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Near-infrared (NIR) spectroscopy is an effective method for identifying wool and cashmere fibers, with high spectral data providing a wealth of information. However, a key issue is that the accuracy and robustness of subsequent estimates can be reduced by redundant and interfering wavelengths. For this reason, a novel interval-wavelength cascaded optimization method is proposed. Initially, the collected spectral data are preprocessed by standard normal variate transformation (SNV) to eliminate the scattering effect. Then, the backward interval partial least squares (BiPLS) algorithm is applied for the preliminary selection of spectral intervals, followed by the application of three different variable selection algorithms, competitive adaptive reweighted sampling (CARS), successive projection algorithm (SPA) and whale optimization algorithm (WOA), for secondary wavelength optimization, respectively. Finally, both support vector machine (SVM) and random forest (RF) discriminant models are built to identify the extracted subset of wavelengths. In the experimental stage, the cascade method BiPLS-WOA selects 36 wavelengths, in SVM, the accuracy of the validation set reaches 96.9%, and the area under the ROC curve (AUC) can reach 99.3%. The results demonstrate that the proposed method can eliminate redundant and collinear variables, thereby validating the effectiveness of distinguishing wool and cashmere fibers.

Virgin cashmere is highly prized for its superior quality, and chemically modified wool is often used to fake it. However, traditional spectral analysis and image processing methods struggle to identify the two fibers. To address this, combining chemometrics with near-infrared (NIR) spectroscopy is proposed to identify virgin cashmere and chemically modified wool based on fractional order derivatives and improved wavelength extraction algorithm. The original spectra of the two fibers are very close, making identification difficult. Therefore, fractional order derivatives are used to amplify tiny spectral differences, which are often overlooked in conventional analysis. Meanwhile, common wavelength extraction algorithms few consider inherent relationship between spectral features and chemical properties, so an improved wavelength extraction algorithm using Shuffled Frog Leaping Algorithm (SFLA) and Beluga Whale Optimization (BWO) is employed to explore the connection of the two. The proposed method with Partial Least Squares Discriminant Analysis (PLS-DA) achieves an accuracy of 94.4%. Experimental results demonstrate that fractional order derivatives enhance tiny spectral features and differences, while extracted feature wavelengths correspond to main chemical characteristic bands of the fibers. This study shows the feasibility of identifying virgin cashmere and chemically modified wool and offers a novel idea for identifying fibers in the textile industry.

Cashmere and wool fibers have similar chemical compositions, making them difficult to distinguish based on their absorption peaks and band positions in near-infrared spectroscopy. Existing studies commonly use wavelength selection or feature extraction algorithms to obtain significant spectral features, but traditional algorithms often overlook the correlations between wavelengths, resulting in weak adaptability and local optimum issues. To address this problem, this paper proposes a recognition algorithm based on optimal wavelength selection, which can remove redundant information and make the model effective in capturing patterns and key features of the data. The wavelengths are rearranged by computing the information gain ratio for each wavelength. Then, the sorted wavelengths are grouped based on equal density, which ensures that all wavelengths within each group have equal information and avoids over-focusing on individual groups. Meanwhile, the group genetic algorithm is used to find the wavelengths with highly informative and search optimal grouped combinations, in order to explore the entire spectrum wavelength. Finally, combined with a partial least squares discriminant analysis(PLS-DA) model, the recognition accuracy reached 97.3 %. The results indicate that, compared to traditional methods such as CARS, SPA, and GA, our method effectively reduces redundant information, selects fewer but more informative wavelengths, and improves classification accuracy and model adaptability.

【Objective】The global coral reef ecosystem is rapidly degrading due to the combined effects of climate change and human activities, which highlights the need to explore the environmental adaptation mechanisms of corals. The environmental adaptability of coral hosts is closely related to symbiotic Symbiodiniaceae, however, the ecological effects of Symbiodiniaceae driven by seasonal variation still need to be further understood.【Method】An environment-sensitive coral Acropora pruinosa from the Weizhou Island, Beibu Gulf was taken as the research object to carry out fixed-point sampling and environmental data monitoring, and analyze the density, community composition, chlorophyll a concentration and correlation with environmental variables of symbiotic Symbiodiniaceae in four different quarters.【Result】The coral reef area was characterized by high temperature and strong light in summer and low temperature and weak light in winter. The density of Symbiodiniaceae and the concentration of chlorophyll a showed the characteristics of decreasing in summer and increasing in winter. The subclade C1 always occupied the dominant position (79.35%-82.97%), and the relative abundance of background subclades such as C1ca, C1p, C72, and Cspc significantly varied with seasonal variation. There were significant differences in the structure of Symbiodiniaceae communities between summer and winter. The contribution of surface seawater temperature (SST) and photosynthetically active radiation (PAR) to the changes in Symbiodiniaceae community structure was higher than chlorophyll a, Kd490, and particulate organic carbon.【Conclusion】The environmental characteristics of high temperature and strong light in summer and low temperature and weak light in winter on Weizhou Island regulate the seasonal changes of Symbiodiniaceae density and chlorophyll a concentration by affecting the photosynthesis of Symbiodiniaceae. Moreover, the physiological characteristics of the C1 subclade ensure that A. pruinosa can adapt to the environment of Weizhou Island. In addition, the SST and PAR affect the abundance changes of the background Symbiodiniaceae, leading to significant differences in community structure.The correlation analysis showed that the SST and PAR were the main factors driving the changes of density, stable symbiosis (subclade C1), and community structure of Symbiodiniaceae. This study took A. pruinosa as an example to analyze the micro-ecological characteristics of coral-associated Symbiodiniaceae adapting to seasonal variation, providing a new understanding about the adaptation of environment-sensitive corals to environmental changes.

IntroductionListeria monocytogenes is a globally distributed bacterium that exhibits genetic diversity and trait heterogeneity. The alternative sigma factor SigB serves as a crucial transcriptional regulator essential for responding to environmental stress conditions and facilitating host infection.MethodWe employed a comprehensive genetic analysis of sigB in a dataset comprising 46,921 L. monocytogenes genomes. The functional attributes of SigB were evaluated by phenotypic experiments.ResultsOur study revealed the presence of two predominant SigB factors (SigBT1 and SigBT2) in L. monocytogenes, with a robust correlation between SigBT1 and lineages I and III, as well as SigBT2 and lineage II. Furthermore, SigBT1 exhibits superior performance in promoting cellular invasion, cytotoxicity and enhancing biofilm formation and cold tolerance abilities under minimally defined media conditions compared to SigBT2.DiscussionThe functional characteristics of SigBT1 suggest a potential association with the epidemiology of lineages I and III strains in both human hosts and the natural environment. Our findings highlight the important role of distinct SigB factors in influencing the biological traits of L. monocytogenes of different lineages, thus highlighting its distinct pathogenic and adaptive attributes.

Listeria monocytogenes (L. monocytogenes) is a pathogen that is transmitted through contaminated food and causes the illness known as listeriosis. The virulence factor InlA plays a crucial role in the invasion of L. monocytogenes into the human intestinal epithelium. In addition, InlA enhances the pathogenicity of host strains, and different strains of L. monocytogenes contain varying variations of InlA. Our study analyzed a total of 4393 published L. monocytogenes genomes from 511 sequence types (STs) of diverse origins. We identified 300 unique InlA protein sequence types (PSTs) and revealed 45 highly mutated amino acid sites. The leucine-rich repeat (LRR) region was found to be the most conserved among the InlA, while the protein A (PA) region experienced the highest mutation rate. Two new types of mutations were identified in the B-repeat region of InlA. Correspondence analysis (CA) was used to analyze correlations between the lineages or 10 most common sequence types (STs) and amino acid (aa) sites. ST8 was strongly correlated with site 192_F, 454_T. ST7 exhibited a strong correlation with site 51_A, 573_E, 648_S, and 664_A, and it was also associated with ST6 and site 544_N, 671_A, 738_B, 739_B, 740_B, and 774_Y. Additionally, a strong correlation between ST1 and site 142_S, 738_N, ST2 and site 2_K, 142_S, 738_N, as well as ST87 and site2_K, 738_N was demonstrated. Our findings contribute significantly to the understanding of the distribution, composition, and conservation of InlA in L. monocytogenes. These findings also suggest a potential role of InlA in supporting molecular epidemiological tracing efforts.

Microbial distribution patterns are the result of a combination of biotic and abiotic factors, which are the core issues in microbial ecology research. To better understand the biogeographic pattern of bacteria in water environments from the Bohai Sea to the northern Yellow Sea, the effects of environmental factors, and spatial distance on the structure of bacterial communities in marine water were investigated using high-throughput sequencing technology based on 16S rRNA genes. The results showed that Proteobacteria, Bacteroidetes, Actinobacteri, Desulfobacterota, and Bdellovibrionota were the dominant phyla in the study area. A clear spatial pattern in the bacterial community was observed, and environmental factors, including salinity, nutrient concentration, carbon content, total phosphorus, dissolved oxygen, and seawater turbidity emerged as the central environmental factors regulating the variation in bacterial communities. In addition, the study provides direct evidence of the existence of dispersal limitation in this strongly connected marine ecological system. Therefore, these results revealed that the variation in bacterial community characteristics was attributed to environmental selection, accompanied by the regulation of stochastic diffusion. The network analysis demonstrated a nonrandom co-occurrence pattern in the microbial communities with distinct spatial distribution characteristics. It is implied that the biogeography patterns of bacterial community may also be associated with the characteristics of co-occurrence characterize among bacterial species. Furthermore, the PICRUSt analysis indicated a clear spatial distribution of functional characteristics in bacterial communities. This functional variation was significantly modulated by the environmental characteristics of seawater but uncoupled from the taxonomic characteristics of bacterial communities (e.g., diversity characteristics, community structure, and co-occurrence relationships). Together, this findings represent a significant advance in linking seawater to the mechanisms underlying bacterial biogeographic patterns and community assembly, co-occurrence patterns, and ecological functions, providing new insights for identifying the microbial ecology as well as the biogeochemical cycle in the marine environment.

Listeria monocytogenes is an important pathogen that can cause listeriosis. Despite the growing recognition of Listeria spp. as a foodborne and environmental pathogen, the understanding of its prevalence and characteristics of Listeria spp. in the marine environment remains unknown. In this study, we first investigated the genetic and phenotypic characteristics of Listeria species isolated in a coastal city in China. The findings revealed that the sequence type 87 (ST87) L. monocytogenes, a prevalent clinical and seafood strain in China, dominates in recreational beach sands and possesses a notable biofilm-forming capacity in seawater. The presence of ST87 L. monocytogenes in coastal environments indicates the potential health risks for both recreational activities and seafood consumption. Moreover, the ST121 isolates from sand had a versatile plasmid encoding multifunctional genes, including uvrX for UV resistance, gbuC for salt resistance, and npx for oxidative resistance and multiple transposases, which potentially aid in survival under natural environments. Black-headed gulls potentially facilitate the spread of L. monocytogenes, with similar ST35 strains found in gulls and beach sand. As a reservoir of microbes from marine environments and human/animal excrement, coastal sand would play an important role in the spread of L. monocytogenes and is an environmental risk for human listeriosis.

An image edge detection algorithm using multi-directional and multi-scale Gabor filters is proposed in this paper. The main merit of this method is that high edge detection accuracy can be obtained while maintaining noise robustness. The approach proposed in this paper consists of three procedures: firstly, the transformation to the CIE L*a*b* color space, which has a wide shading area and uniform distribution; secondly, under different scales, the edge feature information of the image is extracted from several different directions by Gabor filters, and a new edge strength map is obtained by feature fusion; thirdly, the new fused edge strength map is enhanced with local features, and a noise-resistant image edge detector is obtained under a novel hysteresis threshold calculation. The experiments illustrate that, compared to the methods involved, the designed edge detector outperforms by about 2% to 4%, and also shows competitive performance regarding the ability to handle noise.

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a public health emergency of international concern, and an effective vaccine is urgently needed to control the pandemic. Envelope (E) and membrane (M) proteins are highly conserved structural proteins among SARS-CoV-2 and SARS-CoV and have been proposed as potential targets for the development of cross-protective vaccines. Here, synthetic DNA vaccines encoding SARS-CoV-2 E/M proteins (called p-SARS-CoV-2-E/M) were developed, and mice were immunised with three doses via intramuscular injection and electroporation. Significant cellular immune responses were elicited, whereas no robust humoral immunity was detected. In addition, novel H-2d-restricted T-cell epitopes were identified. Notably, although no drop in lung tissue virus titre was detected in DNA-vaccinated mice post-challenge with SARS-CoV-2, immunisation with either p-SARS-CoV-2-E or p-SARS-CoV-2-M provided minor protection and co-immunisation with p-SARS-CoV-2-E+M increased protection. Therefore, E/M proteins should be considered as vaccine candidates as they may be valuable in the optimisation of vaccination strategies against COVID-19.

The emergence of new variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has generated recurring worldwide infection outbreaks. These highly mutated variants reduce the effectiveness of current coronavirus disease 2019 (COVID-19) vaccines, which are designed to target only the spike (S) protein of the original virus. Except for the S of SARS-CoV-2, the immunoprotective potential of other structural proteins (nucleocapsid, N; envelope, E; membrane, M) as vaccine target antigens is still unclear and worthy of investigation. In this study, synthetic DNA vaccines encoding four SARS-CoV-2 structural proteins (pS, pN, pE, and pM) were developed, and mice were immunized with three doses via intramuscular injection and electroporation. Notably, co-immunization with two DNA vaccines that expressed the S and N proteins induced higher neutralizing antibodies and was more effective in reducing the SARS-CoV-2 viral load than the S protein alone in mice. In addition, pS co-immunization with either pN or pE + pM induced a higher S protein-specific cellular immunity after three immunizations and caused milder histopathological changes than pS alone post-challenge. The role of the conserved structural proteins of SARS-CoV-2, including the N/E/M proteins, should be investigated further for their applications in vaccine design, such as mRNA vaccines.

Ocean acidification is one of many stressors that coral reef ecosystems are currently contending with. Thus, understanding the response of key symbiotic microbes to ocean acidification is of great significance for understanding the adaptation mechanism and development trend of coral holobionts. Here, high-throughput sequencing technology was employed to investigate the coral-associated bacteria and Symbiodiniaceae of the ecologically important coral Acropora valida exposed to different pH gradients. After 30 days of acclimatization, we set four acidification gradients (pH 8.2, 7.8, 7.4, and 7.2, respectively), and each pH condition was applied for 10 days, with the whole experiment lasting for 70 days. Although the Symbiodiniaceae density decreased significantly, the coral did not appear to be bleached, and the real-time photosynthetic rate did not change significantly, indicating that A. valida has strong tolerance to acidification. Moreover, the Symbiodiniaceae community composition was hardly affected by ocean acidification, with the C1 subclade (Cladocopium goreaui) being dominant among the Symbiodiniaceae dominant types. The relative abundance of the Symbiodiniaceae background types was significantly higher at pH 7.2, indicating that ocean acidification might increase the stability of the community composition by regulating the Symbiodiniaceae rare biosphere. Furthermore, the stable symbiosis between the C1 subclade and coral host may contribute to the stability of the real-time photosynthetic efficiency. Finally, concerning the coral-associated bacteria, the stable symbiosis between Endozoicomonas and coral host is likely to help them adapt to ocean acidification. The significant increase in the relative abundance of Cyanobacteria at pH 7.2 may also compensate for the photosynthesis efficiency of a coral holobiont. In summary, this study suggests that the combined response of key symbiotic microbes helps the whole coral host resist the threats of ocean acidification.

We performed a retrospective analysis of the clinical manifestations, laboratory and imaging examinations, treatment, and prognosis of a male infant who was diagnosed with mediastinal and subglottic hemangioma in our hospital. The clinical features of this patient were coughing, wheezing, and dyspnea. Enhanced computed tomography of the neck and chest showed a diffuse abnormality in the right-upper mediastinum. He was diagnosed with a hemangioma after a physical examination combined with bronchoscopy. The clinical symptoms were relieved by oral propranolol. We also investigated the clinical characteristics, treatment, and prognosis of mediastinal and subglottic hemangioma in infants in the previous literature, and searched for case reports of this disease in China and in other countries. We only identified three previous cases of mediastinal and subglottic hemangioma in infants, indicating that this condition is rare. In the proliferative stage, surrounding organs and tissues are compressed, which can be life-threatening. Most of these children develop wheezing, shortness of breath, dyspnea, cyanosis, and other symptoms within 2 months. Enhanced computed tomography and magnetic resonance imaging combined with soft bronchoscopy can confirm the diagnosis of this disease, and oral propranolol achieves a favorable effect.

Channel capacity reflects the ability of the system to transmit information without errors.The path loss and impulse response of the system were calculated based on traversing tiny unit method,and then the frequency response of the system was obtained by the discrete Fourier transform of the impulse response sampling sequence,and the 3 dB bandwidth of the system was calculated.Considering the shot noise caused by signal light,the signal-to-noise ratio of the system was obtained according to the quantum limit method,and then the relationship between the channel capacity and the geometric parameters of transmitter and receiver in non-line-of-sight noncoplanar ultraviolet communication system were simulated and analyzed by Shannon formula.The results show that the channel capacity decreases with the increase of the off axis angle and the communication distance.When the elevation angles of transmitter and receiver are less than 40°,the channel capacity decreases rapidly with the increase of the elevation angles of transmitter and receiver,and the transmitter elevation angle has a great influence on the channel capacity.The system channel capacity is almost constant with the increase of divergence angle,and the larger the receiver field of view angle,the greater the system channel capacity.

Global climate change has resulted in large-scale coral reef decline worldwide, for which the ocean warming has paid more attention. Coral is a typical mutually beneficial symbiotic organism with diverse symbiotic microorganisms, which maintain the stability of physiological functions. This study compared the responses of symbiotic microorganisms and host metabolism in a common coral species, Pavona minuta, under indoor simulated thermal and cold temperatures. The results showed that abnormal temperature stresses had unfavorable impact on the phenotypes of corals, resulting in bleaching and color change. The compositions of symbiotic bacteria and dinoflagellate communities only presented tiny changes under temperature stresses. However, some rare symbiotic members have been showed to be significantly influenced by water temperatures. Finally, by using ultra-performance liquid chromatography tandem mass spectrometry (UPLC–MS) method, we found that different temperature stresses had very different impacts on the metabolism of coral holobiont. The thermal and cold stresses induced the decrease of anti-oxidation metabolites, several monogalactosyldiacylglycerols (MGDGs), and the increase of lipotoxic metabolite, 10-oxo-nonadecanoic acid, in the coral holobiont, respectively. Our study indicated the response patterns of symbiotic microorganisms and host metabolism in coral to the thermal and cold stresses, providing theoretical data for the adaptation and evolution of coral to a different climate in the future.