The human gut microbiota plays a critical role in health and disease, influencing metabolic, immune, and neurological processes. Dietary flavonoids, such as naringenin, a bioactive compound found predominantly in citrus fruits, have been shown to exert multiple beneficial effects, including anti-inflammatory, antioxidant, and metabolic regulatory activities. However, the mechanisms by which naringenin interacts with and modulates gut microbial communities remain incompletely understood. This project aims to explore the modulatory effects of naringenin on gut microbiota composition and function using a combination of 16S rRNA gene sequencing.

This Analysis explores the spatial distribution of distinct cell populations and their gene expression patterns within the mouse small intestine to understand its multifaceted biological roles. Key objectives include assessing the intestine's health status through biomarkers that reflect tissue integrity and functionality, as well as identifying the expression levels and spatial arrangements of disease-related biomarkers that may signal pathological changes. The immunological state is investigated by mapping immune cell types and processes to their specific intestinal regions, shedding light on localized immune responses. Additionally, the spatial variation of nutrient absorption genes is examined to determine functional specialization along the intestinal tract. Lastly, the study delves into microbiome-associated biomarkers to uncover their regional distribution and potential influence on intestinal health, nutrient absorption, and immune interactions.

In this project, I conducted a detailed analysis of single-cell RNA sequencing data from Invasive Ductal Carcinoma (IDC) cells sourced from a 65-year-old female donor, utilizing 10x Genomics technology to uncover tumor heterogeneity and its implications for cancer progression. The data were processed using the Seurat package, with initial steps including quality control to filter out low-quality cells and normalization of gene expression data. I identified distinct cell populations through clustering and dimensionality reduction techniques, such as UMAP and PCA, revealing clusters of tumor cells, macrophages, and other immune cells. A differential gene expression analysis highlighted key markers linked to malignancy, including MYC and KRAS, as well as angiogenic factors like VEGFA, indicating aggressive tumor behavior and metastatic potential. Immune markers such as CD68 and IL6 revealed an immunosuppressive microenvironment, complicating treatment efforts. Furthermore, I visualized the expression patterns of crucial genes via heatmaps and boxplots, ultimately concluding that the identified markers represent critical therapeutic targets for enhancing patient outcomes in IDC treatment.

In this project, I conducted a detailed analysis of single-cell RNA sequencing data from Invasive Ductal Carcinoma (IDC) cells sourced from a 65-year-old female donor, utilizing 10x Genomics technology to uncover tumor heterogeneity and its implications for cancer progression. The data were processed using the Seurat package, with initial steps including quality control to filter out low-quality cells and normalization of gene expression data. I identified distinct cell populations through clustering and dimensionality reduction techniques, such as UMAP and PCA, revealing clusters of tumor cells, macrophages, and other immune cells. A differential gene expression analysis highlighted key markers linked to malignancy, including MYC and KRAS, as well as angiogenic factors like VEGFA, indicating aggressive tumor behavior and metastatic potential. Immune markers such as CD68 and IL6 revealed an immunosuppressive microenvironment, complicating treatment efforts. Furthermore, I visualized the expression patterns of crucial genes via heatmaps and boxplots, ultimately concluding that the identified markers represent critical therapeutic targets for enhancing patient outcomes in IDC treatment.

Objective: To map the cellular composition, gene expression patterns, and spatial organization of the breast cancer tumor microenvironment at high resolution, using spatial transcriptomics and integrated single-cell data. This study aims to uncover cellular heterogeneity, molecular interactions, and spatial dynamics within tumor tissues, contributing to a deeper understanding of tumor progression and potential therapeutic targets.

The objective of this analysis is to explore the immune landscape and tumor microenvironment (TME) in cervical cancer through single-cell RNA sequencing (scRNA-seq) data. By focusing on the expression of key immune markers, I aimed to characterize the different immune cell populations present within the tumor and evaluate their potential roles in tumor biology and immune response.