality eol care: emergency department use, hospitalizations, intensive care unit admissions, chemotherapy, physician house calls, and home care visits near the eol, as well as death in hospital. Crude and standardized rates were calculated. In each province, two separate multivariable logistic regression models examined factors associated with receiving aggressive or supportive care.

RESULTS

Overall, among the identified 200,285 cancer patients who died of their disease, 54% died in a hospital, with British Columbia having the lowest standardized rate of such deaths (50.2%). Emergency department use at eol ranged from 30.7% in Nova Scotia to 47.9% in Ontario. Of all patients, 8.7% received aggressive care (similar across all provinces), and 46.3% received supportive care (range: 41.2% in Nova Scotia to 61.8% in British Columbia). Lower neighbourhood income was consistently associated with a decreased likelihood of supportive care receipt.

INTERPRETATION

We successfully used administrative health care data from four Canadian provinces to create identical cohorts with commonly defined indicators. This work is an important step toward maturing the field of eol care in Canada. Future work in this arena would be facilitated by national-level data-sharing arrangements.

Mild traumatic brain injury

Traumatic Brain Injury (TBI) is among the most frequent neurological disorders. Of all TBIs 90% are considered mild with an annual incidence of 100–300/100.000. Intracranial complications of Mild Traumatic Brain Injury (MTBI) are infrequent (10%), requiring neurosurgical intervention in a minority of cases (1%), but potentially life-threatening (case fatality rate 0,1%). Hence, a true health management problem exists because of the need to exclude the small chance of a life threatening complication in large numbers of individual patients. The 2002 EFNS guidelines used a best evidence approach based on the literature until 2001 to guide initial management with respect to indications for CT, hospital admission, observation and follow up of MTBI patients. This updated EFNS guideline version for initial management inMTBI proposes a more selectively strategy for CT when major (dangerous mechanism, GCS<15, 2 points deterioration on the GCS, clinical signs of (basal) skull fracture, vomiting, anticoagulation therapy, post traumatic seizure) or minor (age, loss of consciousness, persistent anterograde amnesia, focal deficit, skull contusion, deterioration on the GCS) risk factors are present based on published decision rules with a high level of evidence. In addition clinical decision rules for CT now exist for children as well. Since 2001 recommendations, although with a lower level of evidence, have been published for clinical in hospital observation to prevent and treat other potential threads to the patient including behavioral disturbances (amnesia, confusion and agitation) and infection.

Distance measurements in model bis-Gd(III) complexes with flexible "bridge". Emulation of biological molecules having flexible structure with Gd(III) labels attached

In this work, we continue to explore Gd(III) as a possible spin label for high-field Double Electron-Electron Resonance (DEER) based distance measurements in biological molecules with flexible geometry. For this purpose, a bis-Gd(III) complex with a flexible "bridge" was used as a model. The distances in the model were expected to be distributed in the range of 5-26 A, allowing us to probe the shortest limits of accessible distances which were found to be as small as 13 A. The upper distance limit for these labels was also evaluated and was found to be about 60 A. Various pulse duration setups can result in apparent differences in the distribution function derived from DEER kinetics due to short distance limit variations. The advantages, such as the ability to perform measurements at cryogenic temperatures and high repetition rates simultaneously, the use of very short pumping and observation pulses without mutual interference, the lack of orientational selectivity, as well as the shortcomings, such as the limited mw operational frequency range and intrinsically smaller amplitude of oscillation related to dipolar interaction as compared with nitroxide spin labels are discussed. Most probably the use of nitroxide and Gd-based labels for distance measurements will be complementary depending on the particulars of the problem and the availability of instrumentation.

Convergence of reinforcement learning algorithms and acceleration of learning

The techniques of reinforcement learning have been gaining increasing popularity recently. However, the question of their convergence rate is still open. We consider the problem of choosing the learning steps alpha(n), and their relation with discount gamma and exploration degree epsilon. Appropriate choices of these parameters may drastically influence the convergence rate of the techniques. From analytical examples, we conjecture optimal values of alpha(n) and then use numerical examples to verify our conjectures.

EFNS guideline on mild traumatic brain injury: report of an EFNS task force

In 1999, a Task Force on Mild Traumatic Brain Injury (MTBI) was set up under the auspices of the European Federation of Neurological Societies. Its aim was to propose an acceptable uniform nomenclature for MTBI and definition of MTBI, and to develop a set of rules to guide initial management with respect to ancillary investigations, hospital admission, observation and follow-up.

Neural networks for estimating intrinsic dimension

We consider the problem of feature extraction and determination of intrinsic dimensionality of observation data. One of the common approaches to this problem is to use autoassociative neural networks with a "bottleneck" projecting layer. We propose a different approach in which a neural network performs a topological mapping that creates a nonlinear lower-dimensional projection of the data. The mapping preserves relative distances of neighbors. This technique can be efficiently implemented with the help of radial basis function networks, and it is significantly faster than training an autoassotiative network. We show that the proposed technique can be used for estimating the dimension of minimal mathematical model from time series data.

Application of three-dimensional resonant acoustic spectroscopy method to rock and building materials

This paper presents the experimental and theoretical results of applying resonant acoustic spectroscopy (RAS) to determine elastic parameters and losses in such consolidated granular materials as rock and building bricks. First, the theoretical aspects of the RAS method are outlined. A computer code for the rectangular and cylindrical samples was developed and tested. The results of experiments on specimens of rock and ceramic brick are then described. Finally, a modification of the previously published RUS algorithm is presented which permits a significant reduction in computing time for elongated samples.

Chaotic neural control

We consider the problem of stabilizing unstable equilibria by discrete controls (the controls take discrete values at discrete moments of time). We prove that discrete control typically creates a chaotic attractor in the vicinity of an equilibrium. Artificial neural networks with reinforcement learning are known to be able to learn such a control scheme. We consider examples of such systems, discuss some details of implementing the reinforcement learning to controlling unstable equilibria, and show that the arising dynamics is characterized by positive Lyapunov exponents, and hence is chaotic. This chaos can be observed both in the controlled system and in the activity patterns of the controller.