Clinical analysis of secondary glaucoma in Central China.

To describe the epidemiology, clinical and social characteristics, management, and outcomes of patients with secondary glaucoma in Central China, a total of 1,129 cases (1,158 eyes) among 710 males (62.89%) and 419 females (37.11%) were analyzed. The mean age was 53.75 ± 17.11 years. The New Rural Cooperative Medical System (NCMS) played the most important role in reimbursement (60.32%) for secondary glaucoma-related medical expenses. The predominant occupation was "farmer" (53.41%). Neovascularization and trauma were the leading causes of secondary glaucoma. Cases of trauma-induced glaucoma decreased substantially during the coronavirus disease 2019 (COVID-19) pandemic. An education level of senior high school or above was uncommon. Ahmed glaucoma valve implantation was the most commonly performed surgery. At the final follow-up, the overall intraocular pressure (IOP) in patients with vascular disease- and trauma-related secondary glaucoma was 19.53 ± 10.20 mmHg, 20.26 ± 11.75 mmHg, and 16.90 ± 6.72 mmHg, while the mean visual acuity (VA) was 0.33 ± 0.32, 0.34 ± 0.36, and 0.43 ± 0.36. In 814 (70.29%) eyes, the VA was < 0.01. Effective preventive measures for at-risk populations, increased NCMS coverage and the promotion of higher education are necessary. These findings will help ophthalmologists detect secondary glaucoma early and manage it in a timely manner.

Management of autoimmune retinopathy treated with intravitreal dexamethasone implant.

PURPOSE: The purpose of this study is to evaluate clinical outcomes of autoimmune retinopathy (AIR) in the patients treated with intravitreal dexamethasone implant (IDI). METHOD: Twenty-one eyes of 11 AIR patients treated with at least 1 injection of IDI were retrospectively reviewed. Clinical outcomes before and after treatment, including best corrected visual acuity (BCVA), optic coherence tomography (OCT), fundus autofluorescence (FAF), full-field electroretinography (ff-ERG), and visual field (VF) at last visit within 6 and/or 12 months, were recorded. RESULTS: Among all the patients, 3 had cancer-associated retinopathy (CAR) and 8 had non-paraneoplastic-AIR (npAIR) with mean followed up of 8.52 ± 3.03 months (range 4-12 months). All patients achieved improved or stable BCVA within 6 and/or 12 months after the treatment. Cystoid macular edema (CME) in 2 eyes and significant retinal inflammation in 4 eyes were markedly resolved after single injection. Central retinal thickness (CFT) in all eyes without CME, ellipsoid zone (EZ) on OCT in 71.4% of eyes, ERG response in 55% of eyes, and VF in 50% of eyes were stable or improved within 6 months after treatment. At last visit within 12 months, both BCVA and CFT remained stable in the eyes treated with either single or repeated IDI; however, progression of EZ loss and damage of ERG response occurred in some patients with single IDI. CONCLUSION: Clinical outcomes, including BCVA and parameters of OCT, ERG, and VF, were stable or improved after IDI in a majority of AIR patients. Local treatment of AIR with IDI was a good option to initiate the management or an alternative for the patients' refractory to the systemic therapy but with limited side effect.

eHealth Literacy of Chinese Residents During the Coronavirus Disease 2019 Pandemic: A Cross-sectional Survey.

The Coronavirus Disease 2019 (COVID-19) pandemic has become a leading societal concern. eHealth literacy is important in the prevention and control of this pandemic. The purpose of this study is to identify eHealth literacy of Chinese residents about the COVID-19 pandemic and factors influencing eHealth literacy. A total of 15 694 individuals clicked on the link to the questionnaire, and 15 000 agreed to participate and completed the questionnaire for a response rate of 95.58%. Descriptive statistics, χ2 test, and logistic regression analysis were conducted to analyze participants' level of eHealth literacy about COVID-19 and its influencing factors. The results showed 52.2% of participants had relatively lower eHealth literacy regarding COVID-19 (eHealth literacy score ≤ 48). The scores of the information judgment dimension (3.09 ± 0.71) and information utilization dimension (3.18 ± 0.67) of the eHealth literacy scale were relatively lower. The logistics regression showed that sex, age, education level, level of uncertainty, having people around the respondent diagnosed with COVID-19, relationship with family, and relationship with others were associated to eHealth literacy (χ2 = 969.135, P < .001). The public's eHealth literacy about COVID-19 needs to be improved, especially the ability to judge and utilize online information. Close collaboration among global health agencies, governments, healthcare institutions, and media is needed to provide reliable online information to the public. Interventions to improve eHealth literacy should take into account and accentuate the importance of sex, age, educational background, level of uncertainty, exposure to disease, and social support.

Studying pulmonary fibrosis due to microbial infection via automated microscopic image analysis.

Introduction: Pulmonary fibrosis is a consequential complication of microbial infections, which has notably been observed in SARS-CoV-2 infections in recent times. Macrophage polarization, specifically the M2-type, is a significant mechanism that induces pulmonary fibrosis, and its role in the development of Post- COVID-19 Pulmonary Fibrosis is worth investigating. While pathological examination is the gold standard for studying pulmonary fibrosis, manual review is subject to limitations. In light of this, we have constructed a novel method that utilizes artificial intelligence techniques to analyze fibro-pathological images. This method involves image registration, cropping, fibrosis degree classification, cell counting and calibration, and it has been utilized to analyze microscopic images of COVID-19 lung tissue. Methods: Our approach combines the Transformer network with ResNet for fibrosis degree classification, leading to a significant improvement over the use of ResNet or Transformer individually. Furthermore, we employ semi-supervised learning which utilize both labeled and unlabeled data to enhance the ability of the classification network in analyzing complex samples. To facilitate cell counting, we applied the Trimap method to localize target cells. To further improve the accuracy of the counting results, we utilized an effective area calibration method that better reflects the positive density of target cells. Results: The image analysis method developed in this paper allows for standardization, precision, and staging of pulmonary fibrosis. Analysis of microscopic images of COVID-19 lung tissue revealed a significant number of macrophage aggregates, among which the number of M2-type macrophages was proportional to the degree of fibrosis. Discussion: The image analysis method provids a more standardized approach and more accurate data for correlation studies on the degree of pulmonary fibrosis. This advancement can assist in the treatment and prevention of pulmonary fibrosis. And M2-type macrophage polarization is a critical mechanism that affects pulmonary fibrosis, and its specific molecular mechanism warrants further exploration.

Differential renal proteomics analysis in a novel rat model of iodinated contrast-induced acute kidney injury.

Contrast-induced acute kidney injury (CI-AKI), which occurs after the use of iodinated contrast media, has become the third leading cause of hospital-acquired acute kidney injury (AKI). It is associated with prolonged hospitalization and increased risks of end-stage renal disease and mortality. The pathogenesis of CI-AKI is unclear and effective treatments are lacking. By comparing different post-nephrectomy times and dehydration times, we constructed a new, short-course CI-AKI model using dehydration for 24 h two weeks after unilateral nephrectomy. We found that the low-osmolality contrast media iohexol caused more severe renal function decline, renal morphological damage, and mitochondrial ultrastructural alterations compared to the iso-osmolality contrast media iodixanol. The shotgun proteomics based on Tandem Mass Tag (TMT) was used to conduct proteomics research on renal tissue in the new CI-AKI model, and 604 distinct proteins were identified, mainly involving complement and coagulation cascade, COVID-19, PPAR signalling pathway, mineral absorption, cholesterol metabolism, ferroptosis, staphylococcus aureus infection, systemic lupus erythematosus, folate biosynthesis, and proximal tubule bicarbonate reclamation. Then, using parallel reaction monitoring (PRM), we validate 16 candidate proteins, of which five were novel candidates (Serpina1, Apoa1, F2, Plg, Hrg) previously unrelated to AKI and associated with an acute response as well as fibrinolysis. The pathway analysis and 16 candidate proteins may help to discover new mechanisms in the pathogenesis of CI-AKI, allowing for early diagnosis and outcome prediction.

Real-world effectiveness of primary series and booster doses of inactivated COVID-19 vaccine against Omicron BA.2 variant infection in China: a retrospective cohort study.

BACKGROUND: China has been using inactivated COVID-19 vaccines as primary series and booster doses to protect the population from severe to fatal COVID-19. We evaluated primary and booster vaccine effectiveness (VE) against Omicron BA.2 infection outcomes. METHODS: This was a 13-province retrospective cohort study of quarantined close contacts of BA.2-infected individuals. Outcomes were BA.2 infection, COVID-19 pneumonia or worse, and severe/critical COVID-19. Absolute VE was estimated by comparison with an unvaccinated group. RESULTS: There were 289,427 close-contacts ≥3 years old exposed to Omicron BA.2 cases; 31,831 turned nucleic-acid amplification test (NAAT)-positive during quarantine, 97.2% with mild or asymptomatic infection, 2.6% had COVID-19 pneumonia, and 0.15% had severe/critical COVID-19. None died. Adjusted VE against any infection was 17% for primary series and 22% when boosted. Primary series aVE in adults >18 years was 66% against pneumonia or worse infection and 91% against severe/critical COVID-19. Booster dose aVE was 74% against pneumonia or worse, and 93% against severe/critical COVID-19. CONCLUSIONS: Inactivated COVID-19 vaccines provided modest protection from infection, very good protection against pneumonia, and excellent protection against severe/critical COVID-19. Booster doses are necessary to provide strongest protection.

SARS-CoV-2 hijacks cellular kinase CDK2 to promote viral RNA synthesis.

The coronavirus disease 2019 (COVID-19) pandemic has devastated global health. Identifying key host factors essential for SARS-CoV-2 RNA replication is expected to unravel cellular targets for the development of broad-spectrum antiviral drugs which have been quested for the preparedness of future viral outbreaks. Here, we have identified host proteins that associate with nonstructural protein 12 (nsp12), the RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 using a mass spectrometry (MS)-based proteomic approach. Among the candidate factors, CDK2 (Cyclin-dependent kinase 2), a member of cyclin-dependent kinases, interacts with nsp12 and causes its phosphorylation at T20, thus facilitating the assembly of the RdRp complex consisting of nsp12, nsp7 and nsp8 and promoting efficient synthesis of viral RNA. The crucial role of CDK2 in viral RdRp function is further supported by our observation that CDK2 inhibitors potently impair viral RNA synthesis and SARS-CoV-2 infection. Taken together, we have discovered CDK2 as a key host factor of SARS-CoV-2 RdRp complex, thus serving a promising target for the development of SARS-CoV-2 RdRp inhibitors.

A versatile integrated tube for rapid and visual SARS-CoV-2 detection.

The coronavirus disease 2019 (COVID-19) caused by novel severe acute respiratory coronavirus 2 (SARS-CoV-2) has been rapidly spreading worldwide. Rapid and widespread testing is essential to promote early intervention and curb the ongoing COVID-19 pandemic. Current gold standard reverse transcription-polymerase chain reaction (RT-PCR) for detecting SARS-CoV-2 is restricted to professional laboratories and well-trained personnel, thus, limiting its widespread use in resource-limited conditions. To overcome these challenges, we developed a rapid and convenient assay using a versatile integrated tube for the rapid and visual detection of SARS-CoV-2. The reaction conditions of the method were optimized using SARS-CoV-2 RNA standards and the sensitivity and specificity were further determined. Finally, it was verified on clinical specimens. The assay was completed within 40 min, and the result was visible by the naked eye. The limits of detection (LODs) for the target ORF1ab and N genes were 50 copies/µl. No cross-reactivity was observed with the RNA standard samples of four respiratory viruses or clinical samples of common respiratory viral infections. Ninety SARS-CoV-2 positive and 30 SARS-CoV-2 negative patient specimens were analyzed. We compared these results to both prior and concurrent RT-PCR evaluations. As a result, the overall sensitivity and specificity for detection SARS-CoV-2 were 94.5 and 100.0%, respectively. Conclusion: The integrated tube assay has the potential to provide a simple, specific, sensitive, one-pot, and single-step assay for SARS-CoV-2.

COVID-19 Related Early Google Search Behavior and Health Communication in the United States: Panel Data Analysis on Health Measures.

The COVID-19 outbreak at the end of December 2019 spread rapidly all around the world. The objective of this study is to investigate and understand the relationship between public health measures and the development of the pandemic through Google search behaviors in the United States. Our collected data includes Google search queries related to COVID-19 from 1 January to 4 April 2020. After using unit root tests (ADF test and PP test) to examine the stationary and a Hausman test to choose a random effect model, a panel data analysis is conducted to investigate the key query terms with the newly added cases. In addition, a full sample regression and two sub-sample regressions are proposed to explain: (1) The changes in COVID-19 cases number are partly related to search variables related to treatments and medical resources, such as ventilators, hospitals, and masks, which correlate positively with the number of new cases. In contrast, regarding public health measures, social distancing, lockdown, stay-at-home, and self-isolation measures were negatively associated with the number of new cases in the US. (2) In mild states, which ranked one to twenty by the average daily new cases from least to most in 50 states, the query terms about public health measures (quarantine, lockdown, and self-isolation) have a significant negative correlation with the number of new cases. However, only the query terms about lockdown and self-isolation are also negatively associated with the number of new cases in serious states (states ranking 31 to 50). Furthermore, public health measures taken by the government during the COVID-19 outbreak are closely related to the situation of controlling the pandemic.

A versatile integrated tube for rapid and visual SARS-CoV-2 detection

The coronavirus disease 2019 (COVID-19) caused by novel severe acute respiratory coronavirus 2 (SARS-CoV-2) has been rapidly spreading worldwide. Rapid and widespread testing is essential to promote early intervention and curb the ongoing COVID-19 pandemic. Current gold standard reverse transcription-polymerase chain reaction (RT-PCR) for detecting SARS-CoV-2 is restricted to professional laboratories and well-trained personnel, thus, limiting its widespread use in resource-limited conditions. To overcome these challenges, we developed a rapid and convenient assay using a versatile integrated tube for the rapid and visual detection of SARS-CoV-2. The reaction conditions of the method were optimized using SARS-CoV-2 RNA standards and the sensitivity and specificity were further determined. Finally, it was verified on clinical specimens. The assay was completed within 40 min, and the result was visible by the naked eye. The limits of detection (LODs) for the target ORF1ab and N genes were 50 copies/μl. No cross-reactivity was observed with the RNA standard samples of four respiratory viruses or clinical samples of common respiratory viral infections. Ninety SARS-CoV-2 positive and 30 SARS-CoV-2 negative patient specimens were analyzed. We compared these results to both prior and concurrent RT-PCR evaluations. As a result, the overall sensitivity and specificity for detection SARS-CoV-2 were 94.5 and 100.0%, respectively. Conclusion The integrated tube assay has the potential to provide a simple, specific, sensitive, one-pot, and single-step assay for SARS-CoV-2.

Understanding Health Communication Through Google Trends and News Coverage for COVID-19: Multinational Study in Eight Countries.

BACKGROUND: Due to the COVID-19 pandemic, health information related to COVID-19 has spread across news media worldwide. Google is among the most used internet search engines, and the Google Trends tool can reflect how the public seeks COVID-19-related health information during the pandemic. OBJECTIVE: The aim of this study was to understand health communication through Google Trends and news coverage and to explore their relationship with prevention and control of COVID-19 at the early epidemic stage. METHODS: To achieve the study objectives, we analyzed the public's information-seeking behaviors on Google and news media coverage on COVID-19. We collected data on COVID-19 news coverage and Google search queries from eight countries (ie, the United States, the United Kingdom, Canada, Singapore, Ireland, Australia, South Africa, and New Zealand) between January 1 and April 29, 2020. We depicted the characteristics of the COVID-19 news coverage trends over time, as well as the search query trends for the topics of COVID-19-related "diseases," "treatments and medical resources," "symptoms and signs," and "public measures." The search query trends provided the relative search volume (RSV) as an indicator to represent the popularity of a specific search term in a specific geographic area over time. Also, time-lag correlation analysis was used to further explore the relationship between search terms trends and the number of new daily cases, as well as the relationship between search terms trends and news coverage. RESULTS: Across all search trends in eight countries, almost all search peaks appeared between March and April 2020, and declined in April 2020. Regarding COVID-19-related "diseases," in most countries, the RSV of the term "coronavirus" increased earlier than that of "covid-19"; however, around April 2020, the search volume of the term "covid-19" surpassed that of "coronavirus." Regarding the topic "treatments and medical resources," the most and least searched terms were "mask" and "ventilator," respectively. Regarding the topic "symptoms and signs," "fever" and "cough" were the most searched terms. The RSV for the term "lockdown" was significantly higher than that for "social distancing" under the topic "public health measures." In addition, when combining search trends with news coverage, there were three main patterns: (1) the pattern for Singapore, (2) the pattern for the United States, and (3) the pattern for the other countries. In the time-lag correlation analysis between the RSV for the topic "treatments and medical resources" and the number of new daily cases, the RSV for all countries except Singapore was positively correlated with new daily cases, with a maximum correlation of 0.8 for the United States. In addition, in the time-lag correlation analysis between the overall RSV for the topic "diseases" and the number of daily news items, the overall RSV was positively correlated with the number of daily news items, the maximum correlation coefficient was more than 0.8, and the search behavior occurred 0 to 17 days earlier than the news coverage. CONCLUSIONS: Our findings revealed public interest in masks, disease control, and public measures, and revealed the potential value of Google Trends in the face of the emergence of new infectious diseases. Also, Google Trends combined with news media can achieve more efficient health communication. Therefore, both news media and Google Trends can contribute to the early prevention and control of epidemics.

Predicting In Vitro and In Vivo Anti-SARS-CoV-2 Activities of Antivirals by Intracellular Bioavailability and Biochemical Activity.

Cellular drug response (concentration required for obtaining 50% of a maximum cellular effect, EC50) can be predicted by the intracellular bioavailability (F ic) and biochemical activity (half-maximal inhibitory concentration, IC50) of drugs. In an ideal model, the cellular negative log of EC50 (pEC50) equals the sum of log F ic and the negative log of IC50 (pIC50). Here, we measured F ic's of remdesivir, favipiravir, and hydroxychloroquine in various cells and calculated their anti-SARS-CoV-2 EC50's. The predicted EC50's are close to the observed EC50's in vitro. When the lung concentrations of antiviral drugs are higher than the predicted EC50's in alveolar type 2 cells, the antiviral drugs inhibit virus replication in vivo, and vice versa. Overall, our results indicate that both in vitro and in vivo antiviral activities of drugs can be predicted by their intracellular bioavailability and biochemical activity without using virus. This virus-free strategy can help medicinal chemists and pharmacologists to screen antivirals during early drug discovery, especially for researchers who are not able to work in the high-level biosafety lab.

An integrated dual-layer microfluidic platform for multiple respiratory viruses screening.

Currently, the coronavirus disease 2019 (COVID-19) caused by the outbreak of a novel coronavirus (SARS-CoV-2) is spreading rapidly worldwide. Due to the high incidence of influenza coinciding with SARS-CoV-2, rapid detection is crucial to prevent spreading. Here, we present an integrated dual-layer microfluidic platform for specific and highly sensitive SARS-CoV-2, influenza viruses A (FluA) H1N1, H3N2, and influenza virus B (FluB) simultaneous detection. The platform includes a dual microchip (Dµchip) and a portable detection device for real-time fluorescence detection, temperature control and online communication. The Reverse Transcription Loop-mediated Isothermal Amplification (RT-LAMP) and Cas12a cleavage were performed on the Dµchip. The limit of detection (LoD) of the Dµchip assay was 10 copies for SARS-CoV-2, FluA H1N1, H3N2, and FluB RNAs. The Dµchip assay yielded no cross-reactivity against other coronaviruses, so it was suitable for the screening of multiple viruses. Moreover, the positive percentage agreement (PPA) and negative percentage agreement (NPA) of the assay were 97.9% and 100%, respectively, in 75 clinical samples compared to data from RT-PCR-based assays. Furthermore, the assay allowed the detection SARS-CoV-2 and influenza viruses in spiked samples. Overall, the present platform would provide a rapid method for the screening of multiple viruses in hospital emergency, community and primary care settings and facilitate the remote diagnosis and outbreak control of the COVID-19.

Humoral and cellular immunity of two-dose inactivated COVID-19 vaccination in Chinese children: A prospective cohort study.

Children are the high-risk group for COVID-19, and in need of vaccination. However, humoral and cellular immune responses of COVID-19 vaccine remain unclear in vaccinated children. To establish the rational immunization strategy of inactivated COVID-19 vaccine for children, the immunogenicity of either one dose or two doses of the vaccine in children was evaluated. A prospective cohort study of 322 children receiving inactivated COVID-19 vaccine was established in China. The baseline was conducted after 28 days of the first dose, and the follow-up was conducted after 28 days of the second dose. The median titers of receptor binding domain (RBD)-IgG, and neutralizing antibody (NAb) against prototype strain and Omicron variant after the second dose increased significantly compared to those after the first dose (first dose: 70.0, [interquartile range, 30.0-151.0] vs. second dose: 1261.0 [636.0-2060.0] for RBD-IgG; 2.5 [2.5-18.6] vs. 252.0 [138.6-462.1] for NAb against prototype strain; 2.5 [2.5-2.5] vs. 15.0 [7.8-26.5] for NAb against Omicron variant, all p < 0.05). The flow cytometry results showed that the first dose elicited SARS-CoV-2 specific cellular immunity, while the second dose strengthened SARS-CoV-2 specific IL-2+ or TNF-α+  monofunctional, IFN-γ+ TNF-α+  bifunctional, and IFN-γ- IL-2+ TNF-α+ multifunctional CD4+ T cell responses (p < 0.05). Moreover, SARS-CoV-2 specific memory T cells were generated after the first vaccination, including the central memory T cells and effector memory T cells. The present findings provide scientific evidence for the vaccination strategy of the inactive vaccines among children against COVID-19 pandemic.

The Impact of Psychological Capital and Social Capital on Residents' Mental Health and Happiness During COVID-19: Evidence From China.

Objective: This paper studies the mediating and interactive effects of social capital on psychological capital and the feeling of happiness from the impact of COVID-19. Since its emergence, the COVID-19 pandemic has taken a toll on people's mental health and affected their hopes for the future. Lifestyle and economic conditions have also been affected and have subsequently impacted people's sense of confidence in life. This could increase the likelihood of many people developing mental health issues, such as anxiety or depression. Therefore, it is vital to study the influence of psychological capital and social capital on people's subjective psychology and happiness experiences. Materials and Methods: Using an ordered probit model, this paper studied the independent influence and interaction between psychological capital and social capital on people's happiness. The ordered probit model was chosen because subjective well-being (SWB) is an ordered variable. We further used structural equation modeling (SEM) to study the mediating effects of social capital on psychological capital and happiness. Results: The regression results showed that both psychological capital and social capital were significantly positively correlated with happiness when controlling for other factors. In addition, psychological and social capital significantly interacted, in which the psychological capital promotes the effect of social capital on happiness. Moreover, the effect of psychological capital on happiness was greater than that of social capital, demonstrating that happiness is more greatly influenced by subjective psychological experience. The interaction coefficient of psychological and social capital was also significant, showing that the two have mutually reinforcing effects on happiness. Finally, health, income class, real estate, stranger trust, age, and urban household registration had significant positive effects on happiness, while the view of money, being female, education had a negative relationship with happiness. The SEM results showed that the mediating effect of psychological capital on happiness was partly transmitted through social capital: the total effect of psychological capital on happiness was highly significant (p < 0.0001), as was the total effect of social capital on happiness (p < 0.0001); however, the coefficient for psychological capital was greater than that for social capital. Through heterogeneity analysis, we found that the relationship between psychological capital, social capital, and happiness was significantly positive in each sub-sample group. There was also a significant interaction between psychological and social capital for men, women, urban and rural residents, and higher education background sample groups. However, the interaction was not significant in the sample group without higher education. In addition, the relationship between the happiness of rural residents and their educational background and gender was not significant. Conclusion: We found that psychological and social capital have significant positive relationships and effects on happiness. Psychological capital demonstrated both direct and indirect influences on happiness, and further strengthens the influence of social capital on happiness. These results support a scheme to emphasize psychological support during the COVID-19 pandemic period to enhance the mental health of citizens.

Literature Review and Research Prospect on the Drivers and Effects of Green Innovation

With increasing and global environmental and climate problems, green innovation has become an important means to solve the environmental crisis. With the increasing practice of green innovation in enterprises, scholars at home and abroad have discussed the drivers and effects of green innovation from different perspectives. Based on an analysis of 119 articles about the drivers and effects of green innovation in top international journals from 2006 to 2021, this paper tries to find the consistencies and contradictions of research conclusions and to explore the possible research opportunities, sorting out the main theoretical mechanisms of the existing research on the drivers and effects of green innovation, pinpointing the consistency of these theoretical perspectives in explaining the different drivers and effects of green innovation, and putting forward research prospects. The results show that the drivers of green innovation include two kinds of factors: environment and organization. The pressure of external environment and system drives enterprises to adopt green innovation practices to cater to isomorphic factors, to obtain more environmental performance, and to improve organizational legitimacy. The lack of development resources, such as knowledge and technology, within an organization drives enterprises to carry out green innovation practices and enhance organizational competitive advantage by learning and absorbing new external knowledge, new technology and other resources. In addition, resource-based view and institutional theory are two commonly used theoretical perspectives, and their theoretical logic obtains consistent support in explaining the drivers and effects of enterprise green innovation.

Public Opinions on COVID-19 Vaccines-A Spatiotemporal Perspective on Races and Topics Using a Bayesian-Based Method.

The COVID-19 pandemic has been sweeping across the United States of America since early 2020. The whole world was waiting for vaccination to end this pandemic. Since the approval of the first vaccine by the U.S. CDC on 9 November 2020, nearly 67.5% of the US population have been fully vaccinated by 10 July 2022. While quite successful in controlling the spreading of COVID-19, there were voices against vaccines. Therefore, this research utilizes geo-tweets and Bayesian-based method to investigate public opinions towards vaccines based on (1) the spatiotemporal changes in public engagement and public sentiment; (2) how the public engagement and sentiment react to different vaccine-related topics; (3) how various races behave differently. We connected the phenomenon observed to real-time and historical events. We found that in general the public is positive towards COVID-19 vaccines. Public sentiment positivity went up as more people were vaccinated. Public sentiment on specific topics varied in different periods. African Americans' sentiment toward vaccines was relatively lower than other races.

Semi-supervised COVID-19 CT image segmentation using deep generative models.

BACKGROUND: A recurring problem in image segmentation is a lack of labelled data. This problem is especially acute in the segmentation of lung computed tomography (CT) of patients with Coronavirus Disease 2019 (COVID-19). The reason for this is simple: the disease has not been prevalent long enough to generate a great number of labels. Semi-supervised learning promises a way to learn from data that is unlabelled and has seen tremendous advancements in recent years. However, due to the complexity of its label space, those advancements cannot be applied to image segmentation. That being said, it is this same complexity that makes it extremely expensive to obtain pixel-level labels, making semi-supervised learning all the more appealing. This study seeks to bridge this gap by proposing a novel model that utilizes the image segmentation abilities of deep convolution networks and the semi-supervised learning abilities of generative models for chest CT images of patients with the COVID-19. RESULTS: We propose a novel generative model called the shared variational autoencoder (SVAE). The SVAE utilizes a five-layer deep hierarchy of latent variables and deep convolutional mappings between them, resulting in a generative model that is well suited for lung CT images. Then, we add a novel component to the final layer of the SVAE which forces the model to reconstruct the input image using a segmentation that must match the ground truth segmentation whenever it is present. We name this final model StitchNet. CONCLUSION: We compare StitchNet to other image segmentation models on a high-quality dataset of CT images from COVID-19 patients. We show that our model has comparable performance to the other segmentation models. We also explore the potential limitations and advantages in our proposed algorithm and propose some potential future research directions for this challenging issue.

Mesophilic Argonaute-based isothermal detection of SARS-CoV-2

Coronavirus disease (COVID-19), caused by SARS-CoV-2 infection and its mutations, has spread rapidly all over the world and still requires sensitive detection to distinguish mutations. CRISPR-based diagnosis has been regarded as a next-generation detection method;however, it has some limitations, such as the need for specific recognition sequences and multiple enzymes for multiplex detection. Therefore, research on the exploration and development of novel nucleases helps to promote specific and sensitive diagnoses. Prokaryotic Argonaute (Ago) proteins exert directed nuclease activity that can target any sequence. Recently, thermophilic Agos have been developed as new detection techniques achieving multiplexity for multiple targets using a single enzyme, as well as accurate recognition of single-base differential sequences. In this study, to overcome the requirement for high reaction temperature of thermophilic Ago-based methods, we expanded the mining of mesophilic Agos to achieve CRISPR-like isothermal detection, named mesophilic Ago-based isothermal detection method (MAIDEN). The principle of MAIDEN uses mesophilic Ago cleavage combined with reverse transcription, which can provide single-strand DNA as a substrate and allow cleavage of fluorescence probes to sense SARS-CoV-2 at moderate temperature. We first mined and optimized the mesophilic Ago and the fluorescence reporter system and then selected a compatible reverse transcription reaction. Furthermore, we optimized MAIDEN into a one-step reaction that can detect SARS-CoV-2 RNA at the nanomolar concentration at a constant temperature of 42°C within 60 min. Therefore, MAIDEN shows advantageous portability and easy-to-implement operation, avoiding the possibility of open-lid contamination. Our study was the first attempt to demonstrate that mesophilic Agos can be harnessed as diagnostic tools, and MAIDEN was easily extended to detect other pathogens in a rapid and efficient manner.

Health as Battlefield: News and Misinformation in the Early Stage of COVID-19 Outbreak.

From the epidemic center in Wuhan to the entirety of China, with the growing infected population, people are seeking and processing health-related information both online and from traditional media outlets such as newspapers. Online misinformation regarding COVID-19 has been influencing a wide range of readers demonstrating general citizens' virus-related concerns, while press media have been actively participating in health communication in an attempt to build up a robust, harmonious, and healthy environment. Via a comparison between the news data with the misinformation data during the early stage of the COVID-19 pandemic, from 1 January 2020 to 20 February 2020, we conducted an LDA topic-modeling analysis and a sentiment analysis. This study sheds light on the nature of people's methods of health communication with online and press media sources during the early period of the pandemic crisis and provides possible readable explanations for the driving force of misinformation and the emotional changes experienced by the public.