A Decade of Scientific and Technological Innovation at Chinese Academy of Medical Sciences & Peking Union Medical College: Retrospect and Prospect.

Focusing on the reform initiatives of Chinese Academy of Medical Sciences (CAMS) & Peking Union Medical College (PUMC) in medical scientific and technological innovation from perspectives of deepening the reform and optimizing the ecosystem of science and technology innovation, this article summarizes the highlights of CAMS & PUMC's efforts in safeguarding people's health and promoting the Healthy China 2030 strategy through scientific and technological innovation in the fields including basic research, disease prevention and treatment, and medical technology in the past ten years. These achievements embody the endeavors and responsibility of CAMS & PUMC in realizing self-reliance and self-improvement of Chinese medical science and technology and highlight its contributions to the development of medical science and technology of China.

Plasma Metabolomic Profiles and Clinical Features in Recovered COVID-19 Patients Without Previous Underlying Diseases 3 Months After Discharge (preprint)

Knowing the residual and future effect of SARS-CoV-2 on recovered COVID-19 patients is critical for optimized long-term patient management. Recent studies focus on the symptoms and clinical indices of recovered patients, but the pathophysiological change is still unclear. To address this question, we examined the metabolomic profiles of recovered asymptomatic (RA), moderate (RM) and severe and critical (RC) patients without previous underlying diseases discharged from the hospital for 3 months, along with laboratory and CT findings. We found that the serum metabolic profiles in recovered COVID-19 patients still conspicuously differed from that in healthy control (HC), especially in the RM, and RC patients. Additionally, these changes bore close relationship with the function of pulmonary, renal, hepatic, microbial and energetic metabolism and inflammation. These findings suggested that RM and RC patients sustained multi-organ and multi-system damage and these patients should be followed up on regular basis for possible organ and system damage.

Transferrin receptor is another receptor for SARS-CoV-2 entry (preprint)

Angiotensin-converting enzyme 2 (ACE2) has been suggested as a receptor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) entry to cause coronavirus disease 2019 (COVID-19). However, no ACE2 inhibitors have shown definite beneficiaries for COVID-19 patients, applying the presence of another receptor for SARS-CoV-2 entry. Here we show that ACE2 knockout dose not completely block virus entry, while TfR directly interacts with virus Spike protein to mediate virus entry and SARS-CoV-2 can infect mice with over-expressed humanized transferrin receptor (TfR) and without humanized ACE2. TfR-virus co-localization is found both on the membranes and in the cytoplasma, suggesting SARS-CoV-2 transporting by TfR, the iron-transporting receptor shuttling between cell membranes and cytoplasma. Interfering TfR-Spike interaction blocks virus entry to exert significant anti-viral effects. Anti-TfR antibody (EC50 16.6 nM) shows promising anti-viral effects in mouse model. Collectively, this report indicates that TfR is another receptor for SARS-CoV-2 entry and a promising anti-COVID-19 target.

Transferrin receptor is another receptor for SARS-CoV-2 entry (preprint)

Angiotensin-converting enzyme 2 (ACE2) has been suggested as a receptor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) entry to cause coronavirus disease 2019 (COVID-19). However, no ACE2 inhibitors have shown definite beneficiaries for COVID-19 patients, applying the presence of another receptor for SARS-CoV-2 entry. Here we show that ACE2 knockout dose not completely block virus entry, while TfR directly interacts with virus Spike protein to mediate virus entry and SARS-CoV-2 can infect mice with over-expressed humanized transferrin receptor (TfR) and without humanized ACE2. TfR-virus co-localization is found both on the membranes and in the cytoplasma, suggesting SARS-CoV-2 transporting by TfR, the iron-transporting receptor shuttling between cell membranes and cytoplasma. Interfering TfR-Spike interaction blocks virus entry to exert significant anti-viral effects. Anti-TfR antibody (EC50 ∼16.6 nM) shows promising anti-viral effects in mouse model. Collectively, this report indicates that TfR is another receptor for SARS-CoV-2 entry and a promising anti-COVID-19 target.

Temporal Changes of CT Findings between Non-emergency and Emergency Patients with COVID-19 Pneumonia: A Multi-centered, Retrospective, Longitudinal Study (preprint)

Objective: To analyze the differences between clinical evaluation and the detailed imaging features in the time course of lung changes in diverse clinical types.Methods: 73 patients with COVID-19 pneumonia were retrospectively collected from three institutions in China. Radiographic features, CT score were analyzed and compared between non-emergency group (mild- and common-type) and emergency group (severe- and fatal-type).Results: In non-emergency group, the disease slowly aggravated within the first two weeks, peaked during the 2nd week (median superimposed involvement CT score: 9.5), while in emergency group, the disease peaked in the 2nd week rapidly, and the superimposed involvement CT score(median: 20) was higher than that in non-emergency group. Both two groups began to decline in the 4th week, and persistence of high levels. In emergency group, the residual lung lesions were mostly reticular (median single reticular CT score: 10) and consolidation (median single consolidation CT score:7). By contrast, most residual lung lesions in non-emergency group were GGO (median single GGO CT score: 7) and reticular (median single reticular CT score: 4). In both non-emergency and emergency groups, GGO pattern was dominant in the first week, and the proportion in emergency group was higher [20 (65%) and (18 (72%), respectively], the consolidation pattern peaked in the second week, which were 9 (32%) and 19 (73%), respectively, reticular pattern became dominant in and after 4 weeks (both over 40%).Conclusion: The disease in non-emergency and emergency group peaks in the second week. In the non-emergency group, the residual lesions are dominated by GGO and reticular, while those in the emergency group are mainly reticular and consolidation. The transiently CT manifestations of emergency and non-emergency follow certain patterns at different time points of the disease course.

A novel deep learning-based quantification of serial chest computed tomography in Coronavirus Disease 2019 (COVID-19) (preprint)

Objectives: This study aims to explore and compare a novel deep learning-based quantification with the conventional semi-quantitative computed tomography (CT) scoring for the serial chest CT scans of COVID-19. Materials and Methods: 95 patients with confirmed COVID-19 and a total of 465 serial chest CT scans were involved, including 61 moderate patients (moderate group, 319 chest CT scans) and 34 severe patients (severe group, 146 chest CT scans). Conventional CT scoring and deep learning-based quantification were performed for all chest CT scans for two study goals: 1. Correlation between these two estimations; 2. Exploring the dynamic patterns using these two estimations between moderate and severe groups.Results: The Spearman’s correlation coefficient between these two estimation methods was 0.920 (p<0.001). predicted pulmonary involvement (CT score and percent of pulmonary lesions calculated using deep learning-based quantification) increased more rapidly and reached a higher peak on 23rd days from symptom onset in severe group, which reached a peak on 18th days in moderate group with faster absorption of the lesions. Conclusions: The deep learning-based quantification for COVID-19 showed a good correlation with the conventional CT scoring and demonstrated a potential benefit in the estimation of disease severities of COVID-19. 

Comparisons of chest computed tomography patterns between survivors and non-survivors with Coronavirus Disease 2019 (COVID-19): a case-control study (preprint)

Objectives To compare the chest computed tomography (CT) findings between survivors and non-survivors with Coronavirus Disease 2019 (COVID-19).Materials and Methods Between 12 January 2020 to 20 February 2020, the records of 124 consecutive patients diagnosed with COVID-19 were retrospectively reviewed and divided into survivor (83/124) and non-survivor (41/124) groups. Chest CT findings were qualitatively compared on admission and serial chest CT scans were semi-quantitively evaluated between two groups using curve estimations.Results Elder age (median: 69 vs. 43y, p<0.001), higher male ratio (31/41 vs. 32/83, p<0.001), and more comorbidities were observed in non-survivor group. On admission, significantly more bilateral (97.6% vs. 73.5%, p=0.005) and diffuse lesions (39.0% vs. 8.4%, p<0.001) with higher total CT score (median: 10 vs. 4) were observed in non-survivor group compared with survivor group. Besides, crazy-paving pattern was more predominant in non- survivor group than survivor group (39.0% vs. 12.0%, p=0.004). From the prediction of curve estimation, in survivor group total CT score increased in the first 20 days reaching the peak of 6 points and then gradual decreased for more than other 40 days (R2=0.545, p<0.001). In non- survivor group, total CT score rapidly increased over 10 points in the first 10 days and gradually increased afterwards until ARDS occurred with following death events (R2=0.711, p<0.001).Conclusions Persistent progression with predominant crazy-paving pattern was the major manifestation of COVID-19 in non-survivors. Understanding this CT feature could help the clinical physician to predict the prognosis of the patients.

The Pulmonary Sequalae in Discharged Patients With COVID-19: A Short-term Observational Study (preprint)

Background: A cluster of patients with coronavirus disease 2019 (COVID-19) pneumonia were discharged from hospitals in Wuhan, China. We aimed to determine the cumulative percentage of complete radiological resolution at each time point, to explore the relevant affecting factors, and to describe the chest CT findings at different time points after hospital discharge.Methods: Patients with COVID-19 pneumonia confirmed by RT-PCR who were discharged consecutively from the hospital between 5 February 2020 and 10 March 2020 and who underwent serial chest CT scans on schedule were enrolled. The radiological characteristics of all patients were collected and analysed. The total CT score was the sum of non-GGO involvement determined at discharge. Afterwards, all patients underwent chest CT scans during the 1st, 2nd, and 3rd weeks after discharge. Imaging features and distributions were analysed across different time points.Results: A total of 149 patients who completed all CT scans were evaluated; there were 67 (45.0%) men and 82 (55.0%) women, with a median age of 43 years old (IQR 36-56). The cumulative percentage of complete radiological resolution was 8.1% (12 patients), 41.6% (62), 50.3% (75), and 53% (79) at discharge and during the 1st, 2nd, and 3rd weeks after discharge, respectively. Patients ≤44 years old showed a significantly higher cumulative percentage of complete radiological resolution than patients >44 years old at the 3-week follow-up. The predominant patterns of abnormalities observed at discharge were ground-glass opacity (GGO) (65 [43.6%]), fibrous stripe (45 [30.2%]), and thickening of the adjacent pleura (16 [10.7%]). Lung lesions showed obvious resolution from 2 to 3 weeks after discharge, especially in terms of GGO and fibrous stripe. “Tinted” sign and bronchovascular bundle distortion as two special features were discovered during the evolution.Conclusion: Lung lesions in COVID-19 pneumonia patients can be absorbed completely during short-term follow-up with no sequelae. Three weeks after discharge might be the optimal time point for early radiological estimation.