CEUS LI-RADS in Combination With the Serum Biomarker-Based ASAP Model Improves the Diagnostic Performance of HCC in High-Risk Patients.

OBJECTIVE: To assess the diagnostic efficacy of the CEUS LI-RADS combined with a model constructed on the basis of age, sex, AFP, and PIVKA-II (ASAP) for the diagnosis of HCC in high-risk patients. METHODS: This retrospective study included 366 liver lesions from 366 patients who underwent liver CEUS. All liver lesions were characterized and categorized according to CEUS LI-RADS v2017. Two modified methods were applied: LR-3/4/M nodules accompanied by AFP > 200 ng/mL (Criterion 2) or ASAP model score > 0.5256 and CA 19-9 in the normal range (Criterion 3) were recategorized as LR-5. The reference criteria included histopathological or comprehensive imaging and the clinical follow-up results. The diagnostic performance was evaluated and compared by the sensitivity, specificity, PPV, and NPV. RESULTS: The incidence of HCC in LR-3, LR-4, LR-5, and LR-M was 33.3% (4/12), 86.4% (38/44), 98.5% (191/194) and 82.7% (81/98), respectively. After using Criterion 2 compared to CEUS LI-RADS v2017, the sensitivity of the modified LR-5 for diagnosing HCC increased from 60.8% to 70.7% (p < 0.01) with little effect on its specificity (94.2% vs. 92.3%, p = 1.00) or PPV (98.5% vs. 98.2%, p = 0.86). After using Criterion 3, the sensitivity of the modified LR-5 for the diagnosis of HCC was further improved to 86.9% (p < 0.01), and its specificity and PPV were not significantly changed (92.3% and 98.6%, both p > 0.05). CONCLUSION: CEUS LI-RADS combined with the serum biomarker-based ASAP model improved the sensitivity of LR-5 in diagnosing HCC with little effect on its specificity and PPV.

Low-carbon city construction, spatial spillovers and greenhouse gas emission performance: Evidence from Chinese cities.

Low-carbon cities (LCC) are conducive to low-carbon development and reshaping the urban economic growth model. However, it is still unknown whether it has a synergistic mitigation effect on other greenhouse gases (GHGs). In this study, a dataset comprising 283 Chinese cities spanning the period 2003 to 2019 is chosen. We employ spatial difference-in-difference (SDID) modeling to investigate both the impacts and mechanisms of LCC on GHG emissions performance. The results show that (1) LCC notably lowers local GHG emissions, enhances emission efficiency, and improves GHG emissions performance in neighboring cities within a 1000 km radius. (2) LCC indirectly enhances the GHG emissions performance of local and neighboring cities through energy intensity and green technology innovation. Notably, LCC boosts the local GHG emissions performance by industrial structure upgrading and resource allocation but harms the positive spillover effects on nearby cities due to the siphoning effect. (3) The effect and spatial impact of LCC on GHG emission performance is notably pronounced in eastern cities, non-resource cities, and key environmental protection areas. The results of the study will further promote the development of LCC and provide an important decision-making reference for urban low-carbon sustainability.

Assessing the digital economy and its effect on carbon performance: the case of China.

With China's carbon neutrality target and the rapid growth of the digital economy, it is critical to understand how the digital economy can decouple economic growth from carbon emissions. This paper innovatively calculates the digital economy index in China from 2004 to 2019 and explores how the digital economy affects total factor carbon productivity (TFCP) and its spatial spillover effect. The empirical results indicate that (1) the development level of digital economy in eastern provinces is significantly higher than that in other provinces. (2) The digital economy positively promotes TFCP. Interestingly, digital industrialization has a more substantial effect on improving TFCP, while industry digitization has a weaker effect. (3) The digital economy not only helps improve the local TFCP but also has spatial spillovers to the surrounding areas and has the most prominent effect on the TFCP of the northern. (4) The digital economy affects TFCP through four channels industrial digital upgrading, human capital, market integration, and resource allocation. (5) The effects of the digital economy on TFCP exhibit significant heterogeneity in terms of time, region, and pollution degree. The findings of this study have important policy implications for promoting the transition to the digital economy and low-carbon development.

Toward carbon neutrality: a bibliometric analysis of technological innovation and global emission reductions.

In the context of global carbon neutrality, climate change mitigation and response has become a top priority. Currently, countries around the world are setting emission reduction targets or are already involved in carbon-neutral actions, with technological innovation becoming the key to global emission reduction. Therefore, a systematic review of the literature related to technology innovation and emission reduction in response to carbon-neutral actions for climate change is conducted. A global bibliometric visualization analysis is presented using CiteSpace and VOSviewer software. This study visualizes the basic relationship between global emission reduction and technology-related literature under the carbon neutrality target and analyzes and discusses the spatial distribution and hotspot trends of the co-author network and knowledge base. The results show that (1) the trend of the number of relevant studies can be divided into two phases before and after, and starts to increase gradually after 2020. (2) The structural relationship of the author- and institution-based cooperative networks is relatively loose, and the main cooperative networks, mainly by countries, are initially formed by the key contributions of developed and emerging economies. (3) Relevant research hotspots are reflected in multiple perspectives such as investment, management, and policy, in addition to emission reduction targets and technological innovation itself. The causal relationship between relevant research and economic and political dimensions has become an important driving factor for research development. Especially in the paradigm shift phase, there are research characteristics of human intervention and specific actions. (4) In terms of future trends, research involving policy management, methodological efficiency, and systemic models will become important research paths in the future by matching the supply of actions to real needs.

Knowledge domain and emerging trends of carbon footprint in the field of climate change and energy use: a bibliometric analysis.

Carbon footprint (CF) research has attained tremendous popularity for improving the climate environment purposes. In particular, current energy use has been identified as the main cause of climate change. CF plays an irreplaceable role in managing energy use, reducing gas emissions, and improving climate change. The objective of this study was to review studies that have developed CF and to perform a bibliometric analysis using two key terms: "climate change" and "energy use". From bibliometric analysis using CiteSpace and VOSviewer, it was possible to establish a knowledge map of cooperative network structure and research evolution. We are aiming to reveal the main logical chain of CF research leading to climate change, to make up for the lack of current literature, and provide research inspiration for researchers. The research findings mainly focus on four aspects. First, the relevant research began in 2008 and is in a state of continuous rise. Second, due to the law of research development and the prominence of practical problems, related research has experienced a stage from conceptual methods to specific problems. Third, China and the USA assume an important role in which international cooperation is the overall trend. Fourth, related research can be divided into CF algorithm research, ecological environment management research, and specific cross-industry fields. In addition, possible opportunities for change in related research are explored. It is also suggested that the integration of CF with other footprints, when energy use and environmental change are fully considered, may become an important future research trend by providing a more comprehensive environmental impact.

Multiple effects of ICT investment on carbon emissions: evidence from China.

Little research has been conducted on the multiple possible future environmental effects of different types of information and communication technology (ICT) investment. This paper innovatively calculates the ICT productive capital stock (PCS) in China from 2007 to 2018 and explores the multiple effects of ICT PCS on carbon emissions. The results show that (1) ICT PCS is conducive to carbon emission reduction; furthermore, ICT software PCS has a significant carbon emission reduction effect, while ICT hardware PCS has the opposite outcome. (2) The spatial effect demonstrates that ICT and its hardware and software PCS can significantly reduce carbon emissions in surrounding areas. (3) The ICT PCS indirectly affects carbon emissions through the digital economy and energy efficiency, but the role of the influence mechanism varies according to the type of ICT PCS. (4) There is a nonlinear relationship between all ICT PCS and carbon emissions due to differences in green productivity and ICT PCS levels. Finally, this study provides valuable references for optimizing ICT investment and promoting low-carbon development.