Deep learning data augmentation for Raman spectroscopy cancer tissue classification.

Recently, Raman Spectroscopy (RS) was demonstrated to be a non-destructive way of cancer diagnosis, due to the uniqueness of RS measurements in revealing molecular biochemical changes between cancerous vs. normal tissues and cells. In order to design computational approaches for cancer detection, the quality and quantity of tissue samples for RS are important for accurate prediction. In reality, however, obtaining skin cancer samples is difficult and expensive due to privacy and other constraints. With a small number of samples, the training of the classifier is difficult, and often results in overfitting. Therefore, it is important to have more samples to better train classifiers for accurate cancer tissue classification. To overcome these limitations, this paper presents a novel generative adversarial network based skin cancer tissue classification framework. Specifically, we design a data augmentation module that employs a Generative Adversarial Network (GAN) to generate synthetic RS data resembling the training data classes. The original tissue samples and the generated data are concatenated to train classification modules. Experiments on real-world RS data demonstrate that (1) data augmentation can help improve skin cancer tissue classification accuracy, and (2) generative adversarial network can be used to generate reliable synthetic Raman spectroscopic data

Single-shot two-dimensional full-range optical coherence tomography achieved by dispersion control

We present a full-range Fourier-domain optical coherence tomography (OCT) system that is capable of acquiring two-dimensional images of living tissue in a single shot. By using line illumination of the sample in combination with a two-dimensional imaging spectrometer, 1040 depth scans are performed simultaneously on a sub-millisecond timescale. Furthermore, we demonstrate an easy and flexible real-time single-shot technique for full-range (complex-conjugate cancelled) OCT imaging that is compatible with both two-dimensional as well as ultrahighresolution OCT. By implementing a dispersion imbalance between reference and sample arms of the interferometer, we eliminate the complex-conjugate signal through numerical dispersion compensation, effectively increasing the useful depth range by a factor of two. The system allows us to record 6.7 × 3.2 mm images at 5 μm depth resolution in 0.2 ms. Data postprocessing requires only 4 s. We demonstrate the capability of our system by imaging the anterior chamber of a mouse eye in vitro, as well as human skin in vivo. © 2009 Optical Society of America

Alternative Splicing Events Are a Late Feature of Pathology in a Mouse Model of Spinal Muscular Atrophy

Spinal muscular atrophy is a severe motor neuron disease caused by inactivating mutations in the SMN1 gene leading to reduced levels of full-length functional SMN protein. SMN is a critical mediator of spliceosomal protein assembly, and complete loss or drastic reduction in protein leads to loss of cell viability. However, the reason for selective motor neuron degeneration when SMN is reduced to levels which are tolerated by all other cell types is not currently understood. Widespread splicing abnormalities have recently been reported at end-stage in a mouse model of SMA, leading to the proposition that disruption of efficient splicing is the primary mechanism of motor neuron death. However, it remains unclear whether splicing abnormalities are present during early stages of the disease, which would be a requirement for a direct role in disease pathogenesis. We performed exon-array analysis of RNA from SMN deficient mouse spinal cord at 3 time points, pre-symptomatic (P1), early symptomatic (P7), and late-symptomatic (P13). Compared to littermate control mice, SMA mice showed a time-dependent increase in the number of exons showing differential expression, with minimal differences between genotypes at P1 and P7, but substantial variation in late-symptomatic (P13) mice. Gene ontology analysis revealed differences in pathways associated with neuronal development as well as cellular injury. Validation of selected targets by RT–PCR confirmed the array findings and was in keeping with a shift between physiologically occurring mRNA isoforms. We conclude that the majority of splicing changes occur late in SMA and may represent a secondary effect of cell injury, though we cannot rule out significant early changes in a small number of transcripts crucial to motor neuron survival