Stupid Cancer App Connects the DES Community Online

Requires iOS 10.0 or later. Compatible with iPhone, iPad, and iPod touch

A new smartphone app from the nonprofit Stupid Cancer gives the DES community a unique opportunity to seek support from others with DES exposure or cancer diagnosis.

The more DES-exposed individuals who use the app, the more valuable it is to everyone in the DES community.

After downloading the free, secure app (initially for Mac only), participants create a profile. By selecting the DES-exposed option in “What was your primary diagnosis?” individuals are instantly matched to others.

Originally shared via Your DES Action Monthly Email Alert!
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The pitfalls of big data and the cost of missing something

The human insights missing from big data – TEDx Talks, Nov 2016

With stories from Nokia to Netflix to the oracles of ancient Greece, Tricia Wang demystifies big data and identifies its pitfalls, suggesting that we focus instead on “thick data” – precious, unquantifiable insights from actual people – to make the right business decisions and thrive in the unknown.

Can Technology Promote Healthy Lifestyle Choices ?

Americans have the power to prevent disease by making healthy lifestyle choices

Americans are increasingly experiencing a host of health issues, with 29.1 million Americans having diabetes and 27.6 million with heart disease. To help improve these conditions, health care professionals have been leveraging health and wellness technologies, including mobile apps, wearable trackers, and even a wearable headband that can help treat depression.

  • For more about this infographic and topic, read Health and Wellness Providers – How Technology is Helping Promote Healthy Lifestyle Choices, by the Arizona State University, February 2017.
  • Enjoy our health infographics album on Flickr.

EWG’s Healthy Living App

Healthy shopping got much easier

EWG’s ratings for more than 120,000 food and personal care products, now at your finger tips.

Download

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What is the Polycare Project?

A project funded by the EU’s Horizon 2020 research and innovation programme

Polycare is an Horizon 2020 European project that aims for better conditions of life and care for older chronic patients and the improvement of the sustainability of the health and social care systems.

The POLYCARE project aims to develop and test an integrated care model, patient-centred, supported by the use of advanced ICT systems and services that allows the monitoring and care of older chronic patients in acute phases at home.

New tool for the assessment and prioritization of persistence of chemicals under REACH

New computer modelling tool to identify persistent chemicals

Chemicals that persist in the environment can harm humans and wildlife.

This study describes a computer modelling-based approach to predict which chemical compounds are likely to be persistent.

The models were correctly able to predict persistence for 11 of 12 chemicals tested and could provide a cost-effective alternative to laboratory testing.

Abstract

A new integrated in silico strategy for the assessment and prioritization of persistence of chemicals under REACH, science direct, pii/S0160412015301240, 2013.

The fact that chemicals can be recalcitrant and persist in the environment arouses concern since their effects may seriously harm human and environmental health.

We compiled three datasets containing half-life (HL) data on sediment, soil and water compartments in order to build in silico models and, finally, an integrated strategy for predicting persistence to be used within the EU legislation Registration, Evaluation, Authorisation and restriction of CHemicals (REACH). After splitting the datasets into training (80%) and test sets (20%), we developed models for each compartment using the k-nearest neighbor algorithm (k-NN). Accuracy was higher than 0.79 and 0.76 respectively in the training and test sets for all three compartments. To support the k-NN predictions, we identified some structural alerts, using SARpy software, with a high-true positive percentage in the test set and some chemical classes related to persistence using the software IstChemFeat.

All these results were combined to build an integrated model and to reach to an overall conclusion (based on assessment and reliability) on the persistence of the substance. The results on the external validation set were very encouraging and support the idea that this tool can be used successfully for regulatory purposes and to prioritize substances.

Finding good online resources for mental health support

Search engines ‘could help young people find best mental health resources’

Search engines and content providers could have a role to play in helping young people find the most reliable mental health resources online.

With well over 10,000 apps in the mental health area, quantity is not the problem. It’s much more about understanding people’s lives and how they communicate and, of course, it’s about quality.

AyeMind aims to create a digital platform to support young people in mental wellbeing and create digital resources for it; and DocReady is designed to help with a person’s first GP conversation on mental health.

What rules determines a treatment that a medical quiz would recommend?

With great power comes great responsibility

“It seems that no matter what I do, the quiz recommends the client’s drug as the best possible treatment. The only exception is if I say I’m allergic. Or if I say I am already taking it.” Bill Sourour.

Developers are often one of the last lines of defense against potentially dangerous and unethical practices.

We’re approaching a time where software will drive the vehicle that transports your family to soccer practice. There are already AI programs that help doctors diagnose disease. It’s not hard to imagine them recommending prescription drugs soon, too.

“Nothing that we were doing was illegal. In the end, I understood that the real purpose of the site was to push a particular drug.” Bill Sourour.

The more software continues to take over every aspect of our lives, the more important it will be for us to take a stand and ensure that our ethics are ever-present in our code.” 

Read The code I’m still ashamed of, on medium, Nov 13 2016. Code image by Thibault J.

Social media and technology bringing medical information and drugs at our fingertips

Social forums and networking for patients support

International groups of patients are linking up 24/7 through social media to disseminate knowledge, provide peer support, and offer clinical advice. And all of this is delivered quickly, at the touch of a button.

Is social media saving lives? Or is it spreading poor information and damaging private confidentiality? The rapid rise of patient support groups on social media is putting some fundamental ethical questions into the spotlight.

Information and drugs at our fingertips, The BMJ 354:i4527, 18 August 2016.

Tablet image esthervargasc.

Stephen Armstrong explores the role of social media in patient support and considers the benefits, ethical dilemmas, and confidentiality issues that arise.

Maureen Baker, chair of the Royal College of General Practitioners, acknowledges the huge benefit of such groups but cautions that

“these forums should not be seen as a replacement for proper medical care.”

VEGA computer modelling tool to identify persistent chemicals

Chemicals that persist in the environment can harm humans and wildlife

Persistent chemicals (which remain unchanged in the environment for a long time) can accumulate in ecosystems and inside wildlife where they can have damaging effects. People and habitats can remain at risk from these chemicals, even when they are no longer produced, and the substances can also be transported far from their original source.

Under the EU chemicals legislation REACH, all chemicals manufactured or imported above 10 tonnes per year must be assessed for persistent, bioaccumulative and toxic (PBT) properties. Substances are generally assessed based on how easily they biodegrade; chemicals that readily degrade in an experimental test system are considered not persistent. Increasingly sophisticated modelling systems are being developed which can predict the activity of a chemical based on its structure, such as quantitative structure-activity relationship (QSAR) models. These may be particularly efficient when experimental data are not available.

A new integrated in silico strategy for the assessment and prioritization of persistence of chemicals under REACH, science direct, pii/S0160412015301240, 2013.

In this study, collaborators from Germany and Italy describe a novel, integrated approach to assess the persistence of chemicals. The software system, combines multiple computational models to predict persistence in several environmental compartments (e.g. water, soil).

To create the VEGA system, the researchers first used thresholds for ‘persistent’ and ‘very persistent’ substances as defined by REACH, and applied them to the experimental data on the half-life (the time needed to remove half of the starting amount of a substance from the environment) of 12 chemicals in sediment, water and soil. If the half-life of a substance was below the criteria for ‘persistent’ then it was considered ‘not persistent’. A range of sources, including the US Geological Survey, Netherlands National Institute for Public Health and the Environment, the European Chemicals Agency and studies published in journals were used to compile the database of substances with experimental values of persistency.

New computer modelling tool to identify persistent chemicals, Science for Environment Policy, Issue 470, 16 September 2016.

VEGA system is tiered, and involves multiple stages of checks before a prediction is made. First of all, the system checks whether an experimental value (a level of persistence established in previous research) is available for the chemical, as this is generally more reliable than a predicted value. If no experimental value is available, the system checks if the compound is perfluorinated (as these compounds are known to be persistent in the environment). If it is, the chemical is automatically classified as ‘persistent’. If not, the biodegradability of the compound is evaluated using a model. If readily biodegradable, the chemical is classified as ‘not persistent’.

If none of these checks can be carried out, three software models are run on the compound, which predict its persistence in sediment, water and soil: IstKNN, machine learning software, which estimates the activity of chemicals based on similar compounds; SARpy, which automatically identifies structural features of chemicals (‘structural alerts’) that are linked to persistence; and IstCHEMfeat, which separates chemicals into classes based on particular features and chemical groups.

The final assessment is made based on a combination of the predictions and their reliability, and is always conservative (e.g. if a chemical is assessed as ‘very persistent’ in water with medium reliability, but ‘not persistent’ in soil with high reliability, the final outcome will be ‘very persistent’).

After ‘training’ the software using chemicals with known properties, the researchers tested its ability to recognise harmful substances from a set of compounds in the Candidate List of substances of very high concern maintained by the European Chemicals Agency. Of 12 compounds, the persistence of 11 were correctly predicted (the remaining compound could not be assessed as it was too dissimilar to the chemicals used during the training phase). These results suggest this tool could be used to prioritise chemicals for regulatory purposes, such as REACH. It may be a more affordable and speedier alternative to experiments for classifying compounds as ‘persistent’.