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INTRODUCTION: Organoids are three-dimensional cellular aggregates derived from stem cells or primary tissues that can self-organize into organotypic structures and showcase the physiological functions of that organ. Organoids typically comprise multiple organ-specific cell types that are responsible for organ function in vivo. They may also incorporate various cellular and molecular stromal components to recapitulate the in vivo microenvironment of the target organ. METHODS: All articles related to thyroid-like organs were synthesized. Articles published between 1959 and 2023 were assessed, categorized, and analyzed using relevant keywords. RESULTS: As such, organoids provide a model of greater physiological relevance than 2D cell culture for basic and translational research. Murine and human organoids of the thyroid have been established from embryonic stem cells (ESCs), pluripotent stem cells (PSCs) and from various healthy or diseased thyroid tissues. These thyroid organoids have been used in basic and translation research on thyroid-related diseases including hyperthyroidism, Graves' disease, and Hashimoto's thyroiditis. In addition, organoids derived from patients with thyroid cancer retain histopathological features and mutational profile of the original tumor. These patient-derived organoids have been successfully used in in vitro evaluation of drug response of individual patients, demonstrating their potential application in personalized treatment of thyroid cancer. CONCLUSION: In this review article, we have discussed various techniques for establishing thyroid organoids and their applications in thyroid-related diseases as disease models, regenerative medicines, or a tool for drug testing.
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Protected area are the cornerstone of biodiversity and ecosystem service conservation at the local, regional, and global levels. In 2019, China proposed the establishment of a nature reserve system (NRS)centered on national parks, integrating and improving various existing protected areas. This study focuses on the QinlingâDaba Mountains, an area crucial for both biodiversity and ecosystem services. Through assessments of carbon storage (CS), water yield (WY), soil conservation (SC), and habitat quality (HQ), different conservation scenarios are considered in the context of Systematic conservation planning (SCP). An optimization scheme for the NRS in the Qinling-Daba Mountains is proposed, incorporating ecosystem services and comparing them with the existing system. Research indicates that the main protected areas are concentrated in the Min MountainâMotian MountainâLongmen Mountain region, the central Qinling region, and the ShennongjiaâDaba Mountain region. Compared with the original system, the area of protected regions in the NRS expanded by 52,000 km2 after the SCP scheme was incorporated. The number of patches decreased to 50, and the patch density reduced from 2.1 × 10-4(/100 ha) to 1.7 × 10-4(/100 ha), thereby reducing the fragmentation of the conservation system. Additionally, the optimized scheme achieved a conservation ratio of over 30% for CS, WY, SC, and HQ, with the conservation efficiency for WY and HQ increasing by 0.18 and 0.22, respectively. The study results provide support for optimizing the Qinling-Daba Mountains NRS and offer a reference for constructing NRSs in other regions. Considering ecosystem services in the optimization of the NRS helps enhance the supply capacity of ecological products, maintain national ecological security, and achieve harmonious coexistence and sustainable development between humans and nature.
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Pig farming is a major source of carbon emissions in China's livestock industry, and the promotion and application of carbon neutral technologies dedicated to carbon reduction and sequestration is a key measure to promote the realization of carbon neutrality in pig farming industry. In the absence of a system for carbon emission reduction in agriculture, it is important to explore whether large-scale pig farming can spontaneously promote the application of carbon neutral technologies by pig farmers. Combined with the technical background of carbon neutrality in pig farming industry and using the field survey data of 468 pig farmers in Shandong Province, this paper empirically analyzed the effect of large-scale pig farming on the carbon neutral behavior of pig farmers. The findings are threefold. Firstly, because of the effect of economies of scale in the application of carbon neutral technologies, large-scale pig farming can promote the carbon neutral behavior of pig farmers. However, the effect of economies of scale in the application of carbon neutral technologies has a boundary, and the annual output of pigs should be maintained at 3000 to 4999. Secondly, among the effects of pig breeding scale on the application and its degree of composting project, state of planting and breeding cycle has no regulating effect. Thirdly, among the effects of pig breeding scale on the application and its degree of biogas engineering, both state of planting and breeding cycle and subsidy for construction of biogas digester have negative regulating effects. In this paper, the pig farming industry is taken as a typical example to reveal the endogenous incentive mechanism of promoting agricultural carbon emission reduction, which provides theoretical reference and experience enlightenment for the formulation of effective policies to promote agricultural carbon neutrality, which are different from industrial industries.
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Detecting side effects of drugs is a fundamental task in drug development. With the expansion of publicly available biomedical data, researchers have proposed many computational methods for predicting drug-side effect associations (DSAs), among which network-based methods attract wide attention in the biomedical field. However, the problem of data scarcity poses a great challenge for existing DSAs prediction models. Although several data augmentation methods have been proposed to address this issue, most of existing methods employ a random way to manipulate the original networks, which ignores the causality of existence of DSAs, leading to the poor performance on the task of DSAs prediction. In this paper, we propose a counterfactual inference-based data augmentation method for improving the performance of the task. First, we construct a heterogeneous information network (HIN) by integrating multiple biomedical data. Based on the community detection on the HIN, a counterfactual inference-based method is designed to derive augmented links, and an augmented HIN is obtained accordingly. Then, a meta-path-based graph neural network is applied to learn high-quality representations of drugs and side effects, on which the predicted DSAs are obtained. Finally, comprehensive experiments are conducted, and the results demonstrate the effectiveness of the proposed counterfactual inference-based data augmentation for the task of DSAs prediction.
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The Chinese government has pursued comprehensive ecological conservation and restoration by establishing an ecological barrier system. However, the majority of international research tends to focus on the connectivity between habitats, overlooking the functions that ecological barriers play in ecological conservation and restoration. The existing literature lacks a systematic exploration of the theory and practice of ecological barriers. This study employed the literature analysis tool CiteSpace to present the theoretical and developmental trends in ecological barriers from various perspectives, including research fields, historical evolution, research hotspots, and major research nations. By analyzing the differences in the understanding of ecological barriers between China and other countries, examining the ecological barriers construction history in China, and exploring the types and functions of ecological barriers, this study summarizes the framework of China's ecological barriers construction system as "features-functions-problems." Constructing an ecological barrier system can help achieve ecological conservation and restoration goals in China.
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Conservación de los Recursos Naturales , Ecosistema , Conservación de los Recursos Naturales/métodos , China , Ecología , Restauración y Remediación Ambiental/métodosRESUMEN
In recent years, there has been a significant increase in surface ozone (O3) concentrations in the troposphere. Ozone pollution has significant adverse effects on ecosystems, human health, and climate change, particularly on crop growth and yield. This study utilized the observational hourly O3 data, cumulative O3 concentration over 40 ppb per h (AOT40), and the mean daytime 7-h O3 concentration (M7) to analyze the spatiotemporal distributions of relative yield losses (RYLs) and evaluate the yield reduction and economic losses of rice in Sichuan province from 2015 to 2020. The results indicated that the average O3 concentration during the growing rice season ranged from 55.4 to 69.3 µg/m3, with the highest O3 concentration observed in 2017, and the AOT40 ranged from 4.5 to 8.7 ppm h from 2015 to 2020. At the county level, the O3 concentration, AOT40, and the relative yield loss (RYL) of rice based on AOT40 exhibited clear spatiotemporal differences in Sichuan. The RYLs of AOT40 were 4.9-9.2% from 2015 to 2020. According to AOT40 and M7 metrics, the yield loss and economic losses attributed to O3 pollution amounted to 78.75-150.36 (9.74-21.54) ten thousand tons, and 2079.08-4149.89 (257.25-594.45) million Yuan, respectively. Rice yield and economic losses were relatively large in the Chengdu Plain, southern Sichuan, and northeast Sichuan. These findings will contribute to a deeper understanding of the detrimental effects of elevated surface O3 concentrations on rice crops. It is imperative to implement more stringent O3 reduction measures aimed at lowering O3 concentrations, enhancing rice quality, and safeguarding food security in Sichuan.