Surface-layer associated proteins (SLAP) that envelop Lactobacillus paracasei ssp. paracasei M5-L and Lactobacillus casei Q8-L cell surfaces are involved in the adherence of these strain to the human intestinal cell line HT-29. To further elucidate some of the properties of these proteins, we assessed the yields and expressions of SLAP under different incubation conditions. An efficient and selective extraction of SLAP was obtained when cells of Lactobacillus were treated with 5 M LiCl at 37°C in aerobic conditions. The SLAP of Lactobacillus M5-L and Q8-L in cell extracts were visualized by SDS-PAGE and identified by Western blotting with sulfo-N-hydroxysuccinimide-biotin-labeled HT-29 cells as adhesion proteins. Atomic force microscopy contact imaging revealed that Lactobacillus strains M5-L and Q8-L normally display a smooth, homogeneous surface, whereas the surfaces of M5-L and Q8-L treated with 5 M LiCl were rough and more heterogeneous. Analysis of adhesion forces revealed that the initial adhesion forces of 1.41 and 1.28 nN obtained for normal Lactobacillus M5-L and Q8-L strains, respectively, decreased to 0.70 and 0.48 nN, respectively, following 5 M LiCl treatment. Finally, the dominant 45-kDa protein bands of Lactobacillus Q8-L and Lactobacillus M5-L were identified as elongation factor Tu and surface antigen, respectively, by liquid chromatography-tandem mass spectrometry.

Surface-layer associated proteins (SLAP) of Lactobacillus paracasei ssp. paracasei M5-L and Lactobacillus casei Q8-L were examined to identify the functional basis for their protection within intestinal epithelial cells. The results showed that SLAP of M5-L and Q8-L remained active in a trypsin solution and retained a 45-kDa protein band, similar to that observed in controls. In contrast, under conditions of simulated gastric juice, the SLAP were partially degraded. Inhibitory effects of SLAP on adherence of Shigella sonnei to HT-29 cells were assessed with use of exclusion, competition, and replacement assays. In response to M5-L at 50 μg/mL SLAP, an inhibition ratio of 33% was obtained, while for Q8-L at 400 μg/mL SLAP, the inhibition ratio was 48%. Hoechst 33258 test results showed that cells infected with S. sonnei and co-incubated with SLAP of M5-L and Q8-L were only partially apoptotic, with apoptosis rates of 37.67 and 43.67%, respectively. These levels of apoptosis were substantially lower than that observed with cells infected with S. sonnei alone. In addition, the SLAP of Q8-L and M5-L reduced downstream caspase-1 activity and further modified apoptotic cell damage. Finally, SLAP of M5-L and Q8-L were also able to prevent S. sonnei-induced membrane damage by inhibiting delocalization of zonula occludens (ZO)-1 and reducing the amount of occludin produced by S. sonnei.

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Fungi represent an important source of bioactive secondary metabolites (SMs), which have wide applications in many fields, including medicine, agriculture, human health, and many other industries. The genes involved in SM biosynthesis are usually clustered adjacent to each other into a region known as a biosynthetic gene cluster (BGC). The recent advent of a diversity of genetic and genomic technologies has facilitated the identification of many cryptic or uncharacterized BGCs and their associated SMs. However, there are still many challenges that hamper the broader exploration of industrially important secondary metabolites. The recent advanced CRISPR/Cas system has revolutionized fungal genetic engineering and enabled the discovery of novel bioactive compounds. In this review, we firstly introduce fungal BGCs and their relationships with associated SMs, followed by a brief summary of the conventional strategies for fungal genetic engineering. Next, we introduce a range of state-of-the-art CRISPR/Cas-based tools that have been developed and review recent applications of these methods in fungi for research on the biosynthesis of SMs. Finally, the challenges and limitations of these CRISPR/Cas-based systems are discussed and directions for future research are proposed in order to expand their applications and improve efficiency for fungal genetic engineering.

The plant cell wall is dynamically modified during host–pathogen interactions and acts as a crucial factor controlling plant immunity. In the context of recently revised models of plant primary cell walls (PCWs), pectin is considered to be important in determining the mechanical properties of PCWs. A secondary cell wall is present in some cell types and lignin is normally present and acts to strengthen wall rigidity. In this review, we summarize the recent advances in understanding cell-wall-mediated defense responses against pathogens in Brassica napus L. (B. napus). A major part of this response involves pectin and lignin, and these two major cell wall components contribute greatly to immune responses in B. napus. Crosstalk between pectin and lignin metabolism has been detected in B. napus upon pathogen infection, suggesting a synergistic action of pectin and lignin metabolism in regulating cell wall integrity as well as wall-mediated immunity. The transcriptional regulation of cell-wall-mediated immunity in B. napus along with that in Arabidopsis is discussed, and directions for future work are proposed for a better understanding of wall-mediated plant immunity in B. napus.

In this study, we aim to reduce generation latency for Named Entity Recognition (NER) with Large Language Models (LLMs). The main cause of high latency in LLMs is the sequential decoding process, which autoregressively generates all labels and mentions for NER, significantly increase the sequence length. To this end, we introduce Parallel Decoding in LLM for NER (PaDeLLM-NER), a approach that integrates seamlessly into existing generative model frameworks without necessitating additional modules or architectural modifications. PaDeLLM-NER allows for the simultaneous decoding of all mentions, thereby reducing generation latency. Experiments reveal that PaDeLLM-NER significantly increases inference speed that is 1.76 to 10.22 times faster than the autoregressive approach for both English and Chinese. Simultaneously it maintains the quality of predictions as evidenced by the performance that is on par with the state-of-the-art across various datasets.* Code is available at URL masked for anonymous review.* https://huggingface.co/meta-llama/Llama-2-7b * https://huggingface.co/baichuan-inc/ Baichuan2-7B-Base

In order to reduce the damage to the old reinforced concrete walls and work out the best construction scheme during the renovation of old buildings, it is often required to detect the position of rebar buried in concrete walls. In this paper, we propose a non-destructive method to detect the buried rebar by self-inductive sensor combined with surface acoustic wave resonator (SAWR). The proposed method has the advantages of wireless, passive and convenient operations. In our new design, the sensing element of self-inductance coil was made as a component of SAWR matching network. The distribution of rebar could be measured according to the system resonant frequency, using a signal demodulation device set. The depth of buried rebar and the deviation of output resonant frequency from inherent frequency of SAWR have an inverse relation. Finally, the validity of the method was verified in theoretical calculation and simulation.

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