Design of a high-resolution light field miniscope for volumetric imaging in scattering tissue

Integrating light field microscopy techniques with existing miniscope architectures has allowed for volumetric imaging of targeted brain regions in freely moving animals. However, the current design of light field miniscopes is limited by non-uniform resolution and long imaging path length. In an effort to overcome these limitations, this paper proposes an optimized Galilean-mode light field miniscope (Gali-MiniLFM), which achieves a more consistent resolution and a significantly shorter imaging path than its conventional counterparts. In addition, this paper provides a novel framework that incorporates the anticipated aberrations of the proposed Gali-MiniLFM into the point spread function (PSF) modeling. This more accurate PSF model can then be used in 3D reconstruction algorithms to further improve the resolution of the platform. Volumetric imaging in the brain necessitates the consideration of the effects of scattering. We conduct Monte Carlo simulations to demonstrate the robustness of the proposed Gali-MiniLFM for volumetric imaging in scattering tissue.https://www.osapublishing.org/boe/fulltext.cfm?uri=boe-11-3-1662&id=427971https://www.osapublishing.org/boe/fulltext.cfm?uri=boe-11-3-1662&id=427971Published versio

Study on the actual particle size, activity concentration, and migration process adsorption behavior of radioactive substances in liquid effluents from nuclear power plants

Radionuclides emitted by nuclear power plants may have effects on the environment and public health. At present, research on radioactive material effluent in the industry mainly focuses on the treatment of radioactive effluent and the particle size distribution of the primary circuit. There is little research on the particle size of radioactive material during the migration process outside the primary circuit system, as well as the flocculation precipitation and other enrichment phenomena during the collection process of effluent. Therefore, this study relies on the sampling of effluent from an in-service nuclear power plant to measure its radioactivity level by particle size range. At the same time, the mixing process of effluent is simulated in the laboratory to simulate the adsorption behavior of effluent during the migration process. It was found that in the activity concentration of detectable radioactive nuclides in the effluent samples, more than 95% of radioactive nuclides exist in the liquid with particle sizes less than 0.1μm, while particle sizes greater than 0.45 μm account for less than 5%. After the sample was filtered by the demineralizer, the radioactive activity decreased. The flocculation precipitation in the waste liquid of the waste water recovery system has a certain contribution to the enrichment of nuclides. With the extension of time, the enrichment of transition elements such as cobalt and manganese is particularly obvious, so that it is distributed in the liquid again with a large particle size. In addition, large particle size substances such as colloids in seawater have a certain adsorption effect on radionuclides, which will lead to its aggregation effect again

Mitofusin 2 Participates in Mitophagy and Mitochondrial Fusion Against Angiotensin II-Induced Cardiomyocyte Injury

BackgroundMitochondrial dynamics play a critical role in mitochondrial function. The mitofusin 2 (MFN2) gene encodes a mitochondrial membrane protein that participates in mitochondrial fusion to maintain and operate the mitochondrial network. Moreover, MFN2 is essential for mitophagy. In Ang II-induced cardiac remodeling, the combined effects of MFN2-mediated mitochondrial fusion and mitophagy are unclear. This study was designed to explore a novel strategy for preventing cardiomyocyte injury via modulation of mitochondrial dynamics.MethodsWe studied the function of MFN2 in mitochondrial fusion and mitophagy in Ang II-stimulated cardiomyocyte injury. Cardiomyocyte injury experiments, including reactive oxygen species (ROS) production, mitochondrial membrane potential (MMP), and apoptosis rate of cardiomyocytes were performed. The mitochondrial morphology in cardiomyocytes was examined via transmission electron microscopy (TEM) and confocal microscopy. Autophagic levels in response to Ang II were examined by immunoblotting of autophagy-related proteins. Moreover, PINK1/MFN2/Parkin pathway-related proteins were examined.ResultsWith stimulation by Ang II, MFN2 expression was progressively reduced. MFN2 deficiency impaired mitochondrial quality, resulting in exacerbated mitochondrial damage induced by Ang II. The Ang II-induced increases in ROS production and apoptosis rate were alleviated by MFN2 overexpression. Moreover, MFN2 alleviated the Ang II-induced reduction in MMP. MFN2 promoted mitochondrial fusion, and MFN2 promoted Parkin translocation and phosphorylation, leading to mitochondrial autophagy. The effects of MFN2 overexpression were reversed by autophagy inhibitors.ConclusionMitofusin 2 promotes Parkin translocation and phosphorylation, leading to mitophagy to clear damaged mitochondria. However, the beneficial effects of MFN2 were reversed by autophagy inhibitors. Additionally, MFN2 participates in mitochondrial fusion to maintain mitochondrial quality. Thus, MFN2 participated in mitophagy and mitochondrial fusion against Ang II-induced cardiomyocyte injury

Machine learning for polyphenol-based materials

Polyphenol-based materials, primarily composed of polyphenolic compounds, have attracted considerable attention due to their unique chemical structures and biological activities. However, there are many derivatives of polyphenols, resulting in the complexity and diversity of polyphenol-based materials. Traditional methods are difficult to meet the rapid development of polyphenol-based materials. Machine learning, known for its proficiency in predicting performance, optimizing synthesis processes, and designing novel materials, offers significant potential in the intelligent design and applications of polyphenol-based materials. In this review, we summarize the recent advancements in the research and development of polyphenol-based materials and machine learning. The intersection of polyphenol-based materials and machine learning is also discussed, including their applications in biomedical, environmental, and energy fields. The challenges and prospects for the future development of polyphenol-based materials based on machine learning are highlighted

Harnessing Path Optimization to Enhance the Strength of Three-Dimensional (3D) Printed Concrete

The path-dependent strength of three-dimensional printed concrete (3DPC) hinders further engineering application. Printing path optimization is a feasible solution to improve the strength of 3DPC. Here, the mix ratio of 3DPC was studied to print standard concrete specimens with different printing paths using our customized concrete 3D printer, which features fully sealed extrusion and ultrathin nozzles. These paths include crosswise, vertical, arched, and diagonal patterns. Their flexural and compressive strengths were tested. In order to verify the tested results and expose the mechanism of strength enhancement, digital image correlation (DIC) was used to capture the dynamic gradual fracture in the flexural tests. Also, the meso- and microstructures of the 3D-printed concrete specimens were pictured. The results reported here show that arched-path concrete has 30% more flexural strength than others because it makes better use of filament-wise strength. The findings here provide a pathway to improve the strength of 3D-printed concrete by path optimization, boosting 3DPC’s extensive application in civil engineering

Mesenchymal Stem Cell-Derived Extracellular Vesicles: Pleiotropic Impacts on Breast Cancer Occurrence, Development, and Therapy

Breast cancer (BC) is one of the most devastating cancers, with high morbidity and mortality, among the female population worldwide. In BC, mesenchymal stem cells (MSCs), as pluripotent stromal stem cells, play a significant role in TME formation and tumor progression. Recently, an increasing number of studies have demonstrated that extracellular vesicles (EVs) are essential for the crosstalk between MSCs and BC cells. MSC-derived EVs (MSC-EVs) can deliver a diversity of molecules, including lipids, proteins, and nucleic acids, etc., to target cells, and produce corresponding effects. Studies have demonstrated that MSC-EVs exert both inhibitory and promotive effects in different situations and different stages of BC. Meanwhile, MSC-EVs provide novel therapeutic options for BC, such as EVs as carriers for drug delivery. Therefore, in this review, we summarize the role of MSC-EVs in BC progression and application in clinical treatment, in the hope of providing a basis for further research

Current Knowledge of Long Non-Coding RNA HOTAIR in Breast Cancer Progression and Its Application

Breast cancer is one of the most devastating cancers with high morbidity and mortality in females worldwide. Breast tumorigenesis and further development present great uncertainty and complexity, and efficient therapeutic approaches still lack. Accumulating evidence indicates HOX transcript antisense intergenic RNA (HOTAIR) is dysregulated in cancers and has emerged as a novel hotspot in the field. In breast cancer, aberrant HOTAIR expression is responsible for advanced tumor progression by regulating multifarious signaling pathways. Besides, HOTAIR may act as competitive endogenous RNA to bind to several microRNAs and suppress their expressions, which can subsequently upregulate the levels of targeted downstream messenger RNAs, thereby leading to further cancer progression. In addition, HOTAIR works as a promising biomarker and predictor for breast cancer patients’ diagnosis or outcome prediction. Recently, HOTAIR is potentially considered to be a drug target. Here, we have summarized the induction of HOTAIR in breast cancer and its impacts on cell proliferation, migration, apoptosis, and therapeutic resistance, as well as elucidating the underlying mechanisms. This review aims to provide new insights into investigations between HOTAIR and breast cancer development and inspire new methods for studying the association in depth