The COVID-19 pandemic has raised concerns about potential links between SARS-CoV-2 infection and autoimmune diseases. This study investigated changes in the incidence rate (IR) of autoimmune diseases among children following the pandemic's onset.

A retrospective cross-sectional study analyzed data from Clalit Health Services, Israel's largest healthcare provider, examining the IR of different autoimmune diseases in children aged 0-18. The study compared pre-pandemic (2019) with pandemic/post-pandemic periods (2020-2023), encompassing a cohort of over 1.5 million children.

Significant IR increases were observed across multiple autoimmune diseases. Rheumatic diseases (Juvenile Idiopathic Arthritis, Systemic Lupus Erythematosus, Henoch Schoenlein Purpura (HSP)) showed consistent increases, with HSP demonstrating the most pronounced trend. Endocrine disorders exhibited diverse patterns, with autoimmune thyroid diseases and Type 1 diabetes showing overall increases, while diabetic ketoacidosis exhibited an initial spike followed by a decline. Gastrointestinal diseases displayed heterogeneous patterns; Celiac disease and Ulcerative colitis showed general increases, Crohn's disease showed a downward trend, and autoimmune hepatitis exhibited an initial significant decrease followed by a significant increase. Dermatological conditions, including Psoriasis and Vitiligo, demonstrated consistent elevations throughout 2020-2023. Immune Thrombocytopenia Purpura showed initial decreases followed by significant increases in 2022-2023.

This comprehensive analysis reveals significant changes in pediatric autoimmune disease incidence following the COVID-19 pandemic, suggesting potential associations between SARS-CoV-2 infection and autoimmune dysregulation. The diverse patterns observed across different conditions highlight the complex interplay between viral infection and autoimmunity, emphasizing the need for continued surveillance and investigation of long-term immunological consequences of COVID-19 in pediatric populations.

Traditional Chinese medicine has been recognized for its significant role in treating acute lung injury (ALI) due to its distinct therapeutic advantages. Liang-Ge-San (LGS), a formulation from the ancient "Taiping Huimin Hejiju Fang", is believed to possess beneficial effects for treating ALI. However, LGS's precise mechanisms and efficacy in addressing viral ALI remain inadequately explored.

To evaluate LGS's therapeutic effects and underlying mechanisms in treating viral-induced ALI.

The protective effects of LGS were examined in a Polyinosinic-polycytidylic acid [Poly(I:C)]-induced ALI model using real-time quantitative PCR, enzyme-linked immunosorbent assay, and histopathological analysis. A bioinformatics approach combined with network pharmacology was utilized to ascertain the key targets of LGS in viral pneumonia. The pharmacodynamic mechanisms of LGS in viral ALI were further validated through immunofluorescence, overexpression, short hairpin RNA, chromatin immunoprecipitation, and target agonist assays.

LGS administration resulted in a reduction of IL-1β, IL-6, and TNF-α levels, along with a decrease in macrophage infiltration, pulmonary damage, and pneumonedema following the Poly(I:C) challenge. Bioinformatics and network pharmacology analyses suggested that Farnesyl X receptor (FXR) and angiotensin converting enzyme 2 (ACE2) are potential therapeutic targets for LGS in viral pneumonia. Further experiments revealed that LGS suppressed the expression of FXR, ACE2, and NF-κB-p65 in Poly(I:C)-infected cells. Notably, overexpression of FXR counteracted the repressive effects of LGS, while ACE2 expression remained unchanged in FXR-knockdown RAW264.7 cells upon treatment with Poly(I:C) or LGS. Additionally, LGS inhibited the interaction between FXR and ACE2 transcriptional promoters. In vivo, LGS attenuated the Poly(I:C)-induced upregulation of FXR, ACE2, IL-1β, IL-6, and TNF-α in ALI zebrafish and mice models, effects that could be reversed by chenodeoxycholic acid (CDCA), an FXR agonist. Moreover, LGS markedly alleviated weight loss, improved survival rates, reduced lung index, diminished viral load, and inhibited lung pathological changes in H1N1-PR8-induced ALI mice. IL-1β, IL-6, TNF-α, INF-γ, FXR, ACE2, small heterodimer partner, and NF-κB-p65 levels were markedly reduced by LGS, with these effects being reversed by CDCA.

This investigation provides the first evidence that FXR/ACE2 signaling is pivotal in acute respiratory viral infections, while LGS demonstrates antiviral activity against viral-induced ALI. LGS inhibits ACE2 expression induced by viral infection via FXR inhibition and modulates the cytokine storm, thus alleviating viral ALI. These findings suggest that LGS may be a promising treatment strategy for treating viral ALI.

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has led to a significant burden on global healthcare systems. COVID-19-induced acute kidney injury (AKI) is among one of the complications, that has emerged as a critical and frequent condition in COVID-19 patients. This AKI among COVID-19 patients is associated with poor outcomes, and high mortality rates, especially in those with severe AKI or requiring renal replacement therapy. COVID-19-induced AKI represents a significant complication with complex pathophysiology and multifactorial risk factors. Indeed, several pathophysiological mechanisms, including direct viral invasion of renal cells, systemic inflammation, endothelial and thrombotic abnormalities as well as nephrotoxic drugs and rhabdomyolysis are believed to underlie this condition. Moreover, histopathological and immunohistopathological findings commonly observed in postmortem studies include acute tubular necrosis, glomerular injury, and the presence of viral particles within renal tissue and urine. Identified risk factors for developing AKI vary among studies, depending on regions, underlying conditions, and the severity of the disease. Moreover, histopathological and immunohistopathological findings commonly observed in postmortem studies include show acute tubular necrosis, glomerular injury, and viral particles within renal tissue and urine. While, identified risk factors for developing AKI vary among studies, according to regions, underlying conditions, and the gravity of the disease. This narrative review aims to synthesize current knowledge on the incidence, pathophysiology, risk factors, histopathology, and outcomes of AKI induced by COVID-19.

Severe COVID-19 is often complicated by hypoxemic respiratory failure and acute respiratory distress syndrome (ARDS). Mechanisms governing lung injury and repair in ARDS remain poorly understood. We hypothesized that plasma proteomics may uncover protein biomarkers correlated with COVID-19 ARDS severity. We analyzed the plasma proteome from 32 patients with ARDS and COVID-19 using an aptamer-based platform of 7289 proteins, and correlated protein measurements with sequential organ failure assessment (SOFA) scores at days 1 and 7 of ICU admission. We identified 184 differentially abundant proteins correlated with SOFA at day 1 and 46 proteins at day 7. In a longitudinal analysis, we correlated dynamic changes in protein abundance and SOFA between days 1 and 7 and identified 40 significant proteins. Pathway analysis of significant proteins identified increased ephrin signaling and acute phase response signaling correlated with increased SOFA scores between days 1 and 7, while pathways related to pulmonary fibrosis signaling and wound healing had a negative correlation. These findings suggest that persistent inflammation may drive disease severity, while repair processes correlate with improvements in organ dysfunction. This approach is generalizable to future ARDS cohorts for identification of biomarkers and disease mechanisms as we strive towards targeted therapies in ARDS.

The clinical spectrum of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is broad; it can range from asymptomatic cases to mild upper respiratory tract illness, respiratory failure, and severe multiorgan failure resulting in death. Therefore, it is important to identify the clinical course of the disease and the factors associated with mortality.

The aim of this study is to identify the risk factors associated with the severity of the disease, intensive care unit admission, and mortality in COVID-19 patients.

A total of 1075 patients with clinical and radiological findings compatible with COVID-19 pneumonia and positive SARS-CoV-2 PCR were selected and retrospectively screened. All included patients were classified according to the 7th edition of the 2019 Coronavirus Disease Guidelines published by the National Health Commission of China.

It was observed that elevated white blood count (WBC) increased the severity of COVID-19 by 3.26 times and the risk of intensive care unit (ICU) admission by 3.47 times. Patients with high D-dimer levels had a 91% increased risk, and those with high fibrinogen levels had a 2.08 times higher risk of severe disease. High C-reactive protein (CRP) values were found to increase disease severity by 6.89 times, mortality by 12.84 times, and ICU admission by 3.37 times.

Identifying the factors associated with disease severity, ICU admission, and mortality in COVID-19 patients could help reduce disability and mortality rates in pandemics.

The global pandemic of novel coronavirus pneumonia (COVID-19) has resulted in millions of deaths over the past three years. As one of the most commonly affected extra-pulmonary organs, numerous studies have reported varying degrees of liver injury in a significant proportion of patients with COVID-19, particularly in severe and critically ill patients. Early prediction of liver dysfunction in hospitalized patients would facilitate the clinical management of COVID-19 and improve clinical prognosis, but reliable and valid predictive models are still lacking.MethodsWe collected data from 286 patients with RT-PCR confirmed COVID-19 admitted to various ICUs from the case system. These patients were randomly divided into a training cohort (50%) and a validation cohort (50%). In the training cohort, we first used ROC curves to measure the predictive efficiency of each of the variables for the development of liver damage during hospitalization in patients with COVID-19, followed by LASSO regression analysis to screen the variables for predictive models and logistic regression analysis to identify relevant risk factors. A nomogram based on these variables was created following the above model. Finally, the efficiency of the prediction models in the training and validation cohorts was assessed using AUC, consistency index (C index), calibration curves and Decision Curve Analysis.ResultsOut of a total of 80 parameters for COVID-19 patients admitted to the ICUs, 10 were determined to be significantly associated with the occurrence of liver dysfunction during hospitalization. Based on these predictors, further prediction models were used to construct and develop a nomogram that was offered for practical clinical application. The C-index of the column line graphs for the training and validation cohorts was 0.956 and 0.844 respectively. in addition, the calibration curves for the model showed a high degree of agreement between the predicted and actual incidence of liver dysfunction in patients with COVID-19.ConclusionBy developing a predictive model and associated nomogram, we predicted the incidence of liver dysfunction during hospitalization in patients with COVID-19 in the ICU. The model's predictive performance was determined in both the training and validation cohorts, contributing to the clinical management of COVID-19.

Regulatory T cells (Tregs) play a crucial role in maintaining immune tolerance by suppressing immune responses against pathogens. The fluctuation of Treg proportions in COVID-19 remains a topic of debate, and the mechanisms triggering Treg activation in COVID-19 are still unclear. Understanding these issues is essential for better managing immune responses in COVID-19 patients.

We collected a cohort of COVID-19 patients with varying disease severity and stage to explore the transcriptomic and functional traits of Tregs in these individuals. Using transcriptomic analysis, we evaluated the proportion and functionality of different Treg subsets, specifically HLA_DR+ Tregs, across different stages of COVID-19 patients.

Our analysis revealed that the proportion of CCR7 + Tregs decreased as the disease advanced, while the cell proportion of HLA_DR+ regs escalated with the severity of the disease. Moreover, the transcription actor CARHSP1 exhibited apositive correlation with the proportion of HLA_DR+ Tregs. Notably, the heightened suppressive function of HLA_DR+ Tregs in severe COVID-19 patients, with interactions between PF4 and CXCR3, contributed to the homeostasis of HLA_DR+ Tregs in severe COVID-19 patients. Furthermore, we observed that Tregs in COVID-19 patients exhibited weakened TCR clonotype expansion, and the suppression of HLA_DR+ Tregs with expanded TCR clonotypes in severe COVID-19 cases did not show a significant increase compared to asymptomatic and mild COVID-19 groups. The findings indicate that Tregs may be activated through the bystander effect, as evidenced by the analysis of TCR clonotype characteristics.

Our research delineates the diversity of dynamic alterations in Tregs and sheds light on potential mechanisms underlying Treg activation, providing a theoretical foundation and offering treatment strategies for managing COVID-19 patients.

The base excision repair pathway protects DNA from base damage via oxidation, deamination, alkylation and methylation. DNA glycosylases are key enzymes that recognize damaged bases in a lesion-specific manner and initiate the base excision repair process. Among these, the endonuclease VIII-like 1-3 (NEIL1-3) family, which is found in mammalian genomes, is a homolog of bacterial DNA glycosylases known as Fpg/Nei. NEIL enzymes have similar structures and substrates but with slight differences. When repair proteins are impaired, the accumulation of damaged bases can lead to increased genomic instability, which is implicated in various pathologies, including cancer and neurodegeneration. Notably, mutations in these proteins also influence a range of other diseases and inflammation. This review focuses on the influence of the NEIL family on human health across different organ systems. Investigating the relationship between NEIL mutations and diseases can improve our understanding of how these enzymes affect the human body. This information is crucial for understanding the basic mechanisms of DNA repair and enabling the development of novel inhibitors or gene therapies that target only these enzymes. Understanding the role of the NEIL family provides insights into novel therapies and improves our ability to combat genetic diseases.

Coronaviruses are a large group of viruses that infect animals as well as humans, while it is also suggested that, rarely, coronaviruses that infect animals can evolve and infect humans. Current evidence suggests that severe acute respiratory syndrome (SARS) coronavirus-2 leads to coronavirus disease-19 (COVID-19), the respiratory illness responsible for COVID-19 pandemic, while it has a zoonotic origin, closely related to the bat-origin SARS-like coronavirus. Also, as per the current knowledge, the disease may induce significant and persistent lymphopenia which in turn may increase the risk for various opportunistic infections. Cryptococcus laurentii is one such rare, but serious fungal infection which has been reported in post-COVID-19 disease and is a rising cause of concern since it can turn out to be fatal. The infection is caused by a non-neoformans rare human pathogen. The present case report describes the case of a 45-years old male patient who reported to the Outpatient Department (OPD) for a routine dental complaint with a grossly destructed tooth in left lower back tooth region due to extensive carious involvement, while, simultaneously, presenting with fever since 5 days in the post-COVID-19 phase, and was later diagnosed as being positive for C. laurentii infection on urine culture sensitivity test.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19, can induce trained immunity in monocytes. Trained immunity is the result of metabolic and epigenetic reprogramming of progenitor cells leading to an altered inflammatory response to subsequent activation. To investigate the monocyte response 3-6 months post SARS-CoV-2 infection, steady-state gene expression and innate immune receptor stimulation were investigated in monocytes from unvaccinated SARS-CoV-2 naïve individuals and convalescent COVID-19 participants. The differentially expressed genes (DEGs) identified were involved in the regulation of innate immune signalling pathways associated with anti-viral defence. COVID-19 participants who had experienced severe symptoms exhibited a larger number of DEGs than participants that had mild symptoms. Interestingly, genes encoding receptors that recognise SARS-CoV-2 RNA were downregulated. DDX58, encoding retinoic-acid inducible gene I (RIG-I), was downregulated which corresponded with a reduced response to RIG-I activation. Furthermore, toll-like receptor (TLR)1/2 and TLR4 activation also exhibited reduced cytokine secretion from convalescent COVID-19 monocytes. These data suggest that following SARS-CoV-2 infection, monocytes exhibit altered steady-state gene expression and reduced responsiveness to innate immune receptor activation. As both RIG-I and TLRs recognise components of SARS-CoV-2, this may lead to a moderated inflammatory response to SARS-CoV-2 reinfection in the months following the initial infection.

Coronavirus disease-2019 (COVID-19) can cause not only respiratory symptoms but also facial paralysis. Lianhua Qingwen (LHQW) has been reported to have therapeutic effects on COVID-19 and facial neuritis (FN). We explored the potential mechanism of LHQW in the treatment of COVID-19 and FN through a network-pharmacology approach.

Active compounds and relevant targets of LHQW were obtained from the databases of Traditional Chinese Medicine Systems Pharmacology Database, HERB, UniProt Knowledge Base, SwissADME, and Swiss Target Prediction. Disease targets of COVID-19 and FN were acquired from Gene Cards. Database For Annotation, Visualization And Integrated Discovery and Metascape were used to search the biological functions of intersecting targets. After identifying the core targets and their corresponding ingredients, KEGG Mapper analyzes the localization of core targets in key pathways. AutoDock were employed to conduct molecular docking of the core targets and their corresponding ingredients.

We obtained four core genes: interleukin (IL)-8, IL-1B, IL-6, and tumor necrosis factor (TNF)-α. Database searching revealed the anti-inflammatory and antiviral effects of LHQW may be related to the action of aleo-emodin, hyperforin, kaempferol, luteolin, and quercetin on these four genes by regulating the pathways of IL-17 and NOD-like receptor. The molecular-docking results of the four core targets and their corresponding active ingredients showed good binding activity between receptors and ligands.

We uncovered the active ingredients, potential targets, and biological pathways of LHQW for COVID-19 and FN coinfection. Our data provide a theoretical basis for further exploration of the mechanism of action of LHQW in treatment of COVID-19 and FN.

The novel coronavirus SARS-CoV-2, which wrecked havoc around the world in the recent years through COVID-19, gains entry into the host cell through various receptors. Development of therapies targeting host-pathogen interaction will be a key to curb the infection as it potentially suppresses viral attachment and entry into the host. Boundless bioactives abundant in natural resources are the important source of new as well as safer alternatives. Tannic acid, a polyphenolic compound found abundantly in various plant sources, has gained much attention owing to its multifaceted pharmacological properties. This research paper presents a comprehensive investigation on antioxidant, anti-inflammatory and anti-viral abilities of tannic acid, substantiated through a triad of methodologies: in silico, in vitro and in vivo approaches. In vitro experiments, confirmed the antioxidant and anti-inflammatory efficacy as well as the host receptor modulating potential of tannic acid. In silico docking analyses elucidated the molecular interactions between tannic acid and key host receptors involved in inflammation and viral pathogenesis. Furthermore, the in vivo studies involving Danio rerio provided a holistic understanding of the systemic impact of tannic acid, including its antioxidant effects by mitigating the oxidative stress.

Comorbidities, such as obesity, increase the risk of severe COVID-19. However, the mechanisms underlying severe illnesses in individuals with obesity are poorly understood. Here, we used gene-edited leptin knock out (Leptin -/-) obese hamsters to establish a severe infection model. This model exhibits robust viral replication, severe lung lesions, pronounced clinical symptoms, and fatal infection, mirroring severe COVID-19 in patients with obesity. Using single-cell transcriptomics on lung tissues pre- and post-infection, we found that monocyte-derived alveolar macrophages (MD-AM) play a key role in lung hyper-inflammation, including two unique MD-AM cell fate branches specific to Leptin -/- hamsters. Notably, reduced Trem2-dependent efferocytosis pathways in Leptin -/- hamsters indicated weakened inflammation resolution, consistent with the scRNA-seq data from patients with obesity. In summary, our study highlights the obesity-associated mechanisms underlying severe SARS-CoV-2 infections and establishes a reliable preclinical animal model for developing obesity-specific therapeutics for critical COVID-19.

The COVID-19 disease has spread rapidly across the world within just six months, affecting 169 million people and causing 3.5 million deaths globally (2021). The most affected countries include the USA, Brazil, India, and several European countries such as the UK and Russia. Healthcare professionals face new challenges in finding better ways to manage patients and save lives. In this regard, more comprehensive research is needed, including genomic and proteomic studies, personalized medicines and the design of suitable treatments. However, finding novel molecular entities (NME) using a standard or de novo strategy to drug development is a time-consuming and costly process. Another alternate strategy is discovering new therapeutic uses for old/existing/available medications, known as drug repurposing. There are a variety of computational repurposing methodologies, and some of them have been used to counter the coronavirus disease pandemic of 2019 (COVID-19). This review article compiles recently published data on the origin, transmission, pathogenesis, diagnosis, and management of the coronavirus by drug repurposing and vaccine development approach. We have attempted to screen probable drugs in clinical trials by using literature survey. This systematic review aims to create priorities for future research of drugs repurposed and vaccine development for COVID-19.

Background/Objectives: Corona virus disease 2019 (COVID-19) poses a threat to global public health. The early identification of critical cases is crucial to providing timely treatment to patients. Here, we investigated whether the neutrophil levels could predict COVID-19 complications. Methods: We performed a retrospective study of patients with COVID-19, admitted to the Cheikh Khalifa International University Hospital, Casablanca, Morocco. Laboratory test results collected upon admission and during hospitalization were analyzed based on clinical information. Results: Our study revealed that a rise in neutrophil "PNN" levels was associated with respiratory deterioration and intubation. They were positively correlated with the procalcitonin and C-reactive protein levels. Interestingly, PNN (polynuclear neutrophil) levels on day 5 proved to be a better predictor of intubation, acute respiratory distress syndrome (ARDS), and mortality than the initial PNN counts, C-reactive protein, or procalcitonin. Moreover, binary logistic regression with stratified PNN-day 5 data revealed that a PNN level on day 5 > 7.7 (109/L) was an independent risk factor for mortality and ARDS. Finally, the PNN levels on day 5 and proinflammatory cytokine IL-6 were positively correlated. Conclusions: Our data showed that neutrophilia proved to be an excellent predictor of complications and mortality during hospitalization and could be used to improve the management of patients with COVID-19.

Coronavirus 2019 (COVID-19) infection has a significant mortality rate. Despite the disease's extensive effects, little is known about the prognostic indicators that can be used. We aimed to assess the prognostic value of neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-C-reactive protein ratio (LCR) and platelet-to- lymphocyte ratio (PLR) in predicting mortality of intensive care unit (ICU) patients. Demographic data, underlying diseases, laboratory parameters were evaluated. The study included 222 cases. The mortality rate was 57.65%. No significant differences in terms of sex, age, or underlying disease were observed between the two groups with and without mortality. Obesity, oxygen therapy, invasive mechanical ventilation (IMV) rates and high SOFA (Sequential Organ Failure Assessment) scores were found to be significantly higher in the group with a mortal course. The mortality rate was significantly higher in patients with lung involvement over 50%, with a low lymphocyte count at ICU admission. In this patient group, NLR was found to be higher, and LCR was found to be lower (P = .001). Although there was no significant difference in PLR between the two groups in univariate analysis, multivariate analysis revealed that PLR was independently associated with mortality. High NLR and low LCR values at ICU admission might serve as early warning signs for healthcare providers, allowing them to identify patients at higher risk of mortality.

Identification of distinct clinical phenotypes of diseases can guide personalized treatment. This study aimed to classify hospitalized COVID-19 pneumonia subgroups using an unsupervised machine learning approach.

We included hospitalized COVID-19 pneumonia patients from July to September 2021. K-means clustering, an unsupervised machine learning method, was performed to identify clinical phenotypes based on clinical and laboratory variables collected within 24 hours of admission. Variables were normalized before clustering to ensure equal contribution to the analysis. The optimal number of clusters was determined using the elbow method and Silhouette scores. Cox proportional hazard models were used to compare the risk of intubation and 90-day mortality across the identified clusters.

Three clinically distinct clusters were identified among 538 hospitalized COVID-19 pneumonia patients. Cluster 1 (N = 27) consisted predominantly of males and showed significantly elevated serum liver enzymes and LDH levels. Cluster 2 (N = 370) was characterized by lower chest x-ray scores and higher serum albumin levels. Cluster 3 (N = 141) was characterized by older age, diabetes mellitus, higher chest x-ray scores, more severe vital signs, higher creatinine levels, lower hemoglobin levels, lower lymphocyte counts, higher C-reactive protein, higher D-dimer, and higher LDH levels. When compared to cluster 2, cluster 3 was significantly associated with increased risk of 90-day mortality (HR, 6.24; 95% CI, 2.42-16.09) and intubation (HR, 5.26; 95% CI 2.37-11.72). In contrast, cluster 1 had a 100% survival rate with a non-significant increase in intubation risk compared to cluster 2 (HR, 1.40, 95% CI, 0.18-11.04).

We identified three distinct clinical phenotypes of COVID-19 pneumonia patients, with cluster 3 associated with an increased risk of respiratory failure and mortality. These findings may guide tailored clinical management strategies.

The infection with SARS-CoV-2, primarily recognized for its respiratory effects, reveals itself as a multifaceted clinical phenomenon, extending beyond the pulmonary realm. Accompanied by gastrointestinal, neurological, thromboembolic, cardiovascular, and immune-related manifestations, the complexity of the systemic repercussions of the disease becomes apparent. Genetic predisposition is a significant factor in the development of autoimmune hepatitis, as both viruses, such as SARS-CoV-2, and drugs, including vaccines, can act as triggers in genetically susceptible individuals. A profound understanding of these mechanisms is essential to effectively address the clinical complexity of SARS-CoV-2 infection.

COVID-19 remains widespread and poses a threat to people's physical and mental health, especially middle-aged and elderly individuals. Early identification of COVID-19 patients at high risk of progressing to critical disease helps improve overall patient outcomes and healthcare efficiency.

To develop a radiomics nomogram to predict the risk of newly admitted middle-aged and elderly COVID-19 patients progressing to critical disease.

A total of 794 patients (aged 40 years or above) were retrospectively included in the study from two institutions, all of them were with non-critical COVID-19 on admission. At follow-up, patients were divided into non-critical group and critical group. About 443 patients (384 non-critical and 59 critical) from the first hospital were randomly assigned to the training (n = 311) and internal validation (n = 132) set in a 7:3 ratio. Additionally, an independent external cohort of 351 patients (292 non-critical and 59 critical) from another hospital was evaluated. Radiomics signatures and clinical indicators were used to build a radiomics model and a clinical model after computed tomography (CT) image processing, CT whole-lung segmentation, feature extraction, and feature selection. The radiomics nomogram model integrated radiomics model and clinical model. The receiver operating characteristic curve (AUC) was used to assess the performance of the proposed models. Calibration curves and decision curve analysis were used to assess the performance of the radiomics nomogram.

For the training, internal validation, and external validation sets, the AUC values of the radiomic nomogram for the prediction of COVID-19 progression were 0.916, 0.917, and 0.890, respectively. Calibration curves indicated that there was no significant departure between prediction and observation in three sets. The decision curve image demonstrated the clinical utility of the nomogram model.

Our nomogram model incorporates radiomics features and clinical indicators, it provides a new pathway to increase predictive accuracy or clinical utility, further helping to provide personalized management for middle-aged and elderly patients with COVID-19.

Numerous hematological abnormalities have been documented in COVID-19 patients. We conducted an analysis of 82 articles from PubMed, focusing on the hematological characteristics observed in survivors (S) and non-survivors (NS) with moderate and severe COVID-19 symptoms, respectively. Our review underlines neutrophilia, lymphopenia, and thrombocytopenia as hallmark features of the disease. In severe cases, blood cell microscopy revealed the following abnormalities: i) an increased number of neutrophils, often displaying granularity, toxic granulation, and vacuolization; ii) lymphocytes with a notably blue cytoplasm; iii) several monocytes that contain vacuoles; iv) platelet aggregation; and v) basophilic stippling in red blood cells. Furthermore, scattergram analysis of COVID-19 patients revealed two common features: i) an increased neutrophil population and ii) the presence of a distinctive "sandglass pattern". This review underscores the critical role of hematochemical and cytomorphological blood cell analysis in COVID-19 patients, aiding clinicians in better recognizing and understanding the indicators of disease severity.

In recent years, the novel coronavirus infectious disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has led to over 670 million infections and nearly 7 million deaths worldwide. The global pandemic of COVID-19 has precipitated a significant public health crisis. The prevalence of liver function abnormalities associated with SARS-CoV-2 is as high as 53% among healthy individuals or patients with autoimmune hepatitis (AIH) and shows a positive correlation with disease severity; moreover, specific adaptive immune responses can influence the trajectory and outcomes of COVID-19. For instance, SARS-CoV-2 may impact autoimmunity through mechanisms such as excessive stimulation of immune responses and molecular mimicry, particularly in genetically predisposed individuals. Currently, the overall mutational trend of SARS-CoV-2 indicates heightened infectivity and immune evasion capabilities. Consequently, vaccination remains crucial for universal protection against this disease. Nevertheless, alongside the widespread implementation of vaccination programs globally, an increasing number of cases have been documented where COVID-19 vaccination appears to trigger new-onset autoimmune hepatitis; yet definitive evidence is still pending elucidation regarding causality. In this review, we analyse the clinical-immunological characteristics, risks associated with severe disease progression, and prognosis for AIH patients infected with SARS-CoV-2; discuss the detrimental effects exerted by SARS-CoV-2 on hepatic function; summarise the mechanisms and attributes leading to new-onset AIH; as well as provide insights into how vaccination may interfere with autoimmunity processes. We continue to underscore the significance of vaccination while aiming to enhance awareness concerning potential risks associated with it-this could facilitate better management strategies for autoimmune diseases along with appropriate adjustments in vaccination protocols. Although the precise triggering mechanism linking COVID-19-related events to AIH remains unclear, existing evidence suggests that this relationship is far from coincidental.

A 63-year-old male with a history of hypertension had contracted Coronavirus Disease-2019 (COVID-19) five days before visiting our hospital and was recovering at home. He was brought to the hospital for emergency care because of bilateral leg pain, diarrhea, and shortness of breath. On arrival to the hospital, the patient was already suffering from multiple organ failure and was admitted to the intensive care unit. Streptococcus dysgalactiae subsp. equisimilis (SDSE) was detected in blood and sputum cultures, and we started antimicrobial therapy for septic shock/streptococcal toxic shock syndrome. However, multiple organ failure progressed, and the patient died one day after admission. This case suggests the possibility of immunosuppression due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The patient had no history of immunodeficiency, and COVID-19 may have contributed to the poor outcome. COVID-19 combined with SDSE sepsis has not been previously reported. Therefore, this case was considered rare.

Invasive aspergillosis (IA) is a fungal infection, which has traditionally been associated with neutropenia and immunosuppressive therapies. Our understanding of invasive aspergillosis has been evolving and, in the past few decades, IA among ICU patients has been recognized as a common infection and has become more widely recognized. The diagnosis and management of invasive aspergillosis in the ICU is particularly challenging, due to the unstable clinical condition of the patients, lack of diagnostic markers, increased risk of further clinical deterioration, multiple comorbidities, and a need for early assessment and treatment. In this article, we will discuss the challenges and pitfalls of the diagnosis and management of invasive aspergillosis in an ICU setting, along with a review of the current literature that is pertinent and specific to this population.

Pityriasis rosea (PR) is a self-limited exanthem associated with the endogenous systemic reactivation of human herpesvirus (HHV)-6 and HHV-7. The disease typically begins with a single erythematous patch on the trunk (herald patch), followed by a secondary eruption of smaller papulosquamous lesions. Rarely, the herald patch may be the only cutaneous manifestation of PR. The present work aimed to examine the clinical and laboratory features of the PR cases characterized by the herald patch as the sole cutaneous manifestation and to compare them with the classic form of PR. An observational, retrospective study was conducted on patients presenting with herald patch as the only sign of PR (cases) and on a series of age- and sex-matched patients who presented with a typical PR pattern (controls). The records of the patients were extracted from a PR registry, which collected data on patients with PR diagnosed from 2003 to 2023 by at least two dermatologists from the same study team. Nineteen patients (eleven males, eight females) with a mean age of 27.1 years presented the herald patch as the only cutaneous manifestation of PR. Nineteen age- and sex-matched patients were considered controls. In the cases, the exanthem duration was shorter than in controls, and the mean HHV-6 and HHV-7 DNA plasma load was lower than in controls. This rare variant of PR might be considered an abortive form of the exanthem that occurs when the HHV-6/7 reactivation from latency is contrasted by a more robust immunological response than in classic PR.

Acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) are the result of an exaggerated inflammatory response triggered by a variety of pulmonary and systemic insults. The lung tissues are comprised of a variety of cell types, including alveolar epithelial cells, pulmonary vascular endothelial cells, macrophages, neutrophils, and others. There is mounting evidence that these diverse cell populations within the lung interact to regulate lung inflammation in response to both direct and indirect stimuli. The aim of this review is to provide a summary and discussion of recent advances in the understanding of the importance of cell-cell crosstalk in the pathogenesis of ALI/ARDS, with a specific focus on the cell-cell interactions that may offer prospective therapeutic avenues for ALI/ARDS.

COVID-19 severity and high in-hospital mortality are often associated with severe hypoxemia, hyperlactatemia, and acidosis, yet the key players driving this association remain unclear. It is generally assumed that organ damage causes toxic acidosis, but since neutrophil numbers in severe COVID-19 can exceed 80% of the total circulating leukocytes, we asked if metabolic acidosis mediated by the glycolytic neutrophils is associated with lung damage and impaired oxygen delivery in critically ill patients.

Based on prospective mortality outcome, critically ill COVID-19 patients were divided into ICU- survivors and ICU-non-survivors. Samples were analyzed to explore if correlations exist between neutrophil counts, lung damage, glycolysis, blood lactate, blood pH, hemoglobin oxygen saturation, and mortality outcome. We also interrogated isolated neutrophils, platelets, and PBMCs for glycolytic activities.

Arterial blood gas analyses showed remarkable hypoxemia in non-survivors with no consistent differences in PCO2 or [HCO3 -]. The hemoglobin oxygen dissociation curve revealed a right-shift, consistent with lower blood-pH and elevated blood lactate in non-survivors. Metabolic analysis of different blood cells revealed increased glycolytic activity only when considering the total number of neutrophils.

This indicates the role of neutrophilia in hyperlactatemia and lung damage, subsequently contributing to mortality outcomes in severe SARS-CoV-2 infection.

The rapid evolution of the COVID-19 pandemic and subsequent global immunization efforts have rendered early metabolomics studies potentially outdated, as they primarily involved non-exposed, non-vaccinated populations. This paper presents a predictive model developed from up-to-date metabolomics data integrated with clinical data to estimate early mortality risk in critically ill COVID-19 patients. Our study addresses the critical gap in current research by utilizing current patient samples, providing fresh insights into the pathophysiology of the disease in a partially immunized global population.

One hundred elderly patients with severe COVID-19 infection, including 46 survivors and 54 non-survivors, were recruited in January-February 2023 at the Second Hospital affiliated with Harbin Medical University. A predictive model within 24 h of admission was developed using blood metabolomics and clinical data. Differential metabolite analysis and other techniques were used to identify relevant characteristics. Model performance was assessed by comparing the area under the receiver operating characteristic curve (AUROC). The final prediction model was externally validated in a cohort of 50 COVID-19 elderly critically ill patients at the First Hospital affiliated with Harbin Medical University during the same period.

Significant disparities in blood metabolomics and laboratory parameters were noted between individuals who survived and those who did not. One metabolite indicator, Itaconic acid, and four laboratory tests (LYM, IL-6, PCT, and CRP), were identified as the five variables in all four models. The external validation set demonstrated that the KNN model exhibited the highest AUC of 0.952 among the four models. When considering a 50% risk of mortality threshold, the validation set displayed a sensitivity of 0.963 and a specificity of 0.957.

The prognostic outcome of COVID-19 elderly patients is significantly influenced by the levels of Itaconic acid, LYM, IL-6, PCT, and CRP upon admission. These five indicators can be utilized to assess the mortality risk in affected individuals.

Background: During the acute phase of COVID-19, a number of immunological abnormalities have been reported, but few studies longitudinally analyzed the specific subsets of peripheral blood lymphocytes. Methods: In this observational, prospective, and longitudinal study, adult patients developing acute pneumonia during the COVID-19 pandemic have been followed up for 12 months. Peripheral blood lymphocyte subsets were assessed (with a specific focus on the memory markers) at 6 time points after the disease onset until 12 months. Results: A total of 76 patients with acute pneumonia (characterized by a prevalently interstitial pattern of lung inflammation) at the hospital admission (who completed the 12-month follow-up period) were recruited in this study. They were divided into two groups, namely positive (n = 31) and negative (n = 45) patients for the SARS-CoV-2 PCR test. In the acute phase, the general lymphocyte immunophenotyping profile was comparable for most parameters between these groups, except for B cells. When B and T cells were analyzed according to the expression of memory markers, a significant decrease in naïve CD8+ T cells was observed in the SARS-CoV-2-positive pneumonia group during the acute phase. Notably, this aspect was maintained during the follow-up period for at least 9 months. Conclusions: COVID-19 pneumonia seems to be associated with a lower number of naïve CD8+ T cells compared to pneumonia patients negative for this virus. This alteration can persist in the convalescent phase.

The aim of this study was to evaluate how COVID-19 affected acute stroke care and outcome in patients with acute ischemic or hemorrhagic stroke. We performed a retrospective analysis on patients who were admitted with acute ischemic (AIS) or hemorrhagic (ICH) stroke from September 2020 to May 2021 with and without COVID-19. We recorded demographic and clinical data, imaging parameters, functional outcome and mortality at one year. Beside descriptive statistics we performed χ2-probe, Mann-Witney U-test, Student t-probe and multivariate testing. We found a 29%-reduction in the number of AIS cases during the pandemic. The number of the large vessel occlusions /LVOs/ (N = 83, 41.7%), from them 37 (17.7%) had mechanical thrombectomy (MT), was higher than before the COVID-19 period (p = 0.02 and p = 0.001, respectively). From all patients needing acute revascularization therapy (N = 137) 118 patients received it, among them 20 (16.9%) had COVID-19. Those positive for COVID-19 were more likely to have a higher median NIHSS score at baseline and at 24 h (p = 0.02 and p = 0.03, respectively). They also had a lower rate of favourable outcome at discharge (15% vs. 41.8%; p = 0.024) and at three months (25% vs. 52%, p = 0.02), longer median hospitalization (p < 0.0001), and a higher mortality rate (52% vs. 25%; p = 0.03). The incidence of symptomatic intracerebral hemorrhage (sICH) did not differ between the groups. Regarding the ICH patients, NIHSS score at 24 h (p = 0.036), mortality at 3 months (p = 0.004) and at one year (p = 0.00) were higher in the COVID-19 group. We concluded that the pandemic resulted fewer admission due to AIS with an increased number of LVOs and MTs. AIS patients with concomitant SARS-CoV-2 infection have more severe strokes and unfavorable long term outcome. The risk of sICH was not increased in COVID-19 positive patients therefore reperfusion therapies appear to be safe and beneficial for some individuals. Patients with ICH and comorbid COVID-19 have a very poor prognosis.

The coronavirus disease 2019 (COVID-19) global pandemic has been the most severe public health emergency since 2019. Currently, the Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been the most dominant. The most prominent symptom of SARS-CoV-2 infection is respiratory. Meanwhile, the fatality of COVID-19 was mainly from pneumonia. However ,in patients with SARS-CoV-2 infection who have pneumonia and those who do not, the differences in the immune repertoire still require further investigation.

We conducted seven-chain adaptome immune repertoire analyses on patients with SARS-CoV-2 Omicron infection, both with and without pulmonary infiltration.

Patients with pulmonary infiltration exhibit lymphopenia, a decreased proportion of the overall TCR repertoire alongside an increased BCR repertoire, reduced IGHD and IGHM isotype expression, a shorter mean CDR3 length for TRG, and a longer mean length for TRD, as well as diminished clonality and diversity in the TCR/BCR repertoire. Meanwhile, patients with pulmonary infiltration have distinct V-J gene usage and unique CDR3 signature, as well as BCR class switch recombination pattern. Finally, prior vaccination triggered less BCR IGHM/IGHD somatic hypermutation response, preserved the diversity of the entire adaptive immune repertoire, and provided clinical protection against severe or critical conditions following Omicron infection.

We report a unique, comprehensive adaptive immune system signature in patients with pulmonary infiltration, which may serve as potential immunological biomarkers and therapeutic targets.

The COVID-19 pandemic has significantly impacted global health, especially in vulnerable populations like kidney transplant recipients (KTRs). Recently, mass spectrometry-based proteomics has emerged as a powerful tool to shed light on a broad spectrum of dysregulated biological processes in KTRs with COVID-19. In this study, we prospectively collected blood samples from 17 COVID-19-positive KTRs and 10 non-infected KTRs between May and September 2020. Using tandem mass tag-based quantitative proteomics, we analyzed peripheral blood mononuclear cells (PBMCs), plasma protein biomarkers, and lymphocyte counts, followed by bioinformatics analysis. Our results revealed significant proteomic alterations in COVID-19-infected KTRs, particularly in pathways related to glycolysis, glucose metabolism, and neutrophil degranulation. Additionally, we observed an altered immune response characterized by elevated cytokines and decreased lymphocyte counts. Notably, KTRs with AKI exhibited worse clinical outcomes, including higher rates of ICU admission and mechanical ventilation. Comparative analysis of PBMC proteomic profiles between AKI and non-AKI patients identified distinct immune-related pathways, with AKI patients showing marked changes in innate immune responses, particularly neutrophil degranulation. Furthermore, we observed a negative correlation between T cell counts and neutrophil degranulation, suggesting a role for immune dysregulation in COVID-19. Our findings provide critical insights into the immune and metabolic responses in COVID-19-infected KTRs, especially those with AKI, highlighting the need for focused research and therapeutic strategies targeting immune dysregulation in this high-risk population.

(1) Background: The implication of type 2 (T2) inflammatory response in COVID-19 remains controversial. This study aimed to evaluate the association of eosinophils, neutrophils expressing eosinophilic surface markers and T2 cytokines with the severity and outcome of COVID-19. (2) Methods: Patients who were admitted to hospital due to COVID-19 from 18 December 2022 to 31 January 2023 were enrolled. Peripheral blood WBC and differentials, T2 cellular markers (subsets of eosinophils and neutrophils expressing eosinophilic surface markers) and cytokines at admission were measured and compared between subjects with different disease severities and outcomes. (3) Results: Ten mild-to-moderate and 22 severe-to-very severe cases were enrolled for analysis. Of these patients, seven died of severe-to-very severe disease. The severe-to-very severe patients showed a higher number of neutrophils, but lower numbers of eosinophils, lymphocytes cells and neutrophils expressing eosinophilic surface markers. Similarly, deceased cases were also characterized by increased neutrophils, but decreased eosinophils and neutrophils expressing eosinophilic surface markers. The levels of T2 cytokines failed to demonstrate a significant correlation with the severity or outcome of COVID-19. (4) Conclusions: Eosinophils and neutrophils expressing eosinophilic surface markers were associated with milder disease and better outcomes of COVID-19, suggesting that a T2 inflammatory response may confer a potential protective effect against the disease.

Background/Objectives: Studies attempting to predict the development of severe respiratory failure in patients with a COVID-19 infection using machine learning algorithms have yielded different results due to differences in variable selection. We aimed to predict the development of severe respiratory failure, defined as the need for high-flow oxygen support, continuous positive airway pressure, or mechanical ventilation, in patients with COVID-19, using machine learning algorithms to identify the most important variables in achieving this prediction. Methods: This retrospective, cross-sectional study included COVID-19 patients with mild respiratory failure (mostly receiving oxygen through a mask or nasal cannula). We used XGBoost, support vector machines, multi-layer perceptron, k-nearest neighbor, random forests, decision trees, logistic regression, and naïve Bayes methods to accurately predict severe respiratory failure in these patients. Results: A total of 320 patients (62.1% male; average age, 54.67 ± 15.82 years) were included in this study. During the follow-ups of these cases, 114 patients (35.6%) required high-level oxygen support, 67 (20.9%) required intensive care unit admission, and 43 (13.4%) died. The machine learning algorithms with the highest accuracy values were XGBoost, support vector machines, k-nearest neighbor, logistic regression, and multi-layer perceptron (0.7395, 0.7395, 0.7291, 0.7187, and 0.75, respectively). The method that obtained the highest ROC-AUC value was logistic regression (ROC-AUC = 0.7274). The best predictors of severe respiratory failure were a low lymphocyte count, a high computed tomography score in the right and left upper lung zones, an elevated neutrophil count, a small decrease in CRP levels on the third day of admission, a high Charlson comorbidity index score, and a high serum procalcitonin level. Conclusions: The development of severe respiratory failure in patients with COVID-19 could be successfully predicted using machine learning methods, especially logistic regression, and the best predictors of severe respiratory failure were the lymphocyte count and the degree of upper lung zone involvement.

Nicotinamide adenine dinucleotide (NAD+) depletion has been postulated as a contributor to the severity of COVID-19; however, no study has prospectively characterized NAD+ and its metabolites in relation to disease severity in patients with COVID-19. We measured NAD+ and its metabolites in 56 hospitalized patients with COVID-19 and in two control groups without COVID-19: (1) 31 age- and sex-matched adults with comorbidities, and (2) 30 adults without comorbidities. Blood NAD+ concentrations in COVID-19 group were only slightly lower than in the control groups (p < 0.05); however, plasma 1-methylnicotinamide concentrations were significantly higher in patients with COVID-19 (439.7 ng/mL, 95% CI: 234.0, 645.4 ng/mL) than in age- and sex-matched controls (44.5 ng/mL, 95% CI: 15.6, 73.4) and in healthy controls (18.1 ng/mL, 95% CI 15.4, 20.8; p < 0.001 for each comparison). Plasma nicotinamide concentrations were also higher in COVID-19 group and in controls with comorbidities than in healthy control group. Plasma concentrations of 2-methyl-2-pyridone-5-carboxamide (2-PY), but not NAD+, were significantly associated with increased risk of death (HR = 3.65; 95% CI 1.09, 12.2; p = 0.036) and escalation in level of care (HR = 2.90, 95% CI 1.01, 8.38, p = 0.049). RNAseq and RTqPCR analyses of PBMC mRNA found upregulation of multiple genes involved in NAD+ synthesis as well as degradation, and dysregulation of NAD+-dependent processes including immune response, DNA repair, metabolism, apoptosis/autophagy, redox reactions, and mitochondrial function. Blood NAD+ concentrations are modestly reduced in COVID-19; however, NAD+ turnover is substantially increased with upregulation of genes involved in both NAD+ biosynthesis and degradation, supporting the rationale for NAD+ augmentation to attenuate disease severity.

Introduction and objectives. Secondary bacterial infections (SBIs) contribute to worse in-hospital outcomes in patients with Coronavirus disease 2019 (COVID-19). Treatment with proton pump inhibitors (PPIs) is associated with an increased risk of bacterial infections in different clinical settings. However, the association between PPI treatment prior to hospital admission and the occurrence of either SBIs or secondary bacterial sepsis (SBS) as well as their joint impact on clinical outcomes of patients hospitalized for COVID-19 are not clarified.

Patients and methods. We retrospectively analyzed preadmission PPI use, in-hospital occurrence of SBIs and SBS, and in-hospital outcomes of a cohort of patients hospitalized for COVID-19.

Results. Among 1087 patients, 447 (41%) were on PPI treatment prior to hospital admission. During the hospital stay, 197 (18%) and 223 (20%) patients were diagnosed with SBIs and SBS, respectively. The composite endpoint of intensive care unit (ICU) admission/in-hospital death was met by 214 (20%) patients. Preadmission PPI treatment was independently associated with up to a 2.1-fold and 1.7-fold increased risk of SBIs and SBS, respectively. The occurrence of SBS was independently associated with up to a 2.2-fold increased risk of ICU admission/in-hospital death. A significant preadmission PPI treatment x SBS interaction emerged in predicting ICU admission/in-hospital death (F = 5.221, pinteraction = 0.023).

Conclusions. PPI treatment prior to hospital admission for COVID-19 is associated with an increased risk of SBIs and SBS. In addition, it interacts with SBS in predicting in-hospital prognosis. An appropriate use of PPIs may attenuate the risk of adverse clinical outcomes during hospitalization for COVID-19.