Approaches for studying RNA aptamers with molecular dynamics simulation

The objective of this dissertation is to study RNA aptamers with molecular dynamics simulation. It addresses fundamental challenges associated with RNA aptamers that can be investigated via molecular dynamics simulation, including the unavailability of 3D structures for the apo state, the challenge of ensuring good sampling for a flexible molecule, and the uncertainties that accompany molecular properties. The results presented in this dissertation focus on the application of multiple independent simulations to address these issues. I present results from multiple independent molecular dynamics simulations that are started from selected de novo predicted structures, according to experimentally determined base stacking, as a workflow to characterize the flexible apo state of an aptamer. I systematically investigate the sampling of multiple independent simulations by studying the nonlinear dynamic behavior, including principal component analysis and multivariate recurrent quantification analysis. I further propose a simulation assessment approach based on the root mean square deviation (RMSD) matrix eigenvalue and estimate molecular properties of interest with rigorous statistical analysis. I first develop a workflow that combines computational modeling and fluorescence experiments to study the structure and dynamics of the aptamer apo state. The selected predicted structures pass rounds of clustering and satisfy the stacking condition of critical bases in apo state determined from experiments. Multiple independent simulations from these selected structures effectively achieve better sampling than using the available NMR complex structure with ligand removed. It is also noticed that when the backbone is well aligned, a different base at the same position might also be potential binding site. This provides insight to the ligand binding mechanism, specifically, whether the flexible terminal loop adjust its whole structure or a critical base flips to fit the ligand. With the evidence that multiple molecular dynamics simulations can be used to investigate the conformation of aptamer for situations where a 3D structure is not available, I next investigate how well multiple independent simulations from different initial conformations sample the conformational space. The sampling of simulations started from different predicted structures is compared both qualitatively and quantitatively. The projection of sampled structures on selected principal components axes shows overlap among different groups of simulations as well as regions visited only by a specific group. The sampling of different groups of simulations is then further compared via recurrence quantification analysis using the top 10 principal components. The minimum length required for each independent simulation is determined. The number of independent simulations for sufficient sampling of the system is recommended based on the standard error of the mean for the molecular property of interest. Once the number of independent simulations and the minimum length of each simulation are known, it is necessary to systematically perform rigorous statistical analysis on any property of interest. Examination of the simulation quality can be done by looking at the progress of the largest eigenvalue from the RMSD matrix. Simulations or sections of simulations can be grouped as repeated measurements or enrichment, which further determines the uncertainty calculation. I recommend such a procedure because the sampling achieved with molecular dynamics simulations performed with limited timescales might display dependence on the initial conditions. This would lead to an outcome where different simulations could exhibit different error. I urge that care be taken in analyzing simulation outcomes and emphasize that taking the average is not sufficient

Study on Protection and Renewal for Spatial Characteristic of Eaves Gallery Street in Hubei of China under the New Urbanization: Taking Northeast Area of Japan as Comparative Example

要約のみTohoku University石田壽一課

Forecasting the Cross-Correlation of the CSST galaxy survey with the FAST HI Intensity Map

The cross-correlation of optical galaxies with the neutral hydrogen (HI) radiation intensity can enhance the signal-to-noise ratio (SNR) of the HI intensity measurement. In this paper, we investigate the cross-correlation of the galaxy samples obtained by the spectroscopic survey of the China Space Station Telescope (CSST) with the HI Intensity mapping (IM) survey of the Five-hundred-meter Aperture Spherical Telescope (FAST). Using the IllusitrisTNG simulation result at redshift $0.2 \sim 0.3$, we generate mock data of the CSST survey and a FAST L-band drift scan survey. The CSST spectroscopic survey can yield a sample of galaxies with a high comoving number density of 10^{-2} (\unit{Mpc}/h)^{-3} at $z \sim 0.3$. We cross-correlate the foreground-removed radio intensity with the CSST galaxies, including both the whole sample, and red and blue galaxy sub-samples separately. We find that in all cases the HI and optical galaxies are well correlated. The total HI abundance can be measured with a high precision from this correlation. A relative error of $\sim 0.6\%$ for $\Omega_{\rm HI}$ could be achieved at $z\sim 0.3$ for an overlapping survey area of 10000 \unit{deg}^2.Comment: 16 pages, 10 figure

Multiresolution Feature Guidance Based Transformer for Anomaly Detection

Anomaly detection is represented as an unsupervised learning to identify deviated images from normal images. In general, there are two main challenges of anomaly detection tasks, i.e., the class imbalance and the unexpectedness of anomalies. In this paper, we propose a multiresolution feature guidance method based on Transformer named GTrans for unsupervised anomaly detection and localization. In GTrans, an Anomaly Guided Network (AGN) pre-trained on ImageNet is developed to provide surrogate labels for features and tokens. Under the tacit knowledge guidance of the AGN, the anomaly detection network named Trans utilizes Transformer to effectively establish a relationship between features with multiresolution, enhancing the ability of the Trans in fitting the normal data manifold. Due to the strong generalization ability of AGN, GTrans locates anomalies by comparing the differences in spatial distance and direction of multi-scale features extracted from the AGN and the Trans. Our experiments demonstrate that the proposed GTrans achieves state-of-the-art performance in both detection and localization on the MVTec AD dataset. GTrans achieves image-level and pixel-level anomaly detection AUROC scores of 99.0% and 97.9% on the MVTec AD dataset, respectively

A Study of the Testing Effect in an Engineering Classroom

This research paper describes a study that examines a testing effect intervention deployed in an engineering classroom setting. The testing effect is based on the premise that learning is improved when students engage with newly acquired information by challenging themselves to answer questions about the content instead of using other means of interacting with the content, such as rereading a text. The testing effect has been established in laboratory research studies [1]. To translate this finding into educational practice, classroom research studies [2]-[6] aim to define the conditions for which the testing effect remains robust in authentic classroom settings. In the classroom domain, a testing effect intervention often consists of low- or no-stakes quizzing with feedback during the learning period, followed by a summative assessment at the end of the unit. Previous investigations have studied the impact of conditions, such as the question type (identical or related; definitional or application), the quiz participation incentives, and the quiz delivery patterns on the testing effect outcome for all participants in the study. Nguyen & McDaniel [7] review several classroom studies aimed at improving student learning through the use of quizzing

Common Secondary and Tertiary Structural Features of Aptamer–Ligand Interaction Shared by RNA Aptamers with Different Primary Sequences

Aptamer selection can yield many oligonucleotides with different sequences and affinities for the target molecule. Here, we have combined computational and experimental approaches to understand if aptamers with different sequences but the same molecular target share structural and dynamical features. NEO1A, with a known NMR-solved structure, displays a flexible loop that interacts differently with individual aminoglycosides, its ligand affinities and specificities are responsive to ionic strength, and it possesses an adenosine in the loop that is critical for high-affinity ligand binding. NEO2A was obtained from the same selection and, although they are only 43% identical in overall sequence, NEO1A and NEO2A share similar loop sequences. Experimental analysis by 1D NMR and 2-aminopurine reporters combined with molecular dynamics modeling revealed similar structural and dynamical characteristics in both aptamers. These results are consistent with the hypothesis that the target ligand drives aptamer structure and also selects relevant dynamical characteristics for high-affinity aptamer-ligand interaction. Furthermore, they suggest that it might be possible to “migrate” structural and dynamical features between aptamer group members with different primary sequences but with the same target ligand

Dynamic profiling of intact glucosinolates in radish by combining UHPLC-HRMS/MS and UHPLC-QqQ-MS/MS

Glucosinolates (GSLs) and their degradation products in radish confer plant defense, promote human health, and generate pungent flavor. However, the intact GSLs in radish have not been investigated comprehensively yet. Here, an accurate qualitative and quantitative analyses of 15 intact GSLs from radish, including four major GSLs of glucoraphasatin (GRH), glucoerucin (GER), glucoraphenin (GRE), and 4-methoxyglucobrassicin (4MGBS), were conducted using UHPLC-HRMS/MS in combination with UHPLC-QqQ-MS/MS. Simultaneously, three isomers of hexyl GSL, 3-methylpentyl GSL, and 4-methylpentyl GSL were identified in radish. The highest content of GSLs was up to 232.46 μmol/g DW at the 42 DAG stage in the ‘SQY’ taproot, with an approximately 184.49-fold increase compared to the lowest content in another sample. That the GSLs content in the taproots of two radishes fluctuated in a similar pattern throughout the five vegetative growth stages according to the metabolic profiling, whereas the GSLs content in the ‘55’ leaf steadily decreased over the same period. Additionally, the proposed biosynthetic pathways of radish-specific GSLs were elucidated in this study. Our findings will provide an abundance of qualitative and quantitative data on intact GSLs, as well as a method for detecting GSLs, thus providing direction for the scientific progress and practical utilization of GSLs in radish

Anti-inflammatory effect of dental pulp stem cells

Dental pulp stem cells (DPSCs) have received a lot of attention as a regenerative medicine tool with strong immunomodulatory capabilities. The excessive inflammatory response involves a variety of immune cells, cytokines, and has a considerable impact on tissue regeneration. The use of DPSCs for controlling inflammation for the purpose of treating inflammation-related diseases and autoimmune disorders such as supraspinal nerve inflammation, inflammation of the pulmonary airways, systemic lupus erythematosus, and diabetes mellitus is likely to be safer and more regenerative than traditional medicines. The mechanism of the anti-inflammatory and immunomodulatory effects of DPSCs is relatively complex, and it may be that they themselves or some of the substances they secrete regulate a variety of immune cells through inflammatory immune-related signaling pathways. Most of the current studies are still at the laboratory cellular level and animal model level, and it is believed that through the efforts of more researchers, DPSCs/SHED are expected to be transformed into excellent drugs for the clinical treatment of related diseases