Virtual ecological technology: Concepts, systems, and application perspectives.

Virtual ecological technology is a new technology that builds the foundation of a digital ecological system, simulates the process of ecological evolution, and establishes a global knowledge analysis system based on a unified spatio-temporal benchmark. It is a new direction for the interdisciplinary integration and development of eco-logy, geographic information science, computer science and other subjects towards modernization, informatization, and intelligence. Research, development, and application of virtual ecological technology is of great significance for the development of ecology as a discipline, ecosystem management, and regional sustainable development. Curren-tly, research on virtual ecological technology is still in its infancy and lacks a complete and clearly defined framework, making it difficult to support systematic iterative development and scientific analysis. In this paper, starting from the main theories and objectives of modern ecology, we summarized the main contents and technical requirements of virtual ecological construction, and proposed a key technical system of virtual ecology that integrated vir-tual geography and digital twin technology. From the perspective of application scenarios, we analyzed the application capabilities of virtual ecological technology in air pollution and energy analysis. Finally, we summarized the deve-lopment potential of virtual ecological technology in the digital construction of the ecological environment, intelligent computing, and realistic expression of different levels of ecological space resources transformation under the background of new generation of information technology, both at the local computing point breakthrough and the global technology point fusion aspects. This would enrich and advance the technical capabilities that support China's ecological space resource transformation.

The prevalence of drug resistance mutations among treatment-naive HIV-infected individuals in Beijing, China.

To investigate the prevalence of HIV-1 genotypic mutations for drug resistance among patients in Beijing, blood samples from 145 newly confirmed (2006-2007), treatment-naive HIV-1-infected individuals were analyzed. Seven subtypes or CRF were subsequently determined and scored by the Stanford HIV Drug Resistance algorithm: CRF01_AE HIV-1 (27.6%), subtype B' (24.1%), CRF07_BC (21.4%), subtype B (20.7%), CRF08_BC (3.4%), subtype C (2.1%), and CRF06_cpx (0.7%). Eleven of the 145 subjects studied were found to harbor the strains resistant to either protease inhibitors (PIs) (3.4%), or nucleoside reverse transcriptase inhibitors (NRTIs) (2.1%), or nonnucleoside reverse transcriptase inhibitors (NNRTIs) (3.4%). Although the prevalence of drug resistance was relatively low among the treatment-naive HIV-1 patients in Beijing in comparison to those in industrialized countries, we will continue monitoring newly infected subjects for any potential alteration of the prevalence pattern to ensure the success of the ongoing scale-up of antiretroviral treatment.