Darwinism vs. The real world. V

Cardiovascular Function: What Happens When Real Numbers Are Wrong?

Howard Glicksman July 31, 2015 1:57 PM

Editor's note: Physicians have a special place among the thinkers who have elaborated the argument for intelligent design. Perhaps that's because, more than evolutionary biologists, they are familiar with the challenges of maintaining a functioning complex system, the human body. With that in mind, Evolution News & Views is delighted to present this series, "The Designed Body." Dr. Glicksman practices palliative medicine for a hospice organization.

Due to the laws of nature, the body must have enough energy for its trillions of cells to work properly. The body won't function very well if its cells don't have enough oxygen (O₂).

Evolutionary biologists claim that the organs described so far in this series, and the systems that control them, must have come about by chance and the laws of nature alone. But their theory seems to account only for how life looks and not how it actually works to stay alive under the laws of nature. Experience teaches that real numbers have real consequences when it comes to life and death.

Based on what we know about how the body actually works, our earliest ancestors had to be able to provide at least 3,500 mL/min of O₂, mainly to their muscles and heart, to be able to run fast enough and fight hard enough to win the battle for survival. That would have required their lungs to have a rapid enough airflow, a large enough volume, and an efficient enough gas exchange to bring in enough O₂. It would also have required that they have enough iron to make enough hemoglobin to be able to carry enough O₂ in the blood. And finally, their cardiac output (CO) needed to be at least 25 L/min to sustain the kind of activity levels needed to hunt rather than be hunted.

As I've noted in previous articles, lung function, hemoglobin production, and cardiac output are controlled by irreducibly complex systems, each consisting of sensors, integrators, and effectors that must also inherently know what is needed for survival. I call this natural survival capacity, because the systems involved must naturally have the capacity to keep a specific chemical or physical parameter within a certain range to allow for survival. We have looked at what happens to the body when its lung function and hemoglobin production do not measure up to what is needed. Now we will start to look at what happens when cardiac function is not up to snuff.

At rest the average male needs about 250 mL/min of O₂ to keep all of his organs working properly, and any increase in activity requires more. Walking slowly requires 500 mL/min of O₂; walking quickly, 1,000 mL/min; moderate jogging, 2,000 mL/min; and fast running, 3,500 mL/min of O₂. Since we know that the CO has to be at least 25 L/min for maximum activity, we can figure out what the minimum CO levels would have to be for lesser activity levels. We can do this by multiplying 25 L/min by the ratio of the lower and maximum O₂ consumption. So to jog at a moderate pace, the minimum CO would have to be 25 x 2,000/3500 = 14.3 L/min. To walk quickly would take at least a CO of 7.2 L/min, to walk slowly a CO of 3.6 L/min, and to stay at rest would need a CO of 1.8 L/min.

It is important to note here that these are real numbers that reflect real life and the laws of nature. No matter what evolutionary biologists say about how matter must have organized itself into the complex systems we know are needed for life, medical science tells you that if you don't have a CO of 7.2 L/min, you can't walk very quickly, if you don't have a CO of 3.6 L/min, it would be very difficult for you to walk even slowly, and if you don't have a CO of at least 1.8 L/min, you are probably dead. Certain parameters of cardiac function had to be met for our ancestors to survive within the laws of nature, and no expenditure of imaginary effort can deny this fact.

When real numbers lead to chronic debility with respect to the lungs, they usually involve problems with ventilation and/or gas exchange. But when dealing with chronic debility and the heart, we usually encounter four different problems. Each condition, individually, is capable of causing significant debility but, in real life, they often occur in combination. Just as adding a gas exchange problem to a ventilation problem can more quickly lead to worsening debility from pulmonary dysfunction, so too a combination of more than one of these cardiac conditions can quickly lead to significant weakness and a limited ability to be active and manage independently.

The commonest heart condition in developed countries, and what most people think of when they hear someone has heart trouble, is coronary artery disease. Even though the heart pumps blood throughout the body, it must also supply adequate blood flow to itself so it can do its job. As the blood flows out of the left ventricle through the aortic valve, the coronary arteries turn back over the surface of the heart. The heart is the hardest working muscle in the body and when its blood supply is compromised this can lead to significant debility and even death.

Another common cardiac condition is valvular heart disease. The "V" shaped one-way valves between the atria and the ventricles and the ventricles and their outflow tracts are structured in a way that allows them, when open, to facilitate the forward movement of blood, and when closed, to prevent blood from going backward. The efficiency of cardiac function is dependent not only on adequate coronary blood flow, but also on properly working valves. A valve can't be too tight, slowing forward blood flow, or too lax, allowing backward flow.

When the heart cannot meet the metabolic needs of the body it is said to be in heart failure. This third common cardiac condition can involve either the left or the right side of the heart alone, or both at the same time. In addition, left ventricular failure can be systolic, where reduced muscle contractility leads to weaker pumping action, and/or diastolic, where increased muscle stiffness reduces relaxation and the filling of the ventricle with blood. Both coronary artery and valvular heart disease are common causes of heart failure.

The fourth common cardiac condition is the cardiac arrhythmias. It is the sino-atrial node, the natural pacemaker in the right atrium that dominates the other excitable cells in the heart. It controls the heart rate and starts coordinated atrial contraction and the conducting system makes sure that coordinated ventricular contraction takes place soon afterward. Any disruption or short-circuiting of this signal formation, impulse conduction or coordinated muscle contraction can lead to significant debility and even death. All three of the conditions mentioned above, and other disorders, can predispose the heart to cardiac arrhythmias.

When real numbers lead to functional problems of the heart, these are usually the four main conditions that contribute to the situation. In the next few articles we will take a closer look at each of them.

It's Design all the way down III

The Puzzle of Perfection, Thirty Years On

Evolution News & Views July 31, 2015 3:18 AM 

Thirty years ago in his book Evolution: A Theory in Crisis, Michael Denton (above) posed "The Puzzle of Perfection" as a challenge to Darwinism. He described molecular machines in the cell as phenomena inexplicable by chance. He predicted that what was known in 1985 was sure to grow, concluding:

It would be an illusion to think that what we are aware of at present is any more than a fraction of the full extent of biological design. In practically every field of fundamental biological research ever-increasing levels of design and complexity are being revealed at an ever-increasing rate. The credibility of natural selection is weakened, therefore, not only by the perfection we have already glimpsed but by the expectation of further as yet undreamt of depths of ingenuity and complexity. (Denton, p. 82)

If the design argument is scientifically credible, it should get stronger with time. The counter-position of natural selection should correspondingly weaken. Was the perfection of cellular machines an illusion in 1985? Has Darwinian theory risen to the challenge in the meantime? Denton's prediction was made before details of ATP synthase, the bacterial flagellum, and kinesin had come to light (see Denton's 2014 description of kinesins and myosins here). And two recent papers suggest that, if anything, the evidence for design has only grown stronger.

The authors of the first paper, published in PNAS, seem hesitant to use the word "perfect" in their description of ATP synthase, the machine that generates energy currency for most cellular processes in all living things (see our animation of this amazing machine here). They use "near-perfect" in the title and throughout the paper:

ATP synthase produces most of the ATP in respiratory and photosynthetic cells. It is a rotary motor enzyme and its catalytic portion F₁-ATPase hydrolyzes ATP to drive rotation of the central γ subunit. Efficiency of chemomechanical energy conversion by this motor is always near-perfect under different ATP hydrolysis energy (ΔG_ATP) conditions. [Emphasis added.]

Any deviation from perfection, however, could be due to experimental error. In their graph, the error bars transverse the slope for 100 percent efficiency (that is, for conversion of chemical energy to mechanical work). It may well be as close to perfect as is physically possible. What's even more striking is that this "near-perfect" level of efficiency is maintained throughout a "broad range" of operation conditions.

The authors found a "simple" model that maintains this near-perfect efficiency. In the F₁ subunit of ATP synthase, where ATP is synthesized or dissociated (depending on the direction of energy flow), they deduced a spring mechanism that generates a "sawtooth" pattern of mechanical work. The spring automatically adjusts for varying conditions:

The chemomechanical energy conversion efficiency of F1 is close to 100% under various ΔG_ATP conditions. The torque profile found here explains how F₁ achieves this remarkable task. Fig. 5C illustrates how F₁ responds to the increase of [ATP] andadjusts its mechanical work accordingly. The equilibrium constants for nucleotide bindings/dissociations are functions of the γ angle. Therefore, as [ATP] is increased, the angular position of binding/dissociation of ATP shifts to the left (Fig. 5C, red arrow) at the point where the spring is shorter. The shorter the spring becomes, the greater the force to extend becomes because of the nature of a spring (Fig. 5B). This shift invariably increases the area of the sawtooth, that is, the mechanical work. This study shows that the following two properties of the torque profile of the F₁ motor ensure ∼100% energy conversion under various ΔG_ATP conditions: (i) shift of the angular positions of binding/dissociation of substrates according to their concentrations and (ii) changing its force (torque) according to the angular position of substrate binding/dissociation, which isreadily accomplished by a simple spring.

Since each of three catalytic sites has this mechanism, there are three springs in the motor. The "sawtooth" is the torque profile, consisting of three steep jumps and linear descents during each catalytic turnover. The shape of the sawtooth adjusts according to concentration or binding angle because of spring-like action inside the machine. It is "simple" only in the author's model to explain the observations. But hey -- if a simple mechanism achieves perfection, who's complaining? The authors didn't disparage this complex machine's efficiency. They twice called it "remarkable." By the way, is anyone surprised to hear that neither Darwin nor evolution is mentioned in the paper?

Perfection in Gene Translation

The second paper explores the amazing process of gene translation. A set of twenty machines helps translate the genetic code into the protein code. It's a shame the set doesn't have a cool name. They are called the "amino-acyl tRNA synthetases." Fortunately, we can call them aaRS for short. Their job is to read the transfer-RNA (tRNA) triplet codons and charge them with the appropriate amino acids. When the charged tRNAs match up with the messenger RNA (mRNA) codons in the ribosome (if the aaRS's did their job accurately), the correct string of amino acids links up to build a protein. The aaRS enzymes are the keys to the genetic code. They link the DNA code to the protein code.

There are twenty normal amino acids in proteins, but 64 possible combinations of triplet codons from the four DNA bases. The aaRS enzymes have to be able to handle situations where one amino acid may correspond to one to six codons. Not all codons link up with equal ease (there may be reasons for that). That's enough to make an aaRS enzyme's job hard, but it also has to discriminate between similar amino acids, like valine and isoleucine. (Remember, molecular machines have no eyes. This occurs in the dark, by touch.) Additionally, the aaRS enzymes have to work fast.

The d-value is a measure of the system's accuracy, with the maximum representing perfect accuracy. But like the auto mechanic dealing with a frantic businessman with a repair emergency, there's a trade-off: "You want it done fast, or you want it done right?" Since d-values can vary by a factor of 400, some situations could bring translation to a halt if accuracy is of paramount concern.

A team of four from Uppsala University, also publishing in PNAS, examined this trade-off problem. They found that cells are much more clever providing both accuracy and speed than anyone knew 30 years ago. First, a little history from 1957:

The existence of maximal accuracy limits (d values) in amino acid discrimination by an amino acid-selecting protein wassuggested years ago by Linus Pauling. He proposed that these dvalues would be very small for pairs of similar amino acids. For discrimination between valine and isoleucine he estimated a dvalue of 10, leading to the proposal of high intracellular amino acid substitution error frequency, which turned out not to be true. We now know that Pauling greatly underestimated the d value by which the isoleucine-specific aa-tRNA synthetase (IleRS) discriminates against valine, but the notion of d-value limits for enzymatic selections has since continued to guide experimental research on replication, transcription, and genetic code translation.

In fact, the discovery of substrate proofreading was inspired by the challenge of how to transcend the accuracy limits postulated by Pauling.

So there you have it. The cell has a way to get both arms of the tradeoff. First, it goes as fast as it can. Then, other molecular machines proofread the result! Here is a clear case where the expectation of design perfection inspired a major discovery. Somehow, the author's Lamarckian explanation is unconvincing:

From our results we suggest that proofreading has evolved in bacterial protein synthesis to minimize damage on the bacterial proteome by amino acid substitution errors due to initial tRNA selection error hot spots as identified here and maybe others that remain to be found from larger datasets.

While one shares their hope that "future extensions will serve as an inspiration and testing ground for theoretical approaches to explain the accuracy of codon reading," approaches based on design theory are bound to be much more productive than evolutionary approaches that hope perfection might be reached by blind processes.

The Puzzle of Perfection, c. 2015

As these papers illustrate, Denton was right. His "expectation of further as yet undreamt of depths of ingenuity and complexity" has been amply fulfilled.

But it's not just seen in the realm of molecular machines. Throughout all biology -- from the tiniest bacterial cell to the greatest of multicellular organisms -- we see exceptional ingenuity and complexity of design.

Illustra's new film Living Waters includes a wonderful example of an "engineering problem" that was solved ingeniously in the male reproductive organs of the humpback whale. The testes would have had to move inside the body cavity when the whale supposedly evolved from a land mammal, but the heat inside would have killed sperm cells, causing sterility -- the end of the line in evolution. We don't want to give away the solution before you watch the film; suffice it to say that Biologic Institute evolutionary biologist Richard Sternberg, who studied the situation, calls it "an elegant solution to the problem; it's beautiful. It's anatomically complex."

In the film, Tim Standish shows another example of design perfection in salmon, which can discriminate odors at the level of parts per trillion, recalling combinations of odors they had memorized as juveniles.

As Sternberg concludes, the flip side of Darwin's proposal of natural selection as a designer substitute is that "things look designed -- because they are designed." Whether in a whale or a bacterial cell, "things look too optimal," he adds, "to have been cobbled together by some haphazard mechanism."

The invincible scroll II

The Bible—A Remarkable Story of Survival

THE Bible is the most widely distributed book in history—an estimated 4.8 billion copies have already been circulated. In 2007 alone, more than 64,600,000 copies were produced. To put that into perspective, consider that the best-selling work of fiction that year had an initial printing of 12 million copies in the United States.

On its way to becoming the world’s most published book, the Bible survived many hazards. Down through history, it has been banned and burned, and those who would translate it have been oppressed and killed. Yet, one of the greatest threats to the continued existence of the Bible was, not the sudden heat of persecution, but the slow process of decay. Why so?

The Bible is a compilation of 66 smaller books, the oldest of which were written or compiled over 3,000 years ago by members of the nation of Israel. The original writers and those who copied the texts recorded the inspired messages on perishable materials, such as papyrus and leather. None of the original writings have yet been discovered. But thousands of ancient copies of small and large sections of the books of the Bible have been unearthed. A fragment of one of these books, the Gospel of John, dates to within just a few decades of the original document written by the apostle John.

“The transmission of the text of the Hebrew Bible [Old Testament] is of extraordinary exactitude, without parallel in Greek and Latin classical literature.”—Professor Julio Trebolle Barrera

Why is it remarkable that any copies of the Bible have survived? And how accurately do modern Bibles reflect the messages recorded by the original writers?

What Happened to Other Ancient Documents?

The survival of the Bible is extraordinary, considering what happened to the writings of nations contemporary with the Israelites. The Phoenicians, for instance, were neighbors of the Israelites during the first millennium B.C.E. These sea traders spread their alphabetic writing system throughout the Mediterranean area. They also profited from an extensive papyrus trade with Egypt and the Greek world. Even so, the National Geographic magazine observes regarding the Phoenicians: “Their writings, mostly on fragile papyrus, disintegrated—so that we now know the Phoenicians mainly by the biased reports of their enemies. Although the Phoenicians themselves reportedly had a rich literature, it was totally lost in antiquity.”

What about the writings of the ancient Egyptians? The hieroglyphics they carved or painted on temple walls and elsewhere are well-known. The Egyptians are also famous for developing papyrus as a writing material. However, regarding Egyptian records written on papyrus, Egyptologist K. A. Kitchen says: “It has been estimated that some 99 percent of all papyri written from circa 3000 down to the advent of Greco-Roman times have perished completely.”

What about Roman records that were written on papyrus? Consider this example. According to the book Roman Military Records on Papyrus, Roman soldiers were apparently paid three times a year, and a record of the pay was made on papyrus pay vouchers. It is estimated that during the 300 years from Augustus (27 B.C.E.–14 C.E.) to Diocletian (284-305 C.E), there were 225,000,000 individual pay records. How many have survived? Only two have been found that are legible.

Why have so few ancient documents written on papyrus survived? Perishable materials, such as papyrus and another common writing material, leather, decay quickly in damp climates. The Anchor Bible Dictionary says: “Because of the climate, papyrus documents from this period [the first millennium B.C.E.] are likely to be preserved only if they are in a dry desert and in a cave or shelter.”

What About the Bible Texts?

The original Bible books were evidently written on material as fragile as that used by the Phoenicians, Egyptians, and Romans. Why, then, did the material contained in the Bible survive to become the world’s most published book? Professor James L. Kugel provides one reason. He says that the original writings were copied “many, many times even within the biblical period itself.”

How do modern translations of the Bible compare with ancient manuscripts? Professor Julio Trebolle Barrera, a member of the team of experts charged with studying and publishing the ancient manuscripts known as the Dead Sea Scrolls, says: “The transmission of the text of the Hebrew Bible is of extraordinary exactitude, without parallel in Greek and Latin classical literature.” Respected Bible scholar F. F. Bruce says: “The evidence for our New Testament writings is ever so much greater than the evidence for many writings of classical authors, the authenticity of which no one dreams of questioning.” He continues: “If the New Testament were a collection of secular writings, their authenticity would generally be regarded as beyond all doubt.” Certainly, the Bible is a remarkable book. Do you make time to read it each day.

On Jesus's resurrection body.

After Jesus’ Resurrection, Was His Body Flesh or Spirit?

The Bible’s answer

The Bible says that Jesus “was put to death in the flesh but made alive [resurrected] in the spirit.”—1 Peter 3:18; Acts 13:34; 1 Corinthians 15:45;2 Corinthians 5:16.

Jesus’ own words showed that he would not be resurrected with his flesh-and-blood body. He said that he would give his “flesh in behalf of the life of the world,” as a ransom for mankind. (John 6:51; Matthew 20:28) If he had taken back his flesh when he was resurrected, he would have canceled that ransom sacrifice. This could not have happened, though, for the Bible says that he sacrificed his flesh and blood “once for all time.”—Hebrews 9:11, 12.

If Jesus was raised up with a spirit body, how could his disciples see him?

• Spirit creatures can take on human form. For example, angels who did this in the past even ate and drank with humans. (Genesis 18:1-8; 19:1-3) However, they still were spirit creatures and could leave the physical realm.—Judges 13:15-21.
• After his resurrection, Jesus also assumed human form temporarily, just as angels had previously done. As a spirit creature, though, he was able to appear and disappear suddenly. (Luke 24:31; John 20:19, 26) The fleshly bodies that he materialized were not identical from one appearance to the next. Thus, even Jesus’ close friends recognized him only by what he said or did.—Luke 24:30, 31, 35; John 20:14-16; 21:6, 7.
• When Jesus appeared to the apostle Thomas, he took on a body with wound marks. He did this to bolster Thomas’ faith, since Thomas doubted that Jesus had been raised up.—John 20:24-29.

Decanonising Science II

Should we have faith in science? Part II: peer-reviewed science papers
Thursday, February 26, 2015 - 12:51

Kirk Durston



The primary way scientific discoveries and advances are disseminated is through peer-reviewed papers published in scientific journals. The first step is to submit a paper to a journal. Those that survive preliminary filtering by the editor are sent out to be reviewed by qualified scientists in the field. On the basis of the reviewers’ recommendations, the paper is accepted or rejected. Only a fraction of papers submitted for publication make it through this peer-review process and are published.

One would hope that such a process would justify a high level of confidence in scientific publications, but recent findings suggest that our faith in peer-reviewed publications in mainstream journals of science may be on somewhat shaky ground.

The journal Nature, in a paper calling for increased standards in pre-clinical research, revealed that out of 53 papers presenting ‘landmark’ published findings in the field of haematology and oncology, only 6 could be confirmed by subsequent laboratory teams. For the 89% of papers that failed to have their results reproduced, it was found that blind control group analyses was inadequate or data had been selected to support the hypothesis and other data set aside.

Worse still, some of the papers that could not be experimentally reproduced, launched ‘an entire field, with hundreds of secondary publications that expanded on elements of the original observation, but did not actually seek to confirm or falsify its fundamental basis’.

Hundreds of other peer-reviewed, published science papers based on faulty initial papers!

Nature reported in October 2011 that although the number of submissions had increased by 44% over the past ten years, the number of retractions had increased by roughly 900%.

Austin Hughes, in a paper published in the Proceedings of the National Academy of Sciences, focusing on the origin of adaptive phenotypes laments, ‘Thousands of papers are published every year claiming evidence of adaptive evolution on the basis of computational analyses alone, with no evidence whatsoever regarding the phenotypic effects of allegedly adaptive mutations.’ He concludes that ‘This vast outpouring of pseudo-Darwinian hype has been genuinely harmful to the credibility of evolutionary biology as a science.’ Jerry Fodor and Massimo Piattelli-Palmarini write in New Scientist,

"Much of the vast neo-Darwinian literature is distressingly uncritical. The possibility that anything is seriously amiss with Darwin’s account of evolution is hardly considered. … The methodological skepticism that characterizes most areas of scientific discourse seems strikingly absent when Darwinism is the topic."

How can we distinguish the good papers from the poor? This can be very difficult without actually attempting to reproduce their findings. Short of that, apply the same critical thinking skills and healthy skepticism to scientific papers that you do for political, historical or religious claims. 21st century science can often be heavily influenced by poor experimental practices, unproven computational models, political agendas, competition for funding, and scientism (atheism dressed up as science). When going over a paper ask questions like, how large was the data set? What sort of statistical analysis was performed? Are there other papers that independently support or disconfirm these findings? What is not being discussed? One thing for sure, don’t accept something simply because ‘hundreds’ or even ‘thousands’ of papers say so, especially if Darwinian evolution is the topic. Practice critical thinking with the question in the back of your mind, 'Is this one of those papers that will be retracted?'.

Read Part III

Further reading:

http://www.nature.com/nature/journal/v483/n7391/full/483531a.html#t1

http://www.nature.com/news/publishing-the-peer-review-scam-1.16400

http://www.nytimes.com/2012/04/17/science/rise-in-scientific-journal-retractions-prompts-calls-for-reform.html?ref=science

http://dingo.sbs.arizona.edu/~massimo/publications/PDF/JF_MPP_darwinisms...


http://www.nytimes.com/2015/06/16/science/retractions-coming-out-from-under-science-rug.html?

Decanonising Science

Science, Now Under Scrutiny Itself
By BENEDICT CAREYJUNE 15, 2015

The crimes and misdemeanors of science used to be handled mostly in-house, with a private word at the faculty club, barbed questions at a conference, maybe a quiet dismissal. On the rare occasion when a journal publicly retracted a study, it typically did so in a cryptic footnote. Few were the wiser; many retracted studies have been cited as legitimate evidence by others years after the fact.


Retracted Scientific Studies: A Growing List

“Until recently it was unusual for us to report on studies that were not yet retracted,” said Dr. Ivan Oransky, an editor of the blog Retraction Watch, the first news media outlet to report that the study had been challenged. But new technology and a push for transparency from younger scientists have changed that, he said. “We have more tips than we can handle.”

The case has played out against an increase in retractions that has alarmed many journal editors and authors. Scientists in fields as diverse as neurobiology, anesthesia and economics are debating how to reduce misconduct, without creating a police-state mentality that undermines creativity and collaboration.

“It’s an extraordinary time,” said Brian Nosek, a professor of psychology at the University of Virginia, and a founder of the Center for Open Science, which provides a free service through which labs can share data and protocols. “We are now seeing a number of efforts to push for data repositories to facilitate direct replications of findings.”

But that push is not universally welcomed. Some senior scientists have argued that replication often wastes resources. “Isn’t reproducibility the bedrock of science? Yes, up to a point,” the cancer biologist Mina Bissell wrote in a widely circulated blog post. “But it is sometimes much easier not to replicate than to replicate studies,” especially when the group trying to replicate does not have the specialized knowledge or skill to do so.

The experience of Retraction Watch provides a rough guide to where this debate is going and why. Dr. Oransky, who has a medical degree from New York University, and Adam Marcus, both science journalists, discovered a mutual interest in retractions about five years ago and founded the blog as a side project. They had, and still have, day jobs: Mr. Marcus, 46, is the managing editor of Gastroenterology & Endoscopy News, and Dr. Oransky, 42, is the editorial director of MedPage Today (he will take a position as distinguished writer in residence at N.Y.U. later this year).

In its first year, the blog broke a couple of retraction stories that hit the mainstream news media — including a case involving data faked by an anesthesiologist who later served time for health care fraud. The site now has about 150,000 unique visitors a month, about half from outside the United States.

Dr. Oransky and Mr. Marcus are partisans who editorialize sharply against poor oversight and vague retraction notices. But their focus on evidence over accusations distinguishes them from watchdog forerunners who sometimes came off as ad hominem cranks. Last year, their site won a $400,000 grant from the John D. and Catherine T. MacArthur Foundation, to build out their database, and they plan to work with Dr. Nosek to manage the data side.

Their data already tell a story.

The blog has charted a 20 to 25 percent increase in retractions across some 10,000 medical and science journals in the past five years: 500 to 600 a year today from 400 in 2010. (The number in 2001 was 40, according to previous research.) The primary causes of this surge are far from clear. The number of papers published is higher than ever, and journals have proliferated, Dr. Oransky and other experts said. New tools for detecting misconduct, like plagiarism-sifting software, are widely available, so there’s reason to suspect that the surge is a simple product of better detection and larger volume.



The increasing challenges to the veracity of scientists’ work gained widespread attention recently when a study by Michael LaCour on the effect of political canvassing on opinions of same-sex marriage was questioned and ultimately retracted.
Still, the pressure to publish attention-grabbing findings is stronger than ever, these experts said — and so is the ability to “borrow” and digitally massage data. Retraction Watch’s records suggest that about a third of retractions are because of errors, like tainted samples or mistakes in statistics, and about two-thirds are because of misconduct or suspicions of misconduct.

The most common reason for retraction because of misconduct is image manipulation, usually of figures or diagrams, a form of deliberate data massaging or, in some cases, straight plagiarism. In their dissection of the LaCour-Green paper, the two graduate students — David Broockman, now an assistant professor at Stanford, and Joshua Kalla, at California-Berkeley — found that a central figure in Mr. LaCour’s analysis looked nearly identical to one from another study. This and other concerns led Dr. Green, who had not seen any original data, to request a retraction. (Mr. LaCour has denied borrowing anything.)

Data massaging can take many forms. It can mean simply excluding “outliers” — unusually high or low data points — from an analysis to generate findings that more strongly support the hypothesis. It also includes moving the goal posts: that is, mining the data for results first, and then writing the paper as if the experiment had been an attempt to find just those effects. “You have exploratory findings, and you’re pitching them as ‘I knew this all along,’ as confirmatory,” Dr. Nosek said.

The second leading cause is plagiarizing text, followed by republishing — presenting the same results in two or more journals.

The fourth category is faked data. No one knows the rate of fraud with any certainty. In a 2011 survey of more than 2,000 psychologists, about 1 percent admitted to falsifying data. Other studies have estimated a rate of about 2 percent. Yet one offender can do a lot of damage. The Dutch social psychologist Diederik Stapel published dozens of studies in major journals for nearly a decade based on faked data, investigators at the universities where he had worked concluded in 2011. Suspicions were first raised by two of his graduate students.

“If I’m a scientist and I fabricate data and put that online, others are going to assume this is accurate data,” said John Budd, a professor at the University of Missouri and an author of one of the first exhaustive analyses of retractions, in 1999. “There’s no way to know” without inside information.

Here, too, Retraction Watch provides a possible solution. Many of the egregious cases that it posts come from tips. The tipsters are a growing cadre of scientists, specialized journalists and other experts who share the blog’s mission — and are usually not insiders working directly with a suspected offender. One of the blog’s most effective allies has been Dr. Steven Shafer, the current editor of the journal Anesthesia & Analgesia who is now at Stanford, whose aggressiveness in re-examining published papers has led to scores of retractions. The field of anesthesia is a leader in retractions, largely because of Dr. Shafer’s efforts, Mr. Marcus and Dr. Oransky said. (Psychology is another leader, largely because of Dr. Stapel.)

Other cases emerge from issues raised at post-publication sites, where scientists dig into papers, sometimes anonymously. Dr. Broockman, one of the two who challenged the LaCour-Green paper, had first made public some of his suspicions anonymously on a message board called poliscirumors.com. Mr. Marcus said Retraction Watch closely followed a similar site, PubPeer.com. “When it first popped up, a lot of people assumed it would be an ax-grinding place,” he said. “But while some contributors have overstepped, I think it has had a positive impact on the literature.”

What these various tipsters, anonymous post-reviewers and whistle-blowers have in common is a nose for data that looks too good to be true, he said. Sites like Retraction Watch and PubPeer give them a place to discuss their concerns and flag fishy-looking data.

These, along with data repositories like Dr. Nosek’s, may render moot the debate over how to exhaustively replicate findings. That burden is likely to be eased by the community of bad-science bloodhounds who have more and more material to work with when they pick up a foul scent.

“At this point, we see ourselves as part of an ecosystem that is advocating for increased transparency,” Dr. Oransky said. “And that ecosystem is growing.”

Darwinism vs. the real world IV

Computing the "Best Case" Probability of Proteins from Actual Data, and Falsifying a Prediction of Darwinism

Kirk Durston July 28, 2015 4:52 PM | 

 

 

Biological life requires thousands of different protein families, about 70 percent of which are "globular" proteins, with a three-dimensional shape that is unique to each family of proteins. An illustration is shown in the picture at the top of this post. This 3D shape is necessary for a particular biological function and is determined by the sequence of the different amino acids that make up that protein. In other words, it is not biology that determines the shape, but physics. Sequences that produce stable, functional 3D structures are so rare that scientists today do not attempt to find them using random sequence libraries. Instead, they use information they have obtained from reverse-engineering biological proteins to intelligently design artificial proteins.
Indeed, our 21st-century supercomputers are not powerful enough to crunch the variables and locate novel 3D structures. Nonetheless, a foundational prediction of neo-Darwinian theory is that a ploddingly slow evolutionary process consisting of genetic drift, mutations, insertions, and deletions must be able to "find" not just one, but thousands of sequences pre-determined by physics that will have different stable, functional 3D structures. So how does this falsifiable prediction hold up when tested against real data? As ought to be the case in science, I have made my program available so that you can run your own data and verify for yourself the kinds of probabilities these protein families represent.
This program can compute an upper limit for the probability of obtaining a protein family from a wealth of actual data contained in the Pfam database. The first step computes the lower limit for the functional complexity or functional information required to code for a particular protein family, using a method published by Durston et al. This value for I(Ex) can then be plugged into an equation published by Hazen et al. in order to solve the probability M(Ex)/N of "finding" a functional sequence in a single trial.
I downloaded 3,751 aligned sequences for the Ribosomal S7 domain, part of a universal protein essential for all life. When the data was run through the program, it revealed that the lower limit for the amount of functional information required to code for this domain is 332 Fits (Functional Bits). The extreme upper limit for the number of sequences that might be functional for this domain is around 10^92. In a single trial, the probability of obtaining a sequence that would be functional for the Ribosomal S7 domain is 1 chance in 10^100 ... and this is only for a 148 amino acid structural domain, much smaller than an average protein.
For another example, I downloaded 4,986 aligned sequences for the ABC-3 family of proteins and ran it through the program. The results indicate that the probability of obtaining, in a single trial, a functional ABC-3 sequence is around 1 chance in 10^128. This method ignores pairwise and higher order relationships within the sequence that would vastly limit the number of functional sequences by many orders of magnitude, reducing the probability even further by many orders of magnitude -- so this gives us a best-case estimate.
What are the implications of these results, obtained from actual data, for the fundamental prediction of neo-Darwinian theory mentioned above? If we assume 10^30 life forms with a fast replication rate of 30 minutes and a huge genome with a very high mutation rate over a period of 10 billion years, an extreme upper limit for the total number of mutations for all of life's history would be around 10^43. Unfortunately, a protein domain such as Ribosomal S7 would require a minimum average of 10^100 trials, about 10^57 trials more than the entire theoretical history of life could provide -- and this is only for one domain. Forget about "finding" an average sized protein, not to mention thousands.
As we all know from probabilities, you can get lucky once, but not thousands of times. This definitively falsifies the fundamental prediction of Darwinian theory that evolutionary processes can "find" functional protein families. A theory that has an essential prediction thoroughly falsified by the data should have no place in science.
Could natural selection come to the rescue? As we know from genetic algorithms, an evolutionary "search" will only work for hill-climbing problems, not for "needle in a haystack" problems. There are small proteins that require such low levels of functional information to perform simple binding tasks that they form a nice hill-climbing problem that can be easily located in a search. This is not the case, however, for the vast majority of protein families. As real data shows, the probability of finding a functional sequence for one average protein family is so low, there is virtually zero chance of obtaining it anywhere in this universe over its entire history -- never mind finding thousands of protein families.
What are the implications for intelligent design science? A testable, falsifiable hypothesis of intelligent design can be stated as follows:

A unique attribute of an intelligent mind is the ability to produce effects requiring a statistically significant level of functional information.

Given the above testable hypothesis, if we observe an effect that requires a statistically significant level of functional information, we can conclude there is an intelligent mind behind the effect. The average protein family requires a statistically significant level of functional, or prescriptive, information. Therefore, the genomes of life have the fingerprints of an intelligent source all over them.

 

A line in the sand XVIII

Tom Wolfe calls out the Darwinian Gestapo

In The New Yorker, Tom Wolfe Compares Persecution of Intelligent Design Advocates to the "Spanish Inquisition"

David Klinghoffer July 28, 2015 10:44 AM

How did we miss this? The comment is brief but pungent to say the least.Interviewed by The New Yorker earlier this year, the great novelist and journalist Tom Wolfe acknowledged that he's writing a book about evolution -- actually, "a history of the theory of evolution from the nineteenth century to the present." No indication of what his overall thesis might be, but he "invokes the Spanish Inquisition when discussing how academics have cast out proponents of intelligent design for 'not believing in evolution the right way.'"

The metaphor is apt, since the Spanish Inquisition was all about rooting out people who held the wrong beliefs in secret. The expulsion of the Jews from Spain in 1492 had already pushed out anyone openly professing Judaism. It was converted Jews, claiming to be loyal to the dominant faith, who were the focus of the inquisitors.

No metaphor is an exact equation between two things -- it wouldn't be a metaphor if it were. But uncovering and punishing those with secret sympathies for ID is indeed a priority for zealous evolutionists, who insist everyone needs to believe in evolution in "the right way." The anxiety this provokes, especially in academia, is something we deal with all the time behind the scenes.

I don't have any idea what view Wolfe takes on ID other than his obviously deploring such intimidation. But we noted a while back that he was seen in the audience when Eric Metaxas interviewed Stephen Meyer about Darwin's Doubt at the Union League Club. It was already known then that Wolfe was writing a book called The Human Beast.

His attitudes are now slowly coming into focus, demonstrating once again the Thomas Nagel Principle, aka the Tom Stoppard Rule: when you reach a certain level of fame and accomplishment, if you are independent-minded, you can say whatever you want without fear. Which in turn gives courage to others lacking your bullet-proof armor. This, I predict, is going to be good.