جستجوی مقالات مرتبط با کلیدواژه « personalized medicine » در نشریات گروه « پزشکی »

Neutrophils have gained significant interest in recent years due to their ability to promote malignancy. A high neutrophil-to-lymphocyte ratio is seen as a prognostic marker for cancer patients. Neutrophils are now recognized as immunological cells of the innate immune system that have several functions and are actively involved in the pathological process of cancer, rather than being just spectators. Their wide range of variations and adaptability are becoming more and more acknowledged. This review provides a concise overview of prior research investigating the functions and processes of neutrophils in the onset, advancement, spread, and recurrence of cancer. We provide a general overview of many studies that examine the characteristics and roles of neutrophils associated with tumors. Additionally, we discuss the formation of neutrophil extracellular traps, which are web-like structures produced by neutrophils that contribute to the advancement of cancer. Furthermore, we explore the interactions between neutrophils and the tumor microenvironment. Furthermore, several focused research on therapeutic neutrophils have achieved notable advancements and shown promising approaches for cancer therapy.

Acinetobacter baumannii is a common global source of infections linked to healthcare that have a high morbidity and fatality rate. Due to the fast emergence of multidrug-resistant and very drugresistant strains of A. baumannii, the therapeutic management of these infections has become much more challenging. Therefore, the creation of innovative intervention techniques is desperately needed to counteract this infection, which is resistant to several drugs. One of the best medical treatments for infection management is vaccination, which also has the potential to prevent A. baumannii from developing multidrug resistance. Here, we focused on the three most crucial preclinical vaccine development steps: immunological correlates of protection, antigen selection, and model organisms for effectiveness assessment. We also highlighted current developments and future obstacles in the production of A. baumannii vaccines.

In cancer treatment, anesthesia is commonly used during surgery to remove tumors, as well as for other procedures like biopsies, radiation therapy, and chemotherapy administration. Some research suggests that the choice of specific anesthetic drugs and nerve-sparing techniques can have a significant impact on cancer recurrence rates and overall patient survival. It is well-established that a patient's immune system plays a direct role in postoperative complications and long-term outcomes, highlighting the importance of optimizing anesthesia to minimize potential immune system suppression and improve immune function during cancer surgery. Recent studies have revealed a strong connection between the type of anesthesia used during surgery and the likelihood of cancer relapse and related mortality. Therefore, it is crucial to select the appropriate anesthesia technique for cancer resection, focusing on reversible effects, rapid recovery, and resistance to feedback. The specific anesthetic agents used during surgery have a significant impact on survival rates and the risk of cancer-related mortality. Genetic influences on anesthesia response are significant for improving patient care and achieving better results. Additionally, personalized medicine, which combines diagnostic testing and treatment, is now a clinical reality. Anesthesia's effects on depth, pain signals, vital signs, and the motor system are complex and not fully understood, and many researchers believe that anesthesia is regulated by multiple genes, although further research is needed to identify them and understand how they are regulated. The relationship between anesthesia and cancer is complex and evolving with implications for medical treatment. Limited evidence suggests that anesthesia and surgery-related factors can affect cancer biology and outcomes. Further research is needed to understand these interactions and develop strategies for improving cancer care during surgery. Better understanding can lead to safer and more effective cancer treatment, benefitting patients.

Smoking is widely recognized as a significant factor in the global disease burden, leading to 4 million deaths annually throughout the globe. Various research has shown that the prevalence of smoking worldwide is on the rise among both males and females, particularly among the younger demographic. Behavior modification is a primary objective in public health initiatives that prioritises preventive measures before the occurrence of illness. Utilizing innovative personalized medicine programs may serve as a significant prognostic determinant in modifying the behavior of smokers and enhancing societal health. Thus, this review research presents an appropriate framework for personal medical applications that may effectively alter smokers' health and health behavior.

Lung cancer is the prevailing form of cancer globally, with a significant fatality rate among both males and females. Lung cancer is the third most frequent type of cancer in Iran, and it is becoming more common all the time. Patients are frequently diagnosed in the advanced stages of the disease, which contributes to the high death rate. Therefore, the ability to identify molecular markers is essential for both early diagnosis and the choice of conventional treatment for lung cancer. Numerous genetic variations have been found to be strongly linked to the development of lung cancer, according to studies. The aim of this work is to look into the genes that contribute to the development of lung cancer.

The present review was authored using search terms related to lung cancer, key genes, clinical biomarkers, and early diagnosis that were found on PubMed, NCBI, Scopus, Science Direct, and Google Scholar.

Since the EGFR, KRAS, BRAF, and TP53 genes are the most significant and involved in the development of lung cancer, finding mutations in these genes can be a valuable clinical diagnostic for lung cancer diagnosis and therapy.

With an emphasis on personalized medicine, the identification of genes linked to lung cancer may be utilized as clinical biomarkers for the disease's early diagnosis and effective treatment. The state of targeted lung cancer therapy and early detection techniques may be enhanced by molecular biomarkers. In the field of personalized medicine, identifying the genes linked to lung cancer as clinical biomarkers for early diagnosis and assessing treatment response to select a targeted treatment can be crucial in streamlining the therapeutic process, improving treatment response, lowering mortality, and lessening the material and spiritual harm this illness causes.

Autoimmune disorders are complex conditions that result from a combination of genetic and environmental causes and currently have no recognized therapy. Various therapeutic strategies may be used in various illnesses to promote remission or, at the very least, alleviate the symptoms. For customized therapy to be implemented, it is necessary to identify groups of individuals who are generally similar and share pathogenic signaling pathways. Therefore, research about autoimmune disorders mainly focuses on identifying new biomarkers, uncovering novel targets for therapy and agents, and understanding the processes involved in developing various disorders. We are just at the nascent phase of implementing tailored therapy for autoimmune illnesses. Hence, this research delved into the examination of several autoimmune illnesses and the impact of personalized therapy on their progression.

Precision medicine is accomplished by the process of categorising people and administering therapy that specifically targets their condition. Evidence demonstrates that the pathological circumstances of patients who are categorized or diagnosed with a singular disease exhibit significant diversity in nearly all autoimmune disorders. Hence, the use of precision medicine is crucial in the management of patients suffering from autoimmune disorders. At present, precision medicine is not available for any autoimmune disease. This article examines the use of precision medicine in the treatment of psoriasis, Alzheimer’s disease and rheumatoid arthritis. Therefore, after a comprehensive understanding of these autoimmune disorders and their treatment strategies, we will use a personalized medicine approach in the management of these diseases.

Methadone maintenance treatment (MMT) has been a cornerstone in heroin addiction management. However, its efficacy varies among individuals. The complex interplay of genetic backgrounds and demographic data could influence the response to MMT in heroin addiction. No previous adoption study has aimed to merge these findings into a potential pre-treatment screening tool.

This study aimed to investigate the combined influence of dopamine and opioid receptors and receptor endocytosis machinery genes, individual genetic backgrounds, and demographic data on the response toMMT in patients with heroin addiction.

We enrolled 80 heroin addicts receiving MMT for 3 months alongside 80 healthy individuals in a comparative study. The approach utilized multinomial, linear, and binary logistic regression analyses to investigate the interplay of genetic factors (DRD1-5, opioid receptors [µ1, δ1, and κ1], DNM1L, RAB22A, and COMT), demographic independent variables, including, family history, heroin duration, age onset, heroin dose, and methadone dose, and clinical markers Subjective Opiate Withdrawal Scale (SOWS) with compliance with MMT protocols.

Results revealed that a positive family history and a higher level of heroin dose significantly predicted poor compliance to MMT. Additionally, the patients with lower expression levels of DRD2 and higher expression levels of DNM1L and COMT genes were at higher risk for poor compliance with the treatment.

By utilizing a comprehensive dataset of gene expression profiles and demographic and clinical parameters, this study developed a regression model predicting resistance or response to methadone. This innovative approach seeks to bridge the gap between pharmacogenomics and clinical practice and offer a potential pre-treatment screening tool for personalized MMT strategies in opioid addiction management. The obtained findings hold intriguing promise for future research, potentially unlocking deeper insights into the underlying risk factors of addiction.

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.

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.

Cell culture-based technologies are widely utilized in various domains such as drug evaluation, toxicity assessment, vaccine and biopharmaceutical development, reproductive technology, and regenerative medicine. It has been demonstrated that pre-adsorption of extracellular matrix (ECM) proteins including collagen, laminin and fibronectin provide more degrees of support for cell adhesion. The purpose of cell imprinting is to imitate the natural topography of cell membranes by gels or polymers to create a reliable environment for the regulation of cell function. The results of recent studies show that cell imprinting is a tool to guide the behavior of cultured cells by controlling their adhesive interactions with surfaces. Therefore, in this review we aim to compare different cell cultures with the imprinting method and discuss different cell imprinting applications in regenerative medicine, personalized medicine, disease modeling, and cell therapy.

There were more than thirty-eight million HIV infections worldwide. Combination antiretroviral therapy (cART) has progressed to the point where invisible viral loads are now feasible, and HIV carriers frequently lead almost everyday lives with considerably greater average life expectancies than in the past. However, there is still no cure for the disease. Even though the ailment usually advances to a chronic state, an individual's unique course of progression may differ significantly from the average and manifest distinctively for each patient. This diversity begs whether a typical treatment strategy is appropriate for a patient..

It has been known for quite some time that gut microbiota plays an important role in human health and illness. Recent years have seen a surge in interest in the human gut microbiota, and the advent of metagenomic investigations has greatly aided our understanding of the resident species and their potential uses. The human digestive tract is home to billions of bacteria, making up the varied gut microbiota. At birth, the gut microbiome begins to take shape and proliferate, and throughout life, numerous genetic, dietary, and environmental variables will shape and multiply this community. Alterations to the gut microbiota's structure and function may affect digestion, metabolism, and the immune system. Meanwhile, personalized medicine, a new therapeutic approach, has opened a new door in the medical sciences, and the link between the microbiome and personalized medicine is one of the most intriguing areas of study going forward. Since the link between this two axis is new, there are few research on it. Therefore, in this review study, the relationship between the gut microbiome, drug interactions, disease progression, and personalized medicine has been discussed.

Psychiatric disorders are a major health problem in individual and societal aspects, due to their considerable prevalence and burden and treatment issues (1-3). Estimates indicated that about 792 million people, equivalent to 10.7% of the world population, had mental health disorders in 2017 (4). In 2019, mental disorders were among the top ten causes of burden worldwide, as before, and the Disability-Adjusted Life-Years (DALYs) attributed to them was 418 million (16% of global DALYs) (5,6). The associated economic costs have been estimated at $4.7 trillion – even up to $10 trillion (6). These statistics are related to disorders whose medications and alternative treatments have incomplete efficacy and debilitating side effects that result in limitations in both therapy and compliance so that only one-third of patients with major psychiatric disorders achieve complete and stable symptom remission (7). These data make access to a predictive tool of treatment response crucial and desirable. The uniqueness of each person along with the heterogeneity of diseases is the basis of the concept of personalized medicine, in which personalized psychiatry pursues the trends (8,9). Genetics is responsible for 20 to 95% of the variation in medication disposition and pharmacodynamics in the central nervous system (7). Each patient’s unique phenotype, comorbidities, dietary habits, and medication habits can potentially cause changes in the pharmacokinetics and pharmacodynamics of medications. Personalized psychiatry was presented to provide an individually adapted approach for prevention, diagnosis, treatment, follow-up, and rehabilitation. Parts of these depend on developing pharmacogenomics and pharmacogenetics (8,9). The study of the genetic causes of variation among patients in response to medications and the study of the simultaneous effects of multiple mutations in the genome determining the response to medications are called pharmacogenetic and pharmacogenomic, respectively. However, there is no consensus on the difference between the two, and in practice, they overlap (9). Personalized psychiatry that relates the response to medication to its pharmacokinetic and pharmacodynamic changes as a result of the patient’s genotype, in principle, indicates the application of pharmacogenetics in treatment. The primary focus of the pharmacogenetic-psychiatry link has been the YP2D6, CYP2C19, and CYP3A4 enzymes in the liver because of their responsibility for the metabolism of most antidepressants and antipsychotics (7,8). The translation of pharmacogenetic evidence into clinical practice is an important endeavor that began a few years ago. An example of the application of pharmacogenetic information to guide pharmacotherapy in psychiatry is using genetic information on CYP2D6, CYP2C19, CYP1A2, SLC6A4, and HTR2A for dosing, which increased the number of responders to antidepressants in a pioneering study. Overall, pharmacogenetically supported depression improvement was reported to be 1.71 times better than usual. Similarly for antipsychotics, the association of CYP2D6 genotype and risperidone in order to individualize dosing has been shown in a large-scale study. This evidence has grown and matured to the point where guidelines for implementation have been provided. Its psychiatry examples are the Dutch Pharmacogenetics Working Group recommendations regarding CYP2D6 and CYP2C19 genotypes for antidepressants and antipsychotics and the guidance for using genetic information in pharmacotherapy for psychiatry published by The Clinical Pharmacogenetic Implementation Consortium (7,10). In the application of pharmacogenetics in personalized medicine, attention to cost-effectiveness and ethical issues is essential. It seems that having a genetic passport providing polymorphic genes involved in common medications in which dosing is important, after full maturity and reaching the certainty of the evidence, is cost-effective. In other words, in this case, an advantage of integrating pharmacogenetics and psychiatry would be to reduce costs (7). In regard to ethical issues, the guidelines and instructions should be complied in a way so that ethical obstacles such as privacy and confidentiality and knowledge gap and informed consent are overcome, a balance between social and individual interests is established, and ethical decisions are also personalized (11,12). In conclusion, beneficial and adverse effects are intrinsic properties of medications, and pharmacogenetics can increase the possibilities of improving effectiveness and reducing risk. As a result, although the risk-benefit ratio cannot be guaranteed in a patient, it improves in the population. Moreover, determining the patient’s genotype may reduce the time needed to identify the correct medication and its dosage and minimize exposure to ineffective medications. Although the clinical applications of pharmacogenetics are certain, the use of all currently proposed genes is not consensus. In the future, pharmacogenetics can be extended to other genes, encoding enzymes, transporters, receptors, and other downstream molecules. Keywords Behavioral science, Cost effectiveness, Ethical issue, Genetics, Mental disorder, Personalized medicine, Pharmacogenomics, Precision medicine Acknowledgements This paper did not receive any specific grant from public, commercial, or not-for-profit funding agencies. Conflict of Interest The authors had no competing interests.

The process of diagnosis and treatment in Persian medicine (PM) are based on the concept of Mizaj (temperament). Among the indices of Mizaj determination, anthropometric indices are less influenceable regarding age change and other environmental factors. The purpose of this study was to investigate the relationship between anthropometric indices and Mizaj.

Four PM experts determined the Mizaj of 121 participants. Those who had ≥70% agreement in their Mizaj determination by the experts were selected and their anthropometric indices were measured. The best cutoff point of each index and its relationship with the defined Mizaj were extracted using Receiver Operative Characteristic Curve and Binary Logistic Regression.

52 out of 121 participants entered the main study. The warm-Mizaj people had larger dimensions in height, shoulder, chest, palm and sole width, and head height. Cold-Mizaj people had smaller dimensions in weight, height, shoulder, chest and head. High levels of BMI, chest depth and head dimensions had the highest correlation with the wet Mizaj and lower dimensions of these indices had the highest correlation with the dry Mizaj. 

Among the anthropometric indices, chest, palm, sole dimensions, head height and weight had the highest correlation with warmness/coldness and BMI, head width and chest dimensions had the highest correlation with wetness/dryness. The BMI which is more closely related to the soft tissue, only correlates with the wetness/dryness, while, bone dimensions are associated with warmness/coldness. Further studies are needed to metricize the anthropometric indices for Mizaj determination.

The coronavirus disease 2019 (COVID-19) pandemic has prompted researchers to look for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pathogenicity in depth. Immune system dysregulation was one of the major mechanisms in its pathogenesis. The evidence regarding the levels of interferons (IFNs) and pro- and anti-inflammatory cytokines in COVID-19 patients is not well-established.

This study evaluated the expression level of type-I, II, III IFNs, along with interleukin-1 (IL-1), interleukin-6 (IL-6), interleukin-10 (IL-10), and FOXP3 genes in patients with severe COVID-19 to provide additional insights regarding the regulation of these cytokines during COVID-19 infection.

Peripheral blood mononuclear cells were isolated from two groups, including severe COVID-19 patients and healthy controls. Ribonucleic acid was extracted to evaluate the expression level of IFN-a, IFN-b, IFN-g, IFN-la, IL-1, IL-6, IL-10, and FOXP3 genes using real-time polymerase chain reaction. The correlations between the expression levels of these genes were also assessed.

A total of 40 samples were divided into two groups, with each group consisting of 20 samples. When comparing the severe COVID-19 group to the controls, the expression levels of IFN-g, tumor necrosis factor-alpha (TNF-), IL-6, and IL-10 genes were significantly higher in the severe COVID-19 group. The two groups had no significant differences in IFN-a, IFN-b, IFN-la, IL-1, and FOXP3 expression. The correlation analysis revealed a negative correlation between type I and type III IFNs (i.e., IFN-a and IFN-la) and proinflammatory cytokines (i.e., IL-1 and IL-10).

This study suggests the possible upregulation of IFN-g, IL-6, IL-10, and TNF-during SARS-CoV-2 pathogenicity. The preliminary findings of this study and those reported previously show that the levels of IFNs and pro- and anti-inflammatory cytokines are not uniformly expressed among all COVID-19 patients and might differ as the disease progresses to the severe stage.

A number of animal disease models have been created in the past to investigate the molecular basis of neurological diseases and identify novel treatments, but their effectiveness has been limited by the absence of comparable animal models. There are still several important problems that need to be overcome, including the high expenses associated with creating animal models, ethical issues, and a lack of similarity to human disease. More than 90% of medications fail in the last stage of the human clinical trial as a result of inadequate early screening and assessment of the molecules. A novel strategy based on induced pluripotent stem cells has been developed to get around these restrictions (iPSCs). A new road map for clinical translational research and regeneration treatment has been made possible by the discovery of iPSCs. In this paper, we investigate the potential use of patient-derived iPSCs to neurological disorders as well as their significance in scientific and clinical studies for the creation of disease models and a road map for the next of medicine. The role of human iPSCs in the most prevalent neurodegenerative illnesses (such as Parkinson’s and Alzheimer’s disease, diabetic neuropathy) was evaluated. The patient-on-a-chip idea, where iPSCs may be cultivated on 3D matrices within microfluidic devices to produce an in vitro disease model for tailored medication, is another new development in the field of personalized medicine that we looked into.

In the twenty-first century, there still needs more clarity on rheumatoid arthritis (RA). Rheumatoid arthritis is a widespread but heterogeneous illness with a broad range in its history, clinical symptoms, and response to therapy. It is now known that prevention of joint destruction, functional impairment, and a poor disease prognosis depends on early, correct diagnosis and starting therapy with disease-modifying drugs (DMARDs), among which methotrexate (MTX) remains the gold standard in the treatment of RA. Early rheumatoid arthritis diagnosis is crucial since it enables a speedier start to primary therapy. Pharmacogenetic and pharmacogenomic research, which aid in identifying a patient’s genetic profile, may bring personalized treatment closer to reality. Identifying disease-specific genes while the organism’s resistance to them is still intact should be made feasible by further study into RA.