Search

Abstract Peripheral neural interfaces facilitate bidirectional communication between the nervous system and external devices, enabling precise control for prosthetic limbs, sensory feedback systems, and therapeutic interventions in the field of Bioelectronic Medicine. Intraneural interfaces hold great promise since they ensure high selectivity in communicating only with the desired nerve fascicles. Despite significant advancements, challenges such as chronic immune response, signal degradation over time, and lack of long-term biocompatibility remain critical considerations in the development of such devices. Here we report on the development and benchtop characterization of a novel design of an intraneural interface based on carbon fiber bundles. Carbon fibers possess low impedance, enabling enhanced signal detection and stimulation efficacy compared to traditional metal electrodes. We provided a 3D-stabilizing structure for the carbon fiber bundles made of PEDOT:PSS hydrogel, to enhance the biocompatibility between the carbon fibers and the nervous tissue. We further coated the overall bundles with a thin layer of elastomeric material to provide electrical insulation. Taken together, our results demonstrated that our electrode possesses adequate structural and electrochemical properties to ensure proper stimulation and recording of peripheral nerve fibers and a biocompatible interface with the nervous tissue.

Abstract Background In recent years, significant efforts have been directed towards the research and development of disease-modifying therapies for dementia. These drugs focus on prodromal (mild cognitive impairment, MCI) and/or early stages of Alzheimer’s disease (AD). Literature evidence indicates that a considerable proportion of individuals with MCI do not progress to dementia. Identifying individuals at higher risk of developing dementia is essential for appropriate management, including the prescription of new disease-modifying therapies expected to become available in clinical practice in the near future. Methods The ongoing INTERCEPTOR study is a multicenter, longitudinal, interventional, non-therapeutic cohort study designed to enroll 500 individuals with MCI aged 50–85 years. The primary aim is to identify a biomarker or a set of biomarkers able to accurately predict the conversion from MCI to AD dementia within 3 years of follow-up. The biomarkers investigated in this study are neuropsychological tests (mini-mental state examination (MMSE) and delayed free recall), brain glucose metabolism ([18F]FDG-PET), MRI volumetry of the hippocampus, EEG brain connectivity, cerebrospinal fluid (CSF) markers (p-tau, t-tau, Aβ1-42, Aβ1-42/1–40 ratio, Aβ1-42/p-Tau ratio) and APOE genotype. The baseline visit includes a full cognitive and neuropsychological evaluation, as well as the collection of clinical and socio-demographic information. Prognostic models will be developed using Cox regression, incorporating individual characteristics and biomarkers through stepwise selection. Model performance will be evaluated in terms of discrimination and calibration and subjected to internal validation using the bootstrapping procedure. The final model will be visually represented as a nomogram. Discussion This paper contains a detailed description of the statistical analysis plan to ensure the reproducibility and transparency of the analysis. The prognostic model developed in this study aims to identify the population with MCI at higher risk of developing AD dementia, potentially eligible for drug prescriptions. The nomogram could provide a valuable tool for clinicians for risk stratification and early treatment decisions. Trial registration ClinicalTrials.gov NCT03834402. Registered on February 8, 2019

River bifurcations are constituent components of multi-thread fluvial systems, playing a crucial role in their morphodynamic evolution and the partitioning of water and sediment. Although many studies have been directed at exploring bifurcation dynamics, the conditions under which avulsions occur, resulting in the complete abandonment of one branch, are still not well understood. To address this knowledge gap, we develop a novel 1D numerical model based on existing nodal point relations for sediment partitioning, which allows for the simulation of the morphodynamic evolution of a free bifurcation. Model results show that when the discharge asymmetry is so high that the shoaling branch does not transport sediments (partial avulsion conditions) the dominant branch undergoes significant degradation, leading to a higher inlet step between the bifurcates and further amplifying the discharge asymmetry. The degree of asymmetry is found to increase with the length of the downstream channels to the point that when they are sufficiently long, the shoaling branch is completely abandoned (full avulsion conditions). To complement our numerical findings, we also formulate a new analytical model that is able to reproduce the essential characteristics of the partial avulsion equilibrium, which enables us to identify the key parameters that control the transition between different configurations. In summary, this research sheds light on the fundamental processes that drive avulsion through the abandonment of river bifurcations. The insights gained from this study provide a foundation for further investigations and may offer valuable information for the design of sustainable river restoration projects.

Hydrogen storage is a key enabling technology for the extensive use of hydrogen as energy carrier. This is particularly true in the widespread introduction of hydrogen in car transportation. Indeed, one of the greatest technological barriers for such development is an efficient and safe storage method. So, in this tutorial review the existing hydrogen storage technologies are described with a special emphasis on hydrogen storage in hydrogen cars: the current and the ongoing solutions. A particular focus is given on solid storage and some of the recent advances on plasma hydrogen ion implantation, which should allow not only the preparation of metal hydrides, but also the imagination of a new refluing circuit. From hydrogen discovery to its use as an energy vector in cars, this review wants to be as exhaustive as possible, introducing the basics of hydrogen storage, and discussing the experimental practicalities of car hydrogen fuel. It wants to serve as a guide for anyone wanting to undertake such a technology and to equip the reader with an advanced knowledge on hydrogen storage and hydrogen storage in hydrogen cars to stimulate further researches and yet more innovative applications for this highly interesting field.

Abstract Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer’s dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables. 506 subjects from 5 databases were included. MRI images were processed with FreeSurfer, LPA, and TRACULA to obtain brain volumes and thicknesses, white matter lesions and diffusion metrics. MRI metrics were used in conjunction with clinical and demographic data to perform differential diagnosis based on a Support Vector Machine model called MUQUBIA (Multimodal Quantification of Brain whIte matter biomArkers). Age, gender, Clinical Dementia Rating (CDR) Dementia Staging Instrument, and 19 imaging features formed the best set of discriminative features. The predictive model performed with an overall Area Under the Curve of 98%, high overall precision (88%), recall (88%), and F1 scores (88%) in the test group, and good Label Ranking Average Precision score (0.95) in a subset of neuropathologically assessed patients. The results of MUQUBIA were explained by the SHapley Additive exPlanations (SHAP) method. The MUQUBIA algorithm successfully classified various dementias with good performance using cost-effective clinical and MRI information, and with independent validation, has the potential to assist physicians in their clinical diagnosis.

This entry overviews the pioneering experimental studies exploiting eye movement data to investigate language processing in real time. After examining how vision and language were found to be closely related, herein focus the discussion on the evolution of eye-tracking methodologies to investigate children’s language development. To conclude, herein provide some insights about the use of eye-tracking technology for research purposes, focusing on data collection and data analysis.

IntroductionNeural circuit alterations lay at the core of brain physiopathology, and yet are hard to unveil in living subjects. The Virtual Brain (TVB) modeling, by exploiting structural and functional magnetic resonance imaging (MRI), yields mesoscopic parameters of connectivity and synaptic transmission.MethodsWe used TVB to simulate brain networks, which are key for human brain function, in Alzheimer’s disease (AD) and frontotemporal dementia (FTD) patients, whose connectivity and synaptic parameters remain largely unknown; we then compared them to healthy controls, to reveal novel in vivo pathological hallmarks.ResultsThe pattern of simulated parameter differed between AD and FTD, shedding light on disease-specific alterations in brain networks. Individual subjects displayed subtle differences in network parameter patterns that significantly correlated with their individual neuropsychological, clinical, and pharmacological profiles.DiscussionThese TVB simulations, by informing about a new personalized set of networks parameters, open new perspectives for understanding dementias mechanisms and design personalized therapeutic approaches.

Abstract Climate change is expected to alter the distribution of flow discharge in rivers worldwide. We study the impact of climate‐driven flow changes on the shape of riverbed, and specifically on alternate bars, large deposits of gravel/sand that often form in rivers. We consider the illustrative example of the Alpine Rhine River, showing two nearby reaches with similar hydro‐morphological characteristics, but different channel width. Hydrological projections are obtained from literature, while the evolution of alternate bars is predicted through a novel, semi‐analytical model. Results show a remarkably different behavior of the two reaches: the upstream one, being wide enough for a full development of alternate bars, is resistant to flow alterations; the downstream reach, whose width is close to threshold conditions, is highly susceptible to future changes, showing a strong tendency to increase bar prominence. These findings reflect a general tendency of near‐threshold geomorphic systems to be vulnerable to anthropic stressors.

Nerve conduits may represent a valuable alternative to autograft for the regeneration of long-gap damages. However, no NCs have currently reached market approval for the regeneration of limiting gap lesions, which still represents the very bottleneck of this technology. In recent years, a strong effort has been made to envision an engineered graft to tackle this issue. In our recent work, we presented a novel design of porous/3D-printed chitosan/poly-ε-caprolactone conduits, coupling freeze drying and additive manufacturing technologies to yield conduits with good structural properties. In this work, we studied genipin crosslinking as strategy to improve the physiochemical properties of our conduit. Genipin is a natural molecule with very low toxicity that has been used to crosslink chitosan porous matrix by binding the primary amino group of chitosan chains. Our characterization evidenced a stabilizing effect of genipin crosslinking towards the chitosan matrix, with reported modified porosity and ameliorated mechanical properties. Given the reported results, this method has the potential to improve the performance of our conduits for the regeneration of long-gap nerve injuries.

Natural language processing (NLP) is rapidly becoming an important topic in the medical community. The ability to automatically analyze any type of medical document could be the key factor to fully exploit the data it contains. Cutting-edge artificial intelligence (AI) architectures, particularly machine learning and deep learning, have begun to be applied to this topic and have yielded promising results. We conducted a literature search for 1,024 papers that used NLP technology in neuroscience and psychiatry from 2010 to early 2022. After a selection process, 115 papers were evaluated. Each publication was classified into one of three categories: information extraction, classification, and data inference. Automated understanding of clinical reports in electronic health records has the potential to improve healthcare delivery. Overall, the performance of NLP applications is high, with an average F1-score and AUC above 85%. We also derived a composite measure in the form of Z-scores to better compare the performance of NLP models and their different classes as a whole. No statistical differences were found in the unbiased comparison. Strong asymmetry between English and non-English models, difficulty in obtaining high-quality annotated data, and train biases causing low generalizability are the main limitations. This review suggests that NLP could be an effective tool to help clinicians gain insights from medical reports, clinical research forms, and more, making NLP an effective tool to improve the quality of healthcare services.

The aim of this study was to elucidate the chemistry of cellular degeneration in human neuroblastoma cells upon exposure to outer-membrane vesicles (OMVs) produced by Porphyromonas gingivalis (Pg) oral bacteria by monitoring their metabolomic evolution using in situ Raman spectroscopy. Pg-OMVs are a key factor in Alzheimer’s disease (AD) pathogenesis, as they act as efficient vectors for the delivery of toxins promoting neuronal damage. However, the chemical mechanisms underlying the direct impact of Pg-OMVs on cell metabolites at the molecular scale still remain conspicuously unclear. A widely used in vitro model employing neuroblastoma SH-SY5Y cells (a sub-line of the SK-N-SH cell line) was spectroscopically analyzed in situ before and 6 h after Pg-OMV contamination. Concurrently, Raman characterizations were also performed on isolated Pg-OMVs, which included phosphorylated dihydroceramide (PDHC) lipids and lipopolysaccharide (LPS), the latter in turn being contaminated with a highly pathogenic class of cysteine proteases, a key factor in neuronal cell degradation. Raman characterizations located lipopolysaccharide fingerprints in the vesicle structure and unveiled so far unproved aspects of the chemistry behind protein degradation induced by Pg-OMV contamination of SH-SY5Y cells. The observed alterations of cells’ Raman profiles were then discussed in view of key factors including the formation of amyloid β (Aβ) plaques and hyperphosphorylated Tau neurofibrillary tangles, and the formation of cholesterol agglomerates that exacerbate AD pathologies.

2,5-furandicarboxylic acid (FDCA) is one of the most studied bio-based monomers, being considered the best substitute for fossil-derived terephthalic acid in plastic production. FDCA is employed in the preparation of polyethylene furanoate (PEF), demonstrating superior mechanical and thermal proprieties compared to the widely used polyethylene terephthalate (PET). Nevertheless, FDCA synthesis mostly relies on the oxidation of the bio-based platform chemical hydroxymethyl furfural (HMF), whose notoriously instable nature renders FDCA yield and industrial scale-up production complicated. On the contrary, FDCA esters are less studied, even though they have greater solubility in organic media, which would favor their isolation and potential application as monomers for PEF. On these premises, we report herein an alternative green synthetic approach to FDCA methyl ester (FDME) using galactaric acid as the substrate, dimethyl carbonate (DMC) as the green media, and Fe2(SO4)3 as the heterogeneous Lewis acid. Optimization of the reaction conditions allowed the selective production of FDME in a 70% isolated yield; product purification was achieved via flash column chromatography over silica. Furthermore, it was possible to employ up to 5.0 g of galactaric acid in a single reaction, leading to a good isolated yield of FDME.

Abstract Normative modelling is an emerging method for quantifying how individuals deviate from the healthy populational pattern. Several machine learning models have been implemented to develop normative models to investigate brain disorders, including regression, support vector machines and Gaussian process models. With the advance of deep learning technology, the use of deep neural networks has also been proposed. In this study, we assessed normative models based on deep autoencoders using structural neuroimaging data from patients with Alzheimer’s disease (n = 206) and mild cognitive impairment (n = 354). We first trained the autoencoder on an independent dataset (UK Biobank dataset) with 11,034 healthy controls. Then, we estimated how each patient deviated from this norm and established which brain regions were associated to this deviation. Finally, we compared the performance of our normative model against traditional classifiers. As expected, we found that patients exhibited deviations according to the severity of their clinical condition. The model identified medial temporal regions, including the hippocampus, and the ventricular system as critical regions for the calculation of the deviation score. Overall, the normative model had comparable cross-cohort generalizability to traditional classifiers. To promote open science, we are making all scripts and the trained models available to the wider research community.

Abstract The objective of this study is to validate the specific questionnaire for Hepatitis B HBQOL (Hepatitis B Quality of Life Instrument, version 1.0) for the Brazilian version, in addition to testing its applicability in patients with hepatitis B under treatment and comparing the quality of life between patients using first-line drugs (tenofovir and entecavir). For the validation, the back-translation technique was used in a sample of 47 patients. Factor analysis was performed between the items in each domain of the questionnaire and the internal consistency was calculated using Cronbach's α coefficient. In assessing the applicability of the validated questionnaire, interviews were carried out with 124 patients. Sociodemographic and treatment data were collected to characterize the sample and perform correlation analyzes. The results demonstrate that the Brazilian version of the questionnaire was successfully validated. In the analysis carried out among the 124 patients, the domains psychological well-being and stigma obtained the highest scores in quality of life and the lowest level of education conferred better results in these two domains. The comparison between tenofovir and entecavir showed no significant difference in patients' quality of life. The use of this validated instrument can make therapeutic decisions more rational.

Abstract Neural interfaces are bioelectronic devices capable of stimulating a population of neurons or nerve fascicles and recording electrical signals in a specific area. Despite their success in restoring sensory-motor functions in people with disabilities, their long-term exploitation is still limited by poor biocompatibility, mechanical mismatch between the device and neural tissue and the risk of a chronic inflammatory response upon implantation. In this context, the use of nature-derived materials can help address these issues. Examples of these materials, such as extracellular matrix proteins, peptides, lipids and polysaccharides, have been employed for decades in biomedical science. Their excellent biocompatibility, biodegradability in the absence of toxic compound release, physiochemical properties that are similar to those of human tissues and reduced immunogenicity make them outstanding candidates to improve neural interface biocompatibility and long-term implantation safety. The objective of this review is to highlight progress and challenges concerning the impact of nature-derived materials on neural interface design. The use of these materials as biocompatible coatings and as building blocks of insulation materials for use in implantable neural interfaces is discussed. Moreover, future perspectives are presented to show the increasingly important uses of these materials for neural interface fabrication and their possible use for other applications in the framework of neural engineering.

Neuroimaging studies often lack reproducibility, one of the cardinal features of the scientific method. Multisite collaboration initiatives increase sample size and limit methodological flexibility, therefore providing the foundation for increased statistical power and generalizable results. However, multisite collaborative initiatives are inherently limited by hardware, software, and pulse and sequence design heterogeneities of both clinical and preclinical MRI scanners and the lack of benchmark for acquisition protocols, data analysis, and data sharing. We present the overarching vision that yielded to the constitution of RIN-Neuroimaging Network, a national consortium dedicated to identifying disease and subject-specific in-vivo neuroimaging biomarkers of diverse neurological and neuropsychiatric conditions. This ambitious goal needs efforts toward increasing the diagnostic and prognostic power of advanced MRI data. To this aim, 23 Italian Scientific Institutes of Hospitalization and Care (IRCCS), with technological and clinical specialization in the neurological and neuroimaging field, have gathered together. Each IRCCS is equipped with high- or ultra-high field MRI scanners (i.e., ≥3T) for clinical or preclinical research or has established expertise in MRI data analysis and infrastructure. The actions of this Network were defined across several work packages (WP). A clinical work package (WP1) defined the guidelines for a minimum standard clinical qualitative MRI assessment for the main neurological diseases. Two neuroimaging technical work packages (WP2 and WP3, for clinical and preclinical scanners) established Standard Operative Procedures for quality controls on phantoms as well as advanced harmonized quantitative MRI protocols for studying the brain of healthy human participants and wild type mice. Under FAIR principles, a web-based e-infrastructure to store and share data across sites was also implemented (WP4). Finally, the RIN translated all these efforts into a large-scale multimodal data collection in patients and animal models with dementia (i.e., case study). The RIN-Neuroimaging Network can maximize the impact of public investments in research and clinical practice acquiring data across institutes and pathologies with high-quality and highly-consistent acquisition protocols, optimizing the analysis pipeline and data sharing procedures.

A PolSAR is an active sensing device capable of providing images that are robust against variations of weather and atmosphere conditions, irrespective of the time of the day they were acquired. For an efficient use of these images it is necessary to have algorithms capable of classifying these images to generate maps with their content automatically. This paper presents the extension of a PolSAR image classification method based on exponential Fisher Vectors, a Potts smoothing model and different similarity measures. With the proposed extension, improvements in classification with respect to the base method are achieved. Future work consists in extending the codification so as not to have to discard the imaginary part of the data.

The formation of alternate bars in straightened river reaches represents a fundamental process of river morphodynamics that has received great attention in the last decades. It is well-established that migrating alternate bars arise from an autogenic instability mechanism occurring when the channel width-to-depth ratio is sufficiently large. While several empirical and theoretical relations are available for predicting how bar height and length depend on the key dimensionless parameters, there is a lack of direct, quantitative information about the dependence of bar properties on flow discharge. We performed a series of experiments in a long, mobile-bed flume with fixed and straight banks at different discharges. The self-formed bed topography was surveyed, different metrics were analyzed to obtain quantitative information about bar height and shape, and results were interpreted in the light of existing theoretical models. The analysis reveals that the shape of alternate bars highly depends on their formative discharge, with remarkable variations in the harmonic composition and a strong decreasing trend of the skewness of the bed elevation. Similarly, the height of alternate bars clearly decreases with the water discharge, in quantitative agreement with theoretical predictions. However, the disappearance of bars when discharge exceeds a critical threshold is not as sharp as expected due to the formation of so-called “diagonal bars”. This work provides basic information for modeling and interpreting short-term morphological variations during individual flood events and long-term trajectories due to alterations of the hydrological regime.

Abstract Backgrounds To explain the excess cardiovascular mortality observed in the SERVE-HF study, it was hypothesized that the high-pressure ASV default settings used lead to inappropriate ventilation, cascading negative consequences (i.e. not only pro-arrythmogenic effects through metabolic/electrolyte abnormalities, but also lower cardiac output). The aims of this study are: i) to describe ASV-settings for long-term ASV-populations in real-life conditions; ii) to describe the associated minute-ventilations (MV) and therapeutic pressures for servo-controlled-flow versus servo-controlled-volume devices (ASV-F Philips®-devices versus ASV-V ResMed®-devices). Methods The OTRLASV-study is a cross-sectional, 5-centre study including patients who underwent ASV-treatment for at least 1 year. The eight participating clinicians were free to adjust ASV settings, which were compared among i) initial diagnosed sleep-disordered-breathing (SBD) groups (Obstructive-Sleep-Apnea (OSA), Central-Sleep-Apnea (CSA), Treatment-Emergent-Central-Sleep-Apnea (TECSA)), and ii) unsupervised groups (k-means clusters). To generate these clusters, baseline and follow-up variables were used (age, sex, body mass index (BMI), initial diagnosed Obstructive-Apnea-Index, initial diagnosed Central-Apnea-Index, Continuous-Positive-Airway-Pressure used before ASV treatment, presence of cardiopathy, and presence of a reduced left-ventricular-ejection-fraction (LVEF)). ASV-data were collected using the manufacturer’s software for 6 months. Results One hundred seventy-seven patients (87.57% male) were analysed with a median (IQ25–75) initial Apnea-Hypopnea-Index of 50 (38–62)/h, an ASV-treatment duration of 2.88 (1.76–4.96) years, 61.58% treated with an ASV-V. SDB groups did not differ in ASV settings, MV or therapeutic pressures. In contrast, the five generated k-means clusters did (generally described as follows: (C1) male-TECSA-cardiopathy, (C2) male-mostly-CSA-cardiopathy, (C3) male-mostly-TECSA-no cardiopathy, (C4) female-mostly-elevated BMI-TECSA-cardiopathy, (C5) male-mostly-OSA-low-LVEF). Of note, the male-mostly-OSA-low-LVEF-cluster-5 had significantly lower fixed end-expiratory-airway-pressure (EPAP) settings versus C1 (p = 0.029) and C4 (p = 0.007). Auto-EPAP usage was higher in the male-mostly-TECSA-no cardiopathy-cluster-3 versus C1 (p = 0.006) and C2 (p

When a traumatic event causes complete denervation, muscle functional recovery is highly compromised. A possible solution to this issue is the implantation of a biodegradable polymeric tubular scaffold, providing a biomimetic environment to support the nerve regeneration process. However, in the case of consistent peripheral nerve damage, the regeneration capabilities are poor. Hence, a crucial challenge in this field is the development of biodegradable micro- nanostructured polymeric carriers for controlled and sustained release of molecules to enhance nerve regeneration. The aim of these systems is to favor the cellular processes that support nerve regeneration to increase the functional recovery outcome. Drug delivery systems (DDSs) are interesting solutions in the nerve regeneration framework, due to the possibility of specifically targeting the active principle within the site of interest, maximizing its therapeutical efficacy. The scope of this review is to highlight the recent advances regarding the study of biodegradable polymeric DDS for nerve regeneration and to discuss their potential to enhance regenerative performance in those clinical scenarios characterized by severe nerve damage.

In recent years, a great deal of effort has been undertaken with regards to treatment of pathologies at the level of the central nervous system (CNS). Here, the presence of the blood-brain barrier acts as an obstacle to the delivery of potentially effective drugs and makes accessibility to, and treatment of, the CNS one of the most significant challenges in medicine. In this Roadmap article, we present the status of the timeliest developments in the field, and identify the outstanding challenges and opportunities that exist. The format of the Roadmap, whereby experts in each discipline share their viewpoint and present their vision, reflects the dynamic and multidisciplinary nature of this research area, and is intended to generate dialogue and collaboration across traditional subject areas. It is stressed here that this article is not intended to act as a comprehensive review article, but rather an up-to-date and forward-looking summary of research methodologies pertaining to the treatment of pathologies at the level of the CNS.

Background. Volunteers’ participation in scientific research has increased in recent decades. Citizen science (CS) data have been used in quantitative ecology to analyse species ranges by means of species distribution models. We investigated the Italian distribution of five large saproxylic beetles (big five), to describe their niche space, paramount areas for their conservation, and conservation gaps. Methods. CS data from two projects, climate and environmental variables were used to produce Habitat suitability (HS) maps for each species and averaged HS maps. The big five’s conservation status was assessed interpolating HS maps with the distribution of protected areas, concomitantly identifying conservation gaps. Results. The pre-alpine and Apennines arcs, north-eastern Sicily and eastern Sardinia, were identified as conservation’s hotspots. Ranking HS levels from minimum to optimal, the extent of conservation gaps decreases as environmental suitability for the big five increases. Conclusions. For the first time in Italy, CS data have been used to investigate niche space of the largest protected saproxylic beetles and analyse the distribution of their suitable habitat. The resulting HS raster maps and vector layers, reporting HS value in all Italian protected areas (n° 3771), were provided and discussed, reporting an application example for conservation purposes.

Alzheimer’s disease (AD) is a hereditary and sporadic neurodegenerative illness defined by the gradual and cumulative loss of neurons in specific brain areas. The processes that cause AD are still under investigation and there are no available therapies to halt it. Current progress puts at the forefront the “calcium (Ca2+) hypothesis” as a key AD pathogenic pathway, impacting neuronal, astrocyte and microglial function. In this review, we focused on mitochondrial Ca2+ alterations in AD, their causes and bioenergetic consequences in neuronal and glial cells, summarizing the possible mechanisms linking detrimental mitochondrial Ca2+ signals to neuronal death in different experimental AD models.

Staphylococcal enterotoxins are a wide family of bacterial exotoxins with the capacity to activate as much as 20% of the host T cells, which is why they were called superantigens. Superantigens (SAgs) can cause multiple diseases in humans and cattle, ranging from mild to life-threatening infections. Almost all S. aureus isolates encode at least one of these toxins, though there is no complete knowledge about how their production is triggered. One of the main problems with the available evidence for these toxins is that most studies have been conducted with a few superantigens; however, the resulting characteristics are attributed to the whole group. Although these toxins share homology and a two-domain structure organization, the similarity ratio varies from 20 to 89% among different SAgs, implying wide heterogeneity. Furthermore, every attempt to structurally classify these proteins has failed to answer differential biological functionalities. Taking these concerns into account, it might not be appropriate to extrapolate all the information that is currently available to every staphylococcal SAg. Here, we aimed to gather the available information about all staphylococcal SAgs, considering their functions and pathogenicity, their ability to interact with the immune system as well as their capacity to be used as immunotherapeutic agents, resembling the two faces of Dr. Jekyll and Mr. Hyde.

Piezoelectric materials are a class of compounds that is gaining increasing interest in various applications such as energy harvesting. During the last decade, lead-free ZnSnO3 perovskite ceramic has gained attention among the scientific community thanks to its unique symmetry-dependent and spontaneous polarization properties such as piezoelectricity and ferroelectricity. Nevertheless, only a few studies successfully prepared pure ZnSnO3, while most seem to mislead the product for its hydroxide precursor (ZnSn(OH)6) or a mixture of Zn2SnO4 and SnO2. In our work, we investigated the conversion of ZnSn(OH)6 at different temperatures (500, 600, 700, 750 and 800 °C) by X-ray powder diffraction analysis, and in-situ using synchrotron radiation up to 950 °C under ambient atmosphere and in a vacuum, to reproduce conventional reaction conditions. SEM and TEM have been used to understand the evolution of the particle shape and surface structure before and after the thermal treatments. Our results show the instability of the ZnSn(OH)6 phase, which converts into an amorphous structure at low temperature. Above 750 °C, the material segregates into Zn2SnO4 and SnO2, supporting the hypothesis that the thermal treatment of the hydroxide phase under typical conditions results in the formation of an oxide mixture rather than the phase pure ZnSnO3.

Nickel manganite thin films were prepared by chemical solution deposition from nitrate and acetate precursors on polished alumina substrates. By variation of crystallization temperature between 650 ​°C and 900 ​°C and atmosphere during cooling of the films, the morphology, phase formation and electrical properties of the films were investigated. The electrically conductive spinel phase was formed as a main phase independent of processing conditions exhibiting NTCR characteristics. Cooling down in nitrogen atmosphere favored the decomposition of the spinel phase into nickel oxide and a spinel phase with higher manganese content, but it also reduced the resistance drift of the samples. From this finding it can be deduced that a reduced oxygen partial pressure influences defect equilibria and by that decreases cation vacancy concentration. This supports the assumption that cation redistribution by a cation vacancy diffusion mechanism is a relevant mechanism of resistance drift in such thin films.

IntroductionHippocampal volume is one of the main biomarkers of Alzheimer’s Dementia (AD). Over the years, advanced tools that performed automatic segmentation of Magnetic Resonance Imaging (MRI) T13D scans have been developed, such as FreeSurfer (FS) and ACM-Adaboost (AA). Hippocampal volume is considered abnormal when it is below the 5th percentile of the normative population. The aim of this study was to set norms, established from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) population, for hippocampal volume measured with FS v.6.0 and AA tools in the neuGRID platform (www.neugrid2.eu) and demonstrate their applicability for the Italian population.MethodsNorms were set from a large group of 545 healthy controls belonging to ADNI. For each pipeline, subjects with segmentation errors were discarded, resulting in 532 valid segmentations for FS and 421 for AA (age range 56–90 years). The comparability of ADNI and the Italian Brain Normative Archive (IBNA), representative of the Italian general population, was assessed testing clinical variables, neuropsychological scores and normalized hippocampal volumes. Finally, percentiles were validated using the Italian Alzheimer’s disease Repository Without Borders (ARWiBo) as external independent data set to evaluate FS and AA generalizability.ResultsHippocampal percentiles were checked with the chi-square goodness of fit test. P-values were not significant, showing that FS and AA algorithm distributions fitted the data well. Clinical, neuropsychological and volumetric features were similar in ADNI and IBNA (p > 0.01). Hippocampal volumes measured with both FS and AA were associated with age (p < 0.001). The 5th percentile thresholds, indicating left/right hippocampal atrophy were respectively: (i) below 3,223/3,456 mm3 at 56 years and 2,506/2,415 mm3 at 90 years for FS; (ii) below 4,583/4,873 mm3 at 56 years and 3,831/3,870 mm3 at 90 years for AA. The average volumes computed on 100 cognitively intact healthy controls (CN) selected from ARWiBo were close to the 50th percentiles, while those for 100 AD patients were close to the abnormal percentiles.DiscussionNorms generated from ADNI through the automatic FS and AA segmentation tools may be used as normative references for Italian patients with suspected AD.

Abstract Backgrounds As a consequence of the increased mortality observed in the SERVE-HF study, many questions concerning the safety and rational use of ASV in other indications emerged. The aim of this study was to describe the clinical characteristics of ASV-treated patients in real-life conditions. Methods The OTRLASV-study is a prospective, 5-centre study including patients who underwent ASV-treatment for at least 1 year. Patients were consecutively included in the study during the annual visit imposed for ASV-reimbursement renewal. Results 177/214 patients were analysed (87.57% male) with a median (IQ25–75) age of 71 (65–77) years, an ASV-treatment duration of 2.88 (1.76–4.96) years, an ASV-usage of 6.52 (5.13–7.65) hours/day, and 54.8% were previously treated via continuous positive airway pressure (CPAP). The median Epworth Scale Score decreased from 10 (6–13.5) to 6 (3–9) (p 45% in 92.7% of patients. Associated comorbidities/etiologies were cardiac in nature for 75.7% of patients (neurological for 12.4%, renal for 4.5%, opioid-treatment for 3.4%). 9.6% had idiopathic central-sleep-apnea. 6.2% of the patients were hospitalized the year preceding the study for cardiological reasons. In the 6 months preceding inclusion, night monitoring (i.e. polygraphy or oximetry during ASV usage) was performed in 34.4% of patients, 25.9% of whom required a subsequent setting change. According to multivariable, logistic regression, the variables that were independently associated with poor adherence (ASV-usage ≤4 h in duration) were TECSA group versus CSA group (p = 0.010), a higher Epworth score (p = 0.019) and lack of a night monitoring in the last 6 months (p

Alzheimer’s disease (AD) is a neurodegenerative disorder which spans several years from preclinical manifestations to dementia. In recent years, interest in the application of machine learning (ML) algorithms to personalized medicine has grown considerably, and a major challenge that such models face is the transferability from the research settings to clinical practice. The objective of this work was to demonstrate the transferability of the Subtype and Stage Inference (SuStaIn) model from well-characterized research data set, employed as training set, to independent less-structured and heterogeneous test sets representative of the clinical setting. The training set was composed of MRI data of 1043 subjects from the Alzheimer’s disease Neuroimaging Initiative (ADNI), and the test set was composed of data from 767 subjects from OASIS, Pharma-Cog, and ViTA clinical datasets. Both sets included subjects covering the entire spectrum of AD, and for both sets volumes of relevant brain regions were derived from T1-3D MRI scans processed with Freesurfer v5.3 cross-sectional stream. In order to assess the predictive value of the model, subpopulations of subjects with stable mild cognitive impairment (MCI) and MCIs that progressed to AD dementia (pMCI) were identified in both sets. SuStaIn identified three disease subtypes, of which the most prevalent corresponded to the typical atrophy pattern of AD. The other SuStaIn subtypes exhibited similarities with the previously defined hippocampal sparing and limbic predominant atrophy patterns of AD. Subject subtyping proved to be consistent in time for all cohorts and the staging provided by the model was correlated with cognitive performance. Classification of subjects on the basis of a combination of SuStaIn subtype and stage, mini mental state examination and amyloid-β1-42 cerebrospinal fluid concentration was proven to predict conversion from MCI to AD dementia on par with other novel statistical algorithms, with ROC curves that were not statistically different for the training and test sets and with area under curve respectively equal to 0.77 and 0.76. This study proves the transferability of a SuStaIn model for AD from research data to less-structured clinical cohorts, and indicates transferability to the clinical setting.

Electrical activity has a key role in shaping neuronal circuits during development. In most sensory modalities, early in development, internally generated spontaneous activity sculpts the initial layout of neuronal wiring. With the maturation of the sense organs, the system relies more on sensory-evoked electrical activity. Stimuli-driven neuronal discharge is required for the transformation of immature circuits in the specific patterns of neuronal connectivity that subserve normal brain function. The olfactory system (OS) differs from this organizational plan. Despite the important role of odorant receptors (ORs) in shaping olfactory topography, odor-evoked activity does not have a prominent role in refining neuronal wiring. On the contrary, afferent spontaneous discharge is required to achieve and maintain the specific diagram of connectivity that defines the topography of the olfactory bulb (OB). Here, we provide an overview of the development of olfactory topography, with a focus on the role of afferent spontaneous discharge in the formation and maintenance of the specific synaptic contacts that result in the topographic organization of the OB.

Sleep-related breathing disorders, including sleep apnea and hypoxemia during sleep, are common in pulmonary arterial hypertension, but the underlying mechanisms remain unknown. Overnight fluid shift from the legs to the upper airway and to the lungs promotes obstructive and central sleep apnea, respectively, in fluid-retaining states. The main objective was to evaluate if overnight rostral fluid shift from the legs to the upper part of the body is associated with sleep-related breathing disorders in pulmonary arterial hypertension. In a prospective study, a group of stable patients with idiopathic, heritable, related to drugs, toxins, or treated congenital heart disease pulmonary arterial hypertension underwent a polysomnography and overnight fluid shift measurement by bioelectrical impedance in the month preceding or following a one-day hospitalization according to regular pulmonary arterial hypertension follow-up schedule with a right heart catheterization. Results show that among 15 patients with pulmonary arterial hypertension (women: 87%; median (25–75th percentiles); age: 40 (32–61) years; mean pulmonary arterial pressure 56 (46–68) mmHg; pulmonary vascular resistance 8.8 (6.4–10.1) Wood units), two patients had sleep apnea and eight (53%) had hypoxemia during sleep without apnea. The overnight rostral fluid shift was 168 (118–263) mL per leg. Patients with hypoxemia during sleep had a greater fluid shift (221 (141– 361) mL) than those without hypoxemia (118 (44–178) mL, p = 0.045). In conclusion, this pilot study suggests that hypoxemia during sleep is associated with overnight rostral fluid shift in pulmonary arterial hypertension.

In the Romance languages, definite plural articles (e.g., le rane ‘the frogs’) are generally ambiguous between a generic and a specific interpretation, and speakers must reconstruct the intended interpretation through the linguistic or extra-linguistic context. Following the “polar bear” paradigm implemented in Czypionka & Kupisch (2019)’s investigation on German, the goal of the present study is to check the suitability of their test on article semantics, by establishing to what extent native speakers of Italian interpret ambiguous definite plural DPs as generic or specific in the presence of a nonlinguistic picture context. We present judgment and reaction time data monitoring the preferred reading of sentences introduced by different kinds of noun phrases (e.g., Le rane/Queste rane/Le rane di solito sono verdi/gialle ‘The/These/Usually frogs are green/yellow’), while looking at pictures showing prototypical or non-prototypical properties (e.g., green vs. yellow frogs). Our results show that both possible interpretations of definite plural articles are routinely considered in Italian, despite the presence of a picture with specific referents, validating the “polar bear” paradigm as a suitable test of article semantics.

Implantable flexible neural interfaces (IfNIs) are capable of directly modulating signals of the central and peripheral nervous system by stimulating or recording the action potential. Despite outstanding results in acute experiments on animals and humans, their long-term biocompatibility is hampered by the effects of foreign body reactions that worsen electrical performance and cause tissue damage. We report on the fabrication of a polysaccharide nanostructured thin film as a coating of polyimide (PI)-based IfNIs. The layer-by-layer technique was used to coat the PI surface due to its versatility and ease of manufacturing. Two different LbL deposition techniques were tested and compared: dip coating and spin coating. Morphological and physiochemical characterization showed the presence of a very smooth and nanostructured thin film coating on the PI surface that remarkably enhanced surface hydrophilicity with respect to the bare PI surface for both the deposition techniques. However, spin coating offered more control over the fabrication properties, with the possibility to tune the coating’s physiochemical and morphological properties. Overall, the proposed coating strategies allowed the deposition of a biocompatible nanostructured film onto the PI surface and could represent a valid tool to enhance long-term IfNI biocompatibility by improving tissue/electrode integration.

Background: After a stroke, up to three-quarters of acute and subacute stroke survivors exhibit cognitive impairment, with a significant impact on functional recovery, quality of life, and social engagement. Robotic therapy has shown its effectiveness on motor recovery, but its effectiveness on cognitive recovery has not fully investigated.Objective: This study aims to assess the impact of a technological rehabilitation intervention on cognitive functions in patients with stroke, using a set of three robots and one sensor-based device for upper limb rehabilitation.Methods: This is a pilot study in which 51 patients were enrolled. An upper limb rehabilitation program was performed using three robots and one sensor-based device. The intervention comprised motor/cognitive exercises, especially selected among the available ones to train also cognitive functions. Patients underwent 30 rehabilitation sessions, each session lasting 45 minutes, 5 days a week. Patients were assessed before and after the treatment with several cognitive tests (Oxford Cognitive Scale, Symbol Digit Modalities Test, Digit Span, Rey–Osterrieth Complex Figure, Tower of London, and Stroop test). In addition, motor (Fugl–Meyer Assessment and Motricity Index) and disability (modified Barthel Index) scales were used.Results: According to the Oxford Cognitive Scale domains, a significant percentage of patients exhibited cognitive deficits. Excluding perception (with only one patient impaired), the domain with the lowest percentage of patients showing a pathological score was praxis (about 25%), while the highest percentage of impaired patients was found in calculation (about 70%). After the treatment, patients improved in all the investigated cognitive domains, as measured by the selected cognitive assessment scales. Moreover, motor and disability scales confirmed the efficacy of robotics on upper limb rehabilitation in patients with stroke.Conclusions: This explorative study suggests that robotic technology can be used to combine motor and cognitive exercises in a unique treatment session.Clinical Trial Registration:www.ClinicalTrials.gov, identifier: NCT04164381.

Introduction: With the shift of research focus to personalized medicine in Alzheimer's Dementia (AD), there is an urgent need for tools that are capable of quantifying a patient's risk using diagnostic biomarkers. The Medical Informatics Platform (MIP) is a distributed e-infrastructure federating large amounts of data coupled with machine-learning (ML) algorithms and statistical models to define the biological signature of the disease. The present study assessed (i) the accuracy of two ML algorithms, i.e., supervised Gradient Boosting (GB) and semi-unsupervised 3C strategy (Categorize, Cluster, Classify—CCC) implemented in the MIP and (ii) their contribution over the standard diagnostic workup.Methods: We examined individuals coming from the MIP installed across 3 Italian memory clinics, including subjects with Normal Cognition (CN, n = 432), Mild Cognitive Impairment (MCI, n = 456), and AD (n = 451). The GB classifier was applied to best discriminate the three diagnostic classes in 1,339 subjects, and the CCC strategy was used to refine the classical disease categories. Four dementia experts provided their diagnostic confidence (DC) of MCI conversion on an independent cohort of 38 patients. DC was based on clinical, neuropsychological, CSF, and structural MRI information and again with addition of the outcome from the MIP tools.Results: The GB algorithm provided a classification accuracy of 85% in a nested 10-fold cross-validation for CN vs. MCI vs. AD discrimination. Accuracy increased to 95% in the holdout validation, with the omission of each Italian clinical cohort out in turn. CCC identified five homogeneous clusters of subjects and 36 biomarkers that represented the disease fingerprint. In the DC assessment, CCC defined six clusters in the MCI population used to train the algorithm and 29 biomarkers to improve patients staging. GB and CCC showed a significant impact, evaluated as +5.99% of increment on physicians' DC. The influence of MIP on DC was rated from “slight” to “significant” in 80% of the cases.Discussion: GB provided fair results in classification of CN, MCI, and AD. CCC identified homogeneous and promising classes of subjects via its semi-unsupervised approach. We measured the effect of the MIP on the physician's DC. Our results pave the way for the establishment of a new paradigm for ML discrimination of patients who will or will not convert to AD, a clinical priority for neurology.

Chagas disease is an endemic chronic parasitosis in Latin America affecting more than 7 million people. Around 100 million people are currently at risk of acquiring the infection; however, no effective vaccine has been developed yet. Trypanosoma cruzi is the etiological agent of this parasitosis and as an intracellular protozoan it can reside within different tissues, mainly muscle cells, evading host immunity and allowing progression towards the chronic stage of the disease. Considering this intracellular parasitism triggers strong cellular immunity that, besides being necessary to limit infection, is not sufficient to eradicate the parasite from tissues, a differential immune response is required and new strategies for vaccines against Chagas disease need to be explored. In this work, we designed, cloned and expressed a chimeric molecule, named NCz-SEGN24A, comprising a parasite antigen, the N-terminal domain of the major cysteine protease of T. cruzi, cruzipain (Nt-Cz), and a non-toxic form of the staphylococcal superantigen (SAg) G, SEG, with the residue Asn24 mutated to Ala (N24A). The mutant SAg SEGN24A, retains its ability to trigger classical activation of macrophages without inducing T cell apoptosis. To evaluate, as a proof of concept, the immunogenicity and efficacy of the chimeric immunogen vs. its individual antigens, C3H mice were immunized intramuscularly with NCz-SEGN24A co-adjuvanted with CpG-ODN, or the recombinant proteins Nt-Cz plus SEGN24A with the same adjuvant. Vaccinated mice significantly produced Nt-Cz-specific IgG titers after immunization and developed higher IgG2a than IgG1 titers. Specific cell-mediated immunity was assessed by in-vivo DTH and significant responses were obtained. To assess protection, mice were challenged with trypomastigotes of T. cruzi. Both schemes reduced the parasite load throughout the acute phase, but only mice immunized with NCz-SEGN24A showed significant differences against control; moreover, these mice maintained 100% survival. These results encourage testing mutated superantigens fused to specific antigens as immune modulators against pathogens.

Objetivo: Describir las características clínicas y demográficas de los sujetos con lesión medular espinal (LME) que se rehabilitaron en el Instituto Nacional de Rehabilitación Psicofísica del Sur (I.Na.Re.P.S.) e identificar si las mismas se encuentran asociadas a las lesiones traumáticas. Materiales y método: Estudio observacional, analítico, transversal, retrospectivo que incluyó sujetos con LME que ingresaron al I.Na.Re.P.S. entre enero de 2015 y agosto de 2018. Se realizó un análisis de regresión logística múltiple para identificar características asociadas al motivo de LME (traumática versus no traumática). Como medida de asociación se reportaron los Odds Ratios (ORs) con sus respectivos intervalos de confianza al 95% (IC 95%). Se consideró significativo un valor de p4 meses [OR 4,8 (IC 95% 1,3 - 17,2); p=0,015)] y lesión completa [OR 18,0 (IC 95% 3,5 - 93,9); p=0,015)] resultaron características independientes relacionadas con lesión medular traumática. Conclusiones: La LME afectó principalmente a hombres jóvenes, producto de lesiones traumáticas, causadas por accidentes de tránsito. La edad, el tiempo de tratamiento y la lesión de tipo completa fueron características independientes relacionadas con lesión medular traumática.

For Alzheimer’s disease (AD), aging is the main risk factor, but whether cognitive impairments due to aging resemble early AD deficits is not yet defined. When working with mouse models of AD, the situation is just as complicated, because only a few studies track the progression of the disease at different ages, and most ignore how the aging process affects control mice. In this work, we addressed this problem by comparing the aging process of PS2APP (AD) and wild-type (WT) mice at the level of spontaneous brain electrical activity under anesthesia. Using local field potential recordings, obtained with a linear probe that traverses the posterior parietal cortex and the entire hippocampus, we analyzed how multiple electrical parameters are modified by aging in AD and WT mice. With this approach, we highlighted AD specific features that appear in young AD mice prior to plaque deposition or that are delayed at 12 and 16 months of age. Furthermore, we identified aging characteristics present in WT mice but also occurring prematurely in young AD mice. In short, we found that reduction in the relative power of slow oscillations (SO) and Low/High power imbalance are linked to an AD phenotype at its onset. The loss of SO connectivity and cortico-hippocampal coupling between SO and higher frequencies as well as the increase in UP-state and burst durations are found in young AD and old WT mice. We show evidence that the aging process is accelerated by the mutant PS2 itself and discuss such changes in relation to amyloidosis and gliosis.

Abstract Background With the shift of research focus towards the pre-dementia stage of Alzheimer’s disease (AD), there is an urgent need for reliable, non-invasive biomarkers to predict amyloid pathology. The aim of this study was to assess whether easily obtainable measures from structural MRI, combined with demographic data, cognitive data and apolipoprotein E (APOE) ε4 genotype, can be used to predict amyloid pathology using machine-learning classification. Methods We examined 810 subjects with structural MRI data and amyloid markers from the European Medical Information Framework for Alzheimer’s Disease Multimodal Biomarker Discovery study, including subjects with normal cognition (CN, n = 337, age 66.5 ± 7.2, 50% female, 27% amyloid positive), mild cognitive impairment (MCI, n = 375, age 69.1 ± 7.5, 53% female, 63% amyloid positive) and AD dementia (n = 98, age 67.0 ± 7.7, 48% female, 97% amyloid positive). Structural MRI scans were visually assessed and Freesurfer was used to obtain subcortical volumes, cortical thickness and surface area measures. We first assessed univariate associations between MRI measures and amyloid pathology using mixed models. Next, we developed and tested an automated classifier using demographic, cognitive, MRI and APOE ε4 information to predict amyloid pathology. A support vector machine (SVM) with nested 10-fold cross-validation was applied to identify a set of markers best discriminating between amyloid positive and amyloid negative subjects. Results In univariate associations, amyloid pathology was associated with lower subcortical volumes and thinner cortex in AD-signature regions in CN and MCI. The multi-variable SVM classifier provided an area under the curve (AUC) of 0.81 ± 0.07 in MCI and an AUC of 0.74 ± 0.08 in CN. In CN, selected features for the classifier included APOE ε4, age, memory scores and several MRI measures such as hippocampus, amygdala and accumbens volumes and cortical thickness in temporal and parahippocampal regions. In MCI, the classifier including demographic and APOE ε4 information did not improve after additionally adding imaging measures. Conclusions Amyloid pathology is associated with changes in structural MRI measures in CN and MCI. An automated classifier based on clinical, imaging and APOE ε4 data can identify the presence of amyloid pathology with a moderate level of accuracy. These results could be used in clinical trials to pre-screen subjects for anti-amyloid therapies.

The endoplasmic reticulum (ER) extends as a network of interconnected tubules and sheet-like structures in eukaryotic cells. ER tubules dynamically change their morphology and position within the cells in response to physiological stimuli and these network rearrangements depend on the microtubule (MT) cytoskeleton. Store-operated calcium entry (SOCE) relies on the repositioning of ER tubules to form specific ER-plasma membrane junctions. Indeed, the tips of polymerizing MTs are supposed to provide the anchor for ER tubules to move toward the plasma membrane, however the precise role of the cytoskeleton during SOCE has not been conclusively clarified. Here we exploit an in vivo approach involving the manipulation of MT dynamics in Drosophila melanogaster by neuronal expression of a dominant-negative variant of the MT-severing protein spastin to induce MT hyper-stabilization. We show that MT stabilization alters ER morphology, favoring an enrichment in ER sheets at the expense of tubules. Stabilizing MTs has a negative impact on the process of SOCE and results in a reduced ER Ca2+ content, affecting the flight ability of the flies. Restoring proper MT organization by administering the MT-destabilizing drug vinblastine, chronically or acutely, rescues ER morphology, SOCE and flight ability, indicating that MT dynamics impairment is responsible for all the phenotypes observed.

Summary: In mammals, odorant receptors not only detect odors but also define the target in the olfactory bulb, where sensory neurons project to give rise to the sensory map. The odorant receptor is expressed at the cilia, where it binds odorants, and at the axon terminal. The mechanism of activation and function of the odorant receptor at the axon terminal is, however, still unknown. Here, we identify phosphatidylethanolamine-binding protein 1 as a putative ligand that activates the odorant receptor at the axon terminal and affects the turning behavior of sensory axons. Genetic ablation of phosphatidylethanolamine-binding protein 1 in mice results in a strongly disturbed olfactory sensory map. Our data suggest that the odorant receptor at the axon terminal of olfactory neurons acts as an axon guidance cue that responds to molecules originating in the olfactory bulb. The dual function of the odorant receptor links specificity of odor perception and axon targeting. : Odorant receptors play a critical role in the sensory map formation. Zamparo et al. find that axonal odorant receptors respond to cues expressed in the olfactory bulb. Among these, PEBP1 acts as a putative ligand of axonal receptors, and its genetic ablation results in a disrupted sensory map in vivo. Keywords: axon targeting, topographic map, olfactory bulb, axonal odorant receptors

The Rosalia longicorn (Rosalia alpina) is a strictly protected saproxylic beetle, widely distributed in Central and Southern Europe and mainly associated with ancient beech forests. To improve knowledge about the conservation status of R. alpina in Italy, available molecular markers (microsatellites and mitochondrial cytochrome c oxidase I(COI)) were tested for the first time on Italian populations. The study was performed in four sampling sites distributed in two areas placed in Northern (“Foreste Casentinesi” National Park) and Central Apennines (“Abruzzo, Lazio and Molise” National Park) where populational data about Rosalia longicorn were collected in the framework of the European LIFE MIPP Project. The genetic relationship among Apennine and Central/South-eastern European populations was explored by a comparison with mitochondrial DNA (mtDNA) data from literature. Microsatellite markers were only partially informative when applied to R. alpina Italian individuals, although providing some preliminary indication on an extensive gene flow among populations from the Apennines and local ongoing processes of genetic erosion. Genetic data are consistent with previous ecological data suggesting that the maintenance of variability in this species could be related to both habitat continuity and preservation of large senescent or standing dead trees in forests. Finally, a peculiar origin of the Apennine populations of R. alpina from a putative “Glacial Refugium” in Italy was inferred through COI data. The high genetic distance scored among the analysed populations and those from Central and South-eastern Europe indicates that the R. alpina deme from Apennine Mountains might represent a relevant conservation unit in Europe. Further genetic analyses will allow assessing other possible conservation units of R. alpina and, thus, defining large-scale conservation strategies to protect this endangered longhorn beetle in Europe.

Calcium (Ca2+) signaling coordinates are crucial processes in brain physiology. Particularly, fundamental aspects of neuronal function such as synaptic transmission and neuronal plasticity are regulated by Ca2+, and neuronal survival itself relies on Ca2+-dependent cascades. Indeed, impaired Ca2+ homeostasis has been reported in aging as well as in the onset and progression of neurodegeneration. Understanding the physiology of brain function and the key processes leading to its derangement is a core challenge for neuroscience. In this context, Ca2+ imaging represents a powerful tool, effectively fostered by the continuous amelioration of Ca2+ sensors in parallel with the improvement of imaging instrumentation. In this review, we explore the potentiality of the most used animal models employed for Ca2+ imaging, highlighting their application in brain research to explore the pathogenesis of neurodegenerative diseases.

Experiments were performed in a low pressure-high density plasma reactor in order to study the impact of hydrogen retention in aluminium under plasma conditions. Microscopy scans of the surface were performed before and after 1h plasma exposure (fluence 6.1 ×1023ions/m2) where it is seen that blisters start to nucleate at the grain boundaries. Investigation on blister growth kinetics was performed for fluences ranging between 6 ×1023 and 3.7 ×1024ions/m2. The evolution of the characteristic size of the projected area was also analyzed. Finally, a macroscopic rate equations (MRE) code was used to simulate hydrogen retention and diffusion in Al and bubble growth in the bulk was simulated using experimental results. This model was also used to simulate these phenomena in Be and compare its behavior with respect to Al.

Cerambyx cerdo is a longhorn beetle widely distributed in southern and central Europe. This saproxylic beetle is generally associated with oak forests where there are mature or partially dead and sun-exposed trees. Its populations are currently threatened by forest practices such as the removal of partially dead trees and the decline in the number of old oak trees situated in open or semi-open landscapes. Thus, C. cerdo has been included in Annexes II and IV of the Habitats Directive. The present paper is part of a special issue on monitoring of saproxylic beetles which are protected in Europe, based on the research carried out during the LIFE-MIPP project, with a revision of the current knowledge on systematics, ecology and conservation of C. cerdo. The main aim of the present paper is to test different monitoring methods in order to develop a quick and reproducible protocol for the conservation of this species. The methods tested were: artificial sap attracting the adults, baited traps, VES (visual encounter survey) and collecting remains of predation along transects. Based on these results, a detailed monitoring method for C. cerdo using baited trap is proposed in this paper, together with a discussion on its constraints, spatial validity and possible interferences. In order to assess the conservation status of populations of C. cerdo in Europe and to compare populations over time, a method for the calculation of a reference value, based on the monitoring method, is provided.

Rosalia alpina (Linnaeus, 1758) is a large longhorn beetle (Coleoptera: Cerambycidae) which is protected by the Habitats Directive and which typically inhabits beech forests characterised by the presence of mature, dead (or moribund) and sun-exposed trees. A revision of the current knowledge on systematics, ecology and conservation of R. alpina is reported. The research was carried out as part of the LIFE MIPP project which aims to find a standard monitoring method for saproxylic beetles protected in Europe. For monitoring this species, different methods were tested and compared in two areas of the Apennines, utilising wild trees, logs and tripods (artificially built with beech woods), all potentially suitable for the reproduction of the species. Even if all methods succeeded in the survey of the target species, these results showed that the use of wild trees outperformed other methods. Indeed, the use of wild trees allowed more adults to be observed and required less intensive labour. However, monitoring the rosalia longicorn on wild trees has the main disadvantage that they can hardly be considered “standard sampling units”, as each tree may be differently attractive to adults. Our results demonstrated that the most important factors influencing the attraction of single trunks were wood volume, sun-exposure and decay stage. Based on the results obtained during the project LIFE MIPP, as well as on a literature review, a standard monitoring method for R. alpina was developed.

Citizen science, the engagement of people in a research project, has grown rapidly in recent years, also for mapping of species of conservation interest. The Life Project “Monitoring Insects with Public Participation” (MIPP) actively promoted collaboration amongst scientists, public administrations and citizens in the collection of occurrence data of nine insect species listed in the Habitats Directive: Lucanus cervus, Osmoderma eremita, Cerambyx cerdo, Rosalia alpina, Morimus asper/funereus, Lopinga achine, Parnassius apollo, Zerynthia cassandra/polyxena and Saga pedo. These species were selected because they share two main characteristics: (i) they are listed in Annexes II and IV of the Habitats Directive and (ii) they are large and relatively easy to identify. From 2014 to 2016, many different strategies were applied to contact and engage the public and approximately 14,000 citizens were reached directly. Additionally, printed and online material informed the public about this project. Citizens could transmit data on the target species, accompanied by a photograph, via the web-site of the project or through a dedicated application (app) for smartphones and tablets. All records were validated by experts based on the photographs sent by citizens. A total number of 2,308 records were transmitted and 1,691 (73.2%) of these were confirmed. Most of the reports were submitted via the website, although the submission via the app increased over time. The species most commonly recorded was L. cervus, followed by M. asper/funereus and R. alpina. Data collected by citizen scientists allowed a detailed analysis to be made on altitudinal distribution and phenology of the species and the results obtained were compared with literature data on altitudinal distribution and phenology. For example, for L. cervus, 67% of the records collected were from the altitudinal range 0–400 m a.s.l. Interestingly, the data showed that the phenology of this species changed with altitude.