Role of Aquaporin-4 in Airspace-to-Capillary Water Permeability in Intact Mouse Lung Measured by a Novel Gravimetric Method

The mammalian peripheral lung contains at least three aquaporin (AQP) water channels: AQP1 in microvascular endothelia, AQP4 in airway epithelia, and AQP5 in alveolar epithelia. In this study, we determined the role of AQP4 in airspace-to-capillary water transport by comparing water permeability in wild-type mice and transgenic null mice lacking AQP1, AQP4, or AQP1/AQP4 together. An apparatus was constructed to measure lung weight continuously during pulmonary artery perfusion of isolated mouse lungs. Osmotically induced water flux (Jv) between the airspace and capillary compartments was measured from the kinetics of lung weight change in saline-filled lungs in response to changes in perfusate osmolality. Jv in wild-type mice varied linearly with osmotic gradient size (4.4 × 10−5 cm3 s−1 mOsm−1) and was symmetric, independent of perfusate osmolyte size, weakly temperature dependent, and decreased 11-fold by AQP1 deletion. Transcapillary osmotic water permeability was greatly reduced by AQP1 deletion, as measured by the same method except that the airspace saline was replaced by an inert perfluorocarbon. Hydrostatically induced lung edema was characterized by lung weight changes in response to changes in pulmonary arterial inflow or pulmonary venous outflow pressure. At 5 cm H2O outflow pressure, the filtration coefficient was 4.7 cm3 s−1 mOsm−1 and reduced 1.4-fold by AQP1 deletion. To study the role of AQP4 in lung water transport, AQP1/AQP4 double knockout mice were generated by crossbreeding of AQP1 and AQP4 null mice. Jv were (cm3 s−1 mOsm−1 × 10−5, SEM, n = 7–12 mice): 3.8 ± 0.4 (wild type), 0.35 ± 0.02 (AQP1 null), 3.7 ± 0.4 (AQP4 null), and 0.25 ± 0.01 (AQP1/AQP4 null). The significant reduction in Pf in AQP1 vs. AQP1/AQP4 null mice was confirmed by an independent pleural surface fluorescence method showing a 1.6 ± 0.2-fold (SEM, five mice) reduced Pf in the AQP1/AQP4 double knockout mice vs. AQP1 null mice. These results establish a simple gravimetric method to quantify osmosis and filtration in intact mouse lung and provide direct evidence for a contribution of the distal airways to airspace-to-capillary water transport

Aquaporin-1 Deficiency Protects Against Myocardial Infarction by Reducing Both Edema and Apoptosis in Mice

Many studies have determined that AQP1 plays an important role in edema formation and resolution in various tissues via water transport across the cell membrane. The aim of this research was to determine both if and how AQP1 is associated with cardiac ischemic injury, particularly the development of edema following myocardial infarction (MI). AQP1+/+ and AQP1−/− mice were used to create the MI model. Under physiological conditions, AQP1−/− mice develop normally; however, in the setting of MI, they exhibit cardioprotective properties, as shown by reduced cardiac infarct size determined via NBT staining, improved cardiac function determined via left ventricular catheter measurements, decreased AQP1-dependent myocardial edema determined via water content assays and decreased apoptosis determined via TUNEL analysis. Cardiac ischemia caused by hypoxia secondary to AQP1 deficiency stabilized the expression of HIF-1α in endothelial cells and subsequently decreased microvascular permeability, resulting in the development of edema. The AQP1-dependent myocardial edema and apoptosis contributed to the development of MI. AQP1 deficiency protected cardiac function from ischemic injury following MI. Furthermore, AQP1 deficiency reduced microvascular permeability via the stabilization of HIF-1α levels in endothelial cells and decreased cellular apoptosis following MI

A Real-time Non-contact Localization Method for Faulty Electric Energy Storage Components using Highly Sensitive Magnetometers

With the wide application of electric energy storage component arrays, such as battery arrays, capacitor arrays, inductor arrays, their potential safety risks have gradually drawn the public attention. However, existing technologies cannot meet the needs of non-contact and real-time diagnosis for faulty components inside these massive arrays. To solve this problem, this paper proposes a new method based on the beamforming spatial filtering algorithm to precisely locate the faulty components within the arrays in real-time. The method uses highly sensitive magnetometers to collect the magnetic signals from energy storage component arrays, without damaging or even contacting any component. The experimental results demonstrate the potential of the proposed method in securing energy storage component arrays. Within an imaging area of 80 mm $\times$ 80 mm, the one faulty component out of nine total components can be localized with an accuracy of 0.72 mm for capacitor arrays and 1.60 mm for battery arrays

Jaceosidin Induces Apoptosis in U87 Glioblastoma Cells through G2/M Phase Arrest

Artemisia argyi is a widely used medicinal plant in China. The present study was designed to identify the bioactive constituents with antiglioma activity from leaves of Artemesia argyi. A bioactivity guided approach based on MTT assay for cells growth inhibition led to the isolation of a flavonoid, “jaceosidin” from ethanol extract of leaves of Artemesia argyi. The growth inhibitory effect of jaceosidin was explored using flow cytometry and Western blot studies. Our results showed that jaceosidin exerts growth inhibitory effect by arresting the cells at G2/M phase and induction of apoptosis. Furthermore, our study revealed that induction of apoptosis was associated with cell cycle arrest at G2/M phase, upregulation of p53 and Bax, decrease in mitochondrial membrane potential, release of cytochrome c, and activation of caspase 3. This mitochondrial-caspase-3-dependent apoptosis pathway was confirmed by pretreatment with caspase 3 inhibitor, Ac-DEVD-CHO. Our findings suggested that jaceosidin induces mitochondrial-caspase-3-dependent apoptosis in U87 cells by arresting the cell cycle at G2/M phase

Identification method for inter-turn faults in transformers based on digital twin concept

A transformer inter-turn fault identification method is proposed based on the digital twin concept to tackle the challenges of high operational complexity and low accuracy associated with traditional transformer fault identification methods. Initially, the Bald Eagle Search algorithm is employed to optimize the critical parameters of the Extreme Learning Machine (ELM), determining the optimal input layer weight and hidden layer threshold of the Extreme Learning Machine. Subsequently, leveraging the digital twin concept, a digital replica of the physical transformer is established, enabling multi-physical field coupling simulation encompassing electrical, thermal, and acoustic domains to elucidate the variation patterns of various physical parameters across different operational scenarios and fault scenarios. Furthermore, key physical characteristic parameters such as sound pressure and winding hot spot temperature are carefully selected to drive a fault identification model tailored to inter-turn faults within the framework of the digital twin concept. Through a detailed investigation using 630 kV A/10 kV transformers as a case study, the results exhibit an impressive fault identification accuracy of 95.24% for the proposed method. Comparative analysis reveals notable enhancements in fault identification accuracy of 12.22%, 7.85%, and 3.73% for ELM, Support Vector Machine and Tuna Swarm Optimization—ELM models, respectively. These findings underscore the effectiveness and practicality of the transformer inter-turn fault identification method based on the digital twin concept, offering valuable insights for the real-time monitoring and diagnosis of inter-turn faults in transformers

Thiazolidinone CFTR inhibitor identified by high-throughput screening blocks cholera toxin–induced intestinal fluid secretion

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Aggregation‐induced emission luminogens for gas sensors

Luminescent chromophores armed with aggregation-induced emission (AIE) characteristics can switch their fluorescence sensing by manipulating the aggregation and disaggregation states, leading to high sensitivity and high signal-to-noise ratio sensors. Accordingly, aggregation-induced emission luminogens (AIEgens) have been widely applied to various biosensing, one of which is the gas sensors. Due to the weak signal, easy diffusion, difficult capture, and instability of gas molecules, electrochemical or infrared tests are generally used for detection. However, electrochemical tests have high power consumption, and the environment easily disturbs infrared tests. Fortunately, photochemical sensors utilizing AIE properties can effectively overcome these deficiencies. AIEgens usually exhibit large Stokes shift, good photostability, and low random blinking, suggesting excellent sensing reproducibility and many achievements have been obtained in AIEgens-based gas sensors. This review summarizes the gas detection mechanism of AIEgens, and enumerate the reported gas sensors based on AIEgens. Then a perspective on the field and challenges facing it are elaborated so that researchers can better understand the development status of this field and develop more AIE-type spectroscopic probes with gas-responsive functions. It is expected to greatly enrich the types of gas sensors and promote the development of the application of AIE properties

Dopamine promotes Klebsiella quasivariicola proliferation and inflammatory response in the presence of macrophages

BackgroundDopamine, a frequently used therapeutic agent for critically ill patients, has been shown to be implicated in clinical infections recently, however, the precise mechanisms underlying this association remain elusive. Klebsiella quasivariicola, a novel strain belonging to the Klebsiella species, exhibits potential pathogenic attributes. The impact of dopamine on K. quasivariicola infection has aroused our interest.ObjectiveConsidering the contribution of host immune factors during infection, this study aimed to investigate the intricate interactions between K. quasivariicola, dopamine, and macrophages were explored.MethodsRAW264.7 cells and C57/BL6 mice were infected with K. quasivariicola, and the bacterial growth within macrophage, the production of inflammatory cytokines and the pathological changes in mice lungs were detected, in the absence or presence of dopamine. ResultsDopamine inhibited the growth of K. quasivariicola in the medium, but promoted bacterial growth when co-cultured with macrophages. The expression of proinflammatory cytokines increased in RAW 264.7 cells infected with K. quasivariicola, and a significant rise was observed upon the addition of dopamine. The infection of K. quasivariicola in mice induced an inflammatory response and lung injury, which were exacerbated by the administration of dopamine. ConclusionsOur findings suggest that dopamine may be one of the potential risk factors associated with K. quasivariicola infection. This empirical insight provides solid references for clinical precision medicine. Furthermore, an in vitro model of microbes-drugs-host immune cells for inhibitor screening was proposed to more accurately replicate the complex in vivo environment. This fundamental work had contributed to the present understanding of the crosstalk between pathogen, dopamine and host immune cells