Evaluation of Microbiological Culture and Antibiogram of the Patient with Corneal Ulcer due to Exposure Keratitis in the Intensive Care Unit in Sina Farshchian Hospital (2019-2020)

Background: Since patients admitted to the intensive care unit have a compromised im-mune system and are more prone to infection than other patients, timely diagnosis and treatment of corneal ulcers among this group of patients can prevent vision loss. Therefore, it is necessary to treat eye infections and corneal ulcers promptly and economize prohibitive costs. Objective(s): Appropriate treatment with the most effective antibiotic before the answer is available to prevent corneal ulcer complications and blindness. Method(s): This study was conducted from November 2019 to November 2020 and after approval by the ethics committee of Hamedan University of Medical Sciences with the code of ethics: IR.UMSHA.REC.1398.716. First, the corneal secretions of 121 patients admitted to the intensive care unit of Sina Hospital are prepared by an ophthalmologist (after anesthetizing the cornea with tetra-caine drops and sterile swabs) and culture in four growth mediums (blood agar, chocolate agar, thio-glycolate, and EMB). Microbial cultures are examined after 48 hours and a fungal culture is examined one week later. Disc diffusions are placed in positive microbial cultures. Antibiotic susceptibility or resistance of the antibiogram was recorded. Other demographic data, including patients' age and sex, are extracted from ICU files. Also, test results and patient identifications are recorded in a checklist designed for this purpose. Result(s): Of all the antibiotics used against common bacteria, vancomycin (84%), colistin (80.43%), cefazolin (80%), and levofloxacin (60%) had the highest sensitivity and gentamicin (93.75%), ceftazidime (86.42%) Erythromycin (85%) had the highest resistance against isolated bacteria. Conclusion(s): The data obtained from this study showed that the most common microorganisms in the age group under the age of 30 years were Acinetobacter Baumannii, in the group of 30-60 years old was Klebsiella pneumonia, and age group over 61 years old was Staphylococcus aureus, and the most sensitive antibiotics in the age group under 30 years were vancomycin and levofloxacin and the age group30-60 were colistin and vancomycin and in the age group over 61 years were vancomycin and cefazolin.Copyright © 2023 Bentham Science Publishers.

New care settings and innovation will usher diagnostic testing into the future

The article focuses on the future of diagnostic testing in healthcare, highlighting the importance of testing in tracking and treating diseases like COVID-19. It discusses the advancements in diagnostic technology, including combination tests for multiple respiratory diseases and the rise of at-home testing, which will increase access to testing and empower patients to manage their health.

Diffusion of digital technologies in the face of external shocks: The case of the COVID-19 pandemic

This paper investigates the impact of external shocks on the spread of digital technologies. Using the example of the COVID-19 pandemic, we identify and describe four patterns that reflect the uneven response of different digital technologies to external conditions undergoing transformation. The patterns differ in both the magnitude of the pandemic's impact and the timing of the resulting effects. Video conferencing, business continuity and telemedicine services showed a dramatic increase in demand at the beginning of COVID-19 and a gradual decline in the later stages. A more moderate response in the early weeks of the pandemic is typical of e-commerce and online entertainment. Delayed effects are seen in digital logistics services and digital currencies, which reacted much later than other technologies. Finally, a slow decline in significance after the pandemic began has been observed for biometrics and cybersecurity technologies. Similar patterns may describe the transformation of the spread of digital technologies not only under the influence of COVID-19, but also in the face of dramatic economic and social changes of other origins. © 2023 The Author(s).

Nanosponges: As a Dynamic Drug Delivery Approach for Targeted Delivery

Recent advancements in nanotechnology have resulted in improved medicine delivery to the target site. Nanosponges are three-dimensional drug delivery systems that are nanoscale in size and created by cross-linking polymers. The introduction of Nanosponges has been a significant step toward overcoming issues such as drug toxicity, low bioavailability, and predictable medication release. Using a new way of nanotechnology, nanosponges, which are porous with small sponges (below one microm) flowing throughout the body, have demonstrated excellent results in delivering drugs. As a result, they reach the target place, attach to the skin's surface, and slowly release the medicine. Nanosponges can be used to encapsulate a wide range of medicines, including both hydrophilic and lipophilic pharmaceuticals. The medication delivery method using nanosponges is one of the most promising fields in pharmacy. It can be used as a biocatalyst carrier for vaccines, antibodies, enzymes, and proteins to be released. The existing study enlightens on the preparation method, evaluation, and prospective application in a medication delivery system and also focuses on patents filed in the field of nanosponges.Copyright © 2023 The Authors.

Respiratory Muscle Strength in Patients after Covid-19

Respiratory muscles (RM) are a very important part of the respiratory system that enables pulmonary ventilation. This study aimed to assess the post-COVID-19 strength of RM by estimating maximum static inspiratory (MIP or PImax) and expiratory (MEP or PEmax) pressures and to identify the relationship between MIP and MEP and the parameters of lung function. We analyzed the data of 36 patients (72% male;median age 47 years) who underwent spirometry, and body plethysmography, diffusion test for carbon monoxide (DLCO) and measurement of MIP and MEF. The median time between the examinations and onset of COVID-19 was 142 days. The patients were divided into two subgroups. In subgroup 1, as registered with computed tomography, the median of the maximum lung tissue damage volume in the acute period was 27%, in subgroup 2 it reached 76%. The most common functional impairment was decreased DLCO, detected in 20 (55%) patients. Decreased MIP and MEP were observed in 5 and 11 patients, respectively. The subgroups did not differ significantly in MIP and MEP values, but decreased MIP was registered in the second subgroup more often (18%). There were identified no significant dependencies between MIP/MEP and the parameters of ventilation and pulmonary gas exchange. Thus, in patients after COVID-19, MIP and MEP were reduced in 14 and 31% of cases, respectively. It is reasonable to add RM tests to the COVID-19 patient examination plan in order to check them for dysfunction and carry out medical rehabilitation.Copyright © 2022 Obstetrics, Gynecology and Reproduction. All rights reserved.

International Trade Fairs and Inter-Firm Knowledge Flows: Understanding Patterns of Convergence-Divergence in the Technological Specializations of Firms

Against a backdrop of economic uncertainty caused by a shift toward protectionism and the COVID-19 pandemic among other issues, this book suggests that international trade fairs (ITFs) represent a vital source of economic dynamism that can support national and regional economies by creating opportunities for firms to access new markets, network with key actors in their industry or value chain, and tap into valuable external knowledge flows regarding new technologies and innovations. Author Rachael Gibson argues that ITFs have become crucial nodes in the global political economy, driving global economic dynamics and mediating differences between capitalist economies regarding their technological and institutional practices and conditions. In this way, ITFs represent a decisive mechanism by which distinct national patterns of technological specialization may converge or diverge. Trade fairs represent important platforms for networking, interactive learning, and knowledge exchange because they foster intense interactions among actors despite spatial boundaries. ITFs also tend to be organized according to a specific technological or industry focus, which means that they can facilitate interactions between firms from different capitalist varieties. Through the diffusion of state-of-the-art knowledge, ITFs may, thus, serve as drivers of economic globalization, challenging the continuation of distinct capitalist varieties by enabling cross-system convergence regarding the technological specializations of firms. Yet, it is clear that countries have retained competitive advantages in specific industries and that full convergence has not taken place. This book explores this puzzle. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Machine learning-based diffusion model for prediction of coronavirus-19 outbreak.

The coronavirus pandemic has been globally impacting the health and prosperity of people. A persistent increase in the number of positive cases has boost the stress among governments across the globe. There is a need of approach which gives more accurate predictions of outbreak. This paper presents a novel approach called diffusion prediction model for prediction of number of coronavirus cases in four countries: India, France, China and Nepal. Diffusion prediction model works on the diffusion process of the human contact. Model considers two forms of spread: when the spread takes time after infecting one person and when the spread is immediate after infecting one person. It makes the proposed model different over other state-of-the art models. It is giving more accurate results than other state-of-the art models. The proposed diffusion prediction model forecasts the number of new cases expected to occur in next 4 weeks. The model has predicted the number of confirmed cases, recovered cases, deaths and active cases. The model can facilitate government to be well prepared for any abrupt rise in this pandemic. The performance is evaluated in terms of accuracy and error rate and compared with the prediction results of support vector machine, logistic regression model and convolution neural network. The results prove the efficiency of the proposed model.

Influence of Human Behavior on COVID-19 Dynamics Based on a Reaction-Diffusion Model.

To investigate the influence of human behavior on the spread of COVID-19, we propose a reaction-diffusion model that incorporates contact rate functions related to human behavior. The basic reproduction number R0 is derived and a threshold-type result on its global dynamics in terms of R0 is established. More precisely, we show that the disease-free equilibrium is globally asymptotically stable if R0≤1; while there exists a positive stationary solution and the disease is uniformly persistent if R0>1. By the numerical simulations of the analytic results, we find that human behavior changes may lower infection levels and reduce the number of exposed and infected humans.

De Novo Design of Anti-COVID Drugs Using Machine Learning-Based Equivariant Diffusion Model Targeting the Spike Protein.

The drug discovery and research for an anti-COVID-19 drug has been ongoing despite repurposed drugs in the market. Over time, these drugs were discontinued due to side effects. The search for effective drugs is still under process. The role of Machine Learning (ML) is critical in the search for novel drug compounds. In the current work, using the equivariant diffusion model, we built novel compounds targeting the spike protein of SARS-CoV-2. Using the ML models, 196 de novo compounds were generated which had no hits on any major chemical databases. These novel compounds fulfilled all the criteria of ADMET properties to be lead-like and drug-like compounds. Of the 196 compounds, 15 were docked with high confidence in the target. These compounds were further subjected to molecular docking, the best compound having an IUPAC name of (4aS,4bR,8aS,8bS)-4a,8a-dimethylbiphenylene-1,4,5,8(4aH,4bH,8aH,8bH)-tetraone and a binding score of -6.930 kcal/mol. The principal compound is labeled as CoECG-M1. Density Function Theory (DFT) and Quantum optimization was carried out along with the study of ADMET properties. This suggests that the compound has potential drug-like properties. The docked complex was further subjected to MD simulations, GBSA, and metadynamics simulations to gain insights into the stability of binding. The model can be in the future modified to improve the positive docking rate.

The effects of city morphology on airborne transmission of COVID-19. Case study: Port Said City, Egypt.

Looking beyond COVID-19 outbreak, Scholars continue to develop innovative approaches to bring the city on to health and safety. Recent studies have indicated that urban spaces could produce or propagate pathogens, which is an urgent topic at the city level. However, there is a dearth of studies investigating the interrelationship between urban morphology and pandemics outbreak at the neighborhood level. Accordingly, this research will trace the effect of cities morphologies on the rate of spread of COVID-19 through a simulation study held on five areas that form the urban morphology of Port Said City, using Envi-met software. Results are explored based on the degree of concentration and rate of diffusion of coronavirus particles. It was observed on a regular basis that wind speed has a directly proportional relationship with the diffusion of the particles and an inversely proportional relationship with the concentration of the particles. However, certain urban characteristics led to inconsistent and opposing results like wind tunnels, shaded arcades, height variance, and spacious in-between spaces. Moreover, it is obvious that the city morphology is being transformed over time toward safer conditions; urban areas constructed recently have low vulnerability to respiratory pandemics outbreak compared to older areas.

Microstructural alterations in hypoxia-related BRAIN centers after COVID-19 by using DTI: A preliminary study.

PURPOSE: To investigate whether the diffusion tensor imaging (DTI) parameters alterations in the in hypoxia-related neuroanatomical localizations in patients after COVID-19. Additionally, the relationship between DTI findings and the clinical severity of the disease is evaluated. METHODS: The patients with COVID-19 were classified into group 1 (total patients, n = 74), group 2 (outpatient, n = 46), and group 3 (inpatient, n = 28) and control (n = 52). Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values were calculated from the bulbus, pons, thalamus, caudate nucleus, globus pallidum, putamen, and hippocampus. DTI parameters were compared between groups. Oxygen saturation, D dimer and lactate dehydrogenase (LDH) values associated with hypoxia were analyzed in inpatient group. Laboratory findings were correlated with ADC and FA values. RESULTS: Increased ADC values in the thalamus, bulbus and pons were found in group 1 compared to control. Increased FA values in the thalamus, bulbus, globus pallidum and putamen were detected in group 1 compared to control. The FA and ADC values obtained from putamen were higher in group 3 compared to group 2. There was a negative correlation between basal ganglia and hippocampus FA values and plasma LDH values. The ADC values obtained from caudate nucleus were positively correlated with plasma D Dimer values. CONCLUSION: ADC and FA changes may reveal hypoxia-related microstructural damage after COVID-19 infection. We speculated that the brainstem and basal ganglia can affected during the subacute period.

Impact of admission viral load on respiratory outcomes in hospitalized SARS-CoV-2 infected patients with cancer and without cancer: A 2-, 4- and 6-months follow-up prospective study.

BACKGROUND: This prospective follow-up study aimed to determine the temporal changes in respiratory outcomes over 6 months period in patients with and without cancer hospitalized for severe COVID-19 and to determine the associated risk factors based on admission viral load. METHODS: All adult patients hospitalized with a confirmed diagnosis of severe SARS-CoV-2 infection were investigated using rRT-PCR on nasopharyngeal swab specimens. Patients were divided into three arbitrary groups according to their cycle threshold (CT) values obtained at admission as high (CT<25.0), medium (CT between 25.0 and 30.0), and low (CT>30.0) viral load. Patients had pulmonary function tests, chest high-resolution computed tomography (HRCT), and a 6-minute walking time distance measured at each follow-up visit. RESULTS: This follow-up study had a total of 112 participants, of which 75 were cancer-free and 37 had active cancer. Overall, 29.5% had a low viral load, compared to 48.2% who had a high viral load, and 22.3% had a medium viral load. For patients who did not have cancer, the mean age was 57.3 (SD 15.4) and for those who had cancer, it was 62.3 (SD 18.4). Most patients had overall better temporal changes in pulmonary function and tolerance, as well as exercise capacity, even though severe and chronic respiratory abnormalities persisted in a fraction of the patients. In patients without cancer who had a high viral load, we have seen a substantial reduction in diffusion capacity of the lungs for carbon monoxide (DLCO) predicted value with a median of 65 (IQR 63-70) while in patients with cancer, it was 60 (IQR 56-67) at 2 months. At 4 and 6 months, the predicted DLCO values for patients without cancer were 65 (IQR 61-70), whereas the predicted DLCO values for patients with active cancer were 62 (IQR 60-67) and 67 (59-73). Importantly, radiological abnormalities persisted in 22 (29%) non-cancer patients and 16 (43%) cancer patients. Multivariate regression analysis showed an increased odds ratio of impaired HRCT associated with a high viral load of 3.04 (95% CI:1.68-6.14; p < 0.001) for patients without cancer and 5.07 (95% CI: 4.04-10.8; p < 0.0001) for patients with cancer. The CT pneumonia score at hospitalization was 2.25 (95% CI:1.76-3.08; p = 0.041) and 2.85 (95% CI:1.89-5.14; p = 0.031) for non-cancer and cancer patients respectively. CONCLUSIONS: The evidence of persistent pulmonary abnormalities and radiographic changes was found in both patient groups who had high viral load at hospital admission and suggesting that SARS-CoV-2 viral load might serve as a useful indicator to predict the development of respiratory complications in patients with COVID-19.

Psychological Predictors of Intention to Use Fitness Apps: The Role of Subjective Knowledge and Innovativeness

Health and fitness apps have grown exponentially during covid-19 lockdowns. Using a sample of 331 European fitness apps users, this study investigated the psychological drivers of users' intention on fitness apps. This study draws upon the Technology Acceptance Model (TAM) and innovation diffusion theory. Its findings reveal that subjective knowledge and personal innovativeness predict perceived Usefulness, health consciousness, and ease of use. The strongest predictor of intention to use an app is perceived Usefulness, which mediates the influence of subjective knowledge and innovativeness on intention to use. Health consciousness predicts ease of use;however, the latter does not predict behavioural intention. This is one of the first studies on European users of fitness apps and investigating the psychological antecedents of TAM, i.e., innovativeness, subjective knowledge, and consciousness.

Rigidity in crisis: The impact of OHSAS 18001 certification on production repurposing during COVID-19

It is important for firms to repurpose production responsively during a crisis such as the COVID-19 pandemic, to seize the market opportunity and create social value. However, occupational health and safety (OHS) can also be a concern in a crisis, and adherence to OHS management systems can undermine a firm's responsiveness in repurposing decision making. We adopt the "capability-rigidity" lens to construct a connection between OHS management standards (i.e., OHSAS 18001) and firms' adaptation responsiveness. After sampling 734 listed Chinese manufacturing firms, our match-based analysis reveals that firms certified with OHSAS 18001 were less responsive during COVID-19 in terms of production repurposing than those without the certification. Yet, certain experience, namely, prepandemic manufacturing of related products, experience of the severe acute respiratory syndrome (SARS) epidemic, and being geographically located close to firms that produced medical supplies, could attenuate this effect. We discuss the implications of our findings in the context of and adding to the literature on safety management, certified management standards, and organizational adaptation and learning.

Exposure to risk communication, compliance with preventive measures and information-sharing behavior among students during the COVID-19 pandemic

PurposeDuring the coronavirus disease 2019 (COVID-19) pandemic, public health risk communication has been a vital work. Students account for a large proportion of the population and are often highly mobile;thus, they face a high risk of contagion and spreading the disease. Therefore, risk communication to this group during the pandemic has been essential. This research examines the relationship between risk communication to students and their appropriate behaviors (compliance with COVID-19 preventive measures and COVID-19 information sharing).Design/methodology/approachThis research used structural equation model (SEM) and generalized structural equation model (GSEM) to analyze the data collected from students during the COVID-19 pandemic.FindingsThe findings revealed that risk communication in mass media was positively associated with students' compliance with preventive measures and sharing pandemic-related information. Additionally, their compliance behavior was positively associated with their information-sharing behavior.Practical implicationsThis research offers some implications regarding the containment of a highly-infectious virus, especially for the context when the risk of outbreak is high and an effective vaccine is not available, by focusing on risk communication and compliance and information-sharing behaviors.Originality/valueThis research is one of the early attempts to examine the risk communication to students, their compliance with preventive measures and their information-sharing behavior during a pandemic.

Policy entrepreneurs and individuals: Influence and behavior in pandemic response

Policy entrepreneurs have traditionally been recognized for their ability to influence policymakers by framing policy problems and pairing them with preferred solutions. Does their influence extend to the public? We examine this question in the context of the COVID-19 pandemic in the United States. We analyze whether an individual's perception of a visible, national-level policy entrepreneur, director of the National Institute of Allergy and Infectious Diseases (NIAID) Dr. Anthony Fauci, influences their perceived risk of contracting the virus and their uptake of recommended COVID-19 risk mitigation behaviors. Findings indicate that approval of Dr. Fauci predicts individual risk perceptions and uptake of mask wearing practices, with his influence particularly strong among conservatives. However, Dr. Fauci's influence as a policy entrepreneur waned over time and was moderated by a host of factors such as an individual's worldview, perceptions of policy environment, and media consumption.

A numerical method for space‐fractional diffusion models with mass‐conserving boundary conditions

The study of the spread of epidemics has gained significant attention in recent years, due to ongoing and recurring outbreaks of diseases such as COVID‐19, dengue, Ebola, and West Nile virus. In particular, modeling the spatial spread of these epidemics is crucial. This article explores the use of fractional diffusion as a means of describing non‐local infection spread. The Grünwald–Letnikov formulation of fractional diffusion is presented, along with several mass‐conserving boundary conditions, that is, we aim to design the boundary conditions in a mass‐conserving way, by not allowing gain or loss of the total population. The stationary points of the model for both sticky and reflecting boundary conditions are discussed, with numerical examples provided to illustrate the results. It is shown that reflecting boundary conditions are more reasonable, as the stationary point for sticky boundary conditions is infinite at the boundaries, while reflecting boundary conditions only have the trivial stationary point, given sufficiently fine discretization. The numerical results were applied to an SI model with fractional diffusion, highlighting the dependence of the system on the value of the fractional derivative. Results indicate that as the order of the derivative increases, the diffusivity also increases, accompanied by a slight increase in the average number of infected individuals. These models have the potential to provide valuable insights into the dynamics of disease spread and aid in the development of effective control strategies. [ FROM AUTHOR] Copyright of Mathematical Methods in the Applied Sciences is the property of John Wiley & Sons, Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

What the Eye Cannot See: A Case of Persistent Altered Mental Status in a Patient With Cholestatic Liver Disease?

Introduction: Altered mental status (AMS) is a common symptom in patients with liver disease with a wide list of differential diagnoses. Knowledge of etiologies of AMS unique to patients with hepatic dysfunction is vital in order to help recognize, diagnose, and treat the underlying cause in a timely manner. Case Description/Methods: A 46-year-old man with a history of recent COVID infection was transferred to our hospital for further evaluation of acute liver injury and AMS. On arrival, his labs were notable for AST of 408 U/L, ALT of 620 U/L, ALP of 5942 U/L, TB of 11.0 mg/dL, and an INR of 1.1. His work-up included an MRCP that showed segmental biliary ductal dilation with associated restricted diffusion and peribiliary enhancement concerning for sclerosing cholangitis. ERCP revealed a 3cm biliary cast that was removed and noted diffuse rarefaction of ducts throughout the entire biliary tree. A liver biopsy revealed centrizonal cholestasis with portal-based bile ductular reaction and mild bile duct injury. Despite adequate treatment of suspected infection and hepatic encephalopathy, his AMS persisted. His basic metabolic panel (BMP) was notable for Na of 143 mEq/L. A send-out lipid panel that was obtained to work-up his dyslipidemia revealed a total cholesterol of 1018 mg/dL, triglycerides of 420mg/dL, and the presence of lipoprotein X. A venous blood gas (VBG) was obtained showing a Na of 157 mEq/L and serum osmolality was 322 mmol/kg, confirming true hypernatremia. He was slowly treated with hypotonic solutions with significant improvement in his mentation. On follow-up one year later, he has persistent cholestasis and is currently being considered for liver transplant. Discussion(s): The final diagnosis was COVID-related ischemic cholangitis and disappearing bile ducts with persistent cholangiopathy, presenting with severe cholestasis, accumulation of lipoprotein X, and pseudonormonatremia. When faced with severe cholestatic liver disease, clinicians should keep in mind the possibility of accumulation of lipoprotein X and its association with hyperviscosity and spurious electrolyte abnormalities. Clinicians should rely on obtaining blood gas analyses for accurate electrolyte measurement in such cholestatic patients as blood gas analyses utilize direct ion-sensitive electrodes (ISE) to measure electrolytes, whereas routine basic metabolic panels utilize indirect ISE that are liable to spurious results in the presence of hyperlipoproteinemia/lipoprotein X.

Brain imaging and neuropsychological assessment of individuals recovered from a mild to moderate SARS-CoV-2 infection.

As severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) infections have been shown to affect the central nervous system, the investigation of associated alterations of brain structure and neuropsychological sequelae is crucial to help address future health care needs. Therefore, we performed a comprehensive neuroimaging and neuropsychological assessment of 223 nonvaccinated individuals recovered from a mild to moderate SARS-CoV-2 infection (100 female/123 male, age [years], mean ± SD, 55.54 ± 7.07; median 9.7 mo after infection) in comparison with 223 matched controls (93 female/130 male, 55.74 ± 6.60) within the framework of the Hamburg City Health Study. Primary study outcomes were advanced diffusion MRI measures of white matter microstructure, cortical thickness, white matter hyperintensity load, and neuropsychological test scores. Among all 11 MRI markers tested, significant differences were found in global measures of mean diffusivity (MD) and extracellular free water which were elevated in the white matter of post-SARS-CoV-2 individuals compared to matched controls (free water: 0.148 ± 0.018 vs. 0.142 ± 0.017, P < 0.001; MD [10-3 mm2/s]: 0.747 ± 0.021 vs. 0.740 ± 0.020, P < 0.001). Group classification accuracy based on diffusion imaging markers was up to 80%. Neuropsychological test scores did not significantly differ between groups. Collectively, our findings suggest that subtle changes in white matter extracellular water content last beyond the acute infection with SARS-CoV-2. However, in our sample, a mild to moderate SARS-CoV-2 infection was not associated with neuropsychological deficits, significant changes in cortical structure, or vascular lesions several months after recovery. External validation of our findings and longitudinal follow-up investigations are needed.

Heterogeneous Diffusion of Government Microblogs and Public Agenda Networks during Public Policy Communication in China.

During public policy information diffusion, policy interpretation on government microblogs and public attention interact, but there are certain differences. We construct a research framework for the heterogeneous diffusion of public policy information on government microblogs. An empirical study is conducted based on the Network Agenda Setting (NAS) model. First, a combination of topic mining and content analysis is used to identify the issues discussed by government microblogs and citizens. Then, we use the importance of nodes in Degree Structure (DS) and Flow Structure (FS) entropy to measure their attention to different issues. Finally, the Quadratic Assignment Procedure (QAP) correlation and regression analysis explore the degree of heterogeneity and causal relationship between government microblog agenda networks (GMANs) and public agenda networks (PANs). We find that GMANs influence PANs and the degree of heterogeneity between them is relatively low at the beginning of policy implementation. However, as government microblogs reveal positive effects of policy implementation, they fail to influence PANs effectively, and there is a greater degree of heterogeneity between them. Moreover, PANs do not significantly affect GMANs. The dynamic leading relationship between GMANs and PANs in public policy diffusion is clarified, helping to shape the image of digital government in public opinion.