A Novel Apex-Time Network for Cross-Dataset Micro-Expression Recognition

The automatic recognition of micro-expression has been boosted ever since the successful introduction of deep learning approaches. As researchers working on such topics are moving to learn from the nature of micro-expression, the practice of using deep learning techniques has evolved from processing the entire video clip of micro-expression to the recognition on apex frame. Using the apex frame is able to get rid of redundant video frames, but the relevant temporal evidence of micro-expression would be thereby left out. This paper proposes a novel Apex-Time Network (ATNet) to recognize micro-expression based on spatial information from the apex frame as well as on temporal information from the respective-adjacent frames. Through extensive experiments on three benchmarks, we demonstrate the improvement achieved by learning such temporal information. Specially, the model with such temporal information is more robust in cross-dataset validations.Comment: 6 pages, 3 figures, 3 tables, code available, accepted in ACII 201

Exploiting the full power of temporal gene expression profiling through a new statistical test: Application to the analysis of muscular dystrophy data

Background: The identification of biologically interesting genes in a temporal expression profiling dataset is challenging and complicated by high levels of experimental noise. Most statistical methods used in the literature do not fully exploit the temporal ordering in the dataset and are not suited to the case where temporal profiles are measured for a number of different biological conditions. We present a statistical test that makes explicit use of the temporal order in the data by fitting polynomial functions to the temporal profile of each gene and for each biological condition. A Hotelling T2-statistic is derived to detect the genes for which the parameters of these polynomials are significantly different from each other. Results: We validate the temporal Hotelling T2-test on muscular gene expression data from four mouse strains which were profiled at different ages: dystrophin-, beta-sarcoglycan and gammasarcoglycan deficient mice, and wild-type mice. The first three are animal models for different muscular dystrophies. Extensive biological validation shows that the method is capable of finding genes with temporal profiles significantly different across the four strains, as well as identifying potential biomarkers for each form of the disease. The added value of the temporal test compared to an identical test which does not make use of temporal ordering is demonstrated via a simulation study, and through confirmation of the expression profiles from selected genes by quantitative PCR experiments. The proposed method maximises the detection of the biologically interesting genes, whilst minimising false detections. Conclusion: The temporal Hotelling T2-test is capable of finding relatively small and robust sets of genes that display different temporal profiles between the conditions of interest. The test is simple, it can be used on gene expression data generated from any experimental design and for any number of conditions, and it allows fast interpretation of the temporal behaviour of genes. The R code is available from V.V. The microarray data have been submitted to GEO under series GSE1574 and GSE3523

Temporal expression normalisation in natural language texts

Automatic annotation of temporal expressions is a research challenge of great interest in the field of information extraction. In this report, I describe a novel rule-based architecture, built on top of a pre-existing system, which is able to normalise temporal expressions detected in English texts. Gold standard temporally-annotated resources are limited in size and this makes research difficult. The proposed system outperforms the state-of-the-art systems with respect to TempEval-2 Shared Task (value attribute) and achieves substantially better results with respect to the pre-existing system on top of which it has been developed. I will also introduce a new free corpus consisting of 2822 unique annotated temporal expressions. Both the corpus and the system are freely available on-line.Comment: 7 pages, 1 figure, 5 table

M-quantile regression analysis of temporal gene expression data

In this paper, we explore the use of M-regression and M-quantile coefficients to detect statistical differences between temporal curves that belong to different experimental conditions. In particular, we consider the application of temporal gene expression data. Here, the aim is to detect genes whose temporal expression is significantly different across a number of biological conditions. We present a new method to approach this problem. Firstly, the temporal profiles of the genes are modelled by a parametric M-quantile regression model. This model is particularly appealing to small-sample gene expression data, as it is very robust against outliers and it does not make any assumption on the error distribution. Secondly, we further increase the robustness of the method by summarising the M-quantile regression models for a large range of quantile values into an M-quantile coefficient. Finally, we employ a Hotelling T2-test to detect significant differences of the temporal M-quantile profiles across conditions. Simulated data shows the increased robustness of M-quantile regression methods over standard regression methods. We conclude by using the method to detect differentially expressed genes from time-course microarray data on muscular dystrophy

Three-dimensional morphology and gene expression in the Drosophila blastoderm at cellular resolution II: dynamics.

BackgroundTo accurately describe gene expression and computationally model animal transcriptional networks, it is essential to determine the changing locations of cells in developing embryos.ResultsUsing automated image analysis methods, we provide the first quantitative description of temporal changes in morphology and gene expression at cellular resolution in whole embryos, using the Drosophila blastoderm as a model. Analyses based on both fixed and live embryos reveal complex, previously undetected three-dimensional changes in nuclear density patterns caused by nuclear movements prior to gastrulation. Gene expression patterns move, in part, with these changes in morphology, but additional spatial shifts in expression patterns are also seen, supporting a previously proposed model of pattern dynamics based on the induction and inhibition of gene expression. We show that mutations that disrupt either the anterior/posterior (a/p) or the dorsal/ventral (d/v) transcriptional cascades alter morphology and gene expression along both the a/p and d/v axes in a way suggesting that these two patterning systems interact via both transcriptional and morphological mechanisms.ConclusionOur work establishes a new strategy for measuring temporal changes in the locations of cells and gene expression patterns that uses fixed cell material and computational modeling. It also provides a coordinate framework for the blastoderm embryo that will allow increasingly accurate spatio-temporal modeling of both the transcriptional control network and morphogenesis

Temporal and spatial expression of Arabidopsis gene homologs control daylength adaptation and bulb formation in onion (Allium cepa L.)

Genetic studies aimed at onion improvement have been limited because of high heterozygosity, a very large genome size with a high level of repetitive DNA and a biennial life cycle. Onion bulb initiation is daylength-dependent, which places a significant barrier to adapting new varieties for growth at different latitudes. Compared to the photoperiodic regulation of flowering, relatively little is known about genetic regulation of the bulbing process. This study aims to identify the role of gene sequences involved in daylength-regulated bulb formation and tissue specific expression of onion. A comprehensive set of developmental and spatial quantitative mRNA expression experiments were carried out to investigate expression of onion FLOWERING LOCUS T (AcFT), LEAFY (AcLFY) and GIBBERELLIN-3 OXIDASE (GA3ox1) during the bulbing response. Bulbing ratios were used to measure the response of onion plants under long day (LD) and short day (SD) conditions. AcFT1 was expressed in LD, which induces bulb formation, while AcFT4 was expressed in SD, which inhibits bulb formation. AcFT5 and AcFT6 were expressed in LD and might also be involved in bulb formation itself. All AcFT, AcLFY and GA3ox1 genes showed distinctive patterns of tissue specific expression in onion, with AcFT genes found primarily in the sites of perception in the leaf and LFY in the basal tissues, the site of response. The results are consistent with AcFT1 expression being the signal for LD-induced bulb initiation and AcFT4, being involved in suppressing bulbing in SD

The Temporal Expression of Adipokines During Spinal Fusion

Background Context Adipokines are secreted by white adipose tissue and have been associated with fracture healing. Our goal was to report the temporal expression of adipokines during spinal fusion in an established rabbit model. Purpose Our goal was to report the temporal expression of adipokines during spinal fusion in an established rabbit model. Study Design The study design included a laboratory animal model. Methods New Zealand white rabbits were assigned to either sham surgery (n=2), unilateral posterior spinal fusion (n=14), or bilateral posterior spinal fusion (n=14). Rabbits were euthanized 1–6 and 10 weeks out from surgery. Fusion was evaluated by radiographs, manual palpation, and histology. Reverse transcription-polymerase chain reaction on the bone fusion mass catalogued the gene expression of leptin, adiponectin, resistin, and vascular endothelial growth factor (VEGF) at each time point. Results were normalized to the internal control gene, glyceraldehyde-3-phosphate dehydrogenase (GAPDH) (2^ΔCt), and control bone sites (2^ΔΔCt). Quantitative data were analyzed by two-factor analysis of variance (p\u3c.05). Results Manual palpation scores, radiograph scores, and histologic findings showed progression of boney fusion over time (p Conclusions Leptin expression is likely associated with the maturation phase of bone fusion. Adiponectin and resistin may play a role early on during the fusion process. Our results suggest that leptin expression may be upstream of VEGF expression during spinal fusion, and both appear to play an important role in bone spinal fusion