Community-developed checklists for publishing images and image analyses.

Images document scientific discoveries and are prevalent in modern biomedical research. Microscopy imaging in particular is currently undergoing rapid technological advancements. However, for scientists wishing to publish obtained images and image-analysis results, there are currently no unified guidelines for best practices. Consequently, microscopy images and image data in publications may be unclear or difficult to interpret. Here, we present community-developed checklists for preparing light microscopy images and describing image analyses for publications. These checklists offer authors, readers and publishers key recommendations for image formatting and annotation, color selection, data availability and reporting image-analysis workflows. The goal of our guidelines is to increase the clarity and reproducibility of image figures and thereby to heighten the quality and explanatory power of microscopy data.

COVID-19 vaccine booster doses provide increased protection against COVID-19 hospitalization compared with previously vaccinated individuals: Interim findings from the REFORCO-Brazil real-world effectiveness study during Delta and Omicron.

BACKGROUND: Although COVID-19 booster vaccination is widely recommended, there is limited long-term, population-level, real-world evidence on the magnitude of improved protection against severe COVID-19 conferred by boosting with monovalent COVID-19 vaccines developed against ancestral SARS-CoV-2, especially in low- or middle-income countries. We present interim results from the first large-scale assessment of the relative vaccine effectiveness (rVE) of first and second booster doses against severe COVID-19 in a low-/middle-income country. METHODS: REFORCO-Brazil is an ongoing, test-negative case-control study (NCT05697705) utilizing Brazil national severe acute respiratory syndrome (SARS) surveillance and vaccination data. In SARS hospitalizations from August 1, 2021 to July 31, 2022, we matched test-positive (via SARS-CoV-2 antigen/reverse transcription polymerase chain reaction [RT-PCR]) cases and test-negative case-controls (via RT-PCR) based on admission date, preceding vaccinations, and age. We evaluated the rVEs of four monovalent COVID-19 vaccines (AZD1222, Ad26.COV2.S, CoronaVac, and BNT162b2) as second boosters compared with any first boosters received ≥4 months previously, and as first boosters compared with primary-series vaccinations completed ≥4 months previously. RESULTS: The overall rVE of second boosters, from 5668 (2238 test-positive) evaluated hospitalizations, was 24.7 % (95 % confidence interval [CI]: 12.6-35.1); the overall rVE of first boosters, from 30,272 (12,063 test-positive) hospitalizations, was 46.8 % (95 % CI: 43.3-50.0). The rVEs of AZD1222 and BNT162b2 were similar: 29.4 % (95 % CI: 8.6-45.5) and 25.5 % (95 % CI: 4.2-42.2), respectively, for second boosters; and 42.5 % (95 % CI: 28.0-54.0) and 50.8 % (95 % CI: 47.5-54.0), respectively, for first boosters. In general, rVEs were higher in elderly (≥80 years) and immunocompromised/high-risk individuals. CONCLUSIONS: Our results support the use of AZD1222 and other adenoviral/mRNA vaccine boosters to maintain protection against COVID-19 hospitalization from Omicron subvariants, including in elderly and immunocompromised individuals at increased risk of accelerated waning or severe outcomes.

BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets.

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enable generalizable benchmarking. Together with image quality features, we pooled the data in an interactive web application that enables users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and tracing data, and benchmarking of automatic tracing algorithms in user-defined data subsets. The image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. We observed that diverse algorithms can provide complementary information to obtain accurate results and developed a method to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings.

Community-developed checklists for publishing images and image analyses.

Images document scientific discoveries and are prevalent in modern biomedical research. Microscopy imaging in particular is currently undergoing rapid technological advancements. However for scientists wishing to publish the obtained images and image analyses results, there are to date no unified guidelines. Consequently, microscopy images and image data in publications may be unclear or difficult to interpret. Here we present community-developed checklists for preparing light microscopy images and image analysis for publications. These checklists offer authors, readers, and publishers key recommendations for image formatting and annotation, color selection, data availability, and for reporting image analysis workflows. The goal of our guidelines is to increase the clarity and reproducibility of image figures and thereby heighten the quality and explanatory power of microscopy data is in publications.

HEROHE Challenge: Predicting HER2 Status in Breast Cancer from Hematoxylin-Eosin Whole-Slide Imaging.

Breast cancer is the most common malignancy in women worldwide, and is responsible for more than half a million deaths each year. The appropriate therapy depends on the evaluation of the expression of various biomarkers, such as the human epidermal growth factor receptor 2 (HER2) transmembrane protein, through specialized techniques, such as immunohistochemistry or in situ hybridization. In this work, we present the HER2 on hematoxylin and eosin (HEROHE) challenge, a parallel event of the 16th European Congress on Digital Pathology, which aimed to predict the HER2 status in breast cancer based only on hematoxylin-eosin-stained tissue samples, thus avoiding specialized techniques. The challenge consisted of a large, annotated, whole-slide images dataset (509), specifically collected for the challenge. Models for predicting HER2 status were presented by 21 teams worldwide. The best-performing models are presented by detailing the network architectures and key parameters. Methods are compared and approaches, core methodologies, and software choices contrasted. Different evaluation metrics are discussed, as well as the performance of the presented models for each of these metrics. Potential differences in ranking that would result from different choices of evaluation metrics highlight the need for careful consideration at the time of their selection, as the results show that some metrics may misrepresent the true potential of a model to solve the problem for which it was developed. The HEROHE dataset remains publicly available to promote advances in the field of computational pathology.

Estimations of Mutation Rates Depend on Population Allele Frequency Distribution: The Case of Autosomal Microsatellites.

Microsatellites (or short-tandem repeats (STRs)) are widely used in anthropology and evolutionary studies. Their extensive polymorphism and rapid evolution make them the ideal genetic marker for dating events, such as the age of a gene or a population. This usage requires the estimation of mutation rates, which are usually estimated by counting the observed Mendelian incompatibilities in one-generation familial configurations (typically parent(s)-child duos or trios). Underestimations are inevitable when using this approach, due to the occurrence of mutational events that do not lead to incompatibilities with the parental genotypes ('hidden' or 'covert' mutations). It is known that the likelihood that one mutation event leads to a Mendelian incompatibility depends on the mode of genetic transmission considered, the type of familial configuration (duos or trios) considered, and the genotype(s) of the progenitor(s). In this work, we show how the magnitude of the underestimation of autosomal microsatellite mutation rates varies with the populations' allele frequency distribution spectrum. The Mendelian incompatibilities approach (MIA) was applied to simulated parent(s)/offspring duos and trios in different populational scenarios. The results showed that the magnitude and type of biases depend on the population allele frequency distribution, whatever the type of familial data considered, and are greater when duos, instead of trios, are used to obtain the estimates. The implications for molecular anthropology are discussed and a simple framework is presented to correct the naïf estimates, along with an informatics tool for the correction of incompatibility rates obtained through the MIA.

MCL1 alternative polyadenylation is essential for cell survival and mitochondria morphology.

Alternative polyadenylation in the 3' UTR (3' UTR-APA) is a mode of gene expression regulation, fundamental for mRNA stability, translation and localization. In the immune system, it was shown that upon T cell activation, there is an increase in the relative expression of mRNA isoforms with short 3' UTRs resulting from 3' UTR-APA. However, the functional significance of 3' UTR-APA remains largely unknown. Here, we studied the physiological function of 3' UTR-APA in the regulation of Myeloid Cell Leukemia 1 (MCL1), an anti-apoptotic member of the Bcl-2 family essential for T cell survival. We found that T cells produce two MCL1 mRNA isoforms (pA1 and pA2) by 3' UTR-APA. We show that upon T cell activation, there is an increase in both the shorter pA1 mRNA isoform and MCL1 protein levels. Moreover, the less efficiently translated pA2 isoform is downregulated by miR-17, which is also more expressed upon T cell activation. Therefore, by increasing the expression of the more efficiently translated pA1 mRNA isoform, which escapes regulation by miR-17, 3' UTR-APA fine tunes MCL1 protein levels, critical for activated T cells' survival. Furthermore, using CRISPR/Cas9-edited cells, we show that depletion of either pA1 or pA2 mRNA isoforms causes severe defects in mitochondria morphology, increases apoptosis and impacts cell proliferation. Collectively, our results show that MCL1 alternative polyadenylation has a key role in the regulation of MCL1 protein levels upon T cell activation and reveal an essential function for MCL1 3' UTR-APA in cell viability and mitochondria dynamics.

Characterization of the Striatal Extracellular Matrix in a Mouse Model of Parkinson's Disease.

Parkinson's disease's etiology is unknown, although evidence suggests the involvement of oxidative modifications of intracellular components in disease pathobiology. Despite the known involvement of the extracellular matrix in physiology and disease, the influence of oxidative stress on the matrix has been neglected. The chemical modifications that might accumulate in matrix components due to their long half-live and the low amount of extracellular antioxidants could also contribute to the disease and explain ineffective cellular therapies. The enriched striatal extracellular matrix from a mouse model of Parkinson's disease was characterized by Raman spectroscopy. We found a matrix fingerprint of increased oxalate content and oxidative modifications. To uncover the effects of these changes on brain cells, we morphologically characterized the primary microglia used to repopulate this matrix and further quantified the effects on cellular mechanical stress by an intracellular fluorescence resonance energy transfer (FRET)-mechanosensor using the U-2 OS cell line. Our data suggest changes in microglia survival and morphology, and a decrease in cytoskeletal tension in response to the modified matrix from both hemispheres of 6-hydroxydopamine (6-OHDA)-lesioned animals. Collectively, these data suggest that the extracellular matrix is modified, and underscore the need for its thorough investigation, which may reveal new ways to improve therapies or may even reveal new therapies.

QUAREP-LiMi: A community-driven initiative to establish guidelines for quality assessment and reproducibility for instruments and images in light microscopy.

A modern day light microscope has evolved from a tool devoted to making primarily empirical observations to what is now a sophisticated , quantitative device that is an integral part of both physical and life science research. Nowadays, microscopes are found in nearly every experimental laboratory. However, despite their prevalent use in capturing and quantifying scientific phenomena, neither a thorough understanding of the principles underlying quantitative imaging techniques nor appropriate knowledge of how to calibrate, operate and maintain microscopes can be taken for granted. This is clearly demonstrated by the well-documented and widespread difficulties that are routinely encountered in evaluating acquired data and reproducing scientific experiments. Indeed, studies have shown that more than 70% of researchers have tried and failed to repeat another scientist's experiments, while more than half have even failed to reproduce their own experiments. One factor behind the reproducibility crisis of experiments published in scientific journals is the frequent underreporting of imaging methods caused by a lack of awareness and/or a lack of knowledge of the applied technique. Whereas quality control procedures for some methods used in biomedical research, such as genomics (e.g. DNA sequencing, RNA-seq) or cytometry, have been introduced (e.g. ENCODE), this issue has not been tackled for optical microscopy instrumentation and images. Although many calibration standards and protocols have been published, there is a lack of awareness and agreement on common standards and guidelines for quality assessment and reproducibility. In April 2020, the QUality Assessment and REProducibility for instruments and images in Light Microscopy (QUAREP-LiMi) initiative was formed. This initiative comprises imaging scientists from academia and industry who share a common interest in achieving a better understanding of the performance and limitations of microscopes and improved quality control (QC) in light microscopy. The ultimate goal of the QUAREP-LiMi initiative is to establish a set of common QC standards, guidelines, metadata models and tools, including detailed protocols, with the ultimate aim of improving reproducible advances in scientific research. This White Paper (1) summarizes the major obstacles identified in the field that motivated the launch of the QUAREP-LiMi initiative; (2) identifies the urgent need to address these obstacles in a grassroots manner, through a community of stakeholders including, researchers, imaging scientists, bioimage analysts, bioimage informatics developers, corporate partners, funding agencies, standards organizations, scientific publishers and observers of such; (3) outlines the current actions of the QUAREP-LiMi initiative and (4) proposes future steps that can be taken to improve the dissemination and acceptance of the proposed guidelines to manage QC. To summarize, the principal goal of the QUAREP-LiMi initiative is to improve the overall quality and reproducibility of light microscope image data by introducing broadly accepted standard practices and accurately captured image data metrics.

4SpecID: Reference DNA Libraries Auditing and Annotation System for Forensic Applications.

Forensic genetics is a fast-growing field that frequently requires DNA-based taxonomy, namely, when evidence are parts of specimens, often highly processed in food, potions, or ointments. Reference DNA-sequences libraries, such as BOLD or GenBank, are imperative tools for taxonomic assignment, particularly when morphology is inadequate for classification. The auditing and curation of these datasets require reliable mechanisms, preferably with automated data preprocessing. Software tools were developed to grade these datasets considering as primary criterion the number of records, which is not compliant with forensic standards, where the priority is validation from independent sources. Moreover, 4SpecID is an efficient software tool developed to audit and annotate reference libraries, specifically designed for forensic applications. Its intuitive user-friendly interface virtually accesses any database and includes specific data mining functions tuned for the widespread BOLD repositories. The built tool was evaluated in laptop MacBook and a dual-Xeon server with a large BOLD dataset (Culicidae, 36,115 records), and the best execution time to grade the dataset on the laptop was 0.28 s. Datasets of Bovidae and Felidae families were used to evaluate the quality of the tool and the relevance of independent sources validation.

Population Analysis and Evolution of Saccharomyces cerevisiae Mitogenomes.

The study of mitogenomes allows the unraveling of some paths of yeast evolution that are often not exposed when analyzing the nuclear genome. Although both nuclear and mitochondrial genomes are known to determine phenotypic diversity and fitness, no concordance has yet established between the two, mainly regarding strains' technological uses and/or geographical distribution. In the current work, we proposed a new method to align and analyze yeast mitogenomes, overcoming current difficulties that make it impossible to obtain comparable mitogenomes for a large number of isolates. To this end, 12,016 mitogenomes were considered, and we developed a novel approach consisting of the design of a reference sequence intended to be comparable between all mitogenomes. Subsequently, the population structure of 6646 Saccharomyces cerevisiae mitogenomes was assessed. Results revealed the existence of particular clusters associated with the technological use of the strains, in particular regarding clinical isolates, laboratory strains, and yeasts used for wine-associated activities. As far as we know, this is the first time that a positive concordance between nuclear and mitogenomes has been reported for S. cerevisiae, in terms of strains' technological applications. The results obtained highlighted the importance of including the mtDNA genome in evolutionary analysis, in order to clarify the origin and history of yeast species.

Detection of HER2 from Haematoxylin-Eosin Slides Through a Cascade of Deep Learning Classifiers via Multi-Instance Learning.

Breast cancer is the most frequently diagnosed cancer in woman. The correct identification of the HER2 receptor is a matter of major importance when dealing with breast cancer: an over-expression of HER2 is associated with aggressive clinical behaviour; moreover, HER2 targeted therapy results in a significant improvement in the overall survival rate. In this work, we employ a pipeline based on a cascade of deep neural network classifiers and multi-instance learning to detect the presence of HER2 from Haematoxylin-Eosin slides, which partly mimics the pathologist's behaviour by first recognizing cancer and then evaluating HER2. Our results show that the proposed system presents a good overall effectiveness. Furthermore, the system design is prone to further improvements that can be easily deployed in order to increase the effectiveness score.

Engineering hydrogels with affinity-bound laminin as 3D neural stem cell culture systems.

Laminin incorporation into biological or synthetic hydrogels has been explored to recapitulate the dynamic nature and biological complexity of neural stem cell (NSC) niches. However, the strategies currently explored for laminin immobilization within three-dimensional (3D) matrices do not address a critical aspect influencing cell-matrix interactions, which is the control over laminin conformation and orientation upon immobilization. This is a key feature for the preservation of the protein bioactivity. In this work, we explored an affinity-based approach to mediate the site-selective immobilization of laminin into a degradable synthetic hydrogel. Specifically, a four-arm maleimide terminated poly(ethylene glycol) (PEG-4MAL) macromer was functionalized with a mono-PEGylated recombinant human N-terminal agrin (NtA) domain, to promote high affinity binding of laminin. Different NtA concentrations (10, 50 and 100 µM) were used to investigate the impact of NtA density on laminin incorporation, hydrogel biophysical properties, and biological outcome. Laminin was efficiently incorporated for all the conditions tested (laminin incorporation >95%), and the developed hydrogels revealed mechanical properties (average storage modulus (G') ranging from 187 to 256 Pa) within the values preferred for NSC proliferation and neurite branching and extension. Affinity-bound laminin PEG-4MAL hydrogels better preserve laminin bioactivity, compared to unmodified hydrogels and hydrogels containing physically entrapped laminin, this effect being dependent on NtA concentration. This was evidenced by the 10 µM NtA-functionalized PEG-4MAL gels incorporating laminin that support enhanced human NSC proliferation and neurite extension, compared to the latter. Overall, this work highlights the potential of the proposed engineered matrices to be used as defined 3D platforms for the establishment of artificial NSC niches and as extracellular matrix-mimetic microenvironments to support human NSC transplantation.

A dispersal of Homo sapiens from southern to eastern Africa immediately preceded the out-of-Africa migration.

Africa was the birth-place of Homo sapiens and has the earliest evidence for symbolic behaviour and complex technologies. The best-attested early flowering of these distinctive features was in a glacial refuge zone on the southern coast 100-70 ka, with fewer indications in eastern Africa until after 70 ka. Yet it was eastern Africa, not the south, that witnessed the first major demographic expansion, ~70-60 ka, which led to the peopling of the rest of the world. One possible explanation is that important cultural traits were transmitted from south to east at this time. Here we identify a mitochondrial signal of such a dispersal soon after ~70 ka - the only time in the last 200,000 years that humid climate conditions encompassed southern and tropical Africa. This dispersal immediately preceded the out-of-Africa expansions, potentially providing the trigger for these expansions by transmitting significant cultural elements from the southern African refuge.

An affinity-based approach to engineer laminin-presenting cell instructive microenvironments.

Laminin immobilization into diverse biological and synthetic matrices has been explored to replicate the microenvironment of stem cell niches and gain insight into the role of extracellular matrix (ECM) on stem cell behavior. However, the site-specific immobilization of this heterotrimeric glycoprotein and, consequently, control over its orientation and bioactivity has been a challenge that has limited many of the explored strategies to date. In this work, we established an affinity-based approach that takes advantage of the native high affinity interaction between laminin and the human N-terminal agrin (hNtA) domain. This interaction is expected to promote the site-selective immobilization of laminin to a specific substrate, while preserving the exposure of its key bioactive epitopes. Recombinant hNtA (rhNtA) domain was produced with high purity (>90%) and successfully conjugated at its N-terminal with a thiol-terminated poly(ethylene glycol) (PEG) without affecting its affinity to laminin. Self-assembled monolayers (SAMs) of mono-PEGylated rhNtA on gold (mPEG rhNtA-SAMs) were then prepared to evaluate the effectiveness of this strategy. The site-specific immobilization of laminin onto mPEG rhNtA-SAMs was shown to better preserve protein bioactivity in comparison to laminin immobilized on SAMs of thiol-PEG-succinimidyl glutaramide (HS-PEG-SGA), used for the non-selective covalent immobilization of laminin, as evidenced by its enhanced ability to efficiently self-polymerize and mediate cell adhesion and spreading of human neural stem cells. These results highlight the potential of this novel strategy to be used as an alternative to the conventional immobilization approaches in a wide range of applications, including engineered coatings for neuroelectrodes and cell culture, as well as biofunctionalization of 3D matrices.

Key individuals for discerning pedigrees belonging to the same autosomal kinship class.

The existence of pedigrees belonging to the same kinship class (i.e. indistinguishable through independent markers) is well known in the forensic community, and theoretical frameworks for autosomal and X-chromosomal markers were already developed for a pair of individuals. Nevertheless, studies for the cases where a greater number of individuals is available for testing are still lacking. With this work, we intend to pave the way for a theoretical and general framework, identifying the individuals/relatives that should be chosen to distinguish autosomal analyses between such pedigrees. In this work we identify the individuals/relatives that are non-informative for calculations (the pedigrees under discussion remaining indistinguishable independently of their genetic profile), as well as those that will likely be very informative, influencing the statistical outcome. For example, given the respective genotypes, to compare the likelihoods of the father of the individual B to be: (a.) the father, or (b.) a full-brother, of the individual A, the hypotheses H1: "The individual A is paternal half-sibling of the individual B", and H0: "The individual A is paternal uncle/aunt of the individual B" are considered. It is proved that considering just individuals A and B the hypotheses are equally likely. In this work we show that the same is also true for the case where the mother of B is available for testing, notwithstanding the hypotheses being differently weighted if the mother of A is considered. Similar considerations are done for other kinship hypotheses and/or individuals/relatives. Irrelevance of the genetic profile of some specific relatives are mathematically demonstrated, and data obtained from 20,000 simulated families are presented for the other cases.

Mitogenome Diversity in Sardinians: A Genetic Window onto an Island's Past.

Sardinians are "outliers" in the European genetic landscape and, according to paleogenomic nuclear data, the closest to early European Neolithic farmers. To learn more about their genetic ancestry, we analyzed 3,491 modern and 21 ancient mitogenomes from Sardinia. We observed that 78.4% of modern mitogenomes cluster into 89 haplogroups that most likely arose in situ. For each Sardinian-specific haplogroup (SSH), we also identified the upstream node in the phylogeny, from which non-Sardinian mitogenomes radiate. This provided minimum and maximum time estimates for the presence of each SSH on the island. In agreement with demographic evidence, almost all SSHs coalesce in the post-Nuragic, Nuragic and Neolithic-Copper Age periods. For some rare SSHs, however, we could not dismiss the possibility that they might have been on the island prior to the Neolithic, a scenario that would be in agreement with archeological evidence of a Mesolithic occupation of Sardinia.

N3DFix: an Algorithm for Automatic Removal of Swelling Artifacts in Neuronal Reconstructions.

It is well established that not only electrophysiology but also morphology plays an important role in shaping the functional properties of neurons. In order to properly quantify morphological features it is first necessary to translate observational histological data into 3-dimensional geometric reconstructions of the neuronal structures. This reconstruction process, independently of being manual or (semi-)automatic, requires several preparation steps (e.g. histological processing) before data acquisition using specialized software. Unfortunately these processing steps likely produce artifacts which are then carried to the reconstruction, such as tissue shrinkage and formation of swellings. If not accounted for and corrected, these artifacts can change significantly the results from morphometric analysis and computer simulations. Here we present N3DFix, an open-source software which uses a correction algorithm to automatically find and fix swelling artifacts in neuronal reconstructions. N3DFix works as a post-processing tool and therefore can be used in either manual or (semi-)automatic reconstructions. The algorithm's internal parameters have been defined using a "ground truth" dataset produced by a neuroanatomist, involving two complementary manual reconstruction procedures: in the first, neuronal topology was faithfully reconstructed, including all swelling artifacts; in the second procedure a meticulous correction of the artifacts was manually performed directly during neuronal tracing. The internal parameters of N3DFix were set to minimize the differences between manual amendments and the algorithm's corrections. It is shown that the performance of N3DFix is comparable to careful manual correction of the swelling artifacts. To promote easy access and wide adoption, N3DFix is available in NEURON, Vaa3D and Py3DN.

A working memory model for serial order that stores information in the intrinsic excitability properties of neurons.

Models for temporary information storage in neuronal populations are dominated by mechanisms directly dependent on synaptic plasticity. There are nevertheless other mechanisms available that are well suited for creating short-term memories. Here we present a model for working memory which relies on the modulation of the intrinsic excitability properties of neurons, instead of synaptic plasticity, to retain novel information for periods of seconds to minutes. We show that it is possible to effectively use this mechanism to store the serial order in a sequence of patterns of activity. For this we introduce a functional class of neurons, named gate interneurons, which can store information in their membrane dynamics and can literally act as gates routing the flow of activations in the principal neurons population. The presented model exhibits properties which are in close agreement with experimental results in working memory. Namely, the recall process plays an important role in stabilizing and prolonging the memory trace. This means that the stored information is correctly maintained as long as it is being used. Moreover, the working memory model is adequate for storing completely new information, in time windows compatible with the notion of "one-shot" learning (hundreds of milliseconds).