Abstract Methacrylated biopolymers are unique and attractive in preparing photocrosslinkable hydrogels in biomedical applications. Here we report a novel chitosan (CS) derivative‐based injectable hydrogel with anti‐inflammatory capacity via methacrylation modification. First, ibuprofen (IBU) was conjugated to the backbone of CS by carbodiimide chemistry to obtain IBU‐CS conjugate, which converts water‐insoluble unmodified CS into water‐soluble IBU‐CS conjugate. The IBU‐CS conjugate did not precipitate at the pH of 7, which was beneficial to subsequent chemical modification with methacrylic anhydride to prepare IBU‐CS methacrylate (IBU‐CS‐MA) with significantly higher methacrylation substitution. Photocrosslinkable in situ gel formation of injectable IBU‐CS‐MA hydrogel was verified using lithium phenyl‐2,4,6‐trimethylbenzoylphosphinate (LAP) initiator under visible light. The IBU‐CS‐MA hydrogel showed good cytocompatibility as revealed by encapsulating and in vitro culturing murine fibroblasts within hydrogels. It promoted macrophage polarization toward M2 phenotype, as well as downregulated pro‐inflammatory gene expression and upregulated anti‐inflammatory gene expression of macrophages. The hydrogel also significantly reduced the reactive oxygen specifies (ROS) and nitrogen oxide (NO) produced by lipopolysaccharides (LPS)‐stimulated macrophages. Upon subcutaneous implantation in a rat model, it significantly mitigated inflammatory responses as shown by significantly lower inflammatory cell density, less cell infiltration, and much thinner fibrous capsule compared with CS methacrylate (CS‐MA) hydrogel. This study suggests that IBU‐CS conjugate represents a feasible strategy for preparing CS‐based methacrylate hydrogels for biomedical applications.
Abstract Reperfusion therapy is the most effective treatment for acute myocardial infarction, but its efficacy is frequently limited by ischemia‐reperfusion injury (IRI). While antioxidant and anti‐inflammatory therapies have shown significant potential in alleviating IRI, these strategies have not yielded satisfactory clinical outcomes. For that, a thermo‐sensitive myocardial‐injectable poly(amino acid) hydrogel of methoxy poly(ethylene glycol) 45 ‐poly(L‐methionine 20 ‐ co ‐L‐alanine 10 ) (mPEG 45 ‐P(Met 20 ‐ co ‐Ala 10 ), PMA) loaded with FTY720 (PMA/FTY720) is developed to address IRI through synergistic anti‐apoptotic and anti‐inflammatory effects. Upon injection into the ischemic myocardium, the PMA aqueous solution undergoes a sol‐to‐gel phase transition and gradually degrades in response to reactive oxygen species (ROS), releasing FTY720 on demand. PMA acts synergistically with FTY720 to inhibit cardiomyocyte apoptosis and modulate pro‐inflammatory M1 macrophage polarization toward anti‐inflammatory M2 macrophages by clearing ROS, thereby mitigating the inflammatory response and promoting vascular regeneration. In a rat IRI model, PMA/FTY720 reduces the apoptotic cell ratio by 81.8%, increases vascular density by 34.0%, and enhances left ventricular ejection fraction (LVEF) by 12.8%. In a rabbit IRI model, the gel‐based sustained release of FTY720 enhanced LVEF by an additional 7.2% compared to individual treatment. In summary, the engineered PMA hydrogel effectively alleviates IRI through synergistic anti‐apoptosis and anti‐inflammation actions, offering valuable clinical potential for treating myocardial IRI.
The recent outbreak of the coronavirus disease-2019 (COVID-19) caused serious challenges to the human society in China and across the world. COVID-19 induced pneumonia in human hosts and carried a highly inter-person contagiousness. The COVID-19 patients may carry severe symptoms, and some of them may even die of major organ failures. This study utilized the machine learning algorithms to build the COVID-19 severeness detection model. Support vector machine (SVM) demonstrated a promising detection accuracy after 32 features were detected to be significantly associated with the COVID-19 severeness. These 32 features were further screened for inter-feature redundancies. The final SVM model was trained using 28 features and achieved the overall accuracy 0.8148. This work may facilitate the risk estimation of whether the COVID-19 patients would develop the severe symptoms. The 28 COVID-19 severeness associated biomarkers may also be investigated for their underlining mechanisms how they were involved in the COVID-19 infections.
Background: Hemorrhagic fever with renal syndrome (HFRS), caused by orthohantaviruses, occupies one of the leading places among natural focal human diseases, for which there are no modern accurate and highly sensitive diagnostic methods. To improve this situation, a better understanding of the hantavirus pathogenesis of HFRS is required. The expression levels of circulating microRNAs in the serum or plasma of patients during infection make them potential therapeutic biomarkers for the diagnosis of HFRS. The aim of the study: To analyze the expression levels of miR-126 and miR-218 patients with HFRS at different stages of the disease. Materials and methods: The moderate disease severity group of HFRS patients included 105 RNA samples, severe – 99 and severe with complications – 84 RNA samples. Blood samples of HFRS patients for molecular genetic analysis were collected three times – during the initial febrile period (1-4 days of illness), the polyuric period (15-22 days of illness) and during the convalescence period. Total RNA isolation was performed using the miRNeasy Serum/Plasma Advanced Kit (Qiagen, Germany). Quantitative realtime PCR was performed using the miRCURY LNA SYBR Green PCR Kit (Qiagen, Germany) and the real time PCR product detection system LightCycler96 (Roch). Results: A pairwise comparison of miR-126 and miR-218 expression levels in patients with HFRS at the fever stage and at the polyuric stage of HFRS did not reveal statistically significant results (P>0.05). Conclusion: Further studies of the network of genes that are targets of various microRNAs are needed to clarify the molecular mechanisms that can influence the occurrence and development of HFRS.
Hemorrhagic fever with renal syndrome (HFRS) is an acute natural focal viral disease caused by viruses of the genus hantavirus, characterized by damage to small blood vessels, kidneys, lungs and other organs of a person. MicroRNAs (miRNAs) are 18-22 nucleotide endogenously expressed RNA molecules that inhibit gene expression at the post-transcriptional level by binding to the 3-untranslated region of the target mRNA. It has been proven that miRNAs play a significant role in various biological processes, including the cell cycle, apoptosis, cell proliferation and differentiation. It has been proven that miRNAs may be involved in the pathogenesis of infectious diseases, including HFRS. Hantavirus infection predominantly affects endothelial cells and causes dysfunction of the endothelium of capillaries and small vessels. It is known that the immune response induced by Hantavirus infection plays an important role in disrupting the endothelial barrier. In a few studies, both in vitro and in vivo, it has been shown that endothelial dysfunction and the immune response after infection with Hantavirus can be partially regulated by miRNAs by acting on certain genes. Most of the miRNAs is expressed within the cells themselves. However, in some biological fluids of the human body, for example, plasma or blood serum, numerous miRNAs, called circulating miRNAs, have been found. Circulating miRNAs can be secreted by cells into human biological fluids as part of extracellular vesicles as exosomes or be part of an RNA-bound protein complex as miRNA-Argonaute 2 (Ago2). These miRNAs are resistant to nucleases, which makes them attractive as potential biomarkers in various human diseases. There is no specific antiviral therapy for HFRS, and the determination of laboratory parameters that are used to diagnose, assess the severity, and predict the course of the disease remains a challenge due to the peculiarities of the pathophysiology and clinical course of the disease. Studying the role of miRNAs in HFRS seems to be expedient for the development of specific and effective therapy, as well as for use as diagnostic and prognostic biomarkers (in relation to circulating miRNAs).
Background: The recent outbreak of the coronavirus disease-2019 (COVID-19) caused serious challenges to the human society in China and across the world. COVID-19 induced pneumonia in human hosts and carried a highly inter-person contagiousness. The COVID-19 patients may carry severe symptoms, and some of them may even die of major organ failures. We aim to utilize the machine learning algorithms to build the COVID-19 severeness detection model.Methods: This study recruited the binary classification problem between 75 severely illed COVID-19 infected patients and the other 62 patients with mild symptoms. Support vector machine (SVM) demonstrated a promising detection accuracy after 32 features were detected to be significantly associated with the COVID-19 severeness. These 32 features were further screened for inter-feature redundancies.Findings: The severely illed patients had a higher serum level of neutrophil percentage and lower serum levels of monocyte percentage and calcium compared with those mild ones. The blood test features demonstrated much more significant inter-group differences than the urine test features. These three blood test features as candidate severeness biomarkers, i.e., serum ferritin, hs-CRP, interleukin-2R, and tumor necrosis factor-α. The final SVM model achieved the overall accuracy 0.8148 using 28 features.Interpretation: This study utilized the machine learning algorithms to detect the COVID-19 severely ill patients from those with only mild symptoms. Our experimental data demonstrated strong correlations with the COVID-19 severeness. The 28 biomarkers may also be investigated for their underlining mechanisms of their roles in the COVID-19 severely ill patients.Funding Statement: This work was supported by grants from The epidemiology, early warning and response techniques of major infectious diseases in the Belt and Road Initiative (#2018ZX10101002), National Natural Science Foundation of China (#81871699), Jilin Provincial Key Laboratory of Big Data Intelligent Computing (20180622002JC), the Education Department of Jilin Province (JJKH20180145KJ), Foundation of Jilin Province Science and Technology Department (#172408GH010234983), and the startup grant of the Jilin University. This work was also partially supported by the Bioknow MedAI Institute (BMCPP-2018-001), the High Performance Computing Center of Jilin University, and the Fundamental Research Funds for the Central Universities, JLU.Declaration of Interests: The authors declare no competing interests. Ethics Approval Statement: This study was approved by the Ethics Commission of the First Hospital of Jilin University. Informed consent was waived for this emerging infectious disease.
Chitosan (CS)-based photo-cross-linkable hydrogels have gained increasing attention in biomedical applications. In this study, we grafted CS with gallic acid (GA) by carbodiimide chemistry to prepare the GA-CS conjugate, which was subsequently modified with methacrylic anhydride (MA) modification to obtain the methacrylated GA-CS conjugate (GA-CS-MA). Our results demonstrated that the GA-CS-MA hydrogel not only exhibited improved physicochemical properties but also showed antibacterial, antioxidative, and anti-inflammatory capacity. It showed moderate antibacterial activity and especially showed a more powerful inhibitory effect against Gram-positive bacteria. It modulated macrophage polarization, downregulated pro-inflammatory gene expression, upregulated anti-inflammatory gene expression, and significantly reduced reactive oxygen species (ROS) and nitric oxide (NO) production under lipopolysaccharide (LPS) stimulation. Subcutaneously implanted GA-CS-MA hydrogels induced significantly lower inflammatory responses, as evidenced by less inflammatory cell infiltration, thinner fibrous capsule, and predominately promoted M2 polarization. This study provides a feasible strategy to prepare CS-based photo-cross-linkable hydrogels with improved physicochemical properties for biomedical applications.
Nanomedicines are highly promising for cancer therapy due to their minimal side effects. However, little is known regarding their host immune response, which may limit their clinical efficacy and applications. Here, we find that cisplatin (CDDP)-loaded poly(l-glutamic acid)-graft-methoxy poly(ethylene glycol) complex nanoparticles (CDDP-NPs) elicit a strong antitumor CD8+ T cell-mediated immune response in a tumor-bearing mouse model compared to free CDDP. Mechanistically, the sustained retention of CDDP-NPs results in persistent tumor MHC-I overexpression, which promotes the formation of MHC-I-antigen peptide complex (pMHC-I), enhances the interaction between pMHC-I and T cell receptor (TCR), and leads to the activation of TCR signaling pathway and CD8+ T cell-mediated immune response. Furthermore, CDDP-NPs upregulate the costimulatory OX40 on intratumoral CD8+ T cells, and synergize with the agonistic OX40 antibody (aOX40) to suppress tumor growth by 89.2%. Our study provides a basis for the efficacy advantage of CDDP-based nanomedicines and immunotherapy.
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