PCCT: Progressive Class-Center Triplet Loss for Imbalanced Medical Image Classification.

Imbalanced training data in medical image diagnosis is a significant challenge for diagnosing rare diseases. For this purpose, we propose a novel two-stage Progressive Class-Center Triplet (PCCT) framework to overcome the class imbalance issue. In the first stage, PCCT designs a class-balanced triplet loss to coarsely separate distributions of different classes. Triplets are sampled equally for each class at each training iteration, which alleviates the imbalanced data issue and lays solid foundation for the successive stage. In the second stage, PCCT further designs a class-center involved triplet strategy to enable a more compact distribution for each class. The positive and negative samples in each triplet are replaced by their corresponding class centers, which prompts compact class representations and benefits training stability. The idea of class-center involved loss can be extended to the pair-wise ranking loss and the quadruplet loss, which demonstrates the generalization of the proposed framework. Extensive experiments support that the PCCT framework works effectively for medical image classification with imbalanced training images. On four challenging class-imbalanced datasets (two skin datasets Skin7 and Skin 198, one chest X-ray dataset ChestXray-COVID, and one eye dataset Kaggle EyePACs), the proposed approach respectively obtains the mean F1 score 86.20, 65.20, 91.32, and 87.18 over all classes and 81.40, 63.87, 82.62, and 79.09 for rare classes, achieving state-of-the-art performance and outperforming the widely used methods for the class imbalance issue.

An antibody cocktail with broadened mutational resistance and effective protection against SARS-CoV-2.

Neutralizing antibodies have been proven to be highly effective in treating mild and moderate COVID-19 patients, but continuous emergence of SARS-CoV-2 variants poses significant challenges. Antibody cocktail treatments reduce the risk of escape mutants and resistance. In this study, a new cocktail composed of two highly potent neutralizing antibodies (HB27 and H89Y) was developed, whose binding epitope is different from those cocktails that received emergency use authorization. This cocktail showed more potent and balanced neutralizing activities (IC50 0.9-11.3 ng mL-1) against a broad spectrum of SARS-CoV-2 variants over individual HB27 or H89Y antibodies. Furthermore, the cocktail conferred more effective protection against the SARS-CoV-2 Beta variant in an aged murine model than monotherapy. It was shown to prevent SARS-CoV-2 mutational escape in vitro and effectively neutralize 61 types of pseudoviruses harbouring single amino acid mutation originated from variants and escape strains of Bamlanivimab, Casirivimab and Imdevimab with IC50 of 0.6-65 ng mL-1. Despite its breadth of variant neutralization, the HB27+H89Y combo and EUA cocktails lost their potencies against Omicron variant. Our results provide important insights that new antibody cocktails covering different epitopes are valuable tools to counter virus mutation and escape, highlighting the need to search for more conserved epitopes to combat Omicron.

Development of a thermostable SARS-CoV-2 variant-based bivalent protein vaccine with cross-neutralizing potency against Omicron subvariants.

SARS-CoV-2 variants have posed significant challenges to the hopes of using ancestral strain-based vaccines to address the risk of breakthrough infection by variants. We designed and developed a bivalent vaccine based on SARS-CoV-2 Alpha and Beta variants (named SCTV01C). SCTV01C antigens were stable at 25 ^oC for at least 6 months. In the presence of a squalene-based oil-in-water adjuvant SCT-VA02B, SCTV01C showed significant protection efficacy against antigen-matched Beta variant, with favorable safety profiles in rodents. Notably, SCTV01C exhibited cross-neutralization capacity against Omicron subvariants (BA.1, BA.1.1, BA.2, BA.3, and BA.4/5) in mice, superior to a WT (D614G)-based vaccine, which reinforced our previously published findings that SCTV01C exhibited broad-spectrum neutralizing potencies against over a dozen pre-Omicron variants and the Omicron BA.1 variant. In summary, variant-based multivalent protein vaccine could be a platform approach to address the challenging issues of emerging variants, vaccine hesitancy and the needs of affordable and thermal stable vaccines.

Impact of COVID-19 pandemic on consumer behavioural intention to purchase green products.

This study examined the fear of COVID-19 pandemic and its impact on consumer behavioural intention to purchase green products. The data was collected from consumers of Malaysia in hypermarkets. A total of 491 respondents were analyzed using the partial least square technique. The results indicated that the fear of the COVID-19 epidemic has a significant impact on health concerns, social media information, intolerance of uncertainty, and personal relevance, which in turn affect consumers' behavioural intention to purchase green products. With a serial mediating effect the results identified that fear of COVID-19 epidemic is associated with behavioural intention to purchase the green product. The findings of this study are crucial for understanding the swings in the green product purchase behaviour due to the ongoing uncertainty of COVID-19 crisis.

Cuff inflation technique is better than Magill forceps technique to facilitate nasotracheal intubation guiding by GlideScope® video laryngoscope.

Video laryngoscopy is often selected to assist nasotracheal intubation in allowing better laryngeal visualization, although there is no comparative study evaluating the effectiveness between auxiliary techniques by using Magill forceps and inflated cuff in GlideScope video laryngoscopy for nasotracheal intubation. Fifty-one of 100 patients in a Magill forceps group and 47 of 100 patients in a cuff inflation group were included in the final analysis in this randomized, single-blind, parallel, clinical trial study. Induction agents were routinely administered according to body weight, while intubation time spent, attempts, and related side effects were recorded. Compared to the Magill forceps group, the cuff inflation technique shortened the total intubation time (70.0 ± 24.5 s vs. 87.0 ± 25.0 s, p = 0.001) and the time of advancing the nasotracheal tube from oropharyngeal space into the trachea (25.9 ± 16.4 s vs. 42.3 ± 21.2 s, p < 0.001). However, the number of intubation attempts was not significantly different between groups. During tube advancement, the tube was rotated to accommodate the glottis and trachea more frequently in the cuff inflation group (p = 0.009), but the blade of the laryngoscope shifted and was adjusted to the proper position more frequently in the Magill forceps group (p < 0.001). In the Magill forceps group, the tube cuff might be clipped incidentally and the intubator might shift their gaze away from the screen during intubation, although there was no significant difference in intubation-related side effects between groups. Unlike the conventional approach, nasotracheal intubation with the GlideScope® video laryngoscope using the auxiliary technique of cuff inflation could be more suited than using Magill forceps.

Development of a thermostable SARS-CoV-2 variant-based bivalent protein vaccine with cross-neutralizing potency against Omicron subvariants

SARS-CoV-2 variants have posed significant challenges to the hopes of using ancestral strain-based vaccines to address the risk of breakthrough infection by variants. We designed and developed a bivalent vaccine based on SARS-CoV-2 Alpha and Beta variants (named SCTV01C). SCTV01C antigens were stable at 25 oC for at least 6 months. In the presence of a squalene-based oil-in-water adjuvant SCT-VA02B, SCTV01C showed significant protection efficacy against antigen-matched Beta variant, with favorable safety profiles in rodents. Notably, SCTV01C exhibited cross-neutralization capacity against Omicron subvariants (BA.1, BA.1.1, BA.2, BA.3, and BA.4/5) in mice, superior to a WT (D614G)-based vaccine, which reinforced our previously published findings that SCTV01C exhibited broad-spectrum neutralizing potencies against over a dozen pre-Omicron variants and the Omicron BA.1 variant. In summary, variant-based multivalent protein vaccine could be a platform approach to address the challenging issues of emerging variants, vaccine hesitancy and the needs of affordable and thermal stable vaccines.

Feasibility Studies of Nebulized SARS-CoV-2 Neutralizing Antibody in Mice and Cynomolgus Monkeys.

PURPOSE: Neutralizing antibodies, administrated through intravenous infusion, have shown to be highly efficacious in treating mild and moderate COVID-19 caused by SARS-CoV-2 infection in the lung. However, antibodies do not transport across the plasma-lung barrier efficiently, and up to 100 mg/kg dose was used in human causing significant supply and cost burdens. This study was to explore the feasibility of nebulized antibodies inhalation delivery as an alternative route. METHODS: HB27, a potent RBD-specific humanized monoclonal antibody (Zhu et al. in National Sci Rev. 8:nwaa297, 2020), showed excellent protection against SARS-CoV-2 in animal model and good safety profile in clinical studies. The pharmacokinetics and preliminary safety of HB27 administrated through the respiratory tract were studied in mice and cynomolgus monkeys here. RESULTS: At a single 5 mg/kg dose, the peak HB27 concentration in mice pulmonary epithelial lining fluid (ELF) reached 857.8 µg/mL, 670-fold higher than the PRNT90 value of 1.28 µg/mL, and maintained above PRNT90 over 240 h. In contrast, when administrated by intravenous injection at a 5 mg/kg dose, the antibody concentrations in mice ELF were below PRNT90 value throughout, and were about 50-fold lower than that in the serum. In cynomolgus monkeys administrated with a single dose through inhalation, the antibody concentration in ELF remained high within 3 days. No drug-related safety concerns were observed in the studies. CONCLUSIONS: The study demonstrated that nebulized neutralizing antibody delivery though inhalation could be a more efficient and efficacious alternative approach for treating COVID-19 and other respiratory infectious diseases, and warrants further evaluation in clinical studies.

Non-PCR Ultrasensitive Detection of Viral RNA by a Nanoprobe-Coupling Strategy: SARS-CoV-2 as an Example.

Developing efficient and highly sensitive diagnostic techniques for early detections of pathogenic viruses such as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is vitally important for preventing its widespread. However, the conventional polymerase chain reaction (PCR)-based detection features high complexity, excessive time-consumption, and labor-intensiveness, while viral protein-based detections suffer from moderate sensitivity and specificity. Here, a non-PCR but ultrasensitive viral RNA detection strategy is reported based on a facile nanoprobe-coupling strategy without enzymatic amplification, wherein PCR-induced bias and other shortcomings are successfully circumvented. This approach endows the viral RNA detection with ultra-low background to maximum signal ratio in the linear signal amplification by using Au nanoparticles as reporters. The present strategy exhibits 100% specificity toward SARS-CoV-2 N gene, and ultrasensitive detection of as low as 52 cp mL-1 of SARS-CoV-2 N gene without pre-PCR amplification. This approach presents a novel ultrasensitive tool for viral RNA detections for fighting against COVID-19 and other types of pathogenic virus-caused diseases.

Treatment of patients with Covid-19 with a high dose of ulinastatin

Currently, there are no specific therapeutic agents available for the treatment of coronavirus disease 2019 (Covid-19). The present study aimed to assess the efficacy of high-dose ulinastatin for the treatment of patients with Covid-19. A total of 12 patients hospitalized with confirmed severe acute respiratory syndrome coronavirus 2 infection were treated with a high dose of ulinastatin alongside standard care. Changes in clinical manifestations, laboratory examinations and chest images were retrospectively analyzed. A total of 10 patients with severe Covid-19 and two patients with moderate Covid-19 received ulinastatin treatment. The average age of the patients was 68.0±11.9 years (age range, 48-87 years). In total, nine of the 12 patients (75.0%) had one or more comorbidities. The most common symptoms on admission were fever (8/12, 66.7%), cough (5/12, 41.7%) and dyspnea (5/12, 41.7%). The percentage of lymphocytes was decreased in 41.7% of patients (5/12) and 58.3% of patients (7/12) had elevated hypersensitive C-reactive protein (CRP) levels (mean, 49.70±77.70 mg/l). The white blood cell levels and the percentage of lymphocytes returned to normal in all of the patients, and CRP was significantly decreased and returned to normal in 83.3% of patients (10/12;mean, 6.87±6.63 mg/l) on day 7 after ulinastatin treatment. Clinical symptoms were relieved synchronously. The peripheral oxygen saturation improved and 66.7% of the patients (8/12) did not require further oxygen therapy 7 days after ulinastatin treatment. No patients required intensive care unit admission or mechanical ventilation. All patients revealed different degrees of absorption of pulmonary lesions after treatment. Compared with the standard care group, ulinastatin treatment significantly prevented illness deterioration. In conclusion, these preliminary data revealed that high-dose ulinastatin treatment was safe and exhibited a potential beneficial effect for patients with Covid-19. [ FROM AUTHOR] Copyright of Experimental & Therapeutic Medicine is the property of Spandidos Publications UK Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Progress on Pharmaceutical Sciences/Pharmacy Postgraduate Education: a Bibliometric Perspective.

OBJECTIVE: The study quantitatively investigated the related research progress in pharmaceutical sciences/pharmacy education from a bibliometric angle and provided feasible suggestions to facilitate the development of pharmaceutical sciences/pharmacy postgraduate education. METHODS: Bibliometric analysis was conducted using the database of Web of Science Core Collection. The literature published in 1985-2021 was screened and selected. The overall profile description, citation analysis, and research hotspot mining were performed using the citation report of Clarivate Analytics, bibliometrics online platform, and VOSviewer software. The bibliometric results and profiles were plotted and illustrated. RESULTS: The bibliometric analysis of 485 papers of interest showed that the research frontier was continuously expanding; especially the institutions from the USA were the main contributors. The numbers of citing papers have been ascending, and a considerable part of citations were from the areas other than the education research. Mining results showed that the in-school and residency education of pharmacy postgraduates was a research hotspot, as well as interprofessional training and new education styles for Coronavirus Disease 2019 (COVID-19) therapy were the emerging trends in the field. CONCLUSION: Through the analysis of the studies, it was found that encouraging relevant research programs, establishing financial supports, and launching specified publication sources could be helpful to boost the development of pharmaceutical sciences/pharmacy postgraduate education. Besides, the results suggested that this was a less discussed topic and was worthy for the investigators to pay more attention to such an issue. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12247-021-09611-z.

Treatment of patients with Covid-19 with a high dose of ulinastatin.

Currently, there are no specific therapeutic agents available for the treatment of coronavirus disease 2019 (Covid-19). The present study aimed to assess the efficacy of high-dose ulinastatin for the treatment of patients with Covid-19. A total of 12 patients hospitalized with confirmed severe acute respiratory syndrome coronavirus 2 infection were treated with a high dose of ulinastatin alongside standard care. Changes in clinical manifestations, laboratory examinations and chest images were retrospectively analyzed. A total of 10 patients with severe Covid-19 and two patients with moderate Covid-19 received ulinastatin treatment. The average age of the patients was 68.0±11.9 years (age range, 48-87 years). In total, nine of the 12 patients (75.0%) had one or more comorbidities. The most common symptoms on admission were fever (8/12, 66.7%), cough (5/12, 41.7%) and dyspnea (5/12, 41.7%). The percentage of lymphocytes was decreased in 41.7% of patients (5/12) and 58.3% of patients (7/12) had elevated hypersensitive C-reactive protein (CRP) levels (mean, 49.70±77.70 mg/l). The white blood cell levels and the percentage of lymphocytes returned to normal in all of the patients, and CRP was significantly decreased and returned to normal in 83.3% of patients (10/12; mean, 6.87±6.63 mg/l) on day 7 after ulinastatin treatment. Clinical symptoms were relieved synchronously. The peripheral oxygen saturation improved and 66.7% of the patients (8/12) did not require further oxygen therapy 7 days after ulinastatin treatment. No patients required intensive care unit admission or mechanical ventilation. All patients revealed different degrees of absorption of pulmonary lesions after treatment. Compared with the standard care group, ulinastatin treatment significantly prevented illness deterioration. In conclusion, these preliminary data revealed that high-dose ulinastatin treatment was safe and exhibited a potential beneficial effect for patients with Covid-19.

1-year outcomes in hospital survivors with COVID-19: a longitudinal cohort study.

BACKGROUND: The full range of long-term health consequences of COVID-19 in patients who are discharged from hospital is largely unclear. The aim of our study was to comprehensively compare consequences between 6 months and 12 months after symptom onset among hospital survivors with COVID-19. METHODS: We undertook an ambidirectional cohort study of COVID-19 survivors who had been discharged from Jin Yin-tan Hospital (Wuhan, China) between Jan 7 and May 29, 2020. At 6-month and 12-month follow-up visit, survivors were interviewed with questionnaires on symptoms and health-related quality of life (HRQoL), and received a physical examination, a 6-min walking test, and laboratory tests. They were required to report their health-care use after discharge and work status at the 12-month visit. Survivors who had completed pulmonary function tests or had lung radiographic abnormality at 6 months were given the corresponding tests at 12 months. Non-COVID-19 participants (controls) matched for age, sex, and comorbidities were interviewed and completed questionnaires to assess prevalent symptoms and HRQoL. The primary outcomes were symptoms, modified British Medical Research Council (mMRC) score, HRQoL, and distance walked in 6 min (6MWD). Multivariable adjusted logistic regression models were used to evaluate the risk factors of 12-month outcomes. FINDINGS: 1276 COVID-19 survivors completed both visits. The median age of patients was 59·0 years (IQR 49·0-67·0) and 681 (53%) were men. The median follow-up time was 185·0 days (IQR 175·0-198·0) for the 6-month visit and 349·0 days (337·0-361·0) for the 12-month visit after symptom onset. The proportion of patients with at least one sequelae symptom decreased from 68% (831/1227) at 6 months to 49% (620/1272) at 12 months (p<0·0001). The proportion of patients with dyspnoea, characterised by mMRC score of 1 or more, slightly increased from 26% (313/1185) at 6-month visit to 30% (380/1271) at 12-month visit (p=0·014). Additionally, more patients had anxiety or depression at 12-month visit (26% [331/1271] at 12-month visit vs 23% [274/1187] at 6-month visit; p=0·015). No significant difference on 6MWD was observed between 6 months and 12 months. 88% (422/479) of patients who were employed before COVID-19 had returned to their original work at 12 months. Compared with men, women had an odds ratio of 1·43 (95% CI 1·04-1·96) for fatigue or muscle weakness, 2·00 (1·48-2·69) for anxiety or depression, and 2·97 (1·50-5·88) for diffusion impairment. Matched COVID-19 survivors at 12 months had more problems with mobility, pain or discomfort, and anxiety or depression, and had more prevalent symptoms than did controls. INTERPRETATION: Most COVID-19 survivors had a good physical and functional recovery during 1-year follow-up, and had returned to their original work and life. The health status in our cohort of COVID-19 survivors at 12 months was still lower than that in the control population. FUNDING: Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences, the National Natural Science Foundation of China, the National Key Research and Development Program of China, Major Projects of National Science and Technology on New Drug Creation and Development of Pulmonary Tuberculosis, the China Evergrande Group, Jack Ma Foundation, Sino Biopharmaceutical, Ping An Insurance (Group), and New Sunshine Charity Foundation.

[Design and Implementation of Intelligent Monitoring Collar for Potential Patients with Viral Pneumonia Based on DA14699 Chip].

In order to improve the level of epidemic prevention and control, and strengthen the observation and monitoring of potential patients with viral pneumonia in isolated state, a medical intelligent monitoring collar based on DA14699 Bluetooth low-power chip was proposed. DA14699 chip is used as the main controller in the design scheme, and the temperature, cough and location information of potential patients are recorded and analyzed by its high-efficiency wireless multi-core processing ability. The LIS3DH three-axis acceleration sensor is used to judge the cough symptoms. The MLX90640 infrared sensor is used to continuously measure the body temperature. The L218 four frequency GSM / GPRS positioning module is used to complete the rapid and accurate positioning of personnel, so as to realize the comprehensive supervision of the implementation of home isolation measures. DA14699 chip supports Bluetooth BLE5.1 protocol. Epidemic prevention personnel can transmit and read the data recorded in the smart collar from a long distance, and display it directly on the intelligent Bluetooth handheld terminal, effectively avoid the risk of infection caused by close contact. Through the actual test, the monitoring function of the key parameters of the collar is reliable and has high application value.

Artificial intelligence for prediction of COVID-19 progression using CT imaging and clinical data.

OBJECTIVES: Early recognition of coronavirus disease 2019 (COVID-19) severity can guide patient management. However, it is challenging to predict when COVID-19 patients will progress to critical illness. This study aimed to develop an artificial intelligence system to predict future deterioration to critical illness in COVID-19 patients. METHODS: An artificial intelligence (AI) system in a time-to-event analysis framework was developed to integrate chest CT and clinical data for risk prediction of future deterioration to critical illness in patients with COVID-19. RESULTS: A multi-institutional international cohort of 1,051 patients with RT-PCR confirmed COVID-19 and chest CT was included in this study. Of them, 282 patients developed critical illness, which was defined as requiring ICU admission and/or mechanical ventilation and/or reaching death during their hospital stay. The AI system achieved a C-index of 0.80 for predicting individual COVID-19 patients' to critical illness. The AI system successfully stratified the patients into high-risk and low-risk groups with distinct progression risks (p < 0.0001). CONCLUSIONS: Using CT imaging and clinical data, the AI system successfully predicted time to critical illness for individual patients and identified patients with high risk. AI has the potential to accurately triage patients and facilitate personalized treatment. KEY POINT: • AI system can predict time to critical illness for patients with COVID-19 by using CT imaging and clinical data.

Symptomatic features and prognosis of 932 hospitalized patients with coronavirus disease 2019 in Wuhan.

OBJECTIVE: To discern the symptomatic features of coronavirus disease 2019 (COVID-19) and to evaluate the severity and prognosis of the disease. METHODS: In this retrospective cohort study, 932 hospitalized patients with COVID-19 in Wuhan were enrolled, including 52 severe and 880 non-severe cases. All patients were followed up for 3 months after discharge. The symptomatic features and follow-up data of the patients in both groups were analyzed and compared. RESULTS: Of the 932 patients, fever (60.0%), cough (50.8%) and fatigue (36.4%) were the most common symptoms. In total, 32.7% of the severe cases presented with gastrointestinal symptoms at disease onset, including anorexia, nausea, vomiting or diarrhea, which was significantly higher than that of the non-severe group (P = 0.0015). The incidence of olfactory disturbance and dysgeusia was only 3.1% and 6.2%, respectively. After adjusting for age and sex, multivariate regression analysis showed that fever lasting for over 5 days (odds ratio [OR] 1.90, 95% confidence interval [CI] 1.00-3.62, P = 0.0498), anorexia at onset (OR 2.61, 95% CI 1.26-5.40, P = 0.0096), and modified Medical Research Council level above grade 2 when dyspnea occurred (OR 14.19, 95% CI 7.01-28.71, P < 0.0001) were symptomatic risk factors for severe COVID-19. During the follow-up, cough (6.2%), dyspnea (7.2%), fatigue (1.8%), olfactory disturbance and dysgeusia (1.5%) were the significant remaining symptoms. CONCLUSIONS: COVID-19 causes clusters of symptoms with multiple systems involved. Certain symptomatic characteristics have predictive value for severe COVID-19. Short-term follow-up data reveal that most patients have a good prognosis.

Helping Roles of Artificial Intelligence (AI) in the Screening and Evaluation of COVID-19 Based on the CT Images.

OBJECTIVE: The aim of this study was to explore the role of the AI system which was designed and developed based on the characteristics of COVID-19 CT images in the screening and evaluation of COVID-19. METHODS: The research team adopted an improved U-shaped neural network to segment lungs and pneumonia lesions in CT images through multilayer convolution iterations. Then the appropriate 159 cases were selected to establish and train the model, and Dice loss function and Adam optimizer were used for network training with the initial learning rate of 0.001. Finally, 39 cases (29 positive and 10 negative) were selected for the comparative test. Experimental group: an attending physician a and an associate chief physician a read the CT images to diagnose COVID-19 with the help of the AI system. Control group: an attending physician b and an associate chief physician b did the diagnosis only by their experience, without the help of the AI system. The time spent by each doctor in the diagnosis and their diagnostic results were recorded. Paired t-test, univariate ANOVA, chi-squared test, receiver operating characteristic curves, and logistic regression analysis were used for the statistical analysis. RESULTS: There was statistical significance in the time spent in the diagnosis of different groups (P<0.05). For the group with the optimal diagnostic results, univariate and multivariate analyses both suggested no significant correlation for all variables, and thus it might be the assistance of the AI system, the epidemiological history and other factors that played an important role. CONCLUSION: The AI system developed by us, which was created due to COVID-19, had certain clinical practicability and was worth popularizing.

A study on willingness and influencing factors to receive COVID-19 vaccination among Qingdao residents.

This study investigated the willingness of Qingdao residents to receive COVID-19 vaccination in 2020 and any factors that might influence them. All data were collected by telephone questionnaires and were utilized for analyzing the potential factors of willingness to be vaccinated through descriptive analysis and logistic regression analysis. Of the 2,802 respondents, 2,284 (81.5%) said they would agree to receive the vaccine against COVID-19. People who earned high incomes, who carefully followed media news on COVID-19 vaccine, who looked forward to successful vaccine research, and who closely followed vaccine protective efficacy expressed more interest in being vaccinated than other people did. In addition, people who paid attention to protective efficacy of vaccine, vaccine price, and expert opinion were more likely to accept COVID-19 vaccination than people who focused on vaccine safety. When vaccine price was ≥201 RMB, people were less likely to accept vaccination than ≤200 RMB. 1,842 respondents (65.7%) wished that government could provide COVID-19 vaccination for free. This study suggests that the government should increase vaccination compliance by strengthening publicity efforts and decreasing vaccine price.

A materials-science perspective on tackling COVID-19.

The ongoing SARS-CoV-2 pandemic highlights the importance of materials science in providing tools and technologies for antiviral research and treatment development. In this Review, we discuss previous efforts in materials science in developing imaging systems and microfluidic devices for the in-depth and real-time investigation of viral structures and transmission, as well as material platforms for the detection of viruses and the delivery of antiviral drugs and vaccines. We highlight the contribution of materials science to the manufacturing of personal protective equipment and to the design of simple, accurate and low-cost virus-detection devices. We then investigate future possibilities of materials science in antiviral research and treatment development, examining the role of materials in antiviral-drug design, including the importance of synthetic material platforms for organoids and organs-on-a-chip, in drug delivery and vaccination, and for the production of medical equipment. Materials-science-based technologies not only contribute to the ongoing SARS-CoV-2 research efforts but can also provide platforms and tools for the understanding, protection, detection and treatment of future viral diseases.