Subjective memory complaints in young people; their relationship withobjective cognitive performance and the role of neuroticism / Quejas subjetivas de memoria en jóvenes; su relación con el rendimiento cognitivo objetivo y el papel del neuroticismo

Las percepciones de olvidos recurrentes o episodios de distracción en la vida diaria se denominan quejas subjetivas de memoria (QSM). Su naturaleza se ha estudiado ampliamente en adultos mayores, pero su importancia y relación con el rendimiento neurocognitivo no se han abordado por completo en adultos más jóvenes. Se han sugerido algunos rasgos psicológicos como posibles moderadores de la asociación entre el rendimiento de la memoria objetiva y subjetiva. El primer objetivo de este estudio fue analizar la correspondencia entre la percepción objetiva y subjetiva de los fallos de memoria en jóvenes. En segundo lugar, estudiamos si el rasgo psicológico del neuroticismo podría estar influyendo en esta relación. Para ello, medimos QSM, diferentes dominios cognitivos (memoria episódica y de trabajo y funciones ejecutivas) y neuroticismo en 80 hombres y mujeres jóvenes. Los resultados mostraron que solo la memoria episódica inmediata estaba estadísticamente relacionada con los QSM. Curiosamente, las relaciones negativas entre el rendimiento de la memoria objetiva y subjetiva solo aparecieron en participantes con mayor neuroticismo. Por lo tanto, las quejas de memoria reportadas por los jóvenes podrían reflejar un peor rendimiento de la memoria episódica inmediata, mientras que el neuroticismo jugaría un papel principal en la asociación entre los déficits de memoria y las QSM. Este estudio proporciona datos que pueden ayudar a comprender mejor las QSM en los jóvenes.(AU)

Perceptions of recurrent forgetfulness or episodes of distraction in daily life are referred to as subjective memory complaints (SMCs). Their nature has been extensively studied in older adults, but their significance and relationship with neurocognitive performance have not been fully ad-dressed in younger adults. Some psychological traits have been suggested as possible moderators of the association between objective and subjective memory performance. The first aim of this study was to analyze the corre-spondence between the objective and subjective perception of memory failures in young people. Second, we studied whether the psychological trait of neuroticism could be influencing this relationship. Todo this, we measured SMCs, different cognitive domains (episodic and working memory and executive functions), and neuroticism in 80 young men and women. Results showed that only immediate episodic memory was statisti-cally related to SMCs. Interestingly, the negative relationships between ob-jective and subjective memory performance only appeared in participants with higher neuroticism. Thus, memory complaints reported by young people could reflect poorer immediate episodic memory performance, whereas neuroticism would play a main role in the association between memory deficits and SMCs. This study provides data that can help to bet-ter understand SMCs in young people.(AU)

Affective music during episodic memory recollection modulates subsequent false emotional memory traces: an fMRI study.

Music is a powerful medium that influences our emotions and memories. Neuroscience research has demonstrated music's ability to engage brain regions associated with emotion, reward, motivation, and autobiographical memory. While music's role in modulating emotions has been explored extensively, our study investigates whether music can alter the emotional content of memories. Building on the theory that memories can be updated upon retrieval, we tested whether introducing emotional music during memory recollection might introduce false emotional elements into the original memory trace. We developed a 3-day episodic memory task with separate encoding, recollection, and retrieval phases. Our primary hypothesis was that emotional music played during memory recollection would increase the likelihood of introducing novel emotional components into the original memory. Behavioral findings revealed two key outcomes: 1) participants exposed to music during memory recollection were more likely to incorporate novel emotional components congruent with the paired music valence, and 2) memories retrieved 1 day later exhibited a stronger emotional tone than the original memory, congruent with the valence of the music paired during the previous day's recollection. Furthermore, fMRI results revealed altered neural engagement during story recollection with music, including the amygdala, anterior hippocampus, and inferior parietal lobule. Enhanced connectivity between the amygdala and other brain regions, including the frontal and visual cortex, was observed during recollection with music, potentially contributing to more emotionally charged story reconstructions. These findings illuminate the interplay between music, emotion, and memory, offering insights into the consequences of infusing emotional music into memory recollection processes.

Identification of Methamphetamine Abusers Can Be Supported by EEG-Based Wavelet Transform and BiLSTM Networks.

Methamphetamine (MA) is a neurological drug, which is harmful to the overall brain cognitive function when abused. Based on this property of MA, people can be divided into those with MA abuse and healthy people. However, few studies to date have investigated automatic detection of MA abusers based on the neural activity. For this reason, the purpose of this research was to investigate the difference in the neural activity between MA abusers and healthy persons and accordingly discriminate MA abusers. First, we performed event-related potential (ERP) analysis to determine the time range of P300. Then, the wavelet coefficients of the P300 component were extracted as the main features, along with the time and frequency domain features within the selected P300 range to classify. To optimize the feature set, F_score was used to remove features below the average score. Finally, a Bidirectional Long Short-term Memory (BiLSTM) network was performed for classification. The experimental result showed that the detection accuracy of BiLSTM could reach 83.85%. In conclusion, the P300 component of EEG signals of MA abusers is different from that in normal persons. Based on this difference, this study proposes a novel way for the prevention and diagnosis of MA abuse.

Decomposing the multiple encoding benefit in visual long-term memory: Primary contributions by the number of encoding opportunities.

Although access to the seemingly infinite capacity of our visual long-term memory (VLTM) can be restricted by visual working memory (VWM) capacity at encoding and retrieval, access can be improved with repeated encoding. This leads to the multiple encoding benefit (MEB), the finding that VLTM performance improves as the number of opportunities to encode the same information increases over time. However, as the number of encoding opportunities increases, so do other factors such as the number of identical encoded VWM representations and chances to engage in successful retrieval during each opportunity. Thus, across two experiments, we disentangled the contributions of each of these factors to the MEB by having participants encode a varying number of identical objects across multiple encoding opportunities. Along with behavioural data, we also examined two established EEG correlates that track the number of maintained VWM representations, namely the posterior alpha suppression and the negative slow wave. Here, we identified that the primary mechanism behind the MEB was the number of encoding opportunities. That is, recognition memory performance was higher following an increase in the number of encoding opportunities, and this could not be attributed solely to an increase in the number of encoded VWM representations or successful retrieval. Our results thus contribute to the understanding of the fundamental mechanisms behind the influence of VWM on VLTM encoding.

Variation in encoding context benefits item recognition.

The current study assesses whether varying the encoding context of a repeated event is a potential strategy to improve recognition memory across retrieval contexts. Context variability, also known as encoding variability, has historically been investigated primarily using recall and cued recall tasks, with the consensus being that encoding variability is not necessarily beneficial for episodic retrieval. However, recent studies (see text) suggest that test type may determine the strategy's effectiveness. Aligned with these recent findings, we found consistent benefits to simple item recognition when a word was studied in more variable contexts compared to less variable contexts across four experiments. This main effect of context variability occurred when crossed with a manipulation of repetition spacing and when crossed with a manipulation of encoding-retrieval context match. Variation in encoding contexts beyond the future retrieval context led to better item recognition than repeated study exposures within the future retrieval context. We argue that the current study and other recent findings indicate a need to re-evaluate the historical consensus on encoding variability as a beneficial strategy for learning.

Reduced benefit from long-term item frequency contributes to short-term memory deficits in dyslexia.

Dyslexia, a specific difficulty in acquiring proficient reading, is also characterized by reduced short-term memory (STM) capacity. Extensive research indicates that individuals with developmental dyslexia (IDDs) benefit less from exposure, and this hampers their long-term knowledge accumulation. It is well established that long-term knowledge has a great effect on performance in STM tasks, and thus IDDs' reduced benefit of exposure could potentially reduce their relative performance in such tasks, especially when frequent items, such as digit-words, are used. In this study we used a standard, widely used, STM assessment: the Digit Span subtest from the Wechsler Adult Intelligence Scale. The task was conducted twice: in native language and in second language. As exposure to native language is greater than exposure to second language, we predicted that IDDs' performance in the task administered in native language will reveal a larger group difference as compared to second language, due to IDDs' reduced benefit of item frequency. The prediction was confirmed, in line with the hypothesis that reduced STM in dyslexia to a large extent reflects reduced benefits from long-term item frequency and not a reduced STM per se.

Precision Mapping of the Default Network Reveals Common and Distinct (Inter)activity for Autobiographical Memory and Theory of Mind.

The default network is widely implicated as a common neural substrate for self-generated thought, such as remembering one's past (autobiographical memory) and imagining the thoughts and feelings of others (theory of mind). Findings that the default network comprises subnetworks of regions - some commonly and some distinctly involved across processes - suggest that one's own experiences inform their understanding of others. With the advent of precision fMRI methods, however, it is unclear if this shared substrate is observed instead due to traditional group analysis methods. We investigated this possibility using a novel combination of methodological strategies. Twenty-three participants underwent multi-echo resting-state and task fMRI. We used their resting-state scans to conduct cortical parcellation sensitive to individual variation but preserving our ability to conduct group analysis. Using multivariate analyses, we assessed the functional activation and connectivity profiles of default network regions while participants engaged in autobiographical memory, theory of mind, or a sensorimotor control condition. Across the default network, we observed stronger activity associated with both autobiographical memory and theory of mind compared to the control condition. Nonetheless, we also observed that some regions showed preferential activity to either experimental condition, in line with past work. The connectivity results similarly indicated shared and distinct functional profiles. Our results support that autobiographical memory and theory of mind - two theoretically important and widely-studied domains of social cognition - evoke common and distinct aspects of the default network even when ensuring high fidelity to individual-specific characteristics.

Hyperexcitation of the glutamatergic neurons in lateral hypothalamus induced by chronic pain contributes to depression-like behavior and learning and memory impairment in male mice.

Chronic pain can induce mood disorders and cognitive dysfunctions, such as anxiety, depression, and learning and memory impairment in humans. However, the specific neural network involved in anxiety- and depression-like behaviors and learning and memory impairment caused by chronic pain remains poorly understood. In this study, behavioral test results showed that chronic pain induced anxiety- and depression-like behaviors, and learning and memory impairment in male mice. c-Fos immunofluorescence and fiber photometry recording showed that glutamatergic neurons in the LH of mice with chronic pain were selectively activated. Next, the glutamatergic neurons of LH in normal mice were activated using optogenetic and chemogenetic methods, which recapitulates some of the depressive-like behaviors, as well as memory impairment, but not anxiety-like behavior. Finally, inhibition of glutamatergic neurons in the LH of mice with chronic pain, effectively relieved anxiety- and depression-like behaviors and learning and memory impairment. Taken together, our findings suggest that hyperexcitation of glutamatergic neurons in the LH is involved in depression-like behavior and learning and memory impairment induced by chronic pain.

Identification of Escherichia coli strains using MALDI-TOF MS combined with long short-term memory neural networks.

The current study aims to develop a new technique for the precise identification of Escherichia coli strains, utilizing matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) combined with a long short-term memory (LSTM) neural network. A total of 48 Escherichia coli strains were isolated and cultured on tryptic soy agar medium for 24 hours for the generation of MALDI-TOF MS spectra. Eight hundred MALDI-TOF MS spectra were obtained per strain, resulting in a database of 38,400 spectra. Fifty percent of the data was utilized for LSTM neural network training, with fine-tuned parameters for strain-level identification. The other half served as the test set to assess model performance. Traditional PCA dimension reduction of MALDI-TOF MS spectra indicated 47 out of 48 strains to be unclassifiable. In contrast, the LSTM neural network demonstrated remarkable efficacy. After 20 training epochs, the model achieved a loss value of 0.0524, an accuracy of 0.999, a precision of 0.985, and a recall of 0.982. When tested on the unseen data, the model attained an overall accuracy of 92.24%. The integration of MALDI-TOF MS and LSTM neural network markedly enhances the identification of Escherichia coli strains. This innovative approach offers an effective and accurate tool for MALDI-TOF MS-based strain-level identification, thus expanding the analytical capabilities of microbial diagnostics.

Effect of berberine on the hippocampal structure, biochemical factors, memory, and blood-brain barrier in rat model of transient global cerebral ischemia.

Global cerebral ischemia (GCI) results in damage to the neurons and leads to cognitive impairments. Berberine (BBR) is known for its neuroprotective qualities. This study aimed to investigate the effects of BBR on memory, Blood-brain barrier (BBB) permeability, biochemical factors, and neuronal structure. Sixty-three adult male Wistar rats were divided randomly into Sham (21), GCI (21), and GCI + BBR (21) groups. The GCI + BBR group received 50 mg/kg of BBR for 7 days before and 6 h after 20 min of GCI induction. After 24 h, assessments included hippocampal neuronal structure, catalase (CAT), superoxide dismutase (SOD), malondialdehyde (MDA), and glutathione peroxidase (GPX) levels, memory performance, and BBB permeability. The GCI + BBR group reduced volume loss in the CA1 and its sublayers (oriens, pyramidal, and radiatum) compared to the GCI group (p < 0.0001, p < 0.001, p < 0.01 and p < 0.001, respectively). Additionally, the GCI + BBR group showed higher pyramidal neuron density (p < 0.0001) and number (p < 0.0001) compared to the GCI group. BBR also decreased MDA levels (p < 0.0001) and increased CAT activity (p < 0.0001) in the GCI + BBR group compared to the GCI group, with GPX and SOD activity approaching Sham levels (p < 0.0001, both). BBR demonstrated significant improvements in short and long-term memory compared to the GCI group (p < 0.01, p < 0.0001, respectively). Furthermore, BBB permeability in the GCI + BBR group was significantly reduced compared to the GCI group (p < 0.0001). These findings demonstrated BBR's potential to protect the neurons in the CA1 and BBB structures, enhance antioxidant activity, and alleviate GCI-induced memory impairments.

The dual nature of working memory deficits: methamphetamine abusers have more impaired social working memory capacity than canonical working memory capacity.

Social working memory (WM) temporarily retains and manipulates various aspects of social information. Extensive research has highlighted impaired social cognitive functions in individuals with substance addiction. However, the specific deficit in social WM within this population remains notably understudied. Bridging this gap, we investigated social WM capacity using biological motion (BM) stimuli in methamphetamine (MA) abusers compared to an inmate control group, alongside contrasting these findings with their canonical WM deficits. Across two studies, we recruited female MA abusers (N = 80) undergoing post-isolation rehabilitation within a mandatory confinement circumstance. To ensure a pertinent comparison, we recruited female inmates (N = 80) subjected to comparable confinement. Results show substantial BM WM impairment in MA abusers, yet non-BM WM remains mostly intact. These findings highlight a pronounced social WM deficit in MA abusers, surpassing their canonical WM deficit relative to inmate controls. This suggests a distinct dissociation between social and canonical WM processing.

Differential spatial working memory-related functional network reconfiguration in young and older adults.

Functional brain networks have preserved architectures in rest and task; nevertheless, previous work consistently demonstrated task-related brain functional reorganization. Efficient rest-to-task functional network reconfiguration is associated with better cognition in young adults. However, aging and cognitive load effects, as well as contributions of intra- and internetwork reconfiguration, remain unclear. We assessed age-related and load-dependent effects on global and network-specific functional reconfiguration between rest and a spatial working memory (SWM) task in young and older adults, then investigated associations between functional reconfiguration and SWM across loads and age groups. Overall, global and network-level functional reconfiguration between rest and task increased with age and load. Importantly, more efficient functional reconfiguration associated with better performance across age groups. However, older adults relied more on internetwork reconfiguration of higher cognitive and task-relevant networks. These reflect the consistent importance of efficient network updating despite recruitment of additional functional networks to offset reduction in neural resources and a change in brain functional topology in older adults. Our findings generalize the association between efficient functional reconfiguration and cognition to aging and demonstrate distinct brain functional reconfiguration patterns associated with SWM in aging, highlighting the importance of combining rest and task measures to study aging cognition.

Brain networks identified by functional connectivity (FC) have preserved architectures from rest to task and across task demands. Higher similarity, implying more efficient network reconfiguration, was associated with better cognition and task performance in young adults. To examine how it may be influenced by aging, we compared whole-brain and network-level FC similarities between resting-state and spatial working memory fMRI in young and older adults. At whole-brain level and higher order cognitive networks, older adults evidenced less efficient network reconfiguration from rest to task than young adults. Importantly, more efficient reconfiguration was associated with better accuracy. This relationship relied more on internetwork connections in older adults. Despite reduced neural resources compared to young, maintaining efficient network updating still contributes to better cognition at older age.

Mutual learning with memory for semi-supervised pest detection.

Effectively monitoring pest-infested areas by computer vision is essential in precision agriculture in order to minimize yield losses and create early scientific preventative solutions. However, the scale variation, complex background, and dense distribution of pests bring challenges to accurate detection when utilizing vision technology. Simultaneously, supervised learning-based object detection heavily depends on abundant labeled data, which poses practical difficulties. To overcome these obstacles, in this paper, we put forward innovative semi-supervised pest detection, PestTeacher. The framework effectively mitigates the issues of confirmation bias and instability among detection results across different iterations. To address the issue of leakage caused by the weak features of pests, we propose the Spatial-aware Multi-Resolution Feature Extraction (SMFE) module. Furthermore, we introduce a Region Proposal Network (RPN) module with a cascading architecture. This module is specifically designed to generate higher-quality anchors, which are crucial for accurate object detection. We evaluated the performance of our method on two datasets: the corn borer dataset and the Pest24 dataset. The corn borer dataset encompasses data from various corn growth cycles, while the Pest24 dataset is a large-scale, multi-pest image dataset consisting of 24 classes and 25k images. Experimental results demonstrate that the enhanced model achieves approximately 80% effectiveness with only 20% of the training set supervised in both the corn borer dataset and Pest24 dataset. Compared to the baseline model SoftTeacher, our model improves mAP @0.5 (mean Average Precision) at 7.3 compared to that of SoftTeacher at 4.6. This method offers theoretical research and technical references for automated pest identification and management.

A deep learning approach for diagnosis of schizophrenia disorder via data augmentation based on convolutional neural network and long short-term memory.

Schizophrenia (SZ) is a severe, chronic mental disorder without specific treatment. Due to the increasing prevalence of SZ in societies and the similarity of the characteristics of this disease with other mental illnesses such as bipolar disorder, most people are not aware of having it in their daily lives. Therefore, early detection of this disease will allow the sufferer to seek treatment or at least control it. Previous SZ detection studies through machine learning methods, require the extraction and selection of features before the classification process. This study attempts to develop a novel, end-to-end approach based on a 15-layers convolutional neural network (CNN) and a 16-layers CNN- long short-term memory (LSTM) to help psychiatrists automatically diagnose SZ from electroencephalogram (EEG) signals. The deep model uses CNN layers to learn the temporal properties of the signals, while LSTM layers provide the sequence learning mechanism. Also, data augmentation method based on generative adversarial networks is employed over the training set to increase the diversity of the data. Results on a large EEG dataset show the high diagnostic potential of both proposed methods, achieving remarkable accuracy of 98% and 99%. This study shows that the proposed framework is able to accurately discriminate SZ from healthy subject and is potentially useful for developing diagnostic tools for SZ disorder.

Modeling the contribution of theta-gamma coupling to sequential memory, imagination, and dreaming.

Gamma oscillations nested in a theta rhythm are observed in the hippocampus, where are assumed to play a role in sequential episodic memory, i.e., memorization and retrieval of events that unfold in time. In this work, we present an original neurocomputational model based on neural masses, which simulates the encoding of sequences of events in the hippocampus and subsequent retrieval by exploiting the theta-gamma code. The model is based on a three-layer structure in which individual Units oscillate with a gamma rhythm and code for individual features of an episode. The first layer (working memory in the prefrontal cortex) maintains a cue in memory until a new signal is presented. The second layer (CA3 cells) implements an auto-associative memory, exploiting excitatory and inhibitory plastic synapses to recover an entire episode from a single feature. Units in this layer are disinhibited by a theta rhythm from an external source (septum or Papez circuit). The third layer (CA1 cells) implements a hetero-associative net with the previous layer, able to recover a sequence of episodes from the first one. During an encoding phase, simulating high-acetylcholine levels, the network is trained with Hebbian (synchronizing) and anti-Hebbian (desynchronizing) rules. During retrieval (low-acetylcholine), the network can correctly recover sequences from an initial cue using gamma oscillations nested inside the theta rhythm. Moreover, in high noise, the network isolated from the environment simulates a mind-wandering condition, randomly replicating previous sequences. Interestingly, in a state simulating sleep, with increased noise and reduced synapses, the network can "dream" by creatively combining sequences, exploiting features shared by different episodes. Finally, an irrational behavior (erroneous superimposition of features in various episodes, like "delusion") occurs after pathological-like reduction in fast inhibitory synapses. The model can represent a straightforward and innovative tool to help mechanistically understand the theta-gamma code in different mental states.

Bridging Neuroscience and AI: Environmental Enrichment as a Model for Forward Knowledge Transfer.

Continual learning (CL) refers to an agent's capability to learn from a continuous stream of data and transfer knowledge without forgetting old information. One crucial aspect of CL is forward transfer, i.e., improved and faster learning on a new task by leveraging information from prior knowledge. While this ability comes naturally to biological brains, it poses a significant challenge for artificial intelligence (AI). Here, we suggest that environmental enrichment (EE) can be used as a biological model for studying forward transfer, inspiring human-like AI development. EE refers to animal studies that enhance cognitive, social, motor, and sensory stimulation and is a model for what, in humans, is referred to as 'cognitive reserve'. Enriched animals show significant improvement in learning speed and performance on new tasks, typically exhibiting forward transfer. We explore anatomical, molecular, and neuronal changes post-EE and discuss how artificial neural networks (ANNs) can be used to predict neural computation changes after enriched experiences. Finally, we provide a synergistic way of combining neuroscience and AI research that paves the path toward developing AI capable of rapid and efficient new task learning.

Multi-step ahead forecasting of electrical conductivity in rivers by using a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model enhanced by Boruta-XGBoost feature selection algorithm.

Electrical conductivity (EC) is widely recognized as one of the most essential water quality metrics for predicting salinity and mineralization. In the current research, the EC of two Australian rivers (Albert River and Barratta Creek) was forecasted for up to 10 days using a novel deep learning algorithm (Convolutional Neural Network combined with Long Short-Term Memory Model, CNN-LSTM). The Boruta-XGBoost feature selection method was used to determine the significant inputs (time series lagged data) to the model. To compare the performance of Boruta-XGB-CNN-LSTM models, three machine learning approaches-multi-layer perceptron neural network (MLP), K-nearest neighbour (KNN), and extreme gradient boosting (XGBoost) were used. Different statistical metrics, such as correlation coefficient (R), root mean square error (RMSE), and mean absolute percentage error, were used to assess the models' performance. From 10 years of data in both rivers, 7 years (2012-2018) were used as a training set, and 3 years (2019-2021) were used for testing the models. Application of the Boruta-XGB-CNN-LSTM model in forecasting one day ahead of EC showed that in both stations, Boruta-XGB-CNN-LSTM can forecast the EC parameter better than other machine learning models for the test dataset (R = 0.9429, RMSE = 45.6896, MAPE = 5.9749 for Albert River, and R = 0.9215, RMSE = 43.8315, MAPE = 7.6029 for Barratta Creek). Considering the better performance of the Boruta-XGB-CNN-LSTM model in both rivers, this model was used to forecast 3-10 days ahead of EC. The results showed that the Boruta-XGB-CNN-LSTM model is very capable of forecasting the EC for the next 10 days. The results showed that by increasing the forecasting horizon from 3 to 10 days, the performance of the Boruta-XGB-CNN-LSTM model slightly decreased. The results of this study show that the Boruta-XGB-CNN-LSTM model can be used as a good soft computing method for accurately predicting how the EC will change in rivers.

Metabolic requirements of CD160 expressing memory-like NK cells in Gram-negative bacterial infection.

Objective: Unique metabolic requirements accompany the development and functional fates of immune cells. How cellular metabolism is important in natural killer (NK) cells and their memory-like differentiation in bacterial infections remains elusive. Methods: Here, we utilise our established NK cell memory assay to investigate the metabolic requirement for memory-like NK cell formation and function in response to the Gram-negative intracellular bacteria Burkholderia pseudomallei (BP), the causative agent of melioidosis. Results: We demonstrate that CD160+ memory-like NK cells upon BP stimulation upregulate glucose and amino acid transporters in a cohort of recovered melioidosis patients which is maintained at least 3-month post-hospital admission. Using an in vitro assay, human BP-specific CD160+ memory-like NK cells show metabolic priming including increased expression of glucose and amino acid transporters with elevated glucose uptake, increased mTOR activation and mitochondrial membrane potential upon BP re-stimulation. Antigen-specific and cytokine-induced IFN-γ production of this memory-like NK cell subset are highly dependent on oxidative phosphorylation (OXPHOS) with some dependency on glycolysis, whereas the formation of CD160+ memory-like NK cells in vitro is dependent on fatty acid oxidation and OXPHOS and further increased by metformin. Conclusion: This study reveals the link between metabolism and cellular function of memory-like NK cells, which can be exploited for vaccine design and for monitoring protection against Gram-negative bacterial infection.

Episodic memory improvement in illiterate adults attending late-life education irrespective of low socioeconomic status: insights from the PROAME study.

The majority of people with dementia live in low or middle-income countries (LMICs) where resources that play a crucial role in brain health, such as quality education, are still not widely available. In Brazil, illiteracy remains a prevalent issue, especially in communities with lower socioeconomic status (SES). The PROAME study set out to explore basic education in illiterate adults as a means to improve cognitive reserve. Objective: This manuscript aims to explore the relationship between SES and learning, as well as cognitive outcomes, in an older illiterate population. Methods: This six-month clinical trial (NCT04473235) involved 108 participants, of which 77 concluded all assessments, enrolled in late-life basic education. SES assessments included Quality of Urban Living Index, Municipal Human Development Index and Household SES calculated for each participant. Cognitive assessments encompassed the Free and Cued Selective Reminding Test (FCSRT), a word list to assess reading, and the Beta III matrix. Results: The sample consisted primarily of women, with a mean age of 58.5. Participants improved their reading (p=0.01) and their FCSRT (p=0.003). Regarding episodic memory, women outperformed men (p=0.007) and younger participants improved more than their older counterparts (p=0.001). There was no association observed between SES and cognitive outcomes. Conclusion: Irrespective of SES, participants demonstrated positive outcomes after attending basic education. These findings highlight that late life education could be an important non-pharmacologic preventative measure, especially in LMICs.

A maioria das pessoas com demência vive em países de baixa/média renda, onde recursos essenciais para a saúde cerebral, como educação de qualidade, ainda não são amplamente acessíveis. No Brasil, o analfabetismo ainda é frequente, especialmente em comunidades de baixo nível socioeconômico. O estudo PROAME teve como objetivo explorar a educação básica tardia em pessoas analfabetas como ferramenta para o aumento da reserva cognitiva. Objetivo: Investigar a relação entre nível socioeconômico com aprendizado e com desempenho em testes cognitivos, em adultos analfabetos. Métodos: Este estudo clínico de seis meses (NCT04473235) contou com 108 participantes inscritos no projeto Educação para Jovens e Adultos (EJA), dos quais 77 completaram os testes. O nível socioeconômico de cada participante foi medido usando-se: o Índice de Qualidade de Vida Urbana, o Índice de Desenvolvimento Humano Municipal e o nível socioeconômico doméstico. Avaliações cognitivas incluíram: o Teste de Recordação Seletiva Livre e Guiada (TRSLG), uma lista de palavras para avaliar leitura e a matriz Beta III. Resultados: A amostra era predominantemente feminina, com idade média de 58,5. Os participantes melhoraram a leitura (p=0,01) e o TRSLG (p=0,003). Com relação à memoria episódica, as mulheres tiveram resultados superiores aos dos homens (p=0,007) e participantes mais jovens melhoraram mais que seus colegas mais velhos (p=0,001). Não foi observada nenhuma relação entre o nível socioeconômico e o desempenho cognitivo. Conclusão: Independentemente do nível socioeconômico, participantes obtiveram resultados positivos após frequentar a educação básica. Isso sugere que a educação tardia pode ser uma medida preventiva não farmacológica importante, especialmente em países de baixa/média renda.

Peripheral Lymphocyte Changes Associate With the Progression of Necrotizing Enterocolitis in Infants.

INTRODUCTION: Immune factors are important antecedents in the pathophysiology of necrotizing enterocolitis (NEC). However, studies on the peripheral blood lymphocyte subsets changes in NEC patients among different Bell stages and in patients requiring surgery are scarce. METHODS: 34 infants with NEC and 33 age-matched controls were included. Peripheral blood was collected within 48 h after NEC diagnosis. Peripheral blood B and T lymphocytes subsets were detected by 12-color flow cytometry. Cell ratios were calculated, and their relationship to disease severity and their roles as indicators for surgery were assessed. RESULTS: NEC patients showed elevated percentages of unSwB cells (CD27+IgD+ unswitched memory/activated B cells)/B cells, SwB cells (CD27+IgD-switched memory B cells)/B cells, CD8+ T (CD3+CD8+ T cells)/T cells, Tem (CD45RA-CCR7-effector memory T cells)/CD4+ T cells, Tem/CD8+ T cells and decreased Bn (CD27-IgD+ naïve B cells)/B cells, CD4+T (CD3+CD4+ T cells)/T cells, CD45RA+ CCR7+ naïve T cells (CD45RA+CCR7+ naïve T cells)/CD8+T cells. Compared to NEC patients at BELL stage I + II, patients at BELL stage III showed increased percentages of SwB cells/B cells, antibody secreting cell (ASC, CD3-CD20-CD27high CD38high ASCs)/B cells and Tem/CD4+ T cells, and decreased percentages of CD45RA+CCR7+ naïve T cells/CD4+ T cells. The Receiver Operating Characteristic Curve analysis showed that the sensitivity of ASC/B cells ratio (0.52%) is 86.67% and the specificity of Tem/CD4+T ratio (5.22%) is 100%, indicating that NEC patients required surgery. CONCLUSIONS: The severity of NEC exhibits codirectional changes with the maturation of B and T lymphocytes, especially CD4+ T cells. The increased ASC/B and Tem/CD4+ T cells could serve as potential indicators for NEC patients requiring surgery.