Search PubMed⌕ Search

Biomedical subjects

Xuan Xiao

Publications and source records attributed to Xuan Xiao.

4 recordsLinked to original sources
PubMed2026

Cystathionine γ-Lyase-Dependent S-Sulfhydration of Smad3: A Novel Target to Alleviate Fibrosis in Systemic Sclerosis.

OBJECTIVE: The cystathionine γ-lyase (CSE)/hydrogen sulfide (H2S) axis has emerged as a key regulator in tissue fibrogenesis. This study aimed to explore the role of the CSE/H2S axis in systemic sclerosis (SSc) and to investigate its underlying mechanisms to identify promising therapeutic targets. METHODS: CSE/H2S levels were assessed in serum samples from 25 patients with SSc and 28 healthy controls. Human dermal fibroblasts from patients with SSc and healthy controls were used for functional studies, including propargylglycine (CSE inhibitor) treatment, Gyy4137, a slow-releasing hydrogen sulfide donor, CSE silencing, and CSE overexpression, combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based S-sulfhydration proteomics. Molecular dynamics simulations were performed to study the effects of S-sulfhydration on protein structure, and an Smad3 C121S (cysteine [Cys] 121 mutated to Ser) mutant was generated to verify the function targets of S-sulfhydration. In vivo, bleomycin-induced mouse models of skin and lung fibrosis were constructed to evaluate the effects of CSE overexpression. RESULTS: In human samples, CSE/H2S levels were reduced in SSc. CSE inhibition promoted extracellular matrix deposition. S-sulfhydration proteomics showed that S-sulfhydration levels were globally reduced in SSc compared to controls. CSE overexpression increased S-sulfhydration on Smad3, suppressed transforming growth factor β 1 (TGFβ1)/Smad3 signaling, mitigating skin fibrosis. Notably, Cys121 on Smad3, identified as a pivotal target for S-sulfhydration by proteomics, was shown to fine-tune its MH1 domain, with its mutation impairing the antifibrotic effects. In mice, CSE overexpression attenuated bleomycin-induced skin and lung fibrosis. CONCLUSION: Smad3 S-sulfhydration mediates the antifibrotic effect of CSE in SSc, highlighting it as a critical mechanism and promising therapeutic target.

Humans↗
PubMed2006

A probability cellular automaton model for hepatitis B viral infections.

The existing models of hepatitis B virus (HBV) infection dynamics are based on the assumption that the populations of viruses and cells are uniformly mixed. However, the real virus infection system is actually not homogeneous and some spatial factors might play a nontrivial role in governing the development of HBV infection and its outcome. For instance, the localized populations of dead cells might adversely affect the spread of infection. To consider this kind of inhomogeneous feature, a simple 2D (dimensional) probability Cellular Automaton model was introduced to study the dynamic process of HBV infection. The model took into account the existence of different types of HBV infectious and non-infectious particles. The simulation results thus obtained showed that the Cellular Automaton model could successfully account for some important features of the disease, such as its wide variety in manifestation and its age dependency. Meanwhile, the effects of the model's parameters on the dynamical process of the infection were also investigated. It is anticipated that the Cellular Automaton model may be extended to serve as a useful vehicle for studying, among many other complicated dynamic biological systems, various persistent infections with replicating parasites.

Animals↗
PubMed2006

Using pseudo amino acid composition to predict protein structural classes: approached with complexity measure factor.

The structural class is an important feature widely used to characterize the overall folding type of a protein. How to improve the prediction quality for protein structural classification by effectively incorporating the sequence-order effects is an important and challenging problem. Based on the concept of the pseudo amino acid composition [Chou, K. C. Proteins Struct Funct Genet 2001, 43, 246; Erratum: Proteins Struct Funct Genet 2001, 44, 60], a novel approach for measuring the complexity of a protein sequence was introduced. The advantage by incorporating the complexity measure factor into the pseudo amino acid composition as one of its components is that it can catch the essence of the overall sequence pattern of a protein and hence more effectively reflect its sequence-order effects. It was demonstrated thru the jackknife crossvalidation test that the overall success rate by the new approach was significantly higher than those by the others. It has not escaped our notice that the introduction of the complexity measure factor can also be used to improve the prediction quality for, among many other protein attributes, subcellular localization, enzyme family class, membrane protein type, and G-protein couple receptor type.

Algorithms↗
PubMed2005

An application of gene comparative image for predicting the effect on replication ratio by HBV virus gene missense mutation.

Hepatitis B viruses (HBVs) show instantaneous and high-ratio mutations when they are replicated, some sorts of which significantly affect the efficiency of virus replication through enhancing or depressing the viral replication, while others have no influence at all. The mechanism of gene expression is closely correlated with its gene sequence. With the rapid increase in the number of newly found sequences entering into data banks, it is highly desirable to develop an automated method for simulating the gene regulating function. The establishment of such a predictor will no doubt expedite the process of prioritizing genes and proteins identified by genomics efforts as potential molecular targets for drug design. Based on the power of cellular automata (CA) in treating complex systems with simple rules, a novel method to present HBV gene image has been introduced. The results show that the images thus obtained can very efficiently simulate the effects of the gene missense mutation on the virus replication. It is anticipated that CA may also serve as a useful vehicle for many other studies on complicated biological systems.

Computational Biology↗