Upscaling Osteoclast Generation by Enhancing Macrophage Aggregation Using Hollow Microgels.

Osteoclasts, the bone resorbing cells of hematopoietic origin formed by macrophage fusion, are essential in bone health and disease. However, in vitro research on osteoclasts remains challenging due to heterogeneous cultures that only contain a few multinucleated osteoclasts. Indeed, a strategy to generate homogeneous populations of multinucleated osteoclasts in a scalable manner has remained elusive. Here, the investigation focuses on whether microencapsulation of human macrophages in microfluidically generated hollow, sacrificial tyramine-conjugated dextran (Dex-TA) microgels could facilitate macrophage precursor aggregation and formation of multinucleated osteoclasts. Therefore, human mononuclear cells are isolated from buffy coats and differentiated toward macrophages. Macrophages are encapsulated in microgels using flow focus microfluidics and outside-in enzymatic oxidative phenolic crosslinking, and differentiated toward osteoclasts. Morphology, viability, and osteoclast fusion of microencapsulated cells are assessed. Furthermore, microgels are degraded to allow cell sorting of released cells based on osteoclastic marker expression. The successful encapsulation and osteoclast formation of human macrophages in Dex-TA microgels are reported for the first time using high-throughput droplet microfluidics. Intriguingly, osteoclast formation within these 3D microenvironments occurs at a significantly higher level compared to the conventional 2D culture system. Furthermore, the feasibility of establishing a pure osteoclast culture from cell transfer and release from degradable microgels is demonstrated.

Neuroimaging characterization of multiple sclerosis lesions in pediatric patients: an exploratory radiomics approach.

Introduction: Multiple sclerosis (MS), a chronic inflammatory immune-mediated disease of the central nervous system (CNS), is a common condition in young adults, but it can also affect children. The aim of this study was to construct radiomic models of lesions based on magnetic resonance imaging (MRI, T2-weighted-Fluid-Attenuated Inversion Recovery), to understand the correlation between extracted radiomic features, brain and lesion volumetry, demographic, clinical and laboratorial data. Methods: The neuroimaging data extracted from eleven scans of pediatric MS patients were analyzed. A total of 60 radiomic features based on MR T2-FLAIR images were extracted and used to calculate gray level co-occurrence matrix (GLCM). The principal component analysis and ROC analysis were performed to select the radiomic features, respectively. The realized classification task by the logistic regression models was performed according to these radiomic features. Results: Ten most relevant features were selected from data extracted. The logistic regression applied to T2-FLAIR radiomic features revealed significant predictor for multiple sclerosis (MS) lesion detection. Only the variable "contrast" was statistically significant, indicating that only this variable played a significant role in the model. This approach enhances the classification of lesions from normal tissue. Discussion and conclusion: Our exploratory results suggest that the radiomic models based on MR imaging (T2-FLAIR) may have a potential contribution to characterization of brain tissues and classification of lesions in pediatric MS.

Case for diagnosis. Suppurative nodule or something deeper?

Abstract: The authors report the case of a 62-year-old man with a history of total left hip arthroplasty nine years previously presenting with a large infiltrated plaque on the posterior area of the left thigh with three months of evolution without systemic symptoms or elevated inflammatory markers. Computed tomography of the left lower limb revealed a 12-centimeter linear extension of the lesion to the posterior part of the left proximal femur. Prosthesis joint infection, although rare, is a surgical complication to be taken into account, even if the surgery was performed many years before.