Biomedical subjects

Weichuan Yu

Publications and source records attributed to Weichuan Yu.

6 recordsLinked to original sources

PubMed2026

Deciphering the Protein Phosphorylation Dynamics Triggered by Seconds of Force Stimulation.

Plants perceive mechanical forces through phosphosignaling networks, but their relationship with gravity signaling remains elusive. To dissect gravity force signaling components, we performed SILIA-based phosphoproteomics on Arabidopsis aerial organs subjected to 20-s inversion or 30-s gravistimulation, identifying 2,733 and 2,878 phosphoproteins, respectively. Quantitative analysis revealed 34 significantly regulated phosphoproteins specific to inversion and 52 specific to gravistimulation. Inversion-specific phosphoproteins, associated with the initial calcium code, likely mediate calcium signals through EF-hand proteins, CPK1, and calmodulin-interacting proteins, potentially intersecting with receptor-like kinase-initiated MAPK cascades via RAF15 and MKK1/2 to induce gravitropic responses. Gravistimulation-specific phosphoproteins, linked to the secondary calcium code, function in calcium signaling/homeostasis (ACA8, ZAC, IQD2, ANNAT1), membrane vesicle trafficking (ABCG36, ARF-GAP8), and lipid signaling (PIP5K8/9), supporting auxin transport and stress signal transduction. Immunoblot validation confirmed treatment-associated phosphosites pS108-PATL3 and pS107-TREPH2, along with inversion-specific pS1145-ATEH2, exhibiting stem-specific phosphorylation enhancement and force-discriminatory responses. Functional analysis identified the integrin-like protein GREPH1 as a key gravitropism regulator, with greph1 mutants displaying reduced inflorescence stem gravicurvature. Notably, hyperphosphorylation of pS107-TREPH2 and pS1145-ATEH2 peaked at 20 to 50 s in greph1 mutants but persisted from 20 s to 2 h in WT plants. These findings establish a stem-enriched phosphorylation code for gravity force discrimination, with GREPH1 modulating spatiotemporal phosphoprotein dynamics and shoot gravicurvature, potentially functioning as a receptor reminiscent of sedimenting plastids.

Arabidopsis↗

PubMed2006

Towards pointwise motion tracking in echocardiographic image sequences--comparing the reliability of different features for speckle tracking.

In this paper, we studied the problem of feature-based motion tracking in echocardiographic image sequences. We described the relation between possible feature variations and different kinds of tissue motion using a linear convolution model. We also showed that motion-feature decorrelation (which means that the motion parameters estimated using feature tracking fail to represent the underlying tissue motion) compensation is an ill-posed inverse problem. Instead of finding a method that may provide better compensation results than previous approaches, we used an quantitative measure to compare the reliability of tracking features. Experiment results showed that the use of the reliability measure improved the robustness of displacement estimation. With the help of the reliability measure, we compared the performance of different features using simulations and phantom examples. While we noticed that the radio frequency (RF) signal outperforms the B-mode (BM) signal in the analysis of small deformation (e.g., less than 0.1% compression), we also found out that the BM signal works better than the RF signal in the analysis of large deformation (e.g., larger than 2% compression). The use of a band-passed filtered feature does not result in significant improvement in tracking.

Algorithms↗

PubMed2006

MALDI-MS data analysis for disease biomarker discovery.

In this chapter, we address the issue of matrix-assisted laser desorption/ionization mass spectrometry (MS) data analysis for disease biomarker discovery. We first give a general framework of MS data analysis, then focus on several key steps. After that, we show some application examples using an ovarian sera cancer dataset. Finally, we discuss the limitations of current approaches and possible future research directions.

Animals↗

PubMed2005

Detecting and aligning peaks in mass spectrometry data with applications to MALDI.

In this paper, we address the peak detection and alignment problem in the analysis of mass spectrometry data. To deal with the peak redundancy problem existing in the MALDI data acquired in the reflectron mode, we propose to use the amplitude modulation technique in peak detection. The alignment of two peak sets is formulated as a non-rigid registration problem and is solved using a robust point matching (RPM) approach. To align multiple peak sets, we first use a super set method to find a common peak set among all peak sets as a standard and then align all peak sets to the standard using the robust point matching approach in a sequential manner (i.e. We align only one peak set to the standard each time, thus reducing the multiple peak set alignment problem to a simpler two peak set alignment problem). Experimental results from a study of ovarian cancer data set show that the quantitative cross-correlation coefficients among technical replicates are increased after peak alignment. Additional comparisons also demonstrate that our method has a similar performance as the hierarchical clustering method, although the implementations of these methods are different.

Female↗

PubMed2003

Combinative multi-scale level set framework for echocardiographic image segmentation.

In the automatic segmentation of echocardiographic images, a priori shape knowledge has been used to compensate for poor features in ultrasound images. This shape knowledge is often learned via an off-line training process, which requires tedious human effort and is highly expertise-dependent. More importantly, a learned shape template can only be used to segment a specific class of images with similar boundary shape. In this paper, we present a multi-scale level set framework for segmentation of endocardial boundaries at each frame in a multiframe echocardiographic image sequence. We point out that the intensity distribution of an ultrasound image at a very coarse scale can be approximately modeled by Gaussian. Then we combine region homogeneity and edge features in a level set approach to extract boundaries automatically at this coarse scale. At finer scale levels, these coarse boundaries are used to both initialize boundary detection and serve as an external constraint to guide contour evolution. This constraint functions similar to a traditional shape prior. Experimental results validate this combinative framework.

Algorithms↗

PubMedDate not supplied

Multiple peak alignment in sequential data analysis: a scale-space-based approach.

In this paper, we address the multiple peak alignment problem in sequential data analysis with an approach based on the Gaussian scale-space theory. We assume that multiple sets of detected peaks are the observed samples of a set of common peaks. We also assume that the locations of the observed peaks follow unimodal distributions (e.g., normal distribution) with their means equal to the corresponding locations of the common peaks and variances reflecting the extension of their variations. Under these assumptions, we convert the problem of estimating locations of the unknown number of common peaks from multiple sets of detected peaks into a much simpler problem of searching for local maxima in the scale-space representation. The optimization of the scale parameter is achieved using an energy minimization approach. We compare our approach with a hierarchical clustering method using both simulated data and real mass spectrometry data. We also demonstrate the merit of extending the binary peak detection method (i.e., a candidate is considered either as a peak or as a nonpeak) with a quantitative scoring measure-based approach (i.e., we assign to each candidate a possibility of being a peak).

Algorithms↗