Comparison and Evaluation of 2,4-Dinitrofluorobenzene Induced Allergic Contact Dermatitis Model in Mice

Objectives 2,4-Dinitrofluorobenzene (DNFB) induced allergic contact dermatitis model is widely used in the research of inflammation, immune response and pruritus. However, there are several modeling cycles of DNFB model in many literatures, which brings some confusion for choice in the experiments. Here, we established two-weeks and five-weeks models of DNFB and aimed to compare and evaluate them. Methods Two-week and five-week DNFB models were established in male SPF C57BL/6 mice. Results The results showed that the scratching bouts of the ACD mice in two groups both significantly increased. Following the modeling process, the skin of the neck and back of the modeling site of the ACD mice in two-weeks group gradually appeared erythema, edema, ulceration, scabbing, scaling and dryness. The skin surface features of ACD mice in five-weeks group obviously showed erythema, edema, ulceration, scabbing, scaling, re-scabbing, re-scaling, harden and dryness.The whole modeling process are both accompanied by severe scratching reaction after the skin repeated exposure to DNFB. Moreover, the results of hematoxylin-eosin (HE) staining showed that the two modeling methods both had thickened epidermis (p < 0.001) and hyperkeratosis. The toluidine blue (TB) staining revealed obvious inflammatory cell infiltration (p < 0.0001) in two groups. Conclusion In our opinion, the two modeling methods both are feasible. The two-weeks ACD model had a shorter modeling period, and while the 5-weeks model could have enough time to observe the effect of drug. Our results provided further experimental basis and evidence for animal models of skin pruritus and inflammation.

Dependent structure and risk analysis of S&P 500 Index's continuously rising returns and continuously falling returns

PurposeThe stock market price time series can be divided into two processes: continuously rising and continuously falling. The authors can effectively prevent the stock market from crashing by accurately estimating the risk on continuously rising returns (CRR) and continuously falling returns (CFR).Design/methodology/approachThe authors add an exogenous variable into Log-autoregressive conditional duration (Log-ACD) model, and then apply our extended Log-ACD model and Archimedean copula to estimate the marginal distribution and conditional distribution of CRR and CFR. Plus, the authors analyze the conditional value at risk (CVaR) and present back-test results of the CVaR. The back-test shows that our proposed risk estimation method has a good estimation power for the risk of the CRR and CFR, especially the downside risk. In addition, the authors detect whether the dependent structure between the CRR and CFR changes using the change point test method.FindingsThe empirical results indicate that there is no change point here, suggesting that the results on the dependent structure and risk analysis mentioned above are stable. Therefore, major financial events will not affect the dependent structure here. This is consistent with the point that the CRR and CFR can be analyzed to obtain the trend of stock returns from a more macro perspective than daily stock returns scholars usually study.Practical implicationsThe risk estimation method of this paper is of great significance in understanding stock market risk and can provide corresponding valuable information for investment advisors and public policy regulators.Originality/valueThe authors defined a new stock returns, CRR and CFR, since it is difficult to analyze and predict the trend of stock returns according to daily stock returns because of the small autocorrelation among daily stock returns.

Improved ACD-Based Financial Trade Durations Prediction Leveraging LSTM Networks and Attention Mechanism

The liquidity risk factor of security market plays an important role in the formulation of trading strategies. A more liquid stock market means that the securities can be bought or sold more easily. As a sound indicator of market liquidity, the transaction duration is the focus of this study. We concentrate on estimating the probability density function p Δ t i + 1 | G i , where Δ t i + 1 represents the duration of the (i + 1)-th transaction and G i represents the historical information at the time when the (i + 1)-th transaction occurs. In this paper, we propose a new ultrahigh-frequency (UHF) duration modelling framework by utilizing long short-term memory (LSTM) networks to extend the conditional mean equation of classic autoregressive conditional duration (ACD) model while retaining the probabilistic inference ability. And then, the attention mechanism is leveraged to unveil the internal mechanism of the constructed model. In order to minimize the impact of manual parameter tuning, we adopt fixed hyperparameters during the training process. The experiments applied to a large-scale dataset prove the superiority of the proposed hybrid models. In the input sequence, the temporal positions which are more important for predicting the next duration can be efficiently highlighted via the added attention mechanism layer.

Anti-allergy Effect of Sulfated Polysaccharide from Sargassum polycystum on Dinitrofluorobenzene Induced Allergic Contact Dermatitis in Mice

Background: Sargassum polycystum C. Agardh has potent antioxidant and anti-inflammatory properties. However, its anti-allergic effect has not yet been reported. In this study, we investigated the anti-allergic effects of sulfated polysaccharide of S. polycystum (SPSP) in Dinitrofluorobenzene (DNFB)- induced allergic contact dermatitis animal model. Methods: SPSP was extracted through hot water extraction method and was subjected to compositional analyses. For the allergic contact dermatitis (ACD) model, symptoms were induced by the topical application of 0.5% DNFB on the shaved ventral skin of mice. SPSP (500, 1000, and 2000 mg/kg) and Prednisolone were orally administered for seven days after sensitization. Elicitation was performed seven days later with 0.2% DNFB. After this, ear thickness was measured at baseline and 24 hours post elicitation using a dial thickness gauge. Serum of mice was obtained 24 hours post elicitation, and the level of IFNγ and TNF Results: SPSP afforded 33.6% carbohydrates, 23.7% sulfate, 7.5% protein, and 1.5% uronic acid contents. SPSP inhibited the ear swelling and cytokines (IFNγ and TNF Conclusion: These findings showed that the sulfated polysaccharide from S. polycytum is a potential natural source to treat Allergic Contact Dermatitis. The effect is attributed to polysaccharide-protein complex present in the extract, but further studies are needed to establish the exact mechanism of action of SPSP in the treatment of the disease.

Development of Commute Mode Choice Model by Integrating Actively and Passively Collected Travel Data

Travel data collection, which is necessary for travel demand modeling, is always of great concern to modelers due to its huge cost and effort when a large sample is required to achieve satisfactory model precisions. In this paper, travel data collected based on a survey questionnaire and travelers’ active participation are called actively collected data (ACD). It is difficult to guarantee absolute randomness and unbiasedness in a sample when the ACD are collected due to self-selection issues. The aim of this study is to improve the model precision at low cost by using passively collected data (PCD), such as in-vehicle GPS data and transit smart card data, to release sample size restriction and reduce sampling bias of ACD in a commute mode choice model. In an empirical study, a multinomial-logit-based joint model is developed for commute mode choice by integrating ACD and PCD based on the choice-based sampling theory. A comprehensive set of explanatory variables are specified through data integration. Both simulation and empirical results show great improvement in coefficient precisions in the proposed joint model, relative to those in the ACD model and PCD model. In this study, ACD and PCD samples of Shanghai are integrated in the joint model so that several significantly influential level-of-service attributes are identified for auto, rail, and bus modes, and their impacts on commute mode choice probabilities are quantified. The findings can aid in better evaluating the program to improve the existing transit system.

Bank failure intensity modeling: an ACD model approach

PurposeThe purpose of this study is to employ a duration-based approach to model the inter-arrival times of bank failures in the US banking system for the period of 1934-2014, in line with the suggestions of Focardi and Fabozzi (2005), who used a similar model for explaining contagion in credit portfolios.Design/methodology/approachConditional duration models that allow duration between bank failures to depend linearly or nonlinearly on its past history are estimated and evaluated.FindingsThe authors find evidence of strong persistence along with nonmonotonic hazard rates, which imply a financial contagion pattern, according to which a high frequency of bank failures generates turbulence, which shortly after leads to additional fails, whereas prolonged periods without abnormal events signify the absence of contagious dependence, which increases the relative periods between bank failure appearance. Further, the authors obtain statistically significant results when they allow duration to depend linearly on past information variables that capture systemic bank crisis factors along with stock and bond market effects.Originality/valueThe originality of this study consists in proposing a new time series approach for the prediction of bank probability of default by incorporating a default-risk contagion mechanism. As contagious bank failures are a key topic in macroprudential supervision, this study could be of value for supervisory authorities in setting pro-active actions and tightening regulatory measures.

Study on the Duration of Market Microstructure Theory

This paper starts from the theory of market microstructure, by researching in the development of market microstructure and the theoretical framework, it is found that the proposed duration model is of great significance to market participants. Therefore, based on the theory of market microstructure, this paper summarizes and analyzes the related theories and applications of ACD model.