CD169-mediated restrictive SARS-CoV-2 infection of macrophages induces pro-inflammatory responses.

Exacerbated and persistent innate immune response marked by pro-inflammatory cytokine expression is thought to be a major driver of chronic COVID-19 pathology. Although macrophages are not the primary target cells of SARS-CoV-2 infection in humans, viral RNA and antigens in activated monocytes and macrophages have been detected in post-mortem samples, and dysfunctional monocytes and macrophages have been hypothesized to contribute to a protracted hyper-inflammatory state in COVID-19 patients. In this study, we demonstrate that CD169, a myeloid cell specific I-type lectin, facilitated ACE2-independent SARS-CoV-2 fusion and entry in macrophages. CD169-mediated SARS-CoV-2 entry in macrophages resulted in expression of viral genomic and subgenomic RNAs with minimal viral protein expression and no infectious viral particle release, suggesting a post-entry restriction of the SARS-CoV-2 replication cycle. Intriguingly this post-entry replication block was alleviated by exogenous ACE2 expression in macrophages. Restricted expression of viral genomic and subgenomic RNA in CD169+ macrophages elicited a pro-inflammatory cytokine expression (TNFα, IL-6 and IL-1ß) in a RIG-I, MDA-5 and MAVS-dependent manner, which was suppressed by remdesivir treatment. These findings suggest that de novo expression of SARS-CoV-2 RNA in macrophages contributes to the pro-inflammatory cytokine signature and that blocking CD169-mediated ACE2 independent infection and subsequent activation of macrophages by viral RNA might alleviate COVID-19-associated hyperinflammatory response.

Role of cardiovascular magnetic resonance imaging in COVID-19 recovered patients: A short-term follow-up study.

OBJECTIVE: Cardiac involvement in recovered COVID-19 patients assessed by cardiac magnetic resonance imaging (MRI). METHODS: Subjects recently recovered from COVID-19 and with an abnormal left ventricular global longitudinal strain were enrolled. Cardiac MRI in all the enrolled subjects was done at baseline (within 30-90 days following recovery from COVID-19) with a follow-up scan at 6 months in individuals with an abnormal baseline scan. Additionally, 20 age-and sex-matched individuals were enrolled as healthy controls (HCs). RESULTS: All the 30 enrolled subjects were symptomatic during active COVID-19 disease and were categorized as mild: 11 (36.7%), moderate: 6 (20%), and severe: 13 (43.3%). Of the 30 patients, 16 (53.3%) had abnormal CMR findings. Myocardial edema was reported in 12 (40%) patients while 10 (33.3%) had late gadolinium enhancement (LGE). No difference was observed in terms of conventional left ventricular (LV) parameters; however, COVID-19-recovered patients had significantly lower right ventricular (RV) ejection fraction, RV stroke volume, and RV cardiac index compared to HCs. Follow-up scan was abnormal in 4/16 (25%) with LGE persisting in three patients (who had severe COVID-19 [3/4;75%]). Subjects with severe COVID-19 had a greater frequency of LGE (53.8%) and myocardial edema (61.5%) as compared to mild and moderate cases. Myocardial T1 (1284 ± 43.8 ms vs. 1147.6 ± 68.4 ms; p < .0001) and T2 values (50.8 ± 16.7 ms vs. 42.6 ± 3.6 ms; p = .04) were significantly higher in post COVID-19 subjects compared to HCs. Similarly, T1 and T2 values of severe COVID-19 patients were significantly higher compared to mild and moderate cases. CONCLUSIONS: An abnormal CMR was seen in half of the recovered patients with persistent abnormality in one-fourth at 6 months. Our study suggests a need for closer follow-up among recovered subjects in order to evaluate for long-term cardiovascular sequelae. COVID-19 causes structural changes in the myocardium in a small segment of patients with partial spontaneous resolution.

Longitudinal Analysis of Biologic Correlates of COVID-19 Resolution: Case Report.

While the biomarkers of COVID-19 severity have been thoroughly investigated, the key biological dynamics associated with COVID-19 resolution are still insufficiently understood. We report a case of full resolution of severe COVID-19 due to convalescent plasma transfusion. Following transfusion, the patient showed fever remission, improved respiratory status, and rapidly decreased viral burden in respiratory fluids and SARS-CoV-2 RNAemia. Longitudinal unbiased proteomic analysis of plasma and single-cell transcriptomics of peripheral blood cells conducted prior to and at multiple times after convalescent plasma transfusion identified the key biological processes associated with the transition from severe disease to disease-free state. These included (i) temporally ordered upward and downward changes in plasma proteins reestablishing homeostasis and (ii) post-transfusion disappearance of a subset of monocytes characterized by hyperactivated Interferon responses and decreased TNF-α signaling. Monitoring specific dysfunctional myeloid cell subsets in peripheral blood may provide prognostic keys in COVID-19.

Determinants of continuous usage of library resources on handheld devices: findings from PLS-SEM and fuzzy sets (fsQCA)

Purpose>This study aims to investigate the key factors that motivate learners to use handheld devices to access library resources. To do so, this study integrates the technology acceptance model (TAM) and the DeLone and McLean information systems success (D and M-ISS) model.Design/methodology/approach>The relationship between the causes and the outcomes may not be symmetrical. To test this proposition, data were collected from 210 respondents in a Gulf country and analysed using structural equation modelling (SEM) and complemented by fuzzy set qualitative comparative analysis (fsQCA).Findings>The SEM results revealed that three constructs – perceived ease of use (PEOU), service quality (SQ) and system quality (SEQ) are strong drivers of students’ continuous intention to use handheld devices to access library resources. However, perceived usefulness (PU) and information quality (IQ) do not significantly influence students’ intentions. Besides, SQ and PEOU are positively related to PU. Furthermore, fsQCA results show that two different conjunctions, PU*PEOU*IQ*SEQ and PEOU*SQ*IQ*SEQ, cause the students to show a continuous intention to use handheld devices to access library resources.Originality/value>Unlike previous studies on mobile library resource utilization, this analysis extends TAM to investigate the linear additive influence of two basic TAM constructs: PEOU and PU, and three constructs, namely, SEQ, SQ and IQ of the ISS model, on students’ library resource utilization. Furthermore, the findings of SEM were complemented by a set theory-based configuration method, fsQCA, to investigate the asymmetrical, equifinal and configurational causation leading to the desired outcome. The findings of this study have theoretical and practical implications.

Development of a novel human CD147 knock-in NSG mouse model to test SARS-CoV-2 viral infection.

BACKGROUND: An animal model that can mimic the SARS-CoV-2 infection in humans is critical to understanding the rapidly evolving SARS-CoV-2 virus and for development of prophylactic and therapeutic strategies to combat emerging mutants. Studies show that the spike proteins of SARS-CoV and SARS-CoV-2 bind to human angiotensin-converting enzyme 2 (hACE2, a well-recognized, functional receptor for SARS-CoV and SARS-CoV-2) to mediate viral entry. Several hACE2 transgenic (hACE2Tg) mouse models are being widely used, which are clearly invaluable. However, the hACE2Tg mouse model cannot fully explain: (1) low expression of ACE2 observed in human lung and heart, but lung or heart failure occurs frequently in severe COVID-19 patients; (2) low expression of ACE2 on immune cells, but lymphocytopenia occurs frequently in COVID-19 patients; and (3) hACE2Tg mice do not mimic the natural course of SARS-CoV-2 infection in humans. Moreover, one of most outstanding features of coronavirus infection is the diversity of receptor usage, which includes the newly proposed human CD147 (hCD147) as a possible co-receptor for SARS-CoV-2 entry. It is still debatable whether CD147 can serve as a functional receptor for SARS-CoV-2 infection or entry. RESULTS: Here we successfully generated a hCD147 knock-in mouse model (hCD147KI) in the NOD-scid IL2Rgammanull (NSG) background. In this hCD147KI-NSG mouse model, the hCD147 genetic sequence was placed downstream of the endogenous mouse promoter for mouse CD147 (mCD147), which creates an in vivo model that may better recapitulate physiological expression of hCD147 proteins at the molecular level compared to the existing and well-studied K18-hACE2-B6 (JAX) model. In addition, the hCD147KI-NSG mouse model allows further study of SARS-CoV-2 in the immunodeficiency condition which may assist our understanding of this virus in the context of high-risk populations in immunosuppressed states. Our data show (1) the human CD147 protein is expressed in various organs (including bronchiolar epithelial cells) in hCD147KI-NSG mice by immunohistochemical staining and flow cytometry; (2) hCD147KI-NSG mice are marginally sensitive to SARS-CoV-2 infection compared to WT-NSG littermates characterized by increased viral copies by qRT-PCR and moderate body weight decline compared to baseline; (3) a significant increase in leukocytes in the lungs of hCD147KI-NSG mice, compared to infected WT-NSG mice. CONCLUSIONS: hCD147KI-NSG mice are more sensitive to COVID-19 infection compared to WT-NSG mice. The hCD147KI-NSG mouse model can serve as an additional animal model for further interrogation whether CD147 serve as an independent functional receptor or accessory receptor for SARS-CoV-2 entry and immune responses.

Longitudinal Analysis of Biologic Correlates of COVID-19 Resolution: Case Report

While the biomarkers of COVID-19 severity have been thoroughly investigated, the key biological dynamics associated with COVID-19 resolution are still insufficiently understood. We report a case of full resolution of severe COVID-19 due to convalescent plasma transfusion. Following transfusion, the patient showed fever remission, improved respiratory status, and rapidly decreased viral burden in respiratory fluids and SARS-CoV-2 RNAemia. Longitudinal unbiased proteomic analysis of plasma and single-cell transcriptomics of peripheral blood cells conducted prior to and at multiple times after convalescent plasma transfusion identified the key biological processes associated with the transition from severe disease to disease-free state. These included (i) temporally ordered upward and downward changes in plasma proteins reestablishing homeostasis and (ii) post-transfusion disappearance of a subset of monocytes characterized by hyperactivated Interferon responses and decreased TNF-α signaling. Monitoring specific dysfunctional myeloid cell subsets in peripheral blood may provide prognostic keys in COVID-19.

Multiplex PCR Assays for Identifying all Major Severe Acute Respiratory Syndrome Coronavirus 2 Variants.

Variants of concern (VOC) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), including alpha, beta, gamma, delta, and omicron, threaten to prolong the pandemic, leading to more global morbidity and mortality. Genome sequencing is the mainstay of tracking the evolution of the virus, but is costly, slow, and not easily accessible. Multiplex quantitative RT-PCR assays for SARS-CoV-2 have been developed that identify all VOCs as well as other mutations of interest in the viral genome, nine mutations in total, using single-nucleotide discriminating molecular beacons. The presented variant molecular beacon assays showed a limit of detection of 50 copies of viral RNA, with 100% specificity. Twenty-six SARS-CoV-2-positive patient samples were blinded and tested using a two-tube assay. When testing patient samples, the assay was in full agreement with results from deep sequencing with a sensitivity and specificity of 100% (26 of 26). We have used our design methodology to rapidly design an assay that detects the new omicron variant. This omicron assay was used to accurately identify this variant in 17 of 33 additional patient samples. These quantitative RT-PCR assays identify all currently circulating VOCs of SARS-CoV-2, as well as other important mutations in the spike protein coding sequence. These assays can be easily implemented on broadly available five-color thermal cyclers and will help track the spread of these variants.

SARS-CoV-2, SARS-CoV, and MERS-CoV encode circular RNAs of spliceosome-independent origin.

Circular RNAs (circRNAs) are a newly recognized component of the transcriptome with critical roles in autoimmune diseases and viral pathogenesis. To address the importance of circRNA in RNA viral transcriptome, we systematically identified and characterized circRNAs encoded by the RNA genomes of betacoronaviruses using both bioinformatical and experimental approaches. We predicted 351, 224, and 2764 circRNAs derived from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), SARS-CoV, and Middle East respiratory syndrome coronavirus, respectively. We experimentally identified 75 potential SARS-CoV-2 circRNAs from RNA samples extracted from SARS-CoV-2-infected Vero E6 cells. A systematic comparison of viral and host circRNA features, including abundance, strand preference, length distribution, circular exon numbers, and breakpoint sequences, demonstrated that coronavirus-derived circRNAs had a spliceosome-independent origin. We further showed that back-splice junctions (BSJs) captured by inverse reverse-transcription polymerase chain reaction have different level of resistance to RNase R. Through northern blotting with a BSJ-spanning probe targeting N gene, we identified three RNase R-resistant bands that represent SARS-CoV-2 circRNAs that are detected cytoplasmic by single-molecule and amplified fluorescence in situ hybridization assays. Lastly, analyses of 169 sequenced BSJs showed that both back-splice and forward-splice junctions were flanked by homologous and reverse complementary sequences, including but not limited to the canonical transcriptional regulatory sequences. Our findings highlight circRNAs as an important component of the coronavirus transcriptome, offer important evaluation of bioinformatic tools in the analysis of circRNAs from an RNA genome, and shed light on the mechanism of discontinuous RNA synthesis.

Heart rate variability as a marker of cardiovascular dysautonomia in post-COVID-19 syndrome using artificial intelligence.

INTRODUCTION: Cardiovascular dysautonomia comprising postural orthostatic tachycardia syndrome (POTS) and orthostatic hypotension (OH) is one of the presentations in COVID-19 recovered subjects. We aim to determine the prevalence of cardiovascular dysautonomia in post COVID-19 patients and to evaluate an Artificial Intelligence (AI) model to identify time domain heart rate variability (HRV) measures most suitable for short term ECG in these subjects. METHODS: This observational study enrolled 92 recently COVID-19 recovered subjects who underwent measurement of heart rate and blood pressure response to standing up from supine position and a 12-lead ECG recording for 60 s period during supine paced breathing. Using feature extraction, ECG features including those of HRV (RMSSD and SDNN) were obtained. An AI model was constructed with ShAP AI interpretability to determine time domain HRV features representing post COVID-19 recovered state. In addition, 120 healthy volunteers were enrolled as controls. RESULTS: Cardiovascular dysautonomia was present in 15.21% (OH:13.04%; POTS:2.17%). Patients with OH had significantly lower HRV and higher inflammatory markers. HRV (RMSSD) was significantly lower in post COVID-19 patients compared to healthy controls (13.9 ± 11.8 ms vs 19.9 ± 19.5 ms; P = 0.01) with inverse correlation between HRV and inflammatory markers. Multiple perceptron was best performing AI model with HRV(RMSSD) being the top time domain HRV feature distinguishing between COVID-19 recovered patients and healthy controls. CONCLUSION: Present study showed that cardiovascular dysautonomia is common in COVID-19 recovered subjects with a significantly lower HRV compared to healthy controls. The AI model was able to distinguish between COVID-19 recovered patients and healthy controls.

COVID 19-related burnout among healthcare workers in India and ECG based predictive machine learning model: Insights from the BRUCEE- Li study.

OBJECTIVES: COVID-19 pandemic has led to unprecedented increase in rates of stress and burn out among healthcare workers (HCWs). Heart rate variability (HRV) has been shown to be reflective of stress and burnout. The present study evaluated the prevalence of burnout and attempted to develop a HRV based predictive machine learning (ML) model to detect burnout among HCWs during COVID-19 pandemic. METHODS: Mini-Z 1.0 survey was collected from 1615 HCWs, of whom 664, 512 and 439 were frontline, second-line and non-COVID HCWs respectively. Burnout was defined as score ≥3 on Mini-Z-burnout-item. A 12-lead digitized ECG recording was performed and ECG features of HRV were obtained using feature extraction. A ML model comprising demographic and HRV features was developed to detect burnout. RESULTS: Burnout rates were higher among second-line workers 20.5% than frontline 14.9% and non-COVID 13.2% workers. In multivariable analyses, features associated with higher likelihood of burnout were feeling stressed (OR = 6.02), feeling dissatisfied with current job (OR = 5.15), working in a chaotic, hectic environment (OR = 2.09) and feeling that COVID has significantly impacted the mental wellbeing (OR = 6.02). HCWs with burnout had a significantly lower HRV parameters like root mean square of successive RR intervals differences (RMSSD) [p < 0.0001] and standard deviation of the time interval between successive RR intervals (SDNN) [p < 0.001]) as compared to normal subjects. Extra tree classifier was the best performing ML model (sensitivity: 84%) CONCLUSION: In this study of HCWs from India, burnout prevalence was lower than reports from developed nations, and was higher among second-line versus frontline workers. Incorporation of HRV based ML model predicted burnout among HCWs with a good accuracy.

Left ventricular global longitudinal strain in COVID-19 recovered patients.

OBJECTIVES: Myocardial injury during active coronavirus disease-2019 (COVID-19) infection is well described; however, its persistence during recovery is unclear. We assessed left ventricle (LV) global longitudinal strain (GLS) using speckle tracking echocardiography (STE) in COVID-19 recovered patients and its correlation with various parameters. METHODS: A total of 134 subjects within 30-45 days post recovery from COVID-19 infection and normal LV ejection fraction were enrolled. Routine blood investigations, inflammatory markers (on admission) and comprehensive echocardiography including STE were done for all. RESULTS: Of the 134 subjects, 121 (90.3%) were symptomatic during COVID-19 illness and were categorized as mild: 61 (45.5%), moderate: 50 (37.3%) and severe: 10 (7.5%) COVID-19 illness. Asymptomatic COVID-19 infection was reported in 13 (9.7%) patients. Subclinical LV and right ventricle (RV) dysfunction were seen in 40 (29.9%) and 14 (10.5%) patients, respectively. Impaired LVGLS was reported in 1 (7.7%), 8 (13.1%), 22 (44%) and 9 (90%) subjects with asymptomatic, mild, moderate and severe disease, respectively. LVGLS was significantly lower in patients recovered from severe illness(mild: -21 ± 3.4%; moderate: -18.1 ± 6.9%; severe: -15.5 ± 3.1%; p < 0.0001). Subjects with reduced LVGLS had significantly higher interleukin-6 (p < 0.0001), C-reactive protein (p = 0.001), lactate dehydrogenase (p = 0.009), serum ferritin (p = 0.03), and troponin (p = 0.01) levels during index admission. CONCLUSIONS: Subclinical LV dysfunction was seen in nearly a third of recovered COVID-19 patients while 10.5% had RV dysfunction. Our study suggests a need for closer follow-up among COVID-19 recovered subjects to elucidate long-term cardiovascular outcomes.