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111.
Food action plans in many global cities articulate interest in multiple objectives including reducing in‐ and trans‐boundary environmental impacts (water, land, greenhouse gas (GHG)). However, there exist few standardized analytical tools to compare food system characteristics and actions across cities and countries to assess trade‐offs between multiple objectives (i.e., health, equity) with environmental outcomes. This paper demonstrates a streamlined model applied for analysis of four cities with varying characteristics across the United States and India, to quantify system‐wide water, energy/GHG, and land impacts associated with multiple food system actions to address health, equity, and environment. Baseline diet analysis finds key differences between countries in terms of meat consumption (Delhi 4; Pondicherry 16; United States 59, kg/capita/year), and environmental impact of processing of the average diet (21%, 19%, <1%, <1% of community‐wide GHG‐emissions for New York, Minneapolis, Delhi, and Pondicherry). Analysis of supply chains finds city average distance (food‐miles) varies (Delhi 420; Pondicherry 200; United States average 1,640 km/t‐food) and the sensitivity of GHG emissions of food demand to spatial variability of energy intensity of irrigation is greater in Indian than US cities. Analysis also finds greater pre‐consumer waste in India versus larger post‐consumer accumulations in the United States. Despite these differences in food system characteristics, food waste management and diet change consistently emerge as key strategies. Among diet scenarios, all vegetarian diets are not found equal in terms of environmental benefit, with the US Government's recommended vegetarian diet resulting in less benefit than other more focused targeted diet changes. 相似文献
112.
Natural products are important because of their significant pharmaceutical properties such as antiviral, antimicrobial, and anticancer activity. Recent breakthroughs in DNA sequencing reveal that a great number of cryptic natural product biosynthetic gene clusters are encoded in microbial genomes, for example, those of Streptomyces species. However, it is still challenging to access compounds from these clusters because many source organisms are uncultivable or the genes are silent during laboratory cultivation. To address this challenge, we develop an efficient cell-free platform for the rapid, in vitro total biosynthesis of the nonribosomal peptide valinomycin as a model. We achieve this goal in two ways. First, we used a cell-free protein synthesis (CFPS) system to express the entire valinomycin biosynthetic gene cluster (>19 kb) in a single-pot reaction, giving rise to approximately 37 μg/L of valinomycin after optimization. Second, we coupled CFPS with cell-free metabolic engineering system by mixing two enzyme-enriched cell lysates to perform a two-stage biosynthesis. This strategy improved valinomycin production ~5000-fold to nearly 30 mg/L. We expect that cell-free biosynthetic systems will provide a new avenue to express, discover, and characterize natural product gene clusters of interest in vitro. 相似文献
113.
Thdia Evelyn de Araújo Iliana Claudia Balga Milin Guilherme de Souza Rafaela Jos da Silva Alessandra Monteiro Rosini Pmela Mendona Guirelli Priscila Silva Franco Bellisa Freitas Barbosa Eloisa Amlia Vieira Ferro Idessania Nazareth da Costa 《Cell biology international》2020,44(1):36-50
During pregnancy, the placenta regulates the transfer of oxygen, nutrients, and residual products between the maternal and fetal bloodstreams and is a key determinant of fetal exposure to xenobiotics from the mother. To study the disposition of substances through the placenta, various experimental models are used, especially the perfused placenta, placental villi explants, and cell lineage models. In this context, nanotechnology, an area of study that is on the rise, enables the creation of particles on nanometric scales capable of releasing drugs aimed at specific tissues. An important reason for furthering the studies on transplacental transfer is to explore the potential of nanoparticles (NPs), in new delivery strategies for drugs that are specifically aimed at the mother, the placenta, or the fetus and that involve less toxicity. Due to the fact that the placental barrier is essential for the interaction between the maternal and fetal organisms as well as the possibility of NPs being used in the treatment of various pathologies, the aim of this review is to present the main experimental models used in studying the maternal–fetal interaction and the action of NPs in the placental environment. 相似文献
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This review presents a modern perspective on dynamical systems in the context of current goals and open challenges. In particular, our review focuses on the key challenges of discovering dynamics from data and finding data-driven representations that make nonlinear systems amenable to linear analysis. We explore various challenges in modern dynamical systems, along with emerging techniques in data science and machine learning to tackle them. The two chief challenges are (1) nonlinear dynamics and (2) unknown or partially known dynamics. Machine learning is providing new and powerful techniques for both challenges. Dimensionality reduction methods are used for projecting dynamical methods in reduced form, and these methods perform computational efficiency on real-world data. Data-driven models drive to discover the governing equations and give laws of physics. The identification of dynamical systems through deep learning techniques succeeds in inferring physical systems. Machine learning provides advanced new and powerful algorithms for nonlinear dynamics. Advanced deep learning methods like autoencoders, recurrent neural networks, convolutional neural networks, and reinforcement learning are used in modeling of dynamical systems. 相似文献
115.
《Matrix biology》2020
The cells and tissues of the human body are constantly exposed to exogenous and endogenous forces that are referred to as biomechanical cues. They guide and impact cellular processes and cell fate decisions on the nano-, micro- and macro-scale, and are therefore critical for normal tissue development and maintaining tissue homeostasis. Alterations in the extracellular matrix composition of a tissue combined with abnormal mechanosensing and mechanotransduction can aberrantly activate signaling pathways that promote disease development. Such processes are therefore highly relevant for disease modelling or when aiming for the development of novel therapies.In this mini review, we describe the main biomechanical cues that impact cellular fates. We highlight their role during development, homeostasis and in disease. We also discuss current techniques and tools that allow us to study the impact of biomechanical cues on cell and tissue development under physiological conditions, and we point out directions, in which in vitro biomechanics can be of use in the future. 相似文献
116.
《Current biology : CB》2020,30(7):1231-1244.e4
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