Establishment of differential diagnostic model for COVID-19 and influenza A based on laboratory indicators and its clinical significance. TT -.

Objective:To explore the differences in laboratory indicators test results of coronavirus disease 2019 (COVID-19) and influenza A and to establish a differential diagnosis model for the two diseases, and to clarify the clinical significance of the model for distinguishing the two diseases. Methods :A total of 56 common COVID-19 patients and 54 influenza A patients were enrolled , and 24 common COVID-19 patients and 30 influenza A patients were used for model validation. The average values of the laboratory indicators of the patients 5 d after admission were calculated,and the elastic network model and the stepwise Logistic regression model were used to screen the indicators for identifying COVID-19 and influenza A. Elastic network models were used for the first round of selection,in which the optimal cutoff of lambda was chosen by performing 10-fold cross validations. With different random seeds,the elastic net models were fit for 200 times to select the high-frequency indexes ( frequency>90% ). A Logistic regression model with AIC as the selection criterions was used in the second round of screening uses;a nomogram was used to represent the final model;an independent data were used as an external validation set,and the area under the curve (AUC) of the validation set were calculate to evaluate the predictive the performance of the model. Results:After the first round of screening, 16 laboratory indicators were selected as the high-frequency indicators. After the second round of screening,albumin/ globulin (A/G),total bilirubin (TBIL) and erythrocyte volume (HCT) were identified as the final indicators. The model had good predictive performance , and the AUC of the verification set was 0. 844 (95% CI:0. 747-0. 941). Conclusion:A differential diagnosis model for COVID-19 and influenza A based on laboratory indicators is successfully established,and it will help clinical and timely diagnosis of both diseases.Copyright © 2022 Jilin University Press. All rights reserved.

Evaluation of student-pharmacists' experiences in COVID-19 vaccination clinics

Objective: To examine the impact that participation in 2019 coronavirus disease (COVID19) vaccination clinics had on students' self-assessed ability to vaccinate and secondarily, to examine the impact these experiences had on student perspectives of pharmacist engagement in public health. Methods: Student pharmacists who volunteered in COVID-19 vaccination clinics were invited to complete an anonymous, electronic survey consisting of items pertaining to their self-assessed ability to vaccinate and attitudes towards pharmacist engagement in public health in a retrospective pre/post-experience. Results: Students indicated that the experiences were valuable, participation increased their comfort level with vaccination, and they were better prepared to engage in vaccination following engagement. Additionally, student attitudes toward pharmacist engagement in public health improved after engagement. Conclusion: Participation in COVID-19 vaccination clinics had a positive effect on students' self-efficacy toward vaccination and their attitudes toward pharmacist engagement in public health. Similar opportunities should be promoted to student-pharmacists to facilitate their professional development.

Does workplace ostracism negatively affect family life during a pandemic?

PurposeThe study aims to investigate the impact of workplace ostracism (WO) and fear of the COVID-19 pandemic on the family life of restaurant employees. This research is based on the conservation of resources (COR) theory and work-family interface model to understand the theoretical underpinnings of mistreatment in the food sector during the COVID-19 pandemic.Design/methodology/approachThe study utilized a survey with a structured questionnaire to collect time-lagged data from 238 restaurant employees in the central region of Punjab province in Pakistan. The collected data were analyzed using the SPSS tool with modern-day techniques like bootstrapping, process macro and SmartPLS.FindingsThe study reveals that perceived stress levels of the employees increase due to ostracism, leading to work-family conflict. Furthermore, the study found that employees who fear COVID-19 are less stressed by ostracism.Originality/valueThe study's significant contribution lies in demonstrating that the impact of ostracism in the workplace is quite different from what was expected. The results have shown that ostracism can reduce the perceived stress levels of employees, leading to a decrease in work-family conflict, especially in the presence of fear of COVID-19.

VALIDITY AND RELIABILITY OF MEASUREMENT OF PERIPHERAL OXYGEN SATURATION DURING THE 6-MINUTE WALK TEST IN PATIENTS WITH SYSTEMIC SCLEROSIS

BackgroundThe 6-Minute Walk Test (6MWT) is a standardised method routinely used to screen for and monitor interstitiel lunge disease and/or pulmonary arterial hypertension in patients with systemic sclerosis (SSc). Studies shows that esaturations during the 6MWT are associated with severity of pulmonary manifestations in patients with SSc [1]. Digital sensors are commonly used to measure peripheral oxygen saturation (SpO2) during the 6MWT. However, digital-based sensors may have important limitations in patients with SSc due to disease-related microangiopathy, Raynaud's phenomenon, sclerodactyly and motion artifacts during the 6MWT [2]. Sensors located at more central body positions may therefore be more accurate as these as less prone to Raynaud attacks.ObjectivesTo determine the validity and re-test reliability of peripheral oxygen saturation measured at the finger, forehead, and ear during the 6MWT in patients with SSc.Methods82 patients with SSc had an arterial line placed while performing the 6MWT. Peripheral oxygen saturation was simultaneously measured by finger, forehead, and earlobe sensors and compared to the arterial oxygen saturation (SaO2) measured before and after the 6MWT. 40 patients repeated the 6MWT one week later. We used Bland-Altman plots to display the agreement between SpO2 and SaO2, and between the minimal SpO2 (minSpO2) one week apart. The intraclass correlation coefficient (ICC, 95% confidence interval 95% CI]) for repeated measurement of minSpO2 was calculated.ResultsThe mean difference (SpO2 - SaO2, ± standard deviation [SD]) after the 6MWT was –3.3% (±4.82), 0.15% (±1.55), and 1.36% (±1.93) for the finger, forehead, and earlobe, respectively (Table 1).The finger minSpO2 also demonstrated the poorest re-test reliability: The mean difference in minSpO2 (visit2-visit1, ±SD) was 1.28% (±5.3), 0.74% (±4.36) and –1.10% (±2.87),). The ICC (95% CI) showed good agreement using the ear and forehead probe (ICCear = 0.89 [0.80;0.94];ICCforehead = 0.88 [0.60;0.87]), while a modest reliability was found using the finger probe (ICCfinger = 0.65 [0.43;0.80]).ConclusionPeripheral oxygen saturation should be measured using either the earlobe or forehead during the 6MWT in patients with SSc.References[1]Villalba, W. O. et al. Six-minute walk test for the evaluation of pulmonary disease severity in scleroderma patients. Chest 131, 217–222 (2007).[2]Pathania, Y. S. Alternatives for erroneous finger probe pulse oximetry in systemic sclerosis patients during COVID-19 pandemic. Rheumatol. Int. 41, 2243–2244 (2021).Table 1.Validity and re-test reliability of peripheral oxygen during the 6MWT (n= 82)Finger probeForehead probeEar probeMean difference SpO2 - SaO2  Mean difference pre-test (+/-SD)–0.68% (±1.88)0.13% (±1.26)1.54% (±0.69)  Mean difference post--test (+/-SD)–3.30% (±4.82)0.15% (±1.55)1.36% (±1.93)Mean difference of the minSpO2 (visit2-visit1)  Mean difference (±SD)1.28% (±5.3)0.74% (±4.36)1.10% (±2.87)Abbreviations: SpO2, Peripheral oxygen saturation;SaO2, Arterial oxygen saturation;SD, Standard deviation.Acknowledgements:NIL.Disclosure of InterestsAmanda Lynggaard Riis: None declared, Esben Naeser Paid instructor for: Boehringer Ingelheim Denmark, Katja Thorup Aaen: None declared, Henrik Hovgaard: None declared, Peter Juhl-Olsen: None declared, Elisabeth Bendstrup Speakers bureau: Hoffman-la-Roche.Boehringer Ingelheim.Glaxo Smith Kleine.Daichii Sankyo, Klaus Soendergaard Speakers bureau: Boehringer Ingelheim, Consultant of: Boehringer Ingelheim, Grant/research support from: Boehringer Ingelheim.

Psychometric Performance of the Fear of COVID-19 Scale (FCV-19S) and Its Validation in Czechia

The COVID-19 pandemic has brought significant changes to people's lives, causing high levels of anxiety, distress, and fear. In response, the "Fear of COVID-19” scale (FCV-19S) was developed in 2020 to measure the severity of fears related to COVID-19. This study assessed the psychometric properties of the Czech version of the FCV-19S, which was administered to a representative sample of 1372 participants, and confirmatory factor analysis (CFA) was conducted. The sample reflects the structure of a theoretical population aged 15–74 years and is composed of 50% males and 50% females. Moreover, univariate statistics were calculated, internal consistency was tested, and uni-dimensionality based on principal component analysis was performed. In addition, univariate statistical analyses were performed, internal consistency was tested, and univariate consistency was also assessed using principal component analysis. CFA indicated that the scale demonstrated very good standard indices;FCV-19S showed a high level of internal consistency, and it adequately differentiated the levels of fear among diverse subpopulations. The findings suggest that the Czech version of the FCV-19S is a valid and reliable instrument that has robust psychometric properties and can, therefore, be recommended for use in research. The availability of the Czech version of the FCV-19S will contribute to assessments of the impact of the COVID-19 pandemic on the Czech population, providing valuable information in guiding interventions aimed at reducing the negative psychological impacts of the pandemic.

Depressive symptoms and mental representations in a sample of pregnant Italian women during COVID-19: comparison of primipara and multipara

During the COVID-19 outbreak, the risk of depression has increased for pregnant women and especially for first-time mothers-to-be. Pre-COVID-19 literature showed that depression is negatively linked to mental representations during pregnancy. This pilot study explored the difference in depressive symptoms and maternal representations style in primiparous and multiparous pregnant women during the outbreak of COVID-19 (2020-2021). 25 women (14 primiparous, 11 multiparous) were recruited in their last trimester of pregnancy. Participants responded to the Edinburgh Postnatal Depression Scale (EPDS) and Interview for Maternal Representations during Pregnancy (Intervista sulle Rappresentazioni Materne in Gravidanza-IRMAG). Results showed that primiparous women presented higher depressive symptoms than multiparous ones. Moreover, primiparous women reported lower richness of perception (p = 0.008), openness to change (p = 0.035) and dominance of fantasies (p = 0.000) in maternal representation and, globally, more restricted representations (71.4%) than multiparous ones (18.2%) (p = 0.020). Mental representations were related to the level of depression, with integrated representations being associated with lower depression than restricted and ambivalent ones (p = 0.001). A preventive intervention to support primiparous pregnant women during future pandemics would be necessary in particular to avoid negative repercussions also in the post-partum experience.

The Verification & Validation of the Mars 2020 Perseverance Rover Surface Mission Operations System

Leading up to its landing on Mars on February 18, 2021, the Mars 2020 Perseverance rover Surface Mission Operations System (MOS) underwent a verification and validation (V&V) campaign consisting of a series of Super Thread Tests and Operational Readiness Tests. This V&V campaign emphasized incremental testing, mission scenario and capability coverage, and the Test-As-You-Fly approach wherever possible. Although the elements that comprise the Surface System underwent their own internal V&V campaigns, the system-level tests were vital in uncovering findings observable only through the integrated and flight-like nature of these Surface Mission Operations System V & V tests. The COVID-19 pandemic posed additional challenges, including limited facility access, constrained in-person activities, changes to operations paradigms, and evolving safety protocols in the midst of the testing campaign and preparation for surface operations. This paper describes the Verification and Validation campaign of the Mars 2020 Perseverance Rover Surface Mission Operations System that led to the readiness for rover operations on Mars. © 2023 IEEE.

Factors Related to Psychological Distress Among Nursing Students Volunteering in Covid-19 Frontline Prevention In Vietnam

The aim of the study to examine the level of psychological distress among nursing students volunteering in Covid-19 frontline prevention in Vietnam and related factors. Nursing students volunteering in frontline prevention presented emotional effects, including positive and negative effects on their psychological well-being. A cross-sectional study design was used and four hundred seventy-one students who volunteered for frontline prevention were randomly selected in the study using inclusion criteria. Data were collected from October to December 2021. A demographic questionnaire, the General Self-Efficacy Scale, the 6-item Kessler Psychological Distress Scale, the Brief Coping Orientation to Problems Experienced Inventory Questionnaire, and the Quality of life EQ-5D-5L were used to measure the variables. The data analysis was conducted by using descriptive statistics and linear regression. The research found that students presented a high risk of psychological distress. There was a significant correlation between problem-and emotional-coping strategies, quality of life, and psychological distress. Moreover, family support and psychological distress among nursing students had a strong relationship. Lecturers and high education institutions responsible for nursing students should pay more attention to developing psychological interventions in enhancing coping strategies and quality of life and various supports to reduce distress among nursing students fighting the epidemic.

Fitting Percentage of Body Fat to Simple Body Measurements: College Women

Percentage of body fat, age, weight, height, and 14 circumference measurements (e.g., waist) are given for 184 women aged 18–25. Body fat, one measure of health, was accurately determined by an underwater weighing technique which requires special equipment and training of the individuals conducting the process. Modeling body fat percentage using multiple regression provides a convenient method of estimating body fat percentage using measures collected using only a measuring tape and a scale. This dataset can be used to show students the utility of multiple regression and to provide practice in model building.

Medical Image Diagnosis Using Deep Learning Classifiers for COVID-19

COVID-19 and other diseases must be precisely and swiftly classified to minimize disease spread and avoid overburdening the healthcare system. The main purpose of this study is to develop deep-learning classifiers for normal, viral pneumonia, and COVID-19 disorders using CXR pictures. Deep learning image classification algorithms are used to recognize and categorise image data to detect the presence of illnesses. The raw image must be pre-processed since deep neural networks perform the most important aspect of medical image identification, which includes translating the raw image into an intelligible format. The dataset includes three classifications, including normal and viral pneumonia and COVID-19. To aid in quick diagnosis and the proposed models leverage the performance validation of several models, which are summarised in the form of a recall, Fl-score, precision, accuracy, and AUC, to distinguish COVID-19 from other types of pneumonia. When all the deep learning classifiers and performance parameters were analyzed, the ResNetl0lV2 achieved the highest accuracy of COVID-19 classifications is 97.S2%, ResNetl0lV2 had the greatest accuracy of the normal categorization is 92.04% and the Densenet201 had the greatest accuracy of the pneumonia classification is 99.92%. The suggested deep learning system is an excellent choice for clinical use to aid in the COVID-19, normal, and pneumonia processes for diagnosing infections using CXR scans. Furthermore, the suggested approaches provided a realistic technique to implement in real-world practice, assisting medical professionals in diagnosing illnesses from CXR images. © 2023 IEEE.

QSAR and DFT Studies of Some Tacrine-Hydroxamate Derivatives as Inhibitors of Cholinesterase (AChEs) in the Treatment of Alzheimer's Disease

Introduction: This work was devoted to an in silico investigation conducted on twenty-eight Tacrine-hydroxamate derivatives as a potential treatment for Alzheimer's disease using DFT and QSAR modeling techniques. Method(s): The data set was randomly partitioned into a training set (22 compounds) and a test set (6 compounds). Then, fourteen models were built and were used to compute the predicted pIC50 of compounds belonging to the test set. Result(s): Al built models were individualy validated using both internal and external validation methods, including the Y-Randomization test and Golbraikh and Tropsha's model acceptance criteria. Then, one model was selected for its higher R2, R2test, and Q2cv values (R2 = 0.768, R2adj = 0.713, MSE = 0.304, R2test=0.973, Q2cv = 0.615). From these outcomes, the activity of the studied compounds toward the main protease of Cholinesterase (AChEs) seems to be influenced by 4 descriptors, i.e., the total dipole moment of the molecule (mu), number of rotatable bonds (RB), molecular topology radius (MTR) and molecular topology polar surface area (MTPSA). The effect of these descriptors on the activity was studied, in particular, the increase in the total dipole moment and the topological radius of the molecule and the reduction of the rotatable bond and topology polar surface area increase the activity. Conclusion(s): Some newly designed compounds with higher AChEs inhibitory activity have been designed based on the best-proposed QSAR model. In addition, ADMET pharmacokinetic properties were carried out for the proposed compounds, the toxicity results indicate that 7 molecules are nontoxic.Copyright © 2023 Bentham Science Publishers.

Success of digital marketing model for software development industry: validation of survey based results with case study analysis

PurposeThe paper aims to clarify the validity of the digital marketing model for software IT professionals. It proposes a model of buying behavior practices followed in digital era and outlining all six critical factors that were considered for developing this model. So the main objective of the study is to validate the success of digital marketing model through a survey-based results and case study analysis and synthesize the results for the success of digital marketing model for software development industry.Design/methodology/approachThe paper opted for an exploratory study using the structured questionnaire. The data were collected using online platform. The present study covers the analysis of a survey of 406 IT professionals from software development industry to understand their buying behavior through digital marketing. Regression technique has been used to find the important predictors of the digital marketing model with its impact on the demographic variables.FindingsThe paper provides empirical insights about digital marketing model whose validity has been checked by synthesizing the results of both overall and case study. The results show that predictors elucidate Durbin-Watson in the acceptable range and are suitable for the model.Research limitations/implicationsData were collected during Covid period. So it was quite a challenging task and moreover sample size could not be increased due to this problem.Practical implicationThe paper includes implications for the development of digital marketing model for software IT professionals. Finally, this study will contribute to the further research for many prominent researchers who express their doubts about the state and future of digital marketing studies, characterized by contradictory and confusing empirical findings. A larger quantitative study on IT companies' digital marketing from different regions is recommended as a future line of research in order to encourage the unique globalized level model development.Social implicationsMany organizations use digital marketing successfully since with the great amount of awareness generated about the digitalization among the customers has propelled for its development.Originality/valueThis paper fulfills an identified need to study how IT professional's digital buying marketing practices need to be studied.

The role of inference in AI: Start S.M.A.L.L. with mindful modeling

This chapter explores trustworthiness in AI and penetrates the black-box opacity through explainable, fair, and ethical AI solutions. AI remains a spirited topic within academic, government, and industrial literature. Much has occurred since the last AI winter in the early 1990's;yet, numerous sources indicate the initial successes solving problems like computer vision, speech recognition, and natural sciences may wane — plunging AI into another winter. Many factors contributed to advances in AI: more data science courses in universities producing data-science capable graduates, high venture capital funding levels encouraging startups, and a decade of broadening awareness among corporate executives about AI promises, real or perceived. Nonetheless, could sources like Gartner be right? Are we approaching another AI winter? As the world learned during the COVID-19 pandemic, when we find ourselves in a crisis, focusing on the fundamentals can have a powerful effect to easing the troubles. As AI makes history, it relies on progress from other domains such as data availability, computing power, and algorithmic advances. Balance among elements maintains a healthy system. AI is no different. Too much or too little of any elemental capability can slow down overall progress. This chapter integrates fundamental ideas from psychology (heuristics and bias), mindfulness in modeling (conceptual models in group settings), and inference (both classical and contemporary). Practitioners may find the techniques proposed in this chapter useful next steps in AI evolution aimed at understanding human behavior. The techniques we discuss can protect against negative impacts resulting from a future AI winter through proper preparation: appreciating the fundamentals, understanding AI assumptions and limitations, and approaching AI assurance in a mindful manner as it evolves. This chapter will address the fundamentals in a unifying example focused on healthcare, with opportunities for trustworthy AI that is impartial, fair, and unbiased. © 2023 Elsevier Inc. All rights reserved.

Unsupervised Clustering and Binary Classification Analysis for Predicting COVID Syndrome (LONG COVID) in US Adults

Objectives: This study investigated the risk factors of developing COVID Syndrome and identified potential disease profiles that may exist among those who have contracted COVID-19. Method(s): Data on 13,953 adults who had experienced COVID-19 at any time were analyzed from the 2022 US National Health and Wellness Survey. XGBoost binary classification with 10-fold cross-validation was used to predict long COVID among those who reported experiencing COVID-19 and to extract feature importance. Synthetic minority oversampling technique (SMOTE) was used to address class imbalance in the outcome variable. Variable selection was conducted based on SHAP values. Fifty variables including demographic characteristics, COVID-19 symptoms, comorbidities, and health characteristics were used in the final model. Parameters were tuned using AUC. Among the 2,665 respondents who were diagnosed with long COVID, k-medoids clustering with t-SNE dimensionality reduction was implemented to determine whether distinct symptom profiles exist. Average silhouette score was used to determine the optimal number of clusters. Result(s): The XGBoost binary classification for predicting long COVID among those with COVID-19 had an AUC of 0.9145, accuracy of 0.9072, sensitivity of 0.9630, specificity of 0.8328, and Brier score of 0.0928. The most important features in predicting long COVID were age, smoking habits, COVID-19 vaccination status, certain COVID-19 symptoms experienced, and certain comorbidities. Among those diagnosed with long COVID, the clustering analysis found nine unique clusters of symptoms. The cluster that experienced the most severe symptoms was older, female, lower income, lower vaccination rate, and had more comorbidities like asthma, chronic bronchitis, and allergies. Conclusion(s): In a broadly representative US adult population, XGBoost model identified a selection of risk factors for developing long COVID. K-medoids clustering identified clusters of patients that were at risk for developing severe symptoms.Copyright © 2023

Research into Alcohol-Dependent Persons in Treatment during the Covid-19 Pandemic. Part Two- the Role of the Pandemic and Its Consequences

Introduction: The aim of the study was to de-termine the influence of experiences, both personal , those occurring during therapy, of the COVID-19 pandemic on mental perfor-mance of alcohol dependent people receiving treatment.Material and methods: The 2021 study includ-ed 454 people (351 men and 103 women) completing therapy in various treatment centres in Poland. The tools comprised the Scale of Pan-demic-Related Difficulty, the Patient Health Questionnaire (PHQ-9), the Generalized Anx-iety Disorder (GAD-7), the Penn Alcohol Crav-ing Scale (PACS), the Suicidal Behavior Ques-tionnaire-Revised (SBQ-R), the International Trauma Questionnaire (ITQ), the Life Satisfac-tion Scale (SWLS), the Working Alliance Inven-tory-Short Revised (WAI-SR).Results: Among the participants, the women ex-perienced many more associated difficulties , anxiety than the men in the pandemic. During treatment, 13% of respondents have relapsed, with this being more likely among those reporting re-stricted access to therapy. Difficulties at home and in close relationships were strongly associated with symptoms of depression and anxiety. Patients with COVID-19 symptoms were characterised by a high-er degree of psychopathological severity compared to those who did not. No differences were found be-tween those who received the entire therapy "face to face", those who participated remotely and those who received a combination of the two models.Discussion: The experience of a pandemic by those in therapy did not appear to be strong-ly influenced by its course. The greatest neg-ative effects concerned domestic difficulties and problems with close relationships. How-ever, women, those who displayed COVID-19 symptoms and those who lost their jobs during the pandemic period demonstrated worse men-tal performance.Conclusions: Remaining in therapy may have played a protective role in patients with alcohol dependence during the pandemic.

Hematopoietic Stem/Progenitor Cells and Engineering: HEMATOPOIETIC STEM/PROGENITOR CELLS (HPC-A) CRYOPRESERVATION PROCESS VALIDATION USING CRYOSTOR CS10 FREEZE MEDIA

Background & Aim: During the COVID-19 pandemic, we performed HPC-A cryopreservation process validation using the CryoStor CS10 freeze media to replace the current 10% DMSO cryoprotectant (Control), which encountered severe backorder. Methods, Results & Conclusion(s): This process validation included phase I, phase II, and follow-up studies. Ten HPC-A collection cell product samples were cryopreserved in the phase I study using CS10 and Control (1:1) post-plasma depletion. Post-thaw viability tests using the 7-AAD method were performed on the cryopreserved samples for parallel comparison. In phase II, each of three patient HPC-A cell products was split evenly into CS10 and Control cryopreservation. The CS10 cryopreserved HPC-A cell products only were used for infusion. The recipients' engraftment outcomes of white blood cells (WBC), granulocytes (ANC), and platelets (Plts) were monitored. Post-thaw viability test was performed on the quality control samples from both groups. In the follow-up study, engraftment outcomes of WBC, ANC, and Plts were evaluated from ten recipients who received the CS10 cryopreserved HPC-A. In the phase I study, the post-thaw viability of the CS10 group was significantly higher than the Control group (p=0.002). All post-thaw viability results were above 60%, the current lab release criteria. In the phase II study, all cryopreserved cell products met cell product release criteria (> 60%). All engraftment results were within our center-established ranges except for the Pt b's platelet engraftment. Three recipients had not had any cell product infusion-related adverse events post infusion. Both CD34 and CD45 post-thaw viability results in the CS10 group were remarkably higher than the Control group, except for the patient c's CD34 viability. In the follow-up study, the total infused cell product volume ranged from 60 ml to 118 ml, and the WBC concentration in the cryopreserved cell products ranged from 134 to 440 (x10

Enhancer deregulation inTET2-mutant clonal hematopoiesis is associated with increased COVID-19 severity and mortality

Background: COVID-19 causes significant morbidity and mortality, albeit with considerable heterogeneity among affected individuals. It remains unclear which host factors determine disease severity and survival. Given the propensity of clonal hematopoiesis (CH) to promote inflammation in healthy individuals, we investigated its effect on COVID-19 outcomes. Method(s): We performed a multi-omics interrogation of the genome, epigenome, transcriptome, and proteome of peripheral blood mononuclear cells from COVID-19 patients (n=227). We obtained clinical data, laboratory studies, and survival outcomes. We determined CH status and TET2-related DNA methylation. We performed single-cell proteogenomics to understand clonal composition in relation to cell phenotype. We interrogated single-cell gene expression in isolation and in conjunction with DNA accessibility. We integrated these multi-omics data to understand the effect of CH on clonal composition, gene expression, methylation of cis-regulatory elements, and lineage commitment in COVID-19 patients. We performed shRNA knockdowns to validate the effect of one candidate transcription factor in myeloid cell lines. Result(s): The presence of CH was strongly associated with COVID-19 severity and all-cause mortality, independent of age (HR 3.48, 95% CI 1.45-8.36, p=0.005). Differential methylation of promoters and enhancers was prevalent in TET2-mutant, but not DNMT3A-mutant CH. TET2- mutant CH was associated with enhanced classical/intermediate monocytosis and single-cell proteogenomics confirmed an enrichment of TET2 mutations in these cell types. We identified celltype specific gene expression changes associated with TET2 mutations in 102,072 single cells (n=34). Single-cell RNA-seq confirmed the skewing of hematopoiesis towards classical and intermediate monocytes and demonstrated the downregulation of EGR1 (a transcription factor important for monocyte differentiation) along with up-regulation of the lncRNA MALAT1 in monocytes. Combined scRNA-/scATAC-seq in 43,160 single cells (n=18) confirmed the skewing of hematopoiesis and up-regulation of MALAT1 in monocytes along with decreased accessibility of EGR1 motifs in known cis-regulatory elements. Using myeloid cell lines for functional validation, shRNA knockdowns of EGR1 confirmed the up-regulation of MALAT1 (in comparison to wildtype controls). Conclusion(s): CH is an independent prognostic factor in COVID-19 and skews hematopoiesis towards monocytosis. TET2-mutant CH is characterized by differential methylation and accessibility of enhancers binding myeloid transcriptions factors including EGR1. The ensuing loss of EGR1 expression in monocytes causes MALAT1 overexpression, a factor known to promote monocyte differentiation and inflammation. These data provide a mechanistic insight to the adverse prognostic impact of CH in COVID-19.

KAP Study Regarding COVID-19 Amongst Pregnant Women, in Central India

Objectives: To assess the knowledge, attitude and practices of preventive measures against COVID-19 infection among pregnant women. It is our understanding that assessing healthcare needs and healthcare education form the pillars for better healthcare thereby this study was conducted. Methodology: An observational cross-sectional study was conducted in which 150 antenatal women were included. Face-to-face interview was conducted by using a self-developed internally validated semi-structured questionnaire based on 3 major domains, Knowledge (10), Attitude (10) and Practice (4), with close ended questions. Each response-correct was allotted score 1 & incorrect allotted score of 0. The responses were described as frequencies and percentages. Scoring system-Poor score<60%, Fair score 60-75%, Good score > 75% of total score in each domain. Result(s): 103(68.7%) had good knowledge and 121(80.7%) had poor attitude, regarding COVID affecting their pregnancy, antenatal visits and unborn baby. 113(75.3%) were practicing preventive habits. Conclusion(s): Our study showed the anxiety and fear related to Covid-19 affected mental health of women and their adherence to antenatal care which needs to be addressed in providing antenatal care services.Copyright © 2023, Dr Yashwant Research Labs Pvt Ltd. All rights reserved.