COVID-19 progression and recovery involve complex gene expression changes and immune dysregulation, but their dynamic alterations remain poorly understood. Current clinical indicators lack precision in distinguishing severe cases, highlighting the need for molecular biomarkers and diagnostic tools.

Three transcriptomic datasets were analyzed: 1) COVID-19 progression from Healthy, Moderate, Severe, to ICU patients; 2) recovery stages (1, 3, and 6 months) compared to Healthy controls; and 3) COVID-19 ICU versus non-ICU patients. Differential expression analysis, immune cell infiltration estimation, machine learning (LASSO regression and random forest), and functional enrichment were used to identify key genes and molecular mechanisms.

Gene expression analysis revealed dynamic changes during COVID-19 progression. Adaptive immune cells (e.g., B cells and T cells) decreased, while innate immune cells (e.g., monocytes and neutrophils) increased, particularly in ICU patients. Recovery analysis showed significantly reduced adaptive immune cells at 1 month, with partial recovery by 3 and 6 months. Machine learning identified CCR5, CYSLTR1, and KLRG1 as diagnostic biomarkers for distinguishing ICU from non-ICU patients, with AUC values of 0.916, 0.885, and 0.899, respectively.

This study identified CCR5, CYSLTR1, and KLRG1 as efficient diagnostic biomarkers for severe COVID-19 using machine learning and revealed immune regulatory features across COVID-19 progression and recovery.

This study aimed to analyze the characteristics of patients who fail high-flow nasal cannula(HFNC) therapy for acute hypoxemic respiratory failure(AHRF) and to identify predictors of treatment failure.

This single-center, retrospective, observational study analyzed clinical data from 388 patients with AHRF. Patients were divided into two groups: the HFNC success group (HFNC-S, n = 256) and the HFNC failure group (HFNC-F, n = 132). The primary endpoint was the need for escalation of respiratory support to tracheal intubation in the enrolled patients. The demographic data, laboratory tests, blood gas analysis data, CT severity scores, and disease severity scores were analysed to determine the difference between patients who were successful and those who failed HFNC treatment. Univariate and multivariate logistic regression models were used to assess potential predictors of failure of HFNC for patients with acute hypoxaemic respiratory failure.

The mean age of patients enrolled was 67.97 ± 14.40 years. The HFNC-F group had significantly higher PSI(Pneumonia Severity Index) score, CURB(Confusion, Urea, Respiratory Rate, Blood Pressure, and Age)-65 score, CPIS(Clinical Pulmonary Infection Score) score, CT score and SOFA(Sequential Organ Failure Assessment) scores compared to the HFNC-S group. Within 12 h of the initiation of treatment, the HFNC-F group exhibited significantly lower oxygen saturation index (PaO2/FiO2) and significantly higher respiratory rate. Additionally, the HFNC-F group exhibited significantly higher levels of C-reactive protein (CRP), platelet count (PLT), D-dimer, interleukin-10 (IL-10), total bilirubin (TB) and creatinine (CB), but lower albumin levels. Multivariate analysis identified CT score, SOFA score, interleukin-1β (IL-1β), and albumin as independent predictors of HFNC failure.

HFNC is effective for treating AHRF. CT score, SOFA score, IL-1β, and albumin are independent predictors of HFNC failure.

This research aimed to determine the feasibility and accuracy of CLR and clinical features to formulate a prediction model for Peptic Ulcer (PU)-induced Upper Gastrointestinal Bleeding (UGIB).

The clinical data of 146 PU patients were prospectively collected, and patients were divided into the UGIB group (n = 48) and the non-UGIB group (n = 98). The factors affecting UGIB were analyzed using multifactorial logistic regression and collinearity analysis. The prediction model of UGIB was constructed, the predictive value of which was analyzed using the Receiver Operating Characteristic Curve (ROC) and Area Under the Curve (AUC), while the accuracy was analyzed using the calibration curve and Hosmer Lemeshow goodness-of-fit tests, and the application value was assessed using decision curve analysis (DCA).

Statistical significance was observed between the two groups regarding HP infection, ulcer diameter, ulcer stage, use of nonsteroidal anti-inflammatory drugs, Neutrophil, LYM, NEUT/LYM Ratio (NLR), CRP, and CLR. HP infection, ulcer stage, use of NSAIDs, NLR, and CLR were independent risk factors for UGIB, and PCT was a non-independent risk factor. The AUC for this model was 0.921. The calibration curve of the model matched the actual curve. The model achieved a better fitting effect in predicting UGIB (χ2 = 8.5069, df = 8, p = 0.3856) and had a better clinical application value.

A predictive model for PU-induced UGIB, based on CLR and clinical features, can assist in developing clinical treatment plans to prevent UGIB.

The COVID-19 pandemic highlighted the importance of mathematical modeling for understanding viral infection dynamics and accelerated its application into immunological research. Collaborative efforts among international research groups yielded a wealth of experimental data, which facilitated model development and validation. This study focuses on developing a modular mathematical model of the immune response, capturing the interactions between innate and adaptive immunity, with an application to SARS-CoV-2 infection. The model was validated using experimental data from middle-aged individuals with moderate COVID-19 progression, including measurements of viral load in the upper and lower airways, serum antibodies, CD4+ and CD8+ T cells, and interleukin-6 levels. Parameter optimization and sensitivity analysis were performed to improve the model accuracy. Additionally, identifiability analysis was conducted to assess whether the data were sufficient for reliable parameter estimation. The verified model simulates the dynamics of moderate, severe, and critical COVID-19 progressions using measured data on lung epithelium damage, viral load, and IL-6 levels as key indicators of disease severity. We also performed a series of validation scenarios to assess whether the model correctly reproduces biologically relevant behaviors under various conditions, such as immunity hyperactivation, co-infection with HIV, and interferon administration as a therapeutic strategy. The model was developed as a component of the Digital Twin project and represents a general immune module that integrates both innate and adaptive immunity. It can be utilized for further COVID-19 research or serve as a foundation for studying other infectious diseases, provided sufficient data are available.

SARS-CoV-2, first identified in December 2019, caused a global pandemic, resulting in over 6.8 million deaths by March 2023. The elderly, or individuals over 65, accounted for the majority of COVID-19 deaths, with 81% of fatalities in the US in 2020 occurring in this group. Beyond mortality, aging populations are also at higher risk of long-term cardiovascular complications and acute respiratory distress syndrome (ARDS). Although these outcomes may be influenced by comorbidities common in the elderly, age has been found to be a standalone risk factor for severe COVID-19 infection. Therefore, investigating age-related factors in COVID-19 outcomes is crucial in protecting this vulnerable group. Of particular interest is the cytokine storm phenomenon, an excessive inflammatory response that contributes to severe COVID-19 symptoms, including ARDS and cardiovascular damage. Elevated levels of multiple cytokines are common in severe cases of COVID-19. We propose that changes that occur to cytokine profiles as we age may contribute to these aberrant inflammatory responses. This review specifically explored the interleukin class cytokines IL-1, IL-6, IL-17, and IL-23 and considered the potential of biologics targeting these cytokines to alleviate severe outcomes in both COVID-19 and aging individuals.

Critically ill patients in COVID-19 to the intensive care unit (ICU) may develop multiple organ dysfunction syndrome, with some requiring extracorporeal organ support. This study aimed to assess the effects of combined CytoSorb hemoperfusion (HP) and continuous renal replacement therapy (CRRT) on the improvement of the multiorgan failure of patients with COVID-19.

Fifty-six patients hospitalized in the ICU with a confirmed diagnosis of COVID-19 were included in this quasi-experimental study. All the patients had acute respiratory distress syndrome (ARDS). They were treated with 1-4 sessions of HP therapy.

Serum Interleukin-6 (IL6), C-reactive protein (CRP), d-dimer, procalcitonin (PCT), Neutrophil gelatinase-associated lipocalin (NGAL), ferritin, and bilirubin levels were decreased, while the concentration of albumin was significantly increased after HP/CRRT (p < 0.05). No significant differences were observed in O2 saturation (Sao2) and creatinine levels.

Combined HP and CRRT hold promise as a potential intervention for severe COVID-19 cases with multiple organ dysfunction, leading to improved clinical outcomes.

ObjectiveThe aim of this study was to assess the ability of plasma InterLeukin-6 (IL-6) monitoring to predict the failure to switch from volume-controlled ventilation to spontaneous ventilation (SV) in patients with COVID-19-related acute respiratory distress syndrome (ARDS).MethodsWe conducted an observational, single-center and prospective cohort study in the medico-surgical intensive care unit of Avignon Hospital Center. Participants were adult patients requiring invasive mechanical ventilation for COVID-19-related ARDS between August 2021 and August 2022, who were eligible for switching from volume-controlled ventilation to SV.ResultsAmong the 35 patients included in the study, 13 (37%) successfully switched from controlled ventilation to SV, while 22 failed (63%). In the failure group, mean plasma IL-6 levels were higher than in the successful group from hour 0 (defined as the moment of the switch to SV mode) to 48 h. However, differences between groups became significant from 24 h (362.8 vs. 33.6 pg/mL, P = 0.002). Interestingly, between-group differences in plasma C-reactive protein (CRP) levels were only significant between groups from 48 h (129.3 vs. 52.2 mg/L, P = 0.017). Finally, IL-6 and CRP had a similar ability to predict the failure to switch to SV mode: area under the receiving operative curves 0.763 [95%CI: 0.633-0.893] and 0.753 [95%CI: 0.595-0.911], respectively (P = 0.87).ConclusionsIL-6 and CRP are inflammatory biomarkers predictive of failure to switch to SV mode in COVID-19 ARDS patients. Our results showed that IL-6 can detect failure earlier than CRP. However, larger multicenter studies are needed to confirm our results, particularly in other ARDS models.

The pandemic potential of the Middle East Respiratory Syndrome Coronavirus (MERS-CoV) highlights the critical need for effective vaccines due to its high fatality rate of around 36%. In this review, we identified a variety of immunotherapeutic molecules and diagnostic biomarkers that could be used in MERS vaccine development as human-derived adjuvants. We identified immune molecules that have been incorporated into standard clinical diagnostics such as CXCL10/IP10, CXCL8/IL-8, CCL5/RANTES, IL-6, and the complement proteins Ca3 and Ca5. Utilization of different human monoclonal antibodies in the treatment of MERS-CoV patients demonstrates promising outcomes in combatting MERS-CoV infections in vivo, such as hMS-1, 4C2H, 3B11-N, NBMS10-FC, HR2P-M2, SAB-301, M336, LCA60, REGN3051, REGN3048, MCA1, MERs-4, MERs-27, MERs-gd27, and MERs-gd33. Host-derived adjuvants such as CCL28, CCL27, RANTES, TCA3, and GM-CSF have shown significant improvements in immune responses, underscoring their potential to bolster both systemic and mucosal immunity. In conclusion, we believe that host-derived adjuvants like HBD-2, CD40L, and LL-37 offer significant advantages over synthetic options in vaccine development, underscoring the need for clinical trials to validate their efficacy.

COVID-19 was the leading cause of death in Mexico between 2020 and 2021. SARS-CoV-2 infection varies widely among individuals and populations. Since variations in genes related to the immune response may play a role in the susceptibility to and outcome of COVID-19, the associations of gene polymorphisms (SNPs) of IL-6 (- 573G > C, rs1800796), TNF-α (- 308G > A, rs1800629), and IFN-γ (- 1615 C > T, rs2069705) with the expression levels of these proteins in the nasopharynx and serum were evaluated in a Mexican population with mild, severe, or critical COVID-19.

A total of 560 COVID-19 patients (309 mild, 163 severe, and 88 critical cases) and 560 age- and sex-matched COVID-19-negative controls were recruited for this case‒control study. The selected SNPs were genotyped via allelic discrimination. Logistic regression analysis was conducted considering four models of inheritance, and ORs were determined for each genotypic variant, adjusting for associated comorbidities in the multivariate model. The nasopharyngeal mRNA expression levels of IL-6, IFN-γ and TNF-α were determined. The levels of IL-6, IFN-γ, IFN-α2, and TNF-α in the serum were quantified. Significant differences were assessed via the Wilcoxon Mann‒Whitney U test.

The C allele of the IL-6 - 573 SNP was associated with a greater risk of mild and severe COVID-19 (OR: 2.3, CI: 1.897-2.838, p = 0.0001; and OR: 1.5, CI: 1.167-1.949, p = 0.002, respectively), whereas the A allele of the TNF-α - 308 SNP and the T allele of the IFN-γ - 1615 SNP were shown protective roles against severe COVID-19 (OR: 0.3, CI: 0.189-0.537, p = 0.0001; and OR: 0.7, CI: 0.563-1.006, p = 0.05) and against critical COVID-19 (OR: 0.3, CI: 0.158-0.640, p = 0.001; and OR: 0.4, CI: 0.290-0.678, p = 0.0001), adjusting for diabetes and hypertension. Nasopharyngeal IL-6 expression levels were lower in mild COVID-19 patients (p = 0.001) than in critical patients (p = 0.005). Serum IL-6 levels were significantly elevated in the critical cases (p = 0.01).

Our results revealed that the IL-6 - 573 G > C SNP and increased IL-6 nasopharyngeal and serum levels are associated with the risk of severe COVID-19 in a Mexican population.

A mounting evidence links dysregulated immune response to cases of fatal pneumonia seen in COVID-19 infection. We aimed to validate the COVID-19-associated Hyperinflammatory Syndrome (cHIS) score, a novel clinical tool devised to identify those at risk for adverse outcomes, in a local population and investigate the relationship of cHIS score taken at admission and the risk of mortality and the need of mechanical ventilation.

This retrospective cohort study analyzed the sociodemographic, clinical, and laboratory data of 1,881 COVID-19 patients admitted at a tertiary hospital in Davao City, Philippines from January to December 2021. We calculated the cHIS score, composed of six clinical and laboratory criteria from admission, and used multivariate logistic regression to determine the risk of mortality and need of mechanical ventilation.

The cHIS score taken at admission, regardless of cut-off value, was a significant predictor of mortality (OR 0.979 [99% CI 0.894-1.064]) and need of mechanical ventilation (OR 0.586 [99% CI 0.4975-0.6745]). Using the Youden Index, a cut-off cHIS score of 3 or more was a better predictor of mortality (sensitivity, 88.59%; specificity, 71.72%), and a cut-off score of 2 or more was a better predictor of need of mechanical ventilation (sensitivity, 84.02%; specificity, 70.82%) than other cut-off cHIS scores.

Among COVID-19 patients, the cHIS score at admission correlated with the risk of mortality and the need of mechanical ventilation. Cutoff scores of 3 and 2 had the optimal sensitivities and specificities to predict the risk of mortality and the need of mechanical ventilation, respectively.

Since the emergence of COVID-19 in December 2019, the novel SARS-CoV-2 virus has primarily affected adults, with children representing a smaller proportion of cases. However, the escalation of the pandemic has led to a notable increase in pediatric cases of Multisystem Inflammatory Syndrome in Children (MIS-C). The pathogenesis of MIS-C is largely attributed to immune-mediated mechanisms, such as cytokine storms and endothelial damage, following SARS-CoV-2 infection. In this review, we comprehensively describe MIS-C, including its definitions as proposed by the CDC, WHO, and RCPCH, which emphasize persistent fever, excessive inflammatory responses, and multi-organ involvement. Additionally, we summarize current treatment approaches, prioritizing immunotherapy with intravenous immunoglobulin and corticosteroids, along with anticoagulation therapy, and monoclonal antibodies in severe cases.

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.

Dysregulated inflammatory response plays a key role in the pathogenesis of COVID-19. The role of inflammatory markers to predict adverse clinical outcome is still controversial. The aim of this study was to analyze the association of inflammatory markers with disease outcomes independent of the effect of age and co-morbidities.

This is a retrospective analysis of COVID-19 patients admitted at a dedicated COVID center from July 2020 to Mar 2022. Clinical characteristics and inflammatory markers namely serum Ferritin levels, CRP, D-Dimer levels, serum LDH and IL-6 Levels were studied. The following outcome parameters were collected: disease severity at onset and outcome (discharge/death).

48.4% of the of 244 COVID-19 cases included had severe disease while 51.6% had moderate disease. Mean age was 61.3 ± 14.17 years and 71.7% were males. Primary Hypertension (48.4%) and Diabetes Mellitus (39.3%) were the most common co-morbidities. Increasing age, smoking, and alcohol consumption were associated with severe disease. CRP, D-dimer, and IL-6 were independent risk factors for disease severity while CRP, D dimer, LDH, Ferritin, and NLR (Neutrophil Lymphocyte ratio) were independent predictors of disease mortality. D-dimer was the most sensitive (95.8%) and specific (92.2%) marker to predict disease severity and serum LDH was the most sensitive (74.7%) to predict disease mortality at baseline.

Measurement of inflammatory markers might assist clinicians in predicting disease severity and prognosis of COVID-19. This may serve as a benchmark to understand the role of inflammatory markers in other diseases associated with dysregulated inflammatory response.

The 2019 coronavirus illness (COVID 2019) first manifests as a newly identified pneumonia and may quickly escalate to acute respiratory distress syndrome, which has caused a global pandemic. Except for individualized supportive care, no curative therapy has been steadfastly advised for COVID-19 up until this point. T cells and virus-specific T lymphocytes are required to guard against viral infection, particularly COVID-19. Delayed immunological reconstitution (IR) and cytokine storm (CS) continue to be significant barriers to COVID-19 cure. While severe COVID-19 patients who survived the disease had considerable lymphopenia and increased neutrophils, especially in the elderly, their T cell numbers gradually recovered. Exhausted T lymphocytes and elevated levels of pro-inflammatory cytokines, including IL6, IL10, IL2, and IL17, are observed in peripheral blood and the lungs. It implies that while convalescent plasma, IL-6 blocking, mesenchymal stem cells, and corticosteroids might decrease CS, Thymosin α1 and adaptive COVID-19-specific T cells could enhance IR. There is an urgent need for more clinical research in this area throughout the world to open the door to COVID-19 treatment in the future.

During the COVID-19 pandemic, several observational studies proved a certain efficacy of nutraceuticals, herbal products, and other dietary supplements as adjuvant therapies used alongside antiviral drugs. Although their use has not been widespread in Italy, according to preliminary evidence, many supplements with demonstrated immunomodulatory effects, such as vitamins C and D, herbal medicines and essential oils, might relieve the respiratory symptoms of COVID-19, since SARS-CoV-2 can activate inflammasome-mediated inflammatory signaling pathways. Other observational studies have shown that herbal treatments, such as Echinacea purpurea and ginseng, help alleviate respiratory symptoms and reduce serum levels of inflammatory cytokines, which are typically overexpressed in both adult and pediatric SARS-CoV-2 patients. Further, vitamins C and D can attenuate the immune response thanks to their cytokine suppression ability and to their known antimicrobial activity and potential to modulate T helper cell response. The strong immune response triggered by SARS-CoV-2 infection is responsible for the severity of the disease. Preliminary data have also shown that L-arginine, an endothelial-derived relaxing factor, is able to modulate endothelial damage, which appears to be one of the main targets of this systemic disease. Finally, some essential oils and their isolated compounds, such as eucalyptol, may be helpful in reducing many of the respiratory symptoms of COVID-19, although others, such as menthol, are not recommended, since it can lead to an undervaluation of the clinical status of a patient. In this narrative review, despite the lack of strong evidence in this field, we aimed to give an overview of the current available literature (mainly observational and cross-sectional studies) regarding herbal products and dietary supplements and their use in the treatment of mild disease from SARS-CoV-2 infection. Obviously, dietary supplements and herbal products do not constitute a standardized treatment for COVID-19 disease, but they could represent an adjunctive and useful treatment when used together with antivirals.

Objective Community-acquired pneumonia is an acute infectious disease with potentialy life-threatening consequences. Because invasive mechanical ventilation (IMV) requires the attention of many medical staff, early risk prediction at the time of admission is expected to lead to a predictable course of patient care and the appropriate allocation of medical resources. There are a limited number of reports on predictive factors for IMV, such as SMART-COP. Therefore, further studies are required. Patients and Methods We retrospectively reviewed cases of patients with community-acquired pneumonia other than COVID-19 admitted to our institution from 2002 to 2019. We performed competing risks analysis with the need for IMV from the day after admission as the outcome and used multivariable analysis to identify predictive factors of IMV from admission characteristics. Results Among 2,227 patients (mean age 67.3 years, 69.0% male), 39 patients required IMV on or after the day following admission. A multivariable analysis showed that predictive factors of IMV were respiratory rate >30 breaths/min [subdistribution hazard ratio (SHR), 5.53; 95% confidence interval (CI), 2.09 to 14.67; p=0.001], PaO2/FiO2 ratio <250 (SHR, 8.02; 95% CI, 2.78 to 23.13; p<0.001), and Legionella pneumonia (SHR, 4.87; 95% CI, 1.56 to 15.13; p=0.006). Conclusion This study revealed that among other factors including mainly vital signs, specific infection by a microorganism itself (Legionella in this study) was a predictive factor for the need of IMV.

This study explores the relationship between specific SARS-CoV-2 mutations and obesity, focusing on how these mutations may influence COVID-19 severity and outcomes in high-BMI individuals. We analyzed 205 viral mutations from a cohort of 675 patients, examining the association of mutations with BMI, hospitalization, and mortality rates. Logistic regression models and statistical analyses were applied to assess the impact of significant mutations on clinical outcomes, including inflammatory markers and antibody levels. Our findings revealed three key mutations-C14599T, A20268G, and C313T-that were associated with elevated BMI. Notably, C14599T appeared to be protective against hospitalization, suggesting context-dependent effects, while A20268G was linked to a 50% increase in hospitalization risk and elevated antibody levels, potentially indicating an adaptive immune response. C313T showed a 428% increase in mortality risk, marking it as a possible poor-prognosis marker. Interestingly, all three mutations were synonymous, suggesting adaptive roles in obesity-driven environments despite not altering viral protein structures. These results emphasize the importance of studying mutations within the broader context of comorbidities, other mutations, and regional factors to enhance our understanding of SARS-CoV-2 adaptation in high-risk groups. Further validation in larger cohorts is necessary to confirm these associations and to assess their clinical significance.

The SARS-CoV-2 pandemic has significantly impacted global health and has led the population and the scientific community to live in fear of a future pandemic. Based on viral infectious diseases, innate immunity cells such as mast cells and basophils play a fundamental role in the pathogenesis of viral diseases. Understanding these mechanisms could be essential to better study practical therapeutic approaches not only to COVID-19 but also to other viral infections widely spread worldwide, such as influenza A, HIV, and dengue. In this literature review, we want to study these concepts. Mast cells and basophils intervene as a bridge between innate and acquired immunity and seem to have a role in the damage mechanisms during infection and in the stimulation of humoral and cellular immunity. In some cases, these cells can act as reservoirs and favor the replication and spread of the virus in the body. Understanding these mechanisms can be useful not only in therapeutic but also in diagnostic and prognostic perspectives. The prospects of applying artificial intelligence and machine learning algorithms for the creation of very accurate diagnostic/prognostic tools are interesting.

SUMMARYDetection of the presence of infection and its etiology must be accurate and timely to facilitate appropriate antimicrobial use. Diagnostic strategies that rely solely on pathogen detection often are insufficient due to poor test characteristics, inability to differentiate colonization from infection, or protracted delay to result. Understanding the human response across different pathogens on a clinical and molecular level can provide more accurate, timely, and useful answers, especially in critical illness and diagnostic uncertainty. Improvements in understanding the human immune response including genomics, protein analysis, gene expression, and cellular morphology have led to rapid innovation of new host response-based diagnostic tests. This review describes the limitations of pathogen-focused technology and the benefits of examining the breadth of immune response to diagnose infection. It then explores biomarkers that have been studied for this purpose and scrutinizes the performance of host-based multianalyte testing. Currently cleared diagnostics and those in late-stage development are described in depth, with a focus on the purpose of testing and its utility for clinicians. Finally, it concludes by examining opportunities for further host response-derived diagnostic innovation.

COVID-19, the disease caused by SARS-CoV-2, particularly causes severe inflammatory disease in elderly, obese, and male patients. Since both aging and obesity are associated with decreased testosterone and estradiol expression, we hypothesized that decreased hormone levels contribute to excessive inflammation in the context of COVID-19. Previously, we and others have shown that hyperinflammation in severe COVID-19 patients is induced by the production of pathogenic anti-spike IgG antibodies that activate alveolar macrophages. Therefore, we developed an in vitro assay in which we stimulated human macrophages with viral stimuli, anti-spike IgG immune complexes, and different sex hormones. Treatment with levels of testosterone reflecting young adults led to a significant reduction in TNF and IFN-γ production by human macrophages. In addition, estradiol significantly attenuated the production of a very broad panel of cytokines, including TNF, IL-1β, IL-6, IL-10, and IFN-γ. Both testosterone and estradiol reduced the expression of Fc gamma receptors IIa and III, the two main receptors responsible for anti-spike IgG-induced inflammation. Combined, these findings indicate that sex hormones reduce the inflammatory response of human alveolar macrophages to specific COVID-19-associated stimuli, thereby providing a potential immunological mechanism for the development of severe COVID-19 in both older male and female patients.

The integration of nanobiosensors into organ-on-chip (OoC) models offers a promising advancement in the study of viral infections and therapeutic development. Conventional research methods for studying viral infection, such as two-dimensional cell cultures and animal models, face challenges in replicating the complex and dynamic nature of human tissues. In contrast, OoC systems provide more accurate, physiologically relevant models for investigating viral infections, disease mechanisms, and host responses. Nanobiosensors, with their miniaturized designs and enhanced sensitivity, enable real-time, continuous, in situ monitoring of key biomarkers, such as cytokines and proteins within these systems. This review highlights the need for integrating nanobiosensors into OoC systems to advance virological research and improve therapeutic outcomes. Although there is extensive literature on biosensors for viral infection detection and OoC models for replicating infections, real integration of biosensors into OoCs for continuous monitoring remains unachieved. We discuss the advantages of nanobiosensor integration for real-time tracking of critical biomarkers within OoC models, key biosensor technologies, and current OoC systems relevant to viral infection studies. Additionally, we address the main technical challenges and propose solutions for successful integration. This review aims to guide the development of biosensor-integrated OoCs, paving the way for precise diagnostics and personalized treatments in virological research.

COVID-19 can range from a mild to severe acute respiratory syndrome and also could result in multisystemic damage. Additionally, many people develop post-acute symptoms associated with immune and metabolic disturbances in response to viral infection, requiring longitudinal and multisystem studies to understand the complexity of COVID-19 pathophysiology. Here, we conducted a 1H Nuclear Magnetic Resonance metabolomics in saliva of symptomatic subjects presenting mild and moderate respiratory symptoms to investigate prospective changes in the metabolism induced after acute-phase SARS-CoV-2 infection. Saliva from 119 donors presenting non-COVID and COVID-19 respiratory symptoms were evaluated in the acute phase (T1) and the post-acute phase (T2). We found two clusters of metabolite fluctuation in the COVID-19 group. Cluster 1, metabolites such as glucose, (CH3)3 choline-related metabolites, 2-hydroxybutyrate, BCAA, and taurine increased in T2 relative to T1, and in cluster 2, acetate, creatine/creatinine, phenylalanine, histidine, and lysine decreased in T2 relative to T1. Metabolic fluctuations in the COVID-19 group were associated with overweight/obesity, vaccination status, higher viral load, and viral clearance of the respiratory tract. Our data unveil metabolic signatures associated with the transition to the post-acute phase of SARS-CoV-2 infection that may reflect tissue damage, inflammatory process, and activation of tissue repair cascade. Thus, they contribute to describing alterations in host metabolism that may be associated with prolonged symptoms of COVID-19.

SARS-CoV-2 infection causes disruptions in inflammatory pathways, which fundamentally contribute to COVID-19 pathophysiology. The present review critically evaluates the gaps in scientific literature and presents the current status regarding the inflammatory signaling pathways in COVID-19. We propose that phytoconstituents can be used to treat COVID-19 associated inflammation, several already formulated in traditional medications. For this purpose, extensive literature analysis was conducted in the PubMed database to collect relevant in vitro, in vivo, and human patient studies where inflammation pathways were shown to be upregulated in COVID-19. Parallelly, scientific literature was screened for phytoconstituents with known cellular mechanisms implicated for inflammation or COVID-19 associated inflammation. Studies with insufficient evidence on cellular pathways for autophagy and mitophagy were considered out of scope and excluded from the study. The final analysis was visualized in figures and evaluated for accuracy. Our findings demonstrate the frequent participation of NF-κB, a transcription factor, in inflammatory signaling pathways linked to COVID-19. Moreover, the MAPK signaling pathway is also implicated in producing inflammatory molecules. Furthermore, it was also analyzed that the phytoconstituents with flavonoid and phenolic backbones could inhibit either the TLR4 receptor or its consecutive signaling molecules, thereby, decreasing NF-κB activity and suppressing cytokine production. Although, allopathy has treated the early phase of COVID-19, anti-inflammatory phytoconstituents and existing ayurvedic formulations may act on the COVID-19 associated inflammatory pathways and provide an additional treatment strategy. Therefore, we recommend the usage of flavonoids and phenolic phytoconstituents for the treatment of inflammation associated with COVID-19 infection and similar viral ailments.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) illness led to the coronavirus disease 2019 (COVID-19) pandemic, which has caused enormous health and financial losses, as well as challenges to global health. Iron deficiency anaemia (IDA) has been linked to adverse outcomes in patients infected with SARS-COV-2. The present study aimed to assess the association between IDA and the severity of COVID-19 in hospitalized patients. For this purpose, a retrospective data analysis of 100 patients with COVID-19 was conducted. Data of patients hospitalized with SARS-COV-2 infection confirmed by RT-PCR were collected between June, 2021 and March, 2022. The collected data included patient demographics, comorbidities, clinical signs, symptoms and IDA medical laboratory findings, including complete blood count and iron profiles. The results revealed that patients with COVID-19 admitted to the isolation unit represented 61.0% of the study sample, whereas 39.0% were admitted to the intensive care unit (ICU). No patients had stage I IDA, whereas 4 patients (4%) had stage II IDA. Furthermore, 19 patients (19.0%) had stage III IDA. A significantly higher proportion of patients with IDA (69.6%) were admitted to the ICU compared with those without IDA (29.9%, P<0.001). Additionally, patients with IDA had a higher proportion of a history of stroke compared with those without IDA (17.4 vs. 2.6%, respectively, P=0.024). The most common comorbidities identified were hypertension (29%), diabetes (23%) and heart problems (17%). On the whole, the present study demonstrates significant associations between IDA and a longer hospitalization period. A greater incidence of complications was observed in the hospitalized patients who were SARS-COV-2-positive. Although further studies with larger sample sizes are required to confirm these findings, the results presented herein may provide insight for physicians as regards the prevention and treatment of patients with IDA who are infected with coronavirus.

The effect of the COVID-19 pandemic on healthcare systems emphasized the need for rapid and effective triage tools to identify patients at risk of severe or fatal infection. Measuring host response markers of inflammation and endothelial activation at clinical presentation may help to inform appropriate triage and care practices in patients with SARS-CoV-2 infection.

We enrolled patients with COVID-19 across five GeoSentinel clinical sites (in Italy, Belgium, Canada, and the United States) from September 2020 to December 2021, and analyzed the association of plasma markers, including soluble urokinase-type plasminogen activator receptor (suPAR), soluble tumor necrosis factor receptor-1 (sTREM-1), interleukin-6 (IL-6), interleukin-8 (IL-8), complement component C5a (C5a), von Willebrand factor (VWF-a2), and interleukin-1 receptor antagonist (IL-1Ra), with 28-day (D28) mortality and 7-day (D7) severity (discharged, hospitalized on ward, or died/admitted to the ICU).

Of 193 patients, 8.9% (16 of 180) died by D28. Higher concentrations of suPAR were associated with increased odds of mortality at D28 and severity at D7 in univariable and multivariable regression models. The biomarkers sTREM-1 and IL-1Ra showed bivariate associations with mortality at D28 and severity at D7. IL-6, VWF, C5a, and IL-8 were not as indicative of progression to severe disease or death. Conclusions: Our findings confirm previous studies' assertions that point-of-care tests for suPAR and sTREM-1 could facilitate the triage of patients with SARS-CoV-2 infection, which may help guide hospital resource allocation.

Background and Objectives: Elevated levels of pro-inflammatory cytokines have been linked to increased mortality in COVID-19 patients. Infliximab, a tumor necrosis factor inhibitor, has been reported to improve outcomes in COVID-19 patients by targeting the hyperinflammatory response. Our objective was to evaluate the effectiveness of incorporating Infliximab into standard care guidelines for the management of COVID-19. Materials and Methods: A retrospective analysis was conducted on 111 participants who were moderate to severe COVID-19 patients admitted to the hospital. Among them, 74 individuals received solely standard treatment, while 37 received standard therapy plus Infliximab. The primary outcomes of the study centered around the changes in laboratory test parameters. The secondary clinical findings included clinical recovery defined as improvement in patient oxygenation, time till recovery, and assessing necessity for ICU admission, and mortality rates. Results: There was no statistical difference observed in the inflammatory markers including, LDH, Ferritin, CRP, neutrophil to lymphocyte ratio (NLR), and P/F ratio between both groups and in the clinical outcomes including clinical recovery (p = 1.0), time to improvement (p = 0.436), and mortality rate (p = 0.601). However, there was a significant increase in secondary infection (45.9%, 20.3%; p = 0.005), and in liver enzymes, ALT (79.5, 50.0 IU/L; p = 0.02) and AST (57.5, 38.0 IU/L; p = 0.019) in the Infliximab group and the standard care group, respectively. Conclusions: Infliximab therapy did not demonstrate significant benefits compared to standard of care in moderate to severe hospitalized COVID-19 patients.

In China, acupuncture has been employed as an adjunctive therapy for coronavirus disease 2019 (COVID-19). Press needle acupuncture is a special type of acupuncture that provides prolonged stimulation to acupuncture points and simultaneously reduces the pain associated with traditional acupuncture. This study assessed the effectiveness of integrating press needles alongside pharmacologic treatment in patients with mild-to-moderate COVID-19.

Patients hospitalized with mild-to-moderate COVID-19 symptoms between December 2022 and January 2023 were included in the study. The enrolled patients were randomly assigned to receive pharmacologic treatment alone (control group) or both pharmacologic treatment and press needle acupuncture (intervention group). Patients were evaluated for clinical outcomes, including symptom scores, deterioration rates, fever durations, and nucleic acid test results. The patients' complete blood count and C-reactive protein levels were also analyzed using venous blood samples both before and after treatment.

Both groups exhibited a reduction in clinical symptom scores, but symptoms regressed faster in the intervention group. Nucleic acid test negativity was achieved faster in the intervention group than in the control group. The intervention group also had a lower deterioration rate. Furthermore, the increase in the lymphocyte count and decrease in C-reactive protein levels following treatment were more pronounced in the intervention group than in the control group.

This study suggests that utilizing press needle acupuncture as an adjunct to pharmacologic treatment can be effective in patients with mild-to-moderate COVID-19 symptoms.

Endolysosomal compartments are acidic and contain low pH-dependent proteases, and these conditions are exploited by respiratory viruses, such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza virus, for escaping into the cytosol. Moreover, endolysosomes contain various pattern recognition receptors (PRRs), which respond to virus-derived pathogen-associated molecular patterns (PAMPs) by production of proinflammatory cytokines/chemokines. However, excessive proinflammatory responses can lead to a potentially lethal cytokine storm.

Here we investigated the endosomal PRR expression profile in primary human small airway epithelial cells (HSAECs), and whether blockade of endolysosomal acidification affects their cytokine/chemokine production after challenge with virus-derived stimulants.

HSAECs were exposed to stimulants mimicking virus-derived PAMPs, either in the absence or presence of compounds causing blockade of endolysosomal acidification, followed by measurement of cytokine expression and release.

We show that Toll-like receptor 3 (TLR3) is the major endosomal PRR expressed by HSAECs, and that TLR3 expression is strongly induced by TLR3 agonists, but not by a range of other PRR agonists. We also demonstrate that TLR3 engagement with its agonists elicits a robust proinflammatory cytokine/chemokine response, which is profoundly suppressed through blockade of endolysosomal acidification, by bafilomycin A1, monensin, or niclosamide. Using TLR3 reporter cells, it was confirmed that TLR3 signaling is strongly induced by Poly(I:C) and that blockade of endolysosomal acidification efficiently blocked TLR3 signaling. Finally, we show that blockade of endolysosomal acidification causes a reduction in the levels of TLR3 mRNA and protein.

These findings show that blockade of endolysosomal acidification suppresses TLR3-dependent cytokine and chemokine production in HSAECs.

Although antivirals remain important for the treatment COVID-19, methods to assess treatment efficacy are lacking. Here, we investigated the impact of remdesivir on viral dynamics and their contribution to understanding antiviral efficacy in the multicenter Adaptive COVID-19 Treatment Trial 1, which randomized patients to remdesivir or placebo.

Longitudinal specimens collected during hospitalization from a substudy of 642 patients with COVID-19 were measured for viral RNA (upper respiratory tract and plasma), viral nucleocapsid antigen (serum), and host immunologic markers. Associations with clinical outcomes and response to therapy were assessed.

Higher baseline plasma viral loads were associated with poorer clinical outcomes, and decreases in viral RNA and antigen in blood but not the upper respiratory tract correlated with enhanced benefit from remdesivir. The treatment effect of remdesivir was most pronounced in patients with elevated baseline nucleocapsid antigen levels: the recovery rate ratio was 1.95 (95% CI, 1.40-2.71) for levels >245 pg/mL vs 1.04 (95% CI, .76-1.42) for levels <245 pg/mL. Remdesivir also accelerated the rate of viral RNA and antigen clearance in blood, and patients whose blood levels decreased were more likely to recover and survive.

Reductions in SARS-CoV-2 RNA and antigen levels in blood correlated with clinical benefit from antiviral therapy.

NCT04280705 (ClinicalTrials.gov).

COVID-19 is characterized by a broad range of symptoms and disease trajectories. Understanding the correlation between clinical biomarkers and lung pathology during acute COVID-19 is necessary to understand its diverse pathogenesis and inform more effective treatments. Here, we present an integrated analysis of longitudinal clinical parameters, peripheral blood markers, and lung pathology in 142 Brazilian patients hospitalized with COVID-19. We identified core clinical and peripheral blood signatures differentiating disease progression between patients who recovered from severe disease compared with those who succumbed to the disease. Signatures were heterogeneous among fatal cases yet clustered into two patient groups: "early death" (<15 days until death) and "late death" (>15 days). Progression to early death was characterized systemically and in lung histopathological samples by rapid endothelial and myeloid activation and the presence of thrombi associated with SARS-CoV-2+ macrophages. In contrast, progression to late death was associated with fibrosis, apoptosis, and SARS-CoV-2+ epithelial cells in postmortem lung tissue. In late death cases, cytotoxicity, interferon, and T helper 17 (TH17) signatures were only detectable in the peripheral blood after 2 weeks of hospitalization. Progression to recovery was associated with higher lymphocyte counts, TH2 responses, and anti-inflammatory-mediated responses. By integrating antemortem longitudinal blood signatures and spatial single-cell lung signatures from postmortem lung samples, we defined clinical parameters that could be used to help predict COVID-19 outcomes.

The coronavirus disease 2019 (COVID-19) pandemic underscores the critical need to integrate immunomics within the One Health framework to effectively address zoonotic diseases across humans, animals, and environments. Employing advanced high-throughput technologies, this interdisciplinary approach reveals the complex immunological interactions among these systems, enhancing our understanding of immune responses and yielding vital insights into the mechanisms that influence viral spread and host susceptibility. Significant advancements in immunomics have accelerated vaccine development, improved viral mutation tracking, and broadened our comprehension of immune pathways in zoonotic transmissions. This review highlights the role of animals, not merely as carriers or reservoirs, but as essential elements of ecological networks that profoundly influence viral epidemiology. Furthermore, we explore how environmental factors shape immune response patterns across species, influencing viral persistence and spillover risks. Moreover, case studies demonstrating the integration of immunogenomic data within the One Health framework for COVID-19 are discussed, outlining its implications for future research. However, linking humans, animals, and the environment through immunogenomics remains challenging, including the complex management of vast amounts of data and issues of scalability. Despite challenges, integrating immunomics data within the One Health framework significantly enhances our strategies and responses to zoonotic diseases and pandemic threats, marking a crucial direction for future public health breakthroughs.

It is suggested that sepsis may be classified into four clinical phenotypes, using an algorithm employing 29 admission parameters. We applied a simplified phenotyping algorithm among patients with bacterial sepsis and severe COVID-19 and assessed characteristics and outcomes of the derived phenotypes.

Retrospective analysis of data from prospective clinical studies.

Greek ICUs and Internal Medicine departments.

We analyzed 1498 patients, 620 with bacterial sepsis and 878 with severe COVID-19. We implemented a six-parameter algorithm (creatinine, lactate, aspartate transaminase, bilirubin, C-reactive protein, and international normalized ratio) to classify patients with bacterial sepsis intro previously defined phenotypes. Patients with severe COVID-19, included in two open-label immunotherapy trials were subsequently classified. Heterogeneity of treatment effect of anakinra was assessed. The primary outcome was 28-day mortality.

The algorithm validated the presence of the four phenotypes across the cohort of bacterial sepsis and the individual studies included in this cohort. Phenotype α represented younger patients with low risk of death, β was associated with high comorbidity burden, and δ with the highest mortality. Phenotype assignment was independently associated with outcome, even after adjustment for Charlson Comorbidity Index. Phenotype distribution and outcomes in severe COVID-19 followed a similar pattern.

A simplified algorithm successfully identified previously derived phenotypes of bacterial sepsis, which were predictive of outcome. This classification may apply to patients with severe COVID-19 with prognostic implications.

Since the end of 2019, the coronavirus disease 2019 (COVID-19) pandemic has infected nearly 800 million people and caused almost seven million deaths. Obesity was quickly identified as a risk factor for severe COVID-19, ICU admission, acute respiratory distress syndrome, organ support including mechanical ventilation and prolonged length of stay. The relationship among obesity; COVID-19; and respiratory, thrombotic, and renal complications upon admission to the ICU is unclear.

The predominant effect of a hyperinflammatory status or a cytokine storm has been suggested in patients with obesity, but more recent studies have challenged this hypothesis. Numerous studies have also shown increased mortality among critically ill patients with obesity and COVID-19, casting doubt on the obesity paradox, with survival advantages with overweight and mild obesity being reported in other ICU syndromes. Finally, it is now clear that the increase in the global prevalence of overweight and obesity is a major public health issue that must be accompanied by a transformation of our ICUs, both in terms of equipment and human resources. Research must also focus more on these patients to improve their care. In this review, we focused on the central role of obesity in critically ill patients during this pandemic, highlighting its specificities during their stay in the ICU, identifying the lessons we have learned, and identifying areas for future research as well as the future challenges for ICU activity.

While the acute manifestations of infectious diseases are well known, in some individuals, symptoms can either persist or appear after the acute period. Postviral fatigue syndromes are recognized with other viral infections and are described after coronavirus disease 2019 (COVID-19). We have a growing number of individuals with symptoms that persist for weeks, months, and years. Here, we share the evidence regarding the abnormalities associated with postacute sequelae of COVID-19 (PASC) and therapeutics. We describe physiological and biochemical abnormalities seen in individuals reporting PASC. We describe the several evidence-based interventions to offer patients. It is expected that this growing understanding of the mechanisms driving PASC and the benefits seen with certain therapeutics may not only lead to better outcomes for those with PASC but may also have the potential for understanding and treating other postinfectious sequelae.

The optimal timing of tocilizumab treatment during the disease course of COVID-19 has yet to be adequately defined in the context of randomised controlled trials and the effect of tocilizumab on real-world populations remains unclear. We examined the effect of different timing of tocilizumab, on mortality, in a cohort of adults with COVID-19.

All adults (≥18 years old) with confirmed COVID-19 admitted to four hospitals in the West of Scotland between 8 January 2021 and 31 March 2021 and who received tocilizumab were included in a retrospective observational cohort study. Patients were assigned to either an early (day of admission or first day after admission) or late (days 2-7 of admission) cohort based on tocilizumab initiation. The primary outcome was 90-day all-cause mortality in early versus late cohorts. Secondary outcomes were 28 and 180-day all-cause mortality.

203 patients were included in the analysis (138 in the early cohort, 65 in the late cohort). Mortality in 90 days in the early cohort was 22% (n=30) compared with 45% (n=29) in the late cohort (p<0.001). The adjusted mortality was significantly higher in the late cohort compared with the early cohort (adjusted OR: 3.33; 95% CI: 1.29 to 8.54; p=0.012). The secondary outcomes demonstrated the same effect with higher rates of death in 28 days (late cohort adjusted OR: 3.28; 95% CI: 1.23 to 8.75; p=0.018) and 180 days (late cohort adjusted OR: 3.70; 95% CI: 1.45 to 9.45; p=0.006). The effect was seen whether the outcome was adjusted or unadjusted.

Early administration of tocilizumab within the first 2 days of hospitalisation was associated with a significant survival benefit compared with late exposure. Late administration was associated with particularly high mortality. The observed association may be a result of residual confounders and further research is needed.