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Summary: Intimate partner violence (IPV) is a significant public health concern whose neurological/behavioral sequelae remain to be mechanistically explained. Using a mouse model recapitulating an IPV scenario, we evaluated the female brain neuroendocrine alterations produced by a reiterated male-to-female violent interaction (RMFVI). RMFVI prompted anxiety-like behavior in female mice whose hippocampus displayed a marked neuronal loss and hampered neurogenesis, namely reduced BrdU-DCX-positive nuclei and diminished dendritic arborization in the dentate gyrus (DG): effects paralleled by a substantial downregulation of the estrogen receptor β (ERβ). After RMFVI, the DG harbored reduced brain-derived neurotrophic factor (BDNF) pools and tyrosine kinase receptor B (TrkB) phosphorylation. Accordingly, ERβ knockout (KO) mice had heightened anxiety and curtailed BDNF levels at baseline while dying prematurely during the RMFVI procedure. Strikingly, injecting an ERβ antagonist or agonist into the wild-type (WT) female hippocampus enhanced or reduced anxiety, respectively. Thus, reiterated male-to-female violence jeopardizes hippocampal homeostasis, perturbing the ERβ/BDNF axis and ultimately instigating anxiety and chronic stress.

The Chain of Custody (CoC) standard tracks the recycled content (RC) of products, in most cases using the Mass Balance model. This model freely allows the selection of allocation methods and timeframes for the RC evaluation. Our work opens a discussion on the potential effects of this freedom in the RC evaluation. Firstly, we defined the general model representing the viable allocation methods and timeframe, and secondly, we applied the model to a case study. The mass balance model simplifies the monitoring of RC and encourages companies to use recycled materials. However, we outline the need for actions on stricter RC calculation and reporting, for instance, by reducing the timeframe of mass balance calculation or promoting the controlled blending model, which guarantees the physical presence of RC in the product. The results provide a basis for policymakers to set requirements for RC evaluation.

“Beta beams” produce collimated pure electron (anti)neutrino beams by accelerating beta active ions to high energies and having them decay in a racetrack shaped storage ring of 7 km circumference, the decay ring. EUROnu beta beams are based on CERN infrastructures and existing machines. Using existing machines may be an advantage for the cost evaluation, but will also constrain the physics performance. The isotope pair of choice for the beta beam is ^{6}He and ^{18}Ne. However, before the EUROnu studies one of the required isotopes, ^{18}Ne, could not be produced in rates that satisfy the needs for physics of the beta beam. Therefore, studies of alternative beta emitters, ^{8}Li and ^{8}B, with properties interesting for a beta beam have been proposed and have been studied within EUROnu. These alternative isotopes could be produced by using a small storage ring, in which the beam traverses a target, creating the ^{8}Li and ^{8}B isotopes. This production ring, the injection linac and the target system have been evaluated. Measurements of the cross section of the reactions to produce the beta beam isotopes show interesting results. A device to collect the produced isotopes from the target has been developed and tested. However, the yields of ^{8}Li and ^{8}B, using the production ring for production of ^{8}Li and ^{8}B, is not yet, according to simulations, giving the rates of isotopes that would be needed. Therefore, a new method of producing the ^{18}Ne isotope has been developed and tested giving good production rates. A 60 GHz ECRIS prototype, the first in the world, was developed and tested for ion production with contributions from EUROnu. The decay ring lattices for the ^{8}Li and ^{8}B have been developed and the lattice for ^{6}He and ^{18}Ne has been optimized to ensure the high intensity ion beam stability.

The EUROnu project has studied three possible options for future, high intensity neutrino oscillation facilities in Europe. The first is a Super Beam, in which the neutrinos come from the decay of pions created by bombarding targets with a 4 MW proton beam from the CERN High Power Superconducting Proton Linac. The far detector for this facility is the 500 kt MEMPHYS water Cherenkov, located in the Fréjus tunnel. The second facility is the Neutrino Factory, in which the neutrinos come from the decay of μ^{+} and μ^{-} beams in a storage ring. The far detector in this case is a 100 kt magnetized iron neutrino detector at a baseline of 2000 km. The third option is a Beta Beam, in which the neutrinos come from the decay of beta emitting isotopes, in particular ^{6}He and ^{18}Ne, also stored in a ring. The far detector is also the MEMPHYS detector in the Fréjus tunnel. EUROnu has undertaken conceptual designs of these facilities and studied the performance of the detectors. Based on this, it has determined the physics reach of each facility, in particular for the measurement of CP violation in the lepton sector, and estimated the cost of construction. These have demonstrated that the best facility to build is the Neutrino Factory. However, if a powerful proton driver is constructed for another purpose or if the MEMPHYS detector is built for astroparticle physics, the Super Beam also becomes very attractive.

Abstract The present article objective is to determine the net mass balance of the glacier Znosko for periods 2018-2019 and 2019-2020. It is situated on King George Island which belongs to the groups Shetland of the South, Antarctic Peninsula region. For this objective, during February 2018 a net of 19 stakes (which were controlled once during February 2019 and 2020) were installed on the glacier ablation zone, drilling in the accumulation zone and about flights using unmanned aerial vehicles (UAV) to control the glacier zone and geomorphological changes. For the year 2020, it was determined a glacier area of 1.71 ± 0.02 km2, moreover, using five different methods of interpolation, it was obtained on average, as a result, a specific net balance of -590.7 ± 46.6 mm w.e (in water equivalent) for 2018-2019 and -686.7 ± 28.2 mm w.e for 2019-2020, being the ELA altitude 146.5 ± 18.2 m and 144.2 ± 8.3 m respectively. The two consecutive years represent negative net mass balances which are in accordance with other similar studies on this region, also glacier data were obtained on a zone that is characterized by its difficult access.

Não existem dúvidas quanto à importância dos linfonodos axilares no prognóstico e tratamento do câncer da mama. Em 151 mastectomias realizadas, empregando-se as técnicas de Halsted-Meyer (104 casos) e de Patey-Dyson (47 casos), encontrou-se um total de 5.015 linfonodos axilares, com a média de 33,2 por axila. Não houve diferença significativa entre o número médio de linfonodos encontrados na axila, tanto com uma quanto com outra técnica de mastectomia. Os linfonodos foram divididos de acordo com os níveis de drenagem axilar e de acordo com os seus maiores diâmetros. Observou-se uma estreita correlação entre o diâmetro de cada um deles e o seu comprometimento histológico, de onde se conclui que esse parâmetro pode ser considerado como outro indicador prognóstico para o câncer da mama. Os pequenos linfonodos (0,5cm ou menos) estavam presentes em todos os níveis, ao contrário do que ocorreu com aqueles maiores que 2cm de diâmetro, encontrados quase exclusivamente no primeiro nível de drenagem axilar. Por outro lado, estes últimos apresentaram uma taxa de comprometimento histológico mais elevada que os demais. Observou-se uma taxa de falso negativo de 22,5%, a qual foi mais elevada entre os casos mais iniciais de estadiamento da moléstia. O comportamento histológico da axila só poderá ser comprovado se todos os linfonodos encontrados forem examinados, o que será possível após um bom esvaziamento axilar, incluindo a retirada do músculo peitoral menor. Dessa maneira, cirurgias mais conservadoras, com preservação dos músculos peitorais, apenas levarão a uma linfadenectomia axilar incompleta. Foi muito raro o comprometimento de linfonodos situados em níveis superiores sem que o primeiro nível estivesse comprometido. Assim como foi raro encontrar linfonodos pequenos comprometidos sem que os maiores estivessem histologicamente positivos. Foi descrito um grupo de linfonodos, considerado uma das cadeias mais altas da axila, denominado GRUPO PARACEFÁLICO, encontrado em 34 mastectomias (22,5%). Os linfonodos menores que 0,5cm de diâmetro, clinicamente não detectáveis, mas histologicamente com prometidos, foram denominados METASTASES AXILARES MINIMAS DA MAMA.

The wide application of beneficial microorganisms in agriculture as inoculants to combat pests and diseases and/or to improve soil fertility and the nutrients availability for plants has been considered as an effective and more sustainable alternative than chemical fertilizers and agricultural defensives. However, it is necessary to examine all processing steps of these bio-based products under a more integrated view including the type of microorganisms and the whole production process in order to reduce dependence on synthetic chemical inputs. Here, recent developments on the production and formulation technologies of microbial inoculants and the main types of inoculants currently applied in agriculture are addressed. The different types of microbial formulations are compared with emphasis on the encapsulation technology. Moreover, the application of biofertilizers in seed coating and a new approach to apply biocomposites as fertilizers are discussed, presenting the main challenges and future perspectives to promote more sustainable agriculture practices.

Abstract Two-photon fluorescence calcium imaging allows recording the activity of large neural populations with subcellular spatial resolution, but it is typically characterized by low signal-to-noise ratio (SNR) and poor accuracy in detecting single or few action potentials when large number of neurons are imaged. We recently showed that implementing a smart line scanning approach using trajectories that optimally sample the regions of interest increases both the SNR fluorescence signals and the accuracy of single spike detection in population imaging in vivo. However, smart line scanning requires highly specialised software to design recording trajectories, interface with acquisition hardware, and efficiently process acquired data. Furthermore, smart line scanning needs optimized strategies to cope with movement artefacts and neuropil contamination. Here, we develop and validate SmaRT2P, an open-source, user-friendly and easy-to-interface Matlab-based software environment to perform optimized smart line scanning in two-photon calcium imaging experiments. SmaRT2P is designed to interface with popular acquisition software (e.g., ScanImage) and implements novel strategies to detect motion artefacts, estimate neuropil contamination, and minimize their impact on functional signals extracted from neuronal population imaging. SmaRT2P is structured in a modular way to allow flexibility in the processing pipeline, requiring minimal user intervention in parameter setting. The use of SmaRT2P for smart line scanning has the potential to facilitate the functional investigation of large neuronal populations with increased SNR and accuracy in detecting the discharge of single and few action potentials.

Introduction: Cocaine use disorder is a significant public health issue without a current specific approved treatment. Among different approaches to this disorder, it is possible to highlight a promising immunologic strategy in which an immunogenic agent may reduce the reinforcing effects of the drug if they are able to yield sufficient specific antibodies capable to bind cocaine and/or its psychoactive metabolites before entering into the brain. Several carriers have been investigated in the anti-cocaine vaccine development; however, they generally present a very complex chemical structure, which potentially hampers the proper assessment of the coupling efficiency between the hapten units and the protein structure. Objectives: The present study reports the design, synthesis and preclinical evaluation of two novel calix[n]arene-based anti-cocaine immunogens (herein named as V4N2 and V8N2) by the tethering of the hydrolysis-tolerant hapten GNE (15) on calix[4]arene and calix[8]arene moieties. Methods: The preclinical assessment corresponded to the immunogenicity and dose–response evaluation of V4N2 and V8N2. The potential of the produced antibodies to reduce the passage of cocaine analogue through the blood–brain-barrier (BBB), modifying its biodistribution was also investigated. Results: Both calix[n]arene-based immunogens elicited high titers of cocaine antibodies that modified the biodistribution of a cocaine radiolabeled analogue (99mTc-TRODAT-1) and decreased cocaine-induced behavior, according to an animal model. Conclusion: The present results demonstrate the potential of V4N2 and V8N2 as immunogens for the treatment of cocaine use disorder.

Conventional Life Cycle Assessment (LCA) that relies on static coefficients is usually based on yearly averages. However, the impacts of electricity supply vary remarkably on an hourly basis. Thus, a company production plan is reassessed to reduce selected LCA impacts due to electricity consumption. To achieve this, the company will need a forecast of hourly LCA impacts due to electricity consumption, which can be directly forecast with the Direct Forecasting (DF) approach. Alternatively, the Electricity Technological Mix Forecasting (ETMF) forecasts the electricity production of the technologies in the mix and subsequently linearly combines it with unitary LCA impact indicators. Here, we assessed different machine learning models to forecast two LCA impact indicators for the consumption of electricity in the Italy-North control zone. The feed-forward neural network (NN) with the ETMF approach was the best perfomer among the assessed forecasting models. In our dataset, recurrent neural networks (RNNs) performed worse than feed-forward neural networks. Due to its better forecasting performance, the ETMF approach was preferred over the DF approach. This was due to its flexibility and scalability with easy updates or expansion of the selected forecast indicators, and due to its ability to assess technology-specific errors in the forecasting. Finally, we propose to adopt the correlation of LCA impact indicators within the dataset to select indicators while avoiding unconscious burden-shifting.

Aftershocks of earthquakes can destroy many urban infrastructures and exacerbate the damage already inflicted upon weak structures. Therefore, it is important to have a method to forecast the probability of occurrence of stronger earthquakes in order to mitigate their effects. In this work, we applied the NESTORE machine learning approach to Greek seismicity from 1995 to 2022 to forecast the probability of a strong aftershock. Depending on the magnitude difference between the mainshock and the strongest aftershock, NESTORE classifies clusters into two types, Type A and Type B. Type A clusters are the most dangerous clusters, characterized by a smaller difference. The algorithm requires region-dependent training as input and evaluates performance on an independent test set. In our tests, we obtained the best results 6 h after the mainshock, as we correctly forecasted 92% of clusters corresponding to 100% of Type A clusters and more than 90% of Type B clusters. These results were also obtained thanks to an accurate analysis of cluster detection in a large part of Greece. The successful overall results show that the algorithm can be applied in this area. The approach is particularly attractive for seismic risk mitigation due to the short time required for forecasting.

Magicians often rely on misdirection to fool their audience. Acommon way to achieve this is for the magician to provide aplausible and intuitive (but false) account of how an effect isperformed in order to prevent spectators from uncovering thetruth. We hypothesized that analytical thinkers would be morelikely than intuitive thinkers to seek alternative explanationswhen observing a mental magic effect because generating acoherent explanation requires analytical thought. We foundthat while intuitive thinkers often espoused explanations for amagic trick similar to one provided by the magician,analytical thinkers tended to generate new explanations thatechoed rational principles and relied on physical mechanisms(rather than mental capabilities). This difference was notpredicted by differences in numeracy skills or need forcognition.

Ammonium carbonates are a group of fertilizer materials that include ammonium bicarbonate, ammonium carbonate hydrate, and ammonium carbamate. They can be synthesized from diverse nutrient-bearing liquid waste streams but are unstable in a moist environment. While extensively utilized several decades ago, their use gradually decreased in favor of large-scale, facility-synthesized urea fertilizers. The emergence of sustainable agriculture, however, necessitates the recovery and reuse of nutrients using conventional feedstocks, such as natural gas and air-derived nitrogen, and nutrient-containing biogenic waste streams. To this extent, anaerobic digestion liquid presents a convenient source of solid nitrogen and carbon to produce solid fertilizers, since no significant chemical transformations are needed as nitrogen is already present as an ammonium ion. This review describes detailed examples of such feedstocks and the methods required to concentrate and crystallize solid ammonium carbonates. The technologies currently proposed or utilized to stabilize ammonium carbonate materials in the environment are described in detail. Finally, the agricultural efficiency of these materials as nitrogen and carbon source is also described.