Patients with Omicron variant infection can safely undergo elective orthopedic surgery: a retrospective cohort study (preprint)

Background COVID-19 is believed to be associated with significantly increased risks of morbidity and mortality. However, there are lack of reports on how infection with the COVID-19 Omicron variant affects the perioperative prognosis. Therefore, this study sought to find out perioperative differences in laboratory test results and complications between orthopedic surgery patients who were COVID-19 positive and negative at admission, to explore whether patients infected with the Omicron variant need to delay their orthopedic elective surgery.Methods A single-center cohort study of 54 orthopedic inpatients with COVID-19 Omicron variant infection were 1:1 matched to those who did not have a history of COVID-19, laboratory parameters including blood routine, inflammatory factors, coagulogram markers and postoperative complications were recorded and compared.Results Differences can not be found in the incidence of perioperative complications and mortality rates between the group infected with the SARS-CoV-2 Omicron variant and the uninfected group, as well as no statistical differences in laboratory test indicators.Conclusions The SARS-CoV-2 Omicron variant does not appear to pose a huge threat to elective orthopedic surgery, patients with Omicron variant infection can safely undergo elective orthopedic surgery without delay.

A Rapid review on the COVID-19 Pandemic's Global Impact on Breast Cancer Screening Participation Rates and Volumes from January-December 2020 (preprint)

Background: COVID-19 has strained population breast mammography screening programs that aim to diagnose and treat breast cancers earlier. As the pandemic has affected countries differently, we aimed to quantify changes in breast screening volume and uptake during the first year of the COVID-19 pandemic. Methods: We systematically searched Medline, the WHO (World Health Organization) COVID-19 database, and governmental databases. Studies covering January 2020 to March 2022 were included. We extracted and analyzed data regarding study methodology, screening volume and uptake. To assess for risk-of bias, we used the Joanna Briggs Institute Critical Appraisal tool. Results: Twenty-six cross-sectional descriptive studies were included out of 935 independent records. Reductions in screening volume and uptake rates were observed among eight countries. Changes in screening participation volume in five countries with national population-based screening ranged from -13% to -31%. Among two countries with limited population-based programs the decline ranged from -61% to -41%. Within the USA, population participation volumes varied ranging from +18% to -39% with suggestion of differences by insurance status (HMO, Medicare, and low-income programs). Almost all studies had high risk-of-bias due to insufficient statistical analysis and confounding factors. Discussion and Conclusion: Extent of COVID-19-induced reduction in breast screening participation volume differed by region and data suggested potential differences by healthcare setting (e.g., national health insurance vs private health care). Recovery efforts should monitor access to screening and early diagnosis to determine if prevention services need strengthening to increase coverage of marginalized groups and reduce disparities.

Individual Surveillance Around Parked Aircraft at Nighttime: Thermal Infrared Vision-Based Human Action Recognition

The COVID-19 crisis has led to an unusually large number of commercial aircraft being currently parked or stored. For airlines, airports, and civil aviation authorities around the world, monitoring, and protecting these parked aircraft to prevent them from causing human-made damage are becoming urgent problems that are receiving increasing attention. In this study, we use thermal infrared monitoring videos to establish a framework for individual surveillance around parked aircraft by proposing a human action recognition (HAR) algorithm. As the focus of this article, the proposed HAR algorithm seamlessly integrates a preprocessing module in which a novel data structure is constructed to introduce spatiotemporal information of the action;a convolutional neural network-based module for spatial feature extraction;a triple-layer convolutional long short-term memory network for temporal feature extraction;and two fully connected layers for classification. Moreover, because no infrared dataset is available for the HAR task on airport grounds at nighttime, we present a dataset called IIAR-30, which consists of eight action categories that frequently occur on airport grounds and 2000 video clips. The experimental results on the IIAR-30 dataset demonstrated that the recognition accuracy of the proposed method was higher than 96%. We also further evaluated the effectiveness of the proposed method by comparing it with five baselines and four other methods.

Human-in-the-loop Evaluation for Early Misinformation Detection: A Case Study of COVID-19 Treatments (preprint)

We present a human-in-the-loop evaluation framework for fact-checking novel misinformation claims and identifying social media messages that support them. Our approach extracts check-worthy claims, which are aggregated and ranked for review. Stance classifiers are then used to identify tweets supporting novel misinformation claims, which are further reviewed to determine whether they violate relevant policies. To demonstrate the feasibility of our approach, we develop a baseline system based on modern NLP methods for human-in-the-loop fact-checking in the domain of COVID-19 treatments. We make our data and detailed annotation guidelines available to support the evaluation of human-in-the-loop systems that identify novel misinformation directly from raw user-generated content.

Massive‐scale genomic analysis reveals SARS‐CoV‐2 mutation characteristics and evolutionary trends

The severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) pandemic resulted in significant societal costs. Hence, an in‐depth understanding of SARS‐CoV‐2 virus mutation and its evolution will help determine the direction of the COVID‐19 pandemic. In this study, we identified 296,728 de novo mutations in more than 2,800,000 high‐quality SARS‐CoV‐2 genomes. All possible factors affecting the mutation frequency of SARS‐CoV‐2 in human hosts were analyzed, including zinc finger antiviral proteins, sequence context, amino acid change, and translation efficiency. As a result, we proposed that when adenine (A) and tyrosine (T) bases are in the context of AM (M stands for adenine or cytosine) or TA motif, A or T base has lower mutation frequency. Furthermore, we hypothesized that translation efficiency can affect the mutation frequency of the third position of the codon by the selection, which explains why SARS‐CoV‐2 prefers AT3 codons usage. In addition, we found a host‐specific asymmetric dinucleotide mutation frequency in the SARS‐CoV‐2 genome, which provides a new basis for determining the origin of the SARS‐CoV‐2. Finally, we summarize all possible factors affecting mutation frequency and provide insights into the mutation characteristics and evolutionary trends of SARS‐CoV‐2. Impact statement In this study, we analyzed the possible factors affecting mutations in more than 2,800,000 high‐quality severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) genomes. To our knowledge we are the first to propose that when the A or T base conforms to AM or TA motif, the A or T base has a lower mutation frequency;and subsequently, translation efficiency can affect the mutation frequency from C/G to A/T on the third position of the codon by the selection. We found significant host‐specific asymmetric mutations at dinucleotide sites. In addition, we also identified the characteristics of SARS‐CoV‐2 mutations and hypothesized the evolutionary trends of the virus in the human host. These findings are valuable for predicting the development of the COVID‐19 pandemic and bring to light new hypotheses regarding the origin of SARS‐CoV‐2.

Compatibility of Fuzi and Ginseng Significantly Increase the Exposure of Aconitines.

The herb-pair ginseng-Fuzi (the root of Aconitum carmichaelii) is the material basis of Shenfu prescriptions and is popular in traditional Chinese medicine for the treatment of heart failure, and even shock with severe-stage of COVID-19. A narrow therapeutic window of Fuzi may cause significant regional loss of property and life in clinics. Therefore, systemic elucidation of active components is crucial to improve the safety dose window of Shenfu oral prescriptions. A high performance liquid chromatography-mass spectrometry method was developed for quantification of 10 aconitines in SD rat plasma within 9 min. The limit of detection and the limit of quantification were below 0.032 ng/ml and 0.095 ng/ml, respectively. Furthermore, a systemic comparison with their pharmacokinetic characteristics after oral administration of a safe dosage of 2 g/kg of Fuzi and ginseng-Fuzi decoction for 24 h was conducted. Eight representative diester, monoester, and non-ester aconitines and two new active components (i.e., songorine and indaconitine) were all adopted to elucidating the differences of the pharmacokinetic parameters in vivo. The compatibility of Fuzi and ginseng could significantly increase the in vivo exposure of active components. The terminal elimination half-life and the area under the concentration-time curve of mesaconitine, benzoylaconitine, benzoylmesaconitine, benzoylhypaconitine, and songorine were all increased significantly. The hypaconitine, benzoylmesaconitine, and songorine were regarded as the main active components in vivo, which gave an effective clue for the development of new Shenfu oral prescriptions.

Effect of Different Combustion Modes on the Performance of Hydrogen Internal Combustion Engines under Low Load

Detailed hydrogen–air chemical reaction mechanisms were coupled with the three-dimensional grids of an experimental hydrogen internal combustion engine (HICE) to establish a computational fluid dynamics (CFD) combustion model based on the CONVN1 -https://media.proquest.com/media/hms/PFT/1/iyX6N?_a=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%3D%3D&_s=XxDsfbWeNCPMojxxWroCr%2FH0Al4%3D ERGE software. The effects of different combustion modes on the combustion and emission characteristics of HICE under low load were studied. The simulation results showed that, with the increase in excess hydrogen, the equivalent combustion and excessive hydrogen combustion modes with medium-cooled exhaust gas recirculation (EGR) dilution could improve the intensity of the in-cylinder combustion of HICE, increase the peak values of pressure and temperature in the cylinder, and then improve the indicated thermal efficiency of HICE under low load. However, larger excessive hydrogen combustion could weaken the improvement in performance;therefore, the performance of HICE could be comprehensively improved by the adoption of excessive hydrogen combustion with a fuel–air ratio below 1.2 under low load. The obtained conclusions indicate the research disadvantages in the power and emission performances of HICE under low load, and they are of great significance for the performance optimization of HICE. Furthermore, a control strategy was proposed to improve the stability of HICE under low load.

Machine learning elucidates the impact of short-term emission changes on air pollution in Beijing

The Chinese Spring Festival (CSF) is the most solemn traditional festival in China, and the substantial changes in anthropogenic activities in megacities provide a unique natural experiment to assess the influence of short-term emission changes on air quality. Here we applied a machine learning based random forest algorithm to six-year aerosol composition measurements in urban Beijing during the CSFs of 2012–2020 to quantify the relative contributions of meteorology and emission changes to air quality. Our results demonstrate large variabilities of air pollutants during the CSF due to the meteorological changes and holiday effect. By removing the meteorological effect, we found that the reduced emissions during CSF caused an average decrease of 5.1% for non-refractory PM2.5 with chloride and primary organic aerosol being the largest (8.8–18.7%) while the changes in secondary species were small. The COVID-19 lockdown during 2020 led to additional reductions of primary species by 16.3–36.8%, yet increases in nitrate and secondary organic aerosol due to enhanced secondary production. Our study has a significant implication that reducing local traffic and cooking emissions is far from enough for mitigating air pollution in winter in megacities due to the nonlinear effect of secondary production and regional transport. A synergetic control of multiple precursors, e.g., NOx and ammonia, is of great importance to reduce secondary aerosol and improve air quality.

Specific Pupylation as IDEntity Reporter (SPIDER) for the identification of Protein-Biomolecule interactions (preprint)

Protein-biomolecule interactions play pivotal roles in almost all biological processes, the identification of the interacting protein is essential. By combining a substrate-based proximity labelling activity from the pupylation pathway of Mycobacterium tuberculosis , and the streptavidin (SA)-biotin system, we developed S pecific P upylation as IDE ntity R eporter (SPIDER) for identifying protein-biomolecular interactions. As a proof of principle, SPIDER was successfully applied for global identification of interacting proteins, including substrates for enzyme (CobB), the readers of m 6 A, the protein interactome of mRNA, and the target proteins of drug (lenalidomide). In addition, by SPIDER, we identified SARS-CoV-2 Omicron variant specific receptors on cell membrane and performed in-depth analysis for one candidate, Protein-g. These potential receptors could explain the differences between the Omicron variant and the Prototype strain, and further serve as target for combating the Omicron variant. Overall, we provide a robust technology which is applicable for a wide-range of protein-biomolecular interaction studies.

Thrombolysis in STEMI Patients Compared With pPCI on Recanalization Time in the Context of the COVID-19 Outbreak.

SARS-CoV-2 NSP5 and N protein counteract the RIG-I signaling pathway by suppressing the formation of stress granules

As a highly pathogenic human coronavirus, SARS-CoV-2 has to counteract an intricate network of antiviral host responses to establish infection and spread. The nucleic acid-induced stress response is an essential component of antiviral defense and is closely related to antiviral innate immunity. However, whether SARS-CoV-2 regulates the stress response pathway to achieve immune evasion remains elusive. In this study, SARS-CoV-2 NSP5 and N protein were found to attenuate antiviral stress granule (avSG) formation. Moreover, NSP5 and N suppressed IFN expression induced by infection of Sendai virus or transfection of a synthetic mimic of dsRNA, poly (I:C), inhibiting TBK1 and IRF3 phosphorylation, and restraining the nuclear translocalization of IRF3. Furthermore, HEK293T cells with ectopic expression of NSP5 or N protein were less resistant to vesicular stomatitis virus infection. Mechanistically, NSP5 suppressed avSG formation and disrupted RIG-I–MAVS complex to attenuate the RIG-I–mediated antiviral immunity. In contrast to the multiple targets of NSP5, the N protein specifically targeted cofactors upstream of RIG-I. The N protein interacted with G3BP1 to prevent avSG formation and to keep the cofactors G3BP1 and PACT from activating RIG-I. Additionally, the N protein also affected the recognition of dsRNA by RIG-I. This study revealed the intimate correlation between SARS-CoV-2, the stress response, and innate antiviral immunity, shedding light on the pathogenic mechanism of COVID-19.

Work-Related Mental Health Under COVID-19 Restrictions: A Mini Literature Review

Coronavirus Disease 2019 (COVID-19) restrictions, including national lockdown, social distancing, compulsory quarantine, and organizational measures of remote working, are imposed in many countries and organizations to combat the coronavirus. The various restrictions have caused different impacts on the employees' mental health worldwide. The purpose of this mini-review is to investigate the impact of COVID-19 restrictions on employees' mental health across the world. We searched articles in Web of Science and Google Scholar, selecting literature focusing on employees' mental health conditions under COVID-19 restrictions. The findings reveal that the psychological impacts of teleworking are associated with employees' various perceptions of its pros and cons. The national lockdown, quarantine, and resuming to work can cause mild to severe mental health issues, whereas the capability to practice social distancing is positively related to employees' mental health. Generally, employees in developed countries have experienced the same negative and positive impacts on mental health, whereas, in developing countries, employees have reported a more negative effect of the restrictions. One explanation is that the unevenly distributed mental health resources and assistances in developed and developing countries.

Primary case of COVID-19 and its occurrence and development evidence

Primary case, commonly known as "No. 0 patient", refers to the first person who is infected by a virus or bacterial disease when the epidemic situation spreads. "No. 0 patient" often causes a large-scale outbreak of infectious diseases. Tracing the epidemiology of "No. 0 patient" and the origin of the occurrence and development are helpful to make clear and understand the pathogen of infection. It is of great significance to control the source of infection and prevent the disease. In this study, from the confirmation of the first diagnosis case of COVID-19, the analysis of the earliest outbreak time point and the carding of the occurrence and development time line of COVID-19, the process from discovery to outbreak of COVID-19 is preliminarily restored, which has important reference value for further understanding of SARS-CoV-2 and COVID-19.

15-Month Health Outcomes of Hospitalized COVID-19 Patients from Onset: A Cohort Study (preprint)

Background: The long-term impact of COVID-19 on patient health has been a recent focus. This study aims to determine the persistent symptoms and psychological conditions of patients hospitalized with COVID-19 15 months after onset. The potential risk factors were also explored.Methods: A cohort of COVID-19 patients discharged from February 20, 2020 to March 31, 2020 was recruited. Follow-ups were conducted using validated questionnaires and psychological screening scales at 15 months after onset to evaluate the patients’ health status. The risk factors for long-term health impacts and their associations with disease severity was analyzed.Findings: 534 COVID-19 patients were enrolled. The median age of the patients was 62.0 years old (IQR 52.0-70.0) and 295 were female (55.2%). The median time from onset to follow-up was 460.0 (451.0-467.0) days. Sleep disturbance (18.5%, 99/534) and fatigue (17.2%, 92/534) were the most common persistent symptoms. 6.4% (34/534) of the patients had depression, 9.2% (49/534) were anxious, 13.0% (70/534) had insomnia and 4.7% (25/534) suffered from posttraumatic stress disorder (PTSD). Multivariate adjusted logistic regression analysis showed that glucocorticoid use during hospitalization (OR 3.58, 95% CI 1.12-11.44) was significantly associated with an increased risk of fatigue. The OR values for anxiety and sleep disorders were 2.36 (95% CI 1.07-5.20) and 2.16 (95% CI 1.13-4.14) in females compared with males. The OR value of PTSD was 25.6 (95% CI 3.3-198.4) in patients with persistent symptoms to those without persistent symptoms. No significant associations were observed between fatigue syndrome or adverse mental outcomes and disease severity.Interpretation: 15-month follow-up in this study aroused the need of extended rehabilitation intervention for complete recovery in COVID-19 patients. Funding: None to declare. Declaration of Interest: All the authors declare no competing interests.Ethical Approval: The Research Ethics Committee of Shanghai Changzheng Hospital approved this study (2020SL007).

Clinical characteristics of 1327 patients with coronavirus disease 2019 (COVID-19) in the largest Fangcang shelter hospital in Wuhan

This article aimed to study the clinical characteristics of these patients admitted to Jianghan Fangcang shelter hospital, the largest Fangcang shelter hospital in Wuhan, China. It is worth highlighting that six patients had anosmia without nasal congestion as the initial symptom. At the time of discharge from the Fangcang shelter hospital, the findings on chest CT were alleviated in 95.5% (1241/1300) of the patients. However, only one patient had chest CT findings suggestive of disease progression. Symptomatic patients have higher CRP level and lower lymphocytes counts than asymptomatic patients, which might suggest that higher CRP level and lower lymphocytes counts were related to the severity of symptoms. However, CT characteristics were not statistically different between symptomatic and asymptomatic patients, which might indicate that CT characteristics were not associated with the severity of symptoms in non-critical patients. In conclusion, patients with fever and anosmia but without nasal congestion are more likely to be suffering from COVID-19. Higher CRP level and lower lymphocytes counts might relate to the severity of symptoms, while CT abnormalities were not associated with the severity of symptoms in non-critical patients.

Copper(II) Gluconate Boosts the Anti-SARS-CoV-2 Effect of Disulfiram in Vitro (preprint)

Disulfiram is a 70-year-old anti-alcoholism drug, while copper(II) gluconate (Cu(Glu)2) is a commonly used food additive or copper supplement. Here we disclose that the combination of disulfiram and copper(II) gluconate drastically enhances the anti-SARS-CoV-2 activity at the cellular level as compared to disulfiram or copper(II) gluconate alone. A 1:1 mixture of disulfiram and copper(II) gluconate shows an EC50 value of 154 nM against SARS-CoV-2 at the cellular level, much lower than the 17.45 M reported for disulfiram alone. Notably, previous clinical trials have shown that a combination of 250 mg disulfiram (0.843 mmol) and 8 mg copper(II) gluconate (0.0176 mmol) oral capsules per day is well tolerated (NCT03034135, NCT00742911). A preliminary mechanism is proposed to rationalize the observed promotional effect.

Prevention and control strategies for emergency, limited-term, and elective operations in pediatric surgery during the epidemic period of COVID-19

The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread to more than 100 countries. Children approved to be susceptible to SARS-CoV-2 infection. Preventing and controlling the epidemic while ensuring orderly flows of pediatric surgery clinical work has proven to be a big challenge for both patients and clinicians during the epidemic. Based on the transmission characteristics of SARS-CoV-2 and the requirements for prevention and control of COVID-19, the authors proposed some concrete measures and practical strategies of managing emergency, limited-term, and elective pediatric surgeries during the epidemic period.

Pairwise constraints cross entropy fuzzy clustering algorithm based on manifold learning and feature selection

In weakly supervised learning, it is difficult for us to utilize pairwise constraints information in feature selection. In order to solve the problem, we propose Pairwise constraints cross entropy fuzzy clustering algorithm based on manifold learning and feature selection (FCPC-LEFS). There are four phases in our approach: 1) Generate pseudo label;2) Dimension reduction by Laplacian Eigenmaps;3) Feature increment and selection;4) Cross-Entropy semi-Supervised Clustering Based on Pairwise Constraints. We apply our approach to three UCI datasets and a COVID19-CT image dataset. Experiments show that our manifold learning and feature selection method are able to increase improve the clustering performance.