Search Results (920)

Balneology is one of the oldest fields of medicine related to the use of natural raw materials (medicinal waters, medicinal gases, peloids, climatic values) in the treatment, prevention, and rehabilitation of many diseases but also increasingly in cosmetology. Currently, balneotherapy (spa therapy) combines tradition and modernity. The interest in spa treatments, the popularity of a healthy lifestyle, as well as the constant search for active substances of a natural origin for cosmetics make peloids, medicinal, and mineral waters very popular in the cosmetics industry. The main aim of this review was to present current, scientifically proven knowledge about the potential use of peat, huic substances, and sulfurous water in cosmetology. The work describes the potential possibilities of using medicinal waters, especially sulfurous waters, as well as peats and humic compounds, which are the source of active substances with biological activity e.g., antibacterial, anti-inflammatory, and antioxidant, and possess a positive effect on psoriasis, atopic dermatitis, or acne. The therapeutic effects of these substances have been well documented in the literature; however, the validity of their use in cosmetology requires further confirmation. Full article

Most medications undergo metabolism and elimination via CYP450 enzymes, while uptake and efflux transporters play vital roles in drug elimination from various organs. Interactions often occur when multiple drugs share CYP450-transporter-mediated metabolic pathways, necessitating a unique clinical care strategy to address the diverse types of CYP450 and transporter-mediated drug-drug interactions (DDI). The primary focus of this review is to record relevant mechanisms regarding DDI between COVID-19 and tuberculosis (TB) treatments, specifically through the influence of CYP450 enzymes and transporters on drug absorption, distribution, metabolism, elimination, and pharmacokinetics. This understanding empowers clinicians to prevent subtherapeutic and supratherapeutic drug levels of COVID medications when co-administered with TB drugs, thereby mitigating potential challenges and ensuring optimal treatment outcomes. A comprehensive analysis is presented, encompassing various illustrative instances of TB drugs that may impact COVID-19 clinical behavior, and vice versa. This review aims to provide valuable insights to healthcare providers, facilitating informed decision-making and enhancing patient safety while managing co-infections. Ultimately, this study contributes to the body of knowledge necessary to optimize therapeutic approaches and improve patient outcomes in the face of the growing challenges posed by infectious diseases. Full article

Interindividual variation in drug efficacy and toxicity is a significant problem, potentially leading to adverse clinical and economic public health outcomes. While pharmacogenetics and pharmacogenomics have long been considered the primary causes of such heterogeneous responses, pharmacomicrobiomics has recently gained attention. The microbiome, a community of microorganisms living in or on the human body, is a critical determinant of drug response and toxicity. Factors such as diet, lifestyle, exposure to xenobiotics, antibiotics use, illness, and genetics can influence the composition of the microbiota. Changes in the intestinal microbiota are particularly influential in drug responsiveness, especially in cancer chemotherapy. The microbiota can modulate an individual’s response to a drug, affecting its bioavailability, clinical effect, and toxicity, affecting treatment outcomes and patient quality of life. For instance, the microbiota can convert drugs into active or toxic metabolites, influencing their efficacy and side effects. Alternatively, chemotherapy can also alter the microbiota, creating a bidirectional interplay. Probiotics have shown promise in modulating the microbiome and ameliorating chemotherapy side effects, highlighting the potential for microbiota-targeted interventions in improving cancer treatment outcomes. This opinion paper addresses how environmental factors and chemotherapy-induced dysbiosis impact cancer chemotherapy gastrointestinal toxicity. Full article

Stroke, as a serious cerebral vascular disease with high incidence and high rates of disability and mortality, has limited therapeutic options due to the narrow time window. Compelling evidence has highlighted the significance of the gut microbiota and gut–brain axis as critical regulatory factors affecting stroke. Along the microbiota–gut–brain axis, tryptophan metabolism further acquires increasing attention for its intimate association with central nervous system diseases. For the purpose of exploring the potential role of tryptophan metabolism in stroke and providing systematic insights into the intricate connection of the microbiota–gut–brain axis with the pathological procedure of stroke, this review first summarized the practical relationship between microbiota and stroke by compiling the latest case-control research. Then, the microbiota–gut–brain axis, as well as its interaction with stroke, were comprehensively elucidated on the basis of the basic anatomical structure and physiological function. Based on the crosstalk of microbiota–gut–brain, we further focused on the tryptophan metabolism from the three major metabolic pathways, namely, the kynurenine pathway, serotonin pathway, and microbial pathway, within the axis. Moreover, the effects of tryptophan metabolism on stroke were appreciated and elaborated here, which is scarcely found in other reviews. Hopefully, the systematic illustration of the mechanisms and pathways along the microbiota–gut–brain axis will inspire more translational research from metabolic perspectives, along with more attention paid to tryptophan metabolism as a promising pharmaceutical target in order to reduce the risk of stroke, mitigate the stroke progression, and ameliorate the stroke prognosis. Full article

In this scoping review, we delve into the transformative potential of artificial intelligence (AI) in addressing challenges inherent in whole-genome sequencing (WGS) analysis, with a specific focus on its implications in oncology. Unveiling the limitations of existing sequencing technologies, the review illuminates how AI-powered methods emerge as innovative solutions to surmount these obstacles. The evolution of DNA sequencing technologies, progressing from Sanger sequencing to next-generation sequencing, sets the backdrop for AI’s emergence as a potent ally in processing and analyzing the voluminous genomic data generated. Particularly, deep learning methods play a pivotal role in extracting knowledge and discerning patterns from the vast landscape of genomic information. In the context of oncology, AI-powered methods exhibit considerable potential across diverse facets of WGS analysis, including variant calling, structural variation identification, and pharmacogenomic analysis. This review underscores the significance of multimodal approaches in diagnoses and therapies, highlighting the importance of ongoing research and development in AI-powered WGS techniques. Integrating AI into the analytical framework empowers scientists and clinicians to unravel the intricate interplay of genomics within the realm of multi-omics research, paving the way for more successful personalized and targeted treatments. Full article

Depression continues to be a significant and growing public health concern. In clinical practice, it involves a clinical diagnosis. There is currently no defined or agreed upon biomarker/s for depression that can be readily tested. A biomarker is defined as a biological indicator of normal physiological processes, pathogenic processes, or pharmacological responses to a therapeutic intervention that can be objectively measured and evaluated. Thus, as there is no such marker for depression, there is no objective measure of depression in clinical practice. The discovery of such a biomarker/s would greatly assist clinical practice and potentially lead to an earlier diagnosis of depression and therefore treatment. A biomarker for depression may also assist in determining response to medication. This is of particular importance as not all patients prescribed with medication will respond, which is referred to as medication resistance. The advent of pharmacogenomics in recent years holds promise to target treatment in depression, particularly in cases of medication resistance. The role of pharmacogenomics in routine depression management within clinical practice remains to be fully established. Equally so, the use of pharmaceutical grade nutrients known as nutraceuticals in the treatment of depression in the clinical practice setting is largely unknown, albeit frequently self-prescribed by patients. Whether nutraceuticals have a role in not only depression treatment but also in potentially modifying the biomarkers of depression has yet to be proven. The aim of this review is to highlight the potential biomarkers for the diagnosis, prediction, and medication response of depression. Full article

This study aimed to determine the prevalence of adverse events in mechanically ventilated adults with COVID-19 who have undergone prone positioning. A total of 100 patients were included retrospectively; 60% were males, the mean age was 64.8 ± 9.1 years, and hospital mortality was 47%. In all, we recorded 118 removals of catheters and tubes in 66 patients; 29.6% were removals of a nasogastric tube, 18.6% of an arterial line, 14.4% of a urinary catheter, and 12.7% of a central venous catheter. Reintubation or repositioning of a tracheotomy tube was required in 19 patients (16.1%), and cardiopulmonary resuscitation in 2 patients (1.7%). We recorded a total of 184 pressure ulcers in 79 patients (on anterior face in 38.5%, anterior thorax in 23.3% and any extremity anteriorly in 15.2%). We observed that body weight (p = 0.021; β = 0.09 (CI95: 0.01–0.17)) and the cumulative duration of prone positioning (p = 0.005; β = 0.06 (CI95: 0.02–0.11)) were independently associated with the occurrence of any adverse event. The use of prone positioning in our setting was associated with a greater number of adverse events than previously reported. Body weight and cumulative duration of prone positioning were associated with the occurrence of adverse events; however, other factors during a COVID-19 surge, such as working conditions, staffing, and staff education, could also have contributed to a high prevalence of adverse events. Full article

This study investigates the association between circulating microRNA (miRNA) expression and cardiovascular adverse events (CVAE) in multiple myeloma (MM) patients treated with a carfilzomib (CFZ)-based regimen. A cohort of 60 MM patients from the Prospective Observation of Cardiac Safety with Proteasome Inhibitor (PROTECT) study was analyzed. Among these, 31 patients (51.6%) developed CVAE post-CFZ treatment. The Taqman OpenArray Human microRNA panels were used for miRNA profiling. We identified 13 differentially expressed miRNAs at baseline, with higher expressions of miR-125a-5p, miR-15a-5p, miR-18a-3p, and miR-152-3p and lower expression of miR-140-3p in patients who later developed CVAE compared to those free of CVAE, adjusting for age, gender, race, and higher B-type natriuretic peptide levels. We also identified three miRNAs, including miR-150-5p, that were differentially expressed in patients with and without CVAE post-treatment. Additionally, five miRNAs responded differently to CFZ treatment in CVAE vs. non-CVAE patients, including significantly elevated post-treatment expression of miR-140-3p and lower expressions of miR-598, miR-152, miR-21, and miR-323a in CVAE patients. Pathway enrichment analysis highlighted the involvement of these miRNAs in cardiovascular diseases and vascular processes. These findings suggest that specific miRNAs could serve as predictive biomarkers for CVAE and provide insights into the underlying mechanisms of CFZ-CVAE. Further investigation is warranted before these findings can be applied in clinical settings. Full article

Chimeric antigen receptor T-cell (CAR-T) therapy is a novel anticancer therapy using autologous or allogeneic T-cells. To date, six CAR-T therapies for specific B-cell acute lymphoblastic leukemia (B-ALL), non-Hodgkin lymphomas (NHL), and multiple myeloma (MM) have been approved by the Food and Drug Administration (FDA). Significant barriers to the effectiveness of CAR-T therapy include cytokine release syndrome (CRS), neurotoxicity in the case of Allogeneic Stem Cell Transplantation (Allo-SCT) graft-versus-host-disease (GVHD), antigen escape, modest antitumor activity, restricted trafficking, limited persistence, the immunosuppressive microenvironment, and senescence and exhaustion of CAR-Ts. Furthermore, cancer drug resistance remains a major problem in clinical practice. CAR-T therapy, in combination with checkpoint blockades and bispecific T-cell engagers (BiTEs) or other drugs, appears to be an appealing anticancer strategy. Many of these agents have shown impressive results, combining efficacy with tolerability. Biomarkers like extracellular vesicles (EVs), cell-free DNA (cfDNA), circulating tumor (ctDNA) and miRNAs may play an important role in toxicity, relapse assessment, and efficacy prediction, and can be implicated in clinical applications of CAR-T therapy and in establishing safe and efficacious personalized medicine. However, further research is required to fully comprehend the particular side effects of immunomodulation, to ascertain the best order and combination of this medication with conventional chemotherapy and targeted therapies, and to find reliable predictive biomarkers. Full article

The majority of the well-known pharmacogenomics research used in the medical sciences contributes to our understanding of medication interactions. It has a significant impact on treatment and drug development. The broad use of pharmacogenomics is required for the progress of therapy. The main focus is on how genes and an intricate gene system affect the body’s reaction to medications. Novel biomarkers that help identify a patient group that is more or less likely to respond to a certain medication have been discovered as a result of recent developments in the field of clinical therapeutics. It aims to improve customized therapy by giving the appropriate drug at the right dose at the right time and making sure that the right prescriptions are issued. A combination of genetic, environmental, and patient variables that impact the pharmacokinetics and/or pharmacodynamics of medications results in interindividual variance in drug response. Drug development, illness susceptibility, and treatment efficacy are all impacted by pharmacogenomics. The purpose of this work is to give a review that might serve as a foundation for the creation of new pharmacogenomics applications, techniques, or strategies. Full article

Pancreatic cancer (PC) is an increasing cause of cancer-related death, with a dismal prognosis caused by its aggressive biology, the lack of clinical symptoms in the early phases of the disease, and the inefficacy of treatments. PC is characterized by a complex tumor microenvironment. The interaction of its cellular components plays a crucial role in tumor development and progression, contributing to the alteration of metabolism and cellular hyperproliferation, as well as to metastatic evolution and abnormal tumor-associated immunity. Furthermore, in response to intrinsic oncogenic alterations and the influence of the tumor microenvironment, cancer cells undergo a complex oncogene-directed metabolic reprogramming that includes changes in glucose utilization, lipid and amino acid metabolism, redox balance, and activation of recycling and scavenging pathways. The advent of omics sciences is revolutionizing the comprehension of the pathogenetic conundrum of pancreatic carcinogenesis. In particular, metabolomics and genomics has led to a more precise classification of PC into subtypes that show different biological behaviors and responses to treatments. The identification of molecular targets through the pharmacogenomic approach may help to personalize treatments. Novel specific biomarkers have been discovered using proteomics and metabolomics analyses. Radiomics allows for an earlier diagnosis through the computational analysis of imaging. However, the complexity, high expertise required, and costs of the omics approach are the main limitations for its use in clinical practice at present. In addition, the studies of extracellular vesicles (EVs), the use of organoids, the understanding of host–microbiota interactions, and more recently the advent of artificial intelligence are helping to make further steps towards precision and personalized medicine. This present review summarizes the main evidence for the application of omics sciences to the study of PC and the identification of future perspectives. Full article

Pre-treatment genotyping of four well-characterized toxicity risk-variants in the dihydropyrimidine dehydrogenase gene (DPYD) has been widely implemented in Europe to prevent serious adverse effects in cancer patients treated with fluoropyrimidines. Current genotyping practices are largely limited to selected commonly studied variants and are unable to determine phasing when more than one variant allele is detected. Recent evidence indicates that common DPYD variants modulate the functional impact of deleterious variants in a phase-dependent manner, where a cis- or a trans-configuration translates into different toxicity risks and dosing recommendations. DPYD is a large gene with 23 exons spanning nearly a mega-base of DNA, making it a challenging candidate for full-gene sequencing in the diagnostic setting. Herein, we present a time- and cost-efficient long-read sequencing approach for capturing the complete coding region of DPYD. We demonstrate that this method can reliably produce phased genotypes, overcoming a major limitation with current methods. This method was validated using 21 subjects, including two cancer patients, each of whom carried multiple DPYD variants. Genotype assignments showed complete concordance with conventional approaches. Furthermore, we demonstrate that the method is robust to technical challenges inherent in long-range sequencing of PCR products, including reference alignment bias and PCR chimerism. Full article

Pharmacogenomics (PGx) is the hope for the full optimization of drug therapy while minimizing the accompanying adverse drug events that cost billions of dollars annually. Since years before the century, it has been known that inter-individual variations contribute to differences in specific drug responses. It is the bridge to what is well-known today as “personalized medicine”. Addressing the drug’s pharmacokinetics and pharmacodynamics is one of the features of this science, owing to patient characteristics that vary on so many occasions. Mainly in the liver parenchymal cells, intricate interactions between the drug molecules and enzymes family of so-called “Cytochrome P450” occur which hugely affects how the body will react to the drug in terms of metabolism, efficacy, and safety. Single nucleotide polymorphisms, once validated for a transparent and credible clinical utility, can be used to guide and ensure the succession of the pharmacotherapy plan. Novel tools of pharmacoeconomics science are utilized extensively to assess cost-effective pharmacogenes preceding the translation to the bedside. Drug development and discovery incorporate a drug-gene perspective and save more resources. Regulations and laws shaping the clinical PGx practice can be misconceived; however, these pre-/post approval processes ensure the product’s safety and efficacy. National and international regulatory agencies seek guidance on maintaining conduct in PGx practice. In this patient-centric era, social and legal considerations manifest in a way that makes them unavoidable, involving patients and other stakeholders in a deliberate journey toward utmost patient well-being. In this comprehensive review, we contemporarily addressed the scientific leaps in PGx, along with various challenges that face the proper implementation of personalized medicine in Egypt. These informative insights were drawn to serve what the Egyptian population, in particular, would benefit from in terms of knowledge and know-how while maintaining the latest global trends. Moreover, this review is the first to discuss various modalities and challenges faced in Egypt regarding PGx, which we believe could be used as a pilot piece of literature for future studies locally, regionally, and internationally. Full article

Predictive tools provide a unique opportunity to explain the observed differences in outcome between patients of the COVID-19 pandemic. The aim of this study was to associate individual demographic and clinical characteristics with disease severity in COVID-19 patients and to highlight the importance of machine learning (ML) in disease prognosis. The study enrolled 344 unvaccinated patients with confirmed SARS-CoV-2 infection. Data collected by integrating questionnaires and medical records were imported into various classification machine learning algorithms, and the algorithm and the hyperparameters with the greatest predictive ability were selected for use in a disease outcome prediction web tool. Of 111 independent features, age, sex, hypertension, obesity, and cancer comorbidity were found to be associated with severe COVID-19. Our prognostic tool can contribute to a successful therapeutic approach via personalized treatment. Although at the present time vaccination is not considered mandatory, this algorithm could encourage vulnerable groups to be vaccinated. Full article