Using local sinusoidal features in a standard statistical testing framework, we propose a definition of local resolution for 3D density maps. The resulting algorithm has no free parameters and may be extended to other imaging modalities. Evaluating the local resolution of single particle reconstructions and sub-tomogram averages shows variable resolution across a 4 to 40Å range.

Cigarette smoking is a major public health danger. Women and men smoke for different reasons and cessation treatments, such as the nicotine patch, are preferentially beneficial to men. The biological substrates of these sex differences are unknown. Earlier PET studies reported conflicting findings but were each hampered by experimental and/or analytical limitations. Our new image analysis technique, lp-ntPET (Normandin et al., 2012; Morris et al., 2013; Kim et al., 2014), has been optimized for capturing brief (lasting only minutes) and highly localized dopaminergic events in dynamic PET data. We coupled our analysis technique with high-resolution brain scanning and high-frequency motion correction to create the optimal experiment for capturing and characterizing the effects of smoking on the mesolimbic dopamine system in humans. Our main finding is that male smokers smoking in the PET scanner activate dopamine in the right ventral striatum during smoking but female smokers do not. This finding-men activating more ventrally than women-is consistent with the established notion that men smoke for the reinforcing drug effect of cigarettes whereas women smoke for other reasons, such as mood regulation and cue reactivity. lp-ntPET analysis produces a novel multidimensional endpoint: voxel-level temporal patterns of neurotransmitter release ("DA movies") in individual subjects. By examining these endpoints quantitatively, we demonstrate that the timing of dopaminergic responses to cigarette smoking differs between men and women. Men respond consistently and rapidly in the ventral striatum whereas women respond faster in a discrete subregion of the dorsal putamen.

Information contained in medical images differs considerably from that residing in alphanumeric format. The difference can be attributed to four characteristics: (1) the semantics of medical knowledge extractable from images is imprecise; (2) image information contains form and spatial data, which are not expressible in conventional language; (3) a large part of image information is geometric; (4) diagnostic inferences derived from images rest on an incomplete, continuously evolving model of normality. This paper explores the differentiating characteristics of text versus images and their impact on design of a medical image database intended to allow content-based indexing and retrieval. One strategy for implementing medical image databases is presented, which employs object-oriented iconic queries, semantics by association with prototypes, and a generic schema.

Structural heterogeneity of particles can be investigated by their three-dimensional principal components. This paper addresses the question of whether, and with what algorithm, the three-dimensional principal components can be directly recovered from cryo-EM images. The first part of the paper extends the Fourier slice theorem to covariance functions showing that the three-dimensional covariance, and hence the principal components, of a heterogeneous particle can indeed be recovered from two-dimensional cryo-EM images. The second part of the paper proposes a practical algorithm for reconstructing the principal components directly from cryo-EM images without the intermediate step of calculating covariances. This algorithm is based on maximizing the (posterior) likelihood using the Expectation-Maximization algorithm. The last part of the paper applies this algorithm to simulated data and to two real cryo-EM data sets: a data set of the 70S ribosome with and without Elongation Factor-G (EF-G), and a data set of the inluenza virus RNA dependent RNA Polymerase (RdRP). The first principal component of the 70S ribosome data set reveals the expected conformational changes of the ribosome as the EF-G binds and unbinds. The first principal component of the RdRP data set reveals a conformational change in the two dimers of the RdRP.

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