RESUMEN
The global volume of digital data is expected to reach 175 zettabytes by 2025. The volume, variety and velocity of water-related data are increasing due to large-scale sensor networks and increased attention to topics such as disaster response, water resources management, and climate change. Combined with the growing availability of computational resources and popularity of deep learning, these data are transformed into actionable and practical knowledge, revolutionizing the water industry. In this article, a systematic review of literature is conducted to identify existing research that incorporates deep learning methods in the water sector, with regard to monitoring, management, governance and communication of water resources. The study provides a comprehensive review of state-of-the-art deep learning approaches used in the water industry for generation, prediction, enhancement, and classification tasks, and serves as a guide for how to utilize available deep learning methods for future water resources challenges. Key issues and challenges in the application of these techniques in the water domain are discussed, including the ethics of these technologies for decision-making in water resources management and governance. Finally, we provide recommendations and future directions for the application of deep learning models in hydrology and water resources.
Asunto(s)
Aprendizaje Profundo , Recursos Hídricos , Cambio Climático , HidrologíaRESUMEN
The triphosphates of antiviral 2',3'-dideoxynucleosides (ddNs) are the active chemical species that inhibit viral DNA synthesis. The inhibition involves incorporation of ddNMP into DNA and subsequent chain termination. A conceivable strategy for antiviral drugs is to employ nucleoside 5'-triphosphate mimics that can entirely bypass cellular phosphorylation. AZT 5'-alpha-R(P)-borano-beta,gamma-(difluoromethylene)triphosphate (5'-alphaB-betagammaCF(2)TP) has been identified as a potent inhibitor of HIV-1 reverse transcriptase (HIV-1 RT). This work was aimed at confirming that 5'-alphaB-betagammaCF(2)TP is a useful generic triphosphate moiety and can render antiviral ddNs with potent inhibitory effects on HIV-1 RT. Thus, 10 ddNs were converted to their 5'-alphaB-betagammaCF(2)TPs via a sequence (one-pot) of reactions: formation of an activated phosphite, formation of a cyclic triphosphate, boronation, and hydrolysis. Other synthetic routes were also explored. All ddN 5'-alphaB-betagammaCF(2)TPs tested exhibited essentially the same level of inhibition of HIV-1 RT as the corresponding ddNTPs. A conclusion can be made that 5'-alphaB-betagammaCF(2)TP is a generic and promising triphosphate mimic (P3M) concerning HIV-1 RT inhibition and serum stability. It is anticipated that use of 5'-alphaB-betagammaCF(2)TP as P3M moiety will lead to the discovery of a new class of anti-HIV agents.
Asunto(s)
Fármacos Anti-VIH/síntesis química , Compuestos de Boro/síntesis química , Desoxirribonucleótidos/síntesis química , Transcriptasa Inversa del VIH/metabolismo , Inhibidores de la Transcriptasa Inversa/síntesis química , Animales , Fármacos Anti-VIH/química , Fármacos Anti-VIH/metabolismo , Compuestos de Boro/química , Compuestos de Boro/metabolismo , Bovinos , Desoxirribonucleótidos/química , Desoxirribonucleótidos/metabolismo , Técnicas In Vitro , Inhibidores de la Transcriptasa Inversa/química , Inhibidores de la Transcriptasa Inversa/metabolismo , EstereoisomerismoRESUMEN
Treatment of homoadenosine [9-(5-deoxy-beta-D-ribo-hexofuranosyl)adenine] with thionyl chloride and pyridine in acetonitrile gave 6'-chloro-6'-deoxyhomoadenosine, which underwent nucleophilic displacement with L-cysteine or L-homocysteine to give homologated analogues of S-adenosyl-L-homocysteine. Each amino acid in aqueous sodium hydroxide at 60 degrees C gave excellent conversion from the chloronucleoside, and adsorption on Amberlite XAD-4 resin provided more convenient isolation than prior methods. Weak binding of these non-hydrolyzed analogues to S-adenosyl-L-homocysteine hydrolase was observed.