Radiocarbon dating is the most widely used dating technique in the world. Recent advances in Accelerator Mass Spectrometry (AMS) and sample preparation techniques have reduced the sample-size requirements by a factor of 1000 and decreased the measurement time from weeks to minutes. Today, it is estimated that more than 90 percent of all measurements made on accelerator mass spectrometers are for radiocarbon age dates. The production of 14 C in the atmosphere varies through time due to changes in the Earth's geomagnetic field intensity and in its concentration, which is regulated by the carbon cycle. As a result of these two variables, a radiocarbon age is not equivalent to a calendar age. Four decades of joint research by the dendrochronology and radiocarbon communities have produced a radiocarbon calibration data set of remarkable precision and accuracy extending from the present to approximately 12,000 calendar years before present. This paper presents high precision paired 230 Th/ 234 U/ 238 U and 14 C age determinations on pristine coral samples that enable us to extend the radiocarbon calibration curve from 12,000 to 50,000 years before present. We developed a statistical model to properly estimate sample age conversion from radiocarbon years to calendar years, taking full account of combined errors in input ages and calibration uncertainties. Our radiocarbon calibration program is publicly accessible at: http://www.radiocarbon.LDEO.columbia.edu/ along with full documentation of the samples, data, and our statistical calibration model. r

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BackgroundAutomatic quantification of neuronal morphology from images of fluorescence microscopy plays an increasingly important role in high-content screenings. However, there exist very few freeware tools and methods which provide automatic neuronal morphology quantification for pharmacological discovery.ResultsThis study proposes an effective quantification method, called NeurphologyJ, capable of automatically quantifying neuronal morphologies such as soma number and size, neurite length, and neurite branching complexity (which is highly related to the numbers of attachment points and ending points). NeurphologyJ is implemented as a plugin to ImageJ, an open-source Java-based image processing and analysis platform. The high performance of NeurphologyJ arises mainly from an elegant image enhancement method. Consequently, some morphology operations of image processing can be efficiently applied. We evaluated NeurphologyJ by comparing it with both the computer-aided manual tracing method NeuronJ and an existing ImageJ-based plugin method NeuriteTracer. Our results reveal that NeurphologyJ is comparable to NeuronJ, that the coefficient correlation between the estimated neurite lengths is as high as 0.992. NeurphologyJ can accurately measure neurite length, soma number, neurite attachment points, and neurite ending points from a single image. Furthermore, the quantification result of nocodazole perturbation is consistent with its known inhibitory effect on neurite outgrowth. We were also able to calculate the IC50 of nocodazole using NeurphologyJ. This reveals that NeurphologyJ is effective enough to be utilized in applications of pharmacological discoveries.ConclusionsThis study proposes an automatic and fast neuronal quantification method NeurphologyJ. The ImageJ plugin with supports of batch processing is easily customized for dealing with high-content screening applications. The source codes of NeurphologyJ (interactive and high-throughput versions) and the images used for testing are freely available (see Availability).