Quantitative Analysis Research Articles

Obstructive factors encountered when using immersive technology in tourism heritage: the moderating effect of the personal capability via SEM-PLS process

Purpose There is a void in systematically assessing obstructive factors as antecedents in the technology acceptance model (TAM). Three obstructive factors are investigated, namely, discomfort, insecurity and risk. Besides, this study aims to propose the moderator – personal capability (PC) and tested its effects on the relationship between perceived usefulness (PU) and perceived ease of use (PEU) and behavioral intention (BI). Design/methodology/approach Quantitative data analysis was used to verify the adapted model by using Smart PLS4. The data from 327 valid respondents are analyzed. Findings Discomfort is a significant antecedent impacting both PU and PEU. Insecurity and risk are inhibitors of PEU and PU, respectively. This study contributes to the scarce literature on the moderating effects of PC that moderates the influence between PU and BI positively. Originality/value This study contributes a new TAM extension by incorporating obstructive factors and exploring the moderating role of personal capability about AR Glasses. This research also enables innovation companies to enhance the design of their products and services via users’ feedback.

QuPath Edu and OpenMicroanatomy: Open‐source virtual microscopy tools for medical education

AbstractVirtual microscopy is becoming increasingly common in both medical education and routine clinical practice. Virtual microscopy software is typically designed either for (1) training students in anatomy, histology, and histopathology, or (2) quantitative analysis—but not both simultaneously. QuPath is one of the most widely used software applications for histopathology image analysis in research and provides a comprehensive set of computational tools to evaluate histology slides. We have enhanced QuPath by developing a new extension, QuPath Edu, which adapts the software to function as an intuitive microanatomy learning environment. Additionally, we have created an entirely new, complementary software platform called OpenMicroanatomy, which provides an alternative way to access QuPath Edu teaching content through a web interface. These tools have been used in teaching of first year medical and dentistry students at the University of Oulu Medical Faculty, and we conducted a user survey for the Class of 2023 to assess the usability and student experience. In general, the introduced annotation and quiz features were appreciated by the students and the system usability of OpenMicroanatomy was considered excellent (SUS score 84.8). Together, these freely available tools enable teachers to develop and deploy innovative training material for anatomy, histopathology, quantitative analysis, and artificial intelligence in a wide range of contexts. This unique combination can provide the next generation of students with essential multidisciplinary skills.

Li2B4O7 XPS using monochromatic Ag Lα x rays

XPS spectra of lithium tetraborate (Li2B4O7) were obtained using an Ag Lα (2984.3 eV) source and a quartz (1010) crystal monochromator through second order diffraction. Irradiation occurs on the sample at 54.7° to the surface normal. Spectra of the principal lines include O 1s, C 1s, B 1s and Li 1s. Spectra of O KLL, O 2s and Valence band were also acquired. Quantitative analysis was performed using Cant sensitivity factors.

Logistics challenges in used car maritime traffic from Europe to west Africa

This paper addresses the main logistics challenges in used car maritime traffic from Europe to West Africa. Thus, the methodology (quantitative and qualitative) analyses data from the International Organization of Motor Vehicle Manufacturers (OICA), from 2015 to 2023 of government and port authorities to show the importance of used car market for mobility and socioeconomic activities. This is supplemented by surveys based on direct observation in the field, questionnaires and interviews involving in Europe 55 stakeholders and 127 in Africa. The results demonstrate that cars used and their parts, but not wrecks, are essential for motorization in West Africa. A pre-export process needs to be set up to ensure that exported vehicles are parked in better condition to meet the required common environmental standards for sustainable mobility.

Development of video tutorials on building construction and utilities subjects assisted by Bandicam application for grade XI students at vocational high school

The implementation of Building Construction and Utilities learning for class XI in Vocational High School (VHS) has faced several challenges including student understanding, teachers’ competency, and learning media. This study aims to result in a product, including the feasibility test and effectiveness on the topic of door and window frame details drawing assisted by the Bandicam application. We employed the Research and Development (R&D) model of 4D Thiagarajan. The trial was conducted on 14 students of the Building Information and Modeling Design (DPIB) expertise program class XI with input from 2 experts and 1 teacher. The data was collected through interviews, observations, and questionnaires. The obtained data was analysed using quantitative and qualitative descriptive analysis and descriptive statistics. The results show that the 4 video products were feasible and effective as seen from the improvement of student learning outcomes in the subject of building construction and utilities.

The Role of AI in Data Engineering and Integration in Cloud Computing

This article presents a comprehensive analysis of the transformative role of Artificial Intelligence (AI) in revolutionizing data engineering and integration processes within cloud computing environments. The article examines the implementation of AI-driven solutions across multiple dimensions, including automated pipeline generation, intelligent schema matching, anomaly detection, and real-time data integration. Through a mixed-methods approach incorporating both quantitative and qualitative analyses, the article demonstrates significant improvements in data processing efficiency, with organizations achieving up to 67% reduction in processing time and 89% enhancement in accuracy. The article encompasses case studies from financial services, healthcare, and e-commerce sectors, providing concrete evidence of practical applications and scalability. Key findings reveal that AI-powered systems substantially outperform traditional approaches in cost efficiency, scalability, and data quality management, while simultaneously reducing operational overhead. The article also addresses implementation challenges, including legacy system integration and initial deployment complexities, offering strategic insights for organizations pursuing AI integration in their data engineering workflows. These article contribute to the broader understanding of how AI technologies can be effectively leveraged to address the growing challenges of data management in cloud computing environments, while providing a framework for future developments in this rapidly evolving field.

Developing WasteSAM: A novel approach for accurate construction waste image segmentation to facilitate efficient recycling

The escalating volume of construction activities and resultant waste generation underscores the imperative for developing sophisticated segmentation models to facilitate efficient sorting and recycling processes. This study introduces WasteSAM, an enhanced iteration of the segment anything model (SAM), specifically tailored to address the intricate complexities inherent in construction waste imagery. Drawing upon a comprehensive dataset comprising over 15,000 masks representing five distinct categories of construction materials, WasteSAM exhibits notably superior segmentation capabilities. Quantitative analysis demonstrates significant performance improvements, with WasteSAM outperforming the original SAM model by an average of 23.9% in dice similarity coefficient and 30.0% in normalized surface distance metrics. The integration of stereo-image techniques in refining the training dataset has facilitated WasteSAM in more accurately discerning the three-dimensional structure of waste materials, thereby augmenting the precision of waste classification. Noteworthy is the model’s adeptness in handling intricate textures and patterns across diverse imaging modalities, including varying lighting conditions and complex object interactions. While showing promising results, this study also highlights the need for high-quality, diverse datasets that reflect real-world construction site complexities, rather than merely larger datasets.

Implementation of Car-Free Days in Support of Sustainable Development to Reduce Vehicle CO2 Emissions in Urban Areas

The transportation sector is one of the main contributors to global greenhouse gas emissions, accounting for 18.52% of total emissions, with this percentage reaching 40% in developed countries. This research aims to assess the effectiveness of Car-Free Day (CFD) implementation in reducing emissions in Cirebon, Indonesia, as a contribution to the 13th Sustainable Development Goal on climate action. The research method used a mixed approach, combining quantitative analysis of fuel consumption data with qualitative interviews to gain a comprehensive understanding of the impact of CFD. Referring to the Ministry of Environment and Forestry's National Greenhouse Gas Inventory guidelines, Book I: The results showed that while CFD reduced emissions by 13-26% in the designated lane due to traffic diversion, it also led to an 8-14% increase in emissions in the alternative lane. Therefore, the overall emission reduction effort was not optimal, as the emission reduction in one lane was masked by the emission increase in the other lane. The implication of this research is that a more holistic approach is needed to effectively reduce urban greenhouse gas emissions. The results of this research can serve as a basis for formulating more effective transportation policies, such as extending the duration and coverage of CFD, restricting vehicles on alternative routes, and improving public transportation systems that are more environmentally friendly.

Corneal subepithelial nerve fibers in type 2 diabetes: potential biomarker of diabetic neuropathy

AIM: To observe the changes in corneal subepithelial nerve fibers (CNFs) and Langerhans cells (LCs) in patients with type 2 diabetes using corneal laser confocal microscopy (CLCM). METHODS: A total of 60 patients (64 eyes), including 40 patients with type 2 diabetes (DM group) and 20 subjects without diabetes (control group) were included with CLCM. Neuron J plugin of Image J software were used for quantitative analysis of CNF length (CNFL), CNF density (CNFD), corneal nerve branch fiber density (CNBD), main branch length density, branch length density, corneal nerve fiber tortuosity (NT) score, and LCs density. An independent samples t-test to analyze the variability between the two groups was performed, and Pearson correlation analysis was used to analyze the relationships between CNF and multiple biochemical indicators in the DM group. The predictive power of CNF for type 2 diabetes was assessed using the receiver operating characteristic (ROC) curve. RESULTS: There were significant differences in the CNFL, CNFD, and main branch length density between two groups. The results of Pearson correlation analysis showed a significant negative correlation between CNFD and the duration of diabetes as well as triglyceride levels and total cholesterol, and a significant positive correlation between CNFD and serum albumin. In addition, the NT score showed a positive correlation and urea nitrogen, similar to the positive correlation observed between LC density and glycosylated hemoglobin (HbA1c) levels. CNFD showed the highest area under the curve (AUC of ROC) value, followed by main branch length density and CNFL. The AUC of the ROC curve under the logistic regression model also demonstrated good predictive values. The cut-off values of CNFD, CNFL, and main branch length density for diabetes showed 31.25, 18.85, and 12.56, respectively. CONCLUSION: In patients with type 2 diabetes, there is a notable reduction in both CNFL and CNFD. These measurements can be influenced by various blood biochemical factors. However, the compromised nerve fibers can serve as valuable indicators for predicting the onset of type 2 diabetes and also as biomarkers for detecting diabetic neuropathy and its related complications.

Workplace violence against medical students during clinical practice and its relevant factors: a mixed methods study

ABSTRACT Our study aims to describe the status of workplace violence against medical students during clinical practice, which consists of its prevalence, types, perpetrators, students’ responses and influences on them, reasons for workplace violence and to determine some relevant factors of this issue through both quantitative questionnaire and qualitative interview. A descriptive cross-sectional study with mixed methods was conducted on 320 students from the second-year to the sixth-year classes at Hanoi Medical University from August 2022 to February 2023. The questionnaire was based on the WHO questionnaire survey ‘Workplace violence in the health sector – country case studies research instruments – Geneva 2003’. 10 students from quantitative research who completed the questionnaire, experienced at least one type of workplace violence and consented to continue taking part in the research were chosen for in-depth interviews. The prevalence of students witnessing and/or experiencing workplace violence was 35.6% and 19.4% of the sample population had experienced at least one kind of workplace violence. Medical staff were the most common perpetrators. 86.8% of students who were exposed to workplace violence did not report the incidents for a variety of reasons. The major reasons leading to workplace violence related to patients, patients’ relatives and students, among which the first-ranked ones were the patients’ education level and their unsatisfied expectations. Some relevant factors to workplace violence against medical students were determined by quantitative analysis such as students’ grade (OR = 3.09) and region (OR = 3.31) and were explored additionally by qualitative interview such as the student management of the instructors, students’ personality, attitude and appearance as well as hospital environment. Based on the research findings, establishing prevention methods, which require action from both individuals (students, medical staff) and organizations (universities, hospitals) is recommended.

Abstract B010: Improving pancreatic cancer image classification with transfer learning: CD45 vs. PANCK

Abstract Pancreatic ductal adenocarcinoma (PDAC) is known for its high aggressiveness and is the fourth most common cause of death of cancer-related death in the United States. It is highly malignant and often goes undiagnosed until advanced stages due to its late-onset symptoms, resulting in poor prognosis. Using quantitative analyses of histological features, such as the expression of prognostic biomarker, can provide valuable insight to guide treatment decisions, monitor disease progression and predict outcomes. Previous researchers have found that CD45 and PANCK play a huge role in characterizing the tumor microenvironment of PDAC. One study using single-cell RNA sequencing compared the microenvironments of healthy pancreata and pancreatic tumors, revealing differences in cellular composition. Tumor samples showed a higher proportion of immune cells, including CD45+ cells, compared to heathy samples and utilized PANCK to differentiate between epithelial and non-epithelial cells. This study aims to enhance the accuracy of classifying pancreatic cancer pathological images based on prognostic markers using transfer learning techniques. We curated and pre-processed a dataset of pancreatic cancer pathological images with different prognostic markers. Using the pre-trained convolutional neural network (CNN) model VGG16, we fine-tuned it with our dataset to better differentiate between two prognostic markers, CD45 and PANCK. The model's performance was evaluated using a similarity matrix to illustrate distinctions among the two prognostic markers. Our results demonstrate that the transfer learning approach significantly improves classification accuracy, achieving confusion matrix validation results of 90% between CD45 and PANCK prognostic markers. SSIM values were relatively low, highlighting the ability of our model to differentiate between the two prognostic markers. The low SSIM value also shows variability within the two prognostic markers, indicating heterogeneity in structural changes due to pancreatic cancer. These findings indicate that transfer learning can be a powerful tool for improving the classification of pathological images and that there is notable variability in the structural features associated with different prognostic markers in pancreatic cancer. Citation Format: Miracle Thomas. Improving pancreatic cancer image classification with transfer learning: CD45 vs. PANCK [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr B010.

Progressive Bulbar Palsy Care: Exploring the Potential of Functional MRI for Early Detection

Progressive bulbar palsy (PBP) is a neurodegenerative disorder impacting motor neurons involved in speech, swallowing, and breathing. Early diagnosis is challenging due to limited diagnostic tools. Functional MRI (fMRI) holds promise for detecting early biomarkers and tracking disease progression, potentially improving clinical management. This study aims to explore the utility of fMRI in developing imaging biomarkers for the early detection, prognostication, and monitoring of PBP. By addressing existing gaps in the literature, the research seeks to demonstrate how fMRI can enhance diagnostic accuracy, provide predictive insights into disease progression, and improve patient outcomes. A systematic literature review was conducted using databases such as Google Scholar. The search focused on articles published from 2018 onwards, using keywords related to PBP and fMRI. Inclusion criteria included peer-reviewed studies involving human subjects relevant to the use of fMRI in PBP. Exclusion criteria excluded non-peer-reviewed articles, non-English publications, and studies not specifically addressing fMRI in PBP. Data synthesis involved both qualitative and quantitative analyses of identified biomarkers, diagnostic accuracy, and prognostic value. The review identified several fMRI biomarkers that show potential for early detection and monitoring of PBP. These biomarkers, derived from functional and structural changes in corticobulbar pathways, offer enhanced sensitivity compared to traditional diagnostic methods. Predictive models based on fMRI metrics can forecast disease progression, aiding in personalized treatment planning. The study concludes that integrating fMRI into clinical practice could lead to earlier interventions, more accurate prognostic assessments, and improved management of PBP, ultimately enhancing patient quality of life and outcomes.

What does it mean to “do your own research?” A comparative content analysis of DYOR messages in Instagram and Facebook posts about reproductive health, food, and vaccines

Calls to “do your own research” (DYOR) on social media promote a range of claims, from expert-recommended treatments to conspiracy theories. Exploring how the slogan is used offers insight into how individuals navigate concerns about information accuracy in an abundant but low-trust media ecosystem. This quantitative content analysis investigates how DYOR messages in Facebook and Instagram posts about reproductive health, food and diet, and vaccination are used to raise alarms, promote personal agency, and disclaim responsibility. We additionally examine how DYOR messages are associated with content including risk information and product promotion. While DYOR messages sometimes raise alarms about suspected conspiracies and misinformation, more often they advocate for personal agency and education, encouraging people to become as informed as possible to make the best decisions for themselves. In this way, DYOR messages promote individual responsibility for navigating information risks and reflect wider concerns about (mis-)information and distrust of institutions.

Effects of laser treatment on bond strength of epoxy resin and calcium silicate-based sealers: a systematic review and meta-analysis of in vitro studies.

This study aimed to systematically review the effect of laser treatment on the bond strength of epoxy resin-based and calcium silicate-based endodontic sealers to root dentine. The search encompassed four databases: PubMed/MEDLINE, EMBASE, Scopus, and ISI Web of Science. Inclusion criteria were limited to in vitro studies conducted on extracted human teeth evaluating bond strength in megapascals (MPa) of either epoxy resin-based or calcium silicate-based sealers, using the push-out test. Two independent reviewers appraised the methodological quality of the selected studies to assess the risk of bias. Meta-analysis was performed for different laser types, endodontic sealers, and control groups. Standard Mean Difference and 95% Confidence Interval values were calculated. 17 studies met the inclusion criteria for qualitative synthesis, and 15 for quantitative analysis. Meta-analyses revealed that certain lasers (Er,Cr:YSGG, Er:YAG) significantly increased bond strength for epoxy resin-based sealers when compared to negative controls (inert solutions), but did not show a significant advantage over EDTA agent. For calcium silicate-based sealers, laser treatment did not show significant enhancement in bond strength compared to either inert solutions or EDTA. The subgroup analysis suggested that erbium lasers, especially in the PIPS mode, potentially increase the bond strength of epoxy resin-based sealers. Laser treatment enhances the bond strength of epoxy resin-based sealers compared to inert solutions, but not more than EDTA. For calcium silicate-based sealers, laser treatment does not significantly improve bond strength over inert solutions or EDTA. Laser treatment increases the bond strength of epoxy resin-based sealers.

On the Multiscale Processes Leading to an Extreme Gust Wind Event in East China: Insights From Radar Wind Profiler Mesonet Observations

AbstractIn this study, a record‐breaking surface gust wind event of over 45 m s−1, which occurred in the coastal region of East China during the early evening hours of 30 April 2021, is examined. The dynamical characteristics of this event is explored by using a high‐resolution mesonet comprised of eight radar wind profilers (RWPs), surface observations, radar and satellite data. Observational analyses show the development of several cloud clusters ahead of the axis of a midlevel trough with pronounced baroclinicity, and the subsequent organization into a comma‐shaped squall system with a leading convective line over land and a trailing stratiform region moved offshore. The latter is embedded by a mesovortex with intense northerly rear inflows descending to the surface, accounting for the generation of the gusty winds. Results indicate the different roles of multi‐scale processes in accelerating the surface winds to extreme intensity. Specifically, the large‐scale baroclinic trough provides intense background rear inflows that are enhanced by the formation of the mesovortex, while moist downdrafts in the rear inflows account for the downward transport of horizontal momentum, leading to the generation of intense cold outflows and gusty winds close to the leading convective line. Despite the lack of sufficient observations for quantitative analysis, this study provides a qualitative analysis that offers valuable insights into the dynamics of extreme gusty winds. Moreover, the above results underscore the value of RWP mesonet observations in enhancing our understanding of extreme wind events and in improving the nowcasting and prediction efforts in the future.

Harmonizing human-computer interaction: Exploring evolution and integration in media and computing

Abstract. This paper delves into the intricate relationship between Human-Computer Interaction (HCI), media, and computing, examining its historical evolution and contemporary challenges. From the rudimentary interfaces of the 1970s to the immersive digital experiences of the present day, HCI has undergone a profound transformation, driven by advancements in technology and changing user expectations. The convergence of media and computing technologies has blurred traditional boundaries, reshaping user interactions and opening new frontiers for research and innovation. Through quantitative analysis and mathematical modeling, researchers gain insights into user behavior, preferences, and interactions, informing the design of more intuitive and engaging interactive systems. However, this integration also poses challenges related to cross-platform compatibility, ethical considerations, and accessibility. By embracing user-centered design principles, ethical stewardship, and technological innovation, HCI researchers and practitioners can navigate these challenges and shape the future of HCI-Media-Computing integration.

Unveiling the Impact of Emotional Regulation on Academic Procrastination

This study examines how consumer perceptions of the Skintific brand, product quality, and pricing influence product selections among 110 FBHIS students at Muhammadiyah University of Sidoarjo. Using online questionnaires and quantitative analysis methods, including validity and reliability tests, multiple linear regression, and t-tests, the research reveals significant relationships between brand image, product quality, pricing, and consumer purchasing decisions. The findings emphasize the importance of these factors in shaping consumer behavior, particularly among university students, and offer insights for skincare companies targeting this demographic to enhance brand image, maintain product quality, and offer competitive pricing strategies. Highlight: Quantitative Analysis: Validity, reliability tests, regression for consumer behavior research. University Sample: Investigated FBHIS students' purchasing choices at Sidoarjo University. Strong Associations: Brand image, product quality, pricing linked to consumer decisions. Keywoard: Consumer perceptions, Skintific brand, Product quality, Pricing, Decisions

Laser therapy for Bell's palsy: a systematic review and meta-analysis of randomized trials.

This meta-analysis investigated therapeautic effects of laser therapies in patients with Bell's palsy (BP). The authors performed the literature search in the PubMed, Embase, and Cochrane Library databases using the following search terms: (facial paralysis OR Bell's palsy OR facial palsy OR idiopathic facial paralysis) AND (laser OR low-level laser OR photobiomodulation OR phototherapy). Relevant studies published before October 29th 2024 were identified. Randomized trials comparing the outcomes of laser therapies with other interventions, including electrical stimulation and control or usual care in patients with BP were included. The mean difference (MD) was determined as the effect size for continuous outcomes, and outcome accuracy was determined using 95% confidence intervals (CIs). Twelve studies were included, with a total of 597 patients. Nine studies were further included in the quantitative analysis. Our meta-analysis revealed that laser therapy significantly improved disease severity (House-Brackmann facial paralysis scale) (MD = -1.51, 95% CI = -2.43 to -0.59), facial asymmetry (Sunnybrook facial grading system) (MD = 20.63, 95% CI = 10.33 to 30.94), and facial function and disability (Facial disability index) (MD = 17.91, 95% CI = 5.60 to 30.22) when compared with control care in adult patients. Moreover, laser therapy significantly improved facial severity (MD = 21.05, 95% CI = 16.77 to 25.33) when compared with electrical stimulation. In addition, no adverse effects of laser therapy were reported. Laser therapy has favorable effects on disease severity, facial asymmetry, and facial function and disability for patients with BP.

The Effect of Work Communication on Employee Turnover Intention

Work communication encompasses the exchange of information, ideas, and understanding between individuals or groups within an organization. Effective communication can strengthen relationships among team members, management, and employees in creating a healthy work environment. On the other hand, issues such as compensation problems and work stress are frequently experienced by employees and can lead to major challenges like high turnover rates, as faced by PT PG Rajawali II Cirebon. This research aims to determine the influence of work communication on employee turnover intention at PT PG Rajawali II Cirebon, specifically regarding employees' desire to stay or leave the organization. This research employs quantitative methods and statistical analysis with a population of 125 people, applying theories of work communication and turnover intention. The results show that 16.4% of turnover intention within the company is caused by inhibited communication. Communication at PT PG Rajawali II Cirebon is still lacking, as work errors due to employee miscommunication ultimately affect employees' intention to leave the company. The implications of this research indicate that effective work communication within an organization can strengthen relationships, enhance job satisfaction, and reduce turnover intention or the desire to leave. Based on the research results, it can be concluded that good work communication can reduce turnover intention by increasing employee satisfaction and engagement.

Regulatory Effects of Copper on Ghrelin Secretion in Rat Fundic Glands.

Copper (Cu) is an effective additive in feed for promoting growth. Growth dan axis comprising growth hormone (GH), somatostatin (SS) and GH-releasing hormone (GHRH), with ghrelin regulating their release. The growth-promoting effects of Cu are closely related to ghrelin, but the specific mechanism behind the relationship remains unknown. We investigated the adjustment of ghrelin synthesis and secretion by Cu. Sprague-Dawley rats were fed basal diets with an addition of 0, 120 or 240 mg/kg Cu sulfate for 28 day to establish a growth-promoting model. Signalling molecules relevant to ghrelin synthesis and secretion were detected and mechanistically explored using enzyme-linked immunosorbent assay, quantitative reverse-transcription polymerase chain reaction and Western blot analysis. The 120 mg/kg supplement improved growth performance; significantly increased the serum levels of ghrelin, ghrelin O-acyltransferase (GOAT), acylated ghrelin (AG), GH, and reactive oxygen species (ROS) and decreased those of SS; significantly increased the mRNA and protein expression of ghrelin, GOAT, ghrelin receptor (GHS-R1α), and activator protein 1 (AP-1); increased the phosphorylation ratio of JNK and p38 MAPK; and inhibited the mRNA and protein expression of SS and SS receptor subtype 2 (SSTR2) in gastric fundic gland tissues. Thus, Cu may affect gastric ghrelin synthesis at the transcriptional level by activating the JNK/p38 MAPK pathway through increased ROS levels and regulating the activation of the downstream redox-sensitive transcription factor AP-1. SS plays a crucial determinant role in ghrelin regulation via intragastric Cu. Cu promotes GOAT activity and ghrelin secretion by inhibiting SS secretion, affecting AG levels, and promoting ghrelin acylation through ghrelin/GOAT/GHS-R1α system, modulating ghrelin secretion.