Comparison of AI with and without hand-crafted features to classify Alzheimer's disease in different languages.

BACKGROUND: Detecting and analyzing Alzheimer's disease (AD) in its early stages is a crucial and significant challenge. Speech data from AD patients can aid in diagnosing AD since the speech features have common patterns independent of race and spoken language. However, previous models for diagnosing AD from speech data have often focused on the characteristics of a single language, with no guarantee of scalability to other languages. In this study, we used the same method to extract acoustic features from two language datasets to diagnose AD. METHODS: Using the Korean and English speech datasets, we used ten models capable of real-time AD and healthy control classification, regardless of language type. Four machine learning models were based on hand-crafted features, while the remaining six deep learning models utilized non-explainable features. RESULTS: The highest accuracy achieved by the machine learning models was 0.73 and 0.69 for the Korean and English speech datasets, respectively. The deep learning models' maximum achievable accuracy reached 0.75 and 0.78, with their minimum classification time of 0.01s and 0.02s. These findings reveal the models' robustness regardless of Korean and English and real-time diagnosis of AD through a 30-s voice sample. CONCLUSION: Non-explainable deep learning models that directly acquire voice representations surpassed machine learning models utilizing hand-crafted features in AD diagnosis. In addition, these AI models could confirm the possibility of extending to a language-agnostic AD diagnosis.

Decreased Serum Cocaine- and Amphetamine-Regulated Transcript Level in Internet Gaming Disorder.

OBJECTIVE: Vulnerability to internet gaming disorder (IGD) has increased as internet gaming continues to grow. Cocaine- and amphetamine-regulated transcript (CART) is a hormone that plays a role in reward, anxiety, and stress. The purpose of this study was to identify the role of CART in the pathophysiology of IGD. METHODS: The serum CART levels were measured by enzyme-linked immunosorbent assay, and the associations of the serum CART level with psychological variables were analyzed in patients with IGD (n=31) and healthy controls (HC) (n=42). RESULTS: The serum CART level was significantly lower in the IGD than HC group. The IGD group scored significantly higher than the HC group on the psychological domains of depression, anxiety, the reward response in the Behavioral Activation System and Behavioral Inhibition System. There were no significant correlations between serum CART level and other psychological variables in the IGD group. CONCLUSION: Our results indicate that a decrease in the expression of the serum CART level is associated with the vulnerability of developing IGD. This study supports the possibility that CART is a biomarker in the pathophysiology of IGD.

Effects of bilateral tDCS over DLPFC on response inhibition, craving, and brain functional connectivity in Internet gaming disorder: A randomized, double-blind, sham-controlled trial with fMRI.

Background and aims: Impaired inhibitory control accompanied by enhanced craving is hallmark of addiction. This study investigated the effects of transcranial direct current stimulation (tDCS) on response inhibition and craving in Internet gaming disorder (IGD). We examined the brain changes after tDCS and their correlation with clinical variables. Methods: Twenty-four males with IGD were allocated randomly to an active or sham tDCS group, and data from 22 participants were included for analysis. Participants self-administered bilateral tDCS over the dorsolateral prefrontal cortex (DLPFC) for 10 sessions. Stop-signal tasks were conducted to measure response inhibition and participants were asked about their cravings for Internet gaming at baseline and post-tDCS. Functional magnetic resonance imaging data were collected at pre- and post-tDCS, and group differences in resting-state functional connectivity (rsFC) changes from the bilateral DLPFC and nucleus accumbens were examined. We explored the relationship between changes in the rsFC and behavioral variables in the active tDCS group. Results: A significant group-by-time interaction was observed in response inhibition. After tDCS, only the active group showed a decrease in the stop-signal reaction time (SSRT). Although craving decreased, there were no significant group-by-time interactions or group main effects. The anterior cingulate cortex (ACC) showed group differences in post- versus pre-tDCS rsFC from the right DLPFC. The rsFC between the ACC and left middle frontal gyrus was negatively correlated with the SSRT. Discussion and conclusion: Our study provides preliminary evidence that bilateral tDCS over the DLPFC improves inhibitory control and could serve as a therapeutic approach for IGD.

Developing a Cost-Effectiveness Model of Digital Therapeutics for Smoking Cessation.

The purpose of this research was to construct a Markov model of digital therapeutics to predict the lifetime costs and consequences that would be incurred by a hypothetical group of adult smokers in Korea who only made a single attempt to stop smoking. To determine the efficacy of DTx, we created an annual cycle Markov model. The result shows that the NRT strategy is determined as the dominant strategy. Digital therapeutics acts as a complement to pharmacotherapy and is a low-cost option.

The Present and Future of Artificial Intelligence-Based Medical Image in Diabetes Mellitus: Focus on Analytical Methods and Limitations of Clinical Use.

Artificial intelligence (AI)-based diagnostic technology using medical images can be used to increase examination accessibility and support clinical decision-making for screening and diagnosis. To determine a machine learning algorithm for diabetes complications, a literature review of studies using medical image-based AI technology was conducted using the National Library of Medicine PubMed, and the Excerpta Medica databases. Lists of studies using diabetes diagnostic images and AI as keywords were combined. In total, 227 appropriate studies were selected. Diabetic retinopathy studies using the AI model were the most frequent (85.0%, 193/227 cases), followed by diabetic foot (7.9%, 18/227 cases) and diabetic neuropathy (2.7%, 6/227 cases). The studies used open datasets (42.3%, 96/227 cases) or directly constructed data from fundoscopy or optical coherence tomography (57.7%, 131/227 cases). Major limitations in AI-based detection of diabetes complications using medical images were the lack of datasets (36.1%, 82/227 cases) and severity misclassification (26.4%, 60/227 cases). Although it remains difficult to use and fully trust AI-based imaging analysis technology clinically, it reduces clinicians' time and labor, and the expectations from its decision-support roles are high. Various data collection and synthesis data technology developments according to the disease severity are required to solve data imbalance.

Study of the factors influencing the use of MyData platform based on personal health record data sharing system.

BACKGROUND: The application of telemedicine and electronic health (eHealth) technology has grown in importance during the COVID-19 pandemic, and a new approach in personal data management and processing MyData, has emerged. Data portability and informational self-determination are fundamental concepts of MyData. This study analysed the factors that influence acceptance of the MyData platform, which, reflects the right to self-determine personal data. METHODS: The study involved participants having experience using the MyData platform, and the key factors of the unified theory of acceptance and use of technology were used in the research model (performance expectancy, effort expectancy, social influence, facilitation condition and behavioural intention to use). The questionnaire comprided 27 items, and system usage log data were used to confirm that behavioural intention to use affected actual use behaviour through structural equation modeling. RESULTS: In total, 1153 participants completed the survey. The goodness of fit in the structural equation model indices indicates that the data fit the research model well. Performance expectancy, social influence, and facilitating conditions had direct effects on behavioural intention to use. We used system usage log data to confirm that behavioural intention to use positively affected actual use behaviour. The impact of the main factors in the unified theory of acceptance and use of technology was not moderated by age or gender, except for performance expectancy. CONCLUSIONS: This study is the first to examine the factors influencing the use of the MyData platform based on the personal health record data sharing system in Korea. In addition, the study confirmed the use behaviour of the MyData platform utilising the system's actual usage log for each function and analysing the effect of the intention of use on actual use. Our study serves as a significant foundation for the acceptance of data portability and sharing concepts. It also lays the foundation for expanding the data economy and ecosystem in the pandemic era.

Altered connectivity in the right inferior frontal gyrus associated with self-control in adolescents exhibiting problematic smartphone use: A fMRI study.

BACKGROUND: With the continued spread of smartphones and development of the internet, the potential negative effects arising from problematic smartphone use (PSU) in adolescents are being reported on an increasing basis. This study aimed to investigate whether altered resting-state functional connectivity (rsFC) is related to the psychological factors underlying PSU in adolescents. METHODS: Resting-state functional magnetic resonance images were acquired from 47 adolescents with PSU and 46 healthy control adolescents (the CON group). Seed-based functional connectivity analyses were then performed to compare the two groups with respect to rsFC in the right inferior frontal gyrus, associated with various forms of self-control, and rsFC in the left inferior frontal gyrus. RESULTS: Compared to the CON group, the PSU group exhibited a reduction in rsFC between the right inferior frontal gyrus and limbic areas, including the bilateral parahippocampal gyrus, the left amygdala, and the right hippocampus. In addition, a reduction in fronto-limbic rsFC was associated with the severity of PSU, the degree of self-control, and the amount of time the subjects used their smartphones. CONCLUSION: Adolescents with PSU exhibited reduced levels of fronto-limbic functional connectivity; this mechanism is involved in salience attribution and self-control, attributes that are critical to the clinical manifestation of substance and behavioral addictions. Our data provide clear evidence for alterations in brain connectivity with respect to self-control in PSU.

Reduced Volume of a Brainstem Substructure in Adolescents with Problematic Smartphone Use.

OBJECTIVES: Despite the growing concern regarding the adverse effects related to problematic smartphone use (PSU), little is known about underlying morphologic changes in the brain. The brainstem is a deep brain structure that consists of several important nuclei associated with emotions, sensations, and motor functions. In this study, we sought to examine the difference in the volume of brainstem substructures among adolescents with and without PSU. METHODS: A total of 87 Korean adolescents participated in this study. The PSU group (n=20, age=16.2±1.1, female:male=12:8) was designated if participants reported a total Smartphone Addiction Proneness Scale (SAPS) score of ≥42, whereas the remaining participants were assigned to the control group (n=67, age=15.3±1.7, female:male=19:48). High-resolution T1 magnetic resonance imaging was performed, and the volume of each of the four brainstem substructures [midbrain, pons, medulla, and superior cerebellar peduncle (SCP)] was measured. Analysis of covariance was conducted to reveal group differences after adjusting for effects of age, gender, whole brain-stem volume, depressive symptoms, and impulsivity. RESULTS: The PSU group showed a significantly smaller volume of the SCP than the control group (F=8.273, p=0.005). The volume of the SCP and the SAPS score were negatively correlated (Pearson's r=-0.218, p=0.047). CONCLUSION: The present study is the first to reveal an altered volume of the brainstem substructure among adolescents with PSU. This finding suggests that the altered white matter structure in the brainstem could be one of the neurobiological mechanisms underlying behavioral changes in PSU.

Machine learning prediction of dropping out of outpatients with alcohol use disorders.

BACKGROUND: Alcohol use disorder (AUD) is a chronic disease with a higher recurrence rate than that of other mental illnesses. Moreover, it requires continuous outpatient treatment for the patient to maintain abstinence. However, with a low probability of these patients to continue outpatient treatment, predicting and managing patients who might discontinue treatment becomes necessary. Accordingly, we developed a machine learning (ML) algorithm to predict which the risk of patients dropping out of outpatient treatment schemes. METHODS: A total of 839 patients were selected out of 2,206 patients admitted for AUD in three hospitals under the Catholic Central Medical Center in Korea. We implemented six ML models-logistic regression, support vector machine, k-nearest neighbor, random forest, neural network, and AdaBoost-and compared the prediction performances thereof. RESULTS: Among the six models, AdaBoost was selected as the final model for recommended use owing to its area under the receiver operating characteristic curve (AUROC) of 0.72. The four variables affecting the prediction based on feature importance were the length of hospitalization, age, residential area, and diabetes. CONCLUSION: An ML algorithm was developed herein to predict the risk of patients with AUD in Korea discontinuing outpatient treatment. By testing and validating various machine learning models, we determined the best performing model, AdaBoost, as the final model for recommended use. Using this model, clinicians can manage patients with high risks of discontinuing treatment and establish patient-specific treatment strategies. Therefore, our model can potentially enable patients with AUD to successfully complete their treatments by identifying them before they can drop out.

Caudate nucleus volume mediates the link between glutamatergic neurotransmission and problematic smartphone use in youth.

BACKGROUND AND AIMS: Problematic smartphone use (PSU) is growing rapidly among teens. It has similar presentations as other behavioral addictions in terms of excessive use, impulse control problems, and negative consequences. However, the underlying neurobiological mechanisms remain undiscovered. We hypothesized that structural changes in the striatum might serve as an important link between alteration in glutamate signaling and development of PSU. METHODS: Among 88 participants, twenty (F:M, 12:8; age 16.2 ± 1.1) reported high scores in the smartphone addiction proneness scale (SAPS) with a cut-off score of 42; the other 68 (F:M, 19:49; age 15.3 ± 1.7) comprised the control group. Sociodemographic data and depression, anxiety, and impulsivity traits were measured. Striatal volumes (caudate, putamen, and nucleus accumbens) were estimated from T1 imaging data. Serum glutamate levels were estimated from peripheral blood samples. Group comparisons of each data were performed after controlling for age and gender. Mediation analyses were conducted to test the indirect effects of glutamate level alteration on PSU through striatal volumetric alteration. RESULTS: The PSU group showed a decrease in both caudate volumes than the control group. Left caudate volume was positively correlated with serum glutamate level, and negatively with impulsivity traits and SAPS scores. The mediation model revealed a significant indirect effect of serum glutamate on SAS scores through the reduced left caudate volume. DISCUSSION AND CONCLUSIONS: This study suggests that altered glutamatergic neurotransmission may be associated with PSU among teens, possibly through reduced left caudate volume. Current findings might support neural mechanisms of smartphone addiction.

The neural basis underlying impaired attentional control in problematic smartphone users.

As a portable media device that enables ubiquitous access to friends and entertainment, smartphones are inextricably linked with our lives. Although there is growing concern about the detrimental effect of problematic smartphone use on attentional control, the underlying neural mechanisms of impaired attentional control in problematic smartphone users (PSU) has yet to be investigated. Using a modified cognitive conflict task, we examined behavioral performance in the presence of distracting words during functional magnetic resonance imaging in 33 PSU and 33 control participants (CON). Compared with the CON group, the PSU group demonstrated impaired performance that was accompanied by constantly enhanced but not differentiated activation in the frontoparietal regions across all conditions, regardless of distractor saliency. The inferior parietal lobule (IPL) activation in the PSU group, in particular, showed an association with performance deficits in the distractor conditions. Furthermore, the PSU group exhibited decreased functional connectivity of the right IPL with the right superior temporal gyrus of the ventral attention system in the attention-demanding condition relative to the easiest condition, which was associated with the severe dependence on smartphone use. Our findings suggest that greater distractibility in the PSU group during the attentional control task may be associated with inefficient recruitment of the ventral attention network involved in bottom-up attentional processing, as indicated by hyperactivation but less coherence within the network. The present study provides evidence for understanding the neural mechanisms underlying the impaired ability to keep attention from being oriented to task-irrelevant stimuli observed in PSU.

Altered core networks of brain connectivity and personality traits in internet gaming disorder.

BACKGROUND AND AIMS: Although the Internet has provided convenience and efficiency in many areas of everyday life, problems stemming from Internet use have also been identified, such as Internet gaming disorder (IGD). Internet addiction, which includes IGD, can be viewed as a behavioral addiction or impulse control disorder. This study investigated the altered functional and effective connectivity of the core brain networks in individuals with IGD compared to healthy controls (HCs). METHODS: Forty-five adults with IGD and 45 HCs were included in this study. To examine the brain networks related to personality traits that influence problematic online gaming, the left and right central executive network (CEN) and the salience network (SN) were included in the analysis. Also, to examine changes in major brain network topographies, we analyzed the default mode network (DMN). RESULTS: IGD participants showed lower functional connectivity between the dorsal lateral prefrontal cortex (DLPFC) and other regions in the CEN than HC participants during resting state. Also, IGD participants revealed reduced functional connectivity between the dorsal anterior cingulate cortex and other regions in the SN and lower functional connectivity in the medial prefrontal cortex of the anterior DMN. Notably, in IGD individuals but not HC individuals, there was a positive correlation between IGD severity and effective connectivity and a positive correlation between reward sensitivity and effective connectivity within the ventral striatum of the SN. CONCLUSIONS: Problematic online gaming was associated with neurofunctional alterations, impairing the capacity of core brain networks.

Increase of orexin A in the peripheral blood of adolescents with Internet gaming disorder.

BACKGROUND AND AIMS: Overindulgence in Internet gaming, which is related to rapid development of the online game industry, can cause a psychiatric disorder known as Internet gaming disorder (IGD). The number of adolescents with IGD is on the rise in countries with developed Internet technologies, such as South Korea. Therefore, it is important to develop biomarkers to detect patients at high risk of IGD. This study investigated expression levels of proteins in the blood of adolescents to provide insight into the development of biomarkers. METHODS: We collected blood samples from 73 subjects [40 healthy adolescents (Internet gaming control, IGC) and 33 adolescents with IGD] between 13:00 and 15:00. We analyzed the expression levels of orexin A, oxytocin, cortisol, melatonin, BDNF, sICAM-1, RANTES, and NCAM using multiplex assay kits. RESULTS: Orexin A was significantly (p = .016) elevated in the IGD group and the expression levels of melatonin tended to be higher (p = .055) in the IGD group. On the other hand, increased Internet gaming time in the IGD group was negatively correlated (p = .041) with expression of BDNF. On the contrary, sICAM-1 associated with inflammation exhibited the tendency of the positive correlation (p = .073) with Internet gaming time in the IGD group. DISCUSSION AND CONCLUSIONS: We identified elevation of orexin A in the peripheral blood of adolescents with IGD and a negative correlation between Internet gaming time and BDNF in adolescents with IGD. Our results provide useful information to understand the pathophysiology of IGD in adolescents.

Prolonged Bedtime Smartphone Use is Associated With Altered Resting-State Functional Connectivity of the Insula in Adult Smartphone Users.

Prolonged bedtime smartphone use is often associated with poor sleep quality and daytime dysfunction. In addition, the unstructured nature of smartphones may lead to excessive and uncontrolled use, which can be a cardinal feature of problematic smartphone use. This study was designed to investigate functional connectivity of insula, which is implicated in salience processing, interoceptive processing, and cognitive control, in association with prolonged bedtime smartphone use. We examined resting-state functional connectivity (rsFC) of insula in 90 adults who used smartphones by functional magnetic resonance imaging (fMRI). Smartphone time in bed was measured by self-report. Prolonged bedtime smartphone use was associated with higher smartphone addiction proneness scale (SAPS) scores, but not with sleep quality. The strength of the rsFC between the left insula and right putamen, and between the right insula and left superior frontal, middle temporal, fusiform, inferior orbitofrontal gyrus and right superior temporal gyrus was positively correlated with smartphone time in bed. The findings imply that prolonged bedtime smartphone use can be an important behavioral measure of problematic smartphone use and altered insula-centered functional connectivity may be associated with it.

The Correlation between the Frontostriatal Network and Impulsivity in Internet Gaming Disorder.

As excessive use of internet gaming has become a serious public health concern, increasing studies have revealed that impulsivity is one of the important risk factors of internet gaming disorder (IGD). This study was designed to investigate the altered resting-state functional connectivity (FC) of the bilateral orbitofrontal cortex (OFC) in IGD participants and to examine its relationship with impulsivity compared with the normal controls (NC). Seed-based analyses verified that participants with IGD displayed decreased FC between the OFC and frontal, striatal, temporal and occipital regions different from NC. Moreover, IGD participants showed weankened FC from the OFC with dorsal anterior cingulate cortex as well as with dorsolateral prefrontal cortex and dorsal striatum as the results of group difference. These results could suggest that the decreased frontostriatal connectivity was associated with excessive internet gaming. Also, the increased FC in frontostriatal regions was correlated with impulse control in the NC but not the IGD participants. Further insight into the brain circuitry on frontostriatal could provide the target for developing treatment approaches of impulse control in IGD.

Alterations in the connection topology of brain structural networks in Internet gaming addiction.

Internet gaming addiction (IGA), as the most popular subtype of Internet addiction, is becoming a common and widespread mental health concern, but there are still debates on whether IGA constitutes a psychiatric disorder. The view on the brain as a complex network has developed network analysis of neuroimaging data, revealing that abnormalities of brain functional and structural systems are related to alterations in brain network configuration, such as small-world topology, in neuropsychiatric disorders. Here we applied network analysis to diffusion-weighted MRI data of 102 gaming individuals and 41 non-gaming healthy individuals to seek changes in the small-world topology of brain structural networks in IGA. The connection topology of brain structural networks shifted to the direction of random topology in the gaming individuals, irrespective of whether they were diagnosed with Internet gaming disorder. Furthermore, when we simulated targeted or untargeted attacks on nodes, the connection topology of the gaming individuals' brain structural networks under no attacks was comparable to that of the non-gaming healthy individuals' brain structural networks under targeted attacks. Alterations in connection topology provide a clue that Internet gaming addicted brains could be as abnormal as brains suffering from targeted damage.

Role of Frontostriatal Connectivity in Adolescents With Excessive Smartphone Use.

As smartphone use has grown rapidly over recent decade, it has been a growing interest in the potential negative impact of excessive smartphone use. In this study, we aim to identify altered brain connectivity associated with excessive smartphone use, and to investigate correlations between withdrawal symptoms, cortisol concentrations, and frontostriatal connectivity. We focused on investigating functional connectivity in frontostriatal regions, including the orbitofrontal cortex (OFC), midcingulate cortex (MCC), and nucleus accumbens (NAcc), which is related to reward processing and cognitive control. We analyzed data from 38 adolescents with excessive smartphone use (SP) and 42 healthy controls (HC). In the SP group compared with HC, we observed lower functional connectivity between the right OFC and NAcc, and between the left OFC and MCC. Moreover, functional connectivity between the MCC and NAcc was greater in SP compared with HC. Subsequently, we examined the relationship between Internet use withdrawal symptoms, cortisol concentrations, and functional connectivity between the OFC and NAcc in SP and HC. We observed that more severe withdrawal symptoms were associated with higher cortisol concentrations in adolescents with excessive smartphone use. The most interesting finding was that we observed a negative correlation between OFC connectivity with the NAcc and both withdrawal symptoms and cortisol concentrations. The functional connectivity between the OFC and NAcc, and between the OFC and MCC are related to cognitive control of emotional stimuli including reward. The current study suggests that adolescents with SP had reduced functional connectivity in these regions related to cognitive control. Furthermore, Internet use withdrawal symptoms appear to elicit cortisol secretion, and this psychophysiological change may affect frontostriatal connectivity. Our findings provide important clues to understanding the effects of excessive use of smartphones on brain functional connectivity in adolescence.

Discriminating Pathological and Non-pathological Internet Gamers Using Sparse Neuroanatomical Features.

Internet gaming disorder (IGD) is often diagnosed on the basis of nine underlying criteria from the latest version of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Here, we examined whether such symptom-based categorization could be translated into computation-based classification. Structural MRI (sMRI) and diffusion-weighted MRI (dMRI) data were acquired in 38 gamers diagnosed with IGD, 68 normal gamers diagnosed as not having IGD, and 37 healthy non-gamers. We generated 108 features of gray matter (GM) and white matter (WM) structure from the MRI data. When regularized logistic regression was applied to the 108 neuroanatomical features to select important ones for the distinction between the groups, the disordered and normal gamers were represented in terms of 43 and 21 features, respectively, in relation to the healthy non-gamers, whereas the disordered gamers were represented in terms of 11 features in relation to the normal gamers. In support vector machines (SVM) using the sparse neuroanatomical features as predictors, the disordered and normal gamers were discriminated successfully, with accuracy exceeding 98%, from the healthy non-gamers, but the classification between the disordered and normal gamers was relatively challenging. These findings suggest that pathological and non-pathological gamers as categorized with the criteria from the DSM-5 could be represented by sparse neuroanatomical features, especially in the context of discriminating those from non-gaming healthy individuals.

Involvement of amygdala-prefrontal dysfunction in the influence of negative emotion on the resolution of cognitive conflict in patients with schizophrenia.

INTRODUCTION: Patients with schizophrenia often have impaired cognition and abnormal conflict control. Conflict control is influenced by the emotional values of stimuli. This study investigated the neural basis of negative emotion interference with conflict control in schizophrenia. METHODS: Seventeen patients with schizophrenia and 20 healthy controls underwent functional magnetic resonance imaging while performing the emotional Simon task, in which positive or negative emotional pictures were located in congruent or incongruent positions. Analysis was focused on identifying brain regions with the significant interaction among group, emotion, and conflict in whole brain voxel-wise analysis, and abnormality in their functional connectivity in the patient group. RESULTS: The regions showing the targeted interaction was the right amygdala, which exhibited significantly reduced activity in the negative congruent (t = -2.168, p = 0.036) and negative incongruent (t = -3.273, p = 0.002) conditions in patients versus controls. The right amygdala also showed significantly lower connectivity with the right dorsolateral prefrontal cortex in the cognitive and emotional loading contrast (negative incongruent-positive congruent) in patients versus controls (t = -5.154, p < 0.01), but not in the cognitive-only or emotional-only loading contrast. CONCLUSIONS: These results suggest that negative emotion interferes with cognitive conflict resolution in patients with schizophrenia due to amygdala-dorsolateral prefrontal cortex disconnection. Based on these findings, interventions targeting conflict control under negative emotional influence may promote cognitive rehabilitation in patients with schizophrenia.

Effects of acute and chronic methamphetamine administration on cynomolgus monkey hippocampus structure and cellular transcriptome.

Methamphetamine (MA), a psychostimulant abused worldwide, gives rise to neurotoxicity in the hippocampus, resulting in cognitive impairments and hippocampal volume reduction. The cellular and molecular mechanisms associated with hippocampal impairments due to MA remain unknown. The aim of this study was to investigate the effects of MA on structural alterations and gene expressions in the hippocampus. We analyzed the pattern of volumetric changes in the hippocampus using magnetic resonance imaging (MRI) after acute and chronic administration of MA to cynomolgus macaques. In addition, we performed large-scale transcriptome profiling in the hippocampus using RNA-Seq technology. The hippocampus in response to acute and chronic MA exhibited a significant volumetric atrophy compared with the hippocampus of controls. The genes associated with cytoskeleton organization and phagocytosis were downregulated in the acute MA-treated group compared to the control group. On the other hand, genes associated with synaptic transmission, regulation of neuron differentiation and regulation of neurogenesis were downregulated in the chronic MA-treated group. We confirmed that expression patterns for ADM, BMP4, CHRD, PDYN, UBA1, profilin 2 (PFN2), ENO2 and NSE mRNAs were similar to the results from RNA-Seq based on quantitative RT-PCR. In particular, PFN2 mRNA and protein expression levels, which play important roles in actin cytoskeleton dynamics, were decreased by acute and chronic MA administration. These results not only aid the understanding of cellular and molecular mechanisms regulated by MA in the hippocampus but also suggest basic information aiding biomarker and novel drug development for treating hippocampal impairment caused by MA abuse.