Eurasian Journal of Chemical, Medicinal and Petroleum Research

Abstract During treatment with chemotherapy drugs, many cancers become resistant to the therapeutic effects of the drugs used. Various mechanisms have been proposed in relation to drug resistance. One of the most important reasons for drug resistance is the high expression of ATP-dependent membrane proteins from the large family of membrane transporters (ATP Binding Cassette ABC). From this family, the membrane transporter with a molecular weight of 170 KDa named glycoprotein P plays an important role in drug resistance. Other membrane proteins from the MRP (Multidrug Resistance Associated Protein) family are also involved in drug resistance. ABC proteins are also expressed in normal cells. The mentioned proteins are responsible for the transfer of endogenous substrates. The high expression of these proteins in cancer cells is the most important obstacle to cancer treatment. The range of clinical responses is caused by the medicinal qualities of the treatment as well as the internal and acquired molecular and physical characteristics of cancer cells and external environmental factors. The latter can be caused by several factors, such as increased DNA repair capacity, altered drug metabolism, mutated or altered drug targets, reduced drug accumulation, and inactivated cell death signals. Cancer stem cells (CSCs) show drug resistance. Because transporters overexpress adenosine triphosphate (ATP) binding cassette. Through specific regulatory genes, FOXM1, a transcription factor specific for cell proliferation, controls the transition between G1/S and G2/M cell cycle phases. In addition, it is an oncogene that causes the expansion and proliferation of cancer cells. Via ABCC5 (ATP binding cassette subfamily member 5) expression, FOXM1 overexpression causes paclitaxel resistance in nasopharyngeal carcinoma.

Abstract Cosmetic facial filler injections have become a cornerstone in aesthetic dermatology; however, associated complications, ranging from mild erythema to severe vascular compromise, necessitate effective and timely intervention. This study proposes a treatment algorithm grounded in the biological stages of wound healing: hemostasis, inflammation, proliferation, and remodeling. By aligning therapeutic strategies with these stages, clinicians can address adverse events more systematically and promote tissue recovery. Early-stage complications such as edema or erythema can often be managed with conservative measures, whereas mid- to late-stage events like granuloma formation or tissue necrosis require more invasive approaches, including hyaluronidase administration, corticosteroids, or surgical debridement. The algorithm emphasizes the importance of early diagnosis, risk stratification, and individualized care, considering patient history, filler type, and injection technique. Additionally, adjunctive therapies—such as hyperbaric oxygen, laser treatment, or platelet-rich plasma—may enhance healing outcomes. This framework aims to reduce long-term morbidity and provide practitioners with a clear, biologically informed decision-making pathway to manage filler-related complications effectively.

Abstract Facial filler injections are widely used in aesthetic dermatology and plastic surgery for rejuvenation and volume restoration. Despite their popularity and generally favorable safety profile, rare but severe complications, including cerebral embolism, have emerged in the literature. This review aims to explore the existing evidence surrounding cerebral embolism resulting from facial filler injections, with a focus on incidence, anatomical risk factors, pathophysiological mechanisms, clinical manifestations, diagnostic challenges, management strategies, and outcomes. An extensive literature search was conducted using PubMed, Scopus, Embase, and Web of Science for studies published from 2015 to 2024. A total of 37 cases were identified, with the glabella, nasal dorsum, and forehead being the most common sites associated with complications. The pathogenesis involves retrograde arterial embolization with filler materials entering cerebral circulation via branches of the ophthalmic artery. Common clinical signs include sudden vision loss, headache, hemiplegia, aphasia, and altered consciousness. Prompt recognition and early management are crucial but often fail to reverse neurological deficits. Preventive strategies, such as anatomical knowledge, appropriate injection technique, and use of blunt cannulas, are essential. This review highlights the need for greater awareness among practitioners and recommends standardized emergency protocols to reduce the burden of these rare but catastrophic events.

Abstract Oil pollution is one of the most persistent environmental threats affecting terrestrial and marine ecosystems worldwide. Bioremediation, an eco-friendly and cost-effective approach, utilizes microorganisms to degrade petroleum hydrocarbons into non-toxic end products. This review highlights the microbial diversity involved in oil degradation, including key bacterial and fungal genera such as Pseudomonas, Acinetobacter, Rhodococcus, Aspergillus, and Candida. It further discusses the enzymatic mechanisms underlying hydrocarbon degradation, both aerobic and anaerobic, and the environmental factors influencing microbial activity, such as temperature, pH, nutrient availability, and oxygen levels. Special attention is given to the role of biosurfactants in increasing hydrocarbon bioavailability and the advancement of modern technologies such as microbial electrochemical systems and genetic engineering for enhanced degradation. This paper also presents successful case studies of microbial oil bioremediation and compares it to other remediation strategies, emphasizing the potential and challenges of microbial approaches in large-scale applications. The comprehensive understanding provided here aims to guide future research and industrial applications for sustainable environmental restoration.

Abstract Introduction:

This study aimed to compare the outcomes and complications of MIE versus OE in patients with distal esophageal cancer.

Materials and Methods:

This retrospective cohort study included 196 patients with distal esophageal cancer treated between 2015 and 2021 at two tertiary hospitals in Tehran. Patients were equally divided into MIE (n=98) and OE (n=98) groups. Preoperative, intraoperative, and postoperative variables including surgical duration, pain intensity, intraoperative blood loss, transfusion requirements, hospital stay, and complication rates were collected and analyzed using SPSS version 23. Appropriate statistical tests were applied with a significance level set at p<0.05.

Results:

The mean duration of surgery was significantly shorter in the MIE group compared to the OE group (280.71 ± 44.83 vs. 425.36 ± 51.69 minutes, p<0.001). MIE patients experienced significantly less intraoperative blood loss (297.14 ± 89.29 vs. 503.57 ± 122.02 mL, p<0.001), required fewer blood transfusions (2.14 ± 0.52 vs. 2.64 ± 0.90 units, p<0.001), and had a shorter hospital stay (14.14 ± 3.27 vs. 18.64 ± 4.31 days, p<0.001). Postoperative pain was also lower in the MIE group (2.86 ± 1.36 vs. 3.43 ± 2.48, p=0.048). However, the number of lymph nodes dissected was significantly higher in the OE group (18.50 ± 3.48 vs. 9.57 ± 3.79, p<0.001), and the incidence of chylothorax was greater in the MIE group (7 vs. 1 cases, p=0.030). There was no statistically significant difference in tracheal injury between the groups (p=0.054).

Conclusion:

Minimally invasive esophagectomy offers several clinical benefits over open surgery, including reduced blood loss, lower postoperative pain, shorter operative time, and decreased hospital stay. However, it is associated with a higher incidence of chylothorax and a lower lymph node yield, possibly due to the learning curve and technical nuances.

Abstract Lithium-ion batteries have changed the landscape of energy storage and ushered in a new era of clean, efficient and sustainable energy solutions. From powering our smartphones and laptops to fueling the transportation and renewable energy sectors, lithium-ion batteries are essential to modern life. The main goal of the innovative technology is to solve one of the old challenges of the battery industry: The erosion of liquid electrolytes. As research and innovation continue to push the boundaries of battery technology, the future holds exciting opportunities for even more efficient, safer and environmentally friendly energy storage solutions. By harnessing the potential of lithium-ion batteries, we can pave the way to a greener and more electrified future for generations to come. Additionally, this solution can improve battery safety by reducing the risk of thermal runaway – a common concern in older lithium-ion batteries. This development is in line with phenomena such as the global determination for sustainable energy solutions as well as the increasing demand for high-performance batteries.

Abstract Long COVID, also known as post-acute sequelae of SARS-CoV-2 infection (PASC), has emerged as a significant public health challenge, affecting millions of individuals globally. It is characterized by persistent or new symptoms lasting weeks to months beyond the acute phase of COVID-19, including fatigue, dyspnea, cognitive impairment, autonomic dysfunction, and musculoskeletal pain. The underlying pathophysiology is multifactorial and remains under investigation. Current evidence suggests that persistent viral reservoirs in tissues, chronic immune activation, autoimmunity, endothelial dysfunction, microvascular injury, and mitochondrial impairment play major roles. Neurological and autonomic disturbances, along with psychosocial and epigenetic influences, further contribute to the complexity of the syndrome. Management strategies are primarily supportive and multidisciplinary, focusing on symptom relief, rehabilitation, and psychosocial care. Approaches include pulmonary and cardiovascular rehabilitation, pacing and energy conservation for fatigue, pharmacological interventions for dysautonomia, and cognitive therapy for neurocognitive symptoms. Emerging treatments such as immunomodulators, antiviral agents, anticoagulants, and mitochondrial support therapies are under investigation. Despite progress, challenges remain in defining diagnostic criteria, identifying biomarkers, and tailoring personalized interventions. Long COVID represents not only a biomedical issue but also a socioeconomic burden, requiring coordinated healthcare strategies and global research efforts. Understanding its mechanisms and developing effective management approaches are essential to mitigate its long-term impact on individuals and healthcare systems.

Abstract Skin cancer, particularly melanoma, poses significant health risks globally. Early detection is crucial for effective treatment and improved patient outcomes. Dermoscopy, a non-invasive imaging technique, has enhanced dermatologists' ability to examine skin lesions. Recent advancements in artificial intelligence (AI), especially deep learning, have shown promising results in automating the analysis of dermoscopic images for skin cancer detection. AI models, particularly convolutional neural networks (CNNs), have been trained on large datasets of dermoscopic images, achieving diagnostic accuracies comparable to or surpassing those of experienced dermatologists. These AI systems can assist in identifying malignant lesions, thereby aiding in early diagnosis and reducing the workload on healthcare professionals. However, challenges remain, including the need for diverse and representative datasets, addressing biases in AI models, and ensuring the clinical applicability of these technologies. This paper reviews the current state of AI applications in dermoscopic image analysis for skin cancer detection, discusses the methodologies employed, evaluates the performance of various AI models, and examines the potential impact on clinical practice. The integration of AI into dermatology holds the promise of enhancing diagnostic accuracy, improving patient outcomes, and optimizing healthcare resources.

Abstract Nanomaterials have emerged as a transformative technology in drug delivery systems, offering unique properties that enhance therapeutic efficacy and safety. Their small size, high surface area, and ability to be engineered for targeted delivery enable improved solubility, controlled release, and reduced side effects of pharmaceuticals. This paper discusses various types of nanomaterials used in drug delivery, including nanoparticles, liposomes, and dendrimers, highlighting their mechanisms of action and advantages over conventional delivery methods. Despite their potential, the integration of nanomaterials in clinical applications faces several challenges, including manufacturing scalability, regulatory hurdles, bio distribution unpredictability, and concerns regarding toxicity and biocompatibility. Additionally, complex interactions between nanomaterials and biological systems pose significant hurdles. The future of nanomaterials in drug delivery lies in innovative approaches, such as personalized medicine and biodegradable carriers, necessitating continued interdisciplinary research and collaboration. This review aims to provide insights into the current status and future perspectives of nanomaterials in drug delivery, emphasizing the importance of overcoming existing challenges to fully harness their potential in enhancing patient outcomes.

Abstract Methods based on atomic behavior, such as molecular dynamics (MD) simulations, are highly accurate for modeling single-layer graphene sheets. However, their high computational cost limits their use to only small-sized systems. This research addresses this limitation by developing a new atomic-scale finite element method (AFEM) based on the Tersoff-Brenner potential to analyze the mechanical properties of graphene. The proposed AFEM method's efficiency and accuracy were demonstrated through a numerical example of a graphene sheet. When compared to MD simulation results, the new method showed very high accuracy. Additionally, its simulation speed was found to be approximately 100 times faster than that of the MD method. This study also investigated the influence of effective factors on simulation speed, such as the initial non-equilibrium bond length and the number of atoms. The AFEM was further developed to incorporate periodic boundary conditions, as these had not been previously considered for nanostructures using this method. The results showed that AFEM modeling without periodic boundary conditions produced results that were very different from those of MD simulations.

Abstract The development of renewable energy in Iran is of great importance due to its favorable geographical conditions and the need for sustainable energy sources, and the integration of renewable energy sources in oil and gas operations will create a sustainable future for future generations. The world is at a critical juncture where the demand for energy intersects with the urgent need to combat climate change. Traditional energy sources, dependent on fossil fuels, significantly contribute to greenhouse gas emissions and environmental degradation. In response, there is a paradigm shift towards renewable energy sources such as solar, wind, hydro, and geothermal energy. Programming, in conjunction with technological innovations, plays a pivotal role in the use and optimization of these renewable energy solutions. The role of programming in renewable energy solutions is not just supportive but also transformative. From designing efficient systems and optimizing energy production to enabling smart grids and harnessing the power of artificial intelligence, programming is the main axis that drives the renewable energy revolution forward. As the world increasingly embraces sustainable energy sources, the challenges and opportunities for programming in this area continue to expand. By leveraging the capabilities of programming languages, frameworks, and emerging technologies, developers can help create a cleaner and more sustainable energy future. As we navigate the complexities of climate change, programming becomes an essential tool that enables us to harness the potential of renewable energy and lead the global transition to a more sustainable and resilient energy ecosystem.

Abstract Breast cancer remains one of the leading causes of cancer-related mortality among women globally, highlighting the critical need for early detection and accurate diagnosis. Recent advances in artificial intelligence (AI), encompassing both machine learning (ML) and deep learning (DL) approaches, have demonstrated significant potential in enhancing diagnostic accuracy, reducing human error, and supporting clinical decision-making. This systematic review critically analyzes existing studies that employ AI for breast cancer detection, focusing on methodological approaches, dataset characteristics, model performance, and interpretability. ML-based techniques, including support vector machines, random forests, and gradient boosting, show promising results in structured datasets, particularly where dataset sizes are limited, and interpretability is essential. In contrast, DL approaches, primarily convolutional neural networks and their variants, outperform ML in raw image analysis, multi-modal imaging, and complex feature extraction, achieving higher accuracy and sensitivity. Hybrid models integrating ML and DL, often augmented with radiomics features, offer a balanced framework, combining high predictive performance with improved interpretability. Additionally, explainable AI (XAI) techniques are increasingly applied to DL models, mitigating the “black-box” problem and fostering clinical trust. Despite these advancements, challenges remain, including the need for large, high-quality, multi-institutional datasets, computational resource demands, and generalizability across diverse populations. Low-resource and portable AI solutions offer potential for broader accessibility, though with modest reductions in predictive performance. Overall, AI demonstrates transformative potential in early breast cancer detection, particularly when combined with hybrid and explainable frameworks. Future research should prioritize multi-modal integration, rigorous cross-center validation, and deployment strategies that balance accuracy, interpretability, and accessibility, ultimately facilitating clinical adoption and improving patient outcomes.

Abstract Macrophages, as central components of the innate immune system, play a pivotal role in orchestrating inflammatory responses. Recent evidence highlights that macrophage function is closely governed by metabolic reprogramming, a process in which shifts in cellular metabolism modulate immune phenotypes and effector functions. During chronic inflammation, macrophages exhibit altered utilization of glycolysis, oxidative phosphorylation (OXPHOS), fatty acid oxidation, and glutamine metabolism. These metabolic shifts determine the polarization state of macrophages, driving pro-inflammatory (M1-like) or anti-inflammatory (M2-like) phenotypes. Persistent metabolic dysregulation contributes to uncontrolled inflammation and tissue damage in chronic diseases such as atherosclerosis, diabetes, rheumatoid arthritis, and cancer. In atherosclerosis, macrophages accumulate lipids and undergo metabolic stress that sustains inflammatory activation. In diabetes, hyperglycemia-induced metabolic reprogramming enhances macrophage glycolysis and inflammatory cytokine production. In tumors, the hypoxic microenvironment reshapes macrophage metabolism to support immunosuppressive and pro-tumorigenic activity. Understanding how metabolic pathways regulate macrophage function reveals therapeutic opportunities. Targeting key enzymes such as hexokinase 2, isocitrate dehydrogenase, or AMP-activated protein kinase (AMPK) offers potential to reprogram macrophages toward inflammation resolution. This review integrates findings from immunometabolism and pathophysiology to demonstrate that macrophage metabolic reprogramming acts as a central mechanism linking cellular metabolism to chronic inflammation and disease progression. Therapeutic strategies that correct macrophage metabolic imbalance may provide novel approaches for managing chronic inflammatory disorders and improving patient outcomes.

Abstract Coronaviruses are a large family of viruses that, according to evidence, can cause diseases ranging from the common cold to more severe diseases such as Middle East Respiratory Syndrome (MERS) or even more severe diseases such as Severe Acute Respiratory Syndrome (SARS). Epidemiology A disease, whether contagious or non-contagious, may be more or less common in some areas and under some conditions among a large number of people. In other words, a disease can be more or less common. The science that studies how diseases spread and what causes them to spread is called epidemiology, which is a branch of medical science. Basically, epidemiology seeks to prevent the occurrence and spread of a disease or to control it if it does spread. Communicable diseases are a type of infectious disease that can be transmitted from person to person or to humans through insects and other animals. This disease can also be transmitted by organisms in contaminated water or food that has been exposed to the environment by an infected person. For example, a sick child's cough is one way to transmit a cold or flu to others, which must be well taken care of and prevented. In general, the factors that because infectious diseases include viruses, bacteria, and parasites. The signs and symptoms of infectious diseases will also vary depending on the agent causing the infection.

Abstract Regenerative endodontics is evolving rapidly as an alternative to conventional root canal therapy, aiming not merely to disinfect and fill root canals, but to restore viable pulp tissue with physiological functions such as immune defense, innervation, and dentinogenesis. Central to this paradigm are stem cell–based therapies, which, in concert with scaffolds and signaling factors, offer potential to regenerate the pulp–dentin complex in teeth with necrotic or damaged pulps. This review summarizes the latest progress in the field, focusing on (1) sources of stem cells (e.g. dental pulp stem cells, stem cells from the apical papilla, mesenchymal stem cells of non dental origin, and induced pluripotent stem cells), (2) scaffold design and biomaterial strategies, (3) delivery of growth factors and bioactive cues, (4) cell transplantation vs. cell homing approaches, (5) in vitro, in vivo, and early clinical evidence, and (6) major challenges and future directions. Evidence from animal studies and limited human trials shows promise in root maturation, vascularization, and functional tissue formation. However, full regeneration of the native pulp–dentin architecture — particularly with true odontoblast layer, innervation, and predictable function — remains elusive. Key hurdles include controlling stem cell differentiation and proliferation, immune compatibility, standardized protocols, safety (e.g. tumorigenesis risk), and regulatory issues. Emerging innovations such as cell-free secretomes or exosomes, 3D bioprinting of scaffolds, gene engineering for guided differentiation, and smart biomaterials responsive to microenvironment cues may help overcome current limitations. To accelerate translation toward routine clinical use, rigorous multicenter trials with long-term follow-up, development of GMP grade cell banks, and interdisciplinary collaboration are essential.

Abstract Microbiome dysbiosis, an alteration in the composition, diversity, or function of host-associated microbial communities, is increasingly implicated in both gastrointestinal (GI) disorders (e.g., IBS, IBD, colorectal cancer) and systemic metabolic diseases. This study evaluates dysbiosis as a predictive biomarker for incident GI and metabolic disease using integrative multi-omics profiling (16S/shotgun metagenomics, metabolomics, host markers) and machine-learning risk models. We will recruit a prospective cohort (n ≈ 1,000) with baseline stool, blood, and clinical phenotyping and follow participants 3–5 years for disease incidence and progression. Primary outcomes are new diagnoses of IBD, IBS, colorectal neoplasia, NAFLD, and NAFLD; secondary outcomes include changes in glycemic markers, liver enzymes, and bowel-symptom scores. Predictors include alpha/beta diversity, taxon-level signatures (e.g., depletion of butyrate-producers), functional gene modules (SCFA synthesis, bile-acid metabolism, LPS biosynthesis), and metabolite markers (SCFAs, secondary bile acids, trimethylamine N-oxide). Models will adjust for diet, medications (antibiotics, PPIs), BMI, age, and socioeconomic factors. We will validate models internally (cross-validation) and externally (independent cohort). If successful, the work will (1) quantify predictive power of microbiome-derived features beyond traditional risk factors, (2) identify mechanistic microbe–metabolite pathways linking dysbiosis to disease, and (3) provide candidate targets for early intervention. However, clinical translation must consider variability in sampling and current limits of commercial testing; robust standardization and prospective validation are required.

Abstract Asthma is a chronic inflammatory disease of the airways characterized by variable and recurring symptoms, airflow obstruction, bronchial hyperresponsiveness, and underlying inflammation. This condition affects millions worldwide, leading to significant morbidity and healthcare costs. Traditional therapies, such as inhaled corticosteroids (ICS) and bronchodilators, have long been the cornerstone of asthma management. These medications primarily aim to reduce inflammation and relax airway muscles, providing symptomatic relief and preventing exacerbations. However, a subset of patients with severe asthma remains inadequately controlled despite optimal conventional therapy. This unmet need has spurred the development of novel pharmacological agents targeting specific pathways involved in asthma pathophysiology. These novel drugs include biologics, small molecules, and new inhaled formulations. Biologics, such as anti-IL-5, anti-IL-4/IL-13, and anti-IgE therapies, offer targeted treatment options for patients with severe asthma by modulating specific immune responses. Small molecule drugs, like PDE4 inhibitors and tyrosine kinase inhibitors, provide new mechanisms to control inflammation and bronchoconstriction. Additionally, advancements in inhaler technology and formulation have led to the development of new inhaled therapies, improving drug delivery and efficacy. This review discusses these novel drugs, highlighting their mechanisms of action, efficacy, and safety profiles, offering hope for better asthma management and improved patient outcomes.

Abstract This study explores the effects of temperature and pressure variations on catalyst degradation mechanisms—specifically catalyst crushing and catalyst cake formation—in a light naphtha isomerization unit. Operating conditions within the range of 200–280°C and 10–35 bar were simulated to evaluate mechanical and physical stress on the catalyst bed. Two performance indices were defined: the Catalyst Crushing Index (CCI) and Catalyst Cake Thickness (CCT). Results revealed that both CCI and CCT increase significantly with rising temperature and pressure, with pressure having a more pronounced impact. Elevated pressure intensified catalyst compaction, while temperature contributed to structural weakening and sintering. The analysis showed that high-pressure environments above 25 bar and temperatures exceeding 260°C led to accelerated crushing and cake buildup, contributing to pressure drop, pore blockage, and reduced hydrogen diffusion. These degradation mechanisms ultimately reduce catalytic activity and operational efficiency. The findings suggest that maintaining optimal reactor conditions and incorporating real-time monitoring systems are essential for preventing early catalyst failure. This research provides a predictive framework for improving catalyst performance and life cycle in isomerization processes and can support operational decision-making in refinery settings.

Abstract Pre-participation screening and evaluation is an effective strategy for predicting and preventing injuries in athletes before participating in organized sports. Sports injuries are very difficult and dangerous experiences that athletes face during their sports activities. Even after recovery, psychological factors such as fear of movement and anxiety can affect the return to sports. The aim of the study was to compare fear of movement or re-injury and anxiety caused by pain in athletes with and without a history of musculoskeletal injuries. Another problem that leads to injury in high-level athletes, especially national and professional athletes, is overuse of the spine, various organs and joints of the body, without considering sufficient recovery time. Depletion of energy reserves and body resources from nutrients and lack of proper replacement, impaired recovery, insufficient or poor quality sleep, abuse of stimulant drugs, anabolic steroids, peptides, along with technical errors, are the main factors in the occurrence of musculoskeletal injuries. Some of the equipment and techniques available in bodybuilding and functional training are used in rehabilitation and are used by sports medicine and rehabilitation specialists. Paying attention to strengthening the core muscles of the body with specific techniques and methods plays an important role in preventing spinal injuries, and specific and precise methods are used to improve the strength and fitness of these areas.

Abstract Introduction: Acute myocardial infarction remains a leading cause of morbidity and mortality, with impaired myocardial reperfusion and electrical instability playing key roles in adverse outcomes. Atrial conduction abnormalities may reflect ischemic burden and microvascular dysfunction. This study aimed to evaluate the clinical and prognostic significance of atrial electrical indices in relation to reperfusion quality and coronary disease severity.

Material and methods: This retrospective cross‑sectional study included 315 consecutive patients admitted to Shahid Madani Hospital, Tabriz, between March 2023 and March 2024. Clinical, laboratory, electrocardiographic, and angiographic data were extracted from medical records. Standardized ECG measurements, angiographic assessment, and post‑PCI outcomes were analyzed to evaluate electrophysiological and clinical associations.

Results: Among 315 cardiomyopathy patients, ischemic etiology was associated with a significantly higher prevalence of isoelectric T waves in lead aVR compared with non‑ischemic cardiomyopathy (P=0.004 and P=0.030). Other T‑wave amplitude categories showed no significant differences between etiologic groups, nor any significant association with the severity of left ventricular systolic dysfunction (all P>0.05).

Conclusion: This study demonstrates that while traditional cardiovascular risk factors are highly prevalent in patients with cardiomyopathy, T‑wave amplitude in lead aVR provides limited functional insight into left ventricular systolic impairment.

Abstract Genetic technologies in personalized medicine have revolutionized the management of anticoagulant therapy. Despite their vital role in preventing blood clots, these drugs pose numerous challenges in dose adjustment and side effect management due to the varying responses of patients. Genetic analysis has enabled the provision of personalized, safer, and more effective therapy by identifying genetic differences in related genes such as CYP2C9 and VKORC1. By precisely adjusting the dose, reducing side effects, accelerating the treatment process, and reducing costs, this technology not only improves the quality of life of patients but also paves the way for new standards in healthcare. However, challenges such as high costs, limited access, and privacy issues require attention and resolution. In this approach, the genome of the individual in question is compared with reference genomes, and based on the information obtained, the individual can be treated in an appropriate and specific way. In fact, the genetic nature of the individual determines the treatment strategy. One aspect of personalized medicine is the use of pharmacogenomics. In this method, a more appropriate and informed drug is provided by using and knowing the sequence of an individual's genome. In conventional medicine, drugs are often prescribed with the idea that the effect of the drug is the same for everyone, but in fact this is not the case and each person responds differently to the drug depending on the nature of their genome sequence. Therefore, various factors must be taken into account. For example, depending on these sequences, side effects, the required amount of drug, the likelihood of successful treatment, and the prognosis of the disease will all be unique to each individual.

Abstract Introduction: Right ventricular pacing is critical for managing bradyarrhythmia but can impair left ventricular function due to dyssynchrony. This study examines the impact of septal versus apical pacing on left ventricular ejection fraction (LVEF) using three-dimensional echocardiography, aiming to determine which approach better preserves cardiac function by maintaining more physiologic ventricular activation.

Material and methods: This randomized historical control study included 60 patients undergoing permanent pacemaker implantation at Shahid Madani Hospital between 2011 and 2013. Patients were assigned to septal or apical right ventricular pacing. Three dimensional echocardiography was used to compare left ventricular volumes and ejection fraction, with blinded assessment and standard statistical analyses to evaluate functional differences between pacing strategies.

Results: Patients with septal right ventricular pacing demonstrated preserved conventional and three‑dimensional ejection fraction with no significant deviation from normal values (P > 0.05). Compared with apical pacing, septal pacing was associated with significantly higher conventional and 3D ejection fraction and less impaired septal longitudinal strain, with a clear intergroup difference in SPSS‑Sep.A (P = 0.001).

Conclusion: This study demonstrates that right ventricular septal pacing is associated with more favorable left ventricular systolic performance compared with apical pacing when assessed using both conventional and three dimensional echocardiography.

Abstract Introduction: Right ventricular pacing can alter physiological ventricular activation, potentially leading to mechanical dyssynchrony and regional myocardial dysfunction. Advanced echocardiographic techniques, particularly segmental peak systolic strain analysis, allow sensitive detection of these changes. The aim of this study was to evaluate and compare segmental peak systolic strain in patients with septal versus apical right ventricular pacing.

Material and methods: This randomized clinical study with a historical control design was conducted at Shahid Madani Hospital, Tabriz, between 2011 and 2013. Sixty patients requiring permanent pacing were enrolled by census sampling and allocated to septal or apical right ventricular pacing. Segmental peak systolic strain was assessed using speckle‑tracking echocardiography, with blinded analysis and appropriate statistical comparison between groups.

Results: In this cohort, septal right ventricular pacing demonstrated relatively preserved and homogeneous segmental peak systolic strain compared with apical pacing. Both pacing strategies significantly reduced mid and basal septal strain compared with normal values (p < 0.001), with no significant difference between RVS and RVA in Sep.M and Sep.B (p > 0.05). In contrast, anterior septal angle and motion were significantly altered in RVA compared with RVS and normal reference values (p < 0.05).

Conclusion: This study demonstrates that the site of right ventricular pacing plays a critical role in determining regional left ventricular myocardial mechanics. Although both septal and apical pacing are associated with deviations from physiological strain patterns, septal pacing consistently preserves a more uniform and coordinated deformation profile across myocardial segments.

Abstract The present study examined clinical and neurological problems and clinical tests in Alzheimer's patients specializing in Alzheimer's disease. The cause of Alzheimer's disease is the deposition of a series of proteins called amyloid and tau outside or inside brain cells, which occurs by creating plaques or knots in these cells. This begins before the onset of symptoms, and fortunately, this factor makes it possible to diagnose the disease before the onset of symptoms with special devices. Clinical and neurological problems and clinical tests in Alzheimer's patients are of great importance. Over time, with the deposition of these proteins in the brain, the level of neurotransmitters in the brain decreases sharply and various areas in the brain begin to shrink. The results showed that the first area of the brain to be affected is usually the memory area, but it is possible that the visual or speech and language areas of the brain may also be damaged over time. Another factor that increases the severity of this disease is aging, with some studies showing that the risk of developing Alzheimer's doubles for every five years after the age of 65. A family history of dementia, such as Parkinson's, down syndrome, severe brain injury, a sedentary lifestyle, hearing loss, depression, and heart problems are among the factors that increase a person's risk of developing this condition.

Abstract Introduction: Right ventricular pacing can profoundly influence left ventricular mechanics, particularly when non‑physiological activation patterns induce mechanical dyssynchrony and impaired myocardial deformation. Global peak systolic strain is a sensitive marker for detecting pacing‑related alterations in ventricular function. This study aimed to evaluate and compare global peak systolic strain in patients undergoing right ventricular apical versus septal pacing to determine the pacing site associated with more preserved myocardial mechanics.

Material and methods: This randomized historical control study included 60 patients undergoing permanent right ventricular pacing at a tertiary cardiac center. Participants were equally assigned to apical or septal pacing. Standardized echocardiography with speckle tracking analysis was performed to quantify global peak systolic strain, and outcomes were compared using appropriate statistical methods under blinded assessment and ethical approval.

Results: Right ventricular pacing was associated with significant impairment of left ventricular myocardial deformation. Global longitudinal strain showed a stepwise reduction from normal subjects to septal pacing and was most severely attenuated with apical pacing (p < 0.001). Inferior and mid‑inferior segmental strain was preserved with septal pacing but significantly reduced with apical pacing compared with both normal and septal groups (p ≤ 0.01).

Conclusion: This study demonstrates that the site of right ventricular pacing is a critical determinant of left ventricular mechanical performance. Although septal pacing does not fully replicate physiological ventricular activation, it is associated with relatively preserved global and regional myocardial deformation and reduced mechanical heterogeneity compared with apical pacing.