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Objective This study aims to explore the causal relationship between immune cells and obesity risk using the Mendelian randomization (MR) method. Methods Data sets for 731 types of immune cells and obesity were obtained from the Genome Wide Association Study (GWAS) catalog database. The inverse-variance weighted method, weighted median, and other methods were used to investigate the causal relationship between immune cells and obesity.The stability of the results was evaluated using Cochran's Q test,MR-Egger regression,and the leave-one-out method.Results A potential causal relationship(P

Pulmonary hypertension (PH) is a chronic and progressive disease with significant morbidity and mortality. It is characterized by remodeled pulmonary vessels associated with perivascular and intravascular accumulation of inflammatory cells. Although there is compelling evidence that bone marrow‐derived cells, such as macrophages and T cells, cluster in the vicinity of pulmonary vascular lesions in humans and contribute to PH development in different animal models, the role of dendritic cells in PH is less clear. Dendritic cells' involvement in PH is likely since they are responsible for coordinating innate and adaptive immune responses. We hypothesized that dendritic cells drive hypoxic PH. We demonstrate that a classical dendritic cell (cDC) subset (cDC2) is increased and activated in wild‐type mouse lungs after hypoxia exposure. We observe significant protection after the depletion of cDCs in ZBTB46 DTR chimera mice before hypoxia exposure and after established hypoxic PH. In addition, we find that cDC depletion is associated with a reduced number of two macrophage subsets in the lung (FolR2+ MHCII+ CCR2+ and FolR2+ MHCII+ CCR2−). We found that depleting cDC2s, but not cDC1s, was protective against hypoxic PH. Finally, proof‐of‐concept studies in human lungs show increased perivascular cDC2s in patients with Idiopathic Pulmonary Arterial Hypertension (IPAH). Our data points to an essential role of cDCs, particularly cDC2s, in the pathophysiology of experimental PH.Bone‐marrow‐derived immature classical dendritic cells, particularly cDC2s, are activated directly or indirectly by hypoxia, resulting in higher expression of cytokines, chemokines, and growth factors in the lung. Recruitment of monocytes and cDC2s from the circulation culminates in perivascular inflammation and hypoxia‐induced pulmonary hypertension. (Created with Biorender.com). [ABSTRACT FROM AUTHOR]

Introduction: The coronavirus disease 2019 (COVID-19) pandemic has affected billions of people worldwide, and the lessons learned need to be concluded to get better prepared for the next pandemic. Early identification of high-risk patients is important for appropriate treatment and distribution of medical resources. A generalizable and easy-to-use COVID-19 severity stratification model is vital and may provide references for clinicians. Methods: Three COVID-19 cohorts (one discovery cohort and two validation cohorts) were included. Longitudinal peripheral blood mononuclear cells were collected from the discovery cohort (n = 39, mild = 15, critical = 24). The immune characteristics of COVID-19 and critical COVID-19 were analyzed by comparison with those of healthy volunteers (n = 16) and patients with mild COVID-19 using mass cytometry by time of flight (CyTOF). Subsequently, machine learning models were developed based on immune signatures and the most valuable laboratory parameters that performed well in distinguishing mild from critical cases. Finally, single-cell RNA sequencing data from a published study (n = 43) and electronic health records from a prospective cohort study (n = 840) were used to verify the role of crucial clinical laboratory and immune signature parameters in the stratification of COVID-19 severity. Results: Patients with COVID-19 were determined with disturbed glucose and tryptophan metabolism in two major innate immune clusters. Critical patients were further characterized by significant depletion of classical dendritic cells (cDCs), regulatory T cells (Tregs), and CD4+ central memory T cells (Tcm), along with increased systemic interleukin-6 (IL-6), interleukin-12 (IL-12), and lactate dehydrogenase (LDH). The machine learning models based on the level of cDCs and LDH showed great potential for predicting critical cases. The model performances in severity stratification were validated in two cohorts (AUC = 0.77 and 0.88, respectively) infected with different strains in different periods. The reference limits of cDCs and LDH as biomarkers for predicting critical COVID-19 were 1.2% and 270.5 U/L, respectively. Conclusion: Overall, we developed and validated a generalizable and easy-to-use COVID-19 severity stratification model using machine learning algorithms. The level of cDCs and LDH will assist clinicians in making quick decisions during future pandemics. [ABSTRACT FROM AUTHOR]

Introduction: The coronavirus disease 2019 (COVID-19) pandemic has affected billions of people worldwide, and the lessons learned need to be concluded to get better prepared for the next pandemic. Early identification of high-risk patients is important for appropriate treatment and distribution of medical resources. A generalizable and easy-to-use COVID-19 severity stratification model is vital and may provide references for clinicians., Methods: Three COVID-19 cohorts (one discovery cohort and two validation cohorts) were included. Longitudinal peripheral blood mononuclear cells were collected from the discovery cohort (n = 39, mild = 15, critical = 24). The immune characteristics of COVID-19 and critical COVID-19 were analyzed by comparison with those of healthy volunteers (n = 16) and patients with mild COVID-19 using mass cytometry by time of flight (CyTOF). Subsequently, machine learning models were developed based on immune signatures and the most valuable laboratory parameters that performed well in distinguishing mild from critical cases. Finally, single-cell RNA sequencing data from a published study (n = 43) and electronic health records from a prospective cohort study (n = 840) were used to verify the role of crucial clinical laboratory and immune signature parameters in the stratification of COVID-19 severity., Results: Patients with COVID-19 were determined with disturbed glucose and tryptophan metabolism in two major innate immune clusters. Critical patients were further characterized by significant depletion of classical dendritic cells (cDCs), regulatory T cells (Tregs), and CD4 + central memory T cells (Tcm), along with increased systemic interleukin-6 (IL-6), interleukin-12 (IL-12), and lactate dehydrogenase (LDH). The machine learning models based on the level of cDCs and LDH showed great potential for predicting critical cases. The model performances in severity stratification were validated in two cohorts (AUC = 0.77 and 0.88, respectively) infected with different strains in different periods. The reference limits of cDCs and LDH as biomarkers for predicting critical COVID-19 were 1.2% and 270.5 U/L, respectively., Conclusion: Overall, we developed and validated a generalizable and easy-to-use COVID-19 severity stratification model using machine learning algorithms. The level of cDCs and LDH will assist clinicians in making quick decisions during future pandemics., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 He, Cui, Zhao, Wu, Zhang, Xue, Zhang, Ge and Leng.)

Dendritic cells (DCs) comprise a heterogeneous population of antigen (Ag)-presenting cells that play a critical role in both innate and adaptive immunity. DCs orchestrate protective responses against pathogens and tumors while mediating tolerance to host tissues. Evolutionary conservation between species has allowed the successful use of murine models to identify and characterize DC types and functions relevant to human health. Among DCs, type 1 classical DCs (cDC1) are uniquely capable of inducing antitumor responses and therefore present a promising therapeutic target. However, the rarity of DCs, particularly cDC1, limits the number of cells that can be isolated for study. Despite significant effort, progress in the field has been hampered by inadequate methods to produce large quantities of functionally mature DCs in vitro. To overcome this challenge, we developed a culture system in which mouse primary bone marrow cells are cocultured with OP9 stromal cells expressing Notch ligand Delta-like 1 (OP9-DL1) to produce CD8α + DEC205 + XCR1 + cDC1 (Notch cDC1). This novel method provides a valuable tool to facilitate the generation of unlimited cDC1 for functional studies and translational applications such as antitumor vaccination and immunotherapy., (© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: Inflammation that occurred in the tumor microenvironment was characterized by abundant macrophage infiltration, playing role in innate immunity. Multinucleate giant cells (MGCs) occur in a variety of inflammatory, hyperplastic, and neoplastic thyroid disorders. They also have been recognized as a feature of papillary thyroid carcinoma (PTC)., Aim: The aim of this study was to evaluate cases of PTC for the presence of macrophages, and estimate CD68+ TAMs density in tumor stroma, margin and the surrounding tissue. We assessed also MGCs., Methods: Macrophages and MGCs densities were correlated with clinicopathologic parameters to assess the possible prognostic significance. We investigated 56 patients immunohistochemically and immunofluorescence with antibodies against CD68 and IL-17., Results: A statistically significant correlation was established between PTC patients in III stage, containing many MGCs, and PTC in I and II stage, with many MGCs. Eighty Percent of patients in III stage showed many MGCs in comparison with patients in I and II stage, where many MGCs were found only in 21,1% (χ 2 = 6.189, p = 0.013)., Conclusion: Our study demonstrates that the increased density of MGCs is associated with advanced stage of PTC, and therefore with tumor progression and that cases of PTC should be carefully screened for their presence., (Copyright: © 2019 Maya Vladova Gulubova, Koni Vancho Ivanova.)

Dendritic cells (DCs) use effective mechanisms to combat antigens and to bring about adaptive immune responses through their ability to stimulate näive T cells. At present, four major cell types are categorised as DCs: Classical or conventional (cDCs), Plasmacytoid (pDCs), Langerhans cells (LCs), and monocyte-derived DCs (Mo-DCs). It was suggested that pDCs, CD1c+ DCs and CD141+ DCs in humans are equivalent to mouse pDCs, CD11b+ DCs and CD8α+ DCs, respectively. Human CD141+ DCs compared to mouse CD8α+ DCs have remarkable functional and transcriptomic similarities. Characteristic markers, transcription factors, toll-like receptors, T helpers (Th) polarisation, cytokines, etc. of DCs are discussed in this review. Major histocompatibility complex (MHC) I and II antigen presentation, cross-presentation and Th polarisation are defined, and the dual role of DCs in the tumour is discussed. Human DCs are the main immune cells that orchestrate the immune response in the tumour microenvironment., (Copyright: © 2019 Maya Gulubova.)