Controversial role of neutrophilic granulocytes in the immunopathogenesis of COVID-19: correlation with imbalance of pro-inflammatory neutrophil-associated cytokines and interferon alpha deficiency.

Neutrophilic granulocytes (NG) are the main drivers of pathological inflammation in COVID-19. Objective. To specify the mechanisms of immunopathogenesis of COVID-19 based on a comparative immunological study of the number and phenotype of CD16+SD62L+CD11b+CD63- and CD16+SD62L+CD11b+CD63+ subsets with an assessment of their effector functions against changing profile of NG-associated cytokines IL-8, IL-18, IL-17A, VEGF-A, IFNalpha, and IFNgamma. Patients and methods. In patients with moderate-to-severe and severe COVID-19, we determined IL-1beta, TNFalpha, IL-6, IL-8, IL-18, IL-17A, VEGF-A, IFNalpha, and IFNgamma (ELISA), the phenotype of CD16+SD62L+CD11b+CD63- and CD16+SD62L+CD11b+CD63+ subsets, NF-kappaB-NG (CYTOMICS FC500), phagocytically active NG (%), neutrophil extracellular traps (NETs), NG in apoptosis, and the activity of NADPH oxidase. Results. In COVID-19 against the background of IFNalpha and IFNgamma production blockade and high levels of NG-associated IL-8, IL-18, IL-17A, VEGF-A, a reduction in the number of mature and functionally active CD16brightSD62LbrightCD11bbrightCD63-NG subsets was revealed, as well as an increase in the number of CD16dimSD62LdimSD11bbrightCD63-NG subsets with an immunosuppressive phenotype and CD16brightSD62LbrightSD11bbrightCD63bright-NG subsets with high cytotoxic activity and ability to form NETs, a decrease in the percentage of phagocytically active NG and an increase in the activity of NADPH oxidase, NETs, and NG in apoptosis. Conclusion. IFNalpha deficiency provokes a hyperergic response of NG-associated cytokines, which leads to the formation of uncontrolled immune inflammation involving NG subsets with an immunosuppressive and cytotoxic phenotype, exacerbating the course of COVID-19. The use of recombinant IFNalpha-2b with antioxidants (Viferon) in the early stages of the disease can help to restore immune homeostasis, normalize the level of NG-associated cytokines, reduce NERTs, and achieve good clinical efficacy.Copyright © 2022, Dynasty Publishing House. All rights reserved.

Identifying the Influencing Factors of Depressive Symptoms among Nurses in China by Machine Learning: A Multicentre Cross-Sectional Study

Background. Nurses' high workload can result in depressive symptoms. However, the research has underexplored the internal and external variables, such as organisational support, career identity, and burnout, which may predict depressive symptoms among Chinese nurses via machine learning (ML). Aim. To predict nurses' depressive symptoms and identify the relevant factors by machine learning (ML) algorithms. Methods. A self-administered smartphone questionnaire was delivered to nurses to evaluate their depressive symptoms;1,431 questionnaires and 28 internal and external features were collected. In the training set, the use of maximum relevance minimum redundancy ranked the features' importance. Five ML algorithms were used to establish models to identify nurses' depressive symptoms using different feature subsets, and the area under the curve (AUC) determined the optimal feature subset. Demographic characteristics were added to the optimal feature subset to establish the combined models. Each model's performance was evaluated using the test set. Results. The prevalence rate of depressive symptoms among Chinese nurses was 31.86%. The optimal feature subset comprised of sleep disturbance, chronic fatigue, physical fatigue, exhaustion, and perceived organisation support. The five models based on the optimal feature subset had good prediction performance on the test set (AUC: 0.871–0.895 and accuracy: 0.798–0.815). After adding the significant demographic characteristics, the performance of the five combined models slightly improved;the AUC and accuracy increased to 0.904 and 0.826 on the test set, respectively. The logistic regression analysis results showed the best and most stable performance while the univariate analysis results showed that external and internal personal features (AUC: 0.739–0.841) were more effective than demographic characteristics (AUC: 0.572–0.588) for predicting nurses' depressive symptoms. Conclusions. ML could effectively predict nurses' depressive symptoms. Interventions to manage physical fatigue, sleep disorders, burnout, and organisational support may prevent depressive symptoms.

The stock market and NO2 emissions effects of COVID‐19 around the world

In this paper, we study the impact of the coronavirus disease 2019 pandemic in estimated panel vector autoregression models for 92 countries. The large cross‐section of countries allows us to shed light on the heterogeneity of the responses of stock markets and nitrogen dioxide emissions as high‐frequency measures of economic activity. We quantify the effect of the number of infections and four dimensions of policy measures: (1) containment and closure, (2) movement restrictions, (3) economic support, and (4) adjustments of health systems. Our main findings show that a surprise increase in the number of infections triggers a drop in our two measures of economic activity. Propping up economic support measures, in contrast, raises stock returns and emissions and, thus, contributes to the economic recovery. We also document vast differences in the responses across subsets of countries and between the first and the second wave of infections.

Fitting Percentage of Body Fat to Simple Body Measurements: College Women

Percentage of body fat, age, weight, height, and 14 circumference measurements (e.g., waist) are given for 184 women aged 18–25. Body fat, one measure of health, was accurately determined by an underwater weighing technique which requires special equipment and training of the individuals conducting the process. Modeling body fat percentage using multiple regression provides a convenient method of estimating body fat percentage using measures collected using only a measuring tape and a scale. This dataset can be used to show students the utility of multiple regression and to provide practice in model building.

Global [formula omitted]-Commerce (G[formula omitted]C) theory by intuitionistic fuzzy [formula omitted]-submodule

Intuitionistic fuzzy set (IFS) theory can be applied for multi-aspect systems due to its capability to address uncertainty and incomplete information in terms of membership and non-membership degrees. Unfortunately, classical Γ -structures cannot handle fuzzy and imprecise information in real problems. In fact, there is no rigorous base to practically express the effectiveness of multi-attribute systems in IFS environment. Here, we develop a generalized IFS with the notion of Γ -module called intuitionistic fuzzy Γ -submodule (IF Γ M) to establish a novel " Global electronic (e)-Commerce (GeC) Theory ". To simplify the analysis of parameters, (α , β) -cut representation is proposed in terms of comprehensive distribution of fuzzy number for the classification of components. On the other hand, Cartesian product is implemented to correspond the elements. Substantial properties of IF Γ M including (α , β) -cut, Cartesian product and t -intuitionistic fuzzy Γ -submodule (t -IF Γ M) are characterized with illustrative examples to extend the framework of IF Γ M, where (α , β) -cut and support t -IF Γ M are verified to be Γ -submodules based on the properties of IF Γ M. Through Γ -module homomorphism, image and inverse image, the parametric connections between (α , β) -cuts are systematically investigated. In addition, a mathematical relationship between the Cartesian product and (α , β) -cut is determined. The overlapping intersection of a collection of t -IF Γ M is proved to be t -IF Γ M, and the image and inverse image are preserved under Γ -module homomorphism. As global e -trades are increasingly expanding after the recent coronavirus disease 2019 (COVID-19) hit, with the growth of 26.7-trillion dollars, businesses are required to transform their traditional functional natures to online (or blended) strategies for cost efficiency and self-survival in the present competitive environment. Therefore, compared to recent studies on IFS in the context of Γ -structures, the main contribution of this study is to provide a theoretical basis for the establishment of a new GeC Theory through the developed IF Γ M method and Γ -module M which targets the purchasing rate of customers through e -commerce companies. In the end, the performance of the proposed method in terms of upper and lower cut, t -intuitionistic fuzzy set, support and IF Γ M model, is analyzed in the developed GeC Theory. The proposed GeC Theory is validated using real datasets of e -commerce mega companies, i.e., Amazon, Alibaba, eBay, Shopify. They are characterized based on the amount of online shopping by samples (individuals). Compared to the existing methods, the GeC approach is an effective IFS-based method for complex systems with uncertainty. [ FROM AUTHOR] Copyright of Engineering Applications of Artificial Intelligence is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Monocyte Differentiation and Heterogeneity: Inter-Subset and Interindividual Differences.

The three subsets of human monocytes, classical, intermediate, and nonclassical, show phenotypic heterogeneity, particularly in their expression of CD14 and CD16. This has enabled researchers to delve into the functions of each subset in the steady state as well as in disease. Studies have revealed that monocyte heterogeneity is multi-dimensional. In addition, that their phenotype and function differ between subsets is well established. However, it is becoming evident that heterogeneity also exists within each subset, between health and disease (current or past) states, and even between individuals. This realisation casts long shadows, impacting how we identify and classify the subsets, the functions we assign to them, and how they are examined for alterations in disease. Perhaps the most fascinating is evidence that, even in relative health, interindividual differences in monocyte subsets exist. It is proposed that the individual's microenvironment could cause long-lasting or irreversible changes to monocyte precursors that echo to monocytes and through to their derived macrophages. Here, we will discuss the types of heterogeneity recognised in monocytes, the implications of these for monocyte research, and most importantly, the relevance of this heterogeneity for health and disease.

Th17 overexpression in severe COVID-19: a prospective observational study.

INTRODUCTION: The objective of the study was to determine T-cell subtypes, Natural Killer cell activity and cytokines in COVID-19 patients with mild to moderate disease and compare them between patients who had recovered and those who had progressed to severe disease. METHODS: Peripheral blood samples of COVID-19 patients were collected at the time of hospital admission and after one week. These samples were analysed for interleukins (IL-6, IL-17a) using chemiluminescence ELISA. The T-cell subsets (T naïve, T regulatory, Th17, Th1, Th2, CD8+ T cells] were studied using flow cytometry. Mild, moderate and severe COVID-19 are defined as per CDC guidelines. RESULTS: Nineteen COVID-19-positive patients were enrolled between June 2020 to December 2021. Nine had mild COVID-19 and 10 had moderate COVID-19 at recruitment. All mild cases recovered without progression to severe disease, while five patients from the moderate group progressed to severe disease. Overall, there is a decrease in lymphocyte count in patients with moderate-severe disease, but the ratio of Th17 [5.91 (2.69-12.01)] was higher compared to Th1 [1.12 (0.27-3.13)] and Th2[2.34 (2-3.5)]. The high baseline level of IL-6 observed in patients with moderate disease leads to the proliferation of more Th17 type of CD4+ T-cells(p=0.002) and suppression of Treg cells. A higher Th17 subset leads to neutrophilic inflammation in patients with severe COVID-19. CONCLUSION: Interpretation conclusions: Higher baseline IL-6 leads to depletion of regulatory T-cells, Th1 Th2 CD4 cells. IL-6 leads to the proliferation of Th17 type of CD4+ subsets in moderate COVID-19. Higher Th17 cells in moderate COVID-19 patients lead to the production of IL-17a, which may result in intense neutrophilic inflammatory response and cytokine storm.

Impact of novel agent therapies on immune cell subsets and infectious complications in patients with relapsed/refractory multiple myeloma.

Introduction: Infections are a leading cause of morbidity and mortality in patients with multiple myeloma (MM). Methods: To examine the effects of modern second-generation novel agent therapy on immune cell subsets, in particular CD4+-T-cells, and infectious complications in patients with relapsed/refractory MM (RRMM), we conducted a prospective cohort study in 112 RRMM patients. Results: Substantially decreased CD4+-T-cells <200/µl before initiation of relapse therapy were detected in 27.7% of patients and were associated with a higher number of previous lines of therapy. Relapse therapy with carfilzomib or pomalidomide showed a significant further decrease of CD4+-T-cells. All novel agents led to a significant decrease of B-cell counts. Overall, infections were frequent with 21.3% of patients requiring antibacterial therapy within the first 3 months of relapse therapy, 5.6% requiring hospitalization. However, in the setting of standard antimicrobial prophylaxis in RRMM patients with very low CD4+-T-cells, no significant association of CD4+T-cell count and an increased risk of infection could be detected. Discussion: Our findings imply that reduced CD4+-T-cell numbers and infections are common in patients with RRMM. We also demonstrate an association with the number of previous therapies and certain substances suggesting an increased need for personalized prophylaxis strategies for opportunistic infections in this patient cohort.

Age-dependent NK cell dysfunctions in severe COVID-19 patients.

Natural Killer (NK) cells are key innate effectors of antiviral immune response, and their activity changes in ageing and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Here, we investigated the age-related changes of NK cell phenotype and function during SARS-CoV-2 infection, by comparing adult and elderly patients both requiring mechanical ventilation. Adult patients had a reduced number of total NK cells, while elderly showed a peculiar skewing of NK cell subsets towards the CD56lowCD16high and CD56neg phenotypes, expressing activation markers and check-point inhibitory receptors. Although NK cell degranulation ability is significantly compromised in both cohorts, IFN-γ production is impaired only in adult patients in a TGF-ß-dependent manner. This inhibitory effect was associated with a shorter hospitalization time of adult patients suggesting a role for TGF-ß in preventing an excessive NK cell activation and systemic inflammation. Our data highlight an age-dependent role of NK cells in shaping SARS-CoV-2 infection toward a pathophysiological evolution.

Controversial role of neutrophilic granulocytes in the immunopathogenesis of COVID-19: correlation with imbalance of pro-inflammatory neutrophil-associated cytokines and interferon alpha deficiency.

Neutrophilic granulocytes (NG) are the main drivers of pathological inflammation in COVID-19. Objective. To specify the mechanisms of immunopathogenesis of COVID-19 based on a comparative immunological study of the number and phenotype of CD16+SD62L+CD11b+CD63- and CD16+SD62L+CD11b+CD63+ subsets with an assessment of their effector functions against changing profile of NG-associated cytokines IL-8, IL-18, IL-17A, VEGF-A, IFNalpha, and IFNgamma. Patients and methods. In patients with moderate-to-severe and severe COVID-19, we determined IL-1beta, TNFalpha, IL-6, IL-8, IL-18, IL-17A, VEGF-A, IFNalpha, and IFNgamma (ELISA), the phenotype of CD16+SD62L+CD11b+CD63- and CD16+SD62L+CD11b+CD63+ subsets, NF-kappaB-NG (CYTOMICS FC500), phagocytically active NG (%), neutrophil extracellular traps (NETs), NG in apoptosis, and the activity of NADPH oxidase. Results. In COVID-19 against the background of IFNalpha and IFNgamma production blockade and high levels of NG-associated IL-8, IL-18, IL-17A, VEGF-A, a reduction in the number of mature and functionally active CD16brightSD62LbrightCD11bbrightCD63-NG subsets was revealed, as well as an increase in the number of CD16dimSD62LdimSD11bbrightCD63-NG subsets with an immunosuppressive phenotype and CD16brightSD62LbrightSD11bbrightCD63bright-NG subsets with high cytotoxic activity and ability to form NETs, a decrease in the percentage of phagocytically active NG and an increase in the activity of NADPH oxidase, NETs, and NG in apoptosis. Conclusion. IFNalpha deficiency provokes a hyperergic response of NG-associated cytokines, which leads to the formation of uncontrolled immune inflammation involving NG subsets with an immunosuppressive and cytotoxic phenotype, exacerbating the course of COVID-19. The use of recombinant IFNalpha-2b with antioxidants (Viferon) in the early stages of the disease can help to restore immune homeostasis, normalize the level of NG-associated cytokines, reduce NERTs, and achieve good clinical efficacy.Copyright © 2022, Dynasty Publishing House. All rights reserved.

Prognostic role of simple inflammatory biomarkers in patients with severe COVID-19: an observational study.

BACKGROUND/AIM: Simple inflammatory biomarkers, such as neutrophil to lymphocyte ratio (NLR), could serve as prognosis indicators in patients with Coronavirus disease 2019 (COVID-19). The utility of on-admission inflammatory biomarkers in predicting outcomes was investigated in patients suffering from severe COVID-19 infection. METHODS: We performed a retrospective study to assess the role of white blood count (WBC), neutrophils (N), lymphocyte (L), platelets (PLTs), C-reactive protein (CRP), reverse transcription polymerase chain reaction (RT-PCR), NLR (N/L), PLR (P/L), dv (derived variation of)-NLR (N/WBC-L), LNR (L/N), dv (derived variation of)-LNR (L/WBC-N), and CLR (CRP/L), in predicting the need for high-flow nasal cannula (HFNC) use, admission to Intensive Care Unit (ICU), and death in adult patients with severe COVID-19 admitted to the Department of Respiratory Medicine from April to September 2021. RESULTS: One hundred and fifteen patients (60 % males) with a mean age of 57.7 ± 16.3 years were included. Thirty-seven patients (32.2 %) required escalation with HFNC, eight patients (7 %) were admitted to the ICU, and nine patients (7.8%) died. Based on univariate analysis, CRP [odds ratio (OR): 1.25, 95 % confidence interval (CI): 1.1-1.42), LNR (OR: 0.015, 95 % CI: 0.00-0.35), dv-NLR (OR: 5*106, 95 % CI: 26.7-9*109), CLR (OR: 7*1058, 95 % CI: 3*1025-2*1092), length of hospitalization (LOH; OR: 1.44, 95 % CI: 1.22-1.63), dyspnea at presentation (OR: 2.83, 95 % CI: 1.23-6.52), and ratio of arterial oxygen partial pressure to fractional inspired oxygen (PaO2/FiO2) on admission (OR: 0.967, 95 % CI: 0.952-0.983) were independent predictors for oxygen requirements. However, the multivariate analysis showed that LNR (OR: 1.686e0-4, 95 % CI: 6.441e00-8-0.441), PaO2/FiO2 on admission (OR: 0.965, 95 % CI: 0.941-0.989), and LOH (OR: 1.717, 95 % CI: 1.274-2.314) were the most important predictor for HFNC use. Nasal congestion at presentation (OR: 11.5, 95 % CI: 1.61-82.8) was a unique and independent predictor for ICU admission. As far as death is concerned, the univariate analysis identified elevated CRP (OR: 1.11, 95 % CI: 1.0-1.24), low RT-PCR (OR: 0.829, 95 % CI: 0.688-0.999), high CLR (OR: 3.2*1033, 95 % CI: 5.8-1.8*1066), age (OR: 1.08, 95 % CI: 1.02-1.14), body mass index (BMI) over 30 (OR: 5.25, 95 % CI: 1.26-21.96), the chronic use of angiotensin-converting enzyme inhibitors (OR: 5.72, 95 % CI: 1.35-24.09), nitrates (OR: 14.85, 95 % CI: 1.81-121.8), diuretics (OR: 8.21, 95 % CI: 1.97-34.32), PaO2/FiO2 on admission (OR: 0.983, 95 % CI: 0.970-0.998), and nasal congestion at presentation (OR: 9.81, 95 % CI: 1.40-68.68) as independent predictors. However, the multivariate analysis pinpointed that obesity (BMI >30) (OR: 10.498, 95 % CI: 1.107-99.572) remained the most important predictor for death. CONCLUSION: LNR and PaO2/FiO2 on admission could be used to timely identify patients requiring HFNC during hospitalization, while obesity (BMI >30) could be an independent predictor of death. Nasal congestion emerges as a unique predictor for ICU admission. HIPPOKRATIA 2022, 26 (2):70-77.

The characteristics and predictive role of lymphocyte subsets in COVID-19 patients.

OBJECTIVE: To investigate the characteristics and predictive roles of lymphocyte subsets in COVID-19 patients. METHOD: We evaluated lymphocyte subsets and other clinical features of COVID-19 patients, and analyzed their potential impacts on COVID-19 outcomes. RESULTS: 1. Lymphocyte subset counts in the peripheral blood of patients with COVID-19 were significantly reduced, especially in patients with severe disease. 2. In patients with non-severe disease, the time from symptom onset to hospital admission was positively correlated with total T cell counts. 3. Among COVID-19 patients who did not reach the composite endpoint, lymphocyte subset counts were higher than in patients who had reached the composite endpoint. 4. The Kaplan-Meier survival curves showed significant differences in COVID-19 patients, classified by the levels of total, CD8+, and CD4+ T cells at admission. CONCLUSION: Our study showed that total, CD8+, and CD4+ T cell counts in patients with COVID-19 were significantly reduced, especially in patients with severe disease. Lower T lymphocyte subsets were significantly associated with a higher occurrence of composite endpoint events. These subsets may help identify patients with a high risk of composite endpoint events.

A systematic review and meta-analysis of the relationship between T-lymphocytes and respiratory tract infection in children.

The objective of this paper was to investigate the relationship between T-lymphocytes and respiratory tract infection in children. A meta-analysis was performed of studies related to virus-infected respiratory illnesses in children, and the change in the ratio of their T-lymphocyte subsets CD4+/CD8+. A systematic literature review was performed using MEDLINE (through PubMed), CINAHL (via Ebsco), Scopus, and Web of Science, for studies describing change in T-lymphocyte levels in children suffering from acute respiratory illnesses. Studies were included as per the Population, Intervention, Comparison, Outcomes and Study (PICOS) criteria, and relevant event data were extracted. A risk of publication bias and a risk of bias assessment were performed, and a funnel plot was designed using RevMan software. A column histogram was designed to compare the adverse effects. A total of 12 studies from the years 2000-2022 were included in the meta-analysis, containing information about 1111 patients. The current meta-analysis has a low risk of publication bias with the Egger's test p-value being 0.583 (p > 0.05) and the Begg's test p-value being 0.772 (p > 0.05). The odds ratio (OR) value was 3.66 (95% confidence interval (95% CI): 1.08-12.43), the risk ratio (RR) value was 1.91 (95% CI: 1.07-3.40) and the significance level was p < 0.05, which indicates that an alteration in T-lymphocyte levels occurs in respiratory infections. T-lymphocyte levels are altered during infection, and the association between T-lymphocytes and respiratory diseases in children was investigated in this study. Based on statistically significant data (p < 0.05), we concluded that T-lymphocyte levels are adjusted in the event of viral respiratory sickness in children to alleviate the infection.

Global e-Commerce (GeC) theory by intuitionistic fuzzy Γ-submodule

Intuitionistic fuzzy set (IFS) theory can be applied for multi-aspect systems due to its capability to address uncertainty and incomplete information in terms of membership and non-membership degrees. Unfortunately, classical Γ-structures cannot handle fuzzy and imprecise information in real problems. In fact, there is no rigorous base to practically express the effectiveness of multi-attribute systems in IFS environment. Here, we develop a generalized IFS with the notion of Γ-module called intuitionistic fuzzy Γ-submodule (IFΓM) to establish a novel "Global electronic (e)-Commerce (GeC) Theory”. To simplify the analysis of parameters, (α,β)-cut representation is proposed in terms of comprehensive distribution of fuzzy number for the classification of components. On the other hand, Cartesian product is implemented to correspond the elements. Substantial properties of IFΓM including (α,β)-cut, Cartesian product and t-intuitionistic fuzzy Γ-submodule (t-IFΓM) are characterized with illustrative examples to extend the framework of IFΓM, where (α,β)-cut and support t-IFΓM are verified to be Γ-submodules based on the properties of IFΓM. Through Γ-module homomorphism, image and inverse image, the parametric connections between (α,β)-cuts are systematically investigated. In addition, a mathematical relationship between the Cartesian product and (α,β)-cut is determined. The overlapping intersection of a collection of t-IFΓM is proved to be t-IFΓM, and the image and inverse image are preserved under Γ-module homomorphism. As global e-trades are increasingly expanding after the recent coronavirus disease 2019 (COVID-19) hit, with the growth of 26.7-trillion dollars, businesses are required to transform their traditional functional natures to online (or blended) strategies for cost efficiency and self-survival in the present competitive environment. Therefore, compared to recent studies on IFS in the context of Γ-structures, the main contribution of this study is to provide a theoretical basis for the establishment of a new GeC Theory through the developed IFΓM method and Γ-module M which targets the purchasing rate of customers through e-commerce companies. In the end, the performance of the proposed method in terms of upper and lower cut, t-intuitionistic fuzzy set, support and IFΓM model, is analyzed in the developed GeC Theory. The proposed GeC Theory is validated using real datasets of e-commerce mega companies, i.e., Amazon, Alibaba, eBay, Shopify. They are characterized based on the amount of online shopping by samples (individuals). Compared to the existing methods, the GeC approach is an effective IFS-based method for complex systems with uncertainty. © 2023 Elsevier Ltd

Cross-Theoretical Compliance: An Integrative Compliance Analysis of COVID-19 Mitigation Responses in Israel

To understand the question why people obey or break rules, different approaches have focused on different theories and subsets of variables. The present research develops a cross-theoretical approach that integrates these perspectives. We apply this in a survey of compliance with COVID-19 pandemic mitigation rules in Israel. The data reveal that compliance in this setting was shaped by a combination of variables originating from legitimacy, capacity, and opportunity theories (but not rational choice or social theories). This demonstrates the importance of moving beyond narrow theoretical perspectives of compliance, to a cross-theoretical understanding—in which different theoretical approaches are systematically integrated.

Circulating neutrophil extracellular trap (NET)-forming 'rogue' neutrophil subset, immunotype [DEspR + CD11b +], mediate multi-organ failure in COVID-19-an observational study.

Background: Cumulative research show association of neutrophils and neutrophil extracellular traps (NETs) with poor outcomes in severe COVID-19. However, to date, there is no curative intent therapy able to block neutrophil/NETs-mediated progression of multi-organ dysfunction. Because of emerging neutrophil heterogeneity, the study of subsets of circulating NET-forming neutrophils [NET + Ns] as mediators of multi-organ failure progression among patients with COVID-19 is critical to identification of therapeutic targets. Methods: We conducted a prospective observational study of circulating levels of CD11b + [NET + N] immunotyped for dual endothelin-1/signal peptide receptor (DEspR ±) expression by quantitative immunofluorescence-cytology and causal mediation analysis. In 36 consented adults hospitalized with mod-severe COVID-19, May to September 2020, we measured acute multi-organ failure via SOFA-scores and respiratory failure via SaO2/FiO2 (SF)-ratio at time points t1 (average 5.5 days from ICU/hospital admission) and t2 (the day before ICU-discharge or death), and ICU-free days at day28 (ICUFD). Circulating absolute neutrophil counts (ANC) and [NET + N] subset-specific counts were measured at t1. Spearman correlation and causal mediation analyses were conducted. Results: Spearman correlation analyses showed correlations of t1-SOFA with t2-SOFA (rho r S = 0.80) and ICUFD (r S = -0.76); circulating DEspR + [NET + Ns] with t1-SOFA (r S = 0.71), t2-SOFA (r S = 0.62), and ICUFD (r S = -0.63), and ANC with t1-SOFA (r S = 0.71), and t2-SOFA (r S = 0.61).Causal mediation analysis identified DEspR + [NET + Ns] as mediator of 44.1% [95% CI:16.5,110.6] of the causal path between t1-SOFA (exposure) and t2-SOFA (outcome), with 46.9% [15.8,124.6] eliminated when DEspR + [NET + Ns] were theoretically reduced to zero. Concordantly, DEspR + [NET + Ns] mediated 47.1% [22.0,72.3%] of the t1-SOFA to ICUFD causal path, with 51.1% [22.8,80.4%] eliminated if DEspR + [NET + Ns] were reduced to zero. In patients with t1-SOFA > 1, the indirect effect of a hypothetical treatment eliminating DEspR + [NET + Ns] projected a reduction of t2-SOFA by 0.98 [0.29,2.06] points and ICUFD by 3.0 [0.85,7.09] days. In contrast, there was no significant mediation of SF-ratio through DEspR + [NET + Ns], and no significant mediation of SOFA-score through ANC. Conclusions: Despite equivalent correlations, DEspR + [NET + Ns], but not ANC, mediated progression of multi-organ failure in acute COVID-19, and its hypothetical reduction is projected to improve ICUFD. These translational findings warrant further studies of DEspR + [NET + Ns] as potential patient-stratifier and actionable therapeutic target for multi-organ failure in COVID-19. Supplementary Information: The online version contains supplementary material available at 10.1186/s41231-023-00143-x.

Dendritic Cell Subsets in Melanoma: Pathophysiology, Clinical Prognosis and Therapeutic Exploitation.

Evasion from immunity is a hallmark of cancer development. Dendritic cells (DCs) are strategic immune cells shaping anti-tumor immune responses, but tumor cells exploit DC versatility to subvert their functions. Unveiling the puzzling role of DCs in the control of tumor development and mechanisms of tumor-induced DC hijacking is critical to optimize current therapies and to design future efficient immunotherapies for melanoma. Dendritic cells, crucially positioned at the center of anti-tumor immunity, represent attractive targets to develop new therapeutic approaches. Harnessing the potencies of each DC subset to trigger appropriate immune responses while avoiding their subversion is a challenging yet promising step to achieve tumor immune control. This review focuses on advances regarding the diversity of DC subsets, their pathophysiology and impact on clinical outcome in melanoma patients. We provide insights into the regulation mechanisms of DCs by the tumor, and overview DC-based therapeutic developments for melanoma. Further insights into DCs' diversity, features, networking, regulation and shaping by the tumor microenvironment will allow designing novel effective cancer therapies. The DCs deserve to be positioned in the current melanoma immunotherapeutic landscape. Recent discoveries strongly motivate exploitation of the exceptional potential of DCs to drive robust anti-tumor immunity, offering promising tracks for clinical successes.

The Role of Lymphocyte Subsets, PD-1, and FAS (CD95) in COVID-19 Cancer Patients.

Lymphocytes are the main orchestrators that regulate the immune response in SARS-COV-2 infection. The exhaustion of T lymphocytes is a contributing factor to lymphopenia, which is responsible for the COVID-19 adverse outcome. However, it is still not demonstrated on a large scale, including cancer patients. Peripheral blood samples were obtained from 83 SARS-CoV2 infected cancer patients, and 29 COVID-19 infected noncancer patients compared to 28 age-matched healthy controls. Lymphocyte subsets were assessed for CD3, CD4, CD8, CD56, PD-1, and CD95 using flow cytometry. The data were correlated to the patients' clinical features, COVID-19 severity and outcomes. Lymphopenia, and decreased CD4+ T cells and CD8+ T cells were significantly observed in COVID-19 cancer and noncancer patients compared to the control group (p < 0.001, for all). There was a significantly increased expression of CD95 and PD-1 on the NK cells, CD4+ T cells, and CD8+ T cells in COVID-19 cancer and noncancer patients in comparison to the control group. The increased expression of CD95 on CD8+ T cells, as well as the increased expression of PD-1 on CD8+ T cells and NK cells are significantly associated with the severity of COVID-19 infection in cancer patients. The increased expression of CD95 and PD-1 on the CD4+ T cells, CD8+ T cells, and NK cells was observed significantly in nonsurviving patients and those who were admitted to the intensive care unit in COVID-19 cancer and noncancer patients. The increased expression of PD-1 and CD95 could be possible prognostic factors for COVID-19 severity and adverse outcomes in COVID-19 cancer and noncancer patients.

Interplay between lymphocyte subpopulation, inflammatory cytokines and their correlation with oxidative stress parameters in COVID-19

Our objective was to investigate the inflammatory and oxidative stress markers in patients with moderate and severe form of coronavirus disease 2019 (COVID-19). In addition, we show the correlation between changes in lymphocyte subsets and markers of oxidative stress as a tool for patient classification. Interleukin-6 (IL-6) and VEGF were analyzed by utilizing a High Sensitivity Evidence InvestigatorTM Biochip Array technology. The total antioxidant capacity (PAT) and the free radical concentrations (d-ROM) were measured in serum utilizing analytical photometric system FRAS5. Peripheral blood was used to determine CD45 + mononuclear, B, T, and NK cells using a multi-parameter flow cytometric immunophenotypic test. Statistionly cally significant differences in IL-6 and VEGF levels were observed between the two patient groups. Decreased values of the absolute number of lymphocytes and their CD4 + and CD8 + positive T cells, NK cells, and CD8 were obtained. In the moderate group, good correlations were found between IL-6 and VEGF and NK cells (r=0.6973, P<0.05;for IL-6 and r=0.6498, P<0, for VEGF. 05). Cytokines were correlated with CD45+ (r=0.5610, P<0.05;for IL-6 and r=0.5462, P<0.05 for VEGF). The oxidative stress index can be used as a cheaper alternative and as a triage tool between severe and moderate illnesses, after showing good correlation with more expensive patient classification analysis.Copyright © the Author(s), 2022 Licensee PAGEPress, Italy.

T HELPER CELL SUBSETS AND RELATED TARGET CELLS IN ACUTE COVID-19.

Current review presents a brief overview of the immune system dysregulation during acute COVID-19 and illustrates the main alterations in peripheral blood CD4+ T-cell (Th) subsets as well as related target cells. Effects of dendritic cell dysfunction induced by SARS-CoV-2 exhibited decreased expression of cell-surface HLA-DR, CCR7 as well as co-stimulatory molecules CD80 and CD86, suggesting reduced antigen presentation, migratory and activation capacities of peripheral blood dendritic cells. SARS-CoV-2-specific Th cells could be detected as early as days 2-4 post-symptom onset, whereas the prolonged lack of SARS-CoV-2-specific Th cells was associated with severe and/or poor COVID-19 outcome. Firstly, in acute COVID-19 the frequency of Th1 cell was comparable with control levels, but several studies have reported about upregulated inhibitory immune checkpoint receptors and exhaustion-associated molecules (TIM3, PD-1, BTLA, TIGIT etc.) on circulating CD8+ T-cells and NK-cells, whereas the macrophage count was increased in bronchoalveolar lavage (BAL) samples. Next, type 2 immune responses are mediated mainly by Th2 cells, and several studies have revealed a skewing towards dominance of Th2 cell subset in peripheral blood samples from patients with acute COVID-19. Furthermore, the decrease of circulating main Th2 target cells - basophiles and eosinophils - were associated with severe COVID-19, whereas the lung tissue was enriched with mast cells and relevant mediators released during degranulation. Moreover, the frequency of peripheral blood Th17 cells was closely linked to COVID-19 severity, so that low level of Th17 cells was observed in patients with severe COVID-19, but in BAL the relative number of Th17 cells as well as the concentrations of relevant effector cytokines were dramatically increased. It was shown that severe COVID-19 patients vs. healthy control had higher relative numbers of neutrophils if compared, and the majority of patients with COVID-19 had increased frequency and absolute number of immature neutrophils with altered ROS production. Finally, the frequency of Tfh cells was decreased during acute COVID-19 infection. Elevated count of activated Tfh were found as well as the alterations in Tfh cell subsets characterized by decreased "regulatory" Tfh1 cell and increased "pro-inflammatory" Tfh2 as well as Tfh17 cell subsets were revealed. Descriptions of peripheral blood B cells during an acute SARS-CoV-2 infection werev reported as relative B cell lymphopenia with decreased frequency of "naive" and memory B cell subsets, as well as increased level of CD27hiCD38hiCD24- plasma cell precursors and atypical CD21low B cells. Thus, the emerging evidence suggests that functional alterations occur in all Th cell subsets being linked with loss-of-functions of main Th cell subsets target cells. Furthermore, recovered individuals could suffer from long-term immune dysregulation and other persistent symptoms lasting for many months even after SARS-CoV-2 elimination, a condition referred to as post-acute COVID-19 syndrome.Copyright © 2022 Saint Petersburg Pasteur Institute. All rights reserved.