Biomedical subjects

Shuyu Li

Publications and source records attributed to Shuyu Li.

18 recordsLinked to original sources

PubMed2026

Machine learning-assisted Mn-N-C nanozyme colorimetric sensor array for trace-level detection of biogenic amines in meat.

Accurate detection of biogenic amines (BAs) in meat remains challenging due to their high structural similarity and co-occurrence. Herein, an Mn-N-C nanozyme was synthesized via a metal-organic framework confined pyrolysis strategy, possessing excellent oxidase (OXD)- and peroxidase (POD)-like activities. The dual enzyme-like activity showed Km values of 0.1584 mM (OXD) and 0.1498 mM (POD), respectively, in detection system. Leveraging these properties, a colorimetric sensor array was constructed, enabling the detection of four representative BAs within a concentration range of 2-10 ppm with 100% classification accuracy. In addition, a concentration independent recognition model based on an artificial neural network was developed to address signal nonlinearity interference in meat. The integrated system achieved accurate trace-level identification of BAs in perishable fish, pork, and chicken, demonstrating its applicability for early-stage BAs monitoring and quality deterioration warning during storage and transportation.

Biogenic Amines↗

PubMed2025

Machine learning-based analysis of the impact of 5' untranslated region on protein expression.

The 5' untranslated region (5'UTR) plays a crucial regulatory role in messenger RNA (mRNA), with modified 5'UTRs extensively utilized in vaccine production, gene therapy, etc. Nevertheless, manually optimizing 5'UTRs may encounter difficulties in balancing the effects of various cis-elements. Consequently, multiple 5'UTR libraries have been created, and machine learning models have been employed to analyze and predict translation efficiency (TE) and protein expression, providing insights into critical regulatory features. On the one hand, these screening libraries, based on TE and mean ribosome load, struggle to accurately quantify protein expression; on the other hand, a precise method for quantifying 5'UTRs necessitates a significantly costlier library. To resolve this dilemma, we constructed a library utilizing firefly luciferase as the reporter to measure accurate protein expression. In addition, we optimized the library construction method by clustering mRNA sequences to reduce redundant data and minimize the size of the dataset. This dual strategy by increasing accuracy and reducing dataset size was found to be effective in predicting the 5'UTRs from the PC3 cell line.

5' Untranslated Regions↗

PubMed2006

Farnesoid X receptor agonist reduces serum asymmetric dimethylarginine levels through hepatic dimethylarginine dimethylaminohydrolase-1 gene regulation.

The farnesoid X receptor (FXR, NR1H4) is a bile acid-responsive nuclear receptor that plays critical roles in the transcriptional regulation genes involved in cholesterol, bile acid, triglyceride, and carbohydrate metabolism. By microarray analysis of hepatic genes from female Zucker diabetic fatty (ZDF) rats treated with the FXR agonist GW4064, we have identified dimethylarginine dimethylaminohydrolase-1 (DDAH1) as an FXR target gene. DDAH1 is a key catabolic enzyme of asymmetric dimethylarginine (ADMA), a major endogenous nitric-oxide synthase inhibitor. Sequence analysis of the DDAH1 gene reveals the presence of an FXR response element (FXRE) located 90 kb downstream of the transcription initiation site and within the first intron. Functional analysis of the putative FXRE demonstrated GW4064 dose-dependent transcriptional activation from the element, and we have demonstrated that the FXRE sequence binds the FXR-RXR heterodimer. In vivo administration of GW4064 to female ZDF rats promoted a dose-dependent and >6-fold increase in hepatic DDAH1 gene expression. The level of serum ADMA was reduced concomitantly. These findings provide a mechanism by which FXR may increase endothelium-derived nitric oxide levels through modulation of serum ADMA levels via direct regulation of hepatic DDAH1 gene expression. Thus, beneficial clinical outcomes of FXR agonist therapy may include prevention of atherosclerosis and improvement of the metabolic syndrome.

Amidohydrolases↗

PubMed2006

Too much data, but little inter-changeability: a lesson learned from mining public data on tissue specificity of gene expression.

BACKGROUND: The tissue expression pattern of a gene often provides an important clue to its potential role in a biological process. A vast amount of gene expression data have been and are being accumulated in public repository through different technology platforms. However, exploitations of these rich data sources remain limited in part due to issues of technology standardization. Our objective is to test the data comparability between SAGE and microarray technologies, through examining the expression pattern of genes under normal physiological states across variety of tissues. RESULTS: There are 42-54% of genes showing significant correlations in tissue expression patterns between SAGE and GeneChip, with 30-40% of genes whose expression patterns are positively correlated and 10-15% of genes whose expression patterns are negatively correlated at a statistically significant level (p = 0.05). Our analysis suggests that the discrepancy on the expression patterns derived from technology platforms is not likely from the heterogeneity of tissues used in these technologies, or other spurious correlations resulting from microarray probe design, abundance of genes, or gene function. The discrepancy can be partially explained by errors in the original assignment of SAGE tags to genes due to the evolution of sequence databases. In addition, sequence analysis has indicated that many SAGE tags and Affymetrix array probe sets are mapped to different splice variants or different sequence regions although they represent the same gene, which also contributes to the observed discrepancies between SAGE and array expression data. CONCLUSION: To our knowledge, this is the first report attempting to mine gene expression patterns across tissues using public data from different technology platforms. Unlike previous similar studies that only demonstrated the discrepancies between the two gene expression platforms, we carried out in-depth analysis to further investigate the cause for such discrepancies. Our study shows that the exploitation of rich public expression resource requires extensive knowledge about the technologies, and experiment. Informatic methodologies for better interoperability among platforms still remain a gap. One of the areas that can be improved practically is the accurate sequence mapping of SAGE tags and array probes to full-length genes.

Journal Article↗

PubMed2006

Comparative analysis and integrative classification of NCI60 cell lines and primary tumors using gene expression profiling data.

BACKGROUND: NCI60 cell lines are derived from cancers of 9 tissue origins and have been invaluable in vitro models for cancer research and anti-cancer drug screen. Although extensive studies have been carried out to assess the molecular features of NCI60 cell lines related to cancer and their sensitivities to more than 100,000 chemical compounds, it remains unclear if and how well these cell lines represent or model their tumor tissues of origin. Identification and confirmation of correct origins of NCI60 cell lines are critical to their usage as model systems and to translate in vitro studies into clinical potentials. Here we report a direct comparison between NCI60 cell lines and primary tumors by analyzing global gene expression profiles. RESULTS: Comparative analysis suggested that 51 of 59 cell lines we analyzed represent their presumed tumors of origin. Taking advantage of available clinical information of primary tumor samples used to generate gene expression profiling data, we further classified those cell lines with the correct origins into different subtypes of cancer or different stages in cancer development. For example, 6 of 7 non-small cell lung cancer cell lines were classified as lung adenocarcinomas and all of them were classified into late stages in tumor progression. CONCLUSION: Taken together, we developed and applied a novel approach for systematic comparative analysis and integrative classification of NCI60 cell lines and primary tumors. Our results could provide guidance to the selection of appropriate cell lines for cancer research and pharmaceutical compound screenings. Moreover, this gene expression profile based approach can be generally applied to evaluate experimental model systems such as cell lines and animal models for human diseases.

Carcinoma, Non-Small-Cell Lung↗

PubMed2006

Bestatin, an inhibitor of aminopeptidases, provides a chemical genetics approach to dissect jasmonate signaling in Arabidopsis.

Bestatin, a potent inhibitor of some aminopeptidases, was shown previously to be a powerful inducer of wound-response genes in tomato (Lycopersicon esculentum). Here, we present several lines of evidence showing that bestatin specifically activates jasmonic acid (JA) signaling in plants. First, bestatin specifically activates the expression of JA-inducible genes in tomato and Arabidopsis (Arabidopsis thaliana). Second, the induction of JA-responsive genes by bestatin requires the COI1-dependent JA-signaling pathway, but does not depend strictly on JA biosynthesis. Third, microarray analysis using Arabidopsis whole-genome chip demonstrates that the gene expression profile of bestatin-treated plants is similar to that of JA-treated plants. Fourth, bestatin promotes a series of JA-related developmental phenotypes. Taken together, the unique action mode of bestatin in regulating JA-signaled processes leads us to the hypothesis that bestatin exerts its effects through the modulation of some key regulators in JA signaling. We have employed bestatin as an experimental tool to dissect JA signaling through a chemical genetic screening, which yielded a collection of Arabidopsis bestatin-resistant (ber) mutants that are insensitive to the inhibitory effects of bestatin on root elongation. Further characterization efforts demonstrate that some ber mutants are defective in various JA-induced responses, which allowed us to classify the ber mutants into three phenotypic groups: JA-insensitive ber mutants, JA-hypersensitive ber mutants, and mutants insensitive to bestatin but showing normal response to JA. Genetic and phenotypic analyses of the ber mutants with altered JA responses indicate that we have identified several novel loci involved in JA signaling.

Aminopeptidases↗

PubMed2006

A recombination silencer that specifies heterochromatin positioning and ikaros association in the immunoglobulin kappa locus.

Allelic exclusion ensures that individual B lymphocytes produce only one kind of antibody molecule. Previous studies have shown that allelic exclusion of the mouse Igkappa locus occurs by the combination of monoallelic silencing and a low level of monoallelic activation for rearrangement combined with a negative feedback loop blocking additional functional rearrangements. Using yeast artificial chromosome-based single-copy isotransgenic mice, we have identified a cis-acting element that negatively regulates rearrangement in this locus, specifically in B cells. The element, termed Sis, resides in the V-J intervening sequence. Sis specifies the targeting of Igkappa transgenes in pre-B and B cells to centromeric heterochromatin and associates with Ikaros, a repressor protein that also colocalizes with centromeric heterochromatin. Significantly, these are hallmarks of silenced endogenous germline Igkappa genes in B cells. These results lead us to propose that Sis participates in the monoallelic silencing aspect of allelic exclusion regulation.

Animals↗

PubMed2006

OligoMatcher: analysis and selection of specific oligonucleotide sequences for gene silencing by antisense or siRNA.

UNLABELLED: OligoMatcher is a web-based tool for analysis and selection of unique oligonucleotide sequences for gene silencing by antisense oligonucleotides (ASOs) or small interfering RNA (siRNA). A specific BLAST server was built for analysing sequences of ASOs that target pre-mRNA in the cell nucleus. Tissue- and cell-specific expression data of potential cross-reactive genes are integrated in the OligoMatcher program, which allows biologists to select unique oligonucleotide sequences for their target genes in specific experimental systems. AVAILABILITY: The OligoMatcher web server is available at http://shelob.cs.iupui.edu:18081/oligomatch.php. The source code is freely available for non-profit use on request to the authors. CONTACT: Mathew Palakal (mpalakal@cs.iupui.edu) or Shuyu Li (li_shuyu_dan@lilly.com).

Algorithms↗

PubMed2005

Hepatic peroxisomal fatty acid beta-oxidation is regulated by liver X receptor alpha.

Peroxisomes are the exclusive site for the beta-oxidation of very-long-chain fatty acids of more than 20 carbons in length (VLCFAs). Although the bulk of dietary long-chain fatty acids are oxidized in the mitochondria, VLCFAs cannot be catabolized in mitochondria and must be shortened first by peroxisomal beta-oxidation. The regulation of peroxisomal, mitochondrial, and microsomal fatty acid oxidation systems in liver is mediated principally by peroxisome proliferator-activated receptor alpha (PPARalpha). In this study we provide evidence that the liver X receptor (LXR) regulates the expression of the genetic program for peroxisomal beta-oxidation in liver. The genes encoding the three enzymes of the classic peroxisomal beta-oxidation cycle, acyl-coenzyme A (acyl-CoA) oxidase, enoyl-CoA hydratase/L-3-hydroxyacyl-CoA dehydrogenase, and 3-ketoacyl-CoA thiolase, are activated by the LXR ligand, T0901317. Accordingly, administration of T0901317 in mice promoted a dose-dependent and greater than 2-fold increase in the rate of peroxisomal beta-oxidation in the liver. The LXR effect is independent of PPARalpha, because T0901317-induced peroxisomal beta-oxidation in the liver of PPARalpha-null mice. Interestingly, T0901317-induced peroxisomal beta-oxidation is dependent on the LXRalpha isoform, but not the LXRbeta isoform. We propose that induction of peroxisomal beta-oxidation by LXR agonists may serve as a counterregulatory mechanism for responding to the hypertriglyceridemia and liver steatosis that is promoted by potent LXR agonists in vivo; however, additional studies are warranted.

Acetyl-CoA C-Acyltransferase↗

PubMed2005

Overexpression of G protein-coupled receptors in cancer cells: involvement in tumor progression.

G protein-coupled receptors (GPCRs) play important roles in a variety of biological and pathological processes. They are considered among the most desirable targets for drug development. Recent studies have demonstrated that many GPCRs, such as endothelin receptors, chemokine receptors and lysophosphatidic acid receptors have been implicated in the tumorigenesis and metastasis of multiple human cancers. In this study, we conducted an in silico analysis of GPCR gene expression in primary human tumors by analyzing some publicly available gene expression profiling data. Statistical analysis was performed on eight microarray data sets of non-small cell lung cancer, breast cancer, prostate cancer, melanoma, gastric cancer and diffused large B cell lymphoma to identify GPCRs that are up-regulated in primary or metastatic cancer cells. Our analysis has demonstrated overexpression of several GPCRs in primary tumor cells, including chemokine receptors and protease-activated receptors that were shown to be important for tumorigenesis by previous studies. In addition, we have uncovered several GPCRs, such as neuropeptide receptors, adenosine A2B receptor, P2Y purinoceptor, calcium-sensing receptor and metabotropic glutamate receptors, that are expressed at a significantly higher level in some cancer tissue and may play a role in cancer progression. Analysis of cancer samples in different disease stages also suggests that some GPCRs, such as endothelin receptor A, may be involved in early tumor progression and others, such as CXCR4, may play a critical role in tumor invasion and metastasis. The present study demonstrates the value of publicly available microarray data as a resource to gain more understanding of cancer biology, to validate previous findings from in vitro experiments, and to identify potential novel anticancer targets and biomarkers.

Biomarkers, Tumor↗

PubMed2004

Protein kinase C alpha expression in breast and ovarian cancer.

In recent years research has focused on the development of specific, targeted drugs to treat cancer. One approach has been to block intracellular signaling proteins, such as protein kinase C alpha (PKC-alpha). To help support the rationale for clinical studies of a PKC-alpha-targeted therapy in breast and ovarian cancers, we reviewed publications studying PKC-alpha expression in these tumors. Since these investigations were mostly performed in cell lines, we supplemented this review with some preliminary findings from studies examining PKC-alpha expression in tumor tissue biopsies obtained from patients with breast and ovarian cancer. Based on the reviewed publications using representative cell lines and our preliminary findings on tumor tissue of patients with breast cancer, we infer that PKC-alpha levels may especially be increased in breast cancer patients with low or negative estrogen receptor (ER) levels. Thus, clinical studies determining efficacy of selective or specific inhibitors of PKC-alpha should include determination of ER status in order to help answer whether blocking PKC-alpha in patients with low or absent ER can result in clinical benefit.

Antineoplastic Agents↗

PubMed2004

Expression levels of protein kinase C-alpha in non-small-cell lung cancer.

Current treatments of non-small-cell lung cancer (NSCLC) are inadequate and new therapies are being developed that target specific cellular signaling proteins associated with tumor growth. One potential target is protein kinase C (PKC)-alpha, a signaling molecule with an important role in cell regulation and proliferation. The present study examines the expression levels of PKC-alpha in NSCLC to better understand the distribution of PKC-alpha in NSCLC. We analyzed tumor specimens from an independent tumor tissue bank to determine PKC-alpha protein and messenger RNA gene expression in NSCLC. In addition, we used publicly available gene expression array data to further understand PKC-a-associated gene expression profiles in NSCLC. We found that PKC-alpha is highly expressed in < or = 20% of patients with NSCLC. We also found that PKC-alpha was preferentially expressed in adenocarcinoma compared with squamous cell carcinoma of the lung.

Carcinoma, Non-Small-Cell Lung↗

PubMed2004

Automatic recognition of small cell carcinoma based on the self-organizing neural network.

In this paper the recognition of Small Cell Carcinoma (SCC) is studied. For each type we select 128 samples for training, and randomly measure 200 cells in each sample. We introduce multi-scale morphology based on centroid coordinates to extract the boundaries of nuclei and obtain feature images of nuclei. The features of lung cancer cells are described by morphological and colorimetrical parameters, which is valuable to recognize SCC. Then the architecture of self-organizing feature mapping (SOFM) neural network is studied for recognition of SCC. The weights of the network are adjusted by self-organizing competition, and finally inputted patterns are classified. This algorithm has the advantage of parallelism and fast-convergence, and may simplify the analysis of SCC. Clinical experiment results show that the correctness ratio of this system may reach 95.3% while recognizing lung cancer cell types. Our work is significant to the pathological researches of lung cancer, assistant clinic diagnosis, and assessment of therapeutic effects. Meanwhile a software system named as SCC. LUNG is established for automatic analysis.

Adult↗

PubMed2003

A comparative analysis of HGSC and Celera human genome assemblies and gene sets.

MOTIVATION: Since the simultaneous publication of the human genome assembly by the International Human Genome Sequencing Consortium (HGSC) and Celera Genomics, several comparisons have been made of various aspects of these two assemblies. In this work, we set out to provide a more comprehensive comparative analysis of the two assemblies and their associated gene sets. RESULTS: The local sequence content for both draft genome assemblies has been similar since the early releases, however it took a year for the quality of the Celera assembly to approach that of HGSC, suggesting an advantage of HGSC's hierarchical shotgun (HS) sequencing strategy over Celera's whole genome shotgun (WGS) approach. While similar numbers of ab initio predicted genes can be derived from both assemblies, Celera's Otto approach consistently generated larger, more varied gene sets than the Ensembl gene build system. The presence of a non-overlapping gene set has persisted with successive data releases from both groups. Since most of the unique genes from either genome assembly could be mapped back to the other assembly, we conclude that the gene set discrepancies do not reflect differences in local sequence content but rather in the assemblies and especially the different gene-prediction methodologies.

Databases, Protein↗

PubMed2003

The kinetics of V-J joining throughout 3.5 megabases of the mouse Ig kappa locus fit a constrained diffusion model of nuclear organization.

To gain insight into the nuclear organization of the mouse Ig kappa locus and how it may relate to the formation of synapses during recombination, we have studied the kinetics of rearrangement of different V kappa gene families to J kappa gene segments in the pre-B cell line, 103bcl2. Remarkably, V kappa gene families separated by more than 3.5 Mb from J kappa gene segments rearranged with nearly identical kinetics to those as close as 18 kb to J kappa gene segments. These results fit a model of nuclear organization in which the entire V kappa J kappa region resides within a single nuclear subcompartment and is capable of exhibiting multiple reversible contacts through diffusion and Brownian motion.

Animals↗

PubMed2003

Automatic quantitative analysis of ore content of human tooth enamel based on image processing.

Introducing the theory of fuzzy set, mathematical morphology and computerized mask fast scanning, we developed the TOOTH.SCA software and method to analyze the effect of fluoride (NaF) on ore content of human tooth enamel automatically and quantitatively. And we obtained some characteristic parameters, such as the depth, the type and the demineralized content of every scathing layer of dental caries. The smallest scale of mask scanning is 0.1 microm x 0.1 microm and the time required to analyze a sample is only 12 s. The applied software and method we built play an important role to the research on the mechanism of pathological changes of teeth and preventing dental caries.

Bone Density↗

PubMed2002

Chromatin structural analyses of the mouse Igkappa gene locus reveal new hypersensitive sites specifying a transcriptional silencer and enhancer.

To identify new regulatory elements within the mouse Igkappa locus, we have mapped DNase I hypersensitive sites (HSs) in the chromatin of B cell lines arrested at different stages of differentiation. We have focused on two regions encompassing 50 kilobases suspected to contain new regulatory elements based on our previous high level expression results with yeast artificial chromosome-based mouse Igkappa transgenes. This approach has revealed a cluster of HSs within the 18-kilobase intervening sequence, which we cloned and sequenced in its entirety, between the Vkappa gene closest to the Jkappa region. These HSs exhibit pro/pre-B cell-specific transcriptional silencing of a Vkappa gene promoter in transient transfection assays. We also identified a plasmacytoma cell-specific HS in the far downstream region of the locus, which in analogous transient transfection assays proved to be a powerful transcriptional enhancer. Deletional analyses reveal that for each element multiple DNA segments cooperate to achieve either silencing or enhancement. The enhancer sequence is conserved in the human Igkappa gene locus, including NF-kappaB and E-box sites that are important for the activity. In summary, our results pinpoint the locations of presumptive regulatory elements for future knockout studies to define their functional roles in the native locus.

Animals↗

PubMed2002

Comparative analysis of human genome assemblies reveals genome-level differences.

Previous comparative analysis has revealed a significant disparity between the predicted gene sets produced by the International Human Genome Sequencing Consortium (HGSC) and Celera Genomics. To determine whether the source of this discrepancy was due to underlying differences in the genomic sequences or different gene prediction methodologies, we analyzed both genome assemblies in parallel. Using the GENSCAN gene prediction algorithm, we generated predicted transcriptomes that could be directly compared. BLAST-based comparisons revealed a 20-30% difference between the transcriptomes. Further differences between the two genomes were revealed with protein domain PFAM analyses. These results suggest that fundamental differences between the two genome assemblies are likely responsible for a significant portion of the discrepancy between the transcript sets predicted by the two groups.

Chromosome Mapping↗