Dimensionality reduction (DR) algorithms have been proven useful in various tasks when it comes to exploring high-dimensional data. Being one of the most used DR techniques, t-SNE is often valued for its ability to map nonlinear manifolds and preserving local structures. However, t-SNE produces anonymous axes which lack interpretability. To enhance the interpretability of t-SNE, this work proposes DimenFix-t-SNE, an extension of the existing meta-strategy DimenFix. DimenFix-t-SNE implements DimenFix using t-SNE, explicitly preserving the selected input feature in one of t-SNE's output dimensions. We generalize upon DimenFix by introducing individual ranges for every point and allowing more user control on the "pushing" process. For fixing nominal features in particular, we develop a new pushing mode Rescale, as well as an ordering method for the feature along the fixed axis. The extended method also supports traceable switching between features on the fixed axis, adding to the interactive component. Finally, we implement and test the algorithm as a plugin for ManiVault, providing an interactive and explainable visual analytics tool for high-dimensional data.