Disrupted brain functional asymmetry at rest in patients with major depressive disorder associated with sleep disturbances.

Sleep disturbances (SD) are common in major depressive disorder (MDD) patients. Brain functional asymmetry is crucial for understanding MDD pathophysiology. Previous studies using the parameter of asymmetry (PAS) approach have found brain functional asymmetry disruption in MDD. However, this has not been explored in MDD patients with SD. This study examined 26 MDD patients with SD, 34 MDD patients without SD, and 34 healthy controls using resting-state functional magnetic resonance imaging scans. SD symptoms were quantified using the 17-item Hamilton Rating Scale for Depression. PAS approach was used to evaluate functional asymmetry. MDD patients with SD displayed increased PAS in the left middle frontal gyrus (MFG)/inferior frontal gyrus (IFG) and decreased PAS in the left parahippocampal gyrus (PHG) compared to MDD patients without SD. Increased PAS in the left MFG/IFG was positively correlated with SD severity, and a negative correlation was found between decreased PAS in the left PHG and SD scores in all MDD patients. Receiver operating characteristic analysis indicated that increased PAS in the left MFG/IFG and decreased PAS in the left PHG may serve as potential neuroimaging markers to differentiate MDD patients with SD from those without SD with Area Under Curve values of 0.8157 and 0.8068, respectively. These results highlighted that increased PAS in the left MFG/IFG and decreased PAS in the left PHG may be considered a prominent feature associated with SD symptoms of MDD patients, potentially serving as imaging markers to discriminate between MDD patients with and without SD.

A linear compensation method for inference accuracy improvement of memristive in-memory computing.

Memristive computing system (MCS), with the feature of in-memory computing capability, for artificial neural networks (ANNs) deployment showing low power and massive parallelism, is a promising alternative for traditional Von-Neumann architecture computing system. However, because of the various non-idealities of both peripheral circuits and memristor array, the performance of the practical MCS tends to be significantly reduced. In this work, a linear compensation method (LCM) is proposed for the performance improvement of MCS under the effect of non-idealities. By considering the effects of various non-ideal states in the MCS as a whole, the output error of the MCS under different conditions is investigated. Then, a mathematic model for the output error is established based on the experimental data. Furthermore, the MCS is researched at the physical circuit level as well, in order to analyze the specific way in which the non-idealities affect the output current. Finally, based on the established mathematical model, the LCM output current is compensated in real time to improve the system performance. The effectiveness of LCM is verified and showing outstanding performance in the residual neural network-34 network architecture, which is easily affected by the non-idealities in hardware. The proposed LCM can be naturally integrated into the operation processes of MCS, paving the way for optimizing the deployment on generic ANN hardware based on the memristor.

The cap-binding complex modulates ABA-responsive transcript splicing during germination in barley (Hordeum vulgare).

To decipher the molecular bases governing seed germination, this study presents the pivotal role of the cap-binding complex (CBC), comprising CBP20 and CBP80, in modulating the inhibitory effects of abscisic acid (ABA) in barley. Using both single and double barley mutants in genes encoding the CBC, we revealed that the double mutant hvcbp20.ab/hvcbp80.b displays ABA insensitivity, in stark contrast to the hypersensitivity observed in single mutants during germination. Our comprehensive transcriptome and metabolome analysis not only identified significant alterations in gene expression and splicing patterns but also underscored the regulatory nexus among CBC, ABA, and brassinosteroid (BR) signaling pathways.

WRKY10 Regulates Seed Size through the miR397a-LAC2 Module in Arabidopsis thaliana.

In angiosperms, seed size is a critical trait that is influenced by the complex interplay between the endosperm and seed coat. The HAIKU (IKU) pathway, involving the transcription factor WRKY10, plays a crucial role in regulating seed size in Arabidopsis thaliana. However, the downstream targets of WRKY10 and their roles in seed size determination remain largely unexplored. Here, we identified LACCASE2 (LAC2), a laccase gene involved in lignin biosynthesis, as a new downstream target of WRKY10. We observed that the expression of LAC2 was upregulated in the mini3 mutant, which is defective in WRKY10. We demonstrated that WRKY10 directly binds to the promoter of miR397a, activating its expression. miR397a, in turn, represses the expression of LAC2. Genetic analyses revealed that a mutation in LAC2 or overexpression of miR397a partially rescued the small seed phenotype of the MINISEED3 (MINI3) mutant mini3. Conversely, the overexpression of LAC2 in the wild type led to a decrease in seed size. These findings suggest that LAC2 functions as a negative regulator of seed size, and its expression is modulated by WRKY10 through miR397a. Our study uncovers a novel WRKY10-miR397a-LAC2 pathway that regulates seed size in Arabidopsis, providing new insights into the complex regulatory network governing seed development in plants.

Zoledronic acid relieves steroid-induced avascular necrosis of femoral head via inhibiting FOXD3 mediated ANXA2 transcriptional activation.

BACKGROUND: Zoledronic acid (ZOL) is a type of bisphosphonate with good therapeutic effects on orthopaedic diseases. However, the pharmacological functions of ZOL on steroid-induced avascular necrosis of femoral head (SANFH) and the underlying mechanism remain unclear, which deserve further research. METHODS: SANFH models both in vivo and in vitro were established by dexamethasone (Dex) stimulation. Osteoclastogenesis was examined by TRAP staining. Immunofluorescence was employed to examine autophagy marker (LC3) level. Cell apoptosis was analyzed by TUNEL staining. The interaction between Foxhead box D3 protein (FOXD3) and Annexin A2 (ANXA2) promoter was analyzed using ChIP and dual luciferase reporter gene assays. RESULTS: Dex aggravated osteoclastogenesis and induced osteoclast differentiation and autophagy in vitro, which was abrogated by ZOL treatment. PI3K inhibitor LY294002 abolished the inhibitory effect of ZOL on Dex-induced osteoclast differentiation and autophagy. FOXD3 overexpression neutralized the downregulation effects of ZOL on Dex-induced osteoclasts by transcriptionally activating ANXA2. ANXA2 knockdown reversed the effect of FOXD3 overexpression on ZOL-mediated biological effects in Dex-treated osteoclasts. In addition, ZOL improved SANFH symptoms in rats. CONCLUSION: ZOL alleviated SANFH through regulating FOXD3 mediated ANXA2 transcriptional activity and then promoting PI3K/AKT/mTOR pathway, revealing that FOXD3 might be a target for ZOL in SANFH treatment.

Transcriptomic decoding of regional cortical vulnerability to major depressive disorder.

Previous studies in small samples have identified inconsistent cortical abnormalities in major depressive disorder (MDD). Despite genetic influences on MDD and the brain, it is unclear how genetic risk for MDD is translated into spatially patterned cortical vulnerability. Here, we initially examined voxel-wise differences in cortical function and structure using the largest multi-modal MRI data from 1660 MDD patients and 1341 controls. Combined with the Allen Human Brain Atlas, we then adopted transcription-neuroimaging spatial correlation and the newly developed ensemble-based gene category enrichment analysis to identify gene categories with expression related to cortical changes in MDD. Results showed that patients had relatively circumscribed impairments in local functional properties and broadly distributed disruptions in global functional connectivity, consistently characterized by hyper-function in associative areas and hypo-function in primary regions. Moreover, the local functional alterations were correlated with genes enriched for biological functions related to MDD in general (e.g., endoplasmic reticulum stress, mitogen-activated protein kinase, histone acetylation, and DNA methylation); and the global functional connectivity changes were associated with not only MDD-general, but also brain-relevant genes (e.g., neuron, synapse, axon, glial cell, and neurotransmitters). Our findings may provide important insights into the transcriptomic signatures of regional cortical vulnerability to MDD.

Alterations in amygdala subregions-Default mode network connectivity after treatment in patients with schizophrenia.

Disrupted connectivity in the default mode network (DMN) during resting-state functional MRI (rs-fMRI) is well-documented in schizophrenia (SCZ). The amygdala, a key component in the neurobiology of SCZ, comprises distinct subregions that may exert varying effects on the disorder. This study aimed to investigate variations in functional connectivity (FC) between distinct amygdala subregions and the DMN in SCZ individuals and explore the effects of treatment on these connections. Fifty-six SCZ patients and 51 healthy controls underwent FC analysis and questionnaire surveys during resting state. The amygdala was selected as the region of interest (ROI) and subdivided into four parts. Changes in FC were examined, and correlations between questionnaire scores and brain activity were explored. Pre-treatment, SCZ patients exhibited reduced FC between the amygdala and DMN compared to HCs. After treatment, significant differences persisted in the right medial amygdala, while other regions did not differ significantly from controls. In addition, PANSS scores positively correlated with FC between the Right Medial Amygdala and the left SMFC (r = .347, p = .009), while RBANS5A scores showed a positive correlation with FC between the Left Lateral Amygdala and the right MTG (rho = -.347, p = .009). The rsFC between the amygdala and the DMN plays a crucial role in the treatment mechanisms of SCZ. This could provide a promising predictive indicator for understanding the neural mechanisms behind treatment and symptomatic improvement.

Harnessing a silicon carbide nanowire photoelectric synaptic device for novel visual adaptation spiking neural networks.

Visual adaptation is essential for optimizing the image quality and sensitivity of artificial vision systems in real-world lighting conditions. However, additional modules, leading to time delays and potentially increasing power consumption, are needed for traditional artificial vision systems to implement visual adaptation. Here, an ITO/PMMA/SiC-NWs/ITO photoelectric synaptic device is developed for compact artificial vision systems with the visual adaption function. The theoretical calculation and experimental results demonstrated that the heating effect, induced by the increment light intensity, leads to the photoelectric synaptic device enabling the visual adaption function. Additionally, a visual adaptation artificial neuron (VAAN) circuit was implemented by incorporating the photoelectric synaptic device into a LIF neuron circuit. The output frequency of this VAAN circuit initially increases and then decreases with gradual light intensification, reflecting the dynamic process of visual adaptation. Furthermore, a visual adaptation spiking neural network (VASNN) was constructed to evaluate the photoelectric synaptic device based visual system for perception tasks. The results indicate that, in the task of traffic sign detection under extreme weather conditions, an accuracy of 97% was achieved (which is approximately 12% higher than that without a visual adaptation function). Our research provides a biologically plausible hardware solution for visual adaptation in neuromorphic computing.

LsRTDv1, a reference transcript dataset for accurate transcript-specific expression analysis in lettuce.

Accurate quantification of gene and transcript-specific expression, with the underlying knowledge of precise transcript isoforms, is crucial to understanding many biological processes. Analysis of RNA sequencing data has benefited from the development of alignment-free algorithms which enhance the precision and speed of expression analysis. However, such algorithms require a reference transcriptome. Here we generate a reference transcript dataset (LsRTDv1) for lettuce (cv. Saladin), combining long- and short-read sequencing with publicly available transcriptome annotations, and filtering to keep only transcripts with high-confidence splice junctions and transcriptional start and end sites. LsRTDv1 identifies novel genes (mostly long non-coding RNAs) and increases the number of transcript isoforms per gene in the lettuce genome from 1.4 to 2.7. We show that LsRTDv1 significantly increases the mapping rate of RNA-seq data from a lettuce time-series experiment (mock- and Botrytis cinerea-inoculated) and enables detection of genes that are differentially alternatively spliced in response to infection as well as transcript-specific expression changes. LsRTDv1 is a valuable resource for investigation of transcriptional and alternative splicing regulation in lettuce.

Fabrication of Non-Wetting Mg(OH)2 Composites with Photoresponsive Capabilities and Their Environmental Restoration Performance.

Water pollution seriously affects the development of society and human life. There are various kinds of pollutants, including soluble pollutants and insoluble floaters on the water surface. Herein, the photocatalyst semiconductor BiOCl and superhydrophobic functional particles Mg(OH)2 were deposited on the surfaces of canvas and polyester felt to construct superhydrophobic canvas and polyester felt. The contact angles of the synthetic superhydrophobic canvas and polyester felt were measured as 152° and 155.3°, respectively. The selective adsorption of hexadecane was achieved using the wetting difference between the surface of water and pollutants floating on the surface. For dissolved pollutants, the surface wettability needed to be changed with the help of ethanol. The degradation efficiencies were all greater than 90%, demonstrating the versatility of the synthetic superhydrophobic canvas and polyester felt.

Chronic intranasal oxytocin alleviates cognitive impairment and reverses oxytocin signaling upregulation in MK801-induced mice.

OBJECTIVE: Cognitive impairment, especially impaired social cognition, is largely responsible for the deterioration of the social life of patients with schizophrenia (SZ). Oxytocin (OT) is a neuropeptide that offers promising therapy for SZ. This study aimed to explore whether OT could affect dizocilpine (MK801)-induced cognitive impairment and to investigate the effect of exogenous OT on the endogenous OT system in the hippocampus. METHODS: The SZ mouse model was established by repeated administration of dizocilpine [MK801, 0.6 mg/kg, intraperitoneal (i.p.)], and then OT (6-60 µg/kg, intranasal) or risperidone (0.3 mg/kg, i.p.) was administered to explore the effect of OT on cognitive impairment. RESULTS: OT at a dose of 6 µg/kg alleviated MK801-induced hyperactivity, sociability impairment, and spatial memory impairment. OT at a dose of 20 or 60 µg/kg attenuated the hyperactivity and social novelty impairment. In MK801-injected mice, the compensatory upregulation of OT mRNA in the hippocampus was reversed by three OT doses, whereas 60 µg/kg OT reversed the compensatory upregulation of CD38 protein expression. CONCLUSION: OT alleviated cognitive impairment in the SZ mouse model to varying degrees, reversing the compensatory upregulation of OT signaling in the hippocampus.

Cerebellar functional connectivity and its associated genes: A longitudinal study in drug-naive patients with obsessive-compulsive disorder.

The role of cerebellar-cerebral functional connectivity (CC-FC) in obsessive-compulsive disorder (OCD), its trajectory post-pharmacotherapy, and its potential as a prognostic biomarker and genetic mechanism remain uncertain. To address these gaps, this study included 37 drug-naive OCD patients and 37 healthy controls (HCs). Participants underwent baseline functional magnetic resonance imaging (fMRI), followed by four weeks of paroxetine treatment for patients with OCD, and another fMRI scan post-treatment. We examined seed-based CC-FC differences between the patients and HCs, and pre- and post-treatment patients. Support vector regression (SVR) based on CC-FC was performed to predict treatment response. Correlation analysis explored associations between CC-FC and clinical features, as well as gene profiles. Compared to HCs, drug-naive OCD patients exhibited reduced CC-FC in executive, affective-limbic, and sensorimotor networks, with specific genetic profiles associated with altered CC-FC. Gene enrichment analyses highlighted the involvement of these genes in various biological processes, molecular functions, and pathways. Post-treatment, the patients showed partial clinical improvement and partial restoration of the previously decreased CC-FC. Abnormal CC-FC at baseline correlated negatively with compulsions severity and social functional impairment, while changes in CC-FC correlated with cognitive function changes post-treatment. CC-FC emerged as a potential predictor of symptom severity in patients following paroxetine treatment. This longitudinal resting-state fMRI study underscores the crucial role of CC-FC in the neuropsychological mechanisms of OCD and its pharmacological treatment. Transcriptome-neuroimaging spatial correlation analyses provide insight into the neurobiological mechanisms underlying OCD pathology. Furthermore, SVR analyses hold promise for advancing precision medicine approaches in treating patients with OCD.

Twenty-five years of research on resting-state fMRI of major depressive disorder: A bibliometric analysis of hotspots, nodes, bursts, and trends.

Major depressive disorder (MDD) is a debilitating mental health condition that poses significant risks and burdens. Resting-state functional magnetic resonance imaging (fMRI) has emerged as a promising tool in investigating the neural mechanisms underlying MDD. However, a comprehensive bibliometric analysis of resting-state fMRI in MDD is currently lacking. Here, we aimed to thoroughly explore the trends and frontiers of resting-state fMRI in MDD research. The relevant publications were retrieved from the Web of Science database for the period between 1998 and 2022, and the CiteSpace software was employed to identify the influence of authors, institutions, countries/regions, and the latest research trends. A total of 1501 publications met the search criteria, revealing a gradual increase in the number of annual publications over the years. China contributed the largest publication output, accounting for the highest percentage among all countries. Particularly, the University of Electronic Science and Technology of China, Capital Medical University, and Harvard Medical School were identified as key institutions that have made substantial contributions to this growth. Neuroimage, Biological Psychiatry, Journal of Affective Disorders, and Proceedings of the National Academy of Sciences of the United States of America are among the influential journals in the field of resting-state fMRI research in MDD. Burst keywords analysis suggest the emerging research frontiers in this field are characterized by prominent keywords such as dynamic functional connectivity, cognitive control network, transcranial brain stimulation, and childhood trauma. Overall, our study provides a systematic overview into the historical development, current status, and future trends of resting-state fMRI in MDD, thus offering a useful guide for researchers to plan their future research.

Potential correlations between abnormal homogeneity of default mode network and personality or lipid level in major depressive disorder.

BACKGROUND: Default mode network (DMN) is one of the most recognized resting-state networks in major depressive disorder (MDD). However, the homogeneity of this network in MDD remains incompletely explored. Therefore, this study aims to determine whether there is abnormal network homogeneity (NH) of the DMN in MDD patients. At the same time, correlations between clinical variables and brain functional connectivity are examined. METHODS: We enrolled 42 patients diagnosed with MDD and 42 HCs. A variety of clinical variables were collected, and data analysis was conducted using the NH and independent component analysis methods. RESULTS: The study shows that MDD patients have higher NH values in the left superior medial prefrontal cortex (MPFC) and left posterior cingulate cortex (PCC) compared to HCs. Additionally, there is a positive correlation between NH values of the left superior MPFC and Eysenck Personality Questionnaire values. NH values of the left PCC are positively linked to CHOL levels, LDL levels, and utilization scores. However, these correlations lose significance after the Bonferroni correction. CONCLUSION: Our findings indicate the presence of abnormal DMN homogeneity in MDD, underscoring the significance of DMN in the pathophysiology of MDD. Simultaneously, the study provides preliminary evidence for the correlation between clinical variables and brain functional connectivity.

Neural substrates of predicting anhedonia symptoms in major depressive disorder via connectome-based modeling.

MAIN PROBLEM: Anhedonia is a critical diagnostic symptom of major depressive disorder (MDD), being associated with poor prognosis. Understanding the neural mechanisms underlying anhedonia is of great significance for individuals with MDD, and it encourages the search for objective indicators that can reliably identify anhedonia. METHODS: A predictive model used connectome-based predictive modeling (CPM) for anhedonia symptoms was developed by utilizing pre-treatment functional connectivity (FC) data from 59 patients with MDD. Node-based FC analysis was employed to compare differences in FC patterns between melancholic and non-melancholic MDD patients. The support vector machines (SVM) method was then applied for classifying these two subtypes of MDD patients. RESULTS: CPM could successfully predict anhedonia symptoms in MDD patients (positive network: r = 0.4719, p < 0.0020, mean squared error = 23.5125, 5000 iterations). Compared to non-melancholic MDD patients, melancholic MDD patients showed decreased FC between the left cingulate gyrus and the right parahippocampus gyrus (p_bonferroni = 0.0303). This distinct FC pattern effectively discriminated between melancholic and non-melancholic MDD patients, achieving a sensitivity of 93.54%, specificity of 67.86%, and an overall accuracy of 81.36% using the SVM method. CONCLUSIONS: This study successfully established a network model for predicting anhedonia symptoms in MDD based on FC, as well as a classification model to differentiate between melancholic and non-melancholic MDD patients. These findings provide guidance for clinical treatment.

A Quantitative Trait Locus with a Major Effect on Root-Lesion Nematode Resistance in Barley.

Although the root-lesion nematode Pratylenchus thornei is known to affect barley (Hordeum vulgare L.), there have been no reports on the genetic control of P. thornei resistance in barley. In this research, P. thornei resistance was assessed for a panel of 46 barley mapping parents and for two mapping populations (Arapiles/Franklin and Denar/Baudin). With both populations, a highly significant quantitative trait locus (QTL) was mapped at the same position on the long arm of chromosome 7H. Single-nucleotide polymorphisms (SNPs) in this region were anchored to an RGT Planet pan-genome assembly and assayed on the mapping parents and other barley varieties. The results indicate that Arapiles, Denar, RGT Planet and several other varieties likely have the same resistance gene on chromosome 7H. Marker assays reported here could be used to select for P. thornei resistance in barley breeding. Analysis of existing barley pan-genomic and pan-transcriptomic data provided a list of candidate genes along with information on the expression and differential expression of some of those genes in barley root tissue. Further research is required to identify a specific barley gene that affects root-lesion nematode resistance.

Association Between Geriatric Nutrition Risk Index and 90-Day Mortality in Older Adults with Chronic Obstructive Pulmonary Disease: a Retrospective Cohort Study.

Background: Malnutrition adversely affects prognosis in various medical conditions, but its implications in older adults with Chronic Obstructive Pulmonary Disease (COPD) in the ICU are underexplored. The geriatric nutritional risk index (GNRI) is a novel tool for assessing malnutrition risk. This study investigates the association between GNRI and 90-day mortality in this population. Methods: We selected older adults with COPD admitted to the ICU from Medical Information Mart for Intensive Care (MIMIC)-IV 2.2 database. A total of 666 patients were categorized into four groups based on their GNRI score: normal nutrition (>98), mild malnutrition (92-98), moderate malnutrition (82-91), and severe malnutrition (≤81) groups. We employed a restricted cubic spline (RCS) analysis to assess the presence of a curved relationship between them and to investigate any potential threshold saturation effect. Results: In multivariate Cox regression analyses, compared with individuals had normal nutrition (GNRI in Q4 >98), the adjusted HR values for GNRI in Q3 (92-98), Q2 (82-91), and Q1 (≤81) were 1.81 (95% CI: 1.27-2.58, p=0.001), 1.23 (95% CI: 0.84-1.79, p=0.296), 2.27 (95% CI: 1.57-3.29, p<0.001), respectively. The relationship between GNRI and 90-day mortality demonstrates an L-shaped curve (p=0.016), with an approximate inflection point at 101.5. Conclusion: These findings imply that GNRI is a useful prognostic tool in older adults with COPD in the ICU. An L-shaped relationship was observed between GNRI and 90-day mortality in these patients.

Generation of allogeneic CAR-NKT cells from hematopoietic stem and progenitor cells using a clinically guided culture method.

Cancer immunotherapy with autologous chimeric antigen receptor (CAR) T cells faces challenges in manufacturing and patient selection that could be avoided by using 'off-the-shelf' products, such as allogeneic CAR natural killer T (AlloCAR-NKT) cells. Previously, we reported a system for differentiating human hematopoietic stem and progenitor cells into AlloCAR-NKT cells, but the use of three-dimensional culture and xenogeneic feeders precluded its clinical application. Here we describe a clinically guided method to differentiate and expand IL-15-enhanced AlloCAR-NKT cells with high yield and purity. We generated AlloCAR-NKT cells targeting seven cancers and, in a multiple myeloma model, demonstrated their antitumor efficacy, expansion and persistence. The cells also selectively depleted immunosuppressive cells in the tumor microenviroment and antagonized tumor immune evasion via triple targeting of CAR, TCR and NK receptors. They exhibited a stable hypoimmunogenic phenotype associated with epigenetic and signaling regulation and did not induce detectable graft versus host disease or cytokine release syndrome. These properties of AlloCAR-NKT cells support their potential for clinical translation.

Fractional amplitude of low-frequency fluctuations in sensory-motor networks and limbic system as a potential predictor of treatment response in patients with schizophrenia.

BACKGROUND: Previous investigations have revealed substantial differences in neuroimaging characteristics between healthy controls (HCs) and individuals diagnosed with schizophrenia (SCZ). However, we are not entirely sure how brain activity links to symptoms in schizophrenia, and there is a need for reliable brain imaging markers for treatment prediction. METHODS: In this longitudinal study, we examined 56 individuals diagnosed with 56 SCZ and 51 HCs. The SCZ patients underwent a three-month course of antipsychotic treatment. We employed resting-state functional magnetic resonance imaging (fMRI) along with fractional Amplitude of Low Frequency Fluctuations (fALFF) and support vector regression (SVR) methods for data acquisition and subsequent analysis. RESULTS: In this study, we initially noted lower fALFF values in the right postcentral/precentral gyrus and left postcentral gyrus, coupled with higher fALFF values in the left hippocampus and right putamen in SCZ patients compared to the HCs at baseline. However, when comparing fALFF values in brain regions with abnormal baseline fALFF values for SCZ patients who completed the follow-up, no significant differences in fALFF values were observed after 3 months of treatment compared to baseline data. The fALFF values in the right postcentral/precentral gyrus and left postcentral gyrus, and the left postcentral gyrus were useful in predicting treatment effects. CONCLUSION: Our findings suggest that reduced fALFF values in the sensory-motor networks and increased fALFF values in the limbic system may constitute distinctive neurobiological features in SCZ patients. These findings may serve as potential neuroimaging markers for the prognosis of SCZ patients.

Uncovering the crystallography and formation mechanism of nanoscale clusters in Sb-rich SPPs of a p-type (Bi, Sb)2Te3 alloy.

Considering that the crystallographic characteristics of the Sb-rich secondary phase particles (SPPs) greatly affect the thermoelectric properties of Bi2Te3 based materials, it is of great significance to explore the mechanism behind the Sb-rich SPPs in the p-type (Bi, Sb)2Te3 material. Here a conventional TEM technique was used to characterize the composition, size and distribution of Sb-rich SPPs in a spark plasma sintered p-type (Bi, Sb)2Te3 alloy. The results indicated that two different morphologies of Sb-rich SPPs including elongated and circular Sb-rich SPPs were frequently observed. Combined with high-resolution transmission electron microscopy, this work provides atomic-scale evidence for the formation mechanism behind the Sb-rich SPPs in the (Bi, Sb)2Te3 material.