Mesenchymal Stromal Cells Improve Salivary Function and Reduce Lymphocytic Infiltrates in Mice with Sjögren's-Like Disease

Non-obese diabetic (NOD) mice develop Sjögren's-like disease (SS-like) with loss of saliva flow and increased lymphocytic infiltrates in salivary glands (SGs). There are recent reports using multipotent mesenchymal stromal cells (MSCs) as a therapeutic strategy for autoimmune diseases due to their anti-inflammatory and immunomodulatory capabilities. This paper proposed a combined immuno- and cell-based therapy consisting of: A) an injection of complete Freund's adjuvant (CFA) to eradicate autoreactive T lymphocytes, and B) transplantations of MSCs to reselect lymphocytes. The objective of this was to test the effectiveness of CD45(-)/TER119(-) cells (MSCs) in re-establishing salivary function and in reducing the number of lymphocytic infiltrates (foci) in SGs. The second objective was to study if the mechanisms underlying a decrease in inflammation (focus score) was due to CFA, MSCs, or CFA+MSCs combined.Donor MSCs were isolated from bones of male transgenic eGFP mice. Eight week-old female NOD mice received one of the following treatments: insulin, CFA, MSC, or CFA+MSC (combined therapy). Mice were followed for 14 weeks post-therapy. CD45(-)/TER119(-) cells demonstrated characteristics of MSCs as they were positive for Sca-1, CD106, CD105, CD73, CD29, CD44, negative for CD45, TER119, CD11b, had high number of CFU-F, and differentiated into osteocytes, chondrocytes and adipocytes. Both MSC and MSC+CFA groups prevented loss of saliva flow and reduced lymphocytic infiltrations in SGs. Moreover, the influx of T and B cells decreased in all foci in MSC and MSC+CFA groups, while the frequency of Foxp3(+) (T(reg)) cell was increased. MSC-therapy alone reduced inflammation (TNF-α, TGF-β), but the combination of MSC+CFA reduced inflammation and increased the regenerative potential of SGs (FGF-2, EGF).The combined use of MSC+CFA was effective in both preventing saliva secretion loss and reducing lymphocytic influx in salivary glands

Data_Sheet_1_Clinical factors associated with microstructural connectome related brain dysmaturation in term neonates with congenital heart disease.PDF

ObjectiveTerm congenital heart disease (CHD) neonates display abnormalities of brain structure and maturation, which are possibly related to underlying patient factors, abnormal physiology and perioperative insults. Our primary goal was to delineate associations between clinical factors and postnatal brain microstructure in term CHD neonates using diffusion tensor imaging (DTI) magnetic resonance (MR) acquisition combined with complementary data-driven connectome and seed-based tractography quantitative analyses. Our secondary goal was to delineate associations between mild dysplastic structural brain abnormalities and connectome and seed-base tractography quantitative analyses. These mild dysplastic structural abnormalities have been derived from prior human infant CHD MR studies and neonatal mouse models of CHD that were collectively used to calculate to calculate a brain dysplasia score (BDS) that included assessment of subcortical structures including the olfactory bulb, the cerebellum and the hippocampus.MethodsNeonates undergoing cardiac surgery for CHD were prospectively recruited from two large centers. Both pre- and postoperative MR brain scans were obtained. DTI in 42 directions was segmented into 90 regions using a neonatal brain template and three weighted methods. Clinical data collection included 18 patient-specific and 9 preoperative variables associated with preoperative scan and 6 intraoperative (e.g., cardiopulmonary bypass and deep hypothermic circulatory arrest times) and 12 postoperative variables associated with postoperative scan. We compared patient specific and preoperative clinical factors to network topology and tractography alterations on a preoperative neonatal brain MRI, and intra and postoperative clinical factors to network topology alterations on postoperative neonatal brain MRI. A composite BDS was created to score abnormal findings involving the cerebellar hemispheres and vermis, supratentorial extra-axial fluid, olfactory bulbs and sulci, hippocampus, choroid plexus, corpus callosum, and brainstem. The neuroimaging outcomes of this study included (1) connectome metrics: cost (number of connections) and global/nodal efficiency (network integration); (2) seed based tractography methods of fractional anisotropy (FA), radial diffusivity, and axial diffusivity. Statistics consisted of multiple regression with false discovery rate correction (FDR) comparing the clinical risk factors and BDS (including subcortical components) as predictors/exposures and the global connectome metrics, nodal efficiency, and seed based- tractography (FA, radial diffusivity, and axial diffusivity) as neuroimaging outcome measures.ResultsA total of 133 term neonates with complex CHD were prospectively enrolled and 110 had analyzable DTI. Multiple patient-specific factors including d-transposition of the great arteries (d-TGA) physiology and severity of impairment of fetal cerebral substrate delivery (i.e., how much the CHD lesion alters typical fetal circulation such that the highest oxygen and nutrient rich blood from the placenta are not directed toward the fetal brain) were predictive of preoperative reduced cost (p ConclusionPatient-specific (d-TGA anatomy, preoperative impairment of fetal cerebral substrate delivery) and postoperative (e.g., seizures, need for ECMO, or CPR) clinical factors were most predictive of diffuse postnatal microstructural dysmaturation in term CHD neonates. Anthropometric measurements (weight, length, and head size) predicted tractography outcomes. In contrast, subcortical components (cerebellum, hippocampus, olfactory) of a structurally based BDS (derived from CHD mouse mutants), predicted more localized and regional postnatal microstructural differences. Collectively, these findings suggest that brain DTI connectome and seed-based tractography are complementary techniques which may facilitate deciphering the mechanistic relative contribution of clinical and genetic risk factors related to poor neurodevelopmental outcomes in CHD.</p

Lagrangian Postprocessing of Computational Hemodynamics

Recent advances in imaging, modeling and computing have rapidly expanded our capabilities to model hemodynamics in the large vessels (heart, arteries and veins). This data encodes a wealth of information that is often under-utilized. Modeling (and measuring) blood flow in the large vessels typically amounts to solving for the time-varying velocity field in a region of interest. Flow in the heart and larger arteries is often complex, and velocity field data provides a starting point for investigating the hemodynamics. This data can be used to perform Lagrangian particle tracking, and other Lagrangian-based postprocessing. As described herein, Lagrangian methods are necessary to understand inherently transient hemodynamic conditions from the fluid mechanics perspective, and to properly understand the biomechanical factors that lead to acute and gradual changes of vascular function and health. The goal of the present paper is to review Lagrangian methods that have been used in post-processing velocity data of cardiovascular flows