A novel missense mutation in the AIRE gene underlying autoimmune polyglandular syndrome type 1.

The immune regulator gene AIRE plays an essential role in the establishment of immune tolerance and the prevention of autoimmunity. This transcription factor plays a critical role in promoting self-tolerance in the thymus by regulating the expression of a large number of self-antigens that share the common feature of being tissue-restricted in their expression pattern in the periphery. Dysfunction of AIRE in humans causes a rare disease, autoimmune polyglandular syndrome type 1 (APS1), characterized by an autoimmune response against peripheral tissues, particularly endocrine tissues. Although a few dominant mutations have been described, the inactivation of AIRE is usually caused by recessive mutations. Recent data suggests that alterations in AIRE function contribute not only to APS1 but also to more common forms of autoimmune disease. Here, we present a previously unreported missense mutation (NM_000383.2:c.260 T > C) in exon 2 of the AIRE gene, predicted to cause the substitution (p.(Leu87Pro)) in the CARD domain of the AIRE protein. When inherited in conjunction with another dysfunctional AIRE allele, this mutation was associated with immune dysregulation in a pediatric patient. The presence of hypergammaglobulinemia, malabsorption syndrome, ectodermal dysplasia, mucocutaneous candidiasis, vitiligo, and hypothyroidism as well as the presence of multiple autoantibodies allowed us to confirm an APS1 diagnosis.

A dynamic attractor network model of memory formation, reinforcement and forgetting.

Empirical evidence shows that memories that are frequently revisited are easy to recall, and that familiar items involve larger hippocampal representations than less familiar ones. In line with these observations, here we develop a modelling approach to provide a mechanistic understanding of how hippocampal neural assemblies evolve differently, depending on the frequency of presentation of the stimuli. For this, we added an online Hebbian learning rule, background firing activity, neural adaptation and heterosynaptic plasticity to a rate attractor network model, thus creating dynamic memory representations that can persist, increase or fade according to the frequency of presentation of the corresponding memory patterns. Specifically, we show that a dynamic interplay between Hebbian learning and background firing activity can explain the relationship between the memory assembly sizes and their frequency of stimulation. Frequently stimulated assemblies increase their size independently from each other (i.e. creating orthogonal representations that do not share neurons, thus avoiding interference). Importantly, connections between neurons of assemblies that are not further stimulated become labile so that these neurons can be recruited by other assemblies, providing a neuronal mechanism of forgetting.

Single neuron responses underlying face recognition in the human midfusiform face-selective cortex.

Faces are critical for social interactions and their recognition constitutes one of the most important and challenging functions of the human brain. While neurons responding selectively to faces have been recorded for decades in the monkey brain, face-selective neural activations have been reported with neuroimaging primarily in the human midfusiform gyrus. Yet, the cellular mechanisms producing selective responses to faces in this hominoid neuroanatomical structure remain unknown. Here we report single neuron recordings performed in 5 human subjects (1 male, 4 females) implanted with intracerebral microelectrodes in the face-selective midfusiform gyrus, while they viewed pictures of familiar and unknown faces and places. We observed similar responses to faces and places at the single cell level, but a significantly higher number of neurons responding to faces, thus offering a mechanistic account for the face-selective activations observed in this region. Although individual neurons did not respond preferentially to familiar faces, a population level analysis could consistently determine whether or not the faces (but not the places) were familiar, only about 50 ms after the initial recognition of the stimuli as faces. These results provide insights into the neural mechanisms of face processing in the human brain.

Impacto da seleção para participar de um estudo randomizado no perfil clínico/angiográfico e nos resultados: hospitalares de pacientes diabéticos submetidos à intervenção coronária percutânea / Impact of selection to participate in a randomized study on the clinical/angiographic profile and results: hospital admissions of diabetic patients undergoing percutaneous coronary intervention

INTRODUÇÃO: Em geral, pacientes (p) incluídos em estudos randomizados são selecionados e exibem perfil clínico/angiográfico de menor gravidade do que os do mundo real. Na última década, ensaios clínicos envolvendo intervenções coronárias percutâneas (ICP) com novos modelos de stents farmacológicos (SF) tem primado por estabelecer apenas critérios clínicos de avaliação dos resultados, evitando a necessidade de reestudo angiográfico compulsório na evolução, o que pode atenuar discrepâncias significativas entre casos selecionados ou não para participar dos estudos, assim como permitir a inclusão de mais p. OBJETIVO: O objetivo desta investigação foi avaliar a hipótese supracitada. MÉTODOS: Recentemente foi realizada em nosso Serviço a inclusão de p diabéticos (PD) de forma prospectiva e randomizada num estudo que avaliou um novo modelo de SF, quando comparado a outro modelo utilizado na rotina. Havia critérios de exclusão restritos. Decidimos comparar os perfis clínico e angiográfico de PD incluídos ou não no estudo, finalizando aleatoriamente a amostra quando fosse incluído o centésimo p. Desta forma, entre 10/2020 e 07/2021, foram realizadas 336 ICP em PD de forma prospectiva, subdivididos em 2 grupos: A) 100(29%) PD incluídos no estudo; B) os 236(71%) restantes. Estabeleceram-se como significativos valores de p<0.05. RESULTADOS: Sexo, idade, diabetes dependente de insulina e extensão da doença coronária não diferiram entre os grupos. Predominaram significativamente no grupo B: disfunção renal crônica(21% vs 7%; p=0.0033), idade superior a 70 anos(37% vs 23% p=0.015), antecedente de ICP(32% vs 13%; p=<0.001), ICP para pontes de veia safena(5% vs 0% p=0.03) e infarto com elevação de ST(19% vs 8%; p=0.017); antecedente de cirurgia de revascularização miocárdica previa(10% vs 4% P=0.08) e ICP uniarterial (69% vs 57% p=0.054) também foram mais observados em B, mas não de forma significante. Predominaram no grupo A: ICP de múltiplos vasos (43% vs 25%; p=0.0016), apresentação clínica de angina estável (47% vs 31%; p=0.009) e revascularização completa (62% vs 47%; p=0.0016). Embora a permanência de UTI do grupo B foi maior (1.1(±3.5) vs 0.27(±1.5) P=0.024) os resultados imediatos da fase hospitalar, em conjunto ou individualmente, não diferiram. CONCLUSÕES: 1) Cerca de um em cada três PD tratados foram incluídos no estudo; 2) mesmo com critérios de inclusão/exclusão menos rígidos, observamos perfil clínico/angiográfico de menor complexidade nos casos incluídos.

An integrative view of human hippocampal function: Differences with other species and capacity considerations.

We describe an integrative model that encodes associations between related concepts in the human hippocampal formation, constituting the skeleton of episodic memories. The model, based on partially overlapping assemblies of "concept cells," contrast markedly with the well-established notion of pattern separation, which relies on conjunctive, context dependent single neuron responses, instead of the invariant, context independent responses found in the human hippocampus. We argue that the model of partially overlapping assemblies is better suited to cope with memory capacity limitations, that the finding of different types of neurons and functions in this area is due to a flexible and temporary use of the extraordinary machinery of the hippocampus to deal with the task at hand, and that only information that is relevant and frequently revisited will consolidate into long-term hippocampal representations, using partially overlapping assemblies. Finally, we propose that concept cells are uniquely human and that they may constitute the neuronal underpinnings of cognitive abilities that are much further developed in humans compared to other species.

Exploring Scoring Function Space: Developing Computational Models for Drug Discovery.

BACKGROUND: The idea of scoring function space established a systems-level approach to address the development of models to predict the affinity of drug molecules by those interested in drug discovery. OBJECTIVE: Our goal here is to review the concept of scoring function space and how to explore it to develop machine learning models to address protein-ligand binding affinity. METHOD: We searched the articles available in PubMed related to the scoring function space. We also utilized crystallographic structures found in the protein data bank (PDB) to represent the protein space. RESULTS: The application of systems-level approaches to address receptor-drug interactions allows us to have a holistic view of the process of drug discovery. The scoring function space adds flexibility to the process since it makes it possible to see drug discovery as a relationship involving mathematical spaces. CONCLUSION: The application of the concept of scoring function space has provided us with an integrated view of drug discovery methods. This concept is useful during drug discovery, where we see the process as a computational search of the scoring function space to find an adequate model to predict receptor-drug binding affinity.

Convergent Evolution in SARS-CoV-2 Spike Creates a Variant Soup from Which New COVID-19 Waves Emerge.

The first 2 years of the COVID-19 pandemic were mainly characterized by recurrent mutations of SARS-CoV-2 Spike protein at residues K417, L452, E484, N501 and P681 emerging independently across different variants of concern (Alpha, Beta, Gamma, and Delta). Such homoplasy is a marker of convergent evolution. Since Spring 2022 and the third year of the pandemic, with the advent of Omicron and its sublineages, convergent evolution has led to the observation of different lineages acquiring an additional group of mutations at different amino acid residues, namely R346, K444, N450, N460, F486, F490, Q493, and S494. Mutations at these residues have become increasingly prevalent during Summer and Autumn 2022, with combinations showing increased fitness. The most likely reason for this convergence is the selective pressure exerted by previous infection- or vaccine-elicited immunity. Such accelerated evolution has caused failure of all anti-Spike monoclonal antibodies, including bebtelovimab and cilgavimab. While we are learning how fast coronaviruses can mutate and recombine, we should reconsider opportunities for economically sustainable escape-proof combination therapies, and refocus antibody-mediated therapeutic efforts on polyclonal preparations that are less likely to allow for viral immune escape.

[Lessons learned in the Covid-19 pandemic: Novel approaches to respiratory disease prevention] / Lecciones aprendidas en la pandemia de Covid-19: Nuevas perspectivas en prevención de enfermedades respiratorias.

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When shared concept cells support associations: Theory of overlapping memory engrams.

Assemblies of neurons, called concepts cells, encode acquired concepts in human Medial Temporal Lobe. Those concept cells that are shared between two assemblies have been hypothesized to encode associations between concepts. Here we test this hypothesis in a computational model of attractor neural networks. We find that for concepts encoded in sparse neural assemblies there is a minimal fraction cmin of neurons shared between assemblies below which associations cannot be reliably implemented; and a maximal fraction cmax of shared neurons above which single concepts can no longer be retrieved. In the presence of a periodically modulated background signal, such as hippocampal oscillations, recall takes the form of association chains reminiscent of those postulated by theories of free recall of words. Predictions of an iterative overlap-generating model match experimental data on the number of concepts to which a neuron responds.

COVID-19 mitigation by digital contact tracing and contact prevention (app-based social exposure warnings).

A plethora of measures are being combined in the attempt to reduce SARS-CoV-2 spread. Due to its sustainability, contact tracing is one of the most frequently applied interventions worldwide, albeit with mixed results. We evaluate the performance of digital contact tracing for different infection detection rates and response time delays. We also introduce and analyze a novel strategy we call contact prevention, which emits high exposure warnings to smartphone users according to Bluetooth-based contact counting. We model the effect of both strategies on transmission dynamics in SERIA, an agent-based simulation platform that implements population-dependent statistical distributions. Results show that contact prevention remains effective in scenarios with high diagnostic/response time delays and low infection detection rates, which greatly impair the effect of traditional contact tracing strategies. Contact prevention could play a significant role in pandemic mitigation, especially in developing countries where diagnostic and tracing capabilities are inadequate. Contact prevention could thus sustainably reduce the propagation of respiratory viruses while relying on available technology, respecting data privacy, and most importantly, promoting community-based awareness and social responsibility. Depending on infection detection and app adoption rates, applying a combination of digital contact tracing and contact prevention could reduce pandemic-related mortality by 20-56%.

A simple metric to study the mechanisms generating event-related potentials.

BACKGROUND: There is an active debate about the mechanism underlying the generation of event-related potentials, and, particularly, whether these are generated by additive components, independent of the background EEG, or the phase-resetting of ongoing oscillations. METHOD: We present a new metric to evaluate trial-by-trial covariations of successive ERP components. Our main assumption is that if two successive ERP components are generated by phase-resetting of a unitary oscillation, they should be time-locked to each other and their single-trial latencies should covary. In contrast, if the components are generated by independent additive components, single-trial latency covariations should not be observed. To quantify the covariance between the single-trial latencies, we define a metric based on latency-corrected averages, which we applied to both simulated and real ERPs. RESULTS: For the simulated data, there was a clear distinction in latency covariation between the ERPs generated with unitary phase-resetting versus additive models. For real visual and auditory ERPs, we observed a lack of latency covariation of successive components. COMPARISON WITH EXISTING METHODS: The new metric is complementary to other approaches to study the mechanisms underlying ERP generation, and does not suffer from potential caveats due to filtering artifacts. Moreover, the method proved to be more sensitive than another estimation of single-trial latency covariations using the cross-correlation function. CONCLUSION: The observed lack of latency covariation shows the presence of parallel, independent processing within each cortical sensory pathway.

COVID-19 ¿Una Oportunidad O Un Retraso Para La Educación Médica De Pregrado? / COVID-19 an oportunnity or a disaster for undergraduate medical education?

La presente carta al editor expresa una opinión novedosa sobre las perspectivas sobre la educación me´dica de pregrado durante la pandemia del COVID-19. Hace un repaso sobre la educación médica tradicional y sobre los beneficios y perjuicios de los nuevos modelos educacionales, como la telemedicina.

This letter expresses a novel opinion on the prospects for undergraduate medical education during the COVID-19 pandemic. It reviews traditional medical education and the benefits and harms of new educational models, such as telemedicine.

No Pattern Separation in the Human Hippocampus.

Pattern separation is a basic principle of neuronal coding that precludes memory interference in the hippocampus. Its existence is supported by numerous theoretical, computational, and experimental findings in different species. However, I argue that recent evidence from single-neuron recordings suggests that pattern separation may not be present in the human hippocampus and that memories are instead coded by the coactivation of invariant and context-independent engrams. This alternative model prompts a reassessment of the definition of episodic memory and its distinction from semantic memory. Furthermore, I propose that a lack of pattern separation in memory coding may have profound implications that could explain cognitive abilities that are uniquely developed in humans, such as our power of generalization and of creative and abstract thinking.

Searching for the neural correlates of human intelligence.

In this My Word, Rodrigo Quian Quiroga discusses neural mechanisms underlying human memory and uniquely human cognitive abilities.

Single Neuron Coding of Identity in the Human Hippocampal Formation.

Experimental findings show the ubiquitous presence of graded responses and tuning curves in the neocortex, particularly in visual areas [1-15]. Among these, inferotemporal-cortex (IT) neurons respond to complex visual stimuli, but differences in the neurons' responses can be used to distinguish the stimuli eliciting the responses [8, 9, 16-18]. The IT projects directly to the medial temporal lobe (MTL) [19], where neurons respond selectively to different pictures of specific persons and even to their written and spoken names [20-22]. However, it is not clear whether this is done through a graded coding, as in the neocortex, or a truly invariant code, in which the response-eliciting stimuli cannot be distinguished from each other. To address this issue, we recorded single neurons during the repeated presentation of different stimuli (pictures and written and spoken names) corresponding to the same persons. Using statistical tests and a decoding approach, we found that only in a minority of cases can the different pictures of a given person be distinguished from the neurons' responses and that in a larger proportion of cases, the responses to the pictures were different to the ones to the written and spoken names. We argue that MTL neurons tend to lack a representation of sensory features (particularly within a sensory modality), which can be advantageous for the memory function attributed to this area [23-25], and that a full representation of memories is given by a combination of mostly invariant coding in the MTL with a representation of sensory features in the neocortex.

Plugging in to Human Memory: Advantages, Challenges, and Insights from Human Single-Neuron Recordings.

We describe single-neuron recordings in the human hippocampal formation, performed in epileptic patients for clinical reasons, and highlight their advantages, challenges, and limitations compared with non-invasive recordings in humans and invasive recordings in animals. We propose a unified framework to explain different findings-responses to novel stimuli, spatial locations, and specific concepts-linking the rodent and human literature regarding the function of the hippocampal formation. Moreover, we propose a model of how memories are encoded in this area, suggesting that the context-independent, invariant coding by concept cells may provide a uniquely human neural mechanism underlying memory representations.

Bioinformatic Identification of Functionally and Structurally Relevant Residues and Motifs in Protein S-Acyltransferases.

DHHC palmitoyltransferases (DHHC-PATs) are very peculiar in that, outside the DHHC domain, they are very divergent even across orthologs from closely related species. This represents a challenge for the bioinformatic analyses of these proteins. Sequence-based analyses and predictions require a valid sequence alignment, which for this family of proteins requires extensive manual curation and this is difficult to attain for the nonspecialist. Here we present a simple method for the in silico analysis of the sequence of a particular PAT, that would allow for the identification of important structural features and functional residues in a PAT or PAT family.