Based on the prognosis model of immunogenes, the prognosis model was constructed to predict the invasion of immune genes and immune cells related to primary liver cancer and its experimental validation.

Background: Primary liver cancer (PLC) is a prevalent malignancy of the digestive system characterized by insidious symptom onset and a generally poor prognosis. Recent studies have highlighted a significant correlation between the initiation and prognosis of liver cancer and the immune function of PLC patients. Purpose: Revealing the expression of PLC-related immune genes and the characteristics of immune cell infiltration provides assistance for the analysis of clinical pathological parameters and prognosis of PLC patients. Methods: PLC-related differentially expressed genes (DEGs) with a median absolute deviation (MAD > 0.5) were identified from TCGA and GEO databases. These DEGs were intersected with immune-related genes (IRGs) from the ImmPort database to obtain PLC-related IRGs. The method of constructing a prognostic model through immune-related gene pairs (IRGPs) is used to obtain IRGPs and conduct the selection of central immune genes. The central immune genes obtained from the selection of IRGPs are validated in PLC. Subsequently, the relative proportions of 22 types of immune cells in different immune risk groups are evaluated, and the differential characteristics of PLC-related immune cells are verified through animal experiments. Results: Through database screening and the construction of an IRGP prognosis model, 84 pairs of IRGPs (P < 0.001) were ultimately obtained. Analysis of these 84 IRGPs revealed 11 central immune genes related to PLC, showing differential expression in liver cancer tissues compared to normal liver tissues. Results from the CiberSort platform indicate differential expression of immune cells such as naive B cells, macrophages, and neutrophils in different immune risk groups. Animal experiments demonstrated altered immune cell proportions in H22 tumor-bearing mice, validating findings from peripheral blood and spleen homogenate analyses. Conclusion: Our study successfully predicted and validated PLC-related IRGs and immune cells, suggesting their potential as prognostic indicators and therapeutic targets for PLC.

Chitosan interaction with stomach mucin layer to enhances gastric retention and mucoadhesive properties.

The interaction between mucoadhesive materials and mucin layers is of significant interest in the development of drug delivery systems and biomedical applications for effective targeting and prolonged stay in the gastrointestinal tract. In this article, the current advancement and mucoadhesive properties of chitosan concerning the stomach mucin layer and its interactions have been briefly addressed. Chitosan a biocompatible polysaccharide exhibited promising mucoadhesive properties attributed to its cationic nature and ability to establish bonds with mucin glycoproteins. The mucoadhesion mechanism is ascribed to the electrostatic interactions between the positively charged amino (NH2) groups of chitosan and the sialic acid residues in mucin glycoprotein which carry a negative charge. The article provides a succinct overview of prior uses, current trends, and recent advancements in chitosan-based gastric-targeted delivery systems. We look forward to further innovations and emerging research related to chitosan-based methods of delivery that may increase the chitosan suitability for use in novel therapeutic approaches.

Development of machine learning models using multi-source data for geographical traceability and content prediction of Eucommia ulmoides leaves.

Rapid and scientific quality evaluation is a hot topic in the research of food and medicinal plants. With the increasing popularity of derivative products from Eucommia ulmoides leaves, quality and safety have attracted public attention. The present study utilized multi-source data and traditional machine learning to conduct geographical traceability and content prediction research on Eucommia ulmoides leaves. Explored the impact of different preprocessing methods and low-level data fusion strategy on the performance of classification and regression models. The classification analysis results indicated that the partial least squares discriminant analysis (PLS-DA) established by low-level fusion of two infrared spectroscopy techniques based on first derivative (FD) preprocessing was most suitable for geographical traceability of Eucommia ulmoides leaves, with an accuracy rate of up to 100 %. Through regression analysis, it was found that the preprocessing methods and data blocks applicable to the four chemical components were inconsistent. The optimal partial least squares regression (PLSR) model based on aucubin (AU), geniposidic acid (GPA), and chlorogenic acid (CA) had a residual predictive deviation (RPD) value higher than 2.0, achieving satisfactory predictive performance. However, the PLSR model based on quercetin (QU) had poor performance (RPD = 1.541) and needed further improvement. Overall, the present study proposed a strategy that can effectively evaluate the quality of Eucommia ulmoides leaves, while also providing new ideas for the quality evaluation of food and medicinal plants.

Collagen/gelatin and polysaccharide complexes enhance gastric retention and mucoadhesive properties.

This article has focused on collagen-gelatin, the gelation process, as well as blend interaction between collagen/gelatin with various polysaccharides to boost mucoadhesion and gastric retention. The interaction between mucoadhesive materials and mucin layers is of significant interest in the development of drug delivery systems and biomedical applications for effective targeting and prolonged time in the gastrointestinal tract. This paper reviews the current advancement and mucoadhesive properties of collagen/gelatin and different polysaccharide complexes concerning the mucin layer and interactions are briefly highlighted. Collagen/gelatin and polysaccharide blends biocompatible and biodegradable, the complex biomolecules have shown encouraging mucoadhesive properties due to their cationic nature and ability to form hydrogen bonds with mucin glycoproteins. The mucoadhesion mechanism was attributed to the electrostatic interactions between the positively charged amino (NH2) groups of blend biopolymers and the negatively charged sialic acid residues present in mucin glycoprotein. At the end of this article, the encouraging prospect of collagen/polysaccharide complex and mucin glycoprotein is highlighted.

Numerical simulation of the effect of hypergravity on the dendritic growth characteristics of aluminum alloys.

The cellular automata-lattice Boltzmann method is used to simulate the dendritic growth process of aluminum alloys under the action of hypergravity by performing coupling heat and mass transfer, solidification and flow. The dendrite arm spacing, growth rate, and dendrite morphology vary greatly with the size and direction of hypergravity, and solute segregation occurs. Compared with the gravity of the earth (1 g), hypergravity strongly strengthens the buoyancy-driven flow and considerably affects the morphology of the solidified grain. The dendritic growth rate is also accelerating. According to the direction of hypergravity in relation to the dendritic growth direction, there exist different flow states that show stable or unstable dendritic growth dynamics. For columnar crystal growth, when the hypergravity and growth direction are identical, the dendrite tip undergoes downward melt flow, and the dendrite grows in a stable manner. When the hypergravity and the growth direction are opposite, the dendrite tip undergoes upward melt flow, the dendrite grows in an unstable manner, and the primary dendrite spacing decreases. For the growth of equiaxed crystals, the convection induced by hypergravity causes the equiaxed crystals to be asymmetric, and the solute segregates in the direction of gravity. Channel segregation occurs in the mushy zone in the presence of equiaxed crystal chains.

CheV enhances the virulence of Salmonella Enteritidis, and the Chev-deleted Salmonella vaccine provides immunity in mice.

BACKGROUND: Salmonella enteritidis (SE) is a major zoonotic pathogen and causes infections in a variety of hosts. The development of novel vaccines for SE is necessary to eradicate this pathogen. Genetically engineered attenuated live vaccines are more immunogenic and safer. Thus, to develop a live attenuated Salmonella vaccine, we constructed a cheV gene deletion strain of SE (named ΔcheV) and investigated the role of cheV in the virulence of SE. First, the ability to resist environmental stress in vitro, biofilm formation capacity, drug resistance and motility of ΔcheV were analyzed. Secondly, the bacterial adhesion, invasion, intracellular survival assays were performed by cell model. Using a mouse infection model, an in vivo virulence assessment was conducted. To further evaluate the mechanisms implicated by the reduced virulence, qPCR analysis was utilized to examine the expression of the strain's major virulence genes. Finally, the immune protection rate of ΔcheV was evaluated using a mouse model. RESULTS: Compared to C50336, the ΔcheV had significantly reduced survival ability under acidic, alkaline and thermal stress conditions, but there was no significant difference in survival under oxidative stress conditions. There was also no significant change in biofilm formation ability, drug resistance and motility. It was found that the adhesion ability of ΔcheV to Caco-2 cells remained unchanged, but the invasion ability and survival rate in RAW264.7 cells were significantly reduced. The challenge assay results showed that the LD50 values of C50336 and ΔcheV were 6.3 × 105 CFU and 1.25 × 107 CFU, respectively. After the deletion of the cheV gene, the expression levels of fimD, flgG, csgA, csgD, hflK, lrp, sipA, sipB, pipB, invH, mgtC, sodC, rfbH, xthA and mrr1 genes were significantly reduced. The live attenuated ΔcheV provided 100% protection in mice against SE infection. CONCLUSION: All the results confirmed that the deletion of the cheV gene reduces the virulence of SE and provides significant immune protection in mice, indicating that ΔcheV could be potential candidates to be explored as live-attenuated vaccines.

Novel insights into the rhizosphere and seawater microbiome of Zostera marina in diverse mariculture zones.

BACKGROUND: Seagrasses offer various ecosystem services and possess high levels of primary productivity. However, the development of mariculture has affected the homeostasis of seagrass meadow ecosystems. Plant-microbiome associations are essential for seagrasses health, but little is known about the role of environmental microbiomes and how they affect seagrass in a mariculture environment. In this study, we investigated the influence of mariculture on the rhizosphere and seawater microbiome surrounding Zostera marina and focused on the bacterial, eukaryotic, and fungal components in the composition, diversity, metabolism, and responses to mariculture-related environmental factors. RESULTS: Significant differences in the composition, richness, diversity, and internal relations of the bacterial community between the seawater and rhizosphere sediment surrounding Z. marina were observed, while differences in the eukaryotic and fungal communities were less significant. More complex bacterial and fungal co-occurrence networks were found in the seawater and rhizosphere sediment of the Saccharina japonica (SJ) and sea cucumber (SC) culture zones. The seawater in the SJ zone had higher levels of dissimilatory and assimilatory nitrate reduction, denitrification, and nitrogen fixation processes than the other three zones. The assimilatory sulfate reduction enzymes were higher in the rhizosphere sediments of the SJ zone than in the other three zones. Tetracycline, sulfonamide, and diaminopyrimidine resistance genes were enriched in the mariculture SJ and SC zones. CONCLUSIONS: Our findings might contribute to a better understanding of the effects of mariculture on the seagrass and the meadow ecosystems and thus revealing their potential operating mechanisms. These insights may serve to raise awareness of the effects of human activities on natural ecosystems, regulation of antibiotic usage, and environmental restoration. Video Abstract.

Integration of metabolomics and network pharmacology technology to explain the effect mechanisms of Danggui Buxue decoction in vascular dementia.

Danggui Buxue decoction (DBD) is a traditional Chinese medicine herbal decoction that has a good therapeutic effect on vascular dementia (VaD). However, its pharmacodynamic substances and underlying mechanisms are ambiguous. The work aimed to decipher the pharmacodynamic substances and molecular mechanisms of DBD against VaD rats based on gas chromatography-mass spectrometry metabonomics, network pharmacology, molecular docking, and experimental verification. The results indicated that DBD significantly improved the learning abilities and cognitive impairment in the VaD rat model. Integration analysis of the metabolomics and network pharmacology approach revealed that DBD might primarily affect arachidonic acid (AA) and inositol phosphate metabolic pathways by regulating the platelet activation signaling pathways. Six core targets (TNF [tumor necrosis factor], IL-6 [interleukin 6], PTGS2 [prostaglandin-endoperoxide synthase 2], MAPK1, MAPK3, and TP53) in the platelet activation signaling pathways also had a good affinity to seven main active components (saponins, organic acids, flavonoids, and phthalides) of DBD through the verification of molecular docking. Enzyme-linked immunosorbent assay results (ELISA) showed that the levels of TNF, IL-6, PTGS2, thromboxane B2, and caspase-3 in the platelet activation signaling pathway can be regulated by DBD. Our results indicated that DBD treated VaD mainly by modulating the platelet activation signaling pathway, and AA and inositol phosphate metabolism.

Regulatory role of RGMb in lung injury promoted by the combination of carbon ion irradiation and anti-PD-1 antibody through Erk1/2 and p38 MAPK pathways.

The combination of carbon ion radiotherapy and anti-PD-1 antibody represents a new approach to treating thoracic tumors. However, the lung damage caused by this combination therapy may limit its use, and the potential mechanisms for this are worthy of investigation. The objective of this research was to examine the potential involvement of repulsive guidance molecule b (RGMb) in lung damage promoted by the utilization of carbon ion irradiation combined with an anti-PD-1 antibody. The C57BL/6 mice have been randomly separated into four distinct groups: control, anti-PD-1, whole thorax carbon ion irradiation, and irradiation in combination with anti-PD-1 treatment groups (combination group). Detection of pathological changes in lung tissue using HE staining. Detection of pulmonary fibrosis by Masson staining and the hydroxyproline assay. ELISA to detect TNF-α, TGF-ß, IL-6, and IL-1ß expression levels within lung homogenates. The expression of RGMb, p38 MAPK, and Erk1/2 pathways was detected using a fully automated digital Western blotting system WES (ProteinSimple, USA). Flow cytometry was employed to analyze tissue-resident memory T cells (TRM) within the lung. Subsequently, the siRNA gene was employed to induce the downregulation of RGMb in mice in order to validate the involvement of RGMb in radiation-immune lung injury. The present study observed a significant increase in both inflammatory and fibrotic indicators within the mice group's lung tissue that received the combination treatment. The combination group exhibited elevated levels of TGF-ß, TNF-α, IL-6, and IL-1ß in lung homogenates. Anti-PD-1 antibody and carbon ion irradiation, upregulated RGMb, phospho-p38 MAPK and phospho-Erk1/2. The results obtained from the flow cytometry analysis indicated that the combination group was significantly higher in the number of clonal expansion TRMs, which were predominantly characterized by the expression of CD8+CD103+CD69-TRMs. The downregulate of RGMb via siRNA in mice resulted in a decrease in phospho-p38 MAPK and phospho-Erk1/2. The combination group exhibited a reduction in TNF-α, TGF-ß, IL-6, and IL-1ß in their lung tissues, and the number of CD8+CD103+CD69-TRM was significantly reduced. The combination group exhibited a significant improvement in inflammatory and fibrotic indicators within the lung tissues. Anti-PD-1 antibody and carbon ion irradiation synergistically regulate RGMb, leading to strong clonal expansion of lung TRM through the p38 MAPK and Erk1/2 pathways. The present study offers valuable insights into the treatment of lung injury due to the combined administration of carbon ion radiotherapy and anti-PD-1 antibody therapy.

Machine learning applications for multi-source data of edible crops: A review of current trends and future prospects.

The quality and safety of edible crops are key links inseparable from human health and nutrition. In the era of rapid development of artificial intelligence, using it to mine multi-source information on edible crops provides new opportunities for industrial development and market supervision of edible crops. This review comprehensively summarized the applications of multi-source data combined with machine learning in the quality evaluation of edible crops. Multi-source data can provide more comprehensive and rich information from a single data source, as it can integrate different data information. Supervised and unsupervised machine learning is applied to data analysis to achieve different requirements for the quality evaluation of edible crops. Emphasized the advantages and disadvantages of techniques and analysis methods, the problems that need to be overcome, and promising development directions were proposed. To monitor the market in real-time, the quality evaluation methods of edible crops must be innovated.

Carbon Ions Suppress Angiogenesis and Lung Metastases in Melanoma by Targeting CXCL10.

Carbon-ion radiotherapy (CIRT) enhanced local control in patients with malignant melanoma. In several in vitro studies, carbon ions (C ions) have been also shown to decrease the metastatic potential of melanoma cells. CXC motif 10 (CXCL10) has been shown to play a crucial role in regulating tumor metastasis and it significantly increase in human embryonic kidney cells after heavy ion irradiations. This study sought to explore the regulatory effect of C ions on melanoma metastasis, emphasizing the role of CXCL10 in this process. To explore the potential regulatory effect of C ions on tumor metastasis in vivo, we developed a lung metastasis mouse model by injecting B16F10 cells into the footpad and subjected all mice to treatment with X rays and C ions. Subsequently, a series of assays, including histopathological analysis, enzyme-linked immunosorbent assay, real-time PCR, and western blotting, were conducted to assess the regulatory effects of C ions on melanoma. Our results showed that mice treated with C ions exhibited significantly less tumor vascularity, enhanced tumor necrosis, alleviated lung metastasis, and experienced longer survival than X-ray irradiated mice. Moreover, VEGF expression in B16F10 cells was significantly reduced by C-ion treatment, which could be alleviated by CXCL10 knockdown in vitro. Further investigations revealed that co-culturing with HUVECs resulted in a significant inhibition of proliferation, migration, and tube formation ability in the C-ion treated group, while the opposite effect was observed in the C-ion treated with si-CXCL10 group. In conclusion, our findings demonstrate that treatment with carbon-ion radiation can suppress angiogenesis and lung metastases in melanoma by specifically targeting CXCL10. These results suggest the potential utility of carbon ions in treating melanoma.

The toxicity of microplastics and their leachates to embryonic development of the sea cucumber Apostichopus japonicus.

Microplastic pollution has been widely detected across the global ocean, posing a major threat to a wide variety of marine biota. To date, the deleterious impacts of microplastics have predominantly been linked to their direct exposure, while the potential risks posed by the leachates emanating from microplastics have received comparatively less attention. Here, the toxicity of virgin plasticized polyvinyl chloride (PVC) microspheres and their leachates were evaluated on the embryo-larval development of sea cucumber Apostichopus japonicus using an in-vitro assay. Results showed that a significant toxic effect of both PVC microspheres and their leachates on the embryo development and larval growth of sea cucumbers follows a dose-dependent and time-dependent pattern. Nonetheless, the toxicity of PVC leachates surpasses that of the microspheres themselves. Abnormal developmental phenotypes, such as aberrant gastrulation, misaligned mesenchymal cells, and delayed arm development, were also observed in embryos and larvae treated with PVC. Further chemical analyses of PVC microspheres and leachates revealed the existence of five distinct phthalate esters (PAEs), with DIBP (diisobutyl phthalate) and DBP (dibutyl phthalate) exhibiting higher concentrations in the PVC leachates. This finding suggests that the elevated toxicity of plastic leachate may be attributed to the leaching of phthalate additives from the plastic particles.

Sulfide causes histological damage, oxidative stress, metabolic disorders and gut microbiota dysbiosis in juvenile sea cucumber Apostichopus japonicus Selenka.

Sulfide is a common harmful substance in sediments, with an especially high risk for deposit feeder organisms. The sea cucumber Apostichopus japonicus is a typical benthic feeder, and its intestine is the first line of defense and serves as a crucial barrier function. In this study, histological, physiological, gut microbiota, and metabolomic analyses were performed to explore the toxic response in the intestine of juvenile A. japonicus exposed to 0, 0.8, and 1.6 mg/L sulfide stress for 96 h. The results revealed sulfide-induced intestinal inflammatory symptoms and oxidative stress. Moreover, gut bacterial composition was observed after sulfide exposure, with an increase in Proteobacteria and a decrease in Cyanobacteria and Planctomycetes. Specifically, sulfide increased a set of sulfide-removing bacteria and opportunistic pathogens while decreasing several putative beneficial substance-producing bacteria. The metabolomic analysis indicated that sulfide also disturbed metabolic homeostasis, especially lipid and energy metabolism, in intestine. Interestingly, several intestinal bacteria were further identified to be significantly correlated with metabolic changes; for example, the decreased abundance levels of Bacillus, Corynebacterium, and Psychromonas were positively correlated with important energy metabolites, including maleic acid, farnesyl pyrophosphate, thiamine, butynoic acid, and deoxycholic acid. Thus, our research provides new insights into the mechanisms associated with the intestinal metabolic and microbiota response involved in sulfide stress adaptation strategies of juvenile A. japonicus.

Recent trends of machine learning applied to multi-source data of medicinal plants.

In traditional medicine and ethnomedicine, medicinal plants have long been recognized as the basis for materials in therapeutic applications worldwide. In particular, the remarkable curative effect of traditional Chinese medicine during corona virus disease 2019 (COVID-19) pandemic has attracted extensive attention globally. Medicinal plants have, therefore, become increasingly popular among the public. However, with increasing demand for and profit with medicinal plants, commercial fraudulent events such as adulteration or counterfeits sometimes occur, which poses a serious threat to the clinical outcomes and interests of consumers. With rapid advances in artificial intelligence, machine learning can be used to mine information on various medicinal plants to establish an ideal resource database. We herein present a review that mainly introduces common machine learning algorithms and discusses their application in multi-source data analysis of medicinal plants. The combination of machine learning algorithms and multi-source data analysis facilitates a comprehensive analysis and aids in the effective evaluation of the quality of medicinal plants. The findings of this review provide new possibilities for promoting the development and utilization of medicinal plants.

ResNet and MaxEnt modeling for quality assessment of Wolfiporia cocos based on FT-NIR fingerprints.

As a fungus with both medicinal and edible value, Wolfiporia cocos (F. A. Wolf) Ryvarden & Gilb. has drawn more public attention. Chemical components' content fluctuates in wild and cultivated W. cocos, whereas the accumulation ability of chemical components in different parts is different. In order to perform a quality assessment of W. cocos, we proposed a comprehensive method which was mainly realized by Fourier transform near-infrared (FT-NIR) spectroscopy and ultra-fast liquid chromatography (UFLC). A qualitative analysis means was built a residual convolutional neural network (ResNet) to recognize synchronous two-dimensional correlation spectroscopy (2DCOS) images. It can rapidly identify samples from wild and cultivated W. cocos in different parts. As a quantitative analysis method, UFLC was used to determine the contents of three triterpene acids in 547 samples. The results showed that a simultaneous qualitative and quantitative strategy could accurately evaluate the quality of W. cocos. The accuracy of ResNet models combined synchronous FT-NIR 2DCOS in identifying wild and cultivated W. cocos in different parts was as high as 100%. The contents of three triterpene acids in Poriae Cutis were higher than that in Poria, and the one with wild Poriae Cutis was the highest. In addition, the suitable habitat plays a crucial role in the quality of W. cocos. The maximum entropy (MaxEnt) model is a common method to predict the suitable habitat area for W. cocos under the current climate. Through the results, we found that suitable habitats were mostly situated in Yunnan Province of China, which accounted for approximately 49% of the total suitable habitat area of China. The research results not only pave the way for the rational planting in Yunnan Province of China and resource utilization of W. cocos, but also provide a basis for quality assessment of medicinal fungi.

Modeling of glioma growth using modified reaction-diffusion equation on brain MR images.

BACKGROUND AND OBJECTIVE: Modeling of glioma growth and evolution is of key importance for cancer diagnosis, predicting clinical progression and improving treatment outcomes of neurosurgery. However, existing models are unable to characterize spatial variations of the proliferation and infiltration of tumor cells, making it difficult to achieve accurate prediction of tumor growth. METHODS: In this paper, a new growth model of brain tumor using a reaction-diffusion equation on brain magnetic resonance images is proposed. Both the heterogeneity of brain tissue and the density of tumor cells are used to estimate the proliferation and diffusion coefficients of brain tumor cells. The diffusion coefficient that characterizes tumor diffusion and infiltration is calculated based on the ratio of tissues (white and gray matter), while the proliferation coefficient is evaluated using the spatial gradient of tumor cells. In addition, a parameter space is constructed using inverse distance weighted interpolation to describe the spatial distribution of proliferation coefficient. RESULTS: The glioma growth predicted by the proposed model were tested by comparing with the real magnetic resonance images of the patients. Experiments and simulation results show that the proposed method achieves accurate modeling of glioma growth. The interpolation-based growth model has higher average dice score of 0.0647 and 0.0545, and higher average Jaccard index of 0.0673 and 0.0573, respectively, compared to the uniform- and gradient-based growth models. CONCLUSIONS: The experimental results demonstrate the feasibility of calculating the proliferation and diffusion coefficients of the growth model based on patient-specific anatomy. The parameter space that characterizes spatial distribution of proliferation and diffusion coefficients is established and incorporated into the simulation of glioma growth. It enables to obtain patient-specific models about glioma growth by estimating and calibrating only a few model parameters.

The Mechanism of Lung and Intestinal Injury in Acute Pancreatitis: A Review.

Acute pancreatitis (AP), as a common cause of clinical acute abdomen, often leads to multi-organ damage. In the process of severe AP, the lungs and intestines are the most easily affected organs aside the pancreas. These organ damages occur in succession. Notably, lung and intestinal injuries are closely linked. Damage to ML, which transports immune cells, intestinal fluid, chyle, and toxic components (including toxins, trypsin, and activated cytokines to the systemic circulation in AP) may be connected to AP. This process can lead to the pathological changes of hyperosmotic edema of the lung, an increase in alveolar fluid level, destruction of the intestinal mucosal structure, and impairment of intestinal mucosal permeability. The underlying mechanisms of the correlation between lung and intestinal injuries are inflammatory response, oxidative stress, and endocrine hormone secretion disorders. The main signaling pathways of lung and intestinal injuries are TNF-α, HMGB1-mediated inflammation amplification effect of NF-κB signal pathway, Nrf2/ARE oxidative stress response signaling pathway, and IL-6-mediated JAK2/STAT3 signaling pathway. These pathways exert anti-inflammatory response and anti-oxidative stress, inhibit cell proliferation, and promote apoptosis. The interaction is consistent with the traditional Chinese medicine theory of the lung being connected with the large intestine (fei yu da chang xiang biao li in Chinese). This review sought to explore intersecting mechanisms of lung and intestinal injuries in AP to develop new treatment strategies.

Potential Chemoprevention of Paeoniflorin in Colitis-Associated Colorectal Cancer by Network Pharmacology, Molecular Docking, and In Vivo Experiment.

Chronic inflammation plays a positive role in the development and progression of colitis-associated colorectal cancer (CAC). Medicinal plants and their extracts with anti-inflammatory and immunoregulatory properties may be an effective treatment and prevention strategy for CAC. This research aimed to explore the potential chemoprevention of paeoniflorin (PF) for CAC by network pharmacology, molecular docking technology, and in vivo experiments. The results showed that interleukin-6 (IL-6) is a key target of PF against CAC. In the CAC mouse model, PF increased the survival rate of mice and decreased the number and size of colon tumors. Moreover, reduced histological score of colitis and expression of Ki-67 and PCNA were observed in PF-treated mice. In addition, the chemoprevention mechanisms of PF in CAC may be associated with suppression of the IL-6/STAT3 signaling pathway and the IL-17 level. This research provides experimental evidence of potential chemoprevention strategies for CAC treatment.

The Inhibition of Osteoblast Viability by Monosodium Urate Crystal-Stimulated Neutrophil-Derived Exosomes.

Background and Objective: Bone erosion is common in patients with gout. The role of neutrophil-derived exosomes in gouty bone erosion remains elusive. This study aimed to investigate the functions of the neutrophil-derived exosomes in the development of bone erosion in gout. Methods: Neutrophil-derived exosomes were collected and assessed by transmission electron microscopy and nanoparticle tracking analysis. Cell counting kit-8 assay was applied to evaluate cell viability, and cell apoptosis was assessed by flow cytometry. In addition, quantitative Real-time PCR and Western blotting were used to determine the expression levels of alkaline phosphatase (ALP), osteoprotegerin (OPG), and receptor activator of nuclear factor-κB ligand (RANKL). Neutrophil-derived exosomes were tagged with PKH67. The miRNA expression profiles of exosomes and human fetal osteoblasts (hFOB) were compared using high-throughput sequencing. Functional miRNAs transfected into hFOB after co-incubation with exosomes were selected and validated by preliminary qPCR. Results: Neutrophil-derived exosomes were stimulated by monosodium urate (MSU). The exosomes could inhibit the viability of the hFOB, and the expression levels of ALP and OPG were down-regulated, while the expression level of RANKL was up-regulated. However, there was no significant difference in the viability of osteoclasts and the expression of nuclear factor of activated T cells 1. Exosomes were observed in the cytoplasm under a confocal microscopy, confirming that exosomes could be taken up by hFOB. In total, 2590 miRNAs were found, of which 47 miRNAs were differentially expressed. Among the delivered miRNAs, miR-1246 exhibited the highest level of differential expression. The viability of hFOB was reduced by miR-1246 mimics and increased by miR-1246 inhibitors. There was no significant difference in hFOB apoptosis rate between the miR-1246 mimic and miR-1246 inhibitor group. MiR-1246 overexpression decreased the expression levels of ALP and OPG, whereas increasing the expression level of RANKL. In contrast, miR-1246 inhibitor increased the expression levels of ALP and OPG, while decreasing the expression level of RANKL. Neutrophil-derived exosomes stimulated by MSU could increase the expression of miR-1246. Conclusion: Neutrophil-derived exosomes stimulated by MSU could inhibit the viability of osteoblasts.

Lanthanide (Eu3+/Tb3+)-Loaded γ-Cyclodextrin Nano-Aggregates for Smart Sensing of the Anticancer Drug Irinotecan.

The clinical use of anticancer drugs necessitates new technologies for their safe, sensitive, and selective detection. In this article, lanthanide (Eu3+ and Tb3+)-loaded γ-cyclodextrin nano-aggregates (ECA and TCA) are reported, which sensitively detects the anticancer drug irinotecan by fluorescence intensity changes. Fluorescent lanthanide (Eu3+ and Tb3+) complexes exhibit high fluorescence intensity, narrow and distinct emission bands, long fluorescence lifetime, and insensitivity to photobleaching. However, these lanthanide (Eu3+ and Tb3+) complexes are essentially hydrophobic, toxic, and non-biocompatible. Lanthanide (Eu3+ and Tb3+) complexes were loaded into naturally hydrophilic γ-cyclodextrin to form fluorescent nano-aggregates. The biological nontoxicity and cytocompatibility of ECA and TCA fluorescent nanoparticles were demonstrated by cytotoxicity experiments. The ECA and TCA fluorescence nanosensors can detect irinotecan selectively and sensitively through the change of fluorescence intensity, with detection limits of 6.80 µM and 2.89 µM, respectively. ECA can safely detect irinotecan in the cellular environment, while TCA can detect irinotecan intracellularly and is suitable for cell labeling.