Kerrhatcher8416

The Special Issue of "Wheat breeding through genetic and physical mapping" aimed to collect recent advances in research on the genetic and physical mapping of quantitative trait loci (QTLs), candidate genes and regulatory sequences involved in the control of wheat's important agronomic traits, such as grain yield and quality, biotic and abiotic stress resistance [...].Despite a large number of publications on this subject, the pathophysiological mechanisms involved in atrial fibrillation (AF) onset and recurrence are uncertain [...].As a key technology of intelligent transportation systems (ITS), vehicular ad hoc networks (VANETs) have been promising to provide safety and infotainment for drivers and passengers. To support different applications about traffic safety, traffic efficiency, autonomous driving and entertainment, it is important to investigate how to effectively deliver content in VANETs. Since it takes resources such as bandwidth and power for base stations (BSs) or roadside units (RSUs) to deliver content, the optimal pricing strategy for BSs and the optimal caching incentive scheme for RSUs need to be studied. In this paper, a framework of content delivery is proposed first, where each moving vehicle can obtain small-volume content files from either the nearest BS or the nearest RSU according to the competition among them. Then, the profit models for both BSs and RSUs are established based on stochastic geometry and point processes theory. Next, a caching incentive scheme for RSUs based on Stackelberg game is proposed, where both competition sides (i.e., BSs and RSUs) can maximize their own profits. Merbarone mw Besides, a backward introduction method is introduced to solve the Stackelberg equilibrium. Finally, the simulation results demonstrate that BSs can obtain their own optimal pricing strategy for maximizing the profit as well as RSUs can obtain the optimal caching scheme with the maximum profit during the content delivery.This study prognoses the remaining useful life of a turbofan engine using a deep learning model, which is essential for the health management of an engine. The proposed deep learning model affords a significantly improved accuracy by organizing networks with a one-dimensional convolutional neural network, long short-term memory, and bidirectional long short-term memory. In particular, this paper investigates two practical and crucial issues in applying the deep learning model for system prognosis. The first is the requirement of numerous sensors for different components, i.e., the curse of dimensionality. Second, the deep neural network cannot identify the problematic component of the turbofan engine due to its "black box" property. This study thus employs dimensionality reduction and Shapley additive explanation (SHAP) techniques. Dimensionality reduction in the model reduces the complexity and prevents overfitting, while maintaining high accuracy. SHAP analyzes and visualizes the black box to identify the sensors. The experimental results demonstrate the high accuracy and efficiency of the proposed model with dimensionality reduction and show that SHAP enhances the explainability in a conventional deep learning model for system prognosis.Microfluidic lab-on-a-chip cell culture techniques have been gaining popularity by offering the possibility of reducing the amount of samples and reagents and greater control over cellular microenvironment. Polydimethylsiloxane (PDMS) is the commonly used polymer for microfluidic cell culture devices because of the cheap and easy fabrication techniques, non-toxicity, biocompatibility, high gas permeability, and optical transparency. However, the intrinsic hydrophobic nature of PDMS makes cell seeding challenging when applied on PDMS surface. The hydrophobicity of the PDMS surface also allows the non-specific absorption/adsorption of small molecules and biomolecules that might affect the cellular behaviour and functions. Hydrophilic modification of PDMS surface is indispensable for successful cell seeding. This review collates different techniques with their advantages and disadvantages that have been used to improve PDMS hydrophilicity to facilitate endothelial cells seeding in PDMS devices.The inhalation of metal (including lead) nanoparticles poses a real health issue to people and animals living in polluted and/or industrial areas. In this study, we exposed mice to lead(II) nitrate nanoparticles [Pb(NO3)2 NPs], which represent a highly soluble form of lead, by inhalation. We aimed to uncover the effects of their exposure on individual target organs and to reveal potential variability in the lead clearance. We examined (i) lead biodistribution in target organs using laser ablation and inductively coupled plasma mass spectrometry (LA-ICP-MS) and atomic absorption spectrometry (AAS), (ii) lead effect on histopathological changes and immune cells response in secondary target organs and (iii) the clearance ability of target organs. In the lungs and liver, Pb(NO3)2 NP inhalation induced serious structural changes and their damage was present even after a 5-week clearance period despite the lead having been almost completely eliminated from the tissues. The numbers of macrophages significantly decreased after 11-week Pb(NO3)2 NP inhalation; conversely, abundance of alpha-smooth muscle actin (α-SMA)-positive cells, which are responsible for augmented collagen production, increased in both tissues. Moreover, the expression of nuclear factor κB (NF-κB) and selected cytokines, such as tumor necrosis factor alpha (TNFα), transforming growth factor beta 1 (TGFβ1), interleukin 6(IL-6), IL-1α and IL-1β , displayed a tissue-specific response to lead exposure. In summary, diminished inflammatory response in tissues after Pb(NO3)2 NPs inhalation was associated with prolonged negative effect of lead on tissues, as demonstrated by sustained pathological changes in target organs, even after long clearance period.Macrophages are terminally differentiated innate immune cells. Through their activation, they can be polarized towards the pro-inflammatory M1 type or the wound healing-associated, anti-inflammatory M2 type macrophages. In the tumor microenvironment (TME), M2 is the dominant phenotype and these cells are referred to as tumor-associated macrophages (TAMs). TAMs secrete cytokines and chemokines, exerting an antiapoptotic, proliferative and pro-metastatic effect on the tumor cells. TAMs can be found in many cancers, including chronic lymphocytic leukemia (CLL), where they are called nurse-like cells (NLCs). Despite the generally indolent behavior of CLL, the proportion of treatment-refractory patients is significant. As with the majority of cancers, despite significant recent progress, CLL pathogenesis is poorly understood. The emerging role of the TME in nurturing the neoplastic process warrants the investigation of macrophages as a significant pathogenetic element of tumors. In this paper, we review the current knowledge on the role of stromal macrophages in CLL.