Learning Memory Research Articles

Time-Restricted Feeding Mitigates Age-Related Cognitive Decline: Impacts on Neurovascular Coupling and Blood-Brain Barrier

Vascular cognitive impairment (VCI) and age-related cognitive decline are mediated by alterations in microvascular function, cerebral blood flow (CBF), neurovascular coupling (NVC) responses and blood-brain barrier (BBB) permeability. The pathogenesis of VCI can be influenced by lifestyle factors like exercise, nutrition, and dietary habits. Time-restricted feeding (TRF) offers an accessible intervention that can be employed during aging. This study is aimed at investigating the cerebromicrovascular effects of TRF on NVC responses and BBB integrity in aged mice to explore potential novel interventions against the age-related loss of cognitive function. We hypothesized that TRF would improve NVC responses and BBB integrity during aging to prevent age-related cognitive decline. To test this hypothesis, 18-month-old C57BL/6 mice were placed on TRF regimen for 6 months, where they received ad libitum feeding for 6 hours each day. 6- and 24-month-old mice fed 24 hours/day ad libitum were used as controls. All three groups were subjected to cognitive tests including radial-arms water maze (RAWM). NVC was assessed by measuring CBF using last speckle contrast imaging while performing contralateral whisker stimulation, and BBB integrity was measured through extravasation of tracers in various sizes using intravital two-photon imaging. We found that aged mice had significant impairment in NVC responses. 6 months of TRF improved BBB integrity and rescued NVC responses, and significantly improved learning and spatial memory. This study emphasizes the importance of maintaining cerebromicrovascular integrity to promote healthy brain aging and cognitive health. The establishment of the mechanisms by which TRF exerts benefits during aging provides pertinent information to the future development of therapeutic strategies to prevent VCI. Stephenson Cancer Center, National Institute of Aging R03 AG070479, American Heart Association. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Machine Learning Memory Kernels as Closure for Non-Markovian Stochastic Processes.

Finding the dynamical law of observable quantities lies at the core of physics. Within the particular field of statistical mechanics, the generalized Langevin equation (GLE) comprises a general model for the evolution of observables covering a great deal of physical systems with many degrees of freedom and an inherently stochastic nature. Although formally exact, GLE brings its own great challenges. It depends on the complete history of the observables under scrutiny, as well as the microscopic degrees of freedom, all of which are often inaccessible. We show that these drawbacks can be overcome by adopting elements of machine learning from empirical data, in particular coupling a multilayer perceptron (MLP) with the formal structure of GLE and calibrating the MLP with the data. This yields a powerful computational tool capable of describing noisy complex systems beyond the realms of statistical mechanics. It is exemplified with a number of representative examples from different fields: from a single colloidal particle and particle chains in a thermal bath to climatology and finance, showing in all cases excellent agreement with the actual observable dynamics. The new framework offers an alternative perspective for the study of nonequilibrium processes opening also a new route for stochastic modeling.

Electroacupuncture regulates Rab5a-mediating NGF transduction to improve learning and memory ability in the early stage of AD mice.

Nerve growth factor (NGF) loss is a potential factor for the degeneration of basal forebrain cholinergic neurons (BFCNs) in Alzheimer's disease (AD), and Rab5a is a key regulatory molecule of NGF signaling transduction. Here, we investigated the changes of Rab5a in 5 × FAD mice and further explored the mechanism of Electroacupuncture (EA) treatment in improving cognition in the early stage of AD. The total Rab5a and Rab5a-GTP in 5-month-old 5 × FAD mice and wild-type mice were detected using WB and IP technologies. 5 × FAD mice were treated with EA at the Bai hui (DU20) and Shen ting (DU24) acupoints for 4 weeks and CRE/LOXP technology was used to confirm the role of Rab5a in AD mediated by EA stimulation. The Novel Object Recognition and Morris water maze tests were used to evaluate the cognitive function of 5 × FAD mice. The Nissl, immunohistochemistry, and Thioflavin S staining were used to observe pathological morphological changes in the basal forebrain circuit. The Golgi staining was used to investigate the synaptic plasticity of the basal forebrain circuit and WB technology was used to detect the expression levels of cholinergic-related and NGF signal-related proteins. The total Rab5a was unaltered, but Rab5a-GTP increased and the rab5a-positive early endosomes appeared enlarged in the hippocampus of 5 × FAD mice. Notably, EA reduced Rab5a-GTP in the hippocampus in the early stage of 5 × FAD mice. EA could improve object recognition memory and spatial learning memory by reducing Rab5a activity in the early stage of 5 × FAD mice. Moreover, EA could reduce Rab5a activity to increase NGF transduction and increase the levels of phosphorylated TrkA, AKT, and ERK in the basal forebrain and hippocampus, and increase the expression of cholinergic-related proteins, such as ChAT, vAchT, ChT1, m1AchR, and m2AchR in the basal forebrain and ChAT, m1AchR, and m2AchR in the hippocampus, improving synaptic plasticity in the basal forebrain hippocampal circuit in the early stage of 5 × FAD mice. Rab5a hyperactivation is an early pathological manifestation of 5 × FAD mice. EA could suppress Rab5a-GTP to promote the transduction of NGF signaling, and enhance the synaptic plasticity of the basal forebrain hippocampal circuit improving cognitive impairment in the early stage of 5 × FAD mice.

Decoding Nifty50’s Price Enigma: Machine Learning Powered Approach

Abstract: This study uses machine learning and Long Short-Term Memory (LSTM) networks to decipher the price riddle of Nifty50, a well-known stock market index in India. Using Long Short-Term Memory (LSTM) recurrent neural networks, which are renowned for their capacity to recognise sequential patterns, we aim to forecast and comprehend the intricate dynamics influencing Nifty50's price fluctuations.

Bu zhong Yiqi Decoction ameliorates mild cognitive impairment by improving mitochondrial oxidative stress damage via the SIRT3/MnSOD/OGG1 pathway

Ethnopharmacological relevanceBu-Zhong-Yi-Qi Decoction(BZYQD) is a traditional formula commonly used in China, known for its effects in tonifying Qi and raising Yang. It can relieve symptoms of cognitive impairment such as forgetfulness and lack of concentration caused by qi deficiency, which is common in aging and debilitating. However, much of the current research on BZYQD has been focused on its impact on the digestive system, leaving its molecular mechanisms in improving cognitive function largely unexplored. Aim of the studyCognitive decline in the aging central nervous system is intrinsically linked to oxidative damage. This study aims to investigate the therapeutic mechanism of BZYQD in treating mild cognitive impairment caused by qi deficiency, particularly through repair of mitochondrial oxidative damage. Materials and methodsA rat model of mild cognitive impairment (MCI) was established by administering reserpine subcutaneously for two weeks, followed by a two-week treatment with BZYQD/GBE. In vitro experiments were conducted to assess the effects of BZYQD on neuronal cells using a H2O2-induced oxidative damage model in PC12 cells. The open field test and the Morris water maze test evaluated the cognitive and learning memory abilities of the rats. HE staining and TEM were employed to observe morphological changes in the hippocampus and its mitochondria. Mitochondrial activity, ATP levels, and cellular viability were measured using assay kits. Protein expression in the SIRT3/MnSOD/OGG1 pathway was analyzed in tissues and cells through western blotting. Levels of 8-OH-dG in mitochondria extracted from tissues and cells were quantified using ELISA. Mitochondrial morphology in PC12 cells was visualized using Mito Red, and mitochondrial membrane potential was assessed using the JC-1 kit. ResultsBZYQD treatment significantly improved cognitive decline caused by reserpine in rats, as well as enhanced mitochondrial morphology and function in the hippocampus. Our findings indicate that BZYQD mitigates mtDNA oxidative damage in rats by modulating the SIRT3/MnSOD/OGG1 pathway. In PC12 cells, BZYQD reduced oxidative damage to mitochondria and mtDNA in H2O2-induced conditions and was associated with changes in the SIRT3/MnSOD/OGG1 pathway. ConclusionBZYQD effectively counteracts reserpine-induced mild cognitive impairment and ameliorates mitochondrial oxidative stress damage through the SIRT3/MnSOD/OGG1 pathway.

Lambda-cyhalothrin alters locomotion, mood and memory abilities in Swiss mice

Lambda-cyhalothrin (LCT) is a type II pyrethroid widely used in agriculture for plant protection against pests. However, pyrethroids represents a risk for rural female farmworkers, and few studies addressed LCT-behavioural alterations in mice. The present study evaluates the effect of LCT on behaviour of eight weeks aged female mice. Mice were divided into three groups including treated mice that received through gavage (i) 0.5 mg/kg bw and (ii) 2 mg/kg of LCT dissolved in corn oil, and (iii) the vehicle controls. Behavioural tests assess the locomotor activity using open field test, the anxiety by the dark-light box test, the learning memory with novel object recognition test, the memory retention by the elevated plus maze test, and the spatial working memory using the Y-maze test. Subacute treatment with low doses of LCT decreases total distance travelled, induces anxiogenic effect by reducing the time spent in the enlightened compartment, alters memory retention by increasing the latency time, and also affects learning memory by reducing the recognition index parameter. However, LCT does not significantly alter spatial working memory. In conclusion, LCT-treated female mice show an alteration in locomotor activity, mood state and memory abilities probably related to oxidative stress and altered neurotransmission.

The perceived importance of words in large font guides learning and selective memory

People are often presented with large amounts of information to remember, and in many cases, the font size of information may be indicative of its importance (such as headlines or warnings). In the present study, we examined how learners perceive the importance of information in different font sizes and how beliefs about font size influence selective memory. In Experiment 1, participants were presented with to-be-remembered words that were either unrelated or related to a goal (e.g., items for a camping trip) in either small or large font. Participants rated words in large font as more important to remember than words in small font when the words in a list were unrelated but not when the words were schematically related to a goal. In Experiments 2 and 3, we were interested in how learners’ belief that font size is indicative of importance translates to their ability to selectively encode and recall valuable information. Specifically, we presented participants with words in various font sizes, and larger fonts either corresponded to greater point values or smaller point values (values counted towards participants’ scores if recalled). When larger fonts corresponded with greater point values, participants were better able to selectively remember high-value words relative to low-value words. Thus, when to-be-remembered information varies in value, font size may be less diagnostic of an item’s importance (the item’s importance drives memory), and when the value of information is consistent with a learner’s belief, learners can better engage in selective memory.

Nerolidol rescues hippocampal injury of diabetic rats through inhibiting NLRP3 inflammasome and regulation of MAPK/AKT pathway.

Despite the observation of diabetes-induced brain tissue damage and impaired learning and memory, the underlying mechanism of damage remains elusive, and effective, targeted therapeutics are lacking. Notably, the NLRP3 inflammasome is highly expressed in the hippocampus of diabetic individuals. Nerolidol, a naturally occurring compound with anti-inflammatory and antioxidant properties, has been identified as a potential therapeutic option for metabolic disorders. However, the ameliorative capacity of nerolidol on diabetic hippocampal injury and its underlying mechanism remain unclear. Network pharmacology and molecular docking was used to predict the signaling pathways and therapeutic targets of nerolidol for the treatment of diabetes. Then established a diabetic rat model using streptozotocin (STZ) combined with a high-fat diet and nerolidol was administered. Morris water maze to assess spatial learning memory capacity. Hematoxylin and eosin and Nissl staining was used to detect neuronal damage in the diabetic hippocampus. Transmission electron microscopy was used to detect the extent of damage to mitochondria, endoplasmic reticulum (ER) and synapses. Immunofluorescence was used to detect GFAP, IBA1, and NLRP3 expression in the hippocampus. Western blot was used to detect apoptosis (Bcl-2, BAX, and Cleaved-Caspase-3); synapses (postsynaptic densifying protein 95, SYN1, and Synaptophysin); mitochondria (DRP1, OPA1, MFN1, and MFN2); ER (GRP78, ATF6, CHOP, and caspase-12); NLRP3 inflammasome (NLRP3, ASC, and caspase-1); inflammatory cytokines (IL-18, IL-1β, and TNF-α); AKT (P-AKT); and mitogen-activated protein kinase (MAPK) pathway (P-ERK, P-p38, and P-JNK) related protein expression. Network pharmacology showed that nerolidol's possible mechanisms for treating diabetes are the MAPK/AKT pathway and anti-inflammatory effects. Animal experiments demonstrated that nerolidol could improve blood glucose, blood lipids, and hippocampal neuronal damage in diabetic rats. Furthermore, nerolidol could improve synaptic, mitochondrial, and ER damage in the hippocampal ultrastructure of diabetic rats by potentially affecting synaptic, mitochondrial, and ER-related proteins. Further studies revealed that nerolidol decreased neuroinflammation, NLRP3 and inflammatory factor expression in hippocampal tissue while also decreasing MAPK pathway expression and enhancing AKT pathway expression. However, nerolidol improves hippocampal damage in diabetic rats cannot be shown to improve cognitive function. In conclusion, our study reveals for the first time that nerolidol can ameliorate hippocampal damage, neuroinflammation, synaptic, ER, and mitochondrial damage in diabetic rats. Furthermore, we suggest that nerolidol may inhibit NLRP3 inflammasome and affected the expression of MAPK and AKT. These findings provide a new experimental basis for the use of nerolidol to ameliorate diabetes-induced brain tissue damage and the associated disease.

Memory and Attention in Deep Learning

This paper has highlighted the advancements made within the deep learning approached through the evolution of attention and memory algorithms. There has been a gradual replacement of the traditional approaches in deep learning through the inclusion of these algorithms that helps in capturing the data based on time and sequence. The model performance is greatly enhanced through the usage of RNNs that uses these algorithms for developing sequential modelling of data. This paper has performed a peer review to understand the different mechanisms that include GRUs, MANN, LSTM and self-attention mechanisms. Memory mechanism assists in capturing the past sequence of datasets for analysing the hidden state within the datasets. Attention mechanisms help in capturing a particular location within a video dataset to understand the patterns of a data. There is an accurate recognition of human actions in the datasets through the implementation of attention mechanisms. This helps in increasing the model performance by enhancing the prediction accuracy and visibility within a particular dataset.

A coupled neural field model for the standard consolidation theory

The standard consolidation theory states that short-term memories located in the hippocampus enable the consolidation of long-term memories in the neocortex. In other words, the neocortex slowly learns long-term memories with a transient support of the hippocampus that quickly learns unstable memories. However, it is not clear yet what could be the neurobiological mechanisms underlying these differences in learning rates and memory time-scales. Here, we propose a novel modeling approach of the standard consolidation theory, that focuses on its potential neurobiological mechanisms. In addition to synaptic plasticity and spike frequency adaptation, our model incorporates adult neurogenesis in the dentate gyrus as well as the difference in size between the neocortex and the hippocampus, that we associate with distance-dependent synaptic plasticity. We also take into account the interconnected spatial structure of the involved brain areas, by incorporating the above neurobiological mechanisms in a coupled neural field framework, where each area is represented by a separate neural field with intra- and inter-area connections. To our knowledge, this is the first attempt to apply neural fields to this process. Using numerical simulations and mathematical analysis, we explore the short-term and long-term dynamics of the model upon alternance of phases of hippocampal replay and retrieval cue of an external input. This external input is encodable as a memory pattern in the form of a multiple bump attractor pattern in the individual neural fields. In the model, hippocampal memory patterns become encoded first, before neocortical ones, because of the smaller distances between the bumps of the hippocampal memory patterns. As a result, retrieval of the input pattern in the neocortex at short time-scales necessitates the additional input delivered by the memory pattern of the hippocampus. Neocortical memory patterns progressively consolidate at longer times, up to a point where their retrieval does not need the support of the hippocampus anymore. At longer times, perturbation of the hippocampal neural fields by neurogenesis erases the hippocampus pattern, leading to a final state where the memory pattern is exclusively evoked in the neocortex. Therefore, the dynamics of our model successfully reproduces the main features of the standard consolidation theory. This suggests that neurogenesis in the hippocampus and distance-dependent synaptic plasticity coupled to synaptic depression and spike frequency adaptation, are indeed critical neurobiological processes in memory consolidation.

The impact of continuous and intermittent ketogenic diets on cognitive behavior, motor function, and blood lipids in TgF344-AD rats.

Studies suggest that ketogenic diets (KD) may improve memory in mouse models of aging and Alzheimer's disease (AD). This study determined whether a continuous or intermittent KD (IKD) enhanced cognitive behavior in the TgF344-AD rat model of AD. At 6 months-old, TgF344-AD and wild-type (WT) littermates were placed on a control (CD), KD, or IKD (morning CD and afternoon KD) provided as two meals per day for 2 or 6 months. Cognitive and motor behavior and circulating β-hydroxybutyrate (BHB), AD biomarkers and blood lipids were assessed. Animals on a KD diet had elevated circulating BHB, with IKD levels intermediate to CD and KD. TgF344-AD rats displayed impaired spatial learning memory in the Barnes maze at 8 and 12 months of age and impaired motor coordination at 12 months of age. Neither KD nor IKD improved performance compared to CD. At 12 months of age, TgF344-AD animals had elevated blood lipids. IKD reduced lipids to WT levels with KD further reducing cholesterol below WT levels. This study shows that at 8 or 12 months of age, KD or IKD intervention did not improve measures of cognitive or motor behavior in TgF344-AD rats; however, both IKD and KD positively impacted circulating lipids.

An investigation of multivariate data-driven deep learning models for predicting COVID-19 variants

The Coronavirus Disease 2019 (COVID-19) pandemic has swept almost all parts of the world. With the increasing number of COVID-19 cases worldwide, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has mutated into various variants. Given the increasingly dangerous conditions of the pandemic, it is crucial to predict the number of COVID-19 cases. Deep Learning and Long Short-Term Memory (LSTM) have predicted disease progress with reasonable accuracy and small errors. LSTM training is used to predict confirmed cases of COVID-19 based on variants identified using the European Centre for Disease Prevention and Control (ECDC) COVID-19 dataset containing confirmed cases identified from 30 European countries. Tests were conducted using the LSTM and Bidirectional LSTM (BiLSTM) models with the addition of Recurrent Neural Network (RNN) as comparisons on hidden size and layer size. The obtained result showed that in testing hidden sizes 25, 50, 75, and 100, the RNN model provided better results, with the minimum Mean Squared Error (MSE) value of 0.01 and the Root Mean Square Error (RMSE) value of 0.012 for B.1.427/B.1.429 variant with a hidden size of 100. Further testing layer sizes 2, 3, 4, and 5 shows that the BiLSTM model provided better results, with a minimum MSE value of 0.01 and an RMSE of 0.01 for the B.1.427/B.1.429 variant with a hidden size of 100 and layer size of 2.

Introduction of a model for the modification of masticatory activity to investigate induced neural and behavioral alterations in mice

In the literature, there is consistent evidence related to the influence of chewing on brain functions, either from experimental models or in humans. In the case of humans, most results are restricted to functional tests, lacking cellular or molecular evidence. In the described method, the possibility of using experimental models is presented, as well as the mimicry of deprivation and rehabilitation of masticatory activity and without stress impact. By opting for the use of mash feed, instead of extracting or implanting an intraoral device, alternations between restriction and rehabilitation of mastication were imposed on murine models. The animals completed various temporal windows, with aging also representing a potential factor for translational dementia associations. Additionally, animals were segregated into environments characterized as either standard, simulating a sedentary lifestyle, or enriched, rich in sensorimotor and visuospatial stimulation. Thus, it was possible to study the influence of changes in masticatory activity, associated with aging and environmental enrichment, on cells from subregions of the hippocampus, as well as on performance in tests of learning and spatial memory.•Animal model for masticatory activity alteration;•Masticatory deprivation and rehabilitation, and•Models to study the interaction among masticatory activity, aging and enrichment environment.

The phenylpropionamide extract of hemp (Cannabis sativa L.) seed improves learning memory ability and survival rate by attenuating microglia activation and reducing amyloid deposition via the SIRT1-AMAD10 pathway in APP/PS1 mice

BackgroundFructus cannabis (Hemp seed), the dried and mature fruit of Cannabis sativa L., was reported to have effects against Alzheimer's disease (AD) in different experimental models. However, either chemical composition or mechanisms of action was not clear. Our previous work isolated and identified diverse phenylpropionamides such as cannabisin A-F, caffeoyltyramine and feryroyltyramine from hemp seed, which showed antioxidant and anti-neuroinflammatory activity in cell models. PurposeTo study the anti-AD effect and mechanism of the total phenylpropionamides (TPA) extract from hemp seed using APPswe/PS1dE9 mice model. MethodsTPA extract was prepared via extraction and column chromatography techniques, then analyzed and measured using HPLC, HPLC-MS and Folin-Ciocalteu method. The extract was administered by gavage to APPswe/PS1dE9 mice. The learning memory ability of mice were examined using new object recognition test and Morris water maze. Hematoxylin and Eosin staining was used to observe the morphology of neuronal cells in the hippocampal region of brain tissue; ELISA was used to measure the content of IL-1β, TNF-α, IL-6, superoxide dismutase (SOD), malondialdehyde (MDA) in the brain tissue; the deposition of Aβ protein was measured by immunohistochemistry and Western blotting; the activation of microglia was measured by immunofluorescence. The expression of APP, PS1, SIRT1, and ADAM10 proteins was measured by Western blotting. ResultsFolin-Ciocalteu method showed the total phenylpropionamides content was 238.03 μg caffeic acid equivalent /mg TPA. HPLC and HPLC-MS analysis showed the contents of N-trans-caffeoyltyramine, cannabisin A and B were 20.16 μg/mg, 32.16 μg/mg and 214.35 μg/mg, respectively, in TPA extract. TPA treatment significantly increased the survival rate of APP/PS1 mice, improved the learning and memory ability, reversed the neural cell damage in the hippocampal region, and reduced Aβ deposition and activated microglia in brain tissue. Meanwhile, the administration decreased the neuroinflammatory factors TNF-α, IL-6, IL-1β expression, increased antioxidant enzyme SOD activity, and attenuated MDA expression. Western blotting showed that TPA administration increased SIRT1 and ADAM10 protein expression and decreased APP and PS1 protein expression. ConclusionTPA improved learning memory capacity, increased survival rate, attenuated neuroinflammation, oxidative stress, microglia activation and hippocampal apoptosis, and reduced amyloid deposition via the SIRT1-ADAM10 pathway in APP/PS1 mice.

Spinal cord and brain atrophy patterns in neuromyelitis optica spectrum disorder and multiple sclerosis.

Spinal cord and brain atrophy are common in neuromyelitis optica spectrum disorder (NMOSD) and relapsing-remitting multiple sclerosis (RRMS) but harbor distinct patterns accounting for disability and cognitive impairment. This study included 209 NMOSD and 304 RRMS patients and 436 healthy controls. Non-negative matrix factorization was used to parse differences in spinal cord and brain atrophy at subject level into distinct patterns based on structural MRI. The weights of patterns were obtained using a linear regression model and associated with Expanded Disability Status Scale (EDSS) and cognitive scores. Additionally, patients were divided into cognitive impairment (CI) and cognitive preservation (CP) groups. Three patterns were observed in NMOSD: (1) Spinal Cord-Deep Grey Matter (SC-DGM) pattern was associated with high EDSS scores and decline of visuospatial memory function; (2) Frontal-Temporal pattern was associated with decline of language learning function; and (3) Cerebellum-Brainstem pattern had no observed association. Patients with CI had higher weights of SC-DGM pattern than CP group. Three patterns were observed in RRMS: (1) DGM pattern was associated with high EDSS scores, decreased information processing speed, and decreased language learning and visuospatial memory functions; (2) Frontal-Temporal pattern was associated with overall cognitive decline; and (3) Occipital pattern had no observed association. Patients with CI trended to have higher weights of DGM and Frontal-Temporal patterns than CP group. This study estimated the heterogeneity of spinal cord and brain atrophy patterns in NMOSD and RRMS patients at individual level, and evaluated the clinical relevance of these patterns, which may contribute to stratifying participants for targeted therapy.

Melatonin is a Neuroprotective and Antioxidant Agent against Neurotoxicity Induced by an Intrahippocampal Injection of Nickel in Rats.

The investigation into the hippocampal function and its response to heavy metal exposure is crucial for understanding the mechanisms underlying neurotoxicity, this can potentially inform strategies for mitigating the adverse effects associated with heavy metal exposure. Melatonin is an essential neuromodulator known for its efficacy as an antioxidant. In this study, we aimed to determine whether melatonin could protect against Nickel (Ni) neurotoxicity. To achieve this, we performed an intracerebral injection of Ni (300 µM NiCl2) into the right hippocampus of male Wistar rats, followed by melatonin treatment. Based on neurobehavioral and neurobiochemical assessments, our results demonstrate that melatonin efficiently enhances Ni-induced behavioral dysfunction and cognitive impairment. Specifically, melatonin treatment positively influences anxious behavior, significantly reduces immobility time in the forced swim test (FST), and improves learning and spatial memory abilities. Moreover, neurobiochemical assays revealed that melatonin treatment modulates the Ni-induced alterations in oxidative stress balance by increasing antioxidant enzyme activities, such as superoxide dismutase (SOD) and catalase (CAT). Additionally, we observed that melatonin significantly attenuated the increased levels of lipid peroxidation (LPO) and nitric oxide (NO). In conclusion, the data from this study suggests that melatonin attenuates oxidative stress, which is the primary mechanism responsible for Ni-induced neurotoxicity. Considering that the hippocampus is the main structure involved in the pathology associated with heavy metal intoxication, such as Ni, these findings underscore the potential therapeutic efficacy of melatonin in mitigating heavy metal-induced brain damage.

Cognitive decline, Aβ pathology, and blood–brain barrier function in aged 5xFAD mice

BackgroundPatients with Alzheimer's disease (AD) develop blood–brain barrier dysfunction to varying degrees. How aging impacts Aβ pathology, blood–brain barrier function, and cognitive decline in AD remains largely unknown. In this study, we used 5xFAD mice to investigate changes in Aβ levels, barrier function, and cognitive decline over time.Methods5xFAD and wild-type (WT) mice were aged between 9.5 and 15.5 months and tested for spatial learning and reference memory with the Morris Water Maze (MWM). After behavior testing, mice were implanted with acute cranial windows and intravenously injected with fluorescent-labeled dextrans to assess their in vivo distribution in the brain by two-photon microscopy. Images were processed and segmented to obtain intravascular intensity, extravascular intensity, and vessel diameters as a measure of barrier integrity. Mice were sacrificed after in vivo imaging to isolate brain and plasma for measuring Aβ levels. The effect of age and genotype were evaluated for each assay using generalized or cumulative-linked logistic mixed-level modeling and model selection by Akaike Information Criterion (AICc). Pairwise comparisons were used to identify outcome differences between the two groups.Results5xFAD mice displayed spatial memory deficits compared to age-matched WT mice in the MWM assay, which worsened with age. Memory impairment was evident in 5xFAD mice by 2–threefold higher escape latencies, twofold greater cumulative distances until they reach the platform, and twice as frequent use of repetitive search strategies in the pool when compared with age-matched WT mice. Presence of the rd1 allele worsened MWM performance in 5xFAD mice at all ages but did not alter the rate of learning or probe trial outcomes. 9.5-month-old 15.5-month-old 5xFAD mice had twofold higher brain Aβ40 and Aβ42 levels (p < 0.001) and 2.5-fold higher (p = 0.007) plasma Aβ40 levels compared to 9.5-month-old 5xFAD mice. Image analysis showed that vessel diameters and intra- and extravascular dextran intensities were not significantly different in 9.5- and 15.5-month-old 5xFAD mice compared to age-matched WT mice.Conclusion5xFAD mice continue to develop spatial memory deficits and increased Aβ brain levels while aging. Given in vivo MP imaging limitations, further investigation with smaller molecular weight markers combined with advanced imaging techniques would be needed to reliably assess subtle differences in barrier integrity in aged mice.

Combining Machine Learning and Lifetime-Based Resource Management for Memory Allocation and Beyond

Memory management is fundamental to the performance of all applications. On modern server architectures, an application's memory allocator needs to balance memory utilization against the ability to use 2MB huge pages, which are crucial for achieving high performance. This paper shows that prior C++ memory allocators are fundamentally limited because optimizing this trade-off depends on the knowledge of object lifetimes, which is information allocators lack. We introduce a two-step approach to attain high memory utilization in huge pages. We first introduce a novel machine-learning approach that predicts the lifetime of freshly allocated objects using the stack trace at the time of allocation and treats stack traces as natural language. We then present a fundamentally new type of memory allocator that exploits (potentially incorrect) object lifetime predictions to achieve high memory utilization at full huge page usage. In contrast to prior memory allocators that organize their heap around size classes and free lists, our allocator organizes the heap based on predicted lifetime classes and adjusts to mispredictions on the fly. We demonstrate experimentally that this learned lifetime-aware memory allocator (LLAMA) reduces fragmentation with huge pages by up to 78%. Our approach gives rise to a new methodology for applying ML in computer systems. In addition, similar space-time bin packing problems abound in computer science and we discuss how this approach has applications beyond memory allocation to a wide range of problems.

DUEL: Duplicate Elimination on Active Memory for Self-Supervised Class-Imbalanced Learning

Recent machine learning algorithms have been developed using well-curated datasets, which often require substantial cost and resources. On the other hand, the direct use of raw data often leads to overfitting towards frequently occurring class information. To address class imbalances cost-efficiently, we propose an active data filtering process during self-supervised pre-training in our novel framework, Duplicate Elimination (DUEL). This framework integrates an active memory inspired by human working memory and introduces distinctiveness information, which measures the diversity of the data in the memory, to optimize both the feature extractor and the memory. The DUEL policy, which replaces the most duplicated data with new samples, aims to enhance the distinctiveness information in the memory and thereby mitigate class imbalances. We validate the effectiveness of the DUEL framework in class-imbalanced environments, demonstrating its robustness and providing reliable results in downstream tasks. We also analyze the role of the DUEL policy in the training process through various metrics and visualizations.

Galectin-9 and Tim-3 are upregulated in response to microglial activation induced by the peptide Amyloid-β (25–35)

Galectins are a group of β-galactoside-binding lectins associated with regulating immunological response. In the brains of AD patients and 5xFAD (familial AD) mice, galectin-3 (Gal-3) was highly upregulated and found to be expressed in microglia associated with Aβ plaques. However, the participation of other galectins, specifically galectin-9 (Gal-9) and T-cell immunoglobulin and mucin domain 3 (Tim-3) receptors, are unknown in the inflammatory response. The experimental model of the Aβ25–35 peptide will allow us to study the mechanisms of neuroinflammation and describe the changes in the expression of the Gal-9 and Tim-3 receptor. This study aimed to evaluate whether Aβ25–35 peptide administration into the lateral ventricles of rats upregulated Gal-9 and Tim-3 implicated in the modulation of neuroinflammation. The vehicle or Aβ25–35 peptide (1 μg/μL) was bilaterally administered into the lateral ventricles of the rat, and control group. After the administration of the Aβ25–35 peptide, animals were tested for learning (day 29) and spatial memory (day 30) in the novel object recognition test (NOR). On day 31, hippocampus was examined for morphological changes by Nilss stain, biochemical changes by NO2 and MDA, immunohistochemical analysis by astrocytes (GFAP), microglia (Iba1), Gal-9 and Tim-3, and western blot. Our results show the administration of the Aβ25–35 peptide into the lateral ventricles of rats induce memory impairment in the NOR by increases the oxidative stress and inflammatory response. This result is associated with an upregulation of Gal-9 and Tim-3 predominantly detected in the microglia cells of Aβ25–35-treated rats with respect to the control group. Gal-9 and Tim-3 are upregulated in activated microglia that could modulate the inflammatory response and damage in neurodegenerative processes induced by the Aβ25–35 peptide. Therefore, we suggest that Gal-9 and Tim-3 participate in the inflammatory process induced by the administration of the Aβ25–35 peptide.