The human papillomavirus (HPV) is a non-enveloped double-stranded DNA virus capable of infecting skin and mucosa epithelial cells. Commonly, HPV infection is associated with sexually transmitted diseases and is considered the leading cause of cervical cancer and other carcinomas of the anogenital tract. However, several studies reported their involvement in cancers of non-sexual regions, including colorectal, head and neck, and breast cancers. There are several studies from the Middle East and North Africa (MENA) regions on the potential association between high-risk HPVs and cancer; nevertheless, there are limited studies that address the significance of HPV vaccination as a potential guard against these cancers. In the current review, we present a comprehensive description of the current HPV-associated cancers prevalence rates in the MENA region, demonstrating their steady increase with time, especially in African regions. Moreover, we discuss the potential impact of vaccination against HPV infections and its outcome on human health in this region.

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.