Distinct Type 1 Immune Networks Underlie the Severity of Restrictive Lung Disease after COVID-19 (preprint)

The variable etiology of persistent breathlessness after COVID-19 have confounded efforts to decipher the immunopathology of lung sequelae. Here, we analyzed hundreds of cellular and molecular features in the context of discrete pulmonary phenotypes to define the systemic immune landscape of post-COVID lung disease. Cluster analysis of lung physiology measures highlighted two phenotypes of restrictive lung disease that differed by their impaired diffusion and severity of fibrosis. Machine learning revealed marked CCR5+CD95+ CD8+ T-cell perturbations in mild-to-moderate lung disease, but attenuated T-cell responses hallmarked by elevated CXCL13 in more severe disease. Distinct sets of cells, mediators, and autoantibodies distinguished each restrictive phenotype, and differed from those of patients without significant lung involvement. These differences were reflected in divergent T-cell-based type 1 networks according to severity of lung disease. Our findings, which provide an immunological basis for active lung injury versus advanced disease after COVID-19, might offer new targets for treatment.

Predictors of active pulmonary tuberculosis among hospitalized patients with atypical symptom and sign and underlying diseases having impact on the outcome of the COVID-19 (preprint)

Background This study aimed to focus on the diagnostic use of high-resolution computed tomography (HRCT) to identify active pulmonary tuberculosis (aPTB) with atypical symptom and sign among the hospitalized patients with the underlying diseases having the impact on the outcome of the Coronavirus disease 2019 (COVID-19).Methods Within the study period (2018.01.01-2021.12.31), for patients with underlying diseases having the impact on the outcome of the COVID-19, chest –x-ray (CXR) / HRCT scans along with their patients’ charts were reviewed. These patients (n = 4,380) were classified into the [aPTB] group I (G1, n = 277) and pulmonary disease without aPTB (G2, n = 4103). Lung morphology, and lobar (segmental) distribution using CXR/HRCT, the underlying diseases and clinical symptom/sign were analyzed. To identify independent variables associated with G1, multivariate analysis was performed. Independent variables were used to generate prediction scores, which were used to develop models for predicting G1.Results For the HRCT model, multivariate analysis revealed cavitation, clusters nodules/mass (CNM) of the right/left upper lobe or ground-glass opacity were useful predictors for the G1. The negative predictive value of the HRCT model, and the CNM model for the GI were 99.3%, and 97.5%, respectively. However, the CNM model has the highest positive predictive value of 95.4%.Conclusions The CNM model may play an auxiliary role for the identification of G1 with atypical symptom and sign among the patients with underlying diseases having the impact on the outcome of the COVID-19.

Respiratory viral infection promotes the awakening and outgrowth of dormant metastatic breast cancer cells in lungs (preprint)

Breast cancer is the second most common cancer globally. Most deaths from breast cancer are due to metastatic disease which often follows long periods of clinical dormancy1. Understanding the mechanisms that disrupt the quiescence of dormant disseminated cancer cells (DCC) is crucial for addressing metastatic progression. Infection with respiratory viruses (e.g. influenza or SARS-CoV-2) is common and triggers an inflammatory response locally and systemically2,3. Here we show that influenza virus infection leads to loss of the pro-dormancy mesenchymal phenotype in breast DCC in the lung, causing DCC proliferation within days of infection, and a greater than 100-fold expansion of carcinoma cells into metastatic lesions within two weeks. Such DCC phenotypic change and expansion is interleukin-6 (IL-6)-dependent. We further show that CD4 T cells are required for the maintenance of pulmonary metastatic burden post-influenza virus infection, in part through attenuation of CD8 cell responses in the lungs. Single-cell RNA-seq analyses reveal DCC-dependent impairment of T-cell activation in the lungs of infected mice. SARS-CoV-2 infected mice also showed increased breast DCC expansion in lungs post-infection. Expanding our findings to human observational data, we observed that cancer survivors contracting a SARS-CoV-2 infection have substantially increased risks of lung metastatic progression and cancer-related death compared to cancer survivors who did not. These discoveries underscore the significant impact of respiratory viral infections on the resurgence of metastatic cancer, offering novel insights into the interconnection between infectious diseases and cancer metastasis.

Prognostic value of SOFA combined with chest CT severity score in patients with critical COVID-19 pneumonia: a retrospective study (preprint)

Background: Either sequential organ failure assessment (SOFA) score or chest CT severity score (CT-SS) is often used alone to evaluate the prognosis of patients with critical coronavirus disease 2019 (COVID-19), but each of them has intrinsic deficiency. Herein, we attempted to investigate the predictive value of the combination of SOFA and CT-SS for the prognosis of COVID-19. Materials and Methods: A single-center retrospective study was performed in the Second Affiliated Hospital of Zhejiang University School of Medicine from December 2022 to January 2023. Patients with critical COVID-19 pneumonia were divided into two groups of survival or non-survival of hospitalization. The data including clinical characteristics, CT-SS, SOFA score, laboratory results on admission day were collected and analyzed. In addition, the predictive value of SOFAscore, chest CT-SS, or their combination for in-hospital mortality of COVID-19 pneumonia were compared by receiver operating characteristic (ROC) curve. Results: A total of 424 patients with a mean age of 75.46 years and a major proportion of male (69.10%) were finally enrolled, and the total in-hospital mortality was 43.40% (184/424). In comparison with survival group, significant higher proportions of older age (>75 years), comorbidities including obesity, diabetes, and cerebrovascular disease, more needs of mechanical ventilation and continuous renal replacement therapy (CRRT) were observed in the non-survival group (all P﹤0.05). In addition, non-survival patients had a higher value of creatinine, procalcitonin, C-reactive protein, interleukin-6 , SOFA score , CT-SS  (all P﹤0.05) on admission day. Multivariate logistic regression analysis further showed that older age, obesity, diabetes, SOFA score, CT-SS, mechanical ventilation, and lymphocytopenia (all P﹤0.05) were independently related with in-hospital mortality. Moreover, the area under the curve (AUC) of combination of SOFA score and chest CT-SS became significant higher than their respective alone (P＜0.01). Conclusion: A simple combination of SOFA scorewith chest CT-SS on admission elicits a better predictive value for in-hospital mortality of critical COVID-19 patients, which could also serve as a promising indicator for prognosis prediction of other severe lung diseases like severe pneumonia and acute lung injury.

Sustained mTOR inhibition with sirolimus improves respiratory outcomes in LAM patients with COVID-19 (preprint)

Background Lymphangioleiomyomatosis (LAM) is a rare lung disease that predominantly affects women and can lead to severe respiratory complications. The impact of COVID-19 on LAM patients, particularly regarding the use of mammalian target of rapamycin (mTOR) inhibitors, remains poorly understood. This study investigates the clinical outcomes of LAM patients with COVID-19 and evaluates the role of sustained mTOR inhibition in respiratory outcomes.Results Our cohort included 186 LAM patients with COVID-19. Prior to infection, 72.6% were on mTOR inhibitors, with 29.6% discontinuing therapy due to infection. The hospitalization rate was 1.1%, with no reported need for invasive ventilation or fatalities. Patients with FEV1 less than 70% predicted had a higher risk of dyspnea exacerbation and supplemental oxygen requirement. Continuation of mTOR inhibitor therapy was associated with a lower risk of SpO2 decline, especially among patients with impaired lung function. Vaccination status did not significantly affect the prognosis.Conclusions LAM patients with COVID-19 showed a low rate of severe illness and mortality, with impaired lung function correlating with worse respiratory outcomes. Continued mTOR inhibitor therapy during COVID-19 infection may improve respiratory outcomes, suggesting the importance of maintaining treatment during viral pandemics.

Assessing COVID-19 Vaccine Effectiveness in Frail Long-Term Care Facilities Residents in a Middle-Income Country (preprint)

Background: During the COVID-19 pandemic, individuals residing in long-term care facilities (LTCF) are particularly vulnerable to adverse outcomes due to their higher rates of frailty, disabilities, cognitive impairment, dementia, and chronic illnesses. In low and middle-income nations, research on immunizing frail populations is lacking, while most studies on COVID-19 in LTCF come from wealthier nations and may not fully capture the situation in emerging countries.  Methods: We aimed to evaluate the effectiveness of first, second and third COVID-19 vaccine doses, against infections, hospitalizations, and deaths, and their association with frailty, age, sex and chronic disease, among older adults, in a social vulnerability context. This retrospective cohort study, comprises a total of 712 older adults, in a social vulnerability context, of 29 LTCF, in Brazil. Continuous variables were described by medians and interquartile ranges and categorical variables were represented by absolute and relative frequencies. The Mann-Whitney test was used. For evaluating the relation between categorical variables, Pearson's chi-square test was used. When comparing proportions, the Z test of proportion was applied. A significance level of 5% was considered.  Results: Median age was 81.37 years, 72.8% were female, 94.61% were frail, 79.97% had a cognitive impairment, 69.54% had a mobility impairment, 78.37% have, at least, one chronic disease and 72.73% use five or more medications per day. Before the vaccine, mobility impairment was associated with great contamination rates (p=.03); frailty (p=.02) and previous pulmonary disease (p=.03) with symptoms of gravity; frailty (p=.02), pulmonary disease (p=.04) and male sex (p=.02) with emergency care or hospital admission. After the third vaccine dose, only frailty remains associated with admissions (p=.03). The number of positive cases (p=.001), symptomatic patients (p<.001), admissions (p=.001) and deaths (p<.001) were substantially reduced after the three vaccine doses.  Conclusions and Implications: Even in a frail population, the vaccine was effective, in the reduction of positive cases, the number of symptomatic patients, admission to emergency or hospital care and deaths. Before the vaccine, frailty, previous pulmonary disease and male sex were associated with worse outcomes. After the vaccine, frailty remains associated with a major number of admissions.

Resoluteneuronet: Deep Learning-based Segmentation and Classification Covid-19 Using Chest X-ray Images (preprint)

The worldwide healthcare systems are facing substantial problems because of impending COVID-19 pandemic epidemic, necessitating rapid, accurate diagnosis for effective management and control. Chest X-ray (CXR) imaging is a valuable diagnostic tool for identifying COVID-19-related lung abnormalities. However, manual interpretation of CXR images was time-consuming and prone to inter-observer variability. Thisstudy proposes a DL approach to address the limitation of automated COVID-19 segmentation and classification utilizing CXR images. The approach segments and classifies COVID-19. The distinction between COVID-19 and healthy patients in this study was made using CXR images. Using the histogram equalization technique, the gathered CXR images are preprocessed. We can obtain images of the lungs by utilizing the “conditional generative adversarial network” (C-GAN) to segment the raw CXR images. Next, significant points were extracted from the segmented lung pictures using the Wavelet Transform(WT) to remove discriminatory features. In this study, we developed a classification method called ResoluteNeuroNet (Resolute-NN), used in the final stage to classify COVID-19 and standard lung images. The accuracy of our proposed model's performance was compared to that of the currently used COVID-19 detection methods. The experimental findings for our suggested practice demonstrate Resolute-NN superiority over the presently used state-of-the-art approaches.

Biological Effects of Corticosteroids on Pneumococcal Pneumonia in Mice and Humans (preprint)

Background: Streptococcus pneumoniae is the most common bacterial cause of community acquired pneumonia and the acute respiratory distress syndrome (ARDS). Some clinical trials have demonstrated a beneficial effect of corticosteroid therapy in community acquired pneumonia, COVID-19, and ARDS, but the mechanisms of this benefit remain unclear. The objective of this study was to investigate the effects of corticosteroids on the pulmonary biology of pneumococcal pneumonia in an observational cohort of mechanically ventilated patients and in a mouse model of bacterial pneumonia with Streptococcus pneumoniae. Methods: We studied gene expression with lower respiratory tract transcriptomes from a cohort of mechanically ventilated patients and in mice. We also carried out comprehensive physiologic, biochemical, and histological analyses in mice to identify the mechanisms of lung injury in Streptococcus pneumoniae with and without adjunctive steroid therapy. Results: Transcriptomic analysis identified pleiotropic effects of steroid therapy on the lower respiratory tract in critically ill patients with pneumococcal pneumonia, findings that were reproducible in mice. In mice with pneumonia, dexamethasone in combination with ceftriaxone reduced (1) pulmonary edema formation, (2) alveolar protein permeability, (3) proinflammatory cytokine release, (4) histopathologic lung injury score, and (5) hypoxemia but did not increase bacterial burden. Conclusions: The gene expression studies in patients and in the mice support the clinical relevance of the mouse studies, which replicate several features of pneumococcal pneumonia and steroid therapy in humans. In combination with appropriate antibiotic therapy in mice, treatment of pneumococcal pneumonia with steroid therapy reduced hypoxemia, pulmonary edema, lung permeability, and histologic criteria of lung injury, and also altered inflammatory responses at the protein and gene expression level. The results from these studies provide evidence for the mechanisms that may explain the beneficial effects of glucocorticoid therapy in patients with community acquired pneumonia from Streptococcus Pneumoniae.

Pulmonary complications and mortality among COVID-19 patients undergoing a surgery: a multicenter cohort study (preprint)

Background Managing COVID-19-positive patients requiring surgery is complex due to perceived heightened perioperative risks. However, Canadian data in this context remains scarce. To address this gap, we conducted a multicenter cohort study in the province of Québec, the Canadian province most affected during the initial waves of the pandemic, to comprehensively assess the impact of COVID-19 symptoms, and recovery time, on postoperative outcomes in surgical patients. Methods We included adult surgical patients with either active COVID-19 at time of surgery or those who had recovered from the disease, from March 13, 2020, to April 30, 2021. We evaluated the association between symptoms or recovery time and postoperative pulmonary complications and hospital mortality using multivariable logistic regression and Cox models. Results We included 105 patients with an active infection (47 were symptomatic and 58 were asymptomatic) and 206 who had healed from COVID-19 in seven hospitals. Among patients with an active infection, those who were symptomatic had a higher risk of pulmonary complications (odds ratio = 3.19; 95% CI, from 1.12 to 9.68; p = 0.03) and hospital mortality (hazard ratio = 3.67; 95% CI, from 1.19 to 11.32; p = 0.02). We did not observe any significant effect of the duration of recovery prior to surgery on patients who had healed from their infection. Their postoperative outcomes were also similar to those observed in asymptomatic patients. Interpretation Symptomatic status should be considered in the decision to proceed with surgery in COVID-19-positive patients. Our results may help optimize surgical care in this patient population. Trial registration: ClinicalTrials.gov Identifier: NCT04458337, Registration Date: July 7, 2020.

Characteristics and Determinants of Pulmonary Long COVID (preprint)

RATIONALE: Persistent cough and dyspnea are prominent features of post-acute sequelae of SARS-CoV-2 (termed 'Long COVID'); however, physiologic measures and clinical features associated with these pulmonary symptoms remain poorly defined. OBJECTIVES: Using longitudinal pulmonary function testing (PFTs) and CT imaging, this study aimed to identify the characteristics and determinants of pulmonary Long COVID. METHODS: The University of Alabama at Birmingham Pulmonary Long COVID cohort was utilized to characterize lung defects in patients with persistent pulmonary symptoms after resolution primary COVID infection. Longitudinal PFTs including total lung capacity (TLC) and diffusion limitation of carbon monoxide (DLCO) were used to evaluate restriction and diffusion impairment over time in this cohort. Analysis of chest CT imaging was used to phenotype the pulmonary Long COVID pathology. Risk factors linked to development of pulmonary Long COVID were estimated using univariate and multivariate logistic regression models. MEASUREMENTS AND MAIN RESULTS: Longitudinal evaluation 929 patients with post-COVID pulmonary symptoms revealed diffusion impairment (DLCO ≤80%) and restriction (TLC ≤80%) in 51% of the cohort (n=479). In multivariable logistic regression analysis (adjusted odds ratio; aOR, 95% confidence interval [CI]), invasive mechanical ventilation during primary infection conferred the greatest increased odds of developing pulmonary Long COVID with diffusion impaired restriction (aOR=10.9 [4.09-28.6]). Finally, a sub-analysis of CT imaging identified evidence of fibrosis in this population. CONCLUSIONS: Persistent diffusion impaired restriction was identified as a key feature of pulmonary Long COVID. Subsequent clinical trials should leverage combined symptomatic and quantitative PFT measurements for more targeted enrollment of pulmonary Long COVID patients.

Could SP-A and SP-D Serum Levels Predict COVID-19 Severity? (preprint)

Given the various clinical manifestations that characterize COVID-19, the scientific community is constantly searching for biomarkers with prognostic value. SP-A and SP-D collectins play a crucial role in ensuring proper alveolar function and an alteration of their serum levels have been reported in several pulmonary diseases characterized by ARDS and pulmonary fibrosis. Considering that such clinical manifestations can also occur during SARS-CoV-2 infection, we wondered if these collectins could act as prognostic markers. In this regard, serum levels of SP-A and SP-D were measured by enzyme immunoassay in patients with SARS-CoV-2 infection (n=51) at admission (T0) and after 7 days (T1) and compared with healthy donors (n=11). SP-D increased in COVID-19 patients compared to healthy controls during the early phases of infection, while a significant reduction was observed at T1. Stratifying SARS-CoV-2 patients according to disease severity, increased serum SP-D levels were observed in severe compared to mild patients. In the light of these results SP-D, but not SP-A, seems to be an eligible marker of COVID-19 pneumonia and the early detection of SP-D serum levels could be crucial for a preventive clinical management

Pulmonary fibrosis in critically ill patients with COVID-19: A multi-center retrospective cohort study in South Korea (preprint)

Background: Pulmonary fibrosis persists long after recovering from coronavirus disease 2019 (COVID-19) infection, thereby reducing quality of life and lung function. We aimed to evaluate the prevalence and risk factors for pulmonary fibrosis in patients with severe COVID-19 pneumonia requiring mechanical ventilation, a high-risk group for developing pulmonary fibrosis. Methods: Clinical data and chest computed tomography (CT) scans of patients with severe COVID-19 pneumonia requiring mechanical ventilation were retrospectively collected from nine hospitals in South Korea. Fibrotic-like changes on chest CT were visually assessed. Results: We included 125 patients with a mean age of 68.5 years, 60.8% men and 7.2% having underlying lung disease. Based on follow-up chest CT (the median interval: 38.0 days, interquartile range: 24.0–68.0 days), 94 (75.2%) patients exhibited fibrotic-like changes, with traction bronchiectasis and/or bronchiolectasis being the most common change (60.8%). Adjusted Cox regression analysis revealed as association between hemoglobin levels ≤9 g/dL and an increased risk of pulmonary fibrosis development (HR: 3.182, 95% Cl: 1.203–8.415, P=0.025). Among all patients, 17.6% died during hospitalization and 71.2% experienced complications, including intubation-related airway injury (12.8%), ventilator-associated pneumonia (44.8%), lung injury (11.2%), and hemodynamic disturbance (33.4%). In-hospital mortality (16.1% vs. 18.1%) and complications (67.7% vs. 72.3%) were similar between patients with and without fibrotic-like changes. Conclusion: Our study demonstrated that in patients with severe COVID-19 pneumonia requiring mechanical ventilation, chest CT revealed fibrotic-like changes in approximately three-fourths of patients. Low hemoglobin levels might be associated with pulmonary fibrosis in severe COVID-19 pneumonia.

FABP4 as a Therapeutic Host Target Controlling SARS-CoV2 Infection (preprint)

Host metabolic fitness is a critical determinant of infectious disease outcomes. In COVID-19, obesity and aging are major high-risk disease modifiers, although the underlying mechanism remains unknown. Here, we demonstrate that fatty acid binding protein 4 (FABP4), a critical regulator of metabolic dysfunction in these conditions, regulates SARS-CoV2 pathogenesis. Our study revealed that elevated FABP4 levels in COVID-19 patients strongly correlate with disease severity. In adipocytes and airway epithelial cells we found that loss of FABP4 function by genetic or pharmacological means impaired SARS-CoV2 replication and disrupted the formation of viral replication organelles. Furthermore, treatment of infected hamsters with FABP4 inhibitors alleviated lung damage and fibrosis and reduced lung viral titers. These results highlight a novel host factor critical for SARS-CoV2 infection and the therapeutic potential of FABP4-targeting agents in treating COVID-19 patients.

A novel multi class disease detection of chest x-ray images using deep learning with pre trained transfer learning models for medical imaging applications (preprint)

Images from chest X-rays (CXR) are thought to help observe and research various kinds of pulmonary illnesses. Several works were suggested in the literature for recognizing unique lung diseases, and only a few studies were focused on developing a model to identify joint classes of lung diseases. A patient with a negative diagnosis for one condition may have the other disease, and vice versa. However, since many illnesses are lung-related, a patient can have multiple illnesses simultaneously. This paper proposes a deep learning (DL)-based pre-trained transfer learning (TL) model for effectively detecting and classifying the multiclass diseases of lung CXR images. The system involves five phases: preprocessing, dataset balancing, feature learning, feature selection, and multiclass classification. Firstly, the CXR images are preprocessed by performing filtering, contrast enhancement, and data augmentation. After that, the dataset balancing is performed using the Synthetic Minority Oversampling Technique (SMOTE). Next, the features are learned using a spatial and channel-attention-based Xception Network (SCAXN). The optimal features are selected using nonlinear decreasing inertia weight-based rock hyraxes swarm optimization (NIWRHSO). Finally, the multiclass classification uses a soft sign-incorporated bidirectional gated recurrent unit (SBIGRU). Two public datasets, COVID-19 Radiography (C19RY) and Tuberculosis CXR (TB-CXR), have been obtained from Kaggle, and the outcomes confirmed that the proposed system attains superior results to prevailing methods.

Impact of mechanical power on mortality in ventilated critically ill patients. Retrospective study with continuous real-life data (preprint)

Background Over the past decade, numerous studies on potential factors contributing to ventilation-induced lung injury have been carried out. Mechanical power has been pointed out as the parameter that encloses all ventilation-induced lung injury-contributing factors. However, studies conducted to date provide data regarding mechanical power during the early hours of mechanical ventilation that may not correspond to the real scenario. Methods Retrospective observational study conducted at a single center in Spain. Patients admitted to the intensive care unit, > o = 18 years of age, and ventilated for over 24 hours were included. We extracted the mechanical power values throughtout the entire mechanical ventilation period from the clinical information system every two minutes. First, we calculate the cutoff-point for mechanical power beyond which there was a greater change in the probability of death. After, the sum of time values above the safe cut-off point was calculated to obtain the value in hours. We analyzed if the number of hours the patient was under ventilation with a mechanical power above the safe threshold was associated with mortality, invasive mechanical ventilation days, and intensive care unit length of stay. We repeated the analysis in different subgroups based on the degree of hypoxemia and in patients with SARS CoV-2 pneumonia. Results The cut-off point of mechanical power at with there is a higher increase in mortality was 18J/min. The greater the number or hours patients were under mechanical power > 18 J/min the higher the mortality in all the study population, in patients with SARS CoV-2 pneumonia and in mild to moderate hyopoxemic respiratory failure. The risk of death inceases 0.1% for each our with mechanical power exceeding 18 J/min. The number of hours with mechanical power > 18 J/min also affected the days of invasive mechanical ventilation and intensive care unit length of stay. Conclusions Continuous monitoring of mechanical power using an automated clinical information system shows that the number of hours with mechanical power > 18 J/min increases mortality in critically ill patients.

Treadmill Exercise Stress Echocardiography Exposes Impaired Left Ventricular Function in Patients Recovering from Hospitalization with COVID-19 Without Overt Myocarditis Versus Historical Controls (preprint)

Background: Usual clinical testing rarely reveals cardiac abnormalities persisting after hospitalization for COVID-19. Such testing may overlook residual changes responsible for increased adverse cardiac events post-discharge. Methods: To further elucidate long-term status, we performed exercise stress echocardiography (ESE) in 15 patients age 30-63 without myocarditis 3 to 31 months after hospital discharge. We compared patient outcomes to published data in healthy comparisons (HC) exercising according to the same protocol. Results: Patients' treadmill exercise (Bruce protocol), averaging 8.2 min, was halted by dyspnea or fatigue. Pre-stress baselines in recovering patients (RP) matched HC except for higher heart rate: mean 81 bpm for RP and 63 for HC (p<0.0001). At peak stress, RP had significantly lower mean left ventricular (LV) ejection fraction (67% vs 73%, p<0.0017) and higher peak early mitral inflow velocity/early mitral annular velocity (E/e', 9.1 vs 6.6, p<0.006) compared with HC performing equal exercise (8.5 min). Thus, when stressed, patients without known cardiac impairment showed modest but consistently diminished systolic contractile function and diastolic LV compliance during recovery vs HC. Peak HR during stress was significantly elevated in RP vs HC; peak SBP also trended higher. Average pulmonary artery systolic pressures among RP remained normal. Conclusions: Our measurements during ESE uniquely identified residual abnormality in cardiac contractile function not evident in the unstressed condition. This finding exposes a previously-unrecognized residual influence of COVID-19, possibly related to underlying autonomic dysfunction, microvascular disease, or diffuse interstitial changes after subclinical myocarditis; it may have long-term implications for clinical management and later prognosis.

S-RBD-modified and miR-486-5p-engineered exosomes derived from mesenchymal stem cells alleviate radiation-induced lung injury and long-term pulmonary fibrosis via suppression of ferroptosis (preprint)

Background Radiation-induced pulmonary fibrosis (RIPF) is a late-stage complication of therapeutic radiation, associated with poor prognosis and limited therapeutic options. Radiation-induced lung injury (RILI) is an early manifestation of RIPF, and intervention of RILI is an effective method for preventing long-term RIPF. Mesenchymal stem cell (MSC)-derived exosomes exhibit regenerative activity in injured lungs and are effective drug-delivery nanoparticles. SARS-CoV-2-S-RBD enables ACE2+ cell targeting of MSC extracellular vesicles. miR-486-5p is a multifunctional miRNA with angiogenic and anti-fibrotic activities and is enriched in MSC-derived exosomes. In this study, we investigated the therapeutic effects of miR-486-5p and SARS-COV-2-S-RBD-engineered MSC exosomes on RIPF in vitro and in vivo.Results Adenovirus-mediated gene modification led to the overexpression of miR-486-5p in umbilical cord MSCs (UC-MSCs), which further enriched miR-486-5p in UC-MSCs-derived exosomes. MiR-486-5p-engineered MSC exosomes (miR-486-MSC-Exo) promoted the proliferation and migration of irradiated MLE-12 cells in vitro and inhibited RILI in vivo. An in vitro assay revealed the occurrence of ferroptosis, a major form of cell death during radiation injury, indicated by the upregulated expression of fibrosis-related genes. miR-486-MSC-Exo effectively reversed these changes. MiR-486-MSC-Exo strongly reversed the upregulated expression of MLE-12 fibrosis-related genes induced by TGF in vitro and improved pathological fibrosis in the RIPF model in vivo. The distribution of RBD-VSVG-MSC exosomes labeled with DiR dye in hACE2CKI/CKI Sftpc-Cre+ mice demonstrated that the fluorescence of RBD-VSVG exosomes remained in the lungs for a long time. miR-486-RBD-MSC-exosomes significantly improved the survival rate and pathological changes in hACE2CKI/CKI Sftpc-Cre+ RIPF mice. Furthermore, miR-486-MSC-Exo exerted anti-fibrotic effects through targeted inhibition of SMAD2 and activation of Akt phosphorylation.Conclusions Here, miR-486-MSC-Exo inhibited lung injury and alleviated fibrosis in vivo and in vitro. Surface modification with COVID-S-RBD conferred engineered exosomes with the ability to target the lungs of animal models. The therapeutic effects of miR-486-5p and COVID-S-RBD-engineered MSC exosomes on RIPF were significantly enhanced. MSC-derived exosomes modified with recombinant COVID-S-RBD enabled targeted delivery of miR-486-5p, which is an effective approach for the treatment of RIPF.

Predictors of the chest CT score in COVID-19 patients: A cross-sectional study (preprint)

Background: Since the COVID-19 outbreak, pulmonary involvement was one of the most significant concerns in assessing patients. In the current study, we evaluated patient’s clinical and laboratory findings on the first visit to predict the severity of pulmonary involvement and their outcome. Methods: Four hundred seventy-eight COVID-19 patients with positive real-time reverse-transcriptase-polymerase chain reaction (RT-PCR) or highly suggestive symptoms with computed tomography(CT) imaging results with typical findings of COVID-19 were enrolled in the study. The clinical features, initial laboratory, CT findings, and short-term outcomes (ICU admission, mortality, length of hospitalization, and recovery time) were recorded. In addition, the severity of pulmonary involvement was assessed using a semi-quantitative scoring system (0-25). Results: Among 478 participants in this study, 353 (73.6%) were admitted to the hospital, and 57 (11.9%) patients were admitted to the ICU. A review of chest CT scans showed that Ground Glass Opacity (GGO) (58.5%) and consolidation (20.7%) were the most patterns of lung lesions. Among initial clinical and laboratory findings, anosmia (P = 0.01), respiratory rate (RR) ≥ 25 (P = 0.001), C-reactive protein (CRP) ≥ 91 (P = 0.002), white Blood Cell (WBC) >10,000 (P = 0.009), and SpO2 ≥ 93 (P = 0.04) was associated with higher chest CT score. Lung involvement and consolidation lesions on chest CT scans were also associated with more extended hospitalization and recovery period. Conclusions: Initial assessment of COVID-19 patients, including symptoms, vital signs, and routine laboratory tests, can predict the severity of lung involvement and unfavorable outcomes.

The Interleukin 6 (IL-6) blockade for coronavirus disease 2019 (COVID-19) In Lung (preprint)

COVID-19 has caused global pandemics since the emergent outbreak and resulted in a large number of deaths. IL-6, as an important autoimmune cytokine, had been suggested for the treatment of acute respiratory distress syndrome (ARDS) patients in COVID-19. A review of the relevant literature revealed more than one role for IL-6 in the lung infection because of its diverse biological effects. It may have a variety of different physiological functions in the development of lung infection. We have summarized its role in different progress of COVID-19, including lung infection, pneumonia, ALI, pulmonary fibrosis, and lung translation and even lung cancer. This will facilitate a deeper understanding of the role of IL-6 in the treatment of COVID-19.

Association Between Presence of Bacillus Calmette-Guerin Vaccine Scar and Coronavirus Disease 2019 (preprint)

Objective: Bacillus Calmette-Guerin (BCG) vaccine is administered for protection against tuberculosis and may also have beneficial effects against some viral respiratory tract infections. The low incidence and mortality of coronavirus disease (COVID-19) in countries that have BCG vaccination program is impressive, and some studies have shared contradictory results. In this study, it was aimed to investigate the relationship between BCG vaccination which is confirmed by BCG scar, and the frequency and course of COVID-19. Methods: : Among 490 patients who applied to the outpatient clinic for Pulmonary and Enfectious Diseases between March 2021 and June 2021, 400 patients who accepted to participate in the study were included. After the consent of patients; age, gender, body mass index, comorbidities, smoking, history and the progress of COVID-19 of these patients were investigated; presence and number of BCG scar were recorded by physician. Data from groups with and without COVID-19 history were compared. Results: : Of the 400 patients 228 (57%) were female. Mean age was 39.65 ± 13.53. 188 (47%) patients had a history of COVID-19. There was no relation between presence and number of the BCG scar and COVID-19 related hospitalization and intensive care unit admission. When groups with and without COVID-19 history compared, no statistically significant difference was found with the presence and number of BCG scars (p>0,05). Conclusion: No association was found between the presence or number of BCG scars and the frequency and course of COVID-19 in individuals with BCG vaccination history confirmed by the presence of BCG vaccine scars.