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Background and Purpose Asthma is characterized by airway inflammation, mucus hypersecretion and airway hyperresponsiveness (AHR). The activation of cholinergic anti‐inflammatory pathway (CAP) through nicotinic agents has been shown to control experimental asthma. Yet, the effects of vagus nerve stimulation (VNS)-induced CAP on allergic inflammation remain unknown. Experimental Approach BALB/c mice were sensitized and challenged with house dust mite (HDM) extract, and treated with active VNS (5Hz, 0.5 ms, 0.1 mA). Bronchoalveolar lavage (BAL) fluid was assessed for total and differential cell counts and cytokine levels. Lungs were examined by histopathology and electron microscopy. AHR in response to methacholine was also measured. Key Results In the HDM mouse asthma model, active but not sham VNS reduced BAL fluid total and differential cell counts, blocked mucus hypersecretion and suppressed choline acetyltransferase (ChAT) expression in bronchial epithelial cells. Besides, active VNS also abated HDM-induced elevation of type 2 cytokines IL-4 and IL-5. Furthermore, goblet cell hyperplasia and collagen deposition were diminished in VNS-treated mice. Mechanistically, VNS was found to block the phosphorylation of transcription factor STAT6 and the level of IRF4 in total lung lysates. Finally, VNS abrogated methacholine-induced AHR in asthma mice. Therapeutic effects of VNS were abolished by prior administration with α-bungarotoxin, a specific inhibitor of α7 nicotinic receptors (α7nAChR). Conclusion Our data revealed the protective effects of VNS on various clinical features in allergic airway inflammation model. VNS, a clinically approved therapy for depression and epilepsy, appears to be a promising new strategy for controlling allergic asthma through α7nAChR.

WHAT IS ALREADY KNOWN ABOUT THIS TOPIC?: People are likely to engage in collective behaviors online during extreme events, such as the coronavirus disease 2019 (COVID-19) crisis, to express awareness, take action, and work through concerns. WHAT IS ADDED BY THIS REPORT?: This study offers a framework for evaluating interactions among individuals' emotions, perceptions, and online behaviors in Hong Kong Special Administrative Region (SAR) during the first two waves of COVID-19 (February to June 2020). Its results indicate a strong correlation between online behaviors, such as Google searches, and the real-time reproduction numbers. To validate the model's output of risk perception, this investigation conducted 10 rounds of cross-sectional telephone surveys on 8,593 local adult residents from February 1 through June 20 in 2020 to quantify risk perception levels over time. WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICE?: Compared to the survey results, the estimates of the risk perception of individuals using our network-based mechanistic model capture 80% of the trend of people's risk perception (individuals who are worried about being infected) during the studied period. We may need to reinvigorate the public by involving people as part of the solution that reduced the risk to their lives.

Additional file 1. Specific surgical procedures for robot-assisted/laparoscopic inguinal lymphadenectomy.

Additional file 1: Table S1. Spearman correlation coefficients of daily number concentrations of particles with daily mass concentrations of air pollutants and weather conditions. Table S2. Relative risks of VAP at specific combinations of O3 values and lag times. Table S3. Relative risks of VAP at specific combinations of SO2 values and lag times. Figure S1. The criteria for diagnosing Ventilator-Associated Pneumonia. Figure S2. The indoor and outdoor PM2.5 concentration in ICU during 2020. Figure S3. Estimated exposure-response curves for short-term exposures to PM2.5.

Funding Information: Conflicts of interest: BJC consults for AstraZeneca, Fosun Pharma, GlaxoSmithKline, Moderna, Pfizer, Roche and Sanofi Pasteur. BJC is supported by the AIR@innoHK program of the Innovation and Technology Commission of the Hong Kong SAR Government. No other conflicts of interest. Supported by Key Projects of Intergovernmental International Scientific and Technological Innovation Cooperation of National Key R&D Programs (No. 2022YFE0112300) and AIR@InnoHK administered by Innovation and Technology Commission of the Research Grants Council of the Hong Kong SAR Government. Introduction: The ease of coronavirus disease 2019 (COVID-19) non-pharmacological interventions and the increased susceptibility during the past COVID-19 pandemic could be a precursor for the resurgence of influenza, potentially leading to a severe outbreak in the winter of 2022 and future seasons. The recent increased availability of data on Electronic Health Records (EHR) in public health systems, offers new opportunities to monitor individuals to mitigate outbreaks. Methods: We introduced a new methodology to rank individuals for surveillance in temporal networks, which was more practical than the static networks. By targeting previously infected nodes, this method used readily available EHR data instead of the contact-network structure. Results: We validated this method qualitatively in a real-world cohort study and evaluated our approach quantitatively by comparing it to other surveillance methods on three temporal and empirical networks. We found that, despite not explicitly exploiting the contacts’ network structure, it remained the best or close to the best strategy. We related the performance of the method to the public health goals, the reproduction number of the disease, and the underlying temporal-network structure (e.g., burstiness). Discussion: The proposed strategy of using historical records for sentinel surveillance selection can be taken as a practical and robust alternative without the knowledge of individual contact behaviors for public health policymakers.