Streamlining Social Media Information Retrieval for COVID-19 Research with Deep Learning (preprint)

Objective: Social media-based public health research is crucial for epidemic surveillance, but most studies identify relevant corpora with keyword-matching. This study develops a system to streamline the process of curating colloquial medical dictionaries. We demonstrate the pipeline by curating a UMLS-colloquial symptom dictionary from COVID-19-related tweets as proof of concept. Methods: COVID-19-related tweets from February 1, 2020, to April 30, 2022 were used. The pipeline includes three modules: a named entity recognition module to detect symptoms in tweets; an entity normalization module to aggregate detected entities; and a mapping module that iteratively maps entities to Unified Medical Language System concepts. A random 500 entity sample were drawn from the final dictionary for accuracy validation. Additionally, we conducted a symptom frequency distribution analysis to compare our dictionary to a pre-defined lexicon from previous research. Results: We identified 498,480 unique symptom entity expressions from the tweets. Pre-processing reduces the number to 18,226. The final dictionary contains 38,175 unique expressions of symptoms that can be mapped to 966 UMLS concepts (accuracy = 95%). Symptom distribution analysis found that our dictionary detects more symptoms and is effective at identifying psychiatric disorders like anxiety and depression, often missed by pre-defined lexicons. Conclusions: This study advances public health research by implementing a novel, systematic pipeline for curating symptom lexicons from social media data. The final lexicon's high accuracy, validated by medical professionals, underscores the potential of this methodology to reliably interpret and categorize vast amounts of unstructured social media data into actionable medical insights across diverse linguistic and regional landscapes.

A Portable Self‐Powered Turbine Spirometer for Rehabilitation Monitoring on COVID‐19

Coronavirus disease 2019 (COVID‐19) patients may experience persistent impairment of the lungs after recovery and discharge, which can cause a decline in pulmonary function. Therefore, regular pulmonary function tests are essential for COVID‐19 recovered patients, and portable, home‐based pulmonary function test devices are of great significance during the pandemic. Herein, a portable self‐powered turbine spirometer (PSTS) is designed for respiratory flow measurement and assessment of pulmonary function with high accuracy, humidity resistance, good durability, and low cost. The respiratory airflow can directly drive PSTS to produce a sinusoidal signal with a signal‐to‐noise of 40.64 dB. By utilizing the long short‐term memory (LSTM) model, the flow is successfully predicted, and the "lag‐before‐start” and "spin‐after‐stop” defects of the turbine spirometer are eliminated effectively. For pulmonary function tests, the flow‐volume loop curve can be obtained from PSTS, and pulmonary function parameters such as inspiratory capacity (IC), forced vital capacity (FVC) and forced expiratory volume in the first 1 s (FEV1) can be calculated. The accuracy of IC is over 95%, and others can reach over 97%. A portable smart pulmonary function assessment system is further developed and used to test the pulmonary function of COVID‐19 patients one month after symptom onset, demonstrating potential for assessing rehabilitation trends and long‐term follow‐up of COVID‐19 recovered patients. [ FROM AUTHOR] Copyright of Advanced Materials Technologies is the property of John Wiley & Sons, Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

The Effect of Health Action Process Approach on Adherence to Infection Prevention and Control Measures Among Chinese Healthcare Workers in the Post-pandemic Period of COVID-19 (preprint)

Background: Although the COVID-19 pandemic has been brought under control, strict infection and control measures are still recommended for healthcare workers to prevent the rebound of the pandemic. However, adherence to prevention measures might be decreased due to fatigue caused by the prolonged duration of the pandemic.  Objective: This study examines the effects of social-cognitive factors suggested in the health action process approach on adherence to infection prevention and control measures among Chinese healthcare workers two years after the onset of the COVID-19 pandemic. Methods: A total of 521 healthcare workers from two COVID-19 designated hospitals in Beijing participated in the survey in August 2021 and reported risk perception, outcome expectance, action self-efficacy, preventive intention, action control, and prevention behaviors during work. Results: 1) Action self-efficacy and outcome expectancy were positively associated with intention to adhere to preventive measures. 2) Action control mediated the association between intention and preventive behaviors during work. Conclusion: Social-cognitive factors such as action self-efficacy, action control, and intention should be addressed to improve healthcare workers’ adherence to infection and control measures during the COVID-19 pandemic.

Quarantine and the Transformation of Power Dynamics during China's War of Resistance against Japan

Zou and Quan discuss quarantine and the transformation of power dynamics during China's war of resistance against Japan. In the novel Cold Nights (1947), the modern Chinese writer Ba Jin (1904-2005) uses representations of quarantine rather than the frequently used themes of heroic resistance and nationalism to show how China's war of resistance against Japan brought about changes in power relations within the nation. Cold Nights describes how this military engagement in the wartime capital of Chongqing China influences and transforms labor, government, social community, and individuality during an epidemic. In a time when COVID-19 sweeps across the world and also points to the important role quarantine plays in revealing the change and formation of new forms of socio-political power dynamics, more thorough studies of how the enforcement of quarantine can impact different societies and what the consequences of these decisions are for the people are clearly necessary.

Network pharmacology and molecular docking of shiwei qingwen decoction reveal TNF as a potential target for alleviating mild COVID-19 symptoms. (Special Issue: Phytochemicals against SARS-COV-2 infection.)

Objective: Shiwei Qingwen decoction (SWQWD) is effective in preventing COVID-19. This study examined the active components of SWQWD and its potential targets for preventing COVID-19. The study used network pharmacology and molecular docking technology to verify the role of SWQWD targets through animal experiments and explored the mechanisms that enhance immunity to alleviate mild COVID-19 symptoms.

Impact of Media Use on Chinese Public Behavior towards Vaccination with the COVID-19 Vaccine: A Latent Profile Analysis.

(1) Background: research on vaccines has received extensive attention during epidemics. However, few studies have focused on the impact of media use on vaccination behavior and the factors influencing vaccination in groups with different media use degrees; (2) Method: Based on seven items related to media use, a total of 11,031 respondents were categorized by the frequency of media use by using latent profile analysis (LPA). Binary regression analysis was used to study the factors that influence the vaccination behaviors of people with different media use frequencies; (3) Results: All respondents were classified into the following three groups: media use low frequency (9.7%), media use general (67.1%), and media use high frequency (23.2%). Media use low frequency (ß = -0.608, p < 0.001) was negatively associated with COVID-19 vaccination behavior. In the media use low frequency, analysis showed that "aged 41 years or older" ß = 1.784, p < 0.001), had religious belief (ß = 0.075, p < 0.05), were ethnic minorities (ß = 0.936, p < 0.01) and had friends support (ß = 0.923, p < 0.05) were associated with a preference to accept the COVID-19 vaccine. In the media use general, those who aged 41 years old and older (ß = 1.682, p < 0.001), had major depression (ß = 0.951, p < 0.05), had friends support (ß = 0.048, p < 0.001) would be more likely to receive COVID-19 vaccination. However, respondents who live in towns (ß = -0.300, p < 0.01) had lower behaviors to receive vaccination for COVID-19. In the media use high frequency, the respondents who aged 41 or older (ß = 1.010, p < 0.001), were ethnic minorities (ß = 0.741, p < 0.001), had moderate depression (ß = 1.003, p < 0.05) would receive the vaccination for COVID-19 positively; (4) Conclusions: The more occluded the media use is, the less likely the respondents are to get vaccinated against COVID-19. Vaccination behavior is influenced by different factors in groups with different frequencies of media use. Therefore, the government and appropriate departments should make individualized and targeted strategies about COVID-19 vaccination and disseminate the vaccination information to different media use groups.

Trend and co-occurrence network study of symptoms through social media: an example of COVID-19 (preprint)

ImportanceCOVID-19 is a multi-organ disease with broad-spectrum manifestations. Clinical data-driven research can be difficult because many patients do not receive prompt diagnoses, treatment, and follow-up studies. Social medias accessibility, promptness, and rich information provide an opportunity for large-scale and long-term analyses, enabling a comprehensive symptom investigation to complement clinical studies. ObjectivePresent an efficient workflow to identify and study the characteristics and co-occurrences of COVID-19 symptoms using social media. Design, Setting, and ParticipantsThis retrospective cohort study analyzed 471,553,966 COVID-19-related tweets from February 1, 2020, to April 30, 2022. A comprehensive lexicon of symptoms was used to filter tweets through rule-based methods. 948,478 tweets with self-reported symptoms from 689,551 Twitter users were identified for analysis. Main Outcomes and MeasuresThe overall trends of COVID-19 symptoms reported on Twitter were analyzed (separately by the Delta strain and the Omicron strain) using weekly new numbers, overall frequency, and temporal distribution of reported symptoms. A co-occurrence network was developed to investigate relationships between symptoms and affected organ systems. ResultsThe weekly quantity of self-reported symptoms has a high consistency (0.8528, P<0.0001) and one-week leading trend (0. 8802, P<0.0001) with new infections in four countries. We grouped 201 common symptoms (mentioned [≥] 10 times) into 10 affected systems. The frequency of symptoms showed dynamic changes as the pandemic progressed, from typical respiratory symptoms in the early stage to more musculoskeletal and nervous symptoms at later stages. When comparing symptoms reported during the Delta strain versus the Omicron variant, significant changes were observed, with dropped odd ratios of coma (95%CI 0.55-0.49, P<0.01) and anosmia (95%CI, 0.6-0.56), and more pain in the throat (95%CI, 1.86-1.96) and concentration problems (95%CI, 1.58-1.70). The co-occurrence network characterizes relationships among symptoms and affected systems, both intra-systemic, such as cough and sneezing (respiratory), and inter-systemic, such as alopecia (integumentary) and impotence (reproductive). Conclusions and RelevanceWe found dynamic COVID-19 symptom evolution through self-reporting on social media and identified 201 symptoms from 10 affected systems. This demonstrates that social medias prevalence trends and co-occurrence networks can efficiently identify and study public health problems, such as common symptoms during pandemics. Key pointsO_ST_ABSQuestionsC_ST_ABSWhat are the epidemic characteristics and relationships of COVID-19 symptoms that have been extensively reported on social media? FindingsThis retrospective cohort study of 948,478 related tweets (February 2020 to April 2022) from 689,551 users identified 201 self-reported COVID-19 symptoms from 10 affected systems, mitigating the potential missing information in hospital-based epidemiologic studies due to many patients not being timely diagnosed and treated. Coma, anosmia, taste sense altered, and dyspnea were less common in participants infected during Omicron prevalence than in Delta. Symptoms that affect the same system have high co-occurrence. Frequent co-occurrences occurred between symptoms and systems corresponding to specific disease progressions, such as palpitations and dyspnea, alopecia and impotence. MeaningTrend and network analysis in social media can mine dynamic epidemic characteristics and relationships between symptoms in emergent pandemics.

Using Twitter Data to Understand Public Perceptions of Approved versus Off-label Use for COVID-19-related Medications (preprint)

Understanding public discourse on emergency use of unproven therapeutics is crucial for monitoring safe use and combating misinformation. We developed a natural language processing-based pipeline to comprehend public perceptions of and stances on coronavirus disease 2019 (COVID-19)-related drugs on Twitter over time. This retrospective study included 609,189 US-based tweets from January 29, 2020, to November 30, 2021, about four drugs that garnered significant public attention during the COVID-19 pandemic: (1) Hydroxychloroquine and Ivermectin, therapies with anecdotal evidence; and (2) Molnupiravir and Remdesivir, FDA-approved treatments for eligible patients. Time-trend analysis was employed to understand popularity trends and related events. Content and demographic analyses were conducted to explore potential rationales behind people's stances on each drug. Time-trend analysis indicated that Hydroxychloroquine and Ivermectin were discussed more than Molnupiravir and Remdesivir, particularly during COVID-19 surges. Hydroxychloroquine and Ivermectin discussions were highly politicized, related to conspiracy theories, hearsay, and celebrity influences. The distribution of stances between the two major US political parties was significantly different (P < .001); Republicans were more likely to support Hydroxychloroquine (55%) and Ivermectin (30%) than Democrats. People with healthcare backgrounds tended to oppose Hydroxychloroquine (7%) more than the general population, while the general population was more likely to support Ivermectin (14%). Our study found that social media users have varying perceptions and stances on off-label versus FDA-authorized drug use at different stages of COVID-19. This indicates that health systems, regulatory agencies, and policymakers should design tailored strategies to monitor and reduce misinformation to promote safe drug use.

SARS-CoV-2 S protein antagonizes type I interferon downstream signal pathway through interacting and attenuating phosphorylation of STAT1/STAT2 (preprint)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may keep patients in a clinically asymptomatic state by blocking cellular innate antiviral immunity, but the molecular mechanism remains unclear. Here, we screened the viral proteins of SARS-CoV-2 and found that the spike (S) protein inhibits the activation of interferon-stimulated genes (ISGs) and even reduces the expression of these genes to below background values. Mechanistically, the S protein interacted with STAT1, STAT2, and IRF9 and impedes the phosphorylation of STAT1/STAT2, thus preventing the formation of the interferon-stimulating gene factor 3 (ISGF3) complex and inhibiting the downstream production of Interferon-stimulated genes (ISGs). Remarkably, we also have found that the inhibitory mechanism of the S protein was conservative among SARS-CoV-2 variants and other human coronaviruses, including SARS-CoV, MERS-CoV, HCoV-229E, HCoV-NL63, and HCoV-HKU1. Truncation studies indicated that the most conserved S2 domain played a major inhibitory role. Altogether, our findings unveil a new mechanism by which SARS-CoV-2 S protein attenuated the host's antiviral immune response and provide new insights into the pathogenic mechanism of coronavirus.

Optical Image Guided Multi-scale Learning for Synthetic Aperture Radar Image Super-resolution (preprint)

Synthetic Aperture Radar (SAR) image Super-Resolution (SR) has various application including military reconnaissance and marine monitoring. Comparing with other natural images, the SAR images suffer from lower spatial resolution and less amplitude information, which provide insufficient information for SAR image reconstruction. Therefore, current SAR image SR methods show worse performance. In this paper, considering optical images have higher resolution and richer texture information, we propose a multi-scale learning based optical image guidance network (MLOG) to make good use of high-resolution (HR) optical image for SAR image SR. Specifically, we design an optical image weighted guidance network (OWG) to get more discriminative feature and reduce the impact of the lack of detailed information in LR SAR images. Then a multi-scale learning network (MLN) is proposed to obtain the global features from optical image. After that, a residual multi-scale block (RMB) is introduced to extract the global multi-scale context information. Finally, the extracted multi-scale features are reconstructed to generate high-resolution SAR images through a convolutional reconstruction layer. The experimental results show that the proposed MLOG method achieves state-of-the-art performance for SAR image SR on public available datasets.

Changes in primary care visits arising from the COVID-19 pandemic: an international comparative study by the International Consortium of Primary Care Big Data Researchers (INTRePID).

INTRODUCTION: Through the INTernational ConsoRtium of Primary Care BIg Data Researchers (INTRePID), we compared the pandemic impact on the volume of primary care visits and uptake of virtual care in Australia, Canada, China, Norway, Singapore, South Korea, Sweden, the UK and the USA. METHODS: Visit definitions were agreed on centrally, implemented locally across the various settings in INTRePID countries, and weekly visit counts were shared centrally for analysis. We evaluated the weekly rate of primary care physician visits during 2019 and 2020. Rate ratios (RRs) of total weekly visit volume and the proportion of weekly visits that were virtual in the pandemic period in 2020 compared with the same prepandemic period in 2019 were calculated. RESULTS: In 2019 and 2020, there were 80 889 386 primary care physician visits across INTRePID. During the pandemic, average weekly visit volume dropped in China, Singapore, South Korea, and the USA but was stable overall in Australia (RR 0.98 (95% CI 0.92 to 1.05, p=0.59)), Canada (RR 0.96 (95% CI 0.89 to 1.03, p=0.24)), Norway (RR 1.01 (95% CI 0.88 to 1.17, p=0.85)), Sweden (RR 0.91 (95% CI 0.79 to 1.06, p=0.22)) and the UK (RR 0.86 (95% CI 0.72 to 1.03, p=0.11)). In countries that had negligible virtual care prepandemic, the proportion of visits that were virtual were highest in Canada (77.0%) and Australia (41.8%). In Norway (RR 8.23 (95% CI 5.30 to 12.78, p<0.001), the UK (RR 2.36 (95% CI 2.24 to 2.50, p<0.001)) and Sweden (RR 1.33 (95% CI 1.17 to 1.50, p<0.001)) where virtual visits existed prepandemic, it increased significantly during the pandemic. CONCLUSIONS: The drop in primary care in-person visits during the pandemic was a global phenomenon across INTRePID countries. In several countries, primary care shifted to virtual visits mitigating the drop in in-person visits.

Tracking the impact of COVID-19 and lockdown policy on public mental health using social media (preprint)

The COVID-19 pandemic and its corresponding preventive and control measures have increased the mental burden on the public. Social media serve as important platforms to timely track public mental status. In this study, we conducted social-media-based analyses on temporal, geographical and occupational distributions of public mental health status during the pandemic, and how the public reacted to the lock-down policy from the perspective of mental health. We extracted 2,973,319 mental health-related tweets of 1,778,140 users from February 1, 2020 to September 30, 2021. We found that, compared to the general public, healthcare workers had higher concerns on three types of mental health problems (depression, insomnia, addiction) (P<0.001) and focused more on clinical topics while the public worried more about daily life issues. The lockdown policy in New York was correlated with a proportional decrease of mental health-related tweets, while Florida had an opposite correlation (both P<0.05). Our findings indicated that the mental burden brought by the pandemic varied across occupations and locations and changed over time.

Investigating the impact of SARS-CoV-2 infection on basic semen parameters and in vitro fertilization/intracytoplasmic sperm injection outcomes: a retrospective cohort study.

BACKGROUND: This study aimed to evaluate the influences of SARS-CoV-2 infection on semen parameters and investigate the impact of the infection on in vitro fertilization (IVF) outcomes. METHODS: This retrospective study enrolled couples undergoing IVF cycles between May 2020 and February 2021 at Tongji Hospital, Wuhan. Baseline characteristics were matched using propensity score matching. Participants were categorized into an unexposed group (SARS-COV-2 negative) and exposed group (SARS-COV-2 positive) based on a history of SARS-CoV-2 infection, and the populations were 148 and 50 after matching, respectively. IVF data were compared between the matched cohorts. Moreover, semen parameters were compared before and after infection among the infected males. The main measures were semen parameters and IVF outcomes, including laboratory and clinical outcomes. RESULTS: Generally, the concentration and motility of sperm did not significantly differ before and after infection. Infected males seemed to have fewer sperm with normal morphology, while all values were above the limits. Notably, the blastocyst formation rate and available blastocyst rate in the exposed group were lower than those in the control group, despite similar mature oocytes rates, normal fertilization rates, cleavage rates, and high-quality embryo rates. Moreover, no significant differences were exhibited between the matched cohorts regarding the implantation rate, biochemical pregnancy rate, clinical pregnancy rate, or early miscarriage rate. CONCLUSIONS: The results of this retrospective cohort study suggested that the semen quality and the chance of pregnancy in terms of IVF outcomes were comparable between the males with a history of SARS-CoV-2 infection and controls, although a decreased blastocyst formation rate and available blastocyst rate was observed in the exposed group, which needs to be reinforced by a multicenter long-term investigation with a larger sample size.

Lyophilized mRNA-lipid nanoparticles vaccine with long-term stability and high antigenicity against SARS-CoV-2 (preprint)

Advanced mRNA vaccines play vital roles against SARS-CoV-2. However, due to the poor stability, most current mRNA delivery platforms need to be stored at -20 {degrees}C or -70 {degrees}C. Here we present lyophilized thermostable mRNA loaded lipid nanoparticles, which could be stored at room temperature with long-term stability. We demonstrate the applicability of lyophilization techniques to different mRNA sequences and lipid components. Three lyophilized vaccines targeting wild-type, Delta and Omicron SARS-CoV-2 variant were prepared and demonstrated to be able induce high-level of IgG titer and neutralization response. In the Delta challenge in vivo experiment, the lyophilized mRNA vaccine successfully protected the mice from infection and clear the virus. This lyophilization platform could significantly improve the accessibility of mRNA vaccine or therapeutics, particularly in remote regions.

Clonal dynamics of SARS-CoV-2-specific T cells in children and adults with COVID-19 (preprint)

Children infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) develop less severe coronavirus disease 2019 (COVID-19) than adults. The mechanisms for the age-specific differences and the implications for infection-induced immunity are beginning to be uncovered. We show by longitudinal multimodal analysis that SARS-CoV-2 leaves a small footprint in the circulating T cell compartment in children with mild/asymptomatic COVID-19 compared to adult household contacts with the same disease severity who had more evidence of systemic T cell interferon activation, cytotoxicity and exhaustion. Children harbored diverse polyclonal SARS-CoV-2-specific naive T cells whereas adults harbored clonally expanded SARS-CoV-2-specific memory T cells. More naive interferon-activated CD4+ T cells were recruited into the memory compartment and recovery was associated with the development of robust CD4+ memory T cell responses in adults but not children. These data suggest that rapid clearance of SARS-CoV-2 in children may compromise their cellular immunity and ability to resist reinfection.

Evaluation of the occurrence of psychotropic drugs in urban sewage and the abuse during the COVID-19 epidemic period in a city of Guangdong

Using the method of sewage epidemiology, the occurrence characteristics and changes of two typical psychoactive drugs methamphetamine and ketamine in the domestic sewage of a city in Guangdong Province during and before and after the new crown epidemic in 2020 were studied, and the mobile phone signaling data was used to analyze The total population, structural characteristics and their change laws were combined to analyze the changes in the consumption of the two drugs during the epidemic and before and after the epidemic. The results show that the actual population of the city during the epidemic decreased by about 45% compared with before the epidemic. The total consumption of various drugs has dropped by about 75% compared to before the epidemic. The significant decline in total consumption was largely caused by the actual population decline during the epidemic. In fact, the per capita consumption levels of methamphetamine and ketamine in the city during the epidemic Compared with the pre-epidemic drop of less than 50%. Taking into account the strict control measures during the epidemic, this decline shows that the abuse of these two psychotropic substances is extremely stubborn;after the epidemic, the consumption of the two drugs and their concentrations in the environment have increased significantly. It has basically returned to the level before the epidemic, which further proves the stubbornness of psychotropic substance abuse.

Auricular Acupressure for Adverse Events Following Immunization Related To COVID-19 Vaccine Injection: Study Protocol for a Multicenter, Three-Arm, Blinded Randomized Controlled Trial (preprint)

Background: Some pain, fatigue, and gastrointestinal adverse reactions were observed in potential association with injection of COVID-19 vaccines. However, there were no preventive intervention for it. We aim to investigate efficacy of auricular acupressure (AA) therapy in preventing and (or) relieving AEFI after injection of COVID-19 vaccine. Methods/design: The study design is a randomized controlled, multicentre, three-arm, single-blind trial. Participants meeting the inclusion criteria will be advertised and enrolled, and assigned randomly in the medical institutions for post-injection observation. No less than 360 participants will be randomized into one of three groups: auricular acupressure group, sham auricular acupressure group and wait-list group. Interventions will be performed immediately, and will happen 4 to 5 times per day for 5 days. The primary clinical outcomes will be quality and quantity evaluation among participants who reported any AEFI and who reported local pain at injection site. Secondary outcomes will concern headache, muscle and (or) joint pain, fatigue, nausea, vomiting, diarrhoea, and other potential events. All the outcomes will be assessed at baseline, 1, 3, 5, 7, and 14 days after the injection. Both intention-to-treat and per-protocol analyses will be performed, with significance level determined at the 5 % level. Discussion Results of this trial will help clarify the value of auricular acupressure therapy in preventing and (or) relieving overall and certain adverse events following immunization after injection of COVID-19 vaccine. Trial registration: This trial was registered in the China Clinical Trial Registry (ChiCTR) (ChiCTR2100043210) on 8th February, 2021.

Investigating the impact of asymptomatic or mild SARS-CoV-2 infection on female fertility and in vitro fertilization outcomes: A retrospective cohort study.

Background: The current study aimed to investigate the impact of asymptomatic or mild severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on female fertility and laboratory and clinical outcomes in assisted reproductive technology (ART) treatments. Methods: Patients undergoing ART treatments in the Reproductive Medicine Center, Tongji Hospital, Wuhan, from May 2020 to February 2021 were enrolled. Seventy of them were positive for serum SARS-CoV-2 antibodies (IgG and/or IgM), and 3973 patients had negative results. Propensity score matching with a ratio of 1:3 was performed, and there were 65 females in the case group and 195 females in the control group. Findings: The ovarian reserves and ovarian responses between groups after matching were similar. The proportions of mature oocytes, damaged oocytes, fertilized oocytes, cleavage embryos, high-quality embryos, and available blastocysts were also similar, despite a slight decrease in the blastocyst formation rate in the case group. In addition, there were no significant differences in terms of the biochemical pregnancy rate, clinical pregnancy rate, early miscarriage rate, or implantation rate. Interpretation: There is no evidence that a history of asymptomatic or mild SARS-CoV-2 infection in females may negatively affect female fertility, embryo laboratory outcomes, or clinical outcomes in ART treatments.

Broad neutralizing nanobody against SARS-CoV-2 engineered from pre-designed synthetic library (preprint)

SARS-CoV-2 infection is initiated with Spike glycoprotein binding to the receptor of human angiotensin converting enzyme 2 via its receptor binding domain. Blocking this interaction is considered as an effective approach to inhibit virus infection. Here we report the discovery of a neutralizing nanobody, VHH60, directly produced from a humanized synthetic nanobody library. VHH60 competes with human ACE2 to bind the receptor binding domain of the Spike protein with a KD of 2.56 nM, inhibits infections of both live SARS-CoV-2 and pseudotyped viruses harboring wildtype, escape mutations and prevailing variants at nanomolar level. VHH60 also suppresses SARS-CoV-2 infection and propagation 50-fold better and protects mice from death two times longer than that of control group after live virus inoculation on mice. VHH60 therefore is a powerful synthetic nanobody with a promising profile for disease control against COVID19.

Development of a Post-Acute Sequelae of COVID-19 (PASC) Symptom Lexicon Using Electronic Health Record Clinical Notes (preprint)

Objective: To develop a comprehensive post-acute sequelae of COVID-19 (PASC) symptom lexicon from clinical notes to support PASC symptom identification and research. Methods: We identified 26,117 COVID-19 positive patients from the Mass General Brigham's electronic health records (EHR) and extracted 328,879 clinical notes from their post-acute infection period (day 51-110 from first positive COVID-19 test). The PASC symptom lexicon incorporated Unified Medical Language System (UMLS) Metathesaurus concepts and synonyms based on selected semantic types. The MTERMS natural language processing (NLP) tool was used to automatically extract symptoms from a development dataset. The lexicon was iteratively revised with manual chart review, keyword search, concept consolidation, and evaluation of NLP output. We assessed the comprehensiveness of the lexicon and the NLP performance using a validation dataset and reported the symptom prevalence across the entire corpus. Results: The PASC symptom lexicon included 355 symptoms consolidated from 1,520 UMLS concepts. NLP achieved an averaged precision of 0.94 and an estimated recall of 0.84. Symptoms with the highest frequency included pain (43.1%), anxiety (25.8%), depression (24.0%), fatigue (23.4%), joint pain (21.0%), shortness of breath (20.8%), headache (20.0%), nausea and/or vomiting (19.9%), myalgia (19.0%), and gastroesophageal reflux (18.6%). Discussion and Conclusion: PASC symptoms are diverse. A comprehensive PASC symptom lexicon can be derived using a data-driven, ontology-driven and NLP-assisted approach. By using unstructured data, this approach may improve identification and analysis of patient symptoms in the EHR, and inform prospective study design, preventative care strategies, and therapeutic interventions for patient care.