Dynamic analysis and optimal control of knowledge diffusion model in regional innovation ecosystem under digitalization.

Knowledge diffusion in regional innovation ecosystems is an important factor that influences the regional innovation efficiency. In regional innovation ecosystems under digital empowerment, the knowledge diffusion enables the optimal allocation of innovation resources and promotes the sustainable development and ecological evolution of regional innovation ecosystems. In this paper, a SEIR (Susceptible-Exposed-Infected-Recovered) model is proposed for knowledge diffusion in regional innovation ecosystems under digitization. The basic reproduction number of the proposed model is calculated and its stability is validated. Finally, the expressions for the optimal control system and the optimal control parameters are presented. According to the research conclusions of this paper, the knowledge-diffusion ability of innovation agents in an innovation ecosystem affects the knowledge diffusion in a system; the contact rate between innovation agents affects the efficiency of knowledge diffusion in the system and the structure of the system; the digital transmission ability of innovation agents affects the breadth of knowledge diffusion in the system; and the self-learning ability of innovation agents affects the efficiency of knowledge diffusion in the system.The digital technologies help heterogeneous innovation agents in regional innovation ecosystems to break down the knowledge silos. At the same time, the digital technologies enhance the ability of innovation agents to absorb and learn knowledge in regional innovation ecosystems under digitization, thereby increasing the infection rate of knowledge diffusion in such systems.These conclusions extend the theoretical boundaries of innovation ecosystems and knowledge diffusion and offer management implications for enterprises and governments in decision-making.

Nanoparticle-hydrogel composite as dual-drug delivery system for the potential application of corneal graft rejection.

Immune rejection remains the major cause of corneal graft failure. Immunosuppressants (such as rapamycin; RAPA) adjunctive to antibiotics (such as levofloxacin hydrochloride; Lev) are a clinical mainstay after corneal grafts but suffer from poor ocular bioavailability associated with severe side effects. In this study, we fabricated a Lev@RAPA micelle loaded cationic peptide-based hydrogel (NapFFKK) as a dual-drug delivery system by integrating RAPA micelles with Lev into a cationic NapFFKK hydrogel to potentially reduced the risk of corneal graft rejection. The properties of the resulting hydrogels were characterized using transmission electronmicroscopy and rheometer. Lev@RAPA micelles loaded NapFFKK hydrogel provided sustained in vitro drug release without compromising their inherent pharmacological activities. Topical instillation of Lev@RAPA micelles loaded NapFFKK hydrogel resulted in the great ocular tolerance and extended precorneal retention over 60min, thus significantly enhancing the ocular bioavailability of both Lev and RAPA. Overall, such dual-drug delivery system might be a promising formulation for the suppression of corneal graft failure.

Dynamic analysis and optimal control of stochastic information cross-dissemination and variation model with random parametric perturbations.

Information dissemination has a significant impact on social development. This paper considers that there are many stochastic factors in the social system, which will result in the phenomena of information cross-dissemination and variation. The dual-system stochastic susceptible-infectious-mutant-recovered model of information cross-dissemination and variation is derived from this problem. Afterward, the existence of the global positive solution is demonstrated, sufficient conditions for the disappearance of information and its stationary distribution are calculated, and the optimal control strategy for the stochastic model is proposed. The numerical simulation supports the results of the theoretical analysis and is compared to the parameter variation of the deterministic model. The results demonstrate that cross-dissemination of information can result in information variation and diffusion. Meanwhile, white noise has a positive effect on information dissemination, which can be improved by adjusting the perturbation parameters.

Design, Synthesis, Biological Evaluation, and Molecular Docking Studies of Pleuromutilin Derivatives Containing Thiazole.

In this study, we designed and synthesized a series of pleuromutilin derivatives containing thiazole. The in vitro antimicrobial efficacy of these synthesized compounds was examined by using four strains. Compared with tiamulin (MIC = 0.25 µg/mL), compound 14 exhibited potency in inhibiting MRSA growth (MIC = 0.0625 µg/mL) in these derivatives. Meanwhile, the time-killing kinetics further demonstrated that compound 14 could efficiently inhibit the MRSA growth. After exposure at 4 × MIC, the postantibiotic effect (PAE) of compound 14 was 1.29 h. Additionally, in thigh-infected mice, compound 14 exhibited a more potent antibacterial efficacy (-1.78 ± 0.28 log10 CFU/g) in reducing MRSA load compared to tiamulin (-1.21 ± 0.23 log10 CFU/g). Moreover, the MTT assay on RAW 264.7 cells demonstrated that compound 14 (8 µg/mL) had no significant cytotoxicity. Docking studies indicated the strong affinity of compound 14 toward the 50S ribosomal subunit, with a binding free energy of -9.63 kcal/mol. Taken together, it could be deduced that compound 14 was a promising candidate for treating MRSA infections.

An innovative label-free electrochemical aptamer sensor: utilizing Ti3C2Tx/MoS2/Au NPs for accurate interleukin-6 detection.

In the medical field, changes in interleukin-6 (IL-6) concentration serve as essential biomarkers for monitoring and diagnosing various conditions, including acute inflammatory responses such as those seen in trauma and burns, and chronic illnesses like cancer. This paper detailed a label-free electrochemical aptamer sensor designed for IL-6 quantification. A composite material consisting of Ti3C2Tx and MoS2 was successfully synthesized to fabricate this sensor. The synergistic effect of MoS2's catalytic action on hydrogen peroxide (H2O2), used as a signalling marker, when combined with the exceptional conductivity and large specific surface area of Ti3C2Tx, not only enables an increased loading of MoS2 but also significantly boosts the electrochemical response. The in situ-reduced Au NPs provided stable immobilization sites for DNA aptamers (DNAapt) and facilitated electron transfer, ensuring accurate IL-6 recognition. Under optimal conditions, the aptamer sensor exhibited a wide linear range (5 pg/mL to 100 ng/mL) and a low limit of detection (LOD) of 2.9 pg/mL. Its sensing performance in human serum samples highlights its potential as a promising clinical analysis tool.

General anesthetic agents induce neurotoxicity through oligodendrocytes in the developing brain.

General anesthetic agents can impact brain function through interactions with neurons and their effects on glial cells. Oligodendrocytes perform essential roles in the central nervous system, including myelin sheath formation, axonal metabolism, and neuroplasticity regulation. They are particularly vulnerable to the effects of general anesthetic agents resulting in impaired proliferation, differentiation, and apoptosis. Neurologists are increasingly interested in the effects of general anesthetic agents on oligodendrocytes. These agents not only act on the surface receptors of oligodendrocytes to elicit neuroinflammation through modulation of signaling pathways, but also disrupt metabolic processes and alter the expression of genes involved in oligodendrocyte development and function. In this review, we summarize the effects of general anesthetic agents on oligodendrocytes. We anticipate that future research will continue to explore these effects and develop strategies to decrease the incidence of adverse reactions associated with the use of general anesthetic agents.

Exploration of identifying individual tumor tissue based on probabilistic model.

Variations in the tumor genome can result in allelic changes compared to the reference profile of its homogenous body source on genetic markers. This brings a challenge to source identification of tumor samples, such as clinically collected pathological paraffin-embedded tissue and sections. In this study, a probabilistic model was developed for calculating likelihood ratio (LR) to tackle this issue, which utilizes short tandem repeat (STR) genotyping data. The core of the model is to consider tumor tissue as a mixture of normal and tumor cells and introduce the incidence of STR variants (φ) and the percentage of normal cells (Mxn) as a priori parameters when performing calculations. The relationship between LR values and φ or Mxn was also investigated. Analysis of tumor samples and reference blood samples from 17 colorectal cancer patients showed that all samples had Log 10(LR) values greater than 1014. In the non-contributor test, 99.9% of the quartiles had Log 10(LR) values less than 0. When the defense's hypothesis took into account the possibility that the tumor samples came from the patient's relatives, LR greater than 0 was still obtained. Furthermore, this study revealed that LR values increased with decreasing φ and increasing Mxn. Finally, LR interval value was provided for each tumor sample by considering the confidence interval of Mxn. The probabilistic model proposed in this paper could deal with the possibility of tumor allele variability and offers an evaluation of the strength of evidence for determining tumor origin in clinical practice and forensic identification.

Identification of Plasma hsa_circ_0001230 and hsa_circ_0023879 as Potential Novel Biomarkers for Focal Segmental Glomerulosclerosis and circRNA-miRNA-mRNA Network Analysis.

INTRODUCTION: Focal segmental glomerulosclerosis (FSGS) is a common glomerulopathy with an unclear mechanism. The demand for FSGS clinical diagnostic biomarkers has not yet been met. Circular RNA (circRNA) is a novel non-coding RNA with multiple functions, but its diagnostic value for FSGS remains unexplored. This study aimed to identify circRNAs that could aid in early clinical diagnosis and to investigate their mechanisms in podocyte injury. METHODS: The signature of plasma circRNAs for FSGS was identified by circRNA microarray. The existence of circRNAs was confirmed by quantitative real-time polymerase chain reaction (qRT-PCR), RNase R assay, and DNA sequencing. Plasma levels of circRNAs were evaluated by qRT-PCR. The diagnostic value was appraised by the receiver operating characteristic curve. The circRNA-miRNA-mRNA network was built with Cytoscape 7.3.2. Statistically significant differences were calculated by the Mann-Whitney U test. RESULTS: A total of 493 circRNAs (165 upregulated, 328 downregulated) were differentially expressed in the plasma of FSGS patients (n = 3) and normal controls (n = 3). Eight candidate circRNAs were demonstrated to be circular and stable transcripts. Among them, hsa_circ_0001230 and hsa_circ_0023879 were significantly upregulated in FSGS patients (n = 29) compared to normal controls (n = 51). The areas under the curve value of hsa_circ_0001230 and hsa_circ_0023879 were 0.668 and 0.753, respectively, while that of the two-circRNA panel was 0.763. The RNA pull-down analysis revealed that hsa_circ_0001230 and hsa_circ_0023879 could sponge hsa-miR-106a. Additionally, hsa_circ_0001230 and hsa_circ_0023879 positively regulated hsa-miR-106a target genes phosphatase and tensin homolog (PTEN) and Bcl-2-like protein 11 (BCL2L11) in podocytes. CONCLUSION: hsa_circ_0001230 and hsa_circ_0023879 are novel blood biomarkers for FSGS. They may regulate podocyte apoptosis by competitively binding to hsa-miR-106a.

A Self-Amplifying ROS-Responsive Nanoplatform for Simultaneous Cuproptosis and Cancer Immunotherapy.

Cuproptosis is an emerging cell death pathway that depends on the intracellular Cu ions. Elesclomol (ES) as an efficient Cu ionophore can specifically transport Cu into mitochondria and trigger cuproptosis. However, ES can be rapidly removed and metabolized during intravenous administration, leading to a short half-life and limited tumor accumulation, which hampers its clinical application. Here, the study develops a reactive oxygen species (ROS)-responsive polymer (PCP) based on cinnamaldehyde (CA) and polyethylene glycol (PEG) to encapsulate ES-Cu compound (EC), forming ECPCP. ECPCP significantly prolongs the systemic circulation of EC and enhances its tumor accumulation. After cellular internalization, the PCP coating stimulatingly dissociates exposing to the high-level ROS, and releases ES and Cu, thereby triggering cell death via cuproptosis. Meanwhile, Cu2+-stimulated Fenton-like reaction together with CA-stimulated ROS production simultaneously breaks the redox homeostasis, which compensates for the insufficient oxidative stress treated with ES alone, in turn inducing immunogenic cell death of tumor cells, achieving simultaneous cuproptosis and immunotherapy. Furthermore, the excessive ROS accelerates the stimuli-dissociation of ECPCP, forming a positive feedback therapy loop against tumor self-alleviation. Therefore, ECPCP as a nanoplatform for cuproptosis and immunotherapy improves the dual antitumor mechanism of ES and provides a potential optimization for ES clinical application.

Reprogramming the Metabolism of Yeast for High-Level Production of Miltiradiene.

Miltiradiene serves as a crucial precursor in the synthesis of various high-value abietane-type diterpenes, exhibiting diverse pharmacological activities. Previous efforts to enhance miltiradiene production have primarily focused on the mevalonate acetate (MVA) pathway. However, limited emphasis has been placed on optimizing the supply of acetyl-CoA and NADPH. In this study, we constructed a platform yeast strain for miltiradiene production by reinforcing the biosynthetic pathway of geranylgeranyl diphosphate (GGPP) and acetyl-CoA, and addressing the imbalance between the supply and demand of the redox cofactor NADPH within the cytoplasm, resulting in an increase in miltiradiene yield to 1.31 g/L. Furthermore, we conducted modifications to the miltiradiene synthase fusion protein tSmKSL1-CfTPS1. Finally, the comprehensive engineering strategies and protein modification strategies culminated in 1.43 g/L miltiradiene in the engineered yeast under shake flask culture conditions. Overall, our work established efficient yeast cell factories for miltiradiene production, providing a foothold for heterologous biosynthesis of abietane-type diterpenes.

Core-Shell MnFe Nanocatalyst Derived from Prussian Blue Analogs for Peroxymonosulfate Activation: Nonradical Mechanism and Bimetallic Valence Cycle.

Sulfamethazine (SAT) is widely present in sediment, soil, rivers, and groundwater. Unfortunately, traditional water treatment technologies are inefficient at eliminating SAT from contaminated water. Therefore, developing an effective and ecologically friendly treatment procedure to effectively remove SAT is critical. This has raised concerns about its potential impact on the environment and human health. In this study, metal-organic-inorganic composites consisting of graphene-encapsulated Fe-Mn metal catalyst (Mn3Fe1-NC) were synthesized by calcining MnFe Prussian blue analogs (PBA) under a nitrogen atmosphere. The composites were applied to activate peroxymonosulfate (PMS) and facilitate the degradation of SAT in aquatic environments. The Mn3Fe1-NC, dosed with 5 mg, in combination with PMS, dosed with 1.5 mmol L-1, achieved a 91.8% degradation efficiency of SAT. The transformation of the CN skeleton led to the formation of a carbon shell structure, which consequently reduced metal ion leaching from the material. At various pH levels, the iron and manganese ions were observed to leach out at levels lower than 0.1392 and 0.0580 mg L-1, respectively. In contrast, the Mn3Fe1-NC was found to be minimally impacted by pH levels and coexisting ions present in the aqueous environment. Radical burst experiments and electrochemical analysis tests verified that degradation primarily occurs through the nonradical pathway of electron transfer. The active sites responsible for this process were identified as the Mn (IV) and graphitic-N atoms on the material, which facilitate direct electron transfer. Additionally, the presence of Fe atoms promotes the valence cycling of Mn atoms. This study introduces new insights into the reaction mechanism and the constitutive relationship of catalytic centers in nonradical oxidation reactions.

Using simulated microhaplotype genotyping data to evaluate the value of machine learning algorithms for inferring DNA mixture contributor numbers.

Inferring the number of contributors (NoC) is a crucial step in interpreting DNA mixtures, as it directly affects the accuracy of the likelihood ratio calculation and the assessment of evidence strength. However, obtaining the correct NoC in complex DNA mixtures remains challenging due to the high degree of allele sharing and dropout. This study aimed to analyze the impact of allele sharing and dropout on NoC inference in complex DNA mixtures when using microhaplotypes (MH). The effectiveness and value of highly polymorphic MH for NoC inference in complex DNA mixtures were evaluated through comparing the performance of three NoC inference methods, including maximum allele count (MAC) method, maximum likelihood estimation (MLE) method, and random forest classification (RFC) algorithm. In this study, we selected the top 100 most polymorphic MH from the Southern Han Chinese (CHS) population, and simulated over 40 million complex DNA mixture profiles with the NoC ranging from 2 to 8. These profiles involve unrelated individuals (RM type) and related pairs of individuals, including parent-offspring pairs (PO type), full-sibling pairs (FS type), and second-degree kinship pairs (SE type). Our results indicated that how the number of detected alleles in DNA mixture profiles varied with the markers' polymorphism, kinship's involvement, NoC, and dropout settings. Across different types of DNA mixtures, the MAC and MLE methods performed best in the RM type, followed by SE, FS, and PO types, while RFC models showed the best performance in the PO type, followed by RM, SE, and FS types. The recall of all three methods for NoC inference were decreased as the NoC and dropout levels increased. Furthermore, the MLE method performed better at low NoC, whereas RFC models excelled at high NoC and/or high dropout levels, regardless of the availability of a priori information about related pairs of individuals in DNA mixtures. However, the RFC models which considered the aforementioned priori information and were trained specifically on each type of DNA mixture profiles, outperformed RFC_ALL model that did not consider such information. Finally, we provided recommendations for model building when applying machine learning algorithms to NoC inference.

A 2-year mental health follow-up study subsequent to COVID-19.

The COVID-19 pandemic has profoundly impacted the mental health and education of college students. This study examined the interrelationships among loneliness, resilience, and COVID-19 fear among college students in Northern Michigan, a region of the United States severely affected by the pandemic. Data were collected from two student cohorts (n = 258), with half surveyed in early 2022 and the other half in mid-2022, two years after pandemic's onset. The Omicron wave peaked in Michigan in January 2022, but by June 2022, cases, hospitalizations, and deaths had significantly declined. Students completed measures of loneliness, resilience, learning difficulty, and psychological symptoms. Key findings are: 1) Participants' fear, loneliness, and academic difficulty decreased over time, reflecting fluctuations in acute situational and emotional states; 2) Unexpectedly, resilience declined from early to mid-2022, suggesting its diminishing protective role under prolonged, pandemic-induced stress; 3) Despite improvements, students continued reporting high academic difficulties. Loneliness, heightened fear, and dampened happiness together contributed to greater academic difficulties; 4) Pre-existing sex differences equalized two years after the pandemic's onset. While modest improvements were noted, enduring academic and mental health impacts signal a need for continued support.

A novel nomogram for predicting the prolonged length of stay in post-anesthesia care unit after elective operation.

BACKGROUND: Prolonged length of stay in post-anesthesia care unit (PLOS in PACU) is a combination of risk factors and complications that can compromise quality of care and operating room efficiency. Our study aimed to develop a nomogram to predict PLOS in PACU of patients undergoing elective surgery. METHODS: Data from 24017 patients were collected. Least absolute shrinkage and selection operator (LASSO) was used to screen variables. A logistic regression model was built on variables determined by a combined method of forward selection and backward elimination. Nomogram was designed with the model. The nomogram performance was evaluated with the area under the receiver operating characteristic curve (AUC) for discrimination, calibration plot for consistency between predictions and actuality, and decision curve analysis (DCA) for clinical application value. RESULTS: A nomogram was established based on the selected ten variables, including age, BMI < 21 kg/m2, American society of Anesthesiologists Physical Status (ASA), surgery type, chill, delirium, pain, naloxone, operation duration and blood transfusion. The C-index value was 0.773 [95% confidence interval (CI) = 0.765 - 0.781] in the development set and 0.757 (95% CI = 0.744-0.770) in the validation set. The AUC was > 0.75 for the prediction of PLOS in PACU. The calibration curves revealed high consistencies between the predicted and actual probability. The DCA showed that if the threshold probability is over 10% , using the models to predict PLOS in PACU and implement intervention adds more benefit. CONCLUSIONS: This study presented a nomogram to facilitate individualized prediction of PLOS in PACU for patients undergoing elective surgery.

The Function, Underlying Mechanism and Clinical Potential of Exosomes in Colorectal Cancer.

Colorectal cancer (CRC) is a lethal malignancy worldwide. Exosomes are extracellular vesicles derived from the endosomal pathway of nearly all cells and can be found in body fluids. They can be considered an intercellular system in the human body that can mediate near- and long-distance intercellular communication due to their features and functions. Investigations have revealed that exosomes are participated in different processes, physiologically and pathologically, especially in cancer. However, the clinical value of exosomes and their mechanisms of action in CRC are unclear and have not been systematically assessed. The purpose of this review is to discuss how exosomes play a role in the occurrence and development of CRC, with a particular focus on the functions and underlying mechanisms of tumor-derived exosomes as well as non-tumor-derived exosomes. We also describe the evidence that exosomes can be used as diagnostic and prognostic markers for CRC. In addition, the possibilities of exosomes in CRC clinical transformation are also discussed.

Dynamic analysis and optimal control of a stochastic investor sentiment contagion model considering sentiments isolation with random parametric perturbations.

Investor sentiment contagion has a profound influence on economic and social development. This paper explores the diverse influences of various investor sentiments in modern society on the economy and society. It also investigates the interference of various uncertain factors on investor sentiments in the modern economy and society. On this basis, the dual-system stochastic SPA2G2R model was constructed, incorporating positive and negative sentiments, as well as a supervision and isolation mechanism. The global existence of positive solutions was established, and sufficient conditions for the disappearance and steady distribution of investor sentiment were calculated. An optimal control strategy for the stochastic model was put forward, with numerical simulation supporting the theoretical analysis results. A comparison with parameter changes in the deterministic model was also conducted. The research reveals a competitive relationship between different investor sentiments. Enhancing societal guidance mechanisms promotes positive investor sentiment contagion. Timely control by the supervisory department effectively curbs the spread of investor sentiment. Additionally, white noise promotes investor sentiment contagion, suggesting effective regulation through control of noise intensity and disturbance parameters.

Effect of General Anesthetic Agents on Microglia.

The effects of general anesthetic agents (GAAs) on microglia and their potential neurotoxicity have attracted the attention of neuroscientists. Microglia play important roles in the inflammatory process and in neuromodulation of the central nervous system. Microglia-mediated neuroinflammation is a key mechanism of neurocognitive dysfunction during the perioperative period. Microglial activation by GAAs induces anti-inflammatory and pro-inflammatory effects in microglia, suggesting that GAAs play a dual role in the mechanism of postoperative cognitive dysfunction. Understanding of the mechanisms by which GAAs regulate microglia may help to reduce the incidence of postoperative adverse effects. Here, we review the actions of GAAs on microglia and the consequent changes in microglial function. We summarize clinical and animal studies associating microglia with general anesthesia and describe how GAAs interact with neurons via microglia to further explore the mechanisms of action of GAAs in the nervous system.

Nano Self-Assemblies of Caffeic Acid-Fibronectin Mimic a Peptide Conjugate for the Treatment of Corneal Epithelial Injury.

Rapid corneal re-epithelialization is important for corneal wound healing. Corneal epithelial cell motility and oxidative stress are important targets for therapeutic intervention. In this study, we covalently conjugated the antioxidant caffeic acid (CA) with a bioactive peptide sequence (PHSRN) to generate a CA-PHSRN amphiphile, which was formulated into nanoparticular eye drops with an average size of 43.21 ± 16 nm. CA-PHSRN caused minimal cytotoxicity against human corneal epithelial cells (HCECs) and RAW264.7 cells, exhibited an excellent free radical scavenging ability, and remarkably attenuated reactive oxygen species (ROS) levels in H2O2-stimulated HCECs. The antioxidant and anti-inflammatory activities of CA-PHSRN were assessed in lipopolysaccharide (LPS)-stimulated RAW264.7 cells. The results show that CA-PHSRN treatment effectively prevented LPS-induced DNA damage and significantly reduced the levels of LPS-induced pro-inflammatory cytochemokines (i.e., iNOS, NO, TNF-α, IL-6, and COX-2) in a dose-dependent manner. Moreover, using a rabbit corneal epithelial ex vivo migration assay, we demonstrated that the proposed CA-PHSRN accelerated corneal epithelial cell migration and exhibited high ocular tolerance and ocular bioavailability after topical instillation. Taken together, the proposed CA-PHSRN nanoparticular eye drops are a promising therapeutic formulation for the treatment of corneal epithelial injury.

Unraveling the influence of green bonds on environmental sustainability and paving the way for sustainable energy projects in green finance.

The acceleration of renewable energy has emerged as a cornerstone strategy in mitigating climate change and advancing the sustainable stewardship of our natural resources. Nonetheless, financing renewable energy projects remains a challenging issue. In this context, green bonds have surfaced as a promising financial instrument to propel renewable energy projects forward and foster sustainable resource development. This study endeavors to evaluate the transformative impact of green bonds on renewable energy investments in China. Leveraging the fuzzy analytical hierarchy process (AHP) and the fuzzy weighted aggregates sum product assessment (WASPAS) methods, we delve into the Chinese landscape to dissect the correlation between green bonds and renewable energy investment outcomes. Through extensive literature review, we have identified several factors, comprising nuanced sub-factors, alongside distinctive investment strategies pertinent to the effective utilization of green bonds in the renewable energy sector. The fuzzy AHP analysis reveals that financial, environmental, and regulatory are the most influential factors. Employing the fuzzy WASPAS method, our findings emphasize the transformative potential of green bonds in significantly accessing to capital of renewable energy projects in the context of Chinese. This research sheds light on the pivotal role green bonds play in driving sustainable natural resource development through substantial investments in renewable energy projects.

Attenuated Salmonella-delivered PD-1 siRNA enhances the antitumor effects of EZH2 inhibitors in colorectal cancer.

Immunotherapy has made significant progress in the treatment of malignant tumors. However, strategies to combine immunotherapy with anticancer drugs have attracted great attention due to the low response rate and unique toxicity profile of immunotherapies and the subsequent development of acquired resistance in some initial responders. EZH2, a histone methyl transferase subunit of a Polycomb repressor complex,is highly expressed in a variety of tumors, and targeting EZH2 has become a new strategy for tumor therapy and drug combination. Here，we studied the effect of EZH2 inhibitors on colorectal cancer cells and their combination with immunotherapy. Our results demonstrated that EZH2 inhibitors can not only significantly inhibit the survival of colorectal cancer (CRC) cells and induce apoptosis, effectively inhibit cell invasion and migration, but also cause an increase in the expression of PD-L1 receptors on the cell surface. To determine the effect of EZH2 in combination with immunotherapy, we combine EZH2 inhibitors with PD-1 siRNA delivered by attenuated Salmonella. The vivo experiments have shown that the combination of EZH2 inhibitors and Salmonella-delivered PD-1 siRNA can further inhibit the development of CRC, trigger effective anti-tumor immunity, and improve therapeutic efficacy. Its underlying mechanisms mainly involve synergistic immunomodulation and apoptosis. This study suggests an emerging strategy based on a combination of EZH2 inhibitor and immunotherapy based on PD-1 inhibition.