Automatic segmentation of choroidal thickness in optical coherence tomography

The assessment of choroidal thickness from optical coherence tomography (OCT) images of the human choroid is an important clinical and research task, since it provides valuable information regarding the eye’s normal anatomy and physiology, and changes associated with various eye diseases and the development of refractive error. Due to the time consuming and subjective nature of manual image analysis, there is a need for the development of reliable objective automated methods of image segmentation to derive choroidal thickness measures. However, the detection of the two boundaries which delineate the choroid is a complicated and challenging task, in particular the detection of the outer choroidal boundary, due to a number of issues including: (i) the vascular ocular tissue is non-uniform and rich in non-homogeneous features, and (ii) the boundary can have a low contrast. In this paper, an automatic segmentation technique based on graph-search theory is presented to segment the inner choroidal boundary (ICB) and the outer choroidal boundary (OCB) to obtain the choroid thickness profile from OCT images. Before the segmentation, the B-scan is pre-processed to enhance the two boundaries of interest and to minimize the artifacts produced by surrounding features. The algorithm to detect the ICB is based on a simple edge filter and a directional weighted map penalty, while the algorithm to detect the OCB is based on OCT image enhancement and a dual brightness probability gradient. The method was tested on a large data set of images from a pediatric (1083 B-scans) and an adult (90 B-scans) population, which were previously manually segmented by an experienced observer. The results demonstrate the proposed method provides robust detection of the boundaries of interest and is a useful tool to extract clinical data.

The effects and interactions of GABAergic and dopaminergic agents in the prevention of form deprivation myopia by brief periods of normal vision

Intravitreal injections of GABA antagonists, dopamine agonists and brief periods of normal vision have been shown separately to inhibit form-deprivation myopia (FDM). Our study had three aims: (i) establish whether GABAergic agents modify the myopia protective effect of normal vision, (ii) investigate the receptor sub-type specificity of any observed effect, and (iii) consider an interaction with the dopamine (DA) system. Prior to the period of normal vision GABAergic agents were applied either (i) individually, (ii) in combination with other GABAergic agents (an agonist with an antagonist), or (iii) in combination with DA agonists and antagonists. Water injections were given to groups not receiving drug treatments so that all experimental eyes received intravitreal injections. As shown previously, constant form-deprivation resulted in high myopia and when diffusers were removed for 2 h per day the period of normal vision greatly reduced the FDM that developed. GABA agonists inhibited the protective effect of normal vision whereas antagonists had the opposite effect. GABAA/C agonists and D2 DA antagonists when used in combination were additive in suppressing the protective effect of normal vision. A D2 DA agonist restored some of the protective effect of normal vision that was inhibited by a GABA agonist (muscimol). The protective effect of normal vision against form-deprivation is modifiable by both the GABAergic and DAergic pathways.

Differentiation of isomeric N-glycan structures by normal-phase liquid chromatography-MALDI-TOF/TOF tandem mass spectrometry

The detailed characterization of protein N-glycosylation is very demanding given the many different glycoforms and structural isomers that can exist on glycoproteins. Here we report a fast and sensitive method for the extensive structure elucidation of reducing-end labeled N-glycan mixtures using a combination of capillary normal-phase HPLC coupled off-line to matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) and TOF/TOF-MS/MS. Using this method, isobaric N-glycans released from honey bee phospholipase A2 and Arabidopsis thaliana glycoproteins were separated by normal-phase chromatography and subsequently identified by key fragment ions in the MALDI-TOF/TOF tandem mass spectra. In addition, linkage and branching information were provided by abundant cross-ring and "elimination" fragment ions in the MALDI-CID spectra that gave extensive structural information. Furthermore, the fragmentation characteristics of N-glycans reductively aminated with 2-aminobenzoic acid and 2-aminobenzamide were compared. The identification of N-glycans containing 3-linked core fucose was facilitated by distinctive ions present only in the MALDI-CID spectra of 2-aminobenzoic acid-labeled oligosaccharides. To our knowledge, this is the first MS/MS-based technique that allows confident identification of N-glycans containing 3-linked core fucose, which is a major allergenic determinant on insect and plant glycoproteins.

Training-free probability models for whole-image based place recognition

Whole-image descriptors such as GIST have been used successfully for persistent place recognition when combined with temporal filtering or sequential filtering techniques. However, whole-image descriptor localization systems often apply a heuristic rather than a probabilistic approach to place recognition, requiring substantial environmental-specific tuning prior to deployment. In this paper we present a novel online solution that uses statistical approaches to calculate place recognition likelihoods for whole-image descriptors, without requiring either environmental tuning or pre-training. Using a real world benchmark dataset, we show that this method creates distributions appropriate to a specific environment in an online manner. Our method performs comparably to FAB-MAP in raw place recognition performance, and integrates into a state of the art probabilistic mapping system to provide superior performance to whole-image methods that are not based on true probability distributions. The method provides a principled means for combining the powerful change-invariant properties of whole-image descriptors with probabilistic back-end mapping systems without the need for prior training or system tuning.

Fasting increases serum bilirubin levels in clinically normal, healthy males but not females : a retrospective study from phase I clinical trial participants

Aim: To examine if fasting affects serum bilirubin levels in clinical healthy males and females. Methods: We utilised retrospective data from phase 1 clinical trials where blood was collected in either a fed or fasting state at screening and pre-dosing time points and analysed for total bilirubin levels as per standard clinical procedures. Participants were clinically healthy males (n = 105) or females (n = 30) aged 18 to 48 inclusive who participated in a phase 1 clinical trial in 2012 or 2013. Results: We found a statistically significant increase in total serum bilirubin levels in fasting males as compared to non-fasting males. The fasting time correlated positively with increased bilirubin levels. The age of the healthy males did not correlate with their fasting bilirubin level. We found no correlation between fasting and bilirubin levels in clinically normal females. Conclusions: The recruitment and screening of volunteers for a clinical trial is a time-consuming and expensive process. This study clearly demonstrates that testing for serum bilirubin should be conducted on non-fasting male subjects. If fasting is required, then participants should not be excluded from a trial based on an elevated serum bilirubin that is deemed non-clinically significant.

Demand-side response model to avoid spike of electricity price

The aim of this work is to develop a demand-side-response model, which assists electricity consumers exposed to the market price to independently and proactively manage air-conditioning peak electricity demand. The main contribution of this research is to show how consumers can optimize the energy cost caused by the air conditioning load considering to several cases e.g. normal price, spike price, and the probability of a price spike case. This model also investigated how air-conditioning applies a pre-cooling method when there is a substantial risk of a price spike. The results indicate the potential of the scheme to achieve financial benefits for consumers and target the best economic performance for electrical generation distribution and transmission. The model was tested with Queensland electricity market data from the Australian Energy Market Operator and Brisbane temperature data from the Bureau of Statistics regarding hot days from 2011 to 2012.

Do prediction markets produce well-calibrated probability forecasts?

This article presents new theoretical and empirical evidence on the forecasting ability of prediction markets. We develop a model that predicts that the time until expiration of a prediction market should negatively affect the accuracy of prices as a forecasting tool in the direction of a ‘favourite/longshot bias’. That is, high-likelihood events are underpriced, and low-likelihood events are over-priced. We confirm this result using a large data set of prediction market transaction prices. Prediction markets are reasonably well calibrated when time to expiration is relatively short, but prices are significantly biased for events farther in the future. When time value of money is considered, the miscalibration can be exploited to earn excess returns only when the trader has a relatively low discount rate.

Using the quantum probability ranking principle to rank interdependent documents

A known limitation of the Probability Ranking Principle (PRP) is that it does not cater for dependence between documents. Recently, the Quantum Probability Ranking Principle (QPRP) has been proposed, which implicitly captures dependencies between documents through “quantum interference”. This paper explores whether this new ranking principle leads to improved performance for subtopic retrieval, where novelty and diversity is required. In a thorough empirical investigation, models based on the PRP, as well as other recently proposed ranking strategies for subtopic retrieval (i.e. Maximal Marginal Relevance (MMR) and Portfolio Theory(PT)), are compared against the QPRP. On the given task, it is shown that the QPRP outperforms these other ranking strategies. And unlike MMR and PT, one of the main advantages of the QPRP is that no parameter estimation/tuning is required; making the QPRP both simple and effective. This research demonstrates that the application of quantum theory to problems within information retrieval can lead to significant improvements.

Developing the quantum probability ranking principle

In this work, we summarise the development of a ranking principle based on quantum probability theory, called the Quantum Probability Ranking Principle (QPRP), and we also provide an overview of the initial experiments performed employing the QPRP. The main difference between the QPRP and the classic Probability Ranking Principle, is that the QPRP implicitly captures the dependencies between documents by means of quantum interference". Subsequently, the optimal ranking of documents is not based solely on documents' probability of relevance but also on the interference with the previously ranked documents. Our research shows that the application of quantum theory to problems within information retrieval can lead to consistently better retrieval effectiveness, while still being simple, elegant and tractable.

Normal human mammary epithelial cells spontaneously escape senescence and acquire genomic changes

Senescence and genomic integrity are thought to be important barriers in the development of malignant lesions. Human fibroblasts undergo a limited number of cell divisions before entering an irreversible arrest, called senescence. Here we show that human mammary epithelial cells (HMECs) do not conform to this paradigm of senescence. In contrast to fibroblasts, HMECs exhibit an initial growth phase that is followed by a transient growth plateau (termed selection or M0; refs 3-5), from which proliferative cells emerge to undergo further population doublings (approximately 20-70), before entering a second growth plateau (previously termed senescence or M1; refs 4-6). We find that the first growth plateau exhibits characteristics of senescence but is not an insurmountable barrier to further growth. HMECs emerge from senescence, exhibit eroding telomeric sequences and ultimately enter telomere-based crisis to generate the types of chromosomal abnormalities seen in the earliest lesions of breast cancer. Growth past senescent barriers may be a pivotal event in the earliest steps of carcinogenesis, providing many genetic changes that predicate oncogenic evolution. The differences between epithelial cells and fibroblasts provide new insights into the mechanistic basis of neoplastic transformation.

Integrated approach for diagnostics and prognostics of HP LNG pump based on health state probability estimation

Effective machine fault prognostic technologies can lead to elimination of unscheduled downtime and increase machine useful life and consequently lead to reduction of maintenance costs as well as prevention of human casualties in real engineering asset management. This paper presents a technique for accurate assessment of the remnant life of machines based on health state probability estimation technique and historical failure knowledge embedded in the closed loop diagnostic and prognostic system. To estimate a discrete machine degradation state which can represent the complex nature of machine degradation effectively, the proposed prognostic model employed a classification algorithm which can use a number of damage sensitive features compared to conventional time series analysis techniques for accurate long-term prediction. To validate the feasibility of the proposed model, the five different level data of typical four faults from High Pressure Liquefied Natural Gas (HP-LNG) pumps were used for the comparison of intelligent diagnostic test using five different classification algorithms. In addition, two sets of impeller-rub data were analysed and employed to predict the remnant life of pump based on estimation of health state probability using the Support Vector Machine (SVM) classifier. The results obtained were very encouraging and showed that the proposed prognostics system has the potential to be used as an estimation tool for machine remnant life prediction in real life industrial applications.

Probability and story-telling : normative and descriptive models of juridical proof

The operation of the law rests on the selection of an account of the facts. Whether this involves prediction or postdiction, it is not possible to achieve certainty. Any attempt to model the operation of the law completely will therefore raise questions of how to model the process of proof. In the selection of a model a crucial question will be whether the model is to be used normatively or descriptively. Focussing on postdiction, this paper presents and contrasts the mathematical model with the story model. The former carries the normative stamp of scientific approval, whereas the latter has been developed by experimental psychologists to describe how humans reason. Neil Cohen's attempt to use a mathematical model descriptively provides an illustration of the dangers in not clearly setting this parameter of the modelling process. It should be kept in mind that the labels 'normative' and 'descriptive' are not eternal. The mathematical model has its normative limits, beyond which we may need to critically assess models with descriptive origins.

Collagen-induced activation of the Mr. 72,000 type IV collagenase in normal and malignant human fibroblastoid cells

Although the Mr. 72,000 type IV collagenase (matrix metalloproteinase 2) has been implicated in a variety of normal and pathogenic processes, its activation mechanism in vivo is unclear. We have found that fibroblasts from normal and neoplastic human breast, as well as the sarcomatous human Hs578T and HT1080 cell lines, activate endogenous matrix metalloprotease 2 when cultured on type I collagen gels, but not on plastic, fibronectin, collagen IV, gelatin, matrigel, or basement membrane-like HR9 cell matrix. This activation is monitored by the zymographic detection of Mr 59,000 and/or Mr 62,000 species, requires 2-3 days of culture on vitrogen to manifest, is cycloheximide inhibitable, and correlates with an arborized morphology. A similar activation pattern was seen in these cells in response to Concanavalin A but not transforming growth factor β or 12-O-tetradecanoylphorbol-13-acetate. The interstitial matrix may thus play an important role in regulating matrix degradation in vivo.

Epithelial-mesenchymal interconversions in normal ovarian surface epithelium and ovarian carcinomas : an exception to the norm

Cancer that arises from the ovarian surface epithelium (OSE) accounts for approximately 90% of human ovarian cancer, and is the fourth leading cause of cancer-related deaths among women in developed countries. The pathophysiology of epithelial ovarian cancer is still unclear because of the poor understanding of the complex nature of its development and the unusual mechanism(s) of disease progression. Recent studies have reported epithelial-mesenchymal transition (EMT) in cultured OSE and ovarian cancer cell lines in response to various stimuli, but our understanding of the importance of these observations for normal ovarian physiology and cancer progression is not well established. This review highlights the current literature on EMT-associated events in normal OSE and ovarian cancer cell lines, and discusses its implication for normal ovarian function as well as acquisition of neoplastic phenotypes. The pathological changes in OSE in response to EMT during neoplastic transformation and the contribution of hormones, growth factors, and cytokines that initiate and drive EMT to sustain normal ovarian function, as well as cancer development and progression are also discussed. Finally, emphasis is placed on the clinical implications of EMT and potential therapeutic opportunities that may arise from these observations have been proposed.