Quantification of the influence of drugs on zebrafish larvae swimming kinematics and energetics

The use of zebrafish larvae has aroused wide interest in the medical field for its potential role in the development of new therapies. The larvae grow extremely quickly and the embryos are nearly transparent which allows easy examination of its internal structures using fluorescent imaging techniques. Medical treatment of zebrafish larvae can directly influence its swimming behaviours. These behaviour changes are related to functional changes of central nervous system and transformations of the zebrafish body such as muscle mechanical power and force variation, which cannot be measured directly by pure experiment observation. To quantify the influence of drugs on zebrafish larvae swimming behaviours and energetics, we have developed a novel methodology to exploit intravital changes based on observed zebrafish locomotion. Specifically, by using an in-house MATLAB code to process the recorded live zebrafish swimming video, the kinematic locomotion equation of a 3D zebrafish larvae was obtained, and a customised Computational Fluid Dynamics tool was used to solve the fluid flow around the fish model which was geometrically the same as experimentally tested zebrafish. The developed methodology was firstly verified against experiment, and further applied to quantify the fish internal body force, torque and power consumption associated with a group of normal zebrafish larvae vs. those immersed in acetic acid and two neuroactive drugs. As indicated by our results, zebrafish larvae immersed in 0.01% acetic acid display approximately 30% higher hydrodynamic power and 10% higher cost of transport than control group. In addition, 500 μM diphenylhydantoin significantly decreases the locomotion activity for approximately 50% lower hydrodynamic power, whereas 100 mg/L yohimbine has not caused any significant influences on 5 dpf zebrafish larvae locomotion. The approach has potential to evaluate the influence of drugs on the aquatic animal’s behaviour changes and thus support the development of new analgesic and neuroactive drugs

Modeling the gas-solid flow in diameter-changing fluidized beds

Gas-solid diameter-changing fluidized beds are usually used as either a transition section between the two parts with various diameters in circulating fluidized bed systems or a type of independent reactor in many industrial processes. This study focuses on the multiscale modeling of the former including tapered and inverted tapered structures, whose computational complexities mainly lie in addressing the problems related to the continuous variations of superficial gas and solid velocities with height as well as much more significant wall effect in diameter-changing fluidized beds than that in constant-diameter ones. By utilizing the energy-minimization multi-scale (EMMS) theory, the steady-state modeling of this type of reactor is performed to compute the spatial heterogeneous distributions of hydrodynamic parameters. A coarse-grained discrete particle method (DPM) defined by the EMMS model is also deployed for the high resolution simulation of gas-solid diameter-changing fluidized beds, in order to gain an insight into the underlying mechanisms involved in the variation of this heterogeneity with operating conditions. Both the axial and radial heterogeneous distributions of hydrodynamic parameters such as solid velocity and concentration in this type of reactor are firstly predicted in this study, which provides a quantitative reference for the design and scale-up of the tapered or inverted tapered fluidized beds. This study can be expected to further enrich the theory of full-loop modeling of complex gas-solid processes with various geometries and sizes

Concept Design and Analysis of a Novel Steamer-Filling Robot

Steamer-filling operation is a crucially important process in the liquor-making process, directly related to liquor yield and liquor quality. But so far, this process is still dominated by manual operation. In view of working environment and labor shortages in this industry, a novel exclusive steamer-filling robot is proposed in this paper. Firstly, the steamer-filling operation process is described, and the structure composition and function realization of the robot are particularly introduced. Secondly, the kinematics problems in terms of position analysis and workspace of the robot are analyzed in detail. Thirdly, experimental analyses are made to prove the validity and efficiency of the robot system. Finally, some conclusions and the future developing direction are prescribed

Bayesian Analysis of Latent Trait Hierarchical Models for Multiple Binary Outcomes in Cluster Randomized Clinical Trials

In clinical trials, multiple endpoints for treatment efficacy often are obtained, and in addition, data may be collected hierarchically. Statistical analyses become very challenging for this multidimensional hierarchical data, particularly with data collected at more than two levels. We propose a latent variable approach to assess an intervention effect on multiple binary outcomes from three-level hierarchical data. This approach incorporates the correlation structure into one or more latent outcomes, and simultaneously regresses the latent outcome(s) on observed covariates. Random effects are included to model the hierarchical structure. Parameters estimation is done using a fully Bayesian approach implemented in WinBUGS. We first illustrate the approach in a cluster randomized clinical trial of three interventions to improve the processes of care for outpatients with pneumonia. Four binary outcomes are collected at the patient-level and clustered at the provider and clinic site levels. Simulation studies are conducted to check the algorithm and computational implementation. Then, we extend the one latent trait model to a two-latent trait model using eight outcomes from both outpatient and inpatient care. This latent modeling approach provides a comprehensive way to analyze multivariate hierarchical data. The method not only allows assessment of intervention effects with respect to multiple outcomes, but also assesses the relationship between outcomes, identifies those outcomes that carry the most information about the latent trait(s), and provides a summary measure of the "quality of care" at each clinical site.This work extends existing methods to model multivariate binary endpoints in a cluster-randomized clinical trial. The public health significance of this study is the potential usefulness of this approach to quantify intervention (or exposure) effects with regard to multiple outcomes in hierarchical data setting, which arises frequently in medical and epidemiologic studies

A colour preference technique to evaluate acrylamide-induced toxicity in zebrafish

The zebrafish has become a commonly used vertebrate model for toxicity assessment, of particular relevance to the study of toxic effects on the visual system because of the structural similarities shared by zebrafish and human retinae. In this article we present a colour preference-based technique that, by assessing the functionality of photoreceptors, can be used to evaluate the effects of toxicity on behaviour. A digital camera was used to record the locomotor behaviour of individual zebrafish swimming in a water tank consisting of two compartments separated by an opaque perforated wall through which the fish could pass. The colour of the lighting in each compartment could be altered independently (producing distinct but connected environments of white, red or blue) to allow association of the zebrafish's swimming behaviour with its colour preference. The functionality of the photoreceptors was evaluated based on the ability of the zebrafish to sense the different colours and to swim between the compartments. The zebrafish tracking was carried out using our algorithm developed with MATLAB. We found that zebrafish preferred blue illumination to white, and white illumination to red. Acute treatment with acrylamide (2 mM for 36 h) resulted in a marked reduction in locomotion and a concomitant loss of colour-preferential swimming behaviour. Histopathological examination of acrylamide-treated zebrafish eyes showed that acrylamide exposure had caused retinal damage. The colour preference tracking technique has applications in the assessment of neurodegenerative disorders, as a method for preclinical appraisal of drug efficacy and for behavioural evaluation of toxicity

Exploiting Spatial-temporal Correlations for Video Anomaly Detection

Video anomaly detection (VAD) remains a challenging task in the pattern recognition community due to the ambiguity and diversity of abnormal events. Existing deep learning-based VAD methods usually leverage proxy tasks to learn the normal patterns and discriminate the instances that deviate from such patterns as abnormal. However, most of them do not take full advantage of spatial-temporal correlations among video frames, which is critical for understanding normal patterns. In this paper, we address unsupervised VAD by learning the evolution regularity of appearance and motion in the long and short-term and exploit the spatial-temporal correlations among consecutive frames in normal videos more adequately. Specifically, we proposed to utilize the spatiotemporal long short-term memory (ST-LSTM) to extract and memorize spatial appearances and temporal variations in a unified memory cell. In addition, inspired by the generative adversarial network, we introduce a discriminator to perform adversarial learning with the ST-LSTM to enhance the learning capability. Experimental results on standard benchmarks demonstrate the effectiveness of spatial-temporal correlations for unsupervised VAD. Our method achieves competitive performance compared to the state-of-the-art methods with AUCs of 96.7%, 87.8%, and 73.1% on the UCSD Ped2, CUHK Avenue, and ShanghaiTech, respectively.Comment: This paper is accepted at IEEE 26TH International Conference on Pattern Recognition (ICPR) 202

A Ligation-PCR Approach for Generating Gene Replacement Constructs in Magnaporthe grisea

The conventional approach for generating gene replacement constructs involves several sequence-specific cloning steps and is time-consuming. A ligation-PCR approach was developed to efficiently generate gene replacement constructs. Two vectors useful for this ligation-PCR approach and another vector suitable for improving the efficiency of knockout mutant screens were constructed

Association between ALDH2 Glu504Lys polymorphism and colorectal cancer risk: a meta-analysis.

Background: The findings from studies on the relationship between aldehyde dehydrogenases(ALDH) gene Glu504Lys polymorphism and colorectal cancer(CRC) were inconsistent. Objectives: The aim of this meta-analysis was to assess ALDH gene Glu504Lys polymorphism and CRC risk. Methods: All of the relevant studies were identified from PubMed and Embase database. Statistical analyses were conducted with STATA 12.0 software.Odds ratio (OR) with 95% confidence interval (CI) values were applied to evaluate the strength of the association. Nine studies with 2779 cases and 4533 controls were included. Results: No significant variation in CRC risk was detected in any of the genetic models overall. To explore the sources of heterogeneity,we performed further sub-group analyses by ethnicity and quality assessment of these studies.In the sub-group analysis by race,significant associations between ALDH gene Glu504Lys polymorphism and CRC risk were found in China(Glu/ Lys vs Glu/Glu: OR = 0.70, 95%CI = 0.57\u20130.85; the dominant model: OR =0.69, 95%CI =0.48\u20130.98) and Japan(Lys/Lys vs Glu/Glu:OR =0.72, 95%CI =0.55\u20130.95). Conclusion: This meta-analysis suggests that the ALDH2 Glu504Lys polymorphism may be associated with susceptibility to CRC. Furthermore, large and well-designed studies are needed to confirm these conclusions