Polymer syntheses in a high throughput format are still challenging due to the tedious procedures for prior deoxygenation and catalyst removal. 2D metal-organic framework (MOF) nanosheets are advantageous for elevating the catalytic efficiency and catalyst recyclability. Polymerization of a wide variety of monomers, including hydrophilic acrylamides and hydrophobic acrylates, is attempted directly in a multi-well plate by employing Zn-ZnPPF-2D nanosheets (PPF = porphyrin paddlewheel framework) as a heterogeneous photocatalyst. Various parameters such as monomer concentration, catalyst concentration, and light wavelength are investigated with respect to their effects on polymerization rate and the degree of control over the molecular weight and molecular weight distribution. Due to the larger surface area and more accessible catalytic sites, the top-performing Zn-ZnPPF-2D exhibits fast polymerization kinetics over the Zn-ZnPPF-3D bulk crystals. In addition, the synthesis of triblock copolymers with a single loading of catalysts confirms the outstanding catalytic performance of these 2D MOF catalysts. Finally, photopolymerization is demonstrated to be achievable entirely in a microliter-scale human cell culture medium. As such, this strategy provides high levels of control and precision over macromolecular synthesis outcomes that best align with the requirements of high throughput approaches toward biological applications.
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http://dx.doi.org/10.1002/marc.202200020 | DOI Listing |
Front Plant Sci
January 2025
College of Forestry, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China.
Introduction: Plant physiology response and adaptation to drought stress has become a hotspot in plant ecology and evolution. possesses high ecological, ornamental and economic benefits. It has large root system and tolerance to cold, drought and poor soil.
View Article and Find Full Text PDFIran J Basic Med Sci
January 2025
Graduate school, Shenyang Medical College, Shenyang. No. 146, Huanghe North Street, Shenyang, People's Republic of China.
Objectives: Particulate matter 2.5 (PM2.5), particles with an aerodynamic diameter less than 2.
View Article and Find Full Text PDFRNA velocities and generalizations emerge as powerful approaches for extracting time-resolved information from high-throughput snapshot single-cell data. Yet, several inherent limitations restrict applying the approaches to genes not suitable for RNA velocity inference due to complex transcriptional dynamics, low expression, or lacking splicing dynamics, or data of non-transcriptomic modality. Here, we present GraphVelo, a graph-based machine learning procedure that uses as input the RNA velocities inferred from existing methods and infers velocity vectors lying in the tangent space of the low-dimensional manifold formed by the single cell data.
View Article and Find Full Text PDFActa Naturae
January 2024
Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, 117997 Russian Federation.
The growing incidence of infections caused by antibiotic-resistant strains of pathogens is one of the key challenges of the 21 century. The development of novel technological platforms based on single-cell analysis of antibacterial activity at the whole-microbiome level enables the transition to massive screening of antimicrobial agents with various mechanisms of action. The microbiome of wild animals remains largely underinvestigated.
View Article and Find Full Text PDFActa Naturae
January 2024
Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, 117997 Russian Federation.
Despite the achievements brought about by high-throughput screening technologies, there is still a lack of effective platforms to be used to search for new antimicrobial drugs. The antimicrobial activity of compounds continues, for the most part, to be assessed mainly using pathogen cultures, a situation which does not make easy a detailed investigation of the molecular mechanisms underlying host-pathogen interactions. testing of promising compounds using chordate models is labor-intensive and expensive and, therefore, is used in preclinical studies of selected drug candidates but not in primary screening.
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