Circulating Exosomal miRNAs as Novel Biomarkers Perform Superior Diagnostic Efficiency Compared With Plasma miRNAs for Large-Artery Atherosclerosis Stroke

Recently, exosomal miRNAs have been reported to be associated with some diseases, and these miRNAs can be used for diagnosis and treatment. However, diagnostic biomarkers of exosomal miRNAs for ischemic stroke have rarely been studied. In the present study, we aimed to identify exosomal miRNAs that are associated with large-artery atherosclerosis (LAA) stroke, the most common subtype of ischemic stroke; to further verify their diagnostic efficiency; and to obtain promising biomarkers. High-throughput sequencing was performed on samples from 10 subjects. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed on exosomes and plasma in the discovery phase (66 subjects in total) and the validation phase (520 subjects in total). We identified 5 candidate differentially expressed miRNAs (miR-369-3p, miR-493-3p, miR-379-5p, miR-1296-5p, and miR-1277-5p) in the discovery phase according to their biological functions, 4 of which (miR-369-3p, miR-493-3p, miR-379-5p, and miR-1296-5p) were confirmed in the validation phase. These four exosomal miRNAs could be used to distinguish LAA samples from small artery occlusion (SAO) samples, LAA samples from atherosclerosis (AS) samples, and LAA samples from control samples and were superior to plasma miRNAs. In addition, composite biomarkers achieved higher area under the curve (AUC) values than single biomarkers. According to our analysis, the expression levels of exosomal miR-493-3p and miR-1296-5p were negatively correlated with the National Institutes of Health Stroke Scale (NIHSS) score. The four identified exosomal miRNAs are promising biomarkers for the diagnosis of LAA stroke, and their diagnostic efficiency is superior to that of their counterparts in plasma.

Startups – Tom Eisenmann analyzes the most prevalent failure patterns and how to avoid them

Purpose The Fail-Safe Startup: Your Roadmap for Entrepreneurial Success, the new book by entrepreneurship researcher Tom Eisenmann, sets out to help improve the odds by looking more closely at the most prevalent causes of startup failure and how to avoid them. Design/methodology/approach Eisenmann research led him to identify six distinct patterns that explain a large proportion of startup failures, three relating to early stage failures and three to late stage. Findings Strong demand from early adopters may lead a founder to scale up prematurely. Practical/implications Entrepreneurs must research differences in the needs of likely early adopters and mainstream customers during the upfront customer discovery phase. Originality/value Entrepreneurs must research differences in the needs of likely early adopters and mainstream customers during the upfront customer discovery phase. 10; 10;The line between visionary entrepreneur and cult leader can become blurry, and a founder?s ?reality distortion field--useful for motivating others to help pursue the founder?s dream?can become a liability.

Circulating plasma MicroRNA in patients with active acromegaly

Context Excessive production of growth hormone causes marked multiorgan changes in patients with acromegaly, which may involve epigenetic mechanisms. Objective To evaluate differences in circulating microRNAs (miRNAs) associated with chronic growth hormone overproduction in adults. Design and setting A cross-sectional case-control study was conducted at a tertiary medical center. Participants We enrolled 12 consecutive patients with acromegaly along with 12 age and gender matched controls in the discovery phase of the study and then extended this cohort to 47 patients with acromegaly and 28 healthy controls for the validation study. Main Outcome Measures Plasma microRNAs were quantified by next-generation sequencing (NGS) in the discovery phase. Levels of selected miRNAs were validated on extended cohorts using RT-qPCR, compared between groups and correlated with clinical parameters. Results Based on NGS data, we selected three plasma miRNAs downregulated in patients with acromegaly compared to healthy controls: miR-4446-3p –1.317 (p=0.001), miR-215-5p –3.040 (p=0.005), miR-342-5p –1.875 (p=0.013) without multiplicity correction for all three miRNAs. These results were confirmed by RT-qPCR in the validation phase for two miRNAs out of three: miR-4446-3p (p <0.001, p-adj <0.001), AUC 0.862 (95% CI 0.723-0.936) p<0.001 and miR-215-5p (p <0.001, p-adj <0.001), AUC 0.829 (95% CI 0.698-0.907) p<0.001 to differentiate patients with acromegaly from healthy controls. Conclusions In a two-phase experiment using two different techniques we found and validated the downregulation of plasma miR-4446-3p and miR-215-5p in patients with acromegaly compared to healthy subjects, which makes them promising biomarkers for further research.

Knowledge production and learning effects using the example of living labs in Halle (Saale) and Mannheim

Rising average temperatures and the increased occurrence of heat islands increase the vulnerability of urban society in Halle (Saale) and Mannheim as well. Dealing with the associated challenges requires not only locally adapted strategies, but in particular an interdepartmental approach and the participatory involvement of those affected. Real laboratories in both cities open up the possibility of testing this in a transformative process. The aim here is, among other things, to learn with and from each other and to generate new knowledge to address the urgent issues. This article discusses the opportunities and challenges that real laboratories are confronted with in terms of knowledge already in the discovery phase and what needs to be taken into account to support this process in the best possible way.

Plateletworks® as a Point-of-Care Test for ASA Non-Sensitivity

Aspirin (ASA) therapy is proven to be effective in preventing adverse cardiovascular events; however, up to 30% of patients are non-sensitive to their prescribed ASA dosage. In this pilot study, we demonstrated, for the first time, how ASA non-sensitivity can be diagnosed using Plateletworks®, a point-of-care platelet function test. Patients prescribed 81 mg of ASA were recruited in a series of two successive phases—a discovery phase and a validation phase. In the discovery phase, a total of 60 patients were recruited to establish a cut-off point (COP) for ASA non-sensitivity using Plateletworks®. Each sample was simultaneously cross-referenced with a light transmission aggregometer (LTA). Our findings demonstrated that >52% maximal platelet aggregation using Plateletworks® had a sensitivity, specificity, and likelihood ratio of 80%, 70%, and 2.67, respectively, in predicting ASA non-sensitivity. This COP was validated in a secondary cohort of 40 patients prescribed 81 mg of ASA using Plateletworks® and LTA. Our data demonstrated that our established COP had a 91% sensitivity and 69% specificity in identifying ASA non-sensitivity using Plateletworks®. In summary, Plateletworks® is a point-of-care platelet function test that can appropriately diagnose ASA non-sensitive patients with a sensitivity exceeding 80%.

New candidate blood biomarkers potentially associated with white matter hyperintensities progression

We aimed to discover blood biomarkers associated with longitudinal changes in white matter hyperintensities (WMH). This study was divided into a discovery phase and a replication phase. Subjects in both studies were patients with hypertension, aged 50–70, who underwent two magnetic resonance imaging (MRI) sessions and blood extractions over a 4-year follow-up period. In the discovery phase, we screened 1305 proteins in 12 subjects with WMH progression and in 12 matched control subjects. We found that 41 proteins were differentially expressed: 13 were upregulated and 28 were downregulated. We subsequently selected three biomarkers for replication in baseline and follow-up samples in 80 subjects with WMH progression and in 80 control subjects. The selected protein candidates for the replication were MMP9 (matrix metalloproteinase-9), which was higher in cases, MET (hepatocyte growth factor receptor) and ASAH2 (neutral ceramidase), which were both lower in cases of WMH progression. Baseline biomarker concentrations did not predict WMH progression. In contrast, patients with WMH progression presented a steeper decline in MET over time. Furthermore, cases showed higher MMP9 and lower ASAH2 levels than controls at the follow-up. These results indicate that MMP9, MET, and ASAH2 are potentially associated with the progression of WMH, and could therefore be interesting candidates to validate in future studies.

A Molecule Based Nomogram Optimized the Prediction of Relapse in Stage I NSCLC

Background: Early-stage non-small cell lung cancer (NSCLC) is being diagnosed increasingly, and in 30% of diagnosed patients, recurrence will develop within 5 years. Thus, it is urgent to identify recurrence-related markers in order to optimize the management of patient-tailored therapeutics. The aim of the study was to develop a feasible tool to optimize the recurrence prediction of stage I NSCLC. Methods: The eligible datasets were downloaded from TCGA and GEO. In discovery phase, two algorithms, Least Absolute Shrinkage and Selector Operation and Support Vector Machine-Recursive Feature Elimination, were used to identify candidate genes. Recurrence associated signature was developed by penalized cox regression. The nomogram was constructed and further tested via two independent cohorts. Results: In this retrospective study, 14 eligible datasets and 7 published signatures were included. In discovery phase, 42 significant genes were highlighted as candidate predictors by two algorithms. A 13-gene based signature was generated by penalized cox regression categorized training cohort into high-risk and low-risk subgroups (HR = 8.873, 95% CI:4.228–18.480 P < 0.001). Furthermore, a nomogram integrating the recurrence related signature, age, and histology was developed to predict the recurrence-free survival in the training cohort, which performed well in the two external validation cohorts (concordance index: 0.737, 95%CI:0.732–0.742, P < 0.001; 0.666, 95%CI: 0.650–0.682, P < 0.001; 0.651, 95%CI:0.637–0.665, P < 0.001 respectively). Conclusions: The proposed nomogram is a promising tool for estimating recurrence free survival in stage I NSCLC, which might have tremendous value in guiding adjuvant therapy. Prospective studies are needed to test the clinical utility of the nomogram in individualized management of stage I NSCLC.

Longitudinal Trajectories in Cortical Thickness and Volume Atrophy: Superior Cognitive Performance Does Not Protect Against Brain Atrophy in Older Adults

Background: Previous research has identified a small subgroup of older adults that maintain a high level of cognitive functioning well into advanced age. Investigation of those with superior cognitive performance (SCP) for their age is important, as age-related decline has previously been thought to be inevitable. Objective: Preservation of cortical thickness and volume was evaluated in 76 older adults with SCP and 100 typical older adults (TOAs) assessed up to five times over six years. Methods: Regions of interest (ROIs) found to have been associated with super-aging status (a construct similar to SCP status) in previous literature were investigated, followed by a discovery phase analyses of additional regions. SCPs were aged 70 + at baseline, scoring at/above normative memory (CVLT-II) levels for demographically similar individuals aged 30–44 years old, and in the unimpaired range for all other cognitive domains over the course of the study. Results: In linear mixed models, following adjustment for multiple comparisons, there were no significant differences between rates of thinning or volume atrophy between SCPs and TOAs in previously identified ROIs, or the discovery phase analyses. With only amyloid-β negative individuals in the analyses, again there were no significant differences between SCPs and TOAs. Conclusion: The increased methodological rigor in classifying groups, together with the influence of cognitive reserve, are discussed as potential factors accounting for our findings as compared to the extant literature on those with superior cognitive performance for their age.

The discriminative ability of Prostate Health Index to detect prostate cancer is enhanced in combination with miR-222-3p

BACKGROUND: There is an urgent need for better prostate cancer (PCa) biomarkers due to the low specificity of prostate specific antigen (PSA). OBJECTIVE: Prostate Health Index (PHI) is an advanced PSA-based test for early detection of PCa. The present study aim was to investigate the potential improvement of diagnostic accuracy of PHI by its combination with suitable discriminative microRNAs (miRNAs). METHODS: A two-phase study was performed. In a discovery phase, a panel of 177 miRNAs was measured in ten men with biopsy proven PCa and ten men with histologically no evidence of malignancy (NEM). These results were validated in a second phase including 25 patients in each group. The patients of all groups were matched regarding their PSA values and PHI were measured. RESULTS: Based on data in the discovery phase, four elevated miRNAs were selected as potential miRNA candidates for further validation. A combination of miR-222-3p as the best discriminative miRNA with PHI extended the diagnostic accuracy of PHI from an AUC value of 0.690 to 0.787 and resulted in a sensitivity of 72.0% and a specificity of 84.0%. CONCLUSION: Circulating microRNAs show useful diagnostic potential in combination with common used biomarkers to enhance their diagnostic power.

Towards a Scalable Architecture for Smart Villages: The Discovery Phase

Alleviating poverty, reducing inequality, and achieving economic prosperity and well-beingis a global challenge. The spread and quantum of this daunting challenge calls for a scalable solution.The aim of the ‘Scalable Architecture for Smart Villages’ project is to contribute to an eective solutionwhich addresses scale as well as customization. In order to achieve both in our new framework forsmart villages, we take an endogenous approach. This approach emphasizes learning which will createa catalytic eect for scale. Learning is an essential component in the process, both for the researchersas well as members of the community. With these principles in mind, our approach proceeds in fourphases, namely discovery, planning, resourcing and executing. In this paper we outline the discoveryphase, which will lay the foundation for developing our framework of scalable smart villages.The Discovery Phase is a research process where the community learns about itself and the researcherslearn about the underlying factors that can help uplift and develop a smart village. Using conventionalqualitative and quantitative research methodology, the researchers and the community will generatebaseline data which will help calibrate villages for future development into smart villages.