Structural Basis for Parallel G-Quadruplex Recognition by an Ankyrin Protein.

G-Quadruplex (G4) structures formed by guanine-rich DNA and RNA sequences are implicated in various biological processes. Understanding the mechanisms by which proteins recognize G4 structures is crucial for elucidating their functional roles. Here we present the X-ray crystal structure of an ankyrin protein bound to a parallel G4 structure. Our findings reveal a new specific recognition mode in which a bundle of α-helices and loops of the ankyrin form a flat surface to stack on the G-tetrad core. The protein employs a combination of hydrogen bonds and hydrophobic contacts to interact with the G4, and electrostatic interaction is used to enhance the binding affinity. This binding mechanism provides valuable insights into understanding G4 recognition by proteins.

PROM2 overexpression induces metastatic potential through epithelial-to-mesenchymal transition and ferroptosis resistance in human cancers.

INTRODUCTION: Despite considerable therapeutic advances in the last 20 years, metastatic cancers remain a major cause of death. We previously identified prominin-2 (PROM2) as a biomarker predictive of distant metastases and decreased survival, thus providing a promising bio-target. In this translational study, we set out to decipher the biological roles of PROM2 during the metastatic process and resistance to cell death, in particular for metastatic melanoma. METHODS AND RESULTS: Methods and results: We demonstrated that PROM2 overexpression was closely linked to an increased metastatic potential through the increase of epithelial-to-mesenchymal transition (EMT) marker expression and ferroptosis resistance. This was also found in renal cell carcinoma and triple negative breast cancer patient-derived xenograft models. Using an oligonucleotide anti-sense anti-PROM2, we efficaciously decreased PROM2 expression and prevented metastases in melanoma xenografts. We also demonstrated that PROM2 was implicated in an aggravation loop, contributing to increase the metastatic burden both in murine metastatic models and in patients with metastatic melanoma. The metastatic burden is closely linked to PROM2 expression through the expression of EMT markers and ferroptosis cell death resistance in a deterioration loop. CONCLUSION: Our results open the way for further studies using PROM2 as a bio-target in resort situations in human metastatic melanoma and also in other cancer types.

Utilizing 3D Point Cloud Technology with Deep Learning for Automated Measurement and Analysis of Dairy Cows.

This paper introduces an approach to the automated measurement and analysis of dairy cows using 3D point cloud technology. The integration of advanced sensing techniques enables the collection of non-intrusive, precise data, facilitating comprehensive monitoring of key parameters related to the health, well-being, and productivity of dairy cows. The proposed system employs 3D imaging sensors to capture detailed information about various parts of dairy cows, generating accurate, high-resolution point clouds. A robust automated algorithm has been developed to process these point clouds and extract relevant metrics such as dairy cow stature height, rump width, rump angle, and front teat length. Based on the measured data combined with expert assessments of dairy cows, the quality indices of dairy cows are automatically evaluated and extracted. By leveraging this technology, dairy farmers can gain real-time insights into the health status of individual cows and the overall herd. Additionally, the automated analysis facilitates efficient management practices and optimizes feeding strategies and resource allocation. The results of field trials and validation studies demonstrate the effectiveness and reliability of the automated 3D point cloud approach in dairy farm environments. The errors between manually measured values of dairy cow height, rump angle, and front teat length, and those calculated by the auto-measurement algorithm were within 0.7 cm, with no observed exceedance of errors in comparison to manual measurements. This research contributes to the burgeoning field of precision livestock farming, offering a technological solution that not only enhances productivity but also aligns with contemporary standards for sustainable and ethical animal husbandry practices.