Suppression of Sleep Spindle Rhythmogenesis in Mice with Deletion of CaV3.2 and CaV3.3 T-type Ca(2+) Channels.

STUDY OBJECTIVES: Low-threshold voltage-gated T-type Ca(2+) channels (T-channels or CaV3 channels) sustain oscillatory discharges of thalamocortical (TC) and nucleus Reticularis thalami (nRt) cells. The CaV3.3 subtype dominates nRt rhythmic bursting and mediates a substantial fraction of spindle power in the NREM sleep EEG. CaV3.2 channels are also found in nRt, but whether these contribute to nRt-dependent spindle generation is unexplored. We investigated thalamic rhythmogenesis in mice lacking this subtype in isolation (CaV3.2KO mice) or in concomitance with CaV3.3 deletion (CaV3.double-knockout (DKO) mice). METHODS: We examined discharge characteristics of thalamic cells and intrathalamic evoked synaptic transmission in brain slices from wild-type, CaV3.2KO and CaV3.DKO mice through patch-clamp recordings. The sleep profile of freely behaving CaV3.2KO and CaV3.DKO mice was assessed by polysomnographic recordings. RESULTS: CaV3.2 channel deficiency left nRt discharge properties largely unaltered, but additional deletion of CaV3.3 channels fully abolished low-threshold whole-cell Ca(2+) currents and bursting, and suppressed burst-mediated inhibitory responses in TC cells. CaV3.DKO mice had more fragmented sleep, with shorter NREM sleep episodes and more frequent microarousals. The NREM sleep EEG power spectrum displayed a relative suppression of the σ frequency band (10-15 Hz), which was accompanied by an increase in the δ band (1-4 Hz). CONCLUSIONS: Consistent with previous findings, CaV3.3 channels dominate nRt rhythmogenesis, but the lack of CaV3.2 channels further aggravates neuronal, synaptic, and EEG deficits. Therefore, CaV3.2 channels can boost intrathalamic synaptic transmission, and might play a modulatory role adjusting the relative presence of NREM sleep EEG rhythms

Electrocatalytic properties of Pd-based nano-structured material for application in fuel cells

Fuel cells, especially low temperature fuel cells, are clean-energy devices that have high potentiality for use in electric power production and non-polluting vehicles. Platinum is commonly used as electrocatalysts in fuel cell electrodes, because of its excellent electrocatalytic activity and chemical stability. But, because of its high cost and limited resources, its use represents a bottleneck for large-scale application and commercialization of fuel cells. Palladium could be a good substitute for Pt, because of its similar chemical and physical properties, lower cost and higher abundance. Main challenges concern the development of Pd-based materials with high catalytic activity and durability at a reduced cost (i.e. metal content). Crucial technological issue is the optimization of the active surface of the catalysts, by the control of the morphology, shape and dispersion of the metal particles. The talk will describe the main results of the research activity carried out during the second year of the Italia-USA Bilateral Project in ENEA, concerning the fabrication and characterization of different kinds of nanostructured Pd-based electrocatalysts, by using both electrochemical and vacuum thin film deposition techniques

Search for Neutron Flux Generation in a Plasma Discharge Electrolytic Cell

Following some recent unexpected hints of neutron production in setups like high-voltage atmospheric discharges and plasma discharges in electrolytic cells, we present a measurement of the neutron flux in a configuration similar to the latter. We use two different types of neutron detectors, poly-allyl-diglicol-carbonate (PADC, aka CR-39) tracers and Indium disks. At 95% C.L. we provide an upper limit of 1.5 neutrons cm^-2 s^-1 for the thermal neutron flux at ~5 cm from the center of the cell. Allowing for a higher energy neutron component the largest allowed flux is 64 neutrons cm^-2 s^-1. This upper limit is two orders of magnitude smaller than what previously claimed in an electrolytic cell plasma discharge experiment. Furthermore the behavior of the CR-39 is discussed to point our possible sources of spurious signals.Comment: 4 pages, 3 figure

Phasic, nonsynaptic GABA-A receptor-mediated inhibition entrains thalamocortical oscillations.

GABA-A receptors (GABA-ARs) are typically expressed at synaptic or nonsynaptic sites mediating phasic and tonic inhibition, respectively. These two forms of inhibition conjointly control various network oscillations. To disentangle their roles in thalamocortical rhythms, we focally deleted synaptic, γ2 subunit-containing GABA-ARs in the thalamus using viral intervention in mice. After successful removal of γ2 subunit clusters, spontaneous and evoked GABAergic synaptic currents disappeared in thalamocortical cells when the presynaptic, reticular thalamic (nRT) neurons fired in tonic mode. However, when nRT cells fired in burst mode, slow phasic GABA-AR-mediated events persisted, indicating a dynamic, burst-specific recruitment of nonsynaptic GABA-ARs. In vivo, removal of synaptic GABA-ARs reduced the firing of individual thalamocortical cells but did not abolish slow oscillations or sleep spindles. We conclude that nonsynaptic GABA-ARs are recruited in a phasic manner specifically during burst firing of nRT cells and provide sufficient GABA-AR activation to control major thalamocortical oscillations

The Black Sea Physics Analysis and Forecasting System within the Framework of the Copernicus Marine Service

This work describes the design, implementation and validation of the Black Sea physics analysis and forecasting system, developed by the Black Sea Physics production unit within the Black Sea Monitoring and Forecasting Center as part of the Copernicus Marine Environment and Monitoring Service. The system provides analyses and forecasts of the temperature, salinity, sea surface height, mixed layer depth and currents for the whole Black Sea basin, excluding the Azov Sea, and has been operational since 2016. The system is composed of the NEMO (v 3.4) numerical model and an OceanVar scheme, which brings together real time observations (in-situ temperature and salinity profiles, sea level anomaly and sea surface temperature satellite data). An operational quality assessment framework is used to evaluate the accuracy of the products which set the basic standards for the future upgrades, highlighting the strengths and weaknesses of the model and the observing system in the Black Sea

Environmental variables and machine learning models to predict cetacean abundance in the Central-eastern Mediterranean Sea

: Although the Mediterranean Sea is a crucial hotspot in marine biodiversity, it has been threatened by numerous anthropogenic pressures. As flagship species, Cetaceans are exposed to those anthropogenic impacts and global changes. Assessing their conservation status becomes strategic to set effective management plans. The aim of this paper is to understand the habitat requirements of cetaceans, exploiting the advantages of a machine-learning framework. To this end, 28 physical and biogeochemical variables were identified as environmental predictors related to the abundance of three odontocete species in the Northern Ionian Sea (Central-eastern Mediterranean Sea). In fact, habitat models were built using sighting data collected for striped dolphins Stenella coeruleoalba, common bottlenose dolphins Tursiops truncatus, and Risso's dolphins Grampus griseus between July 2009 and October 2021. Random Forest was a suitable machine learning algorithm for the cetacean abundance estimation. Nitrate, phytoplankton carbon biomass, temperature, and salinity were the most common influential predictors, followed by latitude, 3D-chlorophyll and density. The habitat models proposed here were validated using sighting data acquired during 2022 in the study area, confirming the good performance of the strategy. This study provides valuable information to support management decisions and conservation measures in the EU marine spatial planning context

Quantifying Infra-slow Dynamics of Spectral Power and Heart Rate in Sleeping Mice.

Three vigilance states dominate mammalian life: wakefulness, non-rapid eye movement (non-REM) sleep, and REM sleep. As more neural correlates of behavior are identified in freely moving animals, this three-fold subdivision becomes too simplistic. During wakefulness, ensembles of global and local cortical activities, together with peripheral parameters such as pupillary diameter and sympathovagal balance, define various degrees of arousal. It remains unclear the extent to which sleep also forms a continuum of brain states-within which the degree of resilience to sensory stimuli and arousability, and perhaps other sleep functions, vary gradually-and how peripheral physiological states co-vary. Research advancing the methods to monitor multiple parameters during sleep, as well as attributing to constellations of these functional attributes, is central to refining our understanding of sleep as a multifunctional process during which many beneficial effects must be executed. Identifying novel parameters characterizing sleep states will open opportunities for novel diagnostic avenues in sleep disorders. We present a procedure to describe dynamic variations of mouse non-REM sleep states via the combined monitoring and analysis of electroencephalogram (EEG)/electrocorticogram (ECoG), electromyogram (EMG), and electrocardiogram (ECG) signals using standard polysomnographic recording techniques. Using this approach, we found that mouse non-REM sleep is organized into cycles of coordinated neural and cardiac oscillations that generate successive 25-s intervals of high and low fragility to external stimuli. Therefore, central and autonomic nervous systems are coordinated to form behaviorally distinct sleep states during consolidated non-REM sleep. We present surgical manipulations for polysomnographic (i.e., EEG/EMG combined with ECG) monitoring to track these cycles in the freely sleeping mouse, the analysis to quantify their dynamics, and the acoustic stimulation protocols to assess their role in the likelihood of waking up. Our approach has already been extended to human sleep and promises to unravel common organizing principles of non-REM sleep states in mammals

A new search-and-rescue service in the Mediterranean Sea: a demonstration of the operational capability and an evaluation of its performance using real case scenarios

Abstract. A new web-based and mobile decision support system (DSS) for search-and-rescue (SAR) at sea is presented, and its performance is evaluated using real case scenarios. The system, named OCEAN-SAR, is accessible via the website http://www.ocean-sar.com. In addition to the website, dedicated applications for iOS and Android have been created to optimise the user experience on mobile devices. OCEAN-SAR simulates drifting objects at sea, using as input ocean currents and wind data provided, respectively, by the CMEMS and ECMWF. The modelling of the drifting objects is based on the leeway model, which parameterises the wind drag of an object using a series of coefficients. These coefficients have been measured in field experiments for different types of objects, ranging from a person in the water to a coastal freighter adrift. OCEAN-SAR provides the user with an intuitive interface to run simulations and to visualise their results using Google Maps. The performance of the service is evaluated by comparing simulations to data from the Italian Coast Guard pertaining to actual incidents in the Mediterranean Sea

Coordinated infraslow neural and cardiac oscillations mark fragility and offline periods in mammalian sleep.

Rodents sleep in bouts lasting minutes; humans sleep for hours. What are the universal needs served by sleep given such variability? In sleeping mice and humans, through monitoring neural and cardiac activity (combined with assessment of arousability and overnight memory consolidation, respectively), we find a previously unrecognized hallmark of sleep that balances two fundamental yet opposing needs: to maintain sensory reactivity to the environment while promoting recovery and memory consolidation. Coordinated 0.02-Hz oscillations of the sleep spindle band, hippocampal ripple activity, and heart rate sequentially divide non-rapid eye movement (non-REM) sleep into offline phases and phases of high susceptibility to external stimulation. A noise stimulus chosen such that sleeping mice woke up or slept through at comparable rates revealed that offline periods correspond to raising, whereas fragility periods correspond to declining portions of the 0.02-Hz oscillation in spindle activity. Oscillations were present throughout non-REM sleep in mice, yet confined to light non-REM sleep (stage 2) in humans. In both species, the 0.02-Hz oscillation predominated over posterior cortex. The strength of the 0.02-Hz oscillation predicted superior memory recall after sleep in a declarative memory task in humans. These oscillations point to a conserved function of mammalian non-REM sleep that cycles between environmental alertness and internal memory processing in 20- to 25-s intervals. Perturbed 0.02-Hz oscillations may cause memory impairment and ill-timed arousals in sleep disorders