Intra-tumoral susceptibility signals in brain gliomas: where do we stand?

Nowadays, the genetic and biomolecular profile of neoplasms-related with their biological behaviour-have become a key issue in oncology, as they influence many aspects of both diagnosis and treatment. In the neuro-oncology field, neuroradiological research has recently explored the potential of non-invasively predicting the molecular phenotype of primary brain neoplasms, particularly gliomas, based on magnetic resonance imaging (MRI), using both conventional and advanced imaging techniques. Among these, diffusion-weighted imaging (DWI), perfusion-weighted imaging (PWI), MR spectroscopy (MRS) and susceptibility-weighted imaging (SWI) and have been used to explore various aspects of glioma biology, including predicting treatment response and understanding treatment-related changes during follow-up imaging.

Education and training in hand surgery: Upper limb cadaveric dissection course improves the learning curve.

Anatomy is vital for integrating basic science with clinical practice, particularly for surgeons specializing in hand, orthopedic, and plastic surgery. Traditional teaching methods often lack the hands-on experience needed for a thorough understanding. To address this issue, the Italian Society of Hand Surgery (SICM) designed a course focused on cadaveric dissection aimed at enhancing anatomical knowledge and surgical skills.

Primary versus interval cytoreductive surgery in patients with rare epithelial or non-epithelial ovarian cancer.

Background: The standard treatment for advanced epithelial ovarian cancer is primary cytoreductive surgery, with the goal of achieving no residual disease. Neoadjuvant chemotherapy and interval cytoreductive surgery can be viable treatment options for patients with extensive disease that precludes complete tumor removal during initial surgery, or when significant comorbidities increase the surgical risk without adversely impacting overall survival rates. However, published studies mostly included patients with high-grade serous ovarian cancer, with an underrepresentation of non-high-grade serous epithelial and non-epithelial cancers.

Artificial Intelligence-Assisted Drug and Biomarker Discovery for Glioblastoma: A Scoping Review of the Literature.

: Artificial intelligence (AI) has emerged as a transformative tool in healthcare, particularly in drug and biomarker discovery, where it can enhance precision, streamline discovery processes, and optimize treatment strategies. Despite its potential, the application of AI in glioblastoma (GB) research, especially in identifying novel biomarkers and therapeutic targets, remains underexplored. The aim of this review is to map the existing literature on AI-driven approaches for biomarker and drug discovery in GB, highlighting key trends and gaps in current research.

Microbiome and pollutants in the freshwater sponges Ephydatia muelleri (Lieberkühn, 1856) and Spongilla lacustris (Linnaeus, 1758) from the sub-Arctic Pasvik river (Northern Fennoscandia).

Despite the ecosystem functions offered by sponges in freshwater habitats, fragmentary studies have targeted their microbiome and the bioaccumulation of legacy and emerging organic micropollutants, making it difficult to test hypotheses about sponge-microbe specificity and response to environmental factors and stressors. The sponge species Ephydatia muelleri and Spongilla lacustris, coexisting in two sites of the Pasvik River (northern Fennoscandia), were analyzed for persistent organic pollutant (POPs) and chemicals of emerging concern (CECs), along with quali-quantitative microbiological features. River water and sediment were similarly treated to establish if the obtained data were site- or sponge-specific.