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Large language models have abilities in creating high-volume human-like texts and can be used to generate persuasive misinformation. However, the risks remain under-explored. To address the gap, this work first examined characteristics of AI-generated misinformation (AI-misinfo) compared with human creations, and then evaluated the applicability of existing solutions. We compiled human-created COVID-19 misinformation and ed it into narrative prompts for a language model to output AI-misinfo. We found significant linguistic differences within human-AI pairs, and patterns of AI-misinfo in enhancing details, communicating uncertainties, drawing conclusions, and simulating personal tones. While existing models remained capable of classifying AI-misinfo, a significant performance drop compared to human-misinfo was observed. Results suggested that existing information assessment guidelines had questionable applicability, as AI-misinfo tended to meet criteria in evidence credibility, source transparency, and limitation acknowledgment. We discuss implications for practitioners, researchers, and journalists, as AI can create new challenges to the societal problem of misinformation. © 2023 Owner/Author.
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Introduction: COVID-19 is an infectious disease caused by the SARS-CoV-2 virus that commonly involved the respiratory system. However, the virus can affect any organ in the body including the liver. Hepatic involvement in COVID-19 could be related to the direct cytopathic effect of the virus, an uncontrolled immune reaction, sepsis, or drug-induced liver injury. Background: The current study aims to evaluate the relevance of liver enzyme derangement in COVID-19. Methods: The sample size of 165 patients, tested positive for covid 19 and underwent liver enzyme testing. These patients were categorized into mild, severe, and critical diseases based on clinical evaluation, radiological findings, and biochemical parameters. Results: Of 165 patients selected 103 (62.4%) have mild disease, 40(24.2%) have severe and 12(7.2%) suffered from the critical disease. 48(29.1%) patients show deranged liver function. 83.3% of critical patients and 45% of severe patients show deranged liver function.9.09%of patients died due to severe COVID-19 infections showing moderately to severe liver function derangement. Conclusions: This study concludes that the severity of COVID-19 disease may increase due to chronic liver disease, particularly fatty liver. Atypical ALT and AST levels during hospitalization were indicative of liver injury and correlated with the severity of patients.
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Background and purpose: Multisystem Inflammatory Syndrome in Children (MIS-C) occurs after having COVID-19. The severity and outcomes of COVID-19 with gastrointestinal symptoms are higher. The aim of this study was to investigate gastrointestinal manifestations in MIS-C patients in selected referral hospitals in Iran to obtain comprehensive information about the treatment and prevention of MIS-C. Materials and methods: In this cross-sectional study, all MIS-C patients <21 years in Dec 2019 to Oct 2021 were included. The patients were identified by the Centers for Disease Control and Prevention (CDC) checklist and data were analyzed applying t-test and Chi-square in STATA11. Results: There were 225 patients with a median age of 55 months (26-96 months), including 59.56% boys and all had fever on admission. At least one gastrointestinal symptom was seen in 200 patients and the most common symptoms were vomiting (60.9%) and abdominal pain (45.77%). Almost 60% of the patients had positive RT-PCR results. Among the patients with and without gastrointestinal symptoms 85.5% and 48% were admitted to intensive care unit (ICU), respectively. There were significant differences between the two groups in respiratory symptoms, ALT, AST, NT-pro BNP, ESR, and PLT (P < 0.05). All patients without gastrointestinal symptoms were discharged but nine patients in the group with gastrointestinal symptoms deceased. Conclusion: According to the current study, gastrointestinal symptoms are common in MIS-C patients and are associated with higher rates of death and intensive care unit admission. Therefore, in providing services to COVID-19 patients, all typical and atypical signs and symptoms should be considered to prevent unnecessary interventions.
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Objective: Coronavirus disease-2019 (COVID-19) is a newly emerging infectious disease that has become a global pandemic. This study aimed to identify the risk factors at presentation to predict intensive care unit (ICU) admissions. Materials & Methods: This retrospective observational study recruited 188 confirmed laboratory COVID-19 patients who were hospitalized in Jidhafs Maternity Hospital (JMH) from 1st June to 5th July 2020. Univariate and multivariate analyses were used to Explore risk factors associated with the increased risk of ICU admission. Results: The study revealed that older age (>60 years old) (16[38.1%], P=0.044), male gender (30 [40.0%], P=0.000) were significantly associated with the increased risk of ICU admissions. The most prevalent symptoms in admission were myalgia (13[40.6%], P=0.035), fever (39[34.2%], P=0.002) and cough (37[31.4%], P=0.032). In addition, raised serum level of alanine amino-transferase (ALAT) (34.7% vs. 20.7%, P=0.033), D-dimers (30.7% vs 12.2%, P=0.012), lactate dehydrogenase (LDH) (31.6% vs 0.0%, P=0.025) and ferritin (37.7% vs 16.7%, P=0.011) found to be important predictor of ICU admission. Conclusion: The finding indicates that older age, male gender, with increased alanine transferase (ALT), increased lactate dehydrogenase (LDH), high D-dimer and high ferritin was associated with an increased risk of ICU admissions. Identification of such factors will help to detect people who are more likely to develop severe COVID-19 disease and will help physicians to determine if patients need regular health care or ICU admission.
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Feline Infectious Peritonitis (FIP) is highly mortality disease in cats. The reliable and fast diagnosis is crucial to the best prognosis. The aim of this study to evaluate the hemogram profile in cats infected with effusive FIP. Twenty cats had been diagnosed effusive FIP at Animal Clinic Department of Internal Medicine, Faculty Veterinary Medicine, Universitas Gadjah Mada were used in the study. The diagnosis were based on clinical examination, ultrasound, x-ray, rivalta test, and rapid test. The hemogram profile were analyzed include routine hematology and serum biochemistry. Hemogram profile in effusive FIP showed the decreased hematocrit, hyperproteinemia, and leukocytosis with an average 22.9+or-7.4%;9.0+or-2.2 g/dL;22425+or-4116 cells/mm3 respectively. Erythrocyte, hemoglobin and fibrinogen levels were still in the normal range. The results of differential leukocytes revealed that 90% cats had neutrophilia and 75% lymphopenia with an average 20066+or-3337 cells/mm3 and 1861+or-1818 cells/mm3 respectively. The blood chemistry profile showed 60% of cats experienced increase in SGPT and SGOT with an average 138.4+or-72.3 IU/L and 101+or-60.5 IU/L respectively. Hyperglobulinemia was found in 90% samples with an average 6.7+or-0.8 g/dL. All cats have a low albumin:globulin ratio with an average 0.3+or-0.1. The hemogram profile of effusive FIP were: leukocytosis, neutrophilia, lymphopenia, hyperglobulinemia, and decreased albumin-globulin ratio..
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Background: COVID-19 (Corona Virus Disease-2019) pandemic has a high mortality rate especially in Medan, Indonesia. Serum albumin and liver function tests are believed to be predictive biomarkers for prognosis in patients with infectious diseases, including COVID-19. This study aimed to investigate the association between the mortality events and severely ill COVID-19 patients' serum albumin and liver enzymes. Method: This is a cross-sectional study using secondary data from the medical records of H. Adam Malik Hospital patients with COVID-19 who were confirmed by RT-PCR from August to December 2020. All patients were analyzed for age, sex, hypoalbuminemia, increased liver enzymes and outcome using Chi-square tests (P <0.05). Results: The average age of severe COVID-19 patients at H. Adam Malik Hospital ranged from 41 to 60 years, with more women prevalence than men. Most of the patients had hypoalbuminemia (84.2%), an increase in AST (59.4)% and ALT (45.5%). There was no significant association between hypoalbuminemia and the disease outcome (P =0.12). There was a significant association between elevated liver enzymes and mortality in severely ill COVID-19 patients (P <0.001). Conclusion: We found that hypoalbuminemia is common in patients with severe COVID-19. However, we found that albumin levels had no association with the patients' mortality rate. Liver enzymes levels appear to be a predictive biomarker for outcomes in COVID-19 patients of H. Adam Malik Hospital. We found that higher ALT and AST levels were associated with significantly higher mortality.
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Although intensive care medicine (ICM) is a relatively young discipline, it has rapidly developed into a full-fledged and highly specialized specialty covering several fields of medicine. The COVID-19 pandemic led to a surge in intensive care unit demand and also bring unprecedented development opportunities for this area. Multiple new technologies such as artificial intelligence (AI) and machine learning (ML) were gradually being applied in this field. In this study, through an online survey, we have summarized the potential uses of ChatGPT/GPT-4 in ICM range from knowledge augmentation, device management, clinical decision-making support, early warning systems, and establishment of intensive care unit (ICU) database.
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Since early 2020, the global coronavirus pandemic has strained economic activities and traditional lifestyles. For such emergencies, our paper proposes a social sentiment estimation model that changes in response to infection conditions and state government orders. By designing mediation keywords that do not directly evoke coronavirus, it is possible to observe sentiment waveforms that vary as confirmed cases increase or decrease and as behavioral restrictions are ordered or lifted over a long period. The model demonstrates guaranteed performance with transformer-based neural network models and has been validated in New York City, Los Angeles, and Chicago, given that coronavirus infections explode in overcrowded cities. The time-series of the extracted social sentiment reflected the infection conditions of each city during the 2-year period from pre-pandemic to the new normal and shows a concurrency of waveforms common to the three cities. The methods of this paper could be applied not only to analysis of the COVID-19 pandemic but also to analyses of a wide range of emergencies and they could be a policy support tool that complements traditional surveys in the future.
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BACKGROUND: Corona virus disease-19 (COVID -19) infection is an acute infectious disease caused by a newly discovered beta corona virus, severe acute respiratory syndrome corona virus 2 (SARS-CoV-2). While the primary target organ is the lungs, involvement of many other organs is often evident in patients with COVID-19. There is emerging evidence to suggest association of SARS-CoV-2 infection with development of many liver abnormalities. The purpose of this study was to evaluate the prevalence of abnormal liver parameters in COVID-19 patients and their variation in moderate and severe cases. METHODS: This is a retrospective study. All patients with COVID -19, between the ages 20-75 years, encountered between April and May 2021, were included for the study and compared with age-matched controls. Severity of infection was defined based on the presence of symptoms, oxygen saturation, need for respiratory and intensive care support. Liver parameters such as serum total bilirubin (TBIL), serum aminotransferases, alanine aminotransaminase (ALT) and aspartate aminotransaminase (AST) were analysed. Inflammatory markers such as C-reactive protein (CRP) and D-dimer were also included for assay. RESULTS: A total of 52 patients were encountered during the study period. Of these, 29% (15/52) required intensive care. Abnormal liver parameters were observed in 14 (27%) patients, and were significantly elevated compared to healthy controls. Liver dysfunction was markedly profound in severe infection than those with moderate disease. Higher levels of CRP and D-dimer were noted in severe patients of COVID-19. CONCLUSIONS: Mild liver abnormalities in the form of elevated ALT and AST are seen in COVID-19 patients suggesting mild or no liver injury. These abnormal parameters do not generally lead to significant liver function impairment/failure and no specific treatment is required.
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Introduction: Due to the high risk of Covid-19 disease, especially delta variant in pregnant women, as well as the novelty of this epidemic in the world and the lack of similar studies in Iran and the region, it seems necessary to perform a study on mortality rate and laboratory and clinical findings of the disease in pregnant women. Therefore, this study was performed aimed to determine the laboratory and clinical findings in hospitalized pregnant women with Covid -19 based on disease outcome during the outbreak of Delta variant (summer and autumn 2021) in Ardabil province. Methods: In this cross-sectional and descriptive study, all pregnant women with Covid-19 admitted to the hospitals of Ardabil province in summer and autumn 2021 at the time of delta outbreak were included. Finally, 187 infected pregnant mothers were studied. Demographic information, clinical signs and laboratory findings were studied in all mothers. Data were analyzed by SPSS (version 24) and Fisher Exact test and Pearson Correlation. P<0.05 was considered statistically significant. Results: Of the 187 infected pregnant women, 8 mothers died. Comorbidity was observed in 41 pregnant women. The most common clinical finding was shortness of breath (Dyspnea) and cough, and the most common laboratory finding was lymphopenia. Comparing the cured and dead mothers according to laboratory findings using Fisher's exact test showed that the difference between ALT (p <0.05), lactate dehydrogenase (p <0.001), AST (p <0.001), BS (P <0.05), creatinine (p <0.05) and total bilirubin (p <0.05) were statistically significant between the two groups. Conclusion: Infection to delta variant of Covid-19 disease resulted in 187 hospitalizations and 8 deaths of pregnant mothers in Ardabil province. Shortness of breath (Dyspnea) and cough were the most common clinical findings and lymphopenia was the most common laboratory finding.
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BACKGROUND: Since its reporting in December 2019, SARC-COV-2 (COVID -19) has infected more than 230 million people over the world by colonising the respiratory tract, however very little is known about its effect on liver and how the liver injury affects disease prognosis. This study was done to assess the hepatic profile in SARC-COV-2 infection along with inflammatory markers. METHODS: This is a single centred prospective observational study. 400 patients with real time polymerase chain reaction (PCR) confirmed COVID 19 infection admitted in KIMS, Hubballi were taken for study. Patients with decompensated liver disease were excluded from the study. Clinical examination and laboratory investigations including liver function test (LFT), renal function test (RFT), complete blood count (CBC), chest X-ray, D-dimer, ferritin, lactate dehydrogenase (LDH), C reactive protein (CRP) was done for all the patients. RESULTS: Out of the 400 covid-19 positive patients admitted, 286 (71.5%) had abnormal liver enzymes. Significantly raised liver enzymes were seen in males. Raised liver enzymes and inflammatory markers were associated with poor outcome of the disease. Significant reduced albumin was associated with poor outcome of the disease. Significantly raised aspartate transaminase (AST), alanine transaminase (ALT) levels were associated with increased severity of the disease. (P = 0.009 and 0.029 respectively). Significant positive relation was found between liver profile and inflammatory markers. CONCLUSIONS: Majority of patients admitted with SARS-CoV-2 had deranged liver profile. Higher proportion of abnormal liver enzymes were seen in males. Degree of liver injury increases with increasing severity of the disease. Even though abnormal liver enzymes were positively associated with elevated inflammatory markers and severity of the disease, more studies are needed to study implications of liver injury in prognosis of SARS-CoV-2 infection.
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Objective: To compare the clinical manifestations, liver function, and antibody levels between Omicron variant infection patients vaccinated and not vaccinated with COVID-19 vaccine. Methods: Totally 430 convalescent COVID-19 patients infected with Omicron variant in Tianjin were selected, including 150 patients vaccinated with Corona Vaccine(Sinovac group), 185 patients vaccinated with BBIBP-CorV(Beijing biological group), 41 patients vaccinated with Ad5-nCoV vaccine(CanSino group), 16 patients vaccinated with Anhui Zhifei, Changchun Bio, Lanzhou Bio, Shandong Bio, other adenovirus vector vaccines or mixed vaccination(other group), and 38 unvaccinated patients(unvaccinated group). The clinical manifestations, liver function indexes [alanine aminotransferase(ALT), aspartate aminotransferase(AST), total bilirubin(TB), albumin(ALB), total protein(TP), lactate dehydrogenase(LDH)], and antibody levels(IgG, IgM)were compared retrospectively. Results: There was no statistical difference in the sex composition ratio among groups(P > 0.05). The age of the Beijing biological group was significantly lower than that of other groups, and the proportion of time less than 3 months from the last vaccination to admission in the Beijing biological group and CanSino group was significantly higher than that in the Sinovac group and other groups(all P < 0.01). A total of 110 children aged less than 16 years were enrolled, including 7, 88, 0, 1 and 14 cases in the Sinovac group, Beijing biological group, CanSino group, other group, and unvaccinated group, respectively. There were 6 asymptomatic cases, 13 moderate cases, 91 mild cases and 0 severe case. There was no significant difference in the abnormal rate of ALT between Beijing biological group and unvaccinated group(P > 0.05), but the abnormal rates of ALT were higher in the Sinovac group and CanSino group than in the unvaccinated group and Beijing biological group(all P < 0.05). The abnormal rate of AST in the unvaccinated group was higher than that in other groups(P < 0.05). There were no significant differences in AST, TP or TB among the groups(all P > 0.05). The levels of ALT were higher in the Sinovac group and CanSino group than in Beijing biological Group and unvaccinated group, the level of ALB in the unvaccinated group was lower than that in the other groups, and the level of LDH in the Beijing biological group was higher than those in the Sinovac group and CanSino group(both P < 0.05). The IgG and IgM antibody levels of the unvaccinated group were significantly lower than those of the Sinovac group, Beijing biological group and CanSino group(all P < 0.05). Conclusions: Omicron variant infection patients vaccinated with BBIBP-CorV are younger and have a higher proportion of mild conditions, which can protect the liver function of patients to a certain extent. Patients vaccinated with different COVID-19 vaccines can produce higher levels of IgG and IgM antibodies than the unvaccinated patients.
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Background: Tocilizumab (TCZ) is a new therapeutic alternative for severe cases of COVID-19 pneumonia. Aim: To evaluate the cumulative incidence (CI) of suspected adverse drug reactions (ADR) from TCZ in adult patients with COVID-19. Material and methods: An active pharmacological surveillance protocol was carried out in patients older than 18 years old, who received at least one dose of TCZ between May and August 2020 at a clinical hospital. Non-infectious ADRs were categorized according to the Common Terminology Criteria for Adverse Events and the development of infection was classified as present or absent. Causality and preventability of ADRs were determined with the Naranjo Algorithm and the modified Schumock & Thornton criteria, respectively. Results: The CI of ADRs caused by TCZ was 69.6% (95% confidence intervals (CI): 63.5-76.6). A rise in alanine and aspartate aminotransferases and the development of infections were the most frequent adverse events. Seventy-four percent were considered mild in severity. Sixty two percent of suspected non-infectious ADRs were classified as probable and all the infectious events as Possible. Of the ADRs observed, 33% were preventable. Conclusions: The occurrence of ADRs after the use of TCZ is frequent, of mild severity, and in one third of the cases, preventable. We suggest monitoring blood count, liver function tests and ruling out infection prior to TCZ administration.
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Objective: This study determined the correlation between several laboratory variables, chest computed tomography severity score (CTSS), and coronavirus disease-2019 (COVID-19) Reporting and Data System (CO-RADS) in COVID-19 patients. Materials and Methods: Ninety-one patients with COVID-19 infection verified by polymerase chain reaction test, presented to the emergency department with COVID-19 symptoms, and had a thoracic computed tomography (CT) scan at the time of admission were included in this retrospective study. 25-hydroxyvitamin D [25(OH)D] levels, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), D-dimer, glucose, ferritin, creatinine, alanine aminotransferase, aspartate aminotransferase, phosphorous, and calcium levels recorded and CO-RADS and CTSS data. The correlation of laboratory parameters with radiological findings was analyzed. Results: A positive correlation was found between CTSS and age, ESR, CRP, D-dimer while a negative correlation was found between CTSS and lymphocyte count. Patients with high CTSS levels had higher ESR, CRP, D-dimer, ferritin values and lower lymphocyte count, and lower calcium levels. Patients with typical CO-RADS involvement had higher sedimentation, CRP, glucose, and ferritin levels and lower lymphocyte count. No significant correlation was determined between the 25(OH)D level, CO-RADS, and CTSS. Conclusion: The results of this study highlight that the reduced lymphocyte count, high D-dimer, sedimentation, ferritin, and CRP levels are predictors of severe lung involvement in COVID-19 patients. Hypocalcemia can also be considered a marker of severe lung involvement evaluated by CT in COVID-19 patients. the association between vitamin D deficiency and COVID-19 pneumonia should be investigated in future studies.
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Diabetes, hypertension, and cardiovascular disease all raise the risk of hospitalization and mortality in individuals infected with coronavirus disease 2019 (COVID-19). Higher levels of flogosis mediators such as TNF, C-reactive protein (CRP), IL-1, IL-6, leptin, and resistin, as well as increased levels of TNF, C-reactive protein (CRP), IL-1, IL-6, leptin, and resistin, define diabetes. The goal of this study is to evaluate the levels of D-dimer, total serum bilirubin (TSB), glutamic-oxaloacetic transaminase (GOT), glutamic pyruvic transaminase (GPT), and CRP in diabetic patients with COVID-19 infection to COVID-19 patients without diabetes. Blood samples were collected from individuals with diabetes who had COVID-19 and non-diabetic COVID patients as control. Moreover, D-dimer and CRP were evaluated by using Min Vidus and Latx, respectively, whereas AccEnT 200 system was used to measure the serum level of TSB, GPT, and GOT in the hematology lab. Also demonstrated that the average serum concentration of D-dimer, GOT and CRP was high in diabetic COVID-19-infected patients (980.66 ng/mL, 67.71 U/L, and 27.06 mg/L, respectively) compared with non-diabetic COVID-19-infected patients (791.17 ng/mL, 54.023 U/L and 20.11 mg/L, respectively) (p < 0.05), while the situation was inverse for the average concentration of TSB and GTP when their average concentrations were low in diabetic COVID-19-infected patients (12.89 Mmol/L and 59.79 U/L, respectively) (p > 0.05). Moreover, the cut-off values for serum D-dimer, TSB, GPT, GOT, and CRP of COVID-19-infected diabetic patients were ≥ 6500 ng/mL, ≥ 350 Mmol/L, ≥ 133 U/L mg/L, ≥ 150 U/L, and ≥ 15.22 mg/L, respectively, represented a perfect test for predicting COVID-19-infected diabetic patients with 100% sensitivity and specificity. In conclusion, serum D-dimer, TSB, GPT, GOT and CRP increased in diabetic COVID-19-infected patients compared to non-diabetic COVID-19 patients and the D-dimer concentration also increases. TSB and CRP were more pronounced among diabetic patients with corona, while liver enzyme concentrations were decreased.
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In Web discussions, which have become mainstream with COVID-19, the amount of information possessed and the level of understanding of the discussion differ among participants. As a result, some participants may not be able to speak up satisfactorily, and this can hinder consensus building in the discussion as a whole. Therefore, we develop an agent that automatically recommends information related to the discussion as information that facilitates participants to speak up. The agent first obtains necessary discussion data from on-going Web discussions. The information to be recommended is determined by real-time search. Query words for the search are generated using a pre-trained query-term-generation model. When selecting information to recommend from the information obtained in the search, a model that classifies the acquired information according to the discussion phase is used. The results of a discussion experiment in which an agent intervened in a Web-based discussion showed many results indicating the effectiveness of the agent, although there are some points that need to be improved. However, since the scale of the discussion experiment was small, it will be necessary to validate the agent in large-scale discussions in the future. © 2022 IEEE.
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For decades, the genetic modification of coronavirus genomes and the generation of recombinant coronaviruses have been hampered mostly due to the extraordinary large size of the coronaviral genome. The very first reverse genetic system for feline coronaviruses (FCoVs) was established in the early 2000s;the respective approach exclusively enabled the manipulation of the 3'-third of the viral genome. Later on, vaccinia virus-and bacterial artificial chromosome (BAC)-based systems have been developed. Both systems have the advantage that the entire FCoV genome is amenable for mutagenesis. The main focus of this chapter is the vaccinia virus-based reverse genetic system for FCoVs. Here we present protocols for (1) the generation of a full-length cDNA clone, (2) the manipulation of the FCoV genome, and (3) the rescue of recombinant FCoVs. Copyright © Springer Science+Business Media New York 2016.
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Coronavirus disease 2019 (COVID-19) is a kind of viral pneumonia which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The emergence of SARS-CoV-2 has been marked as the third introduction of a highly pathogenic coronavirus into the human population after the severe acute respiratory syndrome coronavirus (SARS-CoV) and the Middle East respiratory syndrome coronavirus (MERS-CoV) in the twenty-first century, Forcing scientists to continue Research to discover a vaccine for this disease in in request to control and boundary the range Of the disease. This study was designed to hit upon out whether here are side effects on vaccinated people who received covid-19 vaccine or not by measuring the body's vitality by some of biochemical tests.Subjects:75 individuals between women and men aged (17-68 years)were enrolled in this study .Several biochemical tests were performed on them before taking the vaccine,a week to10 days after the first dose, and a week to 10 days after the second dose of covid-19 vaccine. RESULT(S): All subjects in this Study received the Pfizer-Bio N Tech vaccine and no systemic side effects were Observed in subjects vaccinated during the study period. Conclusion(s): From the Results of the current study, there were no abnormal biochemical markers, increased, or changes in basic body functions after receiving the Pfizer vaccine. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.
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Since the International Health Regulations National Focal Point for the United Kingdom alerted the WHO of ten cases of acute severe hepatitis of unknown etiology in children on April 5, 2022, relevant cases have been reported worldwide. These patients had acute hepatitis (negative for hepatitis viruses A-E) and elevated aminotransferase (AST) or alanine aminase (ALT) exceeding 500 U/L. Furthermore, severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) and/or adenovirus type F41 have been detected in some cases. This unknown hepatitis has been hypothesized to be induced by a viral reservoir of novel coronavirus superantigen, which repeatedly stimulates the intestines and leads to a multisystem inflammatory syndrome in children (MIS-C), which causes immune abnormalities in the presence of human adenovirus. Although this hypothesis has not been confirmed by any in vivo experimental or clinical studies, it may provide ideas for possible intervention strategies.
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The evolution of digitization and technology has increased the amount of data shared online, inevitably leading to the spread of false information. The issue has skyrocketed as COVID-19 spread across the globe and carried with it a sea-full of fake news. Recent technological advances, such as automatic text generators, have exacerbated the problem by interpolating synthetic text into the fake news. Current fake news detection approaches do not take into account the validity of synthetic news (machine-generated news), thus classifying all machine-generated material as fake. In this paper, the first-ever synthetic news classification model using CT-BERT is implemented, and a framework is proposed that not only distinguishes between human-authored and machine-generated text, but also considers the veracity of text to detect fake news. Moreover, a novel COVID-19 based synthetically generated dataset has been introduced by fusing synthetic text generated by GPT-2 and Grover model. Further, whether the GPT-2 and Grover models are vulnerable to adversarial attacks or not has been investigated. An accuracy of 98.2% and 92.4% respectively in the fake news classification of human-authored and machine-generated text have been achieved. © 2022 IEEE.