Background and Aims: Many women reported experiencing abnormalities in their cycle after being vaccinated with Covid‐19 vaccination. To understand this issue further, our study aimed to evaluate the menstrual cycle patterns among women of childbearing age after receiving COVID‐19 vaccinations.Methods: A cross‐sectional study was conducted to investigate the impact of COVID‐19 vaccine on women aged 18 years and above in Saudi Arabia. A self‐administered online questionnaire was distributed among participants who had received at least one dose of COVID‐19 vaccine. The questionnaire included questions about the participants' demographic characteristics, medical history, and vaccine‐related adverse events.Results: The study included 383 female participants with an average age of 30.8 ± 8.1 years. The majority of participants, 92.7%, were Saudi, and more than half, 51.4%, were single. Of the participants, 78.9% were disease‐free, and a majority of 67.9% had no history of Coronavirus Disease 2019 infection. A significant proportion of participants reported postvaccination changes in the menstrual cycle. Specifically, 43.1% reported changes after the first dose, and 38.4% reported changes after the second dose (p = 0.044). The severity of premenstrual symptoms increased from 44 (11.5%) to 113 (29.5%) after the first dose. Reported pain on the (WONG‐BAKER) scale was also significantly elevated from 34 (8.9%) to 87 (22.7%) (p < 0.001) after the first dose.Conclusion: A relatively high prevalence of menstrual cycle irregularities was reported by Saudi vaccinated women, particularly young adults. These findings suggest the need to further research and explore the underlying causes of these irregularities and develop interventions that may help mitigate their impact on women's health. It is also recommended that women who observe long‐term changes in their menstrual cycles seek follow‐up and consultation with healthcare providers to ensure that any potential health concerns are addressed promptly.

Every two minutes, a woman dies from cervical cancer, which is considered the fourth most common cancer among women worldwide. The dynamic interplay between tumor inflammation, immune crosstalk, oncogenes, and tumor suppressor genes plays a crucial role in tumor development and progression. Using clinical and integrated bioinformatics, the mRNA expression pattern of 168 immune and tumor-related genes in the tumor microenvironment (TME) of HPV-positive cervical squamous cell carcinoma (CSCC) was analyzed. The study identified 94 DEGs, of which 55 genes were remarkably upregulated, including CASP8, ZHX2, BCL2L1, CTNNB1, RB1, BAX, CD274, CCL20, FOXP3, and CCL18. The top three-fold changes were associated with CASP8, ZHX2, and BCL2L1, respectively. In contrast, downregulation was discovered for 39 genes associated with immunity, regulation of cell cycle, and DNA damage response (HRAS, CCND1, ATM, CXCR1, and MIF). Gene-gene interaction and correlation analysis showed positive correlations, including RB1 and CASP8, RB1 and BCL2L1, and CCL20 with CCL18. Notably, six genes exhibited increased expression and showed a strong correlation with enhanced overall survival (OS) and disease-free survival (DFS), indicating their potential utility as prognostic biomarkers. Upregulated genes were positively associated with various immune cells, including B cells, CD8+ and CD4+ T cells, macrophages, neutrophils, and dendritic cells. Functional enrichment analysis revealed involvement in cancer-related processes, inflammatory responses, and cell migration, with key pathways linked to cytokine signaling and chemokine receptor interactions. Through the integration of clinical, experimental, and computational analyses, potential therapeutic targets and prognostic biomarkers were identified that may help improve clinical outcomes. Future studies should focus on the functional assays of identified genes both in vitro and in vivo.

Background: The coronavirus 2019 (COVID-19) disease, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus led to a global pandemic. HCQ and FPV were used early in the pandemic as a treatment modality for COVID-19. Various studies evaluated the HCQ and FPV effectiveness, based on the mortality endpoint and showed conflicting results. We hypothesize that analyzing the difference in the LOS as a significant endpoint would be of a major interest, especially for healthcare providers, to prevent a lengthy hospitalization and disease progression. Methods: This is a retrospective observational study, conducted via a medical chart review of COVD-19 patients who were admitted between April 2020 and March 2021 with a moderate to severe illness. The LOS endpoint was tested using the paired Wilcoxon signed-rank (WSR) model. Prior to using the WSR model, the balance between the HCQ and FPV groups, the propensity score matching, the LOS distribution, and the normality assumptions were tested. Two sensitivity statistical analyses were conducted to confirm the results (stratified log-rank test and U Welch test after transforming the LOS by the squared root values). Results: A total of 200 patients were included for the analysis: 83 patients in the HCQ group and 117 patients in the FPV group. Thirty-seven patients were matched in each group. The LOS data was positively skewed and violated the normality (Shapiro–Wilk p < 0.001) and had an unequal variance (Levene’s test, p = 0.019). The WSR test showed no statistical significance in the LOS endpoint, with a median of −0.75 days (95% confidence interval: −4.0 to 2.5, p = 0.629), in favor of the HCQ group (four days), in comparison to seven days of the FPV group. The WSR findings were further confirmed with the stratified log rank test (p = 740) and the U Welch test (p = 391). Conclusions: The study concluded that the HCQ and FPV treatments have a comparable effectiveness in terms of the LOS in the moderate to severe COVID-19 patients. This study highlights the importance of analyzing the LOS as a relevant endpoint, in order to prevent the costs of a lengthy hospitalization and disease progression. The current study also emphasizes the importance of applying the appropriate statistical testing when dealing with two-sample paired data and analyzing non-parametric data such as the LOS.