Sialic Acid-Functionalized Pyroptosis Nanotuner for Epigenetic Regulation and Enhanced Cancer Immunotherapy.

The efficacy of immune checkpoint blockade (ICB) in promoting an immune response against tumors still encounters challenges such as low response rates and off-target effects. Pyroptosis, an immunogenic cell death (ICD) mechanism, holds the potential to overcome the limitations of ICB by activating and recruiting immune cells. However, the expression of the pyroptosis-related protein Gasdermin-E(GSDME) in some tumors is limited due to mRNA methylation. To overcome this obstacle, sialic acid-functionalized liposomes coloaded with decitabine, a demethylation drug, and triclabendazole, a pyroptosis-inducing drug are developed. This nanosystem primarily accumulates at tumor sites via sialic acid and the Siglec receptor, elevating liposome accumulation in tumors up to 3.84-fold at 24 h and leading to the upregulation of pyroptosis-related proteins and caspase-3/GSDME-dependent pyroptosis. Consequently, it facilitates the infiltration of CD8+ T cells into the tumor microenvironment and enhances the efficacy of ICB therapy. The tumor inhibition rate of the treatment group is 89.1% at 21 days. This study highlights the potential of sialic acid-functionalized pyroptosis nanotuners as a promising approach for improving the efficacy of ICB therapy in tumors with low GSDME expression through epigenetic alteration and ICD.

Robust EMI elimination for RF shielding-free MRI through deep learning direct MR signal prediction.

PURPOSE: To develop a new electromagnetic interference (EMI) elimination strategy for RF shielding-free MRI via active EMI sensing and deep learning direct MR signal prediction (Deep-DSP). METHODS: Deep-DSP is proposed to directly predict EMI-free MR signals. During scanning, MRI receive coil and EMI sensing coils simultaneously sample data within two windows (i.e., for MR data and EMI characterization data acquisition, respectively). Afterward, a residual U-Net model is trained using synthetic MRI receive coil data and EMI sensing coil data acquired during EMI signal characterization window, to predict EMI-free MR signals from signals acquired by MRI receive and EMI sensing coils. The trained model is then used to directly predict EMI-free MR signals from data acquired by MRI receive and sensing coils during the MR signal-acquisition window. This strategy was evaluated on an ultralow-field 0.055T brain MRI scanner without any RF shielding and a 1.5T whole-body scanner with incomplete RF shielding. RESULTS: Deep-DSP accurately predicted EMI-free MR signals in presence of strong EMI. It outperformed recently developed EDITER and convolutional neural network methods, yielding better EMI elimination and enabling use of few EMI sensing coils. Furthermore, it could work well without dedicated EMI characterization data. CONCLUSION: Deep-DSP presents an effective EMI elimination strategy that outperforms existing methods, advancing toward truly portable and patient-friendly MRI. It exploits electromagnetic coupling between MRI receive and EMI sensing coils as well as typical MR signal characteristics. Despite its deep learning nature, Deep-DSP framework is computationally simple and efficient.

Life's Essential 8, genetic susceptibility, and the risk of psoriatic disease: a prospective cohort study.

BACKGROUND: Psoriatic disease (PsD) is closely associated with cardiovascular diseases. The Life's Essential 8 (LE8) score is a new metric for assessing cardiovascular health (CVH), where a higher score indicates better CVH. However, the longitudinal association between LE8 score and the risk of PsD remains uncertain. The main aim of the present study was to explore the association between LE8 scores and the risk of PsD. OBJECTIVE: To investigate the associations between LE8 score, genetic susceptibility, and the risk of PsD within a cohort design. METHODS: This cohort study included 261,642 participants from the UK Biobank without PsD at baseline. LE8 comprises eight indicators: diet, physical activity, nicotine exposure, sleep health, body mass index, blood lipids, blood glucose, and blood pressure. Cox proportional hazard models were employed to examine the association between the participants' LE8 scores, PsD genetic risk, and the risk of PsD. Hazard ratios (HRs) and 95% confidential intervals (CIs) were calculated. RESULTS: During an average follow-up of 12.32 years, 1,501 participants developed PsD. Compared to participants with low LE8 scores, the HRs (95% CIs) of developing PsD for those with moderate and high LE8 scores were 0.51 (0.43, 0.59) and 0.34 (0.27, 0.42) after adjustments, respectively. Dose-response analysis revealed a linear negative association between continuous LE8 score and the risk of developing PsD (P < 0.001), with no evidence of non-linear association detected. The genetic susceptibility to PsD did not modify this association (P for interaction = 0.63). Subgroup analyses revealed that women demonstrated a more pronounced beneficial association between LE8 scores and PsD risk (P for interaction = 0.02). CONCLUSIONS: Our study suggests that a higher LE8 score, regardless of genetic risk, was associated with a lower risk of PsD, particularly among women. Consequently, maintaining a high CVH status is recommended to prevent PsD and assess associated risks.

Sialic Acid-Modified O-GlcNAc Transferase Inhibitor Liposome Presents Antitumor Effect in Hepatocellular Carcinoma.

O-linked-N-acetylglucosaminylation (O-GlcNAcylation) plays a key role in hepatocellular carcinoma (HCC) development, and the inhibition of O-GlcNAcylation has therapeutic potential. To decrease the systemic adverse events and increase targeting, we used sialic acid (SA)-decorated liposomes loaded with OSMI-1, an inhibitor of the O-GlcNAcylation, to further improve the anti-HCC effect. Fifty pairs of HCC tissue samples and the cancer genome atlas database were used to analyze the expression of O-GlcNAc transferase (OGT) and its effects on prognosis and immune cell infiltration. OSMI-1 cells were treated with SA and liposomes. Western blotting, immunofluorescence, cell proliferation assay, flow cytometry, enzyme-linked immunosorbent assay, immunohistochemistry, and tumorigenicity assays were used to investigate the antitumor effect of SA-modified OSMI-1 liposomes in vitro and in vivo. OGT was highly expressed in HCC tissues, negatively correlated with the degree of tumor infiltration of CD8+ and CD4+T cells and prognosis, and positively correlated with the degree of Treg cell infiltration. SA-modified OSMI-1 liposome (OSMI-1-SAL) was synthesized with stable hydrodynamic size distribution. Both in vitro and in vivo, OSMI-1-SAL exhibited satisfactory biosafety and rapid uptake by HCC cells. Compared to free OSMI-1, OSMI-1-SAL had a stronger capacity for suppressing the proliferation and promoting the apoptosis of HCC cells. Moreover, OSMI-1-SAL effectively inhibited tumor initiation and development in mice. OSMI-1-SAL also promoted the release of damage-associated molecular patterns, including anticalreticulin, high-mobility-group protein B1, and adenosine triphosphate, from HCC cells and further promoted the activation and proliferation of the CD8+ and CD4+T cells. In conclusion, the OSMI-1-SAL synthesized in this study can target HCC cells, inhibit tumor proliferation, induce tumor immunogenic cell death, enhance tumor immunogenicity, and promote antitumor immune responses, which has the potential for clinical application in the future.

Parallel imaging reconstruction using spatial nulling maps.

PURPOSE: To develop a robust parallel imaging reconstruction method using spatial nulling maps (SNMs). METHODS: Parallel reconstruction using null operations (PRUNO) is a k-space reconstruction method where a k-space nulling system is derived using null-subspace bases of the calibration matrix. ESPIRiT reconstruction extends the PRUNO subspace concept by exploiting the linear relationship between signal-subspace bases and spatial coil sensitivity characteristics, yielding a hybrid-domain approach. Yet it requires empirical eigenvalue thresholding to mask the coil sensitivity information and is sensitive to signal- and null-subspace division. In this study, we combine the concepts of null-subspace PRUNO and hybrid-domain ESPIRiT to provide a more robust reconstruction method that extracts null-subspace bases of calibration matrix to calculate image-domain SNMs. Multi-channel images are reconstructed by solving an image-domain nulling system formed by SNMs that contain both coil sensitivity and finite image support information, therefore, circumventing the masking-related procedure. The proposed method was evaluated with multi-channel 2D brain and knee data and compared to ESPIRiT. RESULTS: The proposed hybrid-domain method produced quality reconstruction highly comparable to ESPIRiT with optimal manual masking. It involved no masking-related manual procedure and was tolerant of the actual division of null- and signal-subspace. Spatial regularization could be also readily incorporated to reduce noise amplification as in ESPIRiT. CONCLUSION: We provide an efficient hybrid-domain reconstruction method using multi-channel SNMs that are calculated from coil calibration data. It eliminates the need for coil sensitivity masking and is relatively insensitive to subspace separation, therefore, presenting a robust parallel imaging reconstruction procedure in practice.

Calibrationless reconstruction of uniformly-undersampled multi-channel MR data with deep learning estimated ESPIRiT maps.

PURPOSE: To develop a truly calibrationless reconstruction method that derives An Eigenvalue Approach to Autocalibrating Parallel MRI (ESPIRiT) maps from uniformly-undersampled multi-channel MR data by deep learning. METHODS: ESPIRiT, one commonly used parallel imaging reconstruction technique, forms the images from undersampled MR k-space data using ESPIRiT maps that effectively represents coil sensitivity information. Accurate ESPIRiT map estimation requires quality coil sensitivity calibration or autocalibration data. We present a U-Net based deep learning model to estimate the multi-channel ESPIRiT maps directly from uniformly-undersampled multi-channel multi-slice MR data. The model is trained using fully-sampled multi-slice axial brain datasets from the same MR receiving coil system. To utilize subject-coil geometric parameters available for each dataset, the training imposes a hybrid loss on ESPIRiT maps at the original locations as well as their corresponding locations within the standard reference multi-slice axial stack. The performance of the approach was evaluated using publicly available T1-weighed brain and cardiac data. RESULTS: The proposed model robustly predicted multi-channel ESPIRiT maps from uniformly-undersampled k-space data. They were highly comparable to the reference ESPIRiT maps directly computed from 24 consecutive central k-space lines. Further, they led to excellent ESPIRiT reconstruction performance even at high acceleration, exhibiting a similar level of errors and artifacts to that by using reference ESPIRiT maps. CONCLUSION: A new deep learning approach is developed to estimate ESPIRiT maps directly from uniformly-undersampled MR data. It presents a general strategy for calibrationless parallel imaging reconstruction through learning from the coil and protocol-specific data.

Radical Decarboxylative Carbon-Nitrogen Bond Formation.

The carbon-nitrogen bond is one of the most prevalent chemical bonds in natural and artificial molecules, as many naturally existing organic molecules, pharmaceuticals, agrochemicals, and functional materials contain at least one nitrogen atom. Radical decarboxylative carbon-nitrogen bond formation from readily available carboxylic acids and their derivatives has emerged as an attractive and valuable tool in modern synthetic chemistry. The promising achievements in this research topic have been demonstrated via utilizing this strategy in the synthesis of complex natural products. In this review, we will cover carbon-nitrogen bond formation via radical decarboxylation of carboxylic acids, Barton esters, MPDOC esters, N-hydroxyphthalimide esters (NHP esters), oxime esters, aryliodine(III) dicarboxylates, and others, respectively. This review aims to bring readers a comprehensive survey of the development in this rapidly expanding field. We hope that this review will emphasize the knowledge, highlight the proposed mechanisms, and further disclose the fascinating features in modern synthetic applications.

Identification of invasion-metastasis associated MiRNAs in gallbladder cancer by bioinformatics and experimental validation.

BACKGROUND: Recent studies exploring the roles of invasion-metastasis associated miRNAs in gallbladder cancer (GBC) are limited. In the study, we aimed to identify the invasion-metastasis associated miRNAs in GBC by bioinformatics and experimental validation. METHODS: MiRNAs of different expression were identified by comparing GBC tumor samples with different survival from Gene Expression Omnibus database. MiRTarBase was used for identifying the potential target genes of miRNAs. Then, we performed Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. And miRNA-gene and protein-protein interaction (PPI) network were constructed for hub genes evaluation. We further explored and compared miR-642a-3p and miR-145-5p expression in both The Cancer Genome Atlas database and our hospital data. Finally, quantitative real-time PCR, wound healing assay, and Transwell assay were conducted to validate the invasion-metastasis associated miRNAs in GBC. RESULTS: In GSE104165 database, 25 up-regulated and 97 down-regulated miRNAs were detected with significantly different expression in GBC tumor samples. Then, 477 potential target genes were identified from the 2 most up-regulated miRNAs (miR-4430 and miR-642a-3p) and 268 genes from the 2 most down-regulated miRNAs (miR-451a and miR-145-5p). After GO and KEGG analysis, mTOR and PI3K-Akt signaling pathways were found associated with the potential target genes. Based on PPI network, the top 10 highest degree hub nodes were selected for hub genes. Furthermore, the miRNA-hub gene network showed significant miR-642a-3p up-regulation and miR-145-5p down-regulation in both GBC tissues and cell lines. In the experimental validation, miR-145-5p up-regulation and miR-642a-3p down-regulation were confirmed to suppress GBC invasion and metastasis. CONCLUSIONS: MiR-642a-3p and miR-145-5p were identified as invasion-metastasis associated miRNAs via bioinformatics and experimental validation, and both up-regulation of miR-642a-3p and down-regulation of miR-145-5p would be served as novel treatment options for GBC in the future.

Inhibition of AMPK/PFKFB3 mediated glycolysis synergizes with penfluridol to suppress gallbladder cancer growth.

BACKGROUND: Penfluridol (PF) is an FDA-approved antipsychotic drug that has recently been shown to have anticancer activity. However, the anticancer effects and underlying mechanisms of PF are not well-established in gallbladder cancer (GBC). METHODS: The anticancer efficacy of PF on GBC was investigated via a series of cell functions experiments, including cell viability, colony formation, apoptosis assays, and so on. The corresponding signaling changes after PF treatment were explored by western blotting. Then, nude mice were utilized to study and test the anticancer activity of PF in vivo. Besides, glucose consumption and lactic production assays were used to detect the glycolysis alteration. RESULTS: In this study, we discovered that PF greatly inhibited the proliferation and invasion ability of GBC cells (GBCs). The glucose consumption and lactic generation ability of GBCs were dramatically elevated following PF treatment. Additionally, we discovered that inhibiting glycolysis could improve PF's anticancer efficacy. Further studies established that the activation of the AMPK/PFKFB3 signaling pathway medicated glycolysis after PF treatment. We proved mechanistically that inhibition of AMPK/PFKFB3 singling pathway mediated glycolysis was a potential synergetic strategy to improve the anticancer efficacy of PF on GBC. CONCLUSIONS: By inhibiting AMPK, the anticancer effects of PF on GBCs were amplified. As a result, our investigations shed new light on the possibility of repurposing PF as an anticancer drug for GBC, and AMPK inhibition in combination with PF may represent a novel therapeutic strategy for GBC. Video abstract.

Adjuvant transarterial chemoembolization to sorafenib in unresectable hepatocellular carcinoma: A meta-analysis.

BACKGROUND AND AIM: An increasing number of transarterial chemoembolization (TACE) plus sorafenib combination therapy has been applied for unresectable hepatocellular carcinoma (HCC). However, it remains controversial whether combination therapy is superior to sorafenib monotherapy. Therefore, we aimed to perform a meta-analysis to evaluate the efficacy and safety of the combination therapy of TACE plus sorafenib for unresectable HCC. METHODS: This meta-analysis was based on the relative outcomes from a specific search of online databases between January 2008 and November 2019, and subgroup analyses were conducted to identify potential predictive factors. RESULTS: A total of 3868 patients (TACE plus sorafenib vs sorafenib, 1181 vs 2687) were identified from nine studies, including one randomized controlled trial and eight retrospective cohort studies. The pooled results revealed that TACE plus sorafenib combination therapy significantly improves overall survival with the combined hazard ratio 0.74 (95% confidence interval [CI] = 0.66-0.84, P < 0.001), time to progression (hazard ratio = 0.73, 95%CI = 0.65-0.82, P < 0.001), and objective response rate (odds ratio = 2.19, 95% CI = 1.31-3.66, P = 0.003). Subgroup analysis indicated that patients who developed macrovascular invasion achieve significantly great overall survival (P for interaction = 0.001) with combination therapy, in contrast to nonmacrovascular invasion patients. In addition, no significant differences in adverse events were observed. CONCLUSION: This meta-analysis demonstrated that TACE plus sorafenib combination therapy is superior to sorafenib monotherapy and should be recommended as an optimal treatment choice for unresectable HCC.

Role of cellular, molecular and tumor microenvironment in hepatocellular carcinoma: Possible targets and future directions in the regorafenib era.

Hepatocellular carcinoma (HCC) remains as one of the major causes of cancer-related mortality, despite the recent development of new therapeutic options. Regorafenib, an oral multikinase inhibitor, is the first systemic therapy that has a survival benefit for patients with advanced HCC that have a poor response to sorafenib. Even though regorafenib has been approved by the FDA, the clinical trial for regorafenib treatment does not show significant improvement in overall survival. The impaired efficacy of regorafenib caused by various resistance mechanisms, including epithelial-mesenchymal transitions, inflammation, angiogenesis, hypoxia, oxidative stress, fibrosis and autophagy, still needs to be resolved. In this review, we provide insight on regorafenib microenvironmental, molecular and cellular mechanisms and interactions in HCC treatment. The aim of this review is to help physicians select patients that would obtain the maximal benefits from regorafenib in HCC therapy.

Explore the relationship between fish community and environmental factors by machine learning techniques.

In the face of multiple habitat alterations originating from both natural and anthropogenic factors, the fast-changing environments pose significant challenges for maintaining ecosystem integrity. Machine learning is a powerful tool for modeling complex non-linear systems through exploratory data analysis. This study aims at exploring a machine learning-based approach to relate environmental factors with fish community for achieving sustainable riverine ecosystem management. A large number of datasets upon a wide variety of eco-environmental variables including river flow, water quality, and species composition were collected at various monitoring stations along the Xindian River of Taiwan during 2005 and 2012. Then the complicated relationship and scientific essences of these heterogonous datasets are extracted using machine learning techniques to have a more holistic consideration in searching a guiding reference useful for maintaining river-ecosystem integrity. We evaluate and select critical environmental variables by the analysis of variance (ANOVA) and the Gamma test (GT), and then we apply the adaptive network-based fuzzy inference system (ANFIS) for an estimation of fish bio-diversity using the Shannon Index (SI). The results show that the correlation between model estimation and the biodiversity index is higher than 0.75. The GT results demonstrate that biochemical oxygen demand (BOD), water temperature, total phosphorus (TP), and nitrate-nitrogen (NO3-N) are important variables for biodiversity modeling. The ANFIS results further indicate lower BOD, higher TP, and larger habitat (flow regimes) would generally provide a more suitable environment for the survival of fish species. The proposed methodology not only possesses a robust estimation capacity but also can explore the impacts of environmental variables on fish biodiversity. This study also demonstrates that machine learning is a promising avenue toward sustainable environmental management in river-ecosystem integrity.

Autonomous Exploration and Map Construction of a Mobile Robot Based on the TGHM Algorithm.

An a priori map is often unavailable for a mobile robot in a new environment. In a large-scale environment, relying on manual guidance to construct an environment map will result in a huge workload. Hence, an autonomous exploration algorithm is necessary for the mobile robot to complete the exploration actively. This study proposes an autonomous exploration and mapping method based on an incremental caching topology-grid hybrid map (TGHM). Such an algorithm can accomplish the exploration task with high efficiency and high coverage of the established map. The TGHM is a fusion of a topology map, containing the information gain and motion cost for exploration, and a grid map, representing the established map for navigation and localization. At the beginning of one exploration round, the method of candidate target point generation based on geometry rules are applied to extract the candidates quickly. Then, a TGHM is established, and the information gain is evaluated for each candidate topology node on it. Finally, the node with the best evaluation value is selected as the next target point and the topology map is updated after each motion towards it as the end of this round. Simulations and experiments were performed to benchmark the proposed algorithm in robot autonomous exploration and map construction.

IL-27 Alleviates Airway Inflammation and Airway Hyperresponsiveness in Asthmatic Mice by Targeting the CD39/ATP Axis of Dendritic Cells.

Interleukin-27 receptor (IL-27R) is expressed in a variety of immune cells and structural cells, including dendritic cells. The mechanism of IL-27 in asthma has not been fully elucidated. This study aimed to examine whether IL-27 regulated the CD39/ATP axis of dendritic cells in asthma. Our results showed that in ovalbumin (OVA)-induced asthma mouse model, IL-27Rα-/- asthmatic mice showed increased airway resistance, increased infiltration of inflammatory cells in lung tissue, proliferation of goblet cells, enhanced expression of Muc5 AC around airway epithelium, increased total number of cells and eosinophils, increased levels of total IgE, OVA-IgE, IL-4, IL-5, IL-13 and IL-17 A, and increased expression of transcription factors GATA-3 and RORγt in lung tissue. The expression of CD39 mRNA and protein in the lung tissue of IL-27Rα-/- asthmatic mice decreased, and the expression of NLRP3, ASC and Caspase-1 in NLRP3 inflammasome components increased. The concentration of ATP was significantly increased compared with WT asthmatic mice. In vitro experiments showed that the expression of CD39 in lung dendritic cells of IL-27Rα-/- asthmatic mice decreased, while the expression of NLRP3 inflammasome components NLRP3, ASC and Caspase-1 increased. These findings indicate that IL-27 directly and indirectly regulates immunoinflammatory responses in asthma by acting on dendritic cells CD39/ATP Axis.

Corrigendum to "A novel FGFR1 inhibitor CYY292 suppresses tumor progression, invasion, and metastasis of glioblastoma by inhibiting the Akt/GSK3ß/snail signaling axis" [Genes & Diseases 11 (2024) 479-494].

[This corrects the article DOI: 10.1016/j.gendis.2023.02.035.].

A novel FGFR1 inhibitor CYY292 suppresses tumor progression, invasion, and metastasis of glioblastoma by inhibiting the Akt/GSK3ß/snail signaling axis.

Glioblastoma (GBM) is a malignant brain tumor that grows quickly, spreads widely, and is resistant to treatment. Fibroblast growth factor receptor (FGFR)1 is a receptor tyrosine kinase that regulates cellular processes, including proliferation, survival, migration, and differentiation. FGFR1 was predominantly expressed in GBM tissues, and FGFR1 expression was negatively correlated with overall survival. We rationally designed a novel small molecule CYY292, which exhibited a strong affinity for the FGFR1 protein in GBM cell lines in vitro. CYY292 also exerted an effect on the conserved Ser777 residue of FGFR1. CYY292 dose-dependently inhibited cell proliferation, epithelial-mesenchymal transition, stemness, invasion, and migration in vitro by specifically targeting the FGFR1/AKT/Snail pathways in GBM cells, and this effect was prevented by pharmacological inhibitors and critical gene knockdown. In vivo experiments revealed that CYY292 inhibited U87MG tumor growth more effectively than AZD4547. CYY292 also efficiently reduced GBM cell proliferation and increased survival in orthotopic GBM models. This study further elucidates the function of FGFR1 in the GBM and reveals the effect of CYY292, which targets FGFR1, on downstream signaling pathways directly reducing GBM cell growth, invasion, and metastasis and thus impairing the recruitment, activation, and function of immune cells.

Inflammatory Microenvironment-Responsive Hydrogels Enclosed with Quorum Sensing Inhibitor for Treating Post-Traumatic Osteomyelitis.

Non-antibiotic strategies are desperately needed to treat post-traumatic osteomyelitis (PTO) due to the emergence of superbugs, complex inflammatory microenvironments, and greatly enriched biofilms. Previously, growing evidence indicated that quorum sensing (QS), a chemical communication signal among bacterial cells, can accelerate resistance under evolutionary pressure. This study aims to develop a medical dressing to treat PTO by inhibiting QS and regulating the inflammatory microenvironment, which includes severe oxidative stress and acid abscesses, through a reactive oxygen species (ROS)-responsive bond between N1- (4-borobenzoyl)-N3-(4-borobenzoyl)-the N1, the N1, N3, N3-tetramethylpropane-1,3-diamine (TSPBA) and polyvinyl alcohol (PVA), and the amino side chain of hyperbranched polylysine (HBPL). Physically enclosed QS inhibitors subsequently exerted the antibacterial effects. This hydrogel can scavenge hydrogen peroxide (H2O2), superoxide anion free radical (·O2 -), hydroxyl radicals (·OH) and 2,2-di(4-tert-octylphenyl)-1-picryl-hydrazyl (DPPH) to reduce oxidative stress and inhibit "bacteria-to-bacteria communication", thus clearing planktonic bacteria and biofilms, accelerating bacterial plasmolysis, reducing bacterial virulence and interfering with membrane transport. After in vivo treatment with hydrogel, nearly all bacteria are eliminated, inflammation is effectively inhibited, and osteogenesis and bone repair are promoted to facilitate recovery from PTO. The work demonstrates the clinical translational potential of the hydrogel in the treatment of drug-resistant bacteria induced PTO.

An injectable thermosensitive hyaluronic acid/pluronic F-127 hydrogel for deep penetration and combination therapy of frozen shoulder.

Frozen shoulder (FS) is a common and progressive shoulder disorder that causes glenohumeral joint stiffness, characterized by inflammation and fibrosis. The treatment options are quite limited, and the therapeutic response is hindered by the fibrous membrane formed by excessive collagen and the rapid removal by synovial fluid. To address these challenges, we designed a hyaluronic acid/Pluronic F-127 (HP)-based injectable thermosensitive hydrogel as a drug carrier loaded with dexamethasone and collagenase (HPDC). We screened for an optimal HP hydrogel that can sustain drug release for approximately 10 days both in vitro and in vivo. In the meanwhile, we found that HP hydrogel could inhibit the proliferation and diminish the adhesion capacity of rat synovial cells induced by transforming growth factor-ß1. Furthermore, using an established immobilization rat model of FS, intra-articular injection of HPDC significantly improved joint range of motion compared to medication alone. Relying on sustained drug release, the accumulated collagen fibers were degraded by collagenase to promote the deep delivery of dexamethasone. These findings showed a positive combined treatment effect of HPDC, providing a novel idea for the comprehensive treatment of FS.