Robust Electroreduction of CO<sub>2</sub> at a Poly(4‐vinylpyridine)–Copper ElectrodeAbstract The development of efficient and robust catalysts based on earth‐abundant and nontoxic materials is critical for the viability of the electrocatalytic conversion of CO 2 into useful chemicals. Herein, we report a new class of electrocatalysts with incorporated mechanisms of their stabilization. A Cu electrode coated with a poly(4‐vinyl pyridine) film synthesizes formate at a faradaic efficiency of 40 % at an overpotential of −0.67 V, and its catalytic activity does not degrade after 30 h of operation. We attribute the outstanding catalytic properties of the new hybrid material to the formation of Cu–polymer complexes, as well as to new intrinsic mechanisms of the electrode stabilization offered by the N ‐heteroaromatic polymer. This is the first report of CO 2 electroreduction with copper– N ‐heteroaromatic ligand complexes. More generally, our study offers a new simple strategy to design and prepare robust CO 2 reduction electrocatalysts based on earth‐abundant metals.
JASPAR 2026: expansion of transcription factor binding profiles and integration of deep learning modelsJASPAR (https://jaspar.elixir.no/) is an open-access database that has provided high-quality, manually curated, and non-redundant DNA binding profiles for transcription factors (TFs) as position frequency matrices (PFMs) for over 20 years. We expanded the CORE (306 new profiles, 12% increase) and UNVALIDATED (433, 60% increase) collections with new PFMs and updated 13 existing profiles. We updated the TF binding site predictions and genome tracks for eight species. TF binding profile clusters and familial TF binding sites were updated accordingly. We integrate the inMOTIFin software to easily simulate regulatory sequences using JASPAR PFMs. To enrich TFs' annotations, we provide scientific literature-based human TF target information. Notably, this release features a deep learning (DL) collection, providing a paradigm shift in modeling and characterizing TF-DNA interactions with 1259 BPNet models trained on Homo sapiens ENCODE chromatin immunoprecipitation followed by sequencing (ChIP-seq) datasets from 240 TFs and interpreted to reveal predictive motif patterns for the models. The motifs associated with the same TF were clustered to provide a summary of the binding properties, resulting in 240 primary and 113 alternative motif patterns in the DL collection. The JASPAR 2026 collections lay a foundation for future endeavors in genomic research, serving the scientific community in uncovering the mechanisms of gene regulation.