Autocrine, paracrine and necrotic NMDA receptor signalling in mouse pancreatic neuroendocrine tumour cells.

N-Methyl-d-aspartate receptor (NMDAR) activation is implicated in the malignant progression of many cancer types, as previously shown by the growth-inhibitory effects of NMDAR antagonists. NMDAR-mediated calcium influx and its downstream signalling depend critically, however, on the dynamics of membrane potential and ambient glutamate concentration, which are poorly characterized in cancer cells. Here, we have used low-noise whole-cell patch-clamp recording to investigate the electrophysiology of glutamate signalling in pancreatic neuroendocrine tumour (PanNET) cells derived from a genetically-engineered mouse model (GEMM) of PanNET, in which NMDAR signalling is known to promote cancer progression. Activating NMDARs caused excitation and intracellular calcium elevation, and intracellular perfusion with physiological levels of glutamate led to VGLUT-dependent autocrine NMDAR activation. Necrotic cells, which are often present in rapidly-growing tumours, were shown to release endogenous cytoplasmic glutamate, and necrosis induced by mechanical rupture of the plasma membrane produced intense NMDAR activation in nearby cells. Computational modelling, based on these results, predicts that NMDARs in cancer cells can be strongly activated in the tumour microenvironment by both autocrine glutamate release and necrosis

Rainfall data simulation by hidden Markov model and discrete wavelet transformation

In many regions, monthly (or bimonthly) rainfall data can be considered as deterministic while daily rainfall data may be treated as random. As a result, deterministic models may not sufficiently fit the daily data because of the strong stochastic nature, while stochastic models may also not reliably fit into daily rainfall time series because of the deterministic nature at the large scale (i.e. coarse scale). Although there are different approaches for simulating daily rainfall, mixing of deterministic and stochastic models (towards possible representation of both deterministic and stochastic properties) has not hitherto been proposed. An attempt is made in this study to simulate daily rainfall data by utilizing discrete wavelet transformation and hidden Markov model. We use a deterministic model to obtain large-scale data, and a stochastic model to simulate the wavelet tree coefficients. The simulated daily rainfall is obtained by inverse transformation. We then compare the accumulated simulated and accumulated observed data from the Chao Phraya Basin in Thailand. Because of the stochastic nature at the small scale, the simulated daily rainfall on a point to point comparison show deviations with the observed data. However the accumulated simulated data do show some level of agreement with the observed data. © Springer-Verlag 2008.postprin

Rainfall data simulation by hidden Markov model and discrete wavelet transformation

In many regions, monthly (or bimonthly) rainfall data can be considered as deterministic while daily rainfall data may be treated as random. As a result, deterministic models may not sufficiently fit the daily data because of the strong stochastic nature, while stochastic models may also not reliably fit into daily rainfall time series because of the deterministic nature at the large scale (i.e. coarse scale). Although there are different approaches for simulating daily rainfall, mixing of deterministic and stochastic models (towards possible representation of both deterministic and stochastic properties) has not hitherto been proposed. An attempt is made in this study to simulate daily rainfall data by utilizing discrete wavelet transformation and hidden Markov model. We use a deterministic model to obtain large-scale data, and a stochastic model to simulate the wavelet tree coefficients. The simulated daily rainfall is obtained by inverse transformation. We then compare the accumulated simulated and accumulated observed data from the Chao Phraya Basin in Thailand. Because of the stochastic nature at the small scale, the simulated daily rainfall on a point to point comparison show deviations with the observed data. However the accumulated simulated data do show some level of agreement with the observed data. © Springer-Verlag 2008.postprin

A knowledge-based weighting framework to boost the power of genome-wide association studies

Background: We are moving to second-wave analysis of genome-wide association studies (GWAS), characterized by comprehensive bioinformatical and statistical evaluation of genetic associations. Existing biological knowledge is very valuable for GWAS, which may help improve their detection power particularly for disease susceptibility loci of moderate effect size. However, a challenging question is how to utilize available resources that are very heterogeneous to quantitatively evaluate the statistic significances. Methodology/Principal Findings: We present a novel knowledge-based weighting framework to boost power of the GWAS and insightfully strengthen their explorative performance for follow-up replication and deep sequencing. Built upon diverse integrated biological knowledge, this framework directly models both the prior functional information and the association significances emerging from GWAS to optimally highlight single nucleotide polymorphisms (SNPs) for subsequent replication. In the theoretical calculation and computer simulation, it shows great potential to achieve extra over 15% power to identify an association signal of moderate strength or to use hundreds of whole-genome subjects fewer to approach similar power. In a case study on late-onset Alzheimer disease (LOAD) for a proof of principle, it highlighted some genes, which showed positive association with LOAD in previous independent studies, and two important LOAD related pathways. These genes and pathways could be originally ignored due to involved SNPs only having moderate association significance. Conclusions/Significance: With user-friendly implementation in an open-source Java package, this powerful framework will provide an important complementary solution to identify more true susceptibility loci with modest or even small effect size in current GWAS for complex diseases. © 2010 Li et al.published_or_final_versio

High-sensitivity optical preamplifier for WDM systems using an optical parametric amplifier

We propose and demonstrate a novel preamplifier to improve receiver sensitivity for a 10-Gb/s return-to-zero on-off keying format by using a fiber optical parametric amplifier. Receiver sensitivity can reach down to -42 dBm at bit-error rate = 10-9 This sensitivity is only 1.1 dB off the quantum limit. The crosstalk issue is also investigated for this dual-end detection scheme in a wavelength-division-multiplexing system. © 2009 IEEE.published_or_final_versio

FastPval: A fast and memory efficient program to calculate very low P-values from empirical distribution

Motivation: Resampling methods, such as permutation and bootstrap, have been widely used to generate an empirical distribution for assessing the statistical significance of a measurement. However, to obtain a very low P-value, a large size of resampling is required, where computing speed, memory and storage consumption become bottlenecks, and sometimes become impossible, even on a computer cluster. Results: We have developed a multiple stage P-value calculating program called FastPval that can efficiently calculate very low (up to 10-9) P-values from a large number of resampled measurements. With only two input files and a few parameter settings from the users, the program can compute P-values from empirical distribution very efficiently, even on a personal computer. When tested on the order of 109 resampled data, our method only uses 52.94% the time used by the conventional method, implemented by standard quicksort and binary search algorithms, and consumes only 0.11% of the memory and storage. Furthermore, our method can be applied to extra large datasets that the conventional method fails to calculate. The accuracy of the method was tested on data generated from Normal, Poison and Gumbel distributions and was found to be no different from the exact ranking approach. © The Author(s) 2010. Published by Oxford University Press.published_or_final_versio

Sperm retrieval rate and pregnancy rate in infertile couples undergoing in-vitro fertilisation and testicular sperm extraction for non-obstructive azoospermia in Hong Kong

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Subpicosecond fiber optical parametric chirped pulse amplifier based on highly-nonlinear fiber

We experimentally demonstrate a fiber optical parametric chirped pulse amplifier. A 750-fs signal is stretched to 40 ps, amplified with a gain of 30 dB through parametric process and then compressed to 808 fs. 2010 Optical Society of America. © 2010 IEEE.published_or_final_versionThe 2010 Conference on Lasers and Electro-Optics (CLEO) and Quantum Electronics and Laser Science Conference (QELS), San Josa, CA., 16-21 May 2010. In Proceedings of the CLEO/QELS, 2010, p. 1-

Live birth and cumulative live birth rates in expected poor ovarian responders defined by the Bologna criteria following IVF/ICSI treatment

Objective: To determine the live birth and cumulative live birth rates of expected poor ovarian responders according to the Bologna criteria and to compare their outcomes with those of expected normal responders Design: Retrospective analysis Setting: University infertility clinic Patients: A total of 1,152 subfertile women undergoing their first in vitro fertilization (IVF) cycle Interventions: Women were classified into 4 groups according to the Bologna criteria for comparison Main Outcome Measure(s): Live birth and cumulative live birth rates Results: Women with expected poor response (POR) had the lowest live birth rate than the other 3 groups (23.8%, p = 0.031). Cumulative live birth rates were significantly lower in those with expected POR than those with expected normal ovarian response (NOR) (35.8% vs 62.8%, p3 oocytes, p = 0.006) whereas the live birth rates in fresh cycle did not differ (17.8% vs 30.9%, p = 0.108). Conclusion: Women who were expected POR according to the Bologna criteria had lower live birth and cumulative live birth than expected NOR but they still can achieve reasonable treatment outcomes and IVF treatment should not be precluded. © 2015 Chai et al.published_or_final_versio