Digital clubbing, a classic medical sign of chronic hypoxemia, first described by Hippocrates in patients with empyema, has now been explained on the molecular level. A group of clinicians at Leeds University realized that a genetic mutation in one of the genes responsible for the breakdown of PGE2 prostaglandin results in increased clubbing.
And the rest is history:

Prof Bonthron, Dr Chris Bennett of the Yorkshire Regional Genetics Service and their colleagues studied a group of patients suffering from inherited primary hypertrophic osteoarthropathy (PHO), a genetic disorder in which the finger clubbing is accompanied by painful joint enlargement and a thickening of the bone.
Their findings implicated a fatty compound called PGE2, which is produced naturally by the body to mediate the effects of internal inflammation. Crucially, once it has done its work, PGE2 is broken down by an enzyme 15-HPGD, produced in the lungs. The patients followed by the Leeds study were found to have a genetic mutation which prevented the production of 15-HPGD, resulting in up to ten times as much of the PGE2 in their systems.
"If you don’t have this enzyme the PGE2 isn’t broken down normally and simply builds up," said Bonthron, whose findings are published online this week in Nature Genetics.
In lung cancer patients, it is most likely overproduction of PGE2 by the tumour that causes the clubbing. In congenital heart disease, blood bypasses the lungs, where PGE2 is normally broken down by 15-HPGD.
The researchers have suggested that a straightforward urine test for levels of PGE2 may be a useful first step in the diagnosis of individuals with unexplained clubbing, and to understanding whether it is the symptom of something far more serious. The results also suggest that existing drugs such as aspirin, which are already used to prevent PGE2 production, may be effective in reducing the painful symptoms of finger clubbing.
It has taken 2,000 years to make the connection, but Bonthron adds: "Actually, when you look back, it’s rather obvious. When we found this gene, everything else fell neatly into place – it was like a smack on the forehead."

Press release: Leeds medics solve an ancient riddle — and offer new tool for diagnosis…
Abstract: Mutations in 15-hydroxyprostaglandin dehydrogenase cause primary hypertrophic osteoarthropathy Nature Genetics 40, 789 – 793 (2008)

Carnegie Mellon scientists have successfully performed the first rudimentary mind reading using functional magnetic resonance imaging, essentially identifying one of a number of words (“airplane” as opposed to “celery” in the image scan to the right) that subjects inside the machine were thinking about.
From the Carnegie Mellon press release:

In the study, nine subjects underwent fMRI scans while concentrating on 60 stimulus nouns – five words in each of 12 semantic categories including animals, body parts, buildings, clothing, insects, vehicles and vegetables.
To construct their computational model, the researchers used machine learning techniques to analyze the nouns in a trillion-word text corpus that reflects typical English word usage. For each noun, they calculated how frequently it co-occurs in the text with each of 25 verbs associated with sensory-motor functions, including see, hear, listen, taste, smell, eat, push, drive and lift. Computational linguists routinely do this statistical analysis as a means of characterizing the use of words.
These 25 verbs appear to be basic building blocks the brain uses for representing meaning, Mitchell said.
By using this statistical information to analyze the fMRI activation patterns gathered for each of the 60 stimulus nouns, they were able to determine how each co-occurrence with one of the 25 verbs affected the activation of each voxel, or 3-D volume element, within the fMRI brain scans.
To predict the fMRI activation pattern for any concrete noun within the text corpus, the computational model determines the noun’s co-occurrences within the text with the 25 verbs and builds an activation map based on how those co-occurrences affect each voxel.
In tests, a separate computational model was trained for each of the nine research subjects using 58 of the 60 stimulus nouns and their associated activation patterns. The model was then used to predict the activation patterns for the remaining two nouns. For the nine participants, the model had a mean accuracy of 77 percent in matching the predicted activation patterns to the ones observed in the participants’ brains.
The model proved capable of predicting activation patterns even in semantic areas for which it was untrained. In tests, the model was retrained with words from all but two of the 12 semantic categories from which the 60 words were drawn, and then tested with stimulus nouns from the omitted categories. If the categories of vehicles and vegetables were omitted, for instance, the model would be tested with words such as airplane and celery. In these cases, the mean accuracy of the model’s prediction dropped to 70 percent, but was still well above chance (50 percent).

Press release: Carnegie Mellon Computer Model Reveals How Brain Represents Meaning
(hat tip: Drudge Report)

The Chronicle of Higher Education profiles the use of image manipulation in peer reviewed journals, as Photoshop use is becoming common, and technology to detect its use is being developed.

Ten to 20 of the articles accepted by The Journal of Clinical Investigation each year show some evidence of tampering, and about five to 10 of those papers warrant a thorough investigation, says Ms. Neill. (The journal publishes about 300 to 350 articles per year.)
In the case of Ms. Roovers, editors notified the federal Office of Research Integrity, which polices government-financed science projects. The office concluded that the images had been improperly manipulated, as had images the researcher had produced for papers published in three other journals. That finding led two of those journals to retract papers that Ms. Roovers had co-authored, papers that had been cited by other researchers dozens of times.

Much more info on the state of things from the Chronicle of Higher Education…