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The current period of disruptive social change is inextricably bound up with new means and modes of communication, information, and media streams. The Communication, Information Technologies & Media Sociology section of the American Sociological Association (CITAMS) locates these factors at the center of our collective interests, investigating them through a plethora of methods, theories, and empirical cases. Each year, CITAMS runs a special issue in ICS showcasing select works presented at the previous year's American Sociological Association conference and the affiliated Media Sociology preconference. Papers in the 2022 CITAMS Special Issue reflect a social context defined by a prolonged global pandemic and wrought by democratic uncertainty. Across these social circumstances, technology and media loom large. Simultaneously, everyday life continues and classic CITAMS scholarship sustains relevance for the ways people interact, construct identity, consume, and mobilize. All of this and more are contained in the pages of this year's Special Issue, from which readers can get a sense of what CITAMS has to offer and consider how their own work may fit within the broad CITAMS umbrella. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
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Background: COVID-19 has been associated with cerebral microbleeds (CMB). Previously, an association of ApoE4 with COVID-19 severity and CMBs in autopsy was found. In this study, we investigated if carrying the Apoe4 allele relates to the number of CMBs in magnetic resonance imaging (MRI) in patients recovered from COVID-19. Material(s) and Method(s): Adult patients recovered from COVID-19 and a control group without a history of COVID-19 was recruited. Exclusion criteria were major neurologic disease, developmental disability or pregnancy. The participants underwent brain MRI 6 months after infection, and a blinded neuroradiologist analyzed the findings. ApoE was genotyped using a microarray. Statistical analysis was performed using the statistical software R. A negative binomial model was chosen based on the distribution of CMBs. Result(s): Of the 216 subjects that underwent MRI, 168 consented to genetic testing, additionally 2 patients were excluded due to extensive CMBs and 1 due to diffuse axonal injury. We included 113 COVID-19 patients (49 ICU-treated, 29 ward-treated and 35 home-isolated) and 52 controls. The most prevalent comorbidities were hypertension, asthma and diabetes. CMBs was found in 47 subjects, with the number of CMBs ranging from 0 to 26. The ApoeE4 allele was carried by 37%, equally distributed among the groups. After adjustment, age (aRR = 1.06, p = 0.007) and COVID-19 (aRR = 2.59, p = 0.038) were independently associated with CMBs. The ApoE4 allele (aRR = 2.16, p = 0.07, CI = 0.94-5.10) was not significant. Conclusion(s): Age and previous COVID-19, but not possession of the ApoeE4 allele, were independently associated with the number of CMBs.
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Coronavirus disease 2019 (COVID-19) is a fatal pandemic viral disease caused by the severe acute respiratory syndrome corona virus type-2 (SARS-CoV-2). The aim of this study is to observe the associations of IL-6, SARS-COV-2 viral load (RNAemia), IL- 6 gene polymorphism and lymphocytes and monocytes in peripheral blood with disease severity in COVID-19 patients. This study was carried out from March 2021 to January 2022. RT-PCR positive 84 COVID-19 patients and 28 healthy subjects were enrolled. Blood was collected to detect SARS-COV-2 viral RNA (RNAemia) by rRT-PCR, serum IL-6 level by chemiluminescence method, SNPs of IL-6 by SSP-PCR, immunophenotyping of lymphocytes and monocyte by flow cytometry. Serum IL-6 level (pg/ml) was considerably high among critical patients (102.02 +/- 149.7) compared to severe (67.20 +/- 129.5) and moderate patients (47.04 +/- 106.5) and healthy controls (3.5 +/- 1.8). Serum SARS-CoV-2 nucleic acid positive cases detected mostly in critical patients (39.28%) and was correlated with extremely high IL-6 level and high mortality (R =.912, P < 0.001). Correlation between IL-6 and monocyte was statistically significant with disease severity (severe group, p < 0.001, and 0.867*** and critical group p < 0.001 and 0.887***). In healthy controls, moderate, severe and critically ill COVID-19 patients, IL-6 174G/C (rs 1800795) GG genotype was 82.14%, 89.20%, 67.85% and 53.57% respectively. CC and GC genotype had strong association with severity of COVID-19 when compared with GG genotype. Significant statistical difference found in genotypes between critical and moderate groups (p < 0.001, OR-10.316, CI-3.22-23.86), where CC genotype was associated with COVID-19 severity and mortality. The absolute count of T cell, B cell, NK cell, CD4+ T cells and CD8+ T cells were significantly decreased in critical group compared to healthy, moderate and severe group (P < 0.001). Exhaustion marker CD94/NKG2A was increased on NK cells and CD8+ cytotoxic T cell among critical and severe group. Absolute count of monocyte was significantly increased in critical group (P < 0.001). Serum IL-6, IL-6 174 G/C gene and SARS-CoV-2 RNAaemia can be used in clinical practice for risk assessment;T cell subsets and monocyte as biomarkers for monitoring COVID-19 severity. Monoclonal antibody targeting IL-6 receptor and NKG2A for therapeutics may prevent disease progression and decrease morbidity and mortality.Copyright © 2023 Elsevier Inc.
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Background/Objectives: Corticosteroids are widely used for the treatment of coronavirus disease (COVID)-19 caused by SARS-CoV- 2 as they attenuate the immune response with their antiinflammatory properties. Genetic polymorphisms of glucocorticoid receptor, metabolizing enzymes or transporters may affect treatment response to dexamethasone. The aim of this study was to evaluate the association of polymorphisms in glucocorticoid pathway with disease severity and duration of dexamethasone treatment in COVID-19 patients. Method(s): Our study included 107 hospitalized COVID-19 patients treated with dexamethasone. We isolated DNA from peripheral blood and genotyped all samples for polymorphisms in NR3C1 (rs6198, rs33388), CYP3A4 (rs35599367), CYP3A5 (rs776746), GSTP1 (rs1695, rs1138272), GSTM1/GSTT1 deletions and ABCB1 (1045642, rs1128503, rs2032582 Fisher's and Mann- Whitney tests were used in statistical analysis. Result(s): The median (min-max) age of the included patients was 62 (26-85) years, 69.2 % were male and 30.8 % female and they had moderate (1.9 %), severe (83 %) or critical (15.1 %) disease. NR3C1 rs6198 polymorphism was associated with more severe disease in additive genetic model (P = 0.022). NR3C1 rs6198, ABCB1 rs1045642 and ABCB1 rs1128503 polymorphisms were associated with a shorter duration of dexamethasone treatment in additive (P = 0.048, P = 0.047 and P = 0.024, respectively) and dominant genetic models (P = 0.015, P = 0.048 and P = 0.020, respectively), while carriers of the polymorphic CYP3A4 rs35599367 allele required longer treatment with dexamethasone (P = 0.033). Other polymorphisms were not associated with disease severity or dexamethasone treatment duration. Conclusion(s): Genetic variability of glucocorticoid pathway genes was associated with the duration of dexamethasone treatment of COVID-19 patients.
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Case history: We present the case of a 31-year-old Hispanic male with history of recurrent bronchiectasis, invasive aspergillosis, and severe persistent asthma, who is now status post lung transplant for end-stage lung disease. He initially presented at 7 years of age with diarrhea, failure to thrive, and nearly absent immunoglobulin levels (IgG < 33 mg/dL, IgA < 7 mg/dL, IgM = 11 mg/dL, IgE = 4 IU/dL) necessitating IVIG treatment. Small intestinal biopsy showed villous atrophy consistent with autoimmune enteropathy. Sweat chloride was reported as indeterminate (44 me/dL). Initial WBC, platelet, and T- and NK-cell counts were within normal range, and B-cell count and percentage were borderline low. Most recently, he was found to have increased immature B-cell count (CD21low), decreased memory B-cells, and poor pneumococcal vaccine antibody response. Patient has been hospitalized numerous times with increasingly severe bronchiectasis, pneumonitis, and COVID-19 infections twice despite vaccination, leading to respiratory failure and lung transplantation. Family history is negative for immune deficiency and lung diseases. Discussion(s): Of these 3 VUSs (see the table), the one in IRF2BP2 has the most pathogenic potential due to its autosomal dominant inheritance, its location in a conserved domain (Ring), and previous case reports of pathogenic variants at the same or adjacent alleles 1-3. Baxter et al reported a de novo truncating mutation in IRF2BP2 at codon 536 (c.1606CinsTTT), which is similar to our patient's mutation. This patient was noted to have an IPEX-like presentation, with chronic diarrhea, hypogammaglobulinemia, and recurrent infections. Variant Functional Prediction Score for our variant predicts a potentially high damage effect. There are 2 other case reports of heterozygous mutations in loci adjacent to this allele;one (c.1652G>A)2 with a similar clinical phenotype to our patient and the other (C.625-665 del)3 with primarily inflammatory features and few infections. Impact: This case highlights a variant in IRF2BP2 associated with severe hypogammaglobulinemia, recurrent pulmonary infections, and autoimmune enteropathy. [Table presented]Copyright © 2023 Elsevier Inc.
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Introduction: Macrophage activation syndrome (MAS) is a severe hyper inflammatory condition caused by the over-activation and proliferation of T cells, NK cells and macrophages. It is often associated with complications of rheumatic/immune diseases. We present a case of a 15-year-old female who experiences recurrent episodes of MAS without any known definitive underlying etiology. Case Presentation: A 15-year-old previously healthy female developed fatigue, fevers, myalgia, chest pain, splenomegaly and lymphadenopathy 10 days after receiving her first Pfizer COVID-19 vaccine. Her symptoms recurred 10 days after receiving the second dose. Her myocarditis, MIS-C, and infectious work up was negative except for positive EBV IgG. Laboratory studies revealed anemia, hypertriglyceridemia, hypofibrinogenemia, and hyperferritinemia. She initially responded to decadron;however, her symptoms recurred with steroid taper. Bone marrow biopsy revealed hemophagocytosis. Whole exome sequencing (WES) revealed a heterozygous variant of uncertain significance in UNC13D c.962C>A (p.Thr321Asn). She had multiple re-admissions with significantly elevated inflammatory markers, including extremely high IL2-R, IL-18 and CXCL9. Each episode was complicated by an acute viral infection. She responds to high dose steroids, anti-IL-1, and JAK inhibitors. Nonetheless, it has been difficult to wean decadron without triggering a flare. She continues to require increasing doses of baricitinib. Discussion(s): MAS may be seen as a complication of rheumatic diseases, as well as inborn errors of immunity. However, none of these conditions have been diagnosed in this patient despite extensive testing, including WES. The degree of her immune dysregulation has been very severe making her disease process unpredictable and extremely difficult to control. She has frequent flares precipitated by viral infections or attempts at adjusting her immunomodulators. Weaning her medications has been challenging as she continues to require increasing doses of baricitinib and corticosteroids. The UNC13D gene is associated with autosomal recessive familial hemophagocytic lymphohistiocytosis type 3 (FHL3). Our patient is heterozygous for an UNC13D variant of uncertain significance. Additional genetic inquiries with whole genome sequencing to help elucidate the underlying etiology of her severe condition is being conducted. We hypothesize she developed MAS due to a combination of genetic predisposition, prior EBV infection, and immune stress associated with the COVID-19 vaccine. [Formula presented] [Formula presented] [Formula presented]Copyright © 2023 Elsevier Inc.
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Coronavirus disease 2019 (COVID - 19)is an acute viral disease caused by severe acute respiratory syndrome coronavirus 2 (SARS - CoV - 2)infection and is mainly transmitted through the respiratory tract. It not only invades the respiratory system of human body, but also damages various organs and systems. Evidence has shown that there may be a causal association between SARS - CoV - 2 and spontaneous splenic rupture. This article recognizes the possibility of SARS - CoV - 2 - associated spontaneous splenic rupture and discusses its pathogenesis and related diagnosis and treatment regimens, so as to avoid missed diagnosis and misdiagnosis in clinical practice.Copyright © 2022 by the Author(s).
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Background/Objectives: The disease course upon SARS-CoV-2 infection is highly variable and comprises a range from asymptomatic infection to severe (and even lethal) COVID-19. Genetic factors substantially contribute to this variability, as evidenced by epidemiological studies and recent results from genome-wide association studies (GWAS) as well as sequencing-based approaches. The host genetics group of the German COVID-19 OMICs Initiative (DeCOI) has been founded with the aim to identify additional genetic variants that influence COVID-19 severity through whole genome sequencing (WGS) analyses. Method(s): Until January 2022, WGS has been performed on approximately 1200 individuals affected by COVID-19. Result(s): The most recent data freeze comprised 952 individuals. In this dataset, no carrier of a deleterious protein-altering variant has been detected in TLR7, which is the only conclusive risk gene for severe COVID-19. Applying a gene-based association test of rare variants to the subcohort of European individuals (n = 752, mean age: 56 years, females: 44%), including 199 severely affected individuals, we did not observe any significant association after correction for multiple testing. Exome-wide association analysis of common variants in this subcohort replicated the GWAS-locus on chromosome 3. Conclusion(s): With this ongoing work, we are contributing to international efforts to elucidate the host genetics of COVID-19, also by sharing our summary statistics for meta-analyses. Currently, we are sequencing additional severely affected individuals and we are refining analytical strategies, which will also include the joint analysis of common and rare variants at genomewide scale.
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COVID-19 is a raging pandemic that has created havoc with its impact ranging from loss of millions of human lives to social and economic disruptions of the entire world. Therefore, error-free prediction, quick diagnosis, disease identification, isolation and treatment of a COVID patient have become extremely important. Nowadays, mining knowledge and providing scientific decision making for diagnosis of diseases from clinical datasets has found wide-ranging applications in healthcare sector. In this direction, among different data mining tools, association rule mining has already emerged out as a popular technique to extract invaluable information and develop important knowledge-base to help in intelligent diagnosis of distinct diseases quickly and automatically. In this paper, based on 5434 records of COVID cases collected from a popular data science community and using Rapid Miner Studio software, an attempt is put forward to develop a predictive model based on frequent pattern growth algorithm of association rule mining to determine the likelihood of COVID-19 in a patient. It identifies breathing problem, fever, dry cough, sore throat, abroad travel and attended large gathering as the main indicators of COVID-19. Employing the same clinical dataset, a linear regression model is also proposed having a moderately high coefficient of determination of 0.739 in accurately predicting the occurrence of COVID-19. A decision support system can also be developed using the association rules to ease out and automate early detection of other diseases. © 2023 by the authors.
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The traditional de novo drug discovery is time consuming, costly and in some instances the drugs will fail to treat the disease which result in a huge loss to the organization. Drug repurposing is an alternative drug discovery process to overcome the limitations of the De novo drug discovery process. Ithelps for the identification of drugs to the rare diseases as well as in the pandemic situationwithin short span of time in a cost-effective way. The underlying principle of drug repurposing is that most of the drugs identified on a primary purpose have shown to treat other diseases also. One such example is Tocilizumab is primarily used for rheumatoid arthritis and it is repurposed to treat cancer and COVID-19. At present, nearly30% of the FDA approved drugs to treat various diseases are repurposed drugs. The drug repurposing is either drug-centric or disease centric and can be studied by using both experimental and in silico studies. The in silico repurpose drug discovery process is more efficient as it screens thousands of compounds from the diverse libraries within few days by various computational methods like Virtual screening, Docking, MD simulations,Machine Learning, Artificial Intelligence, Genome Wide Association Studies (GWAS), etc. with certain limitations.These limitationscan be addressed by effective integration of advanced technologies to identify a novel multi-purpose drug.Copyright © 2023, Association of Biotechnology and Pharmacy. All rights reserved.
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Diabetes mellitus (DM) is a metabolic disease characterised mainly by signs and symptoms derived from increased serum glucose or hyperglycemia. The coronavirus disease 2019 (COVID-19) pandemic affected the entire world with reports of severe prognosis in diabetic patients infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and high hospital admissions in the intensive care unit (ICU) compared to non-diabetic patients. The objective of the bibliographic review was to evaluate and describe some of the biochemical mechanisms that lead to severe prognosis in patients with DM infected by the SARS-CoV-2 virus through a systematic search for information in different databases. The results showed that the high ICU admission with a severe prognosis of diabetic patients infected by the virus was due to excessive inflammation that causes acute respiratory distress syndrome, cytokine storm, severe pneu-monia, impaired immunity, and hyperglycemia. The virus enters the cell mainly through the endocytic and non-endosomal pathway;the central cellular receptors involved in the mechanisms are insulin receptors (IR), glucose transporter type 2 (GLUT-2), dipeptidyl peptidase-4 (DPP4), glucose transporter type 4 (GLUT-4), glucose converting enzyme angiotensin 2 (ACE2), and the serine transmembrane protease co-receptor 2 (TMPRSS2) essential for viral propagation. The increased susceptibility to devel-oping COVID-19 in diabetic patients is due to the overexpression of ACE2, and serious complications are increased at the microvascular and macrovascular levels, such as nephropathies, neuropathies, and cardiovascular diseases.
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One form of Data Mining application to analyze Market Basket Analysis. Market Basket Analysis helps identify buying patterns formed from concurrent transactions. One of the problems with Market Basket Analysis is that customer needs vary according to season and time of day, especially during this covid-19 season. For this purpose, by using the Artificial Neural Network (ANN) Approach that is connected to Market Basket Analysis, it can analyze and compare purchasing patterns and can identify rules that were formed before and after covid-19;several rule changes were found due to changes in people's behavior patterns. [ FROM AUTHOR] Copyright of Journal of Social Science (2720-9938) is the property of Ridwan Institute 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.)
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Improving the process of strategic management in hospitals preparation and equipping the intensive care units (ICUs) and the availability of medical devices plays an important role for knowing consumer behaviour and need. This cross-sectional study was performed in the ICU of Farhikhtegan Hospital, Tehran, Iran for a period of six months. During these months, ten medical devices have been used 5,497 times. These devices include: ventilator, oxygen cylinder, infusion pump, electrocardiography machine, vital signs monitor, oxygen flowmeter, wavy mattress, ultrasound sonography machine, ultrasound echocardiography machine, and dialysis machine. The Apriori algorithm showed that four devices: ventilator, oxygen cylinder, vital signs monitoring device, oxygen flowmeter are the most used ones by patients. These devices are positively correlated with each other and their confidence is over 80% and their support is 73%. For validating the results, we have used equivalence class clustering and bottom-up lattice traversal (ECLAT) algorithm in our dataset.
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Background/Objectives: SARS-CoV-2 infection clinical manifestations hugely vary among patients, ranging from no symptoms, to life-threatening conditions. This variability is also due to host genetics: COVID-19 Host Genetics Initiative identified six loci associated with COVID-19 severity in a previous case-control genome-wide association study. A different approach to investigate the genetics of COVID-19 severity is looking for variants associated with mortality, e.g. by analyzing the association between genotypes and time-to-event data. Method(s): Here we perform a case-only genome-wide survival analysis, of 1,777 COVID-19 patients from the GEN-COVID cohort, 60 days after infection/hospitalization. Case-only studies has the advantage of eliminating selection biases and confounding related to control subjects. Patients were genotyped using Illumina Infinium Global Screening Arrays. PLINK software was used for data quality check and principal component analysis. GeneAbel R package was used for survival analysis and age, sex and the first four principal components were used as covariates in the Cox proportional hazard model. Result(s): We found four variants associated with COVID-19 patient survival at a nominal P < 1.0 x 10-6. Their minor alleles were associated with a higher mortality risk (i.e. hazard ratios (HR)>1). In detail, we observed: HR=1.03 for rs28416079 on chromosome 19 (P=1.34 x 10-7), HR=1.15 for rs72815354 on chromosome 10 (P=1.66 x 10-7), HR=2.12 for rs2785631 on chromosome 1 (P=5.14 x 10-7), and HR=2.27 for rs2785631 on chromosome 5 (P=6.65 x 10-7). Conclusion(s): The present results suggest that germline variants are COVID-19 prognostic factors. Replication in the remaining HGI COVID-19 patient cohort (EGAS00001005304) is ongoing at the time of submission.
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Introduction: The people worldwide have been affected by severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) infection since its appearance in December, 2019. Kawasaki disease-like hyperinflammatory shock associated with SARS-CoV-2 infection in previously healthy children has been reported in the literature, which is now referred to as a multisystem inflammatory syndrome in children (MIS-C). Some aspects of MIS-C are similar to those of Kawasaki disease, toxic shock syndrome, secondary hemophagocytic syndrome, and macrophage activation syndrome. Case Presentation: This study reported an 11-year-old boy with MIS-C presented with periorbital and peripheral edema, abdominal pain, elevated liver enzymes, severe right pleural effusion, moderate ascites, and severe failure of right and left ventricles. Conclusion(s): Due to the increasing number of reported cases of critically ill patients afflicted with MIS-C and its life-threatening complications, it was recommended that further studies should be carried out in order to provide screening tests for myocardial dysfunction. Adopting a multidisciplinary approach was found inevitable.Copyright © 2023, Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/) which permits copy and redistribute the material just in noncommercial usages, provided the original work is properly cited.
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Background/Objectives: One of the most remarkable features of SARS-CoV-2 infection is that a large proportion of individuals are asymptomatic while others experience progressive, even lifethreatening acute respiratory distress syndrome, and some suffer from prolonged symptoms (long COVID). The contribution of host genetics to susceptibility and severity of infectious disease is well-documented, and include rare monogenic inborn errors of immunity as well as common genetic variation. Studies on genetic risk factors for long COVID have not yet been published. Method(s): We compared long COVID (1534) to COVID-19 patients (96,692) and population controls (800,353) using both questionnaire and EHR- based studies. First meta-analysis of 11 GWAS studies from 8 countries did not show genome-wide significant associations. Result(s): Testing 24 variants earlier associated to COVID-19 susceptibility or severity by COVID-19 Host Genetics Initiative showed genetic variation in rs505922, an intronic variant in ABO blood group gene, to be associated with long COVID compared to population controls (OR = 1.16, 95% CI: 1.07-1.27, p = 0.033). (Within-COVID analysis gave similar OR, but was not significant after conservative Bonferroni correction (OR = 1.17, 95% CI: 1.06-1.30, p = 092)). Conclusion(s): The first data freeze of the Long COVID Host Genetics Initiative suggests that the O blood group is associated with a 14% reduced risk for long COVID. The following data freezes with growing sample sizes will possibly elucidate long COVID pathophysiology and pave the way for possible treatments for long lasting COVID symptoms.
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Mining frequent itemsets is an attractive research activity in data mining whose main aim is to provide useful relationships among data. Consequently, several open-source development platforms are continuously developed to facilitate the users' exploitation of new data mining tasks. Among these platforms, the R language is one of the most popular tools. In this paper, we propose an extension of arules package by adding the option of mining frequent generator itemsets. We discuss in detail how generators can be used for a classification task through an application example in relation with COVID-19.
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Background: SAMD9L is a tumor suppressor involved in regulating the proliferation and maturation of cells, particularly those derived from the bone marrow, and appears to play an important role in cerebellar function. It can be activated in hematopoietic stem cells by type I and type II interferons. It has been hypothesized to act as a critical antiviral gatekeeper regulating interferon dependent demand driven hematopoiesis. Gain of function mutations can present with an immunodeficiency due to transient severe cytopenias during viral infection. Case presentation: We report a 3-year-old boy born full term with a history of severe thrombocytopenia requiring transfusions, developmental delay, ataxia, seizure disorder, and recurrent severe respiratory viral infections. His infectious history was significant for respiratory syncytial virus with shock requiring extracorporeal membrane oxygenation complicated by cerebral infarction and a group A streptococcus empyema, osteomyelitis requiring a left below the knee amputation, and infections with rhinovirus, COVID-19, and parainfluenza requiring hospitalizations for respiratory support. Initial immunologic evaluation was done during his hospitalization for parainfluenza. His full T cell subsets was significant for lymphopenia across all cell lines with CD3 934/microL, CD4 653/microL, CD8 227/microL, CD19 76/microL, and CD1656 61/microL. His mitogen stimulation assay to phytohemagglutinin and pokeweed was normal. Immunoglobulin panel showed a mildly decreased IgM of 25 mg/dL, but normal IgA and IgG. Vaccine titers demonstrated protective titers to 12/22 pneumococcus serotypes, varicella, diphtheria, mumps, rubella, and rubeola. Repeat full T cell subsets 6 weeks later revealed marked improvement in lymphocyte counts with CD3 3083/microL, CD4 2101/microL, CD8 839/microL, CD19 225/microL, and CD1656/microL. A primary immunodeficiency genetic panel was ordered and positive for a heterozygous SAMD9L c.1549T>C (p.Trp517Arg) mutation classified as a variant of unknown significance. Discussion(s): This patient's history of severe viral infections, ataxia, thrombocytopenia, and severe transient lymphopenia during infection is suggestive of a SAM9DL gain of function mutation. Protein modeling done by the laboratory suggests this missense mutation would affect protein structure. The mutation found has been observed in individuals with thrombocytopenia. This case highlights the importance of immunophenotyping both during acute illness and once recovered.Copyright © 2023 Elsevier Inc.
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The ambition of this development study is to explore the opportunity to put the knowledge gained during the COVID-19 pandemic into practice in a blended, post-COVID, learning environment. The focus is to explore how a combination of digital and face-to-face activities may allow for fostering social presence among undergraduate students. The Social Presence model and the five elements of Affective Association, Community of Cohesion, Instructor Investment, Interaction Intensity, and Knowledge and Experience, encompass the theoretical framework of the study. The contextual setting is the first course of The Marketing Programme at Linnaeus University in Sweden, a bachelor program with a 50% Swedish intake and 50% international intake. Given the diverse background of the students in this course, challenges are typically encountered in relation to community building. Empirical data was collected during the fall of 2022 among the enrolled students using an online questionnaire. While the results from this study should be seen as preliminary, they offer an inspiring glimpse of how to nurture social presence in a blended learning environment. Copyright © 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)