Object Recognition Research Articles

SARS-CoV-2 spike S1 protein induces microglial NLRP3-dependent neuroinflammation and cognitive impairment in mice

Cognitive impairment is often found at the acute stages and sequelae of coronavirus disease 2019 (COVID-19), and the underlying mechanisms remain unclear. The S1 protein from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) might be a cause of cognitive impairment associated with COVID-19. The nucleotide-binding domain, leucine-rich–containing family, pyrin domain–containing-3 (NLRP3) inflammasome and neuroinflammation play important roles in Alzheimer's disease (AD) with cognitive impairment. However, their roles remain unknown in COVID-19 with cognitive impairment. We stimulated BV2 cells with S1 protein in vitro and injected the hippocampi of wild-type (WT) mice, NLRP3 knockout (KO), and microglia NLRP3 KO mice in vivo with S1 protein to induce cognitive impairment. We assessed exploratory behavior as associative memory using novel object recognition and Morris water maze tests. Neuroinflammation was analyzed using immunofluorescence and western blotting to detect inflammatory markers. Co-localized NLRP3 and S1 proteins were investigated using confocal microscopy. We found that S1 protein injection led to cognitive impairment, neuronal loss, and neuroinflammation by activating NLRP3 inflammation, and this was reduced by global NLRP3 KO and microglia NLRP3 KO. Furthermore, TAK 242, a specific inhibitor of Toll-like receptor-4, resulted in a significant reduction in NLRP3 and pro-IL-1β in BV2 cells with S1 protein stimulation. These results reveal a distinct mechanism through which the SARS-CoV-2 spike S1 protein promotes NLRP3 inflammasome activation and induces excessive inflammatory responses.

A semantic segmentation network based on CNN and Swin transformer for landslide detection

Abstract To address the issues of poor object localization, difficulty in object recognition, and inadequate segmentation performance of CNN-based semantic segmentation methods in landslide detection, a semantic segmentation model based on the Swin transformer and ResUNet architectures for landslide detection in remote sensing images is proposed in this paper. This method combines the global feature capabilities of the Swin transformer with the local feature extraction abilities of CNN and integrates our proposed RCCT module for landslide segmentation in remote sensing images. We apply this model to the identification and extraction of landslide disasters in Menyuan County and the Sanjiangyuan region of Qinghai Province, China, achieving a promising F1 Score of 81.91. Furthermore, we conducted a comprehensive evaluation of our proposed model on the BiJie Landslide dataset in comparison to four recently developed methods for landslide recognition. The experimental findings indicate the superior performance and effectiveness of our model over the comparative approaches.

Feature-level Fusion vs. Score-level Fusion for Image Retrieval Based on Pre-trained Deep Neural Networks

Today’s complex multimedia content made retrieving images similar to the user’s query from the database a challenging task. The performance of a Content-Based Image Retrieval System (CBIR) system highly depends on the image representation in a form of low-level features and similarity measurement. The traditional visual descriptors that do not provide good prior domain knowledge could lead to poor performance retrieval results. On the other hand, Deep Convolutional Neural Networks (DCNNs) have recently achieved a remarkable success as methods for image classification in various domains. Recently, pre-trained deep convolution neural networks on thousands of classes have the ability to extract very accurate and representative features which, in addition to classification, can also be successfully used in image retrieval systems. ResNet152, GoogLeNet and InceptionV3 are some of the effective and successful examples of pre-trained DCNNs recently applied in a computer vision tasks such as object recognition, clustering, and classification. In this paper, two approaches for a CBIR system, namely early fusion and late fusion, have been presented and compared. The early fusion utilizes concatenation of the features extracted by each possible pair of DCNNs, that is ResNet152-GoogLeNet, ResNet152-InceptionV3, and GoogLeNet-InceptionV3, and the late fusion apply CombSum method with Z-Score standardization to combine the score results provided by each DCNN of the aforementioned pairs. In the experiments on a popular WANG dataset it has been shown that late fusion approach slightly outperforms early fusion approach. The best performance of our experiments in terms of Average Precision (AP) for the top 20 results reaches 96.82%.

Acute exercise performed during the late consolidation phase improves memory persistence by hippocampal protein synthesis and catecholamine modulation

Memory persistence is a crucial aspect of long-term memory (LTM) and involves late consolidation processes that modulate memory stability over time. Acute physical exercise (PE) has emerged as a potential strategy to modulate memory consolidation and enhance memory persistence. While its effects have been extensively explored in the early consolidation phase, its impact on the late phase remains unexplored. In this study, we investigated the effects and mechanisms of an acute PE on the late consolidation window of novel object recognition (NOR) memory in rats. A 30-minute running session applied 11 h after NOR memory acquisition significantly increased memory persistence for at least 7 days. The inhibition of hippocampal protein synthesis immediately after acute PE using anisomycin (a ribosomal inhibitor) or rapamycin (an mTOR pathway inhibitor) impaired the effect of PE on memory persistence. Animals only presented memory 1 day after acquisition. The same effect was observed with the inhibition of beta-adrenergic receptors by timolol. Although there were no differences between the groups' comparison, blocking D1/D5 receptors after acute PE resulted in a lack of memory persistence in the dichotomous testing (remember/non-remember). Therefore, our exploration of the mechanisms underlying this enhancement revealed the involvement of protein synthesis and the requirement of beta-adrenergic and dopaminergic D1/D5 receptors in the dorsal hippocampus. These findings provide valuable insights into PE as a potential memory modulator, contributing to expanding our understanding of memory consolidation dynamics and acute PE effects.

Hypertension and Cognitive Dysfunction in a Pregnant Rat Model of PE; a Role for CD4+ T Cells.

Preeclampsia (PE) is associated with hypertension (HTN) during pregnancy and activated CD4+ T cells, inflammatory cytokines, and autoantibodies to the angiotensin II type I receptor (AT1-AA). Having had COVID-19 (CV) during pregnancy is associated with an increased incidence of a PE-like phenotype. Both PE and CV have long-lasting neurological implications and studies show that nonpregnant COVID patients produce AT1-AA. We have shown that CD4+ T cells from PE women cause a PE phenotype in nude athymic rats. In this study, we sought to examine the role of CD4+ T cells from PE with a CV History (Hx) to contribute to a PE phenotype and to determine the importance of CD4+ T cells in cognitive dysfunction during pregnancy. At delivery, blood and placentas were collected, and one million placental CD4+ T cells from each PE and each normotensive patient, with (NT) or without (NP) a CV (Hx) during pregnancy, were isolated, purified, and injected i.p. into a gestational day (GD) 12 pregnant nude athymic rat (one patient/rat). At GD19, blood pressure (MAP) and circulating factors were assessed in recipient rats. Cognitive function and memory were assessed using Novel Object Recognition and Barnes Maze tests, respectively. Placental ACE-2 activity and AT1-AA were measured from COVID Hx patients. A one- or two-way ANOVA with Bonferroni's multiple comparisons test was used for statistical analysis. Blood pressure was increased in patients with PE, with or without COVID, compared to NT patients. There were no significant changes in placental ACE activity in patients with COVID Hx with or without PE. AT1-AA was elevated in PE patients and in both PE and NT COVID Hx compared to control NP. In pregnant recipient rats, MAP increased in CV Hx PE (113±2, n=8) compared to CV Hx NT (101±5, n=6). PE and PE CV Hx CD4+ T Cell recipient rats exhibited impaired memory and cognitive dysfunction (p < 0.05), compared to control groups. Recipient rats of PE CV Hx CD4+ T cells had elevated AT1-AA compared to NT CV Hx recipients. Both COVID Hx groups and recipients of PE CD4+ T cells had elevated TNF alpha compared to NP. Our findings indicate that pregnant patients with a Hx of COVID during pregnancy produce AT1-AA, with or without PE. Recipients of CD4+ T cells from PE with or without a CV Hx during pregnancy cause HTN and elevated AT1-AA. TNF-α is elevated in PE and in CV Hx NT and PE recipients. Interestingly, recipients of T cells from PE patients with or without a Hx of CV had worse cognitive function during pregnancy, compared to recipient rats of NP CD4+ T cells. These data demonstrate the importance of CD4+ T cells in HTN and impaired neurological function during PE in the presence or absence of a prior COVID-19 infection during pregnancy.

Differences in memory performance: The effects of sex and reproductive experience on object recognition memory in high- and low-yawning Sprague‒Dawley rats

The novel object recognition (NOR) test is an efficient way to measure nonspatial memory in rodents. The NOR performance of female and male rats is sexually dimorphic because memory performance is better in the former than in the latter. In females, maternal experience enhances spatial memory. We used the NOR test to evaluate short- and long-term recognition memory in both sexes in the high- and low-yawning sublines of rats (HY and LY, respectively), which were generated via a strict inbreeding process from the Sprague‒Dawley (SD) strain for more than ninety generations. Additionally, we evaluated the effect of maternal experience using nulliparous, primiparous, biparous, and multiparous HY, LY and SD dams. Our results revealed that LY rats presented less thigmotaxis, with lower central square crosses and more vertical exploration in the open-field arena, suggesting that they experienced anxiety. Additionally, LY males performed significantly better than LY females in short- and long-term NOR memory, and LY males performed significantly better than SD rats did. Among females, two maternal experiences negatively affected short-term memory in the LY and HY sublines with respect to primiparous dams, and HY dams had better memory performance in the NOR test than did SD dams. Our findings suggest that the yawning sublines are suitable for studying the neurobiological basis of different memory processes under different endocrine conditions in highly inbred groups of rats.

TREM1 induces microglial ferroptosis through the PERK pathway in diabetic-associated cognitive impairment

Ferroptosis is involved in neurodegenerative disorders including diabetes-associated cognitive impairment (DACI). As central immune cells, microglia have strong siderophilic properties. However, the role of iron deposition in microglia and the underlying regulatory mechanism remains unclear in DACI. Here, we established high glucose (HG) model in BV2/HMC3 cells and diabetes model in C57BL/6 J mice with HFD and STZ. Transmission Electron Microscopy, Western blot, assay kits of Fe2+, GSH/GSSG, MDA and ROS were carried out in vitro. Prussian blue staining, Western blot and immunofluorescence were implemented in vivo. Y-maze and novel object recognition were performed to assess cognitive performance. LP17 was used to inhibit TREM1 (triggering receptor expressed on myeloid cells 1) specifically in vivo and vitro. We found excessively deposited iron and significant reduction in antioxidants in hippocampal microglia of mice with DACI, concomitant with increased TREM1 (a microglia-specific inflammatory amplifier). Furthermore, LP17 (TREM1 specific inhibitor) ameliorated cognitive impairment caused by HFD/STZ through relieving iron accumulation and antioxidant inactivation. In vitro, ferroptosis was induced by HG in mice microglia-BV2 and human microglia-HMC3 cells, which could be blocked by a ferroptosis inhibitor-Fer-1 and LP17. Moreover, PERK pathway of endoplasmic reticulum stress was activated by HG, and then reversed by PERK inhibitor GSK2606414 and LP17 followed by improved ferroptosis in HG-cultured BV2. In summary, our results indicated that TREM1 effectively aggravates T2DM-associated microglial iron accumulation through the PERK pathway of ERS, which contributes to antioxidant inactivation and lipid peroxidation, eventually, massively boosted ROS result in microglial ferroptosis. The mechanism elucidation in our study may shed light on targeted therapy of DACI.

Discriminative Deep Canonical Correlation Analysis for Multi-View Data.

Over the past few years, multimodal data analysis has emerged as an inevitable method for identifying sample categories. In the multi-view data classification problem, it is expected that the joint representation should include the supervised information of sample categories so that the similarity in the latent space implies the similarity in the corresponding concepts. Since each view has different statistical properties, the joint representation should be able to encapsulate the underlying nonlinear data distribution of the given observations. Another important aspect is the coherent knowledge of the multiple views. It is required that the learning objective of the multi-view model efficiently captures the nonlinear correlated structures across different modalities. In this context, this article introduces a novel architecture, termed discriminative deep canonical correlation analysis (D2CCA), for classifying given observations into multiple categories. The learning objective of the proposed architecture includes the merits of generative models to identify the underlying probability distribution of the given observations. In order to improve the discriminative ability of the proposed architecture, the supervised information is incorporated into the learning objective of the proposed model. It also enables the architecture to serve as both a feature extractor as well as a classifier. The theory of CCA is integrated with the objective function so that the joint representation of the multi-view data is learned from maximally correlated subspaces. The proposed framework is consolidated with corresponding convergence analysis. The efficacy of the proposed architecture is studied on different domains of applications, namely, object recognition, document classification, multilingual categorization, face recognition, and cancer subtype identification with reference to several state-of-the-art methods.

Reliability and validity of facial expression recognition in the screening of generalized anxiety disorder

IntroductionAnxiety disorder is one of the most prevalent mental disorders in China. However, there are obvious subjective factors in the current assessment of anxiety disorders, which may lead to certain diagnostic errors. The identification and diagnosis of anxiety disorders can be further improved if objective biological indicators are added in the assessment process. The current research validates facial expression recognition as a screening tool to assist in detecting generalized anxiety disorder. MethodsBased on the International Affective Picture System, we constructed an aided diagnostic experimental paradigm and recorded their facial expression. The split-half reliability was displayed by the Pearson correlation heatmap. The paradigm, GAD-7 and HAMA scales were administered to 60 generalized anxiety disorder patients and 60 matched healthy controls to evaluate the criterion-related validity. Additionally, we conducted a diagnostic study by using MINI as a gold standard and calculated ROC analysis to examine the screening performance of the facial expressions. ResultsThe heatmap showed very high correlations (r > 0.60, PS < 0.05) along the diagonal of the square heatmap (from the bottom left corner to the top right). The Pearson correlation coefficients between the GAD-7, HAMA and seven facial expressions ranged from −0.35(neutral, P < 0.01) to 0.34(angry, P < 0.01). The intergroup effects of neutral, anger and fear emotions were statistically significant (F = 18.893, P < 0.001; F = 20.535, P < 0.001; F = 9.091, P = 0.003). ROC analysis showed AUC for neutral, angry and scared facial expressions were 0.723, 0.792 and 0.727 respectively. ConclusionThis study constructed a tool for auxiliary screening of GAD patients and provided an objective automatic facial expression recognition method to assist psychological diagnosis.

Design and Practice of Virtual Experimental Scenes Integrating Computer Vision and Image Processing Technologies

In this work, we introduce a novel framework, GAN-based Image Processing (GAN-IP), to design and manipulate digital experimental settings that effectively combine computer vision and image processing technology. Using the skills of Generative Adversarial Networks (GANs), GAN-IP creates and complements virtual scenes and affords rich, adaptive surroundings for analysing and creating computationally smart and perceptive algorithms. GAN-IP solves the pressing troubles of variability and absence of data through synthesising realistic pictures and scenarios, enabling simulations of the diverse environments in which computer vision structures have to function. Our approach improves the fidelity and sort of digital scenes and introduces a way to mechanically alter and evoke a pleasant image, enabling more accurate and powerful computer vision and prescient models. Through extensive experimentation, GAN-IP demonstrates remarkable improvements in the performance of computer vision tasks, including object detection, segmentation, and recognition in complicated virtual environments. This research lays the foundation for future studies in this field and provides an adaptive tool for researchers and practitioners to simulate and test superior computer imaginative and prescient image processing technologies.

ExamGuard: Smart contracts for secure online test

The education sector is currently experiencing profound changes, primarily driven by the widespread adoption of online platforms for conducting examinations. This paper delves into the utilization of smart contracts as a means to revolutionize the monitoring and execution of online examinations, thereby guaranteeing the traceability of evaluation data and examinee activities. In this context, the integration of advanced technologies such as the PoseNet algorithm, derived from the TensorFlow Model, emerges as a pivotal component. By leveraging PoseNet, the system adeptly identifies both single and multiple faces of examinees, thereby ensuring the authenticity and integrity of examination sessions. Moreover, the incorporation of the COCO dataset facilitates the recognition of objects within examination environments, further bolstering the system's capabilities in monitoring examinee activities.of paramount importance is the secure storage of evidence collected during examinations, a task efficiently accomplished through the implementation of the blockchain technology. This platform not only ensures the immutability of data but also safeguards against potential instances of tampering, thereby upholding the credibility of examination results. Through the utilization of smart contracts, the proposed framework not only streamlines the examination process but also instills transparency and integrity, thereby addressing inherent challenges encountered in traditional examination methods. One of the key advantages of this technological integration lies in its ability to modernize examination procedures while concurrently reinforcing trust and accountability within the educational assessment ecosystem. By harnessing the power of smart contracts, educational institutions can mitigate concerns pertaining to data manipulation and malpractice, thereby fostering a more secure and reliable examination environment. Furthermore, the transparency afforded by blockchain technology ensures that examination outcomes are verifiable and auditable, instilling confidence among stakeholders and enhancing the overall credibility of the assessment process. In conclusion, the adoption of smart contracts represents a paradigm shift in the realm of educational assessment, offering a comprehensive solution to the challenges posed by traditional examination methods. By embracing advanced technologies such as PoseNet and blockchain, educational institutions can not only streamline examination procedures but also uphold the highest standards of integrity and accountability. As such, the integration of smart contracts holds immense potential in shaping the future of online examinations, paving the way for a more efficient, transparent, and trustworthy assessment ecosystem.

Joint administration of sub-threshold doses of the acetylcholinesterase inhibitor donepezil with those of the NMDA receptor antagonist ketamine improved rats’ recognition memory abilities

Alzheimer’s Disease (AD) is a serious progressive neurodegenerative illness conducting to the decay of cognitive functions. A few drugs have been approved for the therapy of AD, including the acetylcholinesterase inhibitors (AChEIs) like donepezil. Their efficiency, however, is modest and their application is associated with toxicity. Recently, the N-methyl-D-aspartate (NMDA) receptor antagonist ketamine, a rapidly acting antidepressant, has been proposed as a potential agent for the treatment of AD. The present study was designed to investigate the effects exerted by the combination of sub-threshold doses of donepezil with those of ketamine on rats’ recognition memory abilities. For these experiments, the object recognition task (ORT) and the object location task (OLT), two procedures assessing non-spatial and spatial recognition memory respectively in rodents were used. Post-training acute administration of inactive doses of donepezil (0.3 mg/kg) and ketamine (1 mg/kg) counteracted non-spatial and spatial recognition memory impairments. The present findings, although preliminary, propose that the combined administration of ketamine and donepezil could represent a new strategy for the therapy of memory disorders, a common feature of AD patients.

Dysregulating mTORC1-4E-BP2 signaling in GABAergic interneurons impairs hippocampus-dependent learning and memory.

Memory formation is contingent on molecular and structural changes in neurons in response to learning stimuli-a process known as neuronal plasticity. The initiation step of mRNA translation is a gatekeeper of long-term memory by controlling the production of plasticity-related proteins in the brain. The mechanistic target of rapamycin complex 1 (mTORC1) controls mRNA translation, mainly through phosphorylation of the eukaryotic initiation factor 4E (eIF4E)-binding proteins (4E-BPs) and ribosomal protein S6 kinases (S6Ks). mTORC1 signaling decreases throughout brain development, starting from the early postnatal period. Here, we discovered that in mice, the age-dependent decrease in mTORC1 signaling occurs selectively in excitatory but not inhibitory neurons. Using a gene conditional knockout (cKO) strategy, we demonstrate that either up- or downregulating the mTORC1-4E-BP2 axis in GAD65 inhibitory interneurons, but not excitatory neurons, results in long-term object recognition and object location memory deficits. Our data indicate that the mTORC1 pathway in inhibitory but not excitatory neurons plays a key role in memory formation.

Cognitive-Enhancing Effect of Marine Brown Algae-Derived Phenolics through S100B Inhibition and Antioxidant Activity in the Rat Model of Ischemic Stroke.

Cognitive impairments are frequently reported after ischemic strokes. Novel and effective treatments are required. This study aimed to develop a functional ingredient obtained from marine algae and to determine the effect of the extract on antioxidative stress, as well as neuroprotective effects, in a rat model of MCAO-induced ischemic stroke. Among the selected marine algal extracts, Sargassum polycystum displayed the highest total phenolic content and antioxidative potential, and was subsequently used to evaluate cognitive function in rat models of ischemic stroke. The S. polycystum extract, administered at doses of 100, 300, and 500 mg/kg BW, significantly improved cognitive function by enhancing cognitive performance in the Morris water maze and novel object recognition tests. Biochemical changes revealed that providing S. polycystum increased the activities of SOD, CAT, and GSH-Px by 52.48%, 50.77%, and 66.20%, respectively, and decreased the concentrations of MDA by 51.58% and S100B by 36.64% compared to the vehicle group. These findings suggest that S. polycystum extract may mitigate cognitive impairment in ischemic stroke by reducing oxidative stress and inhibiting S100B expression, thus highlighting its potential as a functional ingredient for drugs and nutraceuticals aimed at neuroprotection.

Dimensionality reduction for off-line object recognition and detection using supervised learning

Dimensionality reduction for off-line object recognition and detection using supervised learning

Treating Traumatic Brain Injury with Exercise: Onset Delay and Previous Training as Key Factors Determining its Efficacy

Purpose Exercise reduces cognitive deficits in traumatic brain injury (TBI), but early post-trauma exercise is often discouraged due to potential harm. The purpose was to evaluate the interaction between pre- and post-injury physical exercise on cognition, neuronal survival and inflammation. Methods Rats were either sham-operated and kept sedentary (Sham) or subjected to controlled cortical impact injury and then distributed into sedentary (Tbi), pre-injury exercise (Pre-Tbi), post-injury exercise with early (24 hours, Tbi-early) or late (6 days, Tbi-late) onset, and a combination of pre- and post-injury exercise with early (Pre-Tbi-early) or late (Pre-Tbi-late) onset. Object recognition memory, hippocampal volume, neuronal survival (NeuN+) in the hippocampus and perirhinal cortex, and microglial activity (Iba-1) in the hippocampus were evaluated. Results All exercise conditions, except TBI-early, attenuated the significant memory impairment at 24-hour retention caused by TBI. Additionally, Pre-TBI-early treatment led to memory improvement at 3-hour retention. Pre-TBI reduced neuronal death and microglial activation in the hippocampus. TBI-late, but not TBI-early, mitigated hippocampal volume loss, loss of mature neurons in the hippocampus, and inflammation. Combining pre-injury and early-onset exercise reduced memory deficits but did not affect neuronal death or microglial activation. Combining pre-injury and late-onset exercise had a similar memory-enhancing effect than late post-injury treatment alone, albeit with reduced effects on neuronal density and neuroinflammation. Conclusions Pre-TBI physical exercise reduces the necessary onset delay of post-TBI exercise to obtain cognitive benefits, yet the exact mechanisms underlying this reduction require further research.

Impact of levetiracetam and ethanol on memory, selected neurotransmitter levels, oxidative stress parameters, and essential elements in rats.

Ethanol disrupts brain activity and memory. There is evidence supporting the beneficial effect of levetiracetam on alcohol consumption. Therefore, the aim of the study was to examine whether levetiracetam has a protective activity against ethanol-induced memory impairment, alterations in selected neurotransmission activities, oxidative stress, and selected essential elements in rats. The rats were given levetiracetam (300mg/kg b.w. po) with ethanol for three weeks prior to behavioral tests. Spatial memory was tested using the Morris water maze, while recognition memory was evaluated using the Novel object recognition test. The GABA and glutamate concentration was determined in three rat brain regions (cerebellum, hippocampus, and cerebral cortex). Serum oxidative stress parameters and selected essential elements concentration (Cu, Mn, Zn, Fe, Mg) in the rat brain were analyzed. Levetiracetam administered with ethanol improved spatial memory, but did not affect abstinence-induced impairment. The drug also decreased ethanol-induced long-term recognition memory impairment. No alterations in glutamate levels were observed. GABA levels were elevated by levetiracetam in the cerebral cortex and by ethanol in the cerebellum. Ethanol increased catalase activity (CAT) and decreased superoxide dismutase activity (SOD) in the serum. Levetiracetam significantly increased the activity of SOD. Alcohol disrupted the levels of trace elements (Mn, Zn, Mg) in the rat brain. Additionally, levetiracetam alone increased Mg, Fe, and Cu concentrations while all animals receiving the drug also had significantly lower concentrations of Zn. Levetiracetam had differential effects against ethanol-induced impairments. These findings could have important implications for future levetiracetam treatment in patients.

Effects of immunosuppression after limb fracture in mice on nociceptive, cognitive, and anxiety-related outcomes.

Chronic pain is a common and problematic consequence of injuries with few proven methods for prevention or treatment. In addition to pain, functional limitations and neuropsychiatric changes such as cognitive impairment and anxiety worsen outcomes. To determine whether inhibiting activation of the adaptive immune response after limb fracture would reduce pain, functional loss, memory changes, and anxiety. These experiments used a murine tibial fracture/cast immobilization model that develops these adverse outcomes. Adaptive immunity was blocked using the immunosuppressant FK506 beginning at the time of fracture. The administration of FK506 reduced mechanical allodynia and hind limb unweighting for weeks after cast removal as well as nonevoked pain measures. Fracture was associated with working memory loss in the Y-maze assay in vehicle- but not FK506-treated mice. Object recognition memory was not improved with FK506 after fracture. Also, vehicle- but not FK506-treated mice developed an anxiety phenotype. Impaired running wheel performance after cast removal over the following 2 weeks was not improved with FK506 administration. In addition, FK506 treatment blocked Immunoglobulin M (IgM) accumulation in the skin of the fractured limbs, and hippocampal enhancement of matrix metalloproteinase-8 expression, a metalloproteinase associated with neuroplastic changes after injuries, was completely blocked. Taken together, our results show that blocking the adaptive immune response after limb trauma reduces the severity of nociceptive and biological changes. The same treatment may reduce the adverse consequences of anxiety and memory deficits using some measures, but other measures of memory are not affected, and activity is not enhanced.

Administration of Aripiprazole Alleviates Memory Impairment and Restores Damaged Glutamatergic System in 5xFAD Mice.

Many patients with Alzheimer's disease (AD) also have psychosis, and it has been reported that these patients have more severely impaired cognitive functions than patients without psychosis. The glutamatergic system in the brain is known to play an important role in memory and learning in the neural circuits. However, there has been limited research on how antipsychotic drugs affect the glutamatergic system of AD. Therefore, we aimed to investigate the effects of aripiprazole on the glutamatergic system in an animal model of AD using functional molecular imaging. In this study, 5xFAD mice were used as the animal model. At the age of 5months, the mice were divided into wild-type, vehicle control, and aripiprazole-treated groups (n = 6 per group). The aripiprazole-treated group was administered aripiprazole for 2months at a dose of 1mg·kg-1·day-1. At 7months of age, the animals underwent behavioral tests and glutamate positron emission tomography (PET) scans. The aripiprazole-treated group exhibited alleviated memory impairment in a novel object recognition test. Moreover, this group displayed 7-8% higher binding in the glutamate PET scan than the vehicle-treated 5xFAD group. Postmortem examination confirmed the recovery of glutamatergic damage. The administration of aripiprazole alleviated memory impairment and restored the damaged glutamatergic system in 5xFAD mice. Although the use of aripiprazole in AD patients may be a constraint in terms of safety, we confirmed the possibility that the administration of antipsychotic drugs can be effective in AD.

Synaptophysin and GSK-3beta activity in the prefrontal cortex may underlie the effects of REM sleep deprivation and lithium on behavioral functions and memory performance in male rats

Rapid-eye movement (REM) stage of sleep serves a critical role in processing cognitive and behavioral functions. Evidence shows that REM sleep deprivation (REM SD) strongly affects the mood state and cognitive abilities. However, there are many inconsistent reports. Although the exact molecular mechanisms underlying REM SD effects have not well been discovered, however, molecular factors including those affected synaptic plasticity and mood state may be involved. There are two important molecular factors that have not been well studied: synaptophysin and glycogen synthase kinase-3 beta (GSK-3beta). The present study aimed to investigate the role of synaptophysin and GSK-3beta in the modulation of memory and behavioral changes induced by REM SD and lithium (as a potent GSK-3beta inhibitor and mood stabilizer). Multiple platform apparatus was used to induce REM SD for 48 h. Lithium was injected at the dose of 50 mg/kg, intraperitoneal (i.p.). Locomotor activity, anxiety-like behavior, pain threshold, novel object recognition memory, and synaptophysin and GSK-3beta level in the prefrontal cortex were evaluated. Results showed REM SD increased locomotor activity, decreased pain threshold, impaired novel object recognition memory, decreased synaptophysin and increased GSK-3beta levels. Lithium reversed these effects. Anxiety-like behavior was unaffected. For the first time, the present study showed that GSK-3beta and synaptophysin may be involved in the modulation of behavior and cognition induced by REM SD and lithium. In conclusion, we suggested that GSK-3beta upregulation and synaptophysin downregulation may underlie the deleterious effects of REM SD, while lithium may counteract REM SD effects via restoring the level of both.