S100 Proteins As an Important Regulator of Macrophage Inflammation

Xia, Chang; Braunstein, Zachary; Toomey, Amelia C.; Zhong, Jixin; Rao, Xiaoquan

doi:10.3389/fimmu.2017.01908

Cited by 329 publications

(294 citation statements)

References 168 publications

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“…The circular chart represents the percentages of proteins altered in both ischemic groups (SE and SC) compared to shams (SH), on days 2 and 4: upregulated (red ) or downregulated proteins (green ) in SE and SC mice; proteins only modified in SC (dark blue ) or in SE mice (light blue ); proteins identified in ischemic mice (SC, SE) but not in SH (purple ); others changes (yellow ). Additionally, the number of proteins differently expressed, with different patterns within the groups described in the main chart is shown: upregulated (a) or downregulated (b) proteins in SE and SC vs SH, proteins only modified in SC (c) or in CAC-treated mice (d) intracellular and extracellular functions participating in proliferation, differentiation, apoptosis, Ca 2+ homeostasis, energy metabolism, inflammation, leukocyte adhesion and migration, and tissue repair [75,76]. Among others, the release of S100A8/A9 has been suggested to facilitate monocyte and neutrophil transmigration.…”

Section: Discussionmentioning

confidence: 99%

Identification of the initial molecular changes in response to circulating angiogenic cells-mediated therapy in critical limb ischemia

et al. 2020

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Background: Critical limb ischemia (CLI) constitutes the most aggressive form of peripheral arterial occlusive disease, characterized by the blockade of arteries supplying blood to the lower extremities, significantly diminishing oxygen and nutrient supply. CLI patients usually undergo amputation of fingers, feet, or extremities, with a high risk of mortality due to associated comorbidities. Circulating angiogenic cells (CACs), also known as early endothelial progenitor cells, constitute promising candidates for cell therapy in CLI due to their assigned vascular regenerative properties. Preclinical and clinical assays with CACs have shown promising results. A better understanding of how these cells participate in vascular regeneration would significantly help to potentiate their role in revascularization. Herein, we analyzed the initial molecular mechanisms triggered by human CACs after being administered to a murine model of CLI, in order to understand how these cells promote angiogenesis within the ischemic tissues.

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Section: Discussionmentioning

confidence: 99%

Identification of the initial molecular changes in response to circulating angiogenic cells-mediated therapy in critical limb ischemia

et al. 2020

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“…From tGPLVM, we can observe this separation from different expression patterns in progenitor cells across dimensions. Dimension three correlates with myeloid cells, demonstrated visually by marker TYROBP (Tomasello and Vivier, 2005) (Pearson’s r = 0.647; Figure 4), in addition to correlations with macrophage-associated genes (Donato et al; Xia et al, 2018) S100A4 (Pearson’s r = 0.623) and S100A6 (Pearson’s r = 0.665). Dimension two correlates to lymphoid cells, visualized by marker LTB (Browning et al, 1993) (Pearson’s r = 0.306; Figure 4), and further supported by correlation with lymphocyte specific protein-1 LSP1 (Pearsons’s r = 0.481).…”

Section: Resultsmentioning

confidence: 94%

A robust nonlinear low-dimensional manifold for single cell RNA-seq data

Verma

Engelhardt

2018

Preprint

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Modern developments in single cell sequencing technologies enable broad insights into cellular state. Single cell RNA sequencing (scRNA-seq) can be used to explore cell types, states, and developmental trajectories to broaden understanding of cell heterogeneity in tissues and organs. Analysis of these sparse, high-dimensional experimental results requires dimension reduction. Several methods have been developed to estimate low-dimensional embeddings for filtered and normalized single cell data. However, methods have yet to be developed for unfiltered and unnormalized count data. We present a nonlinear latent variable model with robust, heavy-tailed error and adaptive kernel learning to estimate low-dimensional nonlinear structure in scRNA-seq data. Gene expression in a single cell is modeled as a noisy draw from a Gaussian process in high dimensions from low-dimensional latent positions. This model is called the Gaussian process latent variable model (GPLVM). We model residual errors with a heavy-tailed Student's t-distribution to estimate a manifold that is robust to technical and biological noise. We compare our approach to common dimension reduction tools to highlight our model's ability to enable important downstream tasks, including clustering and inferring cell developmental trajectories, on available experimental data. We show that our robust nonlinear manifold is well suited for raw, unfiltered gene counts from high throughput sequencing technologies for visualization and exploration of cell states. 62 factor analysis (ZIFA) (Pierson and Yau), t-SNE (Van Der Maaten and Hinton) (perplex-63 ity set to default 30), and PCA (Hotelling, 1933) were tested as comparison methods. To 64 evaluate the robust adaptations of the tGPLVM model, we fit tGPLVM with only an SE 65 kernel or SE and Matérn 1/2 kernel as well as tGPLVM with normally distributed error. 66 Trajectory building with minimum spanning trees 67 tGPLVM was used to fit a two dimensional latent mappings for the Lonnberg (Lönnberg 68 et al., 2017) developmental data. The minimum spanning tree was found on Euclidean 69 distance matrix of the posterior means of the low dimensional embedding and compared 70 to sequencing time to verify correct ordering. The same analysis was performed with 71 ZIFA (Pierson and Yau), t-SNE (Van Der Maaten and Hinton) (perplexity set to default 72 30), and PCA (Hotelling, 1933). 73 Visualization of sparse, raw count matrices 74 tGPLVM was used to fit a three-dimensional mapping for the two 10x data sets, CD34+ 75 cells and mice brain cells. Pearson correlation between latent position posterior mean and 76 expression counts was used to identify genes associated with latent dimensions. ZIFA (Pier-77 son and Yau), t-SNE (Van Der Maaten and Hinton) (perplexity set to default 30), and 78 PCA (truncated SVD (Halko et al.)) were also fit to the CD34+ cell data to compare 79 computational time.

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“…The S100a7a protein (also called S100a15 or Koebnerisin) is belonging to a subgroup of S100 proteins which has mainly an extracellular function. It is enrolled in the inflammatory process, especially in the epidermis where its level is increased and amplified acting as F I G U R E 1 Clinical presentation of a study group patient before (left) and after (right) the therapeutic trial T A B L E 2 Mean S100a7a protein level in study and control groups before and after therapeutic trial chemoattractants for the immune cells (Xia, Braunstein, Toomey, Zhong, & Rao, 2018). The current study showed a high level of this protein among patients with acne vulgaris in both groups before therapeutic trial, which coinsides with the results of Borovaya et al (2014) and Batycka-Baran et al (2015), Batycka-Baran et al (2019) who also found a significant increase of this antimicrobial peptide in chronic inflammatory skin lesions of different dermatoses, which was caused by epidermal keratinocytes overproduction.…”

Section: Discussionmentioning

confidence: 99%

Downregulation of S100a7a antimicrobial peptide in acne vulgaris patients after isotretinoin therapy

Al‐Sudany¹,

Mohammed

Alrifai³

2019

Dermatologic Therapy

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The S100a7a protein is expressed in keratinocytes, its level is increased in acne condition. As isotretinoin therapy is known to alter some of S100 peptides, these could be important specific targets for acne therapy and may have an important role in clinical remission. A randomized controlled trial was held in a dermatology clinic in Baghdad, where 30 patients with moderate to severe acne vulgaris condition aged 16–31 years were enrolled. Five milliliters of venous blood samples were taken before and after 6 weeks of isotretinoin therapeutic trial. A placebo‐control group of 26 acne patients was also enrolled. The S100a7a peptide was measured in both groups using the ELISA technique before and after the trial. High levels of serum S100a7a were found in acne patients of both groups before therapeutic trial. Following the trial, a significant statistical difference (p = .0003) was noticed between mean S100a7a protein level of study and control groups. By comparing the mean S100a7a protein level before and after isotretinoin therapy in the study group, a highly significant statistical difference was also found (p = .001). The current study showed a downregulatory effect of isotretinoin therapy on the S100a7a peptide mean level.

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S100 Proteins As an Important Regulator of Macrophage Inflammation

Cited by 329 publications

References 168 publications

Identification of the initial molecular changes in response to circulating angiogenic cells-mediated therapy in critical limb ischemia

Identification of the initial molecular changes in response to circulating angiogenic cells-mediated therapy in critical limb ischemia

A robust nonlinear low-dimensional manifold for single cell RNA-seq data

Downregulation of S100a7a antimicrobial peptide in acne vulgaris patients after isotretinoin therapy

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