Pharmacoresistant epilepsy is a common neurological disorder in which increased neuronal intrinsic excitability and synaptic excitation lead to pathologically synchronous behavior in the brain. In the majority of experimental and theoretical epilepsy models, epilepsy is associated with reduced inhibition in the pathological neural circuits, yet effects of intrinsic excitability are usually not explicitly analyzed. Here we present a novel neural mass model that includes intrinsic excitability in the form of spike-frequency adaptation in the excitatory population. We validated our model using local field potential data recorded from human hippocampal/subicular slices. We found that synaptic conductances and slow adaptation in the excitatory population both play essential roles for generating seizures and pre-ictal oscillations. Using bifurcation analysis, we found that transitions towards seizure and back to the resting state take place via Andronov-Hopf bifurcations. These simulations therefore suggest that single neuron adaptation as well as synaptic inhibition are responsible for orchestrating seizure dynamics and transition towards the epileptic state.
The article discusses the comparative evaluation of combined treatment results in patients with DTC (differentiated thyroid cancer) at different levels of TSH-stimulated prior to RAI (radioactive iodine) treatment. The study included 197 patients (36 female, 161 male) of the age group 18-75 years with a mean age of 47 years. The data was analyzed using several statistical methods: analysis of variance (ANOVA), linear and logistic regression models. The resulting data from the analysis showed that there was no statistically significant association between serum TSH levels prior to RAI and DTC remission.
Although many real-time neural decoding algorithms have been proposed for brain-machine interface (BMI) applications over the years, an optimal, consensual approach remains elusive. Recent advances in deep learning algorithms provide new opportunities for improving the design of BMI decoders, including the use of recurrent artificial neural networks to decode neuronal ensemble activity in real time. Here, we developed a long-short term memory (LSTM) decoder for extracting movement kinematics from the activity of large (N = 134-402) populations of neurons, sampled simultaneously from multiple cortical areas, in rhesus monkeys performing motor tasks. Recorded regions included primary motor, dorsal premotor, supplementary motor, and primary somatosensory cortical areas. The LSTM's capacity to retain information for extended periods of time enabled accurate decoding for tasks that required both movements and periods of immobility. Our LSTM algorithm significantly outperformed the state-of-the-art unscented Kalman filter when applied to three tasks: center-out arm reaching, bimanual reaching, and bipedal walking on a treadmill. Notably, LSTM units exhibited a variety of well-known physiological features of cortical neuronal activity, such as directional tuning and neuronal dynamics across task epochs. LSTM modeled several key physiological attributes of cortical circuits involved in motor tasks. These findings suggest that LSTM-based approaches could yield a better algorithm strategy for neuroprostheses that employ BMIs to restore movement in severely disabled patients.
A large body of data has identified numerous molecular targets through which ethanol (EtOH) acts on brain circuits. Yet how these multiple mechanisms interact to result in dysregulated dopamine (DA) release under the influence of alcohol in vivo remains unclear. In this manuscript, we delineate potential circuit‐level mechanisms responsible for EtOH‐dependent dysregulation of DA release from the ventral tegmental area (VTA) into its projection areas. For this purpose, we constructed a circuit model of the VTA that integrates realistic Glutamatergic (Glu) inputs and reproduces DA release observed experimentally. We modelled the concentration‐dependent effects of EtOH on its principal VTA targets. We calibrated the model to reproduce the inverted U‐shape dose dependence of DA neuron activity on EtOH concentration. The model suggests a primary role of EtOH‐induced boost in the Ih and AMPA currents in the DA firing‐rate/bursting increase. This is counteracted by potentiated GABA transmission that decreases DA neuron activity at higher EtOH concentrations. Thus, the model connects well‐established in vitro pharmacological EtOH targets with its in vivo influence on neuronal activity. Furthermore, we predict that increases in VTA activity produced by moderate EtOH doses require partial synchrony and relatively low rates of the Glu afferents. We propose that the increased frequency of transient (phasic) DA peaks evoked by EtOH results from synchronous population bursts in VTA DA neurons. Our model predicts that the impact of acute ETOH on dopamine release is critically shaped by the structure of the cortical inputs to the VTA.
Mechanical performances of titanium biomedical implants manufactured by superplastic forming are strongly related to the process parameters: the thickness distribution along the formed sheet has a key role in the evaluation of post-forming characteristics of the prosthesis. In this work, a finite element model able to reliably predict the thickness distribution after the superplastic forming operation was developed and validated in a case study. The material model was built for the investigated titanium alloy (Ti6Al4V-ELI) upon results achieved through free inflation tests in different pressure regimes. Thus, a strain and strain rate dependent material behaviour was implemented in the numerical model. It was found that, especially for relatively low strain rates, the strain rate sensitivity index of the investigated titanium alloy significantly decreases during the deformation process. Results on the case study highlighted that the strain rate has a strong influence on the thickness profile, both on its minimum value and on the position in which such a minimum is found.
Most common drug development failures originate from either bioavailability problems, or unexpected toxic effects. The culprit is often the liver, which is responsible for biotransformation of a majority of xenobiotics. Liver may be modeled using "liver on a chip" devices, which may include established cell lines, primary human cells, and stem cell-derived hepatocyte-like cells. The choice of biological material along with its processing and maintenance greatly influence both the device performance and the resultant toxicity predictions. Impediments to the development of "liver on a chip" technology include the problems with standardization of cells, limitations imposed by culturing and the necessity to develop more complicated fluidic contours. Fortunately, recent breakthroughs in the development of cell-based reporters, including ones with fluorescent label, permits monitoring of the behavior of the cells embed into the "liver on a chip" devices. Finally, a set of computational approaches has been developed to model both particular toxic response and the homeostasis of human liver as a whole; these approaches pave a way to enhance the in silico stage of assessment for a potential toxicity.
Background: Chromosomal rearrangements are the typical phenomena in cancer genomes causing gene disruptions and fusions, corruption of regulatory elements, damage to chromosome integrity. Among the factors contributing to genomic instability are non-B DNA structures with stem-loops and quadruplexes being the most prevalent. We aimed at investigating the impact of specifically these two classes of non-B DNA structures on cancer breakpoint hotspots using machine learning approach.
Methods: We developed procedure for machine learning model building and evaluation as the considered data are extremely imbalanced and it was required to get a reliable estimate of the prediction power. We built logistic regression models predicting cancer breakpoint hotspots based on the densities of stem-loops and quadruplexes, jointly and separately. We also tested Random Forest models varying different resampling schemes (leave-one-out cross validation, train-test split, 3-fold cross-validation) and class balancing techniques (oversampling, stratification, synthetic minority oversampling).
Results: We performed analysis of 487,425 breakpoints from 2234 samples covering 10 cancer types available from the International Cancer Genome Consortium. We showed that distribution of breakpoint hotspots in different types of cancer are not correlated, confirming the heterogeneous nature of cancer. It appeared that stem-loop- based model best explains the blood, brain, liver, and prostate cancer breakpoint hotspot profiles while quadruplex- based model has higher performance for the bone, breast, ovary, pancreatic, and skin cancer. For the overall cancer profile and uterus cancer the joint model shows the highest performance. For particular datasets the constructed models reach high predictive power using just one predictor, and in the majority of the cases, the model built on both predictors does not increase the model performance.
Conclusion: Despite the heterogeneity in breakpoint hotspots’ distribution across different cancer types, our results demonstrate an association between cancer breakpoint hotspots and stem-loops and quadruplexes. Approximately for half of the cancer types stem-loops are the most influential factors while for the others these are quadruplexes. This fact reflects the differences in regulatory potential of stem-loops and quadruplexes at the tissue-specific level, which yet to be discovered at the genome-wide scale. The performed analysis demonstrates that influence of stem- loops and quadruplexes on breakpoint hotspots formation is tissue-specific.
A cancer cell line originating from human epithelial colorectal adenocarcinoma (Caco-2 cells) serves as a high capacity model for a preclinical screening of drugs. Recent need for incorporating barrier tissue into multi-organ chips calls for inclusion of Caco-2 cells into microperfused environment. This article describes a series of systems biology insights obtained from comparing Caco-2 models cells grown as conventional 2D layer and in a microfluidic chip. When basic electrical parameters of Caco-2 monolayers were evaluated using impedance spectrometry and MTT assays, no differences were noted. On the other hand, the microarray profiling of mRNAs and miRNAs revealed that grows on a microfluidic chip leads to the change in the production of specific miRNA, which regulate a set of genes for cell adhesion molecules (CAMs), and provide for more complete differentiation of Caco-2 monolayer. Moreover, the sets of miRNAs secreted at the apical surface of Caco-2 monolayers grown in conventional 2D culture and in microfluidic device differ. When integrated into a multi-tissue platform, Caco-2 cells may aid in generating insights into complex pathophysiological processes, not possible to dissect in conventional cultures.
The paper shows that there is a pattern in the distribution of synthetic (šēp šarrim “the king’s foot”) vs. analytical (kaspum ša awīlim “the boss’s money”) genitive constructions in Old Babylonian. The choice depends on the lexical feature of head nouns known as (in)alienability. Old Babylonian kinship and body part terms, as well as some other substantives, are “inalienable”, which means they take only the synthetic construction. All other Old Babylonian nouns are “alienable”, which means they admit both the synthetic and the analytical construction (kasap tamkārī and kaspum ša tamkārī “the merchants’ money”). In the latter case, there is no general rule to predict the choice, yet in certain cases the two constructions display a non-random frequency distribution.
The paper discusses the techniques which are currently implemented for vaccine production based on virus-like particles (VLPs). The factors which determine the characteristics of VLP monomers assembly are provided in detail. Analysis of the literature demonstrates that the development of the techniques of VLP production and immobilization of target antigens on their surface have led to the development of universal platforms which make it possible for virtually any known antigen to be exposed on the particle surface in a highly concentrated form. As a result, the focus of attention has shifted from the approaches to VLP production to the development of a precise interface between the organism’s immune system and the peptides inducing a strong immune response to pathogens or the organism’s own pathological cells. Immunome-specified techniques for vaccine design and the prospects of immunoprophylaxis are discussed. Certain examples of vaccines against viral diseases and cancers are considered.
Hypoxia of trophoblast cells is an important regulating factor in the process of normal placenta development. However, the effect of hypoxia on the placenta in a number of pathological conditions, such as preeclampsia, leads to impaired cellular functions. A oxyquinoline derivative is capable of inhibiting HIF-prolyl hydroxylases, thereby stabilizing the transcription complex of HIF-1 and activating the cell response to hypoxia. BeWo b30 human choriocarcinoma cells are used to model trophoblast, which forms the basis for placenta barrier. Oxyquinoline effect leads both to an increased expression of a number of the genes that form the core response to hypoxia, and upregulated expression of NOS3, PDK1, and BNIP3 genes and downregulated expression of the PPARGC1B gene. This indicates the activation of mechanisms of metabolic cell reprogramming aimed at reducing oxygen consumption by reducing the number of mitochondria and switching from aerobic glucose metabolism to anaerobic. Possible applications of the obtained results is under discussion.
Introduction. The concept of health-related quality of life as a key factor in patient-doctor interactions is an important basis for making managerial and medical decisions in many foreign health systems. In Russia, the concept of health-related quality of life is in its infancy: it is required the theoretical, methodological and scientific-practical foundations development.
Aims and objectives. The aim of this study is to assess the health- related quality of life for Russian population based on the EQ–5D questionnaire and to form the average health indicators.
Material and methods. The survey was conducted on a sample of 1,602 people aged 18 to 92 years. The final sample is representative for the country and federal districts. We use using the Russian-language version of the EQ–5D questionnaire which allows us to receive two indicators for each respondent – health profile and index based on visual analog scale EQ–VAS.
Results. The study revealed the following results: (1) the majority of the respondents among all ages have the problems in EQ-5D dimension “anxiety/depression”; (2) women tend to detect moderate problems in all dimensions more often than men; (3) EQ–5D descriptive results are decreased in all components with the respondents age; (4) the most infrequent population’s problems among the all dimensions are found in the "self-care" dimension; (5) the age changes related to a decrease of EQ–VAS are associated with the general tendency of a decrease in the dimensions.
Discussion. To obtain the most accurate and objective assessments from the EQ–5D, it is necessary to conduct a study in accordance with established international protocols, compare the estimates with the average population indices and adhere to a thorough research design.
Conclusion. The study reveals the possibilities of using EQ–5D and the first health-related quality of life Russian population indicators that can be used as a basis for comparing between different population groups and patients.