CITEViz: interactively classify cell populations in CITE-Seq via a flow cytometry-like gating workflow using R-Shiny.

BACKGROUND: The rapid advancement of new genomic sequencing technology has enabled the development of multi-omic single-cell sequencing assays. These assays profile multiple modalities in the same cell and can often yield new insights not revealed with a single modality. For example, Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-Seq) simultaneously profiles the RNA transcriptome and the surface protein expression. The surface protein markers in CITE-Seq can be used to identify cell populations similar to the iterative filtration process in flow cytometry, also called "gating", and is an essential step for downstream analyses and data interpretation. While several packages allow users to interactively gate cells, they often do not process multi-omic sequencing datasets and may require writing redundant code to specify gate boundaries. To streamline the gating process, we developed CITEViz which allows users to interactively gate cells in Seurat-processed CITE-Seq data. CITEViz can also visualize basic quality control (QC) metrics allowing for a rapid and holistic evaluation of CITE-Seq data. RESULTS: We applied CITEViz to a peripheral blood mononuclear cell CITE-Seq dataset and gated for several major blood cell populations (CD14 monocytes, CD4 T cells, CD8 T cells, NK cells, B cells, and platelets) using canonical surface protein markers. The visualization features of CITEViz were used to investigate cellular heterogeneity in CD14 and CD16-expressing monocytes and to detect differential numbers of detected antibodies per patient donor. These results highlight the utility of CITEViz to enable the robust classification of single cell populations. CONCLUSIONS: CITEViz is an R-Shiny app that standardizes the gating workflow in CITE-Seq data for efficient classification of cell populations. Its secondary function is to generate basic feature plots and QC figures specific to multi-omic data. The user interface and internal workflow of CITEViz uniquely work together to produce an organized workflow and sensible data structures for easy data retrieval. This package leverages the strengths of biologists and computational scientists to assess and analyze multi-omic single-cell datasets. In conclusion, CITEViz streamlines the flow cytometry gating workflow in CITE-Seq data to help facilitate novel hypothesis generation.

Comparative single-cell RNA sequencing analysis of immune response to inactivated vaccine and natural SARS-CoV-2 infection.

Uncovering the immune response to an inactivated SARS-CoV-2 vaccine (In-Vac) and natural infection is crucial for comprehending COVID-19 immunology. Here we conducted an integrated analysis of single-cell RNA sequencing (scRNA-seq) data from serial peripheral blood mononuclear cell (PBMC) samples derived from 12 individuals receiving In-Vac compared with those from COVID-19 patients. Our study reveals that In-Vac induces subtle immunological changes in PBMC, including cell proportions and transcriptomes, compared with profound changes for natural infection. In-Vac modestly upregulates IFN-α but downregulates NF-κB pathways, while natural infection triggers hyperactive IFN-α and NF-κB pathways. Both In-Vac and natural infection alter T/B cell receptor repertoires, but COVID-19 has more significant change in preferential VJ gene, indicating a vigorous immune response. Our study reveals distinct patterns of cellular communications, including a selective activation of IL-15RA/IL-15 receptor pathway after In-Vac boost, suggesting its potential role in enhancing In-Vac-induced immunity. Collectively, our study illuminates multifaceted immune responses to In-Vac and natural infection, providing insights for optimizing SARS-CoV-2 vaccine efficacy.

Combination of IFN-gamma with STING agonist and PD-1 immune checkpoint blockade: a potential immunotherapy for gastric cancer.

Suppression of the cGAS-STING pathway is an immune escape mechanism in cancer cells. The critical role of this pathway in gastric cancer (GC) is not fully understood. Herein, we evaluated the effect of the interferon-gamma (IFN-gamma), STING agonist, PD-1 immune checkpoint blockade, and their combination on the cGAS-STING pathway in GC. Expression of cGAS and STING in tumor tissue samples and adjacent normal tissue (ANT) biopsies of fifty new GC patients was evaluated by quantitative real-time PCR (qRT-PCR). Moreover, cGAS and STING expression levels were examined in Peripheral Blood Mononuclear Cells (PBMC) samples of forty GC patients and twenty-five healthy subjects. The apoptosis rate of cancer cells was analyzed by Annexin V-FITC/PI. Cell proliferation was measured by the BrdU assay. Also, IFN-ß levels were evaluated in the supernatants of the treated groups. The cGAS expression was decreased in patients with distant metastasis. Co-cultures treated with IFN-gamma showed an elevated level of cGAS and STING expressions in PBMC and cancer cells. The rate of apoptosis increased in all the treatment groups. In addition, the rate of proliferation in PBMCs increased in different treated groups. The main role of PBMCs in cytotoxicity was determined by a comparative analysis of the viability of cells treated with all treatments, both with and without PBMCs. The production of IFN-ß was elevated in all treated groups. The current study suggests that a combination therapy using IFN-gamma, STING agonist, and anti-PD-1 antibody can provide a promising approach to the treatment of GC.

Exploring secretory proteome and cytokine kinetic of human peripheral blood mononuclear cells exposed to methicillin-resistant Staphylococcus aureus biofilms and planktonic bacteria.

Staphylococcus aureus is a highly successful pathogen infecting various body parts and forming biofilms on natural and artificial surfaces resulting in difficult-to-treat and chronic infections. We investigated the secreted cytokines and proteomes of isolated peripheral blood mononuclear cells (PBMCs) from healthy volunteers exposed to methicillin-resistant S. aureus (MRSA) biofilms or planktonic bacteria. Additionally, the cytokine profiles in sera from patients with community-acquired pneumonia (CAP) caused by S. aureus were investigated. The aim was to gain insights into the immune response involved and differentiate between the planktonic and sessile MRSA forms. We identified 321 and 298 targets that were significantly differently expressed in PBMCs when exposed to planktonic or biofilm-embedded bacteria, respectively. PBMCs exposed to planktonic MRSA cells secreted increased levels of TNF-α, while IL-18 was elevated when exposed to the biofilm. The machine-learning analyses of the cytokine profiles obtained for the in vitro PBMCs and CAP sera distinguished between the two types of bacteria forms based on cytokines IL-18, IL12, and IL-17, and with a lower importance IL-6. Particularly, IL-18 which has not been correlated with S. aureus biofilms so far might represent a suitable marker for monitoring chronification during MRSA infection to individualize the therapy, but this hypothesis must be proved in clinical trials.

Blood MALT1 expression could help predict treatment outcomes in psoriasis patients, especially in those receiving biologics.

INTRODUCTION: Mucosa-associated lymphoid tissue 1 (MALT1) modulates T helper cell differentiation, pro-inflammatory cytokine production, and epidermal hyperplasia to participate in the pathology of psoriasis. This study aimed to explore the correlation of blood MALT1 with treatment outcomes in psoriasis patients. METHODS: MALT1 was detected in peripheral blood mononuclear cells by reverse transcription-quantitative polymerase chain reaction in 210 psoriasis patients before starting or converting to a new therapy, 50 disease controls, and 50 healthy controls. The psoriasis area severity index (PASI) score was evaluated at month (M)1, M3, and M6 in psoriasis patients. RESULTS: MALT1 was increased in psoriasis patients versus disease controls and healthy controls (both p < .001); and positively related to body mass index (p = .019) and PASI score (p < .001) in psoriasis patients. PASI75 rate at M1, M3, and M6 was 22.9%, 46.2%, and 71.0%, respectively; while PASI90 rate at M1, M3, and M6 was 3.8%, 29.0%, and 50.5%, respectively, in psoriasis patients. PASI75/90 rates at M1, M3, and M6 were increased in psoriasis patients receiving biologics versus those without (all p < .05). Pretreatment MALT1 was higher in psoriasis patients who achieved PASI75 (p = .001) and PASI90 (p < .001) at M6 compared to those who did not achieve that. Subgroup analyses discovered that pretreatment MALT1 had a stronger ability to predict PASI75 and 90 realizations in psoriasis patients receiving biologics (area under the curve [AUC]: 0.723 and 0.808) versus those without (AUC: 0.594 and 0.675). CONCLUSION: Blood MALT1 measurement may assist in predicting outcomes in psoriasis patients, especially in those receiving biologics.

Ruxolitinib Improves Immune-Dysregulation Features but not Epigenetic Abnormality in a Patient with STAT1 GOF.

PURPOSE: Patients with STAT1 gain-of-function (GOF) mutations often exhibit autoimmune features. The JAK1/2 inhibitor ruxolitinib can be administered to alleviate autoimmune symptoms; however, it is unclear how immune cells are molecularly changed by ruxolitinib treatment. Then, we aimed to investigate the trnscriptional and epigenetic status of immune cells before and after ruxolitinib treatment in a patient with STAT1 GOF. METHODS: A patient with a heterozygous STAT1 GOF variant (p.Ala267Val), exhibiting autoimmune features, was treated with ruxolitinib, and peripheral blood mononuclear cells (PBMCs) were longitudinally collected. PBMCs were transcriptionally analyzed by single-cell cellular indexing of the transcriptomes and epitopes by sequencing (CITE-seq), and epigenetically analyzed by assay of transposase-accessible chromatin sequencing (ATAC-seq). RESULTS: CITE-seq analysis revealed that before treatment, the patient's PBMCs exhibited aberrantly activated inflammatory features, especially IFN-related features. In particular, monocytes showed high expression levels of a subset of IFN-stimulated genes (ISGs). Ruxolitinib treatment substantially downregulated aberrantly overexpressed ISGs, and improved autoimmune features. However, epigenetic analysis demonstrated that genetic regions of ISGs-e.g., STAT1, IRF1, MX1, and OAS1-were highly accessible even after ruxolitinib treatment. When ruxolitinib was temporarily discontinued, the patient's autoimmune features were aggravated, which is in line with sustained epigenetic abnormality. CONCLUSIONS: In a patient with STAT1 GOF, ruxolitinib treatment improved autoimmune features and downregulated aberrantly overexpressed ISGs, but did not correct epigenetic abnormality of ISGs.

Eukaryotic initiation factor 3a promotes the development of diffuse large B-cell lymphoma through regulating cell proliferation.

BACKGROUND: One-third of diffuse large B-cell lymphoma (DLBCL) patients suffer relapse after standard treatment. Eukaryotic initiation factor 3a (eIF3a) is a key player in the initial stage of translation, which has been widely reported to be correlated with tumorigenesis and therapeutic response. This study aimed to explore the biological role of eIF3a, evaluate its prognostic and therapeutic potential in DLBCL. METHODS: RNA-seq datasets from GEO database were utilized to detect the expression and prognostic role of eIF3a in DLBCL patients. Protein level of eIF3a was estimated by western blot and immunohistochemical. Next, DLBCL cells were transfected with lentiviral vector either eIF3a-knockdown or empty to assess the biological role of eIF3a. Then, samples were divided into 2 clusters based on eIF3a expression and differentially expressed genes (DEGs) were identified. Function enrichment and mutation analysis of DEGs were employed to detect potential biological roles. Moreover, we also applied pan-cancer and chemosensitivity analysis for deep exploration. RESULTS: eIF3a expression was found to be higher in DLBCL than healthy controls, which was associated with worse prognosis. The expression of eIF3a protein was significantly increased in DLBCL cell lines compared with peripheral blood mononuclear cells (PBMCs) from healthy donors. eIF3a knockdown inhibited the proliferation of DLBCL cells and the expression of proliferation-related proteins and increase cell apoptosis rate. Besides, 114 DEGs were identified which had a close linkage to cell cycle and tumor immune. eIF3a and DEGs mutations were found to be correlated to chemosensitivity and vital signal pathways. Pan-cancer analysis demonstrated that high eIF3a expression was associated with worse prognosis in several tumors. Moreover, eIF3a expression was found to be related to chemosensitivity of several anti-tumor drugs in DLBCL, including Vincristine and Wee1 inhibitor. CONCLUSIONS: We firstly revealed the high expression and prognostic role of eIF3a in DLBCL, and eIF3a might promote the development of DLBCL through regulating cell proliferation and apoptosis. eIF3a expression was related to immune profile and chemosensitivity in DLBCL. These results suggest that eIF3a could serve as a potential prognostic biomarker and therapeutic target in DLBCL.

Essential oil supplementation in milk replacers: short- and long-term impacts on feed efficiency, the faecal microbiota and the plasma metabolome in dairy calves.

Early supplementation with oregano essential oil (EO) in milk replacer (MR) may improve growth, immune responses, the microbiota and the metabolome in dairy calves during pre-weaning and in adulthood. Sixteen female dairy calves (3 days of age) were divided in two groups (n = 8/group): the control group (no EO) and the EO group (0.23 ml of EO in MR during 45 days). After weaning, calves were kept in a feedlot and fed ad libitum. The animals were weighed, and blood and faecal samples were collected on days 3 (T0), 45 (T1) and 370 (T2) to measure the biochemical profile and characterise peripheral blood mononuclear cells (PBMCs; CD4+, CD8+, CD14+, CD21+ and WC1+), the metabolome and microbiota composition. The EO group only had greater average daily weight gain during the suckling (EO supplementation) period (P = 0.030). The EO group showed higher average CD14+ population (monocytes) values, a lower abundance of Ruminococcaceae UCG-014, Faecalibacterium, Blautia and Alloprevotella and increased abundances of Allistipes and Akkermansia. The modification of some metabolites in plasma, such as butyric acid, 3-indole-propionic acid and succinic acid, particularly at T1, are consistent with intestinal microbiota changes. The data suggest that early EO supplementation increases feed efficiency only during the suckling period with notable changes in the microbiota and plasma metabolome; however, not all of these changes can be considered desirable from a gut health point of view. Additional research studies is required to demonstrate that EOs are a viable natural alternative to antibiotics for improving calf growth performance and health.

Multiparameter immunoprofiling for the diagnosis and differentiation of progressive versus nonprogressive nontuberculous mycobacterial lung disease-A pilot study.

Clinical prediction of nontuberculous mycobacteria lung disease (NTM-LD) progression remains challenging. We aimed to evaluate antigen-specific immunoprofiling utilizing flow cytometry (FC) of activation-induced markers (AIM) and IFN-γ enzyme-linked immune absorbent spot assay (ELISpot) accurately identifies patients with NTM-LD, and differentiate those with progressive from nonprogressive NTM-LD. A Prospective, single-center, and laboratory technician-blinded pilot study was conducted to evaluate the FC and ELISpot based immunoprofiling in patients with NTM-LD (n = 18) and controls (n = 22). Among 18 NTM-LD patients, 10 NTM-LD patients were classified into nonprogressive, and 8 as progressive NTM-LD based on clinical and radiological features. Peripheral blood mononuclear cells were collected from patients with NTM-LD and control subjects with negative QuantiFERON results. After stimulation with purified protein derivative (PPD), mycobacteria-specific peptide pools (MTB300, RD1-peptides), and control antigens, we performed IFN-γ ELISpot and FC AIM assays to access their diagnostic accuracies by receiver operating curve (ROC) analysis across study groups. Patients with NTM-LD had significantly higher percentage of CD4+/CD8+ T-cells co-expressing CD25+CD134+ in response to PPD stimulation, differentiating between NTM-LD and controls. Among patients with NTM-LD, there was a significant difference in CD25+CD134+ co-expression in MTB300-stimulated CD8+ T-cells (p <0.05; AUC-ROC = 0.831; Sensitivity = 75% [95% CI: 34.9-96.8]; Specificity = 90% [95% CI: 55.5-99.7]) between progressors and nonprogressors. Significant differences in the ratios of antigen-specific IFN-γ ELISpot responses were also seen for RD1-nil/PPD-nil and RD1-nil/anti-CD3-nil between patients with nonprogressive vs. progressive NTM-LD. Our results suggest that multiparameter immunoprofiling can accurately identify patients with NTM-LD and may identify patients at risk of disease progression. A larger longitudinal study is needed to further evaluate this novel immunoprofiling approach.

q-Diffusion leverages the full dimensionality of gene coexpression in single-cell transcriptomics.

Unlocking the full dimensionality of single-cell RNA sequencing data (scRNAseq) is the next frontier to a richer, fuller understanding of cell biology. We introduce q-diffusion, a framework for capturing the coexpression structure of an entire library of genes, improving on state-of-the-art analysis tools. The method is demonstrated via three case studies. In the first, q-diffusion helps gain statistical significance for differential effects on patient outcomes when analyzing the CALGB/SWOG 80405 randomized phase III clinical trial, suggesting precision guidance for the treatment of metastatic colorectal cancer. Secondly, q-diffusion is benchmarked against existing scRNAseq classification methods using an in vitro PBMC dataset, in which the proposed method discriminates IFN-γ stimulation more accurately. The same case study demonstrates improvements in unsupervised cell clustering with the recent Tabula Sapiens human atlas. Finally, a local distributional segmentation approach for spatial scRNAseq, driven by q-diffusion, yields interpretable structures of human cortical tissue.

Analysis of Human Peripheral Blood Mononuclear Cells in Patients with Neurodegenerative Diseases.

The role of immune system in the progression of neurodegenerative diseases has been studied for decades in animal models. However, invasive studies in human subjects remain controversial due to the heterogeneity of the presentation of different diagnostic categories at different stages of the disease. Peripheral blood mononuclear cells (PBMCs) contain immune cells including dendritic cells (DCs), monocytes, macrophages, and T lymphocytes. Isolating PBMCs from whole blood samples collected from patients provides a minimally invasive method for analyzing the immune system's function in patients with neurodegenerative diseases. By isolating single cell types from patients' peripheral blood, in vitro analyses can be conducted including RNA sequencing, immunofluorescence, and phagocytic analysis. In this chapter, we discuss PBMC separation and isolation of macrophages in pure culture in vitro. We also outline methods for performing RNA-seq on cultured macrophages and other techniques for investigating the role of macrophages in neurodegenerative disease pathophysiology.

Assessing Antigen-Specific T Cell Responses Through IFN-γ Enzyme-Linked Immune Absorbent Spot (ELISpot).

T cells are instrumental in protecting the host against invading pathogens and the development of cancer. To do so, they produce effector molecules such as granzymes, interleukins, interferons, and perforin. For the development and immunomonitoring of therapeutic applications such as cell-based therapies and vaccines, assessing T cell effector function is paramount. This can be achieved through various methods, such as 51Cr release assays, flow cytometry, and enzyme-linked immune absorbent spot (ELISpot) assays. For T cell ELISpots, plates are coated with antibodies directed against the effector molecule of interest (e.g., IFN-g). Subsequently, peripheral blood mononuclear cells (PBMCs) or isolated T cells are cultured on the plate together with stimuli of choice, and the production of effector molecules is visualized via labeled detection antibodies. For clinical studies, ELISpot is currently the gold standard to determine antigen-specific T cell frequencies. In contrast to 51Cr release assays, ELISpot allows for the exact enumeration of responding T cells, and compared to flow cytometry, ELISpot is more cost-effective and high throughput. Here, we optimize and describe, in a step-by-step fashion, how to perform a controlled IFN-γ ELISpot experiment to determine the frequency of responding or antigen-specific T cells in healthy human volunteers. Of note, this protocol can also be employed to assess the frequency of antigen-specific T cells induced in, e.g., vaccination studies or present in cellular products.

[Study of a patient with Myelodysplastic/myeloproliferative neoplasm with co-morbid neutrophilia and a novel NCOR1::GLYR1 fusion gene].

OBJECTIVE: To explore the genetic background for a patient with refractory myelodysplastic/myeloproliferative neoplasm (MDS/MPN) with co-morbid neutrophilia patient. METHODS: A MDS/MPN patient who was admitted to the First Affiliated Hospital of Nanjing Medical University in May 2021 was selected as the study subject. RNA sequencing was carried out to identify fusion genes in his peripheral blood mononuclear cells. Fusion gene sequence was searched through transcriptome-wide analysis with a STAR-fusion procedure. The novel fusion genes were verified by quantitative real-time PCR and Sanger sequencing. RESULTS: The patient, a 67-year-old male, had progressive thrombocytopenia. Based on the morphological and molecular examinations, he was diagnosed as MDS/MPN with co-morbid neutropenia, and was treated with demethylating agents and Bcl-2 inhibitors. Seventeen months after the diagnosis, he had progressed to AML. A novel fusion gene NCOR1::GLYR1 was identified by RNA-sequencing in his peripheral blood sample, which was verified by quantitative real-time PCR and Sanger sequencing. The patient had attained morphological remission after a DCAG regimen (a combinatory chemotherapy of decitabine, cytarabine, aclarubicin and granulocyte colony-stimulating factors) plus Chidamide treatment. A significant decrease in the NCOR1::GLYR1 expression was revealed by quantitative real-time PCR at post-chemotherapy evaluation. CONCLUSION: NCOR1::GLYR1 gene is considered as the pathogenic factor for the MDS/MPN patient with neutropenia.

Immune features revealed by single-cell RNA and single-cell TCR/BCR sequencing in patients with rheumatoid arthritis receiving COVID-19 booster vaccination.

Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, have profoundly affected human health. Booster COVID-19 vaccines have demonstrated significant efficacy in reducing infection and severe cases. However, the effects of booster COVID-19 vaccines on key immune cell subsets and their responses in rheumatoid arthritis (RA) are not well understood. By using single-cell RNA sequencing (scRNA-seq) combined with scTCR/BCR-seq analysis, a total of 8 major and 27 minor cell clusters were identified from paired peripheral blood mononuclear cells (PBMCs) which were collected 1 week before and 4 weeks after booster vaccination in stable RA patients. Booster vaccination only had limited impact on the composition and proportions of PBMCs cell clusters. CD8+ cytotoxic T cells (CD8+T_CTL) showed a trend toward an increase after vaccination, while naive B cells and conventional dendritic cells (cDCs) showed a trend toward a decrease. Transcriptomic changes were observed after booster vaccination, primarily involving T/B cell receptor signaling pathways, phagosome, antigen processing and presenting, and viral myocarditis pathways. Interferon (IFN) and pro-inflammatory response gene sets were slightly upregulated across most major cell subpopulations in COVID-19 booster-vaccinated RA individuals. Plasma neutralizing antibody titers significantly increased after booster COVID-19 vaccination (p = 0.037). Single-cell TCR/BCR analysis revealed increased B cell clone expansion and repertoire diversity postvaccination, with no consistent alterations in T cells. Several clonotypes of BCRs and TCRs were identified to be significantly over-represented after vaccination, such as IGHV3-15 and TRBV28. Our study provided a comprehensive single-cell atlas of the peripheral immune response and TCR/BCR immune repertoire profiles to inactivated SARS-CoV-2 booster vaccination in RA patients, which helps us to understand vaccine-induced immune responses better.

Metacell-based differential expression analysis identifies cell type specific temporal gene response programs in COVID-19 patient PBMCs.

By profiling gene expression in individual cells, single-cell RNA-sequencing (scRNA-seq) can resolve cellular heterogeneity and cell-type gene expression dynamics. Its application to time-series samples can identify temporal gene programs active in different cell types, for example, immune cells' responses to viral infection. However, current scRNA-seq analysis has limitations. One is the low number of genes detected per cell. The second is insufficient replicates (often 1-2) due to high experimental cost. The third lies in the data analysis-treating individual cells as independent measurements leads to inflated statistics. To address these, we explore a new computational framework, specifically whether "metacells" constructed to maintain cellular heterogeneity within individual cell types (or clusters) can be used as "replicates" for increasing statistical rigor. Toward this, we applied SEACells to a time-series scRNA-seq dataset from peripheral blood mononuclear cells (PBMCs) after SARS-CoV-2 infection to construct metacells, and used them in maSigPro for quadratic regression to find significantly differentially expressed genes (DEGs) over time, followed by clustering expression velocity trends. We showed that such metacells retained greater expression variances and produced more biologically meaningful DEGs compared to either metacells generated randomly or from simple pseudobulk methods. More specifically, this approach correctly identified the known ISG15 interferon response program in almost all PBMC cell types and many DEGs enriched in the previously defined SARS-CoV-2 infection response pathway. It also uncovered additional and more cell type-specific temporal gene expression programs. Overall, our results demonstrate that the metacell-pseudoreplicate strategy could potentially overcome the limitation of 1-2 replicates.

Monocytic myeloid-derived suppressor cells as an immune indicator of early diagnosis and prognosis in patients with sepsis.

BACKGROUND: Immunosuppression is a leading cause of septic death. Therefore, it is necessary to search for biomarkers that can evaluate the immune status of patients with sepsis. We assessed the diagnostic and prognostic value of low-density neutrophils (LDNs) and myeloid-derived suppressor cells (MDSCs) subsets in the peripheral blood mononuclear cells (PBMCs) of patients with sepsis. METHODS: LDNs and MDSC subsets were compared among 52 inpatients with sepsis, 33 inpatients with infection, and 32 healthy controls to investigate their potential as immune indicators of sepsis. The percentages of LDNs, monocytic MDSCs (M-MDSCs), and polymorphonuclear MDSCs (PMN-MDSCs) in PBMCs were analyzed. Sequential organ failure assessment (SOFA) scores, C-reactive protein (CRP), and procalcitonin (PCT) levels were measured concurrently. RESULTS: The percentages of LDNs and MDSC subsets were significantly increased in infection and sepsis as compared to control. MDSCs performed similarly to CRP and PCT in diagnosing infection or sepsis. LDNs and MDSC subsets positively correlated with PCT and CRP levels and showed an upward trend with the number of dysfunctional organs and SOFA score. Non-survivors had elevated M-MDSCs compared with that of patients who survived sepsis within 28 days after enrollment. CONCLUSIONS: MDSCs show potential as a diagnostic biomarker comparable to CRP and PCT, in infection and sepsis, even in distinguishing sepsis from infection. M-MDSCs show potential as a prognostic biomarker of sepsis and may be useful to predict 28-day hospital mortality in patients with sepsis.

mRNA-LNP COVID-19 Vaccine Lipids Induce Complement Activation and Production of Proinflammatory Cytokines: Mechanisms, Effects of Complement Inhibitors, and Relevance to Adverse Reactions.

A small fraction of people vaccinated with mRNA-lipid nanoparticle (mRNA-LNP)-based COVID-19 vaccines display acute or subacute inflammatory symptoms whose mechanism has not been clarified to date. To better understand the molecular mechanism of these adverse events (AEs), here, we analyzed in vitro the vaccine-induced induction and interrelations of the following two major inflammatory processes: complement (C) activation and release of proinflammatory cytokines. Incubation of Pfizer-BioNTech's Comirnaty and Moderna's Spikevax with 75% human serum led to significant increases in C5a, sC5b-9, and Bb but not C4d, indicating C activation mainly via the alternative pathway. Control PEGylated liposomes (Doxebo) also induced C activation, but, on a weight basis, it was ~5 times less effective than that of Comirnaty. Viral or synthetic naked mRNAs had no C-activating effects. In peripheral blood mononuclear cell (PBMC) cultures supplemented with 20% autologous serum, besides C activation, Comirnaty induced the secretion of proinflammatory cytokines in the following order: IL-1α < IFN-γ < IL-1ß < TNF-α < IL-6 < IL-8. Heat-inactivation of C in serum prevented a rise in IL-1α, IL-1ß, and TNF-α, suggesting C-dependence of these cytokines' induction, although the C5 blocker Soliris and C1 inhibitor Berinert, which effectively inhibited C activation in both systems, did not suppress the release of any cytokines. These findings suggest that the inflammatory AEs of mRNA-LNP vaccines are due, at least in part, to stimulation of both arms of the innate immune system, whereupon C activation may be causally involved in the induction of some, but not all, inflammatory cytokines. Thus, the pharmacological attenuation of inflammatory AEs may not be achieved via monotherapy with the tested C inhibitors; efficacy may require combination therapy with different C inhibitors and/or other anti-inflammatory agents.

Metabolic Dysregulation and Its Role in Postoperative Pain among Knee Osteoarthritis Patients.

Knee osteoarthritis (KOA) is characterized by low-grade inflammation, loss of articular cartilage, subchondral bone remodeling, synovitis, osteophyte formation, and pain. Strong, continuous pain may indicate the need for joint replacement in patients with end-stage OA, although postoperative pain (POP) of at least a two-month duration persists in 10-40% of patients with OA. STUDY PURPOSE: The inflammation observed in joint tissues is linked to pain caused by the production of proinflammatory cytokines. Since the biosynthesis of cytokines requires energy, their production is supported by extensive metabolic conversions of carbohydrates and fatty acids, which could lead to a disruption in cellular homeostasis. Therefore, this study aimed to investigate the association between POP development and disturbances in energy metabolic conversions, focusing on carbohydrate and fatty acid metabolism. METHODS: Peripheral blood samples were collected from 26 healthy subjects and 50 patients with end-stage OA before joint replacement surgery. All implants were validated by orthopedic surgeons, and patients with OA demonstrated no inherent abnormalities to cause pain from other reasons than OA disease, such as malalignment, aseptic loosening, or excessive bleeding. Pain levels were assessed before surgery using the visual analogue scale (VAS) and neuropathic pain questionnaires, DN4 and PainDETECT. Functional activity was evaluated using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Three and six months after surgery, pain indices according to a VAS of 30 mm or higher were considered. Total RNA isolated from whole blood was analyzed using quantitative real-time RT-PCR (qRT-PCR) for the expression of genes related to carbohydrate and fatty acid metabolism. Protein levels of the examined genes were measured using an ELISA in the peripheral blood mononuclear cells (PBMCs). We used qRT-PCR because it is the most sensitive and reliable method for gene expression analysis, while an ELISA was used to confirm our qRT-PCR results. KEY FINDINGS: Among the study cohort, 17 patients who reported POP demonstrated significantly higher (p < 0.05) expressions of the genes PKM2, LDH, SDH, UCP2, CPT1A, and ACLY compared to pain-free patients with KOA. Receiver-operating characteristic (ROC) curve analyses confirmed the association between these gene expressions and pain development post-arthroplasty. A principle component analysis identified the prognostic values of ACLY, CPT1A, AMPK, SDHB, Caspase 3, and IL-1ß gene expressions for POP development in the examined subjects. CONCLUSION: These findings suggest that the disturbances in energy metabolism, as observed in the PBMCs of patients with end-stage KOA before arthroplasty, may contribute to POP development. An understanding of these metabolic processes could provide insights into the pathogenesis of KOA. Additionally, our findings can be used in a clinical setting to predict POP development in end-stage patients with KOA before arthroplasty.

Differential gene expression and miRNA regulatory network in coronary slow flow.

Coronary slow flow (CSF) is characterized by slow progression of coronary angiography without epicardial stenosis. The aim of this study was to explore the potential biomarkers and regulatory mechanism for CSF. Peripheral blood mononuclear cells from 3 cases of CSF and 3 healthy controls were collected for high-throughput sequencing of mRNA and miRNA, respectively. The differentially expressed mRNAs (DE-mRNAs) and miRNAs (DE-miRNAs) was identified. A total of 117 DE-mRNAs and 32 DE-miRNAs were obtained and they were mainly enriched in immune and inflammatory responses. Twenty-six DE-mRNAs were the predicted target genes for miRNAs by RAID, and then the regulatory network of 15 miRNAs were constructed. In addition, through the PPI network, we identified the three genes (FPR1, FPR2 and CXCR4) with larger degrees as hub genes. Among them, FPR1 was regulated by hsa-miR-342-3p, hsa-let-7c-5p and hsa-miR-197-3p and participated in the immune response. Finally, we validated the differential expression of hub genes and key miRNAs between 20 CSF and 20 control. Moreover, we found that miR-342-3p has a targeted regulatory relationship with FPR1, and their expression is negatively correlated. Then we established a hypoxia/reoxygenation (H/R) HUVEC model and detected FPR1, cell proliferation and apoptosis. Transfection with miR-342-3p mimics can significantly promote the proliferation of HUVEC under H/R conditions. FPR1 were associated with CSF as a biomarker and may be regulated by miR-342-3p potential biomarkers.

A generalizable and easy-to-use COVID-19 stratification model for the next pandemic via immune-phenotyping and machine learning.

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.