Biological Experiments Research Articles

Exploring ncRNA-Drug Sensitivity Associations via Graph Contrastive Learning.

Increasing evidence has shown that noncoding RNAs (ncRNAs) can affect drug efficiency by modulating drug sensitivity genes. Exploring the association between ncRNAs and drug sensitivity is essential for drug discovery and disease prevention. However, traditional biological experiments for identifying ncRNA-drug sensitivity associations are time-consuming and laborious. In this study, we develop a novel graph contrastive learning approach named NDSGCL to predict ncRNA-drug sensitivity. NDSGCL uses graph convolutional networks to learn feature representations of ncRNAs and drugs in ncRNA-drug bipartite graphs. It integrates local structural neighbours and global semantic neighbours to learn a more comprehensive representation by contrastive learning. Specifically, the local structural neighbours aim to capture the higher-order relationship in the ncRNA-drug graph, while the global semantic neighbours are defined based on semantic clusters of the graph that can alleviate the impact of data sparsity. The experimental results show that NDSGCL outperforms basic graph convolutional network methods, existing contrastive learning methods, and state-of-the-art prediction methods. Visualization experiments show that the contrastive objectives of local structural neighbours and global semantic neighbours play a significant role in contrastive learning. Case studies on two drugs show that NDSGCL is an effective tool for predicting ncRNA-drug sensitivity associations.

Protein-Protein Interaction Prediction Model Based on ProtBert-BiGRU-Attention.

The physiological activities within cells are mainly regulated through protein-protein interactions (PPI). Therefore, studying protein interactions has become an essential part of researching protein function and mechanisms. Traditional biological experiments required for PPI prediction are expensive and time consuming. For this reason, many methods based on predicting PPI from protein sequences have been proposed in recent years. However, existing computational methods usually require the combination of evolutionary feature information of proteins to predict PPI docking situations. Because different relevant features of selected proteins are chosen, there may be differences in the predicted results for PPI. This article proposes a PPI prediction method based on the pretrained protein sequence model ProtBert, combined with the Bidirectional Gated Recurrent Unit (BiGRU) and attention mechanism. Only using protein sequence information and leveraging ProtBert's powerful ability to capture amino acid feature information, BiGRU is used for further feature extraction of the amino acid vectors output by ProtBert. The attention mechanism is then applied to enhance the focus on different amino acid features and improve the expression ability of protein sequence features, ultimately obtaining binary classification results for protein interactions. Experimental results show that our proposed ProtBert-BiGRU-Attention model has good predictive performance for PPI. Through relevant comparative experiments, it has been proven that our model performs well in protein binary prediction. Furthermore, through the ablation experiment of the model, different deep learning modules' contributions to the prediction have been demonstrated.

TRIM25 activates Wnt/β-catenin signalling by destabilising MAT2A mRNA to drive thoracic aortic aneurysm development.

This study explored the roles of methionine adenosyltransferase 2A (MAT2A) and tripartite motif containing 25 (TRIM25) in the progression of thoracic aortic aneurysm (TAA). The TAA model was established based on the β-aminopropionitrile method. The effects of MAT2A on thoracic aortic lesions and molecular levels were analyzed by several pathological staining assays (hematoxylin-eosin, Verhoeff-Van Gieson, TUNEL) and molecular biology experiments (qRT-PCR, Western blot). Angiotensin II (Ang-II) was used to induce injury in vascular smooth muscle cells (VSMCs) in vitro. The effects of MAT2A, shMAT2A, shTRIM25 and/or Wnt inhibitor (IWR-1) on the viability, apoptosis and protein expressions of VSMCs were examined by CCK-8, Annexin V-FITC/PI and Western blot assays. In TAA mice, overexpression of MAT2A alleviated thoracic aortic injury, inhibited the aberrant expressions of aortic contractile proteins and dedifferentiation markers, and blocked the activation of Wnt/β-catenin pathway. In Ang-II-induced VSMCs, up-regulation of MAT2A increased cellular activity and repressed the expression of β-catenin protein. TRIM25 knockdown promoted activity of VSMCs, inhibited apoptosis, and blocked the Wnt/β-catenin pathway activation by binding to MAT2A. IWR-1 partially counteracted the regulatory effects of shMAT2A. Collectively, TRIM25 destabilises the mRNA of MAT2A to activate Wnt/β-catenin signaling and ultimately exacerbate TAA injury.

NEUROTOXIC RISK AND ADSORPTION PROPERTIES OF COARSE NON-FUNCTIONALIZED CARBON PARTICLES DERIVED FROM APPLE WASTE

Aim. Carbon particles have been widely used in different technologies and have great potential for new biological application. Synthesis of carbon particles from agricultural waste using “green” principles is in the mainstream of biotechnology area and attract a great attention in biomedical application. Here, coarse carbon particles (CCPs) were synthesized using “green” principles from dry apple and used in the biological experiments without preliminary functionalization. Methods. Neurotoxic features of CCPs were analysed in isolated presynaptic cortex nerve terminals (synaptosomes) monitoring the extracellular levels of excitatory neurotransmitter L-[14C] glutamate and inhibitory one [3H]GABA, as well as the membrane potential. Results. Measuring the membrane potential of the nerve terminals, it was revealed an inadequate decrease in the fluorescence intensity of the potential-dependent dye rhodamine 6G in the presence of CCPs (1 mg/ml). This decrease was not due to membrane hyperpolarisation because CCPs did not change the extracellular synaptosomal levels of L-[14C] glutamate and [3H]GABA. CCP-induced decrease in the fluorescence intensity of the dye in nerve terminals can be due to its interaction with CCPs. Indeed, the ability of CCPs to interact with rhodamine 6G was shown in synaptosome-free incubation media. Conclusions. Therefore, CCPs did not possess neurotoxic signs, and so are biocompatible. In both experiments, i.e. without bio object and in biological system, CCPs were able to interact with fluorescent dye rhodamine 6G. In prospect, this feature of CCPs can be used in biotechnology after further investigation of dye interaction conditions.

LKLPDA: A Low-Rank Fast Kernel Learning Approach for Predicting piRNA-Disease Associations.

Piwi-interacting RNAs (piRNAs) are increasingly recognized as potential biomarkers for various diseases. Investig-ating the complex relationship between piRNAs and diseases through computational methods can reduce the costs and risks associated with biological experiments. Fast kernel learning (FKL) is a classical method for multi-source data fusion that is widely employed in association prediction research. However, biological networks are noisy due to the limitations of measurement technology and inherent natural variation, which can hamper the effectiveness of the network-based ideal kernel. The conventional FKL method does not address this issue. In this study, we propose a low-rank fast kernel learning (LRFKL) algorithm, which consists of low-rank representation (LRR) and the FKL algorithm. The LRFKL algorithm is designed to mitigate the effects of noise on the network-based ideal kernel. Using LRFKL, we propose a novel approach for predicting piRNA-disease associations called LKLPDA. Specifically, we first compute the similarity matrices for piRNAs and diseases. Then we use the LRFKL to fuse the similarity matrices for piRNAs and diseases separately. Finally, the LKLPDA employs AutoGluon-Tabular for predictive analysis. Computational results show that LKLPDA effectively predicts piRNA-disease associations with higher accuracy compared to previous methods. In addition, case studies confirm the reliability of the model in predicting piRNA-disease associations. Availability and implementation: The LKLPDA software and data are freely available at https://github.com/Shiqzz/LKLPDA-master.git.

DFT-aided stereo-structural and electronic structure studies of poly-hydroxyl substituted chlorophyllous molecules

Numerous chlorophyll-based derivatives have found applications in the dye and pharmaceutical industries. Here, we report the synthesis of a poly-hydroxyl substituted chlorophyll molecule (THM) and its absolute configuration determination using experimental electron circular dichroism (ECD), nuclear magnetic resonance (NMR) spectroscopy, and density functional theory (DFT) calculations. Furthermore, the photoreaction types of THM (type I and type II) were investigated through theoretical calculations and validated by biological experiments. We provide a detailed analysis of electron transfer and excitation processes in THM through theoretical calculation of hole-electron distribution, as well as study intramolecular weak interactions and conjugation effects using Reduced Density Gradient (RDG), Interaction Region Indicator (IRI), and Natural Bond Orbital Analysis (NBO). The photoreaction types (type I, type II) of THM in tumor cells have also been investigated by biological experimental measures and theoretical calculation of the single-triplet state energy gap and hole-electron distribution. Molecular electrostatic potential has also been investigated by DFT methods to give insight into the molecular structure. This study provides useful guidance for the structural and photochemical studies of the chlorophyll-derived photodynamic therapeutic drugs.

Involvement of BcNAC083 in 1-MCP-induced delayed yellowing of pak choi (Brassica rapa subsp. Chinensis) through the regulation of reactive oxygen species metabolism and inhibition of major chlorophyll catabolic genes

Leaf yellowing is a typical senescence feature in postharvest pak choi. Plant-specific NAC transcription factors (TFs) are crucial regulators of plant senescence. In this study, a senescence-related NAC TF, BcNAC083, was investigated to identify its transcriptional regulation effects on the yellowing of pak choi by treatment with 1-methylcyclopropene (1-MCP). Applying 5.0 µL L–1 1-MCP alleviated yellowing and maintained a low respiration rate, high chlorophyll content, and relatively complete chloroplast structure in pak choi during storage. However, 10 μL L–1 ethylene accelerated yellowing, as demonstrated by the higher respiration rate, lower chloroplast structural integrity and chlorophyll content. In contrast to ethylene treatment, 1-MCP suppressed the activity of the reactive oxygen species (ROS) metabolism-related enzymes superoxide dismutase (SOD), catalase (CAT), ascorbic peroxidase (APX), and lipoxygenase (LOX), and correspondingly reduced superoxide anion (O2·–), hydrogen peroxide (H2O2), and malondialdehyde (MDA) accumulation. 1-MCP treatment also suppressed the transcript levels of ROS metabolic genes, including BcRBOHC, BcRBOHD, BcSOD, BcCAT, BcAPX, and BcLOX, and inhibited the activity of the chlorophyll catabolic enzymes chlorophyllase (CLH), Mg-de-chelatase, and pheophytin pheophorbide hydrolase (PPH) and transcript levels of associated genes, including BcCLH1/2, BcPPH1/2, BcPAO, BcNYC1, BcSGR1/2, BcHCAR, BcRCCR, and BcCAO. The expression of BcNAC083 was probably induced by ROS and was downregulated by 1-MCP and upregulated by ethylene. Molecular biology experiments determined that BcNAC083 bound directly to and activated the promoters of the chlorophyll metabolism-related genes BcCLH1, BcPPH1, BcNYC1, and BcHCAR. Importantly, transient overexpression of BcNAC083 stimulated the endogenous genes (NbCLH1, NbPPH1, NbNYC1, and NbHCAR) expression in tobacco leaves, resulting in rapid chlorophyll breakdown and leaf degreening. Treatment with 1-MCP may alleviated the yellowing of pak choi by inhibiting ROS accumulation and the transcriptional regulation of BcNAC083, which had positive regulatory effects on major chlorophyll metabolic genes.

Recycling machinery of integrin coupled with focal adhesion turnover via RAB11-UNC13D-FAK axis for migration of pancreatic cancer cells

BackgroundRecycling of integrin via endosomal vesicles is critical for the migration of cancer cells, which leads to the metastasis of pancreatic cancer and devastating cancer-related death. So, new diagnostic and therapeutic molecules which target the recycling of endosomal vesicles need to be developed.MethodsPublic databases including TCGA, ICGC, GSE21501, GSE28735, and GENT are analyzed to derive diagnostic and therapeutic targets. To reveal biological roles and underlying mechanisms of molecular targets, various molecular biological experiments were conducted.ResultsFirst, we identified UNC13D’s overexpression in patients with pancreatic cancer (n = 824) and its prognostic significance and high hazard ratio (HR) in four independent pancreatic cancer cohorts (TCGA, n = 178, p = 0.014, HR = 3.629; ICGC, n = 91, p = 0.000, HR = 4.362; GSE21501, n = 102, p = 0.002, HR = 2.339; GSE28735, n = 45, p = 0.022, HR = 2.681). Additionally, its expression is associated with the clinicopathological progression of pancreatic cancer. Further biological studies have shown that UNC13D regulates the migration of pancreatic cancer cells by coupling the exocytosis of recycling endosomes with focal adhesion turnover via the regulation of FAK phosphorylation. Immunoprecipitation and immunocytochemistry showed the formation of the RAB11-UNC13D-FAK axis in endosomes during integrin recycling. We observed that UNC13D directly interacted with the FERM domain of FAK and regulated FAK phosphorylation in a calcium-dependent manner. Finally, we found co-expression of UNC13D and FAK showed the poorest survival (TCGA, p = 0.000; ICGC, p = 0.036; GSE28735, p = 0.006).ConclusionsWe highlight that UNC13D, a novel prognostic factor, promotes pancreatic cancer progression by coupling integrin recycling with focal adhesion turnover via the RAB11-UNC13D-FAK axis for the migration of pancreatic cancer cells.

Dynamic remodeling model based on chemotaxis of slime molds.

Social infrastructure networks, essential for daily life and economic activities, encompass utilities such as water, electricity, roads, and telecommunications. Dynamic remodeling of these systems is crucial for responding to continuous changes, unexpected events, and increased demand. This study proposes a new dynamic remodeling model inspired by biological mechanisms, focusing on a model based on the chemotaxis of slime molds. Slime molds adapt spontaneously to environmental changes by remodeling through the growth and degeneration of tubes. This capability can be applied to optimizing and dynamic remodeling social infrastructure networks. This study elucidated the chemotactic response characteristics of slime molds using biological experiments. The mold's response was observed by considering changes in the concentration of chemicals as environmental changes, confirming that slime molds adapt to environmental changes by shortening their periodic cycles. Subsequently, based on this dynamic response, we propose a new dynamic model (oscillated Physarum solver, O-PS) that extends the existing Physarum solver (PS). Numerical simulations demonstrated that the O-PS possesses rapid and efficient path-remodeling capabilities. In particular, within a simplified maze network, the O-PS was confirmed to have the same shortest-path searching ability as the PS, while being capable of faster remodeling. This study offers a new approach for optimizing and dynamically remodeling social infrastructure networks by mimicking biological mechanisms, enabling the rapid identification of solutions considering multiple objectives under complex constraints. Furthermore, the variation in convergence speed with oscillation frequency in the O-PS suggests flexibility in responding to environmental changes. Further research is required to develop more effective remodeling strategies.

Exploring the Effects and Potential Mechanisms of Hesperidin for the Treatment of CPT-11-Induced Diarrhea: Network Pharmacology, Molecular Docking, and Experimental Validation.

Chemotherapy-induced diarrhea (CID) is a potentially serious side effect that often occurs during anticancer therapy and is caused by the toxic effects of chemotherapeutic drugs on the gastrointestinal tract, resulting in increased frequency of bowel movements and fluid contents. Among these agents, irinotecan (CPT-11) is most commonly associated with CID. Hesperidin (HPD), a flavonoid glycoside found predominantly in citrus fruits, has anti-oxidation properties and anti-inflammation properties that may benefit CID management. Nevertheless, its potential mechanism is still uncertain. In this study, we firstly evaluated the pharmacodynamics of HPD for the treatment of CID in a mouse model, then used network pharmacology and molecular docking methods to excavate the mechanism of HPD in relieving CID, and finally further proved the predicted mechanism through molecular biology experiments. The results demonstrate that HPD significantly alleviated diarrhea, weight loss, colonic pathological damage, oxidative stress, and inflammation in CID mice. In addition, 74 potential targets for HPD intervention in CID were verified by network pharmacology, with the top 10 key targets being AKT1, CASP3, ALB, EGFR, HSP90AA1, MMP9, ESR1, ANXA5, PPARG, and IGF1. The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that the PI3K-Akt pathway, FoxO pathway, MAPK pathway, TNF pathway, and Ras pathway were most relevant to the HPD potential treatment of CID genes. The molecular docking results showed that HPD had good binding to seven apoptosis-related targets, including AKT1, ANXA5, CASP3, HSP90AA1, IGF1, MMP9, and PPARG. Moreover, we verified apoptosis by TdT-mediated dUTP nick-end labeling (TUNEL) staining and immunohistochemistry, and the hypothesis about the proteins above was further verified by Western blotting in vivo experiments. Overall, this study elucidates the potential and underlying mechanisms of HPD in alleviating CID.

Rotation and Self-Assembly Driving NLRP3 Activation.

As a critical sensor protein, NLRP3 detects cellular perturbation caused by diverse exogenous and endogenous stimuli. NLRP3 activation requires domain rotation within the NEK7-bound NLRP3 monomer and assembly. However, a detailed molecular mechanism for NLRP3 assembly and activation remains elusive, particularly in terms of dynamics and energetics. In this work, all-atom molecular dynamics (MD) simulations are executed to describe large-amplitude closed-to-open conformational transitions along the rotational pathway. From the MD trajectories, the computed potential of mean force (PMF) shows that NLRP3 activation through monomeric domain rotation is an uphill process, during which the active conformation of the NLRP3-NEK7 monomer cannot be stabilized. Further binding free-energy calculations for two neighboring NLRP3-NEK7 subunits in a disc assembly with the C10 symmetry reveal that the protein self-assembly starts approximately at the 86.5° position on the rotary pathway, along which the NLRP3 activation becomes a downhill process to the active state at 90.5°. The active NLRP3-NEK7 monomeric conformation in the disc assembly is stabilized because of the interactions between the neighboring subunits, involving mainly FISNA loop 1 in one subunit and a "crocodile-clip" structure formed by the NBD helix-loop-strand motif (residues 351-373) and the WHD β-hairpin loop (residues 501-521) in the other. Our simulations also demonstrate that NEK7 plays an important role in the NLRP3 cage dissociation in the centrosome, which is consistent with biological experiments. The computational results provide kinetic, energetic, and structural insights into the molecular mechanisms of the activation of NLRP3 and the NEK7-driven dissociation of inactive NLRP3 cages. The activation mechanism of NLRP3 proposed in this work is significantly different from those of previous structural studies.

MvGraphDTA: multi-view-based graph deep model for drug-target affinity prediction by introducing the graphs and line graphs

BackgroundAccurately identifying drug-target affinity (DTA) plays a pivotal role in drug screening, design, and repurposing in pharmaceutical industry. It not only reduces the time, labor, and economic costs associated with biological experiments but also expedites drug development process. However, achieving the desired level of computational accuracy for DTA identification methods remains a significant challenge.ResultsWe proposed a novel multi-view-based graph deep model known as MvGraphDTA for DTA prediction. MvGraphDTA employed a graph convolutional network (GCN) to extract the structural features from original graphs of drugs and targets, respectively. It went a step further by constructing line graphs with edges as vertices based on original graphs of drugs and targets. GCN was also used to extract the relationship features within their line graphs. To enhance the complementarity between the extracted features from original graphs and line graphs, MvGraphDTA fused the extracted multi-view features of drugs and targets, respectively. Finally, these fused features were concatenated and passed through a fully connected (FC) network to predict DTA.ConclusionsDuring the experiments, we performed data augmentation on all the training sets used. Experimental results showed that MvGraphDTA outperformed the competitive state-of-the-art methods on benchmark datasets for DTA prediction. Additionally, we evaluated the universality and generalization performance of MvGraphDTA on additional datasets. Experimental outcomes revealed that MvGraphDTA exhibited good universality and generalization capability, making it a reliable tool for drug-target interaction prediction.

Preparation, structure, osteogenic differentiation ability, and biosafety of bioglass for root canal disinfection

In this paper, SiO2-P2O5-Ca(Sr/Zn)O-Na2O-F system glasses with varying CaO:SrO and CaO:ZnO ratios were prepared by traditional melting method, which combined the remineralization properties of bioglass with the special functions of Zn2+ and Sr2+. The evolution of glass composition and its thermal properties, network structure, and biological properties was investigated by DSC, FTIR, and biological experiment. The results showed that all the extracts of glass powder could promote the osteogenic differentiation of human periodontal ligament cells (HPDLCs). Among them, the two kinds of glass containing 6 wt% SrO and only 2 wt% ZnO had the greatest potential to accelerate the bone tissue reconstruction. Hematoxylin-eosin (HE) staining histological results showed that 3 months after the two kinds of glass were implanted in the animal model of periapical inflammation, the bone matrix formed a good seal in the apical foramen, and new bone and capillaries were formed in the apical area, which has a clinical application and transformation prospect.

Identification of Pyroptosis-Related Molecular Subtypes and Diagnostic Model development in Major Depressive Disorder.

Major depressive disorder (MDD) is a prevalent psychological disorder associated with inflammation, with complex pathological mechanisms. Pyroptosis has been suggested to contribute to inflammation in central nervous system diseases. Little research, however, has examined what role pyroptosis played in MDD. In the present study, the differential expression pyroptosis-related genes (DE-PRGs) in MDD were identified from the GEO database (GSE98793 and GSE19738). Then, consensus clustering analysis was used to evaluate differences in MDD molecular subtypes characteristics based on PRGs. The characteristic diagnostic biomarkers for MDD were identified by Weighted Correlation Network Analysis (WGCNA) and multiple machine learning algorithms. Three intersection genes (GZMA, AKR1C3, and CD52) were obtained, which are expected to become potential biomarkers for MDD with excellent reliability and accuracy. Subsequently, the immune infiltration characteristics result indicated that the development of MDD is mediated by immune-related function, where three DE-PRGs were strongly related to the immune infiltration landscape of MDD. The biological experiments in vitro further proved that three unique PRGs are emerging as important players in MDD diagnosis. Our research aimed to provide novel ideas and biomarkers targeting MDD.

The promise and peril of comparing fluorescence lifetime in biology revealed by simulations.

Signaling dynamics are crucial in biological systems, and biosensor-based real-time imaging has revolutionized their analysis. Fluorescence lifetime imaging microscopy (FLIM) excels over the widely used fluorescence intensity imaging by allowing the measurement of absolute signal levels, independent of sensor concentration. This capability enables the comparison of signaling dynamics across different animals, body regions, and timeframes. However, FLIM's advantage can be compromised by factors like autofluorescence in biological experiments. To address this, we introduce FLiSimBA, a flexible computational framework for realistic F luorescence Li fetime Sim ulation for B iological A pplications. Through simulations, we analyze the signal-to-noise ratios of fluorescence lifetime data, determining measurement uncertainty and providing necessary error bars for lifetime measurements. Furthermore, we challenge the belief that fluorescence lifetime is unaffected by sensor expression and establish quantitative limits to this insensitivity in biological applications. Additionally, we propose innovations, notably multiplexed dynamic imaging that combines fluorescence intensity and lifetime measurements. This innovation can transform the number of signals that can be simultaneously monitored, thereby enabling a systems approach in studying signaling dynamics. Thus, by incorporating diverse factors into our simulation framework, we uncover surprises, identify limitations, and propose advancements for fluorescence lifetime imaging in biology. This quantitative framework supports rigorous experimental design, facilitates accurate data interpretation, and paves the way for technological advancements in fluorescence lifetime imaging.

Dopaminergic REST/NRSF is protective against manganese-induced neurotoxicity in mice

Chronic exposure to elevated levels of manganese (Mn) may cause a neurological disorder referred to as manganism. The transcription factor REST is dysregulated in several neurodegenerative diseases, such as Alzheimer’s disease and Parkinson’s disease. REST upregulated tyrosine hydroxylase and induced protection against Mn toxicity in neuronal cultures. In the present study, we investigated if dopaminergic REST plays a critical role in protecting against Mn-induced toxicity in vivo using dopaminergic REST conditional knockout (REST-cKO) mice and REST loxP mice as wild-type (WT) controls. Restoration of REST in the substantia nigra (SN) with neuronal REST AAV vector infusion was performed to further support the role of REST in Mn toxicity. Mice were exposed to Mn (330 ug, intranasal, daily for 3 weeks), followed by behavioral tests and molecular biology experiments. Results showed that Mn decreased REST mRNA/protein levels in the SN-containing midbrain, as well as locomotor activity and motor coordination in WT mice, which were further decreased in REST-cKO. Mn-induced mitochondrial insults, such as impairment of fission/fusion and mitophagy, apoptosis, and oxidative stress, in the midbrain of WT mice were more pronounced in REST-cKO. However, REST restoration in the SN of REST cKO mice attenuated Mn-induced neurotoxicity. REST’s molecular target for its protection is unclear, but REST attenuated Mn-induced mitochondrial dysregulation, indicating that it is a primary intracellular target for both Mn and REST. These novel findings suggest that dopaminergic REST in the nigrostriatal pathway is critical in protecting against Mn toxicity, underscoring REST as a potential therapeutic target for treating manganism.

Ti3C2Tx@PLGA/Icaritin microspheres-modified PLGA/β-TCP scaffolds modulate Icaritin release to enhance bone regeneration through near-infrared response

Porous poly (lactic-co-glycolic acid)/β-tricalcium phosphate/Icaritin (PLGA/β-TCP/ICT, PTI) scaffold is a tissue engineering scaffold based on PLGA/β-TCP (PT) containing Icaritin, the main active ingredient of the Chinese medicine Epimedium. Due to its excellent mechanical properties and osteogenic effect, PTI scaffold has the potential to promote bone defect repair. However, the release of ICT from the scaffolds is difficult to control. In this study, we constructed Ti3C2Tx@PLGA/ICT microspheres (TIM) and evaluated their characterization as well as ICT release under near-infrared (NIR) irradiation. We utilized TIM to modify the PT scaffold and performed biological experiments. First, we cultured rat bone marrow mesenchymal stem cells on the scaffold to assess biocompatibility and osteogenic potential under on-demand NIR irradiation. Subsequently, to evaluate the osteogenic properties of TIM-modified scaffoldin vivo, the scaffold was implanted into a femoral condyle defect model. TIM have excellent drug-loading capacity and encapsulation efficiency for ICT, and the incorporation of Ti3C2Txendows TIM with photothermal conversion capability. Under 0.90 W cm-2NIR irradiation, the temperature of TIM maintained at 42.0 ± 0.5 °C and the release of ICT was accelerated. Furthermore, while retaining its original properties, the TIM-modified scaffold was biocompatible and could promote cell proliferation, osteogenic differentiation, and biomineralizationin vitro, as well as the osteogenesis and osseointegrationin vivo, and its effect was further enhanced through the modulation of ICT release under NIR irradiation. In summary, TIM-modified scaffold has the potential to be applied in bone defects repairing.

POP1 Facilitates Proliferation in Triple-Negative Breast Cancer via m6A-Dependent Degradation of CDKN1A mRNA.

Triple-negative breast cancer (TNBC) is currently the worst prognostic subtype of breast cancer, and there is no effective treatment other than chemotherapy. Processing of precursors 1 (POP1) is the most substantially up-regulated RNA-binding protein (RBP) in TNBC. However, the role of POP1 in TNBC remains clarified. A series of molecular biological experiments invitro and invivo and clinical correlation analyses were conducted to clarify the biological function and regulatory mechanism of POP1 in TNBC. Here, we identified that POP1 is significantly up-regulated in TNBC and associated with poor prognosis. We further demonstrate that POP1 promotes the cell cycle and proliferation of TNBC invitro and vivo. Mechanistically, POP1 directly binds to the coding sequence (CDS) region of CDKN1A mRNA and degrades it. The degradation process depends on the N6-methyladenosine (m6A) modification at the 497th site of CDKN1A and the recognition of this modification by YTH N6-methyladenosine RNA binding protein 2 (YTHDF2). Moreover, the m6A inhibitor STM2457 potently impaired the proliferation of POP1-overexpressed TNBC cells and improved the sensitivity to paclitaxel. In summary, our findings reveal the pivotal role of POP1 in promoting TNBC proliferation by degrading the mRNA of CDKN1A and that inhibition of m6A with STM2457 is a promising therapeutic strategy for TNBC.

Radix Rehmanniae Praeparata extracts ameliorate hepatic ischemia-reperfusion injury by restoring lipid metabolism in hepatocytes

Ethnopharmacological relevanceHepatic ischemia/reperfusion injury (HIRI) is a common occurrence during or after liver surgery, representing a major cause for postoperative complications or increased morbidity and mortality in liver diseases. Rehmanniae Radix Praeparata (RRP) is a traditional Chinese medicine frequently used and has garnered extensive attention for its therapeutic potential treating cardiovascular and hepatic ailments. Recent studies have indicated the possibility of RRP in regulating lipid accumulation and apoptosis in hepatocytes. Aim of the studyThis study aimed to investigate the specific mechanisms by which RRP may impede the progression of HIRI through the regulation of lipid metabolism. Materials and methodsHigh-performance liquid chromatography (HPLC) was used to identify the major components of RRP water extract. C57BL/6J mice were orally given RRP at doses of 2.5 g/kg, 5 g/kg, and 10 g/kg for a duration of 7 days before undergoing HIRI surgery. Furthermore, we established a lipid-loaded in vitro model by exposing hepatocytes to oleic acid and palmitic acid (OAPA). The anti-HIRI effect of RRP was determined through transcriptomics and various molecular biology experiments. ResultsAfter identifying active ingredients in RRP, we observed that RRP exerted lipid-lowering and hepatoprotective effects on HIRI mice and OAPA-treated hepatocytes. RRP activated AMP-activated protein kinase (AMPK) and inhibited mammalian target of rapamycin (mTOR), which further on the one hand, inhibited the cleavage and activation of sterol regulatory element binding protein 2 (SREBP2) by limiting the movement of SREBPs cleavage-activating protein (SCAP)-SREBP2 complex with the help of endoplasmic reticulum lipid raft-associated protein 1 (ERLIN1) and insulin-induced gene 1 (INSIG1), and on the other hand, promoted liver X receptor α (LXRα) nuclear transportation and subsequent cholesterol efflux. Meanwhile, the anti-lipotoxic effect of RRP can be partly reversed by an LXRα inhibitor but largely blocked by the application of compound C, an AMPK inhibitor. ConclusionOur study elucidated that RRP served as a potential AMPK activator to alleviate HIRI by blocking SREBP2 activation and cholesterol synthesis, while also activating LXRα to facilitate cholesterol efflux. These findings shed new light on the potential therapeutic use of RRP for improving HIRI.

Identification of Clinical Value and Biological Effects of XIRP2 Mutation in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a prevalent malignant digestive tumor. Numerous genetic mutations have been documented in HCC, yet the clinical significance of these mutations remains largely unexplored. The objective of this study is to ascertain the clinical value and biological effects of xin actin binding repeat containing 2 (XIRP2) mutation in HCC. The gene mutation landscape of HCC was examined using data from the Cancer Genome Atlas and the International Cancer Genome Consortium databases. The prognostic significance of the XIRP2 mutation was assessed through KM plot analysis. The association between drug sensitivity and the XIRP2 mutation was investigated using the TIDE algorithm and CCK-8 experiments. The biological effects of the XIRP2 mutation were evaluated through qRT-PCR, protein stability experiments, and relevant biological experiments. The XIRP2 mutation is one of the high-frequency mutations in HCC, and is associated with poor prognosis. A total of 72 differentially expressed genes (DEGs) were observed in HCC tissues with the XIRP2 mutation as compared to those with the XIRP2 wildtype, and these DEGs were closely related to ion metabolic processes. The XIRP2 mutation was linked to alterations in the sensitivity of fludarabine, oxaliplatin, WEHI-539, and LCL-161. CCK-8 assays demonstrated that HCC cells carrying the XIRP2 mutation exhibited increased resistance to fludarabine and oxaliplatin, but enhanced sensitivity to WEHI-539 and LCL-161 as compared with those HCC cells with the XIRP2 wildtype. The XIRP2 mutation was found to have no impact on the mRNA levels of XIRP2 in tissues and cells, but it did enhance the stability of the XIRP2 protein. Mechanically, the inhibition of XIRP2 resulted in a significant increase in sensitivity to oxaliplatin through an elevation in zinc ions and a calcium ion overload. In conclusion, the XIRP2 mutation holds potential as a biomarker for predicting the prognosis and drug sensitivity of HCC and serves as a therapeutic target to enhance the efficacy of oxaliplatin.