Low-frequency rTMS induces modifications in cortical structural connectivity - functional connectivity coupling in schizophrenia patients with auditory verbal hallucinations.

Auditory verbal hallucinations (AVH) are distinctive clinical manifestations of schizophrenia. While low-frequency repetitive transcranial magnetic stimulation (rTMS) has demonstrated potential in mitigating AVH, the precise mechanisms by which it operates remain obscure. This study aimed to investigate alternations in structural connectivity and functional connectivity (SC-FC) coupling among schizophrenia patients with AVH prior to and following treatment with 1 Hz rTMS that specifically targets the left temporoparietal junction. Initially, patients exhibited significantly reduced macroscopic whole brain level SC-FC coupling compared to healthy controls. Notably, SC-FC coupling increased significantly across multiple networks, including the somatomotor, dorsal attention, ventral attention, frontoparietal control, and default mode networks, following rTMS treatment. Significant alternations in SC-FC coupling were noted in critical nodes comprising the somatomotor network and the default mode network, such as the precentral gyrus and the ventromedial prefrontal cortex, respectively. The alternations in SC-FC coupling exhibited a correlation with the amelioration of clinical symptom. The results of our study illuminate the intricate relationship between white matter structures and neuronal activity in patients who are receiving low-frequency rTMS. This advances our understanding of the foundational mechanisms underlying rTMS treatment for AVH.

Two subtypes of schizophrenia identified by an individual-level atypical pattern of tensor-based morphometric measurement.

Difficulties in parsing the multiaspect heterogeneity of schizophrenia (SCZ) based on current nosology highlight the need to subtype SCZ using objective biomarkers. Here, utilizing a large-scale multisite SCZ dataset, we identified and validated 2 neuroanatomical subtypes with individual-level abnormal patterns of the tensor-based morphometric measurement. Remarkably, compared with subtype 1, which showed moderate deficits of some subcortical nuclei and an enlarged striatum and cerebellum, subtype 2, which showed cerebellar atrophy and more severe subcortical nuclei atrophy, had a higher subscale score of negative symptoms, which is considered to be a core aspect of SCZ and is associated with functional outcome. Moreover, with the neuroimaging-clinic association analysis, we explored the detailed relationship between the heterogeneity of clinical symptoms and the heterogeneous abnormal neuroanatomical patterns with respect to the 2 subtypes. And the neuroimaging-transcription association analysis highlighted several potential heterogeneous biological factors that may underlie the subtypes. Our work provided an effective framework for investigating the heterogeneity of SCZ from multilevel aspects and may provide new insights for precision psychiatry.

The impact of depressive and anxious symptoms on non-suicidal self-injury behavior in adolescents: a network analysis.

PURPOSE: Conceptualizing adolescent NSSI and emotional symptoms as a system of causal elements could provide valuable insights into the development of non-suicidal self-injury (NSSI) in adolescent. This study aimed to explore the intricate relationship between NSSI, depressive symptoms, and anxious symptoms in adolescents, identifying key symptoms to establish a theoretical foundation for targeted and effective interventions addressing NSSI behaviors in this population. METHODS: A total of 412 adolescents with NSSI behaviors were selected from outpatients. Generalized anxious disorder scale (GAD-7) and patient health questionnaire (PHQ-9) were employed to measure anxious symptoms and depressive symptoms, respectively. The adolescent non-suicidal self-injury assessment questionnaire (ANSSIAQ) was used to evaluate NSSI of adolescent. Using network analysis, the NSSI、depressive symptoms and anxious symptoms network were constructed to identify the most central symptoms and the bridge symptoms within the networks. RESULTS: The findings revealed that the NSSI functional nodes "coping with sadness and disappointment" and "relieving stress or anxious" exhibited the strongest correlation, with a regularized partial correlation coefficient was 0.401. The symptoms "having a desire to harm oneself and unable to stop" and the node "depressive symptoms" had the highest strength centrality in the network, and their strength centrality indices were 1.267 and 1.263, respectively. The bridge nodes were "having a desire to harm oneself and unable to stop" and "expressing one's despair and hopelessness", with expected impact indices of 0.389 and 0.396, respectively. CONCLUSION: In adolescents, the network revealed a closer connection between NSSI and depressive symptoms. "The desire to not stop hurting oneself" is not only broadly connected to other nodes but also could activate other nodes to maintain NSSI behavior. In light of these findings, precise targets for pharmacological treatment, psychotherapy, physical therapy, etc., are identified for adolescents with NSSI. Targeting this specific aspect in interventions may contribute to preventing and reducing NSSI behavior in adolescents.

Cerebral blood flow changes in schizophrenia patients with auditory verbal hallucinations during low-frequency rTMS treatment.

Auditory verbal hallucinations (AVH) are a prominent symptom of schizophrenia. Low-frequency repetitive transcranial magnetic stimulation (rTMS) has been evidenced to improve the treatment of AVH in schizophrenia. Although abnormalities in resting-state cerebral blood flow (CBF) have been reported in schizophrenia, the perfusion alterations specific to schizophrenia patients with AVH during rTMS require further investigation. In this study, we used arterial spin labeling (ASL) to investigate changes in brain perfusion in schizophrenia patients with AVH, and their associations with clinical improvement following low-frequency rTMS treatment applied to the left temporoparietal junction area. We observed improvements in clinical symptoms (e.g., positive symptoms and AVH) and certain neurocognitive functions (e.g., verbal learning and visual learning) following treatment. Furthermore, at baseline, the patients showed reductions in CBF in regions associated with language, sensory, and cognition compared to controls, primarily located in the prefrontal cortices (e.g., left inferior frontal gyrus and left middle frontal gyrus), occipital lobe (e.g., left calcarine cortex), and cingulate cortex (e.g., bilateral middle cingulate cortex), compared to controls. Conversely, we observed increased CBF in the left inferior temporal gyrus and bilateral putamen in patients relative to controls, regions known to be involved in AVH. However, the hypoperfusion or hyperperfusion patterns did not persist and instead were normalized, and were related to clinical response (e.g., AVH) in patients during low-frequency rTMS treatment. Importantly, the changes in brain perfusion were related to clinical response (e.g., AVH) in patients. Our findings suggest that low-frequency rTMS can regulate brain perfusion involving critical circuits by its remote effect in schizophrenia, and may play an important mechanistic role in the treatment of AVH.

Aberrant temporal-spatial complexity of intrinsic fluctuations in major depression.

Accumulating evidence suggests that the brain is highly dynamic; thus, investigation of brain dynamics especially in brain connectivity would provide crucial information that stationary functional connectivity could miss. This study investigated temporal expressions of spatial modes within the default mode network (DMN), salience network (SN) and cognitive control network (CCN) using a reliable data-driven co-activation pattern (CAP) analysis in two independent data sets. We found enhanced CAP-to-CAP transitions of the SN in patients with MDD. Results suggested enhanced flexibility of this network in the patients. By contrast, we also found reduced spatial consistency and persistence of the DMN in the patients, indicating reduced variability and stability in individuals with MDD. In addition, the patients were characterized by prominent activation of mPFC. Moreover, further correlation analysis revealed that persistence and transitions of RCCN were associated with the severity of depression. Our findings suggest that functional connectivity in the patients may not be simply attenuated or potentiated, but just alternating faster or slower among more complex patterns. The aberrant temporal-spatial complexity of intrinsic fluctuations reflects functional diaschisis of resting-state networks as characteristic of patients with MDD.

A Duplex Polymerization Strategy for General, Programmable and High-Resolution Nanopore-Based Sensing.

Nanopore sensing is highly promising in single molecular analysis but their broad applications have been challenged by the limited strategies that can transduce a target-of-interest into a specific and anti-false/inference signal, especially for solid-state nanopores with relatively lower resolution and higher noise. Here we report a high-resolution signal-production concept named target-induced duplex polymerization strategy (DPS). Through linking the same or different duplex substrates (DSs) with a special linker (L) and an optional structure tag (ST), the DPS can generate target-specific DS polymers with highly controllable duration times, duration intervals and even distinguished secondary tagging currents. Experimentally, DPS mono-polymerization of single DS and co-polymerization of multiple DSs has verified the duration time of a DPS product is the sum of those for each DS monomer. Tetrahedron-DNA structures with different sizes are used as the STs to provide needle-like secondary peaks for further resolution enhancement and multiplex assay. With these examples DPS represents a general, programmable and advanced strategy that may simultaneously provide size-amplification, concentration amplification, and signal-specificity for molecular recognition. It is also promisingly in various applications regarding to single molecular investigation, such as polymerization degree, structure/side chain conformation, programmable multiplex decoding and information index.

Consistent brain structural abnormalities and multisite individualised classification of schizophrenia using deep neural networks.

BACKGROUND: Previous analyses of grey and white matter volumes have reported that schizophrenia is associated with structural changes. Deep learning is a data-driven approach that can capture highly compact hierarchical non-linear relationships among high-dimensional features, and therefore can facilitate the development of clinical tools for making a more accurate and earlier diagnosis of schizophrenia. AIMS: To identify consistent grey matter abnormalities in patients with schizophrenia, 662 people with schizophrenia and 613 healthy controls were recruited from eight centres across China, and the data from these independent sites were used to validate deep-learning classifiers. METHOD: We used a prospective image-based meta-analysis of whole-brain voxel-based morphometry. We also automatically differentiated patients with schizophrenia from healthy controls using combined grey matter, white matter and cerebrospinal fluid volumetric features, incorporated a deep neural network approach on an individual basis, and tested the generalisability of the classification models using independent validation sites. RESULTS: We found that statistically reliable schizophrenia-related grey matter abnormalities primarily occurred in regions that included the superior temporal gyrus extending to the temporal pole, insular cortex, orbital and middle frontal cortices, middle cingulum and thalamus. Evaluated using leave-one-site-out cross-validation, the performance of the classification of schizophrenia achieved by our findings from eight independent research sites were: accuracy, 77.19-85.74%; sensitivity, 75.31-89.29% and area under the receiver operating characteristic curve, 0.797-0.909. CONCLUSIONS: These results suggest that, by using deep-learning techniques, multidimensional neuroanatomical changes in schizophrenia are capable of robustly discriminating patients with schizophrenia from healthy controls, findings which could facilitate clinical diagnosis and treatment in schizophrenia.

Brain Connectivity, and Hormonal and Behavioral Correlates of Sustained Weight Loss in Obese Patients after Laparoscopic Sleeve Gastrectomy.

The biological mediators that support cognitive-control and long-term weight-loss after laparoscopic sleeve gastrectomy (LSG) remain unclear. We measured peripheral appetitive hormones and brain functional-connectivity (FC) using magnetic-resonance-imaging with food cue-reactivity task in 25 obese participants at pre, 1 month, and 6 month after LSG, and compared with 30 normal weight controls. We also used diffusion-tensor-imaging to explore whether LSG increases brain structural-connectivity (SC) of regions involved in food cue-reactivity. LSG significantly decreased BMI, craving for high-calorie food cues, ghrelin, insulin, and leptin levels, and increased self-reported cognitive-control of eating behavior. LSG increased FC between the right dorsolateral prefrontal cortex (DLPFC) and the pregenual anterior cingulate cortex (pgACC) and increased SC between DLPFC and ACC at 1 month and 6 month after LSG. Reduction in BMI correlated negatively with increased FC of right DLPFC-pgACC at 1 month and with increased SC of DLPFC-ACC at 1 month and 6 month after LSG. Reduction in craving for high-calorie food cues correlated negatively with increased FC of DLPFC-pgACC at 6 month after LSG. Additionally, SC of DLPFC-ACC mediated the relationship between lower ghrelin levels and greater cognitive control. These findings provide evidence that LSG improved functional and structural connectivity in prefrontal regions, which contribute to enhanced cognitive-control and sustained weight-loss following surgery.

A Rebuilding-Free Nucleic Acid Detection Strategy Enables Ultrasensitive Genotyping, N-in-1 Logic Screening and Accurate Multiplex Assay of Dangerous Pathogens.

Sensitive, rapid and low-cost nucleic acid detection is critical for controlling infectious pathogens. Here, we develop a ready-to-use and multimodal detection based on a rebuilding-free, ultrasensitive and selective strategy named dual hairpin ligation-induced isothermal amplification pro (DHLApro). Taking influenza A, influenza B, MERS-CoV, SARS-CoV-2 as model targets, we demonstrate DHLApro provides ≈zM level ultra-sensitivity, being equaling to 0.45 copy/µL in original sample. By simply changing the recognition module, a set of DHLApro components can be applied to a new target without performance loss. Moreover, DHLApro innovatively allows flexible logic/multiplex assay using one set of primer, for example, the "N pathogens-in-1" OR gate screening and accurate multi-channel multiplex assay. Compared with traditional methods, the cost of this logic/multiplex assay has been largely reduced and the cross-interference between the multiple primer sets is also avoided.

Baseline structural and functional magnetic resonance imaging predicts early treatment response in schizophrenia with radiomics strategy.

Multimodal neuroimaging features provide opportunities for accurate classification and personalized treatment options in the psychiatric domain. This study aimed to investigate whether brain features predict responses to the overall treatment of schizophrenia at the end of the first or a single hospitalization. Structural and functional magnetic resonance imaging (MRI) data from two independent samples (N = 85 and 63, separately) of schizophrenia patients at baseline were included. After treatment, patients were classified as responders and non-responders. Radiomics features of gray matter morphology and functional connectivity were extracted using Least Absolute Shrinkage and Selection Operator. Support vector machine was used to explore the predictive performance. Prediction models were based on structural features (cortical thickness, surface area, gray matter regional volume, mean curvature, metric distortion, and sulcal depth), functional features (functional connectivity), and combined features. There were 12 features after dimensionality reduction. The structural features involved the right precuneus, cuneus, and inferior parietal lobule. The functional features predominately included inter-hemispheric connectivity. We observed a prediction accuracy of 80.38% (sensitivity: 87.28%; specificity 82.47%) for the model using functional features, and 69.68% (sensitivity: 83.96%; specificity: 72.41%) for the one using structural features. Our model combining both structural and functional features achieved a higher accuracy of 85.03%, with 92.04% responder and 80.23% non-responders to the overall treatment to be correctly predicted. These results highlight the power of structural and functional MRI-derived radiomics features to predict early response to treatment in schizophrenia. Prediction models of the very early treatment response in schizophrenia could augment effective therapeutic strategies.

Distinct Basal Brain Functional Activity and Connectivity in the Emotional-Arousal Network and Thalamus in Patients With Functional Constipation Associated With Anxiety and/or Depressive Disorders.

OBJECTIVE: Functional constipation (FC) is a common gastrointestinal disorder. Anxiety and/or depressive disorders are common in patients with FC (FCAD). Brain dysfunction may play a role in FC, but the contribution of comorbid anxiety and/or depression in patients with FC is poorly understood. METHODS: Sixty-five FC patients and 42 healthy controls (HCs) were recruited, and a hierarchical clustering algorithm was used to classify FC patients into FCAD and patients without anxiety/depressive status (FCNAD) based on neuropsychological assessment. Resting-state functional magnetic resonance imaging measures including fractional amplitude of low-frequency fluctuation (fALFF) and functional connectivity were used to investigate brain functional differences. RESULTS: Thirty-seven patients were classified as FCAD, and 28 patients were classified as FCNAD; as compared with HC, both groups showed decreased activity (fALFF) in the perigenual anterior cingulate cortex (pACC), dorsomedial prefrontal cortex (DMPFC), and precuneus; enhanced precentral gyrus-thalamus connectivity and attenuated precuneus-thalamus connectivity in FCAD/FCNAD highlighted the thalamus as a critical connectivity node in the brain network (pFWE < .05). In comparison with FCNAD/HC, the FCAD group also had decreased fALFF in the orbitofrontal cortex (OFC) and thalamus, and increased OFC-hippocampus connectivity. In the FCNAD group, brain activities (pACC/DMPFC) and connection (precuneus-thalamus) had correlations only with symptoms; in the FCAD group, brain activities (OFC, pACC/DMPFC) and connectivities (OFC-hippocampus/precentral gyrus-thalamus) showed correlations with both constipation symptoms and anxiety/depressive status ratings. Mediation analysis indicated that the relationship between abdominal distension and OFC activity was completely mediated by anxiety in FCAD. CONCLUSIONS: These findings provide evidence of differences in brain activity and functional connectivity between FCAD and FCNAD, potentially providing important clues for improving treatment strategies.

Polygenic effects of schizophrenia on hippocampal grey matter volume and hippocampus-medial prefrontal cortex functional connectivity.

BACKGROUND: Schizophrenia is a complex mental disorder with high heritability and polygenic inheritance. Multimodal neuroimaging studies have also indicated that abnormalities of brain structure and function are a plausible neurobiological characterisation of schizophrenia. However, the polygenic effects of schizophrenia on these imaging endophenotypes have not yet been fully elucidated. AIMS: To investigate the effects of polygenic risk for schizophrenia on the brain grey matter volume and functional connectivity, which are disrupted in schizophrenia. METHOD: Genomic and neuroimaging data from a large sample of Han Chinese patients with schizophrenia (N = 509) and healthy controls (N = 502) were included in this study. We examined grey matter volume and functional connectivity via structural and functional magnetic resonance imaging, respectively. Using the data from a recent meta-analysis of a genome-wide association study that comprised a large number of Chinese people, we calculated a polygenic risk score (PGRS) for each participant. RESULTS: The imaging genetic analysis revealed that the individual PGRS showed a significantly negative correlation with the hippocampal grey matter volume and hippocampus-medial prefrontal cortex functional connectivity, both of which were lower in the people with schizophrenia than in the controls. We also found that the observed neuroimaging measures showed weak but similar changes in unaffected first-degree relatives of patients with schizophrenia. CONCLUSIONS: These findings suggested that genetically influenced brain grey matter volume and functional connectivity may provide important clues for understanding the pathological mechanisms of schizophrenia and for the early diagnosis of schizophrenia.

The relations among worry, meta-worry, intolerance of uncertainty and attentional bias for threat in men at high risk for generalized anxiety disorder: a network analysis.

BACKGROUND: Improving the psychotherapies for generalized anxiety disorder (GAD) is dependent on a deeper understanding of the relations between GAD and its associated cognitive factors. In the present study, we investigate how the core feature of GAD (i.e., worry) and its associated cognitive factors, such as meta-worry, intolerance of uncertainty, and attention bias towards threat, relate to each other in men at high risk for GAD. METHODS: We used network analysis to explore the relations among these variables in a cross-sectional sample of 122 men at high risk for generalized anxiety disorder. Specifically, we computed the expected influence and predictability of each variable. RESULTS: In the final network, we found that worry and meta-worry had the highest expected influence and predictability. In contrast, attention bias towards threat showed the lowest expected influence and predictability. The estimates of the expected influence of the nodes were stable (correlation stability coefficient = 0.52). CONCLUSIONS: The present study is the first to investigate the relations among worry, meta-worry, intolerance of uncertainty, and attention bias towards threat in men at high risk for generalized anxiety disorder. These findings indicate that worry and meta-worry may play important roles in the present network. The implications for clinical interventions and future studies are discussed.

Ghrelin reductions following bariatric surgery were associated with decreased resting state activity in the hippocampus.

BACKGROUND/OBJECTIVE: Laparoscopic sleeve gastrectomy (LSG) is an effective bariatric surgery to treat obesity, and involves removal of the gastric fundus where ghrelin is mainly produced. Ghrelin stimulates appetite and regulates food intake through its effect on the hypothalamus and hippocampus (HIPP). While ghrelin's role on the hypothalamus has been explored, little is known about its role on HIPP. We tested the hypothesis that LSG-induced reductions in ghrelin levels would be associated with changes in HIPP activity. SUBJECTS/METHODS: Brain activity was measured with amplitude of low-frequency fluctuations (ALFF) captured with resting-state functional magnetic resonance imaging (fMRI) in 30 obese participants, both before and after 1-month of LSG, and in 26 obese controls without surgery that were studied at baseline and 1-month later. A two-way analysis of variance (ANOVA) was performed to model the group and time effects on ALFF and resting-state functional connectivity. RESULTS: One-month post-LSG there were significant decreases in appetite, body mass index (BMI), fasting plasma ghrelin and leptin levels, anxiety, and ALFF in HIPP and ALFF increases in posterior cingulate cortex (PCC, PFWE < 0.05). Decreases in HIPP ALFF correlated positively with decreases in fasting ghrelin and anxiety, and increases in PCC ALFF correlated positively with decreases in anxiety. Seed-voxel correlation analysis showed stronger connectivity between HIPP and insula, and between PCC and dorsolateral prefrontal cortex (DLPFC) post-LSG. CONCLUSIONS: These findings suggest that ghrelin effects in HIPP modulate connectivity with the insula, which processes interoception and might be relevant to LSG-induced reductions in appetite/anxiety. Role of LSG in PCC and its enhanced connectivity with DLPFC in improving self-regulation following LSG requires further investigation.

Fluoxetine ameliorates dysbiosis in a depression model induced by chronic unpredicted mild stress in mice.

Background: Accumulating evidence has shown that neuropsychiatric disorders are associated with gut microbiota through the gut-brain axis. However, the effects of antidepressant treatment on gut microbiota are rarely studied. Here, we investigated whether stress led to gut microbiota changes and whether fluoxetine plays a role in microbiota alteration. Methods: We investigated changes in gut microbiota in a depression model induced by chronic unpredicted mild stress (CUMS) and a restoration model by applying the classic antidepressant drug fluoxetine. Results: We found that stress led to low bacterial diversity, simpler bacterial network, and increased abundance of pathogens, such as Escherichia/Shigella, and conditional pathogens, such as Enterococcus, Vagococcus, and Aerococcus. However, these changes were attenuated by fluoxetine directly and indirectly. Furthermore, the correlation analysis indicated strong correlations between gut microbiota and anxiety- and depression-like behaviors. Conclusions: This study revealed that fluoxetine led to restoration of dysbiosis induced by stress stimulation, which may imply a possible pathway through which one CNS target drug plays its role in reshaping the gut microbiota.

Potential Anti-Depressive Treatment Maneuvers from Bench to Bedside.

Numerous antidepressants are available for the treatment of the major depressive disorder (MDD). Unfortunately, the disadvantages of these antidepressive medications, including inadequate treatment response, the therapeutic lag between drug administration and the onset of symptoms alleviation, and the safety consideration limit their clinical use and accelerate the exploration of advanced antidepressants with novel action mechanisms/newer targets, with fewer side effects. In this chapter, a series of compounds showing clinical potent in the treatment of MDD has been reviewed based on their reported results from different phase clinical trials. Although the majority of these strategies currently only lead to a systematic approach in the aspects of treatment resistant depression, some of them would be a routine clinical practice which is usable in the treatment of MDD, such as ketamine. Additionally, beyond the mechanism of action for novel therapeutic molecules involving glutamatergic, opiate, cholinergic receptors, and neuroplasticity, some supplemental procedures such as polyunsaturated fatty acids were also included in this chapter due to their solid property against MDD.

Transcutaneous electrical acupoint stimulation for post-traumatic stress disorder: Assessor-blinded, randomized controlled study.

AIM: Transcutaneous electrical acupoint stimulation (TEAS) has the potential to alleviate post-traumatic stress disorder (PTSD). The purpose of this study was to determine whether adding TEAS to sertraline or cognitive behavioral therapy (CBT) could improve the anti-PTSD efficacy. METHODS: In this randomized controlled trial, 240 PTSD patients (60 in each group) were assigned to receive simulated TEAS combined with sertraline (group A) or with CBT (group B), active TEAS combined with CBT (group C), or active TEAS combined with CBT plus sertraline (group D) for 12 weeks. The outcomes were measured using the Clinician-Administered PTSD Scale, PTSD Check List-Civilian Version, and 17-item Hamilton Rating Scale for Depression. RESULTS: While PTSD symptoms reduced over time in all patients, groups C and D had markedly greater improvement in both PTSD and depressive measures than groups A and B in all post-baseline measurement points, with moderate to very large effect sizes of 0.484-2.244. Groups C and D also had a significantly higher rate than groups A and B on clinical response (85.0% and 95.0% vs 63.3% and 60.0%, P < 0.001) and on remission (15.0% and 25.0% vs 3.3% and 1.7%, P < 0.001). The incidence of adverse events was similar between groups A and D and between groups B and C. CONCLUSIONS: Additional TEAS augments the anti-PTSD and antidepressant efficacy of antidepressants or CBT, without increasing the incidence of adverse effects. TEAS could serve as an effective intervention for PTSD and comorbid depression. This trial was registered with www.chictr.org (no.: ChiCTR1800017255).

Bariatric surgery in obese patients reduced resting connectivity of brain regions involved with self-referential processing.

Obese individuals exhibit brain alterations of resting-state functional connectivity (RSFC) integrity of resting-state networks (RSNs) related to food intake. Bariatric surgery is currently the most effective treatment for combating morbid obesity. How bariatric surgery influences neurocircuitry is mostly unknown. Functional connectivity density (FCD) mapping was employed to calculate local (lFCD)/global (gFCD) voxelwise connectivity metrics in 22 obese participants who underwent functional magnetic resonance imaging before and 1 month after sleeve gastrectomy (SG), and in 19 obese controls (Ctr) without surgery but tested twice (baseline and 1-month later). Two factor (group, time) repeated measures ANOVA was used to assess main and interaction effects in lFCD/gFCD; regions of interest were identified for subsequent seed to voxel connectivity analyses to assess resting-state functional connectivity and to examine association with weight loss. Bariatric surgery significantly decreased lFCD in VMPFC, posterior cingulate cortex (PCC)/precuneus, and dorsal anterior cingulate cortex (dACC)/dorsomedial prefrontal cortex (DMPFC) and decreased gFCD in VMPFC, right dorsolateral prefrontal cortex (DLPFC) and right insula (pFWE < .05). lFCD decreased in VMPFC and PCC/precuneus correlated with reduction in BMI after surgery. Seed to voxel connectivity analyses showed the VMPFC had stronger connectivity with left DLPFC and weaker connectivity with hippocampus/parahippocampus, and PCC/precuneus had stronger connectivity with right caudate and left DLPFC after surgery. Bariatric surgery significantly decreased FCD in regions involved in self-referential processing (VMPFC, DMPFC, dACC, and precuneus), and interoception (insula), and changes in VMPFC/precuneus were associated with reduction in BMI suggesting a role in improving control of eating behaviors following surgery.

Repetitive transcranial magnetic stimulation inhibits Sirt1/MAO-A signaling in the prefrontal cortex in a rat model of depression and cortex-derived astrocytes.

Repetitive transcranial magnetic stimulation (rTMS) is a useful monotherapy for depression or adjunctive therapy for resistant depression. However, the anti-depressive effects of different parameters and the underlying mechanisms remain unclear. Here, we aimed to assess the effect of rTMS with different parameters (1/5/10 Hz, 0.84/1.26 T) on the depressive-like behaviors, 5-hydroxytryptamine (5-HT), 5-HIAA (5-hydroxyindoleacetic acid) and DA and NE levels, and monoamine oxidase A (MAO-A) activity in chronic unpredictable stress-treated rats, along with the expression of sirtuin 1 (Sirt1) and MAO-A in the prefrontal cortex (PFC) and cortex-derived astrocytes from new-born rats. Moreover, the depressive-like behaviors were monitored following the transcranial injection of the Sirt1 inhibitor EX527 (1 mM) daily for 1 week. We found that rTMS treatment (5/10 Hz, 0.84/1.26 T) ameliorated depressive-like behaviors, increased 5-HT, DA and NE levels, decreased the 5-HIAA level and Sirt1 and MAO-A expression, and reduced MAO-A activity in the PFC. The depressive-like behaviors were also ameliorated after the transcranial injection of EX527. Importantly, rTMS (5/10 Hz, 0.84/1.26 T) inhibited Sirt1 and MAO-A expressions in astrocytes and Sirt1 knockdown with short hairpin RNA decreased MAO-A expression in astrocytes. These results suggest that the inhibition of Sirt1/MAO-A expression in astrocytes in the PFC may contribute to the different anti-depressive effects of rTMS with different parameters, and may also provide a novel insight into the mechanisms underlying major depressive disorder.

Antipsychotic polypharmacy in the treatment of schizophrenia in China and Japan.

BACKGROUND: Although antipsychotic monotherapy is recommended as the main treatment for schizophrenia, antipsychotic polypharmacy is not rare in practice. However, longitudinal data on antipsychotic polypharmacy in schizophrenia treatment are limited. METHODS: This longitudinal database study described antipsychotic polypharmacy in the treatment of schizophrenia in real-world settings in China and Japan. We retrieved information about antipsychotic treatment for schizophrenia from January 2010 to December 2014 from two hospital Electronic Medical Records databases in China and one claims database, Japan Medical Data Centre in Japan. Eligible patients had a diagnosis of schizophrenia (International Classification of Diseases, Tenth Revision F20.x) and at least one prescription for first or second generation antipsychotics. Antipsychotic polypharmacy was defined as having more than one antipsychotic medication overlapping for ⩾60 days. The Japan Medical Data Centre study cohort was further stratified by employees (insurance beneficiaries) and their dependents. RESULTS: The study cohorts comprised 11,961 patients from China and 25,034 (10,661 employee sub-cohort and 14,373 dependent sub-cohort) from 14 days Japan Medical Data Centre in Japan. Most patients were prescribed monotherapy (87.3% in China and 80.1% in Japan), of which oral second-generation antipsychotics were the majority (78.9% in China and 65.8% in Japan). The prevalence rate of antipsychotic polypharmacy was 12.7% in China and 19.9% in Japan (13.7% in employees vs 24.5% in dependents). The most common combinations were two oral antipsychotics. Combinations of more than two drugs were uncommon in China (0.3%) but were prescribed for 5.3% of patients in Japan. Among patients treated with monotherapy, 12.6/100 person-years (11.8%) in China and 9.6/100 person-years (11.0%) in Japan switched to antipsychotic polypharmacy during follow-up. Younger patients were more likely to switch to antipsychotic polypharmacy than older patents in all study cohorts. CONCLUSION: The observed rates of antipsychotic polypharmacy ranged from 12.7% in China to 19.9% in Japan. Switching from monotherapy to antipsychotic polypharmacy was most likely to occur in younger patients with schizophrenia.