Biomedical subjects

Wei Chu

Publications and source records attributed to Wei Chu.

6 recordsLinked to original sources

PubMed2026

Epigenetic-epitranscriptomic crosstalk through TaHAG1-TaNSUN2 coordinates thermotolerance in wheat.

High temperature is a primary abiotic stress that severely constrains crop productivity. Deciphering the regulatory pathways underlying heat responses is essential for breeding heat-tolerant crops with stable yields. Although both epigenetic and epitranscriptomic regulations are involved in plant heat adaptation, their mechanistic interplay remains unclear. Here, integrated epigenomic (H3K9Ac/H3K14Ac) and transcriptomic profiling under heat stress identifies the mRNA m⁵C methyltransferase TaNSUN2 as a key regulator of thermotolerance in wheat. We demonstrate that TaNSUN2 is transcriptionally activated by the histone acetyltransferase TaHAG1, which deposits H3K9Ac at the TaNSUN2 promoter and transcription start site. This recruitment is facilitated by the transcription factors TaE2F1 and TaDP1, which interact with TaHAG1 to form a functional complex. Functional assays revealthat TaNSUN2 operates downstream of TaHAG1 and enhances thermotolerance through m⁵C‑dependent mRNA methylation and stabilization of transcripts involved in chloroplast organization. Furthermore, field trials show that TaNSUN2-overexpressing lines exhibit higher grain yield under normal conditions and reduced yield loss under heat stress. Our findings elucidate an integrated regulatory network linking histone acetylation to RNA m⁵C methylation in heat stress adaptation, providing promising targets for molecular breeding of heat‑resilient wheat.

Triticum↗

PubMed2005

Biomarker discovery in microarray gene expression data with Gaussian processes.

MOTIVATION: In clinical practice, pathological phenotypes are often labelled with ordinal scales rather than binary, e.g. the Gleason grading system for tumour cell differentiation. However, in the literature of microarray analysis, these ordinal labels have been rarely treated in a principled way. This paper describes a gene selection algorithm based on Gaussian processes to discover consistent gene expression patterns associated with ordinal clinical phenotypes. The technique of automatic relevance determination is applied to represent the significance level of the genes in a Bayesian inference framework. RESULTS: The usefulness of the proposed algorithm for ordinal labels is demonstrated by the gene expression signature associated with the Gleason score for prostate cancer data. Our results demonstrate how multi-gene markers that may be initially developed with a diagnostic or prognostic application in mind are also useful as an investigative tool to reveal associations between specific molecular and cellular events and features of tumour physiology. Our algorithm can also be applied to microarray data with binary labels with results comparable to other methods in the literature.

Algorithms↗

PubMed2005

An improved conjugate gradient scheme to the solution of least squares SVM.

The least square support vector machines (LS-SVM) formulation corresponds to the solution of a linear system of equations. Several approaches to its numerical solutions have been proposed in the literature. In this letter, we propose an improved method to the numerical solution of LS-SVM and show that the problem can be solved using one reduced system of linear equations. Compared with the existing algorithm for LS-SVM, the approach used in this letter is about twice as efficient. Numerical results using the proposed method are provided for comparisons with other existing algorithms.

Least-Squares Analysis↗

PubMed2004

Bayesian support vector regression using a unified loss function.

In this paper, we use a unified loss function, called the soft insensitive loss function, for Bayesian support vector regression. We follow standard Gaussian processes for regression to set up the Bayesian framework, in which the unified loss function is used in the likelihood evaluation. Under this framework, the maximum a posteriori estimate of the function values corresponds to the solution of an extended support vector regression problem. The overall approach has the merits of support vector regression such as convex quadratic programming and sparsity in solution representation. It also has the advantages of Bayesian methods for model adaptation and error bars of its predictions. Experimental results on simulated and real-world data sets indicate that the approach works well even on large data sets.

Bayes Theorem↗

PubMed2003

Protein-protein interactions involved in the recognition of p27 by E3 ubiquitin ligase.

The p27(Kip1) protein is a potent cyclin-dependent kinase inhibitor, the level of which is decreased in many common human cancers as a result of enhanced ubiquitin-dependent degradation. The multiprotein complex SCF(Skp2) has been identified as the ubiquitin ligase that targets p27, but the functional interactions within this complex are not well understood. One component, the F-box protein Skp2, binds p27 when the latter is phosphorylated on Thr(187), thus providing substrate specificity for the ligase. Recently, we and others have shown that the small cell cycle regulatory protein Cks1 plays a critical role in p27 ubiquitination by increasing the binding affinity of Skp2 for p27. Here we report the development of a homogeneous time-resolved fluorescence assay that allows the quantification of the molecular interactions between human recombinant Skp2, Cks1 and a p27-derived peptide phosphorylated on Thr(187). Using this assay, we have determined the dissociation constant of the Skp2-Cks1 complex (K(d) 140 +/- 14 nM) and have shown that Skp2 binds phosphorylated p27 peptide with high affinity only in the presence of Cks1 (K(d) 37 +/- 2 nM). Cks1 does not bind directly to the p27 phosphopeptide or to Skp1, which confirms its suggested role as an allosteric effector of Skp2.

Allosteric Regulation↗

PubMed2003

Observations of 2,4,6-trichlorophenol degradation by ozone.

The aqueous reactivity of 2,4,6-trichlorophenol (TCP) with ozone has been studied at laboratory-scale using a simple gas bubble/liquid contacting system. Degradation rate constants were measured directly and found to be 7.6 and 77.2 M(-1)s(-1) at pH 2 and 7.5, respectively. At pH 7.5, 10 min of ozonation ( identical with 15 mM ozone consumption) achieved a 90% degradation of TCP, which corresponded to the release of approximately 2 mol Cl(-) per mol TCP. The presence of hydrogen peroxide in solution did not significantly increase the TCP degradation but increased the overall dechlorination to 2.7 mol Cl(-) per mol TCP. The presence of humic acid (HA) in solution was found to enhance the degradation rate of TCP at low relative HA concentrations (<0.6 g/g HA:TCP), but to reduce the rate at higher HA concentrations.

Chlorophenols↗