Resource-Efficient FPGA Architecture for Real-Time RFI Mitigation in Interferometric Radiometers.

Interferometric radiometers operating at L-band, such as ESA's SMOS mission, enable crucial Earth observations providing high-resolution measurements of soil moisture, ocean salinity, and other geophysical parameters. However, the increasing electromagnetic spectrum utilization has led to significant Radio Frequency Interference (RFI) challenges, particularly critical given the sensors' fine temperature resolution requirements of less than 1 K. This work presents the hardware implementation of an advanced RFI detection and mitigation algorithm specifically designed for interferometric radiometers, targeting future L-band missions.

Development of a Dynamically Re-Configurable Radio-Frequency Interference Detection System for L-Band Microwave Radiometers.

Real-Time RFI Detection and Flagging (RT-RDF) for microwave radiometers is a versatile new FPGA algorithm designed to detect and flag Radio-Frequency Interference (RFI) in microwave radiometers. This block utilizes computationally-efficient techniques to identify and analyze RF signals, allowing the system to take appropriate measures to mitigate interference and maintain reliable performance. With L-Band microwave radiometry as the main application, this RFI detection algorithm focuses on the Kurtogram and Spectrogram to detect non-Gaussian behavior.

Generation of Metastatic Cholangiocarcinoma Patient-Derived Xenograft Models.

Cholangiocarcinoma (CCA) poses a substantial clinical hurdle as it is often detected at advanced metastatic stages with limited therapeutic options. To enhance our understanding of advanced CCA, it is imperative to establish preclinical models that faithfully recapitulate the disease's characteristics. Patient-derived xenograft (PDX) models have emerged as a valuable approach in cancer research, offering an avenue to reproduce and study the genomic, histologic, and molecular features of the original human tumors.

Interactions between BRD4S, LOXL2, and MED1 drive cell cycle transcription in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) often develops resistance to single-agent treatment, which can be circumvented using targeted combinatorial approaches. Here, we demonstrate that the simultaneous inhibition of LOXL2 and BRD4 synergistically limits TNBC proliferation in vitro and in vivo. Mechanistically, LOXL2 interacts in the nucleus with the short isoform of BRD4 (BRD4S), MED1, and the cell cycle transcriptional regulator B-MyB.