WebPARE: web-computing for inferring genetic or transcriptional interactions

Summary: Inferring genetic or transcriptional interactions, when done successfully, may provide insights into biological processes or biochemical pathways of interest. Unfortunately, most computational algorithms require a certain level of programming expertise. To provide a simple web interface for users to infer interactions from time course gene expression data, we present WebPARE, which is based on the pattern recognition algorithm (PARE). For expression data, in which each type of interaction (e.g. activator target) and the corresponding paired gene expression pattern are significantly associated, PARE uses a non-linear score to classify gene pairs of interest into a few subclasses of various time lags. In each subclass, PARE learns the parameters in the decision score using known interactions from biological experiments or published literature. Subsequently, the trained algorithm predicts interactions of a similar nature. Previously, PARE was shown to infer two sets of interactions in yeast successfully. Moreover, several predicted genetic interactions coincided with existing pathways; this indicates the potential of PARE in predicting partial pathway components. Given a list of gene pairs or genes of interest and expression data, WebPARE invokes PARE and outputs predicted interactions and their networks in directed graphs

USCID fourth international conference

Presented at the Role of irrigation and drainage in a sustainable future: USCID fourth international conference on irrigation and drainage on October 3-6, 2007 in Sacramento, California.In addition to increasingly frequent water shortage problems, agricultural water sector is also challenged by environmental issues. The objective of this article is to summarize, as well as propose sustainable strategies for agricultural sector in response to current environmental challenges. For water shortage problems, which are becoming more and more frequent worldwide including Taiwan, measures for irrigation water, such as extending irrigation periods, decreasing number of irrigation application times, or rotational irrigation, are introduced and discussed. When borrowing or transfer of water among sectors is needed in Taiwan, it is usually from agricultural irrigation water to other sectors in almost all cases. The maintenance of water right, and compensation to farmers for their income loss, are the two major issues. As for environmental changes, the impact of the accession of Taiwan to WTO (World Trade Organization) is discussed specifically in this article, and a management scheme in order to save irrigation water, which could be used for other purposes, is suggested in this article

Infectious Alopecia in a Dog Breeder After Renal Transplantation

Tinea capitis rarely occurs in renal transplant recipients. We report this living-related renal transplant patient receiving cyclosporine-based therapy who initially presented with severe exfoliation of the scalp with yellowish-white scales and marked hair loss. The lesions extended to the frontal area and both cheeks, resulting in several skin ulcers with perifocal erythematous inflammatory changes, and palpable cervical lymph nodes. A biopsy of a skin lesion revealed fungal infection and culture yielded Microsporum canis. The patient mentioned an outbreak of ringworm in her breeding dogs during this period. After adequate treatment of the patient and her infected animals with griseofulvin and disinfection of the environment, her skin lesions resolved dramatically, with regrowth of hair

LD2SNPing: linkage disequilibrium plotter and RFLP enzyme mining for tag SNPs

<p>Abstract</p> <p>Background</p> <p>Linkage disequilibrium (LD) mapping is commonly used to evaluate markers for genome-wide association studies. Most types of LD software focus strictly on LD analysis and visualization, but lack supporting services for genotyping.</p> <p>Results</p> <p>We developed a freeware called LD₂SNPing, which provides a complete package of mining tools for genotyping and LD analysis environments. The software provides SNP ID- and gene-centric online retrievals for SNP information and tag SNP selection from dbSNP/NCBI and HapMap, respectively. Restriction fragment length polymorphism (RFLP) enzyme information for SNP genotype is available to all SNP IDs and tag SNPs. Single and multiple SNP inputs are possible in order to perform LD analysis by online retrieval from HapMap and NCBI. An LD statistics section provides <it>D</it>, <it>D'</it>, <it>r</it>², <it>δ</it>_<it>Q</it>, <it>ρ</it>, and the <it>P </it>values of the Hardy-Weinberg Equilibrium for each SNP marker, and Chi-square and likelihood-ratio tests for the pair-wise association of two SNPs in LD calculation. Finally, 2D and 3D plots, as well as plain-text output of the results, can be selected.</p> <p>Conclusion</p> <p>LD₂SNPing thus provides a novel visualization environment for multiple SNP input, which facilitates SNP association studies. The software, user manual, and tutorial are freely available at <url>http://bio.kuas.edu.tw/LD2NPing</url>.</p

Patient-oriented simulation based on Monte Carlo algorithm by using MRI data

<p>Abstract</p> <p>Background</p> <p>Although Monte Carlo simulations of light propagation in full segmented three-dimensional MRI based anatomical models of the human head have been reported in many articles. To our knowledge, there is no patient-oriented simulation for individualized calibration with NIRS measurement. Thus, we offer an approach for brain modeling based on image segmentation process with <it>in vivo </it>MRI T1 three-dimensional image to investigate the individualized calibration for NIRS measurement with Monte Carlo simulation.</p> <p>Methods</p> <p>In this study, an individualized brain is modeled based on <it>in vivo </it>MRI 3D image as five layers structure. The behavior of photon migration was studied for this individualized brain detections based on three-dimensional time-resolved Monte Carlo algorithm. During the Monte Carlo iteration, all photon paths were traced with various source-detector separations for characterization of brain structure to provide helpful information for individualized design of NIRS system.</p> <p>Results</p> <p>Our results indicate that the patient-oriented simulation can provide significant characteristics on the optimal choice of source-detector separation within 3.3 cm of individualized design in this case. Significant distortions were observed around the cerebral cortex folding. The spatial sensitivity profile penetrated deeper to the brain in the case of expanded CSF. This finding suggests that the optical method may provide not only functional signal from brain activation but also structural information of brain atrophy with the expanded CSF layer. The proposed modeling method also provides multi-wavelength for NIRS simulation to approach the practical NIRS measurement.</p> <p>Conclusions</p> <p>In this study, the three-dimensional time-resolved brain modeling method approaches the realistic human brain that provides useful information for NIRS systematic design and calibration for individualized case with prior MRI data.</p

Intraprostatic injection of botulinum toxin type- A relieves bladder outlet obstruction in human and induces prostate apoptosis in dogs

BACKGROUND: With the increasing interest with botulinum toxin – A (BTX-A) application in the lower urinary tract, we investigated the BTX-A effects on the canine prostate and also in men with bladder outlet obstruction (BOO) due to benign prostatic hyperplasia (BPH). METHODS: Transperineal injection into the prostate using transrectal ultrasound (TRUS) was performed throughout the study. Saline with or without 100 U of BTX-A was injected into mongrel dogs prostate. One or 3 months later, the prostate was harvested for morphologic and apoptotic study. In addition, eight BPH patients refractory to α-blockers were treated with ultrasound guided intraprostatic injection of 200 U of BTX-A. RESULTS: In the BTX-A treated dogs, atrophy and diffuse apoptosis was observed with H&E stain and TUNEL stain at 1 and 3 months. Clinically, the mean prostate volume, symptom score, and quality of life index were significantly reduced by 18.8%, 73.1%, and 61.5% respectively. Maximal flow rate significantly increased by 72.0%. CONCLUSION: Intraprostatic BTX-A injection induces prostate apotosis in dogs and relieves BOO in humans. It is therefore a promising alternative treatment for refractory BOO due to BPH

Assessing the Decision-Making Process in Human-Robot Collaboration Using a Lego-like EEG Headset

Human-robot collaboration (HRC) has become an emerging field, where the use of a robotic agent has been shifted from a supportive machine to a decision-making collaborator. A variety of factors can influence the effectiveness of decision-making processes during HRC, including the system-related (e.g., robot capability) and human-related (e.g., individual knowledgeability) factors. As a variety of contextual factors can significantly impact the human-robot decision-making process in collaborative contexts, the present study adopts a Lego-like EEG headset to collect and examine human brain activities and utilizes multiple questionnaires to evaluate participants’ cognitive perceptions toward the robot. A user study was conducted where two levels of robot capabilities (high vs. low) were manipulated to provide system recommendations. The participants were also identified into two groups based on their computational thinking (CT) ability. The EEG results revealed that different levels of CT abilities trigger different brainwaves, and the participants’ trust calibration of the robot also varies the resultant brain activities

A model-based circular binary segmentation algorithm for the analysis of array CGH data

<p>Abstract</p> <p>Background</p> <p>Circular Binary Segmentation (CBS) is a permutation-based algorithm for array Comparative Genomic Hybridization (aCGH) data analysis. CBS accurately segments data by detecting change-points using a maximal-<it>t </it>test; but extensive computational burden is involved for evaluating the significance of change-points using permutations. A recent implementation utilizing a hybrid method and early stopping rules (hybrid CBS) to improve the performance in speed was subsequently proposed. However, a time analysis revealed that a major portion of computation time of the hybrid CBS was still spent on permutation. In addition, what the hybrid method provides is an approximation of the significance upper bound or lower bound, not an approximation of the significance of change-points itself.</p> <p>Results</p> <p>We developed a novel model-based algorithm, extreme-value based CBS (eCBS), which limits permutations and provides robust results without loss of accuracy. Thousands of aCGH data under null hypothesis were simulated in advance based on a variety of non-normal assumptions, and the corresponding maximal-<it>t </it>distribution was modeled by the Generalized Extreme Value (GEV) distribution. The modeling results, which associate characteristics of aCGH data to the GEV parameters, constitute lookup tables (eXtreme model). Using the eXtreme model, the significance of change-points could be evaluated in a constant time complexity through a table lookup process.</p> <p>Conclusions</p> <p>A novel algorithm, eCBS, was developed in this study. The current implementation of eCBS consistently outperforms the hybrid CBS 4× to 20× in computation time without loss of accuracy. Source codes, supplementary materials, supplementary figures, and supplementary tables can be found at <url>http://ntumaps.cgm.ntu.edu.tw/eCBSsupplementary</url>.</p