A quantitative analysis of monochromaticity in genetic interaction networks

<p>Abstract</p> <p>Background</p> <p>A genetic interaction refers to the deviation of phenotypes from the expected when perturbing two genes simultaneously. Studying genetic interactions help clarify relationships between genes, such as compensation and masking, and identify gene groups of functional modules. Recently, several genome-scale experiments for measuring quantitative (positive and negative) genetic interactions have been conducted. The results revealed that genes in the same module usually interact with each other in a consistent way (pure positive or negative); this phenomenon was designated as monochromaticity. Monochromaticity might be the underlying principle that can be utilized to unveil the modularity of cellular networks. However, no appropriate quantitative measurement for this phenomenon has been proposed.</p> <p>Results</p> <p>In this study, we propose the monochromatic index (MCI), which is able to quantitatively evaluate the monochromaticity of potential functional modules of genes, and the MCI was used to study genetic landscapes in different cellular subsystems. We demonstrated that MCI not only amend the deficiencies of MP-score but also properly incorporate the background effect. The results showed that not only within-complex but also between-complex connections present significant monochromatic tendency. Furthermore, we also found that significantly higher proportion of protein complexes are connected by negative genetic interactions in metabolic network, while transcription and translation system adopts relatively even number of positive and negative genetic interactions to link protein complexes.</p> <p>Conclusion</p> <p>In summary, we demonstrate that MCI improves deficiencies suffered by MP-score, and can be used to evaluate monochromaticity in a quantitative manner. In addition, it also helps to unveil features of genetic landscapes in different cellular subsystems. Moreover, MCI can be easily applied to data produced by different types of genetic interaction methodologies such as Synthetic Genetic Array (SGA), and epistatic miniarray profile (E-MAP).</p

Ultrasmall all-optical plasmonic switch and its application to superresolution imaging

Because of their exceptional local-field enhancement and ultrasmall mode volume, plasmonic components can integrate photonics and electronics at nanoscale, and active control of plasmons is the key. However, all-optical modulation of plasmonic response with nanometer mode volume and unity modulation depth is still lacking. Here we show that scattering from a plasmonic nanoparticle, whose volume is smaller than 0.001 μm3, can be optically switched off with less than 100 μW power. Over 80% modulation depth is observed, and shows no degradation after repetitive switching. The spectral bandwidth approaches 100 nm. The underlying mechanism is suggested to be photothermal effects, and the effective single-particle nonlinearity reaches nearly 10−9 m2/W, which is to our knowledge the largest record of metallic materials to date. As a novel application, the non-bleaching and unlimitedly switchable scattering is used to enhance optical resolution to λ/5 (λ/9 after deconvolution), with 100-fold less intensity requirement compared to similar superresolution techniques. Our work not only opens up a new field of ultrasmall all-optical control based on scattering from a single nanoparticle, but also facilitates superresolution imaging for long-term observation

Serotonin receptor HTR6-mediated mTORC1 signaling regulates dietary restriction-induced memory enhancement

Dietary restriction (DR; sometimes called calorie restriction) has profound beneficial effects on physiological, psychological, and behavioral outcomes in animals and in humans. We have explored the molecular mechanism of DR-induced memory enhancement and demonstrate that dietary tryptophan-a precursor amino acid for serotonin biosynthesis in the brain-and serotonin receptor 5-hydroxytryptamine receptor 6 (HTR6) are crucial in mediating this process. We show that HTR6 inactivation diminishes DR-induced neurological alterations, including reduced dendritic complexity, increased spine density, and enhanced long-term potentiation (LTP) in hippocampal neurons. Moreover, we find that HTR6-mediated mechanistic target of rapamycin complex 1 (mTORC1) signaling is involved in DR-induced memory improvement. Our results suggest that the HTR6-mediated mTORC1 pathway may function as a nutrient sensor in hippocampal neurons to couple memory performance to dietary intake

Domain Indexing for Fractal Image Compression

[[abstract]]This paper presents a novel algorithm to accelerate the encoding procedure of fractal image compression. We develop an indexing technology to access candidate domain blocks. The location of maximal gradient is adopted as the key for indexing. Only those blocks whose positions of maximal gradients matching that of a given range block are rested. In our experiments, the new algorithm promises good performance. It takes few seconds to encode a 512 by 512 image on a Pentium II 450 PC with a slight loss of decoded image fidelity.[[fileno]]2030217030015[[department]]資訊工程學

Accelerating Fractal Compression With a Real-time Decoder

[[abstract]]©2001 IIS SINICA-Image data compression by fractal techniques has been widely investigated. Although its high compression ratio and resolution-independent decoding properties are attractive, the encoding process is computationally demanding in order to achieve an optimal compression. A variety of speed-up algorithms have been proposed since Jacquin published a novel fractal coding algorithm. Unfortunately, the quantization strategy of scaling coefficients and the programming techniques lead to the results reported by different researchers are various even on the same image data which causes the speed-up of compression is incomparable. This paper proposes a real-time fractal decoder as a standard. We report the implementation results of a nearly optimal encoding algorithm OPT on commonly used images: Jet, Lenna, Mandrill, and Peppers of size 512?512. An accelerating compression algorithm using maximum gradient MG is shown to be 1300 times faster than OPT with a slight drop of PSNR value when encoding a 512?512 image.[[department]]資訊工程學