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​​​​​​​Vertically resolved information on aerosol particles represents a key aspect in many atmospheric studies, including aerosol–climate interactions and aerosol impacts on air quality and human health. This information is primarily derived by lidar active remote sensing, in particular with extensive networks currently in operation worldwide. In Italy, the Institute of Atmospheric Sciences and Climate (ISAC) of the National Research Council (CNR) established the ALICENET network of automated lidar ceilometers (ALCs) in 2015. Since then, ALICENET has grown as a cooperative effort of Italian institutions dealing with atmospheric science and monitoring, and it currently includes instruments run by regional environmental protection agencies, universities, research centres, and private companies. In the current configuration, the network makes use of both single-channel ALCs and dual-channel, polarisation-sensitive-system ALCs (referred to as PLCs). The systems operate in very different environments (urban, coastal, mountainous, and volcanic areas) from northern to southern Italy, thus allowing the continuous monitoring of the aerosol vertical distribution across the country. ALICENET also contributes to the EUMETNET programme E-PROFILE, filling an Italian observational gap compared to other EU member states, which generally run extended ALC networks through national meteorological services. In this work, we present the ALICENET infrastructure and the specifically developed data processing centralised at CNR-ISAC, converting raw instrumental data into quantitative, quality-controlled information on aerosol properties ranging from attenuated backscatter to aerosol mass and vertical stratifications. This setup allows us to get insights into the 4D aerosol field over Italy with applications from near-real-time monitoring to long-term analyses, examples of which are reported in this work. Specific comparisons of the ALICENET products to independent measurements obtained with different techniques, such as particulate matter (PM) concentrations from in situ samplers and aerosol optical depth (AOD) from sun photometers, are also included here, revealing the good performances of the ALICENET algorithms. Overall, ALICENET represents a valuable resource to extend the current aerosol observational capabilities in Italy and in the Mediterranean area, and it contributes to bridging the gap between atmospheric science and its application to specific sectors, among which are air quality, solar energy, and aviation safety.

The prevalent "core phonological deficit" model of dyslexia proposes that the reading and spelling difficulties characterizing affected children stem from prior developmental difficulties in processing speech sound structure, for example, perceiving and identifying syllable stress patterns, syllables, rhymes and phonemes. Yet spoken word production appears normal. This suggests an unexpected disconnect between speech input and speech output processes. Here we investigated the output side of this disconnect from a speech rhythm perspective by measuring the speech amplitude envelope (AE) of multisyllabic spoken phrases. The speech AE contains crucial information regarding stress patterns, speech rate, tonal contrasts and intonational information. We created a novel computerized speech copying task in which participants copied aloud familiar spoken targets like "Aladdin." Seventy-five children with and without dyslexia were tested, some of whom were also receiving an oral intervention designed to enhance multi-syllabic processing. Similarity of the child's productions to the target AE was computed using correlation and mutual information metrics. Similarity of pitch contour, another acoustic cue to speech rhythm, was used for control analyses. Children with dyslexia were significantly worse at producing the multi-syllabic targets as indexed by both similarity metrics for computing the AE. However, children with dyslexia were not different from control children in producing pitch contours. Accordingly, the spoken production of multisyllabic phrases by children with dyslexia is atypical regarding the AE. Children with dyslexia may not appear to listeners to exhibit speech production difficulties because their pitch contours are intact.

The cross-talk between plant-derived nanovesicles (PDNVs) and mammalian cells has been explored by several investigations, underlining the capability of these natural nanovesicles to regulate several molecular pathways. Additionally, PDNVs possess biological proprieties that make them applicable against pathological conditions, such as hepatic diseases. In this study we explored the antioxidant properties of lemon-derived nanovesicles, isolated at laboratory (LNVs) and industrial scale (iLNVs) in human healthy hepatocytes (THLE-2) and in metabolic syndrome induced by a high-fat diet (HFD) in the rat. Our findings demonstrate that in THLE-2 cells, LNVs and iLNVs decrease ROS production and upregulate the expression of antioxidant mediators, Nrf2 and HO-1. Furthermore, the in vivo assessment reveals that the oral administration of iLNVs improves glucose tolerance and lipid dysmetabolism, ameliorates biometric parameters and systemic redox homeostasis, and upregulates Nrf2/HO-1 signaling in HFD rat liver. Consequently, we believe LNVs/iLNVs might be a promising approach for managing hepatic and dysmetabolic disorders.

Canopy Homolog 2 (CNPY2) is an endoplasmic reticulum (ER) localized protein belonging to the CNPY gene family. We show here that CNPY2 is protective against ER stress induced by tunicamycin in neuronal cells. Overexpression of CNPY2 enhanced, while downregulation of CNPY2 using shRNA expression, reduced the viability of neuroblastoma cells after tunicamycin. Likewise, recombinant CNPY2 increased survival of cortical neurons in culture after ER stress. CNPY2 reduced the activating transcription factor 6 (ATF6) branch of ER stress and decreased the expression of CCAT/Enhancer-Binding Protein Homologous Protein (CHOP) involved in cell death. Immunostaining using mouse brain sections revealed that CNPY2 is expressed by cortical and striatal neurons and is co-expressed with the transcription factor, COUPTF-interacting protein 2 (CTIP2). In transgenic N171-82Q mice, as a model for Huntington’s disease (HD), the number of CNPY2-immunopositive neurons was increased in the cortex together with CTIP2. In the striatum, however, the number of CNPY2 decreased at 19 weeks of age, representing a late-stage of pathology. Striatal cells in culture were shown to be more susceptible to ER stress after downregulation of CNPY2. These results demonstrate that CNPY2 is expressed by corticostriatal neurons involved in the regulation of movement. CNPY2 enhances neuronal survival by reducing ER stress and is a promising factor to consider in HD and possibly in other brain diseases.

A disturbed balance between excitation and inhibition (E/I balance) is increasingly recognized as a key driver of neurodegeneration in multiple sclerosis (MS), a chronic inflammatory disease of the central nervous system. To understand how chronic hyperexcitability contributes to neuronal loss in MS, we transcriptionally profiled neurons from mice lacking inhibitory metabotropic glutamate signaling with shifted E/I balance and increased vulnerability to inflammation- induced neurodegeneration. This revealed a prominent induction of the nuclear receptor NR4A2 in neurons. Mechanistically, NR4A2 increased susceptibility to excitotoxicity by stimulating continuous VGF secretion leading to glycolysis-dependent neuronal cell death. Extending these findings to people with MS (pwMS), we observed increased VGF levels in serum and brain biopsies. Notably, neuron-specific deletion of Vgf in a mouse model of MS ameliorated neurodegeneration. These findings underscore the detrimental effect of a persistent metabolic shift driven by excitatory activity as a fundamental mechanism in inflammation-induced neurodegeneration., Introduction Inflammation-induced neurodegeneration is the principal driver of disease progression and the accumulation of neurological disabilities in people with multiple sclerosis (pwMS) (1, 2), the most prevalent inflammatory disease of [...]

Background: A wealth of evidence underscores the bioactive properties of nutraceuticals and functional foods in addressing oxyinflammatory-based diseases with implications at both peripheral and central levels. Opuntia ficus-indica (OFI) is well-documented for its health-promoting attributes, though its fruit (OFIF) remains relatively understudied. Not only poses Metabolic Syndrome (MetS) cardiometabolic risks but also contributes significantly to cognitive impairment, especially in crucial brain areas such as hippocampus and hypothalamus. Methods: Following 8 weeks of HFD to induce MetS, rats received OFIF oral supplementation for 4 weeks to evaluate cognitive and affective modifications using behavioural paradigms, i.e. open field, burrowing, white-dark box, novelty-suppressed feeding, and object recognition tests. Our investigation extended to biochemical evaluations of lipid homeostasis, central and peripheral oxidative stress and neurotrophic pathways, correlating these measures together with circulating leptin levels. Results: Our data revealed that OFIF modulation of leptin positively correlates with systemic and brain oxidative stress, with markers of increased anxiety-like behaviour and impaired lipid homeostasis. On the other hand, leptin levels reduced by OFIF are associated with improved antioxidant barriers, declarative memory and neurotrophic signalling. Discussion: This study underscores OFIF neuroactive potential in the context of MetS-associated cognitive impairment, offering insights into its mechanisms and implications for future therapeutic strategies.

Slow cortical oscillations play a crucial role in processing the speech amplitude envelope, which is perceived atypically by children with developmental dyslexia. Here we use electroencephalography (EEG) recorded during natural speech listening to identify neural processing patterns involving slow oscillations that may characterize children with dyslexia. In a story listening paradigm, we find that atypical power dynamics and phase-amplitude coupling between delta and theta oscillations characterize dyslexic versus other child control groups (typically-developing controls, other language disorder controls). We further isolate EEG common spatial patterns (CSP) during speech listening across delta and theta oscillations that identify dyslexic children. A linear classifier using four delta-band CSP variables predicted dyslexia status (0.77 AUC). Crucially, these spatial patterns also identified children with dyslexia when applied to EEG measured during a rhythmic syllable processing task. This transfer effect (i.e., the ability to use neural features derived from a story listening task as input features to a classifier based on a rhythmic syllable task) is consistent with a core developmental deficit in neural processing of speech rhythm. The findings are suggestive of distinct atypical neurocognitive speech encoding mechanisms underlying dyslexia, which could be targeted by novel interventions.

Abstract Even prior to producing their first words, infants are developing a sophisticated speech processing system, with robust word recognition present by 4–6 months of age. These emergent linguistic skills, observed with behavioural investigations, are likely to rely on increasingly sophisticated neural underpinnings. The infant brain is known to robustly track the speech envelope, however previous cortical tracking studies were unable to demonstrate the presence of phonetic feature encoding. Here we utilise temporal response functions computed from electrophysiological responses to nursery rhymes to investigate the cortical encoding of phonetic features in a longitudinal cohort of infants when aged 4, 7 and 11 months, as well as adults. The analyses reveal an increasingly detailed and acoustically invariant phonetic encoding emerging over the first year of life, providing neurophysiological evidence that the pre-verbal human cortex learns phonetic categories. By contrast, we found no credible evidence for age-related increases in cortical tracking of the acoustic spectrogram.

From the perspective of circular economy, it is extremely useful to recycle waste products for human health applications. Among the health-beneficial properties of bioactive phyto-compounds, grape pomace represents a precious source of bioactive molecules with potential antitumor properties. Here, we describe the effects of a Sicilian grape pomace hydroalcoholic extract (HE) in colon and breast cancer cells. The characterization of HE composition revealed the predominance of anthoxanthins and phenolic acids. HE treatment was more effective in reducing the viability of colon cancer cells, while breast cancer cells appeared more resistant. Indeed, while colon cancer cells underwent apoptosis, as shown by DNA fragmentation, caspase-3 activation, and PARP1 degradation, breast cancer cells seemed to not undergo apoptosis. To elucidate the underlying mechanisms, reactive oxygen species (ROS) were evaluated. Interestingly, ROS increased in both cell lines but, while in colon cancer, cells’ ROS rapidly increased and progressively diminished over time, in breast cancer, cells’ ROS increase was persistent up to 24 h. This effect was correlated with the induction of pro-survival autophagy, demonstrated by autophagosomes formation, autophagic markers increase, and protection by the antioxidant NAC. The autophagy inhibitor bafilomycin A1 significantly increased the HE effects in breast cancer cells but not in colon cancer cells. Overall, our data provide evidence that HE efficacy in tumor cells depends on a balance between ROS-mediated autophagy and apoptosis. Therefore, inhibiting pro-survival autophagy may be a tool to target those cells that appear more resistant to the effect of HE.

We numerically analyze the feasibility of a platform-neutral, general strategy to perform quantum simulations of fermionic lattice field theories under open boundary conditions. The digital quantum simulator requires solely one- and two-qubit gates and is scalable since integrating each Hamiltonian term requires a finite (non-scaling) cost. The exact local fermion encoding we adopt relies on auxiliary $\mathbb{Z}_2$ lattice gauge fields by adding a pure gauge Hamiltonian term akin to the Toric Code. By numerically emulating the quantum simulator real-time dynamics, we observe a timescale separation for spin- and charge-excitations in a spin-$\frac{1}{2}$ Hubbard ladder in the $t-J$ model limit.

Abstract Exposures to fine particulate matter (PM $$_1$$ 1 ) have been associated with health impacts, but the understanding of the PM $$_1$$ 1 concentration-response (PM $$_1$$ 1 -CR) relationships, especially at low PM $$_1$$ 1 , remains incomplete. Here, we present novel data using a methodology to mimic lung exposure to ambient air (2 $$

We analyze cirrus cloud measurements from two dual-instrument cloud spectrometers, two hygrometers and a backscattersonde with the goal of connecting cirrus optical parameters usually accessible by remote sensing with microphysical size-resolved and bulk properties accessible in situ. Specifically, we compare the particle backscattering coefficient and depolarization ratio to the particle size distribution, effective and mean radius, surface area density, particle aspherical fraction, and ice water content. Data were acquired by instruments on board the M55 Geophysica research aircraft in July and August 2017 during the Asian Monsoon campaign based in Kathmandu, Nepal, in the framework of the StratoClim (Stratospheric and upper tropospheric processes for better climate predictions) project. Cirrus clouds have been observed over the Himalayan region between 10 km and the tropopause, situated at 17–18 km. The observed particle number densities varied between 10 and 10−4 cm−3 in the dimensional range from 1.5 to 468.5 µm in radius. Correspondingly, backscatter ratios from 1.1 up to 50 have been observed. Optical-scattering theory has been used to compare the backscattering coefficients computed from the measured particle size distribution with those directly observed by the backscattersonde. The aspect ratio of the particles, modeled as spheroids for the T-matrix approach, was left as a free parameter to match the calculations to the optical measures. The computed backscattering coefficient can be brought into good agreement with the observed one, but the match between simulated and measured depolarization ratios is insufficient. Relationships between ice particle concentration, mean and effective radius, surface area density, and ice water content with the measured backscattering coefficient are investigated for an estimate of the bulk microphysical parameters of cirrus clouds from remote sensing lidar data. The comparison between particle depolarization and aspherical fraction as measured by one of the cloud spectrometers equipped with a detector for polarization represents a novelty since it was the first time the two instruments were operated simultaneously on an aircraft. The analysis shows the difficulty of establishing an univocal link between depolarization values and the presence and amount of aspherical scatterers. This suggests the need for further investigation that could take into consideration not only the fraction of aspheric particles but also their predominant morphology.

Abstract The application of a mechanical strain to a 2D material can create pseudo-magnetic fields and lead to a quantized valley Hall effect. However, measuring valley-resolved effects remains a challenging task due to their inherent fragility and dependence on the sample’s proper design. Additionally, non-local transport probes based on multiterminal devices have often proven to be inadequate in yielding conclusive evidence of the valley Hall signal. Here, we introduce an alternative way of detecting the quantized valley Hall effect, which entirely relies on local density measurements, performed deep in the bulk of the sample. The resulting quantized signal is a genuine Fermi sea response, independent of the edge physics, and reflects the underlying valley Hall effect through the Widom-Středa formula. Specifically, our approach is based on measuring the variation of the particle density, locally in the bulk, upon varying the strength of the applied strain. This approach to the quantized valley Hall effect is particularly well suited for experiments based on synthetic lattices, where the particle density (or integrated density of states) can be spatially resolved.

Aerosol–cloud interactions play a crucial role in shaping Earth’s climate and hydrological cycle. Observing these interactions with high precision and accuracy is of the utmost importance for improving climate models and predicting Earth’s climate. Over the past few decades, lidar techniques have emerged as powerful tools for investigating aerosol–cloud interactions due to their ability to provide detailed vertical profiles of aerosol particles and clouds with high spatial and temporal resolutions. This review paper provides an overview of recent advancements in the study of ACI using lidar techniques. The paper begins with a description of the different cloud microphysical processes that are affected by the presence of aerosol, and with an outline of lidar remote sensing application in characterizing aerosol particles and clouds. The subsequent sections delve into the key findings and insights gained from lidar-based studies of aerosol–cloud interactions. This includes investigations into the role of aerosol particles in cloud formation, evolution, and microphysical properties. Finally, the review concludes with an outlook on future research. By reporting the latest findings and methodologies, this review aims to provide valuable insights for researchers engaged in climate science and atmospheric research.

Polar stratospheric clouds (PSCs) form in polar regions, typically between 15 and 25 km above mean sea level, when the local temperature is sufficiently low. PSCs play an important role in the ozone chemistry and the dehydration and denitrification of the stratosphere. Lidars with a depolarization channel may be used to detect and classify different classes of PSCs. The main PSC classes are water ice, nitric acid trihydrate (NAT), and supercooled ternary solutions (STSs), the latter being liquid droplets consisting of water, nitric acid, and sulfuric acid. PSCs have been observed at the lidar observatory at Concordia Station from 2014 onward. The harsh environmental conditions at Concordia during winter render successful lidar operation difficult. To facilitate the operation of the observatory, several measures have been put in place to achieve an almost complete remote control of the system. PSC occurrence is strongly correlated with local temperatures and is affected by dynamics, as the PSC coverage during the observation season shows. PSC observations in 2021 are shown as an example of the capability and functionality of the lidar observatory. A comparison of the observations with the satellite-borne CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) lidar has been made to demonstrate the quality of the data and their representativeness for the Antarctic Plateau.