An injectable exosome-loaded hyaluronic acid-polylysine hydrogel for cardiac repair via modulating oxidative stress and the inflammatory microenvironment.

Myocardial infarction (MI) is a serious cardiovascular disease with complex complications and high lethality. Currently, exosome (Exo) therapy has emerged as a promising treatment of ischemic MI due to its antioxidant, anti-inflammatory, and vascular abilities. However, traditional Exo delivery lacks spatiotemporal precision and targeting of microenvironment modulation, making it difficult to localize the lesion site for sustained effects. In this study, an injectable oxidized hyaluronic acid-polylysine (OHA-PL) hydrogel was developed to conveniently load adipose-derived mesenchymal stem cell exosomes (ADSC-Exos) and improve their retention under physiological conditions. The OHA-PL@Exo hydrogel with high spatiotemporal precision is transplanted minimally invasively into the ischemic myocardium to scavenge intracellular and extracellular reactive oxygen species, regulate macrophage polarization, and attenuate inflammation in the early phase of MI. In addition, this synergistic microenvironment modulation can effectively reduce myocardial fibrosis and ventricular remodeling, promote angiogenesis, and restore electrophysiological function in the late stage of MI. Therefore, this hyaluronic acid-polylysine to deliver exosomes has become a promising therapeutic strategy for myocardial repair.

Enhancing cell cryopreservation with acidic polyamino acids integrated liquid marbles.

Cryopreservation is highly desired for long-term maintenance of the viability of living biosamples, while effective cell cryopreservation still relies heavily on the addition of dimethyl sulfoxide (DMSO) and fetal bovine serum (FBS). However, the intrinsic toxicity of DMSO is still a bottleneck, which could not only cause the clinical side effect but also induce cell genetic variants. In the meantime, the addition of FBS may bring potentially the risk of pathogenic microorganism contamination. The liquid marbles (LMs), a novel biotechnology tool for cell cryopreservation, which not only have a small volume system that facilitated recovery, but the hydrophobic shell also resisted the harm to cells caused by adverse environments. Previous LM-based cell cryopreservation relied heavily on the addition of FBS. In this work, we introduced acidic polyaspartic acid and polyglutamic acid as cryoprotectants to construct LM systems. LMs could burst in an instant to facilitate and achieve ultrarapid recovery process, and the hydrophilic carboxyl groups of the cryoprotectants could form hydrogen bonds with water molecules and further inhibit ice growth/formation to protect cells from cryoinjuries. The L929 cells could be well cryopreserved by acidic polyamino acid-based LMs. This new biotechnology platform is expected to be widely used for cell cryopreservation, which has the potential to propel LMs for the preservation of various functional cells in the future.

Exploration of the combined role of immune checkpoints and immune cells in the diagnosis and treatment of ankylosing spondylitis: a preliminary study immune checkpoints in ankylosing spondylitis.

OBJECTIVE: Immune checkpoints have emerged as promising therapeutic targets for autoimmune diseases. However, the specific roles of immune checkpoints in the pathophysiology of ankylosing spondylitis (AS) remain unclear. METHODS: Hip ligament samples were obtained from two patient groups: those with AS and femoral head deformity, and those with femoral head necrosis but without AS, undergoing hip arthroplasty. Label-Free Quantification (LFQ) Protein Park Analysis was used to identify the protein composition of the ligaments. Peripheral blood samples of 104 AS patients from public database were used to validate the expression of key proteins. KEGG, GO, and GSVA were employed to explore potential pathways regulated by immune checkpoints in AS progression. xCell was used to calculate cell infiltration levels, LASSO regression was applied to select key cells, and the correlation between immune checkpoints and immune cells was analyzed. Drug sensitivity analysis was conducted to identify potential therapeutic drugs targeting immune checkpoints in AS. The expression of key genes was validated through immunohistochemistry (IHC). RESULTS: HLA-DMB and HLA-DPA1 were downregulated in the ligaments of AS and this has been validated through peripheral blood datasets and IHC. Significant differences in expression were observed in CD8 + Tcm, CD8 + T cells, CD8 + Tem, osteoblasts, Th1 cells, and CD8 + naive T cells in AS. The infiltration levels of CD8 + Tcm and CD8 + naive T cells were significantly positively correlated with the expression levels of HLA-DMB and HLA-DPA1. Immune cell selection using LASSO regression showed good predictive ability for AS, with AUC values of 0.98, 0.81, and 0.75 for the three prediction models, respectively. Furthermore, this study found that HLA-DMB and HLA-DPA1 are involved in Th17 cell differentiation, and both Th17 cell differentiation and the NF-kappa B signaling pathway are activated in the AS group. Drug sensitivity analysis showed that AS patients are more sensitive to drugs such as doramapimod and GSK269962A. CONCLUSION: Immune checkpoints and immune cells could serve as avenues for exploring diagnostic and therapeutic strategies for AS.

Chemically Programmed Hydrogels for Spatiotemporal Modulation of the Cardiac Pathological Microenvironment.

After myocardial infarction (MI), sustained ischemic events induce pathological microenvironments characterized by ischemia-hypoxia, oxidative stress, inflammatory responses, matrix remodeling, and fibrous scarring. Conventional clinical therapies lack spatially targeted and temporally responsive modulation of the infarct microenvironment, leading to limited myocardial repair. Engineered hydrogels have a chemically programmed toolbox for minimally invasive localization of the pathological microenvironment and personalized responsive modulation over different pathological periods. Chemically programmed strategies for crosslinking interactions, interfacial binding, and topological microstructures in hydrogels enable minimally invasive implantation and in situ integration tailored to the myocardium. This enhances substance exchange and signal interactions within the infarcted microenvironment. Programmed responsive polymer networks, intelligent micro/nanoplatforms, and biological therapeutic cues contribute to the formation of microenvironment-modulated hydrogels with precise targeting, spatiotemporal control, and on-demand feedback. Therefore, this review summarizes the features of the MI microenvironment and chemically programmed schemes for hydrogels to conform, integrate, and modulate the cardiac pathological microenvironment. Chemically programmed strategies for oxygen-generating, antioxidant, anti-inflammatory, provascular, and electrointegrated hydrogels to stimulate iterative and translational cardiac tissue engineering are discussed.

Aluminium-doped Carbon Dots for the Simultaneous Selective Detection of Five Tetracycline Antibiotics.

In this paper, the aluminium-doped carbon dots (Al-CDs) were developed for simultaneous selective detection of five tetracycline antibiotics (TCs), including minocycline (MC), tetracycline (TC), oxytetracycline (OTC), doxycycline (DOC) and chlortetracycline (CTC). With the bright blue fluorescence, Al-CDs displayed excellent stability and showed no obvious fluorescence intensity changes under different ionic strength, acidic or alkaline environment, continuous ultraviolet light illumination, and even longtime storage at room temperature. As adding different antibiotics, the fluorescence of Al-CDs was strongly quenched by five TCs and showed no distinguished changes with the addition of other kinds of antibiotics. The presence of interferential metal ions, anions and small organic molecules imposed no effect on the simultaneous selective detection of five TCs. A good linear relationship was achieved for five TCs in the range of 0-100 µM, and the limit of detection for MC, TC, OTC, DOC, and CTC were 13.91 (0-100 µM), 15.54 (0-100 µM), 14.26 (0-100 µM), 13.48 (0-100 µM) and 13.88 nM (0-100 µM), respectively. Moreover, Al-CDs was successfully used to the detection of five TCs in real samples with recovery ranging from 92.47% to 122.05%, confirming a bright future for the practical applications in the assays of foods, medicines, and environments.

Chronological-Programmed Black Phosphorus Hydrogel for Responsive Modulation of the Pathological Microenvironment in Myocardial Infarction.

Electroactive hydrogels have garnered extensive interest as a promising approach to myocardial tissue engineering. However, the challenges of spatiotemporal-specific modulation of individual pathological processes and achieving nontoxic bioresorption still remain. Herein, inspired by the entire postinfarct pathological processes, an injectable conductive bioresorbable black phosphorus nanosheets (BPNSs)-loaded hydrogel (BHGD) was developed via reactive oxide species (ROS)-sensitive disulfide-bridge and photomediated cross-linking reaction. Significantly, the chronologically programmed BHGD hydrogel can achieve graded modulation during the inflammatory, proliferative, and maturation phases of myocardial infarction (MI). More details, during early infarction, the BHGD hydrogel can effectively reduce ROS levels in the MI area, inhibit cellular oxidative stress damage, and promote macrophage M2 polarization, creating a favorable environment for damaged myocardium repair. Meanwhile, the ROS-responsive structure can protect BPNSs from degradation and maintain good conductivity under MI microenvironments. Therefore, the BHGD hydrogel possesses tissue-matched modulus and conductivity in the MI area, facilitating cardiomyocyte maturation and electrical signal exchange, compensating for impaired electrical signaling, and promoting vascularization in infarcted areas in the maturation phase. More importantly, all components of the hydrogel degrade into nontoxic substances without adverse effects on vital organs. Overall, the presented BPNS-loaded hydrogel offers an expandable and safe option for clinical treatment of MI.

Large-Scale Fabrication of Freestanding Polymer Ultrathin Porous Membranes for Transparent Transwell Coculture Systems.

Advancements in cell coculture systems with porous membranes have facilitated the simulation of human-like in vitro microenvironments for diverse biomedical applications. However, conventional Transwell membranes face limitations in low porosity (ca. 6%) and optical opacity due to their large thickness (ca. 10 µm). In this study, we demonstrated a one-step, large-scale fabrication of freestanding polymer ultrathin porous (PUP) membranes with thicknesses of hundreds of nanometers. PUP membranes were produced by using a gap-controlled bar-coating process combined with polymer blend phase separation. They are 20 times thinner than Transwell membranes, possessing 3-fold higher porosity and exhibiting high transparency. These membranes demonstrate outstanding molecular permeability and significantly reduce the cell-cell distance, thereby facilitating efficient signal exchange pathways between cells. This research enables the establishment of a cutting-edge in vitro cell coculture system, enhancing optical transparency, and streamlining the large-scale manufacturing of porous membranes.

First-Principles Studies on Transition Metal Doped Mo2B2 as Anode Material for Li-Ion Batteries.

New two-dimensional (2D) transition-metal borides have attracted considerable interest in research on electrode materials for Li-ion batteries (LIBs) owing to their promising properties. In this study, 2D molybdenum boride (Mo2 B2 ) with and without transition metal (TM, TM=Mn, Fe, Co, Ni, Ru, and Pt) atom doping was investigated. Our results indicated that all TM-doped Mo2 B2 samples exhibited excellent electronic conductivity, similar to the intrinsic 2D Mo2 B2 metal behavior, which is highly beneficial for application in LIBs. Moreover, we found that the diffusion energy barriers of Li along paths 1 and 2 for all TM-doped Mo2 B2 samples are smaller than 0.30 and 0.24 eV of the pristine Mo2 B2 . In particular, for 2D Co-doped Mo2 B2 , the diffusion energy barriers of Li along paths 1 and 2 are reduced to 0.14 and 0.11 eV, respectively, making them the lowest Li diffusion barriers in both paths 1 and 2. This indicates that TM doping can improve the electrochemical performance of 2D Mo2 B2 and that Co-doped Mo2 B2 is a promising electrode material for LIBs. Our work not only identifies electrode materials with promising electrochemical performance but also provides guidance for the design of high-performance electrode materials for LIBs.

Injectable Asymmetric Adhesive-Antifouling Bifunctional Hydrogel for Peritoneal Adhesion Prevention.

Peritoneal adhesion is a common problem after abdominal surgery and can lead to various medical problems. In response to the lack of in situ retention and pro-wound healing properties of existing anti-adhesion barriers, this work reports an injectable adhesive-antifouling bifunctional hydrogel (AAB-hydrogel). This AAB-hydrogel can be constructed by "two-step" injection. The tissue adhesive hydrogel based on gallic acid-modified chitosan and aldehyde-modified dextran is prepared as the bottom hydrogel (B-hydrogel) by Schiff base reaction. The aldehyde-modified zwitterionic dextran/carboxymethyl chitosan-based hydrogel is formed on the B-hydrogel surface as the antifouling top hydrogel (T-hydrogel). The AAB-hydrogel exhibits good bilayer binding and asymmetric properties, including tissue adhesive, antifouling, and antimicrobial properties. To evaluate the anti-adhesion effect in vivo, the prepared hydrogels are injected onto the wound surface of a mouse abdominal wall abrasion-cecum defect model. Results suggest that the AAB-hydrogel has antioxidant capacity and can reduce the postoperative inflammatory response by modulating the macrophage phenotype. Moreover, the AAB-hydrogel could effectively inhibit the formation of postoperative adhesions by reducing protein deposition, and resisting fibroblast adhesions and bacteria attacking. Therefore, AAB-hydrogel is a promising candidate for the prevention of postoperative peritoneal adhesions.

An Important Role in Novel Immune Mechanism and Diagnostic Model of Ankylosing Spondylitis: The CeRNA-ADRB2 Network.

Objective: The mechanism of ankylosing spondylitis (AS) remains unclear, and clinical diagnosis still pose challenges. This study aims to explore potential regulatory mechanisms underlying AS and develop a novel diagnostic model. Methods: Interspinous ligament (ISL) tissues were collected from control samples and ankylosing spondylitis with kyphotic deformity (AS-KD) samples during surgery, followed by high-throughput sequencing. By integrating gene expression profiles from publicly available AS peripheral blood (PB) samples, differentially expressed immune genes (DEIRGs) were identified. Through gene set enrichment analysis(GSEA), gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, the regulatory mechanisms of the immune gene family in AS were explored. A diagnostic model for AS were constructed and validated it externally. Additionally, a competing endogenous RNA(ceRNA)-protein regulatory network was built for key immune genes. Results: Adrenergic receptor beta 2 (ADRB2) was downregulated in both ISL and PB samples. It was enriched in common pathways, including natural killer cell-mediated cytotoxicity, B cell receptor signaling pathway, Th1 and Th2 cell differentiation. Using the LASSO algorithm, 12 DEIRGs were identified, including the downregulated ADRB2. Based on the DEIRGs family, a novel diagnostic model was constructed with an AUC of 0.87 for the validation set and 0.7 for the test set. The AUC for ADRB2 alone was 0.75. Subgrouping AS based on these immune genes revealed a close association with neutrophils. GSEA and KEGG analysis of ISL, PB, and subgrouping of AS showed that ADRB2 may be involved in regulating the T cell receptor signaling pathway. Immune infiltration analysis indicated a decrease in CD8+ T cell infiltration, which was positively correlated with ADRB2. ADRB2 in AS-KD was regulated by multiple ceRNA-protein (lncRNA-[hsa-miR-513a-5p]-mRNA-protein). Conclusion: The immune gene family, especially ADRB2, participates in the mechanism and contributes to the diagnosis of AS.

Injectable spontaneously formed asymmetric adhesive hydrogel with controllable removal for wound healing.

Healing large-scale wounds has been a long-standing challenge in the field of biomedicine. Herein, we propose an injectable oxidated sodium alginate/gelatin/3,3'-dithiobis(propionic hydrazide)-aurum (Alg-CHO/gelatin/DTPH-Au) hydrogel filler with asymmetric adhesion ability and removability, which is formed by the Schiff-base reaction between aldehyde-based sodium alginate and multi-amino crosslinkers (gelatin and DTPH), combined with the coordination interaction between Au nanoparticles and disulfide bond of DTPH. Consequently, the prepared Alg-CHO/gelatin/DTPH-Au hydrogel exhibits high mechanical properties and injectable behaviors owing to its multiple-crosslinked interactions. Moreover, because various types of interaction bonding form on the contact side with the tissue, denser crosslinking of the upper layer relative to the lower layer occurs. Combined with the temperature difference between the upper and lower surfaces, this results in asymmetric adhesive properties. Owing to the photothermal effect, the reversible coordination interaction between Au nanoparticles and DTPH and the change in the triple helix structure of gelatin to a coil structure impart the filler-phased removability and antibacterial ability. The choice of all natural polymers also allows for favorable degradability of the wound filler and outstanding biocompatibility. Based on these features, this versatile wound filler can achieve a wide range of applications in the field of all-skin wound repair.

Chronological adhesive cardiac patch for synchronous mechanophysiological monitoring and electrocoupling therapy.

With advances in tissue engineering and bioelectronics, flexible electronic hydrogels that allow conformal tissue integration, online precision diagnosis, and simultaneous tissue regeneration are expected to be the next-generation platform for the treatment of myocardial infarction. Here, we report a functionalized polyaniline-based chronological adhesive hydrogel patch (CAHP) that achieves spatiotemporally selective and conformal embedded integration with a moist and dynamic epicardium surface. Significantly, CAHP has high adhesion toughness, rapid self-healing ability, and enhanced electrochemical performance, facilitating sensitive sensing of cardiac mechanophysiology-mediated microdeformations and simultaneous improvement of myocardial fibrosis-induced electrophysiology. As a result, the flexible CAHP platform monitors diastolic-systolic amplitude and rhythm in the infarcted myocardium online while effectively inhibiting ventricular remodeling, promoting vascular regeneration, and improving electrophysiological function through electrocoupling therapy. Therefore, this diagnostic and therapeutic integration provides a promising monitorable treatment protocol for cardiac disease.

A Zwitterionic Hydrogel with Anti-Oxidative and Anti-Inflammatory Properties for the Prevention of Peritoneal Adhesion by Inhibiting Mesothelial-Mesenchymal Transition.

Postoperative peritoneal adhesion is a serious clinical complication. Various hydrogel barriers have been developed to prevent peritoneal adhesion. However, it remains a challenge to design a hydrogel with desirable physicochemical properties and bioactivities. In this study, a zwitterionic polysaccharide-based multifunctional hydrogel is developed using epigallocatechin-3-gallate (EGCG) to prevent postoperative abdominal adhesion. This hydrogel is simple to use and has desirable properties, such as excellent injectability, self-healing, and non-swelling properties. The hydrogel also has ultralow fouling capabilities, such as superior bactericidal performance, cell and protein adhesion, and low immunogenicity resistance. Moreover, the hydrogel exhibits good antioxidant activity, which is attributed to the integration of EGCG. Furthermore, the detailed mechanism from in vivo and in vitro experimental studies illustrates that hydrogel compositions can synergistically prevent adhesion formation through multiple pathways, including anti-inflammatory and antioxidant capabilities and inhibition effects on the mesothelial-mesenchymal transition (MMT) process induced by transforming growth factor (TGF-ß). In summary, this zwitterionic multifunctional hydrogel has great potential to prevent postoperative adhesion formation in the clinical setting.

Development and validation of a machine learning-based nomogram for predicting HLA-B27 expression.

BACKGROUND: HLA-B27 positivity is normal in patients undergoing rheumatic diseases. The diagnosis of many diseases requires an HLA-B27 examination. METHODS: This study screened totally 1503 patients who underwent HLA-B27 examination, liver/kidney function tests, and complete blood routine examination in First Affiliated Hospital of Guangxi Medical University. The training cohort included 509 cases with HLA-B27 positivity whereas 611 with HLA-B27 negativity. In addition, validation cohort included 147 cases with HLA-B27 positivity whereas 236 with HLA-B27 negativity. In this study, 3 ML approaches, namely, LASSO, support vector machine (SVM) recursive feature elimination and random forest, were adopted for screening feature variables. Subsequently, to acquire the prediction model, the intersection was selected. Finally, differences among 148 cases with HLA-B27 positivity and negativity suffering from ankylosing spondylitis (AS) were investigated. RESULTS: Six factors, namely red blood cell count, human major compatibility complex, mean platelet volume, albumin/globulin ratio (ALB/GLB), prealbumin, and bicarbonate radical, were chosen with the aim of constructing the diagnostic nomogram using ML methods. For training queue, nomogram curve exhibited the value of area under the curve (AUC) of 0.8254496, and C-value of the model was 0.825. Moreover, nomogram C-value of the validation queue was 0.853, and the AUC value was 0.852675. Furthermore, a significant decrease in the ALB/GLB was noted among cases with HLA-B27 positivity and AS cases. CONCLUSION: To conclude, the proposed ML model can effectively predict HLA-B27 and help doctors in the diagnosis of various immune diseases.

To infer the probability of cervical ossification of the posterior longitudinal ligament and explore its impact on cervical surgery.

The ossification of the posterior longitudinal ligament (OPLL) in the cervical spine is commonly observed in degenerative changes of the cervical spine. Early detection of cervical OPLL and prevention of postoperative complications are of utmost importance. We gathered data from 775 patients who underwent cervical spine surgery at the First Affiliated Hospital of Guangxi Medical University, collecting a total of 84 variables. Among these patients, 144 had cervical OPLL, while 631 did not. They were randomly divided into a training cohort and a validation cohort. Multiple machine learning (ML) methods were employed to screen the variables and ultimately develop a diagnostic model. Subsequently, we compared the postoperative outcomes of patients with positive and negative cervical OPLL. Initially, we compared the advantages and disadvantages of various ML methods. Seven variables, namely Age, Gender, OPLL, AST, UA, BMI, and CHD, exhibited significant differences and were used to construct a diagnostic nomogram model. The area under the curve (AUC) values of this model in the training and validation groups were 0.76 and 0.728, respectively. Our findings revealed that 69.2% of patients who underwent cervical OPLL surgery eventually required elective anterior surgery, in contrast to 86.8% of patients who did not have cervical OPLL. Patients with cervical OPLL had significantly longer operation times and higher postoperative drainage volumes compared to those without cervical OPLL. Interestingly, preoperative cervical OPLL patients demonstrated significant increases in mean UA, age, and BMI. Furthermore, 27.1% of patients with cervical anterior longitudinal ligament ossification (OALL) also exhibited cervical OPLL, whereas this occurrence was only observed in 6.9% of patients without cervical OALL. We developed a diagnostic model for cervical OPLL using the ML method. Our findings indicate that patients with cervical OPLL are more likely to undergo posterior cervical surgery, and they exhibit elevated UA levels, higher BMI, and increased age. The prevalence of cervical anterior longitudinal ligament ossification was also significantly higher among patients with cervical OPLL.

Clinical model of pulmonary metastasis in patients with osteosarcoma: A new multiple machine learning-based risk prediction.

BACKGROUND: Metastasis is one of the most significant prognostic factors in osteosarcoma (OS). The goal of this study was to construct a clinical prediction model for OS patients in a population cohort and to evaluate the factors influencing the occurrence of pulmonary metastasis. METHODS: We collected data from 612 patients with osteosarcoma (OS), and 103 clinical indicators were collected. After the data were filtered, the patients were randomly divided into training and validation cohorts by using random sampling. The training cohort included 191 patients with pulmonary metastasis in OS and 126 patients with non-pulmonary metastasis, and the validation cohort included 50 patients with pulmonary metastasis in OS and 57 patients with non-pulmonary metastasis. Univariate logistics regression analysis, LASSO regression analysis and multivariate logistic regression analysis were performed to identify potential risk factors for pulmonary metastasis in patients with osteosarcoma. A nomogram was developed that included risk influencing variables selected by multivariable analysis, and used the concordance index (C-index) and calibration curve to validate the model. Receiver operating characteristic curve (ROC), decision analysis curve (DCA) and clinical impact curve (CIC) were employed to assess the model. In addition, we used a predictive model on the validation cohort. RESULTS: Logistic regression analysis was used to identify independent predictors [N Stage + Alkaline phosphatase (ALP)+Thyroid stimulating hormone (TSH)+Free triiodothyronine (FT3)]. A nomogram was constructed to predict the risk of pulmonary metastasis in patients with osteosarcoma. The performance was evaluated by the concordance index (C-index) and calibration curve. The ROC curve provides the predictive power of the nomogram (AUC = 0.701 in the training cohort, AUC = 0.786 in the training cohort). Decision curve analysis (DCA) and clinical impact curve (CIC) demonstrated the clinical value of the nomogram and higher overall net benefits. CONCLUSIONS: Our study can help clinicians effectively predict the risk of lung metastases in osteosarcoma with more readily available clinical indicators, provide more personalized diagnosis and treatment guidance, and improve the prognosis of patients. MINI ABSTRACT: A new risk model was constructed to predict the pulmonary metastasis in patients with osteosarcoma based on multiple machine learning.

Strongly adhesive zwitterionic composite hydrogel paints for surgical sutures and blood-contacting devices.

Hydrogels show eminent advantages in biomedical and pharmaceutical fields. However, their application as coating materials for biomedical devices is limited by several key challenges, such as lack of universality, weak mechanical strength, and low adhesion to the substrate. Here we report versatile and tough adhesion composite hydrogel paints (CHPs), which consist of zwitterionic copolymers and microgels, both with reactive groups. The CHPs exhibit tunable rheology and thickness, hydrophilicity, biofouling resistance, durability, and convenient fabrication on metal, polymer, and inorganic surfaces with arbitrary shapes. As a proof-of-concept, the CHP-surgical sutures demonstrate exceptional lubrication, drug delivery, anti-infection, and anti-fibrous capsule properties. Moreover, the CHP-PVC tubing effectively prevents thrombus formation in vitro and ex vivo rabbit blood circulation without anticoagulants. This work provides valuable insights for enhancing and developing integrated hydrogel technologies for biomedical devices. STATEMENT OF SIGNIFICANCE: The combination of hydrogel and biomedical devices can enable numerous existing applications in medicine. In this study, inspired by the principle of microgel reinforcement in industrial paints, we propose a simple and versatile zwitterionic composite hydrogel paints (CHPs) strategy, which can be easily applied to diverse substrates with arbitrary shapes by covalent grafting between complementary groups by brush, dip, or spray. The CHPs integrated universality, tough adhesion, mechanical durability, and anti-biofouling properties because of their unique chemical composition and coating structure design. This strategy provides a simple and versatile route for surface modification of biomedical devices.

Application of machine learning in prediction of bone cement leakage during single-level thoracolumbar percutaneous vertebroplasty.

BACKGROUND: In the elderly, osteoporotic vertebral compression fractures (OVCFs) of the thoracolumbar vertebra are common, and percutaneous vertebroplasty (PVP) is a common surgical method after fracture. Machine learning (ML) was used in this study to assist clinicians in preventing bone cement leakage during PVP surgery. METHODS: The clinical data of 374 patients with thoracolumbar OVCFs who underwent single-level PVP at The First People's Hospital of Chenzhou were chosen. It included 150 patients with bone cement leakage and 224 patients without it. We screened the feature variables using four ML methods and used the intersection to generate the prediction model. In addition, predictive models were used in the validation cohort. RESULTS: The ML method was used to select five factors to create a Nomogram diagnostic model. The nomogram model's AUC was 0.646667, and its C value was 0.647. The calibration curves revealed a consistent relationship between nomogram predictions and actual probabilities. In 91 randomized samples, the AUC of this nomogram model was 0.7555116. CONCLUSION: In this study, we invented a prediction model for bone cement leakage in single-segment PVP surgery, which can help doctors in performing better surgery with reduced risk.

Comprehensive AI-assisted tool for ankylosing spondylitis based on multicenter research outperforms human experts.

Introduction: The diagnosis and treatment of ankylosing spondylitis (AS) is a difficult task, especially in less developed countries without access to experts. To address this issue, a comprehensive artificial intelligence (AI) tool was created to help diagnose and predict the course of AS. Methods: In this retrospective study, a dataset of 5389 pelvic radiographs (PXRs) from patients treated at a single medical center between March 2014 and April 2022 was used to create an ensemble deep learning (DL) model for diagnosing AS. The model was then tested on an additional 583 images from three other medical centers, and its performance was evaluated using the area under the receiver operating characteristic curve analysis, accuracy, precision, recall, and F1 scores. Furthermore, clinical prediction models for identifying high-risk patients and triaging patients were developed and validated using clinical data from 356 patients. Results: The ensemble DL model demonstrated impressive performance in a multicenter external test set, with precision, recall, and area under the receiver operating characteristic curve values of 0.90, 0.89, and 0.96, respectively. This performance surpassed that of human experts, and the model also significantly improved the experts' diagnostic accuracy. Furthermore, the model's diagnosis results based on smartphone-captured images were comparable to those of human experts. Additionally, a clinical prediction model was established that accurately categorizes patients with AS into high-and low-risk groups with distinct clinical trajectories. This provides a strong foundation for individualized care. Discussion: In this study, an exceptionally comprehensive AI tool was developed for the diagnosis and management of AS in complex clinical scenarios, especially in underdeveloped or rural areas that lack access to experts. This tool is highly beneficial in providing an efficient and effective system of diagnosis and management.