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大家好，这是第27期的第二次小分队，也是捉妖第二次发帖，希望没有二到大家
今天科技不关乎物理关乎生理了~来看看科学家们是怎么倒腾我们的细胞的吧：）
Part I：Speaker
Anxiety Increases With Online Health Searches
[Rephrase 1]
[Dialog, 1:23]
Transcript hided
A hypochondriac can turn indigestion into a heart attack faster than you can say myocardial infarction. And thanks to the internet’s unlimited supply of medical information, there’s an online version of the condition—call it cyberchondria.
Now a study has identified which people are most at risk of becoming victims of serious cyberchondria.
More than 500 adults were surveyed about their ability to handle uncertainty, and their levels of anxiety about their current health. They were also asked to rate how much they felt online health searches affected their anxiety.
The results: those volunteers who were poorest at dealing with uncertainty did the most searching about symptoms and illnesses. And as they searched, their levels of anxiety significantly increased. The study is in the journal Cyberpsychology, Behavior and Social Networking.
The researchers say that people with an “intolerance of uncertainty” can alleviate anxiety by using cognitive strategies—for example, reminding themselves that it’s doubtful they will find a definitive explanation for their ambiguous symptoms. After all, although Google says that the throbbing in your head might mean you have six weeks to live, it’s much more likely that Arnold is right: “It’s not a tumor! It’s not a tumor, at all.”
Source: Scientific American
http://www.scientificamerican.com/podcast/episode.cfm?id=anxiety-increases-with-online-healt-13-10-26
Part II：Speed
Our Final Invention
By Sid Perkins 4:00pm, October 22, 2013
[Time 2]
Computers already make all sorts of decisions for you. With little or no human guidance, they deduce what books you would like to buy, trade your stocks and distribute electrical power. They do all this quickly and efficiently using a simple form of artificial intelligence. Now, imagine if computers controlled even more aspects of life and could truly think for themselves.
Barrat, a documentary filmmaker and author, chronicles his discussions with scientists and engineers who are developing ever more complex artificial intelligence, or AI. The goal of many in the field is to make a mechanical brain as intelligent — creative, flexible and capable of learning — as the human mind. But an increasing number of AI visionaries have misgivings.
Science fiction has long explored the implications of humanlike machines (think of Asimov’s I, Robot), but Barrat’s thoughtful treatment adds a dose of reality. Through his conversations with experts, he argues that the perils of AI can easily, even inevitably, outweigh its promise.
By mid-century — maybe within a decade, some researchers say — a computer may achieve human-scale artificial intelligence, an admittedly fuzzy milestone. (The Turing test provides one definition: a computer would pass the test by fooling humans into thinking it’s human.) AI could then quickly evolve to the point where it is thousands of times smarter than a human. But long before that, an AI robot or computer would become self-aware and would not be interested in remaining under human control, Barrat argues.
One AI researcher notes that self-aware, self-improving systems will have three motivations: efficiency, self-protection and acquisition of resources, primarily energy. Some people hesitate to even acknowledge the possible perils of this situation, believing that computers programmed to be superintelligent can also be programmed to be “friendly.” But others, including Barrat, fear that humans and AI are headed toward a mortal struggle. Intelligence isn’t unpredictable merely some of the time or in special cases, he writes. “Computer systems advanced enough to act with human-level intelligence will likely be unpredictable and inscrutable all of the time.”
Humans, he says, need to figure out now, at the early stages of AI’s creation, how to coexist with hyperintelligent machines. Otherwise, Barrat worries, we could end up with a planet — eventually a galaxy — populated by self-serving, self-replicating AI entities that act ruthlessly toward their creators.
[384 words]
Source: Science News
https://www.sciencenews.org/article/our-final-invention
New definition of 'full term' narrows on-time arrival window
By Laura Sanders 6:42pm, October 24, 2013
[Time 3]
To the chagrin of pregnant women terrified of giving birth on a dingy Metro platform, due dates are far from certain. Due dates are also weird: They are calculated as 280 days (or 40 weeks) from the day of a woman’s last menstrual period, rendering a woman officially “pregnant” before she’s even ovulated. The odds of a little bundle of joy arriving precisely on his or her due date are actually pretty low. But thankfully, doctors are pretty good at ballparking the big day.
Until now, babies born at any time during a wide five-week window (three weeks before a due date and two weeks after) were considered fully cooked. Now, a panel of clinicians says otherwise.
In an October 22 announcement and an opinion piece in the November Obstetrics & Gynecology, the American College of Obstetricians and Gynecologists and the Society for Maternal-Fetal Medicine narrowed the definition of “full term” by shaving off two weeks at the beginning and one at the end. Instead of a luxurious five-week window, babies now have a two-week window to hit. Under the new definition, babies born during weeks 37 and 38 of pregnancy are “early term,” babies who hit weeks 39 and 40 are “full term,” those who arrive during week 41 are “late term,” and babies born beyond week 42 are “post term.”
These narrowed definitions better reflect outcome realities for babies, the scientists write. The old definition assumed that all babies born during that five-week window were equally healthy. But a growing mountain of data says otherwise. Even though they were considered full term, babies born on the early side, around 37 weeks, are known to be at a higher risk for poorer outcomes.
The new definitions are an effort to discourage clinicians and pregnant women from scheduling elective births, either by Cesarean section or by induced labor, before 39 weeks. Even during the last few weeks of pregnancy, the growing body and brain are still cramming in loads of last-minute work, and that important time shouldn’t be cut short for trivial reasons.
[343 words]
Source: Science News
https://www.sciencenews.org/blog/growth-curve/new-definition-full-term-narrows-time-arrival-window
How Many Cells Are In Your Body?
By Carl Zimmer
A simple question deserves a simple answer. How many cells are in your body?
Unfortunately, your cells can’t fill out census forms, so they can’t tell you themselves. And while it’s easy enough to look through a microscope and count off certain types of cells, this method isn’t practical either. Some types of cells are easy to spot, while others–such as tangled neurons–weave themselves up into obscurity. Even if you could count ten cells each second, it would take you tens of thousands of years to finish counting. Plus, there would be certain logistical problems you’d encounter along the way to counting all the cells in your body–for example, chopping your own body up into tiny patches for microscopic viewing.
For now, the best we can hope for is a study published recenty in Annals of Human Biology, entitled, with admirable clarity, “An Estimation of the Number of Cells in the Human Body.”
The authors–a team of scientists from Italy, Greece, and Spain–admit that they’re hardly the first people to tackle this question. They looked back over scientific journals and books from the past couple centuries and found many estimates. But those estimates sprawled over a huge range, from 5 billion to 200 million trillion cells. And practically none of scientists who offered those numbers provided an explanation for how they came up with them. Clearly, this is a subject ripe for research.
[238 words]
[Time 5]
If scientists can’t count all the cells in a human body, how can they estimate it? The mean weight of a cell is 1 nanogram. For an adult man weighing 70 kilograms, simple arithmetic would lead us to conclude that that man has 70 trillion cells.
On the other hand, it’s also possible to do this calculation based on the volume of cells. The mean volume of a mammal cell is estimated to be 4 billionths of a cubic centimeter. (To get a sense of that size, check out The Scale of the Universe.) Based on an adult man’s typical volume, you might conclude that the human body contains 15 trillion cells.
So if you pick volume or weight, you get drastically different numbers. Making matters worse, our bodies are not packed with cells in a uniform way, like a jar full of jellybeans. Cells come in different sizes, and they grow in different densities. Look at a beaker of blood, for example, and you’ll find that the red blood cells are packed tight. If you used their density to estimate the cells in a human body, you’d come to a staggering 724 trillion cells. Skin cells, on the other hand, are so sparse that they’d give you a paltry estimate of 35 billion cells.
So the author of the new paper set out to estimate the number of cells in the body the hard way, breaking it down by organs and cell types. (They didn’t try counting up all the microbes that also call our body home, sticking only to human cells.) They’ve scoured the scientific literature for details on the volume and density of cells in gallbladders, knee joints, intestines, bone marrow, and many other tissues. They then came up with estimates for the total number of each kind of cell. They estimate, for example, that we have 50 billion fat cells and 2 billion heart muscle cells.
Adding up all their numbers, the scientists came up with…drumroll…37.2 trillion cells.
[332 words]
[Time 6]
This is not a final number, but it’s a very good start. While it’s true that people may vary in size–and thus vary in their number of cells–adult humans don’t vary by orders of magnitude except in the movies. The scientists declare with great confidence that the common estimate of a trillion cells in the human body is wrong. But they see their estimate as an opportunity for a collaboration–perhaps through an online database assembled by many experts on many different body parts–to zero in on a better estimate.
Curiosity is justification enough to ponder how many cells the human body contains, but there can also be scientific benefits to pinning down the number too. Scientists are learning about the human body by building sophisticated computer models of lungs and hearts and other organs. If these models have ten times too many cells as real organs do, their results may veer wildly off the mark.
The number of cells in an organ also has bearing on some medical conditions. The authors of the new study find that a healthy liver has 240 billion cells in it, for example, but some studies on cirrhosis have found the disease organ have as few as 172 billion.
Perhaps most importantly, the very fact that some 34 trillion cells can cooperate for decades, giving rise to a single human body instead of a chaotic war of selfish microbes, is amazing. The evolution of even a basic level of multicellularity is remarkable enough. But our ancestors went way beyond a simple sponge-like anatomy, evolving a vast collective made of many different types. To understand that collective on a deep level, we need to know how big it really is.
[288 words]
Source: National Geographic
http://phenomena.nationalgeographic.com/2013/10/23/how-many-cells-are-in-your-body/
Part III： Obstacle
New Microscopes Reveal Live, Developing Cells in Unprecedented 3-D Clarity
Based on materials provided by National Institute of Biomedical Imaging and Bioengineering.
Researchers at NIH have developed two new microscopes, both the first of their kind. The first captures small, fast moving organisms at an unprecedented rate and the second displays large cell samples in three dimensions while decreasing the amount of harmful light exposure to the cells. Both microscopes surpass in clarity any other currently on the market.
[Paraphrase 7]
The first microscope allows researchers to obtain fast moving images at double the spatial resolution of a conventional microscope. This provides a vastly clearer picture, enabling cell components that were once quite blurry to now become sharply defined; the difference is similar to that of a 1990's-era standard TV set versus today's high-definition TVs. The microscope is also 10 to 100 times faster than traditional technologies.
"It's always helpful to look at smaller and smaller things," said Hari Shroff, Ph.D., at NIH's National Institute of Biomedical Imaging and Bioengineering (NIBIB) lab chief of NIBIB's section on High Resolution Optical Imaging (HROI.) "Looking at a fixed cell at high resolution can tell you where different parts of the cell are at any given moment; but because much of biology depends on the movement of very small proteins finding each other and interacting, we really needed to look at how things move in a live cell."
The problem is that the higher the resolution, the harder it is to eliminate the blur from both light diffraction (the glow that sometimes occurs as light bends around objects) and the motion going on inside the live cell. Traditional linear structured illumination microscopy (SIM) cannot maintain the high resolution desired by researchers when the sample is moving quickly.
Shroff and his research fellow Andrew York, Ph.D., found an answer to these problems with their new instant linear structured illumination microscopy (iSIM), described in a paper published in Nature Methods on October 6th. Building on traditional SIM technology, the iSIM allows real-time, 3-D super resolution imaging of small, rapidly moving structures -- such as individual blood cells moving through a live zebrafish embryo. This kind of imaging is impossible with other microscopes; the ones that are fast enough to record rapid movement do not have a high enough resolution to see inside the cells; and other microscopes with similar resolution are just too slow to capture that amount of motion clearly.
If a photographer wants to take a better photograph, he can either buy a camera with a better lens and higher pixels or he can modify the picture after it's taken, using Photoshop. The principle is similar in microscopy. Instead of approaching the problem by creating better imaging software that helps to increase the resolution after the fact, as most high resolution microscopes do, Shroff and his lab developed a microscope with better lenses and mirrors so that the higher resolution is captured in the original image.
"What we've essentially done is eliminate the need for extensive computer processing by creating a better microscope at every stage of data gathering," said Shroff. "Before, we relied on computer software and algorithms to do things like sort through hundreds of images, eliminate out of focus light, and combine the individual images together. Now, we can do most of that optically with the microscope itself." This means that researchers can skip the time-consuming steps in which computers process the massive amounts of data normally required for such high resolution imaging. Now they will be able to see the images instantly instead of waiting hours or sometimes days, and the data itself takes about 1% of the hard drive space as that produced by previous microscopes.
The second microscope, described in a paper published in Nature Biotechnology online on October 13, builds on selective plane illumination microscopy (SPIM). Traditional microscopes expose the whole sample to light even though they are only imaging one small section at a time. However, just as the sun can damage skin cells, too much light exposure can damage or even kill biological samples like embryos. SPIM uses a thin beam of light to illuminate only the single plane that is currently being imaged so the biological sample is not damaged by overexposure to light. However, the technology is limited because looking at a 3-D object from only one point of view does not provide a complete representation of the object -- in the same way that viewing a globe from one perspective gives no information about what is on the other side of the world. Traditionally, SPIM microscopes rotate the sample so that they can clearly see all the dimensions, but this severely limits the imaging speed and can increase the damage done to the cells from light exposure because of the many extra images taken at multiple angles. As a result imaging is also slowed down, and the ability to capture much of the fast moving cellular motion is lost.
In order to combat this problem, Shroff and NIBIB staff scientist Yicong, Wu, Ph.D., developed a dual-view SPIM (diSPIM) microscope with two separate detection cameras. The cameras are set at a 90 degree angle to capture perpendicular views of the sample. This perpendicular view results in undistorted 3-dimensional images, and since only two views are acquired, the microscope can still capture events at very high speed. Additionally, with relatively simple modifications, traditional single camera SPIM microscopes can be converted into the dual-camera diSPIM. The real challenge in developing this technology was to find a way to combine the two disparate images from the two cameras, which required the creation of a new post-processing software algorithm.
The increased speed at which the new dual microscope can image the cells allows for clearer images of even very fast moving viruses. Being able to see how a virus enters a cell, and once it's in, how it moves around, could go a long way towards scientists' understanding of how infections occur and potentially how to fight them more effectively. In the same way, observing the migration of cancer cells in a 3-D environment could unlock information on how cancer grows, finds nutrients, and spreads.
"Biology is three-dimensional, not two dimensional. The nucleus of a cell is spherical, not circular, and as scientists, it's up to us to find ways to observe cells as accurately as possible, Shroff said. "We're really moving biology into the third dimension with this microscope." There's a lot of attention right now on how neurons fire and interact with each other, but the truth is, we don't even understand how a brain develops -- even in the most simple of organisms like C. elegans, a worm with only 300 brain cells. We don't know why brain cells go where they do or what determines their organization. We can't understand more about this process without observing it, and that's something that these devices can help to provide."
The Shroff lab has already begun multiple collaborations with biological labs both inside the NIH as well as external institutions, including Yale, Sloan Kettering, and the University of Connecticut Health Center.
[1105 words]
Source: Science Daily
http://www.sciencedaily.com/releases/2013/10/131025123056.htm
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发表于 2013-10-28 22:04:21
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