Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography.

Many COVID-19 patients infected by SARS-CoV-2 virus develop pneumonia (called novel coronavirus pneumonia, NCP) and rapidly progress to respiratory failure. However, rapid diagnosis and identification of high-risk patients for early intervention are challenging. Using a large computed tomography (CT) database from 3,777 patients, we developed an AI system that can diagnose NCP and differentiate it from other common pneumonia and normal controls. The AI system can assist radiologists and physicians in performing a quick diagnosis especially when the health system is overloaded. Significantly, our AI system identified important clinical markers that correlated with the NCP lesion properties. Together with the clinical data, our AI system was able to provide accurate clinical prognosis that can aid clinicians to consider appropriate early clinical management and allocate resources appropriately. We have made this AI system available globally to assist the clinicians to combat COVID-19.

Biomedical Research Goes Viral: Dangers and Opportunities.

Researchers around the globe have been mounting, accelerating, and redeploying efforts across disciplines and organizations to tackle the SARS-CoV-2 outbreak. However, humankind continues to be afflicted by numerous other devastating diseases in increasing numbers. Here, we outline considerations and opportunities toward striking a good balance between maintaining and redefining research priorities.

ORF8 and ORF3b antibodies are accurate serological markers of early and late SARS-CoV-2 infection.

The SARS-CoV-2 virus emerged in December 2019 and has caused a worldwide pandemic due to the lack of any pre-existing immunity. Accurate serology testing is urgently needed to help diagnose infection, determine past exposure of populations and assess the response to a future vaccine. The landscape of antibody responses to SARS-CoV-2 is unknown. In this study, we utilized the luciferase immunoprecipitation system to assess the antibody responses to 15 different SARS-CoV-2 antigens in patients with COVID-19. We identified new targets of the immune response to SARS-CoV-2 and show that nucleocapsid, open reading frame (ORF)8 and ORF3b elicit the strongest specific antibody responses. ORF8 and ORF3b antibodies, taken together as a cluster of points, identified 96.5% of COVID-19 samples at early and late time points of disease with 99.5% specificity. Our findings could be used to develop second-generation diagnostic tests to improve serological assays for COVID-19 and are important in understanding pathogenicity.

Single-cell landscape of immunological responses in patients with COVID-19.

In coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, the relationship between disease severity and the host immune response is not fully understood. Here we performed single-cell RNA sequencing in peripheral blood samples of 5 healthy donors and 13 patients with COVID-19, including moderate, severe and convalescent cases. Through determining the transcriptional profiles of immune cells, coupled with assembled T cell receptor and B cell receptor sequences, we analyzed the functional properties of immune cells. Most cell types in patients with COVID-19 showed a strong interferon-α response and an overall acute inflammatory response. Moreover, intensive expansion of highly cytotoxic effector T cell subsets, such as CD4+ effector-GNLY (granulysin), CD8+ effector-GNLY and NKT CD160, was associated with convalescence in moderate patients. In severe patients, the immune landscape featured a deranged interferon response, profound immune exhaustion with skewed T cell receptor repertoire and broad T cell expansion. These findings illustrate the dynamic nature of immune responses during disease progression.

Immunology of COVID-19: Current State of the Science.

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has affected millions of people worldwide, igniting an unprecedented effort from the scientific community to understand the biological underpinning of COVID19 pathophysiology. In this Review, we summarize the current state of knowledge of innate and adaptive immune responses elicited by SARS-CoV-2 infection and the immunological pathways that likely contribute to disease severity and death. We also discuss the rationale and clinical outcome of current therapeutic strategies as well as prospective clinical trials to prevent or treat SARS-CoV-2 infection.

Unbiased Screens Show CD8+ T Cells of COVID-19 Patients Recognize Shared Epitopes in SARS-CoV-2 that Largely Reside outside the Spike Protein.

Developing effective strategies to prevent or treat coronavirus disease 2019 (COVID-19) requires understanding the natural immune response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We used an unbiased, genome-wide screening technology to determine the precise peptide sequences in SARS-CoV-2 that are recognized by the memory CD8+ T cells of COVID-19 patients. In total, we identified 3-8 epitopes for each of the 6 most prevalent human leukocyte antigen (HLA) types. These epitopes were broadly shared across patients and located in regions of the virus that are not subject to mutational variation. Notably, only 3 of the 29 shared epitopes were located in the spike protein, whereas most epitopes were located in ORF1ab or the nucleocapsid protein. We also found that CD8+ T cells generally do not cross-react with epitopes in the four seasonal coronaviruses that cause the common cold. Overall, these findings can inform development of next-generation vaccines that better recapitulate natural CD8+ T cell immunity to SARS-CoV-2.

Orthogonal SARS-CoV-2 Serological Assays Enable Surveillance of Low-Prevalence Communities and Reveal Durable Humoral Immunity.

We conducted a serological study to define correlates of immunity against SARS-CoV-2. Compared to those with mild coronavirus disease 2019 (COVID-19) cases, individuals with severe disease exhibited elevated virus-neutralizing titers and antibodies against the nucleocapsid (N) and the receptor binding domain (RBD) of the spike protein. Age and sex played lesser roles. All cases, including asymptomatic individuals, seroconverted by 2 weeks after PCR confirmation. Spike RBD and S2 and neutralizing antibodies remained detectable through 5-7 months after onset, whereas α-N titers diminished. Testing 5,882 members of the local community revealed only 1 sample with seroreactivity to both RBD and S2 that lacked neutralizing antibodies. This fidelity could not be achieved with either RBD or S2 alone. Thus, inclusion of multiple independent assays improved the accuracy of antibody tests in low-seroprevalence communities and revealed differences in antibody kinetics depending on the antigen. We conclude that neutralizing antibodies are stably produced for at least 5-7 months after SARS-CoV-2 infection.

Acute SARS-CoV-2 Infection Impairs Dendritic Cell and T Cell Responses.

The SARS-CoV-2 pandemic has resulted in millions of infections, yet the role of host immune responses in early COVID-19 pathogenesis remains unclear. By investigating 17 acute and 24 convalescent patients, we found that acute SARS-CoV-2 infection resulted in broad immune cell reduction including T, natural killer, monocyte, and dendritic cells (DCs). DCs were significantly reduced with functional impairment, and ratios of conventional DCs to plasmacytoid DCs were increased among acute severe patients. Besides lymphocytopenia, although neutralizing antibodies were rapidly and abundantly generated in patients, there were delayed receptor binding domain (RBD)- and nucleocapsid protein (NP)-specific T cell responses during the first 3 weeks after symptoms onset. Moreover, acute RBD- and NP-specific T cell responses included relatively more CD4 T cells than CD8 T cells. Our findings provided evidence that impaired DCs, together with timely inverted strong antibody but weak CD8 T cell responses, could contribute to acute COVID-19 pathogenesis and have implications for vaccine development.

Population flow drives spatio-temporal distribution of COVID-19 in China.

Sudden, large-scale and diffuse human migration can amplify localized outbreaks of disease into widespread epidemics1-4. Rapid and accurate tracking of aggregate population flows may therefore be epidemiologically informative. Here we use 11,478,484 counts of mobile phone data from individuals leaving or transiting through the prefecture of Wuhan between 1 January and 24 January 2020 as they moved to 296 prefectures throughout mainland China. First, we document the efficacy of quarantine in ceasing movement. Second, we show that the distribution of population outflow from Wuhan accurately predicts the relative frequency and geographical distribution of infections with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) until 19 February 2020, across mainland China. Third, we develop a spatio-temporal 'risk source' model that leverages population flow data (which operationalize the risk that emanates from epidemic epicentres) not only to forecast the distribution of confirmed cases, but also to identify regions that have a high risk of transmission at an early stage. Fourth, we use this risk source model to statistically derive the geographical spread of COVID-19 and the growth pattern based on the population outflow from Wuhan; the model yields a benchmark trend and an index for assessing the risk of community transmission of COVID-19 over time for different locations. This approach can be used by policy-makers in any nation with available data to make rapid and accurate risk assessments and to plan the allocation of limited resources ahead of ongoing outbreaks.

Virological assessment of hospitalized patients with COVID-2019.

Coronavirus disease 2019 (COVID-19) is an acute infection of the respiratory tract that emerged in late 20191,2. Initial outbreaks in China involved 13.8% of cases with severe courses, and 6.1% of cases with critical courses3. This severe presentation may result from the virus using a virus receptor that is expressed predominantly in the lung2,4; the same receptor tropism is thought to have determined the pathogenicity-but also aided in the control-of severe acute respiratory syndrome (SARS) in 20035. However, there are reports of cases of COVID-19 in which the patient shows mild upper respiratory tract symptoms, which suggests the potential for pre- or oligosymptomatic transmission6-8. There is an urgent need for information on virus replication, immunity and infectivity in specific sites of the body. Here we report a detailed virological analysis of nine cases of COVID-19 that provides proof of active virus replication in tissues of the upper respiratory tract. Pharyngeal virus shedding was very high during the first week of symptoms, with a peak at 7.11 × 108 RNA copies per throat swab on day 4. Infectious virus was readily isolated from samples derived from the throat or lung, but not from stool samples-in spite of high concentrations of virus RNA. Blood and urine samples never yielded virus. Active replication in the throat was confirmed by the presence of viral replicative RNA intermediates in the throat samples. We consistently detected sequence-distinct virus populations in throat and lung samples from one patient, proving independent replication. The shedding of viral RNA from sputum outlasted the end of symptoms. Seroconversion occurred after 7 days in 50% of patients (and by day 14 in all patients), but was not followed by a rapid decline in viral load. COVID-19 can present as a mild illness of the upper respiratory tract. The confirmation of active virus replication in the upper respiratory tract has implications for the containment of COVID-19.

Desorption Separation Ionization Mass Spectrometry (DSI-MS) for Rapid Analysis of COVID-19.

During the coronavirus disease 2019 (COVID-19) pandemic, which has witnessed over 772 million confirmed cases and over 6 million deaths globally, the outbreak of COVID-19 has emerged as a significant medical challenge affecting both affluent and impoverished nations. Therefore, there is an urgent need to explore the disease mechanism and to implement rapid detection methods. To address this, we employed the desorption separation ionization (DSI) device in conjunction with a mass spectrometer for the efficient detection and screening of COVID-19 urine samples. The study encompassed patients with COVID-19, healthy controls (HC), and patients with other types of pneumonia (OP) to evaluate their urine metabolomic profiles. Subsequently, we identified the differentially expressed metabolites in the COVID-19 patients and recognized amino acid metabolism as the predominant metabolic pathway involved. Furthermore, multiple established machine learning algorithms validated the exceptional performance of the metabolites in discriminating the COVID-19 group from healthy subjects, with an area under the curve of 0.932 in the blind test set. This study collectively suggests that the small-molecule metabolites detected from urine using the DSI device allow for rapid screening of COVID-19, taking just three minutes per sample. This approach has the potential to expand our understanding of the pathophysiological mechanisms of COVID-19 and offers a way to rapidly screen patients with COVID-19 through the utilization of machine learning algorithms.

Application value of P-selectin and Clara cell secretory protein 16 expression in children with severe adenovirus pneumonia.

This study investigated the roles of P-selectin and Clara cell secretory protein 16 (CC16) levels in the pathogenesis of severe adenovirus (ADV) pneumonia in children and evaluated their ability to predict disease. Fifty-one children (age, 1-5 years) with ADV pneumonia who were admitted to Xiamen Children's Hospital were included in this study and divided into the mild group (24 patients) and severe group (27 patients). A control group comprising healthy children of the same age who underwent routine physical examinations during the same period (30 patients) was also included. The univariate analysis demonstrated that the levels of the white blood cell count and C-reactive protein, procalcitonin, d-dimer, and P-selectin were increased in a severe group compared with a mild group, while CC16 levels were significantly decreased (p < 0.05). The logistic regression analysis revealed that P-selectin and CC16 levels were independent risk factors for severe ADV pneumonia in children. The areas under the ROC curves suggested that P-selectin and CC16 exhibited high predictive value for severe ADV pneumonia. P-selectin values more than 898.58 pg/mL and CC16 values less than 11.355 ng/mL predicted severe ADV pneumonia. P-selectin and CC16 levels are correlated with the severity of ADV pneumonia in children.

Prognostic significance of plasma cytomegalovirus (CMV) DNA load in immunocompetent patients with CMV pneumonia: A retrospective cohort study.

Cytomegalovirus (CMV) pneumonia, often presented as pneumonitis, is characterized by respiratory failure and large interstitial infiltrates visible on chest radiographs. This retrospective cohort study investigates the predictive significance of plasma CMV DNA load on the short- and long-term mortality among immunocompetent patients diagnosed with CMV pneumonia. The study included 61 immunocompetent patients suspected of having CMV pneumonia, treated with intravenous ganciclovir after positive CMV DNA results from bronchoalveolar lavage or plasma. Our multivariate Cox regression analysis identified several independent predictors of mortality. Having idiopathic pulmonary fibrosis (IPF) significantly increased the risk of in-hospital mortality (HR: 7.27, 95% CI: 1.62-32.52, p = 0.009), as did shorter durations of antiviral therapy (HR: 0.90, 95% CI: 0.84-0.97, p = 0.005) and higher CMV DNA levels (>3870 IU/mL; HR: 9.63, 95% CI: 2.32-39.98, p = 0.002). High CMV DNA levels (>5154 IU/mL) were also predictors of 30-day mortality (HR: 9.39, 95% CI: 2.20-40.01, p = 0.002). For 1-year mortality, the presence of IPF (HR: 2.96, 95% CI: 1.08-8.06, p = 0.034), hypersensitivity pneumonia (HP) (HR: 4.30, 95% CI: 1.57-11.78, p = 0.005), shorter duration of total antiviral therapy (HR: 0.95, 95% CI: 0.93-0.99, p = 0.010), and higher CMV DNA levels (>327 IU/mL) (HR: 3.36, 95% CI: 1.33-8.47, p = 0.010) were identified as independent determinants. The study reveals that IPF increases short and long-term mortality risks, while HP increases long-term mortality. Extended antiviral treatment duration results in a 10% reduction in in-hospital mortality for each additional day of treatment. Furthermore, elevated viral loads are associated with higher mortality rates, highlighting the necessity for careful monitoring.

Value of a secretomic approach for distinguishing patients with COVID-19 viral pneumonia among patients with respiratory distress admitted to intensive care unit.

In intensive care units, COVID-19 viral pneumonia patients (VPP) present symptoms similar to those of other patients with Nonviral infection (NV-ICU). To better manage VPP, it is therefore interesting to better understand the molecular pathophysiology of viral pneumonia and to search for biomarkers that may clarify the diagnosis. The secretome being a set of proteins secreted by cells in response to stimuli represents an opportunity to discover new biomarkers. The objective of this study is to identify the secretomic signatures of VPP with those of NV-ICU. Plasma samples and clinical data from NV-ICU (n = 104), VPP (n = 30) or healthy donors (HD, n = 20) were collected at Nantes Hospital (France) upon admission. Samples were enriched for the low-abundant proteins and analyzed using nontarget mass spectrometry. Specifically deregulated proteins (DEP) in VPP versus NV-ICU were selected. Combinations of 2 to 4 DEPs were established. The differences in secretome profiles of the VPP and NV-ICU groups were highlighted. Forty-one DEPs were specifically identified in VPP compared to NV-ICU. We describe five of the best combinations of 3 proteins (complement component C9, Ficolin-3, Galectin-3-binding protein, Fibrinogen alpha, gamma and beta chain, Proteoglycan 4, Coagulation factor IX and Cdc42 effector protein 4) that show a characteristic receptor function curve with an area under the curve of 95.0%. This study identifies five combinations of candidate biomarkers in VPP compared to NV-ICU that may help distinguish the underlying causal molecular alterations.

Cytomegalovirus pneumonia with intermittent pulmonary hemorrhage leading to asphyxia death: a case report and literature review.

Neonatal pulmonary hemorrhage is a late manifestation of various diseases. Premature delivery and low body weight are frequently observed as high-risk factors, characterized by acute onset, rapid progression, and high mortality rates. Pulmonary hemorrhage caused by cytomegalovirus infection in newborns with normal immune function is a rare occurrence. This case report focuses on a term neonate with normal birth weight who presented solely with nasal obstruction shortly after birth. However, 4 days after birth, the newborn experienced a sudden onset of blood gushing from both the mouth and nasal cavity. The patient was diagnosed with gastrointestinal bleeding, neonatal pneumonia and neonatal lung consolidation. And he was discharged after ten days of symptomatic treatment. However, upon returning home, the patient experienced a sudden onset of bleeding from the mouth and nose, leading to his untimely demise. Subsequent autopsy revealed the presence of pulmonary hemorrhage in newborn, which presented as interstitial pneumonia. The cause of pulmonary hemorrhage is cytomegalovirus infection. This case emphasizes the importance of pediatricians enhancing their skills in differentiating pulmonary hemorrhage, especially from cytomegalovirus pneumonia.

Prolonged viral pneumonia and high mortality in COVID-19 patients on anti-CD20 monoclonal antibody therapy.

PURPOSE: In clinical practice, we observed an apparent overrepresentation of COVID-19 patients on anti-CD20 monoclonal antibody therapy. The aim of this study was to characterize the clinical picture of COVID-19 in these patients. METHODS: All adult patients from Turku University Hospital, Turku, Finland, with COVID-19 diagnosis and/or positive SARS-CoV-2 PCR test result up to March 2023, and with anti-CD20 therapy within 12 months before COVID-19 were included. Data was retrospectively obtained from electronic patient records. RESULTS: Ninety-eight patients were identified. 44/93 patients (47.3%) were hospitalized due to COVID-19. Patients with demyelinating disorder (n = 20) were youngest (median age 36.5 years, interquartile range 33-45 years), had less comorbidities, and were least likely to be hospitalized (2/20; 10.0%) or die (n = 0). COVID-19 mortality was 13.3% in the whole group, with age and male sex as independent risk factors. Persistent symptoms were documented in 33/94 patients (35.1%) alive by day 30, in 21/89 patients (23.6%) after 60 days, and in 15/85 after 90 days (17.6%), mostly in patients with haematological malignancy or connective tissue disease. Prolonged symptoms after 60 days predisposed to persistent radiological findings (odds ratio 64.0; 95% confidence interval 6.3-711; p < 0.0001) and persistently positive PCR (odds ratio 45.5, 95% confidence interval 4.0-535; p < 0.0001). Several patients displayed rapid response to late antiviral therapy. CONCLUSION: Anti-CD20 monoclonal antibody therapy is associated with high COVID-19 mortality and with a phenotype consistent with prolonged viral pneumonia. Our study provides rationale for retesting of immunocompromised patients with prolonged COVID-19 symptoms and considering antiviral therapy.

Biomarkers: Are They Useful in Severe Community-Acquired Pneumonia?

Community acquired pneumonia (CAP) is a prevalent infectious disease often requiring hospitalization, although its diagnosis remains challenging as there is no gold standard test. In severe CAP, clinical and radiologic criteria have poor sensitivity and specificity, and microbiologic documentation is usually delayed and obtained in less than half of sCAP patients. Biomarkers could be an alternative for diagnosis, treatment monitoring and establish resolution. Beyond the existing evidence about biomarkers as an adjunct diagnostic tool, most evidence comes from studies including CAP patients in primary care or emergency departments, and not only sCAP patients. Ideally, biomarkers used in combination with signs, symptoms, and radiological findings can improve clinical judgment to confirm or rule out CAP diagnosis, and may be valuable adjunctive tools for risk stratification, differentiate viral pneumonia and monitoring the course of CAP. While no single biomarker has emerged as an ideal one, CRP and PCT have gathered the most evidence. Overall, biomarkers offer valuable information and can enhance clinical decision-making in the management of CAP, but further research and validation are needed to establish their optimal use and clinical utility.

Viral Pneumonia: From Influenza to COVID-19.

Respiratory viruses are increasingly recognized as a cause of community-acquired pneumonia (CAP). The implementation of new diagnostic technologies has facilitated their identification, especially in vulnerable population such as immunocompromised and elderly patients and those with severe cases of pneumonia. In terms of severity and outcomes, viral pneumonia caused by influenza viruses appears similar to that caused by non-influenza viruses. Although several respiratory viruses may cause CAP, antiviral therapy is available only in cases of CAP caused by influenza virus or respiratory syncytial virus. Currently, evidence-based supportive care is key to managing severe viral pneumonia. We discuss the evidence surrounding epidemiology, diagnosis, management, treatment, and prevention of viral pneumonia.

Exploratory analysis of serum Krebs von den Lungen-6, blood gas analysis & Brixia score in determining COVID-19 severity & mortality.

Background & objectives Krebs von den Lungen-6 (KL-6) is primarily expressed by the damaged type II pneumocytes. In this context, the relationship of KL-6 with blood gas analysis (BGA) parameters and Brixia score is still limitedly discussed. This study aims to analyze the correlation of KL-6, BGA and Brixia scores to the severity and mortality of COVID-19. Methods A cross-sectional study was conducted in adult COVID-19 positive individuals at Universitas Airlangga Hospital, Surabaya, East Java, Indonesia, from March to August 2021. KL-6, BGA, and Brixia scores were compared according to severity (severe vs. non-severe) and mortality (non-survivor vs. survivor). The receiver operating characteristic (ROC) analysis was also performed to define the optimal cut-off, sensitivity, as well as the specificity of KL-6, BGA and Brixia scores to determine the COVID-19 severity and mortality. Results Total 35 severe and 20 non-severe COVID-19 positive individuals were enrolled in this study. Of those, there were 22 non-survivors. No significant difference in serum KL-6 levels was observed in the severity and mortality groups. KL-6 and HCO3- had positive correlation in the severe group (r=0.37). KL-6 and Brixia scores showed a significant negative correlation among COVID-19 positive individuals (r=-0.283; P=0.036). KL-6 and Brixia scores together served as the best severity markers in the current study [AUC 0.809 (0.697-0.920); Sn/Sp=0.686/0.900)], followed by KL-6 and P/F ratio [AUC 0.800 (0.637-0.963); Sn/Sp=0.971/0.750]. Interpretation & conclusions The findings of this study suggest that KL-6 has the potential to be a useful adjunct laboratory parameter to the BGA and Brixia score representing COVID-19 severity and mortality.