Lateral Decubitus Dynamic CT Myelography with Real-Time Bolus Tracking (dCTM-BT) for Evaluation of CSF-Venous Fistulas: Diagnostic Yield Stratified by Brain Imaging Findings.

Background And Purpose: CSF-venous fistulas (CVFs) associated with spontaneous intracranial hypotension (SIH) may have a transient appearance, relative to contrast arrival, which may influence the diagnostic performance of lateral decubitus CT myelography (CTM). We developed a dynamic CTM protocol using real-time bolus-tracking (dCTM-BT) to improve the temporal resolution and standardize the timing of CTM acquisitions post-intrathecal contrast administration. The purpose of our study was to evaluate the feasibility of the dCTM-BT technique and evaluate its diagnostic yield for CVF detection, stratified by brain MRI SIH findings.

Eukaryotic Initiation Factor 5A2 localizes to actively translating ribosomes to promote cancer cell protrusions and invasive capacity.

Background: Eukaryotic Initiation Factor 5A (eIF-5A), an essential translation factor, is post-translationally activated by the polyamine spermidine. Two human genes encode eIF-5A, being eIF5-A1 constitutively expressed whereas eIF5-A2 is frequently found overexpressed in human tumours. The contribution of both isoforms with regard to cellular proliferation and invasion in non-small cell lung cancer remains to be characterized.

New roles for AP-1/JUNB in cell cycle control and tumorigenic cell invasion via regulation of cyclin E1 and TGF-β2.

Background: JUNB transcription factor contributes to the formation of the ubiquitous transcriptional complex AP-1 involved in the control of many physiological and disease-associated functions. The roles of JUNB in the control of cell division and tumorigenic processes are acknowledged but still unclear.

Results: Here, we report the results of combined transcriptomic, genomic, and functional studies showing that JUNB promotes cell cycle progression via induction of cyclin E1 and repression of transforming growth factor (TGF)-β2 genes.

LPDA: A new classification method based on linear programming.

The search of separation hyperplanes is an efficient way to find rules with classification purposes. This paper presents an alternative mathematical programming formulation to existing methods to find a discriminant hyperplane. The hyperplane H is found by minimizing the sum of all the distances to the area assigned to the group each individual belongs to.

Correction: Pardo-Sánchez et al. Increased Tumor Growth Rate and Mesenchymal Properties of NSCLC-Patient-Derived Xenograft Models during Serial Transplantation. 2021, , 2980.

The authors would like to make a correction to their published paper [...