Hantaviruses represent an important and growing source of disease emergence in both established and developing countries. The New World hantaviruses have been touted as potential biological weapons because of their lethality to humans and high infectivity as an aerosol. It is also important to acknowledge the threat that hantaviruses can represent to US troops that operate in a foreign territory endemic for hantavirus infection, as was demonstrated in the Korean War. Effective vaccines, immunotherapeutics and antivirals for the prophylaxis or treatment of hantaviral infections are not available. Recent evidence that hantaviruses are prone to error catastrophe opens the door to the development of new therapeutic strategies. Possible future directions for applying lethal mutagenesis as a strategy for the development of novel and more effective antiviral therapies for treatment of hantavirus infections are discussed.
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http://dx.doi.org/10.1016/j.virusres.2004.11.009 | DOI Listing |
Biology (Basel)
December 2024
Division of Biochemistry, Faculty of Pharmaceutical Sciences, Tohoku Medical and Pharmaceutical University, Sendai 981-8558, Japan.
We propose a hypothesis for the simultaneous emergence of bacteria, archaea, viruses, and mobile elements by sequential and concrete biochemical pathways. The emergence process can be considered analogous to crystallization, where genetic and biochemical systems stabilize as organisms evolve from their common ancestor, the LUCA, which was a non-free-living pool of single operon type genomes including double-stranded (ds) DNA at an ancient submarine alkaline vent. Each dsDNA operon was transcribed by different systems in σ, TFIIB, or TBP genomes.
View Article and Find Full Text PDFActa Paediatr
January 2025
Neonatal Intensive Care Unit, Children's Hospital, ASST Spedali Civili Brescia, Brescia, Italy.
Aim: To quantify and categorise retrospectively all adverse events occurring during unplanned neonatal emergency interhospital transfers conducted by the Transfer Service of the Spedali Civili di Brescia over 3 years.
Methods: The revised data were extracted from specific questionnaires filled out by staff. The events were classified according to an adapted retrieval team model (PANSTAR); the risk level was assessed using an effective risk assessment score.
Phys Rev E
November 2024
Université Grenoble Alpes, CEA List, 38000 Grenoble, France.
Models for viral populations with high replication error rates (such as RNA viruses) rely on the quasispecies concept, in which mutational pressure beyond the so-called "error threshold" leads to a loss of essential genetic information and population collapse, an effect known as the "error catastrophe." We explain how crossing this threshold, as a result of increasing mutation rates, can be understood as a second-order phase transition, even in the presence of lethal mutations. In particular, we show that, in fitness landscapes with a single peak, this collapse is equivalent to a ferroparamagnetic transition, where the back-mutation rate plays the role of the external magnetic field.
View Article and Find Full Text PDFTrends Genet
December 2024
Department of Biology, New York University, New York, NY 10003, USA. Electronic address:
Meiotic cells introduce numerous programmed DNA double-strand breaks (DSBs) into their genome to stimulate crossover recombination. DSB numbers must be high enough to ensure each homologous chromosome pair receives the obligate crossover required for accurate meiotic chromosome segregation. However, every DSB also increases the risk of aberrant or incomplete DNA repair, and thus genome instability.
View Article and Find Full Text PDFPeerJ Comput Sci
September 2024
Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia.
Background: The Automatic Essay Score (AES) prediction system is essential in education applications. The AES system uses various textural and grammatical features to investigate the exact score value for AES. The derived features are processed by various linear regressions and classifiers that require the learning pattern to improve the overall score.
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