RCSB PDB Mobile: iOS and Android mobile apps to provide data access and visualization to the RCSB Protein Data Bank.

SummaryThe Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) resource provides tools for query, analysis and visualization of the 3D structures in the PDB archive. As the mobile Web is starting to surpass desktop and laptop usage, scientists and educators are beginning to integrate mobile devices into their research and teaching. In response, we have developed the RCSB PDB Mobile app for the iOS and Android mobile platforms to enable fast and convenient access to RCSB PDB data and services. Using the app, users from the general public to expert researchers can quickly search and visualize biomolecules, and add personal annotations via the RCSB PDB's integrated MyPDB service.Availability and implementationRCSB PDB Mobile is freely available from the Apple App Store and Google Play (http://www.rcsb.org)

The RCSB Protein Data Bank: views of structural biology for basic and applied research and education.

The RCSB Protein Data Bank (RCSB PDB, http://www.rcsb.org) provides access to 3D structures of biological macromolecules and is one of the leading resources in biology and biomedicine worldwide. Our efforts over the past 2 years focused on enabling a deeper understanding of structural biology and providing new structural views of biology that support both basic and applied research and education. Herein, we describe recently introduced data annotations including integration with external biological resources, such as gene and drug databases, new visualization tools and improved support for the mobile web. We also describe access to data files, web services and open access software components to enable software developers to more effectively mine the PDB archive and related annotations. Our efforts are aimed at expanding the role of 3D structure in understanding biology and medicine

RCSB Protein Data Bank: visualizing groups of experimentally determined PDB structures alongside computed structure models of proteins

Recent advances in Artificial Intelligence and Machine Learning (e.g., AlphaFold, RosettaFold, and ESMFold) enable prediction of three-dimensional (3D) protein structures from amino acid sequences alone at accuracies comparable to lower-resolution experimental methods. These tools have been employed to predict structures across entire proteomes and the results of large-scale metagenomic sequence studies, yielding an exponential increase in available biomolecular 3D structural information. Given the enormous volume of this newly computed biostructure data, there is an urgent need for robust tools to manage, search, cluster, and visualize large collections of structures. Equally important is the capability to efficiently summarize and visualize metadata, biological/biochemical annotations, and structural features, particularly when working with vast numbers of protein structures of both experimental origin from the Protein Data Bank (PDB) and computationally-predicted models. Moreover, researchers require advanced visualization techniques that support interactive exploration of multiple sequences and structural alignments. This paper introduces a suite of tools provided on the RCSB PDB research-focused web portal RCSB. org, tailor-made for efficient management, search, organization, and visualization of this burgeoning corpus of 3D macromolecular structure data

Homoharringtonine exhibits potent anti-tumor effect and modulates DNA epigenome in acute myeloid leukemia by targeting SP1/TET1/5hmC

Homoharringtonine, a plant alkaloid, has been reported to suppress protein synthesis and has been approved by the US Food and Drug Administration for the treatment of chronic myeloid leukemia. Here we show that in acute myeloid leukemia (AML), homoharringtonine potently inhibits cell growth/viability and induces cell cycle arrest and apoptosis, significantly inhibits disease progression in vivo, and substantially prolongs survival of mice bearing murine or human AML. Strikingly, homoharringtonine treatment dramatically decreases global DNA 5-hydroxymethylcytosine abundance through targeting the SP1/TET1 axis, and TET1 depletion mimics homoharringtonine’s therapeutic effects in AML. Our further 5hmC-seq and RNA-seq analyses, followed by a series of validation and functional studies, suggest that FLT3 is a critical down-stream target of homoharringtonine/SP1/TET1/5hmC signaling, and suppression of FLT3 and its downstream targets (e.g. MYC) contributes to the high sensitivity of FLT3-mutated AML cells to homoharringtonine. Collectively, our studies uncover a previously unappreciated DNA epigenome-related mechanism underlying the potent antileukemic effect of homoharringtonine, which involves suppression of the SP1/TET1/5hmC/FLT3/MYC signaling pathways in AML. Our work also highlights the particular promise of clinical application of homoharringtonine to treat human AML with FLT3 mutations, which accounts for more than 30% of total cases of AML

The Partial Derivative Method for Dynamic Stiffness and Damping Coefficients of Supercritical CO2 Foil Bearings

Supercritical CO2 foil bearings are promising bearing technology for supercritical CO2 high-speed turbomachinery. The partial derivative method including complete variable perturbation of the compressible turbulent lubrication Reynolds equation is effective to predict the frequency dependent dynamic stiffness and damping coefficients of supercritical CO2 bearings. In this research, the structural perturbation of foil dynamic model was introduced into this method and then the dynamic coefficients of supercritical CO2 foil bearings were calculated. The results of parametric analysis show that the structural loss factor has little influence on the trend of dynamic coefficients changing with the dimensionless support stiffness but mainly affects the value of stiffness coefficients as well as damping coefficients. Due to the turbulence effect, the bearing number is not able to directly determine the characteristics of supercritical CO2 foil bearings, which is different from air bearings. Compared to the bearing number, the influence of the average Reynolds number on the change of dynamic coefficients with dimensionless support stiffness is more obvious

The Partial Derivative Method for Dynamic Stiffness and Damping Coefficients of Supercritical CO₂ Foil Bearings

Supercritical CO2 foil bearings are promising bearing technology for supercritical CO2 high-speed turbomachinery. The partial derivative method including complete variable perturbation of the compressible turbulent lubrication Reynolds equation is effective to predict the frequency dependent dynamic stiffness and damping coefficients of supercritical CO2 bearings. In this research, the structural perturbation of foil dynamic model was introduced into this method and then the dynamic coefficients of supercritical CO2 foil bearings were calculated. The results of parametric analysis show that the structural loss factor has little influence on the trend of dynamic coefficients changing with the dimensionless support stiffness but mainly affects the value of stiffness coefficients as well as damping coefficients. Due to the turbulence effect, the bearing number is not able to directly determine the characteristics of supercritical CO2 foil bearings, which is different from air bearings. Compared to the bearing number, the influence of the average Reynolds number on the change of dynamic coefficients with dimensionless support stiffness is more obvious

Dynamic Coefficients of Tilting Pad Bearing by Perturbing the Turbulence Model

Tilting pad bearings are appropriate for the trend of high efficiency and reliability design of rotating machinery due to their high stability. The laminar and turbulent flow states exist in the lubricating oil film of high-speed and heavy-load tilting pad bearings simultaneously. By perturbing the multiple flow state lubrication model with a partial derivative method, together with the pad-pivot structural perturbations, the frequency-dependent stiffness and damping coefficients of tilting pad bearings, embracing the effect of dynamical variations of both turbulence and pressure-viscous, were numerically solved in this research. The importance of each perturbed variable was studied, and the results indicate that the perturbed film thickness included in turbulence coefficients perturbations is significant enough to be taken into account otherwise the equivalent stiffness coefficients will be obviously overestimated. Unlike the perturbed film thickness, the consideration of the perturbed viscosity is optional, because it makes the stiffness and damping coefficients larger at both laminar and turbulent flow states. For a simplified simulation and conservative prediction results, the perturbed viscosity can be neglected

Dynamic Coefficients of Tilting Pad Bearing by Perturbing the Turbulence Model

Tilting pad bearings are appropriate for the trend of high efficiency and reliability design of rotating machinery due to their high stability. The laminar and turbulent flow states exist in the lubricating oil film of high-speed and heavy-load tilting pad bearings simultaneously. By perturbing the multiple flow state lubrication model with a partial derivative method, together with the pad-pivot structural perturbations, the frequency-dependent stiffness and damping coefficients of tilting pad bearings, embracing the effect of dynamical variations of both turbulence and pressure-viscous, were numerically solved in this research. The importance of each perturbed variable was studied, and the results indicate that the perturbed film thickness included in turbulence coefficients perturbations is significant enough to be taken into account otherwise the equivalent stiffness coefficients will be obviously overestimated. Unlike the perturbed film thickness, the consideration of the perturbed viscosity is optional, because it makes the stiffness and damping coefficients larger at both laminar and turbulent flow states. For a simplified simulation and conservative prediction results, the perturbed viscosity can be neglected

Fantasy curiosity:a new theoretical perspective to understand anime pilgrimage

Curiosity stands as a significant driving force in comprehending tourist behaviour. Nonetheless, within the realm of anime pilgrims, the objects of interest, the underlying mechanisms and the resulting behaviours stemming from their curiosity deviate notably from those exhibited by typical tourists. Through the utilization of in-depth case studies of anime pilgrims, this research unveils an innovative impetus for tourism known as ‘fantasy curiosity’ with four distinct attributes, differentiating it from prevailing conceptualizations of general curiosity. Moreover, by utilizing a Latent Dirichlet Allocation model, we pinpoint distinct characteristics of anime-related behaviours across different phases of anime tours. These findings serve to propel the progression of research within the realms of tourism motivations, while concurrently broadening the horizons of curiosity theory.</p