Weakly Semi-Supervised Detection in Lung Ultrasound Videos (preprint)

Frame-by-frame annotation of bounding boxes by clinical experts is often required to train fully supervised object detection models on medical video data. We propose a method for improving object detection in medical videos through weak supervision from video-level labels. More concretely, we aggregate individual detection predictions into video-level predictions and extend a teacher-student training strategy to provide additional supervision via a video-level loss. We also introduce improvements to the underlying teacher-student framework, including methods to improve the quality of pseudo-labels based on weak supervision and adaptive schemes to optimize knowledge transfer between the student and teacher networks. We apply this approach to the clinically important task of detecting lung consolidations (seen in respiratory infections such as COVID-19 pneumonia) in medical ultrasound videos. Experiments reveal that our framework improves detection accuracy and robustness compared to baseline semi-supervised models, and improves efficiency in data and annotation usage.

The impacts of patient mistreatment on healthcare workers’ role behaviors: a study in Chinese Fangcang shelter hospitals (preprint)

Background: Fangcang shelter hospitals have played an important role in the battle against the COVID-19 epidemic in China. Verbal and physical attacks on patients are prone to occur in such hospitals. This study explored the impacts of patient mistreatment on healthcare workers’ role behaviors (service performance and patient-oriented organizational citizenship behavior). Methods: We examined the influence of patient mistreatment on service performance and patient-oriented organizational citizenship behavior, as well as the mediating effect of emotional exhaustion and the moderating effect of displaced aggression by patients, using hierarchical linear regression and conditional process analysis. Results: Patient mistreatment was positively associated with emotional exhaustion among healthcare workers, while emotional exhaustion was negatively associated with service performance and patient-oriented organizational citizenship behavior. Mediation analysis revealed that emotional exhaustion mediated the association between patient mistreatment and both types of role behaviors. Moderated mediation analysis found that the mediation effect was weaker when the displaced aggression by patients was high. Conclusions: The findings clarified the relationship between patient mistreatment, emotional exhaustion, service performance, and patient-oriented organizational citizenship behavior. Additional assistance should be provided to healthcare workers dealing with patient mistreatment. Displaced aggression by patients attenuates the positive effects of patient mistreatment on the emotional exhaustion of healthcare workers. Our findings reveal the mechanism and boundary conditions of patient mistreatment affecting healthcare workers' service performance and patient-oriented organizational citizenship behavior.

Renewable Energy and Governance Resilience in the Gulf

The six Gulf monarchies—Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and United Arab Emirates (UAE)—are more politically stable than their peers in the Middle East and North Africa. Explanations for governance resilience range from repression to neopatrimonial and instrumental legitimacy, hydrocarbon-based rentierism, and permissive regional and international environments. This paper considers, in view of the proliferation and uptake of renewable energy in the Gulf, how governance resilience may be affected as a result of changes in state-society relations during the energy transition away from a fossil-fuel-based energy system. It offers a qualitative analysis of the impact of renewable energy deployment in the Gulf, supported by a rich array of secondary literature and data. It also offers a deep, if brief, dive to highlight intra-regional nuances. The authors conclude that in the short term, renewable energy deployment has a very modest impact given its limited share of power generation. In the longer term, even assuming that stated ambitions for renewable energy are fulfilled, no negative impact on monarchial resilience is expected thanks to gains in legitimacy and revenue streams, as well as purposeful alignment with an external environment supportive of renewable power in developing countries.

Public Opinions toward COVID-19 Vaccine Mandates: A Machine Learning-based Analysis of U.S. Tweets

While it has been scientifically proven that COVID-19 vaccine is a safe and effective measure to reduce the severity of infection and curbing the spread of the SARS-CoV-2 virus, skepticism remains widespread, and in many countries vaccine mandates have been met with strong opposition. In this study, we applied machine learning-based analyses of the U.S.-based tweets covering the periods leading toward and after the Biden Administration's announcement of federal vaccine mandates, supplemented by a qualitative content analysis of a random sample of relevant tweets. The objective was to examine the beliefs held among twitter users toward vaccine mandates, as well as the evidence that they used to support their positions. The results show that while approximately 30% of the twitter users included in the dataset supported the measure, more users expressed differing opinions. Concerns raised included questioning on the political motive, infringement of personal liberties, and ineffectiveness in preventing infection.

Determinants of quality of life in frontline healthcare providers caring for COVID-19 patients.

AIMS AND OBJECTIVES: To investigate the factors affecting quality of life in healthcare providers who care for patients with COVID-19. BACKGROUND: Healthcare providers caring for COVID-19 patients during the pandemic suffered a deterioration in their quality of life. Several studies have explored their psychological impact of working with COVID patients, but none have examined the causes of this deterioration. DESIGN: A cross-sectional study. METHODS: In the current study, the authors investigated the factors affecting quality of life in 293 healthcare providers recruited from a medical centre in northern Taiwan who had recently cared for patients with suspected or confirmed COVID-19 by analysing their responses to an online self-report questionnaire, using bivariate correlations and structural equation modelling. Reporting of this research adheres to the STROBE guideline. RESULTS: The study identified an important sequence of factors that mediated the effects of perceived success of epidemic prevention policies, family relations problems and education level on quality of life in a sample of healthcare workers caring for COVID-19 patients. The mediators were use of approach-oriented coping strategies and current mental health status. Specifically, use of approach-oriented coping strategies was found to directly cause improved quality of life and indirectly cause improved mental health, whereas use of avoidant coping strategies was found to directly cause worsening of mental health. Poor mental health predicted poor quality of life. CONCLUSIONS: Results suggest that implementation of sound epidemic prevention policies that promote adoption of approach-oriented coping behaviour should lead to a better quality of life in the future for healthcare providers working in challenging circumstances. RELEVANCE TO CLINICAL PRACTICE: Assessment of these policies as well as the providers' family relations are necessary first steps to improving the success of approach-oriented coping behaviour in this population, which in turn can improve their mental health and quality of life. PATIENT OR PUBLIC CONTRIBUTION: Neither patients nor members of the public were involved in the design or execution of the study.

Facile and Unplugged Surface Plasmon Resonance Biosensor with NIR-Emitting Perovskite Nanocomposites for Fast Detection of SARS-CoV-2.

The emergence of the coronavirus disease 2019 (COVID-19) pandemic prompted researchers to develop portable biosensing platforms, anticipating to detect the analyte in a label-free, direct, and simple manner, for deploying on site to prevent the spread of the infectious disease. Herein, we developed a facile wavelength-based SPR sensor built with the aid of a 3D printing technology and synthesized air-stable NIR-emitting perovskite nanocomposites as the light source. The simple synthesis processes for the perovskite quantum dots enabled low-cost and large-area production and good emission stability. The integration of the two technologies enabled the proposed SPR sensor to exhibit the characteristics of lightweight, compactness, and being without a plug, just fitting the requirements of on-site detection. Experimentally, the detection limit of the proposed NIR SPR biosensor for refractive index change reached the 10-6 RIU level, comparable with that of state-of-the-art portable SPR sensors. In addition, the bio-applicability of the platform was validated by incorporating a homemade high-affinity polyclonal antibody toward the SARS-CoV-2 spike protein. The results demonstrated that the proposed system was capable of discriminating between clinical swab samples collected from COVID-19 patients and healthy subjects because the used polyclonal antibody exhibited high specificity against SARS-CoV-2. Most importantly, the whole measurement process not only took less than 15 min but also needed no complex procedures or multiple reagents. We believe that the findings disclosed in this work can open an avenue in the field of on-site detection for highly pathogenic viruses.

The colonic interleukin-19 aggravates the dextran sodium sulfate/stress-induced comorbidities due to colitis and anxiety

Comorbidities due to inflammatory bowel disease (IBD) and anxiety are commonly acknowledged;however, their underlying basis is unclear. In the current study, we first conducted a clinical retrospective analysis to identify the enhancive incidence rate of IBD before or after the epidemic of Corona Virus Disease 2019 (COVID-19), with higher Generalized Anxiety Disorder-7 (GAD-7), as well as poorer Gastrointestinal Quality of Life Index (GIQLI). Then, the dextran sodium sulfate (DSS) and chronic unpredictable stress (CUS)-induced IBD and anxiety comorbid models were established with the correlational relations between symptoms of IBD and anxiety-related behaviors. We found dysfunctional up-regulation of a new inflammatory factor interleukin (IL)-19 in the colon of DSS/CUS treated mice. Overexpression of IL-19 in colon induced anxious phenotypes, and accelerated the anxious condition and symptoms of colitis in the DSS/CUS model by promoting the expression of inducible nitric oxide synthase (iNOS), IL-1β, and IL-6 pro-inflammatory factors, and activating signal transducer and activator of transcription 3 (STAT3) signaling pathway in the colon. Furthermore, overexpression of IL-19 in the colon also reduced the expression levels of brain-derived neurotrophic factor (BDNF), extracellular signal-regulated kinase (ERK), and cAMP-response element binding protein (CREB) signaling pathways activity in the hippocampus. These results suggest that IL-19 was a pivotal player in DSS/CUS-induced comorbidities of colitis and anxiety with different signaling pathways for the colon and hippocampus, which provides a candidate gene to explore the pathophysiology of comorbidities due to colitis and anxiety.

The colonic interleukin-19 aggravates the dextran sodium sulfate/stress-induced comorbidities due to colitis and anxiety.

Comorbidities due to inflammatory bowel disease (IBD) and anxiety are commonly acknowledged; however, their underlying basis is unclear. In the current study, we first conducted a clinical retrospective analysis to identify the enhancive incidence rate of IBD before or after the epidemic of Corona Virus Disease 2019 (COVID-19), with higher Generalized Anxiety Disorder-7 (GAD-7), as well as poorer Gastrointestinal Quality of Life Index (GIQLI). Then, the dextran sodium sulfate (DSS) and chronic unpredictable stress (CUS)-induced IBD and anxiety comorbid models were established with the correlational relations between symptoms of IBD and anxiety-related behaviors. We found dysfunctional up-regulation of a new inflammatory factor interleukin (IL)-19 in the colon of DSS/CUS treated mice. Overexpression of IL-19 in colon induced anxious phenotypes, and accelerated the anxious condition and symptoms of colitis in the DSS/CUS model by promoting the expression of inducible nitric oxide synthase (iNOS), IL-1ß, and IL-6 pro-inflammatory factors, and activating signal transducer and activator of transcription 3 (STAT3) signaling pathway in the colon. Furthermore, overexpression of IL-19 in the colon also reduced the expression levels of brain-derived neurotrophic factor (BDNF), extracellular signal-regulated kinase (ERK), and cAMP-response element binding protein (CREB) signaling pathways activity in the hippocampus. These results suggest that IL-19 was a pivotal player in DSS/CUS-induced comorbidities of colitis and anxiety with different signaling pathways for the colon and hippocampus, which provides a candidate gene to explore the pathophysiology of comorbidities due to colitis and anxiety.

Understanding underlying moral values and language use of COVID-19 vaccine attitudes on twitter.

Public sentiment toward the COVID-19 vaccine as expressed on social media can interfere with communication by public health agencies on the importance of getting vaccinated. We investigated Twitter data to understand differences in sentiment, moral values, and language use between political ideologies on the COVID-19 vaccine. We estimated political ideology, conducted a sentiment analysis, and guided by the tenets of moral foundations theory (MFT), we analyzed 262,267 English language tweets from the United States containing COVID-19 vaccine-related keywords between May 2020 and October 2021. We applied the Moral Foundations Dictionary and used topic modeling and Word2Vec to understand moral values and the context of words central to the discussion of the vaccine debate. A quadratic trend showed that extreme ideologies of both Liberals and Conservatives expressed a higher negative sentiment than Moderates, with Conservatives expressing more negative sentiment than Liberals. Compared to Conservative tweets, we found the expression of Liberal tweets to be rooted in a wider set of moral values, associated with moral foundations of care (getting the vaccine for protection), fairness (having access to the vaccine), liberty (related to the vaccine mandate), and authority (trusting the vaccine mandate imposed by the government). Conservative tweets were found to be associated with harm (around safety of the vaccine) and oppression (around the government mandate). Furthermore, political ideology was associated with the expression of different meanings for the same words, e.g. "science" and "death." Our results inform public health outreach communication strategies to best tailor vaccine information to different groups.

Recent computational drug repositioning strategies against SARS-CoV-2.

Since COVID-19 emerged in 2019, significant levels of suffering and disruption have been caused on a global scale. Although vaccines have become widely used, the virus has shown its potential for evading immunities or acquiring other novel characteristics. Whether current drug treatments are still effective for people infected with Omicron remains unclear. Due to the long development cycles and high expense requirements of de novo drug development, many researchers have turned to consider drug repositioning in the search to find effective treatments for COVID-19. Here, we review such drug repositioning and combination efforts towards providing better handling. For potential drugs under consideration, aspects of both structure and function require attention, with specific categories of sequence, expression, structure, and interaction, the key parameters for investigation. For different data types, we show the corresponding differing drug repositioning methods that have been exploited. As incorporating drug combinations can increase therapeutic efficacy and reduce toxicity, we also review computational strategies to reveal drug combination potential. Taken together, we found that graph theory and neural network were the most used strategy with high potential towards drug repositioning for COVID-19. Integrating different levels of data may further improve the success rate of drug repositioning.

Towards hospital-on-chip supported by 2D MXenes-based 5th generation intelligent biosensors.

Existing public health emergencies due to fatal/infectious diseases such as coronavirus disease (COVID-19) and monkeypox have raised the paradigm of 5th generation portable intelligent and multifunctional biosensors embedded on a single chip. The state-of-the-art 5th generation biosensors are concerned with integrating advanced functional materials with controllable physicochemical attributes and optimal machine processability. In this direction, 2D metal carbides and nitrides (MXenes), owing to their enhanced effective surface area, tunable physicochemical properties, and rich surface functionalities, have shown promising performances in biosensing flatlands. Moreover, their hybridization with diversified nanomaterials caters to their associated challenges for the commercialization of stability due to restacking and oxidation. MXenes and its hybrid biosensors have demonstrated intelligent and lab-on-chip prospects for determining diverse biomarkers/pathogens related to fatal and infectious diseases. Recently, on-site detection has been clubbed with solution-on-chip MXenes by interfacing biosensors with modern-age technologies, including 5G communication, internet-of-medical-things (IoMT), artificial intelligence (AI), and data clouding to progress toward hospital-on-chip (HOC) modules. This review comprehensively summarizes the state-of-the-art MXene fabrication, advancements in physicochemical properties to architect biosensors, and the progress of MXene-based lab-on-chip biosensors toward HOC solutions. Besides, it discusses sustainable aspects, practical challenges and alternative solutions associated with these modules to develop personalized and remote healthcare solutions for every individual in the world.

Dynamic characteristics of a COVID-19 outbreak in Nanjing, Jiangsu province, China.

Objectives: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineage B.1.617.2 (also named the Delta variant) was declared as a variant of concern by the World Health Organization (WHO). This study aimed to describe the outbreak that occurred in Nanjing city triggered by the Delta variant through the epidemiological parameters and to understand the evolving epidemiology of the Delta variant. Methods: We collected the data of all COVID-19 cases during the outbreak from 20 July 2021 to 24 August 2021 and estimated the distribution of serial interval, basic and time-dependent reproduction numbers (R0 and Rt), and household secondary attack rate (SAR). We also analyzed the cycle threshold (Ct) values of infections. Results: A total of 235 cases have been confirmed. The mean value of serial interval was estimated to be 4.79 days with the Weibull distribution. The R0 was 3.73 [95% confidence interval (CI), 2.66-5.15] as estimated by the exponential growth (EG) method. The Rt decreased from 4.36 on 20 July 2021 to below 1 on 1 August 2021 as estimated by the Bayesian approach. We estimated the household SAR as 27.35% (95% CI, 22.04-33.39%), and the median Ct value of open reading frame 1ab (ORF1ab) genes and nucleocapsid protein (N) genes as 25.25 [interquartile range (IQR), 20.53-29.50] and 23.85 (IQR, 18.70-28.70), respectively. Conclusions: The Delta variant is more aggressive and transmissible than the original virus types, so continuous non-pharmaceutical interventions are still needed.

Booster shot of inactivated SARS-CoV-2 vaccine induces potent immune responses in people living with HIV.

This study aimed to investigate the immunogenicity to SARS-CoV-2 and evasive subvariants BA.4/5 in people living with HIV (PLWH) following a third booster shot of inactivated SARS-CoV-2 vaccine. We conducted a cross-sectional study in 318 PLWH and 241 healthy controls (HC) using SARS-CoV-2 immunoassays. Vaccine-induced immunological responses were compared before and after the third dose. Serum levels of IgG anti-RBD and inhibition rate of NAb were significantly elevated at the "post-third dose" sampling time compared with the pre-third dose in PLWH, but were relatively decreased in contrast with those of HCs. Induced humoral and cellular responses attenuated over time after triple-dose vaccination. The neutralizing capacity against BA.4/5 was also intensified but remained below the positive inhibition threshold. Seropositivity of SARS-CoV-2-specific antibodies in PLWH was prominently lower than that in HC. We also identified age, CD4 cell counts, time after the last vaccination, and WHO staging type of PLWH as independent factors associated with the seropositivity of antibodies. PLWH receiving booster shot of inactivated vaccines generate higher antibody responses than the second dose, but lower than that in HCs. Decreased anti-BA.4/5 responses than that of WT impede the protective effect of the third dose on Omicron prevalence.

Impact of public transport disruption on access to healthcare facility and well-being during the COVID-19 pandemic: A qualitative case study in Metro Manila, Philippines.

The COVID-19 pandemic has forced many governments to halt public transport operations. A consequence of such disruption is the reduction in access to critical facilities by individuals who rely on public transport for their daily mobility. We investigate the impact disparities caused by the restriction of public transportation on the access of healthcare workers and patients to healthcare facilities during the COVID-19 pandemic. Metro Manila is an appropriate case study site because the duration of suspension of public transport in the mega-city is one of the longest in the world. The prolonged duration of the lockdown could have devastating impacts on the well-being of individuals who are reliant on public transport to access essential services. Guided by the Yin-Eisenhardt approach to qualitative research, we examined the data from 55 individuals using within-case and cross-case analyses iteratively for the purpose of building a model on the impact of change in access due to public transport disruption on well-being. We mobilized constructs and concepts known in the literature, such as well-being, access, disruption, resistance, resilience, and vulnerability, in developing our two-step conceptual model. Given the profound impact of the prolonged and system-wide suspension of public transport on the well-being of individuals, it is necessary to provide sufficient public transport and active transport infrastructure and services that can cover their mobility needs. The two-step conceptual model from this study can provide guidance on specific policy interventions.

Identification of potentional immunological biomarkers of COVID-19 by blood transcriptome analysis (preprint)

Backgroud:The COVID-19 pandemic has swept the globe since 2019, threatening people's health. Many studies indicate that infection is closely related to immune response disorder. We searched for potential immune-related biomarkers through systems biological analysis, and performed immune infiltration analysis on relevant data. Methods and findings: We used CIBERSORT to analyze the blood transcriptomics data of the controls, the mild COVID-19 patients, and the severe COVID-19 patients. And we further obtained the essential infiltration immune cells of COVID-19 by the Wilcoxon test and LASSO algorithm. Then we used a limma package to find significant DE-IRGs. The GO and pathways analysis of these important immune genes were also applied. Subsequently, we used STRING and Cytoscape to screen hub genes and evaluated their value as a potential biomarker according to their expression at different stages and the ROC curve. Moreover, the results were verified by high-throughput data. Finally, we formed a TFs-mRNA-miRNA regulatory network diagram. Through the analysis above, we obtained four important immune cells. And the immune-related gene chip of the blood samples was analyzed to figure out the 36 significant DE-IRGs. Based on the operations above, we confirmed six immune-related hub genes involved in the pathogenesis of COVID-19 and analyzed their relationship with critical immune cells. Conclusions:It was concluded that TLR2, CAMP, S100A9, BCL6, CD4, and IL7R could be used as potential biomarkers to provide corresponding value for the diagnosis and the prognosis of COVID-19.

Dynamic characteristics of a COVID-19 outbreak in Nanjing, Jiangsu province, China

Objectives Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineage B.1.617.2 (also named the Delta variant) was declared as a variant of concern by the World Health Organization (WHO). This study aimed to describe the outbreak that occurred in Nanjing city triggered by the Delta variant through the epidemiological parameters and to understand the evolving epidemiology of the Delta variant. Methods We collected the data of all COVID-19 cases during the outbreak from 20 July 2021 to 24 August 2021 and estimated the distribution of serial interval, basic and time-dependent reproduction numbers (R0 and Rt), and household secondary attack rate (SAR). We also analyzed the cycle threshold (Ct) values of infections. Results A total of 235 cases have been confirmed. The mean value of serial interval was estimated to be 4.79 days with the Weibull distribution. The R0 was 3.73 [95% confidence interval (CI), 2.66–5.15] as estimated by the exponential growth (EG) method. The Rt decreased from 4.36 on 20 July 2021 to below 1 on 1 August 2021 as estimated by the Bayesian approach. We estimated the household SAR as 27.35% (95% CI, 22.04–33.39%), and the median Ct value of open reading frame 1ab (ORF1ab) genes and nucleocapsid protein (N) genes as 25.25 [interquartile range (IQR), 20.53–29.50] and 23.85 (IQR, 18.70–28.70), respectively. Conclusions The Delta variant is more aggressive and transmissible than the original virus types, so continuous non-pharmaceutical interventions are still needed.

Multiparameter mobile blood analyzer for complete blood count utilizing contrast-enhanced defocusing imaging (preprint)

Blood analysis, though complete blood count (CBC), is the most basic medical test for disease diagnosis and health monitoring. However, the need for bulky and expensive laboratory facilities and skilled technicians limits the universal medical practices based on blood analysis outside of well-equipped laboratory environments. Here, we proposed a multiparameter mobile blood analyzer utilizing label-free contrast-enhanced defocusing imaging (CEDI) with the assistance of machine vision for instant and on-site blood analysis. The analyzer using CEDI obtains both the blood cell morphological characteristics and hemoglobin spectrophotometric information for simultaneous five-part white blood cell differential count, red blood cell count, and hemoglobin quantification without the need for sample staining. In addition, we have designed a miniature microscope with a sub-micron spatial resolution of (~0.98 μm), which is quite small, lightweight, and cost-effective for blood imaging. We have shown that our assay can analyze a sample within 10 minutes, using just a drop of fingertip blood (~7 μl) and measurements (30 samples) from the analyzer have strong correlations with clinical reference values (significant level: P < 0.0001). The proposed mobile blood analyzer can help provide universal access to blood analysis and has great potential for integrated surveillance of various epidemic diseases, including coronavirus infection, invermination, and anemia, especially in low-and middle-income countries.

Clinical features and effectiveness of Chinese medicine in patients with COVID-19 from overseas: A retrospective study in Xiamen, China.

COVID-19, referred to as new coronary pneumonia, is an acute infectious disease caused by a new type of coronavirus SARS-CoV-2. To evaluate the effect of integrated Chinese medicine and Western medicine in patients with COVID-19 from overseas. Data were collected from 178 COVID-19 patients overseas at First Affiliated Hospital of Xiamen University from April 1, 2021 to July 31, 2021. These patients received therapy of integrated Chinese medicine and western medicine. Demographic data and clinical characteristics were extracted and analyzed. In addition, the prescription which induced less length of PCR positive days and hospitalization days than the median value was obtained. The top 4 frequently used Chinese medicine and virus-related genes were analyzed by network pharmacology and bioinformatics analysis. According to the chest computed tomography (CT) measurement, abnormal lung findings were observed in 145 subjects. The median length of positive PCR/hospitalization days was 7/7 days for asymptomatic subjects, 14/24 days for mild subjects, 10/15 days for moderate subjects, and 14/20 days for severe subjects. The most frequently used Chinese medicine were Scutellaria baicalensis (Huangqin), Glycyrrhiza uralensis (Gancao), Bupleurum chinense (Chaihu), and Pinellia ternata (Banxia). The putative active ingredients were baicalin, stigmasterol, sigmoidin-B, cubebin, and troxerutin. ACE, SARS-CoV-2 3CL, SARS-CoV-2 Spike, SARS-CoV-2 ORF7a, and caspase-6 showed good binding properties to active ingredients. In conclusion, the clinical results showed that integrated Chinese medicine and Western medicine are effective in treating COVID-19 patients from overseas. Based on the clinical outcomes, the putative ingredients from Chinese medicine and the potential targets of SARS-CoV-2 were provided, which could provide a reference for the clinical application of Chinese medicine in treating COVID-19 worldwide.