Moscow Institute of Physics and Technology

About: Moscow Institute of Physics and Technology is a education organization based out in Dolgoprudnyy, Russia. It is known for research contribution in the topics: Laser & Large Hadron Collider. The organization has 8594 authors who have published 16968 publications receiving 246551 citations. The organization is also known as: MIPT & Moscow Institute of Physics and Technology (State University).

On the mean profiles of radio pulsars – I. Theory of propagation effects

Abstract: We study the influence of propagation effects on the mean profiles of radio pulsars using the method of wave propagation in inhomogeneous media described by Kravtsov & Orlov. This approach allows us first to take into consideration the transition from geometrical optics to vacuum propagation, the cyclotron absorption and the wave refraction simultaneously. In addition, the non-dipole magnetic field configuration, the drift motion of plasma particles and their realistic energy distribution are taken into account. It is confirmed that, for ordinary pulsars (period P ∼ 1 s, surface magnetic field B0 ∼ 1012 G) and typical plasma generation near the magnetic poles (multiplicity parameter λ = ne/nGJ ∼ 103), the polarization is formed inside the light cylinder at a distance resc ∼ 1000 R from the neutron star, the circular polarization being 5–20 per cent which is in agreement with observational data. A one-to-one correspondence between the signs of circular polarization and position angle (PA) derivative along the profile for both ordinary and extraordinary waves is predicted. Using numerical integration we now can model the mean profiles of radio pulsars. It is shown that the standard S-shape form of the PA swing can be realized for small enough multiplicity λ and large enough bulk Lorentz factor γ only. It is also shown that the value of the maximum derivative of PA, which is often used for determination of the angle between magnetic dipole and rotation axis, depends on the plasma parameters and could differ from the rotation vector model (RVM) prediction.

Single-cell transcriptomics of human embryos identifies multiple sympathoblast lineages with potential implications for neuroblastoma origin.

Abstract: Characterization of the progression of cellular states during human embryogenesis can provide insights into the origin of pediatric diseases. We examined the transcriptional states of neural crest- and mesoderm-derived lineages differentiating into adrenal glands, kidneys, endothelium and hematopoietic tissue between post-conception weeks 6 and 14 of human development. Our results reveal transitions connecting the intermediate mesoderm and progenitors of organ primordia, the hematopoietic system and endothelial subtypes. Unexpectedly, by using a combination of single-cell transcriptomics and lineage tracing, we found that intra-adrenal sympathoblasts at that stage are directly derived from nerve-associated Schwann cell precursors, similarly to local chromaffin cells, whereas the majority of extra-adrenal sympathoblasts arise from the migratory neural crest. In humans, this process persists during several weeks of development within the large intra-adrenal ganglia-like structures, which may also serve as reservoirs of originating cells in neuroblastoma.

From binding motifs in ChIP-Seq data to improved models of transcription factor binding sites.

Abstract: Chromatin immunoprecipitation followed by deep sequencing (ChIP-Seq) became a method of choice to locate DNA segments bound by different regulatory proteins. ChIP-Seq produces extremely valuable information to study transcriptional regulation. The wet-lab workflow is often supported by downstream computational analysis including construction of models of nucleotide sequences of transcription factor binding sites in DNA, which can be used to detect binding sites in ChIP-Seq data at a single base pair resolution. The most popular TFBS model is represented by positional weight matrix (PWM) with statistically independent positional weights of nucleotides in different columns; such PWMs are constructed from a gapless multiple local alignment of sequences containing experimentally identified TFBSs. Modern high-throughput techniques, including ChIP-Seq, provide enough data for careful training of advanced models containing more parameters than PWM. Yet, many suggested multiparametric models often provide only incremental improvement of TFBS recognition quality comparing to traditional PWMs trained on ChIP-Seq data. We present a novel computational tool, diChIPMunk, that constructs TFBS models as optimal dinucleotide PWMs, thus accounting for correlations between nucleotides neighboring in input sequences. diChIPMunk utilizes many advantages of ChIPMunk, its ancestor algorithm, accounting for ChIP-Seq base coverage profiles ("peak shape") and using the effective subsampling-based core procedure which allows processing of large datasets. We demonstrate that diPWMs constructed by diChIPMunk outperform traditional PWMs constructed by ChIPMunk from the same ChIP-Seq data. Software website: http://autosome.ru/dichipmunk/

Sop‐GPU: Accelerating biomolecular simulations in the centisecond timescale using graphics processors

Abstract: Theoretical exploration of fundamental biological processes involving the forced unraveling of multimeric proteins, the sliding motion in protein fibers and the mechanical deformation of biomolecular assemblies under physiological force loads is challenging even for distributed computing systems. Using a C(α)-based coarse-grained self organized polymer (SOP) model, we implemented the Langevin simulations of proteins on graphics processing units (SOP-GPU program). We assessed the computational performance of an end-to-end application of the program, where all the steps of the algorithm are running on a GPU, by profiling the simulation time and memory usage for a number of test systems. The ∼90-fold computational speedup on a GPU, compared with an optimized central processing unit program, enabled us to follow the dynamics in the centisecond timescale, and to obtain the force-extension profiles using experimental pulling speeds (v(f) = 1-10 μm/s) employed in atomic force microscopy and in optical tweezers-based dynamic force spectroscopy. We found that the mechanical molecular response critically depends on the conditions of force application and that the kinetics and pathways for unfolding change drastically even upon a modest 10-fold increase in v(f). This implies that, to resolve accurately the free energy landscape and to relate the results of single-molecule experiments in vitro and in silico, molecular simulations should be carried out under the experimentally relevant force loads. This can be accomplished in reasonable wall-clock time for biomolecules of size as large as 10(5) residues using the SOP-GPU package.