Antecedents of Responsible Leadership: Proactive and Passive Responsible Leadership Behavior

Due to the massive global impact of the current COVID-19 pandemic, the call for social and environment responsibility has grown stronger, and discussion regarding responsible leadership has been aroused. Agreement on the antecedents of responsible leadership has not yet been reached, however, and most studies are theoretical and focus on the personal characteristics of leaders. In this paper, we explore the antecedents of responsible leadership behavior at the organizational and situational level, through case studies of companies in China. Based on the organizational strategy, organizational ownership, mass media, crisis, local community, and other influencing factors, we determine two types of responsible leadership behaviors: Proactive responsible leadership behavior, which involves leaders showing initiative in dealing with relationships with stakeholders both inside and outside the organization, as well as voluntarily striving to assume relevant responsibilities in order to achieve economic and/or social development goals;and passive responsible leadership behavior, which involves acts of being responsible to some stakeholders under pressure from external circumstances or when unexpected events occur, even though this behavior may go against the actor's original intention. We further explore the influence mechanism of these factors on responsible leadership and discuss the development trend from passive to proactive responsible leadership behavior.

Coronaviruses using different strategies to antagonize antiviral responses and pyroptosis (preprint)

Viral infection triggers inflammasome-mediated caspase-1 activation. However, less is known about how viruses use the active caspase-1 to evade host immune response. Here, we use porcine epidemic diarrhea virus (PEDV) as a model of coronaviruses (CoVs) to illustrate the sophisticated regulation of CoVs to counteract IFN-I signaling and pyroptosis. We show that PEDV infection stabilizes caspase-1 expression via papain-like protease PLP2's deubiquitinase activity and the enhanced stabilization of caspase-1 disrupts IFN-I signaling by cleaving RIG-I at D189 residue. Meanwhile, PLP2 can degrade GSDMD-p30 by removing its K27-linked ubiquitin chain at K275 to restrain pyroptosis. Papain-like proteases from other genera of CoVs (PDCoV and SARS-CoV-2) have the similar activity to degrade GSDMD-p30. We further demonstrate that SARS-CoV-2 N protein induced NLRP3 inflammasome activation also uses the active caspase-1 to counter IFN-I signaling by cleaving RIG-I. Therefore, our work unravels a novel antagonistic mechanism employed by CoVs to evade host antiviral response.

A Wide-bandwidth Nanocomposite-Sensor Integrated Smart Mask for Tracking Multi-phase Respiratory Activities for COVID-19 Endemic (preprint)

A global sentiment in early 2022 is that the COVID-19 virus could become endemic just like common cold flu viruses soon. The most optimistic view is that, with minimal precautions, such as vaccination, boosters and optional masking, life for most people will proceed as normal soon. However, as warned by A. Katzourakis of Oxford University recently [1], we must set aside lazy optimism, and must be realistic about the likely levels of death, disability and sickness that will be brought on by a COVID-19 endemic. Moreover, the world must also consider that continual circulation of the virus could give rise to new variants such as the new BA.2 variant (a subvariant of Omicron) continues to spread across the US and parts of Europe. Data from the CDC is already showing that BA.2 has been tripling in prevalence every two weeks [2]. Hence, globally, we must use available and proven weapons to continue to fight the COVID-19 viruses, i.e., effective vaccines, antiviral medications, diagnostic tests and stop an airborne virus transmission through social distancing, and mask wearing. For this work, we have demonstrated a smart mask with an optimally-coupled ultra-thin flexible soundwave sensors for tracking, classifying, and recognizing different respiratory activities, including breathing, speaking, and two-/tri-phase coughing; the masks functionality can also be augmented in the future to monitor other human physiological signals. Although researchers have integrated sensors into masks to detect respiratory activities in the past, they only based on measuring temperature and air flow during coughing, i.e., counting only the number of coughs. However, coughing is a process consisting of several phases, including an explosion of the air with glottal opening producing some noise-like waveform, a decrease of airflow to decrease sound amplitude, and a voiced stage which is the interruption of the air flow due to the closure of glottal and periodical vibration of partly glottis, which is not always present. Therefore, sensors used for cough detection should not be only sensitive to subtle air pressure but also the high-frequency vibrations, i.e., a pressure sensor that needs to be responsive to a wide input amplitude and bandwidth range, in order to detect air flows between hundreds of hertz from breath, and acoustic signals from voice that could reach [~] 8000 Hz. Respiratory activities data from thirty-one (31) human subjects were collected. Machine learning methods such as Support Vector Machines and Convolutional Neural Networks were used to classify the collected sensor data from the smart mask, which show an overall macro-recall of about 93.88% for the three respiratory sounds among all 31 subjects. For individual subjects, the 31 human subjects have the average macro-recall of 95.23% (ranging from 90% to 100%) for these 3 respiratory activities. Our work bridges the technological gap between ultra-lightweight but high-frequency response sensor material fabrication, signal transduction and conditioning, and applying machining learning algorithms to demonstrate a reliable wearable device for potential applications in continual healthy monitoring of subjects with cough symptoms during the eventual COVID-19 endemic. The monitoring and analysis of cough sound should be highly beneficial for human health management. These health monitoring data could then be shared with doctors via cloud storage and transmission technique to help disease diagnosis more effectively. Also, communication barriers caused by wearing masks can be alleviated by combining with the speech recognition techniques. In general, this research helps to advance the wearable device technology for tracking respiratory activities, similar to an Apple Watch or a Fitbit smartwatch in tracking physical and physiological activities.

DNA damage contributes to age-associated differences in SARS-CoV-2 infection (preprint)

Coronavirus disease 2019 (COVID-19), caused by coronavirus SARS-CoV-2, is known to disproportionately affect older individuals1,2. How aging processes affect the disease progression remains largely unknown. Here we found that DNA damage, one of the major causes of aging3, promoted susceptibility to SARS-CoV-2 infection in cells and intestinal organoids. SARS-CoV-2 entry was facilitated by DNA damage caused by telomere attrition or extrinsic genotoxic stress and hampered by inhibition of DNA damage response (DDR). Mechanistic analysis revealed that DDR increased expression of ACE2, the receptor of SARS-CoV-2, by activation of transcription factor c-Jun in vitro and in vivo. Expression of ACE2 was elevated in the older tissues and positively correlated with γH2Ax and phosphorylated c-Jun (p-c-Jun). Finally, targeting DNA damage by increasing the DNA repair capacity, alleviated cell susceptibility to SARS-CoV-2. Our data provide insights into the age-associated differences in SARS-CoV-2 infection and a novel target for anti-viral intervention.

Early Risk Factors for Extrapulmonary Organ Injury in Adult COVID-19 Patients (preprint)

Objective COVID-19 is becoming a global pandemic and often develops extrapulmonary organ injury. However, the risk factors for extrapulmonary organ injury are still unclear. We aim to explore the risk factors for extrapulmonary organ injury for COVID-19 and the association between extrapulmonary organ injury and the prognosis of COVID-19 patients. Methods This is a single-center, retrospective, observational study and total 349 confirmed COVID-19 patients admitted to Tongji Hospital from January 25 to February 25, 2020 were enrolled. We collected demographic, clinical, laboratory and treatment data from electronic medical records. Potential risk factors for extrapulmonary organ injury of COVID-19 patients were analyzed by a multivariable binary logistic model, and multivariable COX proportional hazard regression model was used for survival analysis in the patients with extrapulmonary organ injury. Results Average age of the included patients was 61.73±14.64 years. In the final logistic model, variables including aged 60 or older (OR 1.826, 95% CI 1.060-3.142), ARDS (OR 2.748, 95% CI 1.051-7.185), lymphocytes count lower than 1.1 ×109/L (OR 0.478, 95% CI 0.240-0.949), level of IL-6 greater than 7 pg/ml (OR 1.664, 95% CI 1.005-2.751) and D-Dimer greater than 0.5 μg/ml (OR 2.190, 95% CI 1.176-4.084) were significantly associated with the extrapulmonary organ injury. Kaplan-Meier curve and log-rank test showed that the probabilities of survival for patients with extrapulmonary organ injury were significantly lower than those without extrapulmonary organ injury.between Multivariate COX proportional hazards model showed that only myocardial injury (P=0.000, HR: 5.068, 95% CI: 2.728-9.417) and circulatory system injury (P=0.000, HR: 4.076, 95% CI: 2.216-7.498) were the independent factors associated with COVID-19 patients’ poor prognosis. Conclusion Older age, lymphocytopenia, high level of D-Dimer and IL-6 and the severity of lung injury were the high-risk factors of extrapulmonary organ injury in COVID-19 patients. Myocardial and circulatory system injury were the most important risk factors related to poor outcomes of COVID-19 patients. It may help clinicians to identify extrapulmonary organ injury early and provide relevant management strategy.

Exhaled breath is a significant source of SARS-CoV-2 emission (preprint)

Despite notable efforts in airborne SARS-CoV-2 detection, no clear evidence has emerged to show how SARS-CoV-2 is emitted into the environments. Here, 35 COVID-19 subjects were recruited; exhaled breath condensate (EBC), air samples and surface swabs were collected and analyzed for SARS-CoV-2 using reverse transcription-polymerase chain reaction (RT-PCR). EBC samples had the highest positive rate (16.7%, n=30), followed by surface swabs (5.4%, n=242), and air samples (3.8%, n=26). COVID-19 patients were shown to exhale SARS-CoV-2 into the air at an estimated rate of 103-105 RNA copies/min; while toilet and floor surfaces represented two important SARS-CoV-2 reservoirs. Our results imply that airborne transmission of SARS-CoV-2 plays a major role in COVID-19 spread, especially during the early stages of the disease.

Detection of SARS-CoV-2 in Exhaled Breath from COVID-19 Patients Ready for Hospital Discharge (preprint)

The COVID-19 pandemic has brought an unprecedented crisis to the global health sector1. When recovering COVID-19 patients are discharged in accordance with throat or nasal swab protocols using reverse transcription polymerase chain reaction (RT-PCR), the potential risk of re-introducing the infection source to humans and the environment must be resolved 2,3,4. Here we show that 20% of COVID-19 patients, who were ready for a hospital discharge based on current guidelines, had SARS-CoV-2 in their exhaled breath (~105 RNA copies/m3). They were estimated to emit about 1400 RNA copies into the air per minute. Although fewer surface swabs (1.3%, N=318) tested positive, medical equipment frequently contacted by healthcare workers and the work shift floor were contaminated by SARS-CoV-2 in four hospitals in Wuhan. All air samples (N=44) appeared negative likely due to the dilution or inactivation through natural ventilation (1.6-3.3 m/s) and applied disinfection. Despite the low risk of cross environmental contamination in the studied hospitals, there is a critical need for strengthening the hospital discharge standards in preventing re-emergence of COVID-19 spread.