Motif-Based Contrastive Learning for Community Detection.

Community detection has become a prominent task in complex network analysis. However, most of the existing methods for community detection only focus on the lower order structure at the level of individual nodes and edges and ignore the higher order connectivity patterns that characterize the fundamental building blocks within the network. In recent years, researchers have shown interest in motifs and their role in network analysis. However, most of the existing higher order approaches are based on shallow methods, failing to capture the intricate nonlinear relationships between nodes. In order to better fuse higher order and lower order structural information, a novel deep learning framework called motif-based contrastive learning for community detection (MotifCC) is proposed. First, a higher order network is constructed based on motifs. Subnetworks are then obtained by removing isolated nodes, addressing the fragmentation issue in the higher order network. Next, the concept of contrastive learning is applied to effectively fuse various kinds of information from nodes, edges, and higher order and lower order structures. This aims to maximize the similarity of corresponding node information, while distinguishing different nodes and different communities. Finally, based on the community structure of subnetworks, the community labels of all nodes are obtained by using the idea of label propagation. Extensive experiments on real-world datasets validate the effectiveness of MotifCC.

ResD-Net: A model for rapid prediction of antioxidant activity in gentian root using FT-IR spectroscopy.

Gentian, an herb resource known for its antioxidant properties, has garnered significant attention. However, existing methods are time-consuming and destructive for assessing the antioxidant activity in gentian root samples. In this study, we propose a method for swiftly predicting the antioxidant activity of gentian root using FT-IR spectroscopy combined with chemometrics. We employed machine learning and deep learning models to establish the relationship between FT-IR spectra and DPPH free radical scavenging activity. The results of model fitting reveal that the deep learning model outperforms the machine learning model. The model's performance was enhanced by incorporating the Double-Net and residual connection strategy. The enhanced model, named ResD-Net, excels in feature extraction and also avoids gradient vanishing. The ResD-Net model achieves an R2 of 0.933, an RMSE of 0.02, and an RPD of 3.856. These results support the accuracy and applicability of this method for rapidly predicting antioxidant activity in gentian root samples.

The anti-photoaging effect of C-phycocyanin on ultraviolet B-irradiated BALB/c-nu mouse skin.

Introduction: C-phycocyanin (C-PC), a photosynthetic protein obtained from Spirulina, is regarded a highly promising commercially available biochemical. Numerous in vitro and in vivo studies have provided evidence of C-PC's ability to mitigate the inflammatory response, alleviate oxidative stress, and facilitate wound healing. However, despite the existing knowledge regarding C-PC's protective mechanism against cellular apoptosis induced by ultraviolet B (UVB) radiation, further in vivo experiments are needed to explore its anti-photoaging mechanism. Methods: In this study, a UVB-induced skin photoaging model was established using BALB/c-nu mice, and the potential protective effects of topically administered c-PC were investigated by various molecular biology tools. In addition, a novel delivery system, C-PC nanodispersion, was developed to facilitate the transdermal delivery of C-PC. Results: C- PC demonstrated significant anti-photoaging activities in the UVB-induced skin. The application of C-PC to the dorsal skin of the mice resulted in improved macroscopic characteristics, such as reduced sagging and coarse wrinkling, under UVB irradiation Histological analyses showed that C-PC treatment significantly decreased the symptoms of epidermal thickening, prevented dermal collagen fiber loosening, increased the hydroxyproline (Hyp) content and activities of antioxidant enzymes (such as superoxide dismutase, catalase, and glutathione peroxidase) in mouse skin, decreased malondialdehyde levels and expressions of inflammatory factors (interleukin-1α [IL-1α], IL-1ß, IL-6, and tumor necrosis factor-α), reduced matrix metalloproteinase [MMP-3 and MMP-9] expressions, and inhibited the phosphorylation of c-Jun N-terminal kinase, extracellular signal-regulated kinase, and p38 proteins in the mitogen-activated protein kinase family. Discussion: By analyzing the results of the study, a new drug delivery system, C-PC nano-dispersion, was proposed, and the anti-photoaging effect of C-PC and its mechanism were investigated.

Identification of Gentian-Related Species Based on Two-Dimensional Correlation Spectroscopy (2D-COS) Combined with Residual Neural Network (ResNet).

Gentian is a traditional Chinese herb with heat-clearing, damp-drying, inflammation-alleviating and digestion-promoting effects, which is widely used in clinical practice. However, there are many species of gentian. According to the pharmacopoeia, Gentiana manshurica Kitag, Gentiana scabra Bge, Gentiana triflora Pall and Gentianarigescens Franch are included. Therefore, accurately identifying the species of gentian is important in clinical use. In recent years, with the advantages of low cost, convenience, fast analysis and high sensitivity, infrared spectroscopy (IR) has been extensively used in herbal identification. Unlike one-dimensional spectroscopy, a two-dimensional correlation spectrum (2D-COS) can improve the resolution of the spectrum and better highlight the details that are difficult to detect. In addition, the residual neural network (ResNet) is an important breakthrough in convolutional neural networks (CNNs) for significant advantages related to image recognition. Herein, we propose a new method for identifying gentian-related species using 2D-COS combined with ResNet. A total of 173 gentian samples from seven different species are collected in this study. In order to eliminate a large amount of redundant information and improve the efficiency of machine learning, the extracted feature band method was used to optimize the model. Four feature bands were selected from the infrared spectrum, namely 3500-3000 cm-1, 3000-2750 cm-1, 1750-1100 cm-1 and 1100-400 cm-1, respectively. The one-dimensional spectral data were converted into synchronous 2D-COS images, asynchronous 2D-COS images, and integrative 2D-COS images using Matlab (R2022a). The identification strategy for these three 2D-COS images was based on ResNet, which analyzes 2D-COS images based on single feature bands and full bands as well as fused feature bands. According to the results, (1) compared with the other two 2D-COS images, synchronous 2D-COS images are more suitable for the ResNet model, and (2) after extracting a single feature band 1750-1100 cm-1 to optimize ResNet, the model has the best convergence performance, the accuracy of training, test and external validation is 1 and the loss value is only 0.155. In summary, 2D-COS combined with ResNet is an effective and accurate method to identify gentian-related species.

Laser speckle contrast imaging based on spatial frequency domain filtering.

We proposed a novel method to separate static and dynamic speckles based on spatial frequency domain filtering. First, the raw speckle image sequence is processed frame by frame through 2D Fourier transform, low-pass and high-pass filtering in the spatial frequency domain, and inverse Fourier transform. Then, we can obtain low- and high-frequency image sequences in the spatial domain. Second, we averaged both sequences in the time domain. After the above processing, we obtain the mean intensities of the dynamic and static speckle components in the spatial domain. Finally, we calculated the time-averaged modulation depth to map the 2-D blood flow distribution. Both phantom and vivo experiments demonstrated that the proposed method could effectively suppress the background non-uniformity and has the advantage of high computational efficiency. It also can effectively improve image contrast, contrast-to-noise ratio, and imaging dynamic range.

Ganoderma lucidum polysaccharides attenuates pressure-overload-induced pathological cardiac hypertrophy.

Pathological cardiac hypertrophy is an important risk factor for cardiovascular disease. However, drug therapies that can reverse the maladaptive process and restore heart function are limited. Ganoderma lucidum polysaccharides (GLPs) are one of the main active components of G. lucidum (Ganoderma lucidum), and they have various pharmacological effects. GLPs have been used as Chinese medicine prescriptions for clinical treatment. In this study, cardiac hypertrophy was induced by transverse aortic constriction (TAC) in mice. We found that GLPs ameliorate Ang II-induced cardiomyocyte hypertrophy in vitro and attenuate pressure overload-induced cardiac hypertrophy in vivo. Further research indicated that GLPs attenuated the mRNA levels of hypertrophic and fibrotic markers to inhibit cardiac hypertrophy through the PPARγ/PGC-1α pathway. Overall, these results indicate that GLPs inhibit cardiac hypertrophy through downregulating key genes for hypertrophy and fibrosis and attenuate pressure overload-induced pathological cardiac hypertrophy by activating PPARγ. This study provides important theoretical support for the potential of using GLPs to treat pathological myocardial hypertrophy and heart failure.

Dihydrotanshinone I preconditions myocardium against ischemic injury via PKM2 glutathionylation sensitive to ROS.

Ischemic preconditioning (IPC) is a potential intervention known to protect the heart against ischemia/reperfusion injury, but its role in the no-reflow phenomenon that follows reperfusion is unclear. Dihydrotanshinone I (DT) is a natural compound and this study illustrates its role in cardiac ischemic injury from the aspect of IPC. Pretreatment with DT induced modest ROS production and protected cardiomyocytes against oxygen and glucose deprivation (OGD), but the protection was prevented by a ROS scavenger. In addition, DT administration protected the heart against isoprenaline challenge. Mechanistically, PKM2 reacted to transient ROS via oxidization at Cys423/Cys424, leading to glutathionylation and nuclear translocation in dimer form. In the nucleus, PKM2 served as a co-factor to promote HIF-1α-dependent gene induction, contributing to adaptive responses. In mice subjected to permanent coronary ligation, cardiac-specific knockdown of Pkm2 blocked DT-mediated preconditioning protection, which was rescued by overexpression of wild-type Pkm2, rather than Cys423/424-mutated Pkm2. In conclusion, PKM2 is sensitive to oxidation, and subsequent glutathionylation promotes its nuclear translocation. Although IPC has been viewed as a protective means against reperfusion injury, our study reveals its potential role in protection of the heart from no-reflow ischemia.

Rapid Identification of Wild Gentiana Genus in Different Geographical Locations Based on FT-IR and an Improved Neural Network Structure Double-Net.

Gentiana Genus, a herb mainly distributed in Asia and Europe, has been used to treat the damp heat disease of the liver for over 2000 years in China. Previous studies have shown significant differences in the compositional contents of wild Gentiana Genus samples from different geographical origins. Therefore, the traceable geographic locations of the wild Gentiana Genus samples are essential to ensure practical medicinal value. Over the last few years, the developments in chemometrics have facilitated the analysis of the composition of medicinal herbs via spectroscopy. Notably, FT-IR spectroscopy is widely used because of its benefit of allowing rapid, nondestructive measurements. In this paper, we collected wild Gentiana Genus samples from seven different provinces (222 samples in total). Twenty-one different FT-IR spectral pre-processing methods that were used in our experiments. Meanwhile, we also designed a neural network, Double-Net, to predict the geographical locations of wild Gentiana Genus plants via FT-IR spectroscopy. The experiments showed that the accuracy of the neural network structure Double-Net we designed can reach 100%, and the F1_score can reach 1.0.

A fish-scale derived multifunctional nanofiber membrane for infected wound healing.

The rapid development of modern medicine has put forward new requirements for wound infection healing methods in clinical treatment. Despite the great achievements made in the research and development of various types of dressings in recent years, yet there is still a challenge of multifunctional dressings for effective wound treatment. Herein, a multifunctional nanofibrous membrane was prepared by encapsulating NIR-adsorbed CuS (FSC/CuS) nanoparticles, polyvinylpyrrolidone (PVP) and polyvinyl butyral (PVB) with electrospun fish scale collagen. During the evaluation of wound healing, four parameters, including hemostasis time, inflammatory response, cell proliferation, and tissue remodeling, were considered. The results of H&E, Masson and immunohistochemical staining showed that the synergistic effect of composite nanofibers and near-infrared light can inhibit the inflammatory response, promote the proliferation and migration of fibroblasts and keratinocytes, rebuild new tissues, form well-dispersed collagen fibers, etc. It was shown that the FSC/CuS NPs combined with an NIR-driven experimental group exhibited excellent performance in accelerating wound healing in these stages. This kind of nanofibrous scaffold prepared with fish scale and NIR-absorbing agents will have broad application prospects in the healing of infected wounds.

Significance of T-Cell Subsets for Clinical Response to Peginterferon Alfa-2a Therapy in HBeAg-Positive Chronic Hepatitis B Patients.

Introduction: The adaptive immune response may reflect the immunomodulatory efficacy during peginterferon alfa-2a (PEG-IFN α-2a) treatment in chronic hepatitis B (CHB) patients. We evaluated the predictive efficiency of T-cell subsets on patient's response to PEG-IFN α-2a treatment. Methods: The proportions of CD8+PD-1+, CD8+Tim-3+ and CD4+CD25high T-cells were measured at baseline and week 52 in CHB patients who underwent PEG-IFN α-2a treatment. The proportions of T-cell subsets were compared among different responders and non-responders (determined by biochemical, serological, and virological responses). Results: The baseline proportions of the three T-cell subsets were significantly higher in CHB patients (65 cases) than in healthy controls (28 cases), while the proportions declined significantly after 52 weeks of PEG-IFN treatment. Responders (ALT < 40 IU/L, 89.2% [58/65]; HBV DNA < 2.7 log10 IU/ml, 66.2% [43/65]; and HBeAg seroconversion [SR], 53.9% [35/65]) experienced more pronounced declines in the proportion of T-cell subsets compared to non-responders. In particular, the baseline proportions of CD4+CD25high T-cells displayed significant difference between SR and non-SR groups. The stepwise logistic regression analysis identified that CD4+CD25high T-cells combined with baseline HBV DNA and ALT can predict SR and CR (ALT < 40 IU/L, HBV DNA < 2.7 log10 IU/mL and HBeAg seroconversion) after 52 weeks of PEG-IFN treatment with high accuracy. Conclusion: PEG-IFN therapy induces significant declines in the proportion of some key T-cell subsets in HBeAg-positive patients. The model constructed with CD4+CD25high T-cells combined with ATL and HBV DNA may help to predict the efficacy of PEG-IFN α-2a therapy.

Transdermal Delivery of Indirubin-Loaded Microemulsion Gel: Preparation, Characterization and Anti-Psoriatic Activity.

Psoriasis is an immune disease caused by rapid and incomplete differentiation of skin basal cells. Natural products such as indirubin have historically served as excellent sources for the treatments of psoriasis. However, the poor solubility and bioavailability due to its plane and rigid crystal structure, which limits its efficacy. Herein, to improve the efficacy of indirubin, a hydrogel-based microemulsion drug delivery system was developed for transdermal delivery. The mean droplet size of the optimized microemulsion was 84.37 nm, with a polydispersity index (PDI) less than 0.2 and zeta potential value of 0~-20 mV. The transdermal flux and skin retention of indirubin at 24 h were 47.34 ± 3.59 µg/cm2 and 8.77 ± 1.26 µg/cm2, respectively. The optimized microemulsion was dispersed in carbomer 934 hydrogel to increase the consistency. The indirubin-loaded microemulsion gel was tested on an imiquimod-induced psoriasis mouse model. Results showed that this preparation can improve psoriasis symptoms by down-regulating the expression of IL-17A, Ki67, and CD4+T. This experiment provides great scalability for researchers to treat psoriasis, avoid first-pass effects, and increase the concentration of targeted drugs.

Protocatechuic aldehyde protects cardiomycoytes against ischemic injury via regulation of nuclear pyruvate kinase M2.

Rescuing cells from stress damage emerges a potential therapeutic strategy to combat myocardial infarction. Protocatechuic aldehyde (PCA) is a major phenolic acid in Chinese herb Danshen (Salvia miltiorrhiza root). This study investigated whether PCA regulated nuclear pyruvate kinase isoform M2 (PKM2) function to protect cardiomyocytes. In rats subjected to isoprenaline, PCA attenuated heart injury and protected cardiomyocytes from apoptosis. Through DARTS and CETSA assays, we identified that PCA bound and promoted PKM2 nuclear translocation in cardiomyocytes exposed to oxygen/glucose deprivation (OGD). In the nucleus, PCA increased the binding of PKM2 to ß-catenin via preserving PKM2 acetylation, and the complex, in cooperation with T-cell factor 4 (TCF4), was required for transcriptional induction of genes encoding anti-apoptotic proteins, contributing to rescuing cardiomyocyte survival. In addition, PCA ameliorated mitochondrial dysfunction and prevented mitochondrial apoptosis dependent on PKM2. Consistently, PCA increased the binding of PKM2 to ß-catenin, improved heart contractive function, normalized heart structure and attenuated oxidative damage in mice subjected to artery ligation, but the protective effects were lost in Pkm2-deficient heart. Together, we showed that PCA regulated nuclear PKM2 function to rescue cardiomyocyte survival via ß-catenin/TCF4 signaling cascade, suggesting the potential of pharmacological intervention of PKM2 shuttle to protect the heart.

Target Characterization of Kaempferol against Myocardial Infarction Using Novel In Silico Docking and DARTS Prediction Strategy.

Target identification is a crucial process for advancing natural products and drug leads development, which is often the most challenging and time-consuming step. However, the putative biological targets of natural products obtained from traditional prediction studies are also informatively redundant. Thus, how to precisely identify the target of natural products is still one of the major challenges. Given the shortcomings of current target identification methodologies, herein, a novel in silico docking and DARTS prediction strategy was proposed. Concretely, the possible molecular weight was detected by DARTS method through examining the protected band in SDS-PAGE. Then, the potential targets were obtained from screening and identification through the PharmMapper Server and TargetHunter method. In addition, the candidate target Src was further validated by surface plasmon resonance assay, and the anti-apoptosis effects of kaempferol against myocardial infarction were further confirmed by in vitro and in vivo assays. Collectively, these results demonstrated that the integrated strategy could efficiently characterize the targets, which may shed a new light on target identification of natural products.

Probing specific ligand-protein interactions by native-denatured exchange mass spectrometry.

Probing ligand-target protein interactions provides essential information for deep understanding of biochemical machinery and design of drug screening assays. Native electrospray ionization-mass spectrometry (ESI-MS) is promising for direct analysis of ligand-protein complexes. However, it lacks the ability to distinguish between specific and non-specific ligand-protein interactions, and to further recognize the specifically bound proteins as drug target candidates, which remains as a major challenge in the field of drug developments by far. Herein we report a native-denatured exchange (NDX) mass spectrometry (MS) acquisition approach using a liquid sample-desorption electrospray ionization (LS-DESI) setup, and demonstrate its capability in enabling a change from native detection of noncovalent ligand-protein complexes to denatured analysis using three model ligand-protein complexes including myoglobin, CDP-ribonuclease and N,N',N″-triacetylchitotriose (NAG3)-lysozyme. Notably, we found the NDX-MS approach can readily discriminate specific ligand-protein interactions from nonspecific ones, as revealed by their distinct dynamic profiles of Kd as a function of the DESI spraying flow rate. Consequently, this NDX-MS approach holds promise for future applications to discovering specific protein targets for ligands of interest, and to screening compounds with high specificity to drug targets and thus eliminates off-target effects.

Characterization of anti-leukemia components from Indigo naturalis using comprehensive two-dimensional K562/cell membrane chromatography and in silico target identification.

Traditional Chinese Medicine (TCM) has been developed for thousands of years and has formed an integrated theoretical system based on a large amount of clinical practice. However, essential ingredients in TCM herbs have not been fully identified, and their precise mechanisms and targets are not elucidated. In this study, a new strategy combining comprehensive two-dimensional K562/cell membrane chromatographic system and in silico target identification was established to characterize active components from Indigo naturalis, a famous TCM herb that has been widely used for the treatment of leukemia in China, and their targets. Three active components, indirubin, tryptanthrin and isorhamnetin, were successfully characterized and their anti-leukemia effects were validated by cell viability and cell apoptosis assays. Isorhamnetin, with undefined cancer related targets, was selected for in silico target identification. Proto-oncogene tyrosine-protein kinase (Src) was identified as its membrane target and the dissociation constant (Kd) between Src and isorhamnetin was 3.81 µM. Furthermore, anti-leukemia effects of isorhamnetin were mediated by Src through inducing G2/M cell cycle arrest. The results demonstrated that the integrated strategy could efficiently characterize active components in TCM and their targets, which may bring a new light for a better understanding of the complex mechanism of herbal medicines.

Nano-porous nitrocellulose liquid bandage modulates cell and cytokine response and accelerates cutaneous wound healing in a mouse model.

Nitrocellulose liquid bandage (L-Bandage) is extensively used in hard-to-cover cuts and wounds management, owing to its flexibility, softness, transparency, and conformability. However, evidence supporting their mechanisms of action as wound dressing is scanty. This study introduces a novel nano-porous L-Bandage, and provides results from a mouse full-thickness wound model investigating its mechanism of action on wound healing. Different characteristics, such as porosity, mechanical properties and water vapor transmission rate (WVTR) were determined. The L-Bandage formed film had a porous network structure with mean diameter of 18 nm that could effectively prevent the bacterial invasion, and favorable properties of tensile strength, elongation, and WVTR. The L-Bandage treated wound exhibited accelerated healing, with reduced inflammations, enhanced wound re-epithelialization, contraction, granulation tissue formation, and rapid angiogenesis. Our data suggested that L-Bandage could serve as a promising wound dressing, because of its desirable properties for wound healing.

On-line comprehensive two-dimensional HepG2 cell membrane chromatographic analysis system for charactering anti-hepatoma components from rat serum after oral administration of Radix scutellariae: A strategy for rapid screening active compounds in vivo.

Cell membrane chromatography (CMC) is a bioaffinity chromatography technique for characterizing interactions between drugs and membrane receptors and has been widely used to screen active components from complex samples such as herbal medicines (HMs). However, it has never been applied in vivo due to its relatively high limit of detection (LOD) and the matrix interferences. In this study, a novel on-line comprehensive two-dimensional HepG2/CMC/enrich columns/high performance liquid chromatography/time-of-flight mass spectrometry system was developed to rapidly screen potential anti-hepatoma components from drug-containing serum of rats after oral administration of Radix scutellariae. A matrix interference deduction method with a home-written program in MATLAB was developed, which could successfully eliminate the interference of endogenous substances in serum. Baicalein, wogonin, chrysin, oroxylin A, neobaicalein and rivularin from Radix scutellariae extraction were significantly retained in the HepG2/CMC column. Three potential active components, wogonin, oroxylin A and neobaicalein were firstly screened from the drug-containing serum as well. The cell counting kit-8 assay demonstrated that wogonin, oroxylin A and chrysin showed high inhibitory activities in a dose-dependent manner on HepG2 cells at the concentration of 12.5-200 µM (p<0.05) and the IC50 values were 69.83, 16.66 and 51.6 µM, respectively. Wogonin and oroxylin A, which were screened both from Radix scutellariae extraction and the drug-containing serum, could be selected as lead compounds to obtain good anti-hepatoma effects. The proposed comprehensive 2D CMC system and matrix interference elimination strategy have significant advantages for in vivo screening of active components from complex biological samples and could be applied to other biochromatography models.

[Targeting angiogenesis and vascular remodeling as a novel therapeutic approach to liver fibrosis].

Development of liver fibrosis is closely associated with angiogenesis and abnormal vascular remodeling. Recent studies have highlighted the importance of angiogenesis and vascular remodeling in fibrogenesis, the results that inhibition of angiogenesis is effective in suppression of liver fibrosis demonstrate that therapies with several molecular targets against angiogenesis, inflammation and fibrosis might be beneficial for the treatment of cirrhosis. However, there is some evidence that inhibition of angiogenesis can even worsen fibrosis. This article outlines recent advances regarding the interplay between inflammation, angiogenesis and fibrogenesis in terms of cellular and molecular mechanisms, and suggests a requirement of greater understanding to intervene in these key processes, such as liver sinusoidal endothelial cell fenestration and impact distinct chemokine actions driving monocyte migration and differentiation, for therapeutic benefit in the future.