Exosomes from osteoarthritic fibroblast-like synoviocytes promote cartilage ferroptosis and damage via delivering microRNA-19b-3p to target SLC7A11 in osteoarthritis

ObjectiveOur previous studies revealed that normal synovial exosomes promoted chondrogenesis, and microRNA (miR)-19b-3p independently related to osteoarthritis (OA) risk. Subsequently, this study intended to further explore the effect of OA fibroblast-like synoviocyte (OA-FLS) exosomal miR-19b-3p on OA ferroptosis and its potential mechanisms.MethodsInterleukin (IL)-1β-stimulated chondrocytes and medial meniscus surgery were used to construct the OA cellular model and the OA rat model, respectively. OA-FLS exosomes with/without miR-19b-3p modification were added to the IL-1β-stimulated chondrocytes and OA rat models, followed by direct miR-19b-3p mimic/inhibitor transfection with/without SLC7A11 overexpression plasmids. miR-19b-3p, ferroptosis-related markers (malondialdehyde (MDA), glutathione (GSH)/oxidized glutathione (GSSG), ferrous ion (Fe2+), glutathione peroxidase 4 (GPX4), solute carrier family 7 member 11 (SLC7A11), and acyl-CoA synthetase long-chain family member 4 (ACSL4)), mitochondrial membrane potential (MMP), and reactive oxygen species (ROS) levels were detected.ResultsEnhanced ferroptosis reflected by dysregulated ferroptosis-related markers, a reduced MMP, and an increased ROS was observed in cartilage tissues from OA patients vs. controls, IL-1β-stimulated chondrocytes vs. normal ones, and OA rat models vs. sham, so did miR-19b-3p. OA-FLS exosomes promoted MDA, Fe2+, ACSL4, and ROS but reduced cell viability, GSH/GSSG, GPX4, SLC7A11, and MMP in IL-1β-stimulated chondrocytes, whose effect was enhanced by miR-19b-3p mimics and attenuated by miR-19b-3p inhibitors. miR-19b-3p negatively regulated SLC7A11 and directly bound to SLC7A11 via luciferase reporter gene assay. Furthermore, SLC7A11 overexpression weakened miR-19b-3p mimics’ effect on ferroptosis-related markers, MMP, or ROS in IL-1β-stimulated chondrocytes. OA-FLS exosomes also induced cartilage damage and ferroptosis in OA rats whose influence was tempered by miR-19b-3p inhibitors.ConclusionOA-FLS exosomal miR-19b-3p enhances cartilage ferroptosis and damage by sponging SLC7A11 in OA, indicating a potential linkage among synovium, cartilage, and ferroptosis during the OA process

FCOS-LSC: A novel model for green fruit detection in a complex orchard environment

To better address the difficulties in designing green fruit recognition techniques in machine vision systems, we propose an optimized FCOS (full convolutional one-stage object detection) algorithm based on LSC attention blocks (FCOS-LSC) that are performed on level scales, spaces and channels of feature map. The method achieves efficient recognition and localization of green fruit images affected by overlapping occlusions, lighting conditions and capture angles. Specifically, the improved feature extraction network ResNet50 with added deformable convolution is used to fully extract green fruit feature information. The feature pyramid network (FPN) is employed to fully fuse low-level detail information and high-level semantic information in a cross-connected and top-down connected way. Next, the attention mechanisms are added to each of the three dimensions of scale, space (including the height and width of the feature map) and channel of the generated multi-scale feature map to improve the feature perception capability of the network. Finally, the classification and regression sub-networks of the model are applied to predict the fruit category and bounding box. In the classification branch, a new positive and negative sample selection strategy is applied to better distinguish supervised signals by designing weights in the loss function to achieve more accurate fruit detection. The proposed FCOS-LSC model has 38.65M parameters (Params), 38.72G floating point operations (FLOPs), and mean average precision (mAP) of 63.0% and 75.2% for detecting green apples and green persimmons, respectively. In summary, FCOS-LSC outperforms the state-of-the-art models in terms of precision and complexity to meet the accurate and efficient requirements of green fruit recognition by intelligent agricultural equipment. Correspondingly, FCOS-LSC can be used to improve the robustness and generalization of the green fruit detection models

Earthquakes: from chemical alteration to mechanical rupture

In the standard rebound theory of earthquakes, elastic deformation energy is progressively stored in the crust until a threshold is reached at which it is suddenly released in an earthquake. We review three important paradoxes, the strain paradox, the stress paradox and the heat flow paradox, that are difficult to account for in this picture, either individually or when taken together. Resolutions of these paradoxes usually call for additional assumptions on the nature of the rupture process (such as novel modes of deformations and ruptures) prior to and/or during an earthquake, on the nature of the fault and on the effect of trapped fluids within the crust at seismogenic depths. We review the evidence for the essential importance of water and its interaction with the modes of deformations. Water is usually seen to have mainly the mechanical effect of decreasing the normal lithostatic stress in the fault core on one hand and to weaken rock materials via hydrolytic weakening and stress corrosion on the other hand. We also review the evidences that water plays a major role in the alteration of minerals subjected to finite strains into other structures in out-of-equilibrium conditions. This suggests novel exciting routes to understand what is an earthquake, that requires to develop a truly multidisciplinary approach involving mineral chemistry, geology, rupture mechanics and statistical physics.Comment: 44 pages, 1 figures, submitted to Physics Report

Critical Reynolds number for nonlinear flow through rough-walled fractures: The role of shear processes

This paper experimentally investigates the role of shear processes on the variation of critical Reynolds number and nonlinear flow through rough-walled rock fractures. A quantitative criterion was developed to quantify the onset of nonlinear flow by comprehensive combination of Forchheimer's law and Reynolds number. At each shear displacement, several high-precision water flow tests were carried out with different hydraulic gradients then the critical Reynolds number was determined based on the developed criterion. The results show that (i) the Forchheimer's law was fitted very well to experimental results of nonlinear fluid flow through rough-walled fractures, (ii) the coefficients of viscous and inertial pressure drops experience 4 and 7 orders of magnitude reduction during shear displacement, respectively, and (iii) the critical Reynolds number varies from 0.001 to 25 and experiences 4 orders of magnitude enlargement by increasing shear displacement from 0 to 20 mm. These findings may prove useful in proper understanding of fluid flow through rock fractures, or inclusions in computational studies of large-scale nonlinear flow in fractured rocks

Machine learning methods for helium flux analysis with DAMPE experiment

DAMPE is a space-borne experiment for the measurement of the cosmic-ray fluxes at energies up to around 100 TeV per nucleon. At energies above several tens of TeV, the electronics of DAMPE calorimeter would saturate, leaving certain bars with no energy recorded. It is also observed that at high energies the tracker and the scintillator detector that serve for the charge identification become heavily populated with back-splash tracks. Both effects interfere in precise measurements of the helium flux at highest energies. In the present contribution we discuss the application of machine learning techniques for the treatment of DAMPE data, to compensate the calorimeter energy lost by saturation and to identify helium events

Observations of Forbush Decreases of Cosmic-Ray Electrons and Positrons with the Dark Matter Particle Explorer

The Forbush decrease (FD) represents the rapid decrease of the intensities of charged particles accompanied with the coronal mass ejections or high-speed streams from coronal holes. It has been mainly explored with the ground-based neutron monitor network, which indirectly measures the integrated intensities of all species of cosmic rays by counting secondary neutrons produced from interaction between atmospheric atoms and cosmic rays. The space-based experiments can resolve the species of particles but the energy ranges are limited by the relatively small acceptances except for the most abundant particles like protons and helium. Therefore, the FD of cosmic-ray electrons and positrons have just been investigated by the PAMELA experiment in the low-energy range (<5 GeV) with limited statistics. In this paper, we study the FD event that occurred in 2017 September with the electron and positron data recorded by the Dark Matter Particle Explorer. The evolution of the FDs from 2 GeV to 20 GeV with a time resolution of 6 hr are given. We observe two solar energetic particle events in the time profile of the intensity of cosmic rays, the earlier, and weaker, one has not been shown in the neutron monitor data. Furthermore, both the amplitude and recovery time of fluxes of electrons and positrons show clear energy dependence, which is important in probing the disturbances of the interplanetary environment by the coronal mass ejections

The Time Course of the Influence of Valence and Arousal on the Implicit Processing of Affective Pictures

In the current study, we investigated the time course of the implicit processing of affective pictures with an orthogonal design of valence (negative vs. positive) by arousal (low vs. high). Previous studies with explicit tasks suggested that valence mainly modulates early event-related potential (ERP) components, whereas arousal mainly modulates late components. However, in this study with an implicit task, we observed significant interactions between valence and arousal at both early and late stages over both parietal and frontal sites, which were reflected by three different ERP components: P2a (100–200 ms), N2 (200–300 ms), and P3 (300–400 ms). Furthermore, there was also a significant main effect of arousal on P2b (200–300 ms) over parieto-occipital sites. Our results suggest that valence and arousal effects on implicit affective processing are more complicated than previous ERP studies with explicit tasks have revealed

Search for gamma-ray lines in the Galaxy with DAMPE

DArk Matter Particle Explorer (DAMPE) has a great potential in the search of monochromatic and sharp gamma-ray structures in GeV-TeV range thanks to its good energy resolution. In this work, we search for gamma-ray line structures using 5.0 years of DAMPE data. To improve the sensitivity, we develop two types of data sets and adopt the signal-to-noise ratio optimized regions of interest (ROIs) for different DM density profiles. No line signals or candidates, including those located at 133 GeV and 43 GeV, are found between 10 GeV and 300 GeV in the Galaxy. Therefore we calculate the 95% confidence level constraints on the velocity-averaged cross section for χχ → γγ and the decay lifetime for χ → γν with systematic uncertainties included. Our constraints on DM parameters are mostly comparable to the Fermi-LAT 5.8-yr results. The lower limit for DM decay lifetime below 100 GeV are better than that of Fermi-LAT

Charge measurement of cosmic rays by Plastic Scintillator Detector of DAMPE

Plastic Scintillator Detector (PSD) of DArk Matter Particle Explorer (DAMPE) is designed to measure the charge of cosmic-rays and it servers as a veto for gamma-rays. In this work, we present some updated correction methods to further improve the quality of PSD charge measurement, especially for heavy nuclei. DAMPE has collected nearly 10 billions events by middle of 2021, it has substantial potential to measure the spectra of cosmic ray nuclei up to hundreds of TeV energies. These measurements could largely benefit from the correction of the PSD signal