Potential Therapeutic Applications of Exosomes in Bone Regenerative Medicine

The ability of bone regeneration is relatively robust, which is crucial for fracture healing, but delayed healing and nonunion are still common problems in clinical practice. Fortunately, exciting results have been achieved for regenerative medicine in recent years, especially in the area of stem cell-based treatment, but all these cell-based approaches face challenging problems, including immune rejection. For this reason, exosomes, stem cell-derived small vesicles of endocytic origin, have attracted the attention of many investigators in the field of bone regeneration. One of the attractive features of exosomes is that they are small and can travel between cells and deliver bioactive products, including miRNA, mRNA, proteins, and various other factors, to promote bone regeneration, with undetectable immune rejection. In this chapter, we intend to briefly update the recent progressions, and discuss the potential challenges in the target areas. Hopefully, our discussion would be helpful not only for the clinicians and the researchers in the specific disciplines but also for the general audiences as well

Design and implementation of cloud platform for nuclear accident simulation

Introduction: To meet the multi-user, cross-time-and-space, cross-platform online demand of work, and professional training teaching in nuclear reactor safety analysis under the normalization of Coronavirus Disease 2019.Method: Taking the nuclear accident simulation software PCTRAN as an example, this study adopts cloud computing technology to build the NasCloud, a nuclear accident simulation cloud platform based on Browser/Server architecture, and successfully realizes multi-user, cross-time-and-space, cross-platform applications. Targeting the AP1000, a pressurized water reactor nuclear power plant, the simulation of cold-leg Small Break Loss of Coolant Accident and cold-leg Large Break Loss of Coolant Accident were carried out to verify the correctness of the NasCloud’s accident simulation function.Results: The result shows that the simulation functions and results of the NasCloud in multi-terminal are consistent with the single version of PCTRAN. At the same time, the platform has high scalability, concurrency and security characteristics.Discussion: Therefore, the nuclear accident simulation cloud platform built in this study can provide solutions for the work and training of nuclear reactor safety analysis, and provide reference for other engineering design and simulation software cloud to computing transformation

Clinical Applications of Mesenchymal Stromal Cells (MSCs) in Orthopedic Diseases

Mesenchymal stromal cells (MSCs) have the capacity for self-renewal and multi-lineage differentiation, have many advantages over other cells, and are thought to be one of the most promising cell sources for cell-based treatments. In fact, MSCs have already been widely applied in clinics as a treatment for numerous disorders, including orthopedic diseases, such as bone fracture, articular cartilage injury, osteoarthritis (OA), femoral head necrosis, degenerative disc, meniscus injury, osteogenesis imperfecta (OI), and other systemic bone diseases. With the progressions in R&D, the safety and efficacy of MSC-based treatments in orthopedic diseases have been largely recognized, but many challenges still exist. In this chapter, we intend to briefly update the recent progressions and discuss the potential issues in the target areas. Hopefully, our discussion would be helpful not only for the clinicians and the researchers in the specific disciplines but also for the general audiences

Probing Meiotic Recombination and Aneuploidy of Single Sperm Cells by Whole-Genome Sequencing

Meiotic recombination creates genetic diversity and ensures segregation of homologous chromosomes. Previous population analyses yielded results averaged among individuals and affected by evolutionary pressures. We sequenced 99 sperm from an Asian male by using the newly developed amplification method—multiple annealing and looping-based amplification cycles—to phase the personal genome and map recombination events at high resolution, which are nonuniformly distributed across the genome in the absence of selection pressure. The paucity of recombination near transcription start sites observed in individual sperm indicates that such a phenomenon is intrinsic to the molecular mechanism of meiosis. Interestingly, a decreased crossover frequency combined with an increase of autosomal aneuploidy is observable on a global per-sperm basis.Chemistry and Chemical Biolog

Development and Validation of a Nuclear Power Plant Fault Diagnosis System Based on Deep Learning

As artificial intelligence technology has progressed, numerous businesses have used intelligent diagnostic technology. This study developed a deep LSTM neural network for a nuclear power plant to defect diagnostics. PCTRAN is used to accomplish data extraction for distinct faults and varied fault degrees of the PCTRAN code, and some essential nuclear parameters are chosen as feature quantities. The training, validation, and test sets are collected using random sampling at a ratio of 7:1:2, and the proper hyperparameters are selected to construct the deep LSTM neural network. The test findings indicate that the fault identification rate of the nuclear power plant fault diagnostic model based on a deep LSTM neural network is more than 99 percent, first validating the applicability of a deep LSTM neural network for a nuclear power plant fault-diagnosis model

Direct Numerical Simulation and Visualization of Biswirling Jets

Two parallel swirling/rotating jets with a distance between them are termed biswirling jets here, which have important and complicated vortex structures different from the single swirling jet due to the negligible vortex-vortex interactions. The visualization of vortex-vortex interaction between the biswirling jets is accomplished by using direct numerical simulation. The evolution of vortex structures of the biswirling jets is found rather complicated. The turbulent kinetic energy and turbulence dissipation in the central convergence region are augmented locally and rather strongly. The modulation of turbulent kinetic energy by jet-jet interaction upon different scales of vortices is dominated by the swirling levels and the distance between the jets. The turbulent kinetic energy upon intermediate and small scale vortices in bijets with not very high swirling level and at a very close distance is smaller than that in single swirling jets, whereas the opposite is true under a far distance, and so forth

Development and Validation of a Nuclear Power Plant Fault Diagnosis System Based on Deep Learning

As artificial intelligence technology has progressed, numerous businesses have used intelligent diagnostic technology. This study developed a deep LSTM neural network for a nuclear power plant to defect diagnostics. PCTRAN is used to accomplish data extraction for distinct faults and varied fault degrees of the PCTRAN code, and some essential nuclear parameters are chosen as feature quantities. The training, validation, and test sets are collected using random sampling at a ratio of 7:1:2, and the proper hyperparameters are selected to construct the deep LSTM neural network. The test findings indicate that the fault identification rate of the nuclear power plant fault diagnostic model based on a deep LSTM neural network is more than 99 percent, first validating the applicability of a deep LSTM neural network for a nuclear power plant fault-diagnosis model

The Influence Mechanism of Neutron Kinetics of the Accelerator-Driven Subcritical Reactor Based on the Fast/Thermal Neutron Spectra by Monte Carlo Homogenization Method

For the sake of understanding the mechanism of deep subcriticality and high heterogeneity of neutron fluence rate in time–space on the neutron kinetics of the Accelerator-driven Subcritical Reactor Subcritical Reactor (ADSR) under varied beam transients and neutron spectra. A Monte Carlo homogenization approach for the neutron time–space kinetics of the ADSR is proposed in this study, and the influence mechanism on the kinetic parameters of the ADSR under varied neutron spectra, subcriticality, and beam transients is examined. The results show that the Monte Carlo homogenization for the α eigenvalue mode is more adaptable to the subcriticality characteristics under varied subcriticality; under beam transients, the relative differences in the kinetic parameters of the different modes of the ADSR with fast/thermal spectra increase with the depth of subcriticality, and the differences in neutron generation time for varied modes are larger than those of effective fraction of delayed neutron. Thus, it is recommended to use a more adaptable Monte Carlo homogenization method for the time–space kinetics of ADSR, and the effects of the high heterogeneity of neutron fluence rate and deep subcriticality in time–space on the neutron generation time should be considered

Direct Numerical Simulation of Particle-Laden Swirling Flows on Turbulence Modulation

The modulation of turbulence by the laden particles in swirling flows is studied via direct numerical simulation. The statistical characteristics of turbulence modulation are investigated in detail under the effects of different mass loadings as well as Stokes numbers. It is found that the characteristics of turbulence modulation for different Stokes numbers are very similar to each other when the mass loading is light. As the mass loading increases, small particles seem to modulate turbulence more rapidly than large particles. The number concentration or the number flow rate of particles plays an important role in modulation of turbulence. It induces the preferential attenuation of turbulence for small particles in the near field region. Moreover, the trends of modulation of the axial/azimuthal fluctuations, the turbulent kinetic energy, and the Reynolds stress tenor as well as its invariants are similar in the near field region. However, when the turbulence is decayed sufficiently in the downstream region, the inverse turbulence modulation may occur especially for the regions with local intensive accumulation of small particles