Safety and immunogenicity of a heterologous booster with an RBD virus-like particle vaccine following two- or three-dose inactivated COVID-19 vaccine (preprint)

Background: Reduced protection against COVID-19 due to the waning vaccine-induced immunity over time and emergence of immune-evading SARS-CoV-2 variants of concern (VOCs) indicate the need for vaccine boosters. LYB001 is an innovative recombinant SARS-CoV-2 vaccine which displays a repetitive array of the Spike glycoprotein's receptor binding domain (RBD) on a virus-like particle (VLP) vector to boost the immune system, produced using a Covalink plug-and-display protein binding technology. Methods: The safety and immunogenicity of LYB001 as a heterologous booster at an interval of 6-12 months was assessed in 119 participants receiving a booster with (1) 30g LYB001 (I-I-30L) or CoronaVac (I-I-C), (2) escalated dose of 60g LYB001 (I-I-60L) or CoronaVac in a ratio of 2:1 after two-dose primary series of inactivated COVID-19 vaccine in part 1 of this study, or (3) 30g LYB001 (I-I-I-30L) after three-dose primary series of inactivated COVID-19 vaccine in part 2 of this study. Results: A well-tolerated reactogenicity profile was observed for LYB001 as a heterologous booster, with adverse reactions predominantly being mild in severity and transient. The peak neutralizing antibody response was observed at 28 days after booster, with GMT (95%CI) against prototype SARS-CoV-2 being 1237.8 (747.2, 2050.6), 554.3 (374.6, 820.2), 181.9 (107.6, 307.6) and 1200.2 (831.5, 1732.3) in the I-I-30L, I-I-60L, I-I-C, and I-I-I-30L groups, respectively. LYB001 also elicited a cross-neutralizing antibody response against the BA.4/5 strain, dominant during the study period, with GMT being 201.1 (102.7, 393.7), 63.0 (35.1, 113.1), 29.2 (16.9, 50.3) and 115.3 (63.9, 208.1) at 28 days after booster in the I-I-30L, I-I-60L, I-I-C, and I-I-I-30L groups, respectively. Additionally, RBD-specific IFN-{gamma}, IL-2, IL-4 secreting T cells, as measured by ELISpot assay, dramatically increased (more than 10 times versus baseline) at 14 days after a single LYB001 booster. Conclusions: Our data confirm the favorable safety and immunogenicity profile of the LYB001 vaccine when used as a heterologous booster, and support the continued clinical development of this promising candidate that utilize VLP platform to provide protection against COVID-19.

Challenges of COVID-19 Case Forecasting in the US, 2020-2021 (preprint)

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub (https://covid19forecasthub.org). We evaluated approximately 9.7 million forecasts of weekly state-level COVID-19 cases for predictions 1-4 weeks into the future submitted by 24 teams from August 2020 to December 2021. We assessed coverage of central prediction intervals and weighted interval scores (WIS), adjusting for missing forecasts relative to a baseline forecast, and used a Gaussian generalized estimating equation (GEE) model to evaluate differences in skill across epidemic phases that were defined by the effective reproduction number. Overall, we found high variation in skill across individual models, with ensemble-based forecasts outperforming other approaches. Forecast skill relative to the baseline was generally higher for larger jurisdictions (e.g., states compared to counties). Over time, forecasts generally performed worst in periods of rapid changes in reported cases (either in increasing or decreasing epidemic phases) with 95% prediction interval coverage dropping below 50% during the growth phases of the winter 2020, Delta, and Omicron waves. Ideally, case forecasts could serve as a leading indicator of changes in transmission dynamics. However, while most COVID-19 case forecasts outperformed a naive baseline model, even the most accurate case forecasts were unreliable in key phases. Further research could improve forecasts of leading indicators, like COVID-19 cases, by leveraging additional real-time data, addressing performance across phases, improving the characterization of forecast confidence, and ensuring that forecasts were coherent across spatial scales. In the meantime, it is critical for forecast users to appreciate current limitations and use a broad set of indicators to inform pandemic-related decision making. Author SummaryAs SARS-CoV-2 began to spread throughout the world in early 2020, modelers played a critical role in predicting how the epidemic could take shape. Short-term forecasts of epidemic outcomes (for example, infections, cases, hospitalizations, or deaths) provided useful information to support pandemic planning, resource allocation, and intervention. Yet, infectious disease forecasting is still a nascent science, and the reliability of different types of forecasts is unclear. We retrospectively evaluated COVID-19 case forecasts, which were often unreliable. For example, forecasts did not anticipate the speed of increase in cases in early winter 2020. This analysis provides insights on specific problems that could be addressed in future research to improve forecasts and their use. Identifying the strengths and weaknesses of forecasts is critical to improving forecasting for current and future public health responses.

Characterization and Evaluation of the Pathogenicity of a Natural Gene-Deleted Transmissible Gastroenteritis Virus in China

Porcine transmissible gastroenteritis virus is the major pathogen that causes fatal diarrhea in newborn piglets. In this study, a TGEV strain was isolated from the small intestine of diarrhea piglets in Sichuan Province, China, and designated SC2021. The complete genomic sequence of TGEV SC2021 was 28561 bp, revealing a new natural deletion TGEV strain. Based on phylogenetic analyses, TGEV SC2021 belonged to the Miller cluster and was closely related to CN strains. The newborn piglets orally challenged with TGEV SC2021 showed typical watery diarrhea. In addition, macro and micropathological changes in the lungs and intestines were observed. In conclusion, we isolated a new natural deletion virus strain and confirmed that the virus strain has high pathogenicity in newborn piglets. Moreover, macroscopic and microscopic lesions were observed in the lungs and intestines of all TGEV SC2021-infected piglets. In summary, we isolated a new natural deletion TGEV strain and demonstrated that the natural deletion strain showed high pathogenicity in newborn piglets. These data enrich the diversity of TGEV strains and help us to understand the genetic evolution and molecular pathogenesis of TGEV.

The post-discharge coping difficulty of puerperal women in a middle and low-income tourist city during the COVID-19 epidemic: a cross-sectional study (preprint)

Background Since the coronavirus disease 2019 (COVID-19) pandemic outbreak, the incidence of mental health problems in perinatal women has been high, and particularly prominent in China which was the first country affected by COVID-19. This paper aims to investigate the current situation of maternal coping difficulties after discharge during COVID-19, analyze the related factors and provide a theoretical basis for targeted continuing care.Methods General information questionnaires (the Perinatal Maternal Health Literacy Scale, Postpartum Social Support Scale and Post-Discharge Coping Difficulty Scale-New Mother Form) were used to investigate 226 puerperal women in the third week of puerperium. The influencing factors were analyzed by single factor analysis, correlation and multiple linear regression.Results The total score of coping difficulties after discharge was 48.92 ± 12.05. At the third week after delivery, the scores of health literacy and social support were 21.34 ± 5.18 and 47.96 ± 12.71. There were negative correlations among health literacy, social support and coping difficulties after discharge (γ = -0.34, γ = -0.38, P < 0.001). Health literacy, social support, primipara, family income and education level were the main factors influencing maternal coping difficulties after discharge.Conclusion During the COVID-19 epidemic, puerperal women in a low- and middle-income city had moderate coping difficulties after discharge and were affected by many factors. To meet the different needs of parturients and improve their psychological coping ability, medical staff should perform adequate assessment of social resources relevant to parturients and their families when they are discharged, so they can smoothly adapt to the role of mothers.

Counterfactual Neural Temporal Point Process for Estimating Causal Influence of Misinformation on Social Media (preprint)

Recent years have witnessed the rise of misinformation campaigns that spread specific narratives on social media to manipulate public opinions on different areas, such as politics and healthcare. Consequently, an effective and efficient automatic methodology to estimate the influence of the misinformation on user beliefs and activities is needed. However, existing works on misinformation impact estimation either rely on small-scale psychological experiments or can only discover the correlation between user behaviour and misinformation. To address these issues, in this paper, we build up a causal framework that model the causal effect of misinformation from the perspective of temporal point process. To adapt the large-scale data, we design an efficient yet precise way to estimate the Individual Treatment Effect(ITE) via neural temporal point process and gaussian mixture models. Extensive experiments on synthetic dataset verify the effectiveness and efficiency of our model. We further apply our model on a real-world dataset of social media posts and engagements about COVID-19 vaccines. The experimental results indicate that our model recognized identifiable causal effect of misinformation that hurts people's subjective emotions toward the vaccines.

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.

The Flare of Rheumatic Disease After SARS-CoV-2 Vaccination: A Review

As the coronavirus disease 2019 (COVID-19) pandemic continues worldwide, vaccination has been considered an effective measure to protect people from the COVID-19 and end the pandemic. However, for patients with rheumatic diseases (RD), concern for the induction of RD flare may combat the enthusiasm for vaccination. In general, current evidence doesn’t support the increased risk of disease flare after COVID-19 vaccination. However, the disease flare of RDs may be triggered by COVID-19 vaccinations, especially for patients with high disease activity. Most of these flares after vaccination are mild and need no treatment escalation. Considering the benefits and risks, RD patients are recommended to receive the COVID-19 vaccination but should be vaccinated when the RDs are in stable states.

Rapid PCR-Based Nanopore Adaptive Sequencing Improves Sensitivity and Timeliness of Viral Clinical Detection and Genome Surveillance

Nanopore sequencing has been widely used for the real-time detection and surveillance of pathogens with portable MinION. Nanopore adaptive sequencing can enrich on-target sequences without additional pretreatment. In this study, the performance of adaptive sequencing was evaluated for viral genome enrichment of clinical respiratory samples. Ligation-based nanopore adaptive sequencing (LNAS) and rapid PCR-based nanopore adaptive sequencing (RPNAS) workflows were performed to assess the effects of enrichment on nasopharyngeal swab samples from human adenovirus (HAdV) outbreaks. RPNAS was further applied for the enrichment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from nasopharyngeal swab samples to evaluate sensitivity and timeliness. The RPNAS increased both the relative abundance (7.87–12.86-fold) and data yield (1.27–2.15-fold) of HAdV samples, whereas the LNAS increased only the relative abundance but had no obvious enrichment on the data yield. Compared with standard nanopore sequencing, RPNAS detected the SARS-CoV-2 reads from two low-abundance samples, increased the coverage of SARS-CoV-2 by 36.68–98.92%, and reduced the time to achieve the same coverage. Our study highlights the utility of RPNAS for virus enrichment directly from clinical samples, with more on-target data and a shorter sequencing time to recover viral genomes. These findings promise to improve the sensitivity and timeliness of rapid identification and genomic surveillance of infectious diseases.

The Impact of Uncertainties on Crude Oil Prices: Based on a Quantile-on-Quantile Method

There has always been a complex relationship between uncertainty and crude oil prices. Three types of uncertainty, i.e., economic policy uncertainty, geopolitical risk uncertainty, and climate policy uncertainty (EPU, GPR, and CPU for short), have exacerbated abnormal fluctuations in the energy market, making crude oil prices volatile more and more frequently, especially from the perspective of the financial attribute of crude oil. Based on the time-series data related to uncertainties and crude oil prices from December 2001 to March 2021, this paper uses the quantile-on-quantile regression (QQR) method to explore the overall impact of various uncertainties on crude oil prices. Moreover, this paper adopts the QQR method based on the wavelet transform to investigate the heterogeneous effects of various uncertainties on crude oil prices at different time scales. The following conclusions are obtained. First, there are significant differences in the overall impact of the three types of uncertainties on crude oil prices, and this heterogeneity is reflected in quantiles of the peak impact intensity, the impact direction, and the fluctuation change. Second, the impact intensities of the three types of uncertainties on crude oil prices are significantly different at different time scales. This is mainly reflected in the different periods of significant impact of the three uncertainties on crude oil prices. Third, the impact directions and fluctuations of the three types of uncertainties on crude oil prices are heterogeneous at different time scales.

Respiratory mucosal vaccination of peptide-poloxamine-DNA nanoparticles provides complete protection against lethal SARS-CoV-2 challenge (preprint)

The ongoing SARS-CoV-2 pandemic represents a brutal reminder of the continual threat of mucosal infectious diseases. Mucosal immunity may provide robust protection at the predominant sites of SARS-CoV-2 infection. However, it remains unclear whether respiratory mucosal administration of DNA vaccines could confer protective immune responses against SARS-CoV-2 challenge due to the insurmountable barriers posed by the airway. Here, we applied self-assembled peptide-poloxamine nanoparticles with mucus-penetrating properties for pulmonary inoculation of a COVID-19 DNA vaccine (pSpike/PP-sNp). Not only displays the pSpike/PP-sNp superior gene-transfection and favorable biocompatibility in the mouse airway, but pSpike/PP-sNp promotes a tripartite immunity consisting of systemic, cellular and mucosal immune responses that are characterized by mucosal IgA secretion, high levels of neutralizing antibodies, and resident memory phenotype T-cell responses in the lungs of mice. Most importantly, pSpike/PP-sNp completely eliminates SARS-CoV-2 infection in both upper and lower respiratory tracts and enables 100% survival rate of mice following lethal SARS-CoV-2 challenge. Our findings indicate PP-sNp might be a promising platform in mediating DNA vaccines to elicit all-around mucosal immunity against SARS-CoV-2.

A Bispecific Antibody Targeting RBD and S2 Potently Neutralizes SARS-CoV-2 Omicron and Other Variants of Concern (preprint)

Emerging severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) variants, especially the Omicron variant, have impaired the efficacy of existing vaccines and most therapeutic antibodies, highlighting the need for additional antibody-based tools that can efficiently neutralize emerging SARS-CoV-2 variants. The use of a "single" agent to simultaneously target multiple distinct epitopes on the spike is desirable to overcome the neutralizing escape of SARS-CoV-2 variants. Herein, we generated a human-derived IgG-like bispecific antibody (bsAb), Bi-Nab35B5-47D10, which successfully retained the specificity and simultaneously bound to the two distinct epitopes on RBD and S2. Bi-Nab35B5-47D10 showed improved spike binding breadth among wild-type (WT) SARS-CoV-2, variants of concern (VOCs) and variants being monitored (VBMs) compared with its parental mAbs. Furthermore, pseudotyped virus neutralization demonstrated that Bi-Nab35B5-47D10 can efficiently neutralize VBMs including Alpha (B.1.1.7), Beta (B.1.351) and Kappa (B.1.617.1) and VOCs including Delta (B.1.617.2), Omicron BA.1 and Omicron BA.2. Crucially, Bi-Nab35B5-47D10 substantially improved neutralizing activity against Omicron BA.1 (IC50= 27.3 ng/mL) and Omicron BA.2 (IC50= 121.1 ng/mL) compared with their parental mAbs. Therefore, Bi-Nab35B5-47D10 represents a potential effective countermeasure against SARS-CoV-2 Omicron and other variants of concern.

Preclinical evaluation of RQ3013, a broad-spectrum mRNA vaccine against SARS-CoV-2 variants (preprint)

The global emergence of SARS-CoV-2 variants has led to increasing breakthrough infections in vaccinated populations, calling for an urgent need to develop more effective and broad-spectrum vaccines to combat COVID-19. Here we report the preclinical development of RQ3013, an mRNA vaccine candidate intended to bring broad protection against SARS-CoV-2 variants of concern (VOCs). RQ3013, which contains pseudouridine-modified mRNAs formulated in lipid nanoparticles, encodes the spike(S) protein harboring a combination of mutations responsible for immune evasion of VOCs. Here we characterized the expressed S immunogen and evaluated the immunogenicity, efficacy, and safety of RQ3013 in various animal models. RQ3013 elicited robust immune responses in mice, hamsters, and nonhuman primates (NHP). It can induce high titers of antibodies with broad cross-neutralizing ability against the Wild-type, B.1.1.7, B.1.351, B.1.617.2, and the omicron B.1.1.529 variants. In mice and NHP, two doses of RQ3013 protected the upper and lower respiratory tract against infection by SARS-CoV-2 and its variants. We also proved the safety of RQ3013 in NHP models. Our results provided key support for the evaluation of RQ3013 in clinical trials.

Rapid differentiation of SARS-CoV-2 variants on a nanotechnology enhanced DNA-chip (preprint)

With the persistence of the COVID-19 pandemic caused primarily by constant viral mutations, rapid identification of different lineages of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by large-scale screening at the point-of-care could be key to monitoring and assessing viral evolutions. Herein, we developed a Fluorescence Enhanced Microarray for Multiplex Analysis of Nucleic acids (FEMMAN) for detecting 8 SARS-CoV-2 variants simultaneously in ~ 3 hours without the need of RNA extraction, opening the possibility of point-of-care testing of multiple SARS-CoV-2 variants while reducing the cost significantly to ~ $ 7 per sample from ~ $100 by Next-Generation Sequencing (NGS). Combined with isothermal amplification, the multiplexed RNA assay achieved single-copy detection sensitivity and single nucleotide variant (SNV) distinction owing to the nanotechnology based plasmonic gold (pGOLD) near-infrared fluorescence enhancing platform. Probing 10 targets of three mutational hotspots in S gene, we differentiated 8 viral lineages (Wild type, Alpha, Beta, Gamma, Delta, Lambda, Mu, and Omicron) of SARS-CoV-2, validated using nasopharyngeal swabs obtained from 127 individuals, achieving a 100% sensitivity and 100% specificity in SARS-CoV-2 detection, and a 91.1% concordance with NGS in variant identification. The scalable, multiplexed FEMMAN assay could shift the paradigm of COVID-19 diagnostic and surveillance from positive/negative assessments to simultaneous lineage identification in large-scale screening, greatly facilitating the global monitoring of SARS-CoV-2 variants.

Temporal variation of gaseous elemental mercury in a northern coastal city in China: Monsoon and COVID-19 lockdown effects

Continuous measurements of gaseous elemental mercury (GEM) were conducted in Qingdao from March 2020 to March 2021. The average concentration of GEM was (2.39 ± 1.07 ng/m3) with a variation range of 0.27–10.78 ng/m3. GEM exhibited a clear pattern of daily variation, with daily peaks occurring between 11:00–13:00. GEM concentrations were higher in winter (2.80 ± 1.28 ng/m3) than that in summer (2.18 ± 1.05 ng/m3). The high winter concentrations were related to coal-fired heating and the increased frequency of polluted weather in northern China. Principal component analysis showed that the main factors affecting GEM concentration were fossil fuel combustion, natural source release and atmospheric diffusion conditions. The anthropogenic emission sources were the main source of GEM in spring and winter, and natural sources of GEM was large in summer. The potential source contribution function suggested that North and Central China were the main potential sources of GEM, and there were large differences in the potential sources of GEM in different seasons. Comparing the GEM in the same time periods in 2018, 2020, and 2021, government policies, temporary lockdown measures for the COVID-19 epidemic, and urban village renovation led to a decreasing trend of GEM concentrations. This study contributes to a better understanding of the effects of long-range transport of air masses and anthropogenic emissions on atmospheric mercury in eastern coastal cities and offshore areas.

Delta/ Omicron and Omicron/BA.2 co-infections occurring in Immunocompromised hosts (preprint)

Concomitant infection of multiple SARS-CoV-2 variants has become an increasing concern, as this scenario increases the likelihood of recombinant variants. Detecting co-infection of SARS-CoV-2 variants is difficult to detect by whole genome sequencing approaches, but genotyping methods facilitate detection. We describe 2 cases of Delta/Omicron and 2 cases of Omicron/ BA.2 co-infection as detected by a multiplex genotyping fragment analysis method. Findings were confirmed by whole genome sequencing. Review of the patient characteristics revealed co-morbidities and conditions which weaken the immune system and may make them more susceptible to harboring SARS-CoV-2 variant co-infections.

Gender-Specific Related Factors for Suicidal Ideation During COVID-19 Pandemic Lockdown Among 5,175 Chinese Adolescents

Background Suicide was an urgent issue during the pandemic period in adolescents. However, few studies were focused on suicide during the coronavirus disease 2019 (COVID-19) pandemic lockdown. Methods An online survey was conducted among 5,175 Chinese adolescents from June 9th to 29th in 2020 to investigate the prevalence of suicidal ideation (SI) during COVID-19 pandemic lockdown. A gender-specific stepwise logistic regression model was used. All analyses were performed with STATA 15.0. Results About 3% of the participants had reported having SI during the COVID-19 pandemic lockdown period. The prevalence of female SI (3.64%, 95% CI: 2.97–4.45%) was higher than that of males (2.39%, 95% CI: 1.88–3.05%) (χ2 = 6.87, p = 0.009). Quarreling with parents [odds ratio (OR) = 9.73, 95% CI: 5.38–17.59], insomnia (OR = 5.28, 95% CI: 2.81–9.93), previous suicide attempt history (OR = 3.68, 95% CI: 1.69–8.03), previous SI history (OR = 2.81, 95% CI: 1.30–6.06), and feeling depressed during pandemic lockdown (OR = 2.26, 95% CI: 1.22–4.18) were positively associated with the males' SI. However, having emptiness inside (OR = 4.39, 95% CI: 2.19–8.79), quarreling with parents (OR = 3.72, 95% CI: 2.16–6.41), insomnia (OR = 3.28, 95% CI: 1.85–5.80), feeling anxious (OR = 2.62, 95% CI: 1.46–4.70), and longing for father's emotional warmth (OR = 0.38, 0.20–0.72) were associated mostly with females' SI. Conclusions Female adolescents, who felt emptiness from their families and their fathers' emotional warmth, were at much higher risk of having SI during COVID-19 lockdown. We must specify a suicide prevention policy and interventions for adolescents in the pandemic crisis based on gender gaps.

Use of Electronic Auscultation in Full Personal Protective Equipment to Detect Ventilation Status in Selective Lung Ventilation: A Randomized Controlled Trial

Chest auscultation is the first procedure performed to detect endotracheal tube malpositioning but conventional stethoscopes do not conform to the personal protective equipment (PPE) protocol during the COVID-19 pandemic. This double-blinded randomized controlled trial evaluated the feasibility of using ear-contactless electronic stethoscope to identify endobronchial blocker established selective lung ventilation, simulating endobronchial intubation during thoracic surgery with full PPE. Conventional and electronic auscultation was performed without and with full PPE, respectively, of 50 patients with selective lung ventilation. The rates of correct ventilation status detection were 86 and 88% in the conventional and electronic auscultation groups (p = 1.00). Electronic auscultation revealed a positive predictive value of 87% (95% CI 77 to 93%), and a negative predictive value of 91% (95% CI 58 to 99%), comparable to the results for conventional auscultation. For detection of the true unilateral lung ventilation, the F1 score and the phi were 0.904 and 0.654, respectively for conventional auscultation;were 0.919 and 0.706, respectively for electronic auscultation. Furthermore, the user experience questionnaire revealed that the majority of participant anesthesiologists (90.5%) rated the audio quality of electronic lung sounds as comparable or superior to that of conventional acoustic lung sounds. In conclusion, electronic auscultation assessments of ventilation status as examined during thoracic surgery in full PPE were comparable in accuracy to corresponding conventional auscultation assessments made without PPE. Users reported satisfactory experience with the electronic stethoscope.

Construction of Large-Scale Misinformation Labeled Datasets from Social Media Discourse using Label Refinement (preprint)

Malicious accounts spreading misinformation has led to widespread false and misleading narratives in recent times, especially during the COVID-19 pandemic, and social media platforms struggle to eliminate these contents rapidly. This is because adapting to new domains requires human intensive fact-checking that is slow and difficult to scale. To address this challenge, we propose to leverage news-source credibility labels as weak labels for social media posts and propose model-guided refinement of labels to construct large-scale, diverse misinformation labeled datasets in new domains. The weak labels can be inaccurate at the article or social media post level where the stance of the user does not align with the news source or article credibility. We propose a framework to use a detection model self-trained on the initial weak labels with uncertainty sampling based on entropy in predictions of the model to identify potentially inaccurate labels and correct for them using self-supervision or relabeling. The framework will incorporate social context of the post in terms of the community of its associated user for surfacing inaccurate labels towards building a large-scale dataset with minimum human effort. To provide labeled datasets with distinction of misleading narratives where information might be missing significant context or has inaccurate ancillary details, the proposed framework will use the few labeled samples as class prototypes to separate high confidence samples into false, unproven, mixture, mostly false, mostly true, true, and debunk information. The approach is demonstrated for providing a large-scale misinformation dataset on COVID-19 vaccines.