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COVID-19 has a dramatic impact on human health, besides respiratory system, reproduction system would be impaired by SARS-CoV-2. For male, the virus has various negative impacts on testes, including overheating and hormone level fluctuation, which have impacts on the spermatogenesis or spermatogonia development. For female, COVID-19 may increase the risk of endocrine and metabolic dysfunction. However, the impact of SARS-CoV-2 on the ovaries is not clear, and further researches are needed to clarify it. Nearly 60% of the pregnant women develop symptoms of infection and more attention should be paid to the increased risk of adverse pregnancy outcomes including preeclampsia, eclampsia, and severe infection. For the newborns of infected pregnant women, vertical transmission of SARS-CoV-2 is still unclear, and further evaluation are required. Meantime, the pregnant women's fear of the potential infection may reduce their access to the prenatal genetic test. In this chapter, we summarize the latest basic and clinical researches on COVID-19 impacts on male, female reproduction, and prenatal genetic test, hoping to provide guidance and advice for people of reproductive age and reproductive healthcare practitioners. © 2023 Elsevier Inc. All rights reserved.
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Objective: To explore the double psychosocial threats of the COVID-19 pandemic, targeted behavior toward Chinese Americans, and the correlates to their mental health. Methods: A quantitative, cross-sectional, and descriptive design was utilized by using a purposive convenience sample of 301 Chinese Americans over the age of 18 residing in the United States. Online data collection was conducted through the social media platform WeChat from April 8–21, 2021. Descriptive statistical analysis was used for the participants' demographic characteristics, Multidimensional Scale of Perceived Social Support (MSPSS), Double Threat Situations, COVID-19 Racial Discrimination, and General Anxiety Disorder-7 (GAD-7). Stepwise logistic regression was conducted to verify predictors for anxiety levels by GAD-7. Results: In this sample (N = 301), 127 (42.19%) were male and 174 (57.81%) were female. The average age was 41.67 (SD = 5.89). Among MSPSS subscales, social support from family (MSPSS-Fam, 79.73%, n = 240) and social support from significant others (MSPSS-SO, 73.75%, n = 222) were high. 231 (76.74%) reported threats due to their Chinese ethnic background during the COVID-19 outbreak. Predictors for the high anxiety level by GAD-7 were COVID-19 racial discrimination from the local community (OR = 0.47, 95% CI = 0.39–0.71, p < 0.001), media/online (OR = 0.36, 95% CI = 0.26–0.53, p < 0.001), the perceived threat from the COVID-19 virus (OR = 0.33, 95% CI = 0.23–0.51, p < 0.001) and Perceived racism threat from Chinese background related to COVID-19 (OR = 0.31, 95% CI = 0.21–0.49, p < 0.001). Conclusions: COVID-19 double-threats (The virus and racial discrimination) situations are significantly related to the high level of anxiety among Chinese Americans. The sense of belonging and social perceptions of Chinese immigrants is closely related to public health problems in Western societies and needs to be addressed at all levels. Our findings call for the attention of healthcare workers to specific racism double-threatened situations and high mental health risks, as well as direct and indirect ethnic discrimination that Chinese Americans are experiencing during this pandemic, the long-term influences and effective coping ways related to this issue should be explored in further research. © 2023, Tech Science Press. All rights reserved.
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Indoor environment has significant impacts on human health as people spend 90% of their time indoors. The COVID-19 pandemic and the increased public health awareness have further elevated the urgency for cultivating and maintaining a healthy indoor environment. The advancement in emerging digital twin technologies including building information modeling (BIM), Internet of Things (IoT), data analytics, and smart control have led to new opportunities for building design and operation. Despite the numerous studies on developing methods for creating digital twins and enabling new functionalities and services in smart building management, very few have focused on the health of indoor environment. There is a critical need for understanding and envisaging how digital twin paradigms can be geared towards healthy indoor environment. Therefore, this study reviews the techniques for developing digital twins and discusses how the techniques can be customized to contribute to public health. Specifically, the current applications of BIM, IoT sensing, data analytics, and smart building control technologies for building digital twins are reviewed, and the knowledge gaps and limitations are discussed to guide future research for improving environmental and occupant health. Moreover, this paper elaborates a vision for future research on integrated digital twins for a healthy indoor environment with special considerations of the above four emerging techniques and issues. This review contributes to the body of knowledge by advocating for the consideration of health in digital twin modeling and smart building services and presenting the research roadmap for digital twin-enabled healthy indoor environment.
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Businesses reeling from the impact of COVID are struggling to achieve sustainability, amidst many other challenges, including finance and capacity shortfalls. One of the pathways to achieving 3BL in businesses is to create closed-loop supply chains (CLSC) covering the entire lifecycle of products. CLSC have proven to be important for sustainable supply chain (SC) operations, given the shortage of materials and labour globally following the COVID-19 pandemic. While it is widely acknowledged that the success of CLSC depends on successful collaboration between SC members, factors for successful CLSC collaboration are not sufficiently understood from the literature. Employing an observation-based case study and a survey of SC members, we develop our contribution in the context of an Indian packaging company, to delineate and verify a collaborative CLSC framework. The results confirm that the success of CLSC collaboration lies in the involvement and commitment of SC members. Collaboration for forward and reverse SC operations also facilitate the involvement of SC members in CLSC collaborations. Our research suggests that SC collaborations are enhanced by explicit incentive-sharing schemes and having the same SC members for both forward and reverse SC operations. © 2023 The Authors
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The emergence of the SARS-CoV-2 Omicron variant raises concerns for school operations worldwide. The Omicron variant spread faster than other variants that cause COVID-19, and breakthrough infections are reported in vaccinated people. Schools are hotbeds for the transmission of the highly contagious virus. Therefore it is crucial to understand the risks of Omicron transmission and the effectiveness of different measures to prevent the surge of infection cases. This study estimates the risks of airborne transmission and fomite transmission of Omicron variants using simulations and the data of 11,485 public and private schools in the U.S. It also analyzes the impact of different mitigation measures on limiting airborne transmission and fomite transmission risks in schools. It was found that the Omicron variant caused relatively high infection risks in schools. The risk of airborne transmission is nine times higher than fomite transmission. The effective mitigation measures can significantly decrease the transmission risk. © 2022 IEEE.
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The outbreak of COVID-19 has caused concerns globally. To reduce the rapid transmission of the virus, strict city lockdown measures were conducted in different regions. China is the country that takes the earliest home-based quarantine for people. Although normal industrial and social activities were suspended, the spread of virus was efficiently controlled. Simultaneously, another merit of the city lockdown measure was noticed, which is the improvement of the air quality. Contamination levels of multiple atmospheric pollutants were decreased. However, in this work, 24 and 14 air fine particulate matter (PM2.5) samples were continuously collected before and during COVID-19 city lockdown in Linfen (a typical heavy industrial city in China), and intriguingly, the unreduced concentration was found for environmentally persistent free radicals (EPFRs) in PM2.5 after normal life suspension. The primary non-stopped coal combustion source and secondary Cu-related atmospheric reaction may have impacts on this phenomenon. The cigarette-based assessment model also indicated possible exposure risks of PM2.5-bound EPFRs during lockdown of Linfen. This study revealed not all the contaminants in the atmosphere had an apparent concentration decrease during city lockdown, suggesting the pollutants with complicated sources and formation mechanisms, like EPFRs in PM2.5, still should not be ignored. © 2022
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To examine how and when stress affect individual (i.e., psychological health) and relationship well-being (i.e., marital satisfaction) during the COVID-19 pandemic, the present study used latent profile analysis to identify the typologies of communication and investigated whether the typologies would moderate the associations between stress and individual and relationship well-being in a sample of adults living in China (N = 3,354). Results revealed that (a) stress was negatively associated with psychological health and marital satisfaction during the COVID-19 pandemic and that its effect on psychological health was greater than that on marital satisfaction and (b) four profiles were identified: low communication (10%), moderate communication (43%), positive communication (43%), and contradictory communication (5%). Further, the typologies moderated the effects of stress on psychological health and marital satisfaction, but the patterns of moderation differed in psychological health and marital satisfaction. © 2022 Taylor & Francis Group, LLC.
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The transit bus environment is considered one of the primary sources of transmission of the COVID-19 (SARS-CoV-2) virus. Modeling disease transmission in public buses remains a challenge, especially with uncertainties in passenger boarding, alighting, and onboard movements. Although there are initial findings on the effectiveness of some of the mitigation policies (such as face-covering and ventilation), evidence is scarce on how these policies could affect the onboard transmission risk under a realistic bus setting considering different headways, boarding and alighting patterns, and seating capacity control. This study examines the specific policy regimes that transit agencies implemented during early phases of the COVID-19 pandemic in USA, in which it brings crucial insights on combating current and future epidemics. We use an agent-based simulation model (ABSM) based on standard design characteristics for urban buses in USA and two different service frequency settings (10-min and 20-min headways). We find that wearing face-coverings (surgical masks) significantly reduces onboard transmission rates, from no mitigation rates of 85% in higher-frequency buses and 75% in lower-frequency buses to 12.5%. The most effective prevention outcome is the combination of KN-95 masks, open window policies, and half-capacity seating control during higher-frequency bus services, with an outcome of nearly 0% onboard infection rate. Our results advance understanding of COVID-19 risks in the urban bus environment and contribute to effective mitigation policy design, which is crucial to ensuring passenger safety. The findings of this study provide important policy implications for operational adjustment and safety protocols as transit agencies seek to plan for future emergencies. © 2023
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Within the context of the COVID-19 pandemic, community-level medical institutions as health service centres have been gaining importance in the medical reform expansion. As prior research has not fully addressed how to index and evaluate the quality of medical service, this article proposes a framework based on the service quality gap theory and the three-faceted "structure-process-outcome"quality evaluation theory. The study took the medical services at Beijing's Tianqiao Community Health Service Centre as an example to construct an index system for medical service quality evaluations. Data was collected from 211 people, and SPSS software was used for data processing and analysis. Due to the COVID-19 pandemic, patients without serious diseases tend to choose community hospitals to reduce their infection risk. As a result, they have growing requirements for clinics to have more departments and specialists. The studied community health service centre has encountered difficulties connected to low patient expectations, a poor medical environment, outdated hardware and equipment, and a low level of medical services. Some suggestions have been made to add specialised departments and consider the convenience of medical treatment for the elderly. © 2022 Qiong He et al., published by Sciendo.
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Respiratory symptoms are most commonly experienced by patients in the early stages of novel coronavirus disease 2019 (COVID-19). However, with a better understanding of COVID-19, gastrointestinal symptoms such as diarrhea, nausea, and vomiting have attracted increasing attention. The gastrointestinal tract may be a target organ of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The intestinal microecological balance is a crucial factor for homeostasis, including immunity and inflammation, which are closely related to COVID-19. Herbal medicine can restore intestinal function and regulate the gut flora structure. Herbal medicine has a long history of treating lung diseases from the perspective of the intestine, which is called the gut–lung axis. The physiological activities of guts and lungs influence each other through intestinal flora, microflora metabolites, and mucosal immunity. Microecological modulators are included in the diagnosis and treatment protocols for COVID-19. In this review, we demonstrate the relationship between COVID-19 and the gut, gut–lung axis, and the role of herbal medicine in treating respiratory diseases originating from the intestinal tract. It is expected that the significance of herbal medicine in treating respiratory diseases from the perspective of the intestinal tract could lead to new ideas and methods for treatment.Graphical :: http://links.lww.com/AHM/A33.
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Background and Aims: Breast cancer is the most prevalent malignancy in women worldwide, and chemotherapy is one of the most important treatment modalities for breast cancer. Recent studies have shown that chemotherapy may exert anti-tumor effects by enhancing anti-tumor immunity in the tumor microenvironment. Therefore, this study was conducted to identify the changes in tumor-associated macrophages (TAMs) and relevant genes before and after neoadjuvant chemotherapy (NAC) in breast cancer patients by bioinformatics analysis and to evaluate the effect of NAC on immune functions in breast cancer patients. Methods: Information searching was performed by entering "Breast Cancer", "TAMs", "Chemotherapy" and selecting the human breast cancer tissue in the GEO database, and the GSE134600 dataset was selected for analysis. Differentially expressed genes (DEGs) in tissue samples from breast cancer patients before and after NAC were screened by R package (limma function). GO function enrichment and KEGG pathway analysis were performed for all DRGs. The protein interaction network of DEGs was visualized by Cytoscape software, and hub genes were screened and 10 hub genes were analyzed for mutations by cBioPortal. Immune cell distribution and correlation in GSE134600 data were evaluated using the R package“CIBERSORT”. Results: A total of 751 DEGs (409 up-regulated and 342 down-regulated genes) were identified before and after NAC for breast cancer. The biology of DEGs was analyzed by GO enrichment for biological process（BP）, cellular component （CC）, and molecular function（MF）. In BP function, they were mainly enriched in type I interferon(IFN-I) signaling pathway/viral response and defense and viral life cycle;in CC function, they were mainly enriched in extrinsic components of cell membrane and cytoplasmic side of cell membrane;in MF function, they were mainly enriched in cytokine receptor binding, double-stranded RNA binding and lipopeptide binding. In the analysis of KEGG pathway enrichment, DEGs were mainly enriched in influenza A (H1N1), measles, hepatitis C, coronavirus disease COVID-19, NF-κB signaling pathway, EBV virus infection, NOD-like receptor signaling pathway, and amoeba disease signaling pathway. The top 10 hub genes with the highest degree of interaction with TAMs before and after NAC for breast cancer were screened by CytoHubba plug-in: IFIT1, ISG15, MX1, MX2, IRF7, RSAD2, IFIT3, IFI35, IFI6, and IFITM1. Multi-omics analysis revealed that IFIT1, MX1 and MX2 were mainly deletion mutations, IFIT1 mainly had deep gene deletion, while MX1 and MX2 were mainly associated with gene amplifications. The content of M0 macrophages, CD8+T cells and M2 macrophages in breast cancer tissues decreased after NAC, and M0 macrophages were positively correlated with memory B cells (r=0.64) and negatively correlated with unactivated CD4+ memory T cells (r=-0.66). Conclusion: The identified DEGs associated with TAMs in breast cancer patients before and after NAC are closely related to interferon signaling pathway, suggesting that interferon signaling pathway may play an important role by altering TAMs in NAC. Meanwhile, M0 macrophages are significantly altered before and after NAC, indicating that chemotherapy may regulate the immune response to tumor by changing the distribution of M0 macrophages and immune function. © 2022 Central South University. All right reserved.
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Infectious diseases pose a severe threat to human health, especially the outbreak of COVID-19. After the infectious disease enters the stage of large-scale epidemics, vaccination is an effective way to control infectious diseases. However, when formulating a vaccination strategy, some restrictions still exist, such as insufficient vaccines or insufficient government funding to afford everyone's vaccination. Therefore, in this paper, we propose a vaccination optimization problem with the lowest total cost based on the susceptible-infected-recovered (SIR) model, which is called the Lowest Cost Of Vaccination Strategy (LCOVS) problem. We first establish a mathematical model of the LCOVS problem. Then we propose a practical Differential Evolution based Simulated Annealing (DESA) method to solve the mathematical optimization problem. We use the simulated annealing algorithm (SA) as a local optimizer for the results obtained by the differential evolution algorithm (DE) and optimized the mutation and crossover steps of DE. Finally, the experimental results on the six data sets demonstrate that our proposed DESA can achieve a more low-cost vaccination strategy than the baseline algorithms. IEEE
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The spread of drug-resistance bacteria is a serious issue of environment. Tools allowing to image single-cell genes can provide key information about the spatial pattern and heterogeneity of cell population. Herein, we explored the possibility of in situ activation of collateral trans-cleavage activity of CRISPR/Cas12a inside cells, to achieve a direct detection of single-cell non-repetitive genes. CRISPR/Cas12a allows to recognize target genes without the need for denaturation or digestion process. Particularly, the target gene-activated trans-cleavage by CRISPR/ Cas12a inside cells outputs an amplified signal for the gene recognition, allowing to visualize non-repetitive genes. The signal-to-background ratio for imaging drug-resistance gene, oqxB in the Salmonella enterica subsp. enterica serovar Typhimurium (S. Typhimurium) was further improved by combining multiple binding of Cas12a, enabled imaging of drug-resistance S. Typhimurium isolated from poultry farm and in the intestinal tract sec-tions. Single-cell investigation of S. Typhimurium under salt stress indicated that drug-sensitive strain owned a survival advantage over drug-resistance strain at high-content salt environment. This gene imaging methods holds potential for detecting the spread of drug resistance in the environment and serves as a means to inves-tigate the relationship between genotype and phenotype at single-cell level.
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Misinformation and rumors can spread rapidly and widely through online social networks, seriously endangering social stability. Therefore, rumor blocking on social networks has become a hot research topic. In the existing research, when users receive two opposing opinions, they tend to believe the one arrives first. In this article, we argue that users will dialectically trust the information based on their own opinions rather than the rule of first-come-first-listen. We propose a confidence-based opinion adoption (CBOA) model, which considers the opinion and confidence according to the traditional linear threshold (LT) model. Based on this model, we propose the directed graph convolutional network (DGCN) method to select the <inline-formula> <tex-math notation="LaTeX">$k$</tex-math> </inline-formula> most influential positive cascade nodes to suppress the propagation of rumors. Finally, we verify our method on four real network datasets. The experimental results show that our method can sufficiently suppress the propagation of rumors and obtains smaller number of rumor nodes than the baseline algorithms. IEEE
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The long-lasting global pandemic of Coronavirus disease 2019 (COVID-19) has changed our daily life in many ways and put heavy burden on our mental health. Having a predictive model of negative emotions during COVID-19 is of great importance for identifying potential risky population. To establish a neural predictive model achieving both good interpretability and predictivity, we have utilized a large-scale (n =542) longitudinal dataset, alongside two independent samples for external validation. We built a predictive model based on psychologically meaningful resting state neural activities. The whole-brain resting-state neural activity and social-psychological profile of the subjects were obtained from Sept. to Dec. 2019 (Time 1). Their negative emotions were tracked and re-assessed twice, on Feb 22 (Time 2) and Apr 24 (Time 3), 2020, respectively. We first applied canonical correlation analysis on both the neural profiles and psychological profiles collected on Time 1, this step selects only the psychological meaningful neural patterns for later model construction. We then trained the neural predictive model using those identified features on data obtained on Time 2. It achieved a good prediction performance (r =0.44, p =8.13 ×10-27). The two most important neural predictors are associated with self-control and social interaction. This study established an effective neural prediction model of negative emotions, achieving good interpretability and predictivity. It will be useful for identifying potential risky population of emotional disorders related to COVID-19. IEEE
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The spread of the novel coronavirus disease 2019 (COVID-19) has claimed millions of lives. Automatic segmentation of lesions from CT images can assist doctors with screening, treatment, and monitoring. However, accurate segmentation of lesions from CT images can be very challenging due to data and model limitations. Recently, Transformer-based networks have attracted a lot of attention in the area of computer vision, as Transformer outperforms CNN at a bunch of tasks. In this work, we propose a novel network structure that combines CNN and Transformer for the segmentation of COVID-19 lesions. We further propose an efficient semi-supervised learning framework to address the shortage of labeled data. Extensive experiments showed that our proposed network outperforms most existing networks and the semi-supervised learning framework can outperform the base network by 3.0% and 8.2% in terms of Dice coefficient and sensitivity. © 2022 IEEE.
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Since December 2019, the COVID-19 outbreak has spread in over 100 countries and regions at a stunning pace. To prevent humanitarian health hazards such as COVID-19, people are strongly suggested to purchase and use Personal Protective Equipments (PPEs) for self-protection. However, the fraction of the population who refused to comply with the PPEs is high (and also much higher in some regions than others). In this paper, we focus on an empirically tested behavioral explanation for the compliance obstacle (a lack of self-control) based on the present-bias effect, which means the trend to give a higher valuation to a present reward but a lower valuation to a future reward (O’Donoghue & Rabin, 2006). Since the utility of PPEs is realized in the future, a consumer may postpone his purchase decision but finally abandon his purchase plan in the future period due to this present-bias effect. The key take-away we focus on is that advance selling can be beneficial to the consumers as a commitment device (Bryan et al., 2010). However, the effect of advance selling may be limited, especially for consumers with low valuation, and can only encourage a part of consumers to purchase PPEs. Advance selling alone cannot fully address the compliance obstacles in PPEs. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Objective: To assess the level of pulmonary ventilation function in patients with COVID‑19 after six months post⁃discharge and analyze the relevant influencing factors. Methods: In November 2020, patients with COVID‑19 were investigated in a district of Wuhan City, Hubei Province. Their pulmonary ventilation function indicators were measured, including forced vital capacity of percent predicted (FVC%pred), forced expiratory volume in one second of percent predicted (FEV1%pred), FEV1/FVC ratio (FEV1/FVC%), forced expiratory flow at 50% of percent predicted (FEF50%pred), forced expiratory flow at 75% of percent predicted (FEF75%pred), mean forced expiratory flow between 25% and 75% of percent predicted (MMEF%pred). The related factors affecting pulmonary ventilation function were analyzed. Results: A total of 151 discharged cases were recruited, which included 64 cases of mild illness, 87 cases of moderate illness. The average age of both men and women in the mild group was significantly higher than that in the moderate group (P<0.05). The mean values of the lung ventilation function indexes were all within the normal range. The FVC%pred in both male and female and FEV1%pred in female were better in the mild group than that in the moderate group (P<0.05). Some patients had mild abnormal pulmonary ventilation function and 11 cases in the mild group, 46 cases in the moderate group. Multi‑factor logistic regression analysis showed that women [OR=3.012, 95%CI(1.249,7.264)], the presence of a previous history of chronic disease [OR=2.739, 95%CI(1.186,6.326)], and cases of moderate illness [OR=6.365, 95%CI(2.730,14.840)] were the risk factors for abnormal pulmonary ventilation function after discharge. Conclusion: Half a year after discharge, the pulmonary ventilation function of both mild and moderate group patients recovered well. Women and those with chronic disease in the past should have more targeted health guidance during the post‑discharge recovery period. © 2022, Editorial Board of Medical Journal of Wuhan University. All right reserved.