RESUMEN
Single-cell transcriptomics (scRNA-seq) is revolutionizing biological research, yet it faces challenges such as inefficient transcript capture and noise. To address these challenges, methods like neighbor averaging or graph diffusion are used. These methods often rely on k-nearest neighbor graphs from low-dimensional manifolds. However, scRNA-seq data suffer from the 'curse of dimensionality', leading to the over-smoothing of data when using imputation methods. To overcome this, sc-PHENIX employs a PCA-UMAP diffusion method, which enhances the preservation of data structures and allows for a refined use of PCA dimensions and diffusion parameters (e.g., k-nearest neighbors, exponentiation of the Markov matrix) to minimize noise introduction. This approach enables a more accurate construction of the exponentiated Markov matrix (cell neighborhood graph), surpassing methods like MAGIC. sc-PHENIX significantly mitigates over-smoothing, as validated through various scRNA-seq datasets, demonstrating improved cell phenotype representation. Applied to a multicellular tumor spheroid dataset, sc-PHENIX identified known extreme phenotype states, showcasing its effectiveness. sc-PHENIX is open-source and available for use and modification.
RESUMEN
Lifestyle modifications, metformin, and linagliptin reduce the incidence of type 2 diabetes (T2D) in people with prediabetes. The gut microbiota (GM) may enhance such interventions' efficacy. We determined the effect of linagliptin/metformin (LM) vs metformin (M) on GM composition and its relationship to insulin sensitivity (IS) and pancreatic ß-cell function (Pßf) in patients with prediabetes. A cross-sectional study was conducted at different times: basal, six, and twelve months in 167 Mexican adults with prediabetes. These treatments increased the abundance of GM SCFA-producing bacteria M (Fusicatenibacter and Blautia) and LM (Roseburia, Bifidobacterium, and [Eubacterium] hallii group). We performed a mediation analysis with structural equation models (SEM). In conclusion, M and LM therapies improve insulin sensitivity and Pßf in prediabetics. GM is partially associated with these improvements since the SEM models suggest a weak association between specific bacterial genera and improvements in IS and Pßf.
