Cell‐derived microparticles, which are recognized as nanosized phospholipid bilayer membrane vesicles, have exhibited great potential to serve as drug delivery systems in cancer therapy. However, for the purpose of comprehensive therapy, microparticles decorated with multiple therapeutic components are needed, but effective engineering strategies are limited and still remain enormous challenges. Herein, Bi2Se3 nanodots and doxorubicin hydrochloride (DOX) co‐embedded tumor cell‐derived microparticles (Bi2Se3/DOX@MPs) are successfully constructed through ultraviolet light irradiation‐induced budding of parent cells which are preloaded with Bi2Se3 nanodots and DOX via electroporation. The multifunctional microparticles are obtained with high controllability and drug‐loading capacity without unfavorable membrane surface destruction, maintaining their excellent intrinsic biological behaviors. Through membrane fusion cellular internalization, Bi2Se3/DOX@MPs show enhanced cellular internalization and deepened tumor penetration, resulting in extreme cell damage in vitro without considering endosomal escape. Because of their distinguished photothermal performance and tumor homing target capability, Bi2Se3/DOX@MPs exhibit admirable dual‐modal imaging capacity and outstanding tumor suppression effect. Under 808 nm laser irradiation, intravenous injection of Bi2Se3/DOX@MPs into H22 tumor‐bearing mice results in remarkably synergistic antitumor efficacy by combining photothermal therapy with low‐dose chemotherapy in vivo. Furthermore, the negligible hemolytic activity, considerable metabolizability, and low systemic toxicity of Bi2Se3/DOX@MPs imply their distinguished biocompatibility and great potential for tumor theranostics.

Objective: To compare the accuracies of quantitative computed tomography (CT) parameters and semiquantitative visual score in evaluating clinical classification of severity of coronavirus disease (COVID-19). Materials and Methods: We retrospectively enrolled 187 patients with COVID-19 treated at Tongji Hospital of Tongji Medical College from February 15, 2020, to February 29, 2020. Demographic data, imaging characteristics, and clinical data were collected, and based on the clinical classification of severity, patients were divided into groups 1 (mild) and 2 (severe/ critical). A semiquantitative visual score was used to estimate the lesion extent. A three-dimensional slicer was used to precisely quantify the volume and CT value of the lung and lesions. Correlation coefficients of the quantitative CT parameters, semiquantitative visual score, and clinical classification were calculated using Spearman's correlation. A receiver operating characteristic curve was used to compare the accuracies of quantitative and semi-quantitative methods. Results: There were 59 patients in group 1 and 128 patients in group 2. The mean age and sex distribution of the two groups were not significantly different. The lesions were primarily located in the subpleural area. Compared to group 1, group 2 had larger values for all volume-dependent parameters (p < 0.001). The percentage of lesions had the strongest correlation with disease severity with a correlation coefficient of 0.495. In comparison, the correlation coefficient of semiquantitative score was 0.349. To classify the severity of COVID-19, area under the curve of the percentage of lesions was the highest (0.807; 95% confidence interval, 0.744-0.861: p < 0.001) and that of the quantitative CT parameters was significantly higher than that of the semiquantitative visual score (p = 0.001). Conclusion: The classification accuracy of quantitative CT parameters was significantly superior to that of semiquantitative visual score in terms of evaluating the severity of COVID-19.

Background: The aim of this study was to evaluate long-term longitudinal changes in chest computed tomography (CT) findings in coronavirus disease 2019 survivors and their correlations with dyspnea after discharge.Methods: A total of 337 COVID-19 survivors who underwent CT scan during hospitalization and between 102 and 361 days after onset were retrospectively included. Subjective CT findings, lesion volume, therapeutic measures and laboratory parameters were collected. The severity of the survivors' dyspnea was determined by follow-up questionnaire. The evolution of the CT findings from the peak period to discharge and throughout follow-up and the abilities of CT findings and clinical parameters to predict survival with and without dyspnea were analyzed.Results: Ninety-one COVID-19 survivors still had dyspnea at follow-up. The age, comorbidity score, duration of hospital stays, receipt of hormone administration, receipt of immunoglobulin injections, intensive care unit (ICU) admission, receipt of mechanical ventilation, laboratory parameters, clinical classifications and parameters associated with lesion volume of the survivors with dyspnea were significantly different from those of survivors without dyspnea. Among the clinical parameters and CT parameters used to identify dyspnea, parameters associated with lesion volume showed the largest area under the curve (AUC) values, with lesion volume at discharge showing the largest AUC (0.820). Lesion volume decreased gradually from the peak period to discharge and through follow-up, with a notable decrease observed after discharge.Absorption of lesions continued 6 months after discharge.Conclusions: Among the clinical parameters and subjective CT findings, CT findings associated with lesion volume were the best predictors of post-discharge dyspnea in COVID-19 survivors.