Personalized and Precision Medicine Journal

Abstract Introduction: In this context, the use of medicinal plants as a natural and effective remedy for relieving Menstrual pain has been acknowledged in the western border region of Iran, serving as an alternative or complementary therapeutic approach. The aim of this study is to identify the medicinal plants employed in this region of Iran for the treatment of menstrual pain.
Methodology: This review study employed keywords such as medicinal plants, Iran, menstrual pain, and the provinces of West Azerbaijan, East Azerbaijan, Ardabil, Kurdistan, Kermanshah, Ilam, Khuzestan, and their cities, along with ethnobotany terms. Databases such as Google Scholar, SID, MegaIran, PubMed, and Scopus were utilized for article searches. Ethnobotanical articles related to the topic were selected for text review.
Results: Based on the ethnobotanical review, it was identified that in the cities and provinces of the western border region of Iran, medicinal plants such as fennel, wild parsley, shepherd's purse, black cumin, thyme, dandelion, rue, safflower, myrtle, European hornbeam, Kurdistan pistachio, mint, marshmallow root, male orchid, yarrow, agrimony, nettle, bitter herb, verbena, horsetail, periwinkle, marigold, saffron, wild thyme, savory, rhubarb, and eastern chamomile are commonly used for managing, controlling, and treating menstrual pain. Notably, the highest diversity of plant species was observed in the regions of Behbahan, Khuzestan, and Zrewar, Kurdistan. Leaves were the most commonly used plant part, and the Asteraceae and Lamiaceae families presented the highest number of species, indicating the rich diversity of medicinal and traditional plant applications.
Conclusion: The findings of this study demonstrate that the local communities in the western border region of Iran possess extensive knowledge regarding the use of medicinal plants for alleviating menstrual pain. Documenting and scientifically exploring this knowledge could lay the groundwork for the development of effective and natural herbal medicines in the domain of women’s health.

Abstract Breast cancer is responsible for more than 2.3 million newly diagnosed cases each year, according to the statistics. A hormonal imbalance, which is defined by unregulated activity of estrogen and progesterone, is often the cause of this type of cancer. It has become easier to handle patients who have HR+ breast cancer, particularly in women who have both advanced and early-stage disease, as a result of the deployment of estrogen-blocking hormone treatment. The permissiveness of tamoxifen, which was the first selective estrogen receptor modulator (SERM) to be commercialized, made it possible for more hormonal therapies to be developed. The cornerstone of breast cancer treatment is comprised of aromatase inhibitors (AIs), selective estrogen receptor degraders (SERDs), and cyclin-dependent kinase inhibitors (CDK) 4/6. These three types of drugs ultimately lead to improved patient outcomes. On the other hand, the inherent or acquired resistance of cancers to hormone therapy continues to be a serious cause for concern. Alterations in the genetic makeup of the tumor, as well as the activation of alternate pathways, make this situation even worse. The increasing development of molecular biology, precision medicine, and targeted therapies, on the other hand, is pointing to a new strategy for dealing with these problems. The purpose of this study is to investigate prospective treatment options and to shed light on the significant role that hormone therapy plays in the management of HR-positive breast cancer.

Abstract Rheumatic inflammatory diseases, besides affecting joints and other bodily systems, are linked to heightened mortality and morbidity. Cardiovascular reasons are among the most prevalent mortality factors in individuals with these disorders, attributable to the disease's etiology and pathophysiology, chronic inflammation, and the pharmacological treatments employed. Although rheumatoid arthritis, systemic lupus erythematosus, psoriatic arthritis, and gout exhibit distinct pathophysiology and symptoms, persistent inflammation remains their shared pathophysiological characteristic. Metabolic syndrome has recently been linked to several of these disorders. The investigation of metabolic syndrome in inflammatory rheumatic diseases is significant for multiple reasons, including its correlation with cardiovascular disease onset, the emergence of a pre-inflammatory condition, treatment selection, and associated monitoring. This review article initially explores the significance of metabolic syndrome in rheumatic diseases, followed by a detailed analysis of each condition individually. This study concludes, through a review of previous studies, that abdominal obesity in rheumatoid arthritis and lupus patients, abdominal obesity and hypertension in psoriatic arthritis patients, and hypertriglyceridemia and hypertension in gout are significant elements of metabolic syndrome warranting increased focus.

Abstract Precision nutrition is now feasible thanks to recent developments in genomic and multi-omic technology, which have significantly changed our understanding of the complex interactions between nutrition, genetics, and health.Sometimes shortened to nutrigenetics, epigenetics, metagenomics, and nutrigenomics, nutritional genomics is the study of how environmental influences, gut flora, genetic variants, and gene expression affect food responses and illness risk. This new work offers significant fresh ideas for modifying diets to fit traditional food systems, cultural conventions, and personal genetic profiles. Diet evolution aims to solve the flaws in the "one-diet-fits-all" approach in view of the worldwide increase in chronic diseases. Variations in genes and cultural standards call into doubt the health advantages of often advised diets, including the Mediterranean model, when considered in specific communities. Customized diet regimens aimed at enhancing health should take into account lifestyle, regional cuisine, microbiome variety, genetic inheritance, and other elements. Combining traditional cooking skills with modern scientific information provides a culturally sensitive, environmentally friendly, and effective method to prevent diseases and promote long-term health improvement as is becoming the case in public health strategies.

Abstract A common and incapacitating condition, chronic pain offers a difficult field of work because of its variability and response to conventional treatments. Genomic and proteomic-based personalized medicine including epigenetic and biomarker information could help to lower treatment variability, so improving diagnosis, phenotypic classification, and individualized approaches to treatment. Recent developments in genetics and pharmacogenetics of pain, pain phenotyping techniques, and the development of focused therapies including epigenetic modulators, peptides, biologics and nanomedicine are underlined in this review. Personalized medicine seeks to match every patient's individual genetic makeup to their course of treatment. It is increasingly accepted that pain chronology involves epigenetic processes, including DNA methylation and histone modifications. Furthermore discussed are the value of biomarkers in evaluating therapy response and prognosis as well as ethical, financial, and data availability-related issues. Finally, future directions involve the use of artificial intelligence mixed with multi-omics data for tailored optimal pain management. Adopting these changes can help patients to have less chronic pain and improve the therapeutic outcomes.

Abstract Background and Objective: Gene therapy can be employed to treat several disorders, including cancer. Globally, women are more frequently diagnosed with breast cancer than any other cancer type, underscoring the necessity for innovative strategies. Algorithms driven by artificial intelligence can enhance the gene therapy process for breast cancer by analyzing vast data sets, identifying intricate patterns, and classifying those patterns. This project aims to perform a literature evaluation focusing on the therapeutic uses of artificial intelligence in gene therapy for breast cancer.

Materials and Methods: For the aim of this study, data was gathered by reading previously published articles and searching the PubMed database for phrases that were relevant to the question being investigated.
Findings: The AI-driven algorithm analyzes complex molecular pathways in the human body, replicates the knowledge of scientists and physicians in clinical research, and simulates biological processes related to gene regulation, thereby improving the effectiveness of gene vectors, managing gene and drug delivery parameters, and modeling cellular behavior. This method diminishes medical errors and promotes early disease identification and drug efficacy forecasting, thereby providing patients with optimal results from advanced treatments like gene therapy with minimal side effects.
Conclusion: Over the period of the past decade, a multitude of efforts have been made to deploy various gene therapy procedures for breast cancer patients, to achieve the highest possible level of efficacy while minimizing the risk of adverse consequences. As a result, artificial intelligence is considered to be a powerful tool for improving early diagnosis and efficient gene therapy for breast cancer.

Abstract Background: Campylobacter, a zoonotic pathogen, is the primary bacterial agent responsible for gastrointestinal (GI) infections in humans. Domestic animals, including cattle, are reservoirs of this bacterium, and can be one of the main sources of infection transmission to humans. This study aimed to investigate the prevalence of Campylobacter species using a multiplex PCR assay in cattle in the Gorgan province.
Materials and Methods: A total of 200 fecal samples were collected from healthy dairy cattle and genus and species were identified using multiplex PCR.
Results: The frequency of the genus Campylobacter in 200 samples in our study was 17.5% (35 cases), C. jejuni and C. coli species were not identified in these 35 cases.
Conclusion: Isolating Campylobacter from animal fecal samples is a challenging process, but this study showed that Campylobacter contamination was relatively high in cattle in the Gorgan province, and its transmission to humans through meat consumption must be monitored.

Abstract Variability in medication reactions and illness susceptibility among individuals is often seen in clinical settings. Personalized medicine is now highly esteemed for its focus on prescribing the appropriate medication to each patient. Metabolomics is a developing field that thoroughly assesses all metabolite and low-molecular-weight compounds in a biological sample. Metabolic profiling offers a quick overview of a cell's physiology, making the technique a direct indicator of an organism's physiological condition. Quantifiable correlations exist between the metabolome and other cellular components such as the genome, transcriptome, proteome, and lipidome. These correlations can be utilized to forecast metabolite levels in biological samples based on mRNA levels. One of the key problems in systems biology is to incorporate metabolomics with other -omics data to enhance comprehension of cellular biology. Metabolomics is used to assess the effectiveness of clinical substances by analyzing the metabolic characteristics of patients before treatment to predict their responses (pharmacometabolomic) and to identify individuals at risk of developing diseases (patient stratification). The rapid progress in metabolomics technique highlights its significant potential for use in customized treatment. We reviewed the unique benefits of metabolomics, including instances in assessing medication treatment and individual stratification, and emphasized metabolomics' promise in personalized medicine.

Abstract Myeloproliferative neoplasm (MPN) is a neoplasm with three categories; essential thrombocythemia (ET), polycythemia vera (PV), and primary myelofibrosis (PMF) and it usually is diagnosed through mutation analysis in several essential genes; JAK2, MPL, CALR. The mutations of mentioned genes in 50 patients with MPN and 50 healthy volunteers were determined via allele-specific PCR and sequencing. Based on the results, MPN and its subtypes have significant relation with mutations (p<0.05). JAK2 (exon 14) mutation was related to MPN and its subtypes except for ET and CALR (exon 9) type 1 was merely related to ET, but CALR (exon 9) type 2 mutation was more prevalent in MPN and PV (p<0.05). None of the mutations co-occurred simultaneously. There was no evidence of mutation in JAK2 (exon 12) and MPL (exon 9 and 10) in our study, so they are unsuitable diagnostic candidates. So, mutations in JAK2 (exon 14), and CALR (exon 9) type 1 and 2 are essential in MPN diagnosis in Iranians.

Abstract Precision medicine is a medical approach that involves customizing therapy for an individual by using extensive biological and external data. The rapid progress in the disciplines of molecular biology, gene sequencing, machine learning, and related technologies has facilitated the use of precision medicine. This approach utilizes the wealth of comprehensive information obtained from these advancements to improve the decision-making process in clinical treatment for individuals, particularly in real-time scenarios during the progression of a disease. Diabetes mellitus is a significant worldwide health issue, requiring the implementation of novel strategies to enhance patient outcomes. The efficacy of conventional treatment options that use a uniform approach has been shown to be limited in effectively addressing the heterogeneous character of the illness. In recent times, personalized medicine has surfaced as a revolutionary resolution, customizing treatment strategies in accordance with an individual's health attributes, lifestyle choices, and genetic composition. This review underscores the significance of genetic screening in forecasting susceptibility to diabetes and treatment response, while also emphasizing the potential of pharmacogenomics to optimize medication selection.