Preparation and Decomposition of Spherical CL-20 Composites with Enhanced Laser Absorbance and Decreased Mechanical Sensitivity.

Direct initiation of secondary explosives by a semiconductor laser is highly demanded, but it is challenging to exclude the use of sensitive primers. Most laser-sensitive energetic materials are usually mechanically sensitive. In order to reduce the mechanical sensitivity (MS) of 2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane (CL-20) while improving laser absorbance in the near-infrared band, spherical CL-20 composites (SCCs) embedded with nano aluminum (Al) powder and graphene-based catalyst (GO-CHZ-Co) were prepared by a spray drying method. These SCCs have been characterized comprehensively in terms of their morphologies, particle size distribution, laser absorbance, thermal decomposition behaviors, MS, and laser ignition properties. Results show that the maximum critical impact energy of SCCs was 3.8 J, which is 2.8 J higher than that of pristine ε-CL-20. The critical friction load was increased by at most 108 N compared to pristine CL-20. The absorbance has also been significantly increased up to almost 70% in the wavelength between 400 and 1400 nm, where the peak absorption is located in the region of 800-900 nm. In addition, the initial decomposition temperature (Ti) of SCCs is lower than that of pure CL-20, especially in the presence of GO-CHZ-Co. The apparent activation energy (Ea) for the decomposition of SCCs was largely dependent on the particle size of Al. Preliminary ignition tests indicate that the SCCs can be ignited successfully by a small-power laser.

Assessing the Accuracy and Efficiency of Free Energy Differences Obtained from Reweighted Flow-Based Probabilistic Generative Models.

Computing free energy differences between metastable states characterized by nonoverlapping Boltzmann distributions is often a computationally intensive endeavor, usually requiring chains of intermediate states to connect them. Targeted free energy perturbation (TFEP) can significantly lower the computational cost of FEP calculations by choosing a set of invertible maps used to directly connect the distributions of interest, achieving the necessary statistically significant overlaps without sampling any intermediate states. Probabilistic generative models (PGMs) based on normalizing flow architectures can make it much easier via machine learning to train invertible maps needed for TFEP. However, the accuracy and applicability of approaches based on empirically learned maps depend crucially on the choice of reweighting method adopted to estimate the free energy differences. In this work, we assess the accuracy, rate of convergence, and data efficiency of different free energy estimators, including exponential averaging, Bennett acceptance ratio (BAR), and multistate Bennett acceptance ratio (MBAR), in reweighting PGMs trained by maximum likelihood on limited amounts of molecular dynamics data sampled only from end-states of interest. We carry out the comparisons on a set of simple but representative case studies, including conformational ensembles of alanine dipeptide and ibuprofen. Our results indicate that BAR and MBAR are both data efficient and robust, even in the presence of significant model overfitting in the generation of invertible maps. This analysis can serve as a stepping stone for the deployment of efficient and quantitatively accurate ML-based free energy calculation methods in complex systems.

LPS exacerbates TRPV4-mediated itch through the intracellular TLR4-PI3K signalling.

Pruritus is often accompanied with bacterial infections, but the underlying mechanism is not fully understood. Although previous studies revealed that lipopolysaccharides (LPS) could directly activate TRPV4 channel and TRPV4 is involved in the generation of both acute itch and chronic itch, whether and how LPS affects TRPV4-mediated itch sensation remains unclear. Here, we showed that LPS-mediated TRPV4 sensitization exacerbated GSK101-induced scratching behaviour in mice. Moreover, this effect was compromised in TLR4-knockout mice, suggesting LPS acted through a TLR4-dependent mechanism. Mechanistically, LPS enhanced GSK101-evoked calcium influx in mouse ear skin cells and HEK293T cells transfected with TRPV4. Further, LPS sensitized TRPV4 channel through the intracellular TLR4-PI3K-AKT signalling. In summary, our study found a modulatory role of LPS in TRPV4 function and highlighted the TLR4-TRPV4 interaction in itch signal amplification.

Electrical Responsive Coating with a Multilayered TiO2-SnO2-RuO2 Heterostructure on Ti for Controlling Antibacterial Ability and Improving Osseointegration.

The bacterial infection and poor osseointegration of Ti implants could significantly compromise their applications in bone repair and replacement. Based on the carrier separation ability of the heterojunction and the redox reaction of pseudocapacitive metal oxides, we report an electrically responsive TiO2-SnO2-RuO2 coating with a multilayered heterostructure on a Ti implant. Owing to the band gap structure of the TiO2-SnO2-RuO2 coating, electron carriers are easily enriched at the coating surface, enabling a response to the endogenous electrical stimulation of the bone. With the formation of SnO2-RuO2 pseudocapacitance on the modified surface, the postcharging mode can significantly change the surface chemical state of the coating due to the redox reaction, enhancing the antibacterial ability and osteogenesis-related gene expression of the human bone marrow mesenchymal stem cells. Owing to the attraction for Ca2+, only the negatively postcharged SnO2@RuO2 can promote apatite deposition. The in vivo experiment reveals that the S-SnO2@RuO2-NP could effectively kill the bacteria colonized on the surface and promote osseointegration with the synostosis bonding interface. Thus, negatively charging the electrically responsive coating of TiO2-SnO2-RuO2 is a good strategy to endow modified Ti implants with excellent antibacterial ability and osseointegration.

Accurate classification of glomerular diseases by hyperspectral imaging and transformer.

BACKGROUND AND OBJECTIVE: In renal disease research, precise glomerular disease diagnosis is crucial for treatment and prognosis. Currently reliant on invasive biopsies, this method bears risks and pathologist-dependent variability, yielding inconsistent results. There is a pressing need for innovative diagnostic tools that enhance traditional methods, streamline processes, and ensure accurate and consistent disease detection. METHODS: In this study, we present an innovative Convolutional Neural Networks-Vision Transformer (CVT) model leveraging Transformer technology to refine glomerular disease diagnosis by fusing spectral and spatial data, surpassing traditional diagnostic limitations. Using interval sampling, preprocessing, and wavelength optimization, we also introduced the Gramian Angular Field (GAF) method for a unified representation of spectral and spatial characteristics. RESULTS: We captured hyperspectral images ranging from 385.18 nm to 1009.47 nm and employed various methods to extract sample features. Initial models based solely on spectral features achieved a accuracy of 85.24 %. However, the CVT model significantly outperformed these, achieving an average accuracy of 94 %. This demonstrates the model's superior capability in utilizing sample data and learning joint feature representations. CONCLUSIONS: The CVT model not only breaks through the limitations of existing diagnostic techniques but also showcases the vast potential of non-invasive, high-precision diagnostic technology in supporting the classification and prognosis of complex glomerular diseases. This innovative approach could significantly impact future diagnostic strategies in renal disease research. CONCISE ABSTRACT: This study introduces a transformative hyperspectral image classification model leveraging a Transformer to significantly improve glomerular disease diagnosis accuracy by synergizing spectral and spatial data, surpassing conventional methods. Through a rigorous comparative analysis, it was determined that while spectral features alone reached a peak accuracy of 85.24 %, the novel Convolutional Neural Network-Transformer (CVT) model's integration of spatial-spectral features via the Gramian Angular Field (GAF) method markedly enhanced diagnostic precision, achieving an average accuracy of 94 %. This methodological innovation not only overcomes traditional diagnostic limitations but also underscores the potential of non-invasive, high-precision technologies in advancing the classification and prognosis of complex renal diseases, setting a new benchmark in the field.

The role of the natural compound naringenin in AMPK-mitochondria modulation and colorectal cancer inhibition.

BACKGROUND: Although AMP-activated protein kinase (AMPK) has been extensively studied in cellular processes, the understanding of its substrates, downstream functions, contributions to cell fate and colorectal cancer (CRC) progression remains incomplete. PURPOSE: The aim of this study was to investigate the effects and mechanisms of naringenin on CRC. METHODS: The biological and cellular properties of naringenin and its anticancer activity were evaluated in CRC. In addition, the effect of combined treatment with naringenin and 5-fluorouracil on tumor growth in vitro and in vivo was evaluated. RESULTS: The present study found that naringenin inhibits the proliferation of CRC and promote its apoptosis. Compared with the naringenin group, naringenin combined with 5-fluorouracil had significant effect on inhibiting cell proliferation and promoting its apoptosis. It is showed that naringenin activates AMPK phosphorylation and mitochondrial fusion in CRC. Naringenin combined with 5-fluorouracil significantly reduces cardiotoxicity and liver damage induced by 5-fluorouracil in nude mice bearing subcutaneous CRC tumors, and attenuates colorectal injuries in azoxymethane/DSS dextran sulfate (AOM/DSS)-induced CRC. The combination of these two drugs alters mitochondrial function by increasing reactive oxygen species (ROS) levels and decreasing the mitochondrial membrane potential (MMP), thereby stimulating AMPK/mTOR signaling. Mitochondrial dynamics are thereby regulated by activating the AMPK/p-AMPK pathway, and mitochondrial homeostasis is coordinated through increased mitochondrial fusion and reduced fission to activate apoptosis in cancer cells. CONCLUSIONS: Our data suggest that naringenin is important for inhibiting CRC proliferation, possibly through the AMPK pathway, to regulate mitochondrial function and induce apoptosis in CRC.

Plasma extracellular vesicles proteomics in meningioma patients.

Tumor derived Extracellular vesicles (EVs) in circulating system may contain tumor-specific markers, and EV detection in body fluids could become an important tool for early tumor diagnosis, prognosis assessment. Meningiomas are the most common benign intracranial tumors, few studies have revealed specific protein markers for meningiomas from patients' body fluids. In this study, using proximity labeling technology and non-tumor patient plasma as a control, we detected protein levels of EVs in plasma samples from meningioma patients before and after surgery. Through bioinformatics analysis, we discovered that the levels of EV count and protein count in meningioma patients were significantly higher than those in healthy controls, and were significantly decreased postoperatively. Among EV proteins in meningioma patients, the levels of MUC1, SIGLEC11, E-Cadherin, KIT, and TASCTD2 were found not only significantly elevated than those in healthy controls, but also significantly decreased after tumor resection. Moreover, using publicly available GEO databases, we verified that the mRNA level of MUC1, SIGLEC11, and CDH1 in meningiomas were significantly higher in comparison with normal dura mater tissues. Additionally, by analyzing human meningioma specimens collected in this study, we validated the protein levels of MUC1 and SIGLEC11 were significantly increased in WHO grade 2 meningiomas and were positively correlated with tumor proliferation levels. This study indicates that meningiomas secret EV proteins into circulating system, which may serve as specific markers for diagnosis, malignancy predicting and tumor recurrent assessment.

The first report and biological characterization of Avian Orthoavulavirus 16 in wild migratory waterfowl and domestic poultry in China reveal a potential threat to birds.

RESEARCH HIGHLIGHTS: First confirmation of AOAV-16 in domestic and wild birds in China.AOAV-16 are low virulent viruses for chickens.Co-circulation/co-infection of AOAV-16 and H9N2 subtype AIV enhanced pathogenicity.Different intergenic sequences and recombination events exist within AOAV-16.

The epigenetically regulated PP1α expression by KDM1A may contribute to oxycodone conditioned place preference in mice.

The lysine-specific demethylase 1 (KDM1A) is reported to be a regulator in learning and memory. However, the effect of KDM1A in oxycodone rewarding memory has yet to be studied. In our study, rewarding memory was assessed by using conditioned place preference (CPP) in male mice. Next generation sequencing and chromatin immunoprecipitation-PCR were used to explore the molecular mechanisms. Oxycodone significantly decreased PP1α mRNA and protein levels in hippocampal neurons. Oxycodone significantly increased KDM1A and H3K4me1 levels, while significantly decreased H3K4me2 levels in a time- and dose-dependent manner. Behavioral data demonstrated that intraperitoneal injection of ORY-1001 (KDM1A inhibitor) or intra-hippocampal injection of KDM1A siRNA/shRNA blocked the acquisition and expression of oxycodone CPP and facilitated the extinction of oxycodone CPP. The decrease of PP1α was markedly blocked by the injection of ORY-1001 or KDM1A siRNA/shRNA. Oxycodone-induced enhanced binding of CoRest with KDM1A and binding of CoRest with the PP1α promoter was blocked by ORY-1001. The level of H3K4me2 demethylation was also decreased by the treatment. The results suggest that oxycodone-induced upregulation of KDM1A via demethylation of H3K4me2 promotes the binding of CoRest with the PP1α promoter, and the subsequent decrease in PP1α expression in hippocampal neurons may contribute to oxycodone reward.

An improved genome assembly of Chrysanthemum nankingense reveals expansion and functional diversification of terpene synthase gene family.

BACKGROUND: Terpenes are important components of plant aromas, and terpene synthases (TPSs) are the key enzymes driving terpene diversification. In this study, we characterized the volatile terpenes in five different Chrysanthemum nankingense tissues. In addition, genome-wide identification and expression analysis of TPS genes was conducted utilizing an improved chromosome-scale genome assembly and tissue-specific transcriptomes. The biochemical functions of three representative TPSs were also investigated. RESULTS: We identified tissue-specific volatile organic compound (VOC) and volatile terpene profiles. The improved Chrysanthemum nankingense genome assembly was high-quality, including a larger assembled size (3.26 Gb) and a better contig N50 length (3.18 Mb) compared to the old version. A total of 140 CnTPS genes were identified, with the majority representing the TPS-a and TPS-b subfamilies. The chromosomal distribution of these TPS genes was uneven, and 26 genes were included in biosynthetic gene clusters. Closely-related Chrysanthemum taxa were also found to contain diverse TPS genes, and the expression profiles of most CnTPSs were tissue-specific. The three investigated CnTPS enzymes exhibited versatile activities, suggesting multifunctionality. CONCLUSIONS: We systematically characterized the structure and diversity of TPS genes across the Chrysanthemum nankingense genome, as well as the potential biochemical functions of representative genes. Our results provide a basis for future studies of terpene biosynthesis in chrysanthemums, as well as for the breeding of improved chrysanthemum varieties.

Association of the SHOX2 and RASSF1A methylation levels with the pathological evolution of early-stage lung adenocarcinoma.

Background The methylation of SHOX2 and RASSF1A shows promise as a potential biomarker for the early screening of lung cancer, offering a solution to remedy the limitations of morphological diagnosis. The aim of this study is to diagnose lung adenocarcinoma by measuring the methylation levels of SHOX2 and RASSF1A, and provide an accurate pathological diagnosis to predict the invasiveness of lung cancer prior to surgery.Material and methods The methylation levels of SHOX2 and RASSF1A were quantified using a LungMe® test kit through methylation-specific PCR (MS-PCR). The diagnostic efficacy of SHOX2 and RASSF1A and the cutoff values were validated using ROC curve analysis. The hazardous factors influencing the invasiveness of lung adenocarcinoma were calculated using multiple regression.Results: The cutoff values of SHOX2 and RASSF1A were 8.3 and 12.0, respectively. The sensitivities of LungMe® in IA, MIA and AIS patients were 71.3% (122/171), 41.7% (15/36), and 16.1% (5/31) under the specificity of 94.1% (32/34) for benign lesions. Additionally, the methylation level of SHOX2, RASSF1A and LungMe® correlated with the high invasiveness of clinicopathological features, such as age, gender, tumor size, TNM stage, pathological type, pleural invasion and STAS. The tumor size, age, CTR values and LungMe® methylation levels were identified as independent hazardous factors influencing the invasiveness of lung adenocarcinoma.Conclusion: SHOX2 and RASSF1A combined methylation can be used as an early detection indicator of lung adenocarcinoma. SHOX2 and RASSF1A combined (LungMe®) methylation is significantly correlated to age, gender, tumor size, TNM stage, pathological type, pleural invasion and STAS. The SHOX2 and RASSF1A methylation levels, tumor size and CTR values could predict the invasiveness of the tumor prior to surgery, thereby providing guidance for the surgical procedure.

Amorphous Bismuth-Tin Oxide Nanosheets with Optimized C-N Coupling for Efficient Urea Synthesis.

Closing the carbon and nitrogen cycles by electrochemical methods using renewable energy to convert abundant or harmful feedstocks into high-value C- or N-containing chemicals has the potential to transform the global energy landscape. However, efficient conversion avenues have to date been mostly realized for the independent reduction of CO2 or NO3-. The synthesis of more complex C-N compounds still suffers from low conversion efficiency due to the inability to find effective catalysts. To this end, here we present amorphous bismuth-tin oxide nanosheets, which effectively reduce the energy barrier of the catalytic reaction, facilitating efficient and highly selective urea production. With enhanced CO2 adsorption and activation on the catalyst, a C-N coupling pathway based on *CO2 rather than traditional *CO is realized. The optimized orbital symmetry of the C- (*CO2) and N-containing (*NO2) intermediates promotes a significant increase in the Faraday efficiency of urea production to an outstanding value of 78.36% at -0.4 V vs RHE. In parallel, the nitrogen and carbon selectivity for urea formation is also enhanced to 90.41% and 95.39%, respectively. The present results and insights provide a valuable reference for the further development of new catalysts for efficient synthesis of high-value C-N compounds from CO2.

Achieving Negatively Charged Pt Single Atoms on Amorphous Ni(OH)2 Nanosheets with Promoted Hydrogen Absorption in Hydrogen Evolution.

Single-atom (SA) catalysts with nearly 100% atom utilization have been widely employed in electrolysis for decades, due to the outperforming catalytic activity and selectivity. However, most of the reported SA catalysts are fixed through the strong bonding between the dispersed single metallic atoms with nonmetallic atoms of the substrates, which greatly limits the controllable regulation of electrocatalytic activity of SA catalysts. In this work, Pt-Ni bonded Pt SA catalyst with adjustable electronic states was successfully constructed through a controllable electrochemical reduction on the coordination unsaturated amorphous Ni(OH)2 nanosheet arrays. Based on the X-ray absorption fine structure analysis and first-principles calculations, Pt SA was bonded with Ni sites of amorphous Ni(OH)2, rather than conventional O sites, resulting in negatively charged Ptδ-. In situ Raman spectroscopy revealed that the changed configuration and electronic states greatly enhanced absorbability for activated hydrogen atoms, which were the essential intermediate for alkaline hydrogen evolution reaction. The hydrogen spillover process was revealed from amorphous Ni(OH)2 that effectively cleave the H-O-H bond of H2O and produce H atom to the Pt SA sites, leading to a low overpotential of 48 mV in alkaline electrolyte at -1000 mA cm-2 mg-1Pt, evidently better than commercial Pt/C catalysts. This work provided new strategy for the controllable modulation of the local structure of SA catalysts and the systematic regulation of the electronic states.

Roles of glutamic pyruvate transaminase 2 in reprogramming of airway epithelial lipidomic and metabolomic profiles after smoking.

Metabolic abnormalities represent one of the pathological features of chronic obstructive pulmonary disease (COPD). Glutamic pyruvate transaminase 2 (GPT2) is involved in glutamate metabolism and lipid synthesis pathways, whilst the exact roles of GPT2 in the occurrence and development of COPD remains uncertain. This study aims at investigating how GPT2 and the associated genes modulate smoking-induced airway epithelial metabolism and damage by reprogramming lipid synthesis. The circulating or human airway epithelial metabolomic and lipidomic profiles of COPD patients or cell-lines explored with smoking were assessed to elucidate the pivotal roles of GPT2 in reprogramming processes. We found that GPT2 regulate the reprogramming of lipid metabolisms caused by smoking, especially phosphatidylcholine (PC) and triacylglycerol (TAG), along with changes in the expression of lipid metabolism-associated genes. GPT2 modulated cell sensitivities and survival in response to smoking by enhancing mitochondrial functions and maintaining lipid and energy homeostasis. Our findings provide evidence for the involvement of GPT2 in the reprogramming of airway epithelial lipids following smoking, as well as the molecular mechanisms underlying GPT2-mediated regulation, which may offer an alternative of therapeutic strategies for chronic lung diseases.

Population genetic variation and geographic distribution of suitable areas of Coptis species in China.

Introduction: The rhizomes of Coptis plants have been used in traditional Chinese medicine over 2000 years. Due to increasing market demand, the overexploitation of wild populations, habitat degradation and indiscriminate artificial cultivation of Coptis species have severely damaged the native germplasms of species in China. Methods: Genome-wide simple-sequence repeat (SSR) markers were developed using the genomic data of C. chinensis. Population genetic diversity and structure of 345 Coptis accessions collected from 32 different populations were performed based on these SSRs. The distribution of suitable areas for three taxa in China was predicted and the effects of environmental variables on genetic diversity in relation to different population distributions were further analyzed. Results: 22 primer pairs were selected as clear, stable, and polymorphic SSR markers. These had an average of 16.41 alleles and an average polymorphism information content (PIC) value of 0.664. In the neighbor-joining (N-J) clustering analysis, the 345 individuals clustered into three groups, with C. chinensis, C. chinensis var. brevisepala and C. teeta being clearly separated. All C. chinensis accessions were further divided into four subgroups in the population structure analysis. The predicted distributions of suitable areas and the environmental variables shaping these distributions varied considerably among the three species. Discussion: Overall, the amount of solar radiation, precipitation and altitude were the most important environmental variables influencing the distribution and genetic variation of three species. The findings will provide key information to guide the conservation of genetic resources and construction of a core reserve for species.

A novel long non-coding RNA LINC00524 facilitates invasion and metastasis through interaction with TDP43 in breast cancer.

Breast cancer (BC) remains a significant health concern worldwide, with metastasis being a primary contributor to patient mortality. While advances in understanding the disease's progression continue, the underlying mechanisms, particularly the roles of long non-coding RNAs (lncRNAs), are not fully deciphered. In this study, we examined the influence of the lncRNA LINC00524 on BC invasion and metastasis. Through meticulous analyses of TCGA and GEO data sets, we observed a conspicuous elevation of LINC00524 expression in BC tissues. This increased expression correlated strongly with a poorer prognosis for BC patients. A detailed Gene Ontology analysis suggested that LINC00524 likely exerts its effects through RNA-binding proteins (RBPs) mechanisms. Experimentally, LINC00524 was demonstrated to amplify BC cell migration, invasion and proliferation in vitro. Additionally, in vivo tests showed its potent role in promoting BC cell growth and metastasis. A pivotal discovery was LINC00524's interaction with TDP43, which leads to the stabilization of TDP43 protein expression, an element associated with unfavourable BC outcomes. In essence, our comprehensive study illuminates how LINC00524 accelerates BC invasion and metastasis by binding to TDP43, presenting potential avenues for therapeutic interventions.

Novel Uncertainty Quantification through Perturbation-Assisted Sample Synthesis.

This paper introduces a novel Perturbation-Assisted Inference (PAI) framework utilizing synthetic data generated by the Perturbation-Assisted Sample Synthesis (PASS) method. The framework focuses on uncertainty quantification in complex data scenarios, particularly involving unstructured data while utilizing deep learning models. On one hand, PASS employs a generative model to create synthetic data that closely mirrors raw data while preserving its rank properties through data perturbation, thereby enhancing data diversity and bolstering privacy. By incorporating knowledge transfer from large pre-trained generative models, PASS enhances estimation accuracy, yielding refined distributional estimates of various statistics via Monte Carlo experiments. On the other hand, PAI boasts its statistically guaranteed validity. In pivotal inference, it enables precise conclusions even without prior knowledge of the pivotal's distribution. In non-pivotal situations, we enhance the reliability of synthetic data generation by training it with an independent holdout sample. We demonstrate the effectiveness of PAI in advancing uncertainty quantification in complex, data-driven tasks by applying it to diverse areas such as image synthesis, sentiment word analysis, multimodal inference, and the construction of prediction intervals.

[Identification and expression of genome of uridine diphosphate glycosyltransferase (UGT) gene family from Chrysanthemum indicum].

Uridine diphosphate glycosyltransferase(UGT) is involved in the glycosylation of a variety of secondary metabolites in plants and plays an important role in plant growth and development and regulation of secondary metabolism. Based on the genome of a diploid Chrysanthemum indicum, the UGT gene family from Ch. indicum was identified by bioinformatics methods, and the physical and chemical properties, subcellular localization prediction, conserved motif, phylogeny, chromosome location, gene structure, and gene replication events of UGT protein were analyzed. Transcriptome and real-time fluorescence quantitative polymerase chain reaction(PCR) were used to analyze the expression pattern of the UGT gene in flowers and leaves of Ch. indicum. Quasi-targeted metabolomics was used to analyze the differential metabolites in flowers and leaves. The results showed that a total of 279 UGT genes were identified in the Ch. indicum genome. Phylogenetic analysis showed that these UGT genes were divided into 8 subfamilies. Members of the same subfamily were distributed in clusters on the chromosomes. Tandem duplications were the main driver of the expansion of the UGT gene family from Ch. indicum. Structural domain analysis showed that 262 UGT genes had complete plant secondary metabolism signal sequences(PSPG box). The analysis of cis-acting elements indicated that light-responsive elements were the most ubiquitous elements in the promoter regions of UGT gene family members. Quasi-targeted metabolome analysis of floral and leaf tissue revealed that most of the flavonoid metabolites, including luteolin-7-O-glucoside and kaempferol-7-O-glucoside, had higher accumulation in flowers. Comparative transcriptome analysis of flower and leaf tissue showed that there were 72 differentially expressed UGT genes, of which 29 genes were up-regulated in flowers, and 43 genes were up-regulated in leaves. Correlation network and phylogenetic analysis showed that CindChr9G00614970.1, CindChr2G00092510.1, and CindChr2G00092490.1 may be involved in the synthesis of 7-O-flavonoid glycosides in Ch. indicum, and real-time fluorescence quantitative PCR analysis further confirmed the reliability of transcriptome data. The results of this study are helpful to understand the function of the UGT gene family from Ch. indicum and provide data reference and theoretical basis for further study on the molecular regulation mechanism of flavonoid glycosides synthesis in Ch. indicum.

Effective oxygen activation on polyoxometalate-based hybrids for epoxidation of alkenes.

Two polyoxometalate-based hybrids, [M(btap)3(H2O)3(HPW12O40)]·xH2O (M-PW, M = Co/Mn, btap = 3,5-bis(1',2',4'-triazol-1'-yl)pyridine) were synthesized. Co-PW exhibited higher activity and selectivity towards olefin epoxidation than Mn-PW due to the synergistic effect between CoII and PW, in which the Co centers activate O2 to ˙O2- and further binding of free H+ from PW affords the active peroxyacid.

Isorhamnetin: what is the in vitro evidence for its antitumor potential and beyond?

Isorhamnetin (ISO) is a phenolic compound belonging to flavonoid family, showcasing important in vitro pharmacological activities such as antitumor, anti-inflammation, and organ protection. ISO is predominantly extracted from Hippophae rhamnoides L. This plant is well-known in China and abroad because of its "medicinal and food homologous" characteristics. As a noteworthy natural drug candidate, ISO has received considerable attention in recent years owing to its low cost, wide availability, high efficacy, low toxicity, and minimal side effects. To comprehensively elucidate the multiple biological functions of ISO, particularly its antitumor activities and other pharmacological potentials, a literature search was conducted using electronic databases including Web of Science, PubMed, Google Scholar, and Scopus. This review primarily focuses on ISO's ethnopharmacology. By synthesizing the advancements made in existing research, it is found that the general effects of ISO involve a series of in vitro potentials, such as antitumor, protection of cardiovascular and cerebrovascular, anti-inflammation, antioxidant, and more. This review illustrates ISO's antitumor and other pharmacological potentials, providing a theoretical basis for further research and new drug development of ISO.