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Terahertz biotechnology has been increasingly applied in various biomedical fields and has especially shown great potential for application in brain sciences. In this article, we review the development of terahertz biotechnology and its applications in the field of neuropsychiatry. Available evidence indicates promising prospects for the use of terahertz spectroscopy and terahertz imaging techniques in the diagnosis of amyloid disease, cerebrovascular disease, glioma, psychiatric disease, traumatic brain injury, and myelin deficit. In vitro and animal experiments have also demonstrated the potential therapeutic value of terahertz technology in some neuropsychiatric diseases. Although the precise underlying mechanism of the interactions between terahertz electromagnetic waves and the biosystem is not yet fully understood, the research progress in this field shows great potential for biomedical noninvasive diagnostic and therapeutic applications. However, the biosafety of terahertz radiation requires further exploration regarding its two-sided efficacy in practical applications. This review demonstrates that terahertz biotechnology has the potential to be a promising method in the field of neuropsychiatry based on its unique advantages.
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Background: Schizophrenia is a devastating mental disease with high heritability. A growing number of susceptibility genes associated with schizophrenia, as well as their corresponding SNPs loci, have been revealed by genome-wide association studies. However, using SNPs as predictors of disease and diagnosis remains difficult. Here, we aimed to uncover susceptibility SNPs in a Chinese population and to construct a prediction model for schizophrenia. Methods: A total of 210 participants, including 70 patients with schizophrenia, 70 patients with bipolar disorder, and 70 healthy controls, were enrolled in this study. We estimated 14 SNPs using published risk loci of schizophrenia, and used these SNPs to build a model for predicting schizophrenia via comparison of genotype frequencies and regression. We evaluated the efficacy of the diagnostic model in schizophrenia and control patients using ROC curves and then used the 70 patients with bipolar disorder to evaluate the model's differential diagnostic efficacy. Results: 5 SNPs were selected to construct the model: rs148415900, rs71428218, rs4666990, rs112222723 and rs1716180. Correlation analysis results suggested that, compared with the risk SNP of 0, the risk SNP of 3 was associated with an increased risk of schizophrenia (OR = 13.00, 95% CI: 2.35-71.84, p = 0.003). The ROC-AUC of this prediction model for schizophrenia was 0.719 (95% CI: 0.634-0.804), with the greatest sensitivity and specificity being 60% and 80%, respectively. The ROC-AUC of the model in distinguishing between schizophrenia and bipolar disorder was 0.591 (95% CI: 0.497-0.686), with the greatest sensitivity and specificity being 60% and 55.7%, respectively. Conclusion: The SNP risk score prediction model had good performance in predicting schizophrenia. To the best of our knowledge, previous studies have not applied SNP-based models to differentiate between cases of schizophrenia and other mental illnesses. It could have several potential clinical applications, including shaping disease diagnosis, treatment, and outcomes.
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OBJECTIVE: Cognition impairments are considered as a fundamental characteristic of severe mental disorders (SMD). Recent studies suggest that hyperprolactinemia may exert a detrimental influence on cognitive performance in patients with SMD. The objective of this study was to investigate the correlation between serum prolactin levels and cognitive function in female individuals diagnosed with SMD. METHODS: We conducted a study on 294 patients with SMD and 195 healthy controls, aged between 14 to 55 years old. Cognitive function was assessed using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), while prolactin levels were measured in serum. Descriptive analysis and comparative analysis were performed to compare cognitive function and prolactin levels between groups, and linear regression models were used to explore the relationship between prolactin and cognitive function. RESULTS: Compared to the healthy control, individuals with SMD exhibited significantly higher levels of prolactin, while scoring lower on RBANS total and every index scores. Furthermore, a negative association between prolactin levels and cognitive function (RBANS total index score, attention, and delayed memory) was observed in SMD patients. Importantly, this inverse correlation between prolactin and cognition function (RBANS total index score, total scale score, and attention) persisted in patients who were not taking medications that could potentially influence serum prolactin levels. CONCLUSION: Our study reveals a significant correlation between elevated prolactin levels and cognitive impairment in female patients with SMD, underscoring the importance of monitoring prolactin levels in order to prevent cognitive deterioration among female SMD patients.
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Meditation, mental training that aims to improve one's ability to regulate their cognition, has been widely applied in clinical medicine. However, the mechanism by which meditation affects brain activity is still unclear. To explore this question, electroencephalogram data were recorded in 20 long-term meditators and 20 nonmeditators during 2 high-level cognitive tasks (meditation and mental calculation) and a relaxed resting state (control). Then, the power spectral density and phase synchronization of the electroencephalogram were extracted and compared between these 2 groups. In addition, machine learning was used to discriminate the states within each group. We found that the meditation group showed significantly higher classification accuracy and calculation efficiency than the control group. Then, during the calculation task, both the power and global phase synchronism of the gamma response decreased in meditators compared to their relaxation state; yet, no such change was observed in the control group. A potential explanation for our observations is that meditation improved the flexibility of the brain through neural plastic mechanism. In conclusion, we provided robust evidence that long-term meditation experience could produce detectable neurophysiological changes in brain activity, which possibly enhance the functional segregation and/or specialization in the brain.
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Attention , Brain , Electroencephalography , Meditation , Humans , Male , Attention/physiology , Brain/physiology , Female , Adult , Middle Aged , Machine LearningABSTRACT
The utilization of atypical antipsychotics (AAPs) often leads to metabolic syndrome (MetS) in schizophrenia (SZ) patients. Macrophage migration inhibitory factor (MIF) is an important MetS-related cytokine. To investigate the potential association between the MIF-794 CATT5-8 polymorphism and AAP-induced MetS in SZ patients, data from 375 chronic SZ patients who received AAP treatment for a minimum of one year were included. MIF-794 CATT polymorphism genotyping and plasma MIF quantification was performed. The metabolism status of all patients was assessed according to the NCEP-ATP III criteria. Individuals who displayed at least three of the five risk factors (waist circumference, high-density lipoprotein cholesterol, triglycerides, fasting glucose levels, and blood pressure) were diagnosed with MetS. The prevalence of MetS in SZ patients with MIF CATT >5/6 was significantly higher than in those with CATT 5/5-5/6. In female patients, MIF CATT >5/6 was associated with an elevated risk of AAP-induced MetS after adjusting for covariates, particularly regarding abdominal obesity, and the mediating effect of plasma MIF levels was significant. In conclusion, MIF CATT >5/6 increased the risk of AAP-induced MetS among females with chronic SZ. The MIF-794 CATT5-8 microsatellite polymorphism may be a unique indicator for AAP-induced metabolic adverse effects in female SZ patients.
Subject(s)
Antipsychotic Agents , Intramolecular Oxidoreductases , Macrophage Migration-Inhibitory Factors , Metabolic Syndrome , Schizophrenia , Humans , Schizophrenia/drug therapy , Schizophrenia/blood , Female , Macrophage Migration-Inhibitory Factors/blood , Macrophage Migration-Inhibitory Factors/genetics , Metabolic Syndrome/chemically induced , Metabolic Syndrome/epidemiology , Metabolic Syndrome/blood , Antipsychotic Agents/adverse effects , Adult , Male , Intramolecular Oxidoreductases/blood , Intramolecular Oxidoreductases/genetics , Middle Aged , Chronic DiseaseABSTRACT
Atypical antipsychotics (AAPs) are primary medications for schizophrenia (SZ). However, their use is frequently associated with the development of adverse metabolic effects, and the mechanisms behind these negative effects remain inadequately elucidated. To investigate the role of macrophage migration inhibitory factor (MIF) in regulating antipsychotic-induced metabolic abnormalities, between 2017 and 2020, a cross-sectional study was conducted, involving 142 healthy individuals and 388 SZ patients undergoing treatment with either typical antipsychotic (TAP) or AAP medications. Symptoms of SZ patients were evaluated using the Positive and Negative Syndrome Scale (PANSS), and measurements of metabolic indices and plasma MIF levels were performed on all individuals. A significant increase in plasma MIF levels was observed in groups receiving five major AAP monotherapies in comparison to healthy controls (all p < 0.0001). There was no such increase shown in the group receiving TAP treatment (p > 0.05). Elevated plasma MIF levels displayed a notable correlation with insulin resistance (ß = 0.024, p = 0.020), as well as with the levels of triglycerides (ß = 0.019, p = 0.001) and total cholesterol (ß = 0.012, p = 0.038) in the groups receiving AAPs. However, while the TAP group also displayed certain metabolic dysfunction compared to healthy controls, no significant association was evident with plasma MIF levels (all p > 0.05). In conclusion, plasma MIF levels exhibit a distinctive correlation with metabolic abnormalities triggered by AAPs. Hence, there is potential for further development of MIF as a distinctive marker for monitoring adverse metabolic effects induced by AAPs in clinical settings.
Subject(s)
Antipsychotic Agents , Intramolecular Oxidoreductases , Macrophage Migration-Inhibitory Factors , Schizophrenia , Humans , Macrophage Migration-Inhibitory Factors/blood , Male , Antipsychotic Agents/adverse effects , Antipsychotic Agents/therapeutic use , Female , Adult , Schizophrenia/drug therapy , Schizophrenia/blood , Cross-Sectional Studies , Intramolecular Oxidoreductases/blood , Middle Aged , Insulin Resistance , Case-Control Studies , Triglycerides/bloodABSTRACT
AIM: This study investigated the impact of an 8-month daily-guided intensive meditation-based intervention (iMI) on persistent hallucinations/delusions and health-related quality of life (QoL) in male inpatients with schizophrenia with treatment-refractory hallucinations and delusions (TRHDs). METHODS: A randomized controlled trial assigned 64 male inpatients with schizophrenia and TRHD equally to an 8-month iMI plus general rehabilitation program (GRP) or GRP alone. Assessments were conducted at baseline and the third and eighth months using the Positive and Negative Syndrome Scale (PANSS), 36-Item Short Form-36 (SF-36), and Five Facet Mindfulness Questionnaire (FFMQ). Primary outcomes measured PANSS reduction rates for total score, positive symptoms, and hallucinations/delusions items. Secondary outcomes assessed PANSS, SF-36, and FFMQ scores for psychotic symptoms, health-related QoL, and mindfulness skills, respectively. RESULTS: In the primary outcome, iMI significantly improved the reduction rates of PANSS total score, positive symptoms, and hallucination/delusion items compared with GRP at both the third and eighth months. Treatment response rates (≥25% reduction) for these measures significantly increased in the iMI group at the eighth month. Concerning secondary outcomes, iMI significantly reduced PANSS total score and hallucination/delusion items, while increasing scores in physical activity and mindfulness skills at both the third and eighth months compared with GRP. These effects were more pronounced with an 8-month intervention compared with a 3-month intervention. CONCLUSIONS: An iMI benefits patients with TRHDs by reducing persistent hallucinations/delusions and enhancing health-related QoL. Longer iMI duration yields superior treatment outcomes.
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Meditation , Schizophrenia , Humans , Male , Schizophrenia/complications , Schizophrenia/therapy , Delusions/therapy , Quality of Life , Inpatients , Hallucinations/etiology , Hallucinations/therapyABSTRACT
Schizophrenia, a complex neuropsychiatric disorder, frequently experiences a high rate of misdiagnosis due to subjective symptom assessment. Consequently, there is an urgent need for innovative and objective diagnostic tools. In this study, we used cutting-edge extracellular vesicles' (EVs) proteome profiling and XGBoost-based machine learning to develop new markers and personalized discrimination scores for schizophrenia diagnosis and prediction of treatment response. We analysed plasma and plasma-derived EVs from 343 participants, including 100 individuals with chronic schizophrenia, 34 first-episode and drug-naïve patients, 35 individuals with bipolar disorder, 25 individuals with major depressive disorder and 149 age- and sex-matched healthy controls. Our innovative approach uncovered EVs-based complement changes in patients, specific to their disease-type and status. The EV-based biomarkers outperformed their plasma counterparts, accurately distinguishing schizophrenia individuals from healthy controls with an area under curve (AUC) of 0.895, 83.5% accuracy, 85.3% sensitivity and 82.0% specificity. Moreover, they effectively differentiated schizophrenia from bipolar disorder and major depressive disorder, with AUCs of 0.966 and 0.893, respectively. The personalized discrimination scores provided a personalized diagnostic index for schizophrenia and exhibited a significant association with patients' antipsychotic treatment response in the follow-up cohort. Overall, our study represents a significant advancement in the field of neuropsychiatric disorders, demonstrating the potential of EV-based biomarkers in guiding personalized diagnosis and treatment of schizophrenia.
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Antipsychotic Agents , Depressive Disorder, Major , Extracellular Vesicles , Schizophrenia , Humans , Depressive Disorder, Major/diagnosis , Schizophrenia/diagnosis , Biomarkers , Complement System ProteinsABSTRACT
Attenuation of adipose hormone sensitive lipase (HSL) may impair lipolysis and exacerbate obesity. We investigate the role of cytokine, macrophage migration inhibitory factor (MIF) in regulating adipose HSL and adipocyte hypertrophy. Extracellular MIF downregulates HSL in an autocrine fashion, by activating the AMPK/JNK signaling pathway upon binding to its membrane receptor, CD74. WT mice fed high fat diet (HFD), as well as mice overexpressing MIF, both had high circulating MIF levels and showed suppression of HSL during the development of obesity. Blocking the extracellular action of MIF by a neutralizing MIF antibody significantly reduced obesity in HFD mice. Interestingly, intracellular MIF binds with COP9 signalosome subunit 5 (Csn5) and JNK, which leads to an opposing effect to inhibit JNK phosphorylation. With global MIF deletion, adipocyte JNK phosphorylation increased, resulting in decreased HSL expression, suggesting that the loss of MIF's intracellular inhibitory action on JNK was dominant in Mif-/- mice. Adipose tissue from Mif-/- mice also exhibited higher Akt and lower PKA phosphorylation following HFD feeding compared with WT, which may contribute to the downregulation of HSL activation during more severe obesity. Both intracellular and extracellular MIF have opposing effects to regulate HSL, but extracellular actions predominate to downregulate HSL and exacerbate the development of obesity during HFD.
Subject(s)
Macrophage Migration-Inhibitory Factors , Animals , Mice , Adipocytes/metabolism , Adipose Tissue/metabolism , Macrophage Migration-Inhibitory Factors/genetics , Macrophage Migration-Inhibitory Factors/metabolism , Obesity/metabolism , Sterol Esterase/metabolismABSTRACT
Nerve injury induced microglia activation, which released inflammatory mediators and developed neuropathic pain. Picroside â ¡ (Pâ ¡) attenuated neuropathic pain by inhibiting the neuroinflammation of the spinal dorsal horn; however, how it engaged in the cross talk between microglia and neurons remained ambiguous. This study aimed to investigate Pâ ¡ in the modulation of spinal synaptic transmission mechanisms on pain hypersensitivity in neuropathic rats. We investigated the analgesia of Pâ ¡ in mechanical and thermal hyperalgesia using the spinal nerve ligation (SNL)-induced neuropathic pain model and formalin-induced tonic pain model, respectively. RNA sequencing and network pharmacology were employed to screen core targets and signaling pathways. Immunofluorescence staining and qPCR were performed to explore the expression level of microglia and inflammatory mediator mRNA. The whole-cell patch-clamp recordings were utilized to record miniature excitatory postsynaptic currents in excitatory synaptic transmission. Our results demonstrated that the analgesic of Pâ ¡ was significant in both pain models, and the underlying mechanism may involve inflammatory signaling pathways. Pâ ¡ reversed the SNL-induced overexpression of microglia and inflammatory factors. Moreover, Pâ ¡ dose dependently inhibited excessive glutamate transmission. Thus, this study suggested that Pâ ¡ attenuated neuropathic pain by inhibiting excitatory glutamate transmission of spinal synapses, induced by an inflammatory response on microglia.
Subject(s)
Cinnamates , Iridoid Glucosides , Neuralgia , Synaptic Transmission , Rats , Animals , Rats, Sprague-Dawley , Synaptic Transmission/physiology , Hyperalgesia/drug therapy , Spinal Nerves/metabolism , Neuralgia/drug therapy , Neuralgia/metabolism , Inflammation/drug therapy , GlutamatesABSTRACT
OBJECTIVE: Sex differences have been observed in many aspects of schizophrenia, including cognitive deficits. Despite extensive research into the relationship between metabolic factors and cognitive deficits in schizophrenia, few studies have explored the potential sex difference in their association. METHODS: We recruited 358 schizophrenia patients and 231 healthy controls. The participants underwent measurements of body mass index (BMI), waist circumference, blood pressure, triglycerides, high-density lipoprotein cholesterol, and fasting blood glucose. Metabolic risk factors included abdominal obesity, hypertension, hyperglycemia, and dyslipidemia. A collection of these metabolic risk factors has been defined as metabolic syndrome. These diagnoses were based on the criteria of the National Cholesterol Education Program's Adult Treatment Panel III. Cognitive performance was measured using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). A descriptive analysis, difference analysis, and linear regression model were used to identify the metabolic risk factors for cognitive function in schizophrenia. RESULTS: Our findings revealed sex differences in the rate of abdominal obesity and hypertension in schizophrenic patients. Additionally, we observed sex differences in the association between metabolic risk factors and cognitive impairment in schizophrenia. Specifically, hyperglycemia was associated with the immediate memory index score of RBANS in male patients, while dyslipidemia was associated with language, attention, delayed memory index scores, and RBANS total score in female patients. CONCLUSION: Our results suggest that sex should be considered when evaluating the impact of metabolic disorders on the cognitive function of schizophrenic patients. Moreover, our study identifies hyperglycemia and dyslipidemia as potential targets for precise treatment by sex stratification, which could benefit the improvement of cognitive impairment in schizophrenic patients.
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Aims/hypothesis: It is widely thought that the intestinal microbiota plays a significant role in the pathogenesis of metabolic disorders. However, the gut microbiota composition and characteristics of schizophrenia patients with metabolic syndrome (MetS) have been largely understudied. Herein, we investigated the association between the metabolic status of mainland Chinese schizophrenia patients with MetS and the intestinal microbiome. Methods: Fecal microbiota communities from 115 male schizophrenia patients (57 with MetS and 58 without MetS) were assessed by 16S ribosomal RNA gene sequencing. We assessed the variations of gut microbiome between both groups and explored potential associations between intestinal microbiota and parameters of MetS. In addition, the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) based on the KEGG database was used to predict the function of intestinal microbiota. We also conducted Decision Tree Analysis to develop a diagnostic model for the MetS in patients with schizophrenia based on the composition of intestinal microbiota. Results: The fecal microbial diversity significantly differed between groups with or without MetS (α-diversity (Shannon index and Simpson index): p=0.0155, p=0.0089; ß-diversity: p=0.001). Moreover, the microbial composition was significantly different between the two groups, involving five phyla and 38 genera (p<0.05). In addition, a significant correlation was observed between the metabolic-related parameters and abundance of altered microbiota including HDL-c (r2 = 0.203, p=0.0005), GLU (r2 = 0.286, p=0.0005) and WC (r2 = 0.061, p=0.037). Furthermore, KEGG pathway analysis showed that 16 signaling pathways were significantly enriched between the two groups (p<0.05). Importantly, our diagnostic model based on five microorganisms established by decision tree analysis could effectively distinguish between patients with and without MetS (AUC = 0.94). Conclusions/interpretation: Our study established the compositional and functional characteristics of intestinal microbiota in schizophrenia patients with MetS. These new findings provide novel insights into a better understanding of this disease and provide the theoretical basis for implementing new interventional therapies in clinical practice.
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Gastrointestinal Microbiome , Metabolic Syndrome , Microbiota , Schizophrenia , Humans , Gastrointestinal Microbiome/genetics , Metabolic Syndrome/diagnosis , Schizophrenia/complications , Schizophrenia/diagnosis , PhylogenyABSTRACT
While insulin resistance (IR) is associated with inflammation in white adipose tissue, we report a non-inflammatory adipose mechanism of high fat-induced IR mediated by loss of Pref-1. Pref-1, released from adipose Pref-1+ cells with characteristics of M2 macrophages, endothelial cells or progenitors, inhibits MIF release from both Pref-1+ cells and adipocytes by binding with integrin ß1 and inhibiting the mobilization of p115. High palmitic acid induces PAR2 expression in Pref-1+ cells, downregulating Pref-1 expression and release in an AMPK-dependent manner. The loss of Pref-1 increases adipose MIF secretion contributing to non-inflammatory IR in obesity. Treatment with Pref-1 blunts the increase in circulating plasma MIF levels and subsequent IR induced by a high palmitic acid diet. Thus, high levels of fatty acids suppress Pref-1 expression and secretion, through increased activation of PAR2, resulting in an increase in MIF secretion and a non-inflammatory adipose mechanism of IR.
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Background: Advancements in research have confirmed that gut microbiota can influence health through the microbiota-gut-brain axis. Meditation, as an inner mental exercise, can positively impact the regulation of an individual's physical and mental health. However, few studies have comprehensively investigated faecal microbiota following long-term (several years) deep meditation. Therefore, we propose that long-term meditation may regulate gut microbiota homeostasis and, in turn, affect physical and mental health. Aims: To investigate the effects of long-term deep meditation on the gut microbiome structure. Methods: To examine the intestinal flora, 16S rRNA gene sequencing was performed on faecal samples of 56 Tibetan Buddhist monks and neighbouring residents. Based on the sequencing data, linear discriminant analysis effect size (LEfSe) was employed to identify differential intestinal microbial communities between the two groups. Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) analysis was used to predict the function of faecal microbiota. In addition, we evaluated biochemical indices in the plasma. Results: The α-diversity indices of the meditation and control groups differed significantly. At the genus level, Prevotella and Bacteroides were significantly enriched in the meditation group. According to the LEfSe analysis, two beneficial bacterial genera (Megamonas and Faecalibacterium) were significantly enriched in the meditation group. Functional predictive analysis further showed that several pathways-including glycan biosynthesis, metabolism and lipopolysaccharide biosynthesis-were significantly enriched in the meditation group. Moreover, plasma levels of clinical risk factors were significantly decreased in the meditation group, including total cholesterol and apolipoprotein B. Conclusions: Long-term traditional Tibetan Buddhist meditation may positively impact physical and mental health. We confirmed that the gut microbiota composition differed between the monks and control subjects. The microbiota enriched in monks was associated with a reduced risk of anxiety, depression and cardiovascular disease and could enhance immune function. Overall, these results suggest that meditation plays a positive role in psychosomatic conditions and well-being.
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BACKGROUND: Residual negative symptoms and cognitive impairment are common for chronic schizophrenia patients. The aim of this study was to investigate the efficacy of a mindfulness-based intervention (MBI) on negative and cognitive symptoms of schizophrenia patients with residual negative symptoms. METHODS: In this 6-week, randomized, single-blind, controlled study, a total of 100 schizophrenia patients with residual negative symptoms were randomly assigned to the MBI or control group. The 6-week MBI group and the control group with general rehabilitation programs maintained their original antipsychotic treatments. The scores for the Positive and Negative Syndrome Scale (PANSS), the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), and the Symptom Checklist 90 (SCL-90) were recorded at baseline and week 6 to assess psychotic symptoms, cognitive performance, and emotional state, respectively. RESULTS: Compared with general rehabilitation programs, MBI alleviated the PANSS-negative subscore, general psychopathology subscore, and PANSS total score in schizophrenia patients with residual negative symptoms (F = 33.77, pBonferroni < 0.001; F = 42.01, pBonferroni < 0.001; F = 52.41, pBonferroni < 0.001, respectively). Furthermore, MBI improved RBANS total score and immediate memory subscore (F = 8.80, pBonferroni = 0.024; F = 11.37, pBonferroni = 0.006), as well as SCL-90 total score in schizophrenia patients with residual negative symptoms (F = 18.39, pBonferroni < 0.001). CONCLUSIONS: Our results demonstrate that MBI helps schizophrenia patients with residual negative symptoms improve clinical symptoms including negative symptom, general psychopathology symptom, and cognitive impairment. TRIAL REGISTRATION: ChiCTR2100043803.
Subject(s)
Antipsychotic Agents , Cognitive Dysfunction , Mindfulness , Schizophrenia , Humans , Schizophrenia/complications , Schizophrenia/therapy , Schizophrenia/diagnosis , Follow-Up Studies , Single-Blind Method , Antipsychotic Agents/therapeutic use , Cognitive Dysfunction/therapy , Cognitive Dysfunction/drug therapy , Double-Blind MethodABSTRACT
The brain is susceptible to perturbations of redox balance, affecting neurogenesis and increasing the risks of psychiatric disorders. Thioredoxin-interacting protein (TXNIP) is an endogenous inhibitor of the thioredoxin antioxidant system. Its deletion or inhibition suggests protection for a brain with ischemic stroke or Alzheimer's disease. Combined with conditional knockout mice and schizophrenia samples, we aimed to investigate the function of TXNIP in healthy brain and psychiatric disorders, which are under-studied. We found TXNIP was remarkedly expressed in the prefrontal cortex (PFC) during healthy mice's prenatal and early postnatal periods, whereas it rapidly decreased throughout adulthood. During early life, TXNIP was primarily distributed in inhibitory and excitatory neurons. Contrary to the protective effect, the embryonic deletion of TXNIP in GABAergic (gamma-aminobutyric acid-ergic) neurons enhanced oxidative stress in PV+ interneurons of aging mice. The deleterious impact was brain region-specific. We also investigated the relationship between TXNIP and schizophrenia. TXNIP was significantly increased in the PFC of schizophrenia-like mice after MK801 administration, followed by oxidative stress. First episode and drug naïve schizophrenia patients with a higher level of plasma TXNIP displayed severer psychiatric symptoms than patients with a low level. We indicated a bidirectional function of TXNIP in the brain, whose high expression in the early stage is protective for development but might be harmful in a later period, associated with mental disorders.
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BACKGROUND: There have been mixed reports on the beneficial effects of meditation in cardiovascular disease (CVD), which is widely considered the leading cause of death worldwide. METHODS: To clarify the role of meditation in modulating the heart-brain axis, we implemented an extreme phenotype strategy, i.e., Tibetan monks (BMI > 30) who practised 19.20 ± 7.82 years of meditation on average and their strictly matched non-meditative Tibetan controls. Hypothesis-free advanced proteomics strategies (Data Independent Acquisition and Targeted Parallel Reaction Monitoring) were jointly applied to systematically investigate and target the plasma proteome underlying meditation. Total cholesterol, low-density lipoprotein cholesterol (LDL-C), apolipoprotein B (Apo B) and lipoprotein (a) [Lp(a)] as the potential cardiovascular risk factors were evaluated. Heart rate variability (HRV) was assessed by electrocardiogram. FINDINGS: Obesity, hypertension, and reduced HRV is offset by long-term meditation. Notably, meditative monks have blood pressure and HRV comparable to their matched Tibetan controls. Meditative monks have a protective plasma proteome, related to decreased atherosclerosis, enhanced glycolysis, and oxygen release, that confers resilience to the development of CVD. In addition, clinical risk factors in plasma were significantly decreased in monks compared with controls, including total cholesterol, LDL-C, Apo B, and Lp(a). INTERPRETATION: To our knowledge, this work is the first well-controlled proteomics investigation of long-term meditation, which opens up a window for individuals characterized by a sedentary lifestyle to improve their cardiovascular health with an accessible method practised for more than two millennia. FUNDING: See the Acknowledgements section.
Subject(s)
Cardiovascular Diseases , Cardiovascular System , Meditation , Monks , Apolipoproteins B , Brain , Cardiovascular Diseases/etiology , Cardiovascular Diseases/prevention & control , Cholesterol, LDL , Humans , Proteome , Proteomics , TibetABSTRACT
OBJECTIVE: To explore the effect and mechanism of peppermint essential oil on learning and memory ability of APP/PS1 transgenic mice. METHODS: Morris water maze test and shuttle box test were used to explore the changes in learning and memory ability of APP/PS1 transgenic mice after sniffing essential oil. The cellular status of neurons in the hippocampal CA1 region of the right hemisphere, Aß deposition, oxidative stress level, and serum metabonomics were detected to explore its mechanism. RESULTS: Sniffing peppermint essential oil can improve the learning and memory ability of APP/PS1 transgenic mice. Compared with the model group, the state of neurons in the hippocampal CA1 region of the peppermint essential oil group returned to normal, and the deposition of Aß decreased. The MDA of brain tissue decreased significantly, and the activity of SOD and GSH-PX increased significantly to the normal level. According to the results of metabonomics, it is speculated that peppermint essential oil may improve cognitive function in AD by regulating arginine and proline metabolism, inositol phosphate metabolism, and cysteine and methionine metabolism.
Subject(s)
Alzheimer Disease , Oils, Volatile , Alzheimer Disease/metabolism , Amyloid beta-Peptides/metabolism , Amyloid beta-Protein Precursor/metabolism , Animals , CA1 Region, Hippocampal/metabolism , Disease Models, Animal , Hippocampus/metabolism , Maze Learning , Mentha piperita/metabolism , Mice , Mice, Inbred C57BL , Mice, Transgenic , Oils, Volatile/metabolism , Oils, Volatile/pharmacology , Presenilin-1/genetics , Presenilin-1/metabolismABSTRACT
Our objective was to explore the mechanism of essential oil that was extracted from Cinnamomum camphora chvar. Borneol (Borneol essential oil) for improving learning and memory impairment in mice. Brain tissue and plasma samples of a normal group, a model group, a Borneol essential oil group and a reference group were detected using gas chromatography time-of-flight mass spectrometry (GC-TOFMS) in order to find differential metabolites and analyze metabolic pathways. Results showed that there were 11 different metabolites --including glycine and azelaic acid --in plasma samples, and that there were 26 different metabolites--including adenine and aspartic acid --in brain tissue samples. These metabolites are involved in phenylalanine, tyrosine, and tryptophan biosynthesis, phenylalanine metabolism, alanine, aspartate and glutamate metabolism, arginine biosynthesis, beta-alanine metabolism, glyoxylate acid and dicarboxylate metabolism, and aminoacyl-tRNA biosynthesis. Thus, Borneol essential oil may improve learning and memory impairment by regulating amino acid metabolism and/or neurotransmitter changes.
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Bipolar disorder (BD) is a complex and dynamic condition with a typical onset in late adolescence or early adulthood followed by an episodic course with intervening periods of subthreshold symptoms or euthymia. It is complicated by the accumulation of comorbid medical and psychiatric disorders. The etiology of BD remains unknown and no reliable biological markers have yet been identified. This is likely due to lack of comprehensive ontological framework and, most importantly, the fact that most studies have been based on small nonrepresentative clinical samples with cross-sectional designs. We propose to establish large, global longitudinal cohorts of BD studied consistently in a multidimensional and multidisciplinary manner to determine etiology and help improve treatment. Herein we propose collection of a broad range of data that reflect the heterogenic phenotypic manifestations of BD that include dimensional and categorical measures of mood, neurocognitive, personality, behavior, sleep and circadian, life-story, and outcomes domains. In combination with genetic and biological information such an approach promotes the integrating and harmonizing of data within and across current ontology systems while supporting a paradigm shift that will facilitate discovery and become the basis for novel hypotheses.