STAN, a computational framework for inferring spatially informed transcription factor activity across cellular contexts.

Transcription factors (TFs) drive significant cellular changes in response to environmental cues and intercellular signaling. Neighboring cells influence TF activity and, consequently, cellular fate and function. Spatial transcriptomics (ST) captures mRNA expression patterns across tissue samples, enabling characterization of the local microenvironment. However, these datasets have not been fully leveraged to systematically estimate TF activity governing cell identity. Here, we present STAN ( S patially informed T ranscription factor A ctivity N etwork), a linear mixed-effects computational method that predicts spot-specific, spatially informed TF activities by integrating curated TF-target gene priors, mRNA expression, spatial coordinates, and morphological features from corresponding imaging data. We tested STAN using lymph node, breast cancer, and glioblastoma ST datasets to demonstrate its applicability by identifying TFs associated with specific cell types, spatial domains, pathological regions, and ligand-receptor pairs. STAN augments the utility of ST to reveal the intricate interplay between TFs and spatial organization across a spectrum of cellular contexts.

Effective Technique and Mechanism for Simultaneous Adsorption of As(III/V) from Wastewater by Fe-ZIF-8@MXene.

Arsenic (As) contamination of surface water has become a global concern, especially for the third world countries, and it is imperative to develop advanced materials and an effective treatment method to address the issue. In this paper, iron doped ZIF-8@MXene (Fe-ZIF-8@MXene) was prepared as a potential adsorbent to effectively and simultaneously remove As(III/V) from wastewater. To investigate this, Fe-ZIF-8@MXene was characterized before and after the removal of mixed As(III/V). The results of Fourier transform infrared (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), specific surface area (BET) and point of zero charge (pHpzc) showed that Fe-ZIF-8@MXene was prepared successfully and kept a stable structure after As(III) and As(V) adsorption. The particle size of Fe-ZIF-8@MXene was in the range of 0.5 µm to 2.5 µm, where its BET was 531.7 m2/g. For both contaminants, adsorption was found to follow pseudo-second-order kinetics and was best-fitted by the Langmuir adsorption model with correlation coefficients (R2) of 0.998 and 0.997, for As(III) and As(V), respectively. The adsorbent was then applied to remove As from two actual water samples, giving maximum removal rates of 91.07% and 98.96% for As(III) and As(V), respectively. Finally, removal mechanisms for As(III/V) by Fe-ZIF-8@MXene were also explored. During the adsorption, multiple complexes were formed under the effect of its abundant surface functional groups involving multiple mechanisms, which included Van der Waals force, surface adsorption, chemical complexation and electrostatic interactions. In conclusion, this study demonstrated that Fe-ZIF-8@MXene was an advanced and reusable material for simultaneous removal of As(III/V) in wastewater.