Prime-boost vaccination of mice and rhesus macaques with two novel adenovirus vectored COVID-19 vaccine candidates.

ABSTRACTCOVID-19 vaccines are being developed urgently worldwide. Here, we constructed two adenovirus vectored COVID-19 vaccine candidates of Sad23L-nCoV-S and Ad49L-nCoV-S carrying the full-length gene of SARS-CoV-2 spike protein. The immunogenicity of two vaccines was individually evaluated in mice. Specific immune responses were observed by priming in a dose-dependent manner, and stronger responses were obtained by boosting. Furthermore, five rhesus macaques were primed with 5 × 109 PFU Sad23L-nCoV-S, followed by boosting with 5 × 109 PFU Ad49L-nCoV-S at 4-week interval. Both mice and macaques well tolerated the vaccine inoculations without detectable clinical or pathologic changes. In macaques, prime-boost regimen induced high titers of 103.16 anti-S, 102.75 anti-RBD binding antibody and 102.38 pseudovirus neutralizing antibody (pNAb) at 2 months, while pNAb decreased gradually to 101.45 at 7 months post-priming. Robust T-cell response of IFN-γ (712.6 SFCs/106 cells), IL-2 (334 SFCs/106 cells) and intracellular IFN-γ in CD4+/CD8+ T cell (0.39%/0.55%) to S peptides were detected in vaccinated macaques. It was concluded that prime-boost immunization with Sad23L-nCoV-S and Ad49L-nCoV-S can safely elicit strong immunity in animals in preparation of clinical phase 1/2 trials

Measuring of the COVID-19 Based on Time-Geography

At the end of 2019, the COVID-19 pandemic began to emerge on a global scale, including China, and left deep traces on all societies. The spread of this virus shows remarkable temporal and spatial characteristics. Therefore, analyzing and visualizing the characteristics of the COVID-19 pandemic are relevant to the current pressing need and have realistic significance. In this article, we constructed a new model based on time-geography to analyze the movement pattern of COVID-19 in Hebei Province. The results show that as time changed COVID-19 presented an obvious dynamic distribution in space. It gradually migrated from the southwest region of Hebei Province to the northeast region. The factors affecting the moving patterns may be the migration and flow of population between and within the province, the economic development level and the development of road traffic of each city. It can be divided into three stages in terms of time. The first stage is the gradual spread of the epidemic, the second is the full spread of the epidemic, and the third is the time and again of the epidemic. Finally, we can verify the accuracy of the model through the standard deviation ellipse and location entropy

Geometric calibration of large-scale SAR images using wind turbines as ground control points

The geometric positioning accuracy of synthetic aperture radar images is a key factor impacting their application, necessitating geometric calibration for improved accuracy. Traditional geometric calibration methods rely on ground calibration fields and supportive equipment such as corner reflectors, which often fall short in meeting both domestic and international geometric calibration demands. To enable convenient, swift, and large-scale or even global SAR calibration, we proposed a method that employs wind turbines as ground control points for SAR geometric calibration, and have constructed a wind turbine database for China. This database allows for precise positioning of wind turbine targets in SAR images. In this study, we applied the wind turbine geometric calibration model for the first time to four imaging modes of Gaofen-3 images. The results indicate that the positioning accuracy post-calibration ranges from 2.70 m to 8.72 m. The mean square error of positioning for the multi-scene calibration of 12 images spanning six provinces is less than 9 m, validating the method's applicability for large-scale calibration. Our proposed method presents a cost-effective solution for large-scale geometric calibration and can notably enhance the positioning accuracy of Gaofen-3 images, thereby increasing their application potential in remote sensing mapping, environmental monitoring, and resource management

Lesion based diagnostic performance of dual phase 99mTc-MIBI SPECT/CT imaging and ultrasonography in patients with secondary hyperparathyroidism

Abstract Background We aimed to evaluate the diagnostic performance of 99mTc-MIBI SPECT/CT and ultrasonography in patients with secondary hyperparathyroidism (SHPT), and explored the factors that affect the diagnostic performance. Methods 99mTc-MIBI SPECT/CT and ultrasonography were performed in 50 patients with SHPT within 1 month before they underwent surgery. Imaging results were confirmed by the pathology. Pearson correlation analysis was used to determine the correlation of PTH level with clinical data. The optimal cutoff value for predicting positive 99mTc-MIBI results was evaluated by ROC analysis in lesions diameter. Results Forty-nine patients had a positive 99mTc-MIBI imaging results and 39 patients had positive ultrasonography results. The sensitivities of 99mTc-MIBI and ultrasonography were 98.00% and 78.00%, respectively. A total of 199 lesions were resected in 50 patients. Among them, 183 lesions were proved to be parathyroid hyperplasia. On per-lesion basis analysis, the sensitivity and specificity of 99mTc-MIBI and ultrasonography were 59.34% and 75.00% vs 46.24% and 80.00%, respectively. The Pearson correlation analysis showed that the serum AKP and PTH level had a significant linear association (r = 0.699, P < 0.001). The lesion diameter was a statistically significant predictive factor in predicting positive 99mTc-MIBI SPECT/CT. The optimal cutoff value for predicting positive 99mTc-MIBI results evaluated by ROC analysis in lesions diameter was 8.05 mm. Conclusion Dual phase 99mTc-MIBI SPECT/CT imaging had a higher sensitivity in patients with SHPT than ultrasonography. Therefore, using 99mTc-MIBI positioning the lesion could be an effective method pre-surgical in patients with SHPT

Pixel-Level Projection of PM_2.5 Using Landsat Images and Cellular Automata Models in the Yangtze River Delta, China

In this study, we proposed a pixel-level projection method for fine particulate matter (PM2.5) over a long term and across a large area using a combination of Landsat images, PM2.5 data from monitoring stations, and historical gridded PM2.5 data. We considered the spatial dependence effects of the particulate matter using a spatial lag model to quantify the relationship between PM2.5 concentration and land coverage indices, where the latter were calculated by the built-up, vegetation, and water indices. The future land coverage indices for the pixel-level projection of PM2.5 were derived from the future land-use scenario predicted by the Futureland model. We applied the method to analyze the spatial patterns of PM2.5 in the Yangtze River Delta (YRD), China, from 2000 to 2020, and then projected its pixel-level scenario in 2030. The projected PM2.5 shows high concentrations in the north and low in the south and temporally decreases compared to 2010. The projection of the fine-grained PM2.5 scenario can help adjust YRDs environmental and industrial policies, as well as implement its management strategies for sustainable urban development. Our method can be used to predict future patterns not only for long-term and large-scale pixel-level PM2.5 concentrations but also for other environmental parameters