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| http://dx.doi.org/10.1245/s10434-023-13557-6 | DOI Listing |
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Adjustment of Molecular Sorption Equilibrium on Catalyst Surface for Boosting Catalysis.
Acc Chem Res
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Key Lab of Biomass Chemical Engineering of Ministry of Education, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China.
ConspectusFor chemical reactions with complex pathways, it is extremely difficult to adjust the catalytic performance. The previous strategies on this issue mainly focused on modifying the fine structures of the catalysts, including optimization of the geometric/electronic structure of the metal nanoparticles (NPs), regulation of the chemical composition/morphology of the supports, and/or adjustment of the metal-support interactions to modulate the reaction kinetics on the catalyst surface. Although significant advances have been achieved, the catalytic performance is still unsatisfactory.
View Article and Find Full Text PDFRecent advances in recombinant production of soluble proteins in E. coli.
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Lab of Environmental and Life Sciences, University of Nova Gorica, Vipavska cesta 13, Nova Gorica, 5000, Slovenia.
Background: E. coli still remains the most commonly used organism to produce recombinant proteins in research labs. This condition is mirrored by the attention that researchers dedicate to understanding the biology behind protein expression, which is then exploited to improve the effectiveness of the technology.
View Article and Find Full Text PDFHigh-reward, high-risk technologies? An ethical and legal account of AI development in healthcare.
BMC Med Ethics
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Faculty of Law, University of Montreal, Ch de la Tour, Montreal, QC, H3T 1J7, Canada.
Background: Considering the disruptive potential of AI technology, its current and future impact in healthcare, as well as healthcare professionals' lack of training in how to use it, the paper summarizes how to approach the challenges of AI from an ethical and legal perspective. It concludes with suggestions for improvements to help healthcare professionals better navigate the AI wave.
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Use of generative large language models for patient education on common surgical conditions: a comparative analysis between ChatGPT and Google Gemini.
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There is a growing importance for patients to easily access information regarding their medical conditions to improve their understanding and participation in health care decisions. Artificial Intelligence (AI) has proven as a fast, efficient, and effective tool in educating patients regarding their health care conditions. The aim of the study is to compare the responses provided by AI tools, ChatGPT and Google Gemini, to assess for conciseness and understandability of information provided for the medical conditions Deep vein thrombosis, decubitus ulcers, and hemorrhoids.
View Article and Find Full Text PDFGestaltGAN: synthetic photorealistic portraits of individuals with rare genetic disorders.
Eur J Hum Genet
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Institute for Genomic Statistics and Bioinformatics, Bonn, NRW, Germany.
The facial gestalt (overall facial morphology) is a characteristic clinical feature in many genetic disorders that is often essential for suspecting and establishing a specific diagnosis. Therefore, publishing images of individuals affected by pathogenic variants in disease-associated genes has been an important part of scientific communication. Furthermore, medical imaging data is also crucial for teaching and training deep-learning models such as GestaltMatcher.
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