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INTRODUCTION: Argentina authorized COVID-19 vaccination for adolescents 12 years and older in August 2021, and then for children three years and older in October 2021. Children aged 6 months-2 years received a two-dose regimen beginning July 2022. OBJECTIVE: This study aims to analyze the impact of COVID-19 vaccination among children aged 0-17, considering vaccination status and mortality for the 2020-2022 period. METHODS: We conducted a population-level analysis examining all-cause mortality, COVID-19 cases, deaths, and vaccination records. We compared outcomes with child mortality for diseases for which vaccination is compulsory, before and after each vaccine rollout. RESULTS: A decrease in COVID-19-related deaths was observed in 2022 for pediatric age groups (3-11 and 12-17) with relatively higher vaccination coverage. However, no decrease was observed for the 0-2 year old age group, which had the longest delay in access to immunization and lowest vaccination coverage. When compared to unvaccinated populations in 2022, we observe an 8-15-fold reduction in cumulative death rates for pediatric populations vaccinated with 1 or more doses, and a 16-18-fold reduction for those vaccinated with 2 or more doses. Historical analysis shows that for diseases for which vaccination is now compulsory in many countries, pre-vaccine-rollout mortality was lower than COVID-19 deaths during 2020-2022. CONCLUSIONS AND RELEVANCE: SARS-CoV-2 immunization was associated with reduced COVID-19 deaths for children and adolescents in Argentina. Our findings suggest that greater efforts should be undertaken to ensure wider COVID-19 vaccine coverage in children and adolescents, especially infants.
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Classical scoring functions may exhibit low accuracy in determining ligand binding affinity for proteins. The availability of both protein-ligand structures and affinity data make it possible to develop machine-learning models focused on specific protein systems with superior predictive performance. Here, we report a new methodology named SAnDReS that combines AutoDock Vina 1.2 with 54 regression methods available in Scikit-Learn to calculate binding affinity based on protein-ligand structures. This approach allows exploration of the scoring function space. SAnDReS generates machine-learning models based on crystal, docked, and AlphaFold-generated structures. As a proof of concept, we examine the performance of SAnDReS-generated models in three case studies. For all three cases, our models outperformed classical scoring functions. Also, SAnDReS-generated models showed predictive performance close to or better than other machine-learning models such as KDEEP, CSM-lig, and ΔVinaRF20. SAnDReS 2.0 is available to download at https://github.com/azevedolab/sandres.
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Aprendizado de Máquina , Proteínas , Proteínas/química , Proteínas/metabolismo , Ligantes , Software , Simulação de Acoplamento MolecularRESUMO
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.
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Mutação de Sentido Incorreto , Poliendocrinopatias Autoimunes , Criança , Humanos , Proteína AIRE , Mutação , Poliendocrinopatias Autoimunes/genética , Poliendocrinopatias Autoimunes/diagnóstico , Fatores de Transcrição/genética , Fatores de Transcrição/metabolismoRESUMO
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.
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Aprendizagem , Reforço Psicológico , Aprendizagem/fisiologia , Rememoração Mental/fisiologia , Neurônios/fisiologia , Hipocampo/fisiologia , Plasticidade Neuronal/fisiologia , Modelos NeurológicosRESUMO
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.
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Glândulas Endócrinas , Reconhecimento Facial , Feminino , Humanos , Masculino , Neurônios , Encéfalo , Córtex CerebralRESUMO
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.
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Ensaios Clínicos Controlados Aleatórios como Assunto , Diabetes MellitusRESUMO
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.
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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.
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Hipocampo , Memória Episódica , Humanos , Hipocampo/fisiologia , Neurônios/fisiologiaRESUMO
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.
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COVID-19 , SARS-CoV-2 , Humanos , SARS-CoV-2/genética , Pandemias , Glicoproteína da Espícula de Coronavírus/genética , Anticorpos NeutralizantesRESUMO
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.
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Memória/fisiologia , Modelos Neurológicos , Neurônios/citologia , Biologia Computacional , Hipocampo/citologia , Hipocampo/fisiologia , Humanos , Rede Nervosa/citologia , Rede Nervosa/fisiologia , Lobo Temporal/citologia , Lobo Temporal/fisiologiaRESUMO
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%.
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COVID-19/prevenção & controle , Busca de Comunicante/métodos , Smartphone , Humanos , Pandemias/prevenção & controle , SARS-CoV-2/patogenicidadeRESUMO
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.
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Eletroencefalografia , Potenciais Evocados , Artefatos , Humanos , Tempo de ReaçãoRESUMO
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.
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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.
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Hipocampo , Memória Episódica , Hipocampo/fisiologia , Humanos , Neurônios/fisiologiaRESUMO
In this My Word, Rodrigo Quian Quiroga discusses neural mechanisms underlying human memory and uniquely human cognitive abilities.
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Cognição , Inteligência/fisiologia , Memória , Fenômenos Fisiológicos do Sistema Nervoso , Animais , HumanosRESUMO
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.