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This study investigated the efficacy of three spray adjuvants (Coerce, Wetcit, and Silwet408) in enhancing dinotefuran permeation in rice leaves. Different concentrations of these adjuvants were tested using an external standard method. The rice leaf surface was analyzed by using the van Oss–Chaudhury–Good method to establish a link between surface free energy (SFE) and dinotefuran permeation. All of the adjuvants effectively increased dinotefuran permeation in rice leaves, with the highest permeation of 8.496 mg/kg achieved using Wetcit at 1000 mg/L. The SFE of the rice leaf surface was determined to be 29.28 mJ/m2. A notable correlation was observed between the energy difference (the SFE of the pesticide liquid versus the SFE of the rice leaf surface) and permeation. Various fitting methods, including linear, exponential, logarithmic, polynomial, and power methods, were applied. Polynomial fitting demonstrated the highest coefficient of determination (R2 > 0.9000). The relationship between the permeation (y) and energy difference (Δγ) conformed to the polynomial equation y = aΔγ2 + bΔγ + c, where a, b, and c are constants. This model provides a predictive tool for the optimal dosage of spray adjuvants according to target plant characteristics, enhancing the understanding of the interaction between pests and pesticides.

The anthranilic diamide insecticide chlorantraniliprole is highly effective against Lepidoptera pests, but the underlying mechanisms of toxic effects of chlorantraniliprole exposures for adapting to the chemical environment are poorly known in fall armyworm (FAW), Spodoptera frugiperda (J.E.Smith). FAW being one of the most pests of maize in Latin America, suddenly appeared in China in 2019 and spread rapidly. In this study, using bioassay and transcriptomic and biochemical analyses, we comprehensively investigated gene expression changes of third instar larvae in response to different sublethal concentrations (LC10 and LC30) of chlorantraniliprole in this insect. Exposure to LC10 chlorantraniliprole (0.73 mg/L) causes 1266 differentially expressed genes (DEGs), of which 578 are up-regulated and 688 down-regulated. Exposure to LC30 (2.49 mg/L) causes differential expression of 3637 DEGs (1545 up-, 2092 down-regulated). Interestingly, the LC30 treatment led to a significant increase in the number of DEGs compared to that of the LC10, indicating a concentration effect manner. Moreover, enrichment analysis identified important DEGs belonging to specific categories, such as amino acid, carbohydrate, lipid, energy, xenobiotics metabolisms, signal transduction, and posttranslational modification pathways, and enzymes activities in enriched pathways were significantly altered at the LC10 and LC30, which matched transcriptome analysis to mediate toxic mechanisms. The DEGs encoding detoxification-related genes were identified and validated by quantitative real-time PCR (qRT-PCR), which correlated with the RNA-sequencing (RNA-seq) data. To our knowledge, these findings provide the first toxicity mechanisms for a better understanding of chlorantraniliprole action and detoxification in FAW and other insect pests at molecular level.

Argonaute proteins exist widely in eukaryotes and prokaryotes, and they are of great potential for molecular cloning, nucleic acid detection, DNA assembly, and gene editing. However, their overall properties are not satisfactory and hinder their broad applications. Herein, we investigated a prokaryotic Argonaute nuclease from a mesophilic bacterium Clostridium disporicum (CdAgo) and explored its overall properties, especially with 5′-hydroxylated (5′-OH) guides. We found that CdAgo can exclusively use single-stranded DNA (ssDNA) as guide to cleave ssDNA and plasmid targets. Further, we found the length of the efficient guide is narrower for the 5′-OH guide (17–20 nt) than for the 5′-phosphorylated guide (5′-P, 14–21 nt). Furthermore, we discovered that the 5′-OH guides can generally offer stronger mismatch discrimination than the 5′-P ones. The 5′-OH guides offer the narrower length range, higher mismatch discrimination and more accurate cleavage than the 5′-P guides. Therefore, 5′-OH-guide-directed CdAgo has great potential in biological and biomedical applications.

The aim of this article is to develop an Intercultural Business Communication Competence Scale (IBCCS) and provide evidence for the construct, convergent, discriminant, content, criterion, and external validity of the scale. The scale was developed based on 20 key elements of intercultural business communication competence (IBCC) and a review on the scales measuring international business practitioners’ intercultural competence. The three factors extracted with exploratory factor analysis (EFA) were the cognitive ability for the intercultural business communication situation, business English linguistic proficiency, and intercultural business communication motivation. The scale showed sound internal consistency and the confirmatory factor analysis (CFA) demonstrated sound degree of fitness and stable scale structure. The survey results revealed that respondents’ IBCC significantly correlated with their emotion intelligence (EI) and cultural intelligence (CQ). IBCCS was capable of differentiating the participants with hypothesized high IBCC level and tracking their IBCC development, which documented content validity and external validity of the measure. Hierarchical regression analysis indicated that the business students’ IBCC appeared to predict their number of foreign friends and job aspiration for an international career.

Xuanfeibaidu Formula (XFBD) is a Chinese medicine used in the clinical treatment of coronavirus disease 2019 (COVID-19) patients. Although XFBD has exhibited significant therapeutic efficacy in clinical practice, its underlying pharmacological mechanism remains unclear. Here, we combine a comprehensive research approach that includes network pharmacology, transcriptomics, and bioassays in multiple model systems to investigate the pharmacological mechanism of XFBD and its bioactive substances. High-resolution mass spectrometry was combined with molecular networking to profile the major active substances in XFBD. A total of 104 compounds were identified or tentatively characterized, including flavonoids, terpenes, carboxylic acids, and other types of constituents. Based on the chemical composition of XFBD, a network pharmacology-based analysis identified inflammation-related pathways as primary targets. Thus, we examined the anti-inflammation activity of XFBD in a lipopolysaccharide-induced acute inflammation mice model. XFBD significantly alleviated pulmonary inflammation and decreased the level of serum proinflammatory cytokines. Transcriptomic profiling suggested that genes related to macrophage function were differently expressed after XFBD treatment. Consequently, the effects of XFBD on macrophage activation and mobilization were investigated in a macrophage cell line and a zebrafish wounding model. XFBD exerts strong inhibitory effects on both macrophage activation and migration. Moreover, through multimodal screening, we further identified the major components and compounds from the different herbs of XFBD that mediate its anti-inflammation function. Active components from XFBD, including Polygoni cuspidati Rhizoma, Phragmitis Rhizoma, and Citri grandis Exocarpium rubrum, were then found to strongly downregulate macrophage activation, and polydatin, isoliquiritin, and acteoside were identified as active compounds. Components of Artemisiae annuae Herba and Ephedrae Herba were found to substantially inhibit endogenous macrophage migration, while the presence of ephedrine, atractylenolide I, and kaempferol was attributed to these effects. In summary, our study explores the pharmacological mechanism and effective components of XFBD in inflammation regulation via multimodal approaches, and thereby provides a biological illustration of the clinical efficacy of XFBD.

Summary: Deep learning-based cell segmentation is increasingly utilized in cell biology due to the massive accumulation of large-scale datasets and excellent progress in model architecture and instance representation. However, the development of specialist algorithms has long been hampered by a paucity of annotated training data, whereas the performance of generalist algorithms is limited without experiment-specific calibration. Here, we present Scellseg, an adaptive pipeline that utilizes a style-aware pre-trained model coupled to a contrastive fine-tuning strategy that also learns from unlabeled data. Scellseg achieves state-of-the-art transferability in average precision and Aggregated Jaccard Index on disparate datasets containing microscopy images at three biological levels, from organelle, cell to organism. Interestingly, when fine-tuning Scellseg, we show that performance plateaued after approximately eight images, implying that a specialist model can be obtained with few manual efforts. For convenient dissemination, we develop a graphical user interface that allows biologists to easily specialize their self-adaptive segmentation model.

Advancing approaches for drug screening are in great demand to explore natural small molecules that may play important roles in collagen biogenesis, secretion, and assembly, which may find novel lead compounds for treating collagen-related diseases or preventing skin aging. In this study, we generated a single copy insertion transgenic Pcol-19- COL-12::GFP Caenorhabditis elegans (C. elegans) strain to label epidermis collagen XII (COL-12), a cuticle structure component, and established an efficient high-content screening techniques to discover bioactive natural products in this worm strain through quantification of fluorescence imaging. We performed a preliminary screening of 614 compounds from the laboratory’s library of natural small molecule compounds on the COL-12 labeling worm model, which was tested once at a single concentration of 100 µM to screen for compounds that promoted COL-12 protein amount. Besides col-12, the transcriptional levels of worm-associated collagen coding genes col-19 and sqt-3 were also examined, and none of the compounds affected their transcriptional levels. Meanwhile, the protein levels of COL-12 were significantly upregulated after treating with Danshensu, Lawsone, and Sanguinarine. The effects of these drugs on COL-12 overexpressing worms occur mainly after collagen transcription. Through various validation methods, Danshensu, Lawsone, and Sanguinarine were more effective in promoting the synthesis or secretion of COL-12.

This essay attempts to define unreliability in autobiography and explore its major forms and features in relation to unreliability in fiction. It starts with the construction of a narratological framework for autobiography, especially in terms of the narrative communicative situation. Then it goes on to discuss two contrasting approaches to fictional unreliability, the rhetorical and the cognitivist or constructivist. The rhetorical approach deals, in an idealized way, with the gap between the narrator and the implied author and is only concerned with the "implied" or "authorial" reader (critics who try to enter that position). The constructivist approach, by contrast, is also concerned with how actual readers try to resolve textual problems with different integration mechanisms. The present study defines and explores autobiographical unreliability in relation to both the rhetorical model and the constructivist model in fiction studies. To illustrate autobiographical unreliability, this essay analyzes two autobiographies by Frederick Douglass in terms of intertextual unreliability and a recent Chinese autobiography in terms of extratextual (un)reliability. In both cases, the divergent responses highlight the functioning of different integration mechanisms. The analysis brings to light certain integration mechanisms peculiar to the interpretation of autobiography and, moreover, shows how the same integration mechanism can be used to opposed effects. [ABSTRACT FROM AUTHOR]