The formation of memories is a complex, multi-scale phenomenon, especially when it involves integration of information from various brain systems. We have investigated the differences between a novel and consolidated association of spatial cues and amphetamine administration, using an in situ hybridisation method to track the short-term dynamics during the recall testing. We have found that remote recall group involves smaller, but more consolidated groups of neurons, which is consistent with their specialisation. By employing machine learning analysis, we have shown this pattern is especially pronounced in the VTA; furthermore, we also uncovered significant activity patterns in retrosplenial and prefrontal cortices, as well as in the DG and CA3 subfields of the hippocampus. The behavioural propensity towards the associated localisation appears to be driven by the nucleus accumbens, however, further modulated by a trio of the amygdala, VTA and hippocampus, as the trained association is confronted with test experience. Moreover, chemogenetic analysis revealed central amygdala as critical for linking appetitive emotional states with spatial contexts. These results show that memory mechanisms must be modelled considering individual differences in motivation, as well as covering dynamics of the process.

• MeSH
• Amphetamine pharmacology   MeSH
• Amygdala physiology   MeSH
• Hippocampus * physiology   MeSH
• Memory Consolidation * physiology   MeSH
• Rats MeSH
• Brain physiology   MeSH
• Neurons physiology   metabolism   MeSH
• Nucleus Accumbens * physiology   MeSH
• Reward * MeSH
• Memory physiology   MeSH
• Cues MeSH
• Prefrontal Cortex physiology   MeSH
• Mental Recall * physiology   MeSH
• Machine Learning MeSH
• Ventral Tegmental Area * physiology   MeSH
• Animals MeSH
• Check Tag
• Rats MeSH
• Male MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH

Mitochondria are central to cellular energy metabolism, contributing to synaptic transmission and plasticity. The mitochondrial membranes present the cannabinoid type-1 receptor (mito-CB1R), which has been functionally linked to neuronal energy supply and cognitive processing. Prenatal exposure to Δ9-tetrahydrocannabinol (pTHC) has been associated with cognitive impairments associated with molecular cellular and functional abnormalities in several brain regions, including the hippocampus. This study aims at assessing whether, besides the memory impairment, pTHC exposure may result in mitochondrial molecular and functional alterations in the hippocampus of the offspring. Moreover, the assessment of CB1R expression is also carried out as a proxy of CB1 signalling in pTHC-exposed offspring. THC (2 mg/Kg), or vehicle, was administered to the dams from gestational day (GD) 5 to GD20, and the offspring were tested for declarative memory using the Novel Object Recognition test in the L-maze. We also assessed: mitochondrial respiration by high-resolution respirometry; mitochondrial respiratory complex-I subunit NDUFS1 protein levels, and mito-CB1R expression by ELISA. Our results revealed: significant memory impairment in pTHC-exposed offspring; attenuated mitochondrial respiration in the hippocampus alongside a marked reduction in complex-I-subunit NDUFS1; a significant increase in mito-CB1R expression. This is the first evidence of pTHC exposure-induced impairment in memory processing in the offspring that suggests a functional link between an attenuation in mitochondrial bioenergetics and abnormal CB1R signalling in the hippocampus.

• MeSH
• Maze Learning drug effects   MeSH
• Cell Respiration drug effects   MeSH
• Hippocampus * metabolism   drug effects   MeSH
• Rats MeSH
• Mitochondria * metabolism   drug effects   MeSH
• Memory drug effects   MeSH
• Memory Disorders * metabolism   chemically induced   MeSH
• Rats, Wistar MeSH
• Receptor, Cannabinoid, CB1 * metabolism   MeSH
• Pregnancy MeSH
• Dronabinol * toxicity   MeSH
• Prenatal Exposure Delayed Effects * metabolism   chemically induced   MeSH
• Animals MeSH
• Check Tag
• Rats MeSH
• Male MeSH
• Pregnancy MeSH
• Female MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH

Even though cognitive testing in animals is widespread, many issues remain open - for example the influence of behavioural parameters on cognitive performance, stability of cognitive performance upon repeated testing, or comparability of cognitive variables across different tasks (i.e. cross-contextual consistency). In this study we tested thirty six male Long Evans laboratory rats and assessed their cognitive performance in two standard tasks of spatial navigation - Active allothetic place avoidance and Morris water maze test. Using multivariate analyses, we detected different aspects of cognition within these complex tasks (the ability to learn fast, cognitive flexibility, general ability to solve a task successfully). We found that consistency of cognitive performance in these two tasks (estimates of cognitive repeatability) differed substantially, reflecting differences in the experimental procedures. Moreover, we inspected cognitive performance of the animals in more detail by creating a correlation matrix of factors derived from these procedures. Nevertheless, we found no correlation and therefore no indication of a general cognitive ability in spatial navigation using these two tasks. In addition, we found no link between personality and cognition when correlating cognitive performance of the animals with parameters from personality tests, which were derived from a previous study conducted on the same animals. These findings highlight a task-dependent nature of cognitive performance in these two tasks of spatial navigation and suggest that general cognitive ability in spatial navigation may not be reliably inferred from these two tasks, while also indicating no evident link between cognition and personality in this context.

• MeSH
• Maze Learning physiology   MeSH
• Behavior, Animal physiology   MeSH
• Cognition * physiology   MeSH
• Rats MeSH
• Personality physiology   MeSH
• Rats, Long-Evans MeSH
• Spatial Navigation * physiology   MeSH
• Avoidance Learning physiology   MeSH
• Animals MeSH
• Check Tag
• Rats MeSH
• Male MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH

Protein misfolding diseases, including α1-antitrypsin deficiency (AATD), pose substantial health challenges, with their cellular progression still poorly understood1-3. We use spatial proteomics by mass spectrometry and machine learning to map AATD in human liver tissue. Combining Deep Visual Proteomics (DVP) with single-cell analysis4,5, we probe intact patient biopsies to resolve molecular events during hepatocyte stress in pseudotime across fibrosis stages. We achieve proteome depth of up to 4,300 proteins from one-third of a single cell in formalin-fixed, paraffin-embedded tissue. This dataset reveals a potentially clinically actionable peroxisomal upregulation that precedes the canonical unfolded protein response. Our single-cell proteomics data show α1-antitrypsin accumulation is largely cell-intrinsic, with minimal stress propagation between hepatocytes. We integrated proteomic data with artificial intelligence-guided image-based phenotyping across several disease stages, revealing a late-stage hepatocyte phenotype characterized by globular protein aggregates and distinct proteomic signatures, notably including elevated TNFSF10 (also known as TRAIL) amounts. This phenotype may represent a critical disease progression stage. Our study offers new insights into AATD pathogenesis and introduces a powerful methodology for high-resolution, in situ proteomic analysis of complex tissues. This approach holds potential to unravel molecular mechanisms in various protein misfolding disorders, setting a new standard for understanding disease progression at the single-cell level in human tissue.

• MeSH
• alpha 1-Antitrypsin metabolism   MeSH
• Single-Cell Analysis MeSH
• alpha 1-Antitrypsin Deficiency * pathology   metabolism   genetics   MeSH
• Phenotype MeSH
• Hepatocytes metabolism   pathology   MeSH
• Liver Cirrhosis pathology   metabolism   MeSH
• Liver pathology   metabolism   MeSH
• Humans MeSH
• Disease Progression MeSH
• Proteome * analysis   metabolism   MeSH
• Proteomics * methods   MeSH
• Unfolded Protein Response MeSH
• Machine Learning MeSH
• Check Tag
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

Space and time are fundamental attributes of the external world. Deciphering the brain mechanisms involved in processing the surrounding environment is one of the main challenges in neuroscience. This is particularly defiant when situations change rapidly over time because of the intertwining of spatial and temporal information. However, understanding the cognitive processes that allow coping with dynamic environments is critical, as the nervous system evolved in them due to the pressure for survival. Recent experiments have revealed a new cognitive mechanism called time compaction. According to it, a dynamic situation is represented internally by a static map of the future interactions between the perceived elements (including the subject itself). The salience of predicted interactions (e.g. collisions) over other spatiotemporal and dynamic attributes during the processing of time-changing situations has been shown in humans, rats, and bats. Motivated by this ubiquity, we study an artificial neural network to explore its minimal conditions necessary to represent a dynamic stimulus through the future interactions present in it. We show that, under general and simple conditions, the neural activity linked to the predicted interactions emerges to encode the perceived dynamic stimulus. Our results show that this encoding improves learning, memorization and decision making when dealing with stimuli with impending interactions compared to no-interaction stimuli. These findings are in agreement with theoretical and experimental results that have supported time compaction as a novel and ubiquitous cognitive process.

• MeSH
• Humans MeSH
• Brain physiology   MeSH
• Neural Networks, Computer * MeSH
• Memory physiology   MeSH
• Decision Making physiology   MeSH
• Learning physiology   MeSH
• Time Perception physiology   MeSH
• Space Perception physiology   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH

Research has shown that external focus (EF) instructions-directing attention to intended movement effects (e.g., ball's or dart's path)-are more effective for enhancing motor performance and learning than internal focus (IF) instructions, which focus on body movements (e.g., arm or foot motion). Nonetheless, the impact of visuospatial working memory capacity (WMC) in this context, especially among children, has been less investigated. This research sought to examine the effects of EF compared to IF on the skill acquisition and motor learning of a dart-throwing task among children with both high and low visuospatial WMC. Forty-eight boys aged 9-11 (Mage: 9.67 ± 0.76 years) were grouped by high or low WMC based on spatial span and memory tests, then assigned to receive either EF or IF instructions. The experiment comprised three stages: practice, retention, and two transfer tests, including throwing from a longer distance and a dual-task scenario with added cognitive load (tone counting). Results showed that EF outperformed IF at all stages. While WMC did not affect performance during practice and retention, children with low WMC performed better than those with high WMC during the longer distance test. In dual-task conditions, an EF continued to surpass an IF, whilst the WMC exerted no significant impact. The present findings suggest that an EF relative to an IF promotes more automatic movement and enhanced multitasking, while the impact of visuospatial WMC was less than expected, highlighting the benefits of EF in teaching motor skills to children, regardless of visuospatial WMC.

• MeSH
• Child MeSH
• Memory, Short-Term * physiology   MeSH
• Humans MeSH
• Motor Skills * physiology   MeSH
• Attention * physiology   MeSH
• Psychomotor Performance * physiology   MeSH
• Learning physiology   MeSH
• Space Perception physiology   MeSH
• Visual Perception physiology   MeSH
• Check Tag
• Child MeSH
• Humans MeSH
• Male MeSH
• Publication type
• Journal Article MeSH

The interaction between the main psychotropic ingredient of Cannabis, Δ9- tetrahydrocannabinol (THC), with the endogenous cannabinoid system (ECS) is a critical and underrated issue that deserves utmost attention. The ECS, indeed, contributes to the formation and regulation of excitatory and inhibitory (E/I) neuronal networks that in the hippocampus underly spatial memory. This study explored sex-specific consequences of prenatal exposure to THC in hippocampus-dependent memory and the underlying cellular and molecular contributors of synaptic plasticity and E/I homeostasis. Sprague Dawley dams were exposed to THC (2 mg/kg) or vehicle, from gestational day 5-20. The adolescent progeny of both sexes was tested for: spatial memory retrieval and flexibility in the Barnes Maze; mRNA expression of relevant players of hippocampal synaptic plasticity; density of cholecystokinin-positive basket cells (CCK+BCs) - a major subtype of hippocampal inhibitory interneurons; mRNA expression of the excitatory and inhibitory synaptic proteins neuroligins (Nlgns), as a proxy of synaptic efficiency. Our results show a sex-specific disruption in spatial memory retrieval and flexibility, a male-specific decrease in CCK+BCs density and increase in the expression of markers of neuroplasticity, and consistent changes in the expression of Nlgn-1 and 3 isoforms. Despite a delay in memory retrieval, flexibility of memory was spared in prenatally-THC-exposed female offspring as well as most of the markers of neuroplasticity; a sex-specific increase in CCK+BCs density, and a consistent expression of Nlgn-3 was observed. The current results highlight a major vulnerability to prenatal exposure to THC on memory processing in the male progeny, and sex-specific alterations in the E/I balance and synaptic plasticity.

• MeSH
• Maze Learning drug effects   MeSH
• Cholecystokinin metabolism   MeSH
• Hippocampus * drug effects   metabolism   MeSH
• Rats MeSH
• Neuronal Plasticity * drug effects   MeSH
• Sex Characteristics * MeSH
• Rats, Sprague-Dawley * MeSH
• Spatial Memory * drug effects   MeSH
• Pregnancy MeSH
• Dronabinol * pharmacology   toxicity   MeSH
• Prenatal Exposure Delayed Effects * chemically induced   MeSH
• Animals MeSH
• Check Tag
• Rats MeSH
• Male MeSH
• Pregnancy MeSH
• Female MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH

PURPOSE: Chronic obstructive pulmonary disease (COPD) is a prevalent and preventable condition that typically worsens over time. Acute exacerbations of COPD significantly impact disease progression, underscoring the importance of prevention efforts. This observational study aimed to achieve two main objectives: (1) identify patients at risk of exacerbations using an ensemble of clustering algorithms, and (2) classify patients into distinct clusters based on disease severity. METHODS: Data from portable medical devices were analyzed post-hoc using hyperparameter optimization with Self-Organizing Maps (SOM), Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Isolation Forest, and Support Vector Machine (SVM) algorithms, to detect flare-ups. Principal Component Analysis (PCA) followed by KMeans clustering was applied to categorize patients by severity. RESULTS: 25 patients were included within the study population, data from 17 patients had the required reliability. Five patients were identified in the highest deterioration group, with one clinically confirmed exacerbation accurately detected by our ensemble algorithm. Then, PCA and KMeans clustering grouped patients into three clusters based on severity: Cluster 0 started with the least severe characteristics but experienced decline, Cluster 1 consistently showed the most severe characteristics, and Cluster 2 showed slight improvement. CONCLUSION: Our approach effectively identified patients at risk of exacerbations and classified them by disease severity. Although promising, the approach would need to be verified on a larger sample with a larger number of recorded clinically verified exacerbations.

• Publication type
• Journal Article MeSH

Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal 'trajectory' of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.

• MeSH
• Algorithms * MeSH
• Adult MeSH
• Hippocampus diagnostic imaging   pathology   MeSH
• Middle Aged MeSH
• Humans MeSH
• Magnetic Resonance Imaging * MeSH
• Brain diagnostic imaging   pathology   MeSH
• Neuroimaging MeSH
• Cross-Sectional Studies MeSH
• Reproducibility of Results MeSH
• Schizophrenia * diagnostic imaging   pathology   MeSH
• Gray Matter * diagnostic imaging   pathology   MeSH
• Machine Learning MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Geographicals
• Europe MeSH
• North America MeSH

ADHD is a common chronic neurodevelopmental disorder and is characterized by persistent inattention, hyperactivity, impulsivity and are often accompanied by learning and memory impairment. Great evidence has shown that learning and memory impairment of ADHD plays an important role in its executive function deficits, which seriously affects the development of academic, cognitive and daily social skills and will cause a serious burden on families and society. With the increasing attention paid to learning and memory impairment in ADHD, relevant research is gradually increasing. In this article, we will present the current research results of learning and memory impairment in ADHD from the following aspects. Firstly, the animal models of ADHD, which display the core symptoms of ADHD as well as with learning and memory impairment. Secondly, the molecular mechanism of has explored, including some neurotransmitters, receptors, RNAs, etc. Thirdly, the susceptibility gene of ADHD related to the learning and impairment in order to have a more comprehensive understanding of the pathogenesis. Key words: Learning and memory, ADHD, Review.

• MeSH
• Attention Deficit Disorder with Hyperactivity * psychology   genetics   MeSH
• Humans MeSH
• Disease Models, Animal MeSH
• Memory MeSH
• Memory Disorders * psychology   etiology   MeSH
• Learning Disabilities psychology   etiology   MeSH
• Learning MeSH
• Animals MeSH
• Check Tag
• Humans MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Review MeSH