Heatwave characteristics complicate the association between PM2.5 components and schizophrenia hospitalizations in a changing climate: Leveraging of the individual residential environment.

BACKGROUND: In the era characterized by global environmental and climatic changes, understanding the effects of PM2.5 components and heatwaves on schizophrenia (SCZ) is essential for implementing environmental interventions at the population level. However, research in this area remains limited, which highlights the need for further research and effort. We aim to assess the association between exposure to PM2.5 components and hospitalizations for SCZ under different heatwave characteristics. METHODS: We conducted a 16 municipalities-wide, individual exposure-based, time-stratified, case-crossover study from January 1, 2017, to December 31, 2020, encompassing 160736 hospitalizations in Anhui Province, China. Daily concentrations of PM2.5 components were obtained from the Tracking Air Pollution in China dataset. Conditional logistic regression models were used to investigate the association between PM2.5 components and hospitalizations. Additionally, restricted cubic spline models were used to identify protective thresholds of residential environment in response to environmental and climate change. RESULTS: Our findings indicate a positive correlation between PM2.5 and its components and hospitalizations. Significantly, a 1 µg/m3 increase in black carbon (BC) was associated with the highest risk, at 1.58% (95%CI: 0.95-2.25). Exposure to heatwaves synergistically enhanced the impact of PM2.5 components on hospitalization risks, and the interaction varied with the intensity and duration of heatwaves. Under the 99th percentile heatwave events, the impact of PM2.5 and its components on hospitalizations was most pronounced, which were PM2.5 (2-4d: 4.59%, 5.09%, and 5.09%), sulfate (2-4d: 21.73%, 23.23%, and 25.25%), nitrate (2-4d: 17.51%, 16.93%, and 20.31%), ammonium (2-4d: 27.49%, 31.03%, and 32.41%), organic matter (2-4d: 32.07%, 25.42%, and 24.48%), and BC (2-4d: 259.36%, 288.21%, and 152.52%), respectively. Encouragingly, a protective effect was observed when green and blue spaces comprised more than 17.6% of the residential environment. DISCUSSION: PM2.5 components and heatwave exposure were positively associated with an increased risk of hospitalizations, although green and blue spaces provided a mitigating effect.

Distinct basolateral amygdala excitatory inputs mediate the somatosensory and aversive-affective components of pain.

Pain is a multidimensional perception that includes unpleasant somatosensory and affective experiences; however, the underlying neural circuits that mediate different components of pain remain elusive. Although hyperactivity of basolateral amygdala glutamatergic (BLAGlu) neurons is required for the somatosensory and emotional processing of pain, the precise excitatory inputs to BLAGlu neurons and their roles in mediating different aspects of pain are unclear. Here, we identified two discrete glutamatergic neuronal circuits in male mice: a projection from the insular cortex glutamatergic (ICGlu) to BLAGlu neurons, which modulates both the somatosensory and affective components of pain, and a projection from the mediodorsal thalamic nucleus (MDGlu) to BLAGlu neurons, which modulates only the aversive-affective component of pain. Using whole-cell recording and fiber photometry, we found that neurons within the IC→BLA and MD→BLA pathways were activated in mice upon inflammatory pain induced by injection of complete Freund's adjuvant (CFA) into their paws. Optical inhibition of the ICGlu→BLA pathway increased the nociceptive threshold and induced behavioral place preference in CFA mice. In contrast, optical inhibition of the MDGlu→BLA pathway did not affect the nociceptive threshold but still induced place preference in CFA mice. In normal mice, optical activation of the ICGlu→BLA pathway decreased the nociceptive threshold and induced place aversion, while optical activation of the MDGlu→BLA pathway only evoked aversion. Taken together, our results demonstrate that discrete ICGlu→BLA and MDGlu→BLA pathways are involved in modulating different components of pain, provide insights into its circuit basis, and better our understanding of pain perception.

Relationship between serum vitamin D and thyroid hormone profiles in male patients with alcohol dependence.

BACKGROUND: Alcohol dependence (AD) results in several medical problems including vitamin D deficiency and thyroid dysfunction. However, the relationship between these two complications remains unclear. The aim of the present study was to explore the relationship between serum vitamin D and thyroid hormone profiles in male patients with AD. METHODS: A total of 117 male patients with AD were enrolled. Vitamin D deficiency was defined as serum concentrations of the main circulating vitamin D, 25-hydroxy vitamin D [25(OH)D], below 50 nmol/L. The AD patients were divided into two groups accordingly: 46 patients with normal vitamin D levels (normal group) and 71 patients with vitamin D deficiency (deficiency group). The levels of thyroid hormone profiles including total triiodothyronine 3 (TT3), total thyroxine 4 (TT4), thyroid stimulating hormone (TSH), free triiodothyronine (fT3), and free thyroxine (fT4) between the two groups were compared. Correlation between the serum levels of 25(OH)D and thyroid hormone profiles was evaluated using simple correlation (Pearson's correlation) and multivariable analysis using linear regression models. RESULTS: The prevalence of vitamin D deficiency in male patients with AD is 60.7% (71/117; 95% confidence interval: 51.6-69.1%). Moreover, the serum levels of TT3 (t = -2.682, p = 0.009), TT4 (t = -2.033, p = 0.044), fT3 (t = -2.986, p = 0.003), and fT4 (t = -2.558, p = 0.012) in deficiency group were significantly higher than those in normal group. Post hoc power analyses showed that the power for fT3 was sufficient (power > 0.80). Furthermore, univariate analysis showed that the serum vitamin D levels were negatively correlated with the TT3 (r = -0.189, p = 0.044), fT3 (r = -0.350, p < 0.001), and fT4 (r = -0.198, p = 0.033) levels, while multivariate analysis indicated that only fT3 was independently related to the serum levels of vitamin D in male patients with AD. CONCLUSIONS: These results suggested that the serum vitamin D levels may be associated with fT3 in male patients with AD.

Correlation between elevated serum interleukin-1ß, interleukin-16 levels and psychiatric symptoms in patients with schizophrenia at different stages.

BACKGROUND: There is increasing evidence that immune dysfunction plays an important role in the pathogenesis of schizophrenia. Meso Scale Discovery (MSD) is bioanalytical method, which can detect serum inflammatory factors in patients. MSD has higher sensitivities, capturing a narrower range of proteins compared to other methods typically used in similar studies. The present study was aimed to explore the correlation between the levels of serum inflammatory factors and psychiatric symptoms in patients with schizophrenia at different stages and investigate a wide panel of inflammatory factors as independent factors for the pathogenesis of schizophrenia. METHODS: We recruited 116 participants, including patients with first-episode schizophrenia (FEG, n = 40), recurrence patients (REG, n = 40) with relapse-episode schizophrenia, and a control group (healthy people, HP, n = 36). Patients are diagnosed according to the DSM -V. The plasma levels of IFN-γ, IL-10, IL-1ß, IL-2, IL-6, TNF-α, CRP, VEGF, IL-15, and IL-16 were tested by the MSD technique. Patient-related data was collected, including sociodemographic data, positive and negative symptom scale (PANSS), and brief psychiatric rating scale (BPRS) and subscale scores. The independent sample T test, χ2 test, Analysis of covariance (ANCOVA), the least significant difference method (LSD), Spearman's correlation test, binary logistic regression analysis and ROC curve analysis were used in this study. RESULTS: There were significant differences in serum IL-1ß (F = 2.37, P = 0.014) and IL-16 (F = 4.40, P < 0.001) levels among the three groups. The level of serum IL-1ß in the first-episode group was significantly higher than in the recurrence group (F = 0.87, P = 0.021) and control group (F = 2.03, P = 0.013), but there was no significant difference between the recurrence group and control group (F = 1.65, P = 0.806). The serum IL-16 levels in the first-episode group (F = 1.18, P < 0.001) and the recurrence group (F = 0.83, P < 0.001) were significantly higher than in the control group, and there was no significant difference between the first-episode group and the recurrence group (F = 1.65, P = 0.61). Serum IL-1ß was negatively correlated with the general psychopathological score (GPS) of PANSS (R=-0.353, P = 0.026). In the recurrence group, serum IL-16 was positively correlated with the negative score (NEG) of the PANSS scale (R = 0.335, P = 0.035) and negatively correlated with the composite score (COM) (R=-0.329, P = 0.038). In the study, IL-16 levels were an independent variable of the onset of schizophrenia both in the first-episode (OR = 1.034, P = 0.002) and recurrence groups (OR = 1.049, P = 0.003). ROC curve analysis showed that the areas under IL-16(FEG) and IL-16(REG) curves were 0.883 (95%CI:0.794-0.942) and 0.887 (95%CI:0.801-0.950). CONCLUSIONS: Serum IL-1ß and IL-16 levels were different between patients with schizophrenia and healthy people. Serum IL-1ß levels in first-episode schizophrenia and serum IL-16 levels in relapsing schizophrenia were correlated with the parts of psychiatric symptoms. The IL-16 level may be an independent factor associating with the onset of schizophrenia.

Potential role between inflammatory cytokines and Tie-2 receptor levels and clinical symptoms in patients with first-episode schizophrenia.

BACKGROUND: Schizophrenia (SCZ) is associated with chronic low-grade inflammation, which may be involved in the underlying pathological mechanism of the disease and may influence patient prognosis. We evaluated the differences in serum cytokine and Tie-2 receptor levels between patients with first-episode SCZ and healthy controls and explored the correlation thereof with clinical symptoms. METHODS: Seventy-six participants were recruited for the present study, including 40 patients with first-episode SCZ and 36 healthy controls. Positive and Negative Syndrome Scale (PANSS) and Brief Psychiatric Rating Scale (BPRS) scores, demographic data, and blood samples were collected at baseline. A hypersensitive Meso Scale Discovery (MSD) electrochemiluminescence assay system was used to measure cytokine and Tie-2 receptor levels. Spearman's correlation and stepwise linear regression were used to analyze the data. RESULTS: Serum interleukin-1ß and -4 levels were significantly increased, and Tie-2 levels were significantly decreased, in first-episode SCZ patients as compared to healthy controls. IL-1ß levels were positively correlated with total BPRS scores, resistance subscores, and PANSS positive subscores. Furthermore, IL-1ß levels were negatively correlated with Tie-2 receptor expression levels. Stepwise linear regression analysis demonstrated that IL-1ß levels correlated positively with PANSS positive subscores and BPRS total scores. PANSS negative subscores, general psychopathology subscores, and PANSS total scores had positive effects on the Tie-2 receptor. Receiver operating characteristic (ROC) curve analysis showed that IL-1ß and Tie-2 were highly sensitive and specific for predicting first-episode SCZ symptoms and achieving an area under the ROC curve of 0.8361 and 0.6462, respectively. CONCLUSION: Our results showed that patients with first-episode SCZ have low-grade inflammation. IL-1ß and Tie-2 receptors may be important mediators between inflammation and vascular dysfunction in patients with SCZ and may underlie the increased cardiovascular disease in this population. TRIAL REGISTRATION: The clinical trial registration date was 06/11/2018, registration number was chiCTR1800019343.

Intricate role of intestinal microbe and metabolite in schizophrenia.

BACKGROUND: The brain-gut axis has gained increasing attention due to its contribution to the etiology of various central nervous system disorders. This study aims to elucidate the hypothesis that schizophrenia is associated with disturbances in intestinal microflora and imbalance in intestinal metabolites. By exploring the intricate relationship between the gut and the brain, with the goal of offering fresh perspectives and valuable insights into the potential contribution of intestinal microbial and metabolites dysbiosis to the etiology of schizophrenia. METHODS: In this study, we used a 16S ribosomal RNA (16S rRNA) gene sequence-based approach and an untargeted liquid chromatography-mass spectrometry-based metabolic profiling approach to measure the gut microbiome and microbial metabolites from 44 healthy controls, 41 acute patients, and 39 remission patients, to evaluate whether microbial dysbiosis and microbial metabolite biomarkers were linked with the severity of schizophrenic symptoms. RESULTS: Here, we identified 20 dominant disturbances in the gut microbial composition of patients compared with healthy controls, with 3 orders, 4 families, 9 genera, and 4 species. Several unique bacterial taxa associated with schizophrenia severity. Compared with healthy controls, 145 unusual microflora metabolites were detected in the acute and remission groups, which were mainly involved in environmental information processing, metabolism, organismal systems, and human diseases in the Kyoto encyclopedia of genes and genomes pathway. The Sankey diagram showed that 4 abnormal intestinal and 4 anomalous intestinal microbial metabolites were associated with psychiatric clinical symptoms. CONCLUSIONS: These findings suggest a possible interactive influence of the gut microbiota and their metabolites on the pathophysiology of schizophrenia.

The impact of cold spells on schizophrenia admissions and the synergistic effect with the air quality index.

OBJECTIVES: Under current global climate conditions, there are insufficient studies on the health influences of cold spells, especially on mental health. This study aimed to examine the effect of cold spells on schizophrenia admissions and to analyze the potential interaction effect with the air quality index (AQI). METHODS: Daily data on schizophrenia admissions and climatic variables in Hefei were collected from 2013 to 2019. Based on 20 definitions, the impacts of cold spells were quantified separately to find the most appropriate definition for the region, and meta-regression was used to explore the different effect sizes of the different days in a cold spell event. In addition, the potential interaction effect was tested by introducing a categorical variable, CSH, reflecting the cold spell and AQI level. RESULTS: The cold spell defined by temperature below the 6th centile while lasting for at least three days produced the optimum model fit performance. In general, the risk of schizophrenia admissions increased on cold spell days. The largest single-day effect occurred on the 12th day with RR = 1.081 (95% CI: 1.044, 1.118). In a single cold spell event, the effect of the 3rd and subsequent days of a cold spell (RR = 1.082, 95% CI: 1.036, 1.130) was higher than that on the 2nd day (RR = 1.054, 95% CI: 1.024, 1.085). Similarly, the effect of the 2nd day was also higher than that of the 1st day (RR = 1.027, 95% CI: 1.012, 1.042). We found a synergistic effect between cold spells and high AQI in the male group, and the relative excess risk due to interaction (RERI) was 0.018 (95% CI: 0.005-0.030). CONCLUSIONS: This study suggested that the impacts of cold spells should be considered based on the definition of the most appropriate for the region when formulating targeted measures of schizophrenia. The discovery of the synergistic effect was referred to help the selection of the timing of precautions for susceptible people.

Prediction of violence in male schizophrenia using sMRI, based on machine learning algorithms.

BACKGROUND: Violent behavior in patients with schizophrenia (SCZ) is a major social problem. The early identification of SCZ patients with violence can facilitate implementation of targeted intervention. METHODS: A total of 57 male SCZ patients were recruited into this study. The general linear model was utilized to compare differences in structural magnetic resonance imaging (sMRI) including gray matter volume, cortical surface area, and cortical thickness between 30 SCZ patients who had exhibited violence and 27 SCZ patients without a history of violence. Based on machine learning algorithms, the different sMRI features between groups were integrated into the models for prediction of violence in SCZ patients. RESULTS: After controlling for the whole brain volume and age, the general linear model showed significant reductions in right bankssts thickness, inferior parietal thickness as well as left frontal pole volume in the patients with SCZ and violence relative to those without violence. Among seven machine learning algorithms, Support Vector Machine (SVM) have better performance in differentiating patients with violence from those without violence, with its balanced accuracy and area under curve (AUC) reaching 0.8231 and 0.841, respectively. CONCLUSIONS: Patients with SCZ who had a history of violence displayed reduced cortical thickness and volume in several brain regions. Based on machine learning algorithms, structural MRI features are useful to improve predictive ability of SCZ patients at particular risk of violence.

Long-term maintenance of synaptic plasticity by Fullerenol Ameliorates lead-induced-impaired learning and memory in vivo.

Fullerenol, a functional and water-soluble fullerene derivative, plays an important role in antioxidant, antitumor and antivirus, implying its enormous potential in biomedical applications. However, the in vivo performance of fullerenol remains largely unclear. We aimed to investigate the effect of fullerenol (i.p., 5 mg/kg) on the impaired hippocampus in a rat model of lead exposure. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) is a kind of newly developed soft-ionization mass spectrometry technology. In the present study, an innovative strategy for biological distribution analysis using MALDI-TOF-MS confirmed that fullerenol could across the blood-brain barrier and accumulate in the brain. Results from behavioral tests showed that a low dose of fullerenol could improve the impaired learning and memory induced by lead. Furthermore, electrophysiology examinations indicated that this potential repair effect of fullerenol was mainly due to the long-term changes in hippocampal synaptic plasticity, with enhancement lasting for more than 2-3 h. In addition, morphological observations and biochemistry analyses manifested that the long-term change in synaptic efficacy was accompanied by some structural alteration in synaptic connection. Our study demonstrates the therapeutic feature of fullerenol will be beneficial to the discovery and development as a new drug and lays a solid foundation for further biomedical applications of nanomedicines.

Sodium salicylate enhances neural excitation via reducing GABAergic transmission in the dentate gyrus area of rat hippocampus in vivo.

Sodium salicylate, one of the non-steroidal anti-inflammatory drugs, is widely prescribed in the clinic, but a high dose of usage can cause hyperactivity in the central nervous system, including the hippocampus. At present, the neural mechanism underlying the induced hyperactivity is not fully understood, in particular, in the hippocampus under an in vivo condition. In this study, we found that systemic administration of sodium salicylate increased the field excitatory postsynaptic potential slope and the population spike amplitude in a dose-dependent manner in the hippocampal dentate gyrus area of rats with in vivo field potential extracellular recordings, which indicates that sodium salicylate enhances basal synaptic transmission and neural excitation. In the presence of picrotoxin, a GABA-A receptor antagonist, sodium salicylate failed to increase the initial slope of the field excitatory postsynaptic potential and the amplitude of the population spike in vivo. To further explore how sodium salicylate enhances the neural excitation, we made whole-cell patch-clamp recordings from hippocampal slices. We found that perfusion of the slice with sodium salicylate decreased electrically evoked GABA receptor-mediated currents, increased paired-pulse ratio, and lowered frequency and amplitude of miniature inhibitory postsynaptic currents. Together, these results demonstrate that sodium salicylate enhances the neural excitation through suppressing GABAergic synaptic transmission in presynaptic and postsynaptic mechanisms in the hippocampal dentate gyrus area. Our findings may help understand the side effects caused by sodium salicylate in the central nervous system.

Ambient concentrations of NO2 and hospital admissions for schizophrenia.

OBJECTIVES: Schizophrenia is a chronic and severe mental disorder affecting more than 21 million people worldwide. Short-term exposure to nitrogen dioxide (NO2) has been associated with hospital admissions (HAs) for mental disorders, but no study has evaluated the specific association of NO2 and schizophrenia. Additionally, the shape of the concentration-response (C-R) curve has not yet been assessed at present. This study aims to investigate the relationship between short-term exposure to NO2 and HAs for schizophrenia in Hefei, from 2014 to 2016. We also attempt to explore the C-R and the underlying effect modifiers of the association. METHODS: Daily number of HAs for schizophrenia was derived from the computerised medical record system of Anhui Mental Health Center. We used a time-series Poisson generalised linear regression combined with distributed lag non-linear models to model the NO2-schizophrenia relationship. RESULTS: A total of 11 373 HAs were identified during the study period. An increase in levels of NO2 was significantly associated with elevated schizophrenia HAs. The estimated relative risk per IQR increase in NO2 at lag 01 was 1.10 (95% CI 1.01 to 1.18). Greater association was observed in young patients (relative risk: 1.11, 95% CI 1.02 to 1.19). The modelled C-R curves of the NO2-schizophrenia relationship suggested possible threshold effects of NO2 for all ages combined, young patients, men and both seasons. CONCLUSIONS: Short-term exposure to NO2 may be associated with increased schizophrenia HAs. Findings indicated potential threshold effects of NO2, which has important implications for health-based risk assessments.

Impact of short-term temperature variability on emergency hospital admissions for schizophrenia stratified by season of birth.

Diurnal temperature range (DTR) and temperature change between neighboring days (TCN) are important meteorological indicators closely associated with global climate change. However, up to date, there have been no studies addressing the impacts of both DTR and TCN on emergency hospital admissions for schizophrenia. We conducted a time-series analysis to assess the relationship between temperature variability and daily schizophrenia onset in Hefei, an inland city in southeast China. Daily meteorological data and emergency hospital admissions for schizophrenia from 2005 to 2014 in Hefei were collected. After stratifying by season of birth, Poisson generalized linear regression combined with distributed lag nonlinear model (DLNM) was used to examine the relationship between temperature variability and schizophrenia, adjusting for long-term trend and seasonality, mean temperature, and relative humidity. Our analysis revealed that extreme temperature variability may increase the risk for schizophrenia onset among patients born in spring, while no such association was found in patients born in summer and autumn. In patients born in spring, the relative risks of extremely high DTR comparing the 95th and 99th percentiles with the reference (50th, 10 °C) at 3-day lag were 1.078 (95 % confidence interval (CI) 1.025-1.135) and 1.159 (95 % CI 1.050-1.279), respectively. For TCN effects, only comparing 99th percentile with reference (50th, 0.7 °C) was significantly associated with emergency hospital admissions for schizophrenia (relative risk (RR) 1.111, 95 % CI 1.002-1.231). This study suggested that exposure to extreme temperature variability in short-term may trigger later days of schizophrenia onset for patients born in spring, which may have important implications for developing intervention strategies to prevent large temperature variability exposure.

Decline in Working Memory in Stable Schizophrenia May Be Related to Attentional Impairment: Mediating Effects of Negative Symptoms, a Cross-Sectional Study.

Background: Schizophrenia (SCZ) is a severe mental illness, Cognitive deficits and negative symptoms (NS) are prevalent in individuals with SCZ and are crucial indicators of functional recovery. It is well known that cognitive symptoms and negative symptoms are interrelated and that negative symptoms can affect the ability to take cognitive tests. However, the specific relationship between attention, working memory (WM), and NS in stable SCZ remains unclear. This study aims to explore these associations and provide valuable insights for the subsequent treatment of SCZ. Methods: We conducted a comprehensive assessment of 145 patients with stable SCZ using the Chinese Brief Neurocognitive Suite of Tests (C-BCT) and the Positive and Negative Symptom Scale (PANSS). Results: Patients with abnormal cognition exhibited significantly higher PANSS total scores, cognitive symptom scores, and NS than those with normal cognition (P<0.05). Pearson's correlation analysis revealed significant positive correlations between digital breadth(DB) and continuous operation(CO) (r=0.389, P<0.001), as well as a significant negative correlation between DB and NS (r=-0.291, P<0.001). Moreover, CO showed a negative correlation with NS (r=-0.173, P<0.05). However, no significant correlations were found between the digital breadth-anterograde score and CO or NS (r=0.148, P>0.05; r=-0.068, P>0.05). Notably, NS were identified as a mediator in the relationship between attention and WM (effect size=0.024). Conclusion: Our findings highlight significant associations between WM, attention, and NS in individuals with stable SCZ. Moreover, attention not only directly impacts WM but also indirectly influences it through NS. Addressing cognitive deficits and NS in the treatment of SCZ may lead to improved overall outcomes for affected individuals.

Identification of male schizophrenia patients using brain morphology based on machine learning algorithms.

BACKGROUND: Schizophrenia is a severe psychiatric disease, and its prevalence is higher. However, diagnosis of early-stage schizophrenia is still considered a challenging task. AIM: To employ brain morphological features and machine learning method to differentiate male individuals with schizophrenia from healthy controls. METHODS: The least absolute shrinkage and selection operator and t tests were applied to select important features from structural magnetic resonance images as input features for classification. Four commonly used machine learning algorithms, the general linear model, random forest (RF), k-nearest neighbors, and support vector machine algorithms, were used to develop the classification models. The performance of the classification models was evaluated according to the area under the receiver operating characteristic curve (AUC). RESULTS: A total of 8 important features with significant differences between groups were considered as input features for the establishment of classification models based on the four machine learning algorithms. Compared to other machine learning algorithms, RF yielded better performance in the discrimination of male schizophrenic individuals from healthy controls, with an AUC of 0.886. CONCLUSION: Our research suggests that brain morphological features can be used to improve the early diagnosis of schizophrenia in male patients.

Dysregulation of interleukin-8 is involved in the onset and relapse of schizophrenia: An independent validation and meta-analysis.

As a major mental health disorder, symptoms of schizophrenia (SCZ) include delusions, reduced motivation, hallucinations, reduced motivation and a variety of cognitive disabilities. Many of these symptoms are now known to be associated with abnormal regulation of the immune system. Low blood levels of cytokines and chemokines have been suggested to be one of the underlying causes of SCZ. However, their biological roles at different stages of SCZ remain unclear. Our objective was to investigate expression patterns of cytokines and chemokines at different stages of onset and relapse in SCZ patients and to conduct an analysis of their relationship to disease progression. We also aimed to identify immune features associated with different disease trajectories in patients with SCZ. Gene set enrichment analysis (GSEA) was used to interrogate the GSE27383 dataset and identify key genes associated with inflammation. These results led us to recruit 36 healthy controls, 40 patients with first-episode psychosis (FEP), and 39 patients with SCZ relapse. Meso Scale Discovery technology was used to independently validate serum levels of 35 cytokines and chemokines. This was followed by a meta-analysis to gain a more comprehensive understanding of the role of interleukin-8 (IL-8/CXCL8) in SCZ. Analysis of the GSE27383 database revealed 3596 genes with distinct expression patterns. A significant portion of these genes were identified as inflammation-related and showed remarkable enrichment in three key pathways: IL-17, cytokine-cytokine receptor, and AGE-RAGE signaling in diabetic complications. We observed co-expression of CXCL8 and IL-16 within these three pathways. In a subsequent analysis of independently validated samples, a notable discrepancy was detected in the inflammatory status between individuals experiencing FEP and those in relapse. In particular, expression of CXCL8 demonstrated superior predictive capability in FEP and relapsed patients. Notably, results of the meta-analysis confirmed that Chinese and European populations were consistent with the overall results (Z = 4.60, P < 0.001; Z = 3.70, P < 0.001). However, in the American subgroup, there was no significant difference in CXCL8 levels between patients with SCZ compared to healthy controls (Z = 1.09, P = 0.277). Our findings suggest that the inflammatory response in patients with SCZ differs across the different stages, with CXCL8 emerging as a potential predictive factor. Collectively, our data suggest that CXCL8 has the potential to serve as a significant immunological signature of SCZ subtypes. Trial registration: The clinical registration number for this trial is ChiCTR2100045240 (Registration Date: 2021/04/09).

Impaired thyroid hormone sensitivity exacerbates the effect of PM2.5 and its components on dyslipidemia in schizophrenia.

BACKGROUND: Dyslipidemia in schizophrenia causes a serious loss of healthy life expectancy, making it imperative to explore key environmental risk factors. We aimed to assess the effect of PM2.5 and its constituents on dyslipidemia in schizophrenia, identify the critical hazardous components, and investigate the role of impaired thyroid hormones (THs) sensitivity in this association. METHODS: We collected disease data on schizophrenia from the Anhui Mental Health Center from 2019 to 2022. Logistic regression was constructed to explore the effect of average annual exposure to PM2.5 and its components [black carbon (BC), organic matter (OM), sulfate (SO42-), ammonium (NH4+), and nitrate (NO3-)] on dyslipidemia, with subgroup analyses for age and gender. The degree of impaired THs sensitivity in participants was reflected by the Thyroid Feedback Quantile-based Index (TFQI), and its role in the association of PM2.5 components with dyslipidemia was explored. RESULTS: A total of 5125 patients with schizophrenia were included in this study. Exposure to PM2.5 and its components (BC, OM, SO42-, NH4+, and NO3-) were associated with dyslipidemia with the odds ratios and 95 % confidence interval of 1.13 (1.04, 1.23), 1.16 (1.07, 1.26), 1.15 (1.06, 1.25), 1.11 (1.03, 1.20), 1.09 (1.00, 1.18), 1.12 (1.04, 1.20), respectively. Mixed exposure modeling indicated that BC played a major role in the effects of the mixture. More significant associations were observed in males and groups <45 years. In addition, we found that the effect of PM2.5 and its components on dyslipidemia was exacerbated as impaired THs sensitivity in the patients. CONCLUSIONS: Exposure to PM2.5 and its components is associated with an increased risk of dyslipidemia in schizophrenia, which may be exacerbated by impaired THs sensitivity. Our results suggest a new perspective for the management of ambient particulate pollution and the protection of thyroid function in schizophrenia.

Correlation analysis of mental health conditions and personality of patients with alcohol addiction.

BACKGROUND: Alcohol addiction, or alcohol dependence, refers to a psychological state of strong craving for alcohol caused by drinking when both the drinking times and alcohol consumption reach a certain level. Alcohol addiction can cause irreversible damage, leading to mental illness or mental disorders, negative changes in their original personality, and a tendency to safety incidents such as committing suicide or violent attacks on others. Significant attention needs to be given to the mental health of alcohol addicts, which could reflect their abnormal personality traits. However, only a few papers on this issue have been reported in China. AIM: To investigate the correlation between mental health and personality in patients with alcohol addiction. METHODS: In this single-center observational study, we selected 80 patients with alcohol addiction as the research subjects, according to the criteria of the K10 scale to evaluate the mental health of patients with alcohol addiction, and divided these patients into four groups based on the evaluation results: Good, average, relatively poor and bad. And then analyzed the correlation between mental health conditions and personality characteristics from these four groups of patients. RESULTS: The average score of the K10 scale (Kessler 10 Simple Psychological Status Assessment Scale) in 80 patients with alcohol addiction was 25.45 points, the median score was 25 points, the highest score was 50 points, and the lowest score was 11 points. Pearson's analysis showed that the K10 score was positively correlated with the scores of these two subscales, such as the P-subscale and the N-subscale (P < 0.05). In contrast, the K10 score had no significant correlation with the scores from the E-subscale and the L-subscale (P > 0.05). CONCLUSION: The mental health conditions of patients with alcohol addiction are positively correlated with their personality characteristics.

Intermediary roles of prospective memory and retrospective memory in the comorbidity of depression and pain.

Background: Patients who suffer comorbidity of major depressive disorder (MDD) and chronic pain (CP) maintain a complex interplay between maladaptive prospective memory (PM) and retrospective memory (RM) with physical pain, and their complications are still unknown. Aims: We aimed to focus on the full cognitive performance and memory complaints in patients with MDD and CP, patients with depression without CP, and control subjects, considering the possible influence of depressed affect and chronic pain severity. Methods: According to the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders and the criteria given by the International Association of Pain, a total of 124 participants were included in this cross-sectional cohort study. Among them, 82 depressed inpatients and outpatients from Anhui Mental Health centre were divided into two groups: a comorbidity group(patients with MDD and CP) (n=40) and a depression group (patients with depression without CP) (n=42). Meanwhile, 42 healthy controls were screened from the hospital's physical examination centre from January 2019 to January 2022. The Hamilton Depression Rating Scale-24 (HAMD-24) and Beck Depression Inventory-II (BDI-II) were used to evaluate the severity of depression. The Pain Intensity Numerical Rating Scale (PI-NRS), Short-Form McGill Pain Questionnaire-2 Chinese version (SF-MPQ-2-CN), Montreal Cognitive Assessment-Basic Section (MoCA-BC), and Prospective and Retrospective Memory Questionnaire (PRMQ) were used to assess pain-related features and the global cognitive functioning of study participants. Results: The impairments in PM and RM differed remarkably among the three groups (F=7.221, p<0.001; F=7.408, p<0.001) and were severe in the comorbidity group. Spearman correlation analysis revealed the PM and RM were positively correlated with continuous pain and neuropathic pain (r=0.431, p<0.001; r=0.253, p=0.022 and r=0.415, p<0.001; r=0.247, p=0.025), respectively. Regression analysis indicated a significant positive relationship between affective descriptors and total BDI-II score (ß=0.594, t=6.600, p<0.001). Examining the mediator pathways revealed the indirect role of PM and RM in patients with comorbid MDD and CP. Conclusions: Patients with comorbid MDD and CP presented more PM and RM impairments than patients with MDD without CP. PM and RM are possibly mediating factors that affect the aetiology of comorbid MDD and CP. Trial registration number: chiCTR2000029917.

Associations of polycyclic aromatic hydrocarbons, water-soluble ions and metals in PM2.5 with liver function: Evidence from schizophrenia cohort.

BACKGROUND: Fine particulate matter (PM2.5) was reported to impact liver function, but the roles of specific PM2.5 chemical components remained to be explored. Besides, severe liver dysfunction in schizophrenia patients deserves attention. OBJECTIVE: To investigate the associations of short-term PM2.5 components with liver function in schizophrenia patients. METHODS: A repeated-measures study based on schizophrenia cohort including 1023 visits (n = 446) was conducted during 2017-2020. Liver function was reflected by 10 indicators including liver enzymes, proteins and bilirubin et al. Monitoring data of PM2.5 and its components, including 16 polycyclic aromatic hydrocarbons (PAHs), 4 water-soluble ions and 10 metals were collected. Linear mixed effect and Bayesian kernel machine regression (BKMR) models were used to evaluate the single and combined effects of PM2.5 components (0-3 day) on liver function in schizophrenia patients. RESULTS: Several PAHs were significantly associated with liver enzymes, while water-soluble ions and metal components had almost no association. Specifically, with per interquartile range (IQR) increased in Fluoranthene, levels of alkaline phosphatase (ALP), alanine transaminase (ALT), aspartate transaminase (AST) and gamma-glutamyl transpeptidase (GGT) increased by 2.06 %, 5.07 %, 4.94 % and 5.56 %, respectively. An IQR increases in Benzo[a]pyrene was significantly associated with 6.62 %, 3.67 % and 7.83 % increase in ALT, AST and GGT. Almost all PAHs, sulfate, nitrate, ammonium, Sb, Al, As, Pb, Mn and Tl were positively associated with albumin (ALB). Phenanthrene was associated with increased levels of direct bilirubin (DBIL) and total bilirubin (TBIL). The combined effects of significant PM2.5 components on ALP, GGT, ALB, globulin (GLOB), ratio of albumin to globulin (A/G), TBIL and total bile acid (TBA) were found by BKMR, respectively. CONCLUSIONS: Findings highlight the short-term combined effects of PM2.5 components, especially PAHs, on liver function in schizophrenia patients, which contribute to the management of PM2.5 sources including combustion activities and traffic emissions as well as improving schizophrenia comorbidities.

The Prediction and Influential Factors of Violence in Male Schizophrenia Patients With Machine Learning Algorithms.

Background: Early to identify male schizophrenia patients with violence is important for the performance of targeted measures and closer monitoring, but it is difficult to use conventional risk factors. This study is aimed to employ machine learning (ML) algorithms combined with routine data to predict violent behavior among male schizophrenia patients. Moreover, the identified best model might be utilized to calculate the probability of an individual committing violence. Method: We enrolled a total of 397 male schizophrenia patients and randomly stratified them into the training set and the testing set, in a 7:3 ratio. We used eight ML algorithms to develop the predictive models. The main variables as input features selected by the least absolute shrinkage and selection operator (LASSO) and logistic regression (LR) were integrated into prediction models for violence among male schizophrenia patients. In the training set, 10 × 10-fold cross-validation was conducted to adjust the parameters. In the testing set, we evaluated and compared the predictive performance of eight ML algorithms in terms of area under the curve (AUC) for the receiver operating characteristic curve. Result: Our results showed the prevalence of violence among male schizophrenia patients was 36.8%. The LASSO and LR identified main risk factors for violent behavior in patients with schizophrenia integrated into the predictive models, including lower education level [0.556 (0.378-0.816)], having cigarette smoking [2.121 (1.191-3.779)], higher positive syndrome [1.016 (1.002-1.031)] and higher social disability screening schedule (SDSS) [1.081 (1.026-1.139)]. The Neural Net (nnet) with an AUC of 0.6673 (0.5599-0.7748) had better prediction ability than that of other algorithms. Conclusion: ML algorithms are useful in early identifying male schizophrenia patients with violence and helping clinicians take preventive measures.