Representations of automorphism groups on the homology of matroids

Given a group $G$ of automorphisms of a matroid $M$, we describe the representations of $G$ on the homology of the independence complex of the dual matroid $M^*$. These representations are related with the homology of the lattice of flats of $M$, and (when $M$ is realizable) with the top cohomology of a hyperplane arrangement. Finally we analyze in detail the case of the complete graph, which has applications to algebraic geometry

Actigraphic Sensors Describe Stroke Severity in the Acute Phase: Implementing Multi-Parametric Monitoring in Stroke Unit

: Actigraphy is a tool used to describe limb motor activity. Some actigraphic parameters, namely Motor Activity (MA) and Asymmetry Index (AR), correlate with stroke severity. However, a long-lasting actigraphic monitoring was never performed previously. We hypothesized that MA and AR can describe different clinical conditions during the evolution of the acute phase of stroke. We conducted a multicenter study and enrolled 69 stroke patients. NIHSS was assessed every hour and upper limbs' motor activity was continuously recorded. We calculated MA and AR in the first hour after admission, after a significant clinical change (NIHSS ± 4) or at discharge. In a control group of 17 subjects, we calculated MA and AR normative values. We defined the best model to predict clinical status with multiple linear regression and identified actigraphic cut-off values to discriminate minor from major stroke (NIHSS ≥ 5) and NIHSS 5-9 from NIHSS ≥ 10. The AR cut-off value to discriminate between minor and major stroke (namely NIHSS ≥ 5) is 27% (sensitivity = 83%, specificity = 76% (AUC 0.86 p < 0.001), PPV = 89%, NPV = 42%). However, the combination of AR and MA of the non-paretic arm is the best model to predict NIHSS score (R2: 0.482, F: 54.13), discriminating minor from major stroke (sensitivity = 89%, specificity = 82%, PPV = 92%, NPV = 75%). The AR cut-off value of 53% identifies very severe stroke patients (NIHSS ≥ 10) (sensitivity = 82%, specificity = 74% (AUC 0.86 p < 0.001), PPV = 73%, NPV = 82%). Actigraphic parameters can reliably describe the overall severity of stroke patients with motor symptoms, supporting the addition of a wearable actigraphic system to the multi-parametric monitoring in stroke units

Imbalance of Essential Metals in Traumatic Brain Injury and Its Possible Link with Disorders of Consciousness

Dysfunction of the complex cerebral networks underlying wakefulness and awareness is responsible for Disorders of Consciousness (DoC). Traumatic Brain Injury (TBI) is a common cause of DoC, and it is responsible for a multi-dimensional pathological cascade that affects the proper functioning of the brainstem and brain consciousness pathways. Iron (Fe), Zinc (Zn), and Copper (Cu) have a role in the neurophysiology of both the ascending reticular activating system, a multi-neurotransmitter network located in the brainstem that is crucial for consciousness, and several brain regions. We aimed to summarize the role of these essential metals in TBI and its possible link with consciousness alterations. We found that TBI alters many neuronal molecular mechanisms involving essential metals, causing neurodegeneration, neural apoptosis, synaptic dysfunction, oxidative stress, and inflammation. This final pattern resembles that described for Alzheimer’s disease (AD) and other neurological and psychiatric diseases. Furthermore, we found that amantadine, zolpidem, and transcranial direct current stimulation (tDCS)—the most used treatments for DoC recovery—seem to have an effect on essential metals-related pathways and that Zn might be a promising new therapeutic approach. This review summarizes the neurophysiology of essential metals in the brain structures of consciousness and focuses on the mechanisms underlying their imbalance following TBI, suggesting their possible role in DoC. The scenario supports further studies aimed at getting a deeper insight into metals’ role in DoC, in order to evaluate metal-based drugs, such as metal complexes and metal chelating agents, as potential therapeutic options

Actigraphic Sensors Describe Stroke Severity in the Acute Phase: Implementing Multi-Parametric Monitoring in Stroke Unit

Actigraphy is a tool used to describe limb motor activity. Some actigraphic parameters, namely Motor Activity (MA) and Asymmetry Index (AR), correlate with stroke severity. However, a long-lasting actigraphic monitoring was never performed previously. We hypothesized that MA and AR can describe different clinical conditions during the evolution of the acute phase of stroke. We conducted a multicenter study and enrolled 69 stroke patients. NIHSS was assessed every hour and upper limbs’ motor activity was continuously recorded. We calculated MA and AR in the first hour after admission, after a significant clinical change (NIHSS ± 4) or at discharge. In a control group of 17 subjects, we calculated MA and AR normative values. We defined the best model to predict clinical status with multiple linear regression and identified actigraphic cut-off values to discriminate minor from major stroke (NIHSS ≥ 5) and NIHSS 5–9 from NIHSS ≥ 10. The AR cut-off value to discriminate between minor and major stroke (namely NIHSS ≥ 5) is 27% (sensitivity = 83%, specificity = 76% (AUC 0.86 p < 0.001), PPV = 89%, NPV = 42%). However, the combination of AR and MA of the non-paretic arm is the best model to predict NIHSS score (R2: 0.482, F: 54.13), discriminating minor from major stroke (sensitivity = 89%, specificity = 82%, PPV = 92%, NPV = 75%). The AR cut-off value of 53% identifies very severe stroke patients (NIHSS ≥ 10) (sensitivity = 82%, specificity = 74% (AUC 0.86 p < 0.001), PPV = 73%, NPV = 82%). Actigraphic parameters can reliably describe the overall severity of stroke patients with motor symptoms, supporting the addition of a wearable actigraphic system to the multi-parametric monitoring in stroke units

Actigraphic Sensors Describe Stroke Severity in the Acute Phase: Implementing Multi-Parametric Monitoring in Stroke Unit

Actigraphy is a tool used to describe limb motor activity. Some actigraphic parameters, namely Motor Activity (MA) and Asymmetry Index (AR), correlate with stroke severity. However, a long-lasting actigraphic monitoring was never performed previously. We hypothesized that MA and AR can describe different clinical conditions during the evolution of the acute phase of stroke. We conducted a multicenter study and enrolled 69 stroke patients. NIHSS was assessed every hour and upper limbs' motor activity was continuously recorded. We calculated MA and AR in the first hour after admission, after a significant clinical change (NIHSS +/- 4) or at discharge. In a control group of 17 subjects, we calculated MA and AR normative values. We defined the best model to predict clinical status with multiple linear regression and identified actigraphic cut-off values to discriminate minor from major stroke (NIHSS >= 5) and NIHSS 5-9 from NIHSS >= 10. The AR cut-off value to discriminate between minor and major stroke (namely NIHSS >= 5) is 27% (sensitivity = 83%, specificity = 76% (AUC 0.86 p < 0.001), PPV = 89%, NPV = 42%). However, the combination of AR and MA of the non-paretic arm is the best model to predict NIHSS score (R-2: 0.482, F: 54.13), discriminating minor from major stroke (sensitivity = 89%, specificity = 82%, PPV = 92%, NPV = 75%). The AR cut-off value of 53% identifies very severe stroke patients (NIHSS >= 10) (sensitivity = 82%, specificity = 74% (AUC 0.86 p < 0.001), PPV = 73%, NPV = 82%). Actigraphic parameters can reliably describe the overall severity of stroke patients with motor symptoms, supporting the addition of a wearable actigraphic system to the multi-parametric monitoring in stroke units

The Immediate Effects of Immersive Virtual Reality on Autonomic Nervous System Function in Patients with Disorders of Consciousness after Severe Acquired Brain Injury: A Pilot Study

Disorders of Consciousness (DoCs) after severe acquired brain injury involve substantial impairment of cognition and physical functioning, requiring comprehensive rehabilitation and support. Technological interventions, such as immersive Virtual Reality (VR), have shown promising results in promoting neural activity and enhancing cognitive and motor recovery. VR can induce physical sensations that may activate the Autonomic Nervous System (ANS) and induce ANS-regulated responses. This study aimed to investigate the effects of immersive VR on the ANS in patients with DoCs through the analysis of the electrodermal activity (EDA). EDA was measured with a wearable device during a single immersive VR session consisting of static and dynamic videos depicting naturalistic environments. A pilot case-control study was conducted with 12 healthy participants and 12 individuals with DoCs. Results showed higher EDA values in patients than in healthy participants (p = 0.035), suggesting stronger autonomic activation during immersive VR exposure, while healthy subjects, in turn, showed a decrease in EDA values. Our results revealed a significant interaction between conditions and groups (p = 0.003), with patients showing significantly increased EDA values from the baseline compared to dynamic video observation (p = 0.014) and final rest (p = 0.007). These results suggest that immersive VR can elicit sympathetic arousal in patients with DoCs. This study highlights the potential of immersive VR as a tool to strengthen autonomic responses in patients with impaired consciousness

sj-pdf-1-eso-10.1177_23969873231186863 – Supplemental material for Anticoagulation in acute ischemic stroke patients with mechanical heart valves: To bridge or not with heparin. The ESTREM study

Supplemental material, sj-pdf-1-eso-10.1177_23969873231186863 for Anticoagulation in acute ischemic stroke patients with mechanical heart valves: To bridge or not with heparin. The ESTREM study by Maurizio Paciaroni, Valeria Caso, Michele Romoli, Cecilia Becattini, Alexander Salerno, Costanza Rapillo, Fanny Simonnet, Davide Strambo, Isabella Canavero, Marialuisa Zedde, Rosario Pascarella, Sung-Il Sohn, Simona Sacco, Raffaele Ornello, Kristian Barlinn, Daniela Schoene, Jan Rahmig, Maria Giulia Mosconi, Ilaria Leone De Magistris, Andrea Alberti, Michele Venti, Giorgio Silvestrelli, Alfonso Ciccone, Marina Padroni, Michele Laudisi, Andrea Zini, Luana Gentile, Odysseas Kargiotis, Georgios Tsivgoulis, Rossana Tassi, Francesca Guideri, Maurizio Acampa, Luca Masotti, Elisa Grifoni, Alessandro Rocco, Marina Diomedi, Theodore Karapanayiotides, Stefan T Engelter, Alexandros A Polymeris, Annaelle Zietz, Fabio Bandini, Pietro Caliandro, Giuseppe Reale, Marco Moci, Aurelia Zauli, Manuel Cappellari, Andrea Emiliani, Antonio Gasparro, Valeria Terruso, Marina Mannino, Elisa Giorli, Danilo Toni, Marco Andrighetti, Anne Falcou, Lina Palaiodimou, George Ntaios, Dimitrios Sagris, Efstathia Karagkiozi, Anastasia Adamou, Panagiotis Halvatsiotis, Yuriy Flomin, Umberto Scoditti, Antonio Genovese, Nemanja Popovic, Leonardo Pantoni, Francesco Mele, Nicola Molitierno, Piergiorgio Lochner, Alessandro Pezzini, Massimo Del Sette, Davide Sassos, Sotirios Giannopoulos, Maria Kosmidou, Evangelos Ntais, Enrico Maria Lotti, Vincenzo Mastrangelo, Alberto Chiti, Andrea Naldi, Peter Vanacker, Mario Ferrante, Vera Volodina, Michelangelo Mancuso, Nicola Giannini, Marco Baldini, Kostantinos Vadikolias, Sofia Kitmeridou, Carlo Emanuele Saggese, Tiziana Tassinari, Valentina Saia and Patrik Michel in European Stroke Journal</p