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Abstract Key message Winter reddening of young Douglas-fir (Pseudotsuga menziesii Mirb. Franco), triggered by large thermal fluctuations in late winter, is a critical problem for European forestry. A literature review identified certain climatic conditions that are characteristic of ‘reddening’ years, including warm daily temperatures, high daily temperature amplitude, low relative humidity, moderate wind speeds, as well as the occurrence of freeze-thaw cycles with cold night temperatures. By describing the triggering environmental and stand factors, we propose three hypotheses for the physiological processes leading to winter reddening, namely (i) hydraulic failure due to winter drought stress, (ii) photo-oxidative stress in shade-acclimated trees, and (iii) early cold deacclimation during warm periods. i) Low soil temperature, by reducing root water uptake, combined with anticyclonic conditions, by increasing water losses, can induce hydraulic failure in the xylem. Hydraulic failure may be further accelerated by night frosts. ii) Winter reddening can occur when low temperature and high irradiance coincide, disrupting photostasis. Overwhelming of winter photo-protection may lead to photodamage and subsequent reddening. iii) Warm periods, by inducing cold deacclimation, make trees susceptible to frost damage. Finally, the three processes may interact under atypical anticyclonic conditions in late winter (e.g. cold or dry soils, warm days, high irradiance and/or freezing nights). Indeed, trees under water stress would develop a higher sensitivity to freezing night and photooxidative stress. We therefore proposed mitigation actions to avoid exposing trees to stressful conditions based on e.g. stand characteristics, understorey vegetation and planting.

Abstract University students have to handle crucial challenges for their future lives, such as succeeding in academic studies and finding attachment figures. These processes could potentially involve their well-being and mental health, with possible sociocultural differences based on the country of study. In order to explore such potential differences, a cross-sectional, multi-center survey was performed involving students from the University of Torino (Italy), Sevilla (Spain), and Lusòfona (Portugal). The survey, conducted from May to November 2023, investigated students’ demographic and educational details, socioeconomic status, social support, mental health, academic environment, perceived COVID-19 pandemic impact, and future plans. Demographic profiles showed a predominance of female participants and straight sexual orientation, followed by bisexuality. Italian students showed the lowest levels of mental well-being and the highest rates of mental problems (anxiety and depression) and suicidal risk across the three countries despite the relatively similar profiles of social support. The prevalence of the students’ confidence in their professional future is higher in Spain than in Italy and Portugal. This study provides a comprehensive examination of university students’ mental health and well-being in three Southern European countries, addressing the major mental health challenges among university students and offering valuable insights for public health purposes.

In this paper, we present an innovative approach inspired by the Path-scan model to detect paths with k adjacent edges (k-path) exhibiting unusual behavior (synonymous with anomaly) within network communications. This work is motivated by the challenge of identifying malicious activities carried out in vulnerable k-path in a small to medium-sized computer network. Each observed edge (time series of the number of events or the number of packets exchanged between two computers in the network) is modeled using the three-state observed Markov model, as opposed to the Path-scan model which uses a two-state model (active state and inactive state), to establish baselines of behavior in order to detect anomalies. This model captures the typical behavior of network communications, as well as patterns of suspicious activity, such as those associated with brute force attacks. We take a perspective by analyzing each vulnerable k-path, enabling the accurate detection of anomalies on the k-path. Using this approach, our method aims to enhance the detection of suspicious activities in computer networks, thus providing a more robust and accurate solution to ensure the security of computer systems.

Abstract Incidental capture of non-target species poses a pervasive threat to many marine species, with sometimes devastating consequences for both fisheries and conservation efforts. Because of the well-known importance of vocalizations in cetaceans, acoustic deterrents have been extensively used for these species. In contrast, acoustic communication for sea turtles has been considered negligible, and this question has been largely unexplored. Addressing this challenge therefore requires a comprehensive understanding of sea turtles’ responses to sensory signals. In this study, we scrutinized the avenue of auditory cues, specifically the natural sounds produced by green turtles (Chelonia mydas) in Martinique, as a potential tool to reduce bycatch. We recorded 10 sounds produced by green turtles and identified those that appear to correspond to alerts, flight or social contact between individuals. Subsequently, these turtle sounds—as well synthetic and natural (earthquake) sounds—were presented to turtles in known foraging areas to assess the behavioral response of green turtles to these sounds. Our data highlighted that the playback of sounds produced by sea turtles was associated with alert or increased the vigilance of individuals. This therefore suggests novel opportunities for using sea turtle sounds to deter them from fishing gear or other potentially harmful areas, and highlights the potential of our research to improve sea turtles populations’ conservation.

Studying underwater soundscapes of critical habitats of marine mammals can provide valuable information on the acoustic environment utilized by sound-reliant animals. For the endangered Hawaiian monk seal Neomonachus schauinslandi (HMS), the acoustic scene of their aquatic habitats is poorly understood. We measured ambient noise levels and characterized sound sources at 4 shallow critical habitats of the HMS. Broadband levels ranged from 107.8-123.4 dB re 1 µPa. Octave band levels showed diel patterns associated with biological and anthropogenic sources that mask HMS vocalizations. Biological sources dominated the soundscape at all sites. We opportunistically recorded 2 large-scale geophonic events: Hurricane Douglas (Category 4) and a 6.2 magnitude earthquake. This study provides the first description of underwater soundscapes at critical habitats of the HMS across its expansive range. These measurements serve as a baseline for future studies to understand the impacts of human activities on underwater soundscapes.

Avalanches are important contributors to the mass balance of glaciers located in mountain ranges with steep topographies. Avalanches result in localized over-accumulation that is seldom accounted for in glacier models due to the difficulty of quantifying this contribution, let alone the occurrence of avalanches in these remote regions. Here, we developed an approach to semi-automatically map avalanche deposits over long time periods and at scales of multiple glaciers, utilizing imagery from Sentinel-1 synthetic aperture radar (SAR). This approach performs particularly well for scenes acquired in winter and in the morning but can also be used to identify avalanche events throughout the year. We applied this method to map 16 302 avalanche deposits over a period of 5 years at a 6 to 12 d interval over the Mt Blanc massif (European Alps), the Everest (central Himalaya) region, and the Hispar (Karakoram) region. These three survey areas are all characterized by steep mountain slopes but also present contrasting climatic characteristics. Our results enable the identification of avalanche hotspots on these glaciers and allow us to quantify the avalanche activity and its spatio-temporal variability across the three regions. The avalanche deposits are preferentially located at lower elevations relative to the hypsometry of the glacierized catchments and are also constrained to a smaller elevation range at the Asian sites, where they have a limited influence on their extensive debris-covered tongues. Avalanche events coincide with solid precipitation events, which explains the high avalanche activity in winter in the Mt Blanc massif and during the monsoon in the Everest region. However, there is also a time lag of 1–2 months, visible especially in the Everest region, between the precipitation and avalanche events, indicative of some snow retention on the mountain headwalls. This study therefore provides critical insights into these mass redistribution processes and tools to account for their influence on glacier mass balance.

Against a backdrop of change in the French public health governance system, this article examines the dynamics of public-sector dispositives in managing livestock epidemics, situations that are typically fraught with doubt and often lead to crises of governance (‘mad cow’ disease, ‘bird flu’, foot-and-mouth, etc.). In such complex, interorganizational situations, marked by uncertainty and tight management time frames, fresh organizational and managerial activity is constantly required, making it a challenging task to characterize and understand the dynamics of the management dispositives that are activated along the way.In order to produce a detailed and dynamic mapping of dispositives, we draw on the theoretical framework of ‘dispositional analysis’, developed by recent rereadings of Michel Foucault’s concept of the dispositive. To this, we bring the micro and situated perspective of the ‘day-to-day administering’, introducing Jacques Girin’s concept of the ‘management situation’. We thus hypothesize that management situations are sites of intensive dispositive recombination and offer a useful interpretive frame for dispositive dynamics. Our methodology is based on a longitudinal and comparative analysis of three animal health disease management situations in a particular region (a health crisis, the reemergence of a disease, and an endemic disease situation).Our analysis reveals an architecture of health dispositives whose relationships change as the management situation evolves. Three modes of recombination are identified, produced through the mechanisms of problematization (reformulating the problem) and stakeholder participation. This article makes visible the complex links between the evolution of the situations and the dynamics of the dispositives and provides food for thought in building a more robust governance of public animal health problems, combining situational and planning approaches.

Background: Health care workers (HCWs) are at increased risk of exposure to hepatitis B virus (HBV). The most effective prevention measure is vaccination, with a serum hepatitis B surface antibody (HBsAb) titre > 10 mIU/ml considered protective. To date, the sociodemographic and occupational characteristics related to HBV serosusceptibility and factors associated with booster hesitancy remain unclear. Therefore, this study aimed to identify factors associated with maintaining a protective HBsAb titre in a large sample of HCWs and to evaluate factors potentially associated with hesitancy towards vaccine boosters. Methods: A cross-sectional study was conducted among HCWs who underwent a health surveillance visit between 2017 and 2022. If the serum HBsAb titre was

Abstract The appropriate use of predictive equations in estimating body composition through bioelectrical impedance analysis (BIA) depends on the device used and the subject’s age, geographical ancestry, healthy status, physical activity level and sex. However, the presence of many isolated predictive equations in the literature makes the correct choice challenging, since the user may not distinguish its appropriateness. Therefore, the present systematic review aimed to classify each predictive equation in accordance with the independent parameters used. Sixty-four studies published between 1988 and 2023 were identified through a systematic search of international electronic databases. We included studies providing predictive equations derived from criterion methods, such as multi-compartment models for fat, fat-free and lean soft mass, dilution techniques for total-body water and extracellular water, total-body potassium for body cell mass, and magnetic resonance imaging or computerized tomography for skeletal muscle mass. The studies were excluded if non-criterion methods were employed or if the developed predictive equations involved mixed populations without specific codes or variables in the regression model. A total of 106 predictive equations were retrieved; 86 predictive equations were based on foot-to-hand and 20 on segmental technology, with no equations used the hand-to-hand and leg-to-leg. Classifying the subject’s characteristics, 19 were for underaged, 26 for adults, 19 for athletes, 26 for elderly and 16 for individuals with diseases, encompassing both sexes. Practitioners now have an updated list of predictive equations for assessing body composition using BIA. Researchers are encouraged to generate novel predictive equations for scenarios not covered by the current literature. Registration code in PROSPERO: CRD42023467894.

Abstract Background The detection of internal defects in seeds via non-destructive imaging techniques is a topic of high interest to optimize the quality of seed lots. In this context, X-ray imaging is especially suited. Recent studies have shown the feasibility of defect detection via deep learning models in 3D tomography images. We demonstrate the possibility of performing such deep learning-based analysis on 2D X-ray radiography for a faster yet robust method via the X-Robustifier pipeline proposed in this article. Results 2D X-ray images of both defective and defect-free seeds were acquired. A deep learning model based on state-of-the-art object detection neural networks is proposed. Specific data augmentation techniques are introduced to compensate for the low ratio of defects and increase the robustness to variation of the physical parameters of the X-ray imaging systems. The seed defects were accurately detected (F1-score >90%), surpassing human performance in computation time and error rates. The robustness of these models against the principal distortions commonly found in actual agro-industrial conditions is demonstrated, in particular, the robustness to physical noise, dimensionality reduction and the presence of seed coating. Conclusion This work provides a full pipeline to automatically detect common defects in seeds via 2D X-ray imaging. The method is illustrated on sugar beet and faba bean and could be efficiently extended to other species via the proposed generic X-ray data processing approach (X-Robustifier). Beyond a simple proof of feasibility, this constitutes important results toward the effective use in the routine of deep learning-based automatic detection of seed defects.

Summary: Human-specific genes are potential drivers of brain evolution. Among them, SRGAP2C has contributed to the emergence of features characterizing human cortical synapses, including their extended period of maturation. SRGAP2C inhibits its ancestral copy, the postsynaptic protein SRGAP2A, but the synaptic molecular pathways differentially regulated in humans by SRGAP2 proteins remain largely unknown. Here, we identify CTNND2, a protein implicated in severe intellectual disability (ID) in Cri-du-Chat syndrome, as a major partner of SRGAP2. We demonstrate that CTNND2 slows synaptic maturation and promotes neuronal integrity. During postnatal development, CTNND2 moderates neuronal excitation and excitability. In adults, it supports synapse maintenance. While CTNND2 deficiency is deleterious and results in synaptic loss of SYNGAP1, another major ID-associated protein, the human-specific protein SRGAP2C, enhances CTNND2 synaptic accumulation in human neurons. Our findings suggest that CTNND2 regulation by SRGAP2C contributes to synaptic neoteny in humans and link human-specific and ID genes at the synapse.

Prenatal maternal stress (PMS) is known to shape the phenotype of the first generation offspring (F1) but according to some studies, it could also shape the phenotype of the offspring of the following generations. We previously showed in the Japanese quail that PMS increased the emotional reactivity of F1 offspring in relation to (i) a variation in the levels of some histone post-translational modification (H3K27me3) in their brains and (ii) a modulation of the hormonal composition of the eggs from which they hatched. Here, we wondered whether PMS could also influence the behaviour of the second (F2) and third (F3) generation offspring due to the persistence of the specific marks we identified. Using a principal component analysis, we found that PMS influenced F2 and F3 quail profiles with subtle differences between generations. It increased F2 neophobia, F3 fearfulness and F3 neophobia but only in females. Interestingly, we did not find any variations in the level of histone post-translational modification in F3 brains and we observed inconsistent modulations of androstenedione levels in F1 and F2 eggs. Although they may vary over generations, our results demonstrate that PMS can have phenotypical effects into the third generation.

Summary: Lineage-specific differentiation of human induced pluripotent stem cells (hiPSCs) relies on complex interactions between biochemical and physical cues. Here we investigated the ability of hiPSCs to undergo lineage commitment in response to inductive signals and assessed how this competence is modulated by substrate stiffness. We showed that Activin A-induced hiPSC differentiation into mesendoderm and its derivative, definitive endoderm, is enhanced on gel-based substrates softer than glass. This correlated with changes in tight junction formation and extensive cytoskeletal remodeling. Further, live imaging and biophysical studies suggested changes in cell motility and interfacial contacts underlie hiPSC layer reshaping on soft substrates. Finally, we repurposed an ultra-soft silicone gel, which may provide a suitable substrate for culturing hiPSCs at physiological stiffnesses. Our results provide mechanistic insight into how epithelial mechanics dictate the hiPSC response to chemical signals and provide a tool for their efficient differentiation in emerging stem cell therapies.

CUORE Upgrade with Particle IDentification (CUPID) is a foreseen ton-scale array of Li2MoO4 (LMO) cryogenic calorimeters with double readout of heat and light signals. Its scientific goal is to fully explore the inverted hierarchy of neutrino masses in the search for neutrinoless double beta decay of 100Mo. Pile-up of standard double beta decay of the candidate isotope is a relevant background. We generate pile-up heat events via injection of Joule heater pulses with a programmable waveform generator in a small array of LMO crystals operated underground in the Laboratori Nazionali del Gran Sasso, Italy. This allows to label pile-up pulses and control both time difference and underlying amplitudes of individual heat pulses in the data. We present the performance of supervised learning classifiers on data and the attained pile-up rejection efficiency.

Abstract Background Long Intergenic noncoding RNA predicting CARdiac remodeling (LIPCAR) is a long noncoding RNA identified in plasma of patients after myocardial infarction (MI) to be associated with left ventricle remodeling (LVR). LIPCAR was also shown to be a predictor of early death in heart failure (HF) patients. However, no information regarding the expression of LIPCAR and its function in heart as well as the mechanisms involved in its transport to the circulation is known. The aims of this study are (1) to characterize the transporter of LIPCAR from heart to circulation; (2) to determine whether LIPCAR levels in plasma isolated-extracellular vesicles (EVs) reflect the alteration of its expression in total plasma and could be used as biomarkers of LVR post-MI. Methods Since expression of LIPCAR is restricted to human species and the limitation of availability of cardiac biopsy samples, serum-free conditioned culture media from HeLa cells were first used to characterize the extracellular transporter of LIPCAR before validation in EVs isolated from human cardiac biopsies (non-failing and ischemic HF patients) and plasma samples (patients who develop or not LVR post-MI). Differential centrifugation at 20,000g and 100,000g were performed to isolate the large (lEVs) and small EVs (sEVs), respectively. Western blot and nanoparticle tracking (NTA) analysis were used to characterize the isolated EVs. qRT-PCR analysis was used to quantify LIPCAR in all samples. Results We showed that LIPCAR is present in both lEVs and sEVs isolated from all samples. The levels of LIPCAR are higher in lEVs compared to sEVs isolated from HeLa conditioned culture media and cardiac biopsies. No difference of LIPCAR expression was observed in tissue or EVs isolated from cardiac biopsies obtained from ischemic HF patients compared to non-failing patients. Interestingly, LIPCAR levels were increased in lEVs and sEVs isolated from MI patients who develop LVR compared to patients who did not develop LVR. Conclusion Our data showed that large EVs are the main extracellular vesicle transporter of LIPCAR from heart into the circulation independently of the status, non-failing or HF, in patients. The levels of LIPCAR in EVs isolated from plasma could be used as biomarkers of LVR in post-MI patients.

Obesity is defined as a complex, systemic disease characterized by excessive and dysfunctional adipose tissue, leading to adverse health effects. This condition is marked by low-grade inflammation, oxidative stress, and metabolic abnormalities, including mitochondrial dysfunction. These factors promote energy dysregulation and impact body composition not only by increasing body fat but also by promoting skeletal muscle mass atrophy. The decline in muscle mass is associated with an increased risk of all-cause mortality in individuals with this disease. The European Food Safety Authority approved pyrroloquinoline quinone (PQQ), a natural compound, as a dietary supplement in 2018. This narrative review aims to provide a comprehensive overview of the potential role of PQQ, based on its anti-inflammatory and antioxidant properties, in addressing dysfunctional adipose tissue metabolism and related disorders.

Background: The international surveillance of antimicrobial resistance (AMR) reports S. pneumoniae as one of leading causes of death associated with AMR. Against invasive disease, several vaccinations are available and a reduction in AMR in S. pneumoniae has been observed. Here, we evaluated the impact of anti-pneumococcal vaccination policy and the SARS-CoV2 outbreak on AMR in S. pneumoniae causing invasive disease. Methods: We collected all strains of S. pneumoniae causing invasive disease from 2008 in the Piedmont region (Italy). Each strain was typed in order to identify the serogroup and data about AMR were collected. The population under surveillance was classified as infants, children, adults, and the old population. Results: We collected n = 2076 S. pneumoniae strains, with 21.9% and 40.3% being resistant to penicillin G and erythromycin, respectively. We reported an increased risk of infection with penicillin-resistant S. pneumoniae among all populations and evaluated whether the infection was caused by a serotype included in the vaccine formulation. A similar increase was observed after the SARS-CoV2 outbreak. Conclusions: In the Piedmont region, subsequently to the introduction of anti-pneumococcal vaccination, a significant increase in the risk of penicillin G-resistant invasive pneumococcal disease among infants and old population was reported. No significant impact was found for the SARS-CoV2 outbreak.