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Background: The majority of stroke survivors experiences significant hand impairments, as weakness and spasticity, with a severe impact on the activity of daily living. To objectively evaluate hand deficits, quantitative measures are needed. The aim of this study is to assess the reliability, the validity and the discriminant ability of the instrumental measures provided by a robotic device for hand rehabilitation, in a sample of patients with subacute stroke. Material and methods: In this study, 120 patients with stroke and 40 controls were enrolled. Clinical evaluation included finger flexion and extension strength (using the Medical Research Council, MRC), finger spasticity (using the Modified Ashworth Scale, MAS) and motor control and dexterity during ADL performance (by means of the Frenchay Arm Test, FAT). Robotic evaluations included finger flexion and extension strength, muscle tone at rest, and instrumented MAS and Modified Tardieu Scale. Subjects were evaluated twice, one day apart, to assess the test-retest reliability of the robotic measures, using the Intraclass Correlation Coefficient (ICC). To estimate the response stability, the standard errors of measurement and the minimum detectable change (MDC) were also calculated. Validity was assessed by analyzing the correlations between the robotic metrics and the clinical scales, using the Spearman's Correlation Coefficient (r). Finally, we investigated the ability of the robotic measures to distinguish between patients with stroke and healthy subjects, by means of Mann-Whitney U tests. Results: All the investigated measures were able to discriminate patients with stroke from healthy subjects (p < 0.001). Test-retest reliability was found to be excellent for finger strength (in both flexion and extension) and muscle tone, with ICCs higher than 0.9. MDCs were equal to 10.6 N for finger flexion, 3.4 N for finger extension, and 14.3 N for muscle tone. Conversely, test-retest reliability of the spasticity measures was poor. Finally, finger strength (in both flexion and extension) was correlated with the clinical scales (r of about 0.7 with MRC, and about 0.5 with FAT). Discussion: Finger strength (in both flexion and extension) and muscle tone, as provided by a robotic device for hand rehabilitation, are reliable and sensitive measures. Moreover, finger strength is strongly correlated with clinical scales. Changes higher than the obtained MDC in these robotic measures could be considered as clinically relevant and used to assess the effect of a rehabilitation treatment in patients with subacute stroke.

Extracellular vesicles (EVs) from mesenchymal stromal cells (MSC) are emerging as valuable therapeutic agents for tissue regeneration and immunomodulation, but their clinical applications have so far been limited by the technical restraints of current isolation and characterisation procedures. This study shows for the first time the successful application of Raman spectroscopy as label-free, sensitive and reproducible means of carrying out the routine bulk characterisation of MSC-derived vesicles before their use in vitro or in vivo, thus promoting the translation of EV research to clinical practice. The Raman spectra of the EVs of bone marrow and adipose tissue-derived MSCs were compared with human dermal fibroblast EVs in order to demonstrate the ability of the method to distinguish the vesicles of the three cytotypes automatically with an accuracy of 93.7%. Our data attribute a Raman fingerprint to EVs from undifferentiated and differentiated cells of diverse tissue origin, and provide insights into the biochemical characteristics of EVs from different sources and into the differential contribution of sphingomyelin, gangliosides and phosphatidilcholine to the Raman spectra themselves.

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The use of exosomes for diagnostic and disease monitoring purposes is becoming particularly appealing in biomedical research because of the possibility to study directly in biological fluids some of the features related to the organs from which exosomes originate. A paradigmatic example are brain-derived exosomes that can be found in plasma and used as a direct read-out of the status of the central nervous system (CNS). Inspired by recent remarkable development of plasmonic biosensors, we have designed a surface plasmon resonance imaging (SPRi) assay that, taking advantage of the fact that exosome size perfectly fits within the surface plasmon wave depth, allows the detection of multiple exosome subpopulations of neural origin directly in blood. By use of an array of antibodies, exosomes derived from neurons and oligodendrocytes were isolated and detected with good sensitivity. Subsequently, by injecting a second antibody on the immobilized vesicles, we were able to quantify the amount of CD81 and GM1, membrane components of exosomes, on each subpopulation. In this way, we have been able to demonstrate that they are not homogeneously expressed but exhibit a variable abundance according to the exosome cellular origin. These results confirm the extreme variability of exosome composition and demonstrate how SPRi can provide an effective tool for their characterization. Besides, our work paves the road toward more precise clinical studies on the use of exosomes as potential biomarkers of neurodegenerative diseases.