The role of nociceptive neurons in allergic rhinitis.

Allergic rhinitis (AR) is a chronic, non-infectious condition affecting the nasal mucosa, primarily mediated mainly by IgE. Recent studies reveal that AR is intricately associated not only with type 2 immunity but also with neuroimmunity. Nociceptive neurons, a subset of primary sensory neurons, are pivotal in detecting external nociceptive stimuli and modulating immune responses. This review examines nociceptive neuron receptors and elucidates how neuropeptides released by these neurons impact the immune system. Additionally, we summarize the role of immune cells and inflammatory mediators on nociceptive neurons. A comprehensive understanding of the dynamic interplay between nociceptive neurons and the immune system augments our understanding of the neuroimmune mechanisms underlying AR, thereby opening novel avenues for AR treatment modalities.

Integrating plasma exosomal miRNAs, ultrasound radiomics and tPSA for the diagnosis and prediction of early prostate cancer: a multi-center study.

INTRODUCTION: This multi-center study aims to explore the roles of plasma exosomal microRNAs (miRNAs), ultrasound (US) radiomics, and total prostate-specific antigen (tPSA) levels in early prostate cancer detection. METHODS: We analyzed the publicly available dataset GSE112264 to identify the differentially expressed miRNAs associated with prostate cancer. Then, PyRadiomics was used to extract image features, and least absolute shrinkage and selection operator (LASSO) was used to screen the data. Subsequently, according to strict inclusion and exclusion criteria, the internal dataset (n = 199) was used to construct a diagnostic model, and the receiver operating characteristic (ROC) curve, calibration curve, decision curve analysis (DCA), and DeLong test were used to evaluate its diagnostic performance. Finally, we used an external dataset (n = 158) for further validation. RESULTS: The number of features extracted by PyRadiomics was 851, and the number of features screened by LASSO was 23. We combined the hsa-miR-320c, hsa-miR-944, radiomics, and tPSA features to construct a joint model. The area under the ROC curve of the combined model was 0.935. In the internal validation, the area under the curve (AUC) of the training set was 0.943, and the AUC of the test set was 0.946. The AUC of the external data set was 0.910. The calibration curve and decision curve were consistent with the performance of the combined model. There was a significant difference in the prediction ability between the combined prediction model and the single index prediction model, indicating the high credibility and accuracy of the combined model in predicting PCa. CONCLUSIONS: The combined prediction model, consisting of plasma exosomal miRNAs (hsa-miR-320c and hsa-miR-944), US radiomics, and clinical tPSA, can be utilized for the early diagnosis of prostate cancer.

PhosBERT: A self-supervised learning model for identifying phosphorylation sites in SARS-CoV-2-infected human cells.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a single-stranded RNA virus, which mainly causes respiratory and enteric diseases and is responsible for the outbreak of coronavirus disease 19 (COVID-19). Numerous studies have demonstrated that SARS-CoV-2 infection will lead to a significant dysregulation of protein post-translational modification profile in human cells. The accurate recognition of phosphorylation sites in host cells will contribute to a deep understanding of the pathogenic mechanisms of SARS-CoV-2 and also help to screen drugs and compounds with antiviral potential. Therefore, there is a need to develop cost-effective and high-precision computational strategies for specifically identifying SARS-CoV-2-infected phosphorylation sites. In this work, we first implemented a custom neural network model (named PhosBERT) on the basis of a pre-trained protein language model of ProtBert, which was a self-supervised learning approach developed on the Bidirectional Encoder Representation from Transformers (BERT) architecture. PhosBERT was then trained and validated on serine (S) and threonine (T) phosphorylation dataset and tyrosine (Y) phosphorylation dataset with 5-fold cross-validation, respectively. Independent validation results showed that PhosBERT could identify S/T phosphorylation sites with high accuracy and AUC (area under the receiver operating characteristic) value of 81.9% and 0.896. The prediction accuracy and AUC value of Y phosphorylation sites reached up to 87.1% and 0.902. It indicated that the proposed model was of good prediction ability and stability and would provide a new approach for studying SARS-CoV-2 phosphorylation sites.

Two-dimensional single-crystalline mesoporous high-entropy oxide nanoplates for efficient electrochemical biomass upgrading.

Mesoporous single crystals have received more attention than ever in catalysis-related applications due to their unique structural functions. Despite great efforts, their progress in engineering crystallinity and composition has been remarkably slower than expected. In this manuscript, a template-free strategy is developed to prepare two-dimensional high-entropy oxide (HEO) nanoplates with single-crystallinity and penetrated mesoporosity, which further ensures precise control over high-entropy compositions and crystalline phases. Single-crystalline mesoporous HEOs (SC-MHEOs) disclose high electrocatalytic performance in 5-hydroxymethylfurfural oxidation reaction (HMFOR) for efficient biomass upgrading, with remarkable HMF conversion of 99.3% and superior 2,5-furandicarboxylic acid (FDCA) selectivity of 97.7%. Moreover, with nitrate reduction as coupling cathode reaction, SC-MHEO realizes concurrent electrosynthesis of value-added FDCA and ammonia in the two-electrode cell. Our study provides a powerful paradigm for producing a library of novel mesoporous single crystals for important catalysis-related applications, especially in the two-electrode cell.

A Sustainable Approach for Degradation of Alternariol by Peroxidase Extracted from Soybean Hulls: Performance, Pathway, and Toxicity Evaluation.

Alternariol (AOH), an emerging mycotoxin, inevitably exists widely in various food and feed commodities with cereals and fruits being particularly susceptible, raising global concerns over its harm to human and livestock health. The development of eco-friendly and efficient strategies to decontaminate AOH has been an urgent task. This study provided insight into the utilization of crude soybean hull peroxidase as a powerful biocatalyst for degrading AOH. The results confirmed that crude soybean hull peroxidase (SHP) could catalyze the oxidation of AOH by use of H2O2 as a co-substrate. The optimum reaction conditions for SHP-catalyzed AOH degradation were recorded at pH 4.0-8.0, at 42-57 °C, and at H2O2 concentration of 100-500 µM. Mass analysis elucidated the degradation of AOH through hydroxylation and methylation by crude SHP. Moreover, toxicological analysis indicated that crude SHP-catalyzed AOH degradation detoxified the hepatotoxicity of this mycotoxin. The performance of crude SHP to degrade AOH in food matrices was further evaluated, and it was found that the enzyme agent could achieve AOH degradation by 77% in wheat flour, 84% in corn flour, 34% in grape juice, and 26% in apple juice. Collectively, these findings establish crude SHP as a promising candidate for effective AOH degradation, with potential applications in the food and feed industry.

2D PtRhPb Mesoporous Nanosheets with Surface-Clean Active Sites for Complete Ethanol Oxidation Electrocatalysis.

The development of active and selective metal electrocatalysts for complete ethanol oxidation reaction (EOR) into desired C1 products is extremely promising for practical application of direct ethanol fuel cells. Despite some encouraging achievements, their activity and selectivity remain unsatisfactory. In this work, it is reported that 2D PtRhPb mesoporous nanosheets (MNSs) with anisotropic structure and surface-clean metal site perform perfectly for complete EOR electrocatalysis in both three-electrode and two-electrode systems. Different to the traditional routes, a selective etching strategy is developed to produce surface-clean mesopores while retaining parent anisotropy quasi-single-crystalline structure without the mesopore-forming surfactants. This method also allows the general synthesis of surface-clean mesoporous metals with other compositions and structures. When being performed for alkaline EOR electrocatalysis, the best PtRhPb MNSs deliver remarkably high activity (7.8 A mg-1) and superior C1 product selectivity (70% of Faradaic efficiency), both of which are much better than reported electrocatalysts. High performance is assigned to multiple structural and compositional synergies that not only stabilized key OHads intermediate by surface-clean mesopores but also separated the chemisorption of two carbons in ethanol by adjacent Pt and Rh sites, which facilitate the oxidation cleavage of stable C─C bond for complete EOR electrocatalysis.

Management of non-alcoholic fatty liver disease: Lifestyle changes.

In this editorial, we commented on a recently released manuscript by Zeng et al in the World Journal of Gastroenterology. We focused specifically on lifestyle changes in patients with non-alcoholic fatty liver disease (NAFLD). NAFLD is a hepatic manifestation of the metabolic syndrome, which ultimately leads to advanced hepatic fibrosis, cirrhosis, and hepatocellular carcinoma and affects more than 25% of the population globally. Existing therapeutic strategies against NAFLD such as pharmacologic therapies focus on liver protection, anti-inflammation, and regulating disease-related metabolic disorder symptoms. Although several drugs are in late-stage development, potent drugs against the diseases are lacking. Additionally, existing surgical approaches such as bariatric surgery are not routinely used to treat NAFLD. Intervening in patients' unhealthy lifestyles, such as weight loss through dietary changes and exercises to ameliorate patient-associated metabolic disorders and metabolic syndrome, is the first-line treatment for patients with NAFLD. With sufficient intrinsic motivation and adherence, the management of unhealthy lifestyles can reduce the severity of the disease, improve the quality of life, and increase the survival expectancy of patients with NAFLD.

Effect of compressive and tensile forces on glucose concentration and cell viability within the intervertebral disc: A finite element study.

Understanding the role of mechanical force on tissue nutrient transport is essential, as sustained force may affect nutrient levels within the disc and initiate disc degeneration. This study aims to evaluate the time-dependent effects of different compressive force amplitudes as well as tensile force on glucose concentration and cell viability within the disc. Based on the mechano-electrochemical mixture theory, a multiphasic finite element model of the lumbar intervertebral disc was developed. The minimum glucose concentration and minimum cell density in both normal and degenerated discs were predicted for different compressive force amplitudes, tensile force, and corresponding creep time. Under high compressive force, the minimum glucose concentration exhibited an increasing and then decreasing trend with creep time in the normal disc, whereas that of the degenerated disc increased, then decreased, and finally increased again. At steady state, a higher compressive force was accompanied by a lower glucose concentration distribution. In the degenerated disc, the minimum cell density was negatively correlated with creep time, with a greater range of affected tissue under a higher compressive force. For tensile force, the minimum glucose concentration of the degenerated disc raised over time. This study highlighted the importance of creep time, force magnitude, and force type in affecting nutrient concentration and cell viability. Sustained weight-bearing activities could deteriorate the nutrient environment of the degenerated disc, while tensile force might have a nonnegligible role in effectively improving nutrient levels within the degenerated disc.

A numerical approach applied to three-dimensional wave scattering problems subjected to obliquely propagating incident waves.

Accurately modeling artificial boundary conditions and wave inputs is paramount for numerical simulations of wave scattering in semi-infinite domains within seismic engineering. Traditionally, analysts focused on one- or two-dimensional free-field problems to determine wave inputs, primarily for vertically incident plane waves or obliquely incident waves parallel to two axes. However, these methods were inadequate for handling arbitrary incident directions in three-dimensional scenarios. This paper proposes a method for modeling seismic wave incidents in arbitrary directions. The basic theory of viscoelastic boundaries is leveraged, and a plane containing an arbitrary incident direction and the vertical coordinate axis is selected to establish a two-dimensional plane coordinate system. The two-dimensional free-field problem in this coordinate system is derived using the transfer matrix method. Subsequently, displacement, velocity, and stress are converted into the coordinate system where the three-dimensional calculation model is located, providing input for the three-dimensional scattering problem. Furthermore, the implementation of transmitting boundary conditions and viscoelastic boundary wave inputs is presented to enable incident wave scattering problems at any angle of the plane. The effect of oblique-incidence soil-structure dynamic interaction is also discussed, focusing on the parallel technology method adopted in this paper. With the relatively mature technology route and method, together with nuclear power systems and large-span deep-water bridge models, through examples of comparative analysis, qualitative and quantitative analyses are made on the impact on the soil mass, foundation, and structure when the seismic wave is an oblique incident.

Whole exome sequencing and proteomics-based investigation of the pathogenesis of coronary artery disease with diffuse long lesion.

OBJECTIVES: The long-term prognosis of patients with coronary artery disease (CAD) with diffuse long lesion underwent coronary artery bypass graft (CABG) or percutaneous coronary intervention (PCI) remains worse. Here, we aimed to identify distinctive genes involved and offer novel insights into the pathogenesis of diffuse long lesion. MATERIALS AND METHODS: Whole exome sequencing was performed on peripheral blood samples from 20 CAD patients with diffuse long lesion (CAD-DLL) and from 10 controls with focal lesion (CAD-FL) through a uniform pipeline. Proteomics analysis was conducted on the serum samples from 10 CAD-DLL patients and from 10 controls with CAD-FL by mass spectrometry. Bioinformatics analysis was performed to elucidate the involved genes, including functional annotation and protein-protein interaction analysis. RESULTS: A total of 742 shared variant genes were found in CAD-DLL patients but not in controls. Of these, 46 genes were identified as high-frequency variant genes (≥ 4/20) distinctive genes. According to the consensus variant site, 148 shared variant sites were found in the CAD-DLL group. The lysosome and cellular senescence-related pathway may be the most significant pathway in diffuse long lesion. Following the DNA-protein combined analysis, eight genes were screened whose expression levels were altered at both DNA and protein levels. Among these genes, the MAN2A2 gene, the only one that was highly expressed at the protein level, was associated with metabolic and immune-inflammatory dysregulation. CONCLUSIONS: Compared to individuals with CAD-FL, patients with CAD-DLL show additional variants. These findings contribute to the understanding of the mechanism of CAD-DLL and provide potential targets for the diagnosis and treatment of CAD-DLL.

Enzymatic Mesoporous Metal Nanocavities for Concurrent Electrocatalysis of Nitrate to Ammonia Coupled with Polyethylene Terephthalate Upcycling.

Electrochemical upcycling of waste pollutants into high value-added fuels and/or chemicals is recognized as a green and sustainable solution that can address the resource utilization on earth. Despite great efforts, their progress has seriously been hindered by the lack of high-performance electrocatalysts. In this work, bimetallic PdCu mesoporous nanocavities (MCs) are reported as a new bifunctional enzymatic electrocatalyst that realizes concurrent electrocatalytic upcycling of nitrate wastewater and polyethylene terephthalate (PET) plastic waste. Abundant metal mesopores and open nanocavities of PdCu MCs provide the enzymatic confinement of key intermediates for the deeper electroreduction of nitrate and accelerate the transport of reactants/products within/out of electrocatalyst, thus affording high ammonia Faradic efficiency (FENH3) of 96.6% and yield rate of 5.6 mg h-1 mg-1 at the cathode. Meanwhile, PdCu MC nanozymes trigger the selective electrooxidation of PET-derived ethylene glycol (EG) into glycolic acid (GA) and formic acid with high FEs of >90% by a facile regulation of potentials at the anode. Moreover, concurrent electrosynthesis of value-added NH3 and GA is disclosed in the two-electrode coupling system, further confirming the high efficiency of bifunctional PdCu MC nanozymes in producing value-added fuels and chemicals from waste pollutants in a sustainable manner.

Water-Oil Interfacial Synthesis of Two-Dimensional Colloidal Lead-Iodide Perovskites with Enhanced Efficiency and Stability.

Two-dimensional Ruddlesden-Popper perovskites L2PbI4 (L = alkylammonium cation) (RPPs) have attracted significant attention due to their unique excitonic characteristics. However, their ultrafast reaction dynamics exacerbates the structural distortion of the inorganic framework, leading to severe deterioration in photoluminescence. Here, we propose a water-oil interfacial synthesis approach to achieve controlled growth of the RPPs nanosheets. By segregating Pb and I precursors in two immiscible solvents, the nucleation and growth of RPPs are prolonged to the minute level. L2PbI4 nanosheets terminated with various alkylammonium are synthesized, and the factors influencing the growth kinetics of RPPs nanosheets are investigated. The resulting (PEA)2PbI4 nanosheets exhibit a 3.6-time enhancement in quantum efficiency and 3.2-time improvement photostability compared to those synthesized using the classical recrystallization method. A white light-emitting diode based on (HDA)2PbI4 nanosheets is fabricated, achieving a color gamut of 119.7% of the NTSC display standards. This innovative approach offers a new method for the controlled growth of 2D RPPs with improved optical quality and stability.

Using part of the initial analgesic dose as the epidural test dose did not delay the onset of labor analgesia: a randomized controlled clinical trial.

BACKGROUND: Epidural test dose for labor analgesia is controversial and varies widely in clinical practice. It is currently unclear whether using a portion of the initial dose for analgesia as the test dose delays the onset time of analgesia, compared to the traditional test dose. METHODS: One hundred and twenty-six parturients who chose epidural analgesia during labor were randomly assigned to two groups. The first dose in group L was 3 ml 1.5% lidocaine, and in the RF group was 10 ml 0.1% ropivacaine combined with 2 µg/ml fentanyl. After 3 min of observation, both groups received 8 ml 0.1% ropivacaine combined with 2 µg/ml fentanyl. The onset time of analgesia, motor and sensory blockade level, numerical pain rating scale, patient satisfaction score, and side effects were recorded. RESULTS: The onset time of analgesia in group RF was similar to that in group L (group RF vs group L, 7.0 [5.0-9.0] minutes vs 8.0 [5.0-11.0] minutes, p = 0.197). The incidence of foot numbness (group RF vs group L, 34.9% vs 57.1%, p = 0.020) and foot warming (group RF vs group L, 15.9% vs 47.6%, p < 0.001) in group RF was significantly lower than that in group L. There was no difference between the two groups on other outcomes. CONCLUSIONS: Compared with 1.5% lidocaine 3 ml, 0.1% ropivacaine 10 ml combined with 2 µg/ml fentanyl as an epidural test dose did not delay the onset of labor analgesia, and the side effects were slightly reduced. CLINICAL TRIAL REGISTRATION: http://www.chictr.org.cn (ChiCTR2100043071).

Unified Convolutional Sparse Transformer for Disease Diagnosis, Monitoring, Drug Development, and Therapeutic Effect Prediction from EEG Raw Data.

Electroencephalogram (EEG) analysis plays an indispensable role across contemporary medical applications, which encompasses diagnosis, monitoring, drug discovery, and therapeutic assessment. This work puts forth an end-to-end deep learning framework that is uniquely tailored for versatile EEG analysis tasks by directly operating on raw waveform inputs. It aims to address the challenges of manual feature engineering and the neglect of spatial interrelationships in existing methodologies. Specifically, a spatial channel attention module is introduced to emphasize the critical inter-channel dependencies in EEG signals through channel statistics aggregation and multi-layer perceptron operations. Furthermore, a sparse transformer encoder is used to leverage selective sparse attention in order to efficiently process long EEG sequences while reducing computational complexity. Distilling convolutional layers further concatenates the temporal features and retains only the salient patterns. As it was rigorously evaluated on key EEG datasets, our model consistently accomplished a superior performance over the current approaches in detection and classification assignments. By accounting for both spatial and temporal relationships in an end-to-end paradigm, this work facilitates a versatile, automated EEG understanding across diseases, subjects, and objectives through a singular yet customizable architecture. Extensive empirical validation and further architectural refinement may promote broader clinical adoption prospects.

Biomimetic peroxidase MOF-Fe promotes bone defect repair by inhibiting TfR2 and activating the BMP2 pathway.

BACKGROUND: Large bone defects pose a clinical treatment challenge; inhibiting transferrin receptor 2 (TfR2), which is involved in iron metabolism, can promote osteogenesis. Iron-based metal-organic frameworks (MOF-Fe) particles not only inhibit TfR2 but also serve as biomimetic catalysts to remove hydrogen peroxide in reactive oxygen species (ROS); excess ROS can disrupt the normal functions of osteoblasts, thereby hindering bone regeneration. This study explored the potential effects of MOF-Fe in increasing osteogenic activity and clearing ROS. METHODS: In vitro experiments were performed to investigate the osteogenic effects of MOF-Fe particles and assess their impact on cellular ROS levels. To further validate the role of MOF-Fe in promoting bone defect repair, we injected MOF-Fe suspensions into the femoral defects of SD rats and implanted MOF-Fe-containing hydrogel scaffolds in rabbit cranial defect models and observed their effects on bone healing. RESULTS: In vitro, the presence of MOF-Fe significantly increased the expression levels of osteogenesis-related genes and proteins compared to those in the control group. Additionally, compared to those in the untreated control group, the cells treated with MOF-Fe exhibited a significantly increased ability to remove hydrogen peroxide from ROS and generate oxygen and water within the physiological pH range. In vivo experiments further confirmed the positive effect of MOF-Fe in promoting bone defect repair. CONCLUSION: This study supports the application of MOF-Fe as an agent for bone regeneration, particularly for mitigating ROS and activating the bone morphogenetic protein (BMP) pathway, demonstrating its potential value.

Isolation and Identification of Salinity-Tolerant Rhizobia and Nodulation Phenotype Analysis in Different Soybean Germplasms.

Increasing the soybean-planting area and increasing the soybean yield per unit area are two effective solutions to improve the overall soybean yield. Northeast China has a large saline soil area, and if soybeans could be grown there with the help of isolated saline-tolerant rhizobia, the soybean cultivation area in China could be effectively expanded. In this study, soybeans were planted in soils at different latitudes in China, and four strains of rhizobia were isolated and identified from the soybean nodules. According to the latitudes of the soil-sampling sites from high to low, the four isolated strains were identified as HLNEAU1, HLNEAU2, HLNEAU3, and HLNEAU4. In this study, the isolated strains were identified for their resistances, and their acid and saline tolerances and nitrogen fixation capacities were preliminarily identified. Ten representative soybean germplasm resources in Northeast China were inoculated with these four strains, and the compatibilities of these four rhizobium strains with the soybean germplasm resources were analyzed. All four isolates were able to establish different extents of compatibility with 10 soybean resources. Hefeng 50 had good compatibility with the four isolated strains, while Suinong 14 showed the best compatibility with HLNEAU2. The isolated rhizobacteria could successfully establish symbiosis with the soybeans, but host specificity was also present. This study was a preliminary exploration of the use of salinity-tolerant rhizobacteria to help the soybean nitrogen fixation in saline soils in order to increase the soybean acreage, and it provides a valuable theoretical basis for the application of saline-tolerant rhizobia.

Polydopamine-Based Resveratrol-Hyaluronidase Nanomedicine Inhibited Pancreatic Cancer Cell Invasive Phenotype in Hyaluronic Acid Enrichment Tumor Sphere Model.

The dense storm microenvironment formed by an excessively cross-linked extracellular matrix, such as hyaluronic acid and collagens, serves as a major barrier that prevents drugs from reaching the deeper tumor. Current traditional two-dimensional (2D) cultures are not capable of modeling this drug delivery barrier in vitro. Thus, tumor spheroids have become increasingly important in cancer research due to their three-dimensional structure. Currently, various methods have been developed to construct tumor spheroids. However, there are still challenges, such as lengthy construction time, complex composition of added growth factors, and high cultivation costs. To address this technical bottleneck, our study combined the GelMA hydrogel system to develop a rapid and high-yield method for tumor spheroids generation. Additionally, we proposed an evaluation scheme to assess the effects of drugs on tumor spheroids. Building on the hyaluronic acid-rich pathological tumor microenvironment, we constructed a resveratrol-loaded nano-drug delivery system with tumor stroma modulation capability and used a three-dimensional (3D) tumor sphere model to simulate in vivo tumor conditions. This process was utilized to completely evaluate the ability of the nano-drug delivery system to enhance the deep penetration of resveratrol in the tumor microenvironment, providing new insights into future oncology drug screening, efficacy assessment, and drug delivery methods.

Enhancing emotion regulation: investigating the efficacy of transcutaneous electrical acupoint stimulation at PC6 in reducing fear of heights.

This study investigated the impact of transcutaneous electrical acupoint stimulation (TEAS) at Neiguan acupoint (PC6) on the physiological and behavioral responses of participants exposed in virtual height. 40 participants were included in the study and were randomly assigned to either a control group or an intervention group. Participants had an immersive experience with a VR interactive platform that provided somatosensory interaction in height stimulation scenes. Psychological scores, behavioral and cognitive performance, and physiological responses were recorded and analyzed. The results indicated that the intervention group had significantly lower fear scores compared to the control group. Analysis of heart rate variability revealed that the intervention group exhibited improved heart rate variability, indicating enhanced cardiovascular function and emotion regulation. The behavioral and cognitive results demonstrated that the intervention group exhibited higher left eye openness, faster reaction times, and greater movement distance, suggesting enhanced attentional focus, cognitive processing, and reduced avoidance behaviors. These findings suggest that TEAS at PC6 can effectively reduce fear and improve the regulation of physiological and behavioral responses to negative emotional stimuli.

Kurarinone, a flavonoid from Radix Sophorae Flavescentis, inhibits RANKL-induced osteoclastogenesis in mouse bone marrow-derived monocyte/macrophages.

Inflammation-induced osteoclast proliferation is a crucial contributor to impaired bone metabolism. Kurarinone (KR), a flavonoid extracted from the Radix Sophorae Flavescentis, exhibits notable anti-inflammatory properties. Nevertheless, the precise influence of KR on osteoclast formation remains unclear. This study's objective was to assess the impact of KR on osteoclast activity in vitro and unravel its underlying mechanism. Initially, a target network for KR-osteoclastogenesis-osteoporosis was constructed using network pharmacology. Subsequently, the intersecting targets were identified through the Venny platform and a PPI network was created using Cytoscape 3.9.1. Key targets within the network were identified employing topological algorithms. GO enrichment and KEGG pathway analysis were then performed on these targets to explore their specific functions and pathways. Additionally, molecular docking of potential core targets of KR was conducted, and the results were validated through cell experiments. A total of 83 target genes overlapped between KR and osteoclastogenesis-osteoporosis targets. Enrichment analysis revealed their role in inflammatory response, protein tyrosine kinase activity, osteoclast differentiation, and MAPK and NF-κB signaling pathways. PPI analysis and molecular docking demonstrate that key targets MAPK14 and MAPK8 exhibit more stable binding with KR compared to other proteins. In vitro experiments demonstrate that KR effectively inhibits osteoclast differentiation and bone resorption without cellular toxicity. It suppresses key osteoclast genes (NFATc1, c-Fos, TRAP, MMP9, Ctsk, Atp6v2), hinders IκB-α degradation, and inhibits ERK and JNK phosphorylation, while not affecting p38 phosphorylation. The results indicate that KR may inhibit osteoclast maturation and bone resorption by blocking NF-κB and MAPK signaling pathways, suggesting its potential as a natural therapeutic agent for osteoporosis.

Prediction of blood-brain barrier penetrating peptides based on data augmentation with Augur.

BACKGROUND: The blood-brain barrier serves as a critical interface between the bloodstream and brain tissue, mainly composed of pericytes, neurons, endothelial cells, and tightly connected basal membranes. It plays a pivotal role in safeguarding brain from harmful substances, thus protecting the integrity of the nervous system and preserving overall brain homeostasis. However, this remarkable selective transmission also poses a formidable challenge in the realm of central nervous system diseases treatment, hindering the delivery of large-molecule drugs into the brain. In response to this challenge, many researchers have devoted themselves to developing drug delivery systems capable of breaching the blood-brain barrier. Among these, blood-brain barrier penetrating peptides have emerged as promising candidates. These peptides had the advantages of high biosafety, ease of synthesis, and exceptional penetration efficiency, making them an effective drug delivery solution. While previous studies have developed a few prediction models for blood-brain barrier penetrating peptides, their performance has often been hampered by issue of limited positive data. RESULTS: In this study, we present Augur, a novel prediction model using borderline-SMOTE-based data augmentation and machine learning. we extract highly interpretable physicochemical properties of blood-brain barrier penetrating peptides while solving the issues of small sample size and imbalance of positive and negative samples. Experimental results demonstrate the superior prediction performance of Augur with an AUC value of 0.932 on the training set and 0.931 on the independent test set. CONCLUSIONS: This newly developed Augur model demonstrates superior performance in predicting blood-brain barrier penetrating peptides, offering valuable insights for drug development targeting neurological disorders. This breakthrough may enhance the efficiency of peptide-based drug discovery and pave the way for innovative treatment strategies for central nervous system diseases.