Dynamics of Advantageous Mutant Spread in Spatial Death-Birth and Birth-Death Moran Models

The spread of an advantageous mutation through a population is of fundamental interest in population genetics. While the classical Moran model is formulated for a well-mixed population, it has long been recognized that in real-world applications, the population usually has an explicit spatial structure which can significantly influence the dynamics. In the context of cancer initiation in epithelial tissue, several recent works have analyzed the dynamics of advantageous mutant spread on integer lattices, using the biased voter model from particle systems theory. In this spatial version of the Moran model, individuals first reproduce according to their fitness and then replace a neighboring individual. From a biological standpoint, the opposite dynamics, where individuals first die and are then replaced by a neighboring individual according to its fitness, are equally relevant. Here, we investigate this death-birth analogue of the biased voter model. We construct the process mathematically, derive the associated dual process, establish bounds on the survival probability of a single mutant, and prove that the process has an asymptotic shape. We also briefly discuss alternative birth-death and death-birth dynamics, depending on how the mutant fitness advantage affects the dynamics. We show that birth-death and death-birth formulations of the biased voter model are equivalent when fitness affects the former event of each update of the model, whereas the birth-death model is fundamentally different from the death-birth model when fitness affects the latter event.

Novel translational rat models of dopamine transporter deficiency

Dopamine （DA） is one of the brain＇s fundamental neurotransmitters. Despite the fact that the dopaminergic synapses constitute less than 1% of all brain synapses, DA is implicated in a number of critical physiological functions and in the pathogenesis of important psychiatric diseases such as schizophrenia, attention-deficit/hyperactivity disorder （ADHD）, Parkinson＇s disease （PD） and others.

Transplantation of tissue-engineered human corneal epithelium in limbal stem cell deficiency rabbit models

AIM: To evaluate the biological functions of tissue-engineered human corneal epithelium (TE-HCEP) by corneal transplantation in limbal stem cell deficiency (LSCD) rabbit models. METHODS: TE-HCEPs were reconstructed with DiI-labeled untransfected HCEP cells and denuded amniotic membrane (dAM) in air-liquid interface culture, and their morphology and structure were characterized by hematoxylin-eosin (HE) staining of paraffin-sections, immunohistochemistry and electron microscopy. LSCD models were established by mechanical and alcohol treatment of the left eyes of New Zealand white rabbits, and their eyes were transplanted with TE-HCEPs with dAM surface outside by lamellar keratoplasty (LKP). Corneal transparency, neovascularization, thickness, and epithelial integrality of both traumatic and post transplantation eyes were checked once a week by slit-lamp corneal microscopy, a corneal pachymeter, and periodic acid-Schiff (PAS) staining. At day 120 post surgery, the rabbits in each group were sacrificed and their corneas were examined by DiI label observation, HE staining, immunohistochemistry and electron microscopy. RESULTS: After cultured for 5 days on dAM, HCEP cells, maintaining keratin 3 expression, reconstructed a 6-7 layer TE-HCEP with normal morphology and structure. The traumatic rabbit corneas, entirely opaque, conjunctivalized and with invaded blood vessels, were used as LSCD models for TE-HCEP transplantation. After transplantation, obvious edema was not found in TE-HCEP-transplanted corneas which became more and more transparent, the invaded blood vessels reduced gradually throughout the monitoring period. The corneas decreased to normal thickness on day 25, while those of dAM eyes were over 575 mu m in thickness during the monitoring period. A 45 layer of epithelium consisting of TE-HCEP originated cells attached tightly to the anterior surface of stroma was reconstructed 120 days after TE-HCEP transplantation, which was similar to the normal control eye in morphology and structure. In contrast, intense corneal edema, turbid, invaded blood vessels were found in dAM eyes, and no multilayer epithelium was found but only a few scattered conjunctiva-like cells appeared. CONCLUSION: The TE-HCEP, with similar morphology and structure to those of innate HCEP, could reconstruct a multilayer corneal epithelium with normal functions in restoring corneal transparency and thickness of LSCD rabbits after transplantation. It may be a promising HCEP equivalent for clinical therapy of corneal epithelial disorders.

Therapeutic effect of secretome from TNF-αstimulated mesenchymal stem cells in an experimental model of corneal limbal stem cell deficiency

AIM:To explore the secretome efficacy in tumor necrosis factor(TNF)-αstimulated mouse mesenchymal stem cells(MSCs)in a murine model of corneal limbal alkali injury.METHODS:Corneal limbal stem cell deficiency(LSCD)was created in the eyes of male C57 mice.Concentrated conditioned medium from TNF-αstimulated MSCs(MSC-CMT)was applied topically for 4 wk,with basal medium and conditioned medium from MSCs as controls.Corneal opacification,corneal inflammatory response,and corneal neovascularization(NV)were evaluated.Corneal epithelial cell apoptosis,corneal conjunctivation,and inflammatory cell infiltration were assessed with TUNEL staining,CK3 and Muc-5 AC immunostaining,and CD11 b immunofluorescence staining,respectively.The effect of TSG-6 was further evaluated by knockdown with short hairpin RNA(sh RNA).RESULTS:Compared to the controls,topical administration of MSC-CMT significantly ameliorated the clinical symptoms of alkali-induced LSCD,with restrained corneal NV,reduced corneal epithelial cell apoptosis,and inhibition of corneal conjunctivation.In addition,MSC-CMT treatment significantly reduced CD11 b+inflammatory cell infiltration,and inhibited the expression of pro-inflammatory cytokines(IL-1β,TNF-αand IL-6).Furthermore,the promotion of corneal epithelial reconstruction by MSC-CMT was largely abolished by TSG-6 knockdown.CONCLUSION:Our study provides evidence that MSCCMT enhances the alleviation of corneal alkali injuries,partially through TSG-6-mediated anti-inflammatory protective mechanisms.MSC-CMT may serve as a potential strategy for treating corneal disorders.

Experimental Study on Observation of Hemorheologic Parameters of Hydrocortisone Caused Shen-Yang Deficiency in Rat Models

Objective:To explore the relationship between Shen deficiency and blood stasis. Methods: Using consecutive intramuscular injection of hydrocortisone to build Shen-yang deficiency model rats, and detect their hemorheological and biochemical parameters. Results: Comparison between the model group and control group showed that the in vitro thrombus significantly lengthened in the model group (P<0.05), the dry weight increased (P<0.01), hematocrit and whole blood viscosity under high sheared change lowered (P<0.05), blood glucose elevated (P<0.01), and RBC infiltration index, aggregation index increased (P close to 0.05). Conclusion: Under the condition of Shen-yang deficiency, although blood does not show such properties of blood stasis as being 'viscous, concentrated, coagulated and aggregated', partial change of hemorheology occurs, and it is liable to form thrombus, which proves that the Shen deficiency status is accompanied with the tendency of blood stasis.

A mouse model of weight-drop closed head injury:emphasis on cognitive and neurological deficiency

Traumatic brain injury（TBI） is a leading cause of death and disability in individuals worldwide.Producing a clinically relevant TBI model in small-sized animals remains fairly challenging.For good screening of potential therapeutics,which are effective in the treatment of TBI,animal models of TBI should be established and standardized.In this study,we established mouse models of closed head injury using the Shohami weight-drop method with some modifications concerning cognitive deficiency assessment and provided a detailed description of the severe TBI animal model.We found that 250 g falling weight from 2 cm height produced severe closed head injury in C57BL/6 male mice.Cognitive disorders in mice with severe closed head injury could be detected using passive avoidance test on day 7 after injury.Findings from this study indicate that weight-drop injury animal models are suitable for further screening of brain neuroprotectants and potentially are similar to those seen in human TBI.

Progressive fragmentation of granular assemblies within rockslides: Insights from discrete-continuous numerical modeling

Rock fragmentation plays a critical role in rock avalanches,yet conventional approaches such as classical granular flow models or the bonded particle model have limitations in accurately characterizing the progressive disintegration and kinematics of multi-deformable rock blocks during rockslides.The present study proposes a discrete-continuous numerical model,based on a cohesive zone model,to explicitly incorporate the progressive fragmentation and intricate interparticle interactions inherent in rockslides.Breakable rock granular assemblies are released along an inclined plane and flow onto a horizontal plane.The numerical scenarios are established to incorporate variations in slope angle,initial height,friction coefficient,and particle number.The evolutions of fragmentation,kinematic,runout and depositional characteristics are quantitatively analyzed and compared with experimental and field data.A positive linear relationship between the equivalent friction coefficient and the apparent friction coefficient is identified.In general,the granular mass predominantly exhibits characteristics of a dense granular flow,with the Savage number exhibiting a decreasing trend as the volume of mass increases.The process of particle breakage gradually occurs in a bottom-up manner,leading to a significant increase in the angular velocities of the rock blocks with increasing depth.The simulation results reproduce the field observations of inverse grading and source stratigraphy preservation in the deposit.We propose a disintegration index that incorporates factors such as drop height,rock mass volume,and rock strength.Our findings demonstrate a consistent linear relationship between this index and the fragmentation degree in all tested scenarios.

Theoretical investigation on axial cyclic performance of monopile in sands using interface constitutive models

Cyclic loads generated by environmental factors,such as winds,waves,and trains,will likely lead to performance degradation in pile foundations,resulting in issues like permanent displacement accumulation and bearing capacity attenuation.This paper presents a semi-analytical solution for predicting the axial cyclic behavior of piles in sands.The solution relies on two enhanced nonlinear load-transfer models considering stress-strain hysteresis and cyclic degradation in the pile-soil interaction.Model parameters are calibrated through cyclic shear tests of the sand-steel interface and laboratory geotechnical testing of sands.A novel aspect involves the meticulous formulation of the shaft loadtransfer function using an interface constitutive model,which inherently inherits the interface model’s advantages,such as capturing hysteresis,hardening,degradation,and particle breakage.The semi-analytical solution is computed numerically using the matrix displacement method,and the calculated values are validated through model tests performed on non-displacement and displacement piles in sands.The results demonstrate that the predicted values show excellent agreement with the measured values for both the static and cyclic responses of piles in sands.The displacement pile response,including factors such as bearing capacity,mobilized shaft resistance,and convergence rate of permanent settlement,exhibit improvements compared to non-displacement piles attributed to the soil squeezing effect.This methodology presents an innovative analytical framework,allowing for integrating cyclic interface models into the theoretical investigation of pile responses.

PAL-BERT:An Improved Question Answering Model

In the field of natural language processing(NLP),there have been various pre-training language models in recent years,with question answering systems gaining significant attention.However,as algorithms,data,and computing power advance,the issue of increasingly larger models and a growing number of parameters has surfaced.Consequently,model training has become more costly and less efficient.To enhance the efficiency and accuracy of the training process while reducing themodel volume,this paper proposes a first-order pruningmodel PAL-BERT based on the ALBERT model according to the characteristics of question-answering(QA)system and language model.Firstly,a first-order network pruning method based on the ALBERT model is designed,and the PAL-BERT model is formed.Then,the parameter optimization strategy of the PAL-BERT model is formulated,and the Mish function was used as an activation function instead of ReLU to improve the performance.Finally,after comparison experiments with traditional deep learning models TextCNN and BiLSTM,it is confirmed that PALBERT is a pruning model compression method that can significantly reduce training time and optimize training efficiency.Compared with traditional models,PAL-BERT significantly improves the NLP task’s performance.

Evolution and Prospects of Foundation Models: From Large Language Models to Large Multimodal Models

Since the 1950s,when the Turing Test was introduced,there has been notable progress in machine language intelligence.Language modeling,crucial for AI development,has evolved from statistical to neural models over the last two decades.Recently,transformer-based Pre-trained Language Models(PLM)have excelled in Natural Language Processing(NLP)tasks by leveraging large-scale training corpora.Increasing the scale of these models enhances performance significantly,introducing abilities like context learning that smaller models lack.The advancement in Large Language Models,exemplified by the development of ChatGPT,has made significant impacts both academically and industrially,capturing widespread societal interest.This survey provides an overview of the development and prospects from Large Language Models(LLM)to Large Multimodal Models(LMM).It first discusses the contributions and technological advancements of LLMs in the field of natural language processing,especially in text generation and language understanding.Then,it turns to the discussion of LMMs,which integrates various data modalities such as text,images,and sound,demonstrating advanced capabilities in understanding and generating cross-modal content,paving new pathways for the adaptability and flexibility of AI systems.Finally,the survey highlights the prospects of LMMs in terms of technological development and application potential,while also pointing out challenges in data integration,cross-modal understanding accuracy,providing a comprehensive perspective on the latest developments in this field.

An improved interval model updating method via adaptive Kriging models

Interval model updating(IMU)methods have been widely used in uncertain model updating due to their low requirements for sample data.However,the surrogate model in IMU methods mostly adopts the one-time construction method.This makes the accuracy of the surrogate model highly dependent on the experience of users and affects the accuracy of IMU methods.Therefore,an improved IMU method via the adaptive Kriging models is proposed.This method transforms the objective function of the IMU problem into two deterministic global optimization problems about the upper bound and the interval diameter through universal grey numbers.These optimization problems are addressed through the adaptive Kriging models and the particle swarm optimization(PSO)method to quantify the uncertain parameters,and the IMU is accomplished.During the construction of these adaptive Kriging models,the sample space is gridded according to sensitivity information.Local sampling is then performed in key subspaces based on the maximum mean square error(MMSE)criterion.The interval division coefficient and random sampling coefficient are adaptively adjusted without human interference until the model meets accuracy requirements.The effectiveness of the proposed method is demonstrated by a numerical example of a three-degree-of-freedom mass-spring system and an experimental example of a butted cylindrical shell.The results show that the updated results of the interval model are in good agreement with the experimental results.

The relationship between compartment models and their stochastic counterparts:A comparative study with examples of the COVID-19 epidemic modeling

Deterministic compartment models(CMs)and stochastic models,including stochastic CMs and agent-based models,are widely utilized in epidemic modeling.However,the relationship between CMs and their corresponding stochastic models is not well understood.The present study aimed to address this gap by conducting a comparative study using the susceptible,exposed,infectious,and recovered(SEIR)model and its extended CMs from the coronavirus disease 2019 modeling literature.We demonstrated the equivalence of the numerical solution of CMs using the Euler scheme and their stochastic counterparts through theoretical analysis and simulations.Based on this equivalence,we proposed an efficient model calibration method that could replicate the exact solution of CMs in the corresponding stochastic models through parameter adjustment.The advancement in calibration techniques enhanced the accuracy of stochastic modeling in capturing the dynamics of epidemics.However,it should be noted that discrete-time stochastic models cannot perfectly reproduce the exact solution of continuous-time CMs.Additionally,we proposed a new stochastic compartment and agent mixed model as an alternative to agent-based models for large-scale population simulations with a limited number of agents.This model offered a balance between computational efficiency and accuracy.The results of this research contributed to the comparison and unification of deterministic CMs and stochastic models in epidemic modeling.Furthermore,the results had implications for the development of hybrid models that integrated the strengths of both frameworks.Overall,the present study has provided valuable epidemic modeling techniques and their practical applications for understanding and controlling the spread of infectious diseases.

Rat Models of Fatty Liver due to Liver Depression and Spleen Deficiency

[Objectives] To establish animal models of fatty liver due to liver depression and spleen deficiency that were suitable for activity discovery of traditional Chinese medicine( TCM) compounds,efficacy evaluation,new drug research and development and correspondence between prescription and syndrome of TCM. [Methods] A syndrome score scale that was suitable for evaluating the rat models was established according to the evolvement rules of etiology and pathogenesis of TCM and the modern clinical pathological mechanism. At the same time,bifendate pills and Sanqi Zhigan pills were selected as drug counterevidence for the models. Rats in model groups were given different proportions of high-fat and low-protein fodder and different concentrations of alcohol every day,and intraperitoneally injected with porcine serum twice a week. Drug groups were given with bifendate pills and Sanqi Zhigan pills( 8. 1 mg/kg,and 2. 7 g/kg) respectively for 14 consecutive days.During the experiment,general status,weight,daily fodder intake and daily water intake of the animals were observed,and TCM syndromes were scored. After the experiment,the levels of alanine aminotransferase( ALT),aspartate aminotransferase( AST),γ-glutamine transpeptidase( γ-GT),total cholesterol( TC),triglycerides( TG),low density lipoprotein-cholesterol( LDL-C),and high density lipoprotein-cholesterol( HDL-C) in serum were detected,and the pathological changes in liver tissue were observed. [Results] Compared with the control group,body weight,daily fodder and water intake of rats increased slowly in the model group,and the levels of ALT,AST,γ-GT,TC,TG and LDL-C increased significantly,while the level of HDL-C dropped. Pathological examination showed that steatosis and fat granule were observed in hepatocytes of rats in the model group. Behavioral observation found that main symptoms and minor symptoms of rats in the model group conformed to the syndrome manifestation of liver depression and spleen deficiency,which suggested that the three model groups were established successfully. Among them,three rats died in model group 1,and one rat died in model group 2. The manifestation of all the above lesions can be alleviated by drug counterevidence. [Conclusions]The animal model of fatty liver due to liver depression and spleen deficiency shows an obviously lower mortality and shorter duration and can be used for research of correlation between prescription and syndrome and its mechanism.

Parameter calibration of the tensile-shear interactive damage constitutive model for sandstone failure

The tensile-shear interactive damage(TSID)model is a novel and powerful constitutive model for rock-like materials.This study proposes a methodology to calibrate the TSID model parameters to simulate sandstone.The basic parameters of sandstone are determined through a series of static and dynamic tests,including uniaxial compression,Brazilian disc,triaxial compression under varying confining pressures,hydrostatic compression,and dynamic compression and tensile tests with a split Hopkinson pressure bar.Based on the sandstone test results from this study and previous research,a step-by-step procedure for parameter calibration is outlined,which accounts for the categories of the strength surface,equation of state(EOS),strain rate effect,and damage.The calibrated parameters are verified through numerical tests that correspond to the experimental loading conditions.Consistency between numerical results and experimental data indicates the precision and reliability of the calibrated parameters.The methodology presented in this study is scientifically sound,straightforward,and essential for improving the TSID model.Furthermore,it has the potential to contribute to other rock constitutive models,particularly new user-defined models.

Smaller & Smarter: Score-Driven Network Chaining of Smaller Language Models

With the continuous evolution and expanding applications of Large Language Models (LLMs), there has been a noticeable surge in the size of the emerging models. It is not solely the growth in model size, primarily measured by the number of parameters, but also the subsequent escalation in computational demands, hardware and software prerequisites for training, all culminating in a substantial financial investment as well. In this paper, we present novel techniques like supervision, parallelization, and scoring functions to get better results out of chains of smaller language models, rather than relying solely on scaling up model size. Firstly, we propose an approach to quantify the performance of a Smaller Language Models (SLM) by introducing a corresponding supervisor model that incrementally corrects the encountered errors. Secondly, we propose an approach to utilize two smaller language models (in a network) performing the same task and retrieving the best relevant output from the two, ensuring peak performance for a specific task. Experimental evaluations establish the quantitative accuracy improvements on financial reasoning and arithmetic calculation tasks from utilizing techniques like supervisor models (in a network of model scenario), threshold scoring and parallel processing over a baseline study.

Application of Modelica Based Multi- Domain Modeling and Simulation for Gravity-1

In the R&D phase of Gravity-1(YL-1), a multi-domain modeling and simulation technology based on Modelica language was introduced, which was a recent attempt in the practice of modeling and simulation method for launch vehicles in China. It realizes a complex coupling model within a unified model for different domains, so that technologists can work on one model. It ensured the success of YL-1 first launch mission, supports rapid iteration, full validation, and tight design collaboration.

Anisotropic time-dependent behaviors of shale under direct shearing and associated empirical creep models

Understanding the anisotropic creep behaviors of shale under direct shearing is a challenging issue.In this context,we conducted shear-creep and steady-creep tests on shale with five bedding orientations (i.e.0°,30°,45°,60°,and 90°),under multiple levels of direct shearing for the first time.The results show that the anisotropic creep of shale exhibits a significant stress-dependent behavior.Under a low shear stress,the creep compliance of shale increases linearly with the logarithm of time at all bedding orientations,and the increase depends on the bedding orientation and creep time.Under high shear stress conditions,the creep compliance of shale is minimal when the bedding orientation is 0°,and the steady-creep rate of shale increases significantly with increasing bedding orientations of 30°,45°,60°,and 90°.The stress-strain values corresponding to the inception of the accelerated creep stage show an increasing and then decreasing trend with the bedding orientation.A semilogarithmic model that could reflect the stress dependence of the steady-creep rate while considering the hardening and damage process is proposed.The model minimizes the deviation of the calculated steady-state creep rate from the observed value and reveals the behavior of the bedding orientation's influence on the steady-creep rate.The applicability of the five classical empirical creep models is quantitatively evaluated.It shows that the logarithmic model can well explain the experimental creep strain and creep rate,and it can accurately predict long-term shear creep deformation.Based on an improved logarithmic model,the variations in creep parameters with shear stress and bedding orientations are discussed.With abovementioned findings,a mathematical method for constructing an anisotropic shear creep model of shale is proposed,which can characterize the nonlinear dependence of the anisotropic shear creep behavior of shale on the bedding orientation.

Development and validation of a prediction model for early screening of people at high risk for colorectal cancer

BACKGROUND Colorectal cancer(CRC)is a serious threat worldwide.Although early screening is suggested to be the most effective method to prevent and control CRC,the current situation of early screening for CRC is still not optimistic.In China,the incidence of CRC in the Yangtze River Delta region is increasing dramatically,but few studies have been conducted.Therefore,it is necessary to develop a simple and efficient early screening model for CRC.AIM To develop and validate an early-screening nomogram model to identify individuals at high risk of CRC.METHODS Data of 64448 participants obtained from Ningbo Hospital,China between 2014 and 2017 were retrospectively analyzed.The cohort comprised 64448 individuals,of which,530 were excluded due to missing or incorrect data.Of 63918,7607(11.9%)individuals were considered to be high risk for CRC,and 56311(88.1%)were not.The participants were randomly allocated to a training set(44743)or validation set(19175).The discriminatory ability,predictive accuracy,and clinical utility of the model were evaluated by constructing and analyzing receiver operating characteristic(ROC)curves and calibration curves and by decision curve analysis.Finally,the model was validated internally using a bootstrap resampling technique.RESULTS Seven variables,including demographic,lifestyle,and family history information,were examined.Multifactorial logistic regression analysis revealed that age[odds ratio(OR):1.03,95%confidence interval(CI):1.02-1.03,P<0.001],body mass index(BMI)(OR:1.07,95%CI:1.06-1.08,P<0.001),waist circumference(WC)(OR:1.03,95%CI:1.02-1.03 P<0.001),lifestyle(OR:0.45,95%CI:0.42-0.48,P<0.001),and family history(OR:4.28,95%CI:4.04-4.54,P<0.001)were the most significant predictors of high-risk CRC.Healthy lifestyle was a protective factor,whereas family history was the most significant risk factor.The area under the curve was 0.734(95%CI:0.723-0.745)for the final validation set ROC curve and 0.735(95%CI:0.728-0.742)for the training set ROC curve.The calibration curve demonstrated a high correlation between the CRC high-risk population predicted by the nomogram model and the actual CRC high-risk population.CONCLUSION The early-screening nomogram model for CRC prediction in high-risk populations developed in this study based on age,BMI,WC,lifestyle,and family history exhibited high accuracy.

采用STAMP-24Model的多组织事故分析

安全生产事故往往由多组织交互、多因素耦合造成,事故原因涉及多个组织。为预防和遏制多组织生产安全事故的发生,基于系统理论事故建模与过程模型(Systems-Theory Accident Modeling and Process,STAMP)、24Model,构建一种用于多组织事故分析的方法,并以青岛石油爆炸事故为例进行事故原因分析。结果显示:STAMP-24Model可以分组织,分层次且有效、全面、详细地分析涉及多个组织的事故原因,探究多组织之间的交互关系;对事故进行动态演化分析,可得到各组织不安全动作耦合关系与形成的事故失效链及管控失效路径,进而为预防多组织事故提供思路和参考。

Establishment and evaluation of a mouse model of bronchial asthma with Yin deficiency syndrome

Objective: To establish and evaluate a mouse model of bronchial asthma with Yin deficiency syndrome. Methods: The mouse model of bronchial asthma with Yin deficiency syndrome was established by the treatment with injecting ovalbumin(OVA) two times to sensitize, inhaling OVA 14 times to stimulate, and using thyroxin through lavage during late stimulation. This model was evaluated through body weight, asthmatic behaviors, respiratory function, autonomous activity, lung pathology, and pulmonary fluid clearance. Results: OVA combined with thyroxin was an appropriate method to induce the mouse model with increased food and water intake, autonomous activity, asthmatic behaviors score, and respiratory rate, decreased body weight, tidal volume, and wet/dry ratio of lung, and changed with pathology of lung tissue. The changes of the above mentioned parameters indicated that the model was the bronchial asthma with Yin deficiency syndrome. Conclusion: The OVA combined with thyroxin is a good pattern to establish a mouse model of bronchial asthma with Yin deficiency syndrome successfully, which can highly simulate the clinical symptoms of this disease.