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Rice phosphatidylcholine transfer protein (PCTP), which contains a steroidogenic acute regulatory protein-related lipid transfer (START) domain, responds to bacterial blight disease. Overexpression of OsPCTP quantitatively enhances resistance to pathogen in rice, whereas depletion of it has the opposite effect. Further analysis showed that OsPCTP physically interacts with OsAPX8, a ROS scavenging enzyme, and influences ascorbate peroxidase enzymatic activity in vivo. In addition, the expression of pathogenesis-related genes PR1a , PR1b and PR10 were significantly induced in OsPCTP-OE plants compared with that in wild-type plants ZH11. Taken together, these results suggested that OsPCTP mediates bacterial blight resistance in rice through regulating the ROS defense pathway.

Passiflora edulis , also known as passion fruit, is celebrated for its rich nutritional content, distinctive flavour, and significant medicinal benefits. At present, viral diseases pose a major challenge to the passion fruit industry, affecting both the production and quality of the fruit. These diseases impede the sustainable and healthy growth of the passion fruit sector. In recent years, with the expansion of P. edulis cultivation areas, virus mutations, and advances in virus detection technology, an increasing number of virus species infecting P. edulis have been discovered. To date, more than 40 different virus species have been identified; however, there are different strains within the same virus. This poses a challenge for the control and prevention of P. edulis virus disease. Therefore, this review discusses the different types of viruses and their characteristics, modes of transmission, and effects on the growth of the passion fruit plant, as well as the mechanisms of virus generation and preventive measures, with the hope that these discussions will provide a comprehensive understanding of and countermeasures for viruses in passion fruit.

5,6-dihydroxyflavone (5,6-DHF), a flavonoid that possesses potential anti-inflammatory and antioxidant activities owing to its special catechol motif on the A ring. However, its function and mechanism of action against inflammation and cellular oxidative stress have not been elucidated. In the current study, 5,6-DHF was observed inhibiting lipopolysaccharide (LPS)-induced nitric oxide (NO) and cytoplasmic reactive oxygen species (ROS) production with the IC 50 of 11.55 ± 0.64 μM and 0.8310 ± 0.633 μM in murine macrophages, respectively. Meanwhile, 5,6-DHF suppressed the overexpression of pro-inflammatory mediators such as proteins and cytokines and eradicated the accumulation of mitochondrial ROS (mtROS). The blockage of the activation of cell surface toll-like receptor 4 (TLR4), impediment of the phosphorylation of c-Jun N-terminal kinase (JNK) and p38 from the mitogen-activated protein kinases (MAPK) pathway, Janus kinase 2 (JAK2) and signal transducer and activator of transcription 3 (STAT3) from the JAK-STAT pathway, and p65 from nuclear factor-κB (NF-κB) pathways were involved in the process of 5,6-DHF suppressing inflammation. Furthermore, 5,6-DHF acted as a cellular ROS scavenger and heme-oxygenase 1 (HO-1) inducer in relieving cellular oxidative stress. Importantly, 5,6-DHF exerted more potent anti-inflammatory activity than its close structural relatives, such as baicalein and chrysin. Overall, our findings pave the road for further research on 5,6-DHF in animal models.

Photodynamic therapy (PDT) is a therapeutic modality that depends on the interaction of light, photosensitizers, and oxygen. The photon absorption and energy transfer process can lead to the Type II photochemical reaction of the photosensitizer and the production of singlet oxygen ( 1 O 2 ), which strongly oxidizes and reacts with biomolecules, ultimately causing oxidative damage to the target cells. Therefore, 1 O 2 is regarded as the key photocytotoxic species accountable for the initial photodynamic reactions for Type II photosensitizers. This article will provide a comprehensive review of 1 O 2 properties, 1 O 2 production, and 1 O 2 detection in the PDT process. The available 1 O 2 data of regulatory-approved photosensitizing drugs will also be discussed.

Background: Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease. The fruits of Illicium verum , which is a medicinal and edible resource, have been shown to have anti-inflammatory properties., Methods: In this study, we investigated the effects of I. verum extracts (IVEs) on human RA fibroblasts-like synoviocytes (RA-FLS) by using a sensitive and selective ultra-high-performance liquid chromatography with high-definition mass spectrometry (UPLC-HDMS) method. We subsequently analyzed the metabolites produced after the incubation of cultured RA-FLS with IVEs., Results: IVEs inhibited the proliferation and suppressed the migration of RA-FLS, and reduced the levels of inflammatory factors including TNF-α and IL-6. Twenty differential metabolites responsible for the effects of IVEs were screened and annotated based on the UPLC-HDMS data by using a cell metabolomics approach., Discussion: Our findings suggest that treating RA-FLS with IVEs can regulate lipid and amino acid metabolism, indicating that this extract has the potential to modify the metabolic pathways that cause inflammation in RA., Conclusions: This might lead to novel therapeutic strategies for managing patients with RA.

Small Heterodimer Partner (SHP; NR0B2 ) is an orphan receptor that acts as a transcriptional regulator, controlling various metabolic processes, and is a potential therapeutic target for cancer. Examining the correlation between the expression of NR0B2 and the risk of gastric diseases could open a new path for treatment and drug development. The Gene Expression Omnibus (GEO) database was utilized to explore NR0B2 gene expression profiles in gastric diseases. Co-expressed genes were identified through Weighted Correlation Network Analysis (WGCNA), and GO enrichment was performed to identify potential pathways. The Xcell method was employed to analyze immune infiltration relationships. To determine the potential causal relationship between NR0B2 expression and gastric diseases, we identified six single-nucleotide polymorphisms (SNPs) as a proxy for NR0B2 expression located within 100 kilobases of NR0B2 and which are associated with triglyceride homeostasis and performed drug-target Mendelian randomization (MR). Bioinformatics analysis revealed that NR0B2 expression levels were reduced in gastric cancer and increased in gastritis. GO analysis and Gene Set Enrichment Analysis (GSEA) showed that NR0B2 is widely involved in oxidation-related processes. Immune infiltration analyses found that NR0B2 was associated with Treg. Prognostic analyses showed that a low expression of NR0B2 is a risk factor for the poor prognoses of gastric cancer. MR analyses revealed that NR0B2 expression is associated with a risk of gastric diseases ( NR0B2 vs. gastric cancer, p = 0.006, OR: 0.073, 95%CI: 0.011-0.478; NR0B2 vs. gastric ulcer, p = 0.03, OR: 0.991, 95%CI: 0.984-0.999; NR0B2 vs. other gastritis, p = 0.006, OR:3.82, 95%CI: 1.468-9.942). Our study confirms the causal relationship between the expression of NR0B2 and the risk of gastric diseases, and highlights its role in the progression of gastric cancer. The present study opens new avenues for exploring the potential of drugs that either activate or inhibit the NR0B2 receptor in the treatment of gastric diseases.

The gardenia flower not only has extremely high ornamental value but also is an important source of natural food and spices, with a wide range of uses. To support the development of gardenia flower products, this study used headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) technology to compare and analyze the volatile organic compounds (VOCs) of fresh gardenia flower and those after using four different drying methods (vacuum freeze-drying (VFD), microwave drying (MD), hot-air drying (HAD), and vacuum drying (VD)). The results show that, in terms of shape, the VFD sample is almost identical to fresh gardenia flower, while the HAD, MD, and VD samples show significant changes in appearance with clear wrinkling; a total of 59 volatile organic compounds were detected in the gardenia flower, including 13 terpenes, 18 aldehydes, 4 esters, 8 ketones, 15 alcohols, and 1 sulfide. Principal component analysis (PCA), cluster analysis (CA), and partial least-squares regression analysis (PLS-DA) were performed on the obtained data, and the research found that different drying methods impact the VOCs of the gardenia flower. VFD or MD may be the most effective alternative to traditional sun-drying methods. Considering its drying efficiency and production cost, MD has the widest market prospects.

Modern research has shown that Cucurbitacin B (Cu B) possesses various biological activities such as liver protection, anti-inflammatory, and anti-tumor effects. However, the majority of research has primarily concentrated on its hepatoprotective effects, with limited attention devoted to exploring its potential impact on the prostate. Our research indicates that Cu B effectively inhibits the proliferation of human prostate stromal cells (WPMY-1) and fibroblasts (HPRF), while triggering apoptosis in prostate cells. When treated with 100 nM Cu B, the apoptosis rates of WPMY-1 and HPRF cells reached 51.73 ± 5.38% and 26.83 ± 0.40%, respectively. In addition, the cell cycle assay showed that Cu B had a G2/M phase cycle arrest effect on WPMY-1 cells. Based on RNA-sequencing analysis, Cu B might inhibit prostate cell proliferation via the p53 signaling pathway. Subsequently, the related gene and protein expression levels were measured using quantitative real-time PCR (RT-qPCR), immunocytochemistry (ICC), and enzyme-linked immunosorbent assays (ELISA). Our results mirrored the regulation of tumor protein p53 (TP53), mouse double minute-2 (MDM2), cyclin D1 (CCND1), and thrombospondin 1 (THBS1) in Cu B-induced prostate cell apoptosis. Altogether, Cu B may inhibit prostate cell proliferation and correlate to the modulation of the p53/MDM2 signaling cascade.

Background: Currently, prostate cancer (PCa) prebiopsy medical image diagnosis mainly relies on mpMRI and PI-RADS scores. However, PI-RADS has its limitations, such as inter- and intra-radiologist variability and the potential for imperceptible features. The primary objective of this study is to evaluate the effectiveness of a machine learning model based on radiomics analysis of MRI T2-weighted (T2w) images for predicting PCa in prebiopsy cases., Method: A retrospective analysis was conducted using 820 lesions (363 cases, 457 controls) from The Cancer Imaging Archive (TCIA) Database for model development and validation. An additional 83 lesions (30 cases, 53 controls) from Hong Kong Queen Mary Hospital were used for independent external validation. The MRI T2w images were preprocessed, and radiomic features were extracted. Feature selection was performed using Cross Validation Least Angle Regression (CV-LARS). Using three different machine learning algorithms, a total of 18 prediction models and 3 shape control models were developed. The performance of the models, including the area under the curve (AUC) and diagnostic values such as sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), were compared to the PI-RADS scoring system for both internal and external validation., Results: All the models showed significant differences compared to the shape control model (all p < 0.001, except SVM model PI-RADS+2 Features p = 0.004, SVM model PI-RADS+3 Features p = 0.002). In internal validation, the best model, based on the LR algorithm, incorporated 3 radiomic features (AUC = 0.838, sensitivity = 76.85%, specificity = 77.36%). In external validation, the LR (3 features) model outperformed PI-RADS in predictive value with AUC 0.870 vs. 0.658, sensitivity 56.67% vs. 46.67%, specificity 92.45% vs. 84.91%, PPV 80.95% vs. 63.64%, and NPV 79.03% vs. 73.77%., Conclusions: The machine learning model based on radiomics analysis of MRI T2w images, along with simulated biopsy, provides additional diagnostic value to the PI-RADS scoring system in predicting PCa.

This study investigated the role of cholecystokinin ( cck ) in the feeding regulation of largemouth bass ( Micropterus salmoides ) via peptide activation and antagonist inhibition. The results show that the cck gene was expressed in various tissues, with the highest expression level occurring in the brain. Feeding, continuous feeding, and refeeding after fasting could significantly improve the mRNA levels of cck in the brain. Moreover, the activation of cck via injecting an exogenous CCK peptide could inhibit feed intake by regulating the mRNA levels of anorexigenic and feed-promoting factors in the brain and intestine. Furthermore, the CCK peptide reduced feed intake; however, the presence of an antagonist (Ly225910-CCK1R and devazepide-CCK2R) could reverse this effect through regulating the mRNA levels of anorexigenic and feed-promoting factors in the brain and intestine. Treatment with devazepide + CCK (CCK2R) reversed feed intake more effectively than Ly225910 + CCK (CCK1R) treatment. In summary, cck could regulate the feed intake of largemouth bass through regulating feeding-related genes in the brain and intestine. In addition, cck required binding with the receptor to inhibit feed intake more effectively in largemouth bass, and the binding effect of CCK1R was better than that of CCK2R.

Colostrum intake is a crucial determinant of survival in newborn rabbits. Neonates rely entirely on passive immunity transfer from their mothers while suckling colostrum. The goal of this study was to explore the protein differences of rabbit milk during different lactation periods. Our findings showed that the daily milk yield exhibited an increasing trend from the 2nd to the 21st day of lactation. A data-independent acquisition proteomics approach identified a total of 2011 proteins. Significantly, different abundances were found for 525 proteins in the colostrum and the mature milk samples. Eleven differentially abundant proteins (DAPs) were examined using parallel reaction monitoring, which verified the reliability of the proteomic data. Gene Ontology analysis revealed that these DAPs were primarily associated with glycosyltransferase activity, macromolecule transmembrane transporter activity, and regulation of acute inflammatory response. The dominant metabolic pathways of the DAPs involve the complement and coagulation cascades. A protein-protein interaction analysis identified apolipoprotein B, apolipoprotein A1, triose phosphate isomerase 1, and albumin as the hub proteins responsible for distinguishing differences between biological properties in rabbit colostrum and mature milk. These findings enhance our comprehension of the rabbit milk proteome, particularly in expanding our knowledge regarding the requirements of neonatal rabbits.

In response to the fact that autonomous vehicles cannot avoid obstacles by emergency braking alone, this paper proposes an active collision avoidance method for autonomous vehicles based on model predictive control (MPC). The method includes trajectory tracking, adaptive cruise control (ACC), and active obstacle avoidance under high vehicle speed. Firstly, an MPC-based trajectory tracking controller is designed based on the vehicle dynamics model. Then, the MPC was combined with ACC to design the control strategies for vehicle braking to avoid collisions. Additionally, active steering for collision avoidance was developed based on the safety distance model. Finally, considering the distance between the vehicle and the obstacle and the relative speed, an obstacle avoidance function is constructed. A path planning controller based on nonlinear model predictive control (NMPC) is designed. In addition, the alternating direction multiplier method (ADMM) is used to accelerate the solution process and further ensure the safety of the obstacle avoidance process. The proposed algorithm is tested on the Simulink and CarSim co-simulation platform in both static and dynamic obstacle scenarios. Results show that the method effectively achieves collision avoidance through braking. It also demonstrates good stability and robustness in steering to avoid collisions at high speeds. The experiments confirm that the vehicle can return to the desired path after avoiding obstacles, verifying the effectiveness of the algorithm.

Gardenia fruit is a popular functional food and raw material for natural pigments. It comes from a wide range of sources, and different products sharing the same name are very common. Volatile organic compounds (VOCs) are important factors that affect the flavor and quality of gardenia fruit. This study used the Heracles NEO ultra-fast gas phase electronic nose with advanced odor analysis performance and high sensitivity to analyze six batches of gardenia fruit from different sources. This study analyzed the VOCs to find a way to quickly identify gardenia fruit. The results show that this method can accurately distinguish the odor characteristics of various gardenia fruit samples. The VOCs in gardenia fruit are mainly organic acid esters, ketones, and aldehyde compounds. By combining principal component analysis (PCA) and discriminant factor analysis (DFA), this study found that the hexanal content varied the most in different gardenia fruit samples. The VOCs allowed for the fruit samples to be grouped into two main categories. One fruit sample was quite different from the fruits of other origins. The results provide theoretical support for feasibility of rapid identification and quality control of gardenia fruit and related products in the future.

A base-induced synthesis of 2-(4-(2-(phenylthio)ethyl)piperazinyl) acetonitriles by reaction of disulfides, 1-(chloromethyl)-4-aza-1-azonia bicyclo[2.2.2]octane chloride and trimethylsilyl cyanide is reported. The scope of the method is demonstrated with 30 examples. The reaction mechanism research indicates that the three-component reaction would be a SN2 reaction. The products exhibit good activities towards advanced synthesis of aqueous soluble acyl-CoA: cholesterol O -acyltransferase-1 (ACAT-1) inhibitors. Our work is superior as it uses less-odor disulfides as carbon sources and EtOH as solvent in a water and dioxygen insensitive reaction system, followed by a simple purification process.

Multifactorial diseases demand therapeutics that can modulate multiple targets for enhanced safety and efficacy, yet the clinical approval of multitarget drugs remains rare. The integration of machine learning (ML) and deep learning (DL) in drug discovery has revolutionized virtual screening. This study investigates the synergy between ML/DL methodologies, molecular representations, and data augmentation strategies. Notably, we found that SVM can match or even surpass the performance of state-of-the-art DL methods. However, conventional data augmentation often involves a trade-off between the true positive rate and false positive rate. To address this, we introduce Negative-Augmented PU-bagging (NAPU-bagging) SVM, a novel semi-supervised learning framework. By leveraging ensemble SVM classifiers trained on resampled bags containing positive, negative, and unlabeled data, our approach is capable of managing false positive rates while maintaining high recall rates. We applied this method to the identification of multitarget-directed ligands (MTDLs), where high recall rates are critical for compiling a list of interaction candidate compounds. Case studies demonstrate that NAPU-bagging SVM can identify structurally novel MTDL hits for ALK-EGFR with favorable docking scores and binding modes, as well as pan-agonists for dopamine receptors. The NAPU-bagging SVM methodology should serve as a promising avenue to virtual screening, especially for the discovery of MTDLs.

Intervertebral disc degeneration (IVDD) stands as the foremost contributor to low back pain (LBP), imposing a substantial weight on the world economy. Traditional treatment modalities encompass both conservative approaches and surgical interventions; however, the former falls short in halting IVDD progression, while the latter carries inherent risks. Hence, the quest for an efficacious method to reverse IVDD onset is paramount. Biomaterial delivery systems, exemplified by hydrogels, microspheres, and microneedles, renowned for their exceptional biocompatibility, biodegradability, biological efficacy, and mechanical attributes, have found widespread application in bone, cartilage, and various tissue engineering endeavors. Consequently, IVD tissue engineering has emerged as a burgeoning field of interest. This paper succinctly introduces the intervertebral disc (IVD) structure and the pathophysiology of IVDD, meticulously classifies biomaterials for IVD repair, and reviews recent advances in the field. Particularly, the strengths and weaknesses of biomaterials in IVD tissue engineering are emphasized, and potential avenues for future research are suggested.

The auxin/indoleacetic acid ( Aux/IAA ) family plays a central role in regulating gene expression during auxin signal transduction. Nonetheless, there is limited knowledge regarding this gene family in sugarcane. In this study, 92 members of the IAA family were identified in Saccharum spontaneum , distributed on 32 chromosomes, and classified into three clusters based on phylogeny and motif compositions. Segmental duplication and recombination events contributed largely to the expansion of this superfamily. Additionally, cis-acting elements in the promoters of SsIAAs involved in plant hormone regulation and stress responsiveness were predicted. Transcriptomics data revealed that most SsIAA expressions were significantly higher in stems and basal parts of leaves, and at nighttime, suggesting that these genes might be involved in sugar transport. QRT-PCR assays confirmed that cold and salt stress significantly induced four and five SsIAAs , respectively. GFP-subcellular localization showed that SsIAA23 and SsIAA12a were localized in the nucleus, consistent with the results of bioinformatics analysis. In conclusion, to a certain extent, the functional redundancy of family members caused by the expansion of the sugarcane IAA gene family is related to stress resistance and regeneration of sugarcane as a perennial crop. This study reveals the gene evolution and function of the SsIAA gene family in sugarcane, laying the foundation for further research on its mode of action.

Triple-negative breast cancer (TNBC) cells are often resistant to FAS (CD95)-mediated apoptosis, but the underlying molecular mechanism(s) is not fully understood yet. Notably, the expression of the type II transmembrane protein, CD74, is correlated with chemotherapy-resistant and more invasive forms of cancers via unknown mechanisms. Here, we analyzed gene expression pattern of cancer patients and/or patient-derived xenograft (PDX) models and found that mRNA and protein levels of CD74 are highly expressed in TNBC and correlated with cancer stem cells (CSCs) and epithelial-mesenchymal transition (EMT) properties. Mechanistically, we found that AKT activation is likely critical for maintaining CD74 expression and protein stability to favor its oncogenic functions. Physiologically, epidermal growth factor (EGF) along with CD74 could activate AKT signaling, likely through binding of phosphorylated AKT (S473) to CD74, whereas inhibition of AKT could impair stability of CD74. We also revealed that CD74 binds to FAS and interferes with the intrinsic signaling of FAS-mediated apoptosis. As such, selective targeting of the CD74/FAS complex using the AKT inhibitor along with the CD74-derived peptide could synergistically restore and activate FAS-mediated apoptosis. Therefore, our approach of mobilizing apoptosis pathways likely provides a rationale for TNBC treatment by targeting the CD74/FAS and CD74-AKT axes.

To reveal the effects of waterborne copper stress on gene expression changes, molecular pathways, and physiological functions in Coilia nasus , juvenile fish were equally divided into two experimental groups, and the copper levels were 1.61 ± 0.03 mg/L (copper-exposed group) and 0 mg/L (control group), respectively. After 4 h, gill tissue samples were collected for transcript sequencing analysis, and two libraries were constructed from the copper treatment group (Cu) and the control group (C) and sequenced using Illumina sequencing technology. The results showed that approximately 40.2-46.0 M clean reads were obtained from each library, and the percentage of uniquely mapped transcripts ranged from 80.57 to 84.93%. A total of 3915 differentially expressed genes (DEGs) were identified under waterborne copper stress, among which 1300 genes were up-regulated, and 2615 genes were down-regulated. Twelve DEGs were randomly selected for quantitative RT-PCR (qRT-PCR) analysis, and the results confirmed that the transcriptome analysis was reliable. Furthermore, the DEGs were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and the results showed that most of the DEGs were involved in metabolic pathways, including steroid biosynthesis, glutathione metabolism, and peroxisome proliferator-activated receptor (PPAR) signaling pathways. Furthermore, due to the waterborne copper levels, gsk-3β was significantly up-regulated, while other metabolism-related genes ( tor , pi3k , lpl , aqp7 , fabp3 ) were significantly down-regulated. In addition, the copper-exposed group significantly reduced the expression of some immunity genes ( ifn-γ , stat1 , cxcl10 , and tgf-β ), and enhanced the expression of il-1β and tnf-α. In summary, these results indicated that copper causes metabolic disorders and insufficient energy supply in the body, and induces oxidative stress, which results in reduced immune functions.

Chronic exposure to harmful pollutants, chemicals, and pathogens from the environment can lead to pathological changes in the epithelial barrier, which increase the risk of developing an allergy. During allergic inflammation, epithelial cells send proinflammatory signals to group 2 innate lymphoid cell (ILC2s) and eosinophils, which require energy and resources to mediate their activation, cytokine/chemokine secretion, and mobilization of other cells. This review aims to provide an overview of the metabolic regulation in allergic asthma, atopic dermatitis (AD), and allergic rhinitis (AR), highlighting its underlying mechanisms and phenotypes, and the potential metabolic regulatory roles of eosinophils and ILC2s. Eosinophils and ILC2s regulate allergic inflammation through lipid mediators, particularly cysteinyl leukotrienes (CysLTs) and prostaglandins (PGs). Arachidonic acid (AA)-derived metabolites and Sphinosine-1-phosphate (S1P) are significant metabolic markers that indicate immune dysfunction and epithelial barrier dysfunction in allergy. Notably, eosinophils are promoters of allergic symptoms and exhibit greater metabolic plasticity compared to ILC2s, directly involved in promoting allergic symptoms. Our findings suggest that metabolomic analysis provides insights into the complex interactions between immune cells, epithelial cells, and environmental factors. Potential therapeutic targets have been highlighted to further understand the metabolic regulation of eosinophils and ILC2s in allergy. Future research in metabolomics can facilitate the development of novel diagnostics and therapeutics for future application.

Accurately predicting drug-target interactions is a critical yet challenging task in drug discovery. Traditionally, pocket detection and drug-target affinity prediction have been treated as separate aspects of drug-target interaction, with few methods combining these tasks within a unified deep learning system to accelerate drug development. In this study, we propose EMPDTA, an end-to-end framework that integrates protein pocket prediction and drug-target affinity prediction to provide a comprehensive understanding of drug-target interactions. The EMPDTA framework consists of three main modules: pocket online detection, multimodal representation learning for affinity prediction, and multi-task joint training. The performance and potential of the proposed framework have been validated across diverse benchmark datasets, achieving robust results in both tasks. Furthermore, the visualization results of the predicted pockets demonstrate accurate pocket detection, confirming the effectiveness of our framework.

Universal image restoration (UIR) aims to accurately restore images with a variety of unknown degradation types and levels. Existing methods, including both learning-based and prior-based approaches, heavily rely on low-quality image features. However, it is challenging to extract degradation information from diverse low-quality images, which limits model performance. Furthermore, UIR necessitates the recovery of images with diverse and complex types of degradation. Inaccurate estimations further decrease restoration performance, resulting in suboptimal recovery outcomes. To enhance UIR performance, a viable approach is to introduce additional priors. The current UIR methods have problems such as poor enhancement effect and low universality. To address this issue, we propose an effective framework based on a diffusion model (DM) for universal image restoration, dubbed ETDiffIR. Inspired by the remarkable performance of text prompts in the field of image generation, we employ text prompts to improve the restoration of degraded images. This framework utilizes a text prompt corresponding to the low-quality image to assist the diffusion model in restoring the image. Specifically, a novel text-image fusion block is proposed by combining the CLIP text encoder and the DA-CLIP image controller, which integrates text prompt encoding and degradation type encoding into time step encoding. Moreover, to reduce the computational cost of the denoising UNet in the diffusion model, we develop an efficient restoration U-shaped network (ERUNet) to achieve favorable noise prediction performance via depthwise convolution and pointwise convolution. We evaluate the proposed method on image dehazing, deraining, and denoising tasks. The experimental results indicate the superiority of our proposed algorithm.

Four new diterpenoids, isodosins A-D ( 1 - 4 ), together with nine known compounds ( 5 - 13 ) were isolated and identified from the aerial parts of Isodon serra (Maxim.) Hara. The structures of the new diterpenoids were elucidated based on the analysis of HR-ESI-MS data, 1D/2D-NMR-spectroscopic data, and electronic circular dichroism (ECD) calculations. Cytotoxicities of compounds 2 , 3 , 5 , 6 , and 9 against the HepG2 and H1975 cell lines were evaluated with the MTT assay. As a result, compounds 2 , 3 , and 6 revealed higher levels of cytotoxicity against HepG2 cells than against H1975 cells. Moreover, compund 6 demonstrated the most efficacy in inhibiting the proliferation of HepG2 cells, with an IC 50 value of 41.13 ± 3.49 μM. This effect was achieved by inducing apoptosis in a dose-dependent manner. Furthermore, the relationships between the structures and activities of these compounds are briefly discussed.

Cangjie Temple was built to commemorate Cangjie, the legendary inventor of Chinese characters. It stands as one of the few remaining temples in China dedicated to the invention and creation of writing. In this study, the material properties of wooden paintings from the Cangjie temple were characterized using Polarized Light Microscopy (PLM), Scanning Electron Microscopy coupled with Energy Dispersive X-ray Spectroscopy (SEM-EDS), Micro-confocal Raman Spectroscopy, X-ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), and Pyrolysis-Gas Chromatography-Mass Spectrometry (Py-GC/MS). It was confirmed that the pigments of the paintings included cinnabar, lapis lazuli, lead white, Paris green, and carbon black. The proteinaceous glue was used as an adhesive in the pigment samples, with tung oil likely being utilized as a primer for the wooden structures before painting. This study not only provides valuable data support for the conservation and restoration of the architectural features of Cangjie Temple but also provides useful reference for the maintenance and inheritance of similar ancient buildings.

Carbon dots (CDs) have aroused colossal attention in the fabrication of nanocomposite membranes ascribed to their ultra-small size, good dispersibility, biocompatibility, excellent fluorescence, facile synthesis, and ease of functionalization. Their unique properties could significantly improve membrane performance, including permeance, selectivity, and antifouling ability. In this review, we summarized the recent development of CDs-based nanocomposite membranes in many application areas. Specifically, we paid attention to the structural regulation and functionalization of CDs-based nanocomposite membranes by CDs. Thus, a detailed discussion about the relationship between the CDs' properties and microstructures and the separation performance of the prepared membranes was presented, highlighting the advantages of CDs in designing high-performance separation membranes. In addition, the excellent optical and electric properties of CDs enable the nanocomposite membranes with multiple functions, which was also presented in this review., Competing Interests: The authors declare no conflict of interest.

In this study, we investigated the feasibility of using electroencephalogram (EEG) signals to differentiate between four distinct subject-driven cognitive states: resting state, narrative memory, music, and subtraction tasks. EEG data were collected from seven healthy male participants while performing these cognitive tasks, and the raw EEG signals were transformed into time-frequency maps using continuous wavelet transform. Based on these time-frequency maps, we developed a convolutional neural network model (TF-CNN-CFA) with a channel and frequency attention mechanism to automatically distinguish between these cognitive states. The experimental results demonstrated that the model achieved an average classification accuracy of 76.14% in identifying these four cognitive states, significantly outperforming traditional EEG signal processing methods and other classical image classification algorithms. Furthermore, we investigated the impact of varying lengths of EEG signals on classification performance and found that TF-CNN-CFA demonstrates consistent performance across different window lengths, indicating its strong generalization capability. This study validates the ability of EEG to differentiate higher cognitive states, which could potentially offer a novel BCI paradigm.

Cinnamon is one of the most popular spices worldwide, and volatile organic compounds (VOCs) are its main metabolic products. The misuse or mixing of cinnamon on the market is quite serious. This study used gas chromatography-ion migration spectroscopy (GC-IMS) technology to analyze the VOCs of cinnamon samples. The measurement results showed that 66 VOCs were detected in cinnamon, with terpenes being the main component accounting for 45.45%, followed by aldehydes accounting for 21.21%. The content of esters and aldehydes was higher in RG-01, RG-02, and RG-04; the content of alcohols was higher in RG-01; and the content of ketones was higher in RG-02. Principal component analysis, cluster analysis, and partial least squares regression analysis can be performed on the obtained data to clearly distinguish cinnamon. According to the VIP results of PLS-DA, 1-Hexanol, 2-heptanone, ethanol, and other substances are the main volatile substances that distinguish cinnamon. This study combined GC-IMS technology with chemometrics to accurately identify cinnamon samples, providing scientific guidance for the efficient utilization of cinnamon. At the same time, this study is of great significance for improving the relevant quality standards of spices and guiding the safe use of spices.

Orthobunyavirus is the largest and most diverse genus in the family Peribunyaviridae. Orthobunyaviruses are widely distributed globally and pose threats to human and animal health. Ebinur Lake virus (EBIV) is a newly classified Orthobunyavirus detected in China, Russia, and Kenya. This study explored the antiviral effects of two broad-spectrum antiviral drugs, favipiravir and ribavirin, in a BALB/c mouse model. Favipiravir significantly improved the clinical symptoms of infected mice, reduced viral titer and RNA copies in serum, and extended overall survival. The median survival times of mice in the vehicle- and favipiravir-treated groups were 5 and 7 days, respectively. Favipiravir significantly reduced virus titers 10- to 100-fold in sera at all three time points compared to vehicle-treated mice. And favipiravir treatment effectively reduced the virus copies by approximately 10-fold across the three time points, relative to vehicle-treated mice. The findings expand the antiviral spectrum of favipiravir for orthobunyaviruses in vivo., Competing Interests: The authors declare no conflicts of interest.

Aiming at the problems of target detection models in traffic scenarios including a large number of parameters, heavy computational burden, and high application cost, this paper introduces an enhanced lightweight real-time detection algorithm, which exhibits higher detection speed and accuracy for vehicle detection. This paper considers the YOLOv7 algorithm as the benchmark model, designs a lightweight backbone network, and uses the MobileNetV3 lightweight network to extract target features. Inspired by the structure of SPPF, the spatial pyramid pooling module is reconfigured by incorporating GSConv, and a lightweight SPPFCSPC-GS module is designed, aiming to minimize the quantity of model parameters and enhance the training speed even further. Furthermore, the CA mechanism is integrated to enhance the feature extraction capability of the model. Finally, the MPDIoU loss function is utilized to optimize the model's training process. Experiments showcase that the refined YOLOv7 algorithm can achieve 98.2% mAP on the BIT-Vehicle dataset with 52.8% fewer model parameters than the original model and a 35.2% improvement in FPS. The enhanced model adeptly strikes a finer equilibrium between velocity and precision, providing favorable conditions for embedding the model into mobile devices.

Olibanum is a resinous traditional Chinese medicine that is directly used as a powder. It is widely used in China and is often combined with other traditional Chinese medicine powders to promote blood circulation and relieve pain, as well as to treat rheumatism, rheumatoid arthritis, and osteoarthritis. Powdered traditional Chinese medicine is often easily contaminated by microorganisms and 60 Co irradiation is one of the good sterilization methods. Volatile organic compounds (VOCs) are the main active ingredient of olibanum. The aim of this study was to validate the optimum doses of 60 Co irradiation and its effect on VOCs. 60 Co irradiation was applied in different doses of 0 kGy, 1.5 kGy, 3.0 kGy, and 6.0 kGy. Changes in VOCs were detected using gas chromatography ion mobility spectrometry. A total of 81 VOCs were identified. The odor fingerprint results showed that, with an increase in irradiation dose, most of the VOCs of olibanum changed. Through principal component analysis, cluster analysis, and partial least squares discriminant analysis, it was demonstrated that, at 1.5 kGy, the impact of radiation on the VOCs of olibanum was minimal, indicating this is a relatively good irradiation dose. This study provides a theoretical basis for the irradiation processing and quality control of resinous medicinal materials such as olibanum and it also provides a good reference for irradiation technology development and its application to functional foods, thus making it both significant from a research perspective and useful from an application perspective.

Mesophase pitch is usually prepared by radical polymerization or catalytic polymerization from coal tar, petroleum, and aromatic compounds, and the catalytic synthesis of mesophase pitch from pure aromatic compounds is more controllable in the preparation of high-quality mesophase pitch. However, the corrosive and highly toxic nature of the catalyst has limited the further development of this method. In this study, mesophase pitch was synthetized using ethylene tar and naphthalene as raw materials and boron trifluoride diethyl etherate as a catalyst. The effect of the catalytic reaction on the structure and properties of the mesophase pitch was investigated. The results show that naphthalene plays an important role in the mesophase content and reaction pressure (from above 6 MPa to 2.35 MPa). Mesophase pitch with fine-flow texture can be prepared by introducing more methylene groups, naphthenic structures, and aliphatic hydrocarbons during synthesis. Carbon fibers prepared from mesophase pitch show a split structure, and the thermal conductivity is 730 W/(m·K). This work provides theoretical support for lower toxicity and causticity and for reaction-controlled technology for the synthesis of high-purity mesophase pitch.

Targets faced by inverse synthetic aperture radar (ISAR) are often non-cooperative, with target maneuvering being the main manifestation of this non-cooperation. Maneuvers cause ISAR imaging results to be severely defocused, which can create huge difficulties in target identification. In addition, as the ISAR bandwidth continues to increase, the impact of migration through resolution cells (MTRC) on imaging results becomes more significant. Target non-cooperation may also result in sparse aperture, leading to the failure of traditional ISAR imaging algorithms. Therefore, this paper proposes an algorithm to realize MTRC correction and sparse aperture ISAR imaging for maneuvering targets simultaneously named whale optimization algorithm-fast iterative shrinkage thresholding algorithm (WOA-FISTA). In this algorithm, FISTA is used to perform MTRC correction and sparse aperture ISAR imaging efficiently and WOA is adopted to estimate the rotational parameter to eliminate the effects of maneuvering on imaging results. Experimental results based on simulation and measured datasets prove that the proposed algorithm implements sparse aperture ISAR imaging and MTRC correction for maneuvering targets simultaneously. The proposed algorithm achieves better results than traditional algorithms under different signal-to-noise ratio conditions.

The durability of wooden heritage objects and sites can be affected by external environmental factors, leading to decay, cracking, and other forms of deterioration, which might ultimately result in significant and irreversible loss. In this study, a FEVE resin was modified with Ag 2 O/OH-MWCNTS (MA), denoted as MAF, where three concentrations were prepared using in situ precipitation, and the resulting composite adhesive was characterized by a high viscosity and effective bacteriostatic properties, demonstrating a better viscosity and thermal stability, as well as antibacterial properties, than pure FEVE resin. The results show that MAF adhesives present good thermal stability, as evidenced by a lower mass loss rate following treatment at 800 °C compared to the pure FEVE resin. At a consistent shear rate, the viscosity of MAF demonstrates a notable increase with the proportion of MA, which is better than that of FEVE. This suggests that the nano-Ag 2 O particles in MA act as physical crosslinking agents in FEVE, improving the viscosity of the composite adhesive MAF. The adhesion strength between MAF and wood exhibits a similar trend, with wooden samples showing higher shear strengths as the proportion of MA increases in comparison to FEVE. Simultaneously, the antibacterial effects of the MAF adhesive exceeded 1 mm for Trichoderma , Aspergillus niger , and white rot fungi . The antibacterial activity of the MAF adhesive exhibited a direct correlation with the concentration of Ag 2 O/OH-MWCNTS, with the most pronounced inhibitory effect observed on Trichoderma. The MAF adhesive demonstrates promising prospects as an adhesive for wooden heritage artifacts, offering a novel approach for the rapid, environmentally friendly, and efficient development of composite adhesives with superior adhesive properties.

Circular RNAs (circRNAs) are important regulatory molecules involved in various biological processes. However, the potential function of circRNAs in the turning red process of Quercus mongolica leaves is unclear. This study used RNA-seq data to identify 6228 circRNAs in leaf samples from four different developmental stages and showed that 88 circRNAs were differentially expressed. A correlation analysis was performed between anthocyanins and the circRNAs. A total of 16 circRNAs that may be involved in regulating the colour of Mongolian oak leaves were identified. CircRNAs may affect the colour of Q. mongolica leaves by regulating auxin, cytokinin, gibberellin, ethylene, and abscisic acid. This study revealed the potential role of circRNAs in the colour change of Q. mongolica leaves.

Fiber diameter is an important characteristic that determines the quality and economic value of rabbit wool. This study aimed to investigate the genetic determinants of wool fiber diameter through an integration analysis using transcriptomic and proteomic datasets from hair follicles of coarse and fine wool from Angora rabbits. Using a 4D label-free technique, we identified 423 differentially expressed proteins (DEPs) in hair follicles of coarse and fine wool in Angora rabbits. Eighteen DEPs were examined using parallel reaction monitoring, which verified the reliability of our proteomic data. Functional enrichment analysis revealed that a set of biological processes and signaling pathways related to wool growth and hair diameter were strongly enriched by DEPs with fold changes greater than two, such as keratinocyte differentiation, skin development, epidermal and epithelial cell differentiation, epidermis and epithelium development, keratinization, and estrogen signaling pathway. Association analysis and protein-protein interaction network analysis further showed that the keratin (KRT) family members, including KRT77, KRT82, KRT72, KRT32, and KRT10, as well as CASP14 and CDSN, might be key factors contributing to differences in fiber diameter. Our results identified DEPs in hair follicles of coarse and fine wool and promoted understanding of the molecular mechanisms underlying wool fiber diameter variation among Angora rabbits.

China leads the world in freshwater pearl production, an industry in which the triangle sail mussel ( Sinohyriopsis cumingii ) plays a pivotal role. In this paper, we report a high-quality chromosome-level genome assembly of S. cumingii with a size of 2.90 Gb-the largest yet reported among bivalves-and 89.92% anchorage onto 19 linkage groups. The assembled genome has 37,696 protein-coding genes and 50.86% repeat elements. A comparative genomic analysis revealed expansions of 752 gene families, mostly associated with biomineralization, and 237 genes under strong positive selection. Notably, the fibrillin gene family exhibited gene family expansion and positive selection simultaneously, and it also exhibited multiple high expressions after mantle implantation by transcriptome analysis. Furthermore, RNA silencing and an in vitro calcium carbonate crystallization assay highlighted the pivotal role played by one fibrillin gene in calcium carbonate deposition and aragonite transformation. This study provides a valuable genomic resource and offers new insights into the mechanism of pearl biomineralization.

In the field of highway construction, the application of styrene-butadiene rubber (SBR)-modified asphalt has gained popularity across different levels of road surfaces. A crucial aspect in ensuring the efficacy of this modification lies in the compatibility between SBR and the matrix asphalt. To address this, the current study utilizes molecular dynamics simulation as a technique. By establishing a model for the SBR-modified asphalt mixture, the research quantifies the compatibility level between the SBR modifier and the asphalt. The aim is to uncover the underlying mechanisms of compatibility between the SBR modifier and the base asphalt, ultimately contributing to the improvement of the storage stability of SBR-modified asphalt, which holds significant importance. The investigation began with the creation of models for both the base asphalt and the SBR modifier. A model for the SBR-modified asphalt blending system was then formulated based on these initial models. After undergoing geometry optimization and annealing procedures, the model attained its lowest energy state, providing a reliable basis for examining the performance of SBR-modified asphalt. The study proceeded to calculate solubility parameters and interaction energies of the system to evaluate the compatibility between the SBR modifier and the base asphalt at various temperatures. The analysis of these parameters shed light on the compatibility mechanism between the two components. Notably, it was found that at a temperature of 160 ℃, the compatibility was significantly enhanced. The findings were further corroborated through scanning electron microscope and rheological tests. The outcomes of this research offer theoretical guidance for the application of SBR-modified asphalt.

S -nitrosoglutathione reductase (GSNOR) is a well-known regulator in controlling protein S -nitrosylation modification and nitric oxide (NO) homeostasis. Here, a GSNOR inhibitor N6022 and SlGSNOR silencing were applied to investigate the roles of SlGSNOR in tomato fruit postharvest ripening. We found that the application of N6022 and S -nitrosoglutathione (GSNO, a NO donor), and SlGSNOR silencing delayed the transition of fruit skin color by improving total chlorophyll level by 88.57%, 44.78%, and 91.03%, respectively. Meanwhile, total carotenoid and lycopene contents were reduced by these treatments. Concurrently, the activity of chlorophyll biosynthesis enzymes and the expression of related genes were upregulated, and the transcript abundances of total carotenoid bioproduction genes were downregulated, by N6022 and GSNO treatments and SlGSNOR silencing. In addition, fruit softening was postponed by N6022, GSNO, and SlGSNOR silencing, through delaying the decrease of firmness and declining cell wall composition; structure-related enzyme activity; and gene expression levels. Furthermore, N6022, GSNO, and SlGSNOR silencing enhanced the accumulation of titratable acid; ascorbic acid; total phenol; and total flavonoid, but repressed the content of soluble sugar and soluble protein accompanied with the expression pattern changes of nutrition-related genes. In addition, the endogenous NO contents were elevated by 197.55%; 404.59%; and 713.46%, and the endogenous SNOs contents were enhanced by 74.65%; 93.49%; and 94.85%; by N6022 and GSNO treatments and SlGSNOR silencing, respectively. Altogether, these results indicate that SlGSNOR positively promotes tomato postharvest fruit ripening, which may be largely on account of its negative roles in the endogenous NO level.

Chilean peppers, cultivated from Capsicum pubescens , are globally renowned as popular vegetable and spice crops. C. pubescens belongs to the Capsicum L. (pepper) family and is one of the five pepper cultivars grown in China. In this study, we assembled and annotated the complete mt genome of C. pubescens . We investigated several aspects of its genome, including characteristics, codon usage, RNA editing sites, repeat sequences, selective pressure, gene clusters, and phylogenetic relationships. Furthermore, we compared it with other plant mt genomes. The data we obtained will provide valuable information for studying evolutionary processes in the Capsicum genus and will assist in the functional analysis of Capsicum mitogenomes.

Mer and c-Met kinases, which are commonly overexpressed in various tumors, are ideal targets for the development of antitumor drugs. This study focuses on the design, synthesis, and evaluation of several 2-substituted aniline pyrimidine derivatives as highly potent dual inhibitors of Mer and c-Met kinases for effective tumor treatment. Compound 18c emerged as a standout candidate, demonstrating robust inhibitory activity against Mer and c-Met kinases, with IC 50 values of 18.5 ± 2.3 nM and 33.6 ± 4.3 nM, respectively. Additionally, compound 18c displayed good antiproliferative activities on HepG2, MDA-MB-231, and HCT116 cancer cells, along with favorable safety profiles in hERG testing. Notably, it exhibited exceptional liver microsomal stability in vitro, with a half-life of 53.1 min in human liver microsome. Compound 18c also exhibited dose-dependent cytotoxicity and hindered migration of HCT116 cancer cells, as demonstrated in apoptosis and migration assays. These findings collectively suggest that compound 18c holds promise as a dual Mer/c-Met agent for cancer treatment.

Crocin is one of the most valuable components of the Chinese medicinal plant Crocus sativus and is widely used in the food, cosmetics, and pharmaceutical industries. Traditional planting of C. sativus is unable to fulfill the increasing demand for crocin in the global market, however, such that researchers have turned their attention to the heterologous production of crocin in a variety of hosts. At present, there are reports of successful heterologous production of crocin in Escherichia coli , Saccharomyces cerevisiae , microalgae, and plants that do not naturally produce crocin. Of these, the microalga Dunaliella salina , which produces high levels of β -carotene, the substrate for crocin biosynthesis, is worthy of attention. This article describes the biosynthesis of crocin, compares the features of each heterologous host, and clarifies the requirements for efficient production of crocin in microalgae.

Cucurbitacin B (Cu B), a triterpenoid compound, has anti-inflammatory and antioxidant activities. Most studies only focus on the hepatoprotective activity of Cu B, and little effort has been geared toward exploring the effect of Cu B on the prostate. Our study identified that Cu B inhibited the proliferation of the benign prostatic hyperplasia epithelial cell line (BPH-1). At the molecular level, Cu B upregulated MDM2 and thrombospondin 1 ( THBS1 ) mRNA levels. Immunocytochemistry results revealed that the protein expressions of p53 and MDM2 were upregulated in BPH-1 cells. Furthermore, Cu B upregulated THBS1 expression and downregulated COX-2 expression in the BPH-1 cell supernatant. Altogether, Cu B may inhibit prostate cell proliferation by activating the p53/MDM2 signaling cascade and downregulating the COX-2 expression.

Osteoarthritis (OA) is a chronic, degenerative joint disease presenting a significant global health threat. While current therapeutic approaches primarily target symptom relief, their efficacy in repairing joint damage remains limited. Recent research has highlighted mesenchymal stem cells (MSCs) as potential contributors to cartilage repair, anti-inflammatory modulation, and immune regulation in OA patients. Notably, MSCs from different sources and their derivatives exhibit variations in their effectiveness in treating OA. Moreover, pretreatment and gene editing techniques of MSCs can enhance their therapeutic outcomes in OA. Additionally, the combination of novel biomaterials with MSCs has shown promise in facilitating the repair of damaged cartilage. This review summarizes recent studies on the role of MSCs in the treatment of OA, delving into their advantages and exploring potential directions for development, with the aim of providing fresh insights for future research in this critical field.

Unsupervised learning has shown immense potential in object tracking, where accurate classification and regression are crucial for unsupervised trackers. However, the classification and regression branches of most unsupervised trackers calculate object similarities by sharing cross-correlation modules. This leads to high coupling between different branches, thus hindering the network performance. To address the above issue, we propose a Decoupled Learning-based Unsupervised Tracker (DLUT). Specifically, we separate the training pipelines of different branches to unlock their inherent learning potential so that different branches can fully explore the focused feature regions of interest. Furthermore, we design independent adaptive decoupling-correlation modules according to the characteristics of each branch to obtain more discriminative and easily locatable feature response maps. Finally, to suppress the noise interference brought by unsupervised pseudo-label training and highlight the foreground object, we propose a novel suppression-ranking-based unsupervised training strategy. Extensive experiments demonstrate that our DLUT outperforms state-of-the-art unsupervised trackers.

The engineering of thermo-optic effects has found broad applications in integrated photonic devices, facilitating efficient light manipulation to achieve various functionalities. Here, we perform both an experimental characterization and a theoretical analysis of these effects in integrated microring resonators made from high-index doped silica, which have had many applications in integrated photonics and nonlinear optics. By fitting the experimental results with theory, we obtain fundamental parameters that characterize their thermo-optic performance, including the thermo-optic coefficient, the efficiency of the optically induced thermo-optic process, and the thermal conductivity. The characteristics of these parameters are compared to those of other materials commonly used for integrated photonic platforms, such as silicon, silicon nitride, and silica. These results offer a comprehensive insight into the thermo-optic properties of doped silica-based devices. Understanding these properties is essential for efficiently controlling and engineering them in many practical applications.

Amylase is an indispensable hydrolase in insect growth and development. Its varied enzymatic parameters cause insects to have strong stress resistance. Amylase gene replication is a very common phenomenon in insects, and different copies of amylase genes enable changes in its location and function. In addition, the classification, structure, and interaction between insect amylase inhibitors and amylases have also invoked the attention of researchers. Some plant-derived amylase inhibitors have inhibitory activities against insect amylases and even mammalian amylases. In recent years, an increasing number of studies have clarified the effects of pesticides on the amylase activity of target and non-target pests, which provides a theoretical basis for exploring safe and efficient pesticides, while the exact lethal mechanisms and safety in field applications remain unclear. Here, we summarize the most recent advances in insect amylase studies, including its sequence and characteristics and the regulation of amylase inhibitors (α-AIs). Importantly, the application of amylases as the nanocide trigger, RNAi, or other kinds of pesticide targets will be discussed. A comprehensive foundation will be provided for applying insect amylases to the development of new-generation insect management tools and improving the specificity, stability, and safety of pesticides.

The incorporation of a naphthyl curing agent (NCA) can enhance the thermal stability of pressure-sensitive adhesives (PSAs). In this study, a PSA matrix was synthesized using a solution polymerization process and consisted of butyl acrylate, acrylic acid, and an ethyl acrylate within an acrylic copolymer. Benzoyl peroxide was used as an initiator during the synthesis. To facilitate the UV curing of the solvent-borne PSAs, glycidyl methacrylate was added to introduce unsaturated carbon double bonds. The resulting UV-curable acrylic PSA tapes exhibited longer holding times at high temperatures (150 °C) compared to uncross-linked PSA tapes, without leaving any residues on the substrate surface. The thermal stability of the PSA was further enhanced by adding more NCA and increasing the UV dosage. This may be attributed to the formation of cross-linking networks within the polymer matrix at higher doses. The researchers successfully balanced the adhesion performance and thermal stability by modifying the amount of NCA and UV radiation, despite the peel strength declining and the holding duration shortening. This research also investigated the effects of cross-linking density on gel content, molecular weight, glass transition temperature, and other properties of the PSAs.

The anthocyanin biosynthetic pathway is the main pathway regulating floral coloration in Iris germanica , a well-known ornamental plant. We investigated the transcriptome profiles and targeted metabolites to elucidate the relationship between genes and metabolites in anthocyanin biosynthesis in the bitone flower cultivar 'Clarence', which has a deep blue outer perianth and nearly white inner perianth. In this study, delphinidin-, pelargonidin-, and cyanidin-based anthocyanins were detected in the flowers. The content of delphinidin-based anthocyanins increased with the development of the flower. At full bloom (stage 3), delphinidin-based anthocyanins accounted for most of the total anthocyanin metabolites, whereas the content of pelargonidin- and cyanidin-based anthocyanins was relatively low. Based on functional annotations, a number of novel genes in the anthocyanin pathway were identified, which included early biosynthetic genes IgCHS , IgCHI, and IgF3H and late biosynthetic genes Ig F3'5'H , IgANS, and IgDFR . The expression of key structural genes encoding enzymes, such as IgF3H , Ig F3'5'H , IgANS, and IgDFR , was significantly upregulated in the outer perianth compared to the inner perianth. In addition, most structural genes exhibited their highest expression at the half-color stage rather than at the full-bloom stage, which indicates that these genes function ahead of anthocyanins synthesis. Moreover, transcription factors (TFs) of plant R2R3-myeloblastosis (R2R3-MYB) related to the regulation of anthocyanin biosynthesis were identified. Among 56 R2R3-MYB genes, 2 members belonged to subgroup 4, with them regulating the expression of late biosynthetic genes in the anthocyanin biosynthetic pathway, and 4 members belonged to subgroup 7, with them regulating the expression of early biosynthetic genes in the anthocyanin biosynthetic pathway. Quantitative real-time PCR (qRT-PCR) analysis was used to validate the data of RNA sequencing (RNA-Seq). The relative expression profiles of most candidate genes were consistent with the FPKM of RNA-seq. This study identified the key structural genes encoding enzymes and TFs that affect anthocyanin biosynthesis, which provides a basis and reference for the regulation of plant anthocyanin biosynthesis in I. germanica.