http://nuclear-news.net/2016/03/02/the-horrendous-truth-about-just-how-big-a-mess-nuclear-corporation-edf-is-in/

The horrendous truth about just how big a mess nuclear corporation EDF is in

EDF’s leaked Board Agenda: Zombie nuclear projects and ‘beyond the grave’ reactors

http://www.theecologist.org/blogs_and_comments/Blogs/2987305/edfs_leaked_board_agenda_zombie_nuclear_projects_and_beyond_the_grave_reactors.html

Jonathon Porritt 29th February 2016


French nuclear parastatal EDF is facing problem after problem – zombie nuclear projects in the UK, Finland, China and France, a fleet of ‘beyond the grave’ reactors, a dropping share price and its drooping credit rating. But is it really as bad as all that? Jonathon Porritt has exclusive access to the leaked Agenda of its latest board meeting. And the answer is – no. It’s even worse.


You seriously wouldn’t want to be a Director of EDF at the moment. The agenda for an average Board Meeting must be seriously gloomy on each and every occasion.

And thanks to an EDF mole (and to judge by the number of leaks to the French press and the UK’s FT there’s a lot of them) I can now state this as fact, not mere opinion.

An annotated copy of the Agenda items for their last meeting on 16th February mysterious showed up in my email today, helpfully summarised by Alexandre Perra, EDF’s Executive Committee Secretary.

Item 1: Existing EPR construction projects

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http://www.reuters.com/article/usa-nuclear-regulator-idUSL2N1692BF

CORRECTED-U.S. NRC engineers urge fix for nuclear power stations

(Changes time frame to late February instead of late January in paragraph 2)

By Timothy Gardner
Tue Mar 1, 2016 6:17pm EST

A group of engineers within the U.S. nuclear power regulator is concerned that a design flaw in nearly all U.S. nuclear plants could endanger emergency core cooling systems. The group has urged the regulator to order power station operators to either fix the problem or face mandatory shutdowns.

Seven engineers in late February petitioned the Nuclear Regulatory Commission to order immediate enforcement actions against licensees of U.S. nuclear power plants, in a little-noticed, but public move.

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The petition said 13 open phase events have occurred at U.S. and international nuclear plants over the last 14 years.

Dave Lochbaum, a nuclear expert at nonprofit group the Union of Concerned Scientists, said it was encouraging that the engineers stepped forward without fear of retribution. But he said those concerns show "something is not right with the safety culture at the agency." The NRC could have eased concerns years ago by forcing plants to take action, he said.

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https://en.wikipedia.org/wiki/Article_9_of_the_Japanese_Constitution

The creation of the openly revisionist lobby Nippon Kaigi in 1997 has considerably accelerated the pressure on Article 9: this very influential organization (289 of the 480 Diet members and 15 of the 19 members of the Shinzo Abe government are affiliated) favors the return to the fundamentals of Imperial Japan, including monarchy, State Shinto, and militarism, and "Nippon Kaigi and its allies aim to revise the constitution, particularly Article 9 (which forbids a standing army)".[20]

https://en.wikipedia.org/wiki/Nippon_Kaigi

Shinzo Abe, the prime minister of Japan, serves as a special advisor to the group's parliamentary league.[2]

http://www.glamour.com/inspired/blogs/the-conversation/2016/02/donald-trump-is-the-best-repub

Donald Trump Is the Best Republican Presidential Candidate on Women's Health Issues Including Planned Parenthood and the Affordable Care Act, Says Columnist Krystal Marie Ball

By Krystal Marie Ball// 4 days ago

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On Planned Parenthood, Trump is better than his opponents. Thanks to doctored videos filmed by now-indicted antiabortion activists, Washington Republicans including the senators Ted Cruz of Texas and Marco Rubio of Florida have led a baseless witch hunt against the women’s health organization and even considered shutting down the government in an effort to deny Planned Parenthood federal funds. Cruz and Rubio were among the Republican cosponsors of legislation to defund the organization with Cruz leading the shutdown threat. Even the allegedly moderate and reasonable Ohio Gov. John Kasich has gone along with these efforts, recently signing a bill in his home state that would defund the organization. Amazingly however, Trump has defended Planned Parenthood repeatedly in debates, has told Sean Hannity “they do good things,” and explained the “very good work” that Planned Parenthood does to Chuck Todd. Trump’s decision to defend Planned Parenthood’s non-abortion work certainly defies the Republican elite orthodoxy but may find some support among Republican women. After all, one in five American women have visited a Planned Parenthood in their life—and Planned Parenthood enjoys a much higher approval rating than the Republican Party itself.

On Obamacare, Trump is better(ish) than his opponents. President Obama and democratic lawmakers designed the Affordable Care Act to improve women’s health. From illegalizing charging women more for insurance to making birth control free to mandating a baseline of care that includes preventive care like mammograms, Obamacare is a big step forward on women’s health that Republicans are chomping at the bit to tear apart. Well, all of the Republicans, except one. With Trump and Obamacare, it’s complicated. He actually shocked conservatives by supporting the Obamacare mandate, one of the most controversial parts of the law, before backing down and echoing the Republicans' calls to repeal it. Trump has made a concerted effort though to distinguish himself from his Republican opponents telling the audience at a CNN Town Hall: “So here’s where I am a little different. I don’t want people dying in the streets,” a sentiment echoing others he’s made about his commitment to health care for all. So how will he keep people from “dying in the streets?” Trump has kept the specifics fuzzy but has suggested the federal government may cover the costs of those who can’t afford the private insurance price tag. Look, I’m not saying Trump’s terrific here. But at least he’s left some wiggle room on Obamacare and seems committed in principle to universal coverage with federal government involvement—that DOES set him apart from his conservative rivals.

And on that most controversial of women’s health issues, abortion, Trump is also the most moderate of the top three contenders. Both Rubio and Cruz believe that a woman should be forced to bear the baby of her rapist. Trump also describes himself as pro-life (after years of defining himself as pro-choice) but unlike the others he supports exceptions for rape, incest, and the life of the mother. If the next president has a Supreme Court pick, Trump’s moderation on abortion may just keep a majority on the court for upholding abortion as a right.

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http://www.marketwatch.com/story/this-test-is-changing-the-way-depression-is-treated-2016-02-17

This test is changing the way depression is treated

By Amy Hoak
Published: Feb 17, 2016 9:40 a.m. ET

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But a company in Mason, Ohio, is making advances in helping pinpoint the medicine best suited to an individual suffering from depression or another mental illness — by analyzing DNA swabbed from the inside of the patient’s cheek. The GeneSight test is based on technology licensed from the Mayo Clinic and Cincinnati Children’s Hospital Medical Center.

So far, 250,000 patients have been tested using GeneSight. Many commercial and government insurance plans — Medicare and the U.S. Department of Veterans Affairs included — cover all or part of the cost of testing.

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Recently, MarketWatch interviewed Virginia C. Drosos, Assurex’s president and chief executive, and Bryan M. Dechairo, the company’s vice president of medical affairs and clinical development. Below is an edited Q & A.

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MW: What type of patient is most likely to benefit from this test? Are there any patients who are less likely to benefit?

Drosos: GeneSight is appropriate for any person who did not respond to the medication prescribed to him or her for a mental health disease. After the first failed medication, only 29% respond to the second medication and only 17% respond on the third. At the same time, side effects go up. Anyone whose medication isn’t working or is taking multiple medications would significantly benefit from GeneSight. Also any people who have multiple or complex health conditions, children, or someone who is elderly.

MW: How successful is the test in pairing a patient with the best medication for him or her?

Drosos: When a doctor [prescribes] medication [he or she believes] is right for the patient, they only get it right 49% of the time the first time and 29% of the time the second time. When the doctor uses GeneSight for patients failing their current medication, we more than double the patient’s response rate to their new medication.

Dechairo: There’s no way that we will make the medications that exist today work for all patients, no matter how good our test is. Without GeneSight, only 1 in 4 patients [who are on their second medication] are getting better. We are making it 2 in 4. That’s a major improvement, but it’s not perfect. Antidepressants currently work through a few brain receptor pathways, including serotonin, norepinephrine, and dopamine. Mental health disorders occur through modulation of a constellation of neuro-networks which will require future molecular medicine discovery to effectively treat all patients.

MW: What is in the future for the company, and this field?

Drosos: We upgraded our test last November, going from 8 genes to 12 genes. We also added a significant number of medications in two new classes. We always had antidepressants and antipsychotics, and added anxiolytics [medications for anxiety] and mood stabilizers. This means that our Psychotropic [medicine that affects mental activity] panel is the most comprehensive available, covering more than 95% of the prescriptions written for depression, anxiety and bipolar disorder. We also have an Analgesic [pain killer] panel, which has broad coverage of medications used to treat chronic back pain, and an Attention Deficit Hyperactivity Disorder [ADHD] panel, which covers 100% of prescribed stimulant and non-stimulant medications. Our mission is to help patients with psychiatric, chronic pain and neurologic conditions achieve wellness, so we will keep expanding our treatment decision support products to achieve this as we make more scientific discoveries.

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http://necir.org/2015/10/03/more-harm-than-good-documentation/

More harm than good? Use of genetic mental health tests has grown rapidly. But evidence they work is scant. (+documentation)

By Beth Daley
October 3, 2015

RUTLAND, Vt. — For the first time in John R. Brown's two-decade quest for the right medication to make his brain behave, his psychiatrist offered him hope in the form of what seemed like rock-solid science.

By collecting the former editor's DNA with a quick cheek swab, a new genetic test retailing at $3,800 would reveal which depression medications Brown would likely respond well to and those he would not.

The GeneSight test result helped prompt Brown's psychiatrist to switch him to a new drug in June, making Brown optimistic that there might be a path back to a job, an apartment and even a new girlfriend. But three weeks later Brown, 40, was suicidal, checking into a mental hospital at his therapist’s urging.

"I can't help but wonder if I should have stuck with the devil I know," Brown now says.

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But a review by the New England Center for Investigative Reporting has found that virtually all the evidence that these psychiatric tests work is based on limited studies funded by the companies themselves or researchers they fund, including all five studies used to promote GeneSight on the company’s website.

The federal government doesn't require companies to prove thousands of tests are accurate before marketing and selling them. Unlike drugs, the Food and Drug Administration does not regulate them, although the agency has announced plans to.

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"It is the Wild West," said Mildred Cho, associate director at the Stanford Center for Biomedical Ethics, who says there is little published evidence on the effectiveness of drug response tests.

Eric Lander, a leader of the Human Genome Project and founding director of the Broad Institute in Cambridge, goes further, saying in a New England Journal of Medicine article earlier this year that the mental health testing company claims are "not harmless and may be quite dangerous."

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"The claims of these companies are weak," said Robert Klitzman, a psychiatrist and bioethicist at Columbia University who had a commentary published last week in a mental health journal calling for vigilance in the marketing of genetic mental health tests.

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Yet critics of these tests say it’s impossible for doctors — or anyone — to truly evaluate many of the tests. GeneSight’s proprietary formula for interpreting genetic information has never been independently assessed. The test examines genes well-known to play a role in antidepressant response, but it adds in others that do not have the same level of evidence, some researchers say.

Robert Howland, associate professor of psychiatry at the University of Pittsburgh, wrote a paper last year concluding that the makers of the GeneSight test have overstated the findings of their studies, making outside review more urgent.

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http://www.huffingtonpost.com/arshya-vahabzadeh/can-machine-learning-decode-depression_b_9283828.html

Can Machine Learning Decode Depression?

 02/23/2016 03:19 pm ET | Updated 5 days ago

Depression affects almost 15 million Americans and is the leading cause of disability among U.S adults, yet many people with depression continue to go undiagnosed and untreated. Depression remains a condition that is identified through a clinical assessment focused on signs and symptoms, and there is currently no available diagnostic blood test or scan for depression. Additionally, choosing the right depression treatment can be tricky, as it remains difficult to predict how a person will respond to a particular medication, or to cognitive behavioral therapy (talk therapy). Furthermore, a national shortage of psychiatrists means patients may not be able to access timely medical care.

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What is Machine Learning?

Machine learning was originally developed through the study of artificial intelligence. It has been defined as giving computers the ability to learn without being explicitly programmed. Well, what does that mean? Machine learning recognizes patterns in data that humans cannot detect either visually or by traditional analytic techniques. Machine learning requires machines to do just that, to learn. While it can take some time for machines to be "trained" on data and for useful algorithms to arise, once this has happened, machines excel at data analysis. Machine learning tools have the ability to speedily process huge amounts of data, with none of the fatigue that humans would rapidly face.

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Can machine learning predict the extent and length of someone's depression, right from the outset? In a study published in Molecular Psychiatry, baseline data from over a thousand people with major depressive disorder was analyzed. The aim was to predict the severity and chronicity of their depression. The authors compared the use of traditional analytics and machine learning approach. They not only found that machine learning could help predict the characteristics of a person's depression, but also that it could do this more effectively, and with less information, than traditional approaches. The authors concluded that machine learning could be a clinically useful way to stratify depression.

How about using machine learning to link clinical depression with biomarkers? In one depression study, machine learning tools were used in addition to traditional statistics to analyze the relationship between 67 biomarkers in 5,227 research subjects. This hybrid technique was able to identify 3 biomarkers for depression, namely red cell distribution of width, serum glucose, and total bilirubin. Red cell distribution of width has been linked to inflammation in the body, and a line of research has linked together depression and inflammation. Serum glucose tests are used to screen for diabetes, a condition that has a complex relationship with depression, often occurring concurrently. Lastly it has been suggested that bilirubin is an antioxidant, and depression has been linked to oxidative stress. While some of these associations are tenuous, or speculative at best, this study does do something very useful, it identifies potential biomarkers that can be taken forward into the next round of research.

Machine Learning and Suicide

Suicide and depression are strongly linked, with suicide being the second leading cause of death for young people ages 15 to 34. Suicide rates in the United States have remained largely unchanged for the last 50 years. One of the most difficult jobs for psychiatrists is to assess suicide risk in our patients. A particular challenge is incorporating all of the clinical data that we obtain, such as patient's history of depression, their use of drugs, and their past suicide attempts, into producing a suicide risk assessment. What if we had a tool that would help us to do that in a more quantitative way, helping us to more accurately identify high risk patients, and give them preventative care? I was particularly intrigued by a pilot study that used data from 144 patients with mood disorders. By using machine learning to evaluate clinical data, the researchers were able to produce three different machine learning algorithms that could distinguish between people that had attempted suicide, and those that had not, based on the patient's prior clinical data. The prediction accuracy varied between 65-72%. These machine learning algorithms could be potential tools to help target suicide prevention interventions.

Predicting Treatment Response

One central challenge is being able to predict how patients will respond to psychiatric treatments. For example, in depression we have a wide range of antidepressant medications and cognitive behavioral therapy based approaches. At the present time there is no way of predicting how an individual is going to respond to a particular medication, although some companies have suggested that genetic testing could help with prediction. One study looking at 4041 patients with depression, found that by using a machine learning approach, they could predict response to the antidepressant citalopram with a highly statistically significant accuracy of 64.6%.

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At the moment the quoted research is still quite preliminary, and I would not expect your family physician or psychiatrist to be using it just yet. However, this research does give us hope, and illustrates the promise of data science, and more specifically machine learning, in mental health.