A novel open-access artificial-intelligence-driven platform for CNS drug discovery utilizing adult zebrafish.

Background: Although zebrafish are increasingly utilized in biomedicine for CNS disease modelling and drug discovery, this generates big data necessitating objective, precise and reproducible analyses. The artificial intelligence (AI) applications have empowered automated image recognition and video-tracking to ensure more efficient behavioral testing.

New Method: Capitalizing on several AI tools that most recently became available, here we present a novel open-access AI-driven platform to analyze tracks of adult zebrafish collected from in vivo neuropharmacological experiments.

Peculiarities of the 7 × 7 to 5 × 5 Superstructure Transition during Epitaxial Growth of Germanium on Silicon (111) Surface.

This paper presents the results of studying the processes of epitaxial growth of germanium on silicon with crystallographic orientation (111) in a wide temperature range. The temperature dependences of the duration of the transition stage from the 7 × 7 to 5 × 5 superstructure and the values of the critical thickness of the transition from two-dimensional to three-dimensional growth in the range from 250 to 700 °C are determined using the reflection high-energy electron diffraction method. It was shown for the first time that the transition time from the 7 × 7 superstructure to 5 × 5 superstructure depends on the temperature of epitaxial growth.

Identification of the autotransporter CFA as a protective antigen and hypervariable target of neutralizing antibodies in mice.

The bacterial genus comprises numerous emerging pathogens that cause a broad spectrum of disease manifestations in humans. The targets and mechanisms of the anti- immune defense are ill-defined and bacterial immune evasion strategies remain elusive. We found that experimentally infected mice resolved infection by mounting antibody responses that neutralized the bacteria, preventing their attachment to erythrocytes and suppressing bacteremia independent of complement or Fc receptors.

[Hyperbolic growth of marine and continental biodiversity through the phanerozoic and community evolution].

Among diverse models that are used to describe and interpret the changes in global biodiversity through the Phanerozoic, the exponential and logistic models (traditionally used in population biology) are the most popular. As we have recently demonstrated (Markov, Korotayev, 2007), the growth of the Phanerozoic marine biodiversity at genus level correlates better with the hyperbolic model (widely used in demography and macrosociology). Here we show that the hyperbolic model is also applicable to the Phanerozoic continental biota at genus and family levels, and to the marine biota at species, genus, and family levels.

[The dynamics of Phanerozoic marine animal diversity agrees with the hyperbolic growth model].

Generic diversity dynamics of the Phanerozoic marine animals is far better described by the hyperbolic model, widely used in demography and macrosociology, than by the exponential and logistic models from population dynamics traditionally employed for this purpose. Exponential and logistic models imply zero influence of interactions between taxa on the dynamics of diversity, with the exception of competing for unoccupied ecological space, whereas the hyperbolic model implies non-linear second-order positive feedback in the development of the biota. The hyperbolic human population growth is caused by positive feedback between population size and the rate of technological and cultural development (the more individuals, the more inventors, the more rapid progress, the more rapid growth of the Earth's bearing capacity; the smaller death-rate, the more accelerated growth-rate of the population).