Ovarian cancer symptom awareness and anticipated delayed presentation in a population sample

Background: While ovarian cancer is recognised as having identifiable early symptoms, understanding of the key determinants of symptom awareness and early presentation is limited. A population-based survey of ovarian cancer awareness and anticipated delayed presentation with symptoms was conducted as part of the International Cancer Benchmarking Partnership (ICBP). Methods: Women aged over 50 years were recruited using random probability sampling (n = 1043). Computer-assisted telephone interviews were used to administer measures including ovarian cancer symptom recognition, anticipated time to presentation with ovarian symptoms, health beliefs (perceived risk, perceived benefits/barriers to early presentation, confidence in symptom detection, ovarian cancer worry), and demographic variables. Logistic regression analysis was used to identify the contribution of independent variables to anticipated presentation (categorised as < 3 weeks or ≥ 3 weeks). Results: The most well-recognised symptoms of ovarian cancer were post-menopausal bleeding (87.4%), and persistent pelvic (79.0%) and abdominal (85.0%) pain. Symptoms associated with eating difficulties and changes in bladder/bowel habits were recognised by less than half the sample. Lower symptom awareness was significantly associated with older age (p ≤ 0.001), being single (p ≤ 0.001), lower education (p ≤ 0.01), and lack of personal experience of ovarian cancer (p ≤ 0.01). The odds of anticipating a delay in time to presentation of ≥ 3 weeks were significantly increased in women educated to degree level (OR = 2.64, 95% CI 1.61 – 4.33, p ≤ 0.001), women who reported more practical barriers (OR = 1.60, 95% CI 1.34 – 1.91, p ≤ 0.001) and more emotional barriers (OR = 1.21, 95% CI 1.06 – 1.40, p ≤ 0.01), and those less confident in symptom detection (OR = 0.56, 95% CI 0.42 – 0.73, p ≤ 0.001), but not in those who reported lower symptom awareness (OR = 0.99, 95% CI 0.91 – 1.07, p = 0.74). Conclusions: Many symptoms of ovarian cancer are not well-recognised by women in the general population. Evidence-based interventions are needed not only to improve public awareness but also to overcome the barriers to recognising and acting on ovarian symptoms, if delays in presentation are to be minimised

End-to-End Probabilistic Inference for Nonstationary Audio Analysis

Accepted to the Thirty-sixth International Conference on Machine Learning (ICML) 2019Accepted to the Thirty-sixth International Conference on Machine Learning (ICML) 2019Accepted to the Thirty-sixth International Conference on Machine Learning (ICML) 2019A typical audio signal processing pipeline includes multiple disjoint analysis stages, including calculation of a time-frequency representation followed by spectrogram-based feature analysis. We show how time-frequency analysis and nonnegative matrix factorisation can be jointly formulated as a spectral mixture Gaussian process model with nonstationary priors over the amplitude variance parameters. Further, we formulate this nonlinear model's state space representation, making it amenable to infinite-horizon Gaussian process regression with approximate inference via expectation propagation, which scales linearly in the number of time steps and quadratically in the state dimensionality. By doing so, we are able to process audio signals with hundreds of thousands of data points. We demonstrate, on various tasks with empirical data, how this inference scheme outperforms more standard techniques that rely on extended Kalman filtering

Implied volatility of basket options at extreme strikes

In the paper, we characterize the asymptotic behavior of the implied volatility of a basket call option at large and small strikes in a variety of settings with increasing generality. First, we obtain an asymptotic formula with an error bound for the left wing of the implied volatility, under the assumption that the dynamics of asset prices are described by the multidimensional Black-Scholes model. Next, we find the leading term of asymptotics of the implied volatility in the case where the asset prices follow the multidimensional Black-Scholes model with time change by an independent increasing stochastic process. Finally, we deal with a general situation in which the dependence between the assets is described by a given copula function. In this setting, we obtain a model-free tail-wing formula that links the implied volatility to a special characteristic of the copula called the weak lower tail dependence function

UNIFYING PROBABILISTIC MODELS FOR TIME-FREQUENCY ANALYSIS

In audio signal processing, probabilistic time-frequency models have many benefits over their non-probabilistic counterparts. They adapt to the incoming signal, quantify uncertainty, and measure correlation between the signal's amplitude and phase information, making time domain resynthesis straightforward. However, these models are still not widely used since they come at a high computational cost, and because they are formulated in such a way that it can be difficult to interpret all the modelling assumptions. By showing their equivalence to Spectral Mixture Gaussian processes, we illuminate the underlying model assumptions and provide a general framework for constructing more complex models that better approximate real-world signals. Our interpretation makes it intuitive to inspect, compare, and alter the models since all prior knowledge is encoded in the Gaussian process kernel functions. We utilise a state space representation to perform efficient inference via Kalman smoothing, and we demonstrate how our interpretation allows for efficient parameter learning in the frequency domain.Comment: Accepted to International Conference on Acoustics, Speech and Signal Processing (ICASSP) 201

Progesterone reduces erectile dysfunction in sleep-deprived spontaneously hypertensive rats

BACKGROUND: Paradoxical sleep deprivation (PSD) associated with cocaine has been shown to enhance genital reflexes (penile erection-PE and ejaculation-EJ) in Wistar rats. Since hypertension predisposes males to erectile dysfunction, the aim of the present study was to investigate the effects of PSD on genital reflexes in the spontaneously hypertensive rat (SHR) compared to the Wistar strain. We also extended our study to examine how PSD affect steroid hormone concentrations involved in genital events in both experimental models. METHODS: The first experiment investigated the effects of PSD on genital reflexes of Wistar and SHR rats challenged by saline and cocaine (n = 10/group). To further examine the impact of the PSD on concentrations of sexual hormones, we performed a hormonal analysis of testosterone and progesterone in the Wistar and in SHR strains. Since after PSD progesterone concentrations decreased in the SHR compared to the Wistar PSD group we extended our study by investigating whether progesterone (25 mg/kg or 50 mg/kg) or testosterone (0.5 mg/kg or 1.0 mg/kg) administration during PSD would have a facilitator effect on the occurrence of genital reflexes in this hypertensive strain. RESULTS: A 4-day period of PSD induced PE in 50% of the Wistar rats against 10% for the SHR. These genital reflexes was potentiated by cocaine in Wistar rats whereas this scenario did not promote significant enhancement in PE and EJ in hypertensive rats, and the percentage of SHR displaying genital reflexes still figured significantly lower than that of the Wistar strain. As for hormone concentrations, both sleep-deprived Wistar and SHR showed lower testosterone concentrations than their respective controls. Sleep deprivation promoted an increase in concentrations of progesterone in Wistar rats, whereas no significant alterations were found after PSD in the SHR strain, which did not present enhancement in erectile responses. In order to explore the role of progesterone in the occurrence of genital reflexes, SHR were treated daily during the sleep deprivation period with progesterone; after the administration of this hormone and challenge with cocaine, we observed a significant increase in erectile events compared with the vehicle PSD SHR+cocaine group. CONCLUSION: Our data showed that the low frequency of genital reflexes found in SHR sleep deprived rats may be attributed to the lower concentrations of progesterone in these rats, based on the observation that progesterone replacement increased genital reflexes in this strain

Systems Analysis Unfolds the Relationship between the Phosphoketolase Pathway and Growth in Aspergillus nidulans

Background: Aspergillus nidulans is an important model organism for studies on fundamental eukaryotic cell biology and on industrial processes due to its close relation to A. niger and A. oryzae. Here we identified the gene coding for a novel metabolic pathway in A. nidulans, namely the phosphoketolase pathway, and investigated the role of an increased phosphoketolase activity. Methodology/Principal Findings: Over-expression of the phosphoketolase gene (phk) improved the specific growth rate on xylose, glycerol and ethanol. Transcriptome analysis showed that a total of 1,222 genes were significantly affected by overexpression of the phk, while more than half of the affected genes were carbon source specific. During growth on glucose medium, the transcriptome analysis showed that the response to phk over-expression is targeted to neutralize the effect of the over-expression by regulating the acetate metabolism and initiate a growth dampening response. Conclusions/Significance: Metabolic flux analysis using 13C-labelled glucose, showed that over-expression of phosphoketolase added flexibility to the central metabolism. Our findings further suggests that A. nidulans is not optimized for growth on xylose, glycerol or ethanol as the sole carbon sources. © 2008 Panagiotou et al.published_or_final_versio

Latent cluster analysis of ALS phenotypes identifies prognostically differing groups

BACKGROUND Amyotrophic lateral sclerosis (ALS) is a degenerative disease predominantly affecting motor neurons and manifesting as several different phenotypes. Whether these phenotypes correspond to different underlying disease processes is unknown. We used latent cluster analysis to identify groupings of clinical variables in an objective and unbiased way to improve phenotyping for clinical and research purposes. METHODS Latent class cluster analysis was applied to a large database consisting of 1467 records of people with ALS, using discrete variables which can be readily determined at the first clinic appointment. The model was tested for clinical relevance by survival analysis of the phenotypic groupings using the Kaplan-Meier method. RESULTS The best model generated five distinct phenotypic classes that strongly predicted survival (p<0.0001). Eight variables were used for the latent class analysis, but a good estimate of the classification could be obtained using just two variables: site of first symptoms (bulbar or limb) and time from symptom onset to diagnosis (p<0.00001). CONCLUSION The five phenotypic classes identified using latent cluster analysis can predict prognosis. They could be used to stratify patients recruited into clinical trials and generating more homogeneous disease groups for genetic, proteomic and risk factor research