Background: The COVID-19 pandemic has highlighted a spectrum of long-term sequelae, with musculoskeletal symptoms being a substantial component of Post-Acute Sequelae of SARS-CoV-2 infection (PASC). This systematic review and meta-analysis aimed to evaluate the incidence and nature of musculoskeletal manifestations in individuals recovering from COVID-19.Methods: A systematic search across PubMed, Embase, and Web of Science was performed up to February 15, 2024, to identify studies reporting on musculoskeletal symptoms post-COVID-19. Observational studies which reported any musculoskeletal symptoms of PASC were included. Data were pooled using a random-effects model to calculate the incidence of symptoms, with subgroup analyses based on time since infection. Statistical analysis were conducted in R software (V 4.3).Results: Sixty-four studies were included, demonstrating a pooled prevalence of muscle pain at 28% (95% CI: 22%−35%), which increased to 25.9% (95% CI: 20.7%−31.7%) at 12 months post-infection. Joint pain showed a pooled prevalence of 14.8% (95% CI: 10.6%−20.2%), with no significant temporal change. Muscle weakness was observed in 12.9% (95% CI: 4.2%−32.9%) of patients. Notable heterogeneity was observed across studies (I² > 89% for all symptoms).Conclusion: Musculoskeletal symptoms are prevalent in individuals with PASC, with muscle pain being the most common. The findings highlight the need for comprehensive clinical management and continuous research to create targeted treatments and revise care protocols as the pandemic evolves.

Artificial intelligence (AI) is transforming drug discovery by enabling the rapid identification of existing drugs with potential anti-cancer properties, a process known as drug repurposing. This approach offers a cost-effective and time-efficient alternative to traditional drug development, particularly in oncology, where the need for novel therapies is urgent. AI-driven methods, including machine learning (ML) and deep learning (DL), analyze vast datasets to uncover hidden drug-disease relationships, predict drug efficacy, and optimize therapeutic combinations. This letter highlights the transformative potential of AI in drug repurposing for cancer therapies, supported by successful examples from recent research. We also discuss the challenges and ethical considerations of integrating AI into drug repurposing efforts, emphasizing the need for robust validation and regulatory oversight to ensure patient safety and efficacy.

Oropouche virus (OROV), a significant arbovirus transmitted by Culicoides paraensis midges, poses a growing public health threat in Latin America. Recent outbreaks in Brazil, Peru, and other Amazonian regions have increased the virus’s visibility, but significant gaps remain in understanding its transmission, pathogenesis, and management. This review aims to provide a comprehensive and critical synthesis of current knowledge on OROV, focusing on its epidemiology, clinical manifestations, diagnostic challenges, and management strategies. Despite its increasing impact, OROV remains underrecognized in the global public health landscape. Key areas for future research, including vaccine development, antiviral treatments, and vector control, are discussed. Additionally, we explore novel findings, such as the role of non-human reservoirs and the emerging potential of OROV reassortant strains.

Background: Academic performance is a critical determinant of career opportunities for medical students. This study aimed to identify the socio-demographic, institutional, and social factors associated with academic achievement among medical students across Egypt's diverse university systems. Methods: A multi-center cross-sectional study utilizing an online survey was conducted from January to May 2025, involving 751 medical students from 38 public, private, and Al-Azhar universities across Egypt. Academic performance was measured using self-reported cumulative percentage. Multivariable linear regression was used to analyze the relationships between academic performance and various predictive factors. Results: The mean cumulative percentage for the cohort was 85 (SD = 8.96). In the final multivariable model, lower academic performance was significantly associated with being male (unstandardized coefficient ( B ) = −1.77, 95% CI = −3.03, −0.52), attending an Al-Azhar university compared to a public one (B = −5.75, 95% CI = −8.23, −3.26), and living in student housing vs. with family ( B = −3.31, 95% CI = −4.68, −1.94). Conversely, higher academic performance was significantly associated with receiving parental support ( B = 2.06, 95% CI = 0.03, 4.08) and being from a medical school in the Lower Egypt region compared to Urban Governorates ( B = 1.94, 95% CI = 0.49, 3.38). Conclusion: Academic performance among Egyptian medical students is significantly influenced by a combination of institutional, demographic, and social support factors, which appear more impactful than traditional socioeconomic markers in this cohort. These findings highlight potential systemic inequities and emphasize the need for targeted educational interventions and policy review to ensure a fair and supportive learning environment for all students.

Nanorobotic technologies for cancer therapy have generated considerable excitement within the oncology community due to their potential for precision drug delivery, reduced systemic toxicity, and real-time therapeutic monitoring. DNA origami-based systems and magnetic navigation platforms demonstrate impressive preclinical capabilities, offering theoretical advantages over conventional chemotherapy through enhanced tumor targeting and reduced off-target effects. However, the pathway from bench to bedside faces substantial translational barriers that require systematic evaluation. The vast majority of current evidence remains confined to theoretical frameworks and preclinical studies, with limited clinical-grade validation and heterogeneous outcome measures across research efforts. Critical gaps include unclear regulatory pathways for complex nanorobotic systems, manufacturing scalability challenges, and incomplete safety assessment protocols for long-term biocompatibility. The absence of standardized reporting frameworks and robust comparative effectiveness research further compounds these limitations. Successful translation requires establishment of prospective patient registries, development of validated efficacy metrics, implementation of systematic reviews following established guidelines, and creation of comprehensive safety evaluation protocols. Only through rigorous, multidisciplinary collaboration between engineers, clinicians, biostatisticians, and outcomes researchers can nanorobotic oncology progress from promising preclinical results to clinically meaningful improvements in cancer patient care. The field must balance optimism with scientific rigor to fulfill its transformative potential.

Tailgut cysts (TGCs) are rare congenital lesions arising from incomplete regression of the embryonic hindgut, typically located in the presacral space and more common in females. Although often benign, these cysts carry a risk of malignant transformation. We report a case of a woman in her early 50s who presented with abdominal pain, urinary retention, and tenesmus. Initial imaging revealed a large presacral cystic lesion, and incomplete surgical excision confirmed benign histology. However, the patient returned 6 months later with recurrent symptoms and new-onset lower limb weakness. Repeat imaging showed a recurrent cystic lesion with liver and bony metastases. MRI showed peripheral nodular enhancement of the lesion and enhancing bone lesions. A liver biopsy confirmed mucinous adenocarcinoma. Despite chemotherapy, the disease progressed rapidly, and the patient passed away within 2 months. This case highlights the potential for malignant degeneration in TGCs, which, though rare, carries significant morbidity. Complete surgical resection and follow-up are critical to prevent recurrence and malignancy risk. Further research is needed to study the malignant transformation predictors of this rare entity.