PFC/M1 activation and excitability: a longitudinal cohort study on fatigue symptoms in healthcare workers post-COVID-19 (preprint)

Background Fatigue is one of the most common neurological symptoms reported post coronavirus disease 2019 (COVID-19) infection. In order to establish effective early intervention strategies, more emphasis should be placed on the correlation between fatigue and cortical neurophysiological changes, especially in healthcare workers, who are at a heightened risk of COVID-19 infection.Methods A prospective cohort study was conducted involving 29 COVID-19 medical workers and 24 healthy controls. The assessment included fatigue, sleep and health quality, psychological status, and physical capacity. Functional near-infrared spectroscopy (fNIRS) was employed to detect activation of brain regions. Bilateral primary motor cortex (M1) excitabilities were measured using single- and paired-pulse transcranial magnetic stimulation. Outcomes were assessed at 1, 3, and 6 months into the disease course.Results At 1-month post-COVID-19 infection, 37.9% of patients experienced severe fatigue symptoms, dropping to 10.3% at 3 months. Interestingly, the remarkable decreased activation/excitability of bilateral prefrontal lobe (PFC) and M1 were closely linked to fatigue symptoms after COVID-19. Notably, greater increase in M1 region excitability correlated with more significant fatigue improvement. Re-infected patients exhibited lower levels of brain activation and excitability compared to single-infection patients.Conclusions Both single infection and reinfection of COVID-19 lead to decreased activation and excitability of the PFC and M1. The degree of excitability improvement in the M1 region correlates with a greater recovery in fatigue. Based on these findings, targeted interventions to enhance and regulate the excitability of M1 may represent a novel strategy for COVID-19 early rehabilitation.Trial registration The Ethics Review Committee of Xijing Hospital, No. KY20232051-F-1, registered February 3, 2023. The Chinese Clinical Trial Registry, ChiCTR2300068444, registered February 20, 2023. https://www.chictr.org.cn

Agricultural Production Networks and Upgrading from a Global-Local Perspective: A Review

The COVID-19 pandemic, extreme temperatures and the Russia-Ukraine conflict have exposed deficiencies in global agricultural production capacity and governance systems, which left low-income countries and regions to face more severe food insecurity. Thus, there is an urgent need for agricultural upgrading and the establishment of a more sustainable agricultural system. Although there is a large body of literature with rich theoretical and empirical case studies, there is still a lack of systematic analysis of these studies, and the summary of global agricultural production networks and the agricultural upgrading process is not sufficient. This article will first set up an organisational framework of global agricultural production networks and explore the implications of governance and agricultural upgrading within this framework. It will then summarise the local agricultural upgrading processes on global, national and local scales based on a review of the existing literature. The article argues that agricultural upgrading in the context of global linkages is mainly driven by private-sector standards while the state also plays multiple roles. Moreover, in the embedding process of global agricultural production networks into local areas, local actors can promote agricultural upgrading through capacity building and organisational innovation. This review has implications for the economic, social and environmental sustainability of agriculture in developing countries, and provides a reference for future research.

Quantitative analysis of the impact of COVID-19 on ship visiting behaviors to ports- A framework and a case study

Corona Virus Disease 2019 (COVID-19) outbreak leads to a significant downturn in the global economy and supply chain. In the maritime sector, trade volume slumped by 3.8% in 2020 compared with 2019. To explore the impacts of COVID-19 on ship visiting behaviors, a framework is proposed to analyze the impact of COVID-19 on port traffic using Automatic Identification System (AIS) data. Firstly, a ship travel behavior-based model is proposed to identify the vessel anchoring and berthing. Then, the diversity in vessel anchoring and berthing time are analyzed, reflecting the impact of COVID-19. The port congestion caused by COVID-19 is quantified by accounting for the number of visiting ships and their residence time. Finally, a case study is carried out on vessels in the Beibu Gulf, China, operating from 2019 to 2020. The results show that the average anchoring time and berthing time increase by 53% and 26% for cargo ships and by 90% and 63% for oil tankers after the outbreak of COVID-19 compared with that before COVID-19. And the density of ships increases in the port area in 2020. Accordingly, the relevant improvements and countermeasures are proposed to reduce the adverse impact of the epidemic on the port navigation system. The paper has the potential to provide a reference for port management and improving port navigation efficiency in the post-pandemic era.

Fiber-Based Masks and Respirators: Using Decontamination Methods and Antimicrobial Treatment to Improve Its Reusability during Pandemic

Shortage of personal protective equipment (PPE) is often projected in response to public health emergencies such as infection outbreaks and pandemics. Respiratory protective devices (RPDs), namely medical face masks and respirators, are considered the last defense for the front-line healthcare workers. Cleaning, decontamination and reuse of the disposable RPDs have been accepted by local health authorities during the pandemic period. To contribute to the mitigation of RPD shortage and ensure the safe adoption of decontamination protocols, this review discusses the regulated testing standards and the most commonly studied decontamination methods in the literature. The reuse of RPDs must fulfill three criteria: remove the microbial thread, maintain original function and structural integrity (including fitting tests) and leave no harmful residuals. Decontamination methods such as ultraviolet germicidal irradiation, moist heat and vaporized hydrogen peroxide appeared to be the most promising methods in balancing the above-mentioned criteria. However, the effectiveness of decontamination methods varies depending on the RPDs’ models, materials and design. Therefore, the adoption of protocols needs to be evidence-based with full validation in the local institutes. Additionally, new technology such as antimicrobial treated PPE that can reduce the risks of fomite during donning and doffing process with an extended lifespan should be encouraged. Overall, good training and guidance for appropriate reuse of RPDs are fundamental to ensure their efficiency in protecting front-line healthcare workers.

3D RegNet: Deep Learning Model for COVID-19 Diagnosis on Chest CT Image (preprint)

In this paper, a 3D-RegNet-based neural network is proposed for diagnosing the physical condition of patients with coronavirus (Covid-19) infection. In the application of clinical medicine, lung CT images are utilized by practitioners to determine whether a patient is infected with coronavirus. However, there are some laybacks can be considered regarding to this diagnostic method, such as time consuming and low accuracy. As a relatively large organ of human body, important spatial features would be lost if the lungs were diagnosed utilizing two dimensional slice image. Therefore, in this paper, a deep learning model with 3D image was designed. The 3D image as input data was comprised of two-dimensional pulmonary image sequence and from which relevant coronavirus infection 3D features were extracted and classified. The results show that the test set of the 3D model, the result: f1 score of 0.8379 and AUC value of 0.8807 have been achieved.

SPEEDS: A Portable Serological Testing Platform for Rapid Electrochemical Detection of SARS-CoV-2 Antibodies (preprint)

The COVID-19 pandemic has resulted in a worldwide health crisis. Rapid diagnosis, new therapeutics and effective vaccines will all be required to stop the spread of COVID-19. Quantitative evaluation of serum antibody levels against the SARS-CoV-2 virus provides a means of monitoring a patient's immune response to a natural viral infection or vaccination, as well as evidence of a prior infection. In this paper, a portable and low-cost electrochemical immunosensor is developed for the rapid and accurate quantification of SARS-CoV-2 serum antibodies. The immunosensor is capable of quantifying the concentrations of immunoglobulin G (IgG) and immunoglobulin M (IgM) antibodies against the SARS-CoV-2 spike protein in human serum. For IgG and IgM, it provides measurements in the range of 10.1 ng/mL--60 g/mL and 1.64 ng/mL -- 50 g/mL, respectively, and both antibodies can be assayed in 13 min. We also developed device stabilization and storage strategies to achieve stable performance of the immunosensor within 24-week storage at room temperature. We evaluated the performance of the immunosensor using COVID-19 patient serum samples collected at different time points after symptom onset. The rapid and sensitive detection of IgG and IgM provided by our immunosensor fulfills the need of rapid COVID-19 serology testing for both point-of-care diagnosis and population immunity screening.