Fast reversible single-step method for enhanced band contrast of polyacrylamide gels for automated detection

The role of Antibody Vκ Framework 3 region towards Antigen binding: Effects on recombinant production and Protein L binding

Antibody research has traditionally focused on heavy chains, often neglecting the important complementary role of light chains in antibody formation and secretion. In the light chain, the complementarity-determining region 3 (VL-CDR3) is specifically implicated in disease states. By modulating VL-CDR3 exposure on the scaffold through deletions in the framework region 3 (VL-FWR3), we further investigated the effects on secretion in recombinant production and antigen binding kinetics. Our random deletions of two residues in the VL-FWR3 of a Trastuzumab model showed that the single deletions could impact recombinant production without significant effect on Her2 binding. When both the selected residues were deleted, antibody secretion was additively decreased, and so was Her2 binding kinetics. Interestingly, we also found allosteric effects on the Protein L binding site at VL-FWR1 elicited by these deletions in VL- FWR3. Together, these findings demonstrate the importance of light chain FWR3 in antigen binding, recombinant production, and antibody purification using Protein L.

Optimal processing for gel electrophoresis images: Applying Monte Carlo Tree Search in GelApp

In biomedical research, gel band size estimation in electrophoresis analysis is a routine process. To facilitate and automate this process, numerous software have been released, notably the GelApp mobile app. However, the band detection accuracy is limited due to a band detection algorithm that cannot adapt to the variations in input images. To address this, we used the Monte Carlo Tree Search with Upper Confidence Bound (MCTS-UCB) method to efficiently search for optimal image processing pipelines for the band detection task, thereby improving the segmentation algorithm. Incorporating this into GelApp, we report a significant enhancement of gel band detection accuracy by 55.9 ± 2.0% for protein polyacrylamide gels, and 35.9 ± 2.5% for DNA SYBR green agarose gels. This implementation is a proof-of-concept in demonstrating MCTS-UCB as a strategy to optimize general image segmentation. The improved version of GelApp-GelApp 2.0-is freely available on both Google Play Store (for Android platform), and Apple App Store (for iOS platform).