The effect of deep and awake extubation on emergence agitation after nasal surgery: a randomized controlled trial.

BACKGROUND: Post-anesthetic emergence agitation is common after general anesthesia and may cause adverse consequences, such as injury as well as respiratory and circulatory complications. Emergence agitation after general anesthesia occurs more frequently in nasal surgery than in other surgical procedures. This study aimed to assess the occurrence of emergence agitation in patients undergoing nasal surgery who were extubated under deep anesthesia or when fully awake. METHODS: A total of 202 patients (18-60 years, American Society of Anesthesiologists classification: I-II) undergoing nasal surgery under general anesthesia were randomized 1:1 into two groups: a deep extubation group (group D) and an awake extubation group (group A). The primary outcome was the incidence of emergence agitation. The secondary outcomes included number of emergence agitations, sedation score, vital signs, and incidence of adverse events. RESULTS: The incidence of emergence agitation was lower in group D than in group A (34.7% vs. 72.8%; p < 0.001). Compared to group A, patients in group D had lower Richmond Agitation-Sedation Scale scores, higher Ramsay sedation scores, fewer agitation episodes, and lower mean arterial pressure when extubated and 30 min after surgery, whereas these indicators did not differ 90 min after surgery. There was no difference in the incidence of adverse events between the two groups. CONCLUSIONS: Extubation under deep anesthesia can significantly reduce emergence agitation after nasal surgery under general anesthesia without increasing the incidence of adverse events. TRIAL REGISTRATION: Registered in Clinicaltrials.gov (NCT04844333) on 14/04/2021.

An FOF1-ATPase motor-embedded chromatophore as a nanorobot for overcoming biological barriers and targeting acidic tumor sites.

Despite the booming progress of anticancer nanomedicines in the past two decades, precise tumor-targetability and sufficient tumor-accumulation are less successful and still require further research. To tackle this challenge, herein we present a biomolecular motor (FOF1-ATPase)-embedded chromatophore as nanorobot to efficiently overcome biological barriers, and thoroughly investigate its chemotactic motility, tumor-accumulation ability and endocytosis. Chromatophores embedded with FOF1-ATPase motors were firstly extracted from Thermus thermophilus, then their properties were fully characterized. Specifically, two microfluidic platforms (laminar flow microchip and tumor microenvironment (TME) microchip) were designed and developed to fully investigate the motility, tumor-accumulation ability and endocytosis of the chromatophore nanorobot (CN). The results from the laminar flow microchip indicated that the obtained CN possessed the strongly positive chemotaxis towards protons. And the TME microchip experiments verified that the CN had a desirable tumor-accumulation ability. Cellular uptake experiments demonstrated that the CN efficiently promoted the endocytosis of the fluorescence DiO into the HT-29 cells. And the in vivo studies revealed that the intravenously administered CN exhibited vigorous tumor-targetability and accumulation ability as well as highly efficient antitumor efficacy. All the results suggested that FOF1-ATPase motors-embedded CN could be promising nanomachines with powerful self-propulsion for overcoming physiological barriers and tumor-targeted drug delivery. STATEMENT OF SIGNIFICANCE: In this study, we demonstrated that FOF1-ATPase-embedded chromatophore nanorobots exhibit a strong proton chemotaxis, which not only plays a key role in tumor-targetability and accumulation, but also promotes tumor tissue penetration and internalization. The results of in vitro and in vivo studies indicated that drug-loaded chromatophore nanorobots are capable to simultaneously accomplish tumor-targeting, accumulation, penetration and internalization for enhanced tumor therapy. Our study provides a fundamental basis for further study on FOF1-ATPase-embedded chromatophore as tumor-targeting drug delivery systems that have promising clinical applications. It offers a new and more efficient delivery vehicle for cancer related therapeutics.

Dual-energy computed tomography in a multiparametric regression model for diagnosing lymph node metastases in pancreatic ductal adenocarcinoma.

OBJECTIVE: To investigate the diagnostic value of dual-energy computed tomography (DECT) quantitative parameters in the identification of regional lymph node metastasis in pancreatic ductal adenocarcinoma (PDAC). METHODS: This retrospective diagnostic study assessed 145 patients with pathologically confirmed pancreatic ductal adenocarcinoma from August 2016-October 2020. Quantitative parameters for targeted lymph nodes were measured using DECT, and all parameters were compared between benign and metastatic lymph nodes to determine their diagnostic value. A logistic regression model was constructed; the receiver operator characteristics curve was plotted; the area under the curve (AUC) was calculated to evaluate the diagnostic efficacy of each energy DECT parameter; and the DeLong test was used to compare AUC differences. Model evaluation was used for correlation analysis of each DECT parameter. RESULTS: Statistical differences in benign and metastatic lymph nodes were found for several parameters. Venous phase iodine density had the highest diagnostic efficacy as a single parameter, with AUC 0.949 [95% confidence interval (CI):0.915-0.972, threshold: 3.95], sensitivity 79.80%, specificity 96.00%, and accuracy 87.44%. Regression models with multiple parameters had the highest diagnostic efficacy, with AUC 0.992 (95% CI: 0.967-0.999), sensitivity 95.96%, specificity 96%, and accuracy 94.97%, which was higher than that for a single DECT parameter, and the difference was statistically significant. CONCLUSION: Among all DECT parameters for regional lymph node metastasis in PDAC, venous phase iodine density has the highest diagnostic efficacy as a single parameter, which is convenient for use in clinical settings, whereas a multiparametric regression model has higher diagnostic value compared with the single-parameter model.

Using the pedicle screw-U rod system for the treatment of double-level lumbar spondylolysis and isthmic spondylolisthesis.

Objective: The aim of this study was to evaluate the efficacy of the pedicle screw-U rod system in treating double-level lumbar spondylolysis with or without spondylolisthesis. Methods: A retrospective study was conducted. Twenty-six patients were included in this study and followed up at 3, 6, and 12 months. Patients without spondylolisthesis were treated with double U-shaped rods (group I), and patients with spondylolisthesis were treated with a lengthened U-shaped rod (group II). Japanese Orthopedic Association (JOA) scores, Oswestry disability index (ODI) scores, disc range of motion (ROM), intervertebral space height of fixed levels and adjacent levels, and grading the degeneration of adjacent segmental intervertebral discs were evaluated preoperatively and postoperatively. Results: JOA and ODI scores improved significantly at 3 months both in groups I and II. The average bone grafting healing time was 6.1 ± 3.1 months for group I and 6 ± 2.8 months for group II. The intervertebral space heights of L4/L5 and L5/S1 were improved significantly at the final follow-up (p < 0.05 for both groups). Surgical segmental and adjacent segmental ROM had no significant change at the final follow-up, in comparison with data preoperatively (p > 0.05). No significant changes of intervertebral space height (L3/L4) and grading of intervertebral disc degeneration were noted before and after surgery (p = 0.141 and 0.484, respectively). Conclusions: The pedicle screw-U rod system provided advantages of being easy in repairing symptomatic double-level lumbar spondylolysis. This technique improved disabilities of patients, preserved the lumbar spine ROM, and delayed the degeneration of adjacent segments.

Dual-Energy Computed Tomography in Detecting and Predicting Lymph Node Metastasis in Malignant Tumor Patients: A Comprehensive Review.

The accurate and timely assessment of lymph node involvement is paramount in the management of patients with malignant tumors, owing to its direct correlation with cancer staging, therapeutic strategy formulation, and prognostication. Dual-energy computed tomography (DECT), as a burgeoning imaging modality, has shown promising results in the diagnosis and prediction of preoperative metastatic lymph nodes in recent years. This article aims to explore the application of DECT in identifying metastatic lymph nodes (LNs) across various cancer types, including but not limited to thyroid carcinoma (focusing on papillary thyroid carcinoma), lung cancer, and colorectal cancer. Through this narrative review, we aim to elucidate the clinical relevance and utility of DECT in the detection and predictive assessment of lymph node metastasis in malignant tumors, thereby contributing to the broader academic discourse in oncologic radiology and diagnostic precision.

Dancr-BRG1 regulates Nfatc1 transcription and Pgc1ß-dependent metabolic shifts in osteoclastogenesis.

Long non-coding RNA (lncRNA) serves as a vital regulator of bone metabolism, but its role in pathologically overactive osteoclast differentiation remains elusive. Here, we identify lncRNA Dancr (Differentiation Antagonizing Non-protein Coding RNA) as a critical suppressor of osteoclastogenesis and bone resorption, which is down-regulated in response to estrogen deficiency. Global or osteoclast-specific Dancr Knockout mice display significant trabecular bone deterioration and enhanced osteoclast activity, but minimal alteration of bone formation. Moreover, the bone-targeted delivery of Dancr by Adeno-associated viral remarkably attenuates ovariectomy-induced osteopenia in mice. Mechanistically, Dancr establishes a direct interaction with Brahma-related gene 1 to prevent its binding and preserve H3K27me3 enrichment at the nuclear factor of activated T cells 1 and proliferator-activated receptor gamma coactivator 1-beta promoters, thereby maintaining appropriate expression of osteoclastic genes and metabolic programs during osteoclastogenesis. These results demonstrate that Dancr is a key molecule maintaining proper osteoclast differentiation and bone homeostasis under physiological conditions, and Dancr overexpression constitutes a potential strategy for treating osteoporosis.

Bacterial Cellulose-Based Bandages with Integrated Antibacteria and Electrical Stimulation for Advanced Wound Management.

Bandages for daily wounds are the most common medical supplies, but there are still ingrained defects in their appearance, comfort, functions, as well as environmental pollution. Here, novel bandages based on bacterial cellulose (BC) membrane for wound monitoring and advanced wound management are developed. The BC membrane is combined with silver nanowires (AgNWs) by using vacuum filtration method to achieve transparent, ultrathin (≈7 µm), breathable (389.98-547.79 g m-2  d-1 ), and sandwich-structured BC/AgNWs bandages with superior mechanical properties (108.45-202.35 MPa), antibacterial activities against Escherichia coli and Staphylococcus aureus, biocompatibility, and conductivity (9.8 × 103 -2.0 × 105  S m-1 ). Significantly, the BC/AgNWs bandage is used in the electrical stimulation (direct current, 600  microamperes for 1 h every other day) treatment of full-thickness skin defect in rats, which obviously promotes wound healing by increasing the secretion of vascular endothelial growth factor (VEGF). The BC bandage is used for monitoring wounds and achieve a high accuracy of 94.7% in classifying wound healing stages of hemostasis, inflammation, proliferation, and remodeling, by using a convolutional neural network. The outcomes of this study not only provide two BC-based bandages as multifunctional wound management, but also demonstrate a new strategy for the development of the next generation of smart bandage.

Mapping the intellectual structure and landscape of nano-drug delivery systems in colorectal cancer.

Background: Colorectal cancer (CRC) is a prevalent malignancy affecting the digestive tract, and its incidence has been steadily rising over the years. Surgery remains the primary treatment modality for advanced colorectal cancer, complemented by chemotherapy. The development of drug resistance to chemotherapy is a significant contributor to treatment failure in colorectal cancer. Nanodrug delivery systems (NDDS) can significantly improve the delivery and efficacy of antitumor drugs in multiple ways. However, there is a lack of visualization of NDDS research structures and research hotspots in the field of colorectal cancer, and the elaboration of potential research areas remains to be discovered. Objective: To comprehensively explore the current research status and development trend of NDDS in CRC research. Methods: Bibliometric analysis of articles and reviews on NDDS for CRC published between 2002 and 2022 using tools including CiteSpace, VOSviewer, R-bibliometrix, and Microsoft Excel was performed. Results: A total of 1866 publications authored by 9,870 individuals affiliated with 6,126 institutions across 293 countries/regions were included in the analysis. These publications appeared in 456 journals. Abnous Khalil has the highest number of publications in this field. The most published journals are the International Journal of Nanomedicine, International Journal of Pharmaceutics, and Biomaterials. Notably, the Journal of Controlled Release has the highest citation count and the third-highest H-index. Thematic analysis identified "inflammatory bowel disease"," "oral drug delivery," and "ulcerative colitis" as areas requiring further development. Keyword analysis revealed that "ulcerative colitis," "exosomes," and "as1411"have emerged as keywords within the last 2 years. These emerging keywords may become the focal points of future research. Conclusion: Our findings reveal the current research landscape and intellectual structure of NDDS in CRC research which helps researchers understand the research trends and hot spots in this field.

From imaging to clinical outcome: dual-region CT radiomics predicting FOXM1 expression and prognosis in hepatocellular carcinoma.

Background: Liver cancer, especially hepatocellular carcinoma (HCC), remains a significant global health challenge. Traditional prognostic indicators for HCC often fall short in providing comprehensive insights for individualized treatment. The integration of genomics and radiomics offers a promising avenue for enhancing the precision of HCC diagnosis and prognosis. Methods: From the Cancer Genome Atlas (TCGA) database, we categorized mRNA of HCC patients by Forkhead Box M1 (FOXM1) expression and performed univariate and multivariate studies to pinpoint autonomous HCC risk factors. We deployed subgroup, correlation, and interaction analyses to probe FOXM1's link with clinicopathological elements. The connection between FOXM1 and immune cells was evaluated using the CIBERSORTx database. The functions of FOXM1 were investigated through analyses of Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). After filtering through TCGA and the Cancer Imaging Archive (TCIA) database, we employed dual-region computed tomography (CT) radiomics technology to noninvasively predict the mRNA expression of FOXM1 in HCC tissues. Radiomic features were extracted from both tumoral and peritumoral regions, and a radiomics score (RS) was derived. The performance and robustness of the constructed models were evaluated using 10-fold cross-validation. A radiomics nomogram was developed by incorporating RS and clinical variables from the TCGA database. The models' discriminative abilities were assessed using metrics such as the area under the curve (AUC) of the receiver operating characteristic curves (ROC) and precision-recall (PR) curves. Results: Our findings emphasized the overexpression of FOXM1 as a determinant of poor prognosis in HCC and illustrated its impact on immune cell infiltration. After selecting arterial phase CT, we chose 7 whole-tumor features and 3 features covering both the tumor and its surroundings to create WT and WP models for FOXM1 prediction. The WT model showed strong predictive capabilities for FOXM1 expression by PR curve. Conversely, the WP model did not demonstrate the good predictive ability. In our study, the radiomics score (RS) was derived from whole-tumor regions on CT images. The RS was significantly associated with FOXM1 expression, with an AUC of 0.918 in the training cohort and 0.837 in the validation cohort. Furthermore, the RS was correlated with oxidative stress genes and was integrated with clinical variables to develop a nomogram, which demonstrated good calibration and discrimination in predicting 12-, 36-, and 60-month survival probabilities. Additionally, bioinformatics analysis revealed FOXM1's potential role in shaping the immune microenvironment, with its expression linked to immune cell infiltration. Conclusion: This study highlights the potential of integrating FOXM1 expression and radiomics in understanding HCC's complexity. Our approach offers a new perspective in utilizing radiomics for non-invasive tumor characterization and suggests its potential in providing insights into molecular profiles. Further research is needed to validate these findings and explore their clinical implications in HCC management.

Endothelial Cell-Derived Lactate Triggers Bone Mesenchymal Stem Cell Histone Lactylation to Attenuate Osteoporosis.

Blood vessels play a role in osteogenesis and osteoporosis; however, the role of vascular metabolism in these processes remains unclear. The present study finds that ovariectomized mice exhibit reduced blood vessel density in the bone and reduced expression of the endothelial glycolytic regulator pyruvate kinase M2 (PKM2). Endothelial cell (EC)-specific deletion of Pkm2 impairs osteogenesis and worsens osteoporosis in mice. This is attributed to the impaired ability of bone mesenchymal stem cells (BMSCs) to differentiate into osteoblasts. Mechanistically, EC-specific deletion of Pkm2 reduces serum lactate levels secreted by ECs, which affect histone lactylation in BMSCs. Using joint CUT&Tag and RNA sequencing analyses, collagen type I alpha 2 chain (COL1A2), cartilage oligomeric matrix protein (COMP), ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1), and transcription factor 7 like 2 (TCF7L2) as osteogenic genes regulated by histone H3K18la lactylation are identified. PKM2 overexpression in ECs, lactate addition, and exercise restore the phenotype of endothelial PKM2-deficient mice. Furthermore, serum metabolomics indicate that patients with osteoporosis have relatively low lactate levels. Additionally, histone lactylation and related osteogenic genes of BMSCs are downregulated in patients with osteoporosis. In conclusion, glycolysis in ECs fuels BMSC differentiation into osteoblasts through histone lactylation, and exercise partially ameliorates osteoporosis by increasing serum lactate levels.

Contrast-enhanced CT-based radiomic analysis for determining the response to anti-programmed death-1 therapy in esophageal squamous cell carcinoma patients: A pilot study.

BACKGROUND: In view of the fact that radiomics features have been reported as predictors of immunotherapy to various cancers, this study aimed to develop a prediction model to determine the response to anti-programmed death-1 (anti-PD-1) therapy in esophageal squamous cell carcinoma (ESCC) patients from contrast-enhanced CT (CECT) radiomics features. METHODS: Radiomic analysis of images was performed retrospectively for image samples before and after anti-PD-1 treatment, and efficacy analysis was performed for the results of two different time node evaluations. A total of 68 image samples were included in this study. Quantitative radiomic features were extracted from the images, and the least absolute shrinkage and selection operator method was applied to select radiomic features. After obtaining selected features, three classification models were used to establish a radiomics model to predict the ESCC status and efficacy of therapy. A cross-validation strategy utilizing three folds was employed to train and test the model. Performance evaluation of the model was done using the area under the curve (AUC) of receiver operating characteristic, sensitivity, specificity, and precision metric. RESULTS: Wavelet and area of gray level change (log-sigma) were the most significant radiomic features for predicting therapy efficacy. Fifteen radiomic features from the whole tumor and peritumoral regions were selected and comprised of the fusion radiomics score. A radiomics classification was developed with AUC of 0.82 and 0.884 in the before and after-therapy cohorts, respectively. CONCLUSIONS: The combined model incorporating radiomic features and clinical CECT predictors helps to predict the response to anti-PD-1therapy in patients with ESCC.

Identification of ROCK1 as a novel biomarker for postmenopausal osteoporosis and pan-cancer analysis.

BACKGROUND: Postmenopausal osteoporosis (PMOP) is a prevalent bone disorder with significant global impact. The elevated risk of osteoporotic fracture in elderly women poses a substantial burden on individuals and society. Unfortunately, the current lack of dependable diagnostic markers and precise therapeutic targets for PMOP remains a major challenge. METHODS: PMOP-related datasets GSE7429, GSE56814, GSE56815, and GSE147287, were downloaded from the GEO database. The DEGs were identified by "limma" packages. WGCNA and Machine Learning were used to choose key module genes highly related to PMOP. GSEA, DO, GO, and KEGG enrichment analysis was performed on all DEGs and the selected key hub genes. The PPI network was constructed through the GeneMANIA database. ROC curves and AUC values validated the diagnostic values of the hub genes in both training and validation datasets. xCell immune infiltration and single-cell analysis identified the hub genes' function on immune reaction in PMOP. Pan-cancer analysis revealed the role of the hub genes in cancers. RESULTS: A total of 1278 DEGs were identified between PMOP patients and the healthy controls. The purple module and cyan module were selected as the key modules and 112 common genes were selected after combining the DEGs and module genes. Five Machine Learning algorithms screened three hub genes (KCNJ2, HIPK1, and ROCK1), and a PPI network was constructed for the hub genes. ROC curves validate the diagnostic values of ROCK1 in both the training (AUC = 0.73) and validation datasets of PMOP (AUC = 0.81). GSEA was performed for the low-ROCK1 patients, and the top enriched field included protein binding and immune reaction. DCs and NKT cells were highly expressed in PMOP. Pan-cancer analysis showed a correlation between low ROCK1 expression and SKCM as well as renal tumors (KIRP, KICH, and KIRC). CONCLUSIONS: ROCK1 was significantly associated with the pathogenesis and immune infiltration of PMOP, and influenced cancer development, progression, and prognosis, which provided a potential therapy target for PMOP and tumors. However, further laboratory and clinical evidence is required before the clinical application of ROCK1 as a therapeutic target.

Neurobehavioral effects of general anesthesia and cochlear implantation on hearing-impaired infants: A prospective observational cohort study.

INTRODUCTION: The potential adverse effects of prolonged exposure to anesthetics in pediatric patients with severe-to-profound sensorineural hearing loss remain unclear. This study aimed to examine whether early bilateral cochlear implantation involving long-duration anesthetic exposure caused greater developmental impairment than that with unilateral cochlear implantation. METHODS: This prospective observational study included normally developing infants with bilateral severe-to-profound sensorineural hearing loss aged 6 months to 2 years who were candidates for unilateral/bilateral cochlear implantation surgery. Baseline (T0), 6-month (T1), and 1-year (T2) Gesell Scale scores were measured. The outcomes included fine motor, adaptability, gross motor, language, and social skills scale 6 and 12 months postoperatively. RESULT: The 90 enrolled children with bilateral severe-to-profound sensorineural hearing loss (unilateral n = 43; bilateral n = 47) had a younger bilateral group (11.00 ± 3.66 vs. 15.63 ± 6.99 months, p < .001). Anesthesia duration was longer in the bilateral group (271.57 ± 36.09 vs. 148.81 ± 25.60 min, p < .001). Gross motor, fine motor, adaptability, and language scores improved in both groups, and no significant between-group differences occurred in the fine motor scale at T1 and T2. Language developmental quotients improved significantly in the bilateral group compared with the unilateral group at T1 (mean differences: 25.07 ± 4.37 vs. 10.88 ± 4.61, p < .001) and T2 (mean differences: 34.98 ± 5.94 vs. 15.28 ± 6.55, p < .001). Stepwise regression revealed that gross motor, adaptability, language, and social skill developmental quotients at T1 were positively correlated with those at T0. Gross motor, fine motor, and social skill developmental quotients at T2 were negatively correlated with age at operation. Language developmental quotients were positively correlated with T0 values (p < .001) and in the bilateral group (p < .001) at T1 and T2. CONCLUSIONS: When evaluating young children with bilateral severe-to-profound sensorineural hearing loss, despite longer exposures to general anesthesia, bilateral cochlear implantations were associated with more improvement in language scores and no differences in other skills compared with those with only unilateral implantation.

Strength and Deformation Characteristics of Fiber and Cement-Modified Waste Slurry.

Using fiber and cement to modify waste slurry and apply it to roads is an effective way to recycle waste slurry. A new type of road material, fiber-cement-modified waste slurry (FRCS), was prepared in this study. The static and dynamic characteristics of the cement soil were studied using an unconfined compressive strength test and dynamic triaxial test. The results show that the optimum fiber content of FRCS is 0.75%. In the unconfined compressive strength test, under this fiber content, the unconfined compressive strength (UCS) of the FRCS is the largest, and the elastic modulus and modulus strength ratio are both the smallest, indicating that the tensile properties of the cement slurry have been enhanced. In the dynamic triaxial test, the hysteretic curve of the FRCS tends to be stable with the increase in the number of cycles, the dynamic elastic modulus of the FRCS decreases first and then increases with the increase in the dosage, while the damping ratio becomes stable after a rapid decline, and the fiber incorporation increases the cumulative strain of the soil-cement under low-stress cycles, indicating that the ductility of the FRCS is improved. In addition, a cumulative strain prediction model of the FRCS is established in this paper, which can provide a reference for the resource application of waste slurry in road engineering.

Co-application of biochar and organic amendments on soil greenhouse gas emissions: A meta-analysis.

Biochar has been shown to reduce soil greenhouse gas (GHG) and increase nutrient retention in soil; however, the interaction between biochar and organic amendments on GHG emissions remain largely unclear. In this study, we collected 162 two-factor observations to explore how biochar and organic amendments jointly affect soil GHG emissions. Our results showed that biochar addition significantly increased soil CO2 emission by 8.62 %, but reduced CH4 and N2O emissions by 27.0 % and 23.9 %, respectively. Meanwhile, organic amendments and the co-application with biochar resulted in an increase of global warming potential based on the 100-year time horizon (GWP100) by an average of 18.3 % and 26.1 %. More importantly, the interactive effect of biochar and organic amendments on CO2 emission was antagonistic (the combined effect was weaker than the sum of their individual effects), while additive on CH4 and N2O emissions. Additionally, our results suggested that when biochar is co-applied with organic amendments, soil GHG emissions were largely influenced by soil initial total carbon, soil texture, and biochar feedstocks. Our work highlights the important interactive effects of biochar and organic amendments on soil GHG emissions, and provides new insights for promoting ecosystem sustainability as well as mitigating future climate change.

Artificial intelligence-based radiomics in bone tumors: Technical advances and clinical application.

Radiomics is the extraction of predefined mathematic features from medical images for predicting variables of clinical interest. Recent research has demonstrated that radiomics can be processed by artificial intelligence algorithms to reveal complex patterns and trends for diagnosis, and prediction of prognosis and response to treatment modalities in various types of cancer. Artificial intelligence tools can utilize radiological images to solve next-generation issues in clinical decision making. Bone tumors can be classified as primary and secondary (metastatic) tumors. Osteosarcoma, Ewing sarcoma, and chondrosarcoma are the dominating primary tumors of bone. The development of bone tumor model systems and relevant research, and the assessment of novel treatment methods are ongoing to improve clinical outcomes, notably for patients with metastases. Artificial intelligence and radiomics have been utilized in almost full spectrum of clinical care of bone tumors. Radiomics models have achieved excellent performance in the diagnosis and grading of bone tumors. Furthermore, the models enable to predict overall survival, metastases, and recurrence. Radiomics features have exhibited promise in assisting therapeutic planning and evaluation, especially neoadjuvant chemotherapy. This review provides an overview of the evolution and opportunities for artificial intelligence in imaging, with a focus on hand-crafted features and deep learning-based radiomics approaches. We summarize the current application of artificial intelligence-based radiomics both in primary and metastatic bone tumors, and discuss the limitations and future opportunities of artificial intelligence-based radiomics in this field. In the era of personalized medicine, our in-depth understanding of emerging artificial intelligence-based radiomics approaches will bring innovative solutions to bone tumors and achieve clinical application.

In Situ Enzymatic Reaction Generates Magnesium-Based Mineralized Microspheres with Superior Bioactivity for Enhanced Bone Regeneration.

Bone is a naturally mineralized tissue with a remarkable hierarchical structure, and the treatment of bone defects remains challenging. Microspheres with facile features of controllable size, diverse morphologies, and specific functions display amazing potentials for bone regeneration. Herein, inspired by natural biomineralization, a novel enzyme-catalyzed reaction is reported to prepare magnesium-based mineralized microspheres. First, silk fibroin methacryloyl (SilMA) microspheres are prepared using a combination of microfluidics and photo-crosslinking. Then, the alkaline phosphatase (ALP)-catalyzed hydrolysis of adenosine triphosphate (ATP) is successfully used to induce the formation of spherical magnesium phosphate (MgP) in the SilMA microspheres. These SilMA@MgP microspheres display uniform size, rough surface structure, good degradability, and sustained Mg2+ release properties. Moreover, the in vitro studies demonstrate the high bioactivities of SilMA@MgP microspehres in promoting the proliferation, migration, and osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs). Transcriptomic analysis shows that the osteoinductivity of SilMA@MgP microspheres may be related to the activation of the PI3K/Akt signaling pathway. Finally, the bone regeneration enhancement units (BREUs) are designed and constructed by inoculating BMSCs onto SilMA@MgP microspheres. In summary, this study demonstrates a new biomineralization strategy for designing biomimetic bone repair materials with defined structures and combination functions.

FOF1-ATPase Motor-Embedded Chromatophore as Drug Delivery System: Extraction, Cargo Loading Ability and Mucus Penetration Ability.

Mucosal drug delivery permits direct and prompt drug absorption, which is capable of reducing undesirable decomposition that occurs before absorption. However, mucus clearance of those mucosal drug delivery systems strongly retards their actual application. Herein, we propose chromatophore nanoparticles embedded with FOF1-ATPase motors to promote mucus penetration. The FOF1-ATPase motor-embedded chromatophores were firstly extracted from Thermus thermophilus by using a gradient centrifugation method. Then, the model drug (curcumin) was loaded onto the chromatophores. The drug loading efficiency and entrapment efficiency were optimized by using different loading approaches. The activity, motility, stability and mucus permeation of the drug-loaded chromatophore nanoparticles were thoroughly investigated. Both the in vitro and in vivo studies revealed that the FOF1-ATPase motor-embedded chromatophore successfully enhanced mucus penetration glioma therapy. This study indicates that the FOF1-ATPase motor-embedded chromatophore is a promising alternative as a mucosal drug delivery system.

Deubiquitinase USP13 regulates glycolytic reprogramming and progression in osteosarcoma by stabilizing METTL3/m6A/ATG5 axis.

Reprogramming metabolism is a hallmark of cancer cells for rapid progression. However, the detailed functional role of deubiquitinating enzymes (DUBs) in tumor glycolytic reprogramming is still unknown and requires further investigation. USP13 was found to upregulate in osteosarcoma (OS) specimens and promote OS progression through regulating aerobic glycolysis. Interestingly, the m6A writer protein, METTL3, has been identified as a novel target of USP13. USP13 interacts with, deubiquitinates, and therefore stabilizes METTL3 at K488 by removing K48-linked ubiquitin chains. Since METTL3 is a well-known m6A writer and USP13 stabilizes METTL3, we further found that USP13 increased global m6A abundance in OS cells. The results of RNA sequencing and methylated RNA immunoprecipitation sequencing indicated METTL3 could bind to m6A-modified ATG5 mRNA, which is crucial for autophagosome formation, and inhibit ATG5 mRNA decay on an IGF2BP3 dependent manner, thereby promoting autophagy and the autophagy-associated malignancy of OS. Using a small-molecule inhibitor named Spautin-1 to pharmacologically inhibit USP13 induced METTL3 degradation and exhibited significant therapeutic efficacy both in vitro and in vivo. Collectively, our study results indicate that USP13 promotes glycolysis and tumor progression in OS by stabilizing METTL3, thereby stabilizing ATG5 mRNA and facilitating autophagy in OS. Our findings demonstrate the role of the USP13-METTL3-ATG5 cascade in OS progression and show that USP13 is a crucial DUB for the stabilization of METTL3 and a promising therapeutic target for treating OS.