U-shaped association between fasting blood glucose and suicide attempts in Chinese patients with first-episode drug-naïve major depressive disorder.

BACKGROUND: Evidence regarding the relationship between fasting blood glucose (FBG) and suicide attempts (SA) in patients with major depressive disorder (MDD) was limited. Therefore, the objective of this research was to investigate whether FBG was independently related to SA in Chinese patients with first-episode drug-naïve (FEDN) MDD after adjusting for other covariates. METHODS: The present study was a cross-sectional study. A total of 1718 participants (average age: 34.9 ± 12.4 years, 65.8% females) with FEDN MDD were involved in a hospital in China from September 2016 to December 2018. Multiple logistic regression analysis and smooth curve fitting were used to estimate the association between FBG and the risk of SA. The threshold effect was examined by the two-piecewise linear regression model. Interaction and stratified analyses were conducted according to sex, education, marital status, comorbid anxiety, and psychotic symptoms. RESULTS: The prevalence of SA in patients with FEDN MDD was 20.1%. The result of fully adjusted binary logistic regression showed FBG was positively associated with the risk of SA (odds ratio (OR) = 1.62, 95% CI: 1.13-2.32). Smoothing plots also revealed a nonlinear relationship between FBG and SA, with the inflection point of FBG being 5.34 mmol/l. The effect sizes and the confidence intervals on the left and right sides of the inflection point were 0.53 (0.32-0.88, P = 0.014) and 1.48 (1.04-2.10, P = 0.030), respectively. CONCLUSIONS: A U-shaped relationship between FBG and SA in FEDN MDD patients was found, with the lowest risk of SA at a FBG of 5.34 mmol/l, indicating that both the lower and higher FBG levels may lead to an increased risk of SA.

The classical D1 dopamine receptor antagonist SCH23390 is a functional sigma-1 receptor allosteric modulator.

SCH23390 is a widely used D1 dopamine receptor (D1R) antagonist that also elicits some D1R-independent effects. We previously found that the benzazepine, SKF83959, an analog of SCH23390, produces positive allosteric modulation of the Sigma-1 receptor (Sig1R). SCH23390 does not bind to the orthodoxic site of Sig1R but enhances the binding of 3H (+)-pentazocine to Sig1R. In this study, we investigated whether SCH23390 functions as an allosteric modulator of Sig1R. We detected increased Sig1R dissociation from binding immunoglobulin protein (BiP) and translocation of Sig1R to the plasma membrane in response to SCH23390 in transfected HEK293T and SH-SY5Y cells, respectively. Activation of Sig1R by SCH23390 was further confirmed by inhibition of GSK3ß activity in a time- and dose-dependent manner; this effect was blocked by pretreatment with the Sig1R antagonist, BD1047, and by knockdown of Sig1R. SCH23390 also inhibited GSK3ß in wild-type mice but not in Sig1R knockout mice. Finally, we showed that SCH23390 allosterically modulated the effect of the Sig1R agonist SKF10047 on inhibition of GSK3ß. This positive allosteric effect of SCH23390 was further confirmed via promotion of neuronal protection afforded by SKF10047 in primary cortical neurons challenged with MPP+. These results provide the first evidence that SCH23390 elicits functional allosteric modulation of Sig1R. Our findings not only reveal novel pharmacological effects of SCH23390 but also indicate a potential mechanism for SCH23390-mediated D1R-independent effects. Therefore, attention should be paid to these Sig1R-mediated effects when explaining pharmacological responses to SCH23390.

The identification of novel schizophrenia-related metabolites using untargeted lipidomics.

Human lipidome still remains largely unexplored among Chinese schizophrenia patients. We aimed to identify novel lipid molecules associated with schizophrenia and cognition among schizophrenia patients. The current study included 96 male schizophrenia patients and 96 gender-matched healthy controls. Untargeted lipidomics profiling was conducted among all participants. Logistic regression models were used to assess metabolite associations with schizophrenia. We further assessed the incremental predictive value of identified metabolites beyond conventional risk factors on schizophrenia status. In addition, identified metabolites were tested for association with cognitive function among schizophrenia patients using linear regression models. A total of 34 metabolites were associated with schizophrenia. Addition of these identified metabolites to age, body mass index, smoking, and education significantly increased the risk reclassification of schizophrenia. Among the schizophrenia-related metabolites, 10 were further associated with cognition in schizophrenia patients, including four metabolites associated with immediate memory, two metabolites associated with delayed memory, three metabolites associated with visuospatial, four metabolites associated with language, one metabolite associated with attention, and two metabolites associated with the total score. Our findings provide novel insights into the biological mechanisms of schizophrenia, suggesting that lipid metabolites may serve as potential diagnostic or therapeutic targets of schizophrenia.

Association between triglyceride glucose index (TyG) and psychotic symptoms in patients with first-episode drug-naïve major depressive disorder.

Objective: Major depressive disorder (MDD) sufferers frequently have psychotic symptoms, yet the underlying triggers remain elusive. Prior research suggests a link between insulin resistance (IR) and increased occurrence of psychotic symptoms. Hence, this study sought to investigate the potential association between psychotic symptoms in Chinese patients experiencing their first-episode drug-naïve (FEDN) MDD and the triglyceride glucose (TyG) index, an alternative measure of insulin resistance (IR). Methods: Between September 2016 and December 2018, 1,718 FEDN MDD patients with an average age of 34.9 ± 12.4 years were recruited for this cross-sectional study at the First Hospital of Shanxi Medical University in China. The study collected clinical and demographic data and included assessments of anxiety, depression, and psychotic symptoms using the 14-item Hamilton Anxiety Rating Scale (HAMA), the 17-item Hamilton Depression Rating Scale (HAMD-17), and the positive subscales of the Positive and Negative Syndrome Scale (PANSS), respectively. Measurements of metabolic parameters, fasting blood glucose (FBG), and thyroid hormones were also gathered. To assess the correlation between the TyG index and the likelihood of psychotic symptoms, the study used multivariable binary logistic regression analysis. Additionally, two-segmented linear regression models were employed to investigate possible threshold effects in case non-linearity relationships were identified. Results: Among the patients, 9.95% (171 out of 1,718) exhibited psychotic symptoms. Multivariable logistic regression analysis showed a positive correlation between the TyG index and the likelihood of psychotic symptoms (OR = 2.12, 95% CI: 1.21-3.74, P = 0.01) after adjusting for confounding variables. Moreover, smoothed plots revealed a nonlinear relationship with the TyG index, revealing an inflection point at 8.42. Interestingly, no significant link was observed to the left of the inflection point (OR = 0.50, 95% CI: 0.04-6.64, P = 0.60), whereas beyond this point, a positive correlation emerged between the TyG index and psychotic symptoms (OR = 2.42, 95% CI: 1.31-4.48, P = 0.01). Particularly, a considerable 142% rise in the probability of experiencing psychotic symptoms was found with each incremental elevation in the TyG index. Conclusions: Understanding the non-linear link between the TyG index and the risk of psychotic symptoms in Chinese patients with FEDN MDD highlights the potential for targeted therapeutic approaches. By acknowledging the threshold effect observed, there is an opportunity to mitigate risk factors associated with IR-related psychiatric comorbidities through tailored interventions. These preliminary results stress the need for further longitudinal research to solidify these insights and contribute to more effective therapeutic strategies.

Abnormal ambiguous facial expression recognition in Chinese patients with schizophrenia.

BACKGROUND: Patients with schizophrenia (SCZ) exhibit difficulties deficits in recognizing facial expressions with unambiguous valence. However, only a limited number of studies have examined how these patients fare in interpreting facial expressions with ambiguous valence (for example, surprise). Thus, we aimed to explore the influence of emotional background information on the recognition of ambiguous facial expressions in SCZ. METHODS: A 3 (emotion: negative, neutral, and positive) × 2 (group: healthy controls and SCZ) experimental design was adopted in the present study. The experimental materials consisted of 36 images of negative emotions, 36 images of neutral emotions, 36 images of positive emotions, and 36 images of surprised facial expressions. In each trial, a briefly presented surprised face was preceded by an affective image. Participants (36 SCZ and 36 healthy controls (HC)) were required to rate their emotional experience induced by the surprised facial expressions. Participants' emotional experience was measured using the 9-point rating scale. The experimental data have been analyzed by conducting analyses of variances (ANOVAs) and correlation analysis. RESULTS: First, the SCZ group reported a more positive emotional experience under the positive cued condition compared to the negative cued condition. Meanwhile, the HC group reported the strongest positive emotional experience in the positive cued condition, a moderate experience in the neutral cued condition, and the weakest in the negative cue condition. Second, the SCZ (vs. HC) group showed longer reaction times (RTs) for recognizing surprised facial expressions. The severity of schizophrenia symptoms in the SCZ group was negatively correlated with their rating scores for emotional experience under neutral and positive cued condition. CONCLUSIONS: Recognition of surprised facial expressions was influenced by background information in both SCZ and HC, and the negative symptoms in SCZ. The present study indicates that the role of background information should be fully considered when examining the ability of SCZ to recognize ambiguous facial expressions.

Interactions between overweight/obesity and alcohol dependence impact human brain white matter microstructure: evidence from DTI.

There is inconsistent evidence for an association of obesity with white matter microstructural alterations. Such inconsistent findings may be related to the cumulative effects of obesity and alcohol dependence. This study aimed to investigate the possible interactions between alcohol dependence and overweight/obesity on white matter microstructure in the human brain. A total of 60 inpatients with alcohol dependence during early abstinence (44 normal weight and 16 overweight/obese) and 65 controls (42 normal weight and 23 overweight/obese) were included. The diffusion tensor imaging (DTI) measures [fractional anisotropy (FA) and radial diffusivity (RD)] of the white matter microstructure were compared between groups. We observed significant interactive effects between alcohol dependence and overweight/obesity on DTI measures in several tracts. The DTI measures were not significantly different between the overweight/obese and normal-weight groups (although widespread trends of increased FA and decreased RD were observed) among controls. However, among the alcohol-dependent patients, the overweight/obese group had widespread reductions in FA and widespread increases in RD, most of which significantly differed from the normal-weight group; among those with overweight/obesity, the alcohol-dependent group had widespread reductions in FA and widespread increases in RD, most of which were significantly different from the control group. This study found significant interactive effects between overweight/obesity and alcohol dependence on white matter microstructure, indicating that these two controllable factors may synergistically impact white matter microstructure and disrupt structural connectivity in the human brain.

Prevalence and risk factors for psychotic symptoms in young, first-episode and drug-naïve patients with major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) is a common psychiatric disorder worldwide. Psychotic depression has been reported to be frequently under-diagnosed due to poor recognition of psychotic features. Therefore, the purpose of this study was to reveal the rate and risk factors of psychotic symptoms in young, drug-naïve patients with major depressive disorder at the time of their first episode. METHODS: A total of 917 patients were recruited and divided into psychotic and non-psychotic subgroups based on the Positive and Negative Syndrome Scale (PANSS) positive subscale score. Anxiety symptoms and depressive symptoms were measured by the Hamilton Anxiety Rating Scale (HAMA) and the 17-item Hamilton Depression Rating Scale (HAMD-17), respectively. Several biochemical indicators such as total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), fasting blood glucose (FBG), thyroid stimulating hormone (TSH), free triiodothyronine (FT3), and free thyroxine (FT4) were also measured. RESULTS: The rate of psychotic symptoms among young adult MDD patients was 9.1%. There were significant differences in TSH (p<0.001), FBG (p<0.001), TC (p<0.0001), TG (p = 0.001), HDL-C (p = 0.049), LDL-C (p = 0.010), diastolic blood pressure (DP) (p<0.001), systolic blood pressure (SP) (p<0.001), and HAMD total score (p<0.001) between young MDD patients with and without psychotic depression. HAMD, TSH, TC, and severe anxiety were independently associated with psychotic symptoms in young adult MDD patients. In addition, among young MDD patients, the rate of suicide attempts in the psychotic subgroup was much higher than in the non-psychotic subgroup (45.8% vs. 16.9%). CONCLUSIONS: Our findings suggest that psychotic symptoms are common in young MDD patients. Several clinical variables and biochemical indicators are associated with the occurrence of psychotic symptoms in young MDD patients.

Artificial Intelligence Iterative Reconstruction in Computed Tomography Angiography: An Evaluation on Pulmonary Arteries and Aorta With Routine Dose Settings.

OBJECTIVE: The objective of this study is to investigate whether a newly introduced deep learning-based iterative reconstruction algorithm, namely, the artificial intelligence iterative reconstruction (AIIR), has a clinical value in computed tomography angiography (CTA), especially for visualizing vascular structures and related lesions, with routine dose settings. METHODS: A total of 63 patients were retrospectively collected from the triple rule-out CTA examinations, where both pulmonary and aortic data were available for each patient and were taken as the example for investigation. The images were reconstructed using the filtered back projection (FBP), hybrid iterative reconstruction (HIR), and the AIIR. The visibility of vasculature and pulmonary emboli and the general image quality were assessed. RESULTS: Artificial intelligence iterative reconstruction resulted in significantly ( P < 0.001) lower noise as well as higher signal-to-noise ratio and contrast-to-noise ratio compared with FBP and HIR. Besides, AIIR achieved the highest subjective scores on general image quality ( P < 0.05). For the vasculature visibility, AIIR offered the best vessel conspicuity, especially for the small vessels ( P < 0.05). Also, >90% of emboli on the AIIR images were graded as sharp (score 5), whereas <15% of emboli on FBP and HIR images were scored 5. CONCLUSION: As demonstrated for pulmonary and aortic CTAs, AIIR improves the image quality and offers a better depiction for vascular structures compared with FBP and HIR. The visibility of the pulmonary emboli was also increased by AIIR.

Notoginsenoside R1 attenuates brain injury in rats with traumatic brain injury: Possible mediation of apoptosis via ERK1/2 signaling pathway.

Traumatic brain injury (TBI) occurs worldwide and is associated with high mortality and disability rate. Apoptosis induced by TBI is one of the important causes of secondary injury after TBI. Notoginsenoside R1 (NGR1) is the main phytoestrogen extracted from Panax notoginseng. Many studies have shown that NGR1 has potent neuroprotective, anti-inflammatory, and anti-apoptotic properties and is effective in ischemia-reperfusion injury. Therefore, we investigated the potential neuroprotective effects of NGR1 after TBI and explored its molecular mechanism of action. A rat model of TBI was established using the controlled cortical impact (CCI) method. The expression levels of Bcl-2, Bax, caspase 3, and ERK1/2-related molecules in the downstream pathway were also detected by western blotting. The expression levels of pro-inflammatory cytokines were detected by real-time quantitative PCR. Nissl staining was used to clarify the morphological changes around the injury foci in rats after TBI. Fluoro-Jade B (FJB) and terminal deoxynucleotidyl transferase (TdT) dUTP Nick-End Labeling (TUNEL) fluorescence staining were used to detect the apoptosis of neural cells in each group of rats. The results showed that NGR1 administration reduced neurological deficits after TBI, as well as brain edema and brain tissue apoptosis. It also significantly inhibited the expression of pro-inflammatory cytokines. Furthermore, NGR1 decreased the expression levels of extracellular signal-regulated kinase (ERK) and p-RSK1, which are phosphorylated after trauma. This study suggests that NGR1 can improve neuronal apoptosis in brain injury by inhibiting the ERK signaling pathway. NGR1 is a potential novel neuroprotective agent for the treatment of secondary brain injury after TBI.

Associations of adverse childhood experiences with common psychiatric disorder in later life: results from the China mental health survey.

BACKGROUND: Associations between adverse childhood experiences (ACEs) and common psychiatric disorders among older Chinese individuals have not been well reported. The objectives of this study are to examine the prevalence of ACEs and the associations of ACEs with common psychiatric disorders among older adults in China. METHODS: The study used data from the China Mental Health Survey (CMHS), a nationally representative epidemiological survey, which used computer-assisted personal interviewing (CAPI), logistic regression models were used to examine community-based adult psychiatric disorders and associated risk factors. Finally, 2,317 individuals aged 60 years or over were included in the CMHS. The national prevalence of ACEs in older adults were estimated and logistic regression were used to analyse the association between ACEs and past-year psychiatric disorders. RESULTS: Prevalence of ACEs among older adults in China was 18.1%. The three most common types of ACEs were neglect (11.6%), domestic violence (9.2%), and parental loss (9.1%). This study proved the association between ACEs and common past-year psychiatric disorders in older adults. ACEs increased the risk of past-year psychiatric disorders in older adults. After adjustment for age, sex, marital status, employment status, education, rural or urban residence, region, and physical diseases, the association between ACEs and past-year psychiatric disorders were still significant. CONCLUSIONS: ACEs are linked to an increased risk for past-year psychiatric disorders in older adults. ACEs may have long-term effects on older adults' mental well-being. Preventing ACEs may help reduce possible adverse health outcomes in later life.

Preclinical validation of a novel deep learning-based metal artifact correction algorithm for orthopedic CT imaging.

PURPOSE: To validate a novel deep learning-based metal artifact correction (MAC) algorithm for CT, namely, AI-MAC, in preclinical setting with comparison to conventional MAC and virtual monochromatic imaging (VMI) technique. MATERIALS AND METHODS: An experimental phantom was designed by consecutively inserting two sets of pedicle screws (size Φ 6.5 × 30-mm and Φ 7.5 × 40-mm) into a vertebral specimen to simulate the clinical scenario of metal implantation. The resulting MAC, VMI, and AI-MAC images were compared with respect to the metal-free reference image by subjective scoring, as well as by CT attenuation, image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and correction accuracy via adaptive segmentation of the paraspinal muscle and vertebral body. RESULTS: The AI-MAC and VMI images showed significantly higher subjective scores than the MAC image (all p < 0.05). The SNRs and CNRs on the AI-MAC image were comparable to the reference (all p > 0.05), whereas those on the VMI were significantly lower (all p < 0.05). The paraspinal muscle segmented on the AI-MAC image was 4.6% and 5.1% more complete to the VMI and MAC images for the Φ 6.5 × 30-mm screws, and 5.0% and 5.1% for the Φ 7.5 × 40-mm screws, respectively. The vertebral body segmented on the VMI was closest to the reference, with only 3.2% and 7.4% overestimation for Φ 6.5 × 30-mm and Φ 7.5 × 40-mm screws, respectively. CONCLUSIONS: Using metal-free reference as the ground truth for comparison, the AI-MAC outperforms VMI in characterizing soft tissue, while VMI is useful in skeletal depiction.

Aberrant degree centrality profiles during rumination in major depressive disorder.

Rumination is closely linked to the onset and maintenance of major depressive disorder (MDD). Prior neuroimaging studies have identified the association between self-reported rumination trait and the functional coupling among a network of brain regions using resting-state functional magnetic resonance imaging (MRI). However, little is known about the underlying neural circuitry mechanism during active rumination in MDD. Degree centrality (DC) is a simple metric to denote network integration, which is critical for higher-order psychological processes such as rumination. During an MRI scan, individuals with MDD (N = 45) and healthy controls (HC, N = 46) completed a rumination state task. We examined the interaction effect between the group (MDD vs. HC) and condition (rumination vs. distraction) on vertex-wise DC. We further characterized the identified brain region's functional involvement with Neurosynth and BrainMap. Network-wise seed-based functional connectivity (FC) analysis was also conducted for the identified region of interest. Finally, exploratory correlation analysis was conducted between the identified region of interest's network FCs and self-reported in-scanner affect levels. We found that a left superior frontal gyrus (SFG) region, generally overlapped with the frontal eye field, showed a significant interaction effect. Further analysis revealed its involvement with executive functions. FCs between this region, the frontoparietal, and the dorsal attention network (DAN) also showed significant interaction effects. Furthermore, its FC to DAN during distraction showed a marginally significant negative association with in-scanner affect level at the baseline. Our results implicated an essential role of the left SFG in the rumination's underlying neural circuitry mechanism in MDD and provided novel evidence for the conceptualization of rumination in terms of impaired executive control.

Gender differences in the association between body mass index and recent suicide attempts in Chinese patients with first-episode drug-naïve major depressive disorder.

Controversial evidence exists on the relationship between body mass index (BMI) and suicide attempts (SA) in patients with major depressive disorder (MDD). This cross-sectional study aimed to explore the association between BMI and SA in first-episode drug-naïve (FEDN) MDD patients in China. The study was conducted from 2016 to 2018 in Taiyuan, China. Univariate and multivariate logistic regression analyzed the BMI-SA association, with subgroup analysis for gender. Threshold effects were examined using two-piecewise regression. In males, BMI was significantly associated with SA (OR = 0.84, 95% CI 0.74-0.94, P = 0.003) after full adjustment, but not in females (OR = 0.97, 95% CI 0.89-1.06, P = 0.541). The interaction with gender was significant (P for interaction < 0.05). Smoothing plots revealed an L-shaped BMI-SA relationship in both genders, with BMI inflection points at 27.3 kg/m2 in males and 21.4 kg/m2 in females. Below the inflection points, BMI is negatively associated with SA in males (OR = 0.75, 95% CI 0.66-0.86, P < 0.001) and females (OR = 0.48, 95% CI 0.32-0.72, P < 0.001). Above the inflection points, no association existed for both genders (all P > 0.05). Results showed an L-shaped nonlinear BMI-SA relationship in FEDN MDD patients but differing BMI inflection points between genders, thus contributing to effective prevention programs for suicide.

Multivariate classification based on large-scale brain networks during early abstinence predicted lapse among male detoxified alcohol-dependent patients.

Identifying biomarkers to predict lapse of alcohol-dependence (AD) is essential for treatment and prevention strategies, but remains remarkably challenging. With an aim to identify neuroimaging features for predicting AD lapse, 66 male AD patients during early-abstinence (baseline) after hospitalized detoxification underwent resting-state functional magnetic resonance imaging and were then followed-up for 6 months. The relevance-vector-machine (RVM) analysis on baseline large-scale brain networks yielded an elegant model for differentiating relapsing patients (n = 38) from abstainers, with the area under the curve of 0.912 and the accuracy by leave-one-out cross-validation of 0.833. This model captured key information about neuro-connectome biomarkers for predicting AD lapse.

Association between triglyceride glucose index and suicide attempts in patients with first-episode drug-naïve major depressive disorder.

Objective: Triglyceride glucose (TyG) index has been suggested as an alternative indicator of insulin resistance (IR); however, the association between TyG index and suicide attempts (SA) in major depressive disorder (MDD) is unclear. The aim of this study was to investigate the relationship between TyG index and SA in Chinese patients with first-episode drug-naïve (FEDN) MDD. Methods: This cross-sectional study enrolled 1,718 patients with FEDN MDD aged 34.9 ± 12.4 years from the First Hospital of Shanxi Medical University (Taiyuan, Shanxi Province, China) from September 2016 to December 2018. Multivariable binary logistic regression analysis was used to estimate the association between TyG index and the risk of SA. A two-piecewise linear regression model was used to investigate the threshold effects if non-linearity associations existed. Interaction and stratified analyses were performed based on sex, education, marital status, comorbid anxiety, and psychotic symptoms. Results: Multivariable logistic regression analysis revealed that TyG index was positively associated with the risk of SA after adjusting for confounders (OR = 1.35, 95% CI: 1.04-1.75, p = 0.03). Smoothing plots also showed a nonlinear relationship between TyG index and SA, with the inflection point of TyG index being 9.29. On the right of the inflection point, a positive association between TyG index and SA was detected (OR = 3.47, 95% CI: 1.81 to 6.66, p < 0.001), while no significant association was observed on the left side of the inflection point (OR = 1.14, 95% CI: 0.79 to 1.66, p = 0.476). Conclusion: The relationship between TyG index and SA risk was non-linear and exhibited a threshold effect in Chinese patients with FEDN MDD. When TyG index was greater than 9.29, they showed a significant positive correlation.

Efficacy and safety of Transcranial Direct Current Stimulation (tDCS) on cognitive function in chronic schizophrenia with Tardive Dyskinesia (TD): a randomized, double-blind, sham-controlled, clinical trial.

OBJECTIVE: Previous studies have shown that transcranial direct current stimulation(tDCS) led to an improvement of cognitive function in patients with schizophrenia, but rare study has explored the effect of tDCS on long-term hospitalized chronic schizophrenia with tardive dyskinesia (TD). The present research explored if cognitive function in patients with long-term hospitalized chronic schizophrenia with TD could be improved through tDCS. METHODS: This study is a randomized, double-blind, sham-controlled clinical trial. Of the 52 patients, 14 dropped out, and 38 completed the experiment. Thirty-eight patients on stable treatment regimens were randomly assigned to receive active tDCS(n = 21) or sham stimulation(n = 17) on weekdays of the first, third, and fifth weeks of treatment. Patients performed the Pattern Recognition Memory (PRM) and the Intra/Extradimensional Set Shift (IED) from the Cambridge Neuropsychological Test Automated Battery (CANTAB) at baseline and the end of week 3, week 5. Clinical symptoms were also measured at the baseline and the fifth week using the Scale for the Assessment of Negative Symptoms (SANS) and the Positive and Negative Syndrome Scale (PANSS). Side effects of tDCS were assessed with an experimenter-administered open-ended questionnaire during the whole experiment. RESULTS: There were no significant differences in PRM and IED performance metrics, SANS total score and PANSS total score between active and sham tDCS groups at the end of week 5 (p > 0.05). Furthermore, there was a significant difference in the adverse effects of the tingling sensation between the two groups (p < 0.05), but there was no significant difference in other side effects (p > 0.05). CONCLUSION: According to these findings, no evidence supports using anodal stimulation over the left dorsolateral prefrontal cortex to improve cognitive function in patients with long-term hospitalized chronic schizophrenia with TD.

Sex-differential association of suicide attempts with thyroid dysfunction in first-episode and drug-naïve young major depressive disorder patients with comorbid anxiety.

This study aimed to explore sex differences in the relationship between thyroid function indicators and suicide attempts in first-episode and drug-naïve young major depressive disorder (MDD) patients with comorbid anxiety (MDA). A total of 917 MDD patients (aged 18-35 years) were recruited. The Hamilton depression rating scale (HAMD-17), Hamilton anxiety rating scale (HAMA), positive and negative syndrome scale (PANSS) positive subscale and clinical global impression of severity scale (CGI-S) were used. 467 patients were classified as MDA. The prevalence of suicide attempts was 31.3% in MDA patients, which was significantly higher than that (7.3%) in MDD patients without anxiety. Compared with MDA patients without suicide attempts, MDA patients with suicide attempts were older, had a later age of onset, higher HAMD-17, HAMA, and PANSS positive symptom subscale scores, as well as higher TSH, TgAb and TPOAb levels. For male patients, TSH and TPOAb levels were independently associated with suicide attempts. For female patients, HAMA, PANSS positive symptom scores, CGI-S score and TPOAb levels were independently associated with suicide attempts. Our results suggest that the indicators of thyroid function which can predict suicide attempts in male and female MDA patients have sex differences.

Association between body mass index and suicide attempts in Chinese patients of a hospital in Shanxi district with first-episode drug-naïve major depressive disorder.

OBJECTIVE: In patients with major depressive disorder (MDD), the relationship between body mass index (BMI) and risk of suicide attempts (SA) remains unclear, and findings are controversial. The aim of this study was to investigate the relationship between BMI and SA in a Chinese population with first-episode drug-naïve (FEDN) MDD. METHODS: A total of 1718 patients with FEDN MDD were enrolled in this cross-sectional study. Their socio-demographic characteristics as well as anthropometric data were collected. The 17-item Hamilton Rating Scale (HAMD-17) and Hamilton Anxiety Scale (HAMA) were used to assess the severity of depression and anxiety symptoms in all participants. Thyroid hormones, lipid profile, and fasting blood glucose (FBG) were measured. A history of suicide attempts was verified based on medical records and interviews with patients and their family members. Multiple logistic regression analysis was used to estimate the association between BMI and the risk of SA. Threshold effects were examined by a two-piecewise logistic regression model. RESULTS: Multiple logistic regression analysis showed that BMI was independently and negatively correlated with SA (OR = 0.91, 95%CI: 0.85 to 0.98, P = 0.01) in patients with FEDN MDD after adjusting for covariates. Smoothing plots also revealed a non-linear (L-shaped) relationship between BMI and SA, and a two-piecewise logistic regression model was used to calculate the inflection point of BMI as 22.1 kg/m2. On the left of the inflection point, a negative association between BMI and SA was detected (OR = 0.54, 95%CI: 0.42 to 0.70, P < 0.001), while no significant association was observed on the right side of the inflection point (OR = 1.01, 95%CI: 0.93 to 1.10, P = 0.75). CONCLUSIONS: Our results suggest that lower BMI is associated with a higher risk of recent SA in Chinese patients with FEDN MDD, especially in those with BMI below 22.1 kg/m2.

Prevalence and clinical correlates of psychotic symptoms in first-episode untreated female chinese patients with major depressive disorder.

BACKGROUND: Recent studies have reported that psychotic symptoms are common in patients with major depressive disorder (MDD). However, few studies have reported the relationship between thyroid function, lipid metabolism and clinical profiles in female MDD patients. Thus, this study aimed to investigate the prevalence of psychotic depression (PD) and its risk factors in first-episode and drug naive (FEDN) depression among the female population in China. METHODS: This was a cross-sectional study involving a representative probability sample of 1,130 FEDN female outpatients with MDD (aged 18 years or older) in China. We collected information relating to socio-demographic characteristics, clinical data and blood samples. The Hamilton Depression Rating Scale 17-item version (HAMD-17), Hamilton Anxiety Rating Scale 14-item version (HAMA-14), and Positive and Negative Syndrome Scale (PANSS) were used to evaluate depressive, anxiety, and psychotic symptoms. RESULTS: The prevalence of psychotic symptoms in female MDD patients was 10.97%. The findings revealed significant differences between MDD female patients with psychotic symptoms and non-PD female patients in the following areas: higher HAMD scores, higher HAMA scores, more severe anxiety and an increased risk of suicide attempts. Further logistic regression analysis showed that psychotic symptoms were associated with higher thyroid-stimulating hormone (TSH) levels and an odds ratio of 1.168. CONCLUSIONS: Our findings supported the hypothesis that higher TSH levels were correlated with psychotic symptoms in female MDD patients. Therefore, serum TSH levels may be a potential biomarker of PD in female MDD patients. In addition, we found that PD was closely associated with suicide attempts and lipid levels, but did not reach statistical significance.

Decreased plasma neuropeptides in first-episode schizophrenia, bipolar disorder, major depressive disorder: associations with clinical symptoms and cognitive function.

Background: There is an urgent need to identify differentiating and disease-monitoring biomarkers of schizophrenia, bipolar disorders (BD), and major depressive disorders (MDD) to improve treatment and management. Methods: We recruited 54 first-episode schizophrenia (FES) patients, 52 BD patients, 35 MDD patients, and 54 healthy controls from inpatient and outpatient clinics. α-Melanocyte Stimulating Hormone (α-MSH), ß-endorphin, neurotensin, orexin-A, oxytocin, and substance P were investigated using quantitative multiplex assay method. Psychotic symptoms were measured using the Brief Psychiatric Rating Scale (BPRS) and Positive and Negative Syndrome Scale (PANSS), manic symptoms using the Young Mania Rating Scale (YMRS), and depressive symptoms using 17 item-Hamilton Depression Rating Scale (HAMD). We additionally measured cognitive function by using a battery of tests given to all participants. Results: α-MSH, neurotensin, orexin-A, oxytocin, and substance P were decreased in the three patient groups compared with controls. Neurotensin outperformed all biomarkers in differentiating patient groups from controls. There were no significant differences for 6 neuropeptides in their ability to differentiate between the three patient groups. Higher neurotensin was associated with better executive function across the entire sample. Lower oxytocin and higher substance p were associated with more psychotic symptoms in FES and BD groups. ß-endorphin was associated with early morning wakening symptom in all three patient groups. Conclusion: Our research shows decreased circulating neuropeptides have the potential to differentiate severe mental illnesses from controls. These neuropeptides are promising treatment targets for improving clinical symptoms and cognitive function in FES, BD, and MDD.