Exosomes based strategies for cardiovascular diseases: Opportunities and challenges.

Exosomes, as nanoscale extracellular vesicles (EVs), are secreted by all types of cells to facilitate intercellular communication in living organisms. After being taken up by neighboring or distant cells, exosomes can alter the expression levels of target genes in recipient cells and thereby affect their pathophysiological outcomes depending on payloads encapsulated therein. The functions and mechanisms of exosomes in cardiovascular diseases have attracted much attention in recent years and are thought to have cardioprotective and regenerative potential. This review summarizes the biogenesis and molecular contents of exosomes and details the roles played by exosomes released from various cells in the progression and recovery of cardiovascular disease. The review also discusses the current status of traditional exosomes in cardiovascular tissue engineering and regenerative medicine, pointing out several limitations in their application. It emphasizes that some of the existing emerging industrial or bioengineering technologies are promising to compensate for these shortcomings, and the combined application of exosomes and biomaterials provides an opportunity for mutual enhancement of their performance. The integration of exosome-based cell-free diagnostic and therapeutic options will contribute to the further development of cardiovascular regenerative medicine.

Association between oxidative balance score and rheumatoid arthritis in female: a cross-sectional study.

OBJECTIVE: Although oxidative stress is a recognized factor of inflammation, the correlation between oxidative balance score (OBS), a biomarker indicating the balance of oxidation and antioxidant, and rheumatoid arthritis (RA), an immune system disease that tends to occur in women, remains unexplored. Hence, the aim of this study was to investigate the potential association between OBS and RA in women. METHODS: Observational surveys were performed by employing information extracted from the National Health and Nutrition Examination Survey (NHANES) for the period 2007-2018. Various statistical techniques were employed to investigate the association between OBS and RA, encompassing multivariable logistic regression analysis, subgroup analyses, smooth curve fitting, and threshold effect analysis. RESULTS: The study included 8219 female participants, including 597 patients with RA. The results showed that higher Total OBS (TOBS) significantly correlated with lower RA prevalence in the entirely modified model [odd ratio (OR) = 0.968; 95% confidence interval (CI) = 0.952 to 0.984; P = 0.0001]. Dietary OBS (DOBS) and lifestyle OBS (LOBS) also negatively correlated with RA. This association was remarkably consistent across TOBS subgroups by age, race, education level, family poverty-to-income ratio (PIR), hypertension and diabetes. Smooth curve fitting and threshold effect analysis also revealed the linear relationship between OBS and RA. CONCLUSIONS: Overall, OBS was negatively associated with RA in female. This study suggested that an antioxidant diet and lifestyle may be promising measures to prevent RA in female.

PeNet: A feature excitation learning approach to advertisement click-through rate prediction.

Since the physical meaning of the fields of the dataset is unknown, we have to use the feature interaction method to select the correlated features and exclude uncorrelated features. The current state-of-the-art methods employ various methods based on feature interaction to predict advertisement Click-Through Rate (CTR); however, the feature interaction based on potential new feature mining is rarely considered, which can provide effective assistance for feature interaction. This motivates us to investigate methods that combine potential new features and feature interactions. Thus, we propose a potential feature excitation learning network (PeNet), which is a neural network model based on feature combination and feature interaction. In PeNet, we treat the row compression and column compression of the original feature matrix as potential new features, and proposed the excitation learning mechanism that is a weighted mechanism based on residual principle. Through this excitation learning mechanism, the original embedded features and potential new features are subjected to weighted interaction based on the residual principle. Moreover, a deep neural network is exploited to iteratively learn and iteratively combine features. The excitation learning structure of PeNet neural network is well demonstrated in this paper, that is, the control flow of embedding, compression, excitation and output, which further strengthens the correlated features and weakens the uncorrelated features by compressing and expanding the features. Experimental results on multiple benchmark datasets indicate the PeNet as a general-purpose plug-in has more superior performance and better efficiency than previous state-of-the-art methods.

Comprehensive view of macrophage autophagy and its application in cardiovascular diseases.

Cardiovascular diseases (CVDs) are the primary drivers of the growing public health epidemic and the leading cause of premature mortality and economic burden worldwide. With decades of research, CVDs have been proven to be associated with the dysregulation of the inflammatory response, with macrophages playing imperative roles in influencing the prognosis of CVDs. Autophagy is a conserved pathway that maintains cellular functions. Emerging evidence has revealed an intrinsic connection between autophagy and macrophage functions. This review focuses on the role and underlying mechanisms of autophagy-mediated regulation of macrophage plasticity in polarization, inflammasome activation, cytokine secretion, metabolism, phagocytosis, and the number of macrophages. In addition, autophagy has been shown to connect macrophages and heart cells. It is attributed to specific substrate degradation or signalling pathway activation by autophagy-related proteins. Referring to the latest reports, applications targeting macrophage autophagy have been discussed in CVDs, such as atherosclerosis, myocardial infarction, heart failure, and myocarditis. This review describes a novel approach for future CVD therapies.

The hippo kinases MST1/2 in cardiovascular and metabolic diseases: A promising therapeutic target option for pharmacotherapy.

Cardiovascular diseases (CVDs) and metabolic disorders are major components of noncommunicable diseases, causing an enormous health and economic burden worldwide. There are common risk factors and developmental mechanisms among them, indicating the far-reaching significance in exploring the corresponding therapeutic targets. MST1/2 kinases are well-established proapoptotic effectors that also bidirectionally regulate autophagic activity. Recent studies have demonstrated that MST1/2 influence the outcome of cardiovascular and metabolic diseases by regulating immune inflammation. In addition, drug development against them is in full swing. In this review, we mainly describe the roles and mechanisms of MST1/2 in apoptosis and autophagy in cardiovascular and metabolic events as well as emphasis on the existing evidence for their involvement in immune inflammation. Moreover, we summarize the latest progress of pharmacotherapy targeting MST1/2 and propose a new mode of drug combination therapy, which may be beneficial to seek more effective strategies to prevent and treat CVDs and metabolic disorders.

Glutathione system enhancement for cardiac protection: pharmacological options against oxidative stress and ferroptosis.

The glutathione (GSH) system is considered to be one of the most powerful endogenous antioxidant systems in the cardiovascular system due to its key contribution to detoxifying xenobiotics and scavenging overreactive oxygen species (ROS). Numerous investigations have suggested that disruption of the GSH system is a critical element in the pathogenesis of myocardial injury. Meanwhile, a newly proposed type of cell death, ferroptosis, has been demonstrated to be closely related to the GSH system, which affects the process and outcome of myocardial injury. Moreover, in facing various pathological challenges, the mammalian heart, which possesses high levels of mitochondria and weak antioxidant capacity, is susceptible to oxidant production and oxidative damage. Therefore, targeted enhancement of the GSH system along with prevention of ferroptosis in the myocardium is a promising therapeutic strategy. In this review, we first systematically describe the physiological functions and anabolism of the GSH system, as well as its effects on cardiac injury. Then, we discuss the relationship between the GSH system and ferroptosis in myocardial injury. Moreover, a comprehensive summary of the activation strategies of the GSH system is presented, where we mainly identify several promising herbal monomers, which may provide valuable guidelines for the exploration of new therapeutic approaches.

The Photoperiod Regulates Granulosa Cell Apoptosis through the FSH-Nodal/ALK7 Signaling Pathway in Phodopus sungorus.

The photoperiod regulates the seasonal reproduction of mammals by affecting the follicle development, for which the granulosa cells provide nutrition. However, the underlying mechanism remains unclear. Here, Djungarian hamsters (Phodopus sungorus) were raised under different photoperiods to study the ovarian status and explore the potential mechanism of the follicle development mediated by the FSH-Nodal/ALK7 signaling pathway. Compared with the moderate daylight (MD) group, the short daylight (SD) group exhibited a significant decrease in the ovarian weight and increase in the atretic follicle number and granulosa cell apoptosis, whereas the long daylight (LD) group showed an increase in the ovarian weight, the growing follicle number, and the antral follicle number, but a decrease in the granulosa cell apoptosis. Based on these findings, the key genes of the Nodal/ALK7 signaling pathway controlling the granulosa cell apoptosis were studied using the quantitative real-time polymerase chain reaction and western blotting. In the SD group, the follicle-stimulating hormone (FSH) concentration significantly decreased and the Nodal/ALK7/Smad signaling pathways were activated, while the phosphatidylinositol 3-kinase (PIK3)/Akt signaling pathway was inhibited. The BAX expression was significantly increased, while the Bcl-xL expression was significantly decreased, leading to an increase in the caspase-3 activity, the granulosa cell apoptosis, and ovarian degeneration. However, in the LD group, the FSH concentration significantly increased, the Nodal/ALK7/Smad signaling pathway was inhibited, and the PIK3/Akt signaling pathway was activated. Taken together, our results indicate that the photoperiod can regulate the apoptosis of the granulosa cells by regulating the concentration of FSH, activating or inhibiting the Nodal/ALK7 signaling pathway, thereby affecting the ovarian function. Our research provides an important theoretical basis for understanding the photoperiod-regulated mechanisms of the mammalian seasonal reproduction.

Littrow 3D measurement based on 2D grating dual-channel equal-optical path interference.

We propose a 3D measurement method based on 2D grating dual-channel and Littrow equal-optical path incidence to detect the 3D displacement of a 2D grating in the X-, Y-, and Z-directions. The 2D grating is combined with the Littrow incidence method and a turning element to cause the Littrow diffracted light with frequency f1 to interfere with the reference light at frequency f2, and the displacement data in the X-, Y-, and Z-directions are obtained using the separation-dual-channel phase decoupling algorithm. A corresponding test experimental platform is constructed, and linear error evaluation and step error evaluation experiments are performed to determine the displacements in the X-, Y-, and Z-directions. The results obtained show that all linearity errors are within ±60 nm in the 10 mm measurement ranges in the X-, Y-, and Z-directions, and the test resolution is within ±5 nm. The proposed method can thus realize nanoscale synchronous measurement of X-, Y-, and Z-direction 3D displacements.

Comprehensive overview of Nrf2-related epigenetic regulations involved in ischemia-reperfusion injury.

Ischemic disease is a class of diseases in which an organ is ischemic due to vascular occlusion, a major contributor to death and disability worldwide. However, when the blood flow is restored, more severe damage occurs than ischemia alone and is known as ischemic-reperfusion injury (IRI). During reperfusion, the imbalance between the production of reactive oxygen species (ROS) and buffering capacity of the antioxidant defense system results in cell damage and death. Nuclear factor E2-related factor 2 (Nrf2) significantly affects antioxidant stress damage. The function of Nrf2 in the pathological process of IRI has been widely discussed, but the impact of epigenetic modifications associated with Nrf2 remains unclear. This article provides a comprehensive overview of the role and mechanism of Nrf2-related epigenetic modifications in the IRI of various organs, including the brain, heart, liver, and kidney. In addition, we summarize agonists that may target epigenetic regulation of Nrf2, which may be beneficial in seeking more effective strategies to improve IRI.

Grating-based 2D displacement measurement with quadruple optical subdivision of a single incident beam.

We propose a new symmetrical heterodyne grating displacement measurement method, based on 2D grating and single diffraction quadruple subdivision method. Using a dual-frequency laser with a wavelength of 632.8 nm, output power of 2.2 mW, and a 1200 l/mm 2D grating, eight diffracted light beams interfere in pairs in the X and Y directions through a turning element. The detection system's measurement accuracy was assessed experimentally. The system measurement resolution in the X and Y directions is better than 3 nm; the grating displacement measurement errors within a 10 mm range are better than ±30 nm and ±40 nm, and the repeatability error is better than ±25 nm. The method is not only applicable to nanoscale 2D displacement measurement technology but also can be used for ultra-precision positioning and ultra-precision processing, with the potential for picometer-level improvement.

Quantitative proteomic analysis of glycosylated proteins enriched from urine samples with magnetic ConA nanoparticles identifies potential biomarkers for small cell lung cancer.

Lung cancer has high morbidity and mortality and small cell lung cancer (SCLC) is a highly invasive malignant tumor with a very unfavorable survival rate. Early diagnosis and treatment can result in better prognosis for the SCLC patients but current diagnostic methods are either invasive or incapable for large-scale screen. Therefore, discovering biomarkers for early diagnosis of SCLC is of importance. In this work, we covalently coupled Concanavalin A (ConA) to functionalized magnetic nanoparticles to obtain magnetic ConA-nanoparticles (ConA-NPs) for the enrichment of glycosylated proteins. We then purified glycosylated proteins in 36 urine samples from 9 healthy controls, 9 SCLC patients, 9 lung adenocarcinoma (LUAD) patients, and 9 lung squamous cell carcinoma (LUSC) patients. The purified glycosylated proteins were digested and analyzed by LC-MS/MS for identification and quantification. Among the 398 identified proteins, 20, 15, and 1 glycosylated protein(s), respectively, were upregulated in the urine of SCLC, LUAD, and LUSC patients. Immunoblotting experiments further demonstrated that cathepsin C and transferrin were significantly upregulated in the ConA-NP purified urine of SCLC patients. This work suggests that glycosylated cathepsin C and transferrin might be able to serve as potential biomarkers for the noninvasive diagnosis of SCLC patients.

An Approach to Dynamic Sensing Data Fusion.

For the research and development of sensor systems, the collection and fusion of sensing data is the core. In order to make sensor data acquisition change with the change in environment, a dynamic data acquisition and fusion method based on feedback control is proposed in this paper. According to the sensing data acquisition and fusion model, the optimal acquisition of sensor data is achieved through real-time dynamic judgment of the collected data, decision-making of the next acquisition time interval, and adjustment. This model enables the sensor system to adapt to different environments. An experimental study of the proposed model was carried out on an experimental platform, and the results show that the proposed model can not only reflect the change in sensing data but also improve the transmission efficiency.

State-dependent switching control of switched positive fractional-order systems.

In this paper, the problem of switching stabilization for a class of continuous-time switched positive fractional-order systems is studied by using state-dependent switching. First, the asymptotic stability condition of switched positive fractional-order systems with state-dependent switching is given, which is based on the fractional co-positive Lyapunov method. Moreover, by the sliding sector method, the stability condition of switched positive fractional-order systems whose subsystems are possibly all unstable is obtained. A variable structure (VS) switching law with sliding sector is also proposed to guarantee the switched positive fractional-order system to be asymptotically stable. Finally, two numerical examples are given to demonstrate the advantages and effectiveness of our developed results.

Stabilization for a Class of Switched Nonlinear Systems With Novel Average Dwell Time Switching by T-S Fuzzy Modeling.

In this paper, the problem of switching stabilization for a class of switched nonlinear systems is studied by using average dwell time (ADT) switching, where the subsystems are possibly all unstable. First, a new concept of ADT is given, which is different from the traditional definition of ADT. Based on the new proposed switching signals, a sufficient condition of stabilization for switched nonlinear systems with unstable subsystems is derived. Then, the T-S fuzzy modeling approach is applied to represent the underlying nonlinear system to make the obtained condition easily verified. A novel multiple quadratic Lyapunov function approach is also proposed, by which some conditions are provided in terms of a set of linear matrix inequalities to guarantee the derived T-S fuzzy system to be asymptotically stable. Finally, a numerical example is given to demonstrate the effectiveness of our developed results.