Syrjäytymisvaarassa olevien vajaakuntoisten nuorten kuntoutustarpeen arviointi

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Ethical principles in machine learning and artificial intelligence: cases from the field and possible ways forward

Decision-making on numerous aspects of our daily lives is being outsourced to machine-learning algorithms and artificial intelligence (AI), motivated by speed and efficiency in the decision process. Machine learning (ML) approaches - one of the typologies of algorithms underpinning artificial intelligence - are typically developed as black boxes. The implication is that ML code scripts are rarely scrutinised; interpretability is usually sacrificed in favour of usability and effectiveness. Room for improvement in practices associated with programme development have also been flagged along other dimensions, including inter alia fairness, accuracy, accountability, and transparency. In this contribution, the production of guidelines and dedicated documents around these themes is discussed. The following applications of AI-driven decision making are outlined: a) Risk assessment in the criminal justice system, and b) autonomous vehicles, highlighting points of friction across ethical principles. Possible ways forward towards the implementation of governance on AI are finally examined

Astaxanthin vs placebo on arterial stiffness, oxidative stress and inflammation in renal transplant patients (Xanthin): a randomised controlled trial

Background: There is evidence that renal transplant recipients have accelerated atherosclerosis manifest by increased cardiovascular morbidity and mortality. The high incidence of atherosclerosis is, in part, related to increased arterial stiffness, vascular dysfunction, elevated oxidative stress and inflammation associated with immunosuppressive therapy. The dietary supplement astaxanthin has shown promise as an antioxidant and anti-inflammatory therapeutic agent in cardiovascular disease. The aim of this trial is to investigate the effects of astaxanthin supplementation on arterial stiffness, oxidative stress and inflammation in renal transplant patients

Affect and subjectivity

Editoria

Twitter permeability to financial events: an experiment towards a model for sensing irregularities

There is a general consensus of the good sensing and novelty character- istics of Twitter as an information media for the complex fi nancial market. This paper investigates the permeability of Twitter sphere, the total universe of Twitter users and their habits, towards relevant events in the financial market. Analysis shows that a general purpose social media is permeable to fi nancial-specifi c events and establishes Twitter as a relevant feeder for taking decisions regarding the fi nancial market and event fraudulent activities in that market. However, the provenance of contributions, their diferent levels of credibility and quality and even the purpose or intention behind them should to be considered and carefully contemplated if Twitter is used as a single source for decision taking. With the overall aim of this research, to deploy an architecture for real-time monitoring of irregularities in the financial market, this paper conducts a series of experiments on the level of permeability and the permeable features of Twitter in the event of one of these irregularities. To be precise, Twitter data is collected concerning an event comprising of a specifi c financial action on the 27th January 2017: the announcement about the merge of two companies Tesco PLC and Booker Group PLC, listed in the main market of the London Stock Exchange (LSE), to create the UK's Leading Food Business. The experiment attempts to answer two research questions which aim to characterize the features of Twitter permeability to the fi nancial market. The experimental results con rm that a far-impacting financial event, such as the merger considered, caused apparent disturbances in all the features considered, that is, information volume, content and sentiment as well as geographical provenance. Analysis shows that despite, Twitter not being a specifi c fi nancial forum, it is permeable to financial events

Renin-angiotensin system inhibitors and risk of fractures: a prospective cohort study and meta-analysis of published observational cohort studies

The renin-angiotensin system (RAS) represents an important target of antihypertensive medications. Angiotensin-converting enzyme inhibitors (ACEI) and angiotensin II receptor blockers (ARB), which are widely-used RAS inhibiting drugs, have been suggested to have beneficial effects on bone tissue. We aimed to assess the associations of use of ACEIs and/or ARBs with the risk of fractures using a population-based prospective cohort and a meta-analysis of published prospective cohort studies. Information on antihypertensive medication use (including both ACEIs and ARBs) were assessed in 1743 men and women of the Kuopio Ischemic Heart Disease prospective cohort study. Hazard ratios (HRs) [95% confidence intervals (CI)] of ACEIs or ARBs use with incident fractures were calculated. A total of 203 composite (hip, humeral, and wrist) fractures occurred during a median follow-up of 14.8 years. In multivariate adjusted analysis, the HR for composite fractures comparing users of ACEIs or ARBs with non-users was 1.00 (0.59–1.69). The corresponding adjusted HR for hip fractures comparing users versus non-users of ACEIs or ARBs was 0.89 (0.32–2.47). Including the current study, a total of 11 observational cohort studies involving 3526,319 participants and &gt;323,355 fractures were included in a meta-analysis. Comparing ACEI users with non-users and ARB users with non-users, the HRs for composite fractures were 1.09 (0.89–1.33) and 0.87 (0.76–1.01) respectively. The corresponding HRs for hip fractures were 0.91 (0.86–0.95) and 0.80 (0.75–0.85) respectively. Use of RAS inhibitors was not associated with long-term risk of composite fractures in both primary and pooled analyses. Pooled evidence however suggests a beneficial effect of RAS blockers on hip fracture risk.</p

Targeting RNS/caveolin-1/MMP signaling cascades to protect against cerebral ischemia-reperfusion injuries: potential application for drug discovery

Reactive nitrogen species (RNS) play important roles in mediating cerebral ischemia-reperfusion injury. RNS activate multiple signaling pathways and participate in different cellular events in cerebral ischemia-reperfusion injury. Recent studies have indicated that caveolin-1 and matrix metalloproteinase (MMP) are important signaling molecules in the pathological process of ischemic brain injury. During cerebral ischemia-reperfusion, the production of nitric oxide (NO) and peroxynitrite (ONOO-), two representative RNS, down-regulates the expression of caveolin-1 (Cav-1) and, in turn, further activates nitric oxide synthase (NOS) to promote RNS generation. The increased RNS further induce MMP activation and mediate disruption of the blood-brain barrier (BBB), aggravating the brain damage in cerebral ischemia-reperfusion injury. Therefore, the feedback interaction among RNS/Cav-1/MMPs provides an amplified mechanism for aggravating ischemic brain damage during cerebral ischemia-reperfusion injury. Targeting the RNS/Cav-1/MMP pathway could be a promising therapeutic strategy for protecting against cerebral ischemia-reperfusion injury. In this mini-review article, we highlight the important role of the RNS/Cav-1/MMP signaling cascades in ischemic stroke injury and review the current progress of studies seeking therapeutic compounds targeting the RNS/Cav-1/MMP signaling cascades to attenuate cerebral ischemia-reperfusion injury. Several representative natural compounds, including calycosin-7-O-β-D-glucoside, baicalin, Momordica charantia polysaccharide (MCP), chlorogenic acid, lutein and lycopene, have shown potential for targeting the RNS/Cav-1/MMP signaling pathway to protect the brain in ischemic stroke. Therefore, the RNS/Cav-1/MMP pathway is an important therapeutic target in ischemic stroke treatment.published_or_final_versio