Sirtuin1 Over-Expression Does Not Impact Retinal Vascular and Neuronal Degeneration in a Mouse Model of Oxygen-Induced Retinopathy

Proliferative retinopathy is a leading cause of blindness, including retinopathy of prematurity (ROP) in children and diabetic retinopathy in adults. Retinopathy is characterized by an initial phase of vessel loss, leading to tissue ischemia and hypoxia, followed by sight threatening pathologic neovascularization in the second phase. Previously we found that Sirtuin1 (Sirt1), a metabolically dependent protein deacetylase, regulates vascular regeneration in a mouse model of oxygen-induced proliferative retinopathy (OIR), as neuronal depletion of Sirt1 in retina worsens retinopathy. In this study we assessed whether over-expression of Sirtuin1 in retinal neurons and vessels achieved by crossing Sirt1 over-expressing flox mice with Nestin-Cre mice or Tie2-Cre mice, respectively, may protect against retinopathy. We found that over-expression of Sirt1 in Nestin expressing retinal neurons does not impact vaso-obliteration or pathologic neovascularization in OIR, nor does it influence neuronal degeneration in OIR. Similarly, increased expression of Sirt1 in Tie2 expressing vascular endothelial cells and monocytes/macrophages does not protect retinal vessels in OIR. In addition to the genetic approaches, dietary supplement with Sirt1 activators, resveratrol or SRT1720, were fed to wild type mice with OIR. Neither treatment showed significant vaso-protective effects in retinopathy. Together these results indicate that although endogenous Sirt1 is important as a stress-induced protector in retinopathy, over-expression of Sirt1 or treatment with small molecule activators at the examined doses do not provide additional protection against retinopathy in mice. Further studies are needed to examine in depth whether increasing levels of Sirt1 may serve as a potential therapeutic approach to treat or prevent retinopathy

Choroid Sprouting Assay: An Ex Vivo Model of Microvascular Angiogenesis

Angiogenesis of the microvasculature is central to the etiology of many diseases including proliferative retinopathy, age-related macular degeneration and cancer. A mouse model of microvascular angiogenesis would be very valuable and enable access to a wide range of genetically manipulated tissues that closely approximate small blood vessel growth in vivo. Vascular endothelial cells cultured in vitro are widely used, however, isolating pure vascular murine endothelial cells is technically challenging. A microvascular mouse explant model that is robust, quantitative and can be reproduced without difficulty would overcome these limitations. Here we characterized and optimized for reproducibility an organotypic microvascular angiogenesis mouse and rat model from the choroid, a microvascular bed in the posterior of eye. The choroidal tissues from C57BL/6J and 129S6/SvEvTac mice and Sprague Dawley rats were isolated and incubated in Matrigel. Vascular sprouting was comparable between choroid samples obtained from different animals of the same genetic background. The sprouting area, normalized to controls, was highly reproducible between independent experiments. We developed a semi-automated macro in ImageJ software to allow for more efficient quantification of sprouting area. Isolated choroid explants responded to manipulation of the external environment while maintaining the local interactions of endothelial cells with neighboring cells, including pericytes and macrophages as evidenced by immunohistochemistry and fluorescence-activated cell sorting (FACS) analysis. This reproducible ex vivo angiogenesis assay can be used to evaluate angiogenic potential of pharmacologic compounds on microvessels and can take advantage of genetically manipulated mouse tissue for microvascular disease research

Undertaking multi-centre randomised controlled trials in primary care: learnings and recommendations from the PULsE-AI trial researchers

Background Conducting effective and translational research can be challenging and few trials undertake formal reflection exercises and disseminate learnings from them. Following completion of our multicentre randomised controlled trial, which was impacted by the COVID-19 pandemic, we sought to reflect on our experiences and share our thoughts on challenges, lessons learned, and recommendations for researchers undertaking or considering research in primary care. Methods Researchers involved in the Prediction of Undiagnosed atriaL fibrillation using a machinE learning AlgorIthm (PULsE-AI) trial, conducted in England from June 2019 to February 2021 were invited to participate in a qualitative reflection exercise. Members of the Trial Steering Committee (TSC) were invited to attend a semi-structured focus group session, Principal Investigators and their research teams at practices involved in the trial were invited to participate in a semi-structured interview. Following transcription, reflexive thematic analysis was undertaken based on pre-specified themes of recruitment, challenges, lessons learned, and recommendations that formed the structure of the focus group/interview sessions, whilst also allowing the exploration of new themes that emerged from the data. Results Eight of 14 members of the TSC, and one of six practices involved in the trial participated in the reflection exercise. Recruitment was highlighted as a major challenge encountered by trial researchers, even prior to disruption due to the COVID-19 pandemic. Researchers also commented on themes such as the need to consider incentivisation, and challenges associated with using technology in trials, especially in older age groups. Conclusions Undertaking a formal reflection exercise following the completion of the PULsE-AI trial enabled us to review experiences encountered whilst undertaking a prospective randomised trial in primary care. In sharing our learnings, we hope to support other clinicians undertaking research in primary care to ensure that future trials are of optimal value for furthering knowledge, streamlining pathways, and benefitting patients

Neuronal sirtuin1 mediates retinal vascular regeneration in oxygen-induced ischemic retinopathy

Regeneration of blood vessels in ischemic neuronal tissue is critical to reduce tissue damage in diseases. In proliferative retinopathy, initial vessel loss leads to retinal ischemia, which can induce either regrowth of vessels to restore normal metabolism and minimize damage, or progress to hypoxia-induced sight-threatening pathologic vaso-proliferation. It is not well understood how retinal neurons mediate regeneration of vascular growth in response to ischemic insults. In this study we aim to investigate the potential role of Sirtuin 1 (Sirt1), a metabolically-regulated protein deacetylase, in mediating the response of ischemic neurons to regulate vascular regrowth in a mouse model of oxygen-induced ischemic retinopathy (OIR). We found that Sirt1 is highly induced in the avascular ischemic retina in OIR. Conditional depletion of neuronal Sirt1 leads to significantly decreased retinal vascular regeneration into the avascular zone and increased hypoxia-induced pathologic vascular growth. This effect is likely independent of PGC-1α, a known Sirt1 target, as absence of PGC-1α in knockout mice does not impact vascular growth in retinopathy. We found that neuronal Sirt1 controls vascular regrowth in part through modulating deacetylation and stability of hypoxia-induced factor 1α and 2α, and thereby modulating expression of angiogenic factors. These results indicate that ischemic neurons induce Sirt1 to promote revascularization into ischemic neuronal areas, suggesting a novel role of neuronal Sirt1 in mediating vascular regeneration in ischemic conditions, with potential implications beyond retinopathy

Activation of the PI3K/AKT Pathway in Merkel Cell Carcinoma

Merkel cell carcinoma (MCC) is a highly aggressive skin cancer with an increasing incidence. The understanding of the molecular carcinogenesis of MCC is limited. Here, we scrutinized the PI3K/AKT pathway, one of the major pathways activated in human cancer, in MCC. Immunohistochemical analysis of 41 tumor tissues and 9 MCC cell lines revealed high levels of AKT phosphorylation at threonine 308 in 88% of samples. Notably, the AKT phosphorylation was not correlated with the presence or absence of the Merkel cell polyoma virus (MCV). Accordingly, knock-down of the large and small T antigen by shRNA in MCV positive MCC cells did not affect phosphorylation of AKT. We also analyzed 46 MCC samples for activating PIK3CA and AKT1 mutations. Oncogenic PIK3CA mutations were found in 2/46 (4%) MCCs whereas mutations in exon 4 of AKT1 were absent. MCC cell lines demonstrated a high sensitivity towards the PI3K inhibitor LY-294002. This finding together with our observation that the PI3K/AKT pathway is activated in the majority of human MCCs identifies PI3K/AKT as a potential new therapeutic target for MCC patients

CD146 expression is associated with a poor prognosis in human breast tumors and with enhanced motility in breast cancer cell lines.

INTRODUCTION: Metastasis is a complex process involving loss of adhesion, migration, invasion and proliferation of cancer cells. Cell adhesion molecules play a pivotal role in this phenomenon by regulating cell-cell and cell-matrix interactions. CD146 (MCAM) is associated with an advanced tumor stage in melanoma, prostate cancer and ovarian cancer. Studies of CD146 expression and function in breast cancer remain scarce except for a report concluding that CD146 could act as a tumor suppressor in breast carcinogenesis. METHODS: To resolve these apparent discrepancies in the role of CD146 in tumor cells, we looked at the association of CD146 expression with histoclinical features in human primary breast cancers using DNA and tissue microarrays. By flow cytometry, we characterized CD146 expression on different breast cancer cell lines. Using siRNA or shRNA technology, we studied functional consequences of CD146 downmodulation of MDA-MB-231 cells in migration assays. Wild-type, mock-transfected and downmodulated transfected cells were profiled using whole-genome DNA microarrays to identify genes whose expression was modified by CD146 downregulation. RESULTS: Microarray studies revealed the association of higher levels of CD146 with histoclinical features that belong to the basal cluster of human tumors. Expression of CD146 protein on epithelial cells was detected in a small subset of cancers with histoclinical features of basal tumors. CD146+ cell lines displayed a mesenchymal phenotype. Downmodulation of CD146 expression in the MDA-MB-231 cell line resulted in downmodulation of vimentin, as well as of a set of genes that include both genes associated with a poor prognosis in a variety of cancers and genes known to promote cell motility. In vitro functional assays revealed decreased migration abilities associated with decreased CD146 expression. CONCLUSIONS: In addition to its expression in the vascular compartment, CD146 is expressed on a subset of epithelial cells in malignant breast. CD146 may directly or indirectly contribute to tumor aggressiveness by promoting malignant cell motility. Changes in molecular signatures following downmodulation of CD146 expression suggest that CD146 downmodulation is associated with the reversal of several biological characteristics associated with epithelial to mesenchymal transition, and the phenomenon associated with the metastatic process.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Identification of undiagnosed atrial fibrillation patients using a machine learning risk prediction algorithm and diagnostic testing (PULsE-AI): Study protocol for a randomised controlled trial

Atrial fibrillation (AF) is associated with an increased risk of stroke, enhanced stroke severity, and other comorbidities. However, AF is often asymptomatic, and frequently remains undiagnosed until complications occur. Current screening approaches for AF lack either cost-effectiveness or diagnostic sensitivity; thus, there is interest in tools that could be used for population screening. An AF risk prediction algorithm, developed using machine learning from a UK dataset of 2,994,837 patients, was found to be more effective than existing models at identifying patients at risk of AF. Therefore, the aim of the trial is to assess the effectiveness of this risk prediction algorithm combined with diagnostic testing for the identification of AF in a real-world primary care setting. Eligible participants (aged =30?years and without an existing AF diagnosis) registered at participating UK general practices will be randomised into intervention and control arms. Intervention arm participants identified at highest risk of developing AF (algorithm risk score?=?7.4%) will be invited for a 12-lead electrocardiogram (ECG) followed by two-weeks of home-based ECG monitoring with a KardiaMobile device. Control arm participants will be used for comparison and will be managed routinely. The primary outcome is the number of AF diagnoses in the intervention arm compared with the control arm during the research window. If the trial is successful, there is potential for the risk prediction algorithm to be implemented throughout primary care for narrowing the population considered at highest risk for AF who could benefit from more intensive screening for AF. Trial Registration: NCT04045639

Undertaking multi-centre randomised controlled trials in primary care: learnings and recommendations from the PULsE-AI trial researchers

Background: Conducting effective and translational research can be challenging and few trials undertake formal reflection exercises and disseminate learnings from them. Following completion of our multicentre randomised controlled trial, which was impacted by the COVID-19 pandemic, we sought to reflect on our experiences and share our thoughts on challenges, lessons learned, and recommendations for researchers undertaking or considering research in primary care. Methods: Researchers involved in the Prediction of Undiagnosed atriaL fibrillation using a machinE learning AlgorIthm (PULsE-AI) trial, conducted in England from June 2019 to February 2021 were invited to participate in a qualitative reflection exercise. Members of the Trial Steering Committee (TSC) were invited to attend a semi-structured focus group session, Principal Investigators and their research teams at practices involved in the trial were invited to participate in a semi-structured interview. Following transcription, reflexive thematic analysis was undertaken based on pre-specified themes of recruitment, challenges, lessons learned, and recommendations that formed the structure of the focus group/interview sessions, whilst also allowing the exploration of new themes that emerged from the data. Results: Eight of 14 members of the TSC, and one of six practices involved in the trial participated in the reflection exercise. Recruitment was highlighted as a major challenge encountered by trial researchers, even prior to disruption due to the COVID-19 pandemic. Researchers also commented on themes such as the need to consider incentivisation, and challenges associated with using technology in trials, especially in older age groups. Conclusions: Undertaking a formal reflection exercise following the completion of the PULsE-AI trial enabled us to review experiences encountered whilst undertaking a prospective randomised trial in primary care. In sharing our learnings, we hope to support other clinicians undertaking research in primary care to ensure that future trials are of optimal value for furthering knowledge, streamlining pathways, and benefitting patients

Systemic Biomarkers of Neutrophilic Inflammation, Tissue Injury and Repair in COPD Patients with Differing Levels of Disease Severity

The identification and validation of biomarkers to support the assessment of novel therapeutics for COPD continues to be an important area of research. The aim of the current study was to identify systemic protein biomarkers correlated with measures of COPD severity, as well as specific protein signatures associated with comorbidities such as metabolic syndrome. 142 protein analytes were measured in serum of 140 patients with stable COPD, 15 smokers without COPD and 30 non-smoking controls. Seven analytes (sRAGE, EN-RAGE, NGAL, Fibrinogen, MPO, TGF-α and HB-EGF) showed significant differences between severe/very severe COPD, mild/moderate COPD, smoking and non-smoking control groups. Within the COPD subjects, univariate and multivariate analyses identified analytes significantly associated with FEV1, FEV1/FVC and DLCO. Most notably, a set of 5 analytes (HB-EGF, Fibrinogen, MCP-4, sRAGE and Sortilin) predicted 21% of the variability in DLCO values. To determine common functions/pathways, analytes were clustered in a correlation network by similarity of expression profile. While analytes related to neutrophil function (EN-RAGE, NGAL, MPO) grouped together to form a cluster associated with FEV1 related parameters, analytes related to the EGFR pathway (HB-EGF, TGF-α) formed another cluster associated with both DLCO and FEV1 related parameters. Associations of Fibrinogen with DLCO and MPO with FEV1/FVC were stronger in patients without metabolic syndrome (r  =  −0.52, p  = 0.005 and r  =  −0.61, p  = 0.023, respectively) compared to patients with coexisting metabolic syndrome (r  =  −0.25, p  = 0.47 and r  =  −0.15, p  = 0.96, respectively), and may be driving overall associations in the general cohort. In summary, our study has identified known and novel serum protein biomarkers and has demonstrated specific associations with COPD disease severity, FEV1, FEV1/FVC and DLCO. These data highlight systemic inflammatory pathways, neutrophil activation and epithelial tissue injury/repair processes as key pathways associated with COPD