Management Applications Research Articles

A Comprehensive Review on the Anti-Obesity Potential of Limonia acidissima L., and its Bioactive Compounds: Mechanisms and Applications in Weight Management

Introduction: Obesity is a global health challenge associated with numerous metabolic disorders, including diabetes and cardiovascular disease. With growing interest in natural remedies for weight management, Limonia acidissima L., has garnered attention due to its rich bioactive composition. Objectives: This systematic review evaluates the anti-obesity potential of Limonia acidissima L., and its key bioactive compounds, including fibres, phytosterols, saponins, polyphenols, flavonoids, and ascorbic acid. Methods: A comprehensive search of databases such as PubMed, Scopus, and Google Scholar was conducted, focusing on studies published between 2000 and 2023 that investigated the metabolic effects of these compounds on lipid and carbohydrate metabolism, fat absorption, and glucose regulation. Results: The results demonstrated that Limonia acidissima L., significantly reduced body weight and fat mass, improved lipid profiles, and enhanced insulin sensitivity in both animal and human studies.Phytosterols and saponins played key roles in modulating lipid metabolism, while fibres and polyphenols were found to regulate carbohydrate metabolism and improve glycemic control. Additionally, the synergistic effects of multiple bioactive compounds amplified their collective anti-obesity potential, with few reported adverse effects, suggesting a favourable safety profile. The discussion highlights the multifaceted mechanisms through which Limonia acidissima L., combats obesity, emphasizing its ability to target multiple metabolic pathways simultaneously.While the findings are promising, the need for further large-scale clinical trials to validate these effects in diverse populations is underscored. Conclusions: In conclusion, Limonia acidissima L., emerges as a potent natural remedy for obesity management, with strong potential for inclusion in weight loss supplements and functional foods.Its bioactive compounds offer a comprehensive and safe approach to addressing the global obesity epidemic, although further research is needed to establish its long-term efficacy and optimal use.

Intelligent Predictive Networks for Cattaneo-Christov Heat and Mass Transfer Dissipated Williamson Fluid Through Double Stratification

This study aims to develop an efficient predictive model for Cattaneo-Christov heat and mass transformation of dissipative Williamson fluid with the effects of double stratification (CCHMT-DWF-DS) using the Levenberg-Marquardt Backpropagation (LMA-BP) algorithm. The under-consideration Williamson fluid flow is magneto-hydro-dynamic, incompressible and two-dimensional through a stretching sheet. The mathematical model of nonlinear partial differential equations for physical phenomena is transformed into ordinary differential equations by means of renowned similarity transformations. The solutions of physical problem are computed by bvp4c technique through MATLAB. The LMA-BP is employed to train a backward neural network capable of accurately predicting velocity, temperature, and concentration profiles under various physical conditions such as changes in the Hartmann number , Prandtl number , Schmidt number , Williamson parameter , the relaxation time of temperature , the relaxation time of concentration , temperature stratification , and concentration stratification for generating a variety of graphical outcomes and statistics. This research is significant for its innovative use of the LMA-BP in analyzing the complex dynamics of non-Newtonian fluids specifically the Williamson fluid, alongside the Cattaneo-Christov heat and mass flux model. The obtaining graphs have been discussed in detail. The thermal and solutal relaxation factors reduce heat and mass flow while fluid motion is delayed by the time-dependent parameter and further reduced by the Hartman number. The Cattaneo-Christov heat flux model enhances simulation accuracy by integrating temporal delays in heat transfer, proving beneficial for sophisticated industrial and scientific endeavors related to non-Newtonian fluids. This analysis offers a powerful predictive tool for applications in thermal management, industrial cooling systems, and biomedical fluid dynamics, advancing machine learning in fluid mechanics.

Risk-averse supply chain management via robust reinforcement learning

Classical reinforcement learning (RL) may suffer performance degradation when the environment deviates from training conditions, limiting its application in risk-averse supply chain management. This work explores using robust RL in supply chain operations to hedge against environment inconsistencies and changes. Two robust RL algorithms, Qˆ-learning and β-pessimistic Q-learning, are examined against conventional Q-learning and a baseline order-up-to inventory policy. Furthermore, this work extends RL applications from forward to closed-loop supply chains. Two case studies are conducted using a supply chain simulator developed with agent-based modeling. The results show that Q-learning can outperform the baseline policy under normal conditions, but notably degrades under environment deviations. By comparison, the robust RL models tend to make more conservative inventory decisions to avoid large shortage penalties. Specifically, fine-tuned β-pessimistic Q-learning can achieve good performance under normal conditions and maintain robustness against moderate environment inconsistencies, making it suitable for risk-averse decision-making.

Highly stretchable and strain-insensitive multilayered electromagnetic interference shielding films prepared via a simple soaking-infiltration strategy

Stretchable electromagnetic interference (EMI) shielding films are crucial for wearable electronics. However, it is challenging to further endow the EMI shielding films with good stretchability and satisfactory EMI shielding effectiveness (EMI SE) under large strains. Herein, we successfully prepared high-performance stretchable polydimethylsiloxane (PDMS)/ single-walled carbon nanotube buckypaper (SWNT BP)/PDMS EMI shielding films with multi-graded conductive networks via a soaking-infiltration strategy. In this multilayered film, infiltration layers of SWNT/PDMS were particularly created between elastic PDMS and brittle SWNT BP. Owing to the multilayered structure and conductivity compensation effects arising from infiltration layers, our EMI shielding films exhibited excellent EMI SE of 34.2 dB with high stretchability of >400%. The outstanding EMI SE could be well maintained under large strains. At <50% strain, the relative change in EMI SE (|ΔSE/SE0|) remained consistently below 10%, while at even 100% strain, |ΔSE/SE0| was only ∼35%. Furthermore, we proposed a parallel-series hybrid model to describe electrical conduction in straining films. Due to their excellent conductivity under strain, the films could also serve as stretchable Joule heaters. This work provides a novel and simple approach for constructing strain-insensitive conductive films, with potential applications in stretchable EMI shielding and thermal management.

Tree Nut Crop Response to Simulated Florpyrauxifen-benzyl and Triclopyr Herbicide Drift

California is the nation’s primary producer of almonds, pistachios, and walnuts, and an important producer of rice. Because of California’s diverse cropping systems, off-target herbicide drift can be a considerable problem, particularly from aerial applications that are commonly used in flooded rice production systems. Triclopyr is an auxin-mimic type herbicide that has been commonly used in rice for many years for control of broadleaf weeds and the industry is familiar with symptoms of off-target triclopyr drift. Florpyrauxifen-benzyl is a newly registered auxin-mimic herbicide in California rice with activity on key weeds and is being rapidly adopted. Although symptoms typically are similar among auxinic herbicides, it is important to understand subtle differences and risks among these herbicides as stewardship for newly registered products. This research was conducted in 2020 and 2021 to determine the relative sensitivity of almond, pistachio, and walnut trees to simulated drift rates of florpyrauxifen-benzyl and triclopyr as well as characterize and compare symptoms caused by these two herbicides. The fractional herbicide rates tested were 1/200X, 1/100X, 1/33X, and 1/10X of the florpyrauxifen-benzyl use rate of 29.4 g·ha−1 a.i. and 1/200X, 1/100X, and 1/33X of the triclopyr use rate of 420.3 g·ha−1 a.e. Florpyrauxifen-benzyl and triclopyr herbicides were applied directly to one side of the canopy of 1- to 2-year-old almond, pistachio, and walnut trees. The general symptoms of florpyrauxifen-benzyl and triclopyr were chlorosis, chlorotic spots, leaf curling, leaf narrowing, leaf distortion, leaf malformation, leaf crinkling, shoot curling, stem coloring, stunting, terminal bud death, and twisting. The florpyrauxifen-benzyl and triclopyr injury symptoms were compared at the same fractional rates and found to be similar to each other. The herbicide injury was observed on the entire pistachio canopy, particularly on developing leaves and terminal buds. In contrast, injury symptoms on almond and walnut were more apparent on the side of the canopy to which the herbicides were applied. Symptom severity peaked at 14 days after treatment with the 1/10X florpyrauxifen-benzyl rate, when the visible injury was 16%, 48%, and 78% on almond, walnut, and pistachio, respectively. Although almond and walnut symptoms from the 1/10X florpyrauxifen-benzyl rate remained visible longer than all other treatments, all trees gradually recovered throughout the growing season. In contrast, pistachio trees did not recover fully and had injury symptoms that persisted for the remainder of the treatment year and at leaf-out the following spring. When drift occurs, it is typically at rates below 1/100X up to 1/33X of herbicide use rates. This research suggested that proper herbicide drift management practices and application precautions are likely to minimize the risk of significant injury from florpyrauxifen-benzyl drift to almond and walnut because of low injury symptoms at the typical drift rates. However, extra precautions may be needed if there are nearby pistachio orchards.

Microchannels-enabled Vertical Alignment of Hexagonal Boron Nitride in Silicone Rubber Composites to Achieve High Through-plane Thermal Conductivity

Hexagonal boron nitride (h-BN) with high vertical alignment in polymer composites is necessary to improve through-plane thermal conductivity (TC) for thermal management applications. However, how to achieve simple, efficient and precise control of h-BN vertical alignment in polymer composites remains a challenge. Herein, a novel concept of inducing vertical alignment of h-BN in silicone rubber (SR) composites via controlling flow patterns in specially designed microchannels was proposed. The extremely strong elongational and shear stresses provided by the narrow section of the microchannels induced h-BN to align perpendicular to the flow direction. In the subsequent channel, the weak shear stress manipulated h-BN to form a ladder structure in the SR composites, including the vertical core layer and horizontal skin layer. Such ladder structure not only improved the through-plane TC of SR composite but also prevented overheating in the face of local heat sources. Moreover, the obtained SR composites exhibit a through-plane TC of 5.08 W/mK at 34.3 vol % h-BN loading when the horizontal skin layer was removed, indicating excellent heat transfer efficiency for thermal management application. We believe that this work would strengthen both scientific and technological cognition of the filler alignment during polymer composites processing.

Spatial multi-criteria analysis based on food web model results: application to a marine conservation area

Effective marine management requires balancing conservation and sustainable use of resources. Food web models are useful for simulating direct and indirect effects of management scenarios on ecosystem functioning by using multiple indicators. However, a key challenge is consolidating these indicators into a single, comprehensive, measure, which is often required to guide management decisions, such as in Strategic Environmental Assessment. This study applies spatial multi-criteria analysis to food web model outputs to develop a single index for different marine management applications. We applied this framework to the case of the “Tegnùe di Chioggia”, a Special Area of Conservation (SAC; IT3250047) under the Natura 2000 European network, located in the northern Adriatic Sea (Italy). This area, characterised by the presence of biogenic rocky outcrops, currently lacks a formal management plan. Using the Ecospace module of the Ecopath with Ecosim software, we simulated three management scenarios: 1) SAC expansion; 2) winter artisanal fishing in the SAC; 3) a combination of both. In line with ecosystem-based management, we focused on economically important trophic groups in the region, such as the Mediterranean mussel, Mytilus galloprovincialis, and striped venus clam, Chamelea gallina, which are present near the SAC. We also considered the efforts of the local fishing fleets. Ecosystem structure and functioning indicators, generated by the spatial food-web model, were linked to three criteria aligned with the management priorities of the area: nature conservation, aquaculture productivity, and fishing productivity. These criteria were aggregated into a final score to compare the management scenarios. The results showed that none of the scenarios would significantly alter community composition or ecosystem functioning compared to the current situation. However, they did show contrasting responses in the food web model. The SAC expansion scenario notably increased total biomass and commercial fish biomass, especially pectinids and cephalopods. The fishing scenario had a minimal impact on trophic groups. Ecosystem resilience and structure indicators were less sensitive to management scenarios than biomass indicators. However, the multi-criteria analysis revealed that the fishing scenario limited the benefits of expanding the SAC, due to reduced catches. The final score effectively ranked proposed scenarios, highlighting key indicators that influenced these variations. The proposed approach shows potential for supporting participatory modelling and engaging stakeholders in developing management scenarios.

Unveiling the Burden: A Six-Year Retrospective Analysis of Pressure Ulcer Epidemiology in a ICU

Objective: This study describes the epidemiological changes in pressure ulcers (PUs) in a Portuguese intensive care unit (ICU) from January 2017 to June 2023, characterizes critically ill patients with PUs, identifies specific risk factors, and assesses the effectiveness of implemented preventive measures. Materials and Methods: A retrospective observational cohort study was conducted, analyzing records of ICU patients with PUs during the specified period. Data were extracted from the institution’s Global Risk Management application and the ICU’s electronic PU registry. The study included patients with ICU stays longer than 24 h and excluded those with ineligible clinical records or incomplete characterization data. Results: Among 3816 evaluated patients, 257 developed a total of 345 PUs, averaging 1.4 PUs per patient. The average PU prevalence rate was 6.81%, with the highest prevalence in 2020 (11.0%) and the lowest in 2022 (3.48%). The average incidence rate was 3.76%, peaking at 5.71% in 2020 and declining to 2.54% in 2023. The sacrum and heels were the most commonly affected areas, with Category 2 PUs being the most frequent. Key intrinsic risk factors included systemic diseases and sensory deficits, with pressure identified as a significant extrinsic factor. Preventive measures focused on risk assessment and pressure control. Conclusions: The study reveals a PU prevalence of 6.81% and an average incidence of 3.76%, underscoring the need for enhanced preventive strategies, especially in anatomical areas like the sacrum and heels. It emphasizes the importance of personalized assessments, continuous education for nursing staff, and a multidisciplinary approach to improve patient outcomes and care quality in the ICU.

Bilateral TENs Application in the Surgical Management of Femur Fracture in a Doberman Puppy

Bilateral TENs Application in the Surgical Management of Femur Fracture in a Doberman Puppy

Synergizing Ai and ERP for Predictive Supply Chain Management and Quality Assurance in Healthcare

This article explores the transformative potential of integrating Artificial Intelligence (AI) with Enterprise Resource Planning (ERP) systems in healthcare, focusing on applications in predictive supply chain management and quality assurance. The healthcare industry faces increasing pressure to improve efficiency while maintaining high-quality care, and AI-ERP integration offers a compelling solution. By combining ERP's comprehensive data management capabilities with AI's predictive and analytical power, healthcare organizations can enhance operational efficiency, improve decision-making, and ultimately deliver better patient outcomes. The article examines current implementations, case studies, and future projections to provide a comprehensive overview of how this technological synergy can help healthcare providers navigate the complex challenges of modern healthcare delivery, from optimizing inventory levels to ensuring regulatory compliance and proactive risk management.

Recent Development of Organic Afterglow Probes for Diagnosis and Treatment of Cancer

Afterglow imaging plays a crucial role in the cancer treatment field. In contrast to inorganic afterglow imaging agents, organic afterglow imaging agents possess easily modifiable structures and exhibit excellent biocompatibility, thereby presenting significant prospects for application in tumor diagnosis and management. In this review, we summarize the design principles and applications of afterglow probes in tumor imaging and therapy. Finally, we discuss the future challenges and prospects of organic afterglow probes in cancer diagnosis and therapy.

Mercury adsorption study and DFT calculations of sulfur-containing biomass composites prepared by inverse vulcanization

This study introduces an innovative and cost-effective biomass adsorbent, the sulfur/cardanol/potato starch composite (SCP), synthesized through inverse vulcanization for the remediation of mercury-contaminated waters. The SCP was characterized using Scanning Electron Microscopy/Energy Dispersive Spectroscopy (SEM/EDS), Fourier Transform Infrared Spectroscopy (FT-IR), Thermogravimetric Analysis (TGA) and X-ray Diffraction (XRD) to confirm its composition, morphology, and properties. The adsorption capacity of SCP for Hg(II) was 246.88 mg/g with a removal rate of 98.75 %. Adsorption kinetics followed a pseudo-second-order model, indicating chemisorption as the dominant mechanism, while adsorption isotherms were best described by the Langmuir model. Thermodynamic studies confirmed the adsorption process as spontaneous and endothermic. Density Functional Theory (DFT) calculations further elucidate the interaction mechanisms between mercury and the adsorbent, revealing that the thiyl radicals play a crucial role in the adsorption process. The SCP also exhibited a high selectivity for Hg(II) over other co-existing ions and maintains an adsorption capacity over 223.93 mg/g after five regeneration cycles, thus promising practical applications in environmental mercury management.

Sherlock Holmes Between Homogeneity Tests: Detection Power Based on Profitability Ratios in the V4 Region

Profitability reveals the key financial ratios that ensure the long-term sustainability of an enterprise’s ability to invest in further growth. Without knowledge of the course of development, particularly changes in profitability, enterprises face financial difficulties that threaten their existence. Although the homogeneity tests serve as a reliable tool for identifying changes, their application in financial management often receives insufficient attention. The aim of this research is to evaluate the detection power of homogeneity tests and identify the one with the highest ability based on testing changes in the development of profitability ratios across sectors in the Visegrad Four. Buishand’s test, Pettitt’s test, the SNHT, and the von Neumann test were run for 8671 enterprises during 2016–2021 and gained from Moody’s Orbis. Comparison tables for ROA, ROC, ROE, ROS, ROR, and ROW using Monte Carlo simulation with a million replications identified the number of Slovak, Czech, Polish, and Hungarian enterprises in which heterogeneity was divided according to the Nomenclature of Economic Activities, NACE. The SNHT disclosed the greatest number of changes in the development of all profitability ratios. The results validate the use of selected tests for ratio assessment. Furthermore, business agencies may replicate this approach to determine the economic situation and sector performance.

AI-Guided Cancer Therapy for Patients with Coexisting Migraines.

Background: Cancer remains a leading cause of death worldwide. Progress in its effective treatment has been hampered by challenges in personalized therapy, particularly in patients with comorbid conditions. The integration of artificial intelligence (AI) into patient profiling offers a promising approach to enhancing individualized anticancer therapy. Objective: This narrative review explores the role of AI in refining anticancer therapy through personalized profiling, with a specific focus on cancer patients with comorbid migraine. Methods: A comprehensive literature search was conducted across multiple databases, including PubMed, Scopus, and Google Scholar. Studies were selected based on their relevance to AI applications in oncology and migraine management, with a focus on personalized medicine and predictive modeling. Key themes were synthesized to provide an overview of recent developments, challenges, and emerging directions. Results: AI technologies, such as machine learning (ML), deep learning (DL), and natural language processing (NLP), have become instrumental in the discovery of genetic and molecular biomarkers of cancer and migraine. These technologies also enable predictive analytics for assessing the impact of migraine on cancer therapy in comorbid cases, predicting outcomes and provide clinical decision support systems (CDSS) for real-time treatment adjustments. Conclusions: AI holds significant potential to improve the precision and effectiveness of the management and therapy of cancer patients with comorbid migraine. Nevertheless, challenges remain over data integration, clinical validation, and ethical consideration, which must be addressed to appreciate the full potential for the approach outlined herein.

Implementation of Risk Management in Asset Management Governance Towards Optimizing Asset Utilization at Public Service Agency State Universities (Case Study of UPN Veteran Yogyakarta)

This study aims to analyze the application of risk management in asset governance at UPN Veteran Yogyakarta to achieve optimal asset utilization. As a Public Service Agency State University (PTN-BLU), UPN Veteran Yogyakarta faces various challenges in asset management, including budget constraints, lack of consistent monitoring, and the unavailability of formal risk evaluation standards. Qualitative descriptive research methods are used to gain in-depth understanding through interviews with asset managers and field observations. The results show that the implementation of risk management can have a significant impact on the efficiency of budget allocation, which includes more appropriate budget distribution based on priority needs and risks. Risk management also has the potential to extend the useful life of assets, with risk mitigation measures taken on assets that show signs of wear or early damage, thus preventing major repair costs due to serious damage. This research highlights that a technology-based monitoring system is an indispensable aspect to support the effectiveness of risk management in asset management. The implementation of structured risk assessment procedures helps in determining asset maintenance priorities, so that the assets that are most critical to the sustainability of campus operations receive greater attention. With the implementation of this comprehensive risk management, optimization of asset utilization can be achieved, which in turn supports the stability and sustainability of UPN Veteran Yogyakarta's operations as a quality higher education institution.

Enhancing Bucket Sort Efficiency: A Combinatorial Approach to Algorithm Optimization

Abstract: The efficiency of sorting algorithms is critical to numerous computational processes, including data management, search operations, and real-time applications. Among these algorithms, Bucket Sort is notable for its linear-time performance when data is uniformly distributed over a defined range. However, its efficiency suffers significantly with non-uniform data distributions, resulting in unbalanced buckets and increased sorting time. In our research, we explore how combinatorial algorithms can enhance Bucket Sort’s efficiency by optimizing bucket partitioning, dynamic allocation, and internal sorting strategies. Through rigorous mathematical proofs and analysis, we demonstrate that the application of combinatorial techniques yields substantial improvements in average-case performance, particularly in handling skewed data distributions. Practical case studies in large-scale data processing illustrate the adaptability and effectiveness of these optimizations, supporting their potential in real-world applications.

Behind Many Visages: The Waluku Cultivating Civilization Tour as Part of the Visitor Flow Management Program in the Borobudur District

The Borobudur Temple is a vulnerable cultural heritage site confronting the challenge of overcrowding impacting site preservation, visitor experience, and economic viability. This study analyzed the extension of visitor flow management applications to the buffer zone in heritage locations, focusing on the enhancement of the trip experience. The Waluku: Cultivating Civilization sub-theme, integral to the Borobudur Trail of Civilization concept, has the ability to enhance preservation via the Visitor Flow Management Process, which encompasses three phases: restricted, redistributive, and interpretative. This research employed qualitative methods by gathering data through interviews, literature reviews, and observations. The research findings revealed that the three stages operate independently and do not significantly affect the preservation of the Borobudur Temple's physical and cultural assets. Restrictions could undermine the objective of enhancing engagement and interaction with culture and nature, rendering them less effective. Meanwhile, the other two stages had minimal impact due to infrequent reservations. Itineraries may vary based on demand, and there is no interpretative narrative concerning the relationship between relief and tourism activities. Conflicts of interest and insufficient local community engagement provide barriers to the program's development.

On the Application of Potter Optimization Algorithm for Solving Supply Chain Management Application

On the Application of Potter Optimization Algorithm for Solving Supply Chain Management Application

Implementing agile management practices in the era of digital transformation

In the era of digital transformation, organizations face unprecedented technological changes that demand a shift toward more adaptive and responsive management practices. This paper Analyses how organizations can strategically implement agile management practices to navigate these rapid changes effectively. Agile management emphasizes flexibility, collaboration, and customer-centricity, enabling organizations to respond swiftly to market dynamics and evolving customer needs. By adopting frameworks such as Scrum, Kanban, and Lean, companies can enhance their management processes, fostering a culture of continuous improvement and innovation. The paper explores the fundamental principles of agile management and their relevance in the context of digital transformation. It discusses how cross-functional teams, iterative development, and regular feedback loops can facilitate quicker decision-making and enhance collaboration among stakeholders. Additionally, the integration of digital tools, such as project management software and communication platforms, supports agile methodologies by streamlining workflows and improving transparency. Key considerations for successful implementation include aligning agile practices with organizational goals, investing in employee training, and promoting a mindset that embraces change. The paper highlights real-world case studies demonstrating the successful application of agile management in various industries, showcasing its potential to improve responsiveness and operational efficiency. Ultimately, this analysis underscores the critical role of agile management practices in enabling organizations to thrive amidst the challenges of digital transformation

Cardioprotective effects of novel antioxidants post-myocardial infarction: An integrative review of preclinical and clinical data

Myocardial infarction (MI), is still a major public health problem, and oxidative stress contributes to the degree of myocardial damage after MI. Oxygen-derived free radicals (ODFR) worsen myocardial injury and result in chronic heart failure in many patients. These harms have led to interest in antioxidant treatment to reduce these adverse effects; new antioxidants with the potential for cardioprotection are the subject of significant interest. This review summarizes basic and clinical research comparing the effectiveness of newly synthesized antioxidants in attenuating oxidative stress and enhancing recovery after myocardial infarction. The review synthesizes evidence of a reduction in infarct size, enhancement of cardiac function, and repression of apoptosis in myocardial cells by the use of antioxidants from animal models. Melatonin, N-acetylcysteine, edaravone, and coenzyme Q10 demonstrated a wide range of preclinical positive effects by acting as ROS free radicals scavengers, modulating mitochondria dysfunction, and reducing inflammation. These findings are extrapolated from humans, although advances in antioxidant therapy are beginning to be viewed in initial clinical trials. From human data, although clinical trials are scarce, the evidence of new antioxidants can improve point and long-term outcomes in patients undergoing MI, help to increase the contractility of the injured myocardium, and decrease the mortality level. However, some issues are still there, such as high inter- and intra-individual variability in patient response and dosing schedule, as well as adverse effects such as pro-oxidant activity at high Oral administered doses of melatonin. The limitations of the current research discussed in this review include the general lack of large-scale, well-controlled clinical trials and the need for long-term follow-up studies. This review also proposed future research directions for improving antioxidant applications in post-MI management.