Ahmad Riyad Alsayed

Cancer remains one of the leading causes of morbidity and mortality worldwide, necessitating continuous advances in therapeutic strategies to improve treatment efficacy and patient outcomes. Over recent decades, cancer management has evolved from conventional cytotoxic approaches toward more sophisticated, individualized interventions that target specific molecular alterations and harness the immune system. This review provides a comprehensive overview of the paradigm shift in cancer treatment, tracing the evolution from conventional chemotherapy to modern precision oncology and immunotherapy. We examine traditional diagnostic staging and highlight the integration of liquid biopsies and advanced biosensor technologies for real-time, non-invasive clinical monitoring. The review explores the mechanistic pillars of cell cycle-specific and non-specific chemotherapeutic agents, alongside the complex multidrug resistance pathways and metabolic rewiring that drive chemoresistance. We also evaluate the growing efficacy of targeted treatments, including small-molecule kinase inhibitors and antibody-drug conjugates, and detail the transformative clinical impact of immune checkpoint inhibitors, CAR-T cell therapies, and therapeutic vaccines. Emphasizing personalized medicine, we discuss the critical role of pharmacogenomics, biomarker-guided therapies, and the integration of artificial intelligence and quantitative systems pharmacology in optimizing dosing. Finally, we address future directions, including CRISPR-engineered cellular therapies and the modulation of the hypoxic tumor microenvironment using natural phytochemicals.

Cancer is a widespread disease and a leading cause of death worldwide. This has increased interest in foods that contribute to lowering its incidence. Olive oil is a key component of the Mediterranean diet and contains numerous bioactive compounds, including oleuropein, hydroxytyrosol, oleocanthal, squalene, sterols, tyrosol, and oleacein, which possess various properties and benefits. This review examines the potential of these compounds as anticancer agents and their ability to manage various types of cancer. Chemical structure, mechanisms of action, and potential to work in combination with conventional treatments were discussed for each compound. Studies discussed in this review show promising anticancer effects of olive oil compounds with high potential to augment conventional treatments through the anticipated anticancer effect of the Mediterranean diet with olive oil. This review focused on in vitro and preclinical studies of using olive oil phytochemicals in cancer research. However, further clinical and experimental studies are needed to determine the optimal dosage of olive oil and better confirm its therapeutic efficacy.

The tumor microenvironment (TME) has now become a fundamental concept in oncology research, as it changes the traditional viewpoint of tumors as an autonomously functioning assembly of cancer cells. In this review, we evaluate recent advances in the understanding of the bidirectional crosstalk between the malignant cells and the neighboring, but non-malignant, stromal/immune cells. The roles of stromal cell subsets – mesenchymal stem cells, endothelial cells, and cancer-associated fibroblasts – as well as immunosuppressive immune cell populations, such as regulatory T cells, tumor-associated macrophages, and myeloid-derived suppressor cells, are considered. Furthermore, the mechanisms underlying the interactions of tumor-derived molecules, metabolic modifications, and exosome signaling with extracellular matrix (ECM) and tumor immune modulation that enable tumor evasion, angiogenesis, and pre-metastasis niche formation are discussed. As a result, we discuss the current state of several therapeutic possibilities, including vascular normalization, ECM disruption, metabolic targeting, and sophisticated nanotechnology-based drug delivery platforms. This review provides evidence that, in order to counteract TME-driven tumor progression, it is vital to develop combinatorial treatments targeting multiple aspects of microenvironmental networks, which form a necessary basis.

Geriatric pharmacotherapy is usually challenged by physiological senescence. For instance, progressive declines in organ function and alterations in body composition can complicate drug disposition. However, conventional pharmacometrics models commonly have limited capacity to map these high-dimensional, nonlinear relationships. In this review, we are examining the recent shift toward integrating machine learning (ML) with mechanistic pharmacokinetic (PK)/pharmacodynamic (PD) models to improve the accuracy and precision of dosing. Machine learning approaches like Random Forest and XGBoost consistently provided more accurate exposure predictions and significantly more efficient computational workflows than conventional methods. Nevertheless, concerns such as “black box” transparency and the potential of algorithmic bias toward specific patient demographics are challenging. It is important to incorporate explainability tools like SHAP, and adopting FAIR data principles is crucial for achieving professional trust and ensuring site-specific generalizability.

Geriatric pharmacotherapy is usually challenged by physiological senescence. For instance, progressive declines in organ function and alterations in body composition can complicate drug disposition. However, conventional pharmacometrics models commonly have limited capacity to map these high-dimensional, non-linear relationships. In this review, we are examining the recent shift toward integrating Machine Learning (ML) with mechanistic Pharmacokinetic (PK)/Pharmacodynamic (PD) models to improve the accuracy and precision of dosing. Machine learning approaches like Random Forest and XGBoost consistently provided more accurate exposure predictions and significantly more efficient computational workflows than conventional methods. Nevertheless, concerns such as "black box" transparency and the potential of algorithmic bias toward specific patient demographics are challenging. It is important to incorporate explainability tools like SHAP, and adopting FAIR data principles is crucial for achieving professional trust and ensuring site-specific generalizability.

Purpose: Pneumonia is still a leading cause of morbidity and death globally, with a significant percentage of cases having an unknown aetiology, and management becoming more difficult due to growing antimicrobial resistance (AMR). This study assessed clinical outcomes, antimicrobial susceptibility patterns, and pathogen detection using both conventional and molecular techniques in hospitalized pneumonia patients in Jordan. Patients and Methods: 111 adults (≥ 18 years) who were admitted to a tertiary private hospital in Amman between May 2021 and January 2022 with either hospital-acquired (HAP) or community-acquired pneumonia (CAP) were included in this prospective study. Multiplex real-time PCR and conventional culture were performed on lower respiratory tract samples (FTD Respiratory Pathogens 33). Data on outcomes, microbiology, antimicrobial susceptibility, clinical, and demographics were gathered. McNemar’s test was used to compare diagnostic performance, and logistic regression and chi-square analyses were used to evaluate the relationships between outcomes and adherence to guidelines. Results: The average age was 64.0± 20.6 years, and 58.6% of the population was male. 78.4% of cases were CAP. PCR detected pathogens in 74.8% of patients, whereas culture detected them in 57.7% (p< 0.001). PCR showed a higher false-positive rate but a significantly higher sensitivity than culture (96.9% vs 86.3%, p=0.039). In 36.9% of cases, bacterial–viral co-infections were found. The overall death rate was 27.0%. Although not an independent predictor in logistic regression, non-guideline-concordant antibiotic therapy was substantially associated with mortality (p=0.023). High ampicillin resistance and notable trends in resistance to specific broad-spectrum agents were among the notable variations in AMR patterns observed. Conclusion: Multiplex PCR reveals complex co-infection patterns in pneumonia and greatly enhances pathogen detection when compared to culture. Antimicrobial stewardship initiatives that incorporate molecular diagnostics may improve targeted treatment. To address changing AMR patterns in Jordan, national guidelines that include molecular testing are necessary.

In parametric statistical analysis, the independent-samples t-test is a widely used method for comparing the means of two different groups. Under the assumption of homogeneity of variances and normally distributed data, it evaluates the statistical significance of observed differences between group means. The fundamental ideas of the independent-samples t-test—including its assumptions, hypotheses, effect size considerations, and methodological applications in research—are investigated in this review. Furthermore, fundamental methodological issues, including the interpretation of statistical significance, are covered. Aiming to increase researchers' competency in using and interpreting the independent-samples t-test across studies, this paper provides a thorough tutorial on the test. In addition, this review highlights JASP (Jeffrey’s Amazing Statistics Program), an open-source statistical platform with an interface for conducting independent-samples t-tests. JASP provides automated assumption checks, effect size calculations, and graphical outputs, making it accessible for researchers with varying levels of statistical expertise.

Descriptive statistics are a cluster of statistical techniques used to summarise, organise, and communicate general features of data already gathered. JASP (Jeffrey’s Amazing Statistics Program) is an open-source, cross-platform software package designed to make statistical analyses accessible, transparent, and reproducible. JASP integrates both frequentist and Bayesian methods within an intuitive interface that emphasises ease of use and high-quality output in the APA format. Unlike traditional statistical software, JASP reduces the technical burden of analysis through drag-and-drop functionality, automated data handling, and direct export options for results, figures and syntax. Its integrated data library and educational resources render it especially advantageous for students, while its sophisticated features, such as regression, factor analysis, and Bayesian modelling, provide robust tools for researchers. This review offers a comprehensive overview of the JASP environment, encompassing file management, data handling, analysis menus, and visualisation tools. Furthermore, it emphasises fundamental statistical principles, including measures of central tendency, dispersion, and data integrity. Researchers can learn data behaviour and enhance their skills using this tutorial, without needing extensive statistical programming knowledge.

Introduction: Hypoxia mediates cancer hallmarks and results from low oxygen levels due to irregularities in tumor vascularization or when the bulk of the tumor prevents oxygen diffusion and stimulates angiogenesis to compensate for low oxygen. Aims: This study aims to identify significant biomarkers associated with tumor hypoxia, focusing on prolonged exposure to hypoxic conditions. Methods: The breast cancer cells (MCF7) were exposed to 8-hour hypoxic episodes (1% oxygen) three times per week for 60 episodes and once weekly for 72 hours for a maximum of 12 episodes. After 60 and 12 episodes of hypoxia, changes in gene expression were profiled using a hypoxia RT- PCR array and compared to normoxic cells. An assay was performed after 60 and 12 episodes of hypoxia to determine the effect of hypoxia on angiogenesis migration. Results: The expression of the Hepatocyte Nuclear Factor 4 gene increased by 32.71-fold following exposure to 12 hypoxic injections and by an additional 14.95-fold following exposure to 60 hypoxic injections. After twelve episodes of hypoxia, the capacity for cell migration increased. Conclusions: This study provides empirical support for the notion that cellular exposure to prolonged durations of hypoxia, specifically three months, induces expression changes distinct from those induced by fleeting durations of hypoxia, which are less than weeks and hours. The study hypothesized that HNF4A could serve as a viable biomarker for tumor hypoxia and a major contributor to the response of MCF7 breast cancer cells to protracted hypoxic conditions.

Objective To investigate the differences in gut microbiota composition between healthy individuals and those with inflammatory bowel disease (IBD) in Jordan and to understand how these differences may contribute to the pathogenesis of IBD. Methods This study involved the comprehensive analysis of 20 gut microbiota samples from diverse populations in Jordan. Using 16S rRNA sequencing, the gut microbiome composition of healthy individuals was compared to that of individuals with IBD. The analysis focused on microbial diversity and the relative abundance of specific bacterial taxa. Results The study revealed significant disparities in the gut microbiota composition between healthy individuals and those with IBD. IBD patients exhibited reduced microbial diversity. There was a notable decrease in the abundance of beneficial taxa such as Firmicutes and Bacteroidetes, specifically the families Erysipelotrichaceae, Ruminococcaceae, and Lachnospiraceae. IBD patients showed elevated levels of potentially harmful bacteria, particularly the Proteobacteria phylum. Three bacterial classes, Pseudomonas, Clostridia, and Escherichia, were significantly increased in IBD patients. Beneficial genera such as Faecalibacterium prausnitzii, Bifidobacterium, Blautia, Coprococcus, and Bacteroides dorei were more prominent in healthy controls, highlighting their roles in maintaining gut health and anti-inflammatory properties. Conclusion The findings underscore a significant association between gut microbiota dysbiosis and IBD. IBD patients in Jordan exhibited lower microbial diversity and an imbalance favoring harmful bacterial taxa. These insights into the gut microbiota composition offer a valuable understanding of IBD pathogenesis and suggest that therapeutic strategies targeting the gut microbiome could be promising for managing the disease. Further research into the interplay between gut microbiota and the immune system is essential for developing novel IBD treatments.