Mid-term outcomes of microfragmented adipose tissue plus arthroscopic surgery for knee osteoarthritis: A randomized, active-control, multicenter clinical trial.

Background: Osteoarthritis (OA) is the most prevalent form of degenerative whole-joint disease. Before the final option of knee replacement, arthroscopic surgery was the most widely used joint-preserving surgical treatment. Emerging regenerative therapies, such as those involving platelet-rich plasma, mesenchymal stem cells, and microfragmented adipose tissue (MFAT), have been pushed to the forefront of treatment to prevent the progression of OA.

Comparison between zero-profile and cage plate devices in the treatment of single-level cervical spondylopathy.

Objective: To compare the new zero-profile (Zero-P) fusion cage with regular cage and plate (CP) in the treatment of anterior cervical single-level cervical degenerative diseases.

Methods: Patients operated from January 2013 to August 2018 were enrolled. They were divided into the Zero-P group ( = 74 cases) and CP groups ( = 116 cases).

An Immune-Related Long Non-Coding RNA Signature to Predict the Prognosis of Ewing's Sarcoma Based on a Machine Learning Iterative Lasso Regression.

The aim of this study was to construct a new immune-associated long non-coding RNA (lncRNA) signature to predict the prognosis of Ewing sarcoma (ES) and explore its molecular mechanisms. We downloaded transcriptome and clinical prognosis data from the Gene Expression Omnibus (GSE17679, which included 88 ES samples and 18 matched normal skeletal muscle samples), and used it as a training set to identify immune-related lncRNAs with different expression levels in ES. Univariable Cox regression was used to screen immune-related lncRNAs related to ES prognosis, and an immune-related lncRNA signature was constructed based on machine learning iterative lasso regression.

Development of a Machine Learning-Based Autophagy-Related lncRNA Signature to Improve Prognosis Prediction in Osteosarcoma Patients.

Background: Osteosarcoma is a frequent bone malignancy in children and young adults. Despite the availability of some prognostic biomarkers, most of them fail to accurately predict prognosis in osteosarcoma patients. In this study, we used bioinformatics tools and machine learning algorithms to establish an autophagy-related long non-coding RNA (lncRNA) signature to predict the prognosis of osteosarcoma patients.

Screening of osteoarthritis diagnostic markers based on immune-related genes and immune infiltration.

Osteoarthritis (OA) is a chronic degenerative disease of the bone and joints. Immune-related genes and immune cell infiltration are important in OA development. We analyzed immune-related genes and immune infiltrates to identify OA diagnostic markers.

Development of a novel immune-related genes prognostic signature for osteosarcoma.

Immune-related genes (IRGs) are responsible for osteosarcoma (OS) initiation and development. We aimed to develop an optimal IRGs-based signature to assess of OS prognosis. Sample gene expression profiles and clinical information were downloaded from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Genotype-Tissue Expression (GTEx) databases.

An immune-related gene signature for determining Ewing sarcoma prognosis based on machine learning.

Purpose: Ewing sarcoma (ES) is one of the most common malignant bone tumors in children and adolescents. The immune microenvironment plays an important role in the development of ES. Here, we developed an optimal signature for determining ES patient prognosis based on immune-related genes (IRGs).

[Role of immunologic abnormality in recurrent parotitis in children].

Objective: To investigate the relationship between immune function and the recurrent parotitis (RP) for children.

Methods: The children diagnosed as RP were divided into two groups: aged under 6y and over 6y and the immune function were measured and compared with that of normal children.

Results: For RP children the ratio of CD4+ T cell in over 6y group was significantly lower than that in under 6y group (P<0.

[CT assist in surgical design for the posterior pharyngeal flap].

Objective: To establish a method for assist design of the posterior pharyngeal flap (PPF).

Methods: The width, length of velopharyngeal space in repose and phonation of "i" in 26 cases with VPI were measured with CT. The width and length of PPF needed, the location of the pedicle and the contact position with the soft palate were analyzed.