Human Rotator Cuff Tears Reveal an Age-Dependent Increase in Markers of Cellular Senescence and Selective Removal of Senescent Cells With Dasatinib + Quercetin Increases Genetic Expression of COL1A1 In Vitro.

PURPOSE: To quantify cellular senescence in supraspinatus tendon and subacromial bursa of humans with rotator cuff tears and to investigate the in vitro efficacy of the senolytic dasatinib + quercetin (D+Q) to eliminate senescent cells and alter tenogenic differentiation. METHODS: Tissue was harvested from 41 patients (mean age, 62 years) undergoing arthroscopic rotator cuff repairs. In part 1 (n = 35), senescence was quantified using immunohistochemistry and gene expression for senescent cell markers (p16 and p21) and the senescence-associated secretory phenotype (SASP) (interleukin [IL] 6, IL-8, matrix metalloproteinase [MMP] 3, monocyte chemoattractant protein [MCP] 1). Senescence was compared between patients <60 and ≥60 years old. In part 2 (n = 6) , an in vitro model of rotator cuff tears was treated with D+Q or control. D+Q, a chemotherapeutic and plant flavanol, respectively, kill senescent cells. Gene expression analysis assessed the ability of D+Q to kill senescent cells and alter markers of tenogenic differentiation. RESULTS: Part 1 revealed an age-dependent significant increase in the relative expression of p21, IL-6, and IL-8 in tendon and p21, p16, IL-6, IL-8, and MMP-3 in bursa (P < .05). A significant increase was seen in immunohistochemical staining of bursa p21 (P = .028). In part 2, D+Q significantly decreased expression of p21, IL-6, and IL-8 in tendon and p21 and IL-8 in bursa (P < .05). Enzyme-linked immunosorbent assay analysis showed decreased release of the SASP (IL-6, MMP-3, MCP-1; P = .002, P = .024, P < .001, respectively). Tendon (P = .022) and bursa (P = .027) treated with D+Q increased the expression of COL1A1. CONCLUSIONS: While there was an age-dependent increase in markers of cellular senescence, this relationship was not consistently seen across all markers and tissues. Dasatinib + quercetin had moderate efficacy in decreasing senescence in these tissues and increasing COL1A1 expression. CLINICAL RELEVANCE: This study reveals that cellular senescence may be a therapeutic target to alter the biological aging of rotator cuffs and identifies D+Q as a potential therapy.

The use of machine learning for predicting candidates for outpatient spine surgery: a review.

While spine surgery has historically been performed in the inpatient setting, in recent years there has been growing interest in performing certain cervical and lumbar spine procedures on an outpatient basis. While conducting these procedures in the outpatient setting may be preferable for both the surgeon and the patient, appropriate patient selection is crucial. The employment of machine learning techniques for data analysis and outcome prediction has grown in recent years within spine surgery literature. Machine learning is a form of statistics often applied to large datasets that creates predictive models, with minimal to no human intervention, that can be applied to previously unseen data. Machine learning techniques may outperform traditional logistic regression with regards to predictive accuracy when analyzing complex datasets. Researchers have applied machine learning to develop algorithms to aid in patient selection for spinal surgery and to predict postoperative outcomes. Furthermore, there has been increasing interest in using machine learning to assist in the selection of patients who may be appropriate candidates for outpatient cervical and lumbar spine surgery. The goal of this review is to discuss the current literature utilizing machine learning to predict appropriate patients for cervical and lumbar spine surgery, candidates for outpatient spine surgery, and outcomes following these procedures.