Intestinal microbiota and gene expression alterations in leopard coral grouper (Plectropomus leopardus) under enteritis.

Enteritis poses a significant threat to fish farming, characterized by symptoms of intestinal and hepatic inflammation, physiological dysfunction, and dysbiosis. Focused on the leopard coral grouper (Plectropomus leopardus) with an enteritis outbreak on a South China Sea farm, our prior scrutiny did not find any abnormalities in feeding or conventional water quality factors, nor were any specific pathogen infections related to enteritis identified. This study further elucidates their intestinal flora alterations, host responses, and their interactions to uncover the underlying pathogenetic mechanisms and facilitate effective prevention and management strategies. Enteritis-affected fish exhibited substantial differences in intestinal flora compared to control fish (P = 0.001). Notably, norank_f_Alcaligenaceae, which has a negative impact on fish health, predominated in enteritis-affected fish (91.76 %), while the probiotic genus Lactococcus dominated in controls (93.90 %). Additionally, certain genera with pathogenesis potentials like Achromobacter, Sphingomonas, and Streptococcus were more abundant in diseased fish, whereas Enterococcus and Clostridium_sensu_stricto with probiotic potentials were enriched in control fish. At the transcriptomic level, strong inflammatory responses, accompanied by impaired metabolic functions, tissue damage, and iron death signaling activation were observed in the intestines and liver during enteritis. Furthermore, correlation analysis highlighted that potential pathogen groups were positively associated with inflammation and tissue damage genes while presenting negatively correlated with metabolic function-related genes. In conclusion, dysbiosis in the intestinal microbiome, particularly an aberrantly high abundance of Alcaligenaceae with pathogenic potential may be the main trigger for this enteritis outbreak. Alcaligenaceae alongside Achromobacter, Sphingomonas, and Streptococcus emerged as biomarkers for enteritis, whereas some species of Lactococcus, Clostridium_sensu_stricto, and Enterococcus showed promise as probiotics to alleviate enteritis symptoms. These findings enhance our understanding of enteritis pathogenesis, highlight intestinal microbiota shifts in leopard coral grouper, and propose biomarkers for monitoring, probiotic selection, and enteritis management.

EFNet: enhancing feature information for 3D object detection in LiDAR point clouds.

With the development of autonomous driving, there has been considerable attention on 3D object detection using LiDAR. Pillar-based LiDAR point cloud detection algorithms are extensively employed in the industry due to their simple structure and high real-time performance. Nevertheless, the pillar-based detection network suffers from significant loss of 3D coordinate information during the feature degradation and extraction process. In the paper, we introduce a novel framework with high performance, termed EFNet. The EFNet uses the Enhancing Pillar Feature Module (EPFM) to provide more accurate representations of features from two directions: pillar internal space and pillar external space. Additionally, the Head Up Module (HUM) is utilized in the detection head to integrate multi-scale information and enhance the network's information perception ability. The EFNet achieves impressive results on the nuScenes datasets, namely, 53.3% NDS and 42.4% mAP. Compared to the baseline PointPillars, EFNet improves 8% NDS and 11.9% mAP. The results demonstrate that the proposed framework can effectively improve the network's accuracy while ensuring deployability.

Synthesis and delivery of Streptococcus pneumoniae capsular polysaccharides by recombinant attenuated Salmonella vaccines.

Streptococcus pneumoniae capsular polysaccharides (CPSs) are major determinants of bacterial pathogenicity. CPSs of different serotypes form the main components of the pneumococcal vaccines Pneumovax, Prevnar7, and Prevnar13, which substantially reduced the S. pneumoniae disease burden in developed countries. However, the laborious production processes of traditional polysaccharide-based vaccines have raised the cost of the vaccines and limited their impact in developing countries. The aim of this study is to develop a kind of low-cost live vaccine based on using the recombinant attenuated Salmonella vaccine (RASV) system to protect against pneumococcal infections. We cloned genes for seven different serotypes of CPSs to be expressed by the RASV strain. Oral immunization of mice with the RASV-CPS strains elicited robust Th1 biased adaptive immune responses. All the CPS-specific antisera mediated opsonophagocytic killing of the corresponding serotype of S. pneumoniae in vitro. The RASV-CPS2 and RASV-CPS3 strains provided efficient protection of mice against challenge infections with either S. pneumoniae strain D39 or WU2. Synthesis and delivery of S. pneumoniae CPSs using the RASV strains provide an innovative strategy for low-cost pneumococcal vaccine development, production, and use.

TS-LCD: Two-Stage Loop-Closure Detection Based on Heterogeneous Data Fusion.

Loop-closure detection plays a pivotal role in simultaneous localization and mapping (SLAM). It serves to minimize cumulative errors and ensure the overall consistency of the generated map. This paper introduces a multi-sensor fusion-based loop-closure detection scheme (TS-LCD) to address the challenges of low robustness and inaccurate loop-closure detection encountered in single-sensor systems under varying lighting conditions and structurally similar environments. Our method comprises two innovative components: a timestamp synchronization method based on data processing and interpolation, and a two-order loop-closure detection scheme based on the fusion validation of visual and laser loops. Experimental results on the publicly available KITTI dataset reveal that the proposed method outperforms baseline algorithms, achieving a significant average reduction of 2.76% in the trajectory error (TE) and a notable decrease of 1.381 m per 100 m in the relative error (RE). Furthermore, it boosts loop-closure detection efficiency by an average of 15.5%, thereby effectively enhancing the positioning accuracy of odometry.

Cross-and-Diagonal Networks: An Indirect Self-Attention Mechanism for Image Classification.

In recent years, computer vision has witnessed remarkable advancements in image classification, specifically in the domains of fully convolutional neural networks (FCNs) and self-attention mechanisms. Nevertheless, both approaches exhibit certain limitations. FCNs tend to prioritize local information, potentially overlooking crucial global contexts, whereas self-attention mechanisms are computationally intensive despite their adaptability. In order to surmount these challenges, this paper proposes cross-and-diagonal networks (CDNet), innovative network architecture that adeptly captures global information in images while preserving local details in a more computationally efficient manner. CDNet achieves this by establishing long-range relationships between pixels within an image, enabling the indirect acquisition of contextual information. This inventive indirect self-attention mechanism significantly enhances the network's capacity. In CDNet, a new attention mechanism named "cross and diagonal attention" is proposed. This mechanism adopts an indirect approach by integrating two distinct components, cross attention and diagonal attention. By computing attention in different directions, specifically vertical and diagonal, CDNet effectively establishes remote dependencies among pixels, resulting in improved performance in image classification tasks. Experimental results highlight several advantages of CDNet. Firstly, it introduces an indirect self-attention mechanism that can be effortlessly integrated as a module into any convolutional neural network (CNN). Additionally, the computational cost of the self-attention mechanism has been effectively reduced, resulting in improved overall computational efficiency. Lastly, CDNet attains state-of-the-art performance on three benchmark datasets for similar types of image classification networks. In essence, CDNet addresses the constraints of conventional approaches and provides an efficient and effective solution for capturing global context in image classification tasks.

The fate and prospects of stem cell therapy in the treatment of hypoxic-ischemic encephalopathy.

Hypoxic-ischemic encephalopathy (HIE) is a leading cause of long-term neurological disability in neonates and adults. Despite emerging advances in supportive care, like the most effective approach, hypothermia, poor prognosis has still been present in current clinical treatment for HIE. Stem cell therapy has been adopted for treating cerebral ischemia in preclinical and clinical trials, displaying its promising therapeutic value. At present, reported treatments for stroke employed stem cells to replace the lost neurons and integrate them into the existing host circuitry, promoting the release of growth factors to support and stimulate endogenous repair processes and so on. In this review, a meaningful overview to numerous studies published up to now was presented by introducing the preclinical and clinical research status of stem cell therapy for cerebral ischemia and hypoxia, discussing potential therapeutic mechanisms of stem cell transplantation for curing HI-induced brain injury, summarizing a series of approaches for marking transplanted cells and existing imaging systems for stem cell labelling and in vivo tracking and expounding the endogenous regeneration capability of stem cells in the newborn brain when subjected to an HI insult. Additionally, it is promising to combine stem therapy with neuromodulation through specific regulation of neural circuits. The crucial neural circuits across different brain areas related to functional recovery are of great significance for the application of neuromodulation strategies after the occurrence of neonatal hypoxic-ischemic encephalopathy (NHIE).

AAGAB is an assembly chaperone regulating AP1 and AP2 clathrin adaptors.

Multimeric cargo adaptors such as AP2 play central roles in intracellular membrane trafficking. We recently discovered that the assembly of the AP2 adaptor complex, a key player in clathrin-mediated endocytosis, is a highly organized process controlled by alpha- and gamma-adaptin-binding protein (AAGAB, also known as p34). In this study, we demonstrate that besides AP2, AAGAB also regulates the assembly of AP1, a cargo adaptor involved in clathrin-mediated transport between the trans-Golgi network and the endosome. However, AAGAB is not involved in the formation of other adaptor complexes, including AP3. AAGAB promotes AP1 assembly by binding and stabilizing the γ and σ subunits of AP1, and its mutation abolishes AP1 assembly and disrupts AP1-mediated cargo trafficking. Comparative proteomic analyses indicate that AAGAB mutation massively alters surface protein homeostasis, and its loss-of-function phenotypes reflect the synergistic effects of AP1 and AP2 deficiency. Taken together, these findings establish AAGAB as an assembly chaperone for both AP1 and AP2 adaptors and pave the way for understanding the pathogenesis of AAGAB-linked diseases.

Engineered Bacterial Outer Membrane Vesicles with Lipidated Heterologous Antigen as an Adjuvant-Free Vaccine Platform for Streptococcus suis.

Bacterial outer membrane vesicles (OMVs) are considered a promising vaccine platform for their high built-in adjuvanticity and ability to efficiently induce immune responses. OMVs can be engineered with heterologous antigens based on genetic engineering strategies. However, several critical issues should still be validated, including optimal exposure to the OMV surface, increased production of foreign antigens, nontoxicity, and induction of powerful immune protection. In this study, engineered OMVs with the lipoprotein transport machinery (Lpp) were designed to present SaoA antigen as a vaccine platform against Streptococcus suis. The results suggest that Lpp-SaoA fusions can be delivered on the OMV surface and do not have significant toxicity. Moreover, they can be engineered as lipoprotein and significantly accumulated in OMVs at high levels, thus accounting for nearly 10% of total OMV proteins. Immunization with OMVs containing Lpp-SaoA fusion antigen induced strong specific antibody responses and high levels of cytokines, as well as a balanced Th1/Th2 immune response. Furthermore, the decorated OMV vaccination significantly enhanced microbial clearance in a mouse infection model. It was found that antiserum against lipidated OMVs significantly promoted the opsonophagocytic uptake of S. suis in RAW246.7 macrophages. Lastly, OMVs engineered with Lpp-SaoA induced 100% protection against a challenge with 8× the 50% lethal dose (LD50) of S. suis serotype 2 and 80% protection against a challenge with 16× the LD50 in mice. Altogether, the results of this study provide a promising versatile strategy for the engineering of OMVs and suggest that Lpp-based OMVs may be a universal adjuvant-free vaccine platform for important pathogens. IMPORTANCE Bacterial outer membrane vesicles (OMVs) have become a promising vaccine platform due to their excellent built-in adjuvanticity properties. However, the location and amount of the expression of the heterologous antigen in the OMVs delivered by the genetic engineering strategies should be optimized. In this study, we exploited the lipoprotein transport pathway to engineer OMVs with heterologous antigen. Not only did lapidated heterologous antigen accumulate in the engineered OMV compartment at high levels, but also it was engineered to be delivered on the OMV surface, thus leading to the optimal activation of antigen-specific B cells and T cells. Immunization with engineered OMVs induced a strong antigen-specific antibodies in mice and conferred 100% protection against S. suis challenge. In general, the data of this study provide a versatile strategy for the engineering of OMVs and suggest that OMVs engineered with lipidated heterologous antigens may be a vaccine platform for significant pathogens.

Recombinant-attenuated Salmonella enterica serovar Choleraesuis vector expressing the PlpE protein of Pasteurella multocida protects mice from lethal challenge.

BACKGROUND: Bacterial surface proteins play key roles in pathogenicity and often contribute to microbial adhesion and invasion. Pasteurella lipoprotein E (PlpE), a Pasteurella multocida (P. multocida) surface protein, has recently been identified as a potential vaccine candidate. Live attenuated Salmonella strains have a number of potential advantages as vaccine vectors, including immunization with live vector can mimic natural infections by organisms, lead to the induction of mucosal, humoral, and cellular immune responses. In this study, a previously constructed recombinant attenuated Salmonella Choleraesuis (S. Choleraesuis) vector rSC0016 was used to synthesize and secrete the surface protein PlpE of P. multocida to form the vaccine candidate rSC0016(pS-PlpE). Subsequently, the immunogenicity of S. Choleraesuis rSC0016(pS-PlpE) as an oral vaccine to induce protective immunity against P. multocida in mice was evaluated. RESULTS: After immunization, the recombinant attenuated S. Choleraesuis vector can efficiently delivered P. multocida PlpE protein in vivo and induced a specific immune response against this heterologous antigen in mice. In addition, compared with the inactivated vaccine, empty vector (rSC0016(pYA3493)) and PBS immunized groups, the rSC0016(pS-PlpE) vaccine candidate group induced higher antigen-specific mucosal, humoral and mixed Th1/Th2 cellular immune responses. After intraperitoneal challenge, the rSC0016(pS-PlpE) immunized group had a markedly enhanced survival rate (80%), a better protection efficiency than 60% of the inactivated vaccine group, and significantly reduced tissue damage. CONCLUSIONS: In conclusion, our study found that the rSC0016(pS-PlpE) vaccine candidate provided good protection against challenge with wild-type P. multocida serotype A in a mouse infection model, and may potentially be considered for use as a universal vaccine against multiple serotypes of P. multocida in livestock, including pigs.

LiDAR-camera-system-based unsupervised and weakly supervised 3D object detection.

LiDAR camera systems are now becoming an important part of autonomous driving 3D object detection. Due to limitations in time and resources, only a few critical frames of the synchronized camera data and acquired LiDAR points may be annotated. However, there is still a large amount of unannotated data in practical applications. Therefore, we propose a LiDAR-camera-system-based unsupervised and weakly supervised (LCUW) network as a novel 3D object-detection method. When unannotated data are put into the network, we propose an independent learning mode, which is an unsupervised data preprocessing module. Meanwhile, for detection tasks with high accuracy requirements, we propose an Accompany Construction mode, which is a weakly supervised data preprocessing module that requires only a small amount of annotated data. Then, we generate high-quality training data from the remaining unlabeled data. We also propose a full aggregation bridge block in the feature-extraction part, which uses a stepwise fusion and deepening representation strategy to improve the accuracy. Our comparative, ablation, and runtime test experiments show that the proposed method performs well while advancing the application of LiDAR camera systems.

Optimized dithering approach for 3D shape measurement using a phase-based chaos genetic algorithm.

A binary defocusing method has a significant impact on improving 3D shape measurement quality for digital fringe projector (DFP) techniques. In this paper, an optimization framework using the dithering method is presented. This framework utilizes genetic algorithm and chaos maps to optimize the bidirectional error-diffusion coefficients. It can effectively avoid quantization errors of binary patterns in a specific direction and obtain the fringe patterns with better symmetry and higher quality. In the process of the optimization, chaos initialization algorithms are used to generate a series of bidirectional error-diffusion coefficients as initial individuals. Additionally, mutation factors generated by chaotic maps, compared with the mutation rate, determine whether the individual position will mutate. Both simulations and experiments demonstrate that the proposed algorithm can improve the quality of phase and reconstruction at different defocus levels.

High Intensity Focused Ultrasound Ablation for Patients With Locally Advanced Pancreatic Adenocarcinoma: A Propensity Score-Matching Analysis.

OBJECTIVES: This retrospective study was conducted to assess the efficacy and safety of high intensity focused ultrasound (HIFU) in combination with chemotherapy compared with chemotherapy alone in treating patients with unresectable locally advanced pancreatic cancer (LAPC). METHODS: The data of unresectable LAPC patients who received chemotherapy with or without HIFU ablation were retrieved retrospectively. The overall survival (OS), objective response rate (ORR), cancer antigen 19-9 response rate, and safety were compared between these two groups before and after propensity score matching (PSM). RESULTS: Overall, 254 patients with LAPC were included, of whom 92 underwent HIFU ablation. After PSM to control for potential biases, HIFU was associated with improved OS (12.8 versus 12.2 months, log-rank P = .046), as compared to patients without HIFU ablation. Patients with numeric rating scale (NRS) less than 4, and receiving HIFU ablation were significantly associated with improved OS (adjusted hazard ratio [aHR] = 0.365 [95% confidence interval (CI) = 0.148-0.655], P = .002; aHR = 0.490 [95% CI = 0.250-0.961], P = .038; respectively) by multivariate analyses with the adjustment of age, NRS, and tumor size. ORR was also observed to be higher in HIFU group of 30.0% than in the chemotherapy group of 13.3% (P = .039). No severe adverse events of special interest or HIFU-caused deaths were observed. CONCLUSIONS: Patients with unresectable LAPC who received gemcitabine-based chemotherapy might benefit from additional HIFU ablation.

A Model for Urban Environment Instance Segmentation with Data Fusion.

Fine-grained urban environment instance segmentation is a fundamental and important task in the field of environment perception for autonomous vehicles. To address this goal, a model was designed with LiDAR pointcloud data and camera image data as the subject of study, and the reliability of the model was enhanced using dual fusion at the data level and feature level. By introducing the Markov Random Field algorithm, the Support Vector Machine classification results were optimized according to the spatial contextual linkage while providing the model with the prerequisite of the differentiation of similar but foreign objects, and the object classification and instance segmentation of 3D urban environments were completed by combining the Mean Shift. The dual fusion approach in this paper is a method for the deeper fusion of data from different sources, and the model, designed more accurately, describes the categories of items in the environment with a classification accuracy of 99.3%, and segments the different individuals into groups of the same kind of objects without instance labels. Moreover, our model does not have high computational resource and time cost requirements, and is a lightweight, efficient, and accurate instance segmentation model.

A Novel Vermiculite/TiO2 Composite: Synergistic Mechanism of Enhanced Photocatalysis towards Organic Pollutant Removal.

There has been increasing concern over water pollution, which poses a threat to human life and health. Absorption by low-cost absorbents is considered to be a cost-effective and efficient route. However, the non-reusability of absorbents greatly limits their applications. In this study, a novel vermiculite/TiO2 composite combining the inexpensive absorbent with the commonly used photocatalyst was firstly synthesized via the sol-gel method. On the one hand, the organic pollutants are absorbed by vermiculite and then decomposed through the photocatalysis process, enabling the next round of absorption and creating an absorption-decomposition reusable cycle. On the other hand, the modulation effect of optical and electronic structure on the prepared TiO2 photocatalyst by the vermiculite incorporation could significantly improve the photocatalytic activity and eventually enhance the aforementioned cyclic degradation capacity. The layer-structured vermiculite (Vt) supports a uniform coverage of TiO2 at an optimized ratio, providing an optimal adsorption environment and contact area between the photocatalyst and methylene blue (MB) molecules. Vt/TiO2 heterojunction is formed with Si-O-Ti bonding, at which electrons transfer from Vt to TiO2, enriching electron density in TiO2 and favoring its photocatalytic activity. Furthermore, the incorporation of Vt increases the light absorption of TiO2 in the visible range by narrowing the optical band gap to 1.98 eV, which could promote the generation of photo-excited carriers. In addition, PL measurements revealed that the carrier recombination is substantially suppressed, and the charge separation and migration are greatly enhanced by a factor of 3. As a result, the decomposition rate of MB is substantially increased 5.3-fold, which is ascribed to the synergistic effects of the elevated photocatalysis and the large absorption capacity governed by the chemisorption mechanism of the intra-particle diffusion. These results pave the way for composite design towards efficient, economical, and pragmatic water pollution treatment.

[A research on epilepsy source localization from scalp electroencephalograph based on patient-specific head model and multi-dipole model].

Accurate source localization of the epileptogenic zone (EZ) is the primary condition of surgical removal of EZ. The traditional localization results based on three-dimensional ball model or standard head model may cause errors. This study intended to localize the EZ by using the patient-specific head model and multi-dipole algorithms using spikes during sleep. Then the current density distribution on the cortex was computed and used to construct the phase transfer entropy functional connectivity network between different brain areas to obtain the localization of EZ. The experiment result showed that our improved methods could reach the accuracy of 89.27% and the number of implanted electrodes could be reduced by (19.34 ± 7.15)%. This work can not only improve the accuracy of EZ localization, but also reduce the additional injury and potential risk caused by preoperative examination and surgical operation, and provide a more intuitive and effective reference for neurosurgeons to make surgical plans.

Genetic evidence for an inhibitory role of tomosyn in insulin-stimulated GLUT4 exocytosis.

Exocytosis is a vesicle fusion process driven by soluble N-ethylmaleimide-sensitive factor attachment protein receptors (SNAREs). A classic exocytic pathway is insulin-stimulated translocation of the glucose transporter type 4 (GLUT4) from intracellular vesicles to the plasma membrane in adipocytes and skeletal muscles. The GLUT4 exocytic pathway plays a central role in maintaining blood glucose homeostasis and is compromised in insulin resistance and type 2 diabetes. A candidate regulator of GLUT4 exocytosis is tomosyn, a soluble protein expressed in adipocytes. Tomosyn directly binds to GLUT4 exocytic SNAREs in vitro but its role in GLUT4 exocytosis was unknown. In this work, we used CRISPR-Cas9 genome editing to delete the two tomosyn-encoding genes in adipocytes. We observed that both basal and insulin-stimulated GLUT4 exocytosis was markedly elevated in the double knockout (DKO) cells. By contrast, adipocyte differentiation and insulin signaling remained intact in the DKO adipocytes. In a reconstituted liposome fusion assay, tomosyn inhibited all the SNARE complexes underlying GLUT4 exocytosis. The inhibitory activity of tomosyn was relieved by NSF and α-SNAP, which act in concert to remove tomosyn from GLUT4 exocytic SNAREs. Together, these studies revealed an inhibitory role for tomosyn in insulin-stimulated GLUT4 exocytosis in adipocytes. We suggest that tomosyn-arrested SNAREs represent a reservoir of fusion capacity that could be harnessed to treat patients with insulin resistance and type 2 diabetes.

HA gene amino acid mutations contribute to antigenic variation and immune escape of H9N2 influenza virus.

Based on differences in the amino acid sequence of the protein haemagglutinin (HA), the H9N2 avian influenza virus (H9N2 virus) has been clustered into multiple lineages, and its rapidly ongoing evolution increases the difficulties faced by prevention and control programs. The HA protein, a major antigenic protein, and the amino acid mutations that alter viral antigenicity in particular have always been of interest. Likewise, it has been well documented that some amino acid mutations in HA alter viral antigenicity in the H9N2 virus, but little has been reported regarding how these antibody escape mutations affect antigenic variation. In this study, we were able to identify 15 HA mutations that were potentially relevant to viral antigenic drift, and we also found that a key amino acid mutation, A180V, at position 180 in HA (the numbering for mature H9 HA), the only site of the receptor binding sites that is not conserved, was directly responsible for viral antigenic variation. Moreover, the recombinant virus with alanine to valine substitution at position 180 in HA in the SH/F/98 backbone (rF/HAA180V virus) showed poor cross-reactivity to immune sera from animals immunized with the SH/F/98 (F/98, A180), SD/SS/94 (A180), JS/Y618/12 (T180), and rF/HAA180V (V180) viruses by microneutralization (MN) assay. The A180V substitution in the parent virus caused a significant decrease in cross-MN titres by enhancing the receptor binding activity, but it did not physically prevent antibody (Ab) binding. The strong receptor binding avidity prevented viral release from cells. Moreover, the A180V substitution promoted H9N2 virus escape from an in vitro pAb-neutralizing reaction, which also slightly affected the cross-protection in vivo. Our results suggest that the A180V mutation with a strong receptor binding avidity contributed to the low reactors in MN/HI assays and slightly affected vaccine efficacy but was not directly responsible for immune escape, which suggested that the A180V mutation might play a key role in the process of the adaptive evolution of H9N2 virus.

Salmonella enterica serovar Choleraesuis vector delivering a dual-antigen expression cassette provides mouse cross-protection against Streptococcus suis serotypes 2, 7, 9, and 1/2.

A universal vaccine protecting against multiple serotypes of Streptococcus suis is urgently needed to improve animal welfare and reduce the consumption of antibiotics. In this study, a dual antigen expression cassette consisting of SS2-SaoA and SS9-Eno was delivered by a recombinant Salmonella Choleraesuis vector to form the vaccine candidate rSC0016(pS-SE). SaoA and Eno were simultaneously synthesized in rSC0016(pS-SE) without affecting the colonization of the recombinant vector in the lymphatic system. In addition, the antiserum of mice immunized with rSC0016(pS-SE) produced a broader and potent opsonophagocytic response against multiple serotypes of S. suis. Finally, rSC0016(pS-SE) provided mice with a 100% protection against a lethal dose of parent S. suis serotype 2 and serotype 9, and provided 90% and 80% protection against heterologous S. suis serotype 7 or 1/2. These values were significantly higher than those obtained with rSC0016(pS-SaoA) or rSC0016(pS-Eno). Together, this study serves as a foundation for developing a universal vaccine against multiple serotypes of S. suis.

Fast reconstruction technology of a laser beam spatial transmission characteristic curve.

The traditional multiposition method of the M2 factor measurement system is a good method, but it is relatively time consuming, so it cannot meet the requirements of the transient test of a Gaussian beam. To solve this problem, a quadriwave lateral shearing interferometer and a wavefront construction method based on a difference Zernike polynomial are analyzed. This interferometer uses a special grating to select four replicas of the wavefront, and the interferogram generated by four replicas includes difference wavefront information. Then the difference Zernike polynomial method is used to analyze quadriwave lateral shearing interferograms. The characteristic parameters are obtained after finding the optimal terms of the Zernike polynomials. As a result, the errors of F-number, beam radius, and radius of curvature are 3.7%, 3.8%, and 0.6%, respectively, which verifies this method to calculate parameters of Gaussian beam. In addition, we also find that the shear amount has influence on the reconstructed wavefront. It is showed that as the amount of shear increases from 20 pixels to 90 pixels, the peak-to-valley (P-V) values and RMS values both gradually decrease with a nonlinear relationship, which could be used to decrease the error of wavefront reconstruction further.

Polarized image near-natural color fusion algorithm for target detection.

In some automatic systems, target detection is a common task, and visible images are common sources of raw data. Researchers have confirmed that polarization information highlights manmade targets. We propose an algorithm that fuses polarized and visible images to improve detection accuracy. First, the polarization parameter and visible images are simultaneously converted to the HSV color space. The initial fused image after adjusting the hue and saturation will be transformed into the lab color space. Then, the bisecting k-means algorithm is employed to segment the visible image. The visible and initial images are divided into three types of regions for color transfer in lab color space. Finally, the fused image is transformed back to the RGB color space, and the PolarLITIS data set is applied. The experimental results show that the gradient and contrast of the fused image are improved by 115% and 235.3%, respectively, compared with the visible image, and the final fused image is suitable to view with the naked eye. The proposed algorithm significantly improves accuracy.