Identification and quantitative analysis of bioactive components from Potentilla kleiniana Wight et Arn with anti HIV-1 proteases activity.

Potentilla kleiniana Wight et Arn（PK, 'Wu Pi Feng' in Chinese） was recorded as Miao ethnic medicine for treatment of fever, cough, ulcer, and erysipelas for thousands years. This study aimed to evaluate the antiviral activity of four PK extracts and seven compounds by using HIV-1 protease (HIV-1 PR). In addition, Ultra-High Performance Liquid Chromatography and High Resolution Mass Spectrometry (UPLC-HRMS) was employed to identify the bioactive components. The toxicity assessment of the extracts was done before antiviral screening using a highly specific human aspartyl protease, renin protease by fluorimetric method. As a result, seven compounds and four extracts of PK inhibited HIV-1 PR with IC50 range from 0.009 to 0.36 mg/mL, and did not appreciably inhibit the general human protease renin. This study first demonstrated that four PK extracts, ellagic acid and ursolic acid potent inhibit HIV-1 protease, could be used as an efficacious drug candidate to treat SARS-CoV-2 infection.

Identification of Flavonoids from Scutellaria barbata D. Don as Inhibitors of HIV-1 and Cathepsin L Proteases and Their Structure-Activity Relationships.

Scutellaria barbata D. Don (SB, Chinese: Ban Zhi Lian), a well-known medicinal plant used in traditional Chinese medicine, is rich in flavonoids. It possesses antitumor, anti-inflammatory, and antiviral activities. In this study, we evaluated the inhibitory activities of SB extracts and its active components against HIV-1 protease (HIV-1 PR) and SARS-CoV2 viral cathepsin L protease (Cat L PR). UPLC/HRMS was used to identify and quantify the major active flavonoids in different SB extracts, and fluorescence resonance energy transfer (FRET) assays were used to determine HIV-1 PR and Cat L PR inhibitions and identify structure-activity relationships. Molecular docking was also performed, to explore the diversification in bonding patterns of the active flavonoids upon binding to the two PRs. Three SB extracts (SBW, SB30, and SB60) and nine flavonoids inhibited HIV-1 PR with an IC50 range from 0.006 to 0.83 mg/mL. Six of the flavonoids showed 10~37.6% inhibition of Cat L PR at a concentration of 0.1 mg/mL. The results showed that the introduction of the 4'-hydroxyl and 6-hydroxyl/methoxy groups was essential in the 5,6,7-trihydroxyl and 5,7,4'-trihydroxyl flavones, respectively, to enhance their dual anti-PR activities. Hence, the 5,6,7,4'-tetrahydroxyl flavone scutellarein (HIV-1 PR, IC50 = 0.068 mg/mL; Cat L PR, IC50 = 0.43 mg/mL) may serve as a lead compound to develop more effective dual protease inhibitors. The 5,7,3',4'-tetrahydroxyl flavone luteolin also showed a potent and selective inhibition of HIV-1 PR (IC50 = 0.039 mg/mL).

Preclinical evaluation of ISH0339, a tetravalent broadly neutralizing bispecific antibody against SARS-CoV-2 with long-term protection.

BACKGROUND: Ending the global COVID-19 pandemic requires efficacious therapies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Nevertheless, the emerging Omicron sublineages largely escaped the neutralization of current authorized monoclonal antibody therapies. Here we report a tetravalent bispecific antibody ISH0339, as a potential candidate for long-term and broad protection against COVID-19. METHODS: We report here the making of ISH0339, a novel tetravalent bispecific antibody composed of a pair of non-competing neutralizing antibodies that binds specifically to two different neutralizing epitopes of SARS-CoV-2 receptor-binding domain (RBD) and contains an engineered Fc region for prolonged antibody half-life. We describe the preclinical characterization of ISH0339 and discuss its potential as a novel agent for both prophylactic and therapeutic purposes against SARS-CoV-2 infection. RESULTS: ISH0339 bound to SARS-CoV-2 RBD specifically with high affinity and potently blocked the binding of RBD to the host receptor hACE2. ISH0339 demonstrated greater binding, blocking and neutralizing efficiency than its parental monoclonal antibodies, and retained neutralizing ability to all tested SARS-CoV-2 variants of concern. Single dosing of ISH0339 showed potent neutralizing activity for treatment via intravenous injection and for prophylaxis via nasal spray. Preclinical studies following single dosing of ISH0339 showed favorable pharmacokinetics and well-tolerated toxicology profile. CONCLUSION: ISH0339 has demonstrated a favorable safety profile and potent anti-SARS-CoV-2 activities against all current variants of concern. Furthermore, prophylactic and therapeutic application of ISH0339 significantly reduced the viral titer in lungs. Investigational New Drug studies to evaluate the safety, tolerability and preliminary efficacy of ISH0339 for both prophylactic and therapeutic purposes against SARS-CoV-2 infection have been filed.

The impact of the COVID-19 pandemic on undergraduate and postgraduate students: A cross-sectional survey.

Background: The COVID-19 pandemic has impacted many facets of life. This study focuses on undergraduate and postgraduate students in China to explore how the pandemic has affected health status, daily life, learning situations, graduation-related situations, and their studies or work planning. Methods: This study sent online questionnaires to 2,395 participants to investigate the extent to which they were affected by the epidemic in the various aspects mentioned above and to understand what help they tend to get in the face of these effects. Results: A total of 2,000 valid questionnaires were collected. The physical health of 82.90% of the respondents was affected to varying degrees, with male students, non-medical students, and graduates being more affected than female students, students with medical majors, and non-graduates, respectively. The proportion of students affected by mental health, the total amount of physical exercise, emotional life, and interpersonal communication was 86.35, 88.65, 80.15, and 90.15%, respectively. Compared with medical students and non-graduates, non-medical students and graduates were more affected. In addition, students' learning and graduation conditions have also been affected to a certain extent: 13.07% of students may not be able to graduate on time, and the proportion of postgraduate students' graduations affected was higher than that of undergraduate students. Conclusion: The COVID-19 pandemic has affected the health status of students, their daily lives, learning situations, and so on to varying degrees. We need to pay attention to the issues, provide practical solutions, and provide a basis for better responses to similar epidemics in the future.

Impact of Human Mobility on COVID-19 Transmission According to Mobility Distance, Location, and Demographic Factors in the Greater Bay Area of China: Population-Based Study.

BACKGROUND: Mobility restriction was one of the primary measures used to restrain the spread of COVID-19 globally. Governments implemented and relaxed various mobility restriction measures in the absence of evidence for almost 3 years, which caused severe adverse outcomes in terms of health, society, and economy. OBJECTIVE: This study aimed to quantify the impact of mobility reduction on COVID-19 transmission according to mobility distance, location, and demographic factors in order to identify hotspots of transmission and guide public health policies. METHODS: Large volumes of anonymized aggregated mobile phone position data between January 1 and February 24, 2020, were collected for 9 megacities in the Greater Bay Area, China. A generalized linear model (GLM) was established to test the association between mobility volume (number of trips) and COVID-19 transmission. Subgroup analysis was also performed for sex, age, travel location, and travel distance. Statistical interaction terms were included in a variety of models that express different relations between involved variables. RESULTS: The GLM analysis demonstrated a significant association between the COVID-19 growth rate ratio (GR) and mobility volume. A stratification analysis revealed a higher effect of mobility volume on the COVID-19 GR among people aged 50-59 years (GR decrease of 13.17% per 10% reduction in mobility volume; P<.001) than among other age groups (GR decreases of 7.80%, 10.43%, 7.48%, 8.01%, and 10.43% for those aged ≤18, 19-29, 30-39, 40-49, and ≥60 years, respectively; P=.02 for the interaction). The impact of mobility reduction on COVID-19 transmission was higher for transit stations and shopping areas (instantaneous reproduction number [Rt] decreases of 0.67 and 0.53 per 10% reduction in mobility volume, respectively) than for workplaces, schools, recreation areas, and other locations (Rt decreases of 0.30, 0.37, 0.44, and 0.32, respectively; P=.02 for the interaction). The association between mobility volume reduction and COVID-19 transmission was lower with decreasing mobility distance as there was a significant interaction between mobility volume and mobility distance with regard to Rt (P<.001 for the interaction). Specifically, the percentage decreases in Rt per 10% reduction in mobility volume were 11.97% when mobility distance increased by 10% (Spring Festival), 6.74% when mobility distance remained unchanged, and 1.52% when mobility distance declined by 10%. CONCLUSIONS: The association between mobility reduction and COVID-19 transmission significantly varied according to mobility distance, location, and age. The substantially higher impact of mobility volume on COVID-19 transmission for longer travel distance, certain age groups, and specific travel locations highlights the potential to optimize the effectiveness of mobility restriction strategies. The results from our study demonstrate the power of having a mobility network using mobile phone data for surveillance that can monitor movement at a detailed level to measure the potential impacts of future pandemics.

Mapping the long-term associations between air pollutants and COVID-19 risks and the attributable burdens in the continental United States.

Numerous studies have investigated the associations between COVID-19 risks and long-term exposure to air pollutants, revealing considerable heterogeneity and even contradictory regional results. Studying the spatial heterogeneity of the associations is essential for developing region-specific and cost-effective air-pollutant-related public health policies for the prevention and control of COVID-19. However, few studies have investigated this issue. Using the USA as an example, we constructed single/two-pollutant conditional autoregressions with random coefficients and random intercepts to map the associations between five air pollutants (PM2.5, O3, SO2, NO2, and CO) and two COVID-19 outcomes (incidence and mortality) at the state level. The attributed cases and deaths were then mapped at the county level. This study included 3108 counties from 49 states within the continental USA. The county-level air pollutant concentrations from 2017 to 2019 were used as long-term exposures, and the county-level cumulative COVID-19 cases and deaths through May 13, 2022, were used as outcomes. Results showed that considerably heterogeneous associations and attributable COVID-19 burdens were found in the USA. The COVID-19 outcomes in the western and northeastern states appeared to be unaffected by any of the five pollutants. The east of the USA bore the greatest COVID-19 burdens attributable to air pollution because of its high pollutant concentrations and significantly positive associations. PM2.5 and CO were significantly positively associated with COVID-19 incidence in 49 states on average, whereas NO2 and SO2 were significantly positively associated with COVID-19 mortality. The remaining associations between air pollutants and COVID-19 outcomes were not statistically significant. Our study provided implications regarding where a major concern should be placed on a specific air pollutant for COVID-19 control and prevention, as well as where and how to conduct additional individual-based validation research in a cost-effective manner.

CovInter: interaction data between coronavirus RNAs and host proteins.

Coronavirus has brought about three massive outbreaks in the past two decades. Each step of its life cycle invariably depends on the interactions among virus and host molecules. The interaction between virus RNA and host protein (IVRHP) is unique compared to other virus-host molecular interactions and represents not only an attempt by viruses to promote their translation/replication, but also the host's endeavor to combat viral pathogenicity. In other words, there is an urgent need to develop a database for providing such IVRHP data. In this study, a new database was therefore constructed to describe the interactions between coronavirus RNAs and host proteins (CovInter). This database is unique in (a) unambiguously characterizing the interactions between virus RNA and host protein, (b) comprehensively providing experimentally validated biological function for hundreds of host proteins key in viral infection and (c) systematically quantifying the differential expression patterns (before and after infection) of these key proteins. Given the devastating and persistent threat of coronaviruses, CovInter is highly expected to fill the gap in the whole process of the 'molecular arms race' between viruses and their hosts, which will then aid in the discovery of new antiviral therapies. It's now free and publicly accessible at: https://idrblab.org/covinter/.

Mental condition and function of resilience among families of frontline medical workers during COVID-19: Potential influencing factors and mediating effect.

BACKGROUND: Studying the role of psychological resilience in self-perceived stress and mental disorders among family members of medical workers can help us understand its importance in mental health care and guide us to develop psychological intervention strategies for family members of medical workers. METHODS: A total of 671 family members of medical workers were enrolled. Self-perceived stress, resilience, depression symptoms, anxiety symptoms, and post-traumatic stress disorder (PTSD) symptoms were measured in our research. RESULTS: The prevalence of anxiety, depression, and PTSD symptoms among relatives of medical workers were 49.0 %, 12.2 %, and 20.3 % respectively during the COVID-19 epidemic. According to the Multivariate regression model, compared with family members of doctor, family members of nurse and medical technologists were more likely to report anxiety symptoms. Female members of medical staff were more likely to have PTSD symptoms than male counterparts; and family members of medical technologist appeared to less likely have PTSD symptoms than family members of either doctor or nurse. The mediation analysis confirmed that mental resilience mediated the relationship between self-perceived stress and anxiety symptoms. LIMITATIONS: Single cross-sectional study design without the follow-up comparative analysis, only self-reported measurements were adopted, and inadequate pre-set demographic variables. CONCLUSIONS: To the best of our knowledge, our study firstly demonstrated the risk of psychological distress present in the family members of medical providers during the COVID-19 epidemic. Meanwhile, our findings highlighted the importance of mental resilience in family members of frontline medical workers as it mediated the relationship between self-perceived stress and anxiety symptoms.

Optimal control strategies of SARS-CoV-2 Omicron supported by invasive and dynamic models.

BACKGROUND: There is a raising concern of a higher infectious Omicron BA.2 variant and the latest BA.4, BA.5 variant, made it more difficult in the mitigation process against COVID-19 pandemic. Our study aimed to find optimal control strategies by transmission of dynamic model from novel invasion theory. METHODS: Based on the public data sources from January 31 to May 31, 2022, in four cities (Nanjing, Shanghai, Shenzhen and Suzhou) of China. We segmented the theoretical curves into five phases based on the concept of biological invasion. Then, a spatial autocorrelation analysis was carried out by detecting the clustering of the studied areas. After that, we choose a mathematical model of COVID-19 based on system dynamics methodology to simulate numerous intervention measures scenarios. Finally, we have used publicly available migration data to calculate spillover risk. RESULTS: Epidemics in Shanghai and Shenzhen has gone through the entire invasion phases, whereas Nanjing and Suzhou were all ended in the establishment phase. The results indicated that Rt value and public health and social measures (PHSM)-index of the epidemics were a negative correlation in all cities, except Shenzhen. The intervention has come into effect in different phases of invasion in all studied cities. Until the May 31, most of the spillover risk in Shanghai remained above the spillover risk threshold (18.81-303.84) and the actual number of the spillovers (0.94-74.98) was also increasing along with the time. Shenzhen reported Omicron cases that was only above the spillover risk threshold (17.92) at the phase of outbreak, consistent with an actual partial spillover. In Nanjing and Suzhou, the actual number of reported cases did not exceed the spillover alert value. CONCLUSIONS: Biological invasion is positioned to contribute substantively to understanding the drivers and mechanisms of the COVID-19 spread and outbreaks. After evaluating the spillover risk of cities at each invasion phase, we found the dynamic zero-COVID strategy implemented in four cities successfully curb the disease epidemic peak of the Omicron variant, which was highly correlated to the way to perform public health and social measures in the early phases right after the invasion of the virus.

Inhibitors of HIV-1 and Cathepsin L Proteases Identified from the Insect Gall of Hypericum kouytchense.

Hypericum kouytchense Lévl is a semi-evergreen plant of the Hypericaceae family. Its roots and seeds have been used in a number of traditional remedies for antipyretic, detoxification, anti-inflammatory, antimicrobial and antiviral functions. However, to date, no bioactivity compounds have been characterized from the insect gall of H. kouytchens. In this study, we evaluated the antiviral activities of different extracts from the insect gall of H. kouytchen against cathepsin L, HIV-1 and renin proteases and identified the active ingredients using UPLC-HRMS. Four different polar extracts (HW, H30, H60 and H85) of the H. kouytchense insect gall exhibited antiviral activities with IC50 values of 10.0, 4.0, 3.2 and 17.0 µg/mL against HIV-1 protease; 210.0, 34.0, 24.0 and 30.0 µg/mL against cathepsin L protease; and 180.0, 65.0, 44.0 and 39.0 µg/mL against human renin, respectively. Ten compounds were identified and quantified in the H. kouytchense insect gall extracts. Epicatechin, eriodictyol and naringenin chalcone were major ingredients in the extracts with contents ranging from 3.9 to 479.2 µg/mg. For HIV-1 protease, seven compounds showed more than 65% inhibition at a concentration of 1000.0 µg/mL, especially for hypericin and naringenin chalcone with IC50 values of 1.8 and 33.0 µg/mL, respectively. However, only hypericin was active against cathepsin L protease with an IC50 value of 17100.0 µg/mL, and its contents were from 0.99 to 11.65 µg/mg. Furthermore, we attempted to pinpoint the interactions between the active compounds and the proteases using molecular docking analysis. Our current results imply that the extracts and active ingredients could be further formulated and/or developed for potential prevention and treatment of HIV or SARS-CoV-2 infections.

The impact of multi-level interventions on the second-wave SARS-CoV-2 transmission in China.

BACKGROUND: A re-emergence of COVID-19 occurred in the northeast of China in early 2021. Different levels of non-pharmaceutical interventions, from mass testing to city-level lockdown, were implemented to contain the transmission of SARS-CoV-2. Our study is aimed to evaluate the impact of multi-level control measures on the second-wave SARS-CoV-2 transmission in the most affected cities in China. METHODS: Five cities with over 100 reported COVID-19 cases within one month from Dec 2020 to Feb 2021 were included in our analysis. We fitted the exponential growth model to estimate basic reproduction number (R0), and used a Bayesian approach to assess the dynamics of the time-varying reproduction number (Rt). We fitted linear regression lines on Rt estimates for comparing the decline rates of Rt across cities, and the slopes were tested by analysis of covariance. The effect of non-pharmaceutical interventions (NPIs) was quantified by relative Rt reduction and statistically compared by analysis of variance. RESULTS: A total of 2,609 COVID-19 cases were analyzed in this study. We estimated that R0 all exceeded 1, with the highest value of 3.63 (1.36, 8.53) in Haerbin and the lowest value of 2.45 (1.44, 3.98) in Shijiazhuang. Downward trends of Rt were found in all cities, and the starting time of Rt < 1 was around the 12th day of the first local COVID-19 cases. Statistical tests on regression slopes of Rt and effect of NPIs both showed no significant difference across five cities (P = 0.126 and 0.157). CONCLUSION: Timely implemented NPIs could control the transmission of SARS-CoV-2 with low-intensity measures for places where population immunity has not been established.

The effect of COVID-19 restrictions on atmospheric new particle formation in Beijing

During the COVID-19 lockdown, the dramatic reduction of anthropogenic emissions provided a unique opportunity to investigate the effects of reduced anthropogenic activity and primary emissions on atmospheric chemical processes and the consequent formation of secondary pollutants. Here, we utilize comprehensive observations to examine the response of atmospheric new particle formation (NPF) to the changes in the atmospheric chemical cocktail. We find that the main clustering process was unaffected by the drastically reduced traffic emissions, and the formation rate of 1.5 nm particles remained unaltered. However, particle survival probability was enhanced due to an increased particle growth rate (GR) during the lockdown period, explaining the enhanced NPF activity in earlier studies. For GR at 1.5–3 nm, sulfuric acid (SA) was the main contributor at high temperatures, whilst there were unaccounted contributing vapors at low temperatures. For GR at 3–7 and 7–15 nm, oxygenated organic molecules (OOMs) played a major role. Surprisingly, OOM composition and volatility were insensitive to the large change of atmospheric NOx concentration;instead the associated high particle growth rates and high OOM concentration during the lockdown period were mostly caused by the enhanced atmospheric oxidative capacity. Overall, our findings suggest a limited role of traffic emissions in NPF.

The impact of attitude toward peer interaction on middle school students' problem-solving self-efficacy during the COVID-19 pandemic.

The outbreak of the COVID-19 epidemic has promoted the popularity of online learning, but has also exposed some problems, such as a lack of interaction, resulting in loneliness. Against this background, students' attitudes toward peer interaction may have become even more important. In order to explore the impact of attitude toward peer interaction on students' mindset including online learning motivation and critical thinking practice that could affect their problem-solving self-efficacy during the COVID-19 pandemic, we developed and administered a questionnaire, receiving 1,596 valid responses. The reliability and validity of the questionnaire were re-tested, and structural equation modeling was applied. It was found that attitude toward peer interaction could positively predict middle school students' online learning motivation and critical thinking. Learning motivation and critical thinking also positively supported problem-solving self-efficacy. It is expected that the results of this study can be a reference for teachers to adopt student-centered online learning in problem solving courses.

Dual Inhibition of HIV-1 and Cathepsin L Proteases by Sarcandra glabra.

The COVID-19 pandemic continues to impose a huge threat on human health due to rapid viral mutations. Thus, it is imperative to develop more potent antivirals with both prophylactic and treatment functions. In this study, we screened for potential antiviral compounds from Sarcandra glabra (SG) against Cathepsin L and HIV-1 proteases. A FRET assay was applied to investigate the inhibitory effects and UPLC-HRMS was employed to identify and quantify the bioactive components. Furthermore, molecular docking was carried out to get a glimpse of the binding of active compounds to the proteases. Our results showed that the SG extracts (SGW, SG30, SG60, and SG85) inhibited HIV-1 protease with an IC50 of 0.003~0.07 mg/mL and Cathepsin L protease with an IC50 of 0.11~0.26 mg/mL. Fourteen compounds were identified along with eight quantified from the SG extracts. Chlorogenic acid, which presented in high content in the extracts (12.7~15.76 µg/mg), possessed the most potent inhibitory activity against HIV-1 protease (IC50 = 0.026 mg/mL) and Cathepsin L protease (inhibition: 40.8% at 0.01 mg/mL). Thus, SG extracts and the active ingredients could potentially be used to prevent/treat viral infections, including SARS-CoV-2, due to their dual-inhibition functions against viral proteases.

COVID-19 lockdown introduces human mobility pattern changes for both Guangdong-Hong Kong-Macao greater bay area and the San Francisco bay area.

In response to the coronavirus disease 2019 (COVID-19) pandemic, various countries have sought to control COVID-19 transmission by introducing non-pharmaceutical interventions. Restricting population mobility, by introducing social distancing, is one of the most widely used non-pharmaceutical interventions. Although similar population mobility restriction interventions were introduced, their impacts on COVID-19 transmission are often inconsistent across different regions and different time periods. These differences may provide critical information for tailoring COVID-19 control strategies. In this paper, anonymized high spatiotemporal resolution mobile-phone location data were employed to empirically analyze and quantify the impact of lockdowns on population mobility. Both the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) in China and the San Francisco Bay Area (SBA) in the United States were studied. In response to the lockdowns, a general reduction in population mobility was observed, but the structural changes in mobility are very different between the two bays: 1) GBA mobility decreased by approximately 74.0-80.1% while the decrease of SBA was about 25.0-42.1%; 2) compared to SBA, the GBA had smoother volatility in daily volume during the lockdown. The volatility change indexes for GBA and SBA were 2.55% and 7.52%, respectively; 3) the effect of lockdown on short- to long-distance mobility was similar in GBA while the medium- and long-distance impact was more pronounced in SBA.

Pregnant Women’s Anxiety and Depression Symptoms and Influence Factors in the COVID-19 Pandemic in Changzhou, China

Background With the coronavirus disease 2019 (COVID-19) pandemic, pregnant women’s psychological conditions have become a global challenge. The aim of the study was to identify the prevalence of anxiety and depression symptoms and analyze their influence factors among pregnant women in Changzhou, China during the COVID-19 pandemic and provide them with appropriate healthcare strategies. Methods Participants were 681 pregnant women who visited various obstetrics and gynecology clinics in Changzhou, China between 25 February 2020 and 7 March 2020. They were asked to complete an online survey. The Generalized Anxiety Disorder Scale-7 (GAD-7) and Patient Health Questionnaire-9 (PHQ-9) were used to detect anxious and depressive symptoms. The chi-squared test and multivariate logistic regression analysis were carried out to examine the associated factors in these groups. Results Overall, the prevalence rates of anxiety and depression symptoms among pregnant women were 31.72 and 36.12%, respectively, but most of them were mild. Having an irregular diet with poor subjective sleep quality, perceiving little family support, spending too much time on news related to the coronavirus, and having severe subjective life impact by the coronavirus were related to anxiety and depression symptoms. In addition, lack of physical exercise and exposure to electronic screens over 5 h per day were associated with depression symptoms. Conclusion Pregnant women with an irregular diet, poor sleep quality, little family support, excessive attention to COVID-19 news, and lives impacted by the coronavirus severely are at high risk for anxiety and depression symptoms during the COVID-19 pandemic. This indicates that targeted measures to address mental health in pregnant women during the pandemic period are needed.

Multiplex metal-detection based assay (MMDA) for COVID-19 diagnosis and identification of disease severity biomarkers†‡ † Dedicated to Prof. Zhifang Chai on the occasion of his 80th birthday.‡ Electronic supplementary information (ESI) available. See DOI: 10.1039/d1sc05852e

The ongoing COVID-19 pandemic caused by SARS-CoV-2 highlights the urgent need to develop sensitive methods for diagnosis and prognosis. To achieve this, multidimensional detection of SARS-CoV-2 related parameters including virus loads, immune response, and inflammation factors is crucial. Herein, by using metal-tagged antibodies as reporting probes, we developed a multiplex metal-detection based assay (MMDA) method as a general multiplex assay strategy for biofluids. This strategy provides extremely high multiplexing capability (theoretically over 100) compared with other reported biofluid assay methods. As a proof-of-concept, MMDA was used for serologic profiling of anti-SARS-CoV-2 antibodies. The MMDA exhibits significantly higher sensitivity and specificity than ELISA for the detection of anti-SARS-CoV-2 antibodies. By integrating the high dimensional data exploration/visualization tool (tSNE) and machine learning algorithms with in-depth analysis of multiplex data, we classified COVID-19 patients into different subgroups based on their distinct antibody landscape. We unbiasedly identified anti-SARS-CoV-2-nucleocapsid IgG and IgA as the most potently induced types of antibodies for COVID-19 diagnosis, and anti-SARS-CoV-2-spike IgA as a biomarker for disease severity stratification. MMDA represents a more accurate method for the diagnosis and disease severity stratification of the ongoing COVID-19 pandemic, as well as for biomarker discovery of other diseases. A MMDA platform is developed by using metal-tagged antibodies as reporting probes combined with machine learning algorithms, as a general strategy for highly multiplexed biofluid assay.

Hyperglycemia and blood glucose deterioration are risk factors for severe COVID-19 with diabetes: A two-center cohort study.

We aimed to assess whether blood glucose control can be used as predictors for the severity of 2019 coronavirus disease (COVID-19) and to improve the management of diabetic patients with COVID-19. A two-center cohort with a total of 241 confirmed cases of COVID-19 with definite outcomes was studied. After the diagnosis of COVID-19, the clinical data and laboratory results were collected, the fasting blood glucose levels were followed up at initial, middle stage of admission and discharge, the severity of the COVID-19 was assessed at any time from admission to discharge. Hyperglycemia patients with COVID-19 were divided into three groups: good blood glucose control, fair blood glucose control, and blood glucose deterioration. The relationship of blood glucose levels, blood glucose control status, and severe COVID-19 were analyzed by univariate and multivariable regression analysis. In our cohort, 21.16% were severe cases and 78.84% were nonsevere cases. Admission hyperglycemia (adjusted odds ratio [aOR], 1.938; 95% confidence interval [95% CI], 1.387-2.707), mid-term hyperglycemia (aOR, 1.758; 95% CI, 1.325-2.332), and blood glucose deterioration (aOR, 22.783; 95% CI, 2.661-195.071) were identified as the risk factors of severe COVID-19. Receiver operating characteristic (ROC) curve analysis, reaching an area under ROC curve of 0.806, and a sensitivity and specificity of 80.40% and 68.40%, respectively, revealed that hyperglycemia on admission and blood glucose deterioration of diabetic patients are potential predictive factors for severe COVID-19. Our results indicated that admission hyperglycemia and blood glucose deterioration were positively correlated with the risk factor for severe COVID-19, and deterioration of blood glucose may be more likely to the occurrence of severe illness in COVID-19.

Assessment of Financial Toxicity Among Patients With Advanced Lung Cancer in Western China.

Background: Lung cancer is the leading source of cancer-caused disability-adjusted life years. Medical cost burden impacts the well-being of patients through reducing income, cutting daily expenses, curtailing leisure activities, and depleting exhausting savings. The COmprehensive Score for Financial Toxicity (COST) was created and validated by De Souza and colleagues. Our study intends to measure the financial burdens of cancer therapy and investigate the link between financial toxicity and health-related quality of life (HRQoL) in an advanced lung cancer population. Methods: Patients aged ≥ 18 years with confirmed stage III to IV lung cancer were eligible. The COST questionnaire verified by de Souza et al. was used to identify financial toxicity. Multivariable linear regression analysis with log transformation univariate analysis and Pearson correlations were used to perform the analysis. Results: The majority of the patients (90.8%, n = 138/152) had an annual income of $50,000 ($7,775). The cohort's insurance situation was as follows: 64.5% of the cohort had social insurance, 20.4% had commercial insurance, and 22.0% had both. Patients who were younger age (50-59, P < 0.001), employed but on sick leave, and had lower income reported increased levels of financial toxicity (P < 0.05). The risk factors for high financial toxicity: (i) younger age (50-59), (ii) <1 month of savings, and (iii) being employed but on sick leave. Increased financial toxicity is moderately correlated with a decrease in QoL. Conclusion: Poorer psychological status and specific demographics are linked to increased financial toxicity (lower COST). Financial toxicity has a modest relationship with HRQoL and may have a clear link with HRQoL measurements.

Multiplex metal-detection based assay (MMDA) for COVID-19 diagnosis and identification of disease severity biomarkers.

The ongoing COVID-19 pandemic caused by SARS-CoV-2 highlights the urgent need to develop sensitive methods for diagnosis and prognosis. To achieve this, multidimensional detection of SARS-CoV-2 related parameters including virus loads, immune response, and inflammation factors is crucial. Herein, by using metal-tagged antibodies as reporting probes, we developed a multiplex metal-detection based assay (MMDA) method as a general multiplex assay strategy for biofluids. This strategy provides extremely high multiplexing capability (theoretically over 100) compared with other reported biofluid assay methods. As a proof-of-concept, MMDA was used for serologic profiling of anti-SARS-CoV-2 antibodies. The MMDA exhibits significantly higher sensitivity and specificity than ELISA for the detection of anti-SARS-CoV-2 antibodies. By integrating the high dimensional data exploration/visualization tool (tSNE) and machine learning algorithms with in-depth analysis of multiplex data, we classified COVID-19 patients into different subgroups based on their distinct antibody landscape. We unbiasedly identified anti-SARS-CoV-2-nucleocapsid IgG and IgA as the most potently induced types of antibodies for COVID-19 diagnosis, and anti-SARS-CoV-2-spike IgA as a biomarker for disease severity stratification. MMDA represents a more accurate method for the diagnosis and disease severity stratification of the ongoing COVID-19 pandemic, as well as for biomarker discovery of other diseases.