Informed by Cancer Stem Cells of Solid Tumors: Advances in Treatments Targeting Tumor-Promoting Factors and Pathways.

Cancer stem cells (CSCs) represent a subpopulation within tumors that promote cancer progression, metastasis, and recurrence due to their self-renewal capacity and resistance to conventional therapies. CSC-specific markers and signaling pathways highly active in CSCs have emerged as a promising strategy for improving patient outcomes. This review provides a comprehensive overview of the therapeutic targets associated with CSCs of solid tumors across various cancer types, including key molecular markers aldehyde dehydrogenases, CD44, epithelial cellular adhesion molecule, and CD133 and signaling pathways such as Wnt/ß-catenin, Notch, and Sonic Hedgehog. We discuss a wide array of therapeutic modalities ranging from targeted antibodies, small molecule inhibitors, and near-infrared photoimmunotherapy to advanced genetic approaches like RNA interference, CRISPR/Cas9 technology, aptamers, antisense oligonucleotides, chimeric antigen receptor (CAR) T cells, CAR natural killer cells, bispecific T cell engagers, immunotoxins, drug-antibody conjugates, therapeutic peptides, and dendritic cell vaccines. This review spans developments from preclinical investigations to ongoing clinical trials, highlighting the innovative targeting strategies that have been informed by CSC-associated pathways and molecules to overcome therapeutic resistance. We aim to provide insights into the potential of these therapies to revolutionize cancer treatment, underscoring the critical need for a multi-faceted approach in the battle against cancer. This comprehensive analysis demonstrates how advances made in the CSC field have informed significant developments in novel targeted therapeutic approaches, with the ultimate goal of achieving more effective and durable responses in cancer patients.

[Application status and challenges of molecular docking in development of traditional Chinese medicine].

Traditional Chinese medicine is precious treasure of ancient Chinese science and a key to unlocking the treasure trove of Chinese civilization. To elucidate the efficacy and mechanism of traditional Chinese medicines, scientists have been engaged in the research on the molecular basis and regulatory targets. Molecular docking is a computer-aided drug design method capable of visualizing the interaction between components and target proteins. With the progress in the modernization of traditional Chinese medicine and the advancement of algorithms and computing power, molecular docking has become an essential approach in the development of new traditional Chinese medicines. This article summarizes the recent research progress in molecular docking in the development of traditional Chinese medicine, aiming to provide valuable references for further screening of active components and offering insights for improving the development of new traditional Chinese medicines.

Drug-Online: an online platform for drug-target interaction, affinity, and binding sites identification using deep learning.

BACKGROUND: Accurately identifying drug-target interaction (DTI), affinity (DTA), and binding sites (DTS) is crucial for drug screening, repositioning, and design, as well as for understanding the functions of target. Although there are a few online platforms based on deep learning for drug-target interaction, affinity, and binding sites identification, there is currently no integrated online platforms for all three aspects. RESULTS: Our solution, the novel integrated online platform Drug-Online, has been developed to facilitate drug screening, target identification, and understanding the functions of target in a progressive manner of "interaction-affinity-binding sites". Drug-Online platform consists of three parts: the first part uses the drug-target interaction identification method MGraphDTA, based on graph neural networks (GNN) and convolutional neural networks (CNN), to identify whether there is a drug-target interaction. If an interaction is identified, the second part employs the drug-target affinity identification method MMDTA, also based on GNN and CNN, to calculate the strength of drug-target interaction, i.e., affinity. Finally, the third part identifies drug-target binding sites, i.e., pockets. The method pt-lm-gnn used in this part is also based on GNN. CONCLUSIONS: Drug-Online is a reliable online platform that integrates drug-target interaction, affinity, and binding sites identification. It is freely available via the Internet at http://39.106.7.26:8000/Drug-Online/ .

Risk prediction of pulse wave for hypertensive target organ damage based on frequency-domain feature map.

The application of deep learning to the classification of pulse waves in Traditional Chinese Medicine (TCM) related to hypertensive target organ damage (TOD) is hindered by challenges such as low classification accuracy and inadequate generalization performance. To address these challenges, we introduce a lightweight transfer learning model named MobileNetV2SCP. This model transforms time-domain pulse waves into 36-dimensional frequency-domain waveform feature maps and establishes a dedicated pre-training network based on these maps to enhance the learning capability for small samples. To improve global feature correlation, we incorporate a novel fusion attention mechanism (SAS) into the inverted residual structure, along with the utilization of 3 × 3 convolutional layers and BatchNorm layers to mitigate model overfitting. The proposed model is evaluated using cross-validation results from 805 cases of pulse waves associated with hypertensive TOD. The assessment metrics, including Accuracy (92.74 %), F1-score (91.47 %), and Area Under Curve (AUC) (97.12 %), demonstrate superior classification accuracy and generalization performance compared to various state-of-the-art models. Furthermore, this study investigates the correlations between time-domain and frequency-domain features in pulse waves and their classification in hypertensive TOD. It analyzes key factors influencing pulse wave classification, providing valuable insights for the clinical diagnosis of TOD.

A dual-target SPR screening system for simultaneous ligand discovery of SARS-CoV-2 spike protein and its receptor ACE2 from Chinese herbs.

Traditional Chinese Medicine (TCM) is a supremely valuable resource for the development of drug discovery. Few methods are capable of hunting for potential molecule ligands from TCM towards more than one single protein target. In this study, a novel dual-target surface plasmon resonance (SPR) biosensor was developed to perform targeted compound screening of two key proteins involved in the cellular invasion process of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2): the spike (S) protein receptor binding domain (RBD) and the angiotensin-converting enzyme 2 (ACE2). The screening and identification of active compounds from six Chinese herbs were conducted taking into consideration the multi-component and multi-target nature of Traditional Chinese Medicine (TCM). Puerarin from Radix Puerariae Lobatae was discovered to exhibit specific binding affinity to both S protein RBD and ACE2. The results highlight the efficiency of the dual-target SPR system in drug screening and provide a novel approach for exploring the targeted mechanisms of active components from Chinese herbs for disease treatment.

Multimodal phototherapy agents target lipid droplets for near-infrared imaging-guided type I photodynamic/photothermal therapy.

The construction and optimization of a single phototherapeutic agent with photoluminescence, type I photodynamic therapy (PDT), and photothermal therapy (PTT) functions remain challenging. In this study, we aimed to design and synthesize four donor-acceptor (D-A) type aggregation-induced emission molecules: PSI, TPSI, PSSI, and TPSSI. We employed phenothiazine as an electron donor and 1,3-bis(dicyanomethylidene)indan as a strong electron acceptor in the synthesis process. Among them, TPSSI exhibited efficient type I reactive oxygen species generation, high photothermal conversion efficiency (45.44 %), and near-infrared emission. These observations can be attributed to the introduction of a triphenylamine electron donor group and a thiophene unit, which resulted in increased D-A strengths, a reduced singlet-triplet energy gap, and increased free intramolecular motion. TPSSI was loaded into bovine serum albumin to prepare biocompatible TPSSI nanoparticles (NPs). Our results have indicated that TPSSI NPs can target lipid droplets with negligible dark toxicity and can efficiently generate O2•- in hypoxic tumor environments. Moreover, TPSSI NPs selectively targeted 4T1 tumor tissues and exhibited a good PDT-PTT synergistic effect in vitro and in vivo. We believe that the successful preparation of multifunctional phototherapeutic agents will promote the development of efficient tumor diagnosis and treatment technologies. STATEMENT OF SIGNIFICANCE: The construction of a single phototherapeutic agent with photoluminescence, type I photodynamic therapy, and photothermal therapy functions, and its optimization remain challenging. In this study, we construct four donor-acceptor aggregation-induced emission molecules using phenothiazine as an electron donor and 1,3-Bis(dicyanomethylidene)indan as a strong electron acceptor. By optimizing the molecular structure, an integrated phototherapy agent with fluorescence imaging ability and high photodynamic / photothermal therapy performance was prepared. We believe that the successful preparation of multifunctional phototherapeutic agents will promote the development of efficient tumor diagnosis and treatment technology.

N-Cinnamoylpyrrole-derived alkaloids from the genus Piper as promising agents for ischemic stroke by targeting eEF1A1.

BACKGROUND: Ischemic stroke (IS) is a serious cerebrovascular disease characterized by significantly elevated mortality and disability rates, and the treatments available for this disease are limited. Neuroinflammation and oxidative stress are deemed the major causes of cerebral ischemic injury. N-Cinnamoylpyrrole alkaloids form a small group of natural products from the genus Piper and have not been extensively analyzed pharmacologically. Thus, identifying the effect and mechanism of N-cinnamoylpyrrole-derived alkaloids on IS is worthwhile. PURPOSE: The present research aimed to explore the antineuroinflammatory and antioxidative stress effects of N-cinnamoylpyrrole-derived alkaloids isolated from the genus Piper and to explain the effects and mechanism on IS. METHODS: N-cinnamoylpyrrole-derived alkaloids were isolated from Piper boehmeriaefolium var. tonkinense and Piper sarmentosum and identified by various chromatographic methods. Lipopolysaccharide (LPS)-induced BV-2 microglia and a mouse model intracerebroventricularly injected with LPS were used to evaluate the antineuroinflammatory and antioxidative stress effects. Oxygen‒glucose deprivation/reperfusion (OGD/R) and transient middle cerebral artery occlusion (tMCAO) models were used to evaluate the effect of PB-1 on IS. To elucidate the fundamental mechanism, the functional target of PB-1 was identified by affinity-based protein profiling (ABPP) strategy and verified by cellular thermal shift assay (CETSA), drug affinity responsive target stability (DARTS), and circular dichroism (CD) analyses. The effect of PB-1 on the NF-κB and NRF2 signaling pathways was subsequently evaluated via western blotting and immunofluorescence staining. RESULTS: The results showed that N-cinnamoylpyrrole-derived alkaloids significantly affected neuroinflammation and oxidative stress. The representative compound, PB-1 not only inhibited neuroinflammation and oxidative stress induced by LPS or OGD/R insult, but also alleviated cerebral ischemic injury induced by tMCAO. Further molecular mechanism research found that PB-1 promoted antineuroinflammatory and antioxidative stress activities via the NF-κB and NRF2 signaling pathways by targeting eEF1A1. CONCLUSION: Our research initially unveiled that the therapeutic impact of PB-1 on cerebral ischemic injury might rely on its ability to target eEF1A1, leading to antineuroinflammatory and antioxidative stress effects. The novel discovery highlights eEF1A1 as a potential target for IS treatment and shows that PB-1, as a lead compound that targets eEF1A1, may be a promising therapeutic agent for IS.

GraphormerDTI: A graph transformer-based approach for drug-target interaction prediction.

The application of Artificial Intelligence (AI) to screen drug molecules with potential therapeutic effects has revolutionized the drug discovery process, with significantly lower economic cost and time consumption than the traditional drug discovery pipeline. With the great power of AI, it is possible to rapidly search the vast chemical space for potential drug-target interactions (DTIs) between candidate drug molecules and disease protein targets. However, only a small proportion of molecules have labelled DTIs, consequently limiting the performance of AI-based drug screening. To solve this problem, a machine learning-based approach with great ability to generalize DTI prediction across molecules is desirable. Many existing machine learning approaches for DTI identification failed to exploit the full information with respect to the topological structures of candidate molecules. To develop a better approach for DTI prediction, we propose GraphormerDTI, which employs the powerful Graph Transformer neural network to model molecular structures. GraphormerDTI embeds molecular graphs into vector-format representations through iterative Transformer-based message passing, which encodes molecules' structural characteristics by node centrality encoding, node spatial encoding and edge encoding. With a strong structural inductive bias, the proposed GraphormerDTI approach can effectively infer informative representations for out-of-sample molecules and as such, it is capable of predicting DTIs across molecules with an exceptional performance. GraphormerDTI integrates the Graph Transformer neural network with a 1-dimensional Convolutional Neural Network (1D-CNN) to extract the drugs' and target proteins' representations and leverages an attention mechanism to model the interactions between them. To examine GraphormerDTI's performance for DTI prediction, we conduct experiments on three benchmark datasets, where GraphormerDTI achieves a superior performance than five state-of-the-art baselines for out-of-molecule DTI prediction, including GNN-CPI, GNN-PT, DeepEmbedding-DTI, MolTrans and HyperAttentionDTI, and is on a par with the best baseline for transductive DTI prediction. The source codes and datasets are publicly accessible at https://github.com/mengmeng34/GraphormerDTI.

Disulfide Cross-Linked Polymeric Redox-Responsive Nanocarrier Based on Heparin, Chitosan and Lipoic Acid Improved Drug Accumulation, Increased Cytotoxicity and Selectivity to Leukemia Cells by Tumor Targeting via "Aikido" Principle.

We have developed a micellar formulation of anticancer drugs based on chitosan and heparin grafted with lipoic and oleic acids that can release the cytotoxic cargo (doxorubicin) in response to external stimuli, such as increased glutathione concentration-a hallmark of cancer. Natural polysaccharides (heparin and chitosan) provide the pH sensitivity of the nanocarrier: the release of doxorubicin (Dox) is enhanced in a slightly acidic environment (tumor microenvironment). Fatty acid residues are necessary for the formation of nanoparticles (micelles) and solubilization of cytostatics in a hydrophobic core. Lipoic acid residues provide the formation of a labile S-S cross-linking between polymer chains (the first variant) or covalently attached doxorubicin molecules through glutathione-sensitive S-S bridges (the second variant)-both determine Redox sensitivity of the anticancer drugs carriers stable in blood circulation and disintegrate after intracellular uptake in the tumor cells. The release of doxorubicin from micelles occurs slowly (20%/6 h) in an environment with a pH of 7.4 and the absence of glutathione, while in a slightly acidic environment and in the presence of 10 mM glutathione, the rate increases up to 6 times, with an increase in the effective concentration up to 5 times after 7 h. The permeability of doxorubicin in micellar formulations (covalent S-S cross-linked and not) into Raji, K562, and A875 cancer cells was studied using FTIR, fluorescence spectroscopy and confocal laser scanning microscopy (CLSM). We have shown dramatically improved accumulation, decreased efflux, and increased cytotoxicity compared to doxorubicin control with three tumor cell lines: Raji, K562, and A875. At the same time, cytotoxicity and permeability for non-tumor cells (HEK293T) are significantly lower, increasing the selectivity index against tumor cells by several times.

Dual-channel hypergraph convolutional network for predicting herb-disease associations.

Herbs applicability in disease treatment has been verified through experiences over thousands of years. The understanding of herb-disease associations (HDAs) is yet far from complete due to the complicated mechanism inherent in multi-target and multi-component (MTMC) botanical therapeutics. Most of the existing prediction models fail to incorporate the MTMC mechanism. To overcome this problem, we propose a novel dual-channel hypergraph convolutional network, namely HGHDA, for HDA prediction. Technically, HGHDA first adopts an autoencoder to project components and target protein onto a low-dimensional latent space so as to obtain their embeddings by preserving similarity characteristics in their original feature spaces. To model the high-order relations between herbs and their components, we design a channel in HGHDA to encode a hypergraph that describes the high-order patterns of herb-component relations via hypergraph convolution. The other channel in HGHDA is also established in the same way to model the high-order relations between diseases and target proteins. The embeddings of drugs and diseases are then aggregated through our dual-channel network to obtain the prediction results with a scoring function. To evaluate the performance of HGHDA, a series of extensive experiments have been conducted on two benchmark datasets, and the results demonstrate the superiority of HGHDA over the state-of-the-art algorithms proposed for HDA prediction. Besides, our case study on Chuan Xiong and Astragalus membranaceus is a strong indicator to verify the effectiveness of HGHDA, as seven and eight out of the top 10 diseases predicted by HGHDA for Chuan-Xiong and Astragalus-membranaceus, respectively, have been reported in literature.

Codonopsis pilosula water extract delays D-galactose-induced aging of the brain in mice by activating autophagy and regulating metabolism.

ETHNOPHARMACOLOGICAL RELEVANCE: Codonopsis pilosula (C. pilosula), also called "Dangshen" in Chinese, is derived from the roots of Codonopsis pilosula (Franch.) Nannf. (C. pilosula), Codonopsis pilosula var. Modesta (Nannf.) L.D.Shen (C. pilosula var. modesta) or Codonopsis pilosula subsp. Tangshen (Oliv.) D.Y.Hong (C. pilosula subsp. tangshen), is a well-known traditional Chinese medicine. It has been regularly used for anti-aging, strengthening the spleen and tonifying the lungs, regulating blood sugar, lowering blood pressure, strengthening the body's immune system, etc. However, the mechanism, by which, C. pilosula exerts its therapeutic effects on brain aging remains unclear. AIM OF THE STUDY: This study aimed to investigate the underlying mechanisms of the protective effects of C. pilosula water extract (CPWE) on the hippocampal tissue of D-galactose-induced aging mice. MATERIALS AND METHODS: In this research, plant taxonomy has been confirmed in the "The Plant List" database (www.theplantlist.org). First, an aging mouse model was established through the intraperitoneal injections of D-galactose solution, and low-, medium-, and high-dose CPWE were administered to mice by gavage for 42 days. Then, the learning and memory abilities of the mice were examined using the Morris water maze tests and step-down test. Hematoxylin and eosin staining was performed to visualize histopathological damage in the hippocampus. A transmission electron microscope was used to observe the ultrastructure of hippocampal neurons. Immunohistochemical staining was performed to examine the expression of glial fibrillary acidic protein (GFAP), the marker protein of astrocyte activation, and autophagy-related proteins, including microtubule-associated protein light chain 3 (LC3) and sequestosome 1 (SQSTM1)/p62, in the hippocampal tissues of mice. Moreover, targeted metabolomic analysis was performed to assess the changes in polar metabolites and short-chain fatty acids in the hippocampus. RESULTS: First, CPWE alleviated cognitive impairment and ameliorated hippocampal tissue damage in aging mice. Furthermore, CPWE markedly alleviated mitochondrial damage, restored the number of autophagosomes, and activated autophagy in the hippocampal tissue of aging mice by increasing the expression of LC3 protein and reducing the expression of p62 protein. Meanwhile, the expression levels of the brain injury marker protein GFAP decreased. Moreover, quantitative targeted metabolomic analysis revealed that CPWE intervention reversed the abnormal levels of L-asparagine, L-glutamic acid, L-glutamine, serotonin hydrochloride, succinic acid, and acetic acid in the hippocampal tissue of aging mice. CPWE also significantly regulated pathways associated with D-glutamine and D-glutamate metabolism, nitrogen metabolism, arginine biosynthesis, alanine, aspartate, and glutamate metabolisms, and aminoacyl-tRNA biosynthesis. CONCLUSIONS: CPWE could improve cognitive and pathological conditions induced by D-galactose in aging mice by activating autophagy and regulating metabolism, thereby slowing down brain aging.

Exploration of the in vitro Antiviral Effects and the Active Components of Changyanning Tablets Against Enterovirus 71.

Purpose: This study aims to investigate the in vitro antiviral effects of the aqueous solution of Changyanning (CYN) tablets on Enterovirus 71 (EV71), and to analyze its active components. Methods: The in vitro anti-EV71 effects of CYN solution and its herbal ingredients were assessed by testing the relative viral RNA (vRNA) expression level and the cell viability rates. Material basis analysis was performed using HPLC-Q-TOF-MS/MS detection. Potential targets and active components were identified by network pharmacology and molecular docking. The screened components were verified by in vitro antiviral experiments. Results: CYN solution exerted anti-EV71 activities as the vRNA is markedly reduced after treatment, with a half maximal inhibitory concentration (IC50) of 996.85 µg/mL. Of its five herbal ingredients, aqueous extract of Mosla chinensis (AEMC) and leaves of Liquidambar formosana Hance (AELLF) significantly inhibited the intracellular replication of EV71, and the IC50 was tested as 202.57 µg/mL and 174.77 µg/mL, respectively. Based on HPLC-Q-TOF-MS/MS results, as well as the comparison with the material basis of CYN solution, a total of 44 components were identified from AEMC and AELLF. Through network pharmacology, AKT1, ALB, and SRC were identified as core targets. Molecular docking performed between core targets and the components indicated that 21 components may have anti-EV71 effects. Of these, nine were selected for in vitro pharmacodynamic verification, and only rosmarinic acid manifested in vitro anti-EV71 activity, with an IC50 of 11.90 µg/mL. Moreover, rosmarinic acid can stably bind with three core targets by forming hydrogen bonds. Conclusion: CYN solution has inhibitory effects on EV71 replication in vitro, and its active component was identified as rosmarinic acid. Our study provides a new approach for screening and confirmation of the effective components in Chinese herbal preparation.

Biomonitoring of mercury and selenium in commercially important shellfish: Distribution pattern, health benefit assessment and consumption advisories.

This study aims to explore the concentrations of Se and Hg in shellfish along the Gulf of Mannar (GoM) coast (Southeast India) and to estimate related risks and risk-based consumption limits for children, pregnant women, and adults. Se concentrations in shrimp, crab, and cephalopods ranged from 0.256 to 0.275 mg kg-1, 0.182 to 0.553 mg kg-1, and 0.176 to 0.255 mg kg-1, respectively, whereas Hg concentrations differed from 0.009 to 0.014 mg kg-1, 0.022 to 0.042 mg kg-1 and 0.011 to 0.024 mg kg-1, respectively. Se and Hg content in bamboo shark (C. griseum) was 0.242 mg kg-1 and 0.082 mg kg-1, respectively. The lowest and highest Se concentrations were found in C. indicus (0.176 mg kg-1) and C. natator (0.553 mg kg-1), while Hg was found high in C. griseum (0.082 mg kg-1) and low in P. vannamei (0.009 mg kg-1). Se shellfishes were found in the following order: crabs > shrimp > shark > cephalopods, while that of Hg were shark > crabs > cephalopods > shrimp. Se in shellfish was negatively correlated with trophic level (TL) and size (length and weight), whereas Hg was positively correlated with TL and size. Hg concentrations in shellfish were below the maximum residual limits (MRL) of 0.5 mg kg-1 for crustaceans and cephalopods set by FSSAI, 0.5 mg kg-1 for crustaceans and 1.0 mg kg-1 for cephalopods and sharks prescribed by the European Commission (EC/1881/2006). Se risk-benefit analysis, the AI (actual intake):RDI (recommended daily intake) ratio was > 100%, and the AI:UL (upper limit) ratio was < 100%, indicating that all shellfish have sufficient level of Se to meet daily requirements without exceeding the upper limit (UL). The target hazard quotient (THQ < 1) and hazard index (HI < 1) imply that the consumption of shellfish has no non-carcinogenic health impacts for all age groups. However, despite variations among the examined shellfish, it was consistently observed that they all exhibited a Se:Hg molar ratio > 1. This finding implies that the consumption of shellfish is generally safe in terms of Hg content. The health benefit indexes, Se-HBV and HBVse, consistently showed high positive values across all shellfish, further supporting the protective influence of Se against Hg toxicity and reinforcing the overall safety of shellfish consumption. Enhancing comprehension of food safety analysis, it is crucial to recognize that the elevated Se:Hg ratio in shellfish may be attributed to regular selenoprotein synthesis and the mitigation of Hg toxicity by substituting Se bound to Hg.

Elucidation of the key therapeutic targets and potential mechanisms of Andrographolide multi-targets against osteoarthritis via network pharmacological analysis and experimental validation.

OBJECTIVE: Our purpose is to unveil Andrographolide's potential multi-target and multi-mechanism therapeutic effects in treating OA via systematic network pharmacological analysis and cell experimental validation. MATERIALS AND METHODS: Initially, we gathered data from Andrographolide and OA-related databases to obtain information on Andrographolide's biological properties and the targets linked with OA. We developed a bioinformatic network about Andrographolide and OA, whereby we analyzed the network to identify potential therapeutic targets and mechanisms of action of Andrographolide. Subsequently, we used molecular docking to analyze the binding sites of Andrographolide to the target proteins. At the same time, SDF-1 was used to construct an OA cell model to verify the therapeutic effect of Andrographolide on OA and its effect on target proteins. RESULTS: Our experimental results show that Andrographolide has excellent pharmaceutical properties, by Lipinski's rules for drugs, suggesting that this compound can be considered to have a high therapeutic potential in drug development. 233 targets were preliminarily investigated, the mechanisms through which Andrographolide targets OA primarily involve the TNF signaling pathway, PI3K-AKT signaling pathway, IL-17 signaling pathway, and TLR signaling pathway. These mechanisms target OA by influencing immune and inflammatory responses in the joints, regulating apoptosis to prevent chondrocyte death. Finally, TNF-α, STAT3, TP53, IL-6, JUN, IL-1ß, HIF-1α, TGF-ß1, and AKT1 were identified as 9 key targets of Andrographolide anti-OA. In addition, our molecular docking analyzes with cell experimental validation further confirm the network pharmacology results. According to our molecular docking results, Andrographolide can bind to all the hub target proteins and has a good binding ability (binding energy < -5 kcal/mol), with the strongest binding affinity to AKT1 of -9.2 kcal/ mol. The results of cell experiments showed that Andrographolide treatment significantly increased the cell viability and the expression of COL2A1 and ACAN proteins. Moreover, 30 µM Andrographolide significantly reversed SDF-1-induced increases in the protein expression of TNF-α, STAT3, TP53, IL-6, JUN, IL-1ß, HIF-1α, and TGF-ß1, and decreases in the protein expression of AKT1. CONCLUSION: This study provides a comprehensive understanding of the potential therapeutic targets and mechanisms of action of Andrographolide in OA treatment. Our findings suggest that Andrographolide is a promising candidate for drug development in the management of OA.

Discussion on the mechanism of Danggui Sini decoction in treating diabetic foot based on network pharmacology and molecular docking and verification of the curative effect by meta-analysis.

Objective: The main active components and mechanism of Danggui Sini decoction (DSD) in treating diabetic foot (DF) were studied and verified by network pharmacology and molecular docking. Evidence-based medicine was used to prove its efficacy. Methods: The TCMSP systematic pharmacology platform screened out DSD's practical components and targets-screening disease targets in GeneCards database, using Cytoscape 3.7.2 to draw DSD-active ingredient-target network diagram, and drawing the protein interaction network diagram through STRING database. The Metascape platform was used to analyze the GO function enrichment and KEGG signal pathway. The molecular docking experiment was carried out by using Auto Dock vina 4.2. The related literature on DSD in treating DF in China Zhiwang, Wanfang, Weipu, and China Biomedical Literature Database was searched. The literature was screened, data was extracted, and quality was evaluated according to the inclusion and exclusion criteria. Then, a meta-analysis was performed using RevMan 5.3 software. Results: A total of 256 targets of all effective components of DSD were obtained. Among 1,272 disease targets, there are 113 common targets. The GO analysis received 6,179 entries, and the KEGG pathway enrichment analysis found 251 related pathways. The molecular docking results of the main targets of diabetic foot and the active substances of DSD all showed a high docking activity. The meta-analysis included six literature, all of which were randomized controlled experiments. The quality grade of the literature was C, and the results showed that the total effective rate of clinical efficacy in the experimental group was significantly higher than that in the control group. Conclusions: DSD may treat DF by participating in biological processes such as cell proliferation regulation, inflammatory reaction, oxidative stress reaction, and promotion of angiogenesis. DSD treats DF through AKT1, TP53, IL6, TNF, VEGFA, and other targets. DSD plays a role in treating DF mainly through the AGE-RAGE signaling pathway and PI3K-AKT signaling pathway. The molecular docking results of AKT1, TP53, IL-6, TNF, and VEGFA with the active substances of DSD show that they all have a high docking activity; among them, VEGFA has a higher docking activity. Compared with conventional treatment, DSD has a high effective rate, short wound healing time, large wound healing area, and high ABI index.

UHPLC-MS/MS and GC-MS Metabolic Profiling of a Medicinal Flourensia Fiebrigii Chemotype.

The comparative metabolic profiling and their biological properties of eight extracts obtained from diverse parts (leaves, flowers, roots) of the medicinal plant Flourensia fiebrigii S.F. Blake, a chemotype growing in highland areas (2750 m a.s.l.) of northwest Argentina, were investigated. The extracts were analysed by GC-MS and UHPLC-MS/MS. GC-MS analysis revealed the presence of encecalin (relative content: 24.86 %) in ethereal flower extract (EF) and this benzopyran (5.93 %) together sitosterol (11.35 %) in the bioactive ethereal leaf exudate (ELE). By UHPLC-MS/MS the main compounds identified in both samples were: limocitrin, (22.31 %), (2Z)-4,6-dihydroxy-2-[(4-hydroxy-3,5-dimethoxyphenyl)methylidene]-1-benzofuran-3-one (21.31 %), isobavachin (14.47 %), naringenin (13.50 %), and sternbin, (12.49 %). Phytocomplexes derived from aerial parts exhibited significant activity against biofilm production of Pseudomonas aeruginosa and Staphylococcus aureus, reaching inhibitions of 74.7-99.9 % with ELE (50 µg/mL). Notably, the extracts did not affect nutraceutical and environmental bacteria, suggesting a selective activity. ELE also showed the highest reactive species scavenging ability. This study provides valuable insights into the potential applications of this chemotype.

Rapid screening and target-guided isolation of antioxidants from German chamomile by 2,2-diphenyl-1-picrylhydrazyl-ultra-high-performance liquid chromatography-mass spectrometry coupled with off-line two-dimensional high-speed countercurrent chromatography.

German chamomile is one of the most effective herbal elements used in anti-allergic products and as an antioxidant. Herein, the antioxidant activity of different extract fractions of German chamomile was initially evaluated using an off-line 2,2-diphenyl-1-picrylhydrazyl spectrophotometric assay. The ethyl acetate extract demonstrated the highest efficacy in scavenging free radicals. Based on this, a rapid screening and separation method using ultra-high-performance liquid chromatography combined with the 2,2-diphenyl-1-picrylhydrazyl assay was implemented to identify antioxidants in the ethyl acetate fraction of German chamomile flowers. Ten potential radical scavengers were tentatively screened from German chamomile using a target-guided isolating approach with off-line two-dimensional high-speed countercurrent chromatography and the structures of the compounds were analyzed and identified. Ultimately, 10 radical scavengers were obtained from the ethyl acetate extract with a purity quotient exceeding 90%. The results demonstrated the effectiveness and reproducibility of this method for isolating potential antioxidants from complex mixtures in a targeted manner. This strategy can be applied to the target-guided isolation of complex mixtures of natural products with broad K-values and similar structures.

Exposure to individual polycyclic aromatic compounds impairs the cardiac performance of American lobster (Homarus americanus) larvae.

The potential for oil spills poses a threat to marine organisms, the toxicity of which has been attributed primarily to polycyclic aromatic compounds (PACs). Predictive tools such as the target lipid model (TLM) have been developed to forecast and assess these risks. The aim of the present study was to characterize the cardiotoxicity of 10 structurally diverse PACs in American lobster (Homarus americanus) larvae by assessing heart rate following a 48 h exposure in a passive dosing system, and subsequently use the TLM framework to calculate a critical target lipid body burden (CTLBB) for bradycardia. Exposure to 8 of the 10 PACs resulted in concentration-dependent bradycardia, with phenanthrene causing the greatest effect. The TLM was able to effectively characterize bradycardia in American lobsters, and the cardiotoxic CTLBB value determined in this study is among the most sensitive endpoints included in the CTLBB database. This study is one of the first to apply the TLM to a cardiac endpoint and will improve predictive models for assessing sublethal impacts of oil spills on American lobster populations.

Pre-heating stress associated with acute oral leucine supplementation effects in rat gastrocnemius muscle: Implications for protein synthesis signaling pathways.

Skeletal muscle is a highly plastic tissue. The role of heat shock protein 72 (Hsp72) in heat stress-induced skeletal muscle hypertrophy has been well demonstrated; however, the precise mechanisms remain unclear. Essential amino acids, such as leucine, mainly mediate muscle protein synthesis. We investigated the effects of pre-heating and increased Hsp72 expression on the mechanistic target of rapamycin (mTOR) signaling and protein synthesis following leucine administration in rat gastrocnemius muscle. To ensure increased Hsp72 expression in both the red and white portions of the muscle, one leg of male Wistar rats (10-week-old, n = 23) was heat-stressed in 43 °C water for 30 min twice at a 48-h-interval (heat-stressed leg, HS leg). The contralateral leg served as a non-heated internal control (CT leg). After the recovery period (48 h), rats were divided into the pre-administration or oral leucine administration groups. We harvested the gastrocnemius muscle (red and white parts) prior to administration and 30 and 90 min after leucine treatment (n = 7-8 per group) and intramuscular signaling responses to leucine ingestion were determined using western blotting. Heat stress significantly upregulated the expression of Hsp72 and was not altered by leucine administration. Although the phosphorylation levels of mTOR/S6K1 and ERK were similar regardless of heating, 4E-BP1 was less phosphorylated in the HS legs than the CT legs after leucine administration in the red portion of the muscles (P < 0.05). Moreover, c-Myc expression differed significantly after leucine administration in both the red and white portions of the muscles. Our findings indicate that following oral leucine administration, pre-heating partially blunted the muscle protein synthesis signaling response in the rat gastrocnemius muscle.

A quality grade classification method for fresh tea leaves based on an improved YOLOv8x-SPPCSPC-CBAM model.

In light of the prevalent issues concerning the mechanical grading of fresh tea leaves, characterized by high damage rates and poor accuracy, as well as the limited grading precision through the integration of machine vision and machine learning (ML) algorithms, this study presents an innovative approach for classifying the quality grade of fresh tea leaves. This approach leverages an integration of image recognition and deep learning (DL) algorithm to accurately classify tea leaves' grades by identifying distinct bud and leaf combinations. The method begins by acquiring separate images of orderly scattered and randomly stacked fresh tea leaves. These images undergo data augmentation techniques, such as rotation, flipping, and contrast adjustment, to form the scattered and stacked tea leaves datasets. Subsequently, the YOLOv8x model was enhanced by Space pyramid pooling improvements (SPPCSPC) and the concentration-based attention module (CBAM). The established YOLOv8x-SPPCSPC-CBAM model is evaluated by comparing it with popular DL models, including Faster R-CNN, YOLOv5x, and YOLOv8x. The experimental findings reveal that the YOLOv8x-SPPCSPC-CBAM model delivers the most impressive results. For the scattered tea leaves, the mean average precision, precision, recall, and number of images processed per second rates of 98.2%, 95.8%, 96.7%, and 2.77, respectively, while for stacked tea leaves, they are 99.1%, 99.1%, 97.7% and 2.35, respectively. This study provides a robust framework for accurately classifying the quality grade of fresh tea leaves.