Electro-magnetic field promotes osteogenic differentiation of BM-hMSCs through a selective action on Ca(2+)-related mechanisms

Exposure to Pulsed Electromagnetic Field (PEMF) has been shown to affect proliferation and differentiation of human mesenchymal stem cells derived from bone marrow stroma (BM-hMSC). These cells offer considerable promise in the field of regenerative medicine, but their clinical application is hampered by major limitations such as poor availability and the time required to differentiate up to a stage suitable for implantation. For this reason, several research efforts are focusing on identifying strategies to speed up the differentiation process. In this work we investigated the in vitro effect of PEMF on Ca2+-related mechanisms promoting the osteogenic differentiation of BM-hMSC. Cells were daily exposed to PEMF while subjected to osteogenic differentiation and various Ca2+-related mechanisms were monitored using multiple approaches for identifying functional and structural modifications related to this process. The results indicate that PEMF exposure promotes chemically induced osteogenesis by mechanisms that mainly interfere with some of the calcium-related osteogenic pathways, such as permeation and regulation of cytosolic concentration, leaving others, such as extracellular deposition, unaffected. The PEMF effect is primarily associated to early enhancement of intracellular calcium concentration, which is proposed here as a reliable hallmark of the osteogenic developmental stage

Deep Learning for real-time neural decoding of grasp

Neural decoding involves correlating signals acquired from the brain to variables in the physical world like limb movement or robot control in Brain Machine Interfaces. In this context, this work starts from a specific pre-existing dataset of neural recordings from monkey motor cortex and presents a Deep Learning-based approach to the decoding of neural signals for grasp type classification. Specifically, we propose here an approach that exploits LSTM networks to classify time series containing neural data (i.e., spike trains) into classes representing the object being grasped. The main goal of the presented approach is to improve over state-of-the-art decoding accuracy without relying on any prior neuroscience knowledge, and leveraging only the capability of deep learning models to extract correlations from data. The paper presents the results achieved for the considered dataset and compares them with previous works on the same dataset, showing a significant improvement in classification accuracy, even if considering simulated real-time decoding

Designing Logic Tensor Networks for Visual Sudoku puzzle classification

Given the increasing importance of the neurosymbolic (NeSy) approach in artificial intelligence, there is a growing interest in studying benchmarks specifically designed to emphasize the ability of AI systems to combine low-level representation learning with high-level symbolic reasoning. One such recent benchmark is Visual Sudoku Puzzle Classification, that combines visual perception with relational constraints. In this work, we investigate the application of Logic Tensork Networks (LTNs) to the Visual Sudoku Classification task and discuss various alternatives in terms of logical constraint formulation, integration with the perceptual module and training procedure

CD19 Cell Count at Baseline Predicts B Cell Repopulation at 6 and 12 Months in Multiple Sclerosis Patients Treated with Ocrelizumab

Background: The kinetics of B cell repopulation in MS patients treated with Ocrelizumab is highly variable, suggesting that a fixed dosage and time scheduling might be not optimal. We aimed to investigate whether B cell repopulation kinetics influences clinical and radiological outcomes and whether circulating immune asset at baseline affects B cell repopulation kinetics. Methods: 218 MS patients treated with Ocrelizumab were included. Every six months we collected data on clinical and magnetic resonance imaging (MRI) activity and lymphocyte subsets at baseline. According to B cell counts at six and twelve months, we identified two groups of patients, those with fast repopulation rate (FR) and those with slow repopulation rate (SR). Results: A significant reduction in clinical and radiological activity was found. One hundred fifty-five patients had complete data and received at least three treatment cycles (twelve-month follow-up). After six months, the FR patients were 41/155 (26.45%) and 10/41 (29.27%) remained non-depleted after twelve months. FR patients showed a significantly higher percentage of active MRI scan at twelve months (17.39% vs. 2.53%; p = 0,008). Furthermore, FR patients had a higher baseline B cell count compared to patients with an SR (p = 0.02 and p = 0.002, at the six- and twelve-month follow-ups, respectively). Conclusion: A considerable proportion of MS patients did not achieve a complete CD19 cell depletion and these patients had a higher baseline CD19 cell count. These findings, together with the higher MRI activity found in FR patients, suggest that the Ocrelizumab dosage could be tailored depending on CD19 cell counts at baseline in order to achieve complete disease control in all patients

Determinants and Biomarkers of Progression Independent of Relapses in Multiple Sclerosis

Clinical, pathological, and imaging evidence in multiple sclerosis (MS) suggests that a smoldering inflammatory activity is present from the earliest stages of the disease and underlies the progression of disability, which proceeds relentlessly and independently of clinical and radiological relapses (PIRA). The complex system of pathological events driving "chronic" worsening is likely linked with the early accumulation of compartmentalized inflammation within the central nervous system as well as insufficient repair phenomena and mitochondrial failure. These mechanisms are partially lesion-independent and differ from those causing clinical relapses and the formation of new focal demyelinating lesions; they lead to neuroaxonal dysfunction and death, myelin loss, glia alterations, and finally, a neuronal network dysfunction outweighing central nervous system (CNS) compensatory mechanisms. This review aims to provide an overview of the state of the art of neuropathological, immunological, and imaging knowledge about the mechanisms underlying the smoldering disease activity, focusing on possible early biomarkers and their translation into clinical practice. ANN NEUROL 2024

Quality of care provided by Multiple Sclerosis Centers during Covid-19 pandemic: Results of an Italian multicenter patient-centered survey

Background: Covid-19 pandemic impacted on management of people with Multiple Sclerosis (pwMS). Level of satisfaction of pwMS regarding the care received by the staff of Multiple Sclerosis Centers (MSCs) during the pandemic was not fully investigated. In a large patient-centered multicenter study, the therapeutic adherence and quality of care of MSCs was assessed. Methods: In April-May 2021, an online survey was widespread by 16 Italian MSCs. Frequencies, percentages and/or means and standard deviations were calculated to describe the sample. ANOVAs were performed to evaluate the effect of sociodemographic and clinical variables on overall pwMS' rating of MSC assistance. Results: 1670 pwMS completed the survey (67.3% women). During the pandemic, 88% did not change their disease modifying therapy schedule, and 89.1% reached their MSCs with no or little difficulties. Even if only 1.3% of participants underwent a tele-health follow-up visit with their MSC staff, the 80.1% believed that tele-health services should be improved regardless of pandemic. 92% of participants were satisfied of how their MSC took charge of their needs; ANOVAs revealed an effect of disease duration on pwMS' level of satisfaction on MSCs management during the pandemic. Conclusions: The results revealed an efficient MSCs response to Covid-19 pandemic and provided the basis for the implementing of tele-health services that would further improve the taking charge of patients, particularly those with longer disease, higher disability, and/or living far from their MSC

Rationale and design of the MULTISTARS AMI Trial: a randomized comparison of immediate versus staged complete revascularization in patients with ST-segment elevation myocardial infarction and multivessel disease

Background: About half of patients with acute ST-segment elevation myocardial infarction (STEMI) present with multivessel coronary artery disease (MVD). Recent evidence supports complete revascularization in these patients. However, optimal timing of non-culprit lesion revascularization in STEMI patients is unknown because dedicated randomized trials on this topic are lacking. Study design: The MULTISTARS AMI trial is a prospective, international, multicenter, randomized, two-arm, open-label study planning to enroll at least 840 patients. It is designed to investigate whether immediate complete revascularization is non-inferior to staged (within 19-45 days) complete revascularization in patients in stable hemodynamic conditions presenting with STEMI and MVD and undergoing primary percutaneous coronary intervention (PCI). After successful primary PCI of the culprit artery, patients are randomized in a 1:1 ratio to immediate or staged complete revascularization. The primary endpoint is a composite of all-cause death, non-fatal myocardial infarction, ischemia-driven revascularization, hospitalization for heart failure, and stroke at 1 year. Conclusions: The MULTISTARS AMI trial tests the hypothesis that immediate complete revascularization is non-inferior to staged complete revascularization in stable patients with STEMI and MVD

Reduced Rate of Hospital Admissions for ACS during Covid-19 Outbreak in Northern Italy

To address the coronavirus (Covid-19) pandemic,1 strict social containment measures have been adopted worldwide, and health care systems have been reorganized to cope with the enormous increase in the numbers of acutely ill patients.2,3 During this same period, some changes in the pattern of hospital admissions for other conditions have been noted. The aim of the present analysis is to investigate the rate of hospital admissions for acute coronary syndrome (ACS) during the early days of the Covid-19 outbreak