Unraveling the role of PlARF2 in regulating deed formancy in Paeonia lactiflora.

MAIN CONCLUSION: PlARF2 can positively regulate the seed dormancy in Paeonia lactiflora Pall. and bind the RY cis-element. Auxin, a significant phytohormone influencing seed dormancy, has been demonstrated to be regulated by auxin response factors (ARFs), key transcriptional modulators in the auxin signaling pathway. However, the role of this class of transcription factors (TFs) in perennials with complex seed dormancy mechanisms remains largely unexplored. Here, we cloned and characterized an ARF gene from Paeonia lactiflora, named PlARF2, which exhibited differential expression levels in the seeds during the process of seed dormancy release. The deduced amino acid sequence of PlARF2 had high homology with those of other plants and contained typical conserved Auxin_resp domain of the ARF family. Phylogenetic analysis revealed that PlARF2 was closely related to VvARF3 in Vitis vinifera. The subcellular localization and transcriptional activation assay showed that PlARF2 is a nuclear protein possessing transcriptional activation activity. The expression levels of dormancy-related genes in transgenic callus indicated that PlARF2 was positively correlated with the contents of PlABI3 and PlDOG1. The germination assay showed that PlARF2 promoted seed dormancy. Moreover, TF Centered Yeast one-hybrid assay (TF-Centered Y1H), electrophoretic mobility shift assay (EMSA) and dual-luciferase reporter assay analysis (Dual-Luciferase) provided evidence that PlARF2 can bind to the 'CATGCATG' motif. Collectively, our findings suggest that PlARF2, as TF, could be involved in the regulation of seed dormancy and may act as a repressor of germination.

The correlation between serum total bile acid and alanine aminotransferase of pregnant women and the disorders of neonatal hyperbilirubinemia-related amino acid metabolism.

BACKGROUND: To explore the association between liver metabolism-related indicators in maternal serum and neonatal hyperbilirubinemia (NHB), and further investigate the predictive value of these indicators in NHB-related amino acid metabolism disorders. METHODS: 51 NHB and 182 No-NHB newborns and their mothers who treated in the Fourth Hospital of Shijiazhuang from 2018 to 2022 were participated in the study. The differences in clinical data were compared by the Mann-Whitney U test and Chi-square test. Multivariate logistic regression was used to analyze the relationship between maternal serum indicators and the occurrence of NHB. The correlation analysis and risk factor assessment of maternal serum indicators with NHB-related amino acid metabolic disorders were performed using Spearman correlation analysis and multivariate logistic regression. RESULTS: Compared to the non NHB group, the NHB group had higher maternal serum levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), ALT/AST, and total bile acid (TBA), while lower levels of serum albumin (ALB), total cholesterol (TC) and high-density lipoprotein (HDL). The levels of alanine (ALA), valine (VAL), ornithine (ORN), and proline (PRO) in the newborns were reduced in NHB group, while arginine (ARG) showed a tendency to be elevated. Multiple logistic regression analysis showed that maternal ALT, AST, ALT/AST, and TBA levels were all at higher risk with the development of NHB, whereas ALB, TC, and HDL levels were negatively associated with NHB development. Increasing maternal TBA level was associated with lower ALA (r=-0.167, p = 0.011), VAL (r=-0.214, p = 0.001), ORN (r=-0.196, p = 0.003), and PRO in the newborns (r=-0.131, p = 0.045). Maternal ALT level was negatively associated with ALA (r=-0.135, p = 0.039), VAL (r=-0.177, p = 0.007), ORN (r=-0.257, p < 0.001), while ALT/AST was positively correlated with ARG (r = 0.133, p = 0.013). After adjustment for confounding factors, maternal serum TBA and ALT were the independent risk factor for neonatal ORN metabolic disorders [(adjusted odds ratio (AOR) = 0.379, 95%CI = 0.188-0.762, p = 0.006), (AOR = 0.441, 95%CI = 0.211-0.922, p = 0.030)]. Maternal ALT level was an independent risk factor for neonatal VAL metabolic disorders (AOR = 0.454, 95%CI = 0.218-0.949, p = 0.036). CONCLUSIONS: The levels of high TBA, ALT, AST, and low HDL, TC of maternal were associated with the risk of NHB. Maternal TBA and ALT levels were independent risk factors for NHB-related amino acid disturbances which have value as predictive makers.

Bioinformatic Analysis of the Significance of the KIR2DL4 Gene in Recurrent Implantation Failure.

Related studies have pointed out that Killer immunoglobulin-like receptor 2DL4 (KIR2DL4) was associated with vascular remodeling in early pregnancy, and it might play an important role in immunity. In this study, recurrent implantation failure (RIF)-related GSE58144 dataset was extracted from the Gene Expression Omnibus (GEO) database. Firstly, the immune micro-environment analyses were conducted to analyze the pathogenesis of KIR2DL4 in RIF. Then, the gene set enrichment analysis (GSEA) was performed to investigate the function of KIR2DL4. Moreover, the TF-mRNA-miRNA and the co-expression networks were constructed to reveal the potential regulation of KIR2DL4. Furthermore, the genes that were associated with KIR2DL4 and differentially expressed in RIF were obtained and defined as key genes, and the functions of these genes were further explored. KIR2DL4 could be used for clinical diagnosis of RIF, and it was correlated with the changes in the immune micro-environment in RIF. From the perspective of function, KIR2DL4 was associated with complement and coagulation cascades, natural killer cell-mediated cytotoxicity, etc. Moreover, the TF-mRNA-miRNA regulatory network was constructed with KIR2DL4, 9 TFs, and 29 miRNAs. Furthermore, KIR2DL4, ACSM1, IL2RB, and PTPN11 were screened as key genes, which were associated with immune-related functions. This study deeply analyzed the function of KIR2DL4 and its role in RIF, and we found that STAT1 might up-regulate KIR2DL4 by INF-γ/JAK2/STAT1 signaling pathway. Besides, over-expressed KIR2DL4 in the mid-luteal endometrium might influence embryo implantation by affecting the embryo implantation microenvironment, which might help deepen the understanding of the molecular mechanism of RIF.

Physiological and transcriptomic responses of silkworms to graphene oxide exposure.

The growing use of nanomaterials has sparked significant interest in assessing the insect toxicities of nanoparticles. The silkworm, as an economically important insect, serves as a promising model for studying how insects respond to harmful substances. Here, we conducted a comprehensive investigation on the impact of graphene oxide (GO) on silkworms using a combination of physiological and transcriptome analyses. GO can enter the midguts and posterior silk glands of silkworms. High GO concentrations (> 25 mg/L) significantly (P < 0.01) inhibited larval growth. Additionally, GO (> 5 mg/L) significantly reduced the cocooning rate, and GO (> 15 mg/L) hindered oviduct development and egg laying in silkworms. GO increased the reactive oxygen species content and regulated catalase activity, suggesting that it may affect insect growth by regulating reactive oxygen detoxification. The transcriptome data analysis showed that 35 metabolism-related genes and 20 ribosome biogenesis-related genes were differentially expressed in response to GO, and their expression levels were highly correlated. Finally, we propose that a Ribosome biogenesis-Metabolic signaling network is involved in responses to GO. The research provides a new perspective on the molecular responses of insects to GO.

Risk factors for high-stage histological chorioamnionitis among pregnancies with cervical incompetence.

AIM: The study aimed to identify predictive risk factor to identify high-stage histological chorioamnionitis (HCA) in pregnancies with cervical incompetence (CIC). METHODS: A retrospective cohort study was conducted by including 116 pregnant women with cervical incompetence that required prophylactical and therapeutical cerclage. The histopathology examination on placenta was conducted with informed patient consent. All the cases included in this study were divided based on the severity degree of HCA. The demographic characteristic and the parameters related to maternal and fetal outcome were all analyzed. Besides, perioperative parameters of cerclage, including cervical length, cervical morphology, and laboratory indexes were also compared between two groups. Univariate and multivariate logistic regression analysis were used to determine the risk factor of severe chorioamnionitis. RESULTS: Severe HCA was significantly associated with cervical morphology, cerclage indication, cerclage type, and cervical length measured via ultrasound and vaginal examination. After adjusted for confounders, V-type funneling and short cervix was indicated as independent risk factors of severe HCA by multivariate logistic regression analysis, respectively. CONCLUSIONS: V-type funneling and short cervix may indicate the elevated risk of high-stage HCA. Due to the negative outcomes related with high-stage HCA, appropriate prenatal treatment would improve the pregnancy outcomes in cerclaged population. To facilitate postpartum treatment, placental histological examination should be routinely recommended to identify the high-stage HCA, especially in high risk pregnancies.

Point Cloud Denoising and Feature Preservation: An Adaptive Kernel Approach Based on Local Density and Global Statistics.

Noise removal is a critical stage in the preprocessing of point clouds, exerting a significant impact on subsequent processes such as point cloud classification, segmentation, feature extraction, and 3D reconstruction. The exploration of methods capable of adapting to and effectively handling the noise in point clouds from real-world outdoor scenes remains an open and practically significant issue. Addressing this issue, this study proposes an adaptive kernel approach based on local density and global statistics (AKA-LDGS). This method constructs the overall framework for point cloud denoising using Bayesian estimation theory. It dynamically sets the prior probabilities of real and noise points according to the spatial function relationship, which varies with the distance from the points to the center of the LiDAR. The probability density function (PDF) for real points is constructed using a multivariate Gaussian distribution, while the PDF for noise points is established using a data-driven, non-parametric adaptive kernel density estimation (KDE) approach. Experimental results demonstrate that this method can effectively remove noise from point clouds in real-world outdoor scenes while maintaining the overall structural features of the point cloud.

A Study on Dimensionality Reduction and Parameters for Hyperspectral Imagery Based on Manifold Learning.

With the rapid advancement of remote-sensing technology, the spectral information obtained from hyperspectral remote-sensing imagery has become increasingly rich, facilitating detailed spectral analysis of Earth's surface objects. However, the abundance of spectral information presents certain challenges for data processing, such as the "curse of dimensionality" leading to the "Hughes phenomenon", "strong correlation" due to high resolution, and "nonlinear characteristics" caused by varying surface reflectances. Consequently, dimensionality reduction of hyperspectral data emerges as a critical task. This paper begins by elucidating the principles and processes of hyperspectral image dimensionality reduction based on manifold theory and learning methods, in light of the nonlinear structures and features present in hyperspectral remote-sensing data, and formulates a dimensionality reduction process based on manifold learning. Subsequently, this study explores the capabilities of feature extraction and low-dimensional embedding for hyperspectral imagery using manifold learning approaches, including principal components analysis (PCA), multidimensional scaling (MDS), and linear discriminant analysis (LDA) for linear methods; and isometric mapping (Isomap), locally linear embedding (LLE), Laplacian eigenmaps (LE), Hessian locally linear embedding (HLLE), local tangent space alignment (LTSA), and maximum variance unfolding (MVU) for nonlinear methods, based on the Indian Pines hyperspectral dataset and Pavia University dataset. Furthermore, the paper investigates the optimal neighborhood computation time and overall algorithm runtime for feature extraction in hyperspectral imagery, varying by the choice of neighborhood k and intrinsic dimensionality d values across different manifold learning methods. Based on the outcomes of feature extraction, the study examines the classification experiments of various manifold learning methods, comparing and analyzing the variations in classification accuracy and Kappa coefficient with different selections of neighborhood k and intrinsic dimensionality d values. Building on this, the impact of selecting different bandwidths t for the Gaussian kernel in the LE method and different Lagrange multipliers λ for the MVU method on classification accuracy, given varying choices of neighborhood k and intrinsic dimensionality d, is explored. Through these experiments, the paper investigates the capability and effectiveness of different manifold learning methods in feature extraction and dimensionality reduction within hyperspectral imagery, as influenced by the selection of neighborhood k and intrinsic dimensionality d values, identifying the optimal neighborhood k and intrinsic dimensionality d value for each method. A comparison of classification accuracies reveals that the LTSA method yields superior classification results compared to other manifold learning approaches. The study demonstrates the advantages of manifold learning methods in processing hyperspectral image data, providing an experimental reference for subsequent research on hyperspectral image dimensionality reduction using manifold learning methods.

Natural products of pentacyclic triterpenoids: from discovery to heterologous biosynthesis.

Covering: up to 2022Pentacyclic triterpenoids are important natural bioactive substances that are widely present in plants and fungi. They have significant medicinal efficacy, play an important role in reducing blood glucose and protecting the liver, and have anti-inflammatory, anti-oxidation, anti-fatigue, anti-viral, and anti-cancer activities. Pentacyclic triterpenoids are derived from the isoprenoid biosynthetic pathway, which generates common precursors of triterpenes and steroids, followed by cyclization with oxidosqualene cyclases (OSCs) and decoration via cytochrome P450 monooxygenases (CYP450s) and glycosyltransferases (GTs). Many biosynthetic pathways of triterpenoid saponins have been elucidated by studying their metabolic regulation network through the use of multiomics and identifying their functional genes. Unfortunately, natural resources of pentacyclic triterpenoids are limited due to their low content in plant tissues and the long growth cycle of plants. Based on the understanding of their biosynthetic pathway and transcriptional regulation, plant bioreactors and microbial cell factories are emerging as alternative means for the synthesis of desired triterpenoid saponins. The rapid development of synthetic biology, metabolic engineering, and fermentation technology has broadened channels for the accumulation of pentacyclic triterpenoid saponins. In this review, we summarize the classification, distribution, structural characteristics, and bioactivity of pentacyclic triterpenoids. We further discuss the biosynthetic pathways of pentacyclic triterpenoids and involved transcriptional regulation. Moreover, the recent progress and characteristics of heterologous biosynthesis in plants and microbial cell factories are discussed comparatively. Finally, we propose potential strategies to improve the accumulation of triterpenoid saponins, thereby providing a guide for their future biomanufacturing.

Upregulation of Formaldehyde in Parkinson's Disease Found by a Near-Infrared Lysosome-Targeted Fluorescent Probe.

Parkinson's disease (PD) is one of the major neurodegenerative diseases caused by complex pathological processes. As a signal molecule, formaldehyde is closely linked to nervous systems, but the relationship between PD and formaldehyde levels remains largely unclear. We speculated that formaldehyde might be a potential biomarker for PD. To prove it, we constructed the first near-infrared (NIR) lysosome-targeted formaldehyde fluorescent probe (named NIR-Lyso-FA) to explore the relationship between formaldehyde and PD. The novel fluorescent probe achieves formaldehyde detection in vitro and in vivo, thanks to its excellent properties such as NIR emission, large Stokes shift, and fast response to formaldehyde. Crucially, utilizing the novel probe NIR-Lyso-FA, formaldehyde overexpression was discovered for the first time in cellular, zebrafish, and mouse PD models, supporting our guess that formaldehyde can function as a possible biomarker for PD. We anticipate that this finding will offer insightful information for PD pathophysiology, diagnosis, medication development, and treatment.

Exploration of the Performance and Mechanism of Uranium Adsorption by a Covalent Organic Framework Possessing the Thiazole Structure.

This study prepared an active 2-D covalent organic skeleton (HDU-27) with a network structure, high crystallinity, considerable specific surface area, excellent pore structure, and excellent stability. Kinetic studies manifested that HDU-27 could effectively capture uranium as monolayer chemisorption within a very short kinetic equilibrium time (10 min). In particular, the temperature significantly and positively impacted the uranium adsorption performance of HDU-27. At 298, 313, and 328 K, the adsorption capacity reached 269.2, 488.8, and 576.2 mg g-1, respectively, suggesting the potential to treat high-temperature industrial wastewater containing uranium. HDU-27 had high stability and recoverability with an adsorption efficiency of 98.5% after five adsorption-desorption cycles. According to X-ray photoelectron spectroscopy, the mechanism of interaction between U(VI) and HDU-27 was mainly the chelation of UO22+ by the N atom in the thiazole structure and the strong coordination of the O atom in the keto structure with UO22+. More excitingly, HDU-27 could chemically reduce soluble U(VI) to insoluble U(IV) and release binding sites for the adsorption of additional U(VI). In conclusion, HDU-27 has outstanding potential for uranium adsorption from industrial wastewater containing uranium.

The association between maternal iron, zinc, copper levels in serum and pregnancy outcomes.

AIMS: To investigate the associations of serum trace elements (iron, zinc, and copper) between women with different pregnancy outcomes. METHODS: About 774 pregnant women who came to The Fourth Hospital of Shijiazhuang for prenatal examination were investigated. The concentrations of trace elements in the serum of pregnant women in the third trimester were collected. Multivariate logistic regression was used to analyze the relationship between serum trace element levels and the different pregnancy outcomes. Multiple linear regression was used to analyze the relationship between serum trace elements levels and hypersensitive-C-reactive-protein. RESULTS: Results of the multiple logistic regression showed that zinc, copper and copper/zinc ratio were found to be associated with the risk of gestational diabetes mellitus, and zinc was a protective factor (p = 0.002) while copper and copper/zinc ratio as risk factors (p = 0.030 and p = 0.001, respectively) after adjusting for major confounders. It was found that iron and zinc were negatively associated with the risk of moderate or severe anemia (p = 0.022 and p = 0.001, respectively). In contrast, the copper/zinc ratio was positively related to the risk of moderate or severe anemia (p = 0.021). The adjusted relationships between copper and copper/zinc ratio with premature rupture of membranes were statistically significant (p = 0.007 and p = 0.037). Iron and zinc were negatively associated with the risk of chorioamnionitis, while copper and copper/zinc ratio were positively associated with the risk of chorioamnionitis (all p < 0.05). CONCLUSIONS: Serum iron, zinc and copper levels are closely related to pregnancy outcomes.

The importance of inflammation control for the treatment of chronic diabetic wounds.

Diabetic chronic wounds cause massive levels of patient suffering and economic problems worldwide. The state of chronic inflammation arises in response to a complex combination of diabetes mellitus-related pathophysiologies. Advanced treatment options are available; however, many wounds still fail to heal, exacerbating morbidity and mortality. This review describes the chronic inflammation pathophysiologies in diabetic ulcers and treatment options that may help address this dysfunction either directly or indirectly. We suggest that treatments to reduce inflammation within these complex wounds may help trigger healing.

Revealing the Effects of Endoplasmic Reticulum Stress on Ferroptosis by Two-Channel Real-Time Imaging of pH and Viscosity.

Endoplasmic reticulum (ER) is sensitive to changes in the intracellular environment such as pH and viscosity, and slight changes may trigger stress response. Besides, different from apoptosis and necrosis, ferroptosis is the result of lipid peroxidation accumulation. There is evidence that ferroptosis is closely related to endoplasmic reticulum stress (ERS). However, the possible changes in the pH and viscosity of the ER during the ferroptosis process have not yet been studied. Therefore, we used a new type of ER-targeted dual-excitation fluorescent probe (DSPI-3) to investigate the possible changes of pH and viscosity of ER during the ferroptosis. The novel probe DSPI-3 exhibited a highly sensitive and selective response to pH and viscosity. During the bioimaging process, it was found that the ER acidified and viscosity increased during the ferroptosis process induced by erastin, while the cells treated with ferrostatin-1 did not alter significantly. In addition, when dithiothreitol (DTT) and erastin stimulated the cells at the same time, we discovered that ER was acidified considerably at short notice, but the pH was slightly increased in the later stage. Besides, the change of the viscosity enhanced slowly with the passage of time, and there was a noteworthy decline in the later stage, demonstrating that the DTT-induced ERS accelerated the process of ferroptosis. We hope that this unique fluorescent probe can provide an effective method for studying the relationship between ERS and ferroptosis.

Imaging and Detection of Hepatocellular Carcinoma with a Hepatocyte-Specific Fluorescent Probe.

Hepatocellular carcinoma is a highly invasive malignant tumor of the liver, which is the main cause of cancer-related death. The cancerization of hepatocytes may lead to the changes of cell microenvironment, active substances, and enzymes. Viscosity is one of the important parameters of cell microenvironment. Therefore, the study of the change in the viscosity of hepatocytes is very important for the detection and treatment of liver cancer. However, the hepatocyte-specific fluorescent probes which can detect viscosity have not been developed yet. Herein, the first hepatocyte-specific fluorescent probe (HT-V) for viscosity detection was designed and synthesized, which exhibited excellent optical properties for biological imaging studies. By using the unique probe HT-V, compared with the normal liver cells, a significant increase of viscosity in the liver cancer cells was observed in the cell imaging experiment. The organ imaging experiments showed that the probe HT-V could be successfully used to diagnose and image hepatocellular carcinoma in vivo. In addition, in situ imaging revealed that the new probe HT-V can specifically target and image hepatocellular carcinoma in mice. We expected that this powerful tool may provide guidance for the detection and imaging of hepatocellular carcinoma in the future.

Evaluation of Cell Viability with a Single Fluorescent Probe Based on Two Kinds of Fluorescence Signal Modes.

Accurate evaluation of cell viability is important for dosage tests of anticancer drugs, pathology, and numerous biological experiments. However, due to the serious insufficieny of fluorescent probes, which can distinguish various cell states, the study of cell viability is immensely limited. To resolve this issue, we design and synthesize a new probe ACD-E to monitor cell viability with two kinds of fluorescence signal modes, the first single fluorescent probe that can distinguish three different cell states and furnish accurate information in biological experiments. ACD-E can discriminate live and dead cells in a dual-color mode by evaluating cell mitochondrial esterase activity and can also discriminate live and early necrosis cells by determining mitochondrial viscosity in a "turn-on" mode in the near-infrared region. Significantly, the novel ACD-E can also distinguish cell viability in vivo. This work establishes a robust strategy for monitoring multiple cell states using a single fluorescent probe.

Activatable Photoacoustic Probe for In Situ Imaging of Endogenous Carbon Monoxide in the Murine Inflammation Model.

Photoacoustic (PA) imaging is an emerging biomedical imaging modality that combines the advantages of optical and ultrasound imaging. Carbon monoxide (CO), which is a vital endogenous cell-signaling molecule in the human body, exerts critical physiological functions such as anti-inflammatory, antiapoptotic, and antiproliferative. The imbalance of CO homeostasis is also associated with numerous diseases. Therefore, it is critically important to noninvasively monitor the steady-state changes of CO in vivo. However, the activatable photoacoustic (PA) probes for detecting CO-associated complicated diseases have not yet developed. In this work, we developed the first turn-on PA probe (MTR-CO) to visualize the CO level in the lipopolysaccharide (LPS)-induced acute inflammation murine model through PA imaging technology. MTR-CO is composed of a near-infrared absorption cyanine-like dye (MTR-OH) and allyl formate, showing a 10.2-fold PA signal enhancement at 690 nm upon activation by CO. Furthermore, the results revealed that MTR-CO has high sensitivity, excellent specificity, and good biocompatibility for CO in vivo. MTR-CO was then applied for PA imaging of CO in cells and for monitoring the development of acute inflammation in the murine model by tracking the changes of the CO level. These findings provide a promising strategy for accurately detecting the steady-state changes of CO in living organisms.

Screen Key Genes Associated with Distraction-Induced Osteogenesis of Stem Cells Using Bioinformatics Methods.

Background: Applying mesenchymal stem cells (MSCs), together with the distraction osteogenesis (DO) process, displayed enhanced bone quality and shorter treatment periods. The DO guides the differentiation of MSCs by providing mechanical clues. However, the underlying key genes and pathways are largely unknown. The aim of this study was to screen and identify hub genes involved in distraction-induced osteogenesis of MSCs and potential molecular mechanisms. Material and Methods: The datasets were downloaded from the ArrayExpress database. Three samples of negative control and two samples subjected to 5% cyclic sinusoidal distraction at 0.25 Hz for 6 h were selected for screening differentially expressed genes (DEGs) and then analysed via bioinformatics methods. The Gene Ontology (GO) terms and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment were investigated. The protein-protein interaction (PPI) network was visualised through the Cytoscape software. Gene set enrichment analysis (GSEA) was conducted to verify the enrichment of a self-defined osteogenic gene sets collection and identify osteogenic hub genes. Results: Three hub genes (IL6, MMP2, and EP300) that were highly associated with distraction-induced osteogenesis of MSCs were identified via the Venn diagram. These hub genes could provide a new understanding of distraction-induced osteogenic differentiation of MSCs and serve as potential gene targets for optimising DO via targeted therapies.

Redox-Responsive Nanobiomaterials-Based Therapeutics for Neurodegenerative Diseases.

Redox regulation has recently been proposed as a critical intracellular mechanism affecting cell survival, proliferation, and differentiation. Redox homeostasis has also been implicated in a variety of degenerative neurological disorders such as Parkinson's and Alzheimer's disease. In fact, it is hypothesized that markers of oxidative stress precede pathologic lesions in Alzheimer's disease and other neurodegenerative diseases. Several therapeutic approaches have been suggested so far to improve the endogenous defense against oxidative stress and its harmful effects. Among such approaches, the use of artificial antioxidant systems has gained increased popularity as an effective strategy. Nanoscale drug delivery systems loaded with enzymes, bioinspired catalytic nanoparticles and other nanomaterials have emerged as promising candidates. The development of degradable hydrogels scaffolds with antioxidant effects could also enable scientists to positively influence cell fate. This current review summarizes nanobiomaterial-based approaches for redox regulation and their potential applications as central nervous system neurodegenerative disease treatments.

An Ultrasensitivity Fluorescent Probe Based on the ICT-FRET Dual Mechanisms for Imaging ß-Galactosidase in Vitro and ex Vivo.

Emergence of fluorescence imaging with real-time and in situ manners has revolutionized the fields of tracing and defining enzymes in biological systems. ß-galactosidase is a kind of enzyme that plays vital roles in controlling multitudes of cellular functions and participating in disease pathogenesis. Thus, building fluorescent probes with high sensitivity and fidelity for visualizing ß-galactosidase in biological systems is very significative. Herein, we engineered the first ultrsensitivity ratiometric fluorescent probe CG based on ICT-FRET synergetic mechanisms for detecting ß-galactosidase. The spectrum data show that probe CG has a fast response (<20 s), as well as a very low detection limit to ß-galactosidase (0.081 U/mL). Moreover, by calculation of a serious of kinetic parameters including Km (1.42 µM), kcat (7.04 s-1), and kcat/Km (4.96 µM-1 s-1), CG demonstrates high affinity and high catalytic efficiency to ß-galactosidase. Because of its excellent water solubility, CG has well biocompatibility to visualize the ß-galactosidase in living cells. Furthermore, for imaging in bioapplications, CG is capable of detecting ß-galactosidase not only in overexpressed cell lines but also in transient expressed cell lines. Significantly, CG can monitor ß-galactosidase ex vivo selectively. We hope ongoing work to employ CG can be as an ultrasensitive powerful tool for further seeking the physiological and pathological functions in biological organisms.