Longitudinal Relationships Among Child School Engagement, Parental Monitoring, and Child Prosocial Behavior: A Child-Parent Synergistic Mechanism.

Numerous contextual factors have been identified that impact the development of children's prosocial behavior, yet the influence of child-initiated factors on prosocial behavior and its underlying mechanism remains unclear. This study employed three longitudinal models to examine in depth how children's school engagement may promote the development of their own prosocial behavior. Three-wave longitudinal data from 4691 children (M age = 9.480, SD = 0.507; 48.2% female) with 2-year intervals were used. Sequentially, a cross-lagged panel model, a random intercept cross-lagged panel model, and a parallel process latent growth model were constructed. The findings indicated that children's school engagement consistently predicted the future level, dynamic changes at within-person level, and long-term trends in their prosocial behavior, and these longitudinal relationships were partially mediated by parental monitoring. These results reveal a child-parent synergistic mechanism for the development of prosocial behavior, wherein children's school engagement both directly promotes their own prosocial behavior and simultaneously enhances prosocial behavior through eliciting increased parental monitoring.

SHOX and sex difference in height: a hypothesis.

The mean height is taller in males than in females, except for early teens. In this regard, previous studies have revealed that (1) distribution of the mean adult heights in subjects with disorders accompanied by discordance between sex chromosome complement and bioactive sex steroids and in control subjects (the British height standards) indicates that, of the ~12.5 cm of sex difference in the mean adult height, ~9 cm is accounted for by the difference in the sex chromosome complement and the remaining ~3.5 cm is explained by the dimorphism in sex steroids (primarily due to the growth-promoting effect of gonadal androgens); (2) according to the infancy-childhood-puberty growth model, the sex difference in the childhood growth function produces height differences of ~1 cm in childhood and 8-10 cm at 18-20 years of age, whereas the sex difference in the pubertal growth function yields height difference of ~4.5 cm at 18-20 years of age; and (3) SHOX expression and methylation analyses using knee cartilage tissues and cultured chondrocytes have shown lower SHOX expression levels in female samples than in male samples and methylation patterns consistent with partial spreading of X-inactivation affecting SHOX in female samples. These findings suggest that small but persistent sex difference in SHOX expression dosage leads to the variation in the sex steroid independent childhood growth function, thereby yielding the sex difference in height which remains small in childhood but becomes obvious in adulthood.

Competitive inhibition and mutualistic growth in co-infections: deciphering Staphylococcus aureus-Acinetobacter baumannii interaction dynamics.

Staphylococcus aureus (Sa) and Acinetobacter baumannii (Ab) are frequently co-isolated from polymicrobial infections that are severe and refractory to therapy. Here, we apply a combination of wet-lab experiments and in silico modeling to unveil the intricate nature of the Ab/Sa interaction using both, representative laboratory strains and strains co-isolated from clinical samples. This comprehensive methodology allowed uncovering Sa's capability to exert a partial interference on Ab by the expression of phenol-soluble modulins. In addition, we observed a cross-feeding mechanism by which Sa supports the growth of Ab by providing acetoin as an alternative carbon source. This study is the first to dissect the Ab/Sa interaction dynamics wherein competitive and cooperative strategies can intertwine. Through our findings, we illuminate the ecological mechanisms supporting their coexistence in the context of polymicrobial infections. Our research not only enriches our understanding but also opens doors to potential therapeutic avenues in managing these challenging infections.

Application progress of latent class growth models in dynamic prevention and control strategies for acquired immunodeficiency syndrome. / æ½œåˆ†ç±»å¢žé•¿æ¨¡åž‹åœ¨èŽ·å¾—æ€§å ç–«ç¼ºé™·ç»¼åˆå¾åŠ¨æ€é˜²æŽ§ç­–ç•¥ä¸­çš„åº”ç”¨è¿›å±•.

The prevention and control requirements for HIV/AIDS vary significantly among different populations, posing substantial challenges to the formulation and implementation of intervention strategies. Dynamically assessing the heterogeneity and disease progression trajectories of various groups is crucial. Latent class growth model (LCGM) serves as a statistical approach that fits a longitudinal data into N subgroups of individual development trajectories, identifying and analyzing the progression paths of different subgroups, thereby offering a novel perspective for disease control strategies. LCGM has shown significant advantages in the application of HIV/AIDS prevention and control, especially in gaining a deeper understanding and analysis of epidemiological characteristics, risk behaviors, psychological research, heterogeneity in testing, and dynamic changes. Summarizing the advantages and limitations of applying LCGM can provide a reliable basis for precise prevention and control of HIV/AIDS.

Recognition of environmental contaminant and pathogenic bacteria by means of redox potential methodology.

The time-consuming nature of culturing methods has urged the exploration of rapid modern technologies. One promising alternative utilizes redox potential, which describes the oxidative changes within complex media, indicating oxygen and nutrient consumption, as well as the production of reduced substances in the investigated biological system. Redox potential measurement can detect microbial activity within 16 h, what is significantly faster than the minimum 24 h incubation time of the reference plate counting technique. The redox potential based method can be specific with selective media, but bacterial strains have unique kinetic pattern as well. The proposed method suggests evaluation of the curve shape for the differentiation of environmental contaminant and pathogenic microbial strains. Six bacterial species were used in validation (Escherichia coli, Pseudomonas aeruginosa, Salmonella enterica, Listeria innocua, Listeria monocytogenes, and Listeria ivanovii). Descriptive parameters reached 98.2 % accuracy and Gompertz model achieved 91.6 % accuracy in classification of the selected 6 bacteria species.•Mathematical model (Gompertz function) and first order descriptive parameters are suggested to describe the specific shape of redox potential curves, while Support Vector Machine (SVM) is recommended for classification.•Due to the concentration dependent time to detection (TTD), pre-processing applies standardization according to the inflection point time.

SpatialWavePredict: a tutorial-based primer and toolbox for forecasting growth trajectories using the ensemble spatial wave sub-epidemic modeling framework.

BACKGROUND: Dynamical mathematical models defined by a system of differential equations are typically not easily accessible to non-experts. However, forecasts based on these types of models can help gain insights into the mechanisms driving the process and may outcompete simpler phenomenological growth models. Here we introduce a friendly toolbox, SpatialWavePredict, to characterize and forecast the spatial wave sub-epidemic model, which captures diverse wave dynamics by aggregating multiple asynchronous growth processes and has outperformed simpler phenomenological growth models in short-term forecasts of various infectious diseases outbreaks including SARS, Ebola, and the early waves of the COVID-19 pandemic in the US. RESULTS: This tutorial-based primer introduces and illustrates a user-friendly MATLAB toolbox for fitting and forecasting time-series trajectories using an ensemble spatial wave sub-epidemic model based on ordinary differential equations. Scientists, policymakers, and students can use the toolbox to conduct real-time short-term forecasts. The five-parameter epidemic wave model in the toolbox aggregates linked overlapping sub-epidemics and captures a rich spectrum of epidemic wave dynamics, including oscillatory wave behavior and plateaus. An ensemble strategy aims to improve forecasting performance by combining the resulting top-ranked models. The toolbox provides a tutorial for forecasting time-series trajectories, including the full uncertainty distribution derived through parametric bootstrapping, which is needed to construct prediction intervals and evaluate their accuracy. Functions are available to assess forecasting performance, estimation methods, error structures in the data, and forecasting horizons. The toolbox also includes functions to quantify forecasting performance using metrics that evaluate point and distributional forecasts, including the weighted interval score. CONCLUSIONS: We have developed the first comprehensive toolbox to characterize and forecast time-series data using an ensemble spatial wave sub-epidemic wave model. As an epidemic situation or contagion occurs, the tools presented in this tutorial can facilitate policymakers to guide the implementation of containment strategies and assess the impact of control interventions. We demonstrate the functionality of the toolbox with examples, including a tutorial video, and is illustrated using daily data on the COVID-19 pandemic in the USA.

Relationships between Food Insecurity, Self-Efficacy, and Changes in Body Mass Index among the Youth in Taiwan: Analysis from a Longitudinal Cohort Survey.

BACKGROUND: Food insecurity is a heightened concern among economically disadvantaged youth, and it may contribute to the atypical body mass index (BMI) patterns frequently observed in this group. Self-efficacy seems to intervene in the negative impacts of contextual restraints. This study investigated the relationship between food insecurity, self-efficacy, and BMI trajectory among economically disadvantaged Taiwanese youth. METHODS: We utilized three-wave longitudinal data from the Taiwan Database of Children and Youth in Poverty. The Food Insecurity Score (FIS) assessed food insecurity with a 4-item scale measuring reduced meal frequency, hunger, skipping meals, and economic constraints. Moreover, the General Self-Efficacy Scale (GSES) assessed self-efficacy, showcasing the ability to handle stress effectively and envision success scenarios, contributing to positive outcomes. By employing latent growth modeling, we were able to delineate the impacts of baseline food insecurity and self-efficacy on initial BMI and its subsequent growth trajectory. RESULTS: Elevated baseline FIS significantly predicted higher initial BMI (coefficient = 0.420, p = 0.042). Baseline GSES was negatively associated with initial BMI (coefficient = -0.093, p < 0.001) but positively predicted the BMI growth rate (coefficient = 0.023, p = 0.011). CONCLUSION: Enhancing self-efficacy may be an effective multidisciplinary intervention to address psychosocial and socioeconomic factors when tackling weight problems in vulnerable youth groups.

Motor dysfunction in Parkinson's patients: depression differences in a latent growth model.

Objective: This study aims to utilize latent growth model (LGM) to explore the developmental trajectory of motor dysfunction in Parkinson's disease (PD) patients and investigate the relationship between depression and motor dysfunction. Methods: Four-year follow-up data from 389 PD patients were collected through the Parkinson's Progression Marker Initiative (PPMI). Firstly, a univariate LGM was employed to examine the developmental trajectory of motor dysfunction in PD patients. Subsequently, depression levels were introduced as covariates into the model, and depression was further treated as a parallel growth latent variable to study the longitudinal relationship between motor dysfunction and depression. Results: In the trajectory analysis of motor dysfunction, the fit indices for the quadratic growth LGM model were χ2 = 7.419, df = 6, CFI = 0.998, TLI = 0.997, SRMR = 0.019, and RMSEA = 0.025, indicating that the growth trend of motor dysfunction follows a quadratic curve rather than a simple linear pattern. Introducing depression symptoms as time-varying covariates to explore their effect on motor dysfunction revealed significant positive correlations (ß = 0.383, p = 0.026; ß = 0.675, p < 0.001; ß = 0.385, p = 0.019; ß = 0.415, p = 0.014; ß = 0.614, p = 0.003), suggesting that as depression levels increase, motor dysfunction scores also increase. Treating depression as a parallel developmental process in the LGM, the regression coefficients for depression intercept on motor dysfunction intercept, depression slope on motor dysfunction slope, and depression quadratic factor on motor dysfunction quadratic factor were 0.448 (p = 0.046), 1.316 (p = 0.003), and 1.496 (p = 0.038), respectively. These significant regression coefficients indicate a complex relationship between depression and motor dysfunction, involving not only initial level associations but also growth trends over time and possible quadratic effects. Conclusion: This study indicates a quadratic growth trajectory for motor dysfunction in PD, suggesting a continuous increase in severity with a gradual deceleration in growth rate. The relationship between depression and motor dysfunction is complex, involving initial associations, evolving trends over time, and potential quadratic effects. Exacerbation of depressive symptoms may coincide with motor function deterioration.

Public health events and economic growth in a neoclassical framework.

Public health events (PHEs) have emerged as significant threats to human life, health, and economic growth. PHEs, such as COVID-19, have prompted a reevaluation for enhanced regular prevention and control (RPC). In this study, we focus on the core concept of prevention and control intensity (PCI), and establish a neoclassical economic growth model from the long-term and macro perspective to balance life protection and economic growth. The model construct the mechanism of PCI on economic growth through population dynamics and capital accumulation under the backdrop of RPC for PHEs. We find the conditions for PCI when the economy achieves steady state, and provides an algorithm establishing the optimal strategy that maximises per capita disposable income based on the optimal PCI and consumption. Simulation result quantifies an inverted U-shaped relationship between PCI and capital per capita, output per capita and consumption per capita in the steady state. The model suggests that, given the PHEs of inducing potential unemployment shock, it is worthwhile to combine the implementation of moderate PCI with coordinated policies of income distribution.

The trajectories of psychosocial adjustment among young to middle-aged women with breast cancer: A prospective longitudinal study.

PURPOSE: This study aims to explore heterogeneous trajectories of psychosocial adjustment among young to middle-aged women with breast cancer and determine the predictive factors influencing these trajectories. METHODS: This study was conducted from October 2019 to October 2022 across two hospitals in Guangzhou. Demographic and disease characteristics, psychosocial adjustment, self-efficacy, social support, and coping modes were collected at baseline. Follow-up evaluations of psychosocial adjustment occurred at 1, 3, and 6 months post-surgery. Latent class growth modeling identified distinct patterns of psychosocial adjustment trajectories. Logistic regression analysis determined the predictive factors. RESULTS: A total of 377 young to middle-aged women with breast cancer participated in this study, with 289 participants completing the 6-month follow-up. Three distinct trajectories of psychosocial adjustment were identified including a "sustained severe maladjustment" trajectory, comprising 22.5% of participants, a "sustained moderate maladjustment" trajectory, comprising 50.4% of participants, and a "well-adjusted class" trajectory, comprising 27.1% of participants. Predictors of psychosocial adjustment trajectories included affected side, surgical type, chemotherapy, self-efficacy, social support, and coping modes. CONCLUSIONS: This study revealed three distinct trajectories of psychosocial adjustment among young to middle-aged women with breast cancer. Those with right-sided breast cancer, undergoing total mastectomy, receiving chemotherapy, low self-efficacy, limited social support, and relying on confrontation or avoidance coping modes may experience sustained maladjustment.

Parent-teacher relationship and students' learning engagement in China: A longitudinal study considering urban-suburban differences.

BACKGROUND: The importance of parent-teacher relationships has been well-discussed in Western contexts. It's still unclear whether and how parent-teacher relationships affect students' academic development, especially in the context of China's uneven development between urban and suburban areas. AIMS: This study examined the urban-suburban differences in the influence of the parent-teacher relationships on students' learning engagement during the last 3 years of primary school to contribute to related policy and practice. SAMPLE AND METHODS: Data were collected annually during the summer period in three waves from Grades 4 to 6. The sample included 1408 students (Mage = 10.35, SD = .48; 49.1% boys) paired with their mothers (Mage = 38.82, SD = 3.54), with 643 pairs from urban areas and 765 pairs from suburban areas in China. In each wave, the parents reported the frequency of contact with their child's teacher during the previous school year as well as the quality of their relationship, and the students reported their learning engagement. Latent growth models were used to examine the hypotheses. RESULTS: A statistically significant decline in learning engagement was seen only in suburban students, while the parent-teacher relationships seemed to increase for both suburban and urban participants. Latent growth modelling showed that the increasing levels of relationship quality reduced the decline in the suburban students' learning engagement, although the contact between parents and teachers did not play such a positive role for both urban and suburban students. CONCLUSIONS: The findings reveal a compensatory effect of the quality of the parent-teacher relationship on suburban students' learning engagement. Considering the difference in students' learning engagement between urban and suburban students, increased effort on high-quality parent-teacher relationships for suburban students is required to better support their academic development.

Analysis of factors influencing the trajectory of fatigue in maintenance haemodialysis patients: a longitudinal study.

OBJECTIVE: To explore the potential categories and influencing factors of fatigue trajectory in maintenance haemodialysis patients. METHODS: Between June 2023 and December 2023, a convenience sample of 306 maintenance haemodialysis patients in a tertiary hospital haemodialysis centre in Zhenjiang City was selected as the study population, and patient information was collected monthly after the baseline survey using the General Information Questionnaire, Pittsburgh Sleep Quality Scale, Piper Fatigue Revision Scale, Collaborative Social Support Scale, Patient Health Questionnaire Depression Scale, Comprehensive Economic Toxicity Rating Scale, and Fear of Disease Progression Simplified Scale, for a total of six follow-up visits. In addition, the potential category growth model was used to identify the developmental trajectory of fatigue, and univariate analysis and binary logistic regression were used to analyse its determinants. RESULTS: The 6 month fatigue trajectory of maintenance haemodialysis patients could be divided into two categories: persistent low-fatigue group (59.8%) and fluctuating high-fatigue group (40.2%). Age, surgical history, level of social support, sleep, economic toxicity, and changes in ultrafiltration volume during dialysis were the influencing factors for repeated fatigue in maintenance haemodialysis patients (p < 0.05). CONCLUSION: The fatigue trajectory of maintenance haemodialysis patients is heterogeneous, suggesting that clinical workers should focus on the haemodialysis patients with repeated fatigue and make targeted interventions to improve their fatigue status and reduce the occurrence of adverse events in patients.

Random effects models of tumour growth for investigating interval breast cancer.

In Nordic countries and across Europe, breast cancer screening participation is high. However, a significant number of breast cancer cases are still diagnosed due to symptoms between screening rounds, termed "interval cancers". Radiologists use the interval cancer proportion as a proxy for the screening false negative rate (ie, 1-sensitivity). Our objective is to enhance our understanding of interval cancers by applying continuous tumour growth models to data from a study involving incident invasive breast cancer cases. Building upon previous findings regarding stationary distributions of tumour size and growth rate distributions in non-screened populations, we develop an analytical expression for the proportion of interval breast cancer cases among regularly screened women. Our approach avoids relying on estimated background cancer rates. We make specific parametric assumptions concerning tumour growth and detection processes (screening or symptoms), but our framework easily accommodates alternative assumptions. We also show how our developed analytical expression for the proportion of interval breast cancers within a screened population can be incorporated into an approach for fitting tumour growth models to incident case data. We fit a model on 3493 cases diagnosed in Sweden between 2001 and 2008. Our methodology allows us to estimate the distribution of tumour sizes at the most recent screening for interval cancers. Importantly, we find that our model-based expected incidence of interval breast cancers aligns closely with observed patterns in our study and in a large Nordic screening cohort. Finally, we evaluate the association between screening interval length and the interval cancer proportion. Our analytical expression represents a useful tool for gaining insights into the performance of population-based breast cancer screening programs.

A longitudinal study on self-rated health changes in disabled older people.

There is a growing demand for quality healthcare for senior citizens among the disabled older population, considering their rising numbers. This study examines the longitudinal change in the health status of disabled older people and determines its effects on social exclusion and differences based on age at disability onset. The analysis was performed using a multilevel growth model on the health data for disabled older people (≥60 years) derived from the Korea Welfare Panel Study (KWePS). The following findings were observed based on the stated model: (1) The Self-Rated Health (SRH) of disabled older people increased over time, with significant individual differences in the initial status and growth rate; (2) The domains of economic and social network exclusion were associated with changes in the health status of disabled older people; and (3) The longitudinal effects of social exclusion on SRH changes in disabled older people varied according to the age at disability onset. Based on these results, strategies and implications for the development of health-promoting interventions for disabled older people were presented.

Evaluating fit indices in a multilevel latent growth model with unbalanced design: a Monte Carlo study.

This study informed researchers about the performance of different level-specific and target-specific model fit indices in the Multilevel Latent Growth Model (MLGM) with unbalanced design. As the use of MLGMs is relatively new in applied research domain, this study helped researchers using specific model fit indices to evaluate MLGMs. Our simulation design factors included three levels of number of groups (50, 100, and 200) and three levels of unbalanced group sizes (5/15, 10/20, and 25/75), based on simulated datasets derived from a correctly specified MLGM. We evaluated the descriptive information of the model fit indices under various simulation conditions. We also conducted ANOVA to calculated the extent to which these fit indices could be influenced by different design factors. Based on the results, we made recommendations for practical and theoretical research about the fit indices. CFI- and TFI-related fit indices performed well in the MLGM and could be trustworthy to use to evaluate model fit under similar conditions found in applied settings. However, RMSEA-related fit indices, SRMR-related fit indices, and chi square-related fit indices varied by the factors included in this study and should be used with caution for evaluating model fit in the MLGM.

Modeling Growth Kinetics of Escherichia coli and Background Microflora in Hydroponically Grown Lettuce.

Hydroponic cultivation of lettuce is an increasingly popular sustainable agricultural technique. However, Escherichia coli, a prevalent bacterium, poses significant concerns for the quality and safety of hydroponically grown lettuce. This study aimed to develop a growth model for E. coli and background microflora in hydroponically grown lettuce. The experiment involved inoculating hydroponically grown lettuce with E. coli and incubated at 4, 10, 15, 25, 30, 36 °C. Growth models for E. coli and background microflora were then developed using Origin 2022 (9.9) and IPMP 2013 software and validated at 5 °C and 20 °C by calculating root mean square errors (RMSEs). The result showed that E. coli was unable to grow at 4 °C and the SGompertz model was determined as the most appropriate primary model. From this primary model, the Ratkowsky square root model and polynomial model were derived as secondary models for E. coli-R168 and background microflora, respectively. These secondary models determined that the minimum temperature (Tmin) required for the growth of E. coli and background microflora in hydroponically grown lettuce was 6.1 °C and 8.7 °C, respectively. Moreover, the RMSE values ranged from 0.11 to 0.24 CFU/g, indicating that the models and their associated kinetic parameters accurately represented the proliferation of E. coli and background microflora in hydroponically grown lettuce.

An open-source, three-dimensional growth model of the mandible.

The available reference data for the mandible and mandibular growth consists primarily of two-dimensional linear or angular measurements. The aim of this study was to create the first open-source, three-dimensional statistical shape model of the mandible that spans the complete growth period. Computed tomography scans of 678 mandibles from children and young adults between 0 and 22 years old were included in the model. The mandibles were segmented using a semi-automatic or automatic (artificial intelligence-based) segmentation method. Point correspondence among the samples was achieved by rigid registration, followed by non-rigid registration of a symmetrical template onto each sample. The registration process was validated with adequate results. Principal component analysis was used to gain insight in the variation within the dataset and to investigate age-related changes and sexual dimorphism. The presented growth model is accessible globally and free-of-charge for scientists, physicians and forensic investigators for any kind of purpose deemed suitable. The versatility of the model opens up new possibilities in the fields of oral and maxillofacial surgery, forensic sciences or biological anthropology. In clinical settings, the model may aid diagnostic decision-making, treatment planning and treatment evaluation.

Modeling the synergistic interplay between malaria dynamics and economic growth.

The mosquito-borne disease (malaria) imposes significant challenges on human health, healthcare systems, and economic growth/productivity in many countries. This study develops and analyzes a model to understand the interplay between malaria dynamics, economic growth, and transient events. It uncovers varied effects of malaria and economic parameters on model outcomes, highlighting the interdependence of the reproduction number (R0) on both malaria and economic factors, and a reciprocal relationship where malaria diminishes economic productivity, while higher economic output is associated with reduced malaria prevalence. This emphasizes the intricate interplay between malaria dynamics and socio-economic factors. The study offers insights into malaria control and underscores the significance of optimizing external aid allocation, especially favoring an even distribution strategy, with the most significant reduction observed in an equal monthly distribution strategy compared to longer distribution intervals. Furthermore, the study shows that controlling malaria in high mosquito biting areas with limited aid, low technology, inadequate treatment, or low economic investment is challenging. The model exhibits a backward bifurcation implying that sustainability of control and mitigation measures is essential even when R0 is slightly less than one. Additionally, there is a parameter regime for which long transients are feasible. Long transients are critical for predicting the behavior of dynamic systems and identifying factors influencing transitions; they reveal reservoirs of infection, vital for disease control. Policy recommendations for effective malaria control from the study include prioritizing sustained control measures, optimizing external aid allocation, and reducing mosquito biting.

Addressing age measurement errors in fish growth estimation from length-stratified samples.

Fish growth models are crucial for fisheries stock assessments and are commonly estimated using fish length-at-age data. This data is widely collected using length-stratified age sampling (LSAS), a cost-effective two-phase response-selective sampling method. The data may contain age measurement errors (MEs). We propose a methodology that accounts for both LSAS and age MEs to accurately estimate fish growth. The proposed methods use empirical proportion likelihood methodology for LSAS and the structural errors in variables methodology for age MEs. We provide a measure of uncertainty for parameter estimates and standardized residuals for model validation. To model the age distribution, we employ a continuation ratio-logit model that is consistent with the random nature of the true age distribution. We also apply a discretization approach for age and length distributions, which significantly improves computational efficiency and is consistent with the discrete age and length data typically encountered in practice. Our simulation study shows that neglecting age MEs can lead to significant bias in growth estimation, even with small but non-negligible age MEs. However, our new approach performs well regardless of the magnitude of age MEs and accurately estimates SEs of parameter estimators. Real data analysis demonstrates the effectiveness of the proposed model validation device. Computer codes to implement the methodology are provided.

Assessing the impact of tear direction in coronary artery dissection on thrombosis development: A hemodynamic computational study.

OBJECTIVE: Iatrogenic coronary artery dissection is a complication of coronary intimal injury and dissection due to improper catheter manipulation. The impact of tear direction on the prognosis of coronary artery dissection (CAD) remains unclear. This study examines the hemodynamic effects of different tear directions (transverse and longitudinal) of CAD and evaluates the risk of thrombosis, rupture and further dilatation of CAD. METHODS: Two types of CAD models (Type I: transverse tear, Type II: longitudinal tear) were reconstructed from the aorto-coronary CTA dataset of 8 healthy cases. Four WSS-based indicators were analyzed, including time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), relative residence time (RRT), and cross flow index (CFI). A thrombus growth model was also introduced to predict the trend of thrombus growth in CAD with two different tear directions. RESULTS: For most of the WSS-based indicators, including TAWSS, RRT, and CFI, no statistically significant differences were observed across the CAD models with varying tear directions, except for OSI, where a significant difference was noted (p < 0.05). Meanwhile, in terms of thrombus growth, the thrombus growing at the tear of the Type I (transverse tear) CAD model extended into the true lumen earlier than that of the Type II (longitudinal tear) model. CONCLUSIONS: Numerical simulations suggest that: (1) The CAD with transverse tear have a high risk of further tearing of the dissection at the distal end of the tear. (2) The CAD with longitudinal tear create a hemodynamic environment characterized by low TAWSS and high OSI in the false lumen, which may additionally increase the risk of vessel wall injury. (3) The CAD with transverse tear may have a higher risk of thrombosis and coronary obstruction and myocardial ischemia in the early phase of the dissection.