Can we rely on magnetic resonance imaging for prostate cancer detection and surgical planning? Comprehensive analysis of a large cohort of patients undergoing transperineal mapped biopsies.

Purpose: To evaluate MRI and histological concordance in prostate cancer (PCa) identification via mapped transperineal biopsies.

Methodology: Retrospective per-lesion analysis of patients undergoing MRI and transperineal biopsy at the Valencian Institute of Oncology (2016-2024) using CAPROSIVO PCa data. Patients underwent MRI, with or without regions of interest (ROI), followed by transperineal biopsies (3-5 cores/ROI, 20-30 systematic).

Antarctic Streptomyces: Promising biocontrol agents for combating f. sp. cubense.

Fusarium wilt of Banana (FWB) caused by f. sp. (Foc) poses a significant threat to the banana industry, with current inadequate control measures.

Recycling and Reutilization of Metals Aided by Deep Eutectic Solvents: from NMC Cathodes of Spent Li-ion Batteries to Electrolytes for Supercapacitors.

With the rapidly increasing demand for lithium ion batteries (LIBs), recycling the metals found in spent cathodes is mandatory to both alleviate shortages resulting from the mining of natural metal ores and manage the disposal of spent LIBs. The use of deep eutectic solvents (DESs) for metals recovery from spent cathodes of LIBs (e. g.

Edge Artificial Intelligence (AI) for real-time automatic quantification of filariasis in mobile microscopy.

Filariasis, a neglected tropical disease caused by roundworms, is a significant public health concern in many tropical countries. Microscopic examination of blood samples can detect and differentiate parasite species, but it is time consuming and requires expert microscopists, a resource that is not always available. In this context, artificial intelligence (AI) can assist in the diagnosis of this disease by automatically detecting and differentiating microfilariae.