ThorImageOCTImageJExport0-4.avi

Real-time SDOCT imaging video of the combined system showing the cross-sectional SDOCT image of the human retinal layers and the FFOCT reference mirror. By translating the whole system with respect to the human eye, the SDOCT image of the reference mirror is overlapped with different retinal layers, achieving a real-time optical path lengths matching for FFOCT retinal imaging

Additional file 1 of Efficient sequential and parallel algorithms for finding edit distance based motifs

Expected number of spurious motifs. This file gives the expression for the expected number of spurious (l,d)-motifs in n random strings of length m from the alphabet ÎŁ. (PDF 143 kb

Table_1_PGAM5: A necroptosis gene associated with poor tumor prognosis that promotes cutaneous melanoma progression.pdf

Cutaneous melanoma is the deadliest type of skin cancer, and its highly aggressive and metastatic nature leads to an extremely poor prognosis. Necrotizing apoptosis, a specific form of programmed cell death, has been extensively studied in recent years. In this study, we analyzed the relationship between necroptosis-related functional genes and cutaneous melanoma in order to identify the biomarkers associated with the prognosis and progression of cutaneous melanoma. Cutaneous melanoma samples were classified into three subgroups on the basis of a necroptosis gene set. These subgroups were subjected to a prognostic survival analysis, and the greatest differences were observed between subgroups C1 and C3. Between these subgroups, 28 necrotizing apoptosis-related genes were significantly differently expressed. Among these, 16 necrotizing apoptosis-related genes were associated with cutaneous melanoma prognosis. Downscaling analysis and prognostic modeling using the least absolute shrinkage and selection operator analysis yielded nine pivotal genes and revealed phosphoglycerate translocase 5 (PGAM5) as the key gene. Then, qRT-PCR was used to verify the expression level of PGAM5. The results showed that PGAM5 was highly expressed in cutaneous melanoma tissues. In this study, a bioinformatics approach was used to identify PGAM5, a biomarker whose high expression is associated with the poor prognosis of cutaneous melanoma.</p

Phantom images with the dotted rectangles as imaging region-of-interest.

<p>(a) The NEMA-IQ phantom is about cm in size, including four hot lesions (10 mm, 13 mm, 17 mm and 22 mm in diameter) and two cold lesions (28 mm and 37 mm in diameter). The region-of-interest size is cm. (b) The Zubal abdomen phantom is about cm in size. The region-of-interest size is cm.</p

Sampled intensity profiles of the reconstructed image shown in Figure 5.

<p>The sample lines in (a) show the locations of the profiles.</p

Sampled intensity profiles for NEMA-IQ phantom obtained from TOF-PET data with different TRs.

<p>The profiles were obtained from the reconstructed images shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0072109#pone-0072109-g007" target="_blank">Figure 7</a>.</p

Reconstructed images of NEMA-IQ phantom obtained from TOF-PET data with different timing resolutions.

<p>Note that only the structures inside the ROI are displayed.</p

Event discrimination in data acquisition.

<p> indicates the arrival time difference of two photons, is the speed of light, is the distance between the annihilation position and the midpoint of line-of-response.</p

Measurable time differences distribution in conventional (a) and region-of-interest imaging (b).

<p>The distribution was assumed as a Gaussian function with full width at half maximum determined by the system timing resolution.</p

Contrast recovery coefficients versus iteration number for the TOF-PET data with different timing resolutions.

<p>To avoid misleading impacts introduced by artifacts and distortions on contrast recovery coefficient values, only image results for 100–400 ps full width at half maximum TOF-PET data were analyzed here.</p