Cellular Index Research Articles

Skin wound healing improvement in diabetic mice through FTIR microspectroscopy after implanting pluripotent stem cells.

Diabetes is a chronic degenerative disease that carries multiple complications. One of the most important complications is the diabetic cutaneous complications, such as skin lesions, ulcerations, and diabetic foot, which are present in 30%-70% of the patients. Currently, the treatments for wound healing include growth factors and cytokines, skin substitutes, hyperbaric oxygen therapy, and skin grafts. However, these treatments are ineffective due to the complex mechanisms involved in developing unhealed wounds. Considering the aforementioned complications, regenerative medicine has focused on this pathology using stem cells to improve these complications. However, it is essential to mention that there is a poor biomolecular understanding of diabetic skin and the effects of treating it with stem cells. For this reason, herein, we investigated the employment of pluripotent stem cells (PSC) in the wound healing process by carrying out morphometric, histological, and Fourier-transform infrared microspectroscopy (FTIRM) analysis. The morphometric analysis was done through a photographic follow-up, measuring the lesion areas. For the histological analysis, hematoxylin & eosin and picrosirius red stains were used to examine the thickness of the epidermis and the cellularity index in the dermis as well as the content and arrangement of collagen type I and III fibers. Finally, for the FTIRM analysis, skin cryosections were obtained and analyzed by employing a Cassegrain objective of 16× of an FTIR microscope coupled to an FTIR spectrometer. For this purpose, 20 mice were divided into two groups according to the treatment they received: the Isotonic Salt Solution (ISS) group and the PSCs group (n = 10). Both groups were induced to diabetes, and six days after diabetes induction, an excisional lesion was made in the dorsal area. Furthermore, using microscopy and FTIRM analysis, the skin healing process on days 7 and 15 post-skin lesion excision was examined. The results showed that the wound healing process over time, considering the lesion size, was similar in both groups; however, the PSCs group evidenced hair follicles in the wound. Moreover, the histological analysis evidenced that the PSCs group exhibited granulation tissue, new vessels, and better polarity of the keratinocytes. In addition, the amount of collagen increased with a good deposition and orientation, highlighting that type III collagen fibers were more abundant in the PSCs. Finally, the FTIR analysis evidenced that the PSCs group exhibited a faster wound healing process. In conclusion, the wounds treated with PSCs showed a more rapid wound healing process, less inflammatory cellular infiltration, and more ordered structures than the ISS group.

P015 CITE-seq analysis revealed immune cell diversity in colonic mesenteric lymph nodes from IBD patients

Abstract Background Mononuclear phagocytes (MNPs), including dendritic cells (DCs), monocytes (Mo), and macrophages (Mac), are key inducers of the adaptive immune response. MNPs could circulate between blood, mucosa, and mesenteric lymph nodes (MLNs), where they interact with T cells, natural killer (NK) cells, and innate lymphoid cells (ILC), contributing to chronic inflammation. MNPs have been previously investigated at the transcriptomic level in the inflamed gut mucosa, but their molecular characterization at the single-cell level remains uncovered in inflamed MLNs of patients with inflammatory bowel diseases (IBD). Methods MLNs were collected from surgical colonic resections of patients with Crohn’s disease (CD; n=3) or ulcerative colitis (UC; n=3). Cell suspensions were multiplexed and then pooled for sorting CD45+CD3+CD19- T cells and CD45+CD3-CD19- non-T/non-B cells by flow cytometry. Next, sorted cells were combined and labeled with BD Abseq antibodies (antibodies conjugated to oligonucleotide tag). CITE-seq (Cellular Indexing of Transcriptomes and Epitopes by Sequencing), combining simultaneous RNA and protein expression, was performed on the BD RhapsodyTM platform. Results High-quality data from 3308 captured single cells (1471 from CD and 1837 from UC) identified four main immune cell populations (myeloid DCs/Mo/Mac, plasmacytoid DCs, T cells, and NK/innate lymphoid cells). We further segregated cell subsets into 16 MNP, 4 NK/ILC, and 9 T cell clusters. MNP subsets were characterized according to specific gene expression (HLA-DRA, CD1c, ITGAX, SIRPA, JCHAIN, IL3RA). They revealed transcriptionally distinct DC clusters, including one cluster of mature regulatory DC (mregDC) (LAMP3, CCR7), one cluster expressing AXL and THBD, and one cluster of CD103+ DCs expressing LTB, FLT3, and IL22RA2. Further analysis of MNP subsets also revealed 6 clusters of monocytes and macrophages, including inflammatory Mo, Inflammatory Mac, and regulatory Mac. Overall, the proportion of myeloid cells and pDC was higher in UC MLNs when compared to CD (29.6% and 21.6% versus 17.1% and 11.7%, p<0.0001) while the proportion of NK/ILC was higher in CD MLNs (11.7% versus 24.9%, p<0.0001). Comparison of differentially expressed genes (fold-change>1.5) between CD and UC samples showed that CD MLNs were enriched in NK-specific marker genes (KLRD1, IL2RB, NKG7, GZMA). In UC, the majority of upregulated genes related to myeloid gene markers (THBS1, HLA-DQA1, HLA-DRA, VCAN, IL1B, JCHAIN, and CXCL8). Conclusion CITE-Seq analysis of the colonic MLNs of patients with active IBD suggests differences in immune cell landscape gene expression between CD and UC.

Multimodal human thymic profiling reveals trajectories and cellular milieu for T agonist selection.

To prevent autoimmunity, thymocytes expressing self-reactive T cell receptors (TCRs) are negatively selected, however, divergence into tolerogenic, agonist selected lineages represent an alternative fate. As thymocyte development, selection, and lineage choices are dependent on spatial context and cell-to-cell interactions, we have performed Cellular Indexing of Transcriptomes and Epitopes by sequencing (CITE-seq) and spatial transcriptomics on paediatric human thymu​​s. Thymocytes expressing markers of strong TCR signalling diverged from the conventional developmental trajectory prior to CD4+ or CD8+ lineage commitment, while markers of different agonist selected T cell populations (CD8αα(I), CD8αα(II), T(agonist), Treg(diff), and Treg) exhibited variable timing of induction. Expression profiles of chemokines and co-stimulatory molecules, together with spatial localisation, supported that dendritic cells, B cells, and stromal cells contribute to agonist selection, with different subsets influencing thymocytes at specific developmental stages within distinct spatial niches. Understanding factors influencing agonist T cells is needed to benefit from their immunoregulatory effects in clinical use.

Terahertz refractive phenotype of living cells.

Cellular refractive index is a vital phenotypic parameter for understanding the cell functional activities. So far, there remains technical challenges to obtain refractive index of viable cells at the terahertz frequency in which contains rich information closely related to their physiological status. Here we introduce a label-free optical platform for interrogating cellular phenotypes to measure the refractive index of living cells in near-physiological environments by using terahertz spectroscopy with the combination of cellular encapsulation in a confined solution droplet. The key technical feature with cells encapsulated in aqueous droplets allows for keeping cellular viability while eliminating the strong adsorption of solvent water to terahertz signal. The obtained high signal-to-noise ratio enables to differentiate different cell types (e.g., E. coli, stem cell and cancer cell) and their states under stress conditions. The integrating of terahertz spectroscopy to droplet microfluidic further realizes automated and high-through sample preparation and detection, providing a practical toolkit for potential application in cellular health evaluation and phenotypic drug discovery.

Longitudinal single-cell analysis of SARS-CoV-2-reactive B cells uncovers persistence of early-formed, antigen-specific clones.

Understanding persistence and evolution of B cell clones after COVID-19 infection and vaccination is crucial for predicting responses against emerging viral variants and optimizing vaccines. Here, we collected longitudinal samples from patients with severe COVID-19 every third to seventh day during hospitalization and every third month after recovery. We profiled their antigen-specific immune cell dynamics by combining single-cell RNA-Seq, Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-Seq), and B cell receptor-Seq (BCR-Seq) with oligo-tagged antigen baits. While the proportion of Spike receptor binding domain-specific memory B cells (MBC) increased from 3 months after infection, the other Spike- and Nucleocapsid-specific B cells remained constant. All patients showed ongoing class switching and sustained affinity maturation of antigen-specific cells, and affinity maturation was not significantly increased early after vaccine. B cell analysis revealed a polyclonal response with limited clonal expansion; nevertheless, some clones detected during hospitalization, as plasmablasts, persisted for up to 1 year, as MBC. Monoclonal antibodies derived from persistent B cell families increased their binding and neutralization breadth and started recognizing viral variants by 3 months after infection. Overall, our findings provide important insights into the clonal evolution and dynamics of antigen-specific B cell responses in longitudinally sampled patients infected with COVID-19.

Robust single-cell matching and multimodal analysis using shared and distinct features

The ability to align individual cellular information from multiple experimental sources is fundamental for a systems-level understanding of biological processes. However, currently available tools are mainly designed for single-cell transcriptomics matching and integration, and generally rely on a large number of shared features across datasets for cell matching. This approach underperforms when applied to single-cell proteomic datasets due to the limited number of parameters simultaneously accessed and lack of shared markers across these experiments. Here, we introduce a cell-matching algorithm, matching with partial overlap (MARIO) that accounts for both shared and distinct features, while consisting of vital filtering steps to avoid suboptimal matching. MARIO accurately matches and integrates data from different single-cell proteomic and multimodal methods, including spatial techniques and has cross-species capabilities. MARIO robustly matched tissue macrophages identified from COVID-19 lung autopsies via codetection by indexing imaging to macrophages recovered from COVID-19 bronchoalveolar lavage fluid by cellular indexing of transcriptomes and epitopes by sequencing, revealing unique immune responses within the lung microenvironment of patients with COVID.

Histological and molecular classifications of pediatric glioma with time-dependent diffusion MRI-based microstructural mapping.

Gliomas are the most common type of central nervous system tumors in children, and the combination of histological and molecular classification is essential for prognosis and treatment. Here, we proposed a newly developed microstructural mapping technique based on diffusion-time-dependent diffusion MRI td-dMRI theory to quantify tumor cell properties and tested these microstructural markers in identifying histological grade and molecular alteration of H3K27. This prospective study included 69 pediatric glioma patients aged 6.14 ± 3.25 years old, who underwent td-dMRI with pulsed and oscillating gradient diffusion sequences on a 3T scanner. dMRI data acquired at varying tds were fitted into a 2-compartment microstructural model to obtain intracellular fraction (fin), cell diameter, cellularity, etc. Apparent diffusivity coefficient (ADC) and T1 and T2 relaxation times were also obtained. H&E stained histology was used to validate the estimated microstructural properties. For histological classification of low- and high-grade pediatric gliomas, the cellularity index achieved the highest area under the receiver-operating-curve (AUC) of 0.911 among all markers, while ADC, T1, and T2 showed AUCs of 0.906, 0.885, and 0.886. For molecular classification of H3K27-altered glioma in 39 midline glioma patients, cell diameter showed the highest discriminant power with an AUC of 0.918, and the combination of cell diameter and extracellular diffusivity further improved AUC to 0.929. The td-dMRI estimated fin correlated well with the histological ground truth with r = 0.7. The td-dMRI-based microstructural properties outperformed routine MRI measurements in diagnosing pediatric gliomas, and the different microstructural features showed complementary strength in histological and molecular classifications.

Brain DNA damaging effects of volatile anesthetics and 1 and 2 Gy gamma irradiation in vivo: Preliminary results

Although both can cause DNA damage, the combined impact of volatile anesthetics halothane/sevoflurane/isoflurane and radiotherapeutic exposure on sensitive brain cells in vivo has not been previously analyzed. Healthy Swiss albino male mice (240 in total, 48 groups) were exposed to either halothane/sevoflurane/isoflurane therapeutic doses alone (2h); 1 or 2gray of gamma radiation alone; or combined exposure. Frontal lobe brain samples from five animals were taken immediately and 2, 6, and 24h after exposure. DNA damage and cellular repair index were analyzed using the alkaline comet assay and the tail intensity parameter. Elevated tail intensity levels for sevoflurane/halothane were the highest at 6h and returned to baseline within 24h for sevoflurane, but not for halothane, while isoflurane treatment caused lower tail intensity than control values. Combined exposure demonstrated a slightly halothane/sevoflurane protective and isoflurane protective effect, which was stronger for 2 than for 1gray. Cellular repair indices and tail intensity histograms indicated different modes of action in DNA damage creation. Isoflurane/sevoflurane/halothane preconditioning demonstrated protective effects in sensitive brain cells in vivo. Owing to the constant increases in the combined use of radiotherapy and volatile anesthetics, further studies should explore the mechanisms behind these effects, including longer and multiple exposure treatments and in vivo brain tumor models.

Enhanced annotation of CD45RA to distinguish T cell subsets in single-cell RNA-seq via machine learning.

T cell heterogeneity presents a challenge for accurate cell identification, understanding their inherent plasticity, and characterizing their critical role in adaptive immunity. Immunologists have traditionally employed techniques such as flow cytometry to identify T cell subtypes based on a well-established set of surface protein markers. With the advent of single-cell RNA sequencing (scRNA-seq), researchers can now investigate the gene expression profiles of these surface proteins at the single-cell level. The insights gleaned from these profiles offer valuable clues and a deeper understanding of cell identity. However, CD45RA, the isoform of CD45 which distinguishes between naive/central memory T cells and effector memory/effector memory cells re-expressing CD45RA T cells, cannot be well profiled by scRNA-seq due to the difficulty in mapping short reads to genes. In order to facilitate cell-type annotation in T cell scRNA-seq analysis, we employed machine learning and trained a classifier on single-cell mRNA count data annotated with known CD45RA antibody levels provided by cellular indexing of transcriptomes and epitopes sequencing data. Among all the algorithms we tested, the trained support vector machine with a radial basis function kernel with optimized hyperparameters achieved a 99.96% accuracy on an unseen dataset. The multilayer perceptron classifier, the second most predictive method overall, also achieved a decent accuracy of 99.74%. Our simple yet robust machine learning approach provides a valid inference on the CD45RA level, assisting the cell identity annotation and further exploring the heterogeneity within human T cells. Based on the overall performance, we chose the support vector machine with a radial basis function kernel as the model implemented in our Python package scCD45RA. The resultant package scCD45RA can be found at https://github.com/BrubakerLab/ScCD45RA and can be installed from the Python Package Index (PyPI) using the command "pip install sccd45ra."

SPECK: an unsupervised learning approach for cell surface receptor abundance estimation for single-cell RNA-sequencing data.

The rapid development of single-cell transcriptomics has revolutionized the study of complex tissues. Single-cell RNA-sequencing (scRNA-seq) can profile tens-of-thousands of dissociated cells from a tissue sample, enabling researchers to identify cell types, phenotypes and interactions that control tissue structure and function. A key requirement of these applications is the accurate estimation of cell surface protein abundance. Although technologies to directly quantify surface proteins are available, these data are uncommon and limited to proteins with available antibodies. While supervised methods that are trained on Cellular Indexing of Transcriptomes and Epitopes by Sequencing data can provide the best performance, these training data are limited by available antibodies and may not exist for the tissue under investigation. In the absence of protein measurements, researchers must estimate receptor abundance from scRNA-seq data. Therefore, we developed a new unsupervised method for receptor abundance estimation using scRNA-seq data called SPECK (Surface Protein abundance Estimation using CKmeans-based clustered thresholding) and primarily evaluated its performance against unsupervised approaches for at least 25 human receptors and multiple tissue types. This analysis reveals that techniques based on a thresholded reduced rank reconstruction of scRNA-seq data are effective for receptor abundance estimation, with SPECK providing the best overall performance. SPECK is freely available at https://CRAN.R-project.org/package=SPECK. Supplementary data are available at Bioinformatics Advances online.

Linking Expression of Cell-Surface Receptors with Transcription Factors by Computational Analysis of Paired Single-Cell Proteomes and Transcriptomes.

Complex signaling and transcriptional programs control the development and physiology of specialized cell types. Genetic perturbations in these programs cause human cancers to arise from a diverse set of specialized cell types and developmental states. Understanding these complex systems and their potential to drive cancer is critical for the development of immunotherapies and druggable targets. Pioneering single-cellmulti-omics technologies that analyze transcriptional states have been coupled with the expression of cell-surface receptors. This chapter describes SPaRTAN (Single-cell Proteomic and RNA-based Transcription factor Activity Network), a computational framework, to link transcription factors with cell-surface protein expression. SPaRTAN uses CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing) data and cis-regulatory sites to model the effect of interactions between transcription factors and cell-surface receptors on gene expression. We demonstrate the pipeline for SPaRTAN using CITE-seq data from peripheral blood mononuclear cells.

Specialized functions and sexual dimorphism explain the functional diversity of the myeloid populations during glioma progression

Malignant gliomas are aggressive, hard-to-treat brain tumors. Their tumor microenvironment is massively infiltrated by myeloid cells, mostly brain-resident microglia, bone marrow (BM)-derived monocytes/macrophages, and dendritic cells that support tumor progression. Single-cell omics studies significantly dissected immune cell heterogeneity, but dynamics and specific functions of individual subpopulations were poorly recognized. We use Cellular Indexing of Transcriptomes and Epitopes by sequencing (CITE-seq) to precisely dissect myeloid cell identities and functionalities in murine GL261 gliomas. We demonstrate that the diversity of myeloid cells infiltrating gliomas is dictated by cell type and cell state. Glioma-activated microglia are the major source of cytokines attracting other immune cells, whereas BM-derived cells show the monocyte-to-macrophage transition in the glioma microenvironment. This transition is coupled with a phenotypic switch from the IFN-related to antigen-presentation and tumor-supportive gene expression. Moreover, we found sex-dependent differences in transcriptional programs and composition of myeloid cells in murine and human glioblastomas.

1044. Identification and Characterization of an Unconventional NK Subset in COVID-19

Abstract Background Coronavirus Disease 2019 (COVID-19) caused by the SARS-CoV-2 virus is associated with dysregulation in the innate immune response including NK cells. NK cells are integral in the innate immune response against viral infections. Canonical NK cells are classified as CD56dim CD16+ and CD56bright CD16-. An unconventional subset of CD56dim CD16- NK cells has previously been identified in COVID-19 that is not present in other viral infections. Here we characterize phenotypic changes in the NK cells of patients with severe COVID-19 as work towards determining the functional status of this unconventional subset. Methods Peripheral blood mononuclear cells (PBMCs) and plasma were isolated from healthy donors (n=5) and patients with severe COVID-19 on Extra Corporeal Membrane Oxygenation (ECMO) (n=15). Primary NK cells were stimulated in vitro with plasma from patients with severe COVID-19 or healthy donors. Flow cytometry was used to phenotype the NK cells. A separate cohort of PBMC samples (n=7) from patients requiring hospitalization for COVID-19 underwent Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-Seq) analysis. Results The CD56bright CD16- NK subset was expanded in PBMCs from patients with severe COVID-19 as compared to healthy controls. CITE-Seq demonstrated that NK cells without surface CD16 clustered separately based on transcriptional profiling and did express FCGR3A at the translational level. Stimulation with COVID-19 plasma recapitulated the loss of CD16 from primary human NK cells and led to increased activity of Caspase 3/7. Figure 1.NK cells shift from the CD56dim CD16+ subset to the CD56dim CD16-subset in patients with severe COVID-19. a) Representative gating of NK cell subsets by Flow Cytometry in healthy and COVID-19 patient peripheral blood mononuclear cells (PBMCs). b) Percentage of total NK cells belonging to a particular cell subset compared between healthy donor samples (n=4) and COVID-19 patient samples (n=8). Data points represent an individual patient sample. Error bars represent the standard deviation of the mean. Differences between groups was analyzed using a two tailed t-test. *: p< 0.05, ns: not significant Figure 2.NK cells shift from the CD56dim CD16+ subset to the CD56dim CD16-subset after stimulation with COVID-19 plasma in vitro a) Representative gating of NK cell subsets by Flow Cytometry analysis in healthy donor NK cells stimulated by healthy plasma and COVID-19 patient plasma. b)Relative change in percentage of total NK cells belonging to a particular cell subset compared between healthy donor plasma (n=6)and COVID-19 patient plasma (n=15) stimulation conditions. Error bars represent the standard deviation of the mean and the difference between groups was analyzed using a two-tailed T-test. **: p< 0.01, ***: p< 0.001, ns: not significant. Conclusion We demonstrate and characterize a nonclassical population of CD56dim CD16- NK cells that are present in patients with severe COVID-19 and replicate this phenotype in vitro. Reproduction of this in vivo phenotype in an in vitro system will allow for additional studies on the functional state of NK cell subsets in COVID-19. The presence of this NK cell population may reflect a dysregulated innate immune response and immunopathogenesis of COVID-19. Disclosures All Authors: No reported disclosures.

Titration of 124 antibodies using CITE-Seq on human PBMCs

Single-cell RNA-sequencing (scRNA-Seq) is widely used to characterize immune cell populations. However, mRNA levels correlate poorly with expression of surface proteins, which are well established to define immune cell types. CITE-Seq (cellular indexing of transcriptomes and epitopes by sequencing) utilizes oligonucleotide-tagged antibodies to simultaneously analyze surface phenotypes and transcriptomes. Considering the high costs of adding surface phenotyping to scRNA-Seq, we aimed to determine which of 188 tested CITE-Seq antibodies can detect their antigens on human peripheral blood mononuclear cells (PBMCs), a commonly interrogated cell population in immunology, and find the optimal concentration for staining. The recommended concentration was optimal for 76 antibodies, whereas staining quality of 7 antibodies improved when the concentration was doubled. 33 and 8 antibodies still worked well when the concentration was reduced to 1/5 or 1/25, respectively. 64 antigens were not detected at any antibody concentration. Optimizing the antibody panel by removing antibodies not able to detect their target antigens and adjusting concentrations of the remaining antibodies will improve the analysis and may reduce costs. In conclusion, our data are a resource for building an informative and cost-effective panel of CITE-Seq antibodies and use them at their optimal concentrations in future CITE-seq experiments on human PBMCs.

Natural Compounds of Lasia spinosa (L.) Stem Potentiate Antidiabetic Actions by Regulating Diabetes and Diabetes-Related Biochemical and Cellular Indexes.

Natural biometabolites of plants have been reported to be useful in chronic diseases including diabetes and associated complications. This research is aimed to investigate how the biometabolites of Lasia spinosa methanol stem (MEXLS) extract ameliorative diabetes and diabetes-related complications. MEXLS was examined for in vitro antioxidant and in vivo antidiabetic effects in a streptozotocin-induced diabetes model, and its chemical profiling was done by gas chromatography-mass spectrometry analysis. The results were verified by histopathological examination and in silico ligand-receptor interaction of characterized natural biometabolites with antidiabetic receptor proteins AMPK (PDB ID: 4CFH); PPARγ (PDB ID: 3G9E); and mammalian α-amylase center (PDB ID: 1PPI). The MEXLS was found to show a remarkable α-amylase inhibition (47.45%), strong antioxidant action, and significant (p < 0.05) decrease in blood glucose level, serum aspartate aminotransferase (AST), alanine aminotransferase (ALT), low-density lipoprotein (LDL), urea, uric acid, creatinine, total cholesterol, triglyceride (TG), liver glycogen, creatinine kinase (CK-MB), and lactate dehydrogenase (LDH) and increase in serum insulin, glucose tolerance, and high-density lipoprotein (HDL). Rat's pancreas and kidney tissues were found to be partially recovered in histopathological analyses. Methyl α-d-galactopyranoside displayed the highest binding affinity with AMPK (docking score, -5.764), PPARγ (docking score, -5.218), and 1PPI (docking score, -5.615) receptors. Data suggest that the MEXLS may be an exciting source to potentiate antidiabetic activities affirming a cell-line study.

Application of Autological Adipose Tissue and its Products in the Treatment 
 of Infected Wounds of Different Genesis

Introduction. Transplantation of autologous adipose tissue and its products to stimulate the wound process is a rapidly developing area of ​​regenerative medicine. Adaptation of the technology to the conditions of infected wound treatment is a great challenge.The aim of the study was to determine the most effective and safe technologies for obtaining, processing and transplanting autologous adipose tissue used to treat infected wounds.Material and methods. The authors searched for relevant papers published in 2011 to 2021 in electronic databases PubMed, eLIBRARY, Embase, Cyberleninka, Web of Science. The analysis included 30 sources: 5 RCTs, 16 clinical studies, 3 case reports, 1 systematic review, 2 literature reviews, and 4 sources published before 2011 due to their fundamental and practical significance for the scope of the issue.Results and discussions. Although the lipoaspiration procedure in patients with infected wounds is described as standard conventional one, it still has a number of significant features that distinguish it from the standard technology of aesthetic surgery. To treat lipoaspirate, both enzymatic and mechanical options were used with the same frequency. The main technique of introducing adipose tissue products was local intradermal injections into the edges and under the wound bed; in a few cases, applications on the wound surface were used, or a combination of these options. As recorded, the cellularity index of adipose tissue products ranged from (min) 1x104/ml to (max) 50x106/ml. It should also be noted that a unified terminology for adipose tissue products used for wound treatment has not yet been adopted, but the most common term is stromal-vascular adipose tissue fraction.Conclusions. Systematization of literature data on the use of autologous adipose tissue products for wound treatment has shown that at present this technology is safe, provided with an accessible instrumental base, has positive results and is being actively developed. Further randomized clinical trials, involving extensive and multiple wounds, are required to determine the minimum effective and maximum tolerable dose in the treatment of wounds with adipose tissue products. In addition, it is promising to develop new means and approaches for delivering adipose tissue products in the treatment of infected wounds of various origins.

The Inter-Relationship between Thrombo-Inflammatory Biomarkers and Cellular Indices of Inflammation in Early-Stage Lung Cancer Patients

Introduction: Despite significant advances in treatment modalities, lung cancer continues to account for more than 18% of all cancer-related deaths globally. Although thrombo-inflammatory biomarkers have been implicated in the pathogenesis and progression of lung cancer, their true function in the augmentation and propagation of the tumoral microenvironment has yet to be comprehensively profiled. In this context, we aimed to characterize the thrombo-inflammatory biomarkers and blood cellular indices of inflammation in early-stage non-small lung cancer patients relative to healthy controls. Materials and Methods: Forty-nine NSCLC patient samples were collected from Loyola University Medical Center and compared to those of fifty healthy controls. Plasma levels of interleukin (IL)-1α, IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, vascular endothelial growth factor (VEGF), interferon (IFN)-γ, tumor necrosis factor (TNF)-α, monocyte chemo-attractant protein (MCP)-1, and endothelial growth factor (EGF) were measured utilizing commercially-available ELISA methods. Platelets, erythrocytes, hemoglobin, and hematocrit were measured in conjunction with the complete blood profile. Results: MCP1 and VEGF levels were found to be significantly elevated in NSCLC patients when compared to healthy controls (p<0.001), as seen in Figure 1. Differences between levels of IL-1α, IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, IFN-γ, and TNF-α, and EGF did not reach statistical significance, as shown in Table 1. Cellular indices of inflammation, such as the platelet-to-hemoglobin, platelet-to-red blood cell, and platelet-to-hematocrit ratios, demonstrated percent changes of -21.4%, 7.2%, and 1.0%, respectively. Conclusion: NSCLC patients demonstrated a significantly altered thrombo-inflammatory biomarker profile with notable correlations to blood cellular indices. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

The Role of Blood Cellular Indices in Diabetic Pulmonary Embolism Patients in Predicting Adverse Outcomes

The Role of Blood Cellular Indices in Diabetic Pulmonary Embolism Patients in Predicting Adverse Outcomes

Meis1 Establishes the Pre-Hemogenic Endothelial State Prior to Runx1 Expression

Hematopoietic Stem Cells (HSCs) are the most primitive cells of the hematopoietic system, defined by their ability to sustain lifelong hematopoiesis and differentiate to all mature hematopoietic lineages. HSC transplant (HSCT) is the first-line treatment for many patients diagnosed with a serious hematological disease, however HSCs are an exceedingly rare cell population that are challenging to expand ex vivo. Generating functional HSCs ex vivo from reprogrammed somatic cells or pluripotent stem cells (PSC) is a promising alternative. However, a gap remains in the knowledge of the developmental pathways regulating HSC ontogenesis, making it challenging to reproducibly engineer bona fide HSCs. Hematopoietic stem and progenitor cells (HSPCs) originate from an endothelial-to-hematopoietic transition (EHT) during embryogenesis. EHT is a step-wise process initiating when a specialized subset of endothelial cells (EC), termed hemogenic endothelial cells (HEC) undergo dyshesion from the endothelial bed and form intra-aortic hematopoietic clusters within the major arteries of the embryo. The processes driving the specification of these HEC rather than a vascular fate is not well understood, despite representing a critical need to replicate EHT in vitro. To define factors in the endothelium that prime EC towards a hemogenic phenotype, we performed Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) on CD31+ FACS-isolated cells from the aorta-gonad-mesonephros (AGM) of E10.5 wildtype mouse embryos (Figure 1). CITE-seq can simultaneously label cells based on surface protein markers and profile single-cell transcriptomes, therefore bypassing the need for isolation of rare cells by FACS. Unsupervised clustering based on single cell transcriptomes showed distinct populations of EC (composed of venous and arterial subpopulations), cells undergoing EHT that expressed both endothelial and hematopoietic genes, and mature hematopoietic cells. In addition to EC and EHT clusters, the CITE-seq data revealed a small population of pre-hemogenic endothelial cells (pre-HE) that was distinct from HE cells, which clustered with "EHT" cells (Figure 1). Pre-HE cells expressed high levels endothelial markers and Cd44, a marker recently associated with hemogenic potential, but lacked expression of the prototypic HE markers Runx1 and Gfi1(Figure 1). To look for drivers of hematopoietic cell fate we identified 12 transcription factors (TFs) that were upregulated between the arterial endothelial cells (aEC) and pre-HE clusters identified by CITE-Seq, and that persisted through EHT. Within this list, Meis1 ranked as being the most significantly enriched, with its binding partner Pbx1 ranked fourth, therefore we hypothesized that Meis1 may be required to drive early hemogenic specification. We generated embryos with endothelial-specific deletion of Meis1 to investigate the functional requirement for Meis1 in EC. Endothelial-specific deletion of Meis1 impaired the formation of functional Runx1-expressing HE which significantly impeded the emergence of pre-HSPC via EHT. In summary, we used a combination of CITE-seq and bulk RNA-seq to identify Meis1 as a candidate early functional marker of hemogenic specification. We show that Meis1 primes arterial endothelial cells towards the hemogenic trajectory, and that it is required in the mouse embryo for the formation of early pre-hemogenic cells prior to the emergence of functional HE and pre-HSPCs. Our findings implicate Meis1 in a critical fate-determining step for establishing EHT potential in endothelial cells. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Cooperation between Mutant IL7R and TLX3 Generates Mixed Myeloid/Lymphoid Leukemia from Thymocyte Progenitors

Acute lymphoblastic leukemia (ALL) is the most common cancer in children. Despite current pediatric treatment protocols that have resulted in 5-year overall survival rates up to 90%, treatments have substantial side effects. Therefore, it is important to identify more specific therapeutic targets and develop more effective and less toxic drugs and drug combinations. We have shown that overexpression of TLX3 in association with mutant IL7R (mutIL7R) is sufficient to generate aggressive leukemia from transduced CD4-CD8- (DN) thymocyte progenitors. To better understand mutIL7R/TLX3-mouse leukemia, we combined single cell RNA sequencing (scRNAseq), Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq), DNA Next Generation Sequencing (NGS) and flow cytometry to explore the cooperation of mutIL7R and TLX3 in orchestrating leukemogenesis. We found that mutIL-7R+TLX3 induced murine mixed T/myeloid leukemia. Myeloid cell clones (CD11b+) expressed identical TCR rearrangements with T cell clones (CD8+), indicating that mutant IL-7R+TLX3 generates mixed leukemia from T cell progenitors. Moreover, the passaged leukemia lost the T-cell phenotype and acquired a pro-B-like phenotype, suggesting preferential expansion of pro-B cells (CD19+, B220+ IgM-), which were not detected in the founder leukemia presumably due to its low frequency. We next sought to determine whether the oncogene combination is sufficient to drive a similar immunophenotype profile in vitro. We showed that ectopic expression of mutIL7R and TLX3 in DN primary thymocytes pushed the cells to myeloid (CD11b+, Gr1+) and B-cell (B220) phenotype over a time course of 4, 8 and 20 days, while T-cell development was blocked, suggesting that TLX3 expression prevented differentiation into CD4+/CD8+ T-cells. To further characterize the mixed T/myeloid leukemia at the molecular level, we compared the leukemia expressed genes to a TLX-bound genes public dataset. We found that 42 TLX3 target genes are expressed in mutIL7R+TLX3 leukemia. Interaction network analysis suggested significant Myc stimulation. We then confirmed Myc upregulation at the protein level in a thymocyte cell line, indicating that mutIL7R alone induces Myc but requires TLX-3 cooperation to induce maximal Myc expression levels. Taken together, we generated a high-resolution dataset with detailed information about the transcriptional landscape and immunophenotype of leukemia generated by mutIL-7R+TLX3, a combination that is observed in patient samples, and suggests new therapeutic drug strategies. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal