Saturday, January 30, 2016
We sort of already know this but this spells out that the likely culprit is processed foods and sugar while fruit and vegetables are the opposite in effect. What is interesting is that it disturbs your natural sleep cycle.
This adds yet one more reason to shift our diets as much as possible to the vegan standard
It also suggests an immediate protocol for those who do have poor sleeping patterns that is direct and testable.
Can't Sleep? Your Dinner Might Be the Problem
—By Tom Philpott
| Wed Jan. 20, 2016 6:00 AM EST
If you're nodding off as you read this, don't blame my prose style. You probably didn't sleep enough last night, or maybe you just slept poorly. According to the Centers for Disease Control and Prevention, between 50 million and 70 million US adults have some kind of sleep disorder—think insomnia, apnea, or narcolepsy. This troubled slumber, in turn, is linked to increased risk of everything from car accidents to Alzheimer's.
It turns out your diet might be to blame for restless nights, a new study by Columbia University researchers suggests. The team subjected 26 normal-weight adults to a controlled food regimen—high in dietary fiber and low in saturated fat and added sugars—for four days. On the fifth day, I'll call this the dietary "free-for-all" day, they let the participants eat whatever they wanted. Each night, they monitored both sleep duration and quality—the number of times the participants woke up during the night, and the amount of time they spent in "slow-wave sleep," the most restorative sleep stage.
Meals low in fiber and high saturated fat were associated with lower quality sleep, while higher levels of sugar led to more wake-ups.
The result: While total time spent snoozing didn't change over the course of the experiment, sleep quality declined the more people spent their free-for-all day loading up on fiber-light, fat- and sugar-heavy foods. Meals low in fiber and high in saturated fat were associated with significantly less slow-wave sleep, while higher levels of sugar led to more wake-ups. The study subjects also fell asleep faster (an average of 17 minutes versus 29 minutes) on the controlled diet than they did on the self-selected one.
That's bad news for the average American, who tends to have a horrible diet—lacking in fruits and vegetables and chock-full of ultra-processed crap and excess sugar.
The study doesn't speculate about why these dietary choices messed with sleep, but a growing body of science links diet to the health and diversity of the gut biome—the trillions of microorganisms that live in our digestive tracts—which in turn affect brain processes. Dietary fiber essentially feeds these vital organisms, and diets low in it have been shown to reduce biome diversity. High-sugar diets, meanwhile, appear to alter the gut biome in ways that seem to promote obesity. The relationship between the gut biome and sleep, however, remains little studied.
Research suggests that sleep deprivation interferes with the hormones that tell us when we're full—meaning that bad sleep can lead to bad dietary choices.
Even so, the Columbia study offers a new twist on the sleep-diet nexus. People who chronically experience poor sleep are more likely to endure diet-related conditions like obesity and diabetes, the CDC states. Previous research suggests that sleep deprivation interferes with the hormones that tell us when we're full—meaning that bad sleep can lead to bad dietary choices. The Columbia study suggests a vicious circle: Bad dietary habits can also muck up sleep.
All the more reason to steer clear of the supermarket's chips and cookie aisles. "The finding that diet can influence sleep has tremendous health implications, given the increasing recognition of the role of sleep in the development of chronic disorders such as hypertension, diabetes and cardiovascular disease," the study's lead author, Columbia's Marie-Pierre St-Onge, said in a press release.
This is a natural and expected result once we understand that mutation is an ongoing process and that cancer immortality blocks elimination. It is a useful insight that allows you to understand what you are seeing in the so called chaos.
It may even help therapeutically.
I do not see it leading to much else though but we may be surprised.
The equation that will help us decode cancer’s secrets
January 18, 2016 11.04am EST
A cancer forms when a cell in the body goes awry, multiplying out of control to form a tumour. A typically-sized cancer tumour is made up of more cells than there are people on the planet, and cells from different areas of a single tumour have different alterations in their genetic code.
This sounds like complete chaos. How can we expect to treat cancer effectively – even with newer “targeted” therapies that hit the products of faulty genes – if every cell is different? In order to find more effective ways to treat the disease, we needed to find some order in the chaos.
Looking for patterns
When we first began to study the patterns of genetic alterations inside human cancers, chaos was exactly what we expected to see. And the first studies seemed to back this idea up.
Surprisingly though, the more we looked, the less chaotic the patterns became. In fact, we realised that there was often such striking regularity in the patterns that they might be able to be explained by a simple mathematical formula.
In our latest work, published in Nature Genetics, we were able to explain how the patterns we found in the chaos of genetic alterations inside a cancer reveal how that cancer grew.
When copying goes wrong
Each time a cell divides to form two new daughter cells, the DNA inside it must be duplicated so that each daughter receives a complete set. Unfortunately, although the process of DNA replication is very accurate, it’s not perfect and errors occur during the copying process. These errors are called genetic mutations.
Each time cells divide, they copy their DNA – including any previous errors – meaning that mutations that occur in one division are inherited by all the descendents of that cell. In this way, the DNA from the first cell is progressively distorted as the cancer grows, eventually leading to the genetic chaos we see in tumours.
Our approach was to try and “read” this process in reverse: starting from the end point of a cancer genome with many mutations and attempting to decipher the sequence of cell divisions that would have led to the particular pattern of mutations we observed.
We used data from 14 different types of cancers that had been collected using a technique called next-generation sequencing, which can tell us two things: first, whether a particular mutation is present in a cancer, and second, the fraction of cells within the cancer that has a given mutation in their DNA.
This technology has produced huge amounts of data, stored in publicly available databases. Many researchers have created complex computer programs that search for patterns in it. But we decided to take a different approach. We realised that the pattern of mutations within a cancer might make more sense if we looked at them while thinking about how the cancer had grown.
We realised that mutations that happened early in a cancer’s development would be present in lots of cells within the cancer, because these mutations would be inherited by all the daughter cells as the cancer grew. On the other hand, mutations that occurred later would be present in only a few cells.
The interesting twist was when we realised that there should be many more rare mutations in the cancer – each present in only a relatively small number of cells – than common ones. This is because later on in a cancer’s development, when the tumour is larger, there are many more cells dividing and so much more opportunity for mutations to happen.
The formula we developed perfectly described the pattern of mutations in more than 200 of the cancers we looked at. This meant we knew exactly how these cancers had grown.
And – importantly – it shows that the pattern of mutations in a cancer often follow something known as a “power-law”.
Power-laws are found in all kinds of natural systems. Take earthquakes, for example. There are small seismic events happening almost constantly around the globe, but cataclysmic earthquakes only happen once a decade or so. It turns out that the average time between different types of earthquakes obeys a power law.
Earthquakes also follow the power law equation. www.shutterstock.com
In cancer, we found that the way the cancer grows means that mutations present in large numbers of cells (large events) were rare, whereas mutations present in only a few cells (small events) were commonplace. In other words, this suggested we could expect to discover a power law underlying cancer’s growth. And that’s exactly what we found.
We’re excited to have found a natural law of cancer growth that reveals striking simplicity in the apparent chaos of a cancer genome. We think this work is important as it is a first entry in what we hope will become a “mathematical rulebook for cancer”, that will serve to simplify and improve our understanding of the disease.
There’s a long road ahead, but now we’re starting to find order among the chaos inside a tumour, we are uncovering new clues as to how we can better target the disease and hopefully make a difference to the people who suffer from it.