A note on domination and minus domination numbers in cubic graphs

Author name used in this publication: C. T. Ng2005-2006 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Molecular cloning, genomic characterization and over-expression of a novel gene, XRRA1, identified from human colorectal cancer cell HCT116(Clone2_XRR )and macaque testis

BACKGROUND: As part of our investigation into the genetic basis of tumor cell radioresponse, we have isolated several clones with a wide range of responses to X-radiation (XR) from an unirradiated human colorectal tumor cell line, HCT116. Using human cDNA microarrays, we recently identified a novel gene that was down-regulated by two-fold in an XR-resistant cell clone, HCT116(Clone2_XRR). We have named this gene as X-ray radiation resistance associated 1 (XRRA1) (GenBank BK000541). Here, we present the first report on the molecular cloning, genomic characterization and over-expression of the XRRA1 gene. RESULTS: We found that XRRA1 was expressed predominantly in testis of both human and macaque. cDNA microarray analysis showed three-fold higher expression of XRRA1 in macaque testis relative to other tissues. We further cloned the macaque XRRA1 cDNA (GenBank AB072776) and a human XRRA1 splice variant from HCT116(Clone2_XRR )(GenBank AY163836). In silico analysis revealed the full-length human XRRA1, mouse, rat and bovine Xrra1 cDNAs. The XRRA1 gene comprises 11 exons and spans 64 kb on chromosome 11q13.3. Human and macaque cDNAs share 96% homology. Human XRRA1 cDNA is 1987 nt long and encodes a protein of 559 aa. XRRA1 protein is highly conserved in human, macaque, mouse, rat, pig, and bovine. GFP-XRRA1 fusion protein was detected in both the nucleus and cytoplasm of HCT116 clones and COS-7 cells. Interestingly, we found evidence that COS-7 cells which over-expressed XRRA1 lacked Ku86 (Ku80, XRCC5), a non-homologous end joining (NHEJ) DNA repair molecule, in the nucleus. RT-PCR analysis showed differential expression of XRRA1 after XR in HCT116 clones manifesting significantly different XR responses. Further, we found that XRRA1 was expressed in most tumor cell types. Surprisingly, mouse Xrra1 was detected in mouse embryonic stem cells R1. CONCLUSIONS: Both XRRA1 cDNA and protein are highly conserved among mammals, suggesting that XRRA1 may have similar functions. Our results also suggest that the genetic modulation of XRRA1 may affect the XR responses of HCT116 clones and that XRRA1 may have a role in the response of human tumor and normal cells to XR. XRRA1 might be correlated with cancer development and might also be an early expressed gene

Neutrix Calculus and Finite Quantum Field Theory

In general, quantum field theories (QFT) require regularizations and infinite renormalizations due to ultraviolet divergences in their loop calculations. Furthermore, perturbation series in theories like QED are not convergent series, but are asymptotic series. We apply neutrix calculus, developed in connection with asymptotic series and divergent integrals, to QFT,obtaining finite renormalizations. While none of the physically measurable results in renormalizable QFT is changed, quantum gravity is rendered more manageable in the neutrix framework.Comment: 10 pages; LaTeX; version to appear in J. Phys. A: Math. Gen. as a Letter to the Edito

A new pulse coupled neural network (PCNN) for brain medical image fusion empowered by shuffled frog leaping algorithm

Recent research has reported the application of image fusion technologies in medical images in a wide range of aspects, such as in the diagnosis of brain diseases, the detection of glioma and the diagnosis of Alzheimer’s disease. In our study, a new fusion method based on the combination of the shuffled frog leaping algorithm (SFLA) and the pulse coupled neural network (PCNN) is proposed for the fusion of SPECT and CT images to improve the quality of fused brain images. First, the intensity-hue-saturation (IHS) of a SPECT and CT image are decomposed using a non-subsampled contourlet transform (NSCT) independently, where both low-frequency and high-frequency images, using NSCT, are obtained. We then used the combined SFLA and PCNN to fuse the high-frequency sub-band images and low-frequency images. The SFLA is considered to optimize the PCNN network parameters. Finally, the fused image was produced from the reversed NSCT and reversed IHS transforms. We evaluated our algorithms against standard deviation (SD), mean gradient (Ḡ), spatial frequency (SF) and information entropy (E) using three different sets of brain images. The experimental results demonstrated the superior performance of the proposed fusion method to enhance both precision and spatial resolution significantly

Effect Modification of the Association between Short-term Meteorological Factors and Mortality by Urban Heat Islands in Hong Kong

Background Prior studies from around the world have indicated that very high temperatures tend to increase summertime mortality. However possible effect modification by urban micro heat islands has only been examined by a few studies in North America and Europe. This study examined whether daily mortality in micro heat island areas of Hong Kong was more sensitive to short term changes in meteorological conditions than in other areas. Method An urban heat island index (UHII) was calculated for each of Hong Kong’s 248 geographical tertiary planning units (TPU). Daily counts of all natural deaths among Hong Kong residents were stratified according to whether the place of residence of the decedent was in a TPU with high (above the median) or low UHII. Poisson Generalized Additive Models (GAMs) were used to estimate the association between meteorological variables and mortality while adjusting for trend, seasonality, pollutants and flu epidemics. Analyses were restricted to the hot season (June-September). Results Mean temperatures (lags 0–4) above 29°C and low mean wind speeds (lags 0–4) were significantly associated with higher daily mortality and these associations were stronger in areas with high UHII. A 1°C rise above 29°C was associated with a 4.1% (95% confidence interval (CI): 0.7%, 7.6%) increase in natural mortality in areas with high UHII but only a 0.7% (95% CI: −2.4%, 3.9%) increase in low UHII areas. Lower mean wind speeds (5th percentile vs. 95th percentile) were associated with a 5.7% (95% CI: 2.7, 8.9) mortality increase in high UHII areas vs. a −0.3% (95% CI: −3.2%, 2.6%) change in low UHII areas. Conclusion The results suggest that urban micro heat islands exacerbate the negative health consequences of high temperatures and low wind speeds. Urban planning measures designed to mitigate heat island effects may lessen the health effects of unfavorable summertime meteorological conditions

An IoT-Based Framework of Webvr Visualization for Medical Big Data in Connected Health

Recently, telemedicine has been widely applied in remote diagnosis, treatment and counseling, where the Internet of Things (IoT) technology plays an important role. In the process of telemedicine, data are collected from remote medical equipment, such as CT machine and MRI machine, and then transmitted and reconstructed locally in three-dimensions. Due to the large amount of data to be transmitted in the reconstructed model and the small storage capacity, data need to be compressed progressively before transmission. On this basis, we proposed a lightweight progressive transmission algorithm based on large data visualization in telemedicine to improve transmission efficiency and achieve lossless transmission of original data. Moreover, a novel four-layer system architecture based on IoT has been introduced, including the sensing layer, analysis layer, network layer and application layer. In this way, the three-dimensional reconstructed data at the local end is compressed and transmitted to the remote end, and then visualized at the remote end to show reconstructed 3D models. Thus, it is conducive to doctors in remote real-time diagnosis and treatment, and then realize the data processing and transmission between doctors, patients and medical equipment

A nine months follow-up study of hemodynamic effect on bioabsorbable coronary stent implantation

Coronary artery disease has emerged as one of the major diseases causing death worldwide. Coronary stent has great effect to improve blood flow to the myocardium subtended by that artery, in which bioresorbable vascular scaffolds are new-generation stents used by people. However, Coronary stents implantation has a risk of restenosis, which is relative to hemodynamic parameters. Most of existing literatures studied in this issue have not taken into account such important factors as the strut thickness and lumen profile, and has yet to analyze the time effects among hemodynamic parameters over a certain period of time based on individual models. In this research, we proposed a framework to assess the chronic impact of hemodynamic on coronary stent implantation. In the framework, the optical coherence tomography (OCT) is combined with angiography to reconstruct patient-specific models of bioresorbable vascular scaffolds. Then, the hemodynamics parameters are extracted through the simulated 3D models, obtaining the distribution of wall shear stress (WSS), relative residence time (RRT) and oscillatory shear index (OSI). Finally, the changes of these parameters representing the effectiveness of hemodynamics exerted on the implanted stent can be assessed to estimate the chronic impacts. By a 9-month follow-up case study, it is observed that the difference of hemodynamic parameters are not significance. Both at baseline and 9-month follow-up experiments show that the hemodynamic parameters remain normal and similar, proving that the coronary stent implantation nowadays appears to have a robust and everlasting curative effect

A clustering based transfer function for volume rendering using gray-gradient mode histogram

Volume rendering is an emerging technique widely used in the medical field to visualize human organs using tomography image slices. In volume rendering, sliced medical images are transformed into attributes, such as color and opacity through transfer function. Thus, the design of the transfer function directly affects the result of medical images visualization. A well-designed transfer function can improve both the image quality and visualization speed. In one of our previous paper, we designed a multi-dimensional transfer function based on region growth to determine the transparency of a voxel, where both gray threshold and gray change threshold are used to calculate the transparency. In this paper, a new approach of the transfer function is proposed based on clustering analysis of gray-gradient mode histogram, where volume data is represented in a two-dimensional histogram. Clustering analysis is carried out based on the spatial information of volume data in the histogram, and the transfer function is automatically generated by means of clustering analysis of the spatial information. The dataset of human thoracic is used in our experiment to evaluate the performance of volume rendering using the proposed transfer function. By comparing with the original transfer function implemented in two popularly used volume rendering systems, visualization toolkit (VTK) and RadiAnt DICOM Viewer, the effectiveness and performance of the proposed transfer function are demonstrated in terms of the rendering efficiency and image quality, where more accurate and clearer features are presented rather than a blur red area. Furthermore, the complex operations on the two-dimensional histogram are avoided in our proposed approach and more detailed information can be seen from our final visualized image

Minimal residual disease-based risk stratification in Chinese childhood acute lymphoblastic leukemia by flow cytometry and plasma DNA quantitative polymerase chain reaction

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