Journal: bioRxiv

Article Title: BARTsc identifies key transcriptional regulators from single-cell omics data

doi: 10.64898/2026.02.24.707729

Figure Lengend Snippet: ( a ) UMAP visualization of the scMultiome dataset for human PDAC, where each point represents a single cell colored by cell type. ( b ) Signature analysis results for selected TRs in human PDAC. The heat map is colored by BARTsc score. Asterisks indicate significance level, *: p < 0.05, **: p < 0.01, ***: p < 0.001. ( c , d ) Performance comparison between BARTsc and other methods in identifying key regulators for each cell type from PDAC scMultiome dataset. Bar plots show the F1 scores for key regulator prediction for different methods across different cell types ( c ). Scatter plot shows the sensitivity and specificity of each method in identifying cell type key regulators ( d ). ( e - h ) UMAP visualizations of the ductal cells from the PDAC scMultiome dataset, where each point represents a single ductal cell colored by sub-clusters ( e ), or the normalized expression level of gene MKI67 ( f ), TOP2A ( g ) and CDK1 ( h ). ( i ) Scatter plot showing TRs ranked by BARTsc score. The top five predicted key regulators are highlighted and labeled. ( j ) Chronos scores quantifying the effects of CRISPR-mediated knockout of the top five predicted key regulators in PDAC cell lines. Each point represents a PDAC cell line, with lower Chronos scores indicating greater loss of cell fitness upon gene knockout. P-values are calculated by one-sided Wilcoxon rank-sum tests. ( k ) RT-qPCR results showing the relative mRNA levels of NELFA and selected genes upon NELFA knock-down by siRNA in PANC-1 cells. Bars represent the mean mRNA levels relative to those under control siRNA transfection groups after normalization to GAPDH mRNA levels, and error bars indicate the standard deviation. Asterisks indicate significance levels between siNELFA and siControl determined by one-sided t -test, *: p < 0.05, **: p < 0.01, ***: p < 0.001. ( l ) Growth of PANC-1 cells three days after NELFA knockdown (siNELFA) compared with the control cells (siControl). Error bars indicate the standard deviation. P-value is calculated by one-sided t -test.

Article Snippet: Human pancreatic carcinoma cell line PANC-1 was originally purchased from the American Type Culture Collection (ATCC) (Cat# CRL-1469).

Techniques: Single Cell, Comparison, Expressing, Labeling, CRISPR, Knock-Out, Gene Knockout, Quantitative RT-PCR, Knockdown, Control, Transfection, Standard Deviation

Journal: International Journal of Nanomedicine

Article Title: Evaluation of TRAM@PPF Nanoparticles for Efficacy Against Pancreatic Cancer in Mice Model

doi: 10.2147/IJN.S556959

Figure Lengend Snippet: Function of KCa3.1 in pancreatic cancer cells. ( A ) Gene level difference of KCa3.1 between normal pancreatic cells HPNE and pancreatic cancer cells PANC-1. ( B ) Protein level difference of KCa3.1 between normal pancreatic cells HPNE and pancreatic cancer cells PANC-1. ( C ) Knockdown gene level of KCa3.1 in pancreatic cancer cells PANC-1. ( D ) Knockdown protein level of KCa3.1 in pancreatic cancer cells PANC-1. ( E ) Cell proliferation ability of pancreatic cancer cells PANC-1 after knocking down KCa3.1. ( F and G ) Cell apoptosis of pancreatic cancer cells PANC-1 after knocking down KCa3.1. Statistical significance is indicated as *** p < 0.001.

Article Snippet: The pancreatic ductal adenocarcinoma cell line PANC-1 was obtained from the American Type Culture Collection.

Techniques: Knockdown

Journal: International Journal of Nanomedicine

Article Title: Evaluation of TRAM@PPF Nanoparticles for Efficacy Against Pancreatic Cancer in Mice Model

doi: 10.2147/IJN.S556959

Figure Lengend Snippet: Characterization of the TRAM@PPF. ( A ) TEM image of the nanoparticles. ( B ) The size distribution of TRAM@PPF. ( C ) Stability profile of nanoparticle size over time. ( D ) Drug release curves showing cumulative drug release from nanoparticles under different pH conditions over time. ( E ) Fluorescence microscopy images of cellular uptake. ( F ) Bar graph of quantitative analysis of cellular uptake (mean ± SD, n = 3). ( G ) Cell viability of PANC-1 cells (mean ± SD, n = 3). ( H ) Flow cytometry scatter plots of apoptosis in treated cells. Statistical significance is indicated as *** p < 0.001.

Article Snippet: The pancreatic ductal adenocarcinoma cell line PANC-1 was obtained from the American Type Culture Collection.

Techniques: Fluorescence, Microscopy, Flow Cytometry

Journal: International Journal of Nanomedicine

Article Title: Evaluation of TRAM@PPF Nanoparticles for Efficacy Against Pancreatic Cancer in Mice Model

doi: 10.2147/IJN.S556959

Figure Lengend Snippet: In vivo antitumor efficacy. ( A ) Treatment regimen. ( B ) Tumor volume changes following PBS administration. ( C ) Tumor volume changes following PPF treatment. ( D ) Tumor volume changes following TRAM-34 treatment. ( E ) Tumor volume changes following TRAM@PPF treatment. ( F ) Comparative tumor volume changes across treatment groups. (n = 4 per group) ( G ) Tumor weight and representative images of tumors from each group. ( H ) Body weight changes during therapy. ( I ) Survival curves of PANC-1 tumor-bearing nude mice under different treatments. ( J ) Histopathological evaluation of excised tumors. Statistical significance is indicated as *** p < 0.001, scale bar = 50μm.

Article Snippet: The pancreatic ductal adenocarcinoma cell line PANC-1 was obtained from the American Type Culture Collection.

Techniques: In Vivo