Rita Spirito’s research while affiliated with Centro Cardiologico Monzino and other places

What is this page?


This page lists works of an author who doesn't have a ResearchGate profile or hasn't added the works to their profile yet. It is automatically generated from public (personal) data to further our legitimate goal of comprehensive and accurate scientific recordkeeping. If you are this author and want this page removed, please let us know.

Publications (95)


Supplementary_Material_Piacentini_et_al.pdf
  • Data
  • File available

December 2023

·

6 Reads

·

·

Pablo Jos\`e Werba

·

[...]

·

Download

Deciphering abdominal aortic diseases through T-cell clonal repertoire of perivascular adipose tissue

December 2023

·

32 Reads

·

1 Citation

Recent studies suggested that immune-mediated inflammation of perivascular adipose tissue (PVAT) of abdominal aortic aneurysms (AAA) contributes to disease development and progression. Whether the PVAT of AAA is characterized by a specific adaptive immune signature remains unknown. To investigate this hypothesis, we sequenced the T-cell receptor β-chain (TCRβ) in the PVAT of AAA patients and compared with patients with aortic occlusive disease (AOD), who share with the former anatomical site of the lesion, risk factors but differ in pathogenic mechanisms. Our results demonstrate that AAA patients have a lower repertoire diversity than those with AOD and significant differences in V/J gene segment usage. Furthermore, we identified a set of 7 public TCRβ clonotypes that distinguished AAA and AOD with very high accuracy. We also found that the TCRβ repertoire differentially characterizes small and large AAA (aortic diameter <55 mm and ≥55 mm, respectively). This work supports the hypothesis that T-cell-mediated immunity is fundamental in AAA pathogenesis and opens up new clinical perspectives. Summary Different immune mechanisms may play a key role in the pathogenesis of distal aortic aneurysm and aortoiliac occlusive disease. The TCRβ repertoire of perivascular adipose tissue differs between the two pathologic conditions, suggesting the involvement of specific antigen-specific immune responses.


Representative mono-dimensional profiles of both LDL (panel A) and HDL (panel B) fractions purified by isopycnic salt gradient ultracentrifugation followed by a further ultracentrifugation step. Fractions were desalted and concentrated using centrifugal filter units with 10 KDa cut-off and resolved by SDS-PAGE in 5% T (panel A) or 15% T (panel B) gels. Grey arrowhead indicates the apolipoprotein B100 band (>550 kDa MW) (panel A), and white arrowhead indicates the apolipoprotein AI band (≃28 kDa MW) (panel B). In both panels, the black arrowheads indicate where the albumin (≃66 kDa MW) band would be located.
Venn diagram showing the distribution between HDL and LDL of the 155 proteins identified. The two lipoprotein fractions shared 61 proteins, whereas 68 and 26 proteins were exclusive to HDL and LDL, respectively.
Gene Ontology (GO) analysis of the 21 proteins identified in this study, which are not yet included in the “likely” LDL proteins list of the Davidson’s Lab database (http://www.DavidsonLab.com, last update 24 April 2019), already reported by either Dashty et al. [25] or Bancells et al. [50] to be associated with LDL.
Protein–protein interaction (PPI) network and Gene Ontology (GO) analysis of differentially expressed proteins in HDL “hard” plaques (A,B, respectively) and HDL “soft” plaques (C,D, respectively), showing the biological processes in which these proteins are involved. Colors of nodes in PPI networks are representative of FCs compared to controls.
Protein–protein interaction (PPI) network and Gene Ontology (GO) analysis of differentially expressed proteins in LDL “hard” plaques (A,B, respectively) and LDL “soft” plaques (C,D, respectively), showing the biological processes in which these proteins are involved. Colors of nodes in PPI networks are representative of FCs compared to controls.

+1

Apolipoprotein Signature of HDL and LDL from Atherosclerotic Patients in Relation with Carotid Plaque Typology: A Preliminary Report

September 2021

·

76 Reads

·

10 Citations

In the past years, it has become increasingly clear that the protein cargo of the different lipoprotein classes is largely responsible for carrying out their various functions, also in relation to pathological conditions, including atherosclerosis. Accordingly, detailed information about their apolipoprotein composition and structure may contribute to the revelation of their role in atherogenesis and the understanding of the mechanisms that lead to atherosclerotic degeneration and toward vulnerable plaque formation. With this aim, shotgun proteomics was applied to identify the apolipoprotein signatures of both high-density and low-density lipoproteins (HDL and LDL) plasma fractions purified from healthy volunteers and atherosclerotic patients with different plaque typologies who underwent carotid endarterectomy. By this approach, two proteins with potential implications in inflammatory, immune, and hemostatic pathways, namely, integrin beta-2 (P05107) and secretoglobin family 3A member 2 (Q96PL1), have been confirmed to belong to the HDL proteome. Similarly, the list of LDL-associated proteins has been enriched with 21 proteins involved in complement and coagulation cascades and the acute-phase response, which potentially double the protein species of LDL cargo. Moreover, differential expression analysis has shown protein signatures specific for patients with “hard” or “soft” plaques.


Patient flow chart. The number in the brackets indicates the number of patients. AVSc, aortic valve sclerosis; CEA, carotid endarterectomy.
Cumulative incidence curves for 5-year all-cause mortality. (A) All-cause mortality was compared between CEA patients with (red dash line) and without (black solid line) aortic valve sclerosis (AVSc). (B) Inset of (A) to better evidence the differences between the two groups. (C) Breakdown of the patients at risk per year in the two groups. (D) Cox regression analysis showing the hazard ratio (HR) unadjusted and adjusted for age (Model 1), for age and estimated glomerular filtration rate (eGFR; Model 2), and for age, eGFR, and left ventricular ejection fraction (LVEF; Model 3).
Cumulative incidence curves for 5-year all-cause mortality in patients with mixed-fibrotic carotid plaque. (A) All-cause mortality was compared between CEA patients with (red dash line) and without (black solid line) aortic valve sclerosis (AVSc). (B) Inset of (A) to better evidence the differences between the two groups. (C) Breakdown of the patients at risk per year in the two groups. (D) Cox regression analysis showing the hazard ratio (HR) unadjusted and adjusted for age (Model 1), for age and estimated glomerular filtration rate (eGFR; Model 2), and for age, eGFR, and left ventricular ejection fraction (LVEF; Model 3).
Predictive ability of eGFR and AVSc for the 5-year all-cause mortality in patients with mixed-fibrotic plaque. (A) The average performance of the three logistic models are shown as ROC curves, where the predictors are aortic valve sclerosis (AVSc; dash black line), estimated glomerular filtration rate (eGFR; dot blue line), and the combination of AVSc and eGFR (red solid line). The grids represent the 1,000 bootstrap iterations (ROC curves) plotted for AVSc (gray), eGFR (light blue), and the combination of AVSc and eGFR (orange). (B) Acc, Classification accuracy; Spe, specificity; Sen, sensitivity; PPV, positive predicted value; NPV, negative predicted value; AUC, area under the ROC curve are summarized as mean and 95% CI for each model took into account.
Aortic Valve Sclerosis as an Important Predictor of Long-Term Mortality in Patients With Carotid Atheromatous Plaque Requiring Carotid Endarterectomy

May 2021

·

36 Reads

·

5 Citations

Background: A strong association between aortic valve sclerosis (AVSc), the earliest manifestation of calcific aortic valve disease, and atherosclerosis exists. The aim of the study was to evaluate the predictive capabilities of AVSc on long-term all-cause mortality, in patients requiring carotid endarterectomy (CEA). Methods and Results: 806 consecutive CEA patients were enrolled. Preoperative echocardiography was used to assess AVSc. Computed tomography angiography was applied for plaque characterization. Kaplan-Meier curves, Cox linear regression, and area under the receiving operator characteristic (AUC) curve analyses were used to evaluate the predictive capability of AVSc. Overall, 348 of 541 patients had AVSc (64%). Age, diabetes, and estimated glomerular filtration rate (eGFR) were associated with AVSc. In the 5-year follow-up, AVSc group had a mortality rate of 16.7% while in no-AVSc group was 7.8%. Independent predictors of all-cause mortality were age, sex, eGFR, left ventricular ejection fraction, and AVSc. After adjustments, AVSc was associated with a significant increase in all-cause mortality risk (hazard ratio, HR = 1.9; 95%CI: 1.04–3.54; p = 0.038). We stratify our cohort based on carotid atheromatous plaque-type: soft, calcified, and mixed-fibrotic. In patients with mixed-fibrotic plaques, the mortality rate of AVSc patients was 15.5% compared to 2.4% in no-AVSc patients. In this group, AVSc was associated with an increased long-term all-cause mortality risk with an adjusted HR of 12.8 (95%CI: 1.71–96.35; p = 0.013), and the AUC, combing eGFR and AVSc was 0.77 ( p < 0.001). Conclusions: Our findings indicate that AVSc together with eGFR may be used to improve long-term risk stratification of patients undergoing CEA surgery.


Transcriptome profiling of the perivascular adipose tissue of aortic occlusive disease reveals dysregulation of genes involved in vessel tone and remodelling

December 2020

·

27 Reads

Atherosclerosis

Background and Aims: Perivascular adipose tissue (PVAT) helps regulate arterial homeostasis and can play a role in the pathogenesis of large vessel diseases. We investigated whether the PVAT of aortic occlusive lesions displays specific, pathophysiology-linked gene-expression patterns. Methods: We enrolled eleven patients (51-79 years) with peripheral artery disease undergoing elective surgery, presenting with either an aortoiliac occlusive disease (AIOD, n=6) or diffuse stenosis of the common iliac arteries and/or aorta (n=5). Using a microarray-based genome-wide approach, we compared the transcriptome of the PVAT surrounding the distal aorta (atherosclerotic lesion) vs. the proximal aorta (plaque-free segment) and vs. other adipose tissue (AT) depots, both within and between groups. Cutting-edge data mining procedures allowed increasing the overall sensitivity and power of the analysis. Results: We found that the PVAT of the distal aorta in both AIOD and stenotic patients lacks locally restricted gene-expression patterns. On the contrary, a specific gene expression profile distinguished the PVAT of AIOD from stenotic patients, irrespective of fat localization (perilesional or proximal). Functional enrichment analysis revealed that this signature was associated with pathways related to cholesterol metabolism, vessel tone regulation, and remodelling, including TGF-β and SMAD signalling. We observed that also gene-expression profiles in omental-visceral or subcutaneous fat were able to distinguish between the two patient groups, suggesting that the atherosclerosis burden is associated with systemic alterations in AT. Conclusions: Our work sheds new light on the potential role of PVAT and, possibly, other adipose tissues in the pathophysiological mechanisms underlying peripheral atherosclerotic disease, including the abdominal aortic occlusive forms.


Figure 1. Unsupervised clustering of AT samples by PCA. Scatterplot of the first two principal components (PC1 and PC2) obtained from the PCA performed on the whole gene-expression dataset. PC1 and PC2 explained together 33% variance and allowed discriminating the different AT samples. Patients with aortic occlusive (red) and stenotic lesions (blue) tend to form two distinct sub-clusters within each AT. Circle, triangle, plus and square shapes associate, respectively, with DA-PVAT, Px-PVAT, subcutaneous (S) and omental-visceral (V) AT. Numbers refer to patient's paired-samples.
Figure 4. Enrichment network for Oc-vs.St-PVAT comparison. The enrichment network shows the pathway/ GO-BP gene-sets (nodes) that are significantly associated (FDR < 0.05) either with Oc-or St-PVAT. The node color refers to the association with the phenotype (Oc-PVAT, red; St-PVAT, blue); node gradient color is proportional to the gene-set normalized enrichment score (NES), from lower (light) to higher (dark); node size is proportional to the gene-set size. Edges connect related pathways/GO-BPs. Edge thickness is proportional to the similarity between two pathway/GO-BP, for a cut-off = 0.15 of the combined Jaccard plus Overlap coefficient. To simplify network reading, only relevant gene-sets are labeled with the name reported in Reactome or GO-BP gene-set collection. Enrichment network was drawn using the Enrichment Map software v.3.2.0, implemented as a plug-in in the Cytoscape v.3.7.0 platform.
PVAT differential expression analysis. Scatterplot of the log2 FC vs. the significance (x-and y-axis, respectively) for the paired DA-PVAT vs. Px-PVAT comparison within patients with aortic occlusive (A) or stenotic (B) lesions, and for the comparison between PVAT of patients with aortic occlusive vs. stenotic lesions (C). Significant DE transcripts with an absolute log2 FC ≥ 0.38 at nominal P-Value < 0.01 are represented by pink and light blue dots, whereas red and dark blue dots mark the transcripts that stood adjustment for multiple testing (adj.P-Value < 0.05). For the latter comparison, the top five up/down DE transcripts with the highest combined rank-score (the product of the log2 FC and the -log10 P-value) are shown.
Unsupervised clustering of AT samples by PCA based on PVAT DE transcripts. Scatterplot of the first two principal components (PC1 and PC2) obtained from the PCA performed on the expression matrix of the 210 DE transcripts obtained by comparing Oc vs. St-PVAT, for PVAT samples (A) and omental-visceral (V), subcutaneous (S) AT (B). PC1 and PC2 explained together 80% and 66% variance for PVAT and V-S depots, respectively, allowing discriminating most of the Oc- vs. St-patients. Red and blue colors represent Oc- and St-patients, respectively. Circle, triangle, plus and square shapes associate, respectively, with DA-PVAT, Px-PVAT, subcutaneous and omental-visceral AT. Numbers refer to patient’s paired-samples.
Gene-expression profiles of abdominal perivascular adipose tissue distinguish aortic occlusive from stenotic atherosclerotic lesions and denote different pathogenetic pathways

April 2020

·

54 Reads

·

11 Citations

Perivascular adipose tissue (PVAT) helps regulate arterial homeostasis and plays a role in the pathogenesis of large vessel diseases. In this study, we investigated whether the PVAT of aortic occlusive lesions shows specific gene-expression patterns related to pathophysiology. By a genome-wide approach, we investigated the PVAT transcriptome in patients with aortoiliac occlusive disease. We compared the adipose layer surrounding the distal aorta (atherosclerotic lesion) with the proximal aorta (plaque-free segment), both within and between patients with complete aortoiliac occlusion (Oc) and low-grade aortic stenosis (St). We found that PVAT of the distal versus proximal aorta within both Oc-and St-patients lacks specific, locally restricted gene-expression patterns. Conversely, singular gene-expression profiles distinguished the PVAT between Oc-and St-patients. Functional enrichment analysis revealed that these signatures were associated with pathways related to metabolism of cholesterol, vessel tone regulation, and remodeling, including TGF-β and SMAD signaling. We finally observed that gene-expression profiles in omental-visceral or subcutaneous fat differentiated between Oc-and St-patients, suggesting that the overall adipose component associates with a different atherosclerosis burden. Our work points out the role of PVAT and, likely, other adipose tissues play in the pathophysiological mechanisms underlying atherosclerotic disease, including the abdominal aortic occlusive forms.


Figure 1. Differential expression between dilated vs nondilated abdominal aortic aneurysm (AAA) perivascular adipose tissues. A, Scatterplot of the log 2 fold-change (FC) vs the significance (x and y axis, respectively) for the paired dilated aortic perivascular adipose tissue (D-PVAT) vs nondilated (ND)-PVAT comparison. Pink and light blue dots represent significant differentially expressed (DE) transcripts at nominal P value <0.01, whereas red and dark blue dots mark the transcripts that stood adjustment for multiple testing (adjusted P value <0.05), with an absolute log 2 FC ≥0.38. The top 5 up/down DE transcripts with the highest combined rank-score (the product of the log 2 FC×the −log 10 P value) are shown. B, Scatterplot of the first 2 principal components (PC1 and PC2) obtained from the Principal Component Analysis performed on the 335 DE transcripts. PC1 and PC2 explained together 60% variance and allowed discriminating most of the PVAT samples. Red dots and blue triangles represent the D-PVAT and NDPVAT samples, respectively. Numbers refer to patient's paired samples.
Figure 2. Differential expression analysis between perivascular adipose depots in large and small abdominal aortic aneurysm (AAA) samples. The figure shows the scatterplots of the log 2 fold-change (FC) vs the significance (x and y axis, respectively) for the paired dilated aortic perivascular adipose tissue (D-PVAT) vs nondilated (ND)-PVAT comparison in large (A) and small (B) AAA. The legend scheme is as in Figure 1A. ALKAL2 indicates ALK and LTK ligand 2; AP-1, transcription factor subunit; CAP2, cyclase-associated actin cytoskeleton regulatory protein 2; CYR61, cysteine-rich angiogenic inducer 61; DES, desmin; DUSP1, dual specificity phosphatase 1; EGR1, early growth response 1; FOS, Fos proto-oncogene; FOSB, FosB proto-oncogene; HOXC8, homeobox C8; KCNMB1, potassium calcium-activated channel subfamily M regulatory beta subunit 1; LDOC1, leucine zipper down-regulated in cancer 1, regulator of NFKB signaling; MYL9, myosin light chain 9; MYH11, myosin heavy chain 11; and SLN, sarcolipin.
Figure 3. Enrichment map for dilated aortic perivascular adipose tissue (D-PVAT) vs nondilated (ND)-PVAT comparison in all abdominal aortic aneurysm (AAA) samples. The enrichment network shows the pathway/gene ontology (GO)-biological processes (BP) gene sets (nodes) that are significantly associated (false discovery rate <0.05) either with D-PVAT or ND-PVAT. The node color refers to the association with the phenotype (D-PVAT, red and ND-PVAT, blue); node gradient color is proportional to the gene-set normalized enrichment score (NES), from lower (light) to higher (dark); node size is proportional to the gene-set size. Edges connect related pathways/GO-BPs. Edge thickness is proportional to the similarity between 2 pathway/GO-BP, for a cutoff=0.15 of the combined Jaccard plus Overlap coefficient. FC indicates fold-change; IFN, interferon; IL, interleukin; and TRIF, TIR domain-containing adaptor protein including IFN-β.
Figure 4. Enrichment map of pathways/gene ontology (GO)-biological processes (BPs) related to disease severity. The network shows the significant gene sets (false discovery rate <0.05) that are enriched in the comparison between dilated aortic perivascular adipose tissue (D-PVAT) vs nondilated (ND)-PVAT uniquely within large abdominal aortic aneurysm (AAA). The legend scheme is as in Figure 3.
Figure 5. Hierarchical clustering by inflammatory/immune response transcripts. The heat map shows that unsupervised clustering based on transcripts related to regulation of inflammatory response and lymphocytes activation strongly associate with the dilated aortic perivascular adipose tissue (D-PVAT) phenotype (red bricks of the first row) because allowed separating 27 out of 30 D-PVAT samples from nondilated (ND)-PVAT (blue), visceral (pink), and subcutaneous (green) adipose tissue (AT). Hierarchical clustering was performed by Euclidean metric and average linkage method; transcripts expression levels are displayed as gradient colors from higher (dark red) to lower (dark blue). IL indicates interleukin; and TLR, Toll-like receptor.
Genome-Wide Expression Profiling Unveils Autoimmune Response Signatures in the Perivascular Adipose Tissue of Abdominal Aortic Aneurysm

February 2019

·

666 Reads

·

46 Citations

Arteriosclerosis Thrombosis and Vascular Biology

Objective— Perivascular adipose tissue (PVAT) is thought to play a role in vascular homeostasis and in the pathogenesis of large vessel diseases, including abdominal aortic aneurysm (AAA). Herein, we tested the hypothesis that locally restricted transcriptional profiles characterize PVAT surrounding AAA, indicating specific dysfunctions associated with the disease. Approach and Results— Using a paired sample design to limit the effects of interindividual variation, we performed a microarray-based investigation of the PVAT transcriptome in 30 patients with AAA, comparing the adipose layer of the dilated abdominal aorta with that of the not-dilated aortic neck in each patient. Furthermore, we used a state-of-the-art data mining procedure to remove the effect of confounders produced by high-throughput gene expression techniques. We found substantial differences in PVAT gene expression clearly distinguishing the dilated from the not-dilated aorta, which increased in number and magnitude with increasing AAA diameter. Comparisons with other adipose depots (omental or subcutaneous fat) confirmed that gene expression changes are locally restricted. We dissected putative mechanisms associated with AAA PVAT dysfunction through a functional enrichment network analysis: both innate and adaptive immune-response genes along with genes related to cell-death pathways, metabolic processes of collagen, sphingolipids, aminoglycans, and extracellular matrix degradation were strongly overrepresented in PVAT of AAA compared with PVAT of the not-dilated aorta. Conclusions— Our results support a possible function of PVAT in AAA pathogenesis and suggest that AAA is an immunologic disease with an underlying autoimmune component. Interfering with these disease-specific pathways would clarify their precise role in AAA pathogenesis.



Identification of differentially expressed plasma proteins in atherosclerotic patients with type 2 diabetes

March 2016

·

32 Reads

·

27 Citations

Journal of Diabetes and its Complications

Besides hyperglycaemia and insulin resistance, several factors are associated with a higher cardiovascular risk in type 2 diabetes mellitus (T2DM), many of them being closely related to each other owing to common origins or pathways. The pathophysiological mechanisms underlying vascular dysfunctions in diabetes include reduced bioavailability of nitric oxide, increased ROS and prothrombotic factors production, as well as activation of receptors for advanced glycation end-products. These alterations contribute to create a pro-inflammatory/thrombotic state that ultimately leads to plaque formation and complication. This study aimed at identifying differentially expressed plasma proteins between T2DM and non-diabetic patients undergoing carotid endarterectomy, by means of two-dimensional electrophoresis coupled with LC-MS/MS. Before analysis, plasma samples were enriched in low-expression proteins through combinatorial hexapeptide ligand libraries. Both mono- and two-dimensional western blotting were performed for data validation. Differentially expressed proteins were mapped onto STRING v10 to build a protein–protein interaction network. Sixteen differentially expressed spots were identified with a high score. Among them, there were fibrinogen beta and gamma chains, complement C1r, C3 and C4-B subcomponents, alpha-1-antitrypsin (AAT), vitronectin and CD5 antigen-like. Protein–Protein interaction analysis evidenced a network among differentially expressed proteins in which vitronectin seems to represent a potentially pivotal node among fibrinolysis, complement dependent immune responses and inflammation in accordance with a number of in vitro and in vivo evidences for a contributory role of these proteins to the development of diabetic atherosclerosis.


Characterization of the Pall Celeris system as a point-of-care device for therapeutic angiogenesis

May 2015

·

1,063 Reads

·

39 Citations

Cytotherapy

The Pall Celeris system is a filtration-based point-of-care device designed to obtain a high concentrate of peripheral blood total nucleated cells (PB-TNCs). We have characterized the Pall Celeris-derived TNCs for their in vitro and in vivo angiogenic potency. PB-TNCs isolated from healthy donors were characterized through the use of flow cytometry and functional assays, aiming to assess migratory capacity, ability to form capillary-like structures, endothelial trans-differentiation and paracrine factor secretion. In a hind limb ischemia mouse model, we evaluated perfusion immediately and 7 days after surgery, along with capillary, arteriole and regenerative fiber density and local bio-distribution. Human PB-TNCs isolated by use of the Pall Celeris filtration system were shown to secrete a panel of angiogenic factors and migrate in response to vascular endothelial growth factor and stromal-derived factor-1 stimuli. Moreover, after injection in a mouse model of hind limb ischemia, PB-TNCs induced neovascularization by increasing capillary, arteriole and regenerative fiber numbers, with human cells detected in murine tissue up to 7 days after ischemia. The Pall Celeris system may represent a novel, effective and reliable point-of-care device to obtain a PB-derived cell product with adequate potency for therapeutic angiogenesis. Copyright © 2015 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.


Citations (59)


... Yet another cell type found in PVAT are immunocytes of the adaptive immune system. Piacentini et al. identified a diverse clonal repertoire of T lymphocytes in PVAT depots in rodents [48], with some found also in humans [49]. The authors hypothesized that the repertoire of T cells in PVAT differs between pathological conditions thus suggesting the involvement of specific antigen-specific immune responses. ...

Reference:

Physiology and Pathobiology of Perivascular Adipose Tissue: Inflammation-based
Deciphering abdominal aortic diseases through T-cell clonal repertoire of perivascular adipose tissue

... However, due to the inherent problems in extracting them from the extracellular lipid-rich matrixes, diagnostic methods rely heavily upon genotyping, imaging, and immunosorbent assays which are time-consuming and not cost-effective. Though there have been several reports on lipoproteomics [66], sample heterogeneity, complexities in lipoproteome purification, and varying mass spectrometry analysis performance have resulted in differences from study to study [67]. To our knowledge, this is the first DIAbased targeted proteomics verification of a high APOB/APOA1 ratio found in complicated atheroma lesions, as shown in Figures 3 and 4, inferring a higher occurrence of erosion, rupture, and calcification. ...

Apolipoprotein Signature of HDL and LDL from Atherosclerotic Patients in Relation with Carotid Plaque Typology: A Preliminary Report

... In addition, the diversity within our patient population, encompassing various age groups, sexes, and comorbidities, strengthens the potential relevance of our findings to a broader spectrum of patients with AVSc. Furthermore, our findings are consistent with those of previous research, 3,4,[35][36][37] which reinforce the notion that AVSc is associated with adverse cardiovascular outcomes. By continuing to unravel the intricate molecular mechanisms underlying this condition, our work may contribute to improved diagnosis and screening, offering potential benefits to patients affected by nonstenotic aortic valve fibro-calcification remodeling. ...

Aortic Valve Sclerosis as an Important Predictor of Long-Term Mortality in Patients With Carotid Atheromatous Plaque Requiring Carotid Endarterectomy

... To this aim, we sought to identify and quantify the clonal repertoire of T lymphocytes (or T-cells) by deep sequencing of the T-cell receptor β-chain (TCRβ) in the PVAT (of both lesion sites and nonlesioned segments) of AAA patients. As a meaningful comparison, we analyzed TCRβ repertoires from patients with abdominal aortic occlusive disease (AOD), due to the common anatomical site of the lesions and shared risk factors but pathogenetic differences (Biros et al., 2015;Criqui and Aboyans, 2015;Horimatsu et al., 2017;Piacentini et al., 2020b). ...

Gene-expression profiles of abdominal perivascular adipose tissue distinguish aortic occlusive from stenotic atherosclerotic lesions and denote different pathogenetic pathways

... DAM hydrogel is derived from the adipose tissue, which is rich in adipose ECM components, such as collagens, glycosaminoglycans, laminin, elastin, and fibronectin. There exists adipose tissue in the periphery of the abdominal aorta, which is involved in vascular homeostasis [18]. To mimic the niche of the aorta, we hypothesized that the DAM could work as perivascular scaffold for delivery of antagomiR-150-5p to inhibit aortic aneurysm. ...

Genome-Wide Expression Profiling Unveils Autoimmune Response Signatures in the Perivascular Adipose Tissue of Abdominal Aortic Aneurysm

Arteriosclerosis Thrombosis and Vascular Biology

... Among the 19 patients, 11 were immunocompromised. K. sedentarius is usually a skin organism that is not harmful but can be associated with infections [1,2,9]. Few K. sedentarius infections have been reported, including pneumonia in a patient with acute leukemia and two cases related to prostheses ( Table 1). ...

Vascular Homograft Use in a Femoropopliteal Rare Bacterial Infection Bypass
  • Citing Article
  • December 2012

The International journal of artificial organs

... CLU has various functions and is a complement inhibitor, it and vitronectin inhibit the C5b-8 complex insertion into membrane attack complex [108,109]. Another complement-related protein, CD5L, is a key regulator of lipid synthesis and regulates inflammatory response, which has been observed to be decreased in the plasma of type 2 diabetes mellitus (T2DM) patients [110,111]. Together, these results suggested that complement may play a critical role in the pathogenesis of GDM. ...

Identification of differentially expressed plasma proteins in atherosclerotic patients with type 2 diabetes
  • Citing Article
  • March 2016

Journal of Diabetes and its Complications

... The cell product obtained has been extensively characterized in terms of composition, recovery, and FACS cell population analysi. 15 After appropriate surgical debridement of the wound bed, multiple injections of 10 mL PBMNC cell suspensions (0.2-0.3 mL in boluses) were injected perilesional using a 21 G needle. ...

Characterization of the Pall Celeris system as a point-of-care device for therapeutic angiogenesis

Cytotherapy

... 10 Specific publications on Zilver PTX without randomization and sponsor influence are few and include <200 patients without a follow-up ≥2 years. [11][12][13][14] In real-world setting, the CLTI patient represent the majority of patients undergone to endovascular lower limb revascularization. 11,15 Also in this case series, CLTI patients are prevalent (about 76%), while in many retrospective experiences this rate is largely inferior, ranging between 8 and 22%. ...

A comparison of sfa treatment with zilver ptx in diabetics vs non diabetics. clinical and functional results after 24 months
  • Citing Article
  • March 2015

The Journal of cardiovascular surgery

... Generation of advanced end glycation products is an example of non-enzymatic PTM. Oxidation of serum albumin at Cys34 is regarded as the marker of oxidative stress-related diseases [10,11]. ...

Human Serum Albumin Cys34 Oxidative Modifications following Infiltration in the Carotid Atherosclerotic Plaque