Multivalent interactions can be applied universally for a targeted strengthening of an interaction between different interfaces or molecules. The binding partners form cooperative, multiple receptor-ligand interactions that are based on individually weak, noncovalent bonds and are thus generally reversible. Hence, multi- and polyvalent interactions play a decisive role in biological systems for recognition, adhesion, and signal processes. The scientific and practical realization of this principle will be demonstrated by the development of simple artificial and theoretical models, from natural systems to functional, application-oriented systems. In a systematic review of scaffold architectures, the underlying effects and control options will be demonstrated, and suggestions will be given for designing effective multivalent binding systems, as well as for polyvalent therapeutics.
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http://dx.doi.org/10.1002/anie.201201114 | DOI Listing |
Adv Mater
January 2025
Extreme Materials Research Center, Korea Institute of Science and Technology, 14-gil 5 Hwarang-ro, Seongbuk-gu, Seoul, 02792, Republic of Korea.
Hydrogen peroxide (HO) electrosynthesis via the 2e oxygen reduction reaction (ORR) is considered as a cost-effective and safe alternative to the energy-intensive anthraquinone process. However, in more practical environments, namely, the use of neutral media and air-fed cathode environments, slow ORR kinetics and insufficient oxygen supply pose significant challenges to efficient HO production at high current densities. In this work, mesoporous B-doped carbons with novel curved BC active sites, synthesized via a carbon dioxide (CO) reduction using a pore-former agent, to simultaneously achieve excellent 2e ORR activity and improved mass transfer properties are introduced.
View Article and Find Full Text PDFExtracell Vesicles Circ Nucl Acids
October 2024
Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA 02114, USA.
The intertwined nature of cardiac and renal failure, where dysfunction in one organ predicts a poor outcome in the other, has long driven the interest in uncovering the exact molecular links between the two. Elucidating the mechanisms driving Cardiorenal Syndrome (CRS) will enable the development of targeted therapies that disrupt this detrimental cycle, potentially improving outcomes for patients. A recent study by Chatterjee .
View Article and Find Full Text PDFHardwareX
March 2025
Industrial Design Engineering, Delft University of Technology, Delft, the Netherlands.
Negative Pressure Wound Therapy (NPWT) is a treatment that promotes healing of chronic wounds. Despite high prevalence of chronic wounds in Low- and Middle-Income Countries (LMICs), NPWT devices are not available nor affordable. This study aims to improve chronic wound care in LMICs by presenting the Wound Care (WOCA) system, designed for building, testing and use in LMICs.
View Article and Find Full Text PDFData Brief
February 2025
Tashkent institute of textile and light industry, 5, Shoxdjaxon str., Tashkent city 100100, Uzbekistan.
In this study, the authors presented a dataset for named entity recognition in the Uzbek language. The dataset consists of 2000 sentences and 25,865 words, and the sources were legal documents and hand-crafted sentences annotated using the BIOES scheme. The study is complemented by the fact that the authors demonstrated the applications of the created dataset by training a language model using the CNN + LSTM architecture, which achieves high accuracy in NER tasks, with an F1 score of 90.
View Article and Find Full Text PDFJ Phys Chem C Nanomater Interfaces
January 2025
Materials Chemistry and Catalysis, Debye Institute for Nanomaterials Science, Utrecht University, Utrecht 3584 CG, The Netherlands.
Machine learning potentials (MLPs) offer efficient and accurate material simulations, but constructing the reference ab initio database remains a significant challenge, particularly for catalyst-adsorbate systems. Training an MLP with a small data set can lead to overfitting, thus limiting its practical applications. This study explores the feasibility of developing computationally cost-effective and accurate MLPs for catalyst-adsorbate systems with a limited number of ab initio references by leveraging a transfer learning strategy from subsets of a comprehensive public database.
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