| 1. |
- Ruilope, LM, et al.
(author)
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Design and Baseline Characteristics of the Finerenone in Reducing Cardiovascular Mortality and Morbidity in Diabetic Kidney Disease Trial
- 2019
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In: American journal of nephrology. - : S. Karger AG. - 1421-9670 .- 0250-8095. ; 50:5, s. 345-356
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Journal article (peer-reviewed)abstract
- <b><i>Background:</i></b> Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. <b><i>Patients and</i></b> <b><i>Methods:</i></b> The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate ≥25 mL/min/1.73 m<sup>2</sup> and albuminuria (urinary albumin-to-creatinine ratio ≥30 to ≤5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level α = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. <b><i>Conclusions:</i></b> FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049.
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| 2. |
- Patke, Rodhan, et al.
(author)
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Epitranscriptomic mechanisms of androgen signalling and prostate cancer
- 2024
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In: Neoplasia. - : Elsevier. - 1522-8002 .- 1476-5586. ; 56
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Research review (peer-reviewed)abstract
- Prostate cancer (PCa) is the second most common cancer diagnosed in men. While radical prostatectomy and radiotherapy are often successful in treating localised disease, post-treatment recurrence is common. As the androgen receptor (AR) and androgen hormones play an essential role in prostate carcinogenesis and progression, androgen deprivation therapy (ADT) is often used to deprive PCa cells of the pro-proliferative effect of androgens. ADTs act by either blocking androgen biosynthesis (e.g. abiraterone) or blocking AR function (e.g. bicalutamide, enzalutamide, apalutamide, darolutamide). ADT is often effective in initially suppressing PCa growth and progression, yet emergence of castrate-resistant PCa and progression to neuroendocrine-like PCa following ADT are major clinical challenges. For this reason, there is an urgent need to identify novel approaches to modulate androgen signalling to impede PCa progression whilst also preventing or delaying therapy resistance. The mechanistic convergence of androgen and epitranscriptomic signalling offers a potential novel approach to treat PCa. The epitranscriptome involves covalent modifications of mRNA, notably, in the context of this review, the N(6)-methyladenosine (m6A) modification. m6A is involved in the regulation of mRNA splicing, stability, and translation, and has recently been shown to play a role in PCa and androgen signalling. The m6A modification is dynamically regulated by the METTL3-containing methyltransferase complex, and the FTO and ALKBH5 RNA demethylases. Given the need for novel approaches to treat PCa, there is significant interest in new therapies that target m6A that modulate AR expression and androgen signalling. This review critically summarises the potential benefit of such epitranscriptomic therapies for PCa patients.
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| 3. |
- Svanberg, Jan, et al.
(author)
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Corporate governance performance ratings with machine learning
- 2022
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In: International Journal of Intelligent Systems in Accounting, Finance & Management. - : John Wiley & Sons. - 1055-615X .- 1099-1174 .- 1550-1949. ; 29:1, s. 50-68
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Journal article (peer-reviewed)abstract
- We use machine learning with a cross-sectional research design to predict governance controversies and to develop a measure of the governance component of the environmental, social, governance (ESG) metrics. Based on comprehensive governance data from 2,517 companies over a period of 10 years and investigating nine machine-learning algorithms, we find that governance controversies can be predicted with high predictive performance. Our proposed governance rating methodology has two unique advantages compared with traditional ESG ratings: it rates companies' compliance with governance responsibilities and it has predictive validity. Our study demonstrates a solution to what is likely the greatest challenge for the finance industry today: how to assess a company's sustainability with validity and accuracy. Prior to this study, the ESG rating industry and the literature have not provided evidence that widely adopted governance ratings are valid. This study describes the only methodology for developing governance performance ratings based on companies' compliance with governance responsibilities and for which there is evidence of predictive validity.
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