Multifaceted Analyses of Isolated Mitochondria Establish the Anticancer Drug 2-Hydroxyoleic Acid as an Inhibitor of Substrate Oxidation and an Activator of Complex IV-Dependent State 3 Respiration.

The synthetic fatty acid 2-hydroxyoleic acid (2OHOA) has been extensively investigated as a cancer therapy mainly based on its regulation of membrane lipid composition and structure, activating various cell fate pathways. We discovered, additionally, that 2OHOA can uncouple oxidative phosphorylation, but this has never been demonstrated mechanistically. Here, we explored the effect of 2OHOA on mitochondria isolated by ultracentrifugation from U118MG glioblastoma cells. Mitochondria were analyzed by shotgun lipidomics, molecular dynamic simulations, spectrophotometric assays for determining respiratory complex activity, mass spectrometry for assessing beta oxidation and Seahorse technology for bioenergetic profiling. We showed that the main impact of 2OHOA on mitochondrial lipids is their hydroxylation, demonstrated by simulations to decrease co-enzyme Q diffusion in the liquid disordered membranes embedding respiratory complexes. This decreased co-enzyme Q diffusion can explain the inhibition of disjointly measured complexes I-III activity. However, it doesn't explain how 2OHOA increases complex IV and state 3 respiration in intact mitochondria. This increased respiration probably allows mitochondrial oxidative phosphorylation to maintain ATP production against the 2OHOA-mediated inhibition of glycolytic ATP production. This work correlates 2OHOA function with its modulation of mitochondrial lipid composition, reflecting both 2OHOA anticancer activity and adaptation to it by enhancement of state 3 respiration.

Hydroxylated Fatty Acids: The Role of the Sphingomyelin Synthase and the Origin of Selectivity.

Sphingolipids are a class of lipids acting as key modulators of many physiological and pathophysiological processes. Hydroxylation patterns have a major influence on the biophysical properties of sphingolipids. In this work, we have studied the mechanism of action of hydroxylated lipids in sphingomyelin synthase (SMS). The structures of the two human isoforms, SMS1 and SMS2, have been generated through neural network supported homology. Furthermore, we have elucidated the reaction mechanism that allows SMS to recover the choline head from a phosphocholine (PC) and transfer it to ceramide, and we have clarified the role of the hydroxyl group in the interaction with the enzyme. Finally, the effect of partial inhibition of SMS on the levels of PC and sphingomyelin was calculated for different rate constants solving ordinary differential equation systems.

Deep Myometrial Infiltration of Endometrial Cancer on MRI: A Radiomics-Powered Machine Learning Pilot Study.

RATIONALE AND OBJECTIVES: To evaluate an MRI radiomics-powered machine learning (ML) model's performance for the identification of deep myometrial invasion (DMI) in endometrial cancer (EC) patients and explore its clinical applicability. MATERIALS AND METHODS: Preoperative MRI scans of EC patients were retrospectively selected. Three radiologists performed whole-lesion segmentation on T2-weighted images for feature extraction. Feature robustness was tested before randomly splitting the population in training and test sets (80/20% proportion). A multistep feature selection was applied to the first, excluding noninformative, low variance features and redundant, highly-intercorrelated ones. A Random Forest wrapper was used to identify the most informative among the remaining. An ensemble of J48 decision trees was tuned and finalized in the training set using 10-fold cross-validation, and then assessed on the test set. A radiologist evaluated all MRI scans without and with the aid of ML to detect the presence of DMI. McNemars's test was employed to compare the two readings. RESULTS: Of the 54 patients included, 17 had DMI. In all, 1132 features were extracted. After feature selection, the Random Forest wrapper identified the three most informative which were used for ML training. The classifier reached an accuracy of 86% and 91% and areas under the Receiver Operating Characteristic curve of 0.92 and 0.94 in the cross-validation and final testing, respectively. The radiologist performance increased from 82% to 100% when using ML (p = 0.48). CONCLUSION: We proved the feasibility of a radiomics-powered ML model for DMI detection on MR T2-w images that might help radiologists to increase their performance.

A Flavone-Based Solvatochromic Probe with A Low Expected Perturbation Impact on the Membrane Physical State.

The study of the cell membrane is an ambitious and arduous objective since its physical state is regulated by a series of processes that guarantee its regular functionality. Among the different methods of analysis, fluorescence spectroscopy is a technique of election, non-invasive, and easy to use. Besides, molecular dynamics analysis (MD) on model membranes provides useful information on the possibility of using a new probe, following its positioning in the membrane, and evaluating the possible perturbation of the double layer. In this work, we report the rational design and the synthesis of a new fluorescent solvatochromic probe and its characterization in model membranes. The probe consists of a fluorescent aromatic nucleus of a 3-hydroxyflavone moiety, provided with a saturated chain of 18 carbon atoms and a zwitterionic head so to facilitate the anchoring to the polar heads of the lipid bilayer and avoid the complete internalization. It was possible to study the behavior of the probe in GUV model membranes by MD analysis and fluorescence microscopy, demonstrating that the new probe can efficiently be incorporated in the lipid bilayer, and give a color response, thanks to is solvatochromic properties. Moreover, MD simulation of the probe in the membrane supports the hypothesis of a reduced perturbation of the membrane physical state.

Plausible Emergence of Autocatalytic Cycles under Prebiotic Conditions.

The emergence of life in a prebiotic world is an enormous scientific question of paramount philosophical importance. Even when life (in any sense we can define it) can be observed and replicated in the laboratory, it is only an indication of one possible pathway for life emergence, and is by no means be a demonstration of how life really emerged. The best we can hope for is to indicate plausible chemical-physical conditions and mechanisms that might lead to self-organizing and autopoietic systems. Here we present a stochastic simulation, based on chemical reactions already observed in prebiotic environments, that might help in the design of new experiments. We will show how the definition of simple rules for the synthesis of random peptides may lead to the appearance of networks of autocatalytic cycles and the emergence of memory.