Application of molecular imaging in immune checkpoints therapy: From response assessment to prognosis prediction.

Recently, immune checkpoint therapy (ICT) represented by programmed cell death1 (PD-1) and its major ligands, programmed death ligand 1 (PD-L1), has achieved significant success. Detection of PD-L1 by immunohistochemistry (IHC) is a classic method to guide the treatment of ICT patients. However, PD-L1 expression in the tumor microenvironment is highly complex. Thus, PD-L1 IHC is inadequate to fully understand the relevance of PD-L1 levels in the whole body and their dynamics to improve therapeutic outcomes. Intriguingly, numerous studies have revealed that molecular imaging technologies could potentially meet this need. Therefore, the purpose of this narrative review is to summarize the preclinical and clinical application of ICT guided by molecular imaging technology, and to explore the future opportunities and practical difficulties of these innovations.

[Assessment of Emergency Emission Reduction Effect During the Heavy Air Pollution Episodes in Beijing, Tianjin, Hebei, and Its Surrounding Area("2+26" Cities) from October to December 2019].

To evaluate the effect of emergency emission reduction measures during the heavy air pollution episodes in Beijing, Tianjin, Hebei, and its surrounding areas, a scenario simulation method was used. The concentrations of PM2.5, PM10, SO2, NO2, CO, and O3-8h, air quality index (AQI), characteristics of heavy air pollution, and climate and meteorological factors were analyzed using the observation data available from October to December 2019. The 24 h, 72 h, and 144 h prediction results of NAQPMS model were analyzed. The uncertainties of the assessment and model prediction were discussed. The results showed that the average PM2.5 concentration in Beijing, Tianjin, and its surrounding 26 cities ("2+26" cities) from October to December 2019 was 64 µg ·m-3, indicating a decrease of 10 µg ·m-3 as compared with that during the same period in 2018. There were 4 occurrences of regional heavy air pollution episodes, with the average PM2.5 concentration of 156 µg ·m-3 of affected cities. The value of evaluation on meteorological condition index of PM2.5 pollution (EMI) of "2+26" cities ranged from -15.6%-16.8%. The meteorological conditions of 12 cities, including Beijing, Tianjin, and Shijiazhuang, deteriorated as compared with those during the same period in 2018, and the changes ranged from 3.2%-16.8%. However, the emergency emission reduction measures effectively reduced the occurrence of regional heavy air pollution episodes, the peak concentration of PM2.5 was decreased significantly, and no severe regional pollution episode occurred. The daily PM2.5 concentrations reduced by 2% to 9% in Beijing, Shijiazhuang, Baoding, Tangshan, and other cities during a typical heavy air pollution period. The quarterly average concentrations of PM2.5 in the "2+26" cities reduced by 1 to 3 µg ·m-3. The regional emergency emission reduction measures have played an active role in protecting the health of the people and improving the quality of ambient air.

[Heavy Pollution Characteristics and Assessment of PM2.5 Predicted Model Results in Beijing-Tianjin-Hebei Region and Surrounding Areas During November 23 to December 4, 2018].

This study discusses the concentration characteristics of PM2.5 and PM10, as well as pollution meteorology in large-scale and long-term heavy pollution in the Beijing-Tianjin-Hebei region and its surrounding areas from November 23 to December 4, 2018, where the primary pollutants are comprised of PM2.5 and PM10. The monitoring results obtained from ground-based and vehicle-mounted lidars, as well as the HYSPLIT-4 backward trajectory combined with meteorological factors analysis are discussed. The accuracy and uncertainty of the air quality forecast model of NAQPMS, CMAQ, and CAMx during heavy air pollution were analyzed retrospectively. The results show that PM2.5 and sand dust in most cities in the south-central region contribute to severe pollution levels. The hourly peak concentrations of PM10 in Zhangjiakou, Beijing, Shijiazhuang, Handan, and Zhengzhou were 1589, 864, 794, 738, and 766 µg·m-3, respectively. The respective hourly peak concentrations of PM2.5 were 239, 319, 387, 321, and 380 µg·m-3. Ground static pressure field, high humidity, inversion, and other static and stable conditions, as well as sand dust transmitted from the northwest, were important pollution meteorological and weather factors. The monitoring data of ground-based lidar and vehicle-mounted lidar combined with the HYSPLIT-4 backward trajectory analysis showed that the air pollutant transmitted from the Southwest and Southeast during the heavy pollution period was primarily PM2.5. The air pollutant transmitted from the Northwest during the two sand dust processes. Moreover, the model of NAQPMS, CMAQ, and CAMx performed well in forecasting the heavy pollution process in the Beijing-Tianjin-Hebei region and its surrounding areas. However there are slight deviations for some individual cities, related to uncertainty in the meteorological model prediction, atmospheric chemical reaction mechanism, and pollution source list. Furthermore, the reduction in pollution source emissions caused by pollution emergency measures was also one of the main reasons for the overestimation.

[Concentration Characteristics and Assessment of Model-Predicted Results of PM2.5 in the Beijing-Tianjin-Hebei Region in Autumn and Winter].

This paper discusses the concentration characteristics of PM2.5, as well as its relationship with meteorological factors in autumn and winter (from September to the following February), from 2013 to 2018 in the Beijing-Tianjin-Hebei (BTH) region. The accuracy and uncertainty of the air quality forecast models NAQPMS(nested air quality prediction modeling system), CMAQ(community multiscale air quality modeling system), and CAMx (comprehensive air quality model with extensions) were analyzed based on the model-predicted and measured PM2.5 concentration in autumn and winter from 2015 to 2018. The accuracy of NAQPMS, CMAQ, and CAMx during typical heavy air pollution was also tested. Moreover, methods to improve the accuracy of the model forecast were discussed. The results showed that the mean concentrations of PM2.5 in the BTH region were 122, 98, 82, 99, and 65 µg·m-3 in the five autumn and winter periods, respectively. When the air quality index (AQI) exceeded 150 during each autumn and winter, it reached 229, 198, 210, 204, and 180 µg·m-3, respectively. There were 64 occurrences of heavy regional PM2.5 air pollution in autumn and winter from 2013 to 2018. The average duration was longest in the 2013 to 2014 period, and shortest in the 2017 to 2018 period. The peak concentration and average concentration of PM2.5 decreased year on year, except for the period from 2016 to 2017. In autumn and winter, PM2.5 concentration had a relatively close relationship with relative humidity, wind and sunshine duration, compared with a weak relationship with temperature and air pressure. Regional heavy air pollution always happened under the condition of low wind speed(less than 2 m·s-1),higher relative humidity(greater than 65%),and southwest and northeast wind direction. In addition, the heavy air pollution of PM2.5 in BTH in autumn and winter can be effectively forecasted by NAQPMS, CMAQ, and CAMx. The predicted and measured PM2.5 concentration showed a close relationship. The models performed well in forecasting Zhangjiakou, Chengde, and Qinhuangdao, but by contrast overestimated in Tangshan, Shijiazhuang, Baoding, Beijing, and Tianjin. The uncertainty of emission sources, measured and predicted meteorological data, and the atmospheric chemical reaction mechanism may be the main reasons for the overestimate.

[A prospective assessment of the diagnostic value of MAIPA test in idiopathic thrombocytopenic purpura].

OBJECTIVE: To evaluate the clinical significance of MAIPA test in diagnosis of idiopathic thrombocytopenic purpura (ITP) and in the differential diagnosis of antoimmune thrombocytopenias from nonimmune thrombocytopenias. METHODS: A total of 321 thrombocytopenic patients (118 males, 203 females) from 14 centers were studied. A modified monoclonal antibody immobilization of platelet antigen (MAIPA) method was used to detect the platelet glycoprotein-specific autoantibodies (anti-GP IIb/IIIa, anti-GPIb/IX) to double-blindly evaluate its sensitivity and specificity for the diagnosis of ITP and to investigate the impact of the antibodies on platelet count. RESULTS: The results showed that for the diagnosis of ITP, anti-GPIIb/IIIa, anti-GPIb/IX and both of them had the sensitivity of 39.75%, 32.64% and 55.23%; the specificity of 97.56%, 93.94% and 92.68%; the positive predictive value of 97.94%, 93.98% and 95.65%; the negative predictive value of 35.71%, 32.35% and 41.53%; and the total efficiency of 54.51%, 48.29% and 64.80%, respectively. The positivity of the autoantibodies in immune thrombocytopenias was incredibly higher than that in nonimmune thrombocytopenias. The platelet counts in the immune thrombocytopenias with autoantibody positivities were significantly lower than those without the autoantibodies. The platelet counts were negatively correlated with the concentration of the autoantibodies. The levels of anti-GPIIb/IIIa or anti-GPIb/IX or both of them dropped or disappeared in patients being responsive to steroid therapy. CONCLUSION: MAIPA assay is proved to be of great value for the diagnosis of ITP and for differential diagnosis of immune thrombocytopenias from nonimmune thrombocytopenias.