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Background: Due to emerging issues such as global climate change and zoonotic disease pandemics, the One Health approach has gained more attention since the turn of the 21st century. Although One Health thinking has deep roots and early applications in Chinese history, significant gaps exist in China's real-world implementation at the complex interface of the human-animal-environment. Methods: We abstracted the data from the global One Health index study and analysed China's performance in selected fields based on Structure-Process-Outcome model. By comparing China to the Belt & Road and G20 countries, the advances and gaps in China's One Health performance were determined and analysed. Findings: For the selected scientific fields, China generally performs better in ensuring food security and controlling antimicrobial resistance and worse in addressing climate change. Based on the SPO model, the "structure" indicators have the highest proportion (80.00%) of high ranking and the "outcome" indicators have the highest proportion (20.00%) of low ranking. When compared with Belt and Road countries, China scores above the median in almost all indicators (16 out of 18) under the selected scientific fields. When compared with G20 countries, China ranks highest in food security (scores 72.56 and ranks 6th), and lowest in climate change (48.74, 11th). Conclusion: Our results indicate that while China has made significant efforts to enhance the application of the One Health approach in national policies, it still faces challenges in translating policies into practical measures. It is recommended that a holistic One Health action framework be established for China in accordance with diverse social and cultural contexts, with a particular emphasis on overcoming data barriers and mobilizing stakeholders both domestically and globally. Implementation mechanisms, with clarified stakeholder responsibilities and incentives, should be improved along with top-level design.
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BACKGROUND: A One Health approach has been increasingly mainstreamed by the international community, as it provides for holistic thinking in recognizing the close links and inter-dependence of the health of humans, animals and the environment. However, the dearth of real-world evidence has hampered application of a One Health approach in shaping policies and practice. This study proposes the development of a potential evaluation tool for One Health performance, in order to contribute to the scientific measurement of One Health approach and the identification of gaps where One Health capacity building is most urgently needed. METHODS: We describe five steps towards a global One Health index (GOHI), including (i) framework formulation; (ii) indicator selection; (iii) database building; (iv) weight determination; and (v) GOHI scores calculation. A cell-like framework for GOHI is proposed, which comprises an external drivers index (EDI), an intrinsic drivers index (IDI) and a core drivers index (CDI). We construct the indicator scheme for GOHI based on this framework after multiple rounds of panel discussions with our expert advisory committee. A fuzzy analytical hierarchy process is adopted to determine the weights for each of the indicators. RESULTS: The weighted indicator scheme of GOHI comprises three first-level indicators, 13 second-level indicators, and 57 third-level indicators. According to the pilot analysis based on the data from more than 200 countries/territories the GOHI scores overall are far from ideal (the highest score of 65.0 out of a maximum score of 100), and we found considerable variations among different countries/territories (31.8-65.0). The results from the pilot analysis are consistent with the results from a literature review, which suggests that a GOHI as a potential tool for the assessment of One Health performance might be feasible. CONCLUSIONS: GOHI-subject to rigorous validation-would represent the world's first evaluation tool that constructs the conceptual framework from a holistic perspective of One Health. Future application of GOHI might promote a common understanding of a strong One Health approach and provide reference for promoting effective measures to strengthen One Health capacity building. With further adaptations under various scenarios, GOHI, along with its technical protocols and databases, will be updated regularly to address current technical limitations, and capture new knowledge.
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Saúde Única , Previsões , Saúde GlobalRESUMO
According to the sequence of P450 cDNA of Eleutherococcus senticosus, specific primers were designed. Frokaryotic ex pression vector pET30a-P450 was constructed and the prokaryotic expression conditions were optimized. Results showed that the BL21 after being transformed with the recombinant expression vector accumulated the high amount of recombinant protein. SDS-PAGE analysis showed that the recombinant protein was about 53 kDa. The recombinant accumulated the highest amount of recombinant protein af ter IPTG (1 mmol x L(-1)) at 27-37 degrees C for 24 h. Consequently P450 gene of E. senticosus could be expressed successfully by prokaryotic expression vector pET30a-P450. Induction temperature, IPTG concentration, medium type and amount of induction time could all influence the expression of target protein, but the impact strength was different.
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Sistema Enzimático do Citocromo P-450/genética , Eleutherococcus/enzimologia , Escherichia coli/genética , Expressão Gênica , Proteínas de Plantas/genética , Clonagem Molecular , Sistema Enzimático do Citocromo P-450/metabolismo , Eleutherococcus/genética , Escherichia coli/metabolismo , Vetores Genéticos/genética , Vetores Genéticos/metabolismo , Proteínas de Plantas/metabolismo , Plasmídeos/genética , Plasmídeos/metabolismo , Proteínas Recombinantes/genética , Proteínas Recombinantes/metabolismoRESUMO
OBJECTIVE: To analyze the codon usage of chloroplast genome and the influencing factor in Eleutherococcus senticosus. METHOD: Codon of 52 genes, which were selected from the chloroplast genome sequence of E. senticosus, was multivariate statistical and correspondence analyzed using CodonW and SPSS software. RESULT: GC content at the three position of codons by turns was 46.46%, 38.26%, 29.88%, whereas GC1 and GC2 had a significant correlation coefficient (P < 0.01). The correlation coefficient with GC12, and GC3 was 0.205 and was not significant correlated. There were 30 codons which relative synonymous codon usage was greater than 1 and 29 codons end with A and T. In the corresponding analysis, the first axis shows 10.35% variation. And there was significant correlation coefficient between ENC and GC3. The correlation coefficients with GC3 and ENC were -0.288 and 0.353, respectively. We defined 16 codons from 16 amino acids as the major preference codons in chloroplast genome of E. senticosus. CONCLUSION: The third positions for all codon are preferred to ending with A and T. The codon usage bias is formed under effect of mutation and selection, as well as other factors. But the selection will have a far greater impact than others.