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Objective: N-butylphthalide (NBP) is a monomeric compound extracted from natural plant celery seeds, whether intestinal microbiota alteration can modify its pharmacokinetics is still unclear. The purpose of this study is to investigate the effect of intestinal microbiota alteration on the pharmacokinetics of NBP and its related mechanisms. Methods: After treatment with antibiotics and probiotics, plasma NBP concentrations in SD rats were determined by high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). The effect of intestinal microbiota changes on NBP pharmacokinetics was compared. Intestinal microbiota changes after NBP treatment were analyzed by 16S rRNA sequencing. Expressions of CYP3A1 mRNA and protein in the liver and small intestine tissues under different intestinal flora conditions were determined by qRT-PCR and Western Blot. KEGG analysis was used to analyze the effect of intestinal microbiota changes on metabolic pathways. Results: Compared to the control group, the values of Cmax, AUC0-8, AUC0-∞, t1/2 in the antibiotic group increased by 56.1% (P<0.001), 56.4% (P<0.001), 53.2% (P<0.001), and 24.4% (P<0.05), respectively. In contrast, the CL and Tmax values decreased by 57.1% (P<0.001) and 28.6% (P<0.05), respectively. Treatment with antibiotics could reduce the richness and diversity of the intestinal microbiota. CYP3A1 mRNA and protein expressions in the small intestine of the antibiotic group were 61.2% and 66.1% of those of the control group, respectively. CYP3A1 mRNA and protein expressions in the liver were 44.6% and 63.9% of those in the control group, respectively. There was no significant change in the probiotic group. KEGG analysis showed that multiple metabolic pathways were significantly down-regulated in the antibiotic group. Among them, the pathways of drug metabolism, bile acid biosynthesis and decomposition, and fatty acid synthesis and decomposition were related to NBP biological metabolism. Conclusion: Antibiotic treatment could affect the intestinal microbiota, decrease CYP3A1 mRNA and protein expressions and increase NBP exposure in vivo by inhibiting pathways related to NBP metabolism. [ABSTRACT FROM AUTHOR]

The Coronavirus Disease 2019(COVID-19) has caused widespread and significant harm globally. In order to address the urgent demand for a rapid and reliable diagnostic approach to mitigate transmission, the application of deep learning stands as a viable solution. The impracticality of many existing models is attributed to excessively large parameters, significantly limiting their utility. Additionally, the classification accuracy of the model with few parameters falls short of desirable levels. Motivated by this observation, the present study employs the lightweight network MobileNetV3 as the underlying architecture. This paper incorporates the dense block to capture intricate spatial information in images, as well as the transition layer designed to reduce the size and channel number of the feature map. Furthermore, this paper employs label smoothing loss to address the inter-class similarity effects and uses class weighting to tackle the problem of data imbalance. Additionally, this study applies the pruning technique to eliminate unnecessary structures and further reduce the number of parameters. As a result, this improved model achieves an impressive 98.71% accuracy on an openly accessible database, while utilizing only 5.94 million parameters. Compared to the previous method, this maximum improvement reaches 5.41%. Moreover, this research successfully reduces the parameter count by up to 24 times, showcasing the efficacy of our approach. This demonstrates the significant benefits in regions with limited availability of medical resources. [ABSTRACT FROM AUTHOR]

Cross‐situational inconsistency is common in the expression of honesty traits; yet, there is insufficient emphasis on behavioral dishonesty across multiple contexts. The current study aimed to investigate behavioral dishonesty in various contexts and reveal the associations between trait honesty, behavioral dishonesty, and neural patterns of observing others behave honestly or dishonestly in videos (abbr.: (dis)honesty video‐watching). First, the results revealed limitations in using trait honesty to reflect variations in dishonest behaviors and predict behavioral dishonesty. The finding highlights the importance of considering neural patterns in understanding and predicting dishonest behaviors. Second, by comparing the predictive performance of seven types of data across three neural networks, the results showed that functional connectivity in the hypothesis‐driven network during (dis)honesty video‐watching provided the highest predictive power in predicting multitask behavioral dishonesty. Last, by applying the feature elimination method, the midline self‐referential regions (medial prefrontal cortex, posterior cingulate cortex, and anterior cingulate cortex), anterior insula, and striatum were identified as the most informative brain regions in predicting behavioral dishonesty. In summary, the study offered insights into individual differences in deception and the intricate connections among trait honesty, behavioral dishonesty, and neural patterns during (dis)honesty video‐watching. [ABSTRACT FROM AUTHOR]

Previous studies have shown that audit quality is influenced by the audit engagement partner's characteristics. Extending this literature, we examine the association between audit engagement partner ideology (i.e. conservatism) and audit quality. We find that clients whose audit engagement partners are ideologically more conservative receive higher quality audits, as indicated by lower discretionary accruals than clients with less conservative auditors. Additionally, we find evidence that the relation between the auditor's ideology and that of the client's executives influences audit quality, as does the ideological homophily between the auditor and the client's audit committee. Homophilous pairings between the audit engagement partner and the client's executives, where the two parties share a similar ideology, are associated with both higher discretionary accruals and higher probabilities of restatement. Discretionary accruals are also shown to be higher when engagement partners share an ideology with their client's audit committee. We interpret these results as evidence of less effective monitoring by the engagement partner when they share political views with their clients. [ABSTRACT FROM AUTHOR]

Summary: Plants are simultaneously attacked by different pests that rely on sugars uptake from plants. An understanding of the role of plant sugar allocation in these multipartite interactions is limited.Here, we characterized the expression patterns of sucrose transporter genes and evaluated the impact of targeted transporter gene mutants and brown planthopper (BPH) phloem‐feeding and oviposition on root sugar allocation and BPH‐reduced rice susceptibility to Meloidogyne graminicola.We found that the sugar transporter genes OsSUT1 and OsSUT2 are induced at BPH oviposition sites. OsSUT2 mutants showed a higher resistance to gravid BPH than to nymph BPH, and this was correlated with callose deposition, as reflected in a different effect on M. graminicola infection. BPH phloem‐feeding caused inhibition of callose deposition that was counteracted by BPH oviposition. Meanwhile, this pivotal role of sugar allocation in BPH‐reduced rice susceptibility to M. graminicola was validated on rice cultivar RHT harbouring BPH resistance genes Bph3 and Bph17.In conclusion, we demonstrated that rice susceptibility to M. graminicola is regulated by BPH phloem‐feeding and oviposition on rice through differences in plant sugar allocation. [ABSTRACT FROM AUTHOR]