LRRK1 regulation of actin assembly in osteoclasts involves serine 5 phosphorylation of L-plastin

Mice with disruption of Lrrk1 and patients with nonfunctional mutant Lrrk1 exhibit severe osteopetrosis phenotypes because of osteoclast cytoskeletal dysfunction. To understand how Lrrk1 regulates osteoclast function by modulating cytoskeleton rearrangement, we examined the proteins that are differentially phosphorylated in wild-type mice and Lrrk1-deficient osteoclasts by metal affinity purification coupled liquid chromatography/mass spectrometry (LC/MS) analyses. One of the candidates that we identified by LC/MS is L-plastin, an actin bundling protein. We found that phosphorylation of L-plastin at serine (Ser) residues 5 was present in wild-type osteoclasts but not in Lrrk1-deficient cells. Western blot analyses with antibodies specific for Ser5 phosphorylated L-plastin confirmed the reduced L-plastin Ser5 phosphorylation in Lrrk1 knockout (KO) osteoclasts. micro computed tomography (Micro-CT) analyses revealed that the trabecular bone volume of the distal femur was increased by 27% in the 16 to 21-week-old L-plastin KO females as compared with the wild-type control mice. The ratio of bone volume to tissue volume and connectivity density were increased by 44% and 47% (both P \u3c 0.05), respectively, in L-plastin KO mice. Our data suggest that targeted disruption of L-plastin increases trabecular bone volume, and phosphorylation of Ser5 in L-plastin in the Lrrk1 signaling pathway may in part contribute to actin assembly in mature osteoclasts

A Prognostic Model Generated from an Apparent Diffusion Coefficient Ratio Reliably Predicts the Outcomes of Oral Tongue Squamous Cell Carcinoma

This study aimed to develop an apparent diffusion coefficient (ADC) ratio-based prognostic model to predict the recurrence and disease-free survival (DFS) of oral tongue squamous cell carcinoma (OTSCC). A total of 188 patients with cT1-2 oral tongue squamous cell carcinoma were enrolled retrospectively. Clinical and laboratory data were extracted from medical records. The ADC values were measured at the regions of interest of the tumor and non-tumor tissues of the MRI images, and the ADC ratio was used for comparison between the patient with recurrence (n = 83 case, 44%) and patients without recurrence (n = 105 cases, 56%). Cox proportional hazards models were generated to analyze the risk factors of cancer recurrence. A nomogram was developed based on significant risk factors to predict 1-, 5- and 10-year DFS. The receiver operator characteristic (ROC) curves of predictors in the multivariable Cox proportional hazards prognostic model were generated to predict the recurrence and DFS. The integrated areas under the ROC curve were calculated to evaluate discrimination of the models. The ADC ratio, tumor thickness and lymph node ratio were reliable predictors in the final prognostic model. The final model had a 71.1% sensitivity and an 81.0% specificity. ADC ratio was the strongest predictor of cancer recurrence in prognostic performance. Discrimination and calibration statistics were satisfactory with C-index above 0.7 for both model development and internal validation. The calibration curve showed that the 5- and 10-year DFS predicted by the nomogram agreed with actual observations