Ferroptosis is a new type of cell death that was discovered in recent years and is usually accompanied by a large amount of iron accumulation and lipid peroxidation during the cell death process; the ...occurrence of ferroptosis is iron-dependent. Ferroptosis-inducing factors can directly or indirectly affect glutathione peroxidase through different pathways, resulting in a decrease in antioxidant capacity and accumulation of lipid reactive oxygen species (ROS) in cells, ultimately leading to oxidative cell death. Recent studies have shown that ferroptosis is closely related to the pathophysiological processes of many diseases, such as tumors, nervous system diseases, ischemia-reperfusion injury, kidney injury, and blood diseases. How to intervene in the occurrence and development of related diseases by regulating cell ferroptosis has become a hotspot and focus of etiological research and treatment, but the functional changes and specific molecular mechanisms of ferroptosis still need to be further explored. This paper systematically summarizes the latest progress in ferroptosis research, with a focus on providing references for further understanding of its pathogenesis and for proposing new targets for the treatment of related diseases.
In this letter, a deep learning framework for direction of arrival (DOA) estimation is developed. We first show that the columns of the array covariance matrix can be formulated as under-sampled ...noisy linear measurements of the spatial spectrum. Then, a deep convolution network (DCN) that learns the inverse transformation from large training dataset is introduced. In contrast to traditional sparsity-inducing methods with computationally complex iterations, the proposed DCN-based framework could efficiently obtain DOA estimates in near real time. Moreover, the utilization of the sparsity prior improves DOA estimation performance compared to existing deep learning based methods. Simulation results have demonstrated the superiority of the proposed method in both DOA estimation precision and computation efficiency especially when SNR is low.
In this letter, we propose a coherent support vector regression (SVR) scheme to address the wideband direction of arrival (DOA) estimation problem. This learning-based method deals with wideband DOA ...estimation by treating it as a function approximation issue. The proposed approach first decomposes the wideband array outputs into several narrowband components, then approximates the functional relationship between the decomposed narrowband data and the DOA with coherent SVR scheme through training. The trained function is then capable of estimating the DOA when wideband signal with unknown impinging direction arrives. We prove the effectiveness and superiority of the presented method by simulation experiments. Simulation results show that the new technique has a better performance in terms of estimation errors than the conventional broadband DOA estimation method, especially in demanding scenarios with low SNR and limited snapshots. Moreover, the proposed approach also relaxes the unambiguous array element-spacing restrictions, i.e., it has extended the frequency range of wideband signals where direction finding without angle ambiguity is achievable.
The computationally prohibitive multi-dimensional searching procedure greatly restricts the application of the maximum likelihood (ML) direction-of-arrival (DOA) estimation method in practical ...systems. In this paper, we propose an efficient ML DOA estimator based on a spatially overcomplete array output formulation. The new method first reconstructs the array output on a predefined spatial discrete grid under the sparsity constraint via sparse Bayesian learning (SBL), thus obtaining a spatial power spectrum estimate that also indicates the coarse locations of the sources. Then a refined 1-D searching procedure is introduced to estimate the signal directions one by one based on the reconstruction result. The new method is able to estimate the incident signal number simultaneously. Numerical results show that the proposed method surpasses state-of-the-art methods largely in performance, especially in demanding scenarios such as low signal-to-noise ratio (SNR), limited snapshots and spatially adjacent signals.
Puerarin suppresses autophagy to alleviate cerebral ischemia/reperfusion injury, and accumulating evidence indicates that the AMPK-mTOR signaling pathway regulates the activation of the autophagy ...pathway through the coordinated phosphorylation of ULK1. In this study, we investigated the mechanisms underlying the neuroprotective effect of puerarin and its role in modulating autophagy via the AMPK-mTOR-ULK1 signaling pathway in the rat middle cerebral artery occlusion model of cerebral ischemia/reperfusion injury. Rats were intraperitoneally injected with puerarin, 50 or 100 mg/kg, daily for 7 days. Then, 30 minutes after the final administration, rats were subjected to transient middle cerebral artery occlusion for 90 minutes. Then, after 24 hours of reperfusion, the Longa score and infarct volume were evaluated in each group. Autophagosome formation was observed by transmission electron microscopy. LC3, Beclin-1 p62, AMPK, mTOR and ULK1 protein expression levels were examined by immunofluorescence and western blot assay. Puerarin substantially reduced the Longa score and infarct volume, and it lessened autophagosome formation in the hippocampal CA1 area following cerebral ischemia/reperfusion injury in a dose-dependent manner. Pretreatment with puerarin (50 or 100 mg/kg) reduced Beclin-1 expression and the LC3-II/LC3-I ratio, as well as p-AMPK and pS317-ULK1 levels. In comparison, it increased p62 expression. Furthermore, puerarin at 100 mg/kg dramatically increased the levels of p-mTOR and pS757-ULK1 in the hippocampus on the ischemic side. Our findings suggest that puerarin alleviates autophagy by activating the APMK-mTOR-ULK1 signaling pathway. Thus, puerarin might have therapeutic potential for treating cerebral ischemia/reperfusion injury.
A circRNA is a type of endogenous noncoding RNA that consists of a closed circular RNA molecule formed by reverse splicing; these RNAs are widely distributed in a variety of biological cells. In ...contrast to linear RNAs, circRNAs have no 5' cap or 3' poly(A) tail. They have a stable structure, a high degree of conservation, and high stability, and they are richly and specifically expressed in certain tissues and developmental stages. CircRNAs play a very important role in the occurrence and progression of malignant tumors. According to their origins, circRNAs can be divided into four types: exon-derived circRNAs (ecRNAs), intron-derived circRNAs (ciRNAs), circRNAs containing both exons and introns (EIciRNAs) and intergenic circRNAs. A large number of studies have shown that circRNAs have a variety of biological functions, participate in the regulation of gene expression and play an important role in the occurrence and progression of tumors. In this paper, the structure and function of circRNAs are reviewed, along with their biological role in malignant tumors of the digestive tract, in order to provide a reference for the diagnosis and treatment of digestive system neoplasms.
Among the existing sparsity-inducing direction-of-arrival (DOA) estimation methods, the sparse Bayesian learning (SBL) based ones have been demonstrated to achieve enhanced precision. However, the ...learning process of those methods converges much slowly when the signal-to-noise ratio (SNR) is relatively low. In this paper, we first show that the covariance vectors (columns of the covariance matrix) of the array output of independent signals share identical sparsity profiles corresponding to the spatial signal distribution, and their SNR exceeds that of the raw array output when moderately many snapshots are collected. Thus the SBL technique can be used to estimate the directions of independent narrowband/wideband signals by reconstructing those vectors with high computational efficiency. The method is then extended to narrowband correlated signals after proper modifications. In-depth analyses are also provided to show the lower bound of the new method in DOA estimation precision and the maximal signal number it can separate in the case of independent signals. Simulation results finally demonstrate the performance of the proposed method in both DOA estimation precision and computational efficiency.
This paper focuses on direction-of-arrival (DOA) estimation of wideband signals, and a method named wideband covariance matrix sparse representation (W-CMSR) is proposed. In W-CMSR, the lower left ...triangular elements of the covariance matrix are aligned to form a new measurement vector, and DOA estimation is then realized by representing this vector on an over-complete dictionary under the constraint of sparsity. The a priori information of the incident signal number is not needed in W-CMSR, and no spectral decomposition or focusing is introduced. Simulation results demonstrate the satisfying performance of W-CMSR in wideband DOA estimation in various settings. Moreover, theoretical analysis and numerical examples show how many simultaneous signals can be separated by W-CMSR on typical array geometries, and that the half-wavelength spacing restriction in avoiding ambiguity can be relaxed from the highest to the lowest frequency of the incident wideband signals.
Venous congestion has been demonstrated to increase the risk of acute kidney injury (AKI) after cardiac surgery. Although many surrogate markers for venous congestion are currently used in clinical ...settings, there is no consensus on which marker is most effective in predicting AKI.
We evaluated various markers of venous congestion, including central venous pressure (CVP), inferior vena cava (IVC) diameter, portal pulsatility fraction (PPF), hepatic vein flow pattern (HVF), intra-renal venous flow pattern (IRVF), and venous excess ultrasound grading score (VExUS) in adult patients undergoing cardiac surgery to compare their ability in predicting AKI.
Among the 230 patients enrolled in our study, 53 (23.0%) developed AKI, and 11 (4.8%) required continuous renal replacement therapy (CRRT). Our multivariate logistic analysis revealed that IRVF, PPF, HVF, and CVP were significantly associated with AKI, with IRVF being the strongest predictor (odds ratio OR 2.27; 95% confidence interval CI, 1.38–3.73). However, we did not observe any association between these markers and CRRT.
Venous congestion is associated with AKI after cardiac surgery, but not necessarily with CRRT. Among the markers tested, IRVF exhibits the strongest correlation with AKI.
•Venous congestion is associated with CSA-AKI, but not necessarily with CRRT.•The surrogates of venous congestion exhibit varying degrees of correlation with each other.•Among all the congestion surrogates, IRVF may be the most closely associated with CSA-AKI.•IVC is not a valuable variable for both venous congestion and CSA-AKI prediction.•Inclusion of IVC may compromise the effectiveness of VExUS in estimating congestion and predicting CSA-AKI.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Electroacupuncture is known as an effective adjuvant therapy in ischemic cerebrovascular disease. However, its underlying mechanisms remain unclear. Studies suggest that autophagy, which is essential ...for cell survival and cell death, is involved in cerebral ischemia reperfusion injury and might be modulate by electroacupuncture therapy in key ways. This paper aims to provide novel insights into a therapeutic target of electroacupuncture against cerebral ischemia/reperfusion injury from the perspective of autophagy. Here we review recent studies on electroacupuncture regulation of autophagy-related markers such as UNC-51-like kinase-1 complex, Beclin1, microtubule-associated protein-1 light chain 3, p62, and autophagosomes for treating cerebral ischemia/reperfusion injury. The results of these studies show that electroacupuncture may affect the initiation of autophagy, vesicle nucleation, expansion and maturation of autophagosomes, as well as fusion and degradation of autophagolysosomes. Moreover, studies indicate that electroacupuncture probably modulates autophagy by activating the mammalian target of the rapamycin signaling pathway. This review thus indicates that autophagy is a therapeutic target of electroacupuncture treatment against ischemic cerebrovascular diseases.
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