Correlation Model Research Articles

Structural deformation dynamic simulation of weft knitted fabric basic stitch

To address the current problem of separating the structural and deformation models of weft knitted fabrics’ basic stitch, and to achieve synchronous simulation of the stitch’s structural form and deformation behavior, we studied the structural form and deformation behavior of the basic stitch, including weft plain stitch, rib stitch, and purl stitch. We established a three-dimensional structural model and conducted data analysis, improving the traditional mass-spring model to obtain a deformation model that fits better with the knitted fabric. We then investigated the connection between the structural and deformation models and constructed a correlation model, and used NURBS (Non-Uniform Rational B-Splines) curve application, force analysis, and dynamic solution to study the simulation of the correlation model. Finally, based on computer technology, we achieved dynamic simulation of the structural deformation of weft knitted fabrics’ basic stitch and demonstrated the simulation effect, proving the feasibility of the method and the rationality of the model.

Extended Phenotyping of Migraine in Children: A Cross-Sectional Study in a Specialist Children's Headache Clinic

BackgroundThe pediatric migraine phenotype may exhibit differences to adults, leading to diagnostic challenges. We aimed to perform a cross-sectional systematic study to characterize the extended phenotype of pediatric migraine. MethodsNew migraine patients presenting to the Children's Headache Clinic were included (n = 105). Data were collected via a detailed symptom questionnaire at the first clinical encounter and were analyzed using descriptive statistics, Cohen kappa (k), Spearman correlation (ρ), and Poisson and binomial logistic regression models within SPSS. ResultsPatients were 65% female and aged five to 17 years (median 14, interquartile range [IQR] 11 to 15), with a mean disease duration of 4.7 years (S.D. 2.8). Monthly headache frequency was 1 to 30 days (median 30, IQR 12 to 30). Attack duration varied between 2 and 168 hours (median 12, IQR 5 to 72). The majority (81%) experienced bilateral headache. Premonitory symptoms (PS) were reported by 93% (range 0 to 7; mood change and tiredness most commonly), cranial autonomic symptoms (CAS) by 58% (range 0 to 6; pallor and lacrimation most commonly), and premonitory CAS by 23%. Vertigo (53%) and allodynia (16%) were present. The laterality of headache and CAS showed agreement (k = 0.5, P < 0.001). For every year of disease duration, 1.07 times more PS were reported (95% confidence interval [CI] 1.03 to 1.12, P < 0.001). The number of CAS (odds ratio 2.13, 95% CI 1.2 to 3.8, P = 0.01) significantly predicted allodynia. ConclusionsChildren display a more enriched PS phenotype with disease chronicity. CAS and allodynia may be markers of central sensitization with shared neurobiological mechanisms in the absence of peripheral nociceptor activation.

Condensation Flow of Refrigerants Inside Mini and Microchannels: A Review

Nowadays, the demand for obtaining high heat flux values in small volumes has increased with the development of technology. Condensing flow inside mini- and microchannels has been becoming a promising solution for refrigeration, HVAC, air-conditioning, heat pumps, heat pipes, and electronic cooling applications. In these applications, employing mini/microchannels in the condenser design results in the working fluid, generally refrigerant, undergoing a phase change inside the mini/microchannels. On the other hand, the reduction in the hydraulic diameter during condensation gives rise to different flow regimes and heat transfer mechanisms in the mini- and microchannels compared to the conventional channels. Therefore, the understanding of fluid flow and heat transfer characteristics during condensation of refrigerant inside mini- and microchannels has been gaining importance in terms of condenser design. This study presents a state-of-the-art review of condensation studies on refrigerants inside mini- and microchannels. The review includes experimental studies as well as correlation models, which are developed to predict condensation heat transfer coefficients and pressure drop. The refrigerant type, thermodynamical performance, and compatibility, as well as the environmental effects of refrigerant, play a decisive role in the design of refrigeration systems. Therefore, the environmental impacts of refrigerants and current regulations against them are also discussed in the present review.

AN INVESTIGATION INTO THE RELATIONSHIPS BETWEEN 8TH-GRADE STUDENTS' MATHEMATICS SELF-EFFICACY PERCEPTIONS AND THEIR MOTIVATION AND ANXIETY LEVELS

This study seeks to examine the relationships between 8th-grade students' mathematics self-efficacy perceptions and their motivation and anxiety levels. The correlational survey model was used in the study. The population of the study consists of 9811 8th-grade students studying at 64 public schools in Batman province in the 2020-2021 academic year. The sample consists of 550 students from 10 secondary schools selected via the random method among 9811 students. Personal Information Form, Mathematics Self-Efficacy Scale, Motivation Scale for Mathematics Lessons, and Mathematics Anxiety Scale were used as data collection tools. Independent samples t-test, one-way analysis of variance (ANOVA), and Pearson product-moment correlation analysis were used to analyze the data. The relationship between mathematics self-efficacy perception, mathematics lesson motivation, and mathematics anxiety was calculated by path analysis. As a result, a positive and moderately significant relationship was found between students' mathematics self-efficacy perceptions and their motivation for mathematics lessons while a negative and moderately significant relationship was found between mathematics self-efficacy perceptions and mathematics anxiety. It was also determined that there was a negative and moderately significant relationship between students' motivation for mathematics lessons and their mathematics anxiety. The Path analysis revealed that as 8th-grade students' mathematics self-efficacy perceptions increase, their motivation for mathematics lessons increases, and their mathematics anxiety levels decrease.&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/soc/0808/a.php" alt="Hit counter" /&gt;&lt;/p&gt;

Quantitative computed tomography assessment of bone mineral density in adolescent idiopathic scoliosis: correlations with Cobb angle, vertebral rotation, and Risser sign.

Adolescent idiopathic scoliosis (AIS) is a prevalent spinal disorder that can potentially influence bone mineral density (BMD), thereby increasing the susceptibility to osteoporosis and fractures. Early identification of reduced bone mass in AIS patients is crucial for clinicians to develop effective preventive strategies against fractures. This study aims to elucidate the correlation between BMD, as measured by quantitative computed tomography (QCT), and various clinical parameters in AIS, including the Cobb angle, vertebral rotation, and the Risser sign. By revealing the potential influences of these factors on BMD, our findings aim to assist clinicians in making informed and timely decisions regarding AIS management, particularly in situations where QCT is unavailable. A cross-sectional study was conducted on 129 adolescents with AIS who were enrolled at The Third People's Hospital of Chengdu, Sichuan, China, between 2021 and 2023. QCT was employed to assess BMD and vertebral rotation. The Cobb angle and Risser sign were determined through radiographic evaluation, while anthropometric and biochemical data were also collected. Statistical analyses, including Pearson and Spearman rank correlation and regression models, were used to investigate the associations between BMD and clinical measures. A significant negative correlation was found between BMD and Cobb angle (coefficient =-0.663; P<0.001), as well as between BMD and vertebral rotation angle (coefficient =-0.442; P<0.001) in patients with AIS. BMD was positively correlated with increased height (coefficient =0.355; P<0.001) and BMI (coefficient =0.199; P=0.02). A significant association was detected between BMD and the Risser sign (P=0.002). No significant sex-based differences in BMD were observed (P=0.052). No significant correlations were observed between BMD and levels of potassium (K), calcium (Ca), inorganic phosphate (P), and iron (Fe) (P>0.05 all). The binary logistic regression analysis identified Cobb angle as a risk factor of lower BMD presence in AIS patients (coefficient =0.072; OR=1.075; P<0.001). Furthermore, the receiver operating characteristic (ROC) analysis of the combined model for predicting low BMD in AIS patients yielded an area under the curve (AUC) value of 0.900, with an optimal threshold determined as 0.398. The sensitivity and specificity were calculated as 0.816 and 0.900, respectively, indicating a robust predictive capacity. This study highlights the significant inverse correlation observed between BMD measured by QCT and both Cobb angle and vertebral rotation angle in patients with AIS. Furthermore, a notable variation in BMD was found across different Risser sign categories, with BMD values generally increasing as Risser sign levels increased. Additionally, our findings indicate that Cobb angle serves as a risk factor for low BMD presence. Moreover, a combined model was developed to predict the likelihood of low BMD occurrence in AIS patients.

183 Earlier Surgery is Associated With Improved Post-operative Language Development in Children With Tuberous Sclerosis Complex (TSC)

INTRODUCTION: Early life epilepsy in TSC has been strongly associated with lifelong intellectual disability. While improved seizure control correlates with improvements in quality of life and cognition, the importance of surgery timing in young children has not been well-studied. METHODS: Changes in patients’ preoperative (0-12 months) to postoperative (36 months) scores in neuropsychologic tests—including the Mullen Scales of Early Learning (MSEL), Vineland Adaptive Behavior Scales, Second Edition (VABS-II), and the Preschool Language Scales, 5th addition (PLS-5)—were calculated. Pearson correlation and multivariate linear regression models were used to correlate changes in test scores with age at surgery and separately with duration of epilepsy prior to surgery. Analysis was limited to those patients who demonstrated improved seizure control post-operatively (n = 18). RESULTS: Age at surgery had a statistically significant negative correlation with changes in the combined verbal sub-tests of the MSEL (R = -0.41, p = 0.04) and predicted the change in that measure outcome in a multivariate linear regression model (β: -0.09, p = 0.03). Similar trends were seen for the change in the total language score of the PLS-5 (R = -0.38, p = 0.06; β: -0.21, p = 0.07). Results were similar when the duration of epilepsy prior to surgery was assessed as the independent variable. However there were no clear trends with the VABS-II questionnaires, even in language domains. CONCLUSIONS: Our data shows that successful earlier surgery and shorter epilepsy duration prior to surgery are both associated with improved post-operative language development in a small cohort of patients with TSC. Prospective clinical trials are necessary to further elucidate this relationship.

Dynamic partial correlation models

We introduce a new scalable model for dynamic conditional correlation matrices based on a recursion of dynamic bivariate partial correlation models. By exploiting the model’s recursive structure and the theory of perturbed stochastic recurrence equations, we establish stationarity, ergodicity, and filter invertibility in the multivariate setting using conditions for bivariate slices of the data only. From this, we establish consistency and asymptotic normality of the maximum likelihood estimator for the model’s static parameters. The new model outperforms benchmarks like the t-cDCC and the multivariate t-GAS, both in simulations and in an in-sample and out-of-sample asset pricing application to US stock returns.

Response of plants and soils to inundation duration and construction of the plant‒soil association mode in the hydro‒fluctuation belt of the reservoir wetland

Hydro-Fluctuation Belt (HFB), a periodically exposed bank area formed by changes in water level fluctuations, is critical for damaging the reservoir wetland landscape and ecological balance. Thus, it is important to explore the mechanism of hydrological conditions on the plant-soil system of the HFB for protection of the reservoir wetland and landscape restoration. Here, we investigated the response of plant community characteristics and soil environment of the HFB of Tonghui River National Wetland Park (China), is a typical reservoir wetland, to the duration of inundation, as well as the correlation between the distribution of dominant plants and soil pH, nutrient contents, and enzyme activity by linear regression and canonical correlation analyses. The results show that as the duration of inundation decreases, the vegetation within the HFB is successional from annual or biennial herbs to perennial herbs and shrubs, with dominant plant species prominent and uneven distribution of species. Soil nutrient contents and enzyme activities of HFB decreased with increasing inundation duration. Dominant species of HFB plant community are related to soil environment, with water content, pH, urease, and available potassium being principle soil environmental factors affecting their distribution. When HFB was inundated for 0–30 days, soil pH was strongly acidic, with available potassium content above 150 mg kg−1 and higher urease activity, distributed with Arundo donax L., Polygonum perfoliatum L., Alternanthera philoxeroides (Mart.) Griseb., and Daucus carota L. communities. When inundated for 30–80 days, soil pH was acidic, with lower available potassium content (50–150 mg kg−1) and urease activity, distributed with Beckmannia syzigachne (Steud.) Fern.+ Polygonum lapathifolium L., Polygonum lapathifolium L., Medicago lupulina L. + Dysphania ambrosioides L. and Leptochloa panicea (Retz.) Ohwi communities. Using the constructed HFB plant-soil correlation model, changes in the wetland soil environment can be quickly judged by the succession of plant dominant species, which provides a simpler method for the monitoring of the soil environment in the reservoir wetland, and is of great significance for the scientific management and reasonable protection of the reservoir-type wetland ecosystem.

Multimodal machine learning for predicting heat transfer characteristics in micro-pin fin heat sinks

As three-dimensional integrated circuit (3D-IC) chip technology advances, thermal management has become increasingly important because of increasing heat flux from thermal stacking. Micro-pin fin-embedded cooling has emerged as a promising solution for 3D-ICs, offering better thermal and hydraulic performance than conventional microchannel heat sinks. It is also easy to integrate into existing 3D-IC structures, such as through-silicon vias between stacks. The utilization of two-phase flow in micro-pin fins further enhances temperature uniformity and improves the heat transfer coefficient by leveraging latent heat. Nevertheless, predicting thermal performance in micro-pin fin heat sinks under boiling conditions remains challenging owing to intricate geometric shapes and diverse operating conditions. The present lack of correlation or theoretical models poses a significant obstacle. To address this problem, our study employed a Multimodal machine-learning (ML) approach, combining image data capturing boiling patterns of two-phase flow and information about geometric shape and operating conditions, to predict heat transfer characteristics in micro-pin fin heat sinks. We utilized experimental data comprising 155 types of boiling heat transfer data with the dielectric fluid FC-72 in two micro-fin shapes directly etched on Si. Four ML algorithms (XGBoost, LightGBM, Multilayer perceptron (MLP), and Multimodal ML) were employed to predict thermal performance. The correlation coefficient analysis before learning revealed the influence of each type of measurement data on the heater surface temperature during two-phase flow. Prediction accuracy was measured using mean absolute percent error (MAPE), and the results were compared in terms of maximum and average temperature depending on the characteristics of each ML algorithm. Overall, the Multimodal approach demonstrated superior capability in predicting temperature distributions with spatial details, surpassing conventional decision-tree algorithms and MLP in performance. When trained with boiling images, the Multimodal ML model achieved remarkable precision, evidenced by a MAPE of 1.81% for the maximum temperature and 0.84% for the average temperature, highlighting its exceptional accuracy in mapping the heated surface temperature profile. By contrast, the traditional MLP model, which lacked training on boiling images, showed diminished accuracy, with a MAPE of 2.54% for the maximum temperature and 1.77% for the average temperature, indicating a comparative shortfall against the Multimodal model results.

The utility of the irritability scale in Huntington's disease patients with evidence of irritability or aggression

IntroductionIrritability, a common neuropsychiatric symptom in Huntington's disease (HD), lacks a standardized measurement. The Irritability Scale (IS), tailored for HD, has patient and informant versions, but variable interrater agreement has been reported frequently in previous studies. To enhance the clinical utility of the IS, this study aimed to identify the most reliable components estimating the underlying construct and develop a shortened version for time-limited contexts. MethodsParticipant and informant/observer concordance and the relationship of individual items to the complete IS scale were assessed. The short-form (SF) items were selected based on interrater agreement, exploratory factor analysis (EFA), and Item Response Theory (IRT) analysis results. Pair-wise correlation and covariance models were used to examine how SF predicted total IS score in 106 participants from the STAIR (Safety, Tolerability, and Activity of SRX246 in Irritable Subjects with Huntington's Disease) trial. Item Response Theory (IRT) analysis was used to evaluate the range and function of the selected items. ResultsIS interrater agreement was statistically significant (r = 0.33, p = .001). In combination with EFA factors and IRT analyses, five items were identified that showed good reliability and performance in differentiating levels of irritability. ConclusionThe proposed 5-item SF IS provided a reliable measure of the full scale and may be less burdensome for use in a clinical setting.

Psychological wellbeing among parents of a child living with a serious chronic illness: A cross-sectional survey study.

Parents of a child with a chronic illness can experience greater distress than the average population, yet little is understood about differences between illness groups. This cross-sectional survey study aimed to compare parents' psychological distress and perceived wellbeing across five chronic illnesses. Parents from one Australian pediatric hospital completed the Kessler Psychological Distress Scale and seven purpose-designed items about their wellbeing. Data from 106 parents (cancer = 48, cystic fibrosis [CF] = 27, kidney disease = 12, gastrointestinal condition/disorder = 9, developmental and epileptic encephalopathy [DEE] = 10) was analysed using bivariate Pearson's Correlation and linear mixed-effects models. Parents' distress scores differed between groups (F(4,80) = 2.50, p = .049), with the DEE group reporting higher distress than the CF group (mean difference = 6.76, 95% CI [0.11, 13.42]). Distress scores were moderately correlated to parents' perceptions of their child's health and their own wellbeing. Parents' self-reported coping with their child's condition/treatments differed (F(4,81) = 3.24, p = .016), with the DEE group rating their coping as poorer than the CF group (mean difference = -25.32, 95% CI [-46.52, 4.11]). Across all groups, parents reported unmet needs, particularly for psychosocial support and practical/financial assistance. Support interventions may be most effective if tailored to the child's illness, with greater support potentially needed for parents who have a child with DEE and/or severe comorbidities.

A hybrid data-driven framework for loss prediction of MCA airfoils

The Multi Circular Arc airfoils family has gained significant popularity in axial compressor design due to its capability to achieve higher pressure ratios with lower losses compared to conventional NACA airfoils. However, modeling their aerodynamic performance for transonic axial compressors remains a challenging task. This research addresses this issue by developing a data driven model for Multi Circular Arc airfoils loss correlation utilizing an automated blade-to-blade flow solver, StarCCM, under specific flow boundary conditions. Since the data built in this research includes high dimensionality, it is subjected to dimensionality reduction using Principal Component Analysis while retaining as much of its important information as possible. What sets our research apart is the comparative analysis of hybrid machine learning approaches. We specifically combine classification techniques based on shock wave formation on the airfoil’s suction side with Multi-Layer Perceptron neural network methods. This unique combination allows for a comprehensive prediction of MCA loss as the main objective of the research. The results demonstrate that this surrogate-based approach provides accurate loss model with 97% of precision error for the classification which results in 0.99 and 0.94 of R2 for loss model related to the transonic and subsonic airfoils loss prediction.

Investigation of The Relationship Between International Students’ Levels of Cultural Intelligence and Their Intercultural Sensitivity and Acculturation

The aim of the present research is to investigate the relation between the cultural intelligence levels of international students and their acculturation and intercultural sensitivity levels. The research was conducted with a total of 353 female and 282 male participants studying at Bursa Uludağ University. The participants were students from different countries and from different ethnic origins. Scales for measuring intercultural sensitivity, cultural intelligence, and acculturation, as well as a personal information form, were employed in the research, which used a correlational survey model inside a quantitative research design. In the analysis of the data, confirmatory factor analysis was utilized to analyze the construct validity of the scales, and to examine the reliability, the Cronbach alpha internal consistency coefficients were calculated and interpreted. While investigating the relationships between the scores obtained from the scales in the study, the Spearman-Brown correlation coefficient was calculated and regression analysis was implemented when examining the predictive status between the scores. According to the results of the current research, there was a low-level positive relationship between international students' levels of cultural intelligence and acculturation and a moderately positive relationship between their levels of cultural intelligence and intercultural sensitivity.

An Examination of How Toxic Leadership Behaviours of School Principals Relate to Teachers' Perceived Stress

The study examines how toxic leadership behaviours of school principals relate to teachers' perceived stress. It is a correlational survey model, and the sample consists of 278 primary and secondary school teachers. We collected the data with the Perceived Stress Scale and Toxic Leadership Scale. The findings show that gender does not cause a statistical difference in perceived stress and all dimensions of toxic leadership. Stress levels of branch teachers are higher than those of primary school teachers, with a statistically significant difference. The perception of branch teachers in ignorance, self-interest, and negative mental state of toxic leadership is significantly higher than classroom teachers. A moderately significant positive relationship exists between teachers' perceptions of stress and all dimensions of toxic leadership. 20% of teachers' perceptions of stress are explained by toxic leadership. The negative mental state of school principals is a significant predictor of teachers' perceptions of stress.

A New Spatial Variation Model for Ground-Motion Intensities Combined with Correlation and Coherency

Abstract Regional seismic risk or loss assessments generally require simulation of spatially distributed ground motions using multiple intensity measures. Hence, in this study, ground-motion model estimation is performed with a spatial correlation. Previously, many researchers have analyzed spatial correlations and developed empirical models using ground-motion recordings. In this study, ground motions occurring in California between 2019 and 2023 were used to analyze spatial correlations using semivariograms for the peak ground acceleration and pseudospectral acceleration in various spectral periods. Based on the analysis results, two aspects need to be revised in the conventional correlation model: (1) the empirical exponential model cannot reasonably reflect the target spatial correlation at a separation distance &amp;lt;10 km, and (2) the variation in the spatial correlation ground-motion intensity cannot be described at a small separation distance &amp;lt;1 km. Owing to these limitations, we revised the fitting model of the semivariogram to better characterize the spatial correlation. In the model, another function called coherency, replaced the spatial correlation to characterize the variation in the Fourier phase rather than the intensity within a separation distance &amp;lt;1 km. This research shows that the spatial variation in any region can be analyzed by combining the coherence and correlation functions for practical seismic-risk or loss assessment problems.

Human–robot interaction-oriented video understanding of human actions

This paper focuses on action recognition tasks oriented to the field of human–robot interaction, which is one of the major challenges in the robotic video understanding field. Previous approaches focus on designing temporal models, lack the ability to capture motion information and build contextual correlation models. This may result in robots being unable to effectively understand long-term video actions. To solve these two problems, this paper propose a novel video understanding framework including: an Adaptive Temporal Sensitivity and Motion Capture Network (ATSMC-Net) and a contextual scene reasoning module called Knowledge Function Graph Module (KFG-Module). The proposed ATSMC-Net can adaptively adjust the frame-level and pixel-level sensitive regions of temporal features to effectively capture motion information. To fuse contextual scene information for cross-temporal inference, the KFG-Module is introduced to achieve fine-grained video understanding based on the relationship between objects and actions. We evaluate the method using three public video understanding benchmarks, including Something-Something-V1&V2 and HMDB51. In addition, we present a dataset with real-world application scenarios of human–robot interactions to verify the effectiveness of our approach on mobile robots. The experimental results show that the proposed method can significantly improve the video understanding of the robots.

The correlation between domestic violence awareness and attitudes toward child marriage: The case of Turkey.

The aim of this study is to determine the correlation between domestic violence awareness and attitudes toward child marriages among individuals living in Iğdır city. The correlational survey model was used in the study. The sample consisted of 814 adult individuals who lived in Iğdır city, did not have any health problem, and volunteered to participate in the study between September 2022 and January 2023. Personal Information Form, Domestic Violence Awareness Scale, and Attitude Toward Child(Girls) Marriages Scale were used to collect data. Data were obtained through online environment and face-to-face interview. It was found that 59.5% of the sample group were female and 27% were aged between 18 and 24 years. 61.9% of the participants were married and 88.1% were married when they were over the age of 18. In addition, 51.9% were university graduates while 50.9% of them stated that they had witnessed domestic violence. The results of the study revealed that while the variables of gender, age, marital status, education level, and place of residence affected the attitudes toward child marriages, the variables of gender, age, age at marriage, education level, place of residence and witnessing domestic violence affected domestic violence awareness. Furthermore, when examining the scales used, it was concluded that the attitude toward child marriages affected the awareness of domestic violence. Since domestic violence and child marriages are very common, it is recommended to conduct further studies on these issues and to identify support systems that will increase the awareness of the society on these issues.

Lespedeza potaninii Vass seed yield response to plant density and phosphate fertilization in Northwest China

Lespedeza potaninii Vass is a highly drought-resistant China native legume plant, which plays an important role in animal husbandry and ecological restoration. However, there are few reports on the agricultural practices of its seed production. We evaluated the effect of four plant densities (33,333, 44,444, 66,666, and 133,333 plants ha−1) and five phosphate fertilizer rates (0, 45, 90, 135, and 180 kg ha−1) on seed yield, seed yield components and agronomic traits from the year 2020–2022. Correlation and structural equation model (SEM) analyses were used to determine the contribution of yield components to seed yield per plant. Year, plant density, phosphorus fertilizer rate and their interaction (P<0.05) significantly influenced the seed yield of L. potaninii Vass. The maximum average seed yield over 3 years (570 kg ha−1) occurred at the plant density of 44,444 plants ha−1 and phosphate fertilizer rate of 90 kg/ha. All the yield components, except 1000-seed weight, were significantly correlated with seed yield per plant. The racemes per stem, florets per raceme and pods per raceme had significant positive correlation, and stems per square meter and biomass had significant negative correlation with seed yield per plant. Increasing phosphorus fertilizer increased seed yield per plant. However, increasing plant density decreased seed yield per plant. Our findings enable further understanding of the mechanism of seed yield response to plant density and phosphorus fertilization in L. potaninii Vass and provide a reference for appropriate agronomic measures to improve seed yield of L. potaninii Vass and similar shrubs.

Effects of the Kahramanmaras, Turkey 2023 earthquakes on balance perception, dizziness and post-traumatic stress: A relational screening model between subjective balance problems and post-traumatic stress

ObjectiveThe aim of the present study was to investigate the effects of the February 6, 2023, earthquakes in Turkey and recurrent aftershocks on balance and post-traumatic stress in surviving victims. MethodsOur study included 1004 participants aged 18–65 years who were exposed to the February 6 earthquakes and aftershocks in Turkey. After obtaining online consent from all participants, the Vertigo Symptom Scale (VSS), the Dizziness Handicap Index (DHI), and the Posttraumatic Post-Traumatic Disorder Checklist Scale (PCL-5) were administered online, and the interactions between the variable sets were examined using a correlational screening model. ResultsAs a result of the structural equation model established with the observed variables, it was found that VSS total scores had a statistically significant positive effect on PCL-5 (β1 = 0.56; p = 0.001 < 0.05). In addition, statistically significant positive high-level correlations were found between VSS and DHI (covVSS-DHI = 0.71), and a positive low level correlation with the number of days with dizziness (covVSS-number of days with dizziness = 0.34), and a positive low level correlation with frequency of days with dizziness (covVSS-frequency of days with dizziness = 0.37). A statistically significant positive low-level relationship was found between DHI and the number of days with dizziness (covDHI-number of days with dizziness = 0.34) and a positive low-level correlation between DHI and the frequency of days with dizziness (covDHI-frequency of days with dizziness = 0.29). ConclusionThe structural equation modeling analysis showed that post-traumatic stress disorder had a significant effect on balance and dizziness.

Abstract 6912: Pretreatment multiomics in conjunction with preclinical trials on patient-derived xenograft models of cholangiocarcinoma can identify chemotherapy response signatures

Abstract Background Cholangiocarcinoma (CCA) is a heterogeneous malignancy. Platinum-based chemotherapy (Gemcitabine and Cisplatin) has been the standard treatment for over a decade and is the base for the current immunotherapy combinations. Response rates are typically between 20-30%. Herein, we present outcomes of preclinical efficacy trials on CCA PDX models in correlation with baseline multiomics profiling of CCA patient-derived xenograft (PDX) models to identify molecular features associated with response. Methods Tumor samples from twenty-eight CCA PDX were used to isolate RNA and protein to be included in multiomics analysis (Phosphoproteomics, Proteomics, and Transcriptomics). A subset of PDX models were treated with various doses of Gemcitabine and Cisplatin. The Median Efficacy Index (MEI) was calculated as the ratio of the difference in median of delta in tumor volume at the last day of the study between the treatment and the control arms divided by the median of delta in tumor volume of the control at the last day of the treatment (positive= growth, negative=inhibition, and 0=no efficacy). A Hierarchical All-Against-All algorithm was utilized to compare multiomics features to the MEI and pathway analysis completed for identified molecular features. Results After conducting preclinical efficacy trials, the five tested CCA PDX models were classified into sensitive, moderately sensitive, and resistant models based on the MEI on each treatment arm. The top up-regulated genes were identified for Gemcitabine response (SRPK2, GLK2, and RIOK2) and Cisplatin response (NTRK1, PRPF4B, and SRPK2). The top up-regulated genes related to Gemcitabine resistance were NTRK1, PIP5K1C, and CSNK2A2, while those related to Cisplatin resistance were SRPK1, PRPF4B, and CSNK2A1. Conclusion Cholangiocarcinoma multiomics signatures can predict therapeutic response to standard-of-care chemotherapy in preclinical models. Novel mechanisms of Gemcitabine and Cisplatin resistance were identified related to NTRK1, SRPK1 and SRPK2. Resistant signatures will be challenged with the appropriate targeted therapies on the resistant CCA PDX models. Citation Format: Amro M. Abdelrahman, Danielle M. Carlson, Erik Jessen, Dong-Gi Mun, Isaac Lynch, Alessandro Fogliati, Stella Konadu Adjei Antwi, Aushinie Abeynayake, Akhilesh Pandey, Mark J. Truty, Gregory J. Gores, Rory L. Smoot. Pretreatment multiomics in conjunction with preclinical trials on patient-derived xenograft models of cholangiocarcinoma can identify chemotherapy response signatures [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6912.