Corrigendum: Identification of immune-related genes in diagnosing atherosclerosis with rheumatoid arthritis through bioinformatics analysis and machine learning.

[This corrects the article DOI: 10.3389/fimmu.2023.1126647.].

Half of the adolescent idiopathic scoliosis patients may have lumbar adjacent segment degeneration following spinal fusion: A systemic review and meta-analysis.

OBJECTIVE: This study aims to assess the impact of surgical approaches and other factors on the incidence of Adjacent Segment Degeneration (ASD) following Spinal Fusion for Adolescent Idiopathic Scoliosis (AIS). METHODS: We conducted a comprehensive search of four electronic databases from their inception until March 30, 2023. Two independent reviewers screened titles, abstracts, and full texts and evaluated the methodological quality of the studies. A random-effects model was used to calculate the incidence of ASD. RESULTS: Our analysis included 14 studies involving 651 individuals. The overall incidence of ASD was 47% (95%CI: 0.37, 0.56). Subgroup analyses revealed that the prevalence of ASD increased with postoperative time (53% (95%CI: 0.31, 0.75) versus 48% (95%CI: 0.36, 0.60) versus 39% (95%CI: 0.22, 0.56)). For the number of fused segments, a group with more than 10 segments had a higher prevalence (49% (95%CI: 0.38, 0.60) versus 44% (95%CI: 0.21, 0.69)). In terms of regions, East Asia had the highest prevalence, followed by Occident and West Asia (52% (95%CI: 0.41, 0.62) versus 43% (95%CI: 0.20, 0.68) versus 37% (95%CI: 0.17, 0.59)). However, the surgical approach, male ratio, and the position of the lowest instrumented vertebra (LIV) did not show significant differences between groups. Funnel plots and Egger's test did not reveal any significant publication bias (Egger's test: t = 1.62, p-value = .1274). CONCLUSION: This meta-analysis found that nearly half of AIS patients following spinal fusion surgery experienced ASD. Long-term follow-up, regular screening, and timely interventions are essential to reduce the prevalence of ASD.

An overview of 3D printed metal implants in orthopedic applications: Present and future perspectives.

With the ability to produce components with complex and precise structures, additive manufacturing or 3D printing techniques are now widely applied in both industry and consumer markets. The emergence of tissue engineering has facilitated the application of 3D printing in the field of biomedical implants. 3D printed implants with proper structural design can not only eliminate the stress shielding effect but also improve in vivo biocompatibility and functionality. By combining medical images derived from technologies such as X-ray scanning, CT, MRI, or ultrasonic scanning, 3D printing can be used to create patient-specific implants with almost the same anatomical structures as the injured tissues. Numerous clinical trials have already been conducted with customized implants. However, the limited availability of raw materials for printing and a lack of guidance from related regulations or laws may impede the development of 3D printing in medical implants. This review provides information on the current state of 3D printing techniques in orthopedic implant applications. The current challenges and future perspectives are also included.

Identification of immune-related genes in diagnosing atherosclerosis with rheumatoid arthritis through bioinformatics analysis and machine learning.

Background: Increasing evidence has proven that rheumatoid arthritis (RA) can aggravate atherosclerosis (AS), and we aimed to explore potential diagnostic genes for patients with AS and RA. Methods: We obtained the data from public databases, including Gene Expression Omnibus (GEO) and STRING, and obtained the differentially expressed genes (DEGs) and module genes with Limma and weighted gene co-expression network analysis (WGCNA). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analysis, the protein-protein interaction (PPI) network, and machine learning algorithms [least absolute shrinkage and selection operator (LASSO) regression and random forest] were performed to explore the immune-related hub genes. We used a nomogram and receiver operating characteristic (ROC) curve to assess the diagnostic efficacy, which has been validated with GSE55235 and GSE73754. Finally, immune infiltration was developed in AS. Results: The AS dataset included 5,322 DEGs, while there were 1,439 DEGs and 206 module genes in RA. The intersection of DEGs for AS and crucial genes for RA was 53, which were involved in immunity. After the PPI network and machine learning construction, six hub genes were used for the construction of a nomogram and for diagnostic efficacy assessment, which showed great diagnostic value (area under the curve from 0.723 to 1). Immune infiltration also revealed the disorder of immunocytes. Conclusion: Six immune-related hub genes (NFIL3, EED, GRK2, MAP3K11, RMI1, and TPST1) were recognized, and the nomogram was developed for AS with RA diagnosis.

Rodent Models of Spinal Cord Injury: From Pathology to Application.

Spinal cord injury (SCI) often has devastating consequences for the patient's physical, mental and occupational health. At present, there is no effective treatment for SCI, and appropriate animal models are very important for studying the pathological manifestations, injury mechanisms, and corresponding treatment. However, the pathological changes in each injury model are different, which creates difficulties in selecting appropriate models for different research purposes. In this article, we analyze various SCI models and introduce their pathological features, including inflammation, glial scar formation, axon regeneration, ischemia-reperfusion injury, and oxidative stress, and evaluate the advantages and disadvantages of each model, which is convenient for selecting suitable models for different injury mechanisms to study therapeutic methods.

Family Functioning Affected by Adolescent Idiopathic Scoliosis in China: A Cross-Sectional Study.

Adolescent idiopathic scoliosis (AIS) is a common chronic disease in youths, presenting with spinal deformity. Previous studies reported that the family functioning of family members would be affected after a child is diagnosed with a chronic health condition. However, no previous study focused on the relationship between AIS and family function. This study is a cross-sectional study that enrolled 54 AIS families and 92 ordinary families and evaluated their family function in 7 domains using the McMaster family assessment device (FAD). The results showed that the AIS family got a lower score than a healthy family in all 7 subscales except for the problem-solving subscale. There was no significant difference between the patients with AIS (1.90 ± 0.42∼2.23 ± 0.32) and their parents (1.92 ± 0.35∼2.21 ± 0.29) in all seven subscales (p ≥ 0.05). The scores of the parents were moderately/strongly correlated with those of the patients with AIS in all seven subscales (γ = 0.456∼0.696, p < 0.05). Approximately, 20.4-87% of the families experienced unhealthy family functioning, with affective involvement (57.4%), and behavior control (87%) representing the unhealthiest subscales with the mean scores above the cutoff. It can be concluded that the AIS family performed better than a healthy family in family functions.