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Abstract Understanding the psychophysiological state during robot-aided rehabilitation is crucial for assessing the patient experience during treatments. This paper introduces a psychophysiological estimation approach using a Fuzzy Logic inference model to assess patients’ perception of robots during upper-limb robot-aided rehabilitation sessions. The patients were asked to perform nine cycles of 3D point-to-point trajectories toward different targets at varying heights with the assistance of an anthropomorphic robotic arm (i.e. KUKA LWR 4+). Physiological parameters, including galvanic skin response, heart rate, and respiration rate, were monitored across ten out of forty daily sessions. This data enabled the construction of an inference model to estimate patients’ perception states. Results expressed in terms of correlation coefficients between the patient state and the increasing number of sessions. Correlation coefficients showed statistically significant strong associations: a state of heightened engagement (formerly described as “Excited”) had $$\rho = -0.73$$ ρ = - 0.73 (p-value=0.01), and a more calm and resting state (namely “Relaxed” state) had $$\rho = 0.70$$ ρ = 0.70 (p-value=0.02) with the number of sessions completed. All patients had positive interaction with the robot, initially expressing curiosity and interest that gradually shifted to a more “Relaxed” state over time.

It is widely acknowledged that microglia actively regulate synaptic function in the brain. Remarkably, much of our understanding regarding the role of microglia in synaptic regulation is derived from studies in acute brain slices. However, it is still uncertain to what extent the preparation and maintenance of acute slices can influence microglial function and whether microglial changes may affect synaptic transmission. In this study, we examined the impact of acute slice resting time on hippocampal CA1 microglia, by assessing morphological and functional parameters at two distinct time intervals. We report that after 4 h from slicing microglia undergo morphological, functional, and transcriptional changes, including a decrease in the number of branches and in their movement speed. Furthermore, microglia acquire a reactive phenotype, characterized by increased amplitude of outward rectifying K+ currents, increased expression of the pro-inflammatory cytokine Tnfα and altered expression of the microglial receptors Cx3cr1 and P2y12r. We also examined time-dependent changes of excitatory synaptic transmission in CA1 pyramidal neurons from acute hippocampal slices, reporting time-dependent decrease in both amplitude and frequency of postsynaptic currents (sEPSCs), along with a decrease in spine density. Noticeably, sEPSCs amplitude decrease was absent in slices prepared from PLX5622 microglia-depleted mice, suggesting that this time-dependent effect on synaptic transmission is microglia-dependent. Our findings highlight possible causal relation between microglia phenotypic changes in the hours following slice preparation and concomitant synaptic changes, pointing to the mechanisms of acute synaptic modulation, whose understanding is crucial for unraveling microglia-neurons interplay in nature. Furthermore, they emphasize the potential issues associated with experimental time windows in ex vivo samples.

Abstract In recent years, several studies described the close relationship between the composition of gut microbiota and brain functions, highlighting the importance of gut-derived metabolites in mediating neuronal and glial cells cross-talk in physiological and pathological condition. Gut dysbiosis may affects cerebral tumors growth and progression, but the specific metabolites involved in this modulation have not been identified yet. Using a syngeneic mouse model of glioma, we have investigated the role of dysbiosis induced by the administration of non-absorbable antibiotics on mouse metabolome and on tumor microenvironment. We report that antibiotics treatment induced: (1) alteration of the gut and brain metabolome profiles; (2) modeling of tumor microenvironment toward a pro-angiogenic phenotype in which microglia and glioma cells are actively involved; (3) increased glioma stemness; (4) trans-differentiation of glioma cells into endothelial precursor cells, thus increasing vasculogenesis. We propose glycine as a metabolite that, in ABX-induced dysbiosis, shapes brain microenvironment and contributes to glioma growth and progression.

Este artículo explora la protección jurídica de la biodiversidad a nivel internacional, europeo y estadounidense, con el fin de evaluar si los enfoques adoptados priorizan una verdadera restauración de la naturaleza o bien podrían seguir fomentando dinámicas de mercantilización de los recursos naturales. Así, se analiza el régimen de protección de la biodiversidad tanto en el ámbito del derecho internacional como en el de los marcos establecidos por el Pacto Verde Europeo (European Green Deal) y el Nuevo Pacto Verde de Estados Unidos (Green New Deal). Ello incluye un análisis, entre otros, de la Estrategia de la UE sobre Biodiversidad para 2030 y del Reglamento UE sobre la Restauración de la Naturaleza, así como de la Hoja de Ruta de Soluciones basadas en la Naturaleza y la Guía para la Evaluación de Cambios en Servicios Ambientales y Ecosistémicos en el Análisis de Costo-Beneficio de Estados Unidos. Los Pactos Verdes, aunque proponen la restauración de ecosistemas, combinan inversiones públicas con el incentivo de mercados verdes, reflejando una continuidad con el modelo económico de crecimiento expansivo actual. Para abordar la crisis climática y de biodiversidad de manera efectiva, los Pactos Verdes deberían comprometerse no solo a la disminución de las emisiones de gases de efecto invernadero, sino también a la reducción de la extracción y el consumo de recursos naturales, a fin de asegurar la capacidad de la naturaleza para sostener la vida en el planeta.

In the dynamic landscape of contemporary healthcare, the imperative for advancing the frontiers of knowledge and improving patient outcomes necessitates a paradigm shift towards a multidisciplinary approach. This background great enhances a nurse's ability to interface with technology and create technical solutions such as robots, patient care devices, or computer simulation for patient care needs and nursing care delivery. This study aims to describe, through a narrative review of evidence, a methodology to develop and manager Nursing-Engineering interdisciplinary project, clarify the key points and facilitate professionals who are not very familiar with this topic. The methodology employed highlights the importance of this kind of research that allows to achieve highest standards of practice leading to improved patient care, innovative solutions and a global contribution to healthcare excellence.

While the disruptive impact of the COVID-19 pandemic continues to unfold around the world, one of its most immediate effects -- beyond significant loss of life and livelihood -- has been the exposure of existing weaknesses in various sectors and systems. This is especially evident in higher education, with its growing overreliance on the (hyper)mobile student body. In this paper we explore critically the challenges and possibilities behind the options of "reframing" and "hospicing" current understandings of student mobility, particularly with respect to the simultaneously romanticized and commodified development of intercultural (communicative) competence. We treat reframing and hospicing as concurrent, co-existing approaches and spaces in which we may dwell as we rethink what it means to engage meaningfully and equitably with difference at both global and local levels. We also explore how "hospicing" may help us to disinvest ourselves from the promises of mobility, letting go of our attachment to it, not simply because of its current impossibility, but rather because of its many ideological and ethical problems. We conclude with a set of critical, reflective questions intended as provocations that may stimulate ongoing dialogue in our shared journeys of knowing, being and relating to ourselves and the Other in the world.

Upper limb amputation severely affects the quality of life of individuals. Therefore, developing closed-loop upper-limb prostheses would enhance the sensory-motor capabilities of the prosthetic user. Considering design priorities based on user needs, the restoration of sensory feedback is one of the most desired features. This study focuses on employing Transcutaneous Electrical Nerve Stimulation (TENS) as a non-invasive somatotopic stimulation technique for restoring somatic sensations in upper-limb amputees. The aim of this study is to propose two encoding strategies to elicit force and slippage sensations in transradial amputees. The former aims at restoring three different levels of force through a Linear Pulse Amplitude Modulation (LPAM); the latter is devoted to elicit slippage sensations through Apparent Moving Sensation (AMS) by means of three different algorithms, i.e. the Pulse Amplitude Variation (PAV), the Pulse Width Variation (PWV) and Inter-Stimulus Delay Modulation (ISDM). Amputees had to characterize perceived sensations and to perform force and slippage recognition tasks. Results demonstrates that amputees were able to correctly identify low, medium and high levels of force, with an accuracy above the 80% and similarly, to also discriminate the slippage moving direction with a high accuracy above 90%, also highlighting that ISDM would be the most suitable method, among the three AMS strategies to deliver slippage sensations. It was demonstrated for the first time that the developed encoding strategies are effective methods to somatotopically reintroduce in the amputees, by means of TENS, force and slippage sensations.

In this article, we highlight the different positions expressed by the European Parliament and the European Commission on the need to provide for the involvement of trade unions in the new directive on Company Due Diligence. The Parliament's position tends to emphasize the importance of prior consultation with trade unions. In the opposite direction, the European Commission's draft directive, from a management perspective, understands due diligence compliance as a governance constraint decided unilaterally by companies. Considering these processes, we try to ask whether trade unions can autonomously contribute to the ecological transition of companies and the protection of human rights, considering the advantages and disadvantages of their involvement.

The state of language education in Australia has long been described as paradoxical. Oscillating between periods of increased attention and seeming invisibility, over the last thirty years, the language learning sector has been punctuated by a succession of aspirational declarations and funding injections with little long-term impact on its overall standing. Despite the increasingly multilingual makeup of Australian society, language education at all levels has largely remained stuck amidst monolingualising education policies and alarmist discourses. The latest instance of this paradoxical condition is a fee-reduction incentive for university students to study a language, which, in practice, stands to further weaken the language offerings in many Higher Education institutions. In this paper, we use the imagery of circularities and ripples to explore the challenges facing language education across sectors in Australia. Through data collected in Queensland secondary schools, we discuss how these challenges transcend the traditional delineation of macro-, meso-, and micro-levels of language policy and planning. We argue that challenges go both in circles within the same level (circularity) and flow outwards to other levels (ripples), which include Higher Education. For this reason, siloed approaches to funding and scholarly research contribute to a wicked state of inertia and, ultimately, diminish opportunities to break free from these cycles in the future. We conclude by acknowledging our complicit roles and ethical responsibilities as Higher Education scholars in the perpetuation of these cycles, as but a first step in engaging productively with the possibilities of leveraging these rippling circularities.

Purpose: The aim of this study was to use acoustic and kinematic speech measures to characterize type of motor speech impairment--apraxia of speech (AOS) versus dysarthria--in individuals with four-repeat tauopathy (4RT)-associated syndromes, including nonfluent variant primary progressive aphasia (nfvPPA), primary progressive AOS (PPAOS), corticobasal syndrome (CBS), and progressive supranuclear palsy syndrome (PSPs). Method: Twenty patient participants were recruited and stratified into two groups: (a) a motor-speech-impaired group of individuals with nfvPPA, PPAOS, CBS, or PSPs and suspected 4RT pathology ("MSI+") and (b) a non-- motor-speech-impaired group of individuals with logopenic variant primary progressive aphasia ("MSI-"). Ten healthy, age-matched controls also participated in the study. Participants completed a battery of speech tasks, and 15 acoustic and kinematic speech measures were derived. Quantitative speech measures were grouped into feature categories ("AOS features," "dysarthria features," "shared features"). In addition to quantitative speech measures, two certified speech-language pathologists made independent, blinded auditoryperceptual ratings of motor speech impairment. A principal component analysis (PCA) was conducted to investigate the relative contributions of quantitative features. Results: Quantitative speech measures were generally concordant with independent clinician ratings of motor speech impairment severity. Hypothesis-driven groupings of quantitative measures differentiated predominantly apraxic from predominantly dysarthric presentations within the MSI+ group. PCA results provided additional evidence for differential profiles of motor speech impairment in the MSI+ group; heterogeneity across individuals is explained in large part by varying levels of overall severity--captured by the shared feature variable group--and degree of apraxia severity, as measured by the AOS feature variable group. Conclusions: Quantitative features reveal heterogeneity of MSI in the 4RT group in terms of both overall severity and subtype of MSI. Results suggest the potential for acoustic and kinematic speech assessment methods to inform characterization of motor speech impairment in 4RT-associated syndromes.

Abstract Background Electroencephalography (EEG)-based brain-computer interfaces (BCIs) allow to modulate the sensorimotor rhythms and are emerging technologies for promoting post-stroke motor function recovery. The Promotoer study aims to assess the short and long-term efficacy of the Promotoer system, an EEG-based BCI assisting motor imagery (MI) practice, in enhancing post-stroke functional hand motor recovery. This paper details the statistical analysis plan of the Promotoer study. Methods The Promotoer study is a randomized, controlled, assessor-blinded, single-centre, superiority trial, with two parallel groups and a 1:1 allocation ratio. Subacute stroke patients are randomized to EEG-based BCI-assisted MI training or to MI training alone (i.e. no BCI). An internal pilot study for sample size re-assessment is planned. The primary outcome is the effectiveness of the Upper Extremity Fugl-Meyer Assessment (UE-FMA) score. Secondary outcomes include clinical, functional, and user experience scores assessed at the end of intervention and at follow-up. Neurophysiological assessments are also planned. Effectiveness formulas have been specified, and intention-to-treat and per-protocol populations have been defined. Statistical methods for comparisons of groups and for development of a predictive score of significant improvement are described. Explorative subgroup analyses and methodology to handle missing data are considered. Discussion The Promotoer study will provide robust evidence for the short/long-term efficacy of the Promotoer system in subacute stroke patients undergoing a rehabilitation program. Moreover, the development of a predictive score of response will allow transferring of the Promotoer system to optimal clinical practice. By carefully describing the statistical principles and procedures, the statistical analysis plan provides transparency in the analysis of data. Trial registration ClinicalTrials.gov NCT04353297 . Registered on April 15, 2020.

Pancreatic malignancy is the fourth cause of cancer-related death in Western countries and is predicted to become the second leading cause of cancer-related mortality by 2030. The standard therapies (FOLFIRINOX and gemcitabine with nab-paclitaxel) are not resolutive because this type of cancer is also characterized by a high chemoresistance, due in part to the activity of the ATP Binding Cassette (ABC) pumps accounting for the reduction in the intracellular concentration of the drugs. In this work, we analyze the occurrence of single-nucleotide polymorphisms (SNPs) in the MDR-1 gene, in different pancreatic cancer cell lines, and in tissues from pancreatic cancer patients by DNA sequencing, as well as the expression levels of MDR-1 mRNA and protein, by qRT-PCR and Western Blot analysis. We found that gemcitabine-resistant cells, in conjunction with homozygosis of analyzed SNPs, showed high MDR-1 basal levels with further increases after gemcitabine treatment. Nevertheless, we did not observe in the human PDAC samples a correlation between the level of MDR-1 mRNA and protein expression and SNPs. Preliminary, we conclude that in our small cohort, these SNPs cannot be used as molecular markers for predicting the levels of MDR-1 mRNA/protein levels and drug responses in patients with PDAC.

ASD is a complex condition primarily rooted in genetics, although influenced by environmental, prenatal, and perinatal risk factors, ultimately leading to genetic and epigenetic alterations. These mechanisms may manifest as inflammatory, oxidative stress, hypoxic, or ischemic damage. To elucidate potential variances in gene expression in ASD, a transcriptome analysis of peripheral blood mononuclear cells was conducted via RNA-seq on 12 ASD patients and 13 healthy controls, all of Sicilian ancestry to minimize environmental confounds. A total of 733 different statistically significant genes were identified between the two cohorts. Gene Set Enrichment Analysis (GSEA) and Gene Ontology (GO) terms were employed to explore the pathways influenced by differentially expressed mRNAs. GSEA revealed GO pathways strongly associated with ASD, namely the GO Biological Process term “Response to Oxygen-Containing Compound”. Additionally, the GO Cellular Component pathway “Mitochondrion” stood out among other pathways, with differentially expressed genes predominantly affiliated with this specific pathway, implicating the involvement of different mitochondrial functions in ASD. Among the differentially expressed genes, FPR2 was particularly highlighted, belonging to three GO pathways. FPR2 can modulate pro-inflammatory responses, with its intracellular cascades triggering the activation of several kinases, thus suggesting its potential utility as a biomarker of pro-inflammatory processes in ASD.

Abstract Affective states are psycho-physiological constructs connecting mental and physiological processes. They can be represented in terms of arousal and valence according to the Russel’s model and can be extracted from physiological changes in human body. However, a well-established optimal feature set and a classification method effective in terms of accuracy and estimation time are not present in the literature. This paper aims at defining a reliable and efficient approach for real-time affective state estimation. To obtain this, the optimal physiological feature set and the most effective machine learning algorithm, to cope with binary as well as multi-class classification problems, were identified. ReliefF feature selection algorithm was implemented to define a reduced optimal feature set. Supervised learning algorithms, such as K-Nearest Neighbors (KNN), cubic and gaussian Support Vector Machine, and Linear Discriminant Analysis, were implemented to compare their effectiveness in affective state estimation. The developed approach was tested on physiological signals acquired on 20 healthy volunteers during the administration of images, belonging to the International Affective Picture System, conceived for inducing different affective states. ReliefF algorithm reduced the number of physiological features from 23 to 13. The performances of machine learning algorithms were compared and the experimental results showed that both accuracy and estimation time benefited from the optimal feature set use. Furthermore, the KNN algorithm resulted to be the most suitable for affective state estimation. The results of the assessment of arousal and valence states on 20 participants indicate that KNN classifier, adopted with the 13 identified optimal features, is the most effective approach for real-time affective state estimation.