ObjectiveTo examine the influencing mechanisms and regional differences in accessible facility utilization behavior among residents in eastern and central-western China. MethodsData were collected through the online questionnaire administered to residents across China using snowball sampling. Descriptive analysis and chi-square tests were conducted to compare the basic characteristics of respondents between the two regions. Welch's t test was used to compare accessible facility utilization behavior and its influencing factors. Multigroup structural equation modeling (SEM) was applied to compare the influencing mechanisms of accessible facility utilization behavior between eastern and central-western China. ResultsA total of 1 039 valid responses were obtained, including 604 from the eastern region and 435 from the central-western region. Residents in eastern regions scored significantly higher than those in central-western regions on both facility-seeking (t = 4.057, P < 0.001) and actual-using (t = 4.551, P < 0.001) behavior. The structural equation models for both regions showed identical and satisfactory goodness-of-fit indices (GFI = 0.950, AGFI = 0.932, IFI = 0.947, CFI = 0.947, RMSEA = 0.028), and all measurement and structural invariance tests met the recommended criteria. Facility configuration showed no significant direct effect on utilization behavior in eastern China, whereas a negative direct effect was observed in central-western China (β = -0.171, P = 0.047), with its influence mainly exerted indirectly through social cognition and user experience. Social cognition and user experience had significant positive effects on utilization behavior (P < 0.001). Meanwhile, social cognition indirectly influences utilization behavior through the mediating path of usage experience. The direct effects of social cognition (β = 0.406) and user experience (β = 0.510) in central-western China were greater than those in eastern China (β = 0.369 and β = 0.335, respectively). The chain mediation effect of "configuration-cognition-experience-behavior" was statistically significant in both regions (P < 0.05), with larger indirect effects observed in central-western China. ConclusionFacility configuration has a limited direct effect on accessible facility utilization, whereas social cognition and user experience play a central role, particularly in central-western China. It is recommended that the construction and renovation of accessible facility be guided by population needs, accompanied by strengthened promotion of accessibility concepts and policies, and that a transition from hardware-oriented construction to service- and management-oriented governance of accessible environments should be promoted in central-western China.

Despite therapy with potent antiviral agents, chronic hepatitis B (CHB) patients remain at high risk of hepatocellular carcinoma (HCC). While metabolites have been rediscovered as active drivers of biological processes including carcinogenesis, the specific metabolites modulating HCC risk in CHB patients are largely unknown. Here, we demonstrate that baseline plasma from CHB patients who later developed HCC during follow-up exhibits growth-promoting properties in a case-control design nested within a large-scale, prospective cohort. Metabolomics analysis reveals a reduction in long-chain acylcarnitines (LCACs) in the baseline plasma of patients with HCC development. LCACs preferentially inhibit the proliferation of HCC cells in vitro at a physiological concentration and prevent the occurrence of HCC in vivo without hepatorenal toxicity. Uptake and metabolism of circulating LCACs increase the intracellular level of acetyl coenzyme A, which upregulates histone H3 Lys14 acetylation at the promoter region of KLF6 gene and thereby activates KLF6/p21 pathway. Indeed, blocking LCAC metabolism attenuates the difference in KLF6/p21 expression induced by baseline plasma of HCC/non-HCC patients. The deficiency of circulating LCACs represents a driver of HCC in CHB patients with viral control. These insights provide a promising direction for developing therapeutic strategies to reduce HCC risk further in the antiviral era.

Objective:To analyze and discuss the implementation of the National Science Funds for Distinguished and Excellent Young Scientists in the past 10 years, and propose suggestions for future developments.Methods:The application and funding data of the National Science Funds for Distinguished and Excellent Young Scientists from 2010 to 2019 were collected. Both the distribution in each subdivision field and the age, gender, title and academic rank of the awardees were analyzed. The funds received before the Distinguished Young Scientists and the funds got after Excellent Young Scientists were discussed respectively.Results:There were Distinguished Young Scientists in field of medical imaging each year with an average funding rate of 10.3%(15/145). The funding rate of Excellent Young Scientists in field of medical imaging was higher than the average in the years of 2012-2014 and 2019. The application amounts of molecular imaging, MRI and medical imaging data processing and analyzing reached the top three positions. As far as the funding amount was concerned, ultrasound (4), molecular imaging (4) and MRI (3) for Distinguished Young Scientists, and medical imaging data processing and analyzing (6), molecular imaging (5) and MRI (4) for Excellent Young Scientists were in the first three priorities respectively. As far as the application and funding of the two projects were concerned, there was obvious difference among different supporting institutions. Certain similar growth characteristics remained for the project directors. Good accumulation of scientific achievements was demanded for the Distinguished Young Scientists. The Excellent Young Scientists grew well after being awarded.Conclusion:The National Science Funds for Distinguished and Excellent Young Scientists promote the development of medical imaging and help to cultivate the young talents.

Objective:To analyze the key projects in medical imaging and biomedical engineering area funded by national natural science foundation of China (NSFC) in the past ten years, so as to provide reference of application for scientific researchers.Methods:The funded projects through fund code H18 (medical imaging and biomedical engineering) of NSFC during 2010 to 2019 was analyzed. The funded fields, geographical distribution, research direction, applicants, supporting institutions, and the characteristics and trends of key researches were summarized.Results:A total of 68 projects were funded under H18, including 58 in projected area and 10 in non-projected area. The average funding rate was 19.0% (68/358) in the last ten years. Institutions of higher learning received 51 grants while scientific research institutes had 17. Thirty-seven supporting institutions received H18 key project funding, among which 22 received 1 grant and 15 received 2 or more. There were 51 (75%) male project leaders and 17 (25%) female leaders. The age of project leaders ranged from 35-66 years. Among the project leaders of H18 key funded projects, 52 leaders were approved once, and 8 were approved twice. The average interval between two approved key projects was 5.8 years.Conclusions:Since the establishment of the Department of Health Sciences in 2009, the sum of the fund and the number of the funded key projects in imaging medicine and biomedical engineering field have increased year by year. With the joint efforts of the majority of clinical workers and scientific researchers, research in this domain will achieve rapid development in our country.

Objective:To investigate the current funding landscape of medical artificial intelligence (AI) projects in National Natural Science Foundation of China (NSFC) from 2015 to 2019.Methods:From 2015 to 2019, AI-related projects in NSFC Medical Science Department were collected. Comprehensive analysis was performed in the projects information including year, title, supporting institution, fund type, research findings, etc.Results:NSFC has funded a total of 278 projects related to artificial intelligence, with the total funding amount of 139 million yuan. The number of projects and the funding amount were increasing year by year. Among these, 90% (249/278) were general programs and young scientist funds; 53% (148/278) of the projects were regionally distributed in Beijing, Shanghai and Guangdong; 66% (184/278) of the projects were imaging-related researches; the projects mainly focused on diseases with high incidence in China, including neoplastic diseases, cardiovascular and nervous system diseases.Conclusion:The AI-related projects funded by NSFC are characterized by rapid growth in number and fund amounts, wide coverage of disciplines, and diverse types of research diseases. However, the unbalanced distribution of regions, research fields, and supporting institutions demands more attention in future.

The mini-review stemmed from a recent meeting on national aging research strategies in China discusses the components and challenges of aging research in China. Highlighted are the major efforts of a number of research teams, funding situations and outstanding examples of recent major research achievements. Finally, authors discuss potential targets and strategies of aging research in China.
Aging ; Animals ; Biomedical Research ; China ; Humans