Prevalence and factors associated with post-traumatic stress disorder in healthcare workers exposed to COVID-19 in Wuhan, China: a cross-sectional survey

BackgroundThe COVID-19 pandemic has posed significant threats to both the physical and psychological health of healthcare workers working in the front-line combating COVID-19. However, studies regarding the medium to long term impact of COVID-19 on mental health among healthcare workers are limited. Therefore, we conducted this cross-sectional survey to investigate the prevalence, factors and impact of post-traumatic stress disorder (PTSD) in healthcare workers exposed to COVID-19 8 months after the end of the outbreak in Wuhan, China.MethodsA web-based questionnaire was delivered as a link via the communication application WeChat to those healthcare workers who worked at several COVID-19 units during the outbreak (from December 2019 to April 2020) in Wuhan, China. The questionnaire included questions on social-demographic data, the post-traumatic stress disorder checklist-5 (PCL-5), the family care index questionnaire (Adaptation, Partnership, Growth, Affection and Resolve, APGAR), and the quality-of-life scale (QOL). The prevalence, risk and protective factors, and impact of PTSD on healthcare workers were subsequently analyzed.ResultsAmong the 659 participants, 90 healthcare workers were still suffering from PTSD 8 months after the end of the outbreak of COVID-19 in Wuhan, in which avoidance and negative impact were the most affected dimensions. Suffering from chronic disease, experiencing social isolation, and job dissatisfaction came up as independent risk factors for PTSD, while obtaining COVID-19 related information at an appropriate frequency, good family function, and working in well-prepared mobile cabin hospitals served as protective factors. The impact of PTSD on COVID-19 exposed healthcare workers was apparent by shortened sleeping time, feeling of loneliness, poorer quality of life and intention to resign.ConclusionsEight months after the end of the COVID-19 outbreak in Wuhan, the level of PTSD in healthcare workers exposed to COVID-19 was still high. Apart from the commonly recognized risk factors, comorbid chronic disease was identified as a new independent risk factor for developing PTSD. For countries where the pandemic is still ongoing or in case of future outbreaks of new communicable diseases, this study may contribute to preventing cases of PTSD in healthcare workers exposed to infectious diseases under such circumstances

Circulating Monocytes Act as a Common Trigger for the Calcification Paradox of Osteoporosis and Carotid Atherosclerosis via TGFB1-SP1 and TNFSF10-NFKB1 Axis

BackgroundOsteoporosis often occurs with carotid atherosclerosis and causes contradictory calcification across tissue in the same patient, which is called the “calcification paradox”. Circulating monocytes may be responsible for this unbalanced ectopic calcification. Here, we aimed to show how CD14+ monocytes contribute to the pathophysiology of coexisting postmenopausal osteoporosis and carotid atherosclerosis.MethodsWe comprehensively analyzed osteoporosis data from the mRNA array dataset GSE56814 and the scRNA-seq dataset GSM4423510. Carotid atherosclerosis data were obtained from the GSE23746 mRNA dataset and GSM4705591 scRNA-seq dataset. First, osteoblast and vascular SMC lineages were annotated based on their functional expression using gene set enrichment analysis and AUCell scoring. Next, pseudotime analysis was applied to draw their differentiated trajectory and identify the key gene expression changes in crossroads. Then, ligand–receptor interactions between CD14+ monocytes and osteoblast and vascular smooth muscle cell (SMC) lineages were annotated with iTALK. Finally, we selected calcification paradox-related expression in circulating monocytes with LASSO analysis.ResultsFirst, we found a large proportion of delayed premature osteoblasts in osteoporosis and osteogenic SMCs in atherosclerosis. Second, CD14+ monocytes interacted with the intermediate cells of the premature osteoblast and osteogenic SMC lineage by delivering TGFB1 and TNFSF10. This interaction served as a trigger activating the transcription factors (TF) SP1 and NFKB1 to upregulate the inflammatory response and cell senescence and led to a retarded premature state in the osteoblast lineage and osteogenic transition in the SMC lineage. Then, 76.49% of common monocyte markers were upregulated in the circulating monocytes between the two diseases, which were related to chemotaxis and inflammatory responses. Finally, we identified 7 calcification paradox-related genes on circulating monocytes, which were upregulated in aging cells and downregulated in DNA repair cells, indicating that the aging monocytes contributed to the development of the two diseases.ConclusionsOur work provides a perspective for understanding the triggering roles of CD14+ monocytes in the development of the calcification paradox in osteoporosis- and atherosclerosis-related cells based on combined scRNA and mRNA data. This study provided us with an elucidation of the mechanisms underlying the calcification paradox and could help in developing preventive and therapeutic strategies

Operational Navigation of Agents and Self-organization Phenomena in Velocity-based Models for Pedestrian Dynamics

While moving in space, pedestrians often adjust their direction of movement and/or their speed to avoid collisions with others and obstacles. This steering process is influenced by physical factors from the environment, as well as psychological factors of pedestrians such as motivation. Therefore, when modeling the movement of pedestrians especially for reproducing self-organization phenomena, it is important to consider these factors. This cumulative dissertation includes four publications related to velocity-based models for pedestrian dynamics. Three of them study the navigation of pedestrians and related self-organization phenomena, and the remaining one is an applied study related to the control measures adopted by German supermarkets during the COVID-19 pandemic. Velocity-based models consider pedestrians as particles also called agents and describe their movement at the operational level, by means of first-order differential equations. Velocity-based models, contrary to cellular automata, are continuous in space. Moreover, the new position of pedestrians is determined directly by a velocity function instead of an integrating of acceleration in force-based models. In publication I, a velocity-based model that considers several basic behaviors of pedestrians is proposed and validated with the fundamental diagram of unidirectional pedestrian flow. Besides, the effect of agents’ shape on the overall dynamics is studied. Although this basic model is able to guarantee the volume exclusion and reproduce the fundamental diagram of unidirectional pedestrian flow, it does not perform well incomplex scenarios, where self-organization phenomena occur. Therefore, in publication II and III, the previously developed basic model is used to quantitatively study clogging in bottleneck scenarios and lane-formation in bidirectional flow scenarios, respectively. In addition, in publication III, an anticipation mechanism is introduced into the basic model to describe lane-formation in bidirectional flow scenarios more realistically

On the Effectiveness of the Measures in Supermarkets for Reducing Contact among Customers during COVID-19 Period

The spread of the COVID-19 virus had a huge impact on human life on the global scale.Many control measures devoted to decrease contact among people have been adopted to slow down the transmission of the disease.A series of measures have been taken in supermarkets, which include restricting the number of customers, keeping social distance, and entering with a shopping cart.In this work, we investigate with numerical simulations the effectiveness of these measures in reducing the contact among customers.Several scenarios with different control measures are designed for numerical analysis.The movements of customers in a supermarket are simulated by a microscopic model for pedestrian dynamics.Moreover, an index based on the distance between customers is defined to measure the degree of contact and therefore evaluate it quantitatively.The effect of these measures on the average contact degree of each customer is explored, and the spatial distribution of the contact among customers in the supermarket is shown in a qualitative way.Simulation results show that except shopping cart measure, the other two measures are effective in reducing contact among customers

Balanced Meta Learning and Diverse Sampling for Lifelong Task-Oriented Dialogue Systems

In real-world scenarios, it is crucial to build a lifelong taskoriented dialogue system (TDS) that continually adapts to new knowledge without forgetting previously acquired experiences. Existing approaches mainly focus on mitigating the catastrophic forgetting in lifelong TDS. However, the transfer ability to generalize the accumulated old knowledge to new tasks is underexplored. In this paper, we propose a two-stage lifelong task-oriented dialogue generation method to mitigate catastrophic forgetting and encourage knowledge transfer simultaneously, inspired by the learning process. In the first stage, we learn task-specific masks which adaptively preserve the knowledge of each visited task so as to mitigate catastrophic forgetting. In this stage, we are expected to learn the task-specific knowledge which is tailored for each task. In the second stage, we bring the knowledge from the encountered tasks together and understand thoroughly. To this end, we devise a balanced meta learning strategy for both forward and backward knowledge transfer in the lifelong learning process. In particular, we perform meta-update with a meta-test set sampled from the current training data for forward knowledge transfer. In addition, we employ an uncertainty-based sampling strategy to select and store representative dialogue samples into episodic memory and perform meta-update with a meta-test set sampled from the memory for backward knowledge transfer. With extensive experiments on 29 tasks, we show that MetaLTDS outperforms the strong baselines in terms of both effectiveness and efficiency. For reproducibility, we submit our code at: https: //github.com/travis-xu/MetaLTDS

Clogging in Velocity-Based Models for Pedestrian Dynamics

In the simulation of pedestrian bottleneck flow with velocity-based models stable clogging could be observed, which is not in line with the movement of pedestrians in the real world. Four velocity-based models with different structures are selected in this paper to explore the cause of the phenomenon by identifying and analysing stable clogging. A series of simulations of pedestrians moving through a bottleneck are designed to investigate the decisive factors behind the unrealistic stable clogging, which includes the width of the exit, the flow of the pedestrian at the entrance and the size of the simulation time-step. The result of simulations with different models are compared and analyzed

Anticipation in a velocity-based model for pedestrian dynamics

Lane formation in bidirectional pedestrian streams is based on a stimulus-response mechanism and strategies of navigation in a fast-changing environment. Although microscopic models that only guarantee volume exclusion can qualitatively reproduce this phenomenon, they are not sufficient for a quantitative description. To quantitatively describe this phenomenon, a minimal anticipatory collision-free velocity model is introduced. Compared to the original velocity model, the new model reduces the occurrence of gridlocks and reproduces the movement of pedestrians more realistically. For a quantitative description of the phenomenon, the definition of an order parameter is used to describe the formation of lanes at transient states and to show that the proposed model compares relatively well with experimental data. Furthermore, the model is validated by the experimental fundamental diagrams of bidirectional flows