Application of AI-assisted MRI for the identification of surgical target areas in pediatric hip and periarticular infections.

OBJECTIVE: To develop an AI-assisted MRI model to identify surgical target areas in pediatric hip and periarticular infections. METHODS: A retrospective study was conducted on the pediatric patients with hip and periarticular infections who underwent Magnetic Resonance Imaging(MRI)examinations from January 2010 to January 2023 in three hospitals in China. A total of 7970 axial Short Tau Inversion Recovery (STIR) images were selected, and the corresponding regions of osteomyelitis (label 1) and abscess (label 2) were labeled using the Labelme software. The images were randomly divided into training group, validation group, and test group at a ratio of 7:2:1. A Mask R-CNN model was constructed and optimized, and the performance of identifying label 1 and label 2 was evaluated using receiver operating characteristic (ROC) curves. Calculation of the average time it took for the model and specialists to process an image in the test group. Comparison of the accuracy of the model in the interpretation of MRI images with four orthopaedic surgeons, with statistical significance set at P < 0.05. RESULTS: A total of 275 patients were enrolled, comprising 197 males and 78 females, with an average age of 7.10 ± 3.59 years, ranging from 0.00 to 14.00 years. The area under curve (AUC), accuracy, sensitivity, specificity, precision, and F1 score for the model to identify label 1 were 0.810, 0.976, 0.995, 0.969, 0.922, and 0.957, respectively. The AUC, accuracy, sensitivity, specificity, precision, and F1 score for the model to identify label 2 were 0.890, 0.957, 0.969, 0.915, 0.976, and 0.972, respectively. The model demonstrated a significant speed advantage, taking only 0.2 s to process an image compared to average 10 s required by the specialists. The model identified osteomyelitis with an accuracy of 0.976 and abscess with an accuracy of 0.957, both statistically better than the four orthopaedic surgeons, P < 0.05. CONCLUSION: The Mask R-CNN model is reliable for identifying surgical target areas in pediatric hip and periarticular infections, offering a more convenient and rapid option. It can assist unexperienced physicians in pre-treatment assessments, reducing the risk of missed and misdiagnosis.

Online System for Monitoring the Degree of Fermentation of Oolong Tea Using Integrated Visible-Near-Infrared Spectroscopy and Image-Processing Technologies.

During the fermentation process of Oolong tea, significant changes occur in both its external characteristics and its internal components. This study aims to determine the fermentation degree of Oolong tea using visible-near-infrared spectroscopy (vis-VIS-NIR) and image processing. The preprocessed vis-VIS-NIR spectral data are fused with image features after sequential projection algorithm (SPA) feature selection. Subsequently, traditional machine learning and deep learning classification models are compared, with the support vector machine (SVM) and convolutional neural network (CNN) models yielding the highest prediction rates among traditional machine learning models and deep learning models with 97.14% and 95.15% in the prediction set, respectively. The results indicate that VIS-NIR combined with image processing possesses the capability for rapid non-destructive online determination of the fermentation degree of Oolong tea. Additionally, the predictive rate of traditional machine learning models exceeds that of deep learning models in this study. This study provides a theoretical basis for the fermentation of Oolong tea.

A Gas Sensors Detection System for Real-Time Monitoring of Changes in Volatile Organic Compounds during Oolong Tea Processing.

The oxidation step in Oolong tea processing significantly influences its final flavor and aroma. In this study, a gas sensors detection system based on 13 metal oxide semiconductors with strong stability and sensitivity to the aroma during the Oolong tea oxidation production is proposed. The gas sensors detection system consists of a gas path, a signal acquisition module, and a signal processing module. The characteristic response signals of the sensor exhibit rapid release of volatile organic compounds (VOCs) such as aldehydes, alcohols, and olefins during oxidative production. Furthermore, principal component analysis (PCA) is used to extract the features of the collected signals. Then, three classical recognition models and two convolutional neural network (CNN) deep learning models were established, including linear discriminant analysis (LDA), k-nearest neighbors (KNN), back-propagation neural network (BP-ANN), LeNet5, and AlexNet. The results indicate that the BP-ANN model achieved optimal recognition performance with a 3-4-1 topology at pc = 3 with accuracy rates for the calibration and prediction of 94.16% and 94.11%, respectively. Therefore, the proposed gas sensors detection system can effectively differentiate between the distinct stages of the Oolong tea oxidation process. This work can improve the stability of Oolong tea products and facilitate the automation of the oxidation process. The detection system is capable of long-term online real-time monitoring of the processing process.

Analysis of risk factors for failed closed reduction in pediatric Gartland Type III supracondylar humerus fracture.

PURPOSE: Gartland Type III supracondylar humerus fractures are commonly treated using closed reduction followed by percutaneous pin fixation. However, conversion to open reduction may be necessary if closed reduction fails. This study aimed to identify risk factors associated with failed closed reduction and provide a theoretical basis for clinical decision-making in the treatment of Gartland Type III fractures. METHODS: A retrospective analysis was conducted on children with Gartland Type III supracondylar humerus fracture who underwent surgical treatment between April 2017 and June 2018. Based on whether or not the closed reduction was successful, patients were split into the open reduction group and the closed reduction group. Within the closed reduction group, subgroup analysis based on surgery duration was carried out. Data were collected from medical records and X-ray images. Univariate and multivariate regression analyses were utilized to evaluate the relationship between variables and failed closed reduction. RESULTS: The study included 36 patients in the open reduction group and 135 patients in the closed reduction group. Multivariate analysis revealed that the presence of angle (P=0.024, OR=3.199), rotation (P=0.000, OR=6.359), skin creases (P=0.013, OR=4.077), anterior-posterior displacement ratio (P=0.011, OR=4.337), fracture angle in the anteroposterior view (P=0.014, OR=0.939), and fracture distal displacement direction (P=0.002, OR=5.384) were independent risk factors for failed closed reduction. Subgroup analysis showed that fracture distal displacement direction (P=0.013), skin folds (P=0.013), lateral displacement ratio (P=0.016), and anterior-posterior displacement value (P=0.005) significantly influenced the duration of closed reduction surgery. CONCLUSION: The presence of sharp angle or rotation at the fracture ends, skin folds on the anterior elbow, minor anterior-posterior displacement of the fracture, higher medial inclination of the fracture plane, and distal fracture displacement towards the radial side are independent risk factors for failed closed reduction in pediatric Gartland Type III supracondylar humerus fracture.

Design and application of virtual simulation teaching platform for intelligent manufacturing.

Aiming at the practical teaching of intelligent manufacturing majors faced with lack of equipment, tense teachers and other problems such as high equipment investment, high material loss, high teaching risk, difficult to implement internship, difficult to observe production, difficult to reproduce the results, and so on, we take the electrical automation technology, mechatronics technology and industrial robotics technology majors of intelligent manufacturing majors as an example, and design and establish a virtual simulation teaching platform for intelligent manufacturing majors by using the cloud computing platform, edge computing technology, and terminal equipment synergy. The platform includes six major virtual simulation modules, including virtual simulation of electrician electronics and PLC control, virtual and real combination of typical production lines of intelligent manufacturing, dual-axis collaborative robotics workstation, digital twin simulation, virtual disassembly of industrial robots, virtual simulation of magnetic yoke axis flexible production line. The platform covers the virtual simulation teaching content of basic principle experiments, advanced application experiments, and advanced integration experiments in intelligent manufacturing majors. In order to test the effectiveness of this virtual simulation platform for practical teaching in engineering, this paper organizes a teaching practice activity involving 246 students from two parallel classes of three different majors. Through a one-year teaching application, we analyzed the data on the grades of 7 core courses involved in three majors in one academic year, the proportion of participation in competitions and innovative activities, the number of awards and certificates of professional qualifications, and the subjective questionnaires of the testers. The analysis shows that the learners who adopt the virtual simulation teaching platform proposed in this paper for practical teaching are better than the learners under the traditional teaching method in terms of academic performance, proportion of participation in competitions and innovative activities, and proportion of awards and certificates by more than 13%, 37%, 36%, 27% and 22%, respectively. Therefore, the virtual simulation teaching platform of intelligent manufacturing established in this paper has obvious superiority in solving the problem of "three highs and three difficulties" existing in the practical teaching of engineering, and according to the questionnaire feedback from the testers, the platform can effectively alleviate the shortage of practical training equipment, stimulate the interest in learning, and help to broaden and improve the knowledge system of the learners.

Impact of foot progression angle on spatiotemporal and plantar loading pattern in intoeing children during gait.

Intoeing in children is a common parental concern, but our understanding of the impact of foot progression angle (FPA) in these children leaves remains limited. This study examines the relationship between FPA and plantar loading pattern, as well as gait symmetry in children with intoeing. The sample included 30 children with intoeing caused by internal tibial torsion, uniformly divided into three groups: unilateral intoeing, bilateral mild intoeing, and bilateral mild-moderate intoeing. The relationship between FPA and plantar loading pattern, and gait symmetry within and among groups were assessed using dynamic pedobarographic and spatiotemporal data. Results indicated a significant correlation between FPA and peak pressure, maximum force, and plantar impulse in the medial and central forefoot, and also the medial and lateral heel zones for both bilateral intoeing groups. Significant differences were observed only in subdivided stance phase, including loading response, single support, and pre-swing phases, between the unilateral intoeing and bilateral mild intoeing groups. These findings suggest that FPA significantly affects the forefoot and heel zones, potentially increasing the load on the support structures and leading to transverse arch deformation. While children with intoeing demonstrate a dynamic self-adjustment capability to maintain gait symmetry, this ability begins to falter as intoeing becomes more pronounced.

Discovery of new tricyclic spiroindole derivatives as potent P-glycoprotein inhibitors for reversing multidrug resistance enabled by a synthetic methodology-based library.

The discovery of novel and highly effective P-gp inhibitors is considered to be an effective strategy for overcoming tumor drug resistance. In this paper, a phenotypic screening via a self-constructed synthetic methodology-based library identified a new class of tricyclic spiroindole derivatives with excellent tumor multidrug resistance reversal activity. A stereospecific compound OY-103-B with the best reversal activity was obtained based on a detailed structure-activity relationship study, metabolic stability optimization and chiral resolution. For the VCR-resistant Eca109 cell line (Eca109/VCR), co-administration of 5.0 µM OY-103-B resulted in a reversal fold of up to 727.2, superior to the typical third-generation P-gp inhibitor tariquidar. Moreover, the compound inhibited the proliferation of Eca109/VCR cells in a concentration-dependent manner in plate cloning and flow cytometry. Furthermore, fluorescence substrate accumulation assay and chemotherapeutic drug reversal activity tests demonstrated that OY-103-B reversed tumor drug resistance via P-gp inhibition. In conclusion, this study provides a novel skeleton that inspires the design of new P-gp inhibitors, laying the foundation for the treatment of drug-resistant tumors.

A meta-analysis of antibiotic residues in the Beibu Gulf.

Antibiotic residue stands as a significant ongoing environmental issue, with aquaculture being a major source of annual antibiotic discharge into the ocean. Nevertheless, there is still an incomplete evaluation of antibiotic residues in the Beibu Gulf, an area encompassed by two prominent aquaculture nations, China and Vietnam. The present systematic review and meta-analysis was conducted to examine the presence antibiotic residues in the Beibu Gulf based on published studies. Data were obtained through eight databases up to December 19th, 2023, and were updated on April 15th, 2024. The pooled concentration of antibiotic residues in seawater was 5.90 (ng/L), ranging from 5.73 to 6.06 (ng/L), and was 8.03 (ng/g), ranging from 7.77 to 8.28 (ng/g) in sediments. Fluoroquinolones, tetracyclines, and macrolides were identified as the main antibiotics found in both seawater and sediment samples. The Beibu Gulf showed higher antibiotic levels in its western and northeastern areas. Additionally, the nearshore mangrove areas displayed the highest prevalence of antibiotic residues. It is strongly advised to conduct regular long-term monitoring of antibiotic residues in the Beibu Gulf. Collaborative surveys covering the entire Beibu Gulf involving China and Vietnam are recommended.

Long-term efficacy and safety of posterior endoscopic cyclophotocoagulation in refractory glaucoma: A 5-year follow-up study at a tertiary eye center.

PURPOSE: To evaluate the long-term efficacy of endoscopic cyclophotocoagulation (ECP) via a pars plana approach in a large cohort of refractory glaucoma patients DESIGN: Single-center, retrospective, longitudinal, cohort study. METHODS: This study recruited patients who underwent ECP and consecutively visited and were followed up for at least 5 years at Beijing Tongren Eye Center, China from January 2013 to December 2017. All patients underwent a complete ophthalmic examination. Treatment success was defined as 6 mmHg ≤ IOP ≤ 21 mmHg with or without anti-glaucoma medications. RESULTS: A total of 121 eyes of 105 patients including 51 children and 54 adults were enrolled. The mean follow-up was 7.2 ± 1.3 years. The most common glaucoma diagnoses were secondary glaucoma (74 eyes, 61.1 %) and primary congenital glaucoma (19 eyes 15.7 %). The mean extent of the first ECP was 259 degrees. There was an overall decrease in IOP of 38.3 % from 33.3 ± 9.0 mmHg preoperatively to 20.5 ± 7.5 mmHg after surgery, which was statistically significant (P < 0.001). The success rate after 1 or more ECP surgery was 65.3 %. After adjusting for sex, number of prior TCP surgeries and the extent of ECP degree, the failure of ECP was associated with being children (as compared with adults; P = 0.028; OR = 2.549) and higher preoperative IOP (P = 0.001; OR = 1.084). CONCLUSION: ECP is an effective procedure for lowing IOP in refractory glaucoma, particularly in patients who are also candidates for vitreoretinal interventions. Hence, a collaborative approach between glaucoma and retinal specialists is of utmost importance in devising an optimal management strategy for glaucoma treatment.

Spatial and diel variations of bacterioplankton and pico-nanoeukaryote communities and potential biotic interactions during macroalgal blooms.

We investigated spatial heterogeneity and diel variations in bacterioplankton and pico-nanoeukaryote communities, and potential biotic interactions at the extinction stage of the Ulva prolifera bloom in the Jiaozhou Bay, Yellow Sea. It was found that the presence of Ulva canopies significantly promoted the cell abundance of heterotrophic bacteria, raised evenness, and altered the community structure of bacterioplankton. A diel pattern was solely significant for pico-nanoeukaryote community structure. >50 % of variation in the heterotrophic bacterial abundance was accounted for by the ratio of Bacteroidota to Firmicutes, and dissolved organic nitrogen effectively explained the variations in cell abundances of phytoplankton populations. The factors representing biotic interactions frequently contributed substantially more than environmental factors in explaining the variations in diversity and community structure of both bacterioplankton and pico-nanoeukaryotes. There were higher proportions of eukaryotic pathogens compared to other marine systems, suggesting a higher ecological risk associated with the Ulva blooms.

Unveiling hidden interactions: Microorganisms, enzymes, and mangroves at different stages of succession in the Shankou Mangrove Nature Reserve, China.

Understanding the interactions between microorganisms, soil extracellular enzymes, and mangroves is crucial for conserving and restoring mangrove ecosystems. However, the unique environments associated with mangroves have resulted in a lack of pertinent data regarding the interactions between these components. Root, stem, leaf, and soil samples were collected at three distinct stages of mangrove succession. Stoichiometry was employed to analyze the carbon, nitrogen, and phosphorus contents of these samples and to quantify extracellular enzyme activities, microbial biomass, and various physicochemical factors in the soil. The results showed that the trends of C, N, and P in the mangrove plants were consistent. Microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), and microbial biomass phosphorus (MBP) were the highest in the Kandelia obovate community. Catalase (CAT) and ß-D-G showed the highest content in K. obovate and Bruguiera gymnorrhiza, whereas cellulase showed the opposite trend. Urease was least abundant in the K. obovate community, whereas neutral protease (NPR) and acid phosphatase (ACP) were most abundant. The overall soil environment in mangroves exhibited a state of N limitation, with varying degrees of limitation observed across different succession stages. The demand for P became more intense in the later stages of succession, particularly in the K. obovate and B. gymnorrhiza communities. In conjunction with correlation analysis, it indicated that the input of mangrove plant litter had a significant regulatory influence on the C, N, and P contents in the soil. There was a significant positive correlation between MBC, MBN, and MBP, indicating synergistic effects of C, N, and P on soil microorganisms. Therefore, evaluating the nutrient ratios and sufficiency of mangroves allowed us to comprehensively understand the present environmental conditions. This study aims to develop sustainable management strategies for the conservation and restoration of mangroves.

Modular preparation of biphenyl triazoles via click chemistry as non-competitive hyaluronidase inhibitors.

Hyaluronidase is a promising target in drug discovery, given its overexpression in a range of physiological and pathological processes, including tumor migration, skin aging, sagging, and wrinkling, as well as inflammation and bacterial infections. In this study, to identify novel hyaluronidase inhibitors, we applied click chemistry for the modular synthesis of 370 triazoles in 96-well plates, starting with biphenyl azide. Utilizing an optimized turbidimetric screening assay in microplates, we identified Fmoc-containing triazoles 5 and 6, as well as quinoline-containing triazoles 15 and 16, as highly effective hyaluronidase inhibitors. Subsequent research indicated that these triazoles potentially interact with a novel binding site of hyaluronidase. Notably, these inhibitors displayed minimal cytotoxicity and showed promising anti-inflammatory effects in LPS-stimulated macrophages. Remarkably, compound 6 significantly reduced NO release by 74 % at a concentration of 20 µM.

Development and validation of a nomogram for predicting the prognosis in children with spinal cord injuries.

AIMS: This research aims to construct and verify an accurate nomogram for forecasting the 3-, 5-, and 7-year outcomes in pediatric patients afflicted with spinal cord injury (SCI). METHODS: Pediatric patients with SCI from multiple hospitals in China, diagnosed between Jan 2005 and Jan 2020, were incorporated into this research. Half of these patients were arbitrarily chosen for training sets, and the other half were designated for external validation sets. The Cox hazard model was employed to pinpoint potential prognosis determinants related to the American Spinal Injury Association (ASIA) and Functional Independence Assessment (FIM) index. These determinants were then employed to formulate the prognostic nomogram. Subsequently, the bootstrap technique was applied to validate the derived model internally. RESULTS: In total, 224 children with SCI were considered for the final evaluation, having a median monitoring duration of 68.0 months. The predictive nomogram showcased superior differentiation capabilities, yielding a refined C-index of 0.924 (95% CI: 0.883-0.965) for the training cohort and a C-index of 0.863 (95% CI: 0.735-0.933) for the external verification group. Additionally, when applying the aforementioned model to prognostic predictions as classified by the FIM, it demonstrated a high predictive value with a C-index of 0.908 (95% CI: 0.863-0.953). Moreover, the calibration diagrams indicated a consistent match between the projected and genuine ASIA outcomes across both sets. CONCLUSION: The crafted and verified prognostic nomogram emerges as a dependable instrument to foresee the 3-, 5-, and 7-year ASIA and FIM outcomes for children suffering from SCI.

DeepAEG: a model for predicting cancer drug response based on data enhancement and edge-collaborative update strategies.

MOTIVATION: The prediction of cancer drug response is a challenging subject in modern personalized cancer therapy due to the uncertainty of drug efficacy and the heterogeneity of patients. It has been shown that the characteristics of the drug itself and the genomic characteristics of the patient can greatly influence the results of cancer drug response. Therefore, accurate, efficient, and comprehensive methods for drug feature extraction and genomics integration are crucial to improve the prediction accuracy. RESULTS: Accurate prediction of cancer drug response is vital for guiding the design of anticancer drugs. In this study, we propose an end-to-end deep learning model named DeepAEG which is based on a complete-graph update mode to predict IC50. Specifically, we integrate an edge update mechanism on the basis of a hybrid graph convolutional network to comprehensively learn the potential high-dimensional representation of topological structures in drugs, including atomic characteristics and chemical bond information. Additionally, we present a novel approach for enhancing simplified molecular input line entry specification data by employing sequence recombination to eliminate the defect of single sequence representation of drug molecules. Our extensive experiments show that DeepAEG outperforms other existing methods across multiple evaluation parameters in multiple test sets. Furthermore, we identify several potential anticancer agents, including bortezomib, which has proven to be an effective clinical treatment option. Our results highlight the potential value of DeepAEG in guiding the design of specific cancer treatment regimens.

Research on Performance Improvement of Emulsified Asphalt Mixture Based on Innovative Forming Process.

Bulk density and porosity have great influence on the technical performance of an emulsified asphalt mixture, so in order to enhance the strength of the asphalt mixture, bulk density should be improved and porosity should be reduced. Considering the forming process of the emulsified asphalt mixture, the decrease in porosity can ensure the state of the mixture. In order to reduce the porosity of the emulsified asphalt mixture, an innovative forming process is proposed to improve the performance of the emulsified asphalt mixture, and its strength formation mechanism is explored in this paper. Three groups of emulsified asphalt mixtures (ARC-8 + SBR, SMA-5 + EVA, SMA-5 + SBR) were prepared by a conventional mixing process and novel mixing process. Marshall test of the emulsified asphalt mixture, CT scanning test of the emulsified asphalt mixture, workability test and analysis were manufactured and tested. The results show that, compared with conventional methods, the innovative forming method can increase the bulk density of the mixture and reduce the porosity, and thus improve its technical performance. The reason is that most of the water in the mixture of the innovative forming method sticks to the outer surface of the fine aggregate, and the water is more easily discharged. Secondly, the fine aggregate of the innovative forming method is directly mixed with the emulsion, and the volume is smaller. The emulsion wraps the fine aggregate in it due to the surface tension, which enhances the adhesion effect, thus improving the strength of the mixture.

Crystal Structure and Optical Properties Characterization in Quasi-0D Lead-Free Bromide Crystals (C6H14N)3Bi2Br9·H2O and (C6H14N)3Sb3Br12.

Low dimensional organic inorganic metal halide materials have shown broadband emission and large Stokes shift, making them widely used in various fields and a promising candidate material. Here, the zero-dimensional lead-free bromide single crystals (C6H14N)3Bi2Br9·H2O (1) and (C6H14N)3Sb3Br12 (2) were synthesized. They crystallized in the monoclinic crystal system with the space group of P21 and P21/n, respectively. Through ultraviolet-visible-near-infrared (UV-vis-NIR) absorption analysis, the band gaps of (C6H14N)3Bi2Br9·H2O and (C6H14N)3Sb3Br12 are found to be 2.75 and 2.83 eV, respectively. Upon photoexcitation, (C6H14N)3Bi2Br9·H2O exhibit broad-band red emission peaking at 640 nm with a large Stokes shift of 180 nm and a lifetime of 2.94 ns, and the emission spectrum of (C6H14N)3Sb3Br12 are similar to those of (C6H14N)3Bi2Br9·H2O. This exclusive red emission is ascribed to the self-trapping exciton transition caused by lattice distortion, which is confirmed through both experiments and first-principles calculations. In addition, due to the polar space group structure and the large spin-orbit coupling (SOC) associated with the heavy elements of Bi and Br of crystal 1, an obvious Rashba effect was observed. The discovery of organic inorganic metal bromide material provides a critical foundation for uncovering the connection between 0D metal halide materials' structures and properties.

A nomogram for predicting the hospital-acquired infections in children with spinal cord injuries: a retrospective, multicenter, observational study.

STUDY DESIGN: Retrospective cohort study. OBJECTIVES: Hospital-acquired infections (HAIs) pose a significant risk for pediatric patients with spinal cord injuries (SCIs), potentially leading to extended hospital stays and increased morbidity. This study aims to identify patients at higher risk for HAIs. SETTING: Hospitals from multiple areas in China. METHODS: This retrospective study included 220 pediatric SCI patients from Jan 2005 to Dec 2023, divided into a training set (n = 154) and a validation set (n = 66). We conducted a multivariate logistic regression analysis to identify risk factors associated with HAIs and constructed a predictive nomogram. The model's performance was assessed using receiver operating characteristic (ROC) curves, area under the ROC curve (AUC) and calibration plots, while decision curve analysis was utilized to determine clinical utility. RESULTS: The nomogram incorporated age, time from injury to the hospital, history of urinary and pulmonary infections, urobilinogen positivity, damaged segments, and admission American Spinal Injury Association (ASIA) scores. The model demonstrated excellent discrimination in the training set (AUC = 0.957) and good discrimination in the validation set (AUC = 0.919). Calibration plots indicated an acceptable fit between predicted probabilities and observed outcomes. Decision curve analysis confirmed the model's net benefit over clinical decision thresholds in both sets. CONCLUSION: We developed and validated a predictive nomogram for HAIs in pediatric SCI patients that shows promise for clinical application. The model can assist healthcare providers in identifying patients at higher risk for HAIs, potentially facilitating early interventions and improved patient care strategies.

Corrigendum to "3D-printed tri-element-doped hydroxyapatite/ polycaprolactone composite scaffolds with antibacterial potential for osteosarcoma therapy and bone regeneration" [Bioact. Mater. 31 (January 2024) 18-37].

[This corrects the article DOI: 10.1016/j.bioactmat.2023.07.004.].

Platelet-derived growth factor subunit-B mediating the effect of dickkopf-1 on acute myocardial infarction risk: a two-step Mendelian randomization study.

Previous studies have indicated a potential connection between plasma levels of Dickkopf-1 (DKK1) and platelet-derived growth factor subunit-B (PDGF-B) with the development of atherosclerosis. However, the causal relationship between DKK1, PDGF-B, and the risk of acute myocardial infarction (AMI) is yet to be established. To address this research gap, we conducted Mendelian randomization (MR) and mediation analyses to investigate the potential mediating role of PDGF-B in the association between DKK1 and AMI risk. Summary statistics for DKK1 (n = 3,301) and PDGF-B (n = 21,758) were obtained from the GWAS meta-analyses conducted by Sun et al. and Folkersen et al., respectively. Data on AMI cases (n = 3,927) and controls (n = 333,272) were retrieved from the UK Biobank study. Our findings revealed that genetic predisposition to DKK1 (odds ratio [OR]: 1.00208; 95% confidence interval [CI]: 1.00056-1.00361; P = 0.0072) and PDGF-B (OR: 1.00358; 95% CI: 1.00136-1.00581; P = 0.0015) was associated with an increased risk of AMI. Additionally, genetic predisposition to DKK1 (OR: 1.38389; 95% CI: 1.07066-1.78875; P = 0.0131) was linked to higher PDGF-B levels. Furthermore, our MR mediation analysis revealed that PDGF-B partially mediated the association between DKK1 and AMI risk, with 55.8% of the effect of genetically predicted DKK1 being mediated through genetically predicted PDGF-B. These findings suggest that genetic predisposition to DKK1 is positively correlated with the risk of AMI, and that PDGF-B partially mediates this association. Therefore, DKK1 and PDGF-B may serve as promising targets for the prevention and treatment of AMI.

3D-printed tri-element-doped hydroxyapatite/ polycaprolactone composite scaffolds with antibacterial potential for osteosarcoma therapy and bone regeneration.

The resection of malignant osteosarcoma often results in large segmental bone defects, and the residual cells can facilitate recurrence. Consequently, the treatment of osteosarcoma is a major challenge in clinical practice. The ideal goal of treatment for osteosarcoma is to eliminate it thoroughly, and repair the resultant bone defects as well as avoid bacterial infections. Herein, we fabricated a selenium/strontium/zinc-doped hydroxyapatite (Se/Sr/Zn-HA) powder by hydrothermal method, and then employed it with polycaprolactone (PCL) as ink to construct composite scaffolds through 3D printing, and finally introduced them in bone defect repair induced by malignant osteosarcoma. The resultant composite scaffolds integrated multiple functions involving anti-tumor, osteogenic, and antibacterial potentials, mainly attributed to the anti-tumor effects of SeO32-, osteogenic effects of Sr2+ and Zn2+, and antibacterial effects of SeO32- and Zn2+. In vitro studies confirmed that Se/Sr/Zn-HA leaching solution could induce apoptosis of osteosarcoma cells, differentiation of MSCs, and proliferation of MC3T3-E1 while showing excellent antibacterial properties. In vivo tests demonstrated that Se/Sr/Zn-HA could significantly suppress tumors after 8 days of injection, and the Se/Sr/Zn-HA-PCLs scaffold repaired femoral defects effectively after 3 months of implantation. Summarily, the Se/Sr/Zn-HA-PCLs composite scaffolds developed in this study were effective for tumor treatment, bone defect repair, and post-operative anti-infection, which provided a great potential to be a facile therapeutic material for osteosarcoma resection.