153 research outputs found
Applicatioin of Nuclear Magnetic Resonance to Protein Structure and Protein-ligand Interation Studies
NMR (Nuclear Magnetic Resonance) has been expanding its application since it was first discovered in the early 50s. In biophysics, it is a very powerful tool complement to X-ray crystallography for protein structure studies. In this dissertation, two different projects studied by two different NMR methods will be presented. In the first part, a membrane protein PLIN1 which resides on the surface of the cellular organelle lipid droplet is investigated by solid-state NMR (ssNMR). It has been shown that PLIN 1 exclusively locates on the surface of lipid droplet and upon phosphorylation, recruits lipase to digest the triglycerides stored in the lipid droplet. However, due to its membrane protein nature, its insolubility resists to crystallization. ssNMR is a perfect tool to study this membrane protein. PLIN1 was reconstituted into DMPG liposomes and multi-dimensional ssNMR spectra were acquired. According to proton spin diffusion data, a membrane interaction model was proposed and later verified by both molecular dynamics (MD) simulation and experimental reconstitution data. In the second part, a soluble protein Mortalin was studied by solution NMR. Mortalin is a heat shock protein 70 (HSP70) family membrane primarily located in the mitochondria. In cancer cells, Mortalin is released to the cytoplasm and forms a complex with p53, sequestering it in the cytoplasm thus inhibiting its translocation to nucleus to induce cell apoptosis. The flexible heteroarotinoid (Flex-Het) SHetA2 with promising anti-cancer activity can bind to Mortalin and release p53 from the complex to induce cell apoptosis. We successfully determined the substrate binding pocket of Mortalin to be the interacting sites with SHetA2 by chemical shift perturbation (CSP). Using AutoDock as the prediction tool, at least two binding configurations of SHetA2 are generated with high binding affinity. According to these results, more SHetA2 analogs were designed and tested in AutoDock. We find that the analogs with longer linkers that can occupy both configurations of SHetA2 yield the highest binding affinity (lowest binding energy). These results will guide future drug designs to increase the efficiency of Flex-Het anti-cancer activity.Physic
Global attractor for a class of nonlinear generalized Kirchhoff models
The paper studies the long time behavior of solutions to the initial boundary value problem(IBVP) for a class of Kirchhoff models flow .We establish the well-posedness, theexistence of the global attractor in natural energy spac
Producing a Standard Dataset of Speed Climbing Training Videos Using Deep Learning Techniques
This dissertation presents a methodology for recording speed climbing
training sessions with multiple cameras and annotating the videos with relevant
data, including body position, hand and foot placement, and timing. The
annotated data is then analyzed using deep learning techniques to create a
standard dataset of speed climbing training videos. The results demonstrate the
potential of the new dataset for improving speed climbing training and
research, including identifying areas for improvement, creating personalized
training plans, and analyzing the effects of different training methods.The
findings will also be applied to the training process of the Jiangxi climbing
team through further empirical research to test the findings and further
explore the feasibility of this study.Comment: 2023 3rd International Conference on Innovative Talents Training and
Sustainable Developmen
Zero Bubble Pipeline Parallelism
Pipeline parallelism is one of the key components for large-scale distributed
training, yet its efficiency suffers from pipeline bubbles which were deemed
inevitable. In this work, we introduce a scheduling strategy that, to our
knowledge, is the first to successfully achieve zero pipeline bubbles under
synchronous training semantics. The key idea behind this improvement is to
split the backward computation into two parts, one that computes gradient for
the input and another that computes for the parameters. Based on this idea, we
handcraft novel pipeline schedules that significantly outperform the baseline
methods. We further develop an algorithm that automatically finds an optimal
schedule based on specific model configuration and memory limit. Additionally,
to truly achieve zero bubble, we introduce a novel technique to bypass
synchronizations during the optimizer step. Experimental evaluations show that
our method outperforms the 1F1B schedule up to 23% in throughput under a
similar memory limit. This number can be further pushed to 31% when the memory
constraint is relaxed. We believe our results mark a major step forward in
harnessing the true potential of pipeline parallelism. We open sourced our
implementation based on the popular Megatron-LM repository on
https://github.com/sail-sg/zero-bubble-pipeline-parallelism
Complex unit lattice cell for low-emittance storage ring light source
To achieve the true diffraction-limited emittance of a storage ring light
source, such as ~10 pm.rad for medium-energy electron beams, within a limited
circumference, it is generally necessary to increase the number of bending
magnets in a multi-bend achromat (MBA) lattice, as in the future upgrade plan
of MAX IV with a 19BA replacing the current 7BA. However, this comes with
extremely strong quadrupole and sextupole magnets and very limited space. The
former can result in very small vacuum chambers, increasing the coupling
impedance and thus enhancing the beam instabilities, and the latter can pose
significant challenges in accommodating the necessary diagnostics and vacuum
components. Inspired by the hybrid MBA lattice concept, in this paper we
propose a new unit lattice concept called the complex unit lattice cell, which
can reduce the magnet strengths and also save space. The complex unit cell is
numerically studied using a simplified model. Then as an example, a 17BA
lattice based on the complex unit cell concept is designed for a 3 GeV storage
ring light source with a circumference of 537.6 m, which has a natural
emittance of 19.3 pm.rad. This 17BA lattice is also compared with the 17BA
lattice designed with conventional unit cells to showcase the benefits of the
complex unit cell concept. This 17BA lattice also suggests a new type of MBA
lattice, which we call the MBA lattice with semi-distributed chromatic
correction
A Comprehensive Analysis of the Downregulation of miRNA-1827 and Its Prognostic Significance by Targeting SPTBN2 and BCL2L1 in Ovarian Cancer
Background: Previous studies demonstrated that miRNA-1827 could repress various cancers on proliferation, angiogenesis, and metastasis. However, little attention has been paid to its role in ovarian cancer as a novel biomarker or intervention target, especially its clinical significance and underlying regulatory network.Methods: A meta-analysis of six microarrays was adopted here to determine the expression trend of miRNA-1827, and was further validated by gene expression profile data and cellular experiments. We explored the functional annotations through enrichment analysis for the differentially expressed genes targeted by miRNA-1827. Subsequently, we identified two hub genes, SPTBN2 and BCL2L1, based on interaction analysis using two online archive tools, miRWALK (it consolidates the resources of 12 miRNA-focused servers) and Gene Expression Profiling Interactive Analysis (GEPIA). Finally, we validated their characteristics and clinical significance in ovarian cancer.Results: The comprehensive meta-analysis revealed that miRNA-1827 was markedly downregulated in clinical and cellular specimens. Transfection of the miRNA-1827 mimic could significantly inhibit cellular proliferation. Concerning its target genes, they were involved in diverse biological processes related to tumorigenesis, such as cell proliferation, migration, and the apoptosis signaling pathway. Moreover, interaction analysis proved that two hub genes, SPTBN2 and BCL2L1, were highly associated with poor prognosis in ovarian cancer.Conclusion: These integrated bioinformatic analyses indicated that miRNA-1827 was dramatically downregulated in ovarian cancer as a tumor suppressor. The upregulation of its downstream modulators, SPTBN2 and BCL2L1, was associated with an unfavorable prognosis. Thus, the present study has identified miRNA-1827 as a potential intervention target for ovarian cancer based on our bioinformatic analysis processes
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