Smart Mushroom-Inspired Imprintable and Lightly Detachable (MILD) Microneedle Patterns for Effective COVID-19 Vaccination and Decentralized Information Storage.

The key to controlling the spread of the coronavirus disease 2019 (COVID-19) and reducing mortality is highly dependent on the safe and effective use of vaccines for the general population. Current COVID-19 vaccination practices (intramuscular injection of solution-based vaccines) are limited by heavy reliance on medical professionals, poor compliance, and laborious vaccination recording procedures, resulting in a waste of health resources and low vaccination coverage, etc. In this study, we developed a smart mushroom-inspired imprintable and lightly detachable (MILD) microneedle platform for the effective and convenient delivery of multidose COVID-19 vaccines and decentralized vaccine information storage. The mushroom-like structure allows the MILD system to be easily pressed into the skin and detached from the patch base, acting as a "tattoo" to record the vaccine counts in situ without any storage equipment, offering quick accessibility and effortless readout, saving a great deal of valuable time and energy for both patients and health professionals. After loading inactivated SARS-CoV-2 virus-based vaccines, MILD system induced a high level of antibodies against the SARS-CoV-2 receptor-binding domain (RBD) in vivo without eliciting systemic toxicity and local damage. Collectively, this smart delivery platform serves as a promising carrier to improve COVID-19 vaccination efficacy through its dual capabilities of vaccine delivery and in situ data storage, thus exhibiting great potential for helping to contain the COVID-19 pandemic or a resurgence.

Mobile monitoring of urban air quality at high spatial resolution by low-cost sensors: impacts of COVID-19 pandemic lockdown

The development of low-cost sensors and novel calibration algorithms provides new hints to complement conventional ground-based observation sites to evaluate the spatial and temporal distribution of pollutants on hyperlocal scales (tens of meters). Here we use sensors deployed on a taxi fleet to explore the air quality in the road network of Nanjing over the course of a year (October 2019–September 2020). Based on GIS technology, we develop a grid analysis method to obtain 50 m resolution maps of major air pollutants (CO, NO2, and O3). Through hotspot identification analysis, we find three main sources of air pollutants including traffic, industrial emissions, and cooking fumes. We find that CO and NO2 concentrations show a pattern: highways > arterial roads > secondary roads > branch roads > residential streets, reflecting traffic volume. The O3 concentrations in these five road types are in opposite order due to the titration effect of NOx. Combined the mobile measurements and the stationary station data, we diagnose that the contribution of traffic-related emissions to CO and NO2 are 42.6 % and 26.3 %, respectively. Compared to the pre-COVID period, the concentrations of CO and NO2 during the COVID-lockdown period decreased for 44.9 % and 47.1 %, respectively, and the contribution of traffic-related emissions to them both decreased by more than 50 %. With the end of the COVID-lockdown period, traffic emissions and air pollutant concentrations rebounded substantially, indicating that traffic emissions have a crucial impact on the variation of air pollutant levels in urban regions. This research demonstrates the sensing power of mobile monitoring for urban air pollution, which provides detailed information for source attribution, accurate traceability, and potential mitigation strategies at the urban micro-scale.

COVID-19 confirmed patients with negative antibodies results.

BACKGROUND: A new coronavirus disease 2019 (COVID-19) has escalated to a pandemic since its first outbreak in Wuhan, China. A small proportion of patients may have difficulty in generating IgM or IgG antibodies against SARS-CoV-2, and little attention has been paid to them. CASE PRESENTATIONS: We present two cases of confirmed COVID-19 patients and characterize their initial symptoms, chest CT results, medication, and laboratory test results in detail (including RT-PCR, IgM/ IgG, cytokine and blood cell counts). CONCLUSION: Both of patients with confirmed COVID-19 pneumonia failed to produce either IgM or IgG even 40 to 50 days after their symptoms onset. This work provides evidence demonstrating that at least a small proportion of patients may have difficulty in rapidly gaining immunity against SARS-CoV-2.

Eosinopenia and elevated C-reactive protein facilitate triage of COVID-19 patients in fever clinic: A retrospective case-control study.

BACKGROUND: Coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently a pandemic affecting over 200 countries. Many cities have established designated fever clinics to triage suspected COVID-19 patients from other patients with similar symptoms. However, given the limited availability of the nucleic acid test as well as long waiting time for both the test and radiographic examination, the quarantine or therapeutic decisions for a large number of mixed patients were often not made in time. We aimed to identify simple and quickly available laboratory biomarkers to facilitate effective triage at the fever clinics for sorting suspected COVID-19 patients from those with COVID-19-like symptoms. METHODS: We collected clinical, etiological, and laboratory data of 989 patients who visited the Fever Clinic at Wuhan Union Hospital, Wuhan, China, from Jan 31 to Feb 21. Based on polymerase chain reaction (PCR) nucleic acid testing for SARS-CoV-2 infection, they were divided into two groups: SARS-CoV-2-positive patients as cases and SARS-CoV-2-negative patients as controls. We compared the clinical features and laboratory findings of the two groups, and analyzed the diagnostic performance of several laboratory parameters in predicting SARS-CoV-2 infection and made relevant comparisons to the China diagnosis guideline of having a normal or decreased number of leukocytes (≤9·5 109/L) or lymphopenia (<1·1 109/L). FINDINGS: Normal or decreased number of leukocytes (≤9·5 109/L), lymphopenia (<1·1 109/L), eosinopenia (<0·02 109/L), and elevated hs-CRP (≥4 mg/L) were presented in 95·0%, 52·2%, 74·7% and 86·7% of COVID-19 patients, much higher than 87·2%, 28·8%, 31·3% and 45·2% of the controls, respectively. The eosinopenia produced a sensitivity of 74·7% and specificity of 68·7% for separating the two groups with the area under the curve (AUC) of 0·717. The combination of eosinopenia and elevated hs-CRP yielded a sensitivity of 67·9% and specificity of 78·2% (AUC=0·730). The addition of eosinopenia alone or the combination of eosinopenia and elevated hs-CRP into the guideline-recommended diagnostic parameters for COVID-19 improved the predictive capacity with higher than zero of both net reclassification improvement (NRI) and integrated discrimination improvement (IDI). INTERPRETATION: The combination of eosinopenia and elevated hs-CRP can effectively triage suspected COVID-19 patients from other patients attending the fever clinic with COVID-19-like initial symptoms. This finding would be particularly useful for designing triage strategies in an epidemic region having a large number of patients with COVID-19 and other respiratory diseases while limited medical resources for nucleic acid tests and radiographic examination.