The temperature dependence (in the range of 479–827 K) of the fluorine-ionic conductivity of nonstoichiometric Na
0.37
Tb
0.63
F
2.26
crystals with fluorite-type structure (sp. gr.
, lattice ...parameter
a
= 5.5785(1) Å) has been investigated. The crystals were grown from melt by the Bridgman method in a fluorinating atmosphere of CF
4
. The formation of cuboctahedral clusters of defects {(Na,Tb)
8
Tb
6
F
37
F
32
} is most likely in the structure of Na
0.37
Tb
0.63
F
2.26
crystals. The ionic conductivity is found to be σ
dc
= 2.6 × 10
–6
and 3 × 10
–3
S/cm at 500 and 827 K, respectively. A crystallophysical model of ion transport in Na
0.37
Tb
0.63
F
2.26
crystals is proposed. The concentration and carrier mobility are calculated to be, respectively,
n
mob
= 1.45 × 10
21
cm
–3
and μ
mob
= 1.1 × 10
–8
cm
2
/(s V) at 500 K.
The article presents data on measurements of methane fluxes at largest Russian reservoirs, carried out in August and September 2021 under long-term research project.
Histone deacetylases play an important role in regulating gene expression by modifying histones and changing chromatin conformation. HDAC dysregulation is involved in many diseases, such as cancer, ...autoimmune and neurodegenerative diseases. Histone deacetylase 1 (HDAC1) inhibitors represent an important class of drugs. Quantitative Structure-Activity Relationship (QSAR) classification models were developed using 2D RDKit molecular descriptors; ECPF4 (Extended Connectivity Fingerprint) circular fingerprints; and the Random Forest, Gradient Boosting, and Support Vector Machine methods. The developed models were integrated into the HDAC1 PREDICTOR application, which is freely available at the link
https://ovttiras-hdac1-inhibitors-hdac1-predictor-app-z3mrbr.streamlitapp.com
. The HDAC1 PREDICTOR web application allows one to reveal the compounds for which the predicted activity to inhibit HDAC1 is higher than that of the reference Vorinostat compound (IC
50
= 11.08 nM). The algorithm implemented in HDAC1 PREDICTOR for determining the contributions of molecular fragments to the inhibitory activity can be used to find the molecule segments that increase or decrease the activity, enabling the researcher to conduct a rational molecular design of new highly active HDAC1 inhibitors. The developed QSAR models and the code for their construction in the Python programming language are freely available on the GitHub platform at
https://github.com/ovttiras/HDAC1-inhibitors
.
The HDAC6 (histone deacetylase 6) enzyme plays a key role in many biological processes, including cell division, apoptosis, and immune response. To date, HDAC6 inhibitors are being developed as ...effective drugs for the treatment of various diseases. In this work, adequate QSAR models of HDAC6 inhibitors are proposed. They are integrated into the developed application HDAC6 Detector, which is freely available at
https://ovttiras-hdac6-detector-hdac6-detector-app-yzh8y5.streamlit.app/
. The web application HDAC6 Detector can be used to perform virtual screening of HDAC6 inhibitors by dividing the compounds into active and inactive ones relative to the reference vorinostat compound (IC
50
= 10.4 nM). The web application implements a structural interpretation of the developed QSAR models. In addition, the application can evaluate the compliance of a compound with Lipinski's rule. The developed models are used for virtual screening of a series of 12 new hydroxamic acids, namely, the derivatives of 3-hydroxyquinazoline-4(3H)-ones and 2-aryl-2,3-dihydroquinazoline-4(1H)-ones. In vitro evaluation of the inhibitory activity of this series of compounds against HDAC6 allowed us to confirm the results of virtual screening and to select promising compounds V-6 and V-11, the IC
50
of which is 0.99 and 0.81 nM, respectively.
Histone deacetylase inhibitors represent the most important class of drugs for the treatment of human cancer and other diseases due to their influence on cell growth, differentiation, and apoptosis. ...Among the well-known eighteen histone deacetylases, histone deacetylase 6 (HDAC6), which is involved in oncogenesis, cell survival, and cancer cell metastasis, is of great importance. Using the CDK and alvaDesc molecular descriptors and the Random Forest and EXtreme Gradient Boosting methods, we propose a number of adequate QSAR classification models, which are integrated into a consensus model and are freely available on the OCHEM web platform (
https://ochem.eu
). The consensus QSAR model is used for virtual screening of a series of seven new compounds, the derivatives of N-((hydroxyamino)-oxoalkyl)-2-(quinazoline-4-ilamino)-benzamides, the synthesis schemes of which are also presented in this work. In vitro evaluation of the inhibitory activity (IC
50
) of this series of compounds against HDAC6 allowed us to confirm the results of virtual screening and to reveal promising compounds V-2 and V-4, IC
50
of which is 3.25 nM and 0.04 nM, respectively. The subsequent in silico evaluation of the main ADMET properties of active compounds V-2 and V-4 allowed us to find that they have acceptable pharmacokinetic parameters and level of acute toxicity.
Technetium(I) tetracarbonyl complexes with diethyldithiocarbamate and methylxanthate ligands TcL(CO)4 (L = S2CNEt2 and S2COMe) were prepared. Conditions required for the formation of these complexes ...were found. The crystal and molecular structure of the xanthate complex was determined by single-crystal X-ray diffraction. Tc(S2CNEt2)(CO)4 undergoes decarbonylation both in solution and in the course of vacuum sublimation with the formation of a dimer Tc(S2CNEt2)(CO)32 whose structure was determined by single-crystal X-ray diffraction. In donor solvents, Tc(S2CNEt2)(CO)4 and Tc(S2COMe)(CO)4 undergo decarbonylation with the formation of tricarbonyl solvates TcL(CO)3(Sol). The crystal structure of the pyridine solvate Tc(S2CNEt2)(CO)3(py), chosen as an example, was determined by single-crystal X-ray diffraction. The possibility of using bidentate S-donor acidic ligands for tethering the tetracarbonyltechnetium fragment to biomolecules was examined.
A method of amplification and shaping of analog signals produced by a large-capacitance signal source is proposed. This method is optimized for reaching the highest signal/noise ratio, and, along ...with that, it allows for recognizing signals that arrive with a small time interval. An amplifying channel is designed that implements the proposed method. This channel is purposed for amplification of avalanche photodiode signals in detectors based of fast scintillators. The structure of the amplifying channel, the principle of recovering the shape of the input signal, and the basic circuit design solutions used in the developed amplifier are described.
In this paper, we present a new mathematical model of the interaction of two languages. In the model, we distinguish percentages of people who speak a non-target language, a target language with low ...and high proficiency, and both languages considering the low and high proficiency levels in the target language. Therefore, the solution consists of five fields. Furthermore, we assume the diffusive and convective spread of the languages, considering the overflow between them. Thus, the mathematical model is defined by a coupled system of partial differential equations for the five fields.
Since the mathematical model is coupled and the medium is heterogeneous, we have implemented a multiscale method. The proposed multiscale method is based on the Generalized Multiscale Finite Element Method (GMsFEM). In addition to offline multiscale basis functions, we also construct online multiscale basis functions. The online basis functions can account for changes in the heterogeneity of the medium caused by migration flows. Numerical results have shown that such online enrichment can significantly improve the accuracy of multiscale modeling.
In this paper, we propose a mathematical model of the interaction of two languages. In our model, we consider two languages, though it can be generalized to multiple languages, which compete in a ...heterogeneous environment, consisting of highly varying properties related to the dynamics of the interaction. We use coupled convection–diffusion–reaction equations to describe the processes. Each equation describes the dynamics of one of the languages and contains terms related to the stand-alone dynamics and some coupling terms. The coupling terms represent the interaction between languages. We propose a numerical approach for solving the proposed model equation. In particular, we consider various inhomogeneities associated with cities and countryside, where languages are used differently (e.g., Sakha republic). These dynamics are essential for understanding the evolution of languages (one being dominant) and linguistic ecology that studies languages and their use in real/social life. Because of heterogeneities associated with geography, we use a multiscale approach. The proposed multiscale approach designs special basis functions to represent the small-scale information on larger scales. This way, we can solve the problem on a much coarser grid. Numerical results are presented that describe the dynamics and interaction of two languages. The main novelty of the paper consists of the proposed model and a multiscale algorithm.
