Aisha Naeem

Obesity is a well-established risk factor for multiple cancers, and Metabolic Bariatric Surgery (MBS) has been associated with reduced cancer incidence and mortality. However, the molecular mechanisms underlying this risk reduction remain incompletely understood. Many recent transcriptomic, proteomic, and metabolomic studies have enabled system-wide molecular profiling following MBS. We performed a systematic analysis of publicly available MBS-related omics datasets, including transcriptomic ( n = 22), proteomic ( n = 6), and metabolomic studies ( n = 5), with pre- and post-operative comparisons. Comparative molecular analyses across all omics datasets were performed using Ingenuity Pathway Analysis (IPA). Sustained suppression of key oncogenic pathways, including Molecular Mechanisms of Cancer, Role of Tissue Factor in Cancer, and metastasis-associated signaling, was observed in tissue transcriptomic datasets (adipose, skeletal muscle, and gastrointestinal tract). In contrast, transcriptomic datasets predominantly showed immune remodeling, characterized by activation of innate immune pathways. Key molecular markers, including CCL2 , EGFL6 , and S100A8, were identified as consistently regulated across multiple datasets. Proteomic analyses revealed early postoperative suppression of inflammatory and acute-phase proteins, progressive downregulation of complement and coagulation cascades, and sustained upregulation of endocrine regulators such as sex hormone-binding globulin and extracellular matrix–stabilizing factors. Metabolomic profiling demonstrated significant alterations in amino acid, bile acid, and lipid metabolism following MBS. These molecular changes collectively reflect a shift toward a less inflammatory, hormonally balanced, and metabolically favorable systemic environment. These findings highlight the impact of MBS in inhibiting cancer-promoting biological processes and identify candidate molecular biomarkers for future translational and oncologic research.

Background: Bariatric surgery improves metabolic health, but long-term transcriptomic remodeling of white adipose tissue (WAT) after Roux-en-Y gastric bypass (RYGB) remains incompletely defined. This study aimed to characterize longitudinal WAT gene-expression patterns after RYGB and prioritize candidate signatures of post-surgical adaptation using a publicly available dataset. Methods: We analyzed subcutaneous WAT transcriptomic data from women with obesity who underwent RYGB, with samples collected before surgery and at 2 and 5 years after surgery. Differential expression analysis was integrated with pathway enrichment, supervised machine-learning-based feature prioritization and classification, and SHAP-based model interpretation. Results: Differential expression and machine-learning analyses showed clear separation between baseline and post-surgery transcriptomic states. Pathway-level findings indicated reduced inflammatory and immune-related signaling, particularly across pathways related to phagosome function, lysosomal activity, antigen presentation, and host-defense responses after surgery. Gene-level analyses additionally suggested extracellular-matrix and metabolic remodeling. Machine-learning models distinguished baseline from post-surgery samples, while SHAP analysis identified genes with the strongest contributions to model predictions. Importantly, several statistically prioritized genes also showed high SHAP attribution, demonstrating concordance between univariate statistical significance and multivariate predictive relevance. This convergence suggests that the models captured biologically meaningful surgery-associated signals rather than purely data-driven classification artifacts. Conclusions: This study advances the interpretation of longitudinal adipose-tissue transcriptomic remodeling after RYGB by combining differential expression, pathway enrichment, supervised machine learning, and explainable AI within a unified framework. The integrated workflow prioritized candidate long-term remodeling genes, particularly immune/inflammatory and extracellular-matrix-related transcriptomic signatures, that warrant validation in independent cohorts.

Ruthenocene (Rc) and its derivatives form a structurally versatile class of metallocenes with unique and multifunctional applicability. This review presents a detailed analysis of Rc chemistry including the structural comparison with ferrocene, its redox behavior, and substituent effects. We also discuss its applications in sensing, energy storage, photochemistry, and biomedicine. Rc exhibits unique conformational and adaptive electronic properties based on one and two-electron oxidation processes. Electrochemical investigations of Rc to date indicate that its redox behavior is strongly dependent on the electrolyte system, exhibiting quasi-Nernstian characteristics, the formation of stabilized dimeric species [Rc₂]²⁺, and interconversion among Ru(II), Ru(III), and Ru(IV) oxidation states. Rc-based systems exhibit superior performance as redox mediators and labels in electrochemical sensing systems in terms of electron-transfer kinetics, signal amplification, and surface immobilization. In the field of energy storage, Rc decreases the charging overpotential and increases the cycle life of Li-O₂ batteries. Rc further acts as a photoinitiator via charge-transfer-to-solvent and efficient photoinduced electron transfer in metalloporphyrin and fullerene dyads. In biomedical research, Rc derivatives as well as bioconjugates possess promising anticancer activities, displaying reactive oxygen species generation, topoisomerase inhibition, thioredoxin reductase inhibition, receptor-mediated uptake, and target peptide conjugation. Given its flexible ligand design, electrolyte driven redox behaviors, and antiproliferative properties, Rc exhibits a very adaptive molecular scaffold for next generation electrochemical technologies as well as metallodrug design.

Paratuberculosis is a chronic zoonotic bacterial infection, primarily affecting ruminants. This review examines the disease in the Arabian Peninsula, focusing on distribution, molecular diversity, prevalence, and associated risk factors. Following PRISMA guidelines, a systematic search was conducted in PubMed, Scopus, and Web of Science. After duplicate removal and eligibility screening, data extraction, analysis, and quality assessment were performed. Pathogen sequences were retrieved from NCBI GenBank for phylogenetic analysis. The review included a total of 31 published articles from 1997 to 2025, of which 26 were used in the meta-analysis. Most studies (n = 12) were published between 2011 and 2015, predominantly from Saudi Arabia (n = 22), with no reports from Qatar, Bahrain, or Yemen. The majority of the studies involved camels and sheep (n = 16 on each species), followed by cattle (n = 9), goats (n = 7), humans (n = 2), and buffalo (n = 1). Phylogenetic analysis delineates two major clades—Type S and Type C—suggesting greater genetic diversity in Type S. The estimated pooled seroprevalence and pathogen prevalence in livestock ruminants were 8.1% and 22.4%, respectively. Herd-level estimated pooled seroprevalence was 26.9%. Small ruminants (19.3%) were more sero-prevalent than large ruminants (7.4%), with goats (28.7%) significantly (p < 0.01) more affected than sheep (21.5%), camel (9.8%), and cattle (6.6%). Clinical signs in ruminants included chronic diarrhea, emaciation, anorexia, alopecia, wry neck, and dehydration. The reviewed study patterns and findings suggest high pathogen diversity and a significant risk of transboundary transmission at the human–animal interface in this region. A One Health surveillance approach is crucial, particularly on farms with diarrheic and emaciated animals. Establishing a national surveillance plan and phased (short-, intermediate-, and long-term) control programs is essential to mitigate economic losses, limit transmission, overcome the cultural barrier, and protect public health.

Colorectal cancer (CRC) remains a significant global health concern, and reliable biomarkers are needed to improve early diagnosis, prognostication, and personalized treatment strategies. This study investigated the expression of cell surface proteins and serum exosomal miRNAs in CRC patients. Tissue microarrays (TMAs) constructed from primary and metastatic CRC samples were analyzed for five cell surface proteins: EphB1, EphB3, EphA2, cMet, and EphB4. Immunohistochemistry was performed on the TMAs to validate their expression levels. We found that the distribution of expression for all four receptors, except EphA2, was significantly higher (p < 0.01) in CRC samples compared to non-cancerous tissue. High expression of EphB3 was detected in 37% of patient samples, followed by cMet, which was observed in 35%. Exosomes were isolated from the serum of three CRC patients with tumors exhibiting high expression of LGR5 and/or EphB3, four healthy donors and two CRC cell lines. Serum exosomal miRNA analysis identified miR-3168 as significantly upregulated in CRC patients, showing a 3.8-fold increase compared to healthy controls (p < 0.001) and a 2.6-fold increase in CRC cell lines compared to controls (p = 0.02). Ingenuity Pathway Analysis (IPA) suggested that miR-3168 may regulate cMet, EphB3, and EphB4, along with other CRC-associated molecules and pathways. These findings highlight the potential of EphB3 and cMet as biomarkers in CRC, and miR-3168 as a promising minimally-invasive biomarker for monitoring disease progression and therapeutic response. However, further validation in larger cohorts is needed to establish their clinical utility.

Cancer remains a major global health challenge, consistently ranking as the second leading cause of mortality worldwide. Despite significant advancements in research and technology, the need to deepen our understanding of tumor biology and improve therapeutic strategies persists. This review focuses on the progress and challenges of four traditional cancer treatment modalities: surgery, chemotherapy, radiation therapy, and hormonal therapy. Surgery, the primary method for tumor removal, has evolved with the integration of fluorescence-based technology and robotic systems, enhancing precision and minimizing collateral damage. Radiation therapy has progressed with improved focus, intensity control, and 3D technology, refining both diagnosis and treatment. Chemotherapy has advanced from natural extracts to synthesized derivatives with amplified cytotoxicity against cancer cells. Hormonal therapy has emerged as a crucial strategy for hormone-dependent cancers, restraining growth or inducing regression. Despite these advancements, each approach faces ongoing challenges. Surgery struggles with complete tumor removal due to heterogeneity. Chemotherapy contends with drug resistance and side effects. Radiation therapy grapples with precision issues and limited access in some regions. Hormonal therapy faces resistance development and quality of life impacts. This study provides a comprehensive analysis of the evolution of these traditional anti-cancer therapies, offering insights into their progress and highlighting areas for future research. By examining these modalities, we aim to underscore their relevance in the current oncology landscape and identify opportunities for improvement in cancer treatment strategies.

Anti-cancer peptides (ACPs) are short peptides known for their ability to inhibit tumor cell proliferation, migration, and the formation of tumor blood vessels. In this study, we designed ACPs to target receptors often overexpressed in cancer using a systematic in silico approach. Three target receptors (CXCR1, DcR3, and OPG) were selected for their significant roles in cancer pathogenesis and tumor cell proliferation. Our peptide design strategy involved identifying interacting residues (IR) of these receptors, with their natural ligands serving as a reference for designing peptides specific to each receptor. The natural ligands of these receptors, including IL8 for CXCR1, TL1A for DcR3, and RANKL for OPG, were identified from the literature. Using the identified interacting residues (IR), we generated a peptide library through simple permutation and predicted the structure of each peptide. All peptides were analyzed using the web-based prediction server for Anticancer peptides, AntiCP. Docking simulations were then conducted to analyze the binding efficiencies of peptides with their respective target receptors, using VEGA ZZ and Chimera for interaction analysis. Our analysis identified HPKFIKELR as the interacting residues (IR) of CXCR-IL8. For DcR3, we utilized three domains from TL1A (TDSYPEP, TKEDKTF, LGLAFTK) as templates, along with two regions (SIKIPSS and PDQDATYP) from RANKL, to generate a library of peptide analogs. Subsequently, peptides for each receptor were shortlisted based on their predicted anticancer properties as determined by AntiCP and were subjected to docking analysis. After docking, peptides that exhibited the least binding energy were further analyzed for their detailed interaction with their respective receptors. Among these, peptides C9 (HPKFELY) and C7 (HPKFEWL) for CXCR1, peptides D6 (ADSYPQP) and D18 (AFSYPFP) for DcR3, and peptides P19 (PDTYPQDP) and p16 (PDQDATYP) for OPG, demonstrated the highest affinity and stronger interactions compared to the other peptides. Although in silico predictions indicated a favorable binding affinity of the designed peptides with target receptors, further experimental validation is essential to confirm their binding affinity, stability and pharmacokinetic characteristics.

Despite the availability of technological advances in traditional anti-cancer therapies, there is a need for more precise and targeted cancer treatment strategies. The wide-ranging shortfalls of conventional anticancer therapies such as systematic toxicity, compromised life quality, and limited to severe side effects are major areas of concern of conventional cancer treatment approaches. Owing to the expansion of knowledge and technological advancements in the field of cancer biology, more innovative and safe anti-cancerous approaches such as immune therapy, gene therapy and targeted therapy are rapidly evolving with the aim to address the limitations of conventional therapies. The concept of immunotherapy began with the capability of coley toxins to stimulate toll-like receptors of immune cells to provoke an immune response against cancers. With an in-depth understating of the molecular mechanisms of carcinogenesis and their relationship to disease prognosis, molecular targeted therapy approaches, that inhibit or stimulate specific cancer-promoting or cancer-inhibitory molecules respectively, have offered promising outcomes. In this review, we evaluate the achievement and challenges of these technically advanced therapies with the aim of presenting the overall progress and perspective of each approach.

Electrochemical biosensing has evolved as a diverse and potent method for detecting and analyzing biological entities ranging from tiny molecules to large macromolecules. Electrochemical biosensors are a desirable option in a variety of industries, including healthcare, environmental monitoring, and food safety, due to significant advancements in sensitivity, selectivity, and portability brought about by the integration of electrochemical techniques with nanomaterials, bio-recognition components, and microfluidics. In this review, we discussed the realm of electrochemical sensors, investigating and contrasting the diverse strategies that have been harnessed to push the boundaries of the limit of detection and achieve miniaturization. Furthermore, we assessed distinct electrochemical sensing methods employed in detection such as potentiometers, amperometers, conductometers, colorimeters, transistors, and electrical impedance spectroscopy to gauge their performance in various contexts. This article offers a panoramic view of strategies aimed at augmenting the limit of detection (LOD) of electrochemical sensors. The role of nanomaterials in shaping the capabilities of these sensors is examined in detail, accompanied by insights into the chemical modifications that enhance their functionality. Furthermore, our work not only offers a comprehensive strategic framework but also delineates the advanced methodologies employed in the development of electrochemical biosensors. This equips researchers with the knowledge required to develop more accurate and efficient detection technologies.

Murine double minute 2 (MDM2) is a well-recognized molecule for its oncogenic potential. Since its identification, various cancer-promoting roles of MDM2 such as growth stimulation, sustained angiogenesis, metabolic reprogramming, apoptosis evasion, metastasis, and immunosuppression have been established. Alterations in the expression levels of MDM2 occur in multiple types of cancers resulting in uncontrolled proliferation. The cellular processes are modulated by MDM2 through transcription, post-translational modifications, protein degradation, binding to cofactors, and subcellular localization. In this review, we discuss the precise role of deregulated MDM2 levels in modulating cellular functions to promote cancer growth. Moreover, we also briefly discuss the role of MDM2 in inducing resistance against anti-cancerous therapies thus limiting the benefits of cancerous treatment.