Computed tomography radiomics in predicting patient satisfaction after robotic-assisted total knee arthroplasty.

PURPOSE: After robotic-assisted total knee arthroplasty (RA-TKA) surgery, some patients still experience joint discomfort. We aimed to establish an effective machine learning model that integrates radiomic features extracted from computed tomography (CT) scans and relevant clinical information to predict patient satisfaction three months postoperatively following RA-TKA. MATERIALS AND METHODS: After careful selection, data from 142 patients were randomly divided into a training set (n = 99) and a test set (n = 43), approximately in a 7:3 ratio. A total of 1329 radiomic features were extracted from the regions of interest delineated in CT scans. The features were standardized using normalization algorithms, and the least absolute shrinkage and selection operator regression model was employed to select radiomic features with ICC > 0.75 and P < 0.05, generating the Rad-score as feature markers. Univariate and multivariate logistic regression was then used to screen clinical information (age, body mass index, operation time, gender, surgical side, comorbidities, preoperative KSS score, preoperative range of motion (ROM), preoperative and postoperative HKA angle, preoperative and postoperative VAS score) as potential predictive factors. The satisfaction scale ≥ 20 indicates patient satisfaction. Finally, three prediction models were established, focusing on radiomic features, clinical features, and their fusion. Model performance was evaluated using Receiver Operating Characteristic curves and decision curve analysis. RESULTS: In the training set, the area under the curve (AUC) of the clinical model was 0.793 (95% CI 0.681-0.906), the radiomic model was 0.854 (95% CI 0.743-0.964), and the combined radiomic-clinical model was 0.899 (95% CI 0.804-0.995). In the test set, the AUC of the clinical model was 0.908 (95% CI 0.814-1.000), the radiomic model was 0.709 (95% CI 0.541-0.878), and the combined radiomic-clinical model was 0.928 (95% CI 0.842-1.000). The AUC of the radiomic-clinical model was significantly higher than the other two models. The decision curve analysis indicated its clinical application value. CONCLUSION: We developed a radiomic-based nomogram model using CT imaging to predict the satisfaction of RA-TKA patients at 3 months postoperatively. This model integrated clinical and radiomic features and demonstrated good predictive performance and excellent clinical application potential.

Robot-assisted total knee arthroplasty system provides more precise control of the femoral rotation angle: A retrospective study.

BACKGROUND: Rotational alignment in total knee arthroplasty (TKA) is a crucial technical point that needs attention. We conducted a retrospective study to investigate whether a new robot-assisted TKA (RA-TKA) could improve the accuracy of rotational alignment and whether rotational alignment affects postoperative pain and functional evaluation of the knee. METHODS: A total of 136 consecutive patients who underwent TKA were included in this study. Half of the patients underwent RA-TKA and the other half underwent conventional TKA (CON-TKA) by the same group of surgeons. Collect the relevant parameters. RESULTS: The postoperative femoral rotation angle (FRA) was -0.72 ± 2.59° in the robot-assisted group and 1.13 ± 2.73° in the conventional group, and were statistically significantly different (p < 0.001). CONCLUSION: This study provides preliminary evidence that the RA-TKA provides more precise control of FRA than CON-TKA, and verifies that tibial rotation angle and combined rotation angle affect postoperative knee pain and functional evaluation.

Corrigendum: Bioinformatic analysis of related immune cell infiltration and key genes in the progression of osteonecrosis of the femoral head.

[This corrects the article DOI: 10.3389/fimmu.2023.1340446.].

Dehydroandrographolide alleviates rheumatoid arthritis by inhibiting neutrophil activation via LMIR3 in collagen induced arthritis rats.

Rheumatoid arthritis (RA) is an inflammatory disease which causes severe pain and disability. Neutrophils play essential roles in the onset and progression of RA; thus, inhibition of neutrophil activation is becoming a popular therapeutic strategy. Dehydroandrographolide has provided satisfactory outcomes in inflammatory diseases; however, its therapeutic effects and mechanism in RA are not fully understood. Leukocyte mono-immunoglobulin-like receptor 3 (LMIR3) is a negative regulator highly expressed in neutrophils. To determine whether dehydroandrographolide negatively regulated neutrophils activation via LMIR3, cytokines release and collagen-induced arthritis (CIA) rats were used in vitro and in vivo. Biacore, molecular docking analysis and molecular dynamics simulation were performed to prove the target of dehydroandrographolide. Moreover, the downstream signaling pathways of LMIR3 activation were analyzed by western blotting. Results showed that oral dehydroandrographolide administration of 2 mg/kg/day to CIA rats attenuated synovitis and bone and cartilage damage after the 28-day intervention, revealed using HE sections and micro-CT. Dehydroandrographolide significantly inhibited cytokine release and chemotaxis of LPS/TNF-α-activated neutrophils in vitro. Dehydroandrographolide inhibited neutrophils activation via binding to LMIR3. Moreover, dehydroandrographolide up-regulated the phosphorylation of SHP-1 and SHP-2, which are the essential kinases in the LMIR3 signaling pathways. This study revealed that dehydroandrographolide attenuated collagen-induced arthritis by suppressing neutrophil activation via LMIR3.

Bioinformatic analysis of related immune cell infiltration and key genes in the progression of osteonecrosis of the femoral head.

Objective: Osteonecrosis of the femoral head (ONFH) is a common orthopedic condition that will prompt joint dysfunction, significantly impacting patients' quality of life. However, the specific pathogenic mechanisms underlying this disease remain elusive. The objective of this study is to examine the differentially expressed messenger RNAs (DE mRNAs) and key genes linked to ONFH, concurrently investigating the immune cell infiltration features in ONFH patients through the application of the CIBERSORT algorithm. Methods: Microarray was applied to scrutinize mRNA expression profiles in both ONFH patients and healthy controls, with data integration sourced from the GEO database. DE mRNAs were screened using the Limma method. The biological functions of DE mRNAs were explored through the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, Gene Ontology (GO) functional analysis, and Gene Set Enrichment Analysis (GSEA). Additionally, support vector machine-recursive feature elimination (SVM-RFE) and the least absolute shrinkage and selection operator (LASSO) were employed to discern diagnostic biomarkers associated with the disease. Receiver operating characteristic (ROC) analysis was utilized to assess the statistical performance of the feature genes. The validation of key genes was performed using qRT-PCR in bone tissues obtained from ONFH patients and healthy controls. Osteogenic differentiation of BMSC was then performed and detected by alkaline phosphatase staining (ALP) and qRT-PCR to verify the correlation between key genes and osteogenic differentiation. Finally, immune cell infiltration analysis was executed to evaluate immune cell dysregulation in ONFH, concurrently exploring the correlation between the infiltration of immune cells and key genes. Results: After consolidating the datasets, the Limma method revealed 107 DEGs, comprising 76 downregulated and 31 upregulated genes. Enrichment analysis revealed close associations of these DE mRNAs with functions such as cell migration, osteoblast differentiation, cartilage development and extracellular region. Machine learning algorithms further identified APOD, FBXO43 and LRP12 as key genes. ROC curves demonstrated the high diagnostic efficacy of these genes. The results of qRT-PCR showed that the expression levels of key genes were consistent with those of microarray analysis. In addition, the results of in vitro experiments showed that APOD was closely related to osteogenic differentiation of BMSC. Immune infiltration analysis suggested a close correlation between ONFH and imbalances in levels of Neutrophils, Monocytes, Macrophages M2, Dendritic cells activated and Dendritic cells resting. Conclusion: APOD is closely related to osteogenic differentiation of BMSCs and can be used as a diagnostic marker of ONFH. Immune cell infiltration significantly differs between controls and ONFH patients.

Astragalin mitigates inflammatory osteolysis by negatively modulating osteoclastogenesis via ROS and MAPK signaling pathway.

Inflammatory bone destruction has gradually attracted attention worldwide and has been observed in several kinds of pathological bone diseases, such as osteoarthritis, osteomyelitis, rheumatic arthritis, and other infectious clinical trials in the skeletal system. In this regard, excessive osteoclasts and bone resorption activity participate in osteolytic processes. Thus, negatively modulating osteoclast differentiation and bone erosion has been considered an effective therapeutic strategy to limit the poor progression of inflammatory osteolysis. Astragalin (AST) is a bioactive component of traditional Chinese drugs, such as Rosa agrestis, which presents anti-inflammatory and antioxidant effects. However, it is unclear how AST may play an essential role in regulating the dynamic balance of the bone matrix by affecting osteoclastogenesis. This study found that AST could inhibit osteoclastic formation and bone resorption activity in a dose-dependent manner without cytotoxicity. Administration of AST also inhibited the expression of cathepsin K, c-Fos, NFATc1, and TRAP at different stages of mRNA and protein levels during osteoclastogenesis. Reactive oxygen species (ROS) signalling could also be modulated by treatment with AST during RANKL-induced osteoclast differentiation through the Nrf2-HO1 signalling pathway. Additionally, AST could negatively regulate mitogen-activated protein kinase (MAPK) signalling in this process. In vivo, AST significantly reduced lipopolysaccharide (LPS)-induced bone loss in an osteolytic mouse model. AST might be a promising therapeutic candidate for treating osteolytic bone diseases in the future.

Melatonin increases bone mass in normal, perimenopausal, and postmenopausal osteoporotic rats via the promotion of osteogenesis.

BACKGROUND: Osteoporosis is a disease threatening the health of millions of individuals. Melatonin is found to be a potential anti-osteoporosis drug. However, whether melatonin plays a role against osteoporosis at different stages of the menopause and the underlying mechanisms are unknown. METHODS: Ovariectomy was utilized as a model of perimenopausal and postmenopausal osteoporosis. A total of 100 mg/kg melatonin, or solvent alone, was added to the drinking water of the rats over 8 weeks. Perimenopausal rats immediately received intervention following ovariectomy while postmenopausal rats received intervention 8 weeks after ovariectomy. All rats underwent overdose anesthesia following intervention after which blood samples and femurs were collected for further analysis. Rat femurs were scanned using micro-CT and examined histologically. The serum levels of melatonin and osteogenic biochemical markers were measured and the expression of osteogenesis-associated genes (Runx2, Sp7) were quantified by real-time quantitative PCR. Alkaline phosphatase (ALP) activity and the gene expression (Col1a1, Runx2, Alpl, and Bglap) were measured after bone marrow mesenchymal stem cells (BMSCs) were osteogenically induced, both with and without melatonin in vitro. ALP staining and Alizarin Red S staining were used to identify osteogenesis. RESULTS: Analysis by micro-CT and histological staining demonstrated that bone mass decreased and bone microarchitecture deteriorated over time after ovariectomy. Intervention with melatonin increased bone mass in normal, perimenopausal, and postmenopausal osteoporotic rats. Serum levels of ALP continuously increased after ovariectomy while osteocalcin levels initially rose, then decreased. Melatonin increased the serum levels of ALP and osteocalcin and mRNA expression levels of Runx2 and Sp7 in normal and postmenopausal rats, the opposite of the markers in perimenopausal rats. In vitro study demonstrated that 100 µmol/L melatonin increased the mRNA expression of Col1a1, Runx2, and Alpl three and/or seven days after intervention, and Alpl and Bglap 14 d after intervention. Melatonin increased ALP activity and the extent of ALP and matrix mineralization in the late stage of osteogenesis. CONCLUSIONS: Bone mass continuously decreased after ovariectomy, while melatonin increased bone mass and ameliorated bone metabolism in normal, perimenopausal, and postmenopausal osteoporotic rats due to the induction of osteogenic differentiation in BMSCs.

Long noncoding RNA LMO7DN inhibits cell proliferation by regulating the cell cycle in lung adenocarcinoma.

In our previous study, we reported that the long noncoding RNA, LMO7 downstream neighbor (LMO7DN), has a strong prognostic value in lung adenocarcinoma (LUAD). In this study, we further investigated the role of LMO7DN in LUAD progression. LMO7DN was found to be expressed at low levels in LUAD tissues, and its high expression predicted good prognosis. Bioinformatics analysis indicated that LMO7DN was closely associated with the cell cycle. Furthermore, we found that cell proliferation was significantly enhanced following knockdown of LMO7DN, and the number of cells in the G2/M phase was markedly decreased, whereas there was no change in apoptosis. Thus, LMO7DN inhibits cell proliferation by affecting the cell cycle and is of significant prognostic value in LUAD.