Resting-state functional magnetic resonance imaging reveals functional connectivity alteration in the experimental autoimmune encephalomyelitis model of multiple sclerosis.

Multiple sclerosis (MS) is an autoimmune degenerative disease targeting white matter in the central nervous system. The most common animal model that mimics MS is experimental autoimmune encephalomyelitis (EAE) and it plays a crucial role in pharmacological research, from the identification of a therapeutic target to the in vivo validation of efficacy. Magnetic resonance imaging (MRI) is largely used to detect MS lesions, and resting-state functional MRI (rsfMRI) to investigate alterations in the brain functional connectivity (FC). MRI was mainly used in EAE studies to detect lesions in the spinal cord and brain. The current longitudinal MRI study aims to validate rsfMRI as a biomarker of the disease progression in the myelin oligodendrocyte glycoprotein 35-55 induced EAE animal model of MS. MR images were acquired 14, 25, and 50 days postimmunization. Seed-based analysis was used to investigate the whole-brain FC with some predefined areas, such as the thalamic regions, cerebellum, motor and somatosensory cortex. When compared with the control group, the EAE group exhibited a slightly altered FC and a decreasing trend in the total number of activated voxels along the disease progression. The most interesting result regards the whole-brain FC with the cerebellum. A hyperconnectivity behavior was found at an early phase and a significant reduced connectivity at a late phase. Moreover, we found a negative correlation between the total number of activated voxels during the late phase and the cumulative disease index. The results obtained provide a clinically relevant experimental platform that may be pivotal for the elucidation of the key mechanisms of accumulation of irreversible disability, as well as the development of innovative therapies for MS. Moreover, the negative correlation between the disease severity and the size of the activated area suggests a possible research pathway to follow for the resolution of the clinico-radiological paradox.

Extracellular vesicles from adipose mesenchymal stem cells target inflamed lymph nodes in experimental autoimmune encephalomyelitis.

BACKGROUND AIMS: Adipose mesenchymal stem cells (ASCs) represent a promising therapeutic approach in inflammatory neurological disorders, including multiple sclerosis (MS). Recent lines of evidence indicate that most biological activities of ASCs are mediated by the delivery of soluble factors enclosed in extracellular vesicles (EVs). Indeed, we have previously demonstrated that small EVs derived from ASCs (ASC-EVs) ameliorate experimental autoimmune encephalomyelitis (EAE), a murine model of MS. The precise mechanisms and molecular/cellular target of EVs during EAE are still unknown. METHODS: To investigate the homing of ASC-EVs, we intravenously injected small EVs loaded with ultra-small superparamagnetic iron oxide nanoparticles (USPIO) at disease onset in EAE-induced C57Bl/6J mice. Histochemical analysis and transmission electron microscopy were carried out 48 h after EV treatment. Moreover, to assess the cellular target of EVs, flow cytometry on cells extracted ex vivo from EAE mouse lymph nodes was performed. RESULTS: Histochemical and ultrastructural analysis showed the presence of labeled EVs in lymph nodes but not in lungs and spinal cord of EAE injected mice. Moreover, we identified the cellular target of EVs in EAE lymph nodes by flow cytometry: ASC-EVs were preferentially located in macrophages, with a consistent amount also noted in dendritic cells and CD4+ T lymphocytes. CONCLUSIONS: This represents the first direct evidence of the privileged localization of ASC-EVs in draining lymph nodes of EAE after systemic injection. These data provide prominent information on the distribution, uptake and retention of ASC-EVs, which may help in the development of EV-based therapy in MS.

Alpha4 beta7 integrin controls Th17 cell trafficking in the spinal cord leptomeninges during experimental autoimmune encephalomyelitis.

Th1 and Th17 cell migration into the central nervous system (CNS) is a fundamental process in the pathogenesis of experimental autoimmune encephalomyelitis (EAE), the animal model of multiple sclerosis (MS). Particularly, leptomeningeal vessels of the subarachnoid space (SAS) constitute a central route for T cell entry into the CNS during EAE. Once migrated into the SAS, T cells show an active motility behavior, which is a prerequisite for cell-cell communication, in situ reactivation and neuroinflammation. However, the molecular mechanisms selectively controlling Th1 and Th17 cell trafficking in the inflamed leptomeninges are not well understood. By using epifluorescence intravital microscopy, we obtained results showing that myelin-specific Th1 and Th17 cells have different intravascular adhesion capacity depending on the disease phase, with Th17 cells being more adhesive at disease peak. Inhibition of αLß2 integrin selectively blocked Th1 cell adhesion, but had no effect on Th17 rolling and arrest capacity during all disease phases, suggesting that distinct adhesion mechanisms control the migration of key T cell populations involved in EAE induction. Blockade of α4 integrins affected myelin-specific Th1 cell rolling and arrest, but only selectively altered intravascular arrest of Th17 cells. Notably, selective α4ß7 integrin blockade inhibited Th17 cell arrest without interfering with intravascular Th1 cell adhesion, suggesting that α4ß7 integrin is predominantly involved in Th17 cell migration into the inflamed leptomeninges in EAE mice. Two-photon microscopy experiments showed that blockade of α4 integrin chain or α4ß7 integrin selectively inhibited the locomotion of extravasated antigen-specific Th17 cells in the SAS, but had no effect on Th1 cell intratissue dynamics, further pointing to α4ß7 integrin as key molecule in Th17 cell trafficking during EAE development. Finally, therapeutic inhibition of α4ß7 integrin at disease onset by intrathecal injection of a blocking antibody attenuated clinical severity and reduced neuroinflammation, further demonstrating a crucial role for α4ß7 integrin in driving Th17 cell-mediated disease pathogenesis. Altogether, our data suggest that a better knowledge of the molecular mechanisms controlling myelin-specific Th1 and Th17 cell trafficking during EAE delevopment may help to identify new therapeutic strategies for CNS inflammatory and demyelinating diseases.

An isoform of the giant protein titin is a master regulator of human T lymphocyte trafficking.

Response to multiple microenvironmental cues and resilience to mechanical stress are essential features of trafficking leukocytes. Here, we describe unexpected role of titin (TTN), the largest protein encoded by the human genome, in the regulation of mechanisms of lymphocyte trafficking. Human T and B lymphocytes express five TTN isoforms, exhibiting cell-specific expression, distinct localization to plasma membrane microdomains, and different distribution to cytosolic versus nuclear compartments. In T lymphocytes, the LTTN1 isoform governs the morphogenesis of plasma membrane microvilli independently of ERM protein phosphorylation status, thus allowing selectin-mediated capturing and rolling adhesions. Likewise, LTTN1 controls chemokine-triggered integrin activation. Accordingly, LTTN1 mediates rho and rap small GTPases activation, but not actin polymerization. In contrast, chemotaxis is facilitated by LTTN1 degradation. Finally, LTTN1 controls resilience to passive cell deformation and ensures T lymphocyte survival in the blood stream. LTTN1 is, thus, a critical and versatile housekeeping regulator of T lymphocyte trafficking.

LFA-1 Controls Th1 and Th17 Motility Behavior in the Inflamed Central Nervous System.

Leukocyte trafficking is a key event during autoimmune and inflammatory responses. The subarachnoid space (SAS) and cerebrospinal fluid are major routes for the migration of encephalitogenic T cells into the central nervous system (CNS) during experimental autoimmune encephalomyelitis (EAE), the animal model of multiple sclerosis, and are sites of T cell activation before the invasion of CNS parenchyma. In particular, autoreactive Th1 and Th17 cell trafficking and reactivation in the CNS are required for the pathogenesis of EAE. However, the molecular mechanisms controlling T cell dynamics during EAE are unclear. We used two-photon laser microscopy to show that autoreactive Th1 and Th17 cells display distinct motility behavior within the SAS in the spinal cords of mice immunized with the myelin oligodendrocyte glycoprotein peptide MOG35-55. Th1 cells showed a strong directional bias at the disease peak, moving in a straight line and covering long distances, whereas Th17 cells exhibited more constrained motility. The dynamics of both Th1 and Th17 cells were strongly affected by blocking the integrin LFA-1, which interfered with the deformability and biomechanics of Th1 but not Th17 cells. The intrathecal injection of a blocking anti-LFA-1 antibody at the onset of disease significantly inhibited EAE progression and also strongly reduced neuro-inflammation in the immunized mice. Our results show that LFA-1 plays a pivotal role in T cell motility during EAE and suggest that interfering with the molecular mechanisms controlling T cell motility can help to reduce the pathogenic potential of autoreactive lymphocytes.

A fuzzy knowledge-based decision support system for groundwater pollution risk evaluation.

In this paper we propose a decision support system that can provide information on the environmental impact of anthropic activities by examining their effects on groundwater quality. We use the combined value of both intrinsic vulnerability of a specific local aquifer, obtained by implementing a parametric managerial model (SINTACS), and a degree of hazard value, which takes into account specific human activities. Incomplete information is notoriously common in environmental planning. To overcome this deficiency we apply an algorithmic and a qualitative approach, based on expert judgment incorporated into the system's knowledge base. The decision support system takes into account the uncertainty of the environmental domain by using fuzzy logic and evaluates the reliability of the results according to information availability.