1,721,004 research outputs found

    Modeling of glycogen resynthesis according to insulin concentration: Towards a system for prevention of late-onset exercise-induced hypoglycemia in Type 1 diabetes patients

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    One of the major barriers for physical activity in type 1 diabetes (T1D) patients is the risk of exercise-induced hypoglycemia, in particular the late-onset one. The identification of the relation between glycogen resynthesis rate after an exercise and insulin concentration would allow the development of new predictive models. The aim of the present work was thus to investigate this relation in T1D patients. We recruited 8 T1D subjects which underwent two 24-h observational experimental sessions: complete rest and a 3-hours treadmill walk. Glucose and insulin concentrations were measured throughout the two sessions. Comparing the data collected in the two sessions, the net glucose uptake was calculated; positive values were suggestive of glycogen repletion while negative values suggested liver glycogen breakdown. A significant correlation (r=0.742, p<0.001) was observed between insulin concentration and net glucose uptake, with the negative values corresponding to time periods showing the lowest insulin concentrations. In conclusion, the present study preliminarily assessed the impact of insulin concentration on the risk of late onset hypoglycemia, which is the first step towards a comprehensive and personalized system for prevention of exercise-induced hypoglycemia in Type 1 diabetes patients

    Influence of smoking and other cardiovascular risk factors on heart rate circadian rhythm in normotensive and hypertensive subjects

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    Circadian heart rate (HR) is influenced by hypertension and other cardiovascular risk factors particularly smoking, obesity and dyslipidemia. Until now, to evaluate the HR changes due to presence of these risk factors, a single HR office measure or a mean evaluated on day time or night time or 24h was used. However, since HR shows a circadian behavior, a single value represents only a rough approximation of this behavior. In this study, we analyzed the influence of smoking, obesity and dyslipidemia on the circadian rhythm in normotensive and hypertensive subject groups presenting only one of these risk factors. The 24h HR recordings of 170 normotensive (83 without risk factors, 20 smokers, 44 with dyslipidemia, 23 obese) and 353 hypertensive (169 without risk factors, 32 smokers, 99 with dyslipidemia, 53 obese) subjects were acquired using a Holter Blood Pressure Monitor. Results highlighted a specific circadian behavior with three characteristic periods presenting different HR means and rates of HR change in the eight subject groups. The slopes could be used both to estimate the morning HR surge associated with acute cardiovascular effects in the awakening and to evaluate the decline during the night. Moreover, we suggest to use three HR mean values (one for each identified period of the day) rather than two HR values to better describe the circadian HR behavior. Furthermore, smoking increased and dyslipidemia decreased mean HR values from 10:00 to 04:00, both in normotensive and hypertensive subjects in comparison with subjects without risk factors. In this time interval, hypertensive obese subjects showed higher values while normotensive ones presented quite similar values than subjects without risk factors. During the awakening (05:00-10:00) the slopes were similar among all groups with no significant difference among the mean HR values

    Neurophysiological adaptations to spaceflight and simulated microgravity

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    Changes in physiological functions after spaceflight and simulated spaceflight involve several mechanisms. Microgravity is one of them and it can be partially reproduced with models, such as head down bed rest (HDBR). Yet, only a few studies have investigated in detail the complexity of neurophysiological systems and their integration to maintain homeostasis. Central nervous system changes have been studied both in their structural and functional component with advanced techniques, such as functional magnetic resonance (fMRI), showing the main involvement of the cerebellum, cortical sensorimotor, and somatosensory areas, as well as vestibular-related pathways. Analysis of electroencephalography (EEG) led to contrasting results, mainly due to the different factors affecting brain activity. The study of corticospinal excitability may enable a deeper understanding of countermeasures' effect, since greater excitability has been shown being correlated with better preservation of functions. Less is known about somatosensory evoked potentials and peripheral nerve function, yet they may be involved in a homeostatic mechanism fundamental to thermoregulation. Extending the knowledge of such alterations during simulated microgravity may be useful not only for space exploration, but for its application in clinical conditions and for life on Earth, as well

    EEG as a marker of brain plasticity in clinical applications

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    Neural networks are dynamic, and the brain has the capacity to reorganize itself. This capacity is named neuroplasticity and is fundamental for many processes ranging from learning and adaptation to new environments to the response to brain injuries. Measures of brain plasticity involve several techniques, including neuroimaging and neurophysiology. Electroencephalography, often used together with other techniques, is a common tool for prognostic and diagnostic purposes, and cortical reorganization is reflected by EEG measurements. Changes of power bands in different cortical areas occur with fatigue and in response to training stimuli leading to learning processes. Sleep has a fundamental role in brain plasticity, restoring EEG bands alterations and promoting consolidation of learning. Exercise and physical inactivity have been extensively studied as both strongly impact brain plasticity. Indeed, EEG studies showed the importance of the physical activity to promote learning and the effects of inactivity or microgravity on cortical reorganization to cope with absent or altered sensorimotor stimuli. Finally, this chapter will describe some of the EEG changes as markers of neural plasticity in neurologic conditions, focusing on cerebrovascular and neurodegenerative diseases. In conclusion, neuroplasticity is the fundamental mechanism necessary to ensure adaptation to new stimuli and situations, as part of the dynamicity of life

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Performance of EEG Motor-Imagery based spatial filtering methods: A BCI study on Stroke patients

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    The study reports the performance of stroke patients to operate Motor-Imagery based Brain-Computer Interface (MI-BCI) in early post-stroke neurorehabilitation and compares three different BCI spatial filtering techniques. The experiment was conducted on five stroke patients who performed a total of 15 MI-BCI sessions targeting paretic limbs. The EEG data were collected during the initial calibration phase of each session, and the individual BCI models were made by using Source Power Co-Modulation (SPoC), Spectrally weighted Common Spatial Patterns (SpecCSP), and Filter-Bank Common Spatial Patterns (FBCSP) BCI approaches. The accuracy of FBCSP was significantly higher than the accuracy of SPoC (85.1±1.9 % vs. 83.0±1.9 %; p=0.002), while the accuracy of FBCSP was slightly higher than the accuracy of SpecCSP (85.1±1.9 % vs. 83.8±2.0 %; p=0.068). No significant difference was found between SPoC and SpecCSP (p=0.616). The average false positive ratio was 16.9%, 17.1%, 14.3%, while the average false negative was 15.5 %, 16.9 %, 15.5 % for SpecCSP, SPoC, FBCSP, respectively. In conclusion, we demonstrated that the stroke patients were capable of controlling MI-BCI, with high accuracy and that FBCSP may be used as the MI-BCI approach for complementary neurorehabilitation during early stroke phases

    Return to school in the COVID-19 era: considerations for temperature measurement

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    COVID-19 pandemics required a reorganisation of social spaces to prevent the spread of the virus. Due to the common presence of fever in the symptomatic patients, temperature measurement is one of the most common screening protocols. Indeed, regulations in many countries require temperature measurements before entering shops, workplaces, and public buildings. Due to the necessity of providing rapid non-contact and non-invasive protocols to measure body temperature, infra-red thermometry is mostly used. Many countries are now facing the need to organise the return to school and universities in the COVID-19 era, which require solutions to prevent the risk of contagion between students and/or teachers and technical/administrative staff. This paper highlights and discusses some of the strengths and limitations of infra-red cameras, including the site of measurements and the influence of the environment, and recommends to be careful to consider such measurements as a single “safety rule” for a good return to normality

    A novel computed tomography perfusion-based quantitative tool for evaluation of perfusional abnormalities in migrainous aura stroke mimic

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    Background: Migrainous aura (MA) represents the third most common stroke mimic (SM). Advanced neuroimaging is pivotal in the assessment of patients with focal neurological acute symptoms. We investigated brain perfusion alterations in MA-SM patients using a novel CT perfusion (CTP)-based quantitative approach in order to improve differential diagnosis between MA and acute stroke. Methods: We processed and analysed the clinical and neuroimaging CTP data, acquired within 4.5 h from symptom onset, of patients with acute focal neurological symptoms receiving a final diagnosis of MA. The differences between ROI, compatible with MA symptoms, and contralateral side were automatically estimated in terms of asymmetry index (AI%) by the newly developed tool for mean transit time (MTT), CBF, and cerebral blood volume (CBV) CTP parameters. The AI% ≥ 10% was considered significant. Results: Out of 923 admitted patients, 14 patients with MA were included. In 13 out of 14 cases, a significant pattern of hypoperfusion was observed by quantitative analysis in at least one of the CTP maps. In 7 patients, all three CTP maps were significantly altered. In particular, MTT-AI% increased in 11 (79%) cases, while CBF-AI% and CBV-AI% decreased in 12 (86%) and in 9 (64%) patients, respectively. All CBV values were above ischemic stroke core threshold and all MTT-AI were below ischemic penumbra threshold. Conclusions: Our data suggest that a novel CTP-quantitative approach may detect during MA a moderate hypoperfusion pattern in the cerebral regions compatible with aura symptoms. The use of this novel tool could support differential diagnosis between MA and acute stroke
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