Blind Source Separation of Hemodynamics from Magnetic Resonance Perfusion Brain Images Using Independent Factor Analysis

Perfusion magnetic resonance brain imaging induces temporal signal changes on brain tissues, manifesting distinct blood-supply patterns for the profound analysis of cerebral hemodynamics. We employed independent factor analysis to blindly separate such dynamic images into different maps, that is, artery, gray matter, white matter, vein and sinus, and choroid plexus, in conjunction with corresponding signal-time curves. The averaged signal-time curve on the segmented arterial area was further used to calculate the relative cerebral blood volume (rCBV), relative cerebral blood flow (rCBF), and mean transit time (MTT). The averaged ratios for rCBV, rCBF, and MTT between gray and white matters for normal subjects were congruent with those in the literature

Regenerating Arbitrary Video Sequences with Distillation Path-Finding

If the video has long been mentioned as a widespread visualization form, the animation sequence in the video is mentioned as storytelling for people. Producing an animation requires intensive human labor from skilled professional artists to obtain plausible animation in both content and motion direction, incredibly for animations with complex content, multiple moving objects, and dense movement. This paper presents an interactive framework to generate new sequences according to the users' preference on the starting frame. The critical contrast of our approach versus prior work and existing commercial applications is that novel sequences with arbitrary starting frame are produced by our system with a consistent degree in both content and motion direction. To achieve this effectively, we first learn the feature correlation on the frameset of the given video through a proposed network called RSFNet. Then, we develop a novel path-finding algorithm, SDPF, which formulates the knowledge of motion directions of the source video to estimate the smooth and plausible sequences. The extensive experiments show that our framework can produce new animations on the cartoon and natural scenes and advance prior works and commercial applications to enable users to obtain more predictable results.Comment: This paper has been accepted for publication on IEEE Transactions on Visualization and Computer Graphics (TVCG), January 2023. Project website: http://graphics.csie.ncku.edu.tw/SDP

Synergistic effect of phosphodiesterase 4 inhibitor and serum on migration of endotoxin-stimulated macrophages.

Macrophage migration is an essential step in host defense against infection and wound healing. Elevation of cAMP by inhibiting phosphodiesterase 4 (PDE4), enzymes that specifically degrade cAMP, is known to suppress various inflammatory responses in activated macrophages, but the role of PDE4 in macrophage migration is poorly understood. Here we show that the migration of Raw 264.7 macrophages stimulated with LPS was markedly and dose-dependently induced by the PDE4 inhibitor rolipram as assessed by scratch wound healing assay. Additionally, this response required the involvement of serum in the culture medium as serum starvation abrogated the effect. Further analysis revealed that rolipram and serum exhibited synergistic effect on the migration, and the influence of serum was independent of PDE4 mRNA expression in LPS-stimulated macrophages. Moreover, the enhanced migration by rolipram was mediated by activating cAMP/exchange proteins directly activated by cAMP (Epac) signaling, presumably via interaction with LPS/TLR4 signaling with the participation of unknown serum components. These results suggest that PDE4 inhibitors, together with serum components, may serve as positive regulators of macrophage recruitment for more efficient pathogen clearance and wound repair