Large-scale uterine myoma MRI dataset covering all FIGO types with pixel-level annotations.

Uterine myomas are the most common pelvic tumors in women, which can lead to abnormal uterine bleeding, abdominal pain, pelvic compression symptoms, infertility, or adverse pregnancy. In this article, we provide a dataset named uterine myoma MRI dataset (UMD), which can be used for clinical research on uterine myoma imaging. The UMD is the largest publicly available uterine MRI dataset to date including 300 cases of uterine myoma T2-weighted imaging (T2WI) sagittal patient images and their corresponding annotation files. The UMD covers 9 types of uterine myomas classified by the International Federation of Obstetrics and Gynecology (FIGO), which were annotated and reviewed by 11 experienced doctors to ensure the authority of the annotated data. The UMD is helpful for uterine myomas classification and uterine 3D reconstruction tasks, which has important implications for clinical research on uterine myomas.

Avian leukosis virus usurps the cellular SERBP1 protein to enhance its transcription and promote productive infections in avian cells.

Avian leukosis virus subgroup K (ALV-K) is composed of newly emerging isolates, which cluster separately from the well-characterized subgroups A, B, C, D, E, and J in sequence analysis, and exhibits a specific host range and a unique pattern of superinfection interference. Avian leukosis virus subgroup K replicate more slowly in avian cells than other ALV strains, leading to escaped detection during ALV eradication, but the underlying mechanism are largely unknown. In our previous study, we have reported that JS11C1 and most of other suspected ALV-K strains possessed unique mutations in the U3 region. Here, we selected 5 mutations in some important transcriptional regulation elements to explore the possible factor contributing for the lower activity of LTR, including CA-TG mutation in the CAAT box, 21 nt deletion in the CAAT box, A-G and A-T mutations in the CArG boxes, 11 nt insertion in the PRE boxes, and C-T mutation in the TATA box. On the basis of infectious clone of JS11C1, we demonstrated that the 11 nt fragment in the PRE boxes was associated with the transcription activity of LTR, the enhancer ability of U3, and the replication capacity of the virus. Notably, we determined the differential U3-protein interaction profile of ALVs and found that the 11 nt fragment specifically binds to cellular SERPINE1 mRNA binding protein 1 (SERBP1) to increase the LTR activity and enhance virus replication. Collectively, these findings reveal that a 11 nt fragment in the U3 gene contributed to its binding ability to the cellular SERBP1 to enhance its transcription and the infectious virus productions in avian cells. This study highlighted the vital role of host factor in retrovirus replication and thus provides a new perspective to elucidate the interaction between retrovirus and its host and a molecular basis to develop efficient strategies against retroviruses.

Fibronectin binds integrin α5ß1 to regulate macular neovascularization through the Wnt/ß-catenin signaling pathway.

Age-related macular degeneration (AMD) is a progressive, degenerative disease of the macula. The formation of macular neovascularization (MNV) and subretinal fibrosis of AMD is the most classic cause of the loss of vision in older adults worldwide. While the underlying causes of MNV and subretinal fibrosis remain elusive, the common feature of many common retinal diseases is changes the proportions of protein deposition in extracellular matrix (ECM) when compared to normal tissue. In ECM, fibronectin (FN) is a crucial component and plays a pivotal part not only in fibrotic diseases but also in the process of angiogenesis. The study aims to understand the role of ligand FN and its common integrin receptor α5ß1 on MNV, and to understand the molecular mechanism involved. To study this, the laser-induced MNV mouse model and the rhesus macaque choroid-retinal endothelial cell line (RF/6A) chemical hypoxia mode were established, and the FN-α5ß1 expression levels were detected by immunohistochemistry (IHC) and quantitative real-time PCR analysis (qRT-PCR). Fibronectin expression was silenced using small interfering RNA (siRNA) targeting FN. The tube formation and vitro scratch assays were used to assess the ability to form blood vessels and cell migration. To measure the formation of MNV, immunofluorescence, and Western blot assays were used. These results revealed that the expressions of FN and integrin α5ß1 were distinctly increased in the laser-induced MNV mouse model and in the RF/6A cytochemically induced hypoxia model, and the expression tendency was identical. After the use of FN siRNA, the tube formation and migration abilities of the RF/6A cells were lower, the ability of endothelial cells to proliferate was confined and the scope of damage caused by the laser in animal models was significantly cut down. In addition, FN gene knockdown dramatically inhibited the expression of Wnt/ß-catenin signal. The interaction of FN with the integrin receptor α5ß1 in the constructed model, which may act through the Wnt/ß-catenin signaling pathway, was confirmed in this study. In conclusion, FN may be a potential new molecular target for the prevention and treatment of subretinal fibrosis and MNV.

Induced Self-Assembly of Vitamin E-Spermine/siRNA Nanocomplexes via Spermine/Helix Groove-Specific Interaction for Efficient siRNA Delivery and Antitumor Therapy.

Gene therapy has been one of potential strategies for the treatment of different diseases, where efficient and safe gene delivery systems are also extremely in need. Current lipid nanoparticles (LNP) technology highly depends on the packing and condensation of nucleic acids with amine moieties. Here, an attempt to covalently link two natural compounds, spermine and vitamin E, is made to develop self-assembled nucleic acid delivery systems. Among them, the spermine moieties specifically interact with the major groove of siRNA helix through salt bridge interaction, while vitamin E moieties are located around siRNA duplex. Such amphiphilic vitamin E-spermine/siRNA complexes can further self-assemble into nanocomplexes like multiblade wheels. Further studies indicate that these siRNA nanocomplexes with the neutrally charged surface of vitamin E can enter cells via caveolin/lipid raft mediated endocytosis pathway and bypass lysosome trapping. With these self-assembled delivery systems, efficient siRNA delivery is successfully achieved for Eg5 and Survivin gene silencing as well as DNA plasmid delivery. Further in vivo study indicates that VE-Su-Sper/DSPE-PEG2000/siSurvivin self-assembled nanocomplexes can accumulate in cancer cells and gradually release siRNA in tumor tissues and show significant antitumor effect in vivo. The self-assembled delivery system provides a novel strategy for highly efficient siRNA delivery.

Interactive segmentation of medical images using deep learning.

Medical image segmentation algorithms based on deep learning have achieved good segmentation results in recent years, but they require a large amount of labeled data. When performing pixel-level labeling on medical images, labeling a target requires marking ten or even hundreds of points along its edge, which requires a lot of time and labor costs. To reduce the labeling cost, we utilize a click-based interactive segmentation method to generate high-quality segmentation labels. However, in current interactive segmentation algorithms, only the interaction information clicked by the user and the image features are fused as the input of the backbone network (so-called early fusion). The early fusion method has the problem that the interactive information is much sparse at this time. Furthermore, the interactive segmentation algorithms do not take into account the boundary problem, resulting in poor model performance. So we propose early fusion and late fusion strategy to prevent the interaction information from being diluted prematurely and make better use of the interaction information. At the same time, we propose a decoupled head structure, by extracting the image boundary information, and combining the boundary loss function to establish the boundary constraint term, so that the network can pay more attention to the boundary information and further improve the performance of the network. Finally, we conduct experiments on three medical datasets (Chaos, VerSe and Uterine Myoma MRI) to verify the effectiveness of our network. The experimental results show that our network greatly improved compared with the baseline, and NoC@80(the number of interactive clicks over 80% of the IoU threshold) improved by 0.1, 0.1, and 0.2. In particular, we have achieved a NoC@80 score of 1.69 on Chaos. According to statistics, manual annotation takes 25 min to label a case(Uterine Myoma MRI). Annotating a medical image with our method can be done in only 2 or 3 clicks, which can save more than 50% of the cost.

An unexpected interfacial Mo-rich phase in 2D molybdenum disulfide and 3D gold heterojunctions.

The interface engineering of two-dimensional transition metal dichalcogenides (2D-TMDs) and metals has been regarded as a promising strategy to modulate their outstanding electrical and optoelectronic properties. Chemical Vapour Deposition (CVD) is an effective strategy to regulate the contact interface between TMDs and metals via directly growing 2D TMDs on a 3D metal substrate. Nevertheless, the underlying mechanisms of interfacial phase formation and evolution during TMD growth on a metallic substrate are less known. In this work, we found a 2D non-van der Waals (vdW) Mo-rich phase (MoNSN+1) during thermal sulfidation of a Mo-Au surface alloy to molybdenum disulfide (MoS2) in a S-poor environment. Systematic atomic-scale observations reveal that the periodic Mo and S atomic layers are arranged separating from each other in the non-vdW Mo-rich phase, and the Mo-rich phase preferentially nucleates between outmost 2D MoS2 and a 3D nanostructured Au substrate which possesses copious surface steps and kinks. Theoretical calculations demonstrate that the appearance of the Mo-rich phase with a unique metallic nature causes an n-type contact interface with an ultralow transition energy barrier height. This study may help understand the formation mechanism of the interfacial second phase during the epitaxial growth of 2D-TMDs on 3D nanostructured metals, and provide a new approach to tune the Schottky barrier height by the design of the interfacial phase structure at the heterojunction.

WA-ResUNet: A Focused Tail Class MRI Medical Image Segmentation Algorithm.

Medical image segmentation can effectively identify lesions in medicine, but some small and rare lesions cannot be well identified. Existing studies do not take into account the uncertainty of the occurrence of diseased tissue, and the problem of long-tailed distribution of medical data. Meanwhile, the grayscale image obtained from Magnetic Resonance Imaging (MRI) detection has problems, such as the features being difficult to extract and invalid features being difficult to distinguish. In order to solve these problems, we propose a new weighted attention ResUNet (WA-ResUNet) and a class weight formula based on the number of images contained in the class, which improves the performance of the model in the low-frequency class and the overall effect of the model by improving the degree of attention paid to the valid features and invalid ones and rebalancing the learning efficiency among the classes. We evaluated our method on an uterine MRI dataset and compared it with the ResUNet. WA-ResUNet increased Intersection over Union (IoU) in the low-frequency class (Nabothian cysts) by 21.87%, and the overall mIoU increased by more than 6.5%.

Cathepsin B-activatable cyclic antisense oligonucleotides for cell-specific target gene knockdown in vitro and in vivo.

Trigger-activatable antisense oligonucleotides have been widely applied to regulate gene function. Among them, caged cyclic antisense oligonucleotides (cASOs) maintain a specific topology that temporarily inhibits their interaction with target genes. By inserting linkers that respond to cell-specific endogenous stimuli, they can be powerful tools and potential therapeutic agents for specific types of cancer cells with low off-target effects on normal cells. Here, we developed enzyme-activatable cASOs by tethering two terminals of linear antisense oligonucleotides through a cathepsin B (CB) substrate peptide (Gly-Phe-Leu-Gly [GFLG]), which could be efficiently uncaged by CB. CB-activatable cASOs were used to successfully knock down two disease-related endogenous genes in CB-abundant PC-3 tumor cells at the mRNA and protein levels but had much less effect on gene knockdown in CB-deficient human umbilical vein endothelial cell (HUVECs). In addition, reduced nonspecific immunostimulation was found using cASOs compared with their linear counterparts. Further in vivo studies indicated that CB-activatable cASOs showed effective tumor inhibition in PC-3 tumor model mice through downregulation of translationally controlled tumor protein (TCTP) protein in tumors. This study applies endogenous enzyme-activatable cASOs for antitumor therapy in tumor model mice, which demonstrates a promising stimulus-responsive cASO strategy for cell-specific gene knockdown upon endogenous activation and ASO prodrug development.

UWV-Yolox: A Deep Learning Model for Underwater Video Object Detection.

Underwater video object detection is a challenging task due to the poor quality of underwater videos, including blurriness and low contrast. In recent years, Yolo series models have been widely applied to underwater video object detection. However, these models perform poorly for blurry and low-contrast underwater videos. Additionally, they fail to account for the contextual relationships between the frame-level results. To address these challenges, we propose a video object detection model named UWV-Yolox. First, the Contrast Limited Adaptive Histogram Equalization method is used to augment the underwater videos. Then, a new CSP_CA module is proposed by adding Coordinate Attention to the backbone of the model to augment the representations of objects of interest. Next, a new loss function is proposed, including regression and jitter loss. Finally, a frame-level optimization module is proposed to optimize the detection results by utilizing the relationship between neighboring frames in videos, improving the video detection performance. To evaluate the performance of our model, We construct experiments on the UVODD dataset built in the paper, and select mAP@0.5 as the evaluation metric. The mAP@0.5 of the UWV-Yolox model reaches 89.0%, which is 3.2% better than the original Yolox model. Furthermore, compared with other object detection models, the UWV-Yolox model has more stable predictions for objects, and our improvements can be flexibly applied to other models.

An Instance Segmentation Model Based on Deep Learning for Intelligent Diagnosis of Uterine Myomas in MRI.

Uterine myomas affect 70% of women of reproductive age, potentially impacting their fertility and health. Manual film reading is commonly used to identify uterine myomas, but it is time-consuming, laborious, and subjective. Clinical treatment requires the consideration of the positional relationship among the uterine wall, uterine cavity, and uterine myomas. However, due to their complex and variable shapes, the low contrast of adjacent tissues or organs, and indistinguishable edges, accurately identifying them in MRI is difficult. Our work addresses these challenges by proposing an instance segmentation network capable of automatically outputting the location, category, and masks of each organ and lesion. Specifically, we designed a new backbone that facilitates learning the shape features of object diversity, and filters out background noise interference. We optimized the anchor box generation strategy to provide better priors in order to enhance the process of bounding box prediction and regression. An adaptive iterative subdivision strategy ensures that the mask boundary details of objects are more realistic and accurate. We conducted extensive experiments to validate our network, which achieved better average precision (AP) results than those of state-of-the-art instance segmentation models. Compared to the baseline network, our model improved AP on the uterine wall, uterine cavity, and myomas by 8.8%, 8.4%, and 3.2%, respectively. Our work is the first to realize multiclass instance segmentation in uterine MRI, providing a convenient and objective reference for the clinical development of appropriate surgical plans, and has significant value in improving diagnostic efficiency and realizing the automatic auxiliary diagnosis of uterine myomas.

Inhibition of AIF-1 alleviates laser-induced macular neovascularization by inhibiting endothelial cell proliferation via restrained p44/42 MAPK signaling pathway.

Age-related macular degeneration (AMD) is a leading blinding disease worldwide, and macular neovascularization (MNV) is a common complication encountered in the advanced stages of AMD. While the underlying causes of MNV remain elusive, aberrant multiplication of choroidal endothelial cells (CECs) and increased vascular endothelial growth factor (VEGF) are thought to play significant roles in the occurrence and development of MNV. Allograft inflammatory factor-1(AIF-1) is a crucial regulatory factor of vascular tubular structure formation and growth, involving the proliferation and migration of vascular endothelial cells and various tumor cells. This study aimed to understand how AIF-1 effects the proliferation of CECs and the subsequent progression of MNV. To study this, a mouse MNV model was established through laser injury, and the AIF-1 expression levels were then measured using western blot and immunohistochemistry. AIF-1 siRNA was intravitreally injected to silence AIF-1 gene expression. Western blot and choroidal flat mount were performed to measure the progression of MNV and proliferation of the CECs. These results showed that the protein expression of AIF-1 was significantly elevated in the laser-induced mouse MNV model, and the expression trend was consistent with VEGF. The protein level of AIF-1 was significantly decreased after the intravitreal injection of AIF-1 siRNA, the damage range of laser lesions was significantly reduced, and the proliferation of endothelial cells was inhibited. Knockdown of the AIF-1 gene significantly inhibited the expression of mitogen-activated protein kinase p44/42 in MNV lesions. In summary, this research demonstrates that AIF-1 promoted MNV progression by promoting the proliferation of CECs and that silencing AIF-1 significantly ameliorates MNV progression in mouse models, which may act through the p44/42 MAPK signaling pathway. AIF-1 could be a new potential molecular target for MNV.

The influence of health information attention and app usage frequency of older adults on persuasive strategies in mHealth education apps.

With the development of mobile communication technology, persuasive technology is widely used in mobile health. Using personalized persuasive strategies in mobile health education (MHE) apps can effectively improve users' health literacy and health behaviors. The transtheoretical model explains the process of user behavior change. Different usage frequency of the app reflects changes in user behavior. However, few studies have examined how the perceived importance of persuasive strategies among older adults changes with increasing use frequency. In this study, we analyzed the sensitivity of 111 older adults in China to persuasive strategies in MHE apps. Thirteen persuasive strategies were selected for this study. A repeated measure analysis of variance (RM-ANOVA) was used to demonstrate the influence of gender, health information attention and frequency of use on the sensitivity of perceived persuasive strategies among older adults. The results revealed older adults with a high usage frequency of health apps were more receptive to persuasive strategies, especially in social comparison strategy. This result may help developers consider factors such as the frequency of use by older users when designing personalized persuasive strategies for MHE apps.

In vitro exposure to environmentally relevant concentrations of norgestrel affects sperm physiology and reproductive success of the Pacific oyster Crassostrea gigas.

Progestins in aquatic environments are of increasing concern, as shown by the results of toxicological studies on adult invertebrates with external fertilization. However, their potential effects on the gametes and reproductive success of such animals remain largely unknown. Thus, the current study assessed the effect of in vitro exposure of environmentally relevant concentrations (10 ng/L and 1000 ng/L) of norgestrel (NGT) on the sperm of Pacific oyster Crassostrea gigas, analyzing sperm motility, ultrastructure, mitochondrial function, ATP status, characteristic enzyme activities, and DNA integrity underlying fertilization and hatching success. The results showed that NGT increased the percentage of motile sperm by elevating intracellular Ca2+ levels, Ca2+-ATPase activity, creatine kinase activity, and ATP content. Although superoxide dismutase activity was enhanced to eliminate reactive oxygen species generated by NGT, oxidative stress occurred, as indicated by the increase in malonaldehyde content and damage to plasma membranes and DNA. As a consequence, fertilization rates decreased. However, hatching rates did not alter significantly, possibly as a result of DNA repair processes. This study demonstrates oyster sperm as a useful, sensitive tool for toxicological research of progestins and provides ecologically relevant information on reproductive disturbance in oysters resulting from exposure to NGT.

FSPLO: a fast sensor placement location optimization method for cloud-aided inspection of smart buildings.

With the awakening of health awareness, people are raising a series of health-related requirements for the buildings they live in, with a view to improving their living conditions. In this context, BIM (Building Information Modeling) makes full use of cutting-edge theories and technologies in many domains such as health, environment, and information technology to provide a new way for engineers to design and build various healthy and green buildings. Specifically, sensors are playing an important role in achieving smart building goals by monitoring the surroundings of buildings, objects and people with the help of cloud computing technology. In addition, it is necessary to quickly determine the optimal sensor placement to save energy and minimize the number of sensors for a building, which is a de-trial task for the cloud platform due to the limited number of sensors available and massive candidate locations for each sensor. In this paper, we propose a Fast Sensor Placement Location Optimization approach (FSPLO) to solve the BIM problem in cloud-aided smart buildings. In particular, we quickly filter out the repeated candidate locations of sensors in FSPLO using Locality Sensitive Hashing (LSH) techniques to maintain only a small number of optimized locations for deploying sensors around buildings. In this way, we can significantly reduce the number of sensors used for health and green buildings. Finally, a set of simulation experiments demonstrates the excellent performance of our proposed FSPLO method.

Engineering chemical-bonded Ti3C2 MXene@carbon composite films with 3D transportation channels for promoting lithium-ion storage in hybrid capacitors.

Lithium-ion capacitors (LICs) are promising energy storage devices because they feature the high energy density of lithium-ion batteries and the high power density of supercapacitors. However, the mismatch of electrochemical reaction kinetics between the anode and cathode in LICs makes exploring anode materials with fast ion diffusion and electron transfer channels an urgent task. Herein, the two-dimensional (2D) Ti3C2 MXene with controllable terminal groups was introduced into 1D carbon nanofibers to form a 3D conductive network by the electrospinning strategy. In such Ti3C2 MXene and carbon matrix composites (named KTi-400@CNFs), the 2D nanosheet structure endows Ti3C2 MXene with more active sites for Li+ ion storage, and the carbon framework is favorable to the conductivity of the composites. Impressively, Ti-O-C bonds are formed at the interface between Ti3C2 MXene and the carbon framework. Such chemical bonding in the composites builds a bridge for rapid electron transportation and quick ion diffusion in the longitudinal direction from layer to layer. As a result, the optimized KTi-400@CNFs composites maintain a good capacity of 235 mA h g-1 for 500 cycles at a current density of 5 A g-1. The LIC consisting of the KTi-400@CNFs//AC configuration achieves high energy density (114.3 W h kg-1) and high power density (12.8 kW kg-1). This paper provides guidance for designing 2D materials and the KTi-400@CNFs composites with such a unique structure and superior electrochemical performance have great potential in the next-generation energy storage fields. Electronic Supplementary Material: Supplementary material is available for this article at 10.1007/s40843-022-2268-9 and is accessible for authorized users.

Norgestrel causes digestive gland injury in the clam Mactra veneriformis: An integrated histological, transcriptomics, and metabolomics study.

The potential adverse effects of progestins on aquatic organisms, especially non-target species, are of increasing concern worldwide. However, the effect and mechanism of progestin toxicity on aquatic invertebrates remain largely unexplored. In the present study, clams Mactra veneriformis were exposed to norgestrel (NGT, 0, 10, and 1000 ng/L), the dominant progestin detected in the aquatic environment, for 21 days. NGT accumulation, histology, transcriptome, and metabolome were assessed in the digestive gland. The bioconcentration factor (BCF) was 386 and 268 in the 10 ng/L NGT group and 1000 ng/L NGT group, respectively, indicating efficient accumulation of NGT in the clams. Histological analysis showed that NGT led to the swelling of epithelial cells and blurring of the basement membrane in the digestive gland. Differentially-expressed genes and KEGG pathway enrichment analysis using a transcriptomic approach suggested that NGT primarily disturbed the detoxification system, antioxidant defense, carbohydrate and amino acid metabolism, and steroid hormone metabolism, which was consistent with the metabolites analyzed using a metabolomic approach. Furthermore, we speculated that the oxidative stress caused by NGT resulted in histological damage to the digestive gland. This study showed that NGT caused adverse effects in the clams and sheds light on the mechanisms of progestin interference in aquatic invertebrates.

Triton modified polyethyleneimine conjugates assembled with growth arrest-specific protein 6 for androgenetic alopecia transdermal gene therapy.

Androgenetic alopecia is an androgen-dependent skin disorder that commonly affects hair follicle growth and hair loss. Gene therapy that can promote the proliferation and survival of hair follicle cells can be a potential choice for its cure. While transdermal application of therapeutic functional nucleic acids across the stratum corneum is quite difficult. Here, we first develop a transdermal agent for functional nucleic acid delivery using Triton X-100-modified low molecular weight polyethyleneimine (PEI-Triton-N, N â€‹= â€‹6 or 8). In vitro cell experiments demonstrate that the PEI-Triton-N conjugates can stably encapsulate and efficiently deliver plasmid DNA to hard-to-transfect keratinocyte HaCaT cells. Further mouse model studies show that PEI-Triton-6 can encapsulate and deliver growth arrest-specific protein 6 (Gas6) plasmid through transdermal administration. The transfected Gas6 prolongs the anagen status, inhibits the apoptosis of hair follicle cells, and further promotes the proliferation and differentiation of hair follicle cells. The PEI-Triton-6/pDNAGas6 complexes can obviously alleviate hair loss in androgenetic alopecia mice and provides a promising strategy for gene therapy via transdermal administration.

Entropy-Stabilized Multicomponent Porous Spinel Nanowires of NiFeXO4 (X = Fe, Ni, Al, Mo, Co, Cr) for Efficient and Durable Electrocatalytic Oxygen Evolution Reaction in Alkaline Medium.

Cost-effective electrochemical water splitting technology hinges on the development of efficient and durable catalysts for oxygen evolution reaction (OER). Spinel oxides (formula: AxB3-xO4) are structurally stable for real applications. Much effort has been devoted to improving the catalytic activity. Here, we report a eutectic dealloying strategy to activate the porous spinel NiFe2O4 nanowires with up to four metal cation substitutions. As-obtained spinel NiFeXO4 (X = Fe, Ni, Al, Mo, Co, Cr) delivers a benchmark current density of 10 mA·cm-2 at an overpotential of only 195 mV, outperforming most spinel phase OER electrocatalysts and comparable to the state-of-the-art NiFe hydroxides. It is stable for over 115 h of electrolysis. Aberration-corrected transmission electron microscopy, high-resolution electron energy loss spectroscopy, and atomic-scale strain mappings reveal that the multivalent cation substitutions result in substantial lattice distortion and significant electronic coupling of metal 3d and O 2p orbitals for increased covalency. Further theoretical calculations suggest that the NiFeXO4 are stabilized by the high configurational entropy, and their synergy favors the absorption of H2O molecules and lowers the adsorption energy barrier of the OOH* intermediate. The improved intrinsic activity together with the highly nanoporous structures contribute to the appealing apparent catalytic performances. The work demonstrates an effective approach for the synthesis of stable multicomponent spinel oxides and highlights the effectiveness of the multication substitution strategy for producing highly durable and active spinel catalysts, which meet multiplexed structure and superior property requirements in practical applications.

Identification of the Origin, Authenticity and Quality of Panax Japonicus Based on a Multistrategy Platform.

BACKGROUND: Panax Japonicus (PJ) is a widely used Chinese herbal medicine, functional food and tonic. However, its origin has a great influence on the quality of PJ, and with the increasing demand for PJ, fake and inferior products, such as Panax Stipuleanatus (PS), often appear. The identification of the origin and authenticity of PJ is critical for ensuring the quality, safety and effectiveness of drugs. OBJECTIVE: Proposing a strategy to identify the origin, authenticity, and quality of PJ using HPLC fingerprints, chemometrics, and network pharmacology. METHODS: The chromatographic fingerprint method was established to analyze the origin and authenticity of PJ. Multiple chemometric methods were performed to analyze the fingerprints, including a Hierarchical Cluster Analysis (HCA), Principal Component Analysis (PCA), and Counter Propagation Artificial Neural Network (CP-ANN). Finally, the network pharmacology method was used to construct the "active ingredient-target" network, predict and assist in analyzing potential Qmarkers in PJ. RESULTS: Ward's method was used for the HCA. The results showed that PJ samples from different origins had significant regional differences and could be accurately distinguished from PS. The PCA classification results are consistent with the HCA classification results, further illustrating the model's accuracy. The CP-ANN model can analyze and predict PJ and PS and accurately obtain PJ and PS chemical markers to identify PJ and PS correctly. The network pharmacology of PJ was constructed, and three PJ Q-markers, namely, ginsenoside Ro, ginsenoside Rb1, and chikusetsu saponin Ⅳa, were identified, which lays a foundation for the establishment of PJ quality standards. CONCLUSION: This research provides a feasible platform for the quality evaluation of PJ in the future.

Discovery of potential Q-marker of traditional Chinese medicine based on chemical profiling, chemometrics, network pharmacology, and molecular docking: Centipeda minima as an example.

INTRODUCTION: The characteristics of chemical components or groups of chemical components in traditional Chinese medicines (TCMs) determine their clinical efficacy. Quality markers (Q-markers) is of great significance for standardizing the quality control system of TCM. OBJECTIVES: We aimed to develop a new strategy to discover potential Q-markers of TCM by integrating chemometrics, network pharmacology, and molecular docking, using Centipeda minima (also known as ebushicao [EBSC]) as an example. MATERIALS AND METHODS: First, fingerprints of different batches of EBSC and its counterfeit Arenaria oreophila (also known as zaozhui [ZZ]) were established. Second, chemometric analysis was conducted to determine the influence of varying authenticity/batches of herbs on quality and the chemical markers were screened out. Third, network pharmacology and molecular docking simulations were used to verify the relationship between active ingredients and targets. Lastly, potential Q-markers were selected based on TCM theory. RESULTS: The chemical profiles of EBSC and ZZ were investigated. It was found that different batches of EBSC have differences in chemical composition. Based on our chemometric analysis, chlorogenic acid, rutin, isochlorogenic acid A, quercetin, arnicolide D, and brevilin A were selected as candidate active ingredients. ATIL6, EGFR, CASP3, MYC, HIF1A, and VEGFA were the main targets. Molecular docking was used to verify the binding ability. Based on the concept of Q-marker, arnicolide D and brevilin A were identified as potential Q-markers for EBSC. CONCLUSIONS: Our strategy could be used as a practical approach to discover Q-markers of TCM to evaluate overall chemical consistency.