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Biomedical subjects

Wenlin Li

Publications and source records attributed to Wenlin Li.

5 recordsLinked to original sources

SIGEL: a context-aware genomic representation learning framework for spatial genomics analysis.

Spatial transcriptomics (ST) integrates spatial information into genomics, yet methods for generating spatially-informed gene representations are limited and computationally intensive. We present SIGEL, a cost-effective framework that derives gene manifolds from ST data by exploiting spatial genomic context. The resulting SIGEL-generated gene representations (SGRs) are context-aware, biologically meaningful, and robust across samples, making them highly effective for key downstream tasks, including imputing missing genes, detecting spatial expression patterns, identifying disease-related genes and interactions, and improving spatial clustering. Extensive experiments across diverse ST datasets validate SIGEL's effectiveness and highlight its potential in advancing spatial genomics research.

Genomics↗

Hepatic differentiation and transcriptional profile of the mouse liver epithelial progenitor cells (LEPCs) under the induction of sodium butyrate.

The liver regenerates by progenitor cells when it is damaged in chronic liver diseases and extensive damage. The progenitor cells, also termed "oval cells" according to their morphological traits, can differentiate into hepatocytes and bile duct cells in vivo. To better understand the transcriptional pattern that accompanies the hepatic differentiation of oval cells, we applied cDNA microarray to analyze the oval cell-derived liver epithelial progenitor cells (LEPCs) during in vitro induced differentiation. Upon exposure to sodium butyrate, a histone deacetylase inhibitor, cultured LEPCs differentiate and express functional hepatocyte markers albumin, tryptophan 2, 3-dioxygenase and alcohol dehydrogenase. For expression profiling, cells were harvested at 6 h, 12 h, 1 d, 3 d and 7 d after exposure to sodium butyrate. After analyzing the microarray data by SOM clustering, total of 796 differentially regulated genes were grouped into 48 clusters. Consistent with the phenotype change of LEPCs after sodium butyrate treatment, many hepatocyte functional genes are revealed by analyzing the clusters containing genes up-regulated through all the time points. The clusters, containing down-regulated genes immediately after the induction, are also analyzed. The microarray data was validated by analyzing the expression of selected genes by quantitative real-time PCR. A set of genes expressed synergistically in these clusters may play a central role during the process of differentiation. Sodium butyrate decreases cyclin B1 and Cdk4 expression, which would be associated with LEPCs growth arrest shortly after treatment. Bmi1, a polycomb group protein, is also down-regulated immediately after treatment and remains at a low level during the induction. These findings highlight the key molecular mechanisms by which sodium butyrate, mediates its effects on cell growth arrest and induction of differentiation. In conclusion, our data reflect a global view of gene expression during hepatic differentiation of LEPCs induced by sodium butyrate.

Animals↗

Enzymatic tissue digestion as an alternative sample preparation approach for quantitative analysis using liquid chromatography-tandem mass spectrometry.

Compound extraction from biological tissue often presents a challenge for the bioanalytical chemist. Labor-intensive homogenization or sonication of whole or powdered tissue is performed before compounds can be extracted and analyzed. Enzymatic digestion is commonly used for tissue dissociation and cell harvesting and offers the advantages of unattended sample preparation, potential automation, and low cost. The feasibility of enzymatic digestion as an alternate tissue preparation technique was evaluated for bioanalysis of drugs in conjunction with LC/MS/MS. Two different enzymes (collagenase and proteinase K) that are known to degrade connective tissues to allow tissue dissolution were chosen for evaluation, employing well-known antidepressants desipramine and fluoxetine as test compounds in dog and rat brain tissue. Comparison between enzymatic digestion and conventional homogenization tissue preparation was performed, including investigation of matrix ionization suppression of both methods using a postcolumn infusion system. Results showed that enzymatic digestion has extraction efficiency comparable to homogenization. Matrix ionization suppression was not observed for either the test compounds evaluated or the sample extraction method. Test compound levels of incurred tissue samples prepared by enzymatic digestion were in good agreement with the values obtained by the conventional homogenization tissue preparation, indicating that enzymatic digestion is an appropriate tissue sample preparation method.

Animals↗

Quantitation of endogenous analytes in biofluid without a true blank matrix.

A method is presented that describes a reliable and practical procedure for quantitation of an analyte present at relatively high background levels in blank (untreated) biological matrixes. Using a "surrogate analyte" approach, an endogenous analyte was quantitated in a variety of biological matrixes containing both very low (<10 ng/mL) and high (>2000 ng/mL) background levels of the desired analyte. This quantitative "surrogate analyte" approach was applied during the development of an HPLC/MS method for alpha-ketoisocaproic acid (KIC), which was identified as a potential biomarker for branched chain amino acid transferase inhibitor activity. Using deuterium-labeled KIC (d(3)) as a surrogate analyte, not an internal standard, to generate the calibration curve, the concentration of KIC in biofluid could be back-calculated based on the regression equation and response factor of KIC to KIC-d(3). In particular, this approach made it possible to prepare standards in control biofluid such as plasma, which greatly facilitated the process of method development. For the validated method, a linear range of 10-5000 ng/mL for KIC-d(3) was observed. Intraday and interday experimental accuracy, calculated as percent error, were in the range of < or =10% for KIC-d(3). This method is simple, rapid, and reliable for the quantitation of KIC in plasma, brain homogenate, cerebrospinal fluid, and other biological samples from discovery and pharmacological studies.

Journal Article↗

Investigation of EDTA anticoagulant in plasma to improve the throughput of liquid chromatography/tandem mass spectrometric assays.

In this study, EDTA and heparin are compared as anticoagulants with respect to their efficiency in preventing clot formation in plasma samples that were subsequently analyzed by liquid chromatography/tandem mass spectrometry (LC/MS/MS). A pilot in vivo pharmacokinetic study for the drug chlorpheniramine was conducted in which both EDTA and heparin plasma samples were collected simultaneously. All conditions except the anticoagulant were held constant during the pharmacokinetic study. Bioanalytical results were compared from samples transferred by manual pipette and by an automated liquid handler workstation. The concentration of chlorpheniramine in samples was determined by LC/MS/MS. Results from the analysis of variances (ANOVA) of log-transformed plasma chlorpheniramine concentrations were used to calculate 90% confidence intervals for the ratio least-squares mean values for anticoagulants and for transfer methods. Analytical concentrations of the drug chlorpheniramine were equivalent in heparin- and EDTA-containing plasma. Results suggest that the failure rate for transfer of EDTA plasma (50 micro L by automated workstation or manually) is less than that for heparinized plasma. As a consequence of these results, the vast majority of plasma samples in our laboratories are now collected in EDTA, which allows for use of automated sample transfer resulting in a three-fold timesaving over manual transfer using a single-channel pipette. The ability to use automation has resulted in improved efficiency and cost savings.

Animals↗