Self-replication is a capacity common to every species of living thing, and simple physical intuition dictates that such a process must invariably be fueled by the production of entropy. Here, we undertake to make this intuition rigorous and quantitative by deriving a lower bound for the amount of heat that is produced during a process of self-replication in a system coupled to a thermal bath. We find that the minimum value for the physically allowed rate of heat production is determined by the growth rate, internal entropy, and durability of the replicator, and we discuss the implications of this finding for bacterial cell division, as well as for the pre-biotic emergence of self-replicating nucleic acids.
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http://dx.doi.org/10.1063/1.4818538 | DOI Listing |
Nucleic Acids Res
January 2025
London Institute for Mathematical Sciences Royal Institution, 21 Albemarle St, London W1S 4BS, UK.
Recent advancements in genomics, propelled by artificial intelligence, have unlocked unprecedented capabilities in interpreting genomic sequences, mitigating the need for exhaustive experimental analysis of complex, intertwined molecular processes inherent in DNA function. A significant challenge, however, resides in accurately decoding genomic sequences, which inherently involves comprehending rich contextual information dispersed across thousands of nucleotides. To address this need, we introduce GENA language model (GENA-LM), a suite of transformer-based foundational DNA language models capable of handling input lengths up to 36 000 base pairs.
View Article and Find Full Text PDFActa Med Philipp
December 2024
Department of Physics, School of Science and Engineering, Ateneo de Manila University, Quezon City, Philippines.
Background And Objective: The adoption of electronic medical records (EMRs) in the Philippines has been initiated and adjusted since the last decade through the Philippine eHealth Agenda framework. EMRs are known to improve clinical management and have been widely adopted in advanced economies. However, empirical research on EMR implementation remains limited.
View Article and Find Full Text PDFACS Energy Lett
January 2025
Department of Materials, Imperial College London, Exhibition Road, London SW7 2AZ, U.K.
Antimony sulfide (SbS) is a promising candidate as an absorber layer for single-junction solar cells and the top subcell in tandem solar cells. However, the power conversion efficiency of SbS-based solar cells has remained stagnant over the past decade, largely due to trap-assisted nonradiative recombination. Here we assess the trap-limited conversion efficiency of SbS by investigating nonradiative carrier capture rates for intrinsic point defects using first-principles calculations and Sah-Shockley statistics.
View Article and Find Full Text PDFNarra J
December 2024
Department of Pharmacy, Faculty of Mathematics and Natural Sciences, Universitas Syiah Kuala, Banda Aceh, Indonesia.
Psoriasis is a chronic skin condition with challenges in the accurate assessment of its severity due to subtle differences between severity levels. The aim of this study was to evaluate deep learning models for automated classification of psoriasis severity. A dataset containing 1,546 clinical images was subjected to pre-processing techniques, including cropping and applying noise reduction through median filtering.
View Article and Find Full Text PDFSci Rep
January 2025
The BioRobotics Institute, Scuola Superiore Sant'Anna, Pontedera, Pisa, Italy.
Millions of individuals surviving a stroke have lifelong gait impairments that reduce their personal independence and quality of life. Reduced walking speed is one of the major problems limiting community mobility and reintegration. Previous studies have shown positive effect of robot-assisted gait training utilizing hip exoskeletons for individuals with gait impairments due to a stroke, leading to increased walking speed in post-treatment compared to pre-treatment assessments.
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