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Studies have confirmed that tumorigenesis is related to an imbalance of polyamine metabolism and over-expression of oncogenes resulting in the up-regulation of ornithine decarboxylase (ODC, the first rate-limiting enzyme for regulating intracellular polyamines biosynthesis), which has become a target for anti-tumor therapy. In this study, an ornithine derivative, N5-(2-[18F]fluoropropionyl) ornithine (N5-[18F]FPO), has been prepared and its potential utility for tumor PET imaging evaluated. N5-[18F]FPO was successfully prepared via a nucleophilic fluorination reaction and a subsequent efficient deprotection step. The in vitro and in vivo stability were determined by HPLC conducted in fetal bovine serum, saline and rat urine. Cellular uptake studies were conducted in HepG2 cells and the biodistribution and micro-PET/CT imaging performed in normal ICR mice and three tumor-bearing mice models, respectively. Total synthesis time of N5-[18F]FPO was about 80 min with a radiochemical yield of 15% ± 6% (uncorrected, based on 18F−, n = 6) and a high radiochemical stability can be seen in vitro and vivo. The N5-[18F]FPO exhibited fast uptake in HepG2 cells and the cellular uptake ability of N5-[18F]FPO can be inhibited by L-ornithine and DFMO, which indicated that the transport pathway of N5-[18F]FPO is similar to that of L-ornithine, interacting with ODC after being transported into the cell. The biodistribution and micro-PET/CT images demonstrate that N5-[18F]FPO was excreted by the urinary system, and excellent tumor visualization with high tumor-to-background ratios can be observed in the three tumor-bearing mice models studied. All the above results suggest that N5-[18F]FPO has the potential to be a novel radiotracer for imaging ODC expression in solid tumors. [Display omitted] [ABSTRACT FROM AUTHOR]

Given the requirements of high sensitivity and spatial resolution, the development of new positron emission tomography (PET) agents is required for PET renography. The objective of this study was to investigate a new fluorine-18 labeled hippurate analogue of picolinamide, N -(6-[18F]Fluoropyridin-3-yl)glycine, as a new renal PET agent for evaluating renal function. N -(6-[18F]Fluoropyridin-3-yl)glycine was prepared via a two-step reaction, including the nucleophilic substitution reaction of Br with 18F using methyl 2-(6-bromonicotinamido)acetate as a precursor followed the hydrolysis with sodium hydroxide and purification by preparative-HPLC. The in vitro and in vivo stability were determined using HPLC, and the plasma protein binding (PPB) and erythrocyte uptake of N -(6-[18F]Fluoropyridin-3-yl)glycine were determined using blood collected from healthy rats at 5 min post-injection. Biodistribution and dynamic micro-PET/CT imaging studies were conducted in healthy rats. N -(6-[18F]Fluoropyridin-3-yl)glycine was prepared within 45 min with an uncorrected radiochemical yield of 24.5 ± 6.7% (n = 6, based on [18F]F−) and a radiochemical purity of >98%. N -(6-[18F]Fluoropyridin-3-yl)glycine demonstrated good stability both in vitro and in vivo. The results of the biodistribution and dynamic micro-PET/CT imaging studies in normal rats indicated that N -(6-[18F]Fluoropyridin-3-yl)glycine was rapidly and exclusively excreted via the renal-urinary pathway. N -(6-[18F]Fluoropyridin-3-yl)glycine is has been shown to be a promising renal PET agent and warrants further evaluation of renal function. [ABSTRACT FROM AUTHOR]

Mitigating climate change is an urgent global issue, and agricultural carbon emissions are an important component of global emissions. Hence, it is imperative to fully understand the current state of carbon emissions in agriculture and accurately evaluate emissions throughout various farming processes. This review aims to understand and evaluate these emissions, focusing on the agricultural sector. A systematic review of existing literature and data on agricultural carbon emissions was conducted, exploring the potential of innovative technology and approaches for mitigation. The effectiveness of energy-saving carbon emission reduction strategies and the role of technological innovation in achieving environmentally sustainable agriculture were assessed. The findings reveal that sustainable development goals have fostered a global strategy for achieving highly productive, efficient, and environmentally sustainable agriculture. In addition, potential transitions towards more sustainable agricultural practices, driven by technological innovation and effective carbon policies, were identified as significant means for mitigating carbon emissions. In this sense, there is an urgent need for a close global effort to implement carbon policies and technological innovation to mitigate the climate impacts of agriculture. Therefore, this research is a time-noting study to help international policymakers achieve environmental sustainability-oriented policies. [Display omitted] • Mitigating climate change has emerged as a crucial agenda. • Carbon emissions from agriculture contribute to 10–12% of total global emissions. • Global policies and technological innovations drive the reduction of emissions in agriculture. • Carbon policies are crucial for tackling climate change in sustainable agriculture. [ABSTRACT FROM AUTHOR]

Reducing greenhouse gas (GHGs) emissions is imperative to achieve sustainable meat production and supply. Few previous studies have assessed the carbon emissions of the whole meat supply chain from the sheep fattening stage to the meat distribution stage. Therefore, this study established a boundary model of the carbon emission system of the mutton supply chain and adopted the life cycle assessment (LCA) method to comprehensively analyze the carbon emissions during breeding, transportation, processing, and distribution, and then assessed the overall carbon emissions, and optimized the route planning of the supply chain subsystems using improved genetic algorithms (GA) in order to reduce energy consumption and carbon emissions. The results show (1) The fattening sheep process generates a relatively large share of carbon emissions, but the unit emissions are stable. The carbon emissions from the transportation and marketing phases are lower than those from the fattening phase, but their carbon emissions are uncertain, which is the focus of optimization. (2) By optimizing the routes of the subsystems in the life cycle analysis model, carbon emissions due to changes in route planning can be reduced by 24.19%. Therefore, life cycle analysis can comprehensively assess the carbon emissions and total carbon emissions of each link in the mutton supply chain, and the optimization strategy plays an important role in energy consumption and carbon emissions. [Display omitted] • The energy type of transport vehicles is a key factor affecting carbon emissions. • LCA is active in assessing carbon emissions in the meat supply chain. • Optimization strategy can cut carbon emissions and drive sustainable development. • Overall supply chain carbon footprint assessment is good for gaining detailed data. [ABSTRACT FROM AUTHOR]

Flexible sensing technology for food quality control has received some attention in recent years. The aim of this research was to develop a novel flexible sensor to assess the freshness of lamb meat, replacing the traditional rigid sensor and lamb quality indicator testing method. Firstly, a low-cost, high-performance flexible impedance-temperature electrode was prepared based on laser direct writing technology, and a complete flexible temperature-impedance measurement system was built in combination with an STM32 microcontroller. Then, a wireless sensor network (WSN) based micro-environment monitoring platform was developed to measure the quality index of lamb, collect gas information, and impedance information under three temperatures of 0 °C, 4 °C, and 8 °C. As the storage time of lamb increases, its biological tissue structure and intracellular ionic conductive properties change, which can be reflected by the impedance amplitude and phase angle. A machine learning prediction model is established with bio-impedance as the input and freshness as the output. The research found that the variation of lamb freshness was influenced by the storage temperature, and that the impedance mode of the flexible system was able to instantly detect the freshness of lamb with an average prediction accuracy of 91.63% when combined with machine learning algorithms. This is higher than the accuracy of the traditional Arrhenius equation method (83.70%) and comparable to the prediction accuracy of gas information (93.24%). Additionally, the temperature mode of the flexible system was able to continuously monitor temperature changes on the surface of lamb, compensating for the inability of traditional impedance sensors to do so, and providing unique insights into accurate monitoring of lamb temperature changes. This research provides a new solution for improving food quality control during the chilled meat cold chain. • A dual-parameter flexible temperature-impedance sensor based on LIG was developed. • A dual-parameter flexible-impedance measurement system based on WSN was built. • Combined with ML algorithms, the freshness of lamb was successfully predicted at three temperatures. • The flexible system has the potential to qualitatively and quantitatively assess the freshness of lamb. [ABSTRACT FROM AUTHOR]