Characterization and immune role of class B scavenger receptor member 1 in spotted sea bass (Lateolabrax maculatus).

Scavenger receptors (SRs) are integral to the innate immune system and function as pattern-recognition receptors that facilitate pathogen clearance and mediate anti-inflammatory responses. However, the role of SRs in the immune response of Lateolabrax maculatus against Aeromonas veronii is unclear. Here, we cloned scavenger receptor B1 from L. maculatus (LmSRB1) and performed bioinformatics analysis to study its potential functions. The open reading frame spans 1530 base pairs and encodes a 509-amino acid protein with a molecular mass of 57.44 kDa. Comparative analysis revealed high sequence conservation among fish species. Expression profiling revealed strong LmSRB1 transcription in various tissues, especially in head kidney and spleen. Following A. veronii exposure, LmSRB1 expression initially increased, peaking after 4-8 h, with a notable secondary peak at 72 h. Fluorescence in situ hybridization indicated that LmSRB1 mainly localized to the cytoplasm, and subcellular-localization studies confirmed LmSRB1 protein expression in the cytoplasm and cell membrane. Enzyme-linked immunosorbent assay data showed dose-dependent binding of LmSRB1 to A. veronii. Modulating LmSRB1 expression significantly altered the levels of IL-8, IL-1ß, TRAF6, and NIK. These results highlight the crucial role of LmSRB1 in L. maculatus's innate immune response to A. veronii and offer insights into improving the management of bacterial infections in aquaculture.

Asymmetric evolution of ISG15 homologs and the immune adaptation to LBUSV infection in spotted seabass (Lateolabrax maculatus).

The battle between host and viral is ubiquitous across all ecosystems. Despite this, research is scarce on the antiviral characteristics of fish, particularly in those that primarily rely on innate immune responses. This study, comprehensively explored the genetic and antiviral features of ISG15 in spotted seabass, focusing on its response to largemouth bass ulcerative syndrome virus (LBUSV). Through whole-genome BLAST and PCR cloning, two ISG15 homologs, namely LmISG15a and LmISG15b, were identified in spotted seabass, both encoding highly conserved proteins. However, a distinctive contrast emerged in their expression patterns, with LmISG15a exhibiting high expression in immune organs while LmISG15b remained largely silent across various organs. Regulatory elements analysis indicated an asymmetric evolution of the two ISG15s, with the minimal expression of LmISG15b may attribute to the loss of a necessary ISRE and an additional instability "ATTTA" motif. Association analysis demonstrated a significant correlation between LmISG15a expression and LBUSV infection. Subsequent antiviral activity detection revealed that LmISG15a interacted with LBUSV, inhibiting its replication by activating ISGylation and downstream pro-inflammatory mediators. In summary, this study unveils a distinct evolutionary strategy of fish antiviral gene ISG15 and delineates its kinetic characteristics in response to LBUSV infection.

Thymosin beta-4 participate in antibacterial immunity and wound healing in black tiger shrimp, Penaeus monodon.

Thymosin beta-4 (Tß4) is a ubiquitous protein with multiple and diverse intracellular and extracellular functions in vertebrates, which play fundamental roles in innate immune against pathogens and wound healing. In this study, the full-length cDNA of Tß4 was cloned from Penaeus monodon (designated as PmTß4), using the technology of rapid amplification of cDNA ends (RACE). The cDNA of PmTß4 was 1361 bp with an open reading frame (ORF) of 501 bp, which encoding a polypeptide of 166 amino acid. The Quantitative Real-time PCR (qRT-PCR) analysis results showed that PmTß4 was ubiquitously expressed in all the tested shrimp tissues, with the highest expression level was detected in the hemolymph, while the lowest expression level in the muscle. The expression level of PmTß4 was significantly up-regulated in hepatopancreas after challenged by Vibrio parahaemolyticus, Vibrio harveyi and Staphylococcus aureus. In vitro antimicrobial test showed that the recombinant protein of PmTß4 (rPmTß4) had broad-spectrum of antimicrobial activity, which could inhibit both the growth of gram-negative bacteria and gram-positive bacteria, including Vibrio vulnificus, V. parahaemolyticus, Streptococcus agalactiae, S. aureus and Aeromonas hydrophila. Moreover, rPmTß4 had a certain binding ability to different bacteria, and this binding ability exhibits a strong dose-dependent effect. In vivo, PmTß4 could facilitate external bacterial clearance in shrimp, and have beneficial to shrimp survival post V. parahaemolyticus infection. Furthermore, wound-healing assay was carried out to study the role of PmTß4 in the process of wound healing. The results showed that the PmTß4 expression was significantly up-regulated by injury treatment, and exerted positive effects to promote wound healing. In addition, PmTß4 can significantly increase the expression level of superoxide dismutase (SOD) and Catalase (CAT) after injury treatment in shrimp, which would involve in scavenging reactive oxygen species (ROS) caused by the wound. In conclusion, these results indicated that PmTß4 may play important roles in antibacterial immunity and wound healing in Penaeus monodon.

A Multi-Resident Number Estimation Method for Smart Homes.

Population aging requires innovative solutions to increase the quality of life and preserve autonomous and independent living at home. A need of particular significance is the identification of behavioral drifts. A relevant behavioral drift concerns sociality: older people tend to isolate themselves. There is therefore the need to find methodologies to identify if, when, and how long the person is in the company of other people (possibly, also considering the number). The challenge is to address this task in poorly sensorized apartments, with non-intrusive sensors that are typically wireless and can only provide local and simple information. The proposed method addresses technological issues, such as PIR (Passive InfraRed) blind times, topological issues, such as sensor interference due to the inability to separate detection areas, and algorithmic issues. The house is modeled as a graph to constrain transitions between adjacent rooms. Each room is associated with a set of values, for each identified person. These values decay over time and represent the probability that each person is still in the room. Because the used sensors cannot determine the number of people, the approach is based on a multi-branch inference that, over time, differentiates the movements in the apartment and estimates the number of people. The proposed algorithm has been validated with real data obtaining an accuracy of 86.8%.

Real-Time Semantic Segmentation with Dual Encoder and Self-Attention Mechanism for Autonomous Driving.

As the techniques of autonomous driving become increasingly valued and universal, real-time semantic segmentation has become very popular and challenging in the field of deep learning and computer vision in recent years. However, in order to apply the deep learning model to edge devices accompanying sensors on vehicles, we need to design a structure that has the best trade-off between accuracy and inference time. In previous works, several methods sacrificed accuracy to obtain a faster inference time, while others aimed to find the best accuracy under the condition of real time. Nevertheless, the accuracies of previous real-time semantic segmentation methods still have a large gap compared to general semantic segmentation methods. As a result, we propose a network architecture based on a dual encoder and a self-attention mechanism. Compared with preceding works, we achieved a 78.6% mIoU with a speed of 39.4 FPS with a 1024 × 2048 resolution on a Cityscapes test submission.

Music emotion detection using hierarchical sparse kernel machines.

For music emotion detection, this paper presents a music emotion verification system based on hierarchical sparse kernel machines. With the proposed system, we intend to verify if a music clip possesses happiness emotion or not. There are two levels in the hierarchical sparse kernel machines. In the first level, a set of acoustical features are extracted, and principle component analysis (PCA) is implemented to reduce the dimension. The acoustical features are utilized to generate the first-level decision vector, which is a vector with each element being a significant value of an emotion. The significant values of eight main emotional classes are utilized in this paper. To calculate the significant value of an emotion, we construct its 2-class SVM with calm emotion as the global (non-target) side of the SVM. The probability distributions of the adopted acoustical features are calculated and the probability product kernel is applied in the first-level SVMs to obtain first-level decision vector feature. In the second level of the hierarchical system, we merely construct a 2-class relevance vector machine (RVM) with happiness as the target side and other emotions as the background side of the RVM. The first-level decision vector is used as the feature with conventional radial basis function kernel. The happiness verification threshold is built on the probability value. In the experimental results, the detection error tradeoff (DET) curve shows that the proposed system has a good performance on verifying if a music clip reveals happiness emotion.

Emotion identification using extremely low frequency components of speech feature contours.

The investigations of emotional speech identification can be divided into two main parts, features and classifiers. In this paper, how to extract an effective speech feature set for the emotional speech identification is addressed. In our speech feature set, we use not only statistical analysis of frame-based acoustical features, but also the approximated speech feature contours, which are obtained by extracting extremely low frequency components to speech feature contours. Furthermore, principal component analysis (PCA) is applied to the approximated speech feature contours so that an efficient representation of approximated contours can be derived. The proposed speech feature set is fed into support vector machines (SVMs) to perform multiclass emotion identification. The experimental results demonstrate the performance of the proposed system with 82.26% identification rate.

Self-Healing and Recyclable Polyurethane/Nanocellulose Elastomer Based on the Diels-Alder Reaction.

With the background of the fossil fuel energy crisis, the development of self-healing and recyclable polymer materials has become a research hotspot. In this work, a kind of cross-linking agent with pendent furan groups was first prepared and then used to produce the Polyurethane elastomer based on Diels-Alder chemistry (EPU-DA). In addition, in order to further enhance the mechanical properties of the elastomer, cellulose nanofibers (CNFs) were added into the Polyurethane system to prepare a series of composites with various contents of CNF (wt% = 0.1~0.7). Herein, the FTIR and DSC were used to confirm structure and thermal reversible character. The tensile test also indicated that the addition of CNF increased the mechanical properties compared to the pure Polyurethane elastomer. Due to their reversible DA covalent bonds, the elastomer and composites were recycled under high-temperature conditions, which extends Polyurethane elastomers' practical applications. Moreover, damaged coating can also be repaired, endowing this Polyurethane material with good potential for application in the field of metal protection.

Polysaccharides isolated from Bangia fuscopurpurea induce apoptosis and autophagy in human ovarian cancer A2780 cells.

Although ovarian cancer is common, its prognosis remains poor because of drug resistance and early metastasis. Polysaccharides extracted from Bangia fuscopurpurea (BFP) are potential anti-cancer agents, but the mechanisms underlying their effects in human ovarian cancer remain unclear. Here, we investigated the mechanisms of action of BFP polysaccharides in A2780 ovarian cancer cells using cell migration, invasion, apoptosis, and autophagy assays. Transwell assays indicated that BFP inhibited cell migration and invasion. Flow cytometry analysis showed that BFP treatment induced apoptosis and reactive oxygen species production, while significantly reducing mitochondrial membrane potential. Reverse transcription-polymerase chain reaction and Western blot analyses revealed changes in the expression of apoptosis- and autophagy-related cellular mRNAs and proteins, respectively, following BFP treatment for 24 h. Transmission electron microscopy revealed that BFP induced autophagy in A2780 cells. These findings demonstrate that BFP may be useful for developing functional foods for cancer therapy.

Schistosoma egg antigens suppress LPS-induced inflammation in human IMR-90 cells by modulation of JAK/STAT1 signaling.

BACKGROUND: The regulation of the balance between inflammatory and anti-inflammatory events during the treatment of pulmonary infection is very important. Soluble Schistosoma egg antigens (SEA) can effectively inhibit the expression of cytokines during hepatic acute inflammation. However, the mechanisms by which these proteins suppress the inflammatory responses in lung cells remain unclear. The purpose of this study was to investigate the ability of SEA to inhibit pulmonary inflammation. METHODS: The effects of SEA were investigated in LPS-treated lung IMR-90 cells. The involvement of the JAK/STAT-1 signaling pathway in these effects was evaluated by employing CBA assays, quantitative polymerase chain reaction, and western blotting experiments. RESULTS: Pretreatment of IMR-90 cells with appropriate concentrations of SEA protected cells against the cytotoxic effects of LPS-induced inflammation in a time-dependent manner. SEA pretreatment significantly attenuated the LPS-induced activation of the JAK/STAT1 signaling pathway, including the upregulation of JAK1/2 and STAT1, as well as the production of inflammatory cytokines. The level of phosphorylated STAT1 gradually declined in response to increasing concentrations of SEA. Based on these findings, we hypothesize that SEA-induced anti-inflammatory effects initiate with the downregulation of the IFN-γ-JAK-STAT1 signaling pathway, resulting in the attenuation of LPS-induced inflammation in IMR-90 cells. CONCLUSION: Our study is the first to demonstrate the anti-inflammatory activity of SEA in an in vitro model of pulmonary inflammation, involving the modulation of JAK/STAT1 signaling. We propose SEA as potential therapeutic or preventive agents for the selective suppression of STAT1 and the control of inflammatory response in lung IMR-90 cells.