Biomedical subjects

Li Liao

Publications and source records attributed to Li Liao.

9 recordsLinked to original sources

PubMed2025

Exploring diagnostic m6A regulators in primary open-angle glaucoma: insight from gene signature and possible mechanisms by which key genes function.

PURPOSE: The purpose of this study was to interrogate the potential role of N6-methyladenosine (m6A) regulators in the process of trabecular meshwork (TM) tissue damage in patients with primary open-angle glaucoma (POAG). METHODS: Firstly, the expression profile of m6A regulators in TM tissues of POAG patients was comprehensively analyzed by bioinformatics analysis; Plasmid transfection and siRNA gene interference were used to enhance or weaken the expression levels of YTHDC2 in human trabecular meshwork cells (HTMCs); Cell migration ability was detected by transwell chamber assay; Immunofluorescence staining assay was used to evaluate the expression of extracellular matrix (ECM) related proteins. RESULTS: Through the analysis of GSE27276 database, 5 m6A regulators with different expression in POAG were screened out. The results of random forest model showed that these 5 m6A regulators exhibited diagnostic potential and were characteristic genes of POAG. All POAG samples could be effectively divided into two groups based on the expression levels of these 5 hub m6A regulators. Immune cell infiltration analysis indicated that the levels of activated CD8+ T cells and regulatory T cells were different in the two subtypes. HTMC oxidative stress cell model and TGF-β2 stimulation cell model were further constructed to verify the expression of the aforementioned hub m6A regulators, and it was found that YTHDC2 mRNA showed the same expression trend in both models. The silencing of YTHDC2 enhanced the migration ability of HTMCs and increased the synthesis ability of ECM. However, when YTHDC2ΔYTH, which lacks the YTH domain, is overexpressed in HTMCs, there is no significant change in the ECM synthesis ability. CONCLUSIONS: The differentially expressed m6A regulators in TM tissues may serve as potential diagnostic biomarkers for POAG. And, in HTMCs, the expression level of YTHDC2 mRNA was changed under oxidative stress or TGF-β2 intervention, and then exerted its regulation on cell migration and ECM synthesis capability through m6A modification, which may be an important part of the disease process of POAG.

Humans↗

PubMed2007

Phylogenetic tree information aids supervised learning for predicting protein-protein interaction based on distance matrices.

BACKGROUND: Protein-protein interactions are critical for cellular functions. Recently developed computational approaches for predicting protein-protein interactions utilize co-evolutionary information of the interacting partners, e.g., correlations between distance matrices, where each matrix stores the pairwise distances between a protein and its orthologs from a group of reference genomes. RESULTS: We proposed a novel, simple method to account for some of the intra-matrix correlations in improving the prediction accuracy. Specifically, the phylogenetic species tree of the reference genomes is used as a guide tree for hierarchical clustering of the orthologous proteins. The distances between these clusters, derived from the original pairwise distance matrix using the Neighbor Joining algorithm, form intermediate distance matrices, which are then transformed and concatenated into a super phylogenetic vector. A support vector machine is trained and tested on pairs of proteins, represented as super phylogenetic vectors, whose interactions are known. The performance, measured as ROC score in cross validation experiments, shows significant improvement of our method (ROC score 0.8446) over that of using Pearson correlations (0.6587). CONCLUSION: We have shown that the phylogenetic tree can be used as a guide to extract intra-matrix correlations in the distance matrices of orthologous proteins, where these correlations are represented as intermediate distance matrices of the ancestral orthologous proteins. Both the unsupervised and supervised learning paradigms benefit from the explicit inclusion of these intermediate distance matrices, and particularly so in the latter case, which offers a better balance between sensitivity and specificity in the prediction of protein-protein interactions.

Computational Biology↗

PubMed2006

[Induction of protective immunity against Schistosoma japonicum by pcDNA3.1/Sj20.8 nucleic acid vaccine in BALB/c mice].

Sj20.8 gene was amplified by PCR and inserted into eukaryotic expression plasmid pcDNA3.1 to construct recombinant plasmid pcDNA3.1/Sj20.8, which was then injected into the quadriceps femoris of the BALB/c mice. Results showed that the Sj20.8 antigen was low expressed in the local tissue of the mice, and was not able to significantly reduce eggs in the liver than in the control mice.

Animals↗

PubMed2005

Comparison of enhancement of pentachlorophenol sonolysis at 20 kHz by dual-frequency sonication.

The comparison of enhancement effect of pentachlorophenol sonolysis at 20 kHz by different dual-frequency ultrasonic irradiations has been investigated. Dual-frequency (20 kHz/40 kHz, 20 kHz/530 kHz, 20 kHz/800 kHz and 20 kHz/1040 kHz) ultrasounds have been used. It has been found that the rate of pentachlorophenol degradation at dual-frequency ultrasonic irradiation is the highest compared to mono-frequency ultrasonic systems. The combination of dual-frequency systems has synergistic effect and the enhancement effect of sonochemical degradation of pentachlorophenol at 20 kHz by dual-frequency systems appears to be remarkable frequency sensitive. The order of contribution to the enhancement effect of sonochemical degradation of pentachlorophenol at 20 kHz is as follows: 530 kHz > 800 kHz > 40 kHz > 1040 kHz.

Hot Temperature↗

PubMed2005

Quasi-consensus-based comparison of profile hidden Markov models for protein sequences.

A simple approach for the sensitive detection of distant relationships among protein families and for sequence-structure alignment via comparison of hidden Markov models based on their quasi-consensus sequences is presented. Using a previously published benchmark dataset, the approach is demonstrated to give better homology detection and yield alignments with improved accuracy in comparison to an existing state-of-the-art dynamic programming profile-profile comparison method. This method also runs significantly faster and is therefore suitable for a server covering the rapidly increasing structure database. A server based on this method is available at http://liao.cis.udel.edu/website/servers/modmod

Algorithms↗

PubMed2005

An improved hidden Markov model for transmembrane protein detection and topology prediction and its applications to complete genomes.

MOTIVATION: Knowledge of the transmembrane helical topology can help identify binding sites and infer functions for membrane proteins. However, because membrane proteins are hard to solubilize and purify, only a very small amount of membrane proteins have structure and topology experimentally determined. This has motivated various computational methods for predicting the topology of membrane proteins. RESULTS: We present an improved hidden Markov model, TMMOD, for the identification and topology prediction of transmembrane proteins. Our model uses TMHMM as a prototype, but differs from TMHMM by the architecture of the submodels for loops on both sides of the membrane and also by the model training procedure. In cross-validation experiments using a set of 83 transmembrane proteins with known topology, TMMOD outperformed TMHMM and other existing methods, with an accuracy of 89% for both topology and locations. In another experiment using a separate set of 160 transmembrane proteins, TMMOD had 84% for topology and 89% for locations. When utilized for identifying transmembrane proteins from non-transmembrane proteins, particularly signal peptides, TMMOD has consistently fewer false positives than TMHMM does. Application of TMMOD to a collection of complete genomes shows that the number of predicted membrane proteins accounts for approximately 20-30% of all genes in those genomes, and that the topology where both the N- and C-termini are in the cytoplasm is dominant in these organisms except for Caenorhabditis elegans. AVAILABILITY: http://liao.cis.udel.edu/website/servers/TMMOD/

Algorithms↗

PubMed2004

[Characteristic analysis of acute leukemia immunophenotyping in 180 cases by flow cytometry].

To study the acute Leukemia immunophenotype and its diagnosis value, three color direct immunofluorescece staining methods of flow cytometry and immunophenotype of antibody integration system were used for detection of 180 cases of acute leukemia. The results showed that patients with ALL expressed lymphocyte antigen, and 49.4% patients with ALL accompanied myeloid antigen; all patients with AML expressed myeloid antigen, and 43.2% patients with AML accompanied lymphocyte antigen. In conclusion, leukemia immunophenotyping by three-color direct immunofluore staining methods could define some particular types of leukemia with an important value in diagnosis, treatment and predicting prognosis of acute leukemia.

Adolescent↗

PubMed2004

[Amplification and sequencing of the gene coding for mucin-like protein from Schistosoma japonicum].

OBJECTIVE: To amplify and sequence the partial gene coding for mucin-like protein from Chinese isolates of Schistosoma japonicum (SjMLP). METHODS: The antigenic determinants of SmMLP were predicted by PCGENE software and specific oligonucleotide primers were designed and synthesized. Total RNA was isolated from adult worms of S. japonicum using Trizol reagent and the coding region gene of SjMLP was amplified by RT-PCR technique. RESULTS: The coding region of SjMLP gene was specifically amplified by RT-PCR and the size of amplified fragment was 756 base pairs. The DNA sequence analysis result indicated that the coding sequence of the MLP was highly homologous between S. mansoni and S. japonicum. CONCLUSION: The amplified fragment is consistent to the predicted one, providing a basis for cloning and further study on DNA immunization.

Amino Acid Sequence↗

PubMed2003

Combining pairwise sequence similarity and support vector machines for detecting remote protein evolutionary and structural relationships.

One key element in understanding the molecular machinery of the cell is to understand the structure and function of each protein encoded in the genome. A very successful means of inferring the structure or function of a previously unannotated protein is via sequence similarity with one or more proteins whose structure or function is already known. Toward this end, we propose a means of representing proteins using pairwise sequence similarity scores. This representation, combined with a discriminative classification algorithm known as the support vector machine (SVM), provides a powerful means of detecting subtle structural and evolutionary relationships among proteins. The algorithm, called SVM-pairwise, when tested on its ability to recognize previously unseen families from the SCOP database, yields significantly better performance than SVM-Fisher, profile HMMs, and PSI-BLAST.

Algorithms↗