FAIR-USE4OS: Guidelines for creating impactful open-source software.

This paper extends the FAIR (Findable, Accessible, Interoperable, Reusable) guidelines to provide criteria for assessing if software conforms to best practices in open source. By adding "USE" (User-Centered, Sustainable, Equitable), software development can adhere to open source best practice by incorporating user-input early on, ensuring front-end designs are accessible to all possible stakeholders, and planning long-term sustainability alongside software design. The FAIR-USE4OS guidelines will allow funders and researchers to more effectively evaluate and plan open-source software projects.

Genomic characterization of an esthesioneuroblastoma with spinal metastases: illustrative case.

Background: Esthesioneuroblastoma (ENB) is a rare neoplasm of the sinonasal tract. Currently, the optimal treatment includes maximal resection combined with radiotherapy and/or chemotherapy. Although ENBs often recur and have an aggressive clinical course, spinal metastases are extremely rare and the underlying molecular mechanisms are poorly understood.

Double inversion recovery to detect cervical spinal cord multiple sclerosis lesions.

Background And Purpose: Magnetic resonance imaging (MRI) plays a key role in diagnosing and monitoring multiple sclerosis (MS). Double inversion recovery (DIR) is a pulse sequence that has proven highly effective at detecting cortical lesions but is understudied in the spinal cord. We hypothesize that DIR images obtained during brain MRI can be of value in assessing the upper spinal cord of MS patients.

DNA methylation provides diagnostic value for meningioma recurrence in clinical practice.

Background: Meningiomas are the most common intracranial tumors. Recent advancements in the genetic profiling of tumors have allowed information including DNA copy number analysis, mutational analysis, and RNA sequencing to be more frequently reported, in turn allowing better characterization of meningiomas. In recent years, analysis of tumor methylomes that reflects both cell-origin methylation signatures and somatically acquired DNA methylation changes has been utilized to better classify meningiomas with great success.