Month: April 2024

Abstract

Background

Myocardial infarction (MI), a representative form of ischemic heart disease, remains a huge burden worldwide. This study aimed to explore whether extracellular vesicles (EVs) secreted from hyaluronic acid (HA)-primed induced mesenchymal stem cells (HA-iMSC-EVs) could enhance the cardiac repair after MI.

Results

HA-iMSC-EVs showed typical characteristics for EVs such as morphology, size, and marker proteins expression. Compared with iMSC-EVs, HA-iMSC-EVs showed enhanced tube formation and survival against oxidative stress in endothelial cells, while reduced reactive oxygen species (ROS) generation in cardiomyocytes. In THP-1 macrophages, both types of EVs markedly reduced the expression of pro-inflammatory signaling players, whereas HA-iMSC-EVs were more potent in augmenting anti-inflammatory markers. A significant decrease of inflammasome proteins was observed in HA-iMSC-EV-treated THP-1. Further, phospho-SMAD2 as well as fibrosis markers in TGF-β1-stimulated cardiomyocytes were reduced in HA-iMSC-EVs treatment. Proteomic data showed that HA-iMSC-EVs were enriched with multiple pathways including immunity, extracellular matrix organization, angiogenesis, and cell cycle. The localization of HA-iMSC-EVs in myocardium was confirmed after delivery by either intravenous or intramyocardial route, with the latter increased intensity. Echocardiography revealed that intramyocardial HA-iMSC-EVs injections improved cardiac function and reduced adverse cardiac remodeling and necrotic size in MI heart. Histologically, MI hearts receiving HA-iMSC-EVs had increased capillary density and viable myocardium, while showed reduced fibrosis.

Conclusions

Our results suggest that HA-iMSC-EVs improve cardiac function by augmenting vessel growth, while reducing ROS generation, inflammation, and fibrosis in MI heart.

Graphical Abstract

Abstract

Every nation treasures its handloom heritage, and in India, the handloom industry safeguards cultural traditions, sustains millions of artisans, and preserves ancient weaving techniques. To protect this legacy, a critical need arises to distinguish genuine handloom products, exemplified by the renowned “gamucha” from India’s northeast, from counterfeit powerloom imitations. Our study’s objective is to create an AI tool for effortless detection of authentic handloom items amidst a sea of fakes. Six deep learning architectures—VGG16, VGG19, ResNet50, InceptionV3, InceptionResNetV2, and DenseNet201—were trained on annotated image repositories of handloom and powerloom towels (17,484 images in total, with 14,020 for training and 3464 for validation). A novel deep learning model was also proposed. Despite respectable training accuracies, the pre-trained models exhibited lower performance on the validation dataset compared to our novel model. The proposed model outperformed pre-trained models, demonstrating superior validation accuracy, lower validation loss, computational efficiency, and adaptability to the specific classification problem. Notably, the existing models showed challenges in generalizing to unseen data and raised concerns about practical deployment due to computational expenses. This study pioneers a computer-assisted approach for automated differentiation between authentic handwoven “gamucha”s and counterfeit powerloom imitations—a groundbreaking recognition method. The methodology presented not only holds scalability potential and opportunities for accuracy improvement but also suggests broader applications across diverse fabric products.

Abstract

Questions surrounding the kind of foreign direct investment that Pakistan attracts become important, especially with the unending debates that such investment can pose environmental challenges for the nation in particular and the world at large. While investment inflows are a prerequisite for economic growth, the environmental consequences are also vital for the quality of life of citizens. This study thus contributes to the debate on the trade-off between cross-border investment flows and environmental status in Pakistan, using annual time-series data spanning 1971–2018. The dynamic connection between foreign direct investment and ecological efficiency is scrutinized while controlling for the effects of environmental determinants—financial integration, economic growth, energy intensity and international trade—by employing dynamic autoregressive distributed lag simulations. The estimated elasticities as well as the counterfactual simulations show that even if ecological efficiency is used as the alternative measure of environmental performance within a dynamic framework, the pollution haven hypothesis still holds in Pakistan. Moroever, while economic growth, financial integration and international trade promote ecological efficiency, energy intensity condenses it. The robustness checks conducted using multivariate Quantle and Quantitle-on-Quantile Regressions also provide similar outcomes to that of the dynamic autoregressive distributed lag simulations.

Abstract

The new permanent seismic station SVZ started working in Arctic (Severnaya Zemlya archipelago, Bolshevik Island), we discuss the first results of the local seismicity study. We have processed 46 local seismic events for 2017–2022. Data processing using a single seismic sensor is difficult, but using waveforms and spectral-temporal analysis of P, S, and surface waves, it is possible to separate shallow earthquakes from glacial events. We distinguish two types of icequakes—glacier-related events and pulses. An increase in seismic background noise is related to processes of glacial nature in summertime. Data processing allows to obtain the main peculiarities of local seismicity, i.e., mutual connection of glacial processes and crustal seismicity. We show the presence of icequakes induced by local crustal events; their epicenters confined to the ice domes edges. Spatio-temporal sequence and the rate of events migration show that the glacial events are a result of the defusing deformations process in the glaciers caused by the impact of shallow tectonic earthquakes. Thousands of pulsed and high-frequency micro-oscillations associate with the sea ice sheet or lake ice. The temporal variation of events’ number and energy per day correlates with air temperature temporal variations. Moreover, there is a sharp increase in the number of pulses with sharp temperature changes. The greatest activity of this pulsed events is in winter and especially in March, connected with ice surface destruction. In case a network deployment is not feasible, even a single seismic station allows to get a useful information about the glacial and seismic processes.

Abstract

Fluorescence imaging in the second near-infrared (NIR-II) window enables deep-tissue imaging with high resolution and improved contrast by taking advantage of the reduced light scattering and tissue autofluorescence in this region of the spectrum. NIR-II fluorescence imaging uses photoluminescent contrast agents — including carbon nanotubes, quantum dots, rare earth-doped nanocrystals, gold nanoclusters, small molecules and their aggregates — and fluorescent proteins, which all exhibit fluorescence in the 1,000–3,000 nm range. After administration of these fluorophores in vivo, live animals can be imaged with specialized detectors and optical instruments, yielding images with contrast and resolution unparalleled by conventional visible and near-infrared fluorescence imaging. This powerful approach enables dynamic imaging of vascular structures and haemodynamics; molecular imaging and image-guided surgery of tumours; and visualization of deep-seated structures, such as the gastrointestinal system. NIR-II fluorescence imaging has revolutionized biomedical imaging over the past 15 years and is poised to make comparable advancements in cardiology, neurobiology and gastroenterology. This Primer describes the principles of NIR-II fluorescence imaging, reviews the most used fluorophores, outlines implementation approaches and discusses specific scientific and clinical applications. Furthermore, the limitations of NIR-II fluorescence imaging are addressed and future opportunities across various scientific domains are explored.

Abstract

The article proposes the concept of “labor border” to explore the evolution of migration policies in the Central America-Mexico-USA region by investigating the dimension of work, through two case studies: (1) the US H-2A program for the temporary recruitment of foreign agricultural workers from Mexico; and subsequently (2) the Mexican regularization programs with temporary labor opportunity, implemented by the Mexican government in the context of the so-called “Central American exodus”: Social Emergency Program (Programa de Emergencia Social) and Sowing Life (Sembrando Vida). The objective of the research is to analyze how the political use of a labor border contributes to the social construction of a hierarchy of immigrant workers, as well as to the progressive closure of borders, and the outsourcing of control operations by the USA to the south of Mexico and other Central American countries. The research took place between March 2016 and December 2021, with a combination of mainly qualitative methodologies.

Abstract

Policymakers increasingly use capital control policies (i.e., capital flow management) to manage capital flows. However, whether the implementation of such policies can effectively affect housing prices and to what extent is less discussed. In this paper, I study the effects of four types of granular capital control policies on housing prices using a large cross-country panel of 53 economies from 1995 to 2017. I find that the estimated effects of capital controls are distinct for different capital flow types and flow directions, but all capital control inflow indices appear to reduce housing prices in the long-run. Additionally, I find that capital controls have asymmetric effects on housing prices for advanced economies and emerging markets. The negative effects of capital controls on housing prices are mainly driven by pre-crisis subsample, which means capital controls have been in effect several times before the Global Financial Crisis. I also estimate the effects for boom and slump periods respectively and find that capital control policies are implemented in an acyclical way. Since there exists endogeneity for capital control on real estate transactions, I further use IPWRA method to rebalance capital control actions and find that IPWRA estimators can weaken the negative effects on housing prices, and the attenuation effects can be attributed to endogenous factors.

Abstract

The metal inert gas (MIG) technique plays a vital role in enhancing the durability and lifespan of 20 steel under harsh operating conditions across various industries. A strong bond is crucial for preventing joint separation. Fe-based materials with appropriate Cr/C exhibit high compatibility with carbon steel bonding. Solid solutions can improve the situation faced by MIG-treated joints. In this work, weld joints were manufactured by MIG, and half of them were treated with a solid solution, and. after the analysis of microstructure and properties, it was found that the untreated fused zone (FZ) showed good forming quality with martensite, retained austenite, and had a carbide microstructure. The solid solution eliminated the retained austenite and exhibited an even hardness. The untreated heat-affected zone had a complex microstructure, dominating upper bainite, and discrepancy-shape ferrite. The untreated group's base material (BM) consisted of grain boundary martensite, ferrite, and pearlite in a matrix, while the solid-solution group's hardness was similar. Tensile tests revealed that the untreated group had a yield strength of 639 MPa, while the solid solution group gained 339 MPa. The untreated group in BM fractures was caused by grain boundary martensite, while the solid-solution group in FZ fractures was caused by α′ and carbides.