Mindfulness-based intervention for hypertension patients with depression and/or anxiety in the community: a randomized controlled trial.

OBJECTIVE: To evaluate mindfulness-based intervention for hypertension with depression and/or anxiety. METHODS: 10-week mindfulness-based intervention, including health education for hypertension, exclusively for the control group, was administered to the intervention group to assist sixty hypertension patients with depression/anxiety. Among them, the intervention group comprised 8 men and 22 women, with a mean age of 60.02 years and a mean duration of hypertension of 6.29 years. The control group consisted of 14 men and 16 women with a mean age of 57.68 years and a mean duration of hypertension of 6.32 years. The severity of depressive and/or anxiety symptoms was assessed using the 9-item Patient Health Questionnaire (PHQ-9) and the 7-item Generalized Anxiety Disorder scale (GAD-7), along with blood pressure (BP) measurements taken twice daily. The study utilized a self-made self-efficacy scale and awareness of physical and mental health to evaluate mental health and state. RESULTS: The depression PHQ-9 or GAD-7 scores reduced by 21.1% or 17.8% in the mindfulness-based intervention group, compared to the control (Z = -2.040, P = 0.041) post 10-week period, suggesting significant reduction in anxiety/stress. These results were consistent with a reduction in systolic BP of 12.24 mm Hg (t = 6.041, P = 0.000). The self-efficacy score of the mindfulness intervention group significantly improved compared to the control (t = 7.818, P < 0.001), while the awareness of physical and mental health in the mindfulness intervention group significantly improved compared to the control (χ2 = 5.781, P = 0.016). CONCLUSION: Mindfulness-based, short-term focused interventions provide modest relief for depression and/or anxiety and are effective in lowering blood pressure and improving self-efficacy scores. TRIAL REGISTRATION: Chinese Clinical Trial Registry, ChiCTR1900028258. Registered 16 December 2019, https://www.chictr.org.cn/showproj.html?proj=43627 .

Altered patterns of dynamic functional connectivity of brain networks in deficit and non-deficit schizophrenia.

This study aims to investigate the altered patterns of dynamic functional network connectivity (dFNC) between deficit schizophrenia (DS) and non-deficit schizophrenia (NDS), and further explore the associations with cognitive impairments. 70 DS, 91 NDS, and 120 matched healthy controls (HCs) were enrolled. The independent component analysis was used to segment the whole brain. The fMRI brain atlas was used to identify functional networks, and the dynamic functional connectivity (FC) of each network was detected. Correlation analysis was used to explore the associations between altered dFNC and cognitive functions. Four dynamic states were identified. Compared to NDS, DS showed increased FC between sensorimotor network and default mode network in state 1 and decreased FC within auditory network in state 4. Additionally, DS had a longer mean dwell time of state 2 and a shorter one in state 3 compared to NDS. Correlation analysis showed that fraction time and mean dwell time of states were correlated with cognitive impairments in DS. This study demonstrates the distinctive altered patterns of dFNC between DS and NDS patients. The associations with impaired cognition provide specific neuroimaging evidence for the pathogenesis of DS.

Efficiency of endoscopic artificial intelligence in the diagnosis of early esophageal cancer.

BACKGROUND: The accuracy of artificial intelligence (AI) and experts in diagnosing early esophageal cancer (EC) and its infiltration depth was summarized and analyzed, thus identifying the advantages of AI over traditional manual diagnosis, with a view to more accurately assisting doctors in evaluating the patients' conditions and improving their cure and survival rates. METHODS: The PubMed, EMBASE, Cochrane, Google, and CNKI databases were searched for relevant literature related to AI diagnosis of early EC and its invasion depth published before August 2023. Summary analysis of pooled sensitivity, specificity, summary receiver operating characteristics (SROC) and area under the curve (AUC) of AI in diagnosing early EC were performed, and Review Manager and Stata were adopted for data analysis. RESULTS: A total of 19 studies were enrolled with a low to moderate total risk of bias. The pooled sensitivity of AI for diagnosing early EC was markedly higher than that of novices and comparable to that of endoscopists. Moreover, AI predicted early EC with markedly higher AUCs than novices and experts (0.93 vs. 0.74 vs. 0.89). In addition, pooled sensitivity and specificity in the diagnosis of invasion depth in early EC were higher than that of experts, with AUCs of 0.97 and 0.92, respectively. CONCLUSION: AI-assistance can diagnose early EC and its infiltration depth more accurately, which can help in its early intervention and the customization of personalized treatment plans. Therefore, AI systems have great potential in the early diagnosis of EC.

Two new sesquiterpenoid glycoside compounds from the calyces of Physalis alkekengi L. var. franchetii (Mast.) Makino.

Two new sesquiterpenoid glycosides, 8α (H)-eudesmane-1,3,11 (13)-triene-2-one -12-O-ß-D-glucopyranoside (1) and dmetelisproside B (2), together with ten known compounds (3-12) were isolated from calyces of Physalis alkekengi L. var. franchetii (Mast.) Makino (PAF). Their structures were unambiguously elucidated through HR-ESI-MS, UV, IR, and NMR spectral data. Compounds 1, 10, and 12 exhibited DPPH scavenging ability with IC50 values of 33.69 ± 6.65, 6.29 ± 0.06, and 25.66 ± 3.06 µM, respectively. Additionally, 10 and 12 demonstrated weak α-glucosidase inhibition activity with IC50 values of 250.9 ± 6.60 and 347.6 ± 2.48 µM, respectively.

Convergent and divergent genes expression profiles associated with brain-wide functional connectome dysfunction in deficit and non-deficit schizophrenia.

Deficit schizophrenia (DS) is a subtype of schizophrenia characterized by the primary and persistent negative symptoms. Previous studies have identified differences in brain functions between DS and non-deficit schizophrenia (NDS) patients. However, the genetic regulation features underlying these abnormal changes are still unknown. This study aimed to detect the altered patterns of functional connectivity (FC) in DS and NDS and investigate the gene expression profiles underlying these abnormal FC. The study recruited 82 DS patients, 96 NDS patients, and 124 healthy controls (CN). Voxel-based unbiased brain-wide association study was performed to reveal altered patterns of FC in DS and NDS patients. Machine learning techniques were used to access the utility of altered FC for diseases diagnosis. Weighted gene co-expression network analysis (WGCNA) was employed to explore the associations between altered FC and gene expression of 6 donated brains. Enrichment analysis was conducted to identify the genetic profiles, and the spatio-temporal expression patterns of the key genes were further explored. Comparing to CN, 23 and 20 brain regions with altered FC were identified in DS and NDS patients. The altered FC among these regions showed significant correlations with the SDS scores and exhibited high efficiency in disease classification. WGCNA revealed associations between DS/NDS-related gene expression and altered FC. Additionally, 22 overlapped genes, including 12 positive regulation genes and 10 negative regulation genes, were found between NDS and DS. Enrichment analyses demonstrated relationships between identified genes and significant pathways related to cellular response, neuro regulation, receptor binding, and channel activity. Spatial and temporal gene expression profiles of SCN1B showed the lowest expression at the initiation of embryonic development, while DPYSL3 exhibited rapid increased in the fetal. The present study revealed different altered patterns of FC in DS and NDS patients and highlighted the potential value of FC in disease classification. The associations between gene expression and neuroimaging provided insights into specific and common genetic regulation underlying these brain functional changes in DS and NDS, suggesting a potential genetic-imaging pathogenesis of schizophrenia.

Polygenic effects on brain functional endophenotype for deficit and non-deficit schizophrenia.

Deficit schizophrenia (DS) is a subtype of schizophrenia (SCZ). The polygenic effects on the neuroimaging alterations in DS still remain unknown. This study aims to calculate the polygenic risk scores for schizophrenia (PRS-SCZ) in DS, and further explores the potential associations with functional features of brain. PRS-SCZ was calculated according to the Whole Exome sequencing and Genome-wide association studies (GWAS). Resting-state fMRI, as well as biochemical features and neurocognitive data were obtained from 33 DS, 47 NDS and 41 HCs, and association studies of genetic risk with neuroimaging were performed in this sample. The analyses of amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo) and functional connectivity (FC) were performed to detect the functional alterations between DS and NDS. In addition, correlation analysis was used to investigate the relationships between functional features (ALFF, ReHo, FC) and PRS-SCZ. The PRS-SCZ of DS was significantly lower than that in NDS and HC. Compared to NDS, there was a significant increase in the ALFF of left inferior temporal gyrus (ITG.L) and left inferior frontal gyrus (IFG.L) and a significant decrease in the ALFF of right precuneus (PCUN.R) and ReHo of right middle frontal gyrus (MFG.R) in DS. FCs were widely changed between DS and NDS, mainly concentrated in default mode network, including ITG, PCUN and angular gyrus (ANG). Correlation analysis revealed that the ALFF of left ITG, the ReHo of right middle frontal gyrus, the FC value between insula and ANG, left ITG and right corpus callosum, left ITG and right PCUN, as well as the scores of Trail Making Test-B, were associated with PRS-SCZ in DS. The present study demonstrated the differential polygenic effects on functional changes of brain in DS and NDS, providing a potential neuroimaging-genetic perspective for the pathogenesis of schizophrenia.

High Stretch Associated with Mechanical Ventilation Promotes Piezo1-Mediated Migration of Airway Smooth Muscle Cells.

Ventilator-induced lung injury (VILI) during mechanical ventilation (MV) has been attributed to airway remodeling involving increased airway smooth muscle cells (ASMCs), but the underlying mechanism is not fully understood. Thus, we aimed to investigate whether MV-associated high stretch (>10% strain) could modulate mechanosensitive Piezo1 expression and thereby alter cell migration of ASMCs as a potential pathway to increased ASMCs in VILI. C57BL/6 mice and ASMCs were subjected to MV at high tidal volume (VT, 18 mL/kg, 3 h) and high stretch (13% strain, 0.5 Hz, 72 h), respectively. Subsequently, the mice or cells were evaluated for Piezo1 and integrin mRNA expression by immunohistochemical staining and quantitative PCR (qPCR), and cell migration and adhesion by transwell and cell adhesion assays. Cells were either treated or not with Piezo1 siRNA, Piezo1-eGFP, Piezo1 knockin, Y27632, or blebbistatin to regulate Piezo1 mRNA expression or inhibit Rho-associated kinase (ROCK) signaling prior to migration or adhesion assessment. We found that expression of Piezo1 in in situ lung tissue, mRNA expression of Piezo1 and integrin αVß1 and cell adhesion of ASMCs isolated from mice with MV were all reduced but the cell migration of primary ASMCs (pASMCs) isolated from mice with MV was greatly enhanced. Similarly, cell line mouse ASMCs (mASMCs) cultured in vitro with high stretch showed that mRNA expression of Piezo1 and integrin αVß1 and cell adhesion were all reduced but cell migration was greatly enhanced. Interestingly, such effects of MV or high stretch on ASMCs could be either induced or abolished/reversed by down/up-regulation of Piezo1 mRNA expression and inhibition of ROCK signaling. High stretch associated with MV appears to be a mechanical modulator of Piezo1 mRNA expression and can, thus, promote cell migration of ASMCs during therapeutic MV. This may be a novel mechanism of detrimental airway remodeling associated with MV, and, therefore, a potential intervention target to treat VILI.

Systemic inflammatory biomarkers in Schizophrenia are changed by ECT administration and related to the treatment efficacy.

Immune inflammation has long been implicated in the pathogenesis of schizophrenia. Despite as a rapid and effective physical therapy, the role of immune inflammation in electroconvulsive therapy (ECT) for schizophrenia remains elusive. The neutrophils to lymphocytes (NLR), platelets to monocytes (PLR) and monocytes to lymphocytes (MLR) are inexpensive and accessible biomarkers of systemic inflammation. In this study, 70 schizophrenia patients and 70 age- and sex-matched healthy controls were recruited. The systemic inflammatory biomarkers were measured before and after ECT. Our results indicated schizophrenia had significantly higher peripheral NLR, PLR and MLR compared to health controls at baseline, while lymphocytes did not differ. After 6 ECT, the psychiatric symptoms were significantly improved, as demonstrated by the Positive and Negative Syndrome Scale (PANSS). However, there was a decline in cognitive function scores, as indicated by the Mini-Mental State Examination (MMSE). Notably, the neutrophils and NLR were significantly reduced following ECT. Although lymphocytes remained unchanged following ECT, responders had significantly higher lymphocytes compared to non-responders. Moreover, the linear regression analyses revealed that higher lymphocytes served as a predictor of larger improvement in positive symptom following ECT. Overall, our findings further highlighted the presence of systemic inflammation in schizophrenia patients, and that ECT may exert a therapeutic effect in part by attenuating systemic inflammation. Further research may therefore lead to new treatment strategies for schizophrenia targeting the immune system.

The role of immune inflammation in electroconvulsive therapy for schizophrenia: Treatment mechanism, and relationship with clinical efficacy: Immune-inflammation in ECT for schizophrenia.

Schizophrenia is a devastating psychiatric disorder that has detrimental effects on a significant portion of the global population. Electroconvulsive therapy (ECT), as a safe and effective physical therapy for schizophrenia, has demonstrated the ability to rapidly improve both positive and negative symptoms. Despite being used to treat schizophrenia for over 80 years, the therapeutic mechanisms of ECT are still in the early stages of exploration. Evidence has suggested that immune inflammation contributes to the pathogenesis of schizophrenia by interacting with neurotransmitters, neurodevelopment, and neurodegeneration. Given the importance of ECT as a fast-acting physical therapy for schizophrenia, gaining a deeper understanding of the role of immune inflammation may lead to developing innovative therapeutic approaches. This review summarized existing research that examined changes in peripheral inflammation following ECT in schizophrenia patients, and the effects of electroconvulsive stimulation (ECS) on neuroinflammation in animal studies.

Chinese expert consensus on imaging diagnosis of drug-resistant pulmonary tuberculosis.

Tuberculosis (TB) remains one of the major infectious diseases in the world with a high incidence rate. Drug-resistant tuberculosis (DR-TB) is a key and difficult challenge in the prevention and treatment of TB. Early, rapid, and accurate diagnosis of DR-TB is essential for selecting appropriate and personalized treatment and is an important means of reducing disease transmission and mortality. In recent years, imaging diagnosis of DR-TB has developed rapidly, but there is a lack of consistent understanding. To this end, the Infectious Disease Imaging Group, Infectious Disease Branch, Chinese Research Hospital Association; Infectious Diseases Group of Chinese Medical Association of Radiology; Digital Health Committee of China Association for the Promotion of Science and Technology Industrialization, and other organizations, formed a group of TB experts across China. The conglomerate then considered the Chinese and international diagnosis and treatment status of DR-TB, China's clinical practice, and evidence-based medicine on the methodological requirements of guidelines and standards. After repeated discussion, the expert consensus of imaging diagnosis of DR-PB was proposed. This consensus includes clinical diagnosis and classification of DR-TB, selection of etiology and imaging examination [mainly X-ray and computed tomography (CT)], imaging manifestations, diagnosis, and differential diagnosis. This expert consensus is expected to improve the understanding of the imaging changes of DR-TB, as a starting point for timely detection of suspected DR-TB patients, and can effectively improve the efficiency of clinical diagnosis and achieve the purpose of early diagnosis and treatment of DR-TB.

Chemical components and against alzheimer's disease effects of the calyxes of Physalis alkekengi L. var. franchetii (Mast.) Makino.

Physalis alkekengi L. var. franchetii (Mast.) Makino (PA), a traditional Chinese medicine, is utilised for treating dermatitis, sore throat, dysuria, and cough. This research aimed to identify the main constituents in the four extracted portions from the calyces of PA (PAC) utilising ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). The Alzheimer's disease (AD) mice model was induced by D-galactose (D-gal) combined with aluminium chloride (AlCl3). Subsequent investigation into the underlying mechanisms involved behavioural and histopathological observations. The results demonstrated that four extracted portions of PAC (PACE) significantly enhanced memory and learning abilities in the Morris water maze. The concentrations of Aß, tau and p-tau in brain tissue exhibited a significant decrease relative to the model group. Moreover, the four PACE treatment groups increased the glutathione (GSH) and superoxide dismutase (SOD) levels, while concurrently reducing malondialdehyde (MDA), interleukin-1ß (IL-1ß) and interleukin-6 (IL-6), tumour necrosis factor-α (TNF-α) levels. In summary, the current study demonstrates that the four PACE formulations exhibit beneficial anti-AD properties, with the most pronounced efficacy observed in the EA group. Additionally, PAC shows potential in mitigating neuroinflammation and oxidative damage by inhibiting the TLR4/NF-κB signalling pathway. This research lays a theoretical groundwork for the future clinical development and utilisation of PAC in treating AD.

Biomarkers of bipolar disorder based on metabolomics: A systematic review.

Bipolar disorder (BD) is a severe affective disorder characterized by recurrent episodes of depression or mania/hypomania, which significantly impair cognitive function, life skills, and social abilities of patients. There is little understanding of the neurobiological mechanisms of BD. The diagnosis of BD is primarily based on clinical assessment and psychiatric examination, highlighting the urgent need for objective markers to facilitate the diagnosis of BD. Metabolomics can be used as a diagnostic tool for disease identification and evaluation. This study summarized the altered metabolites in BD and analyzed aberrant metabolic pathways, which might contribute to the diagnosis of BD. Search of PubMed and Web of science for human BD studies related to metabolism to identify articles published up to November 19, 2022 yielded 987 articles. After screening and applying the inclusion and exclusion criteria, 16 untargeted and 11 targeted metabolomics studies were included. Pathway analysis of the potential differential biometabolic markers was performed using the Kyoto encyclopedia of genes and genomes (KEGG). There were 72 upregulated and 134 downregulated biomarkers in the untargeted metabolomics studies using blood samples. Untargeted metabolomics studies utilizing urine specimens revealed the presence of 78 upregulated and 54 downregulated metabolites. The targeted metabolomics studies revealed abnormalities in the metabolism of glutamate and tryptophan. Enrichment analysis revealed that the differential metabolic pathways were mainly involved in the metabolism of glucose, amino acid and fatty acid. These findings suggested that certain metabolic biomarkers or metabolic biomarker panels might serve as a reference for the diagnosis of BD.

Preparation of luteolin loaded nanostructured lipid carrier based gel and effect on psoriasis of mice.

This study investigated a nanostructured lipid carrier (NLC)-gel system containing luteolin (LUT), a potential drug delivery system for the treatment of psoriasis. LUT-NLC was prepared by solvent emulsification ultrasonication method. The particle size was 199.9 ± 2.6 nm, with the encapsulation efficiency of 99.81% and drug loading of 4.06%. X-ray diffractometry (XRD), Fourier-transform infrared spectroscopy (FTIR) and differential scanning calorimetry (DSC) were used to characterize the LUT-NLC. The NLC was dispersed in Carbomer 940 to form the NLC based gel. The rheological characteristics of LUT-NLC-gel showed an excellent shear-thinning behavior (non-Newtonian properties) and coincided with the Herschel-Bulkley model. LUT-NLC-gel (78.89 µg/cm2) exhibited better permeation properties and released over 36 hours than LUT gel (32.17 µg/cm2). The dye-labeled LUT-NLC presented intense fluorescence in the epidermis and dermis by the visualization of fluorescence and confocal microscopy, and it could accumulate in the hair follicles. The effect of LUT-NLC-gel on imiquimod-induced psoriasis mice was evaluated by psoriasis area severity index scoring, spleen index assay, histopathology, and inflammatory cytokines. These results confirmed that LUT-NLC-gel with high dose (80 mg/kg/day) remarkably reduced the level of inflammatory and proliferation factors such as TNF-α, IL-6, IL-17, and IL-23 in both skin lesions and blood. LUT-NLC-gel improved the macroscopic features. Therefore, the LUT-NLC-gel had great potential as an effective delivery system for skin diseases.

Stabilization effects of saccharides in protein formulations: A review of sucrose, trehalose, cyclodextrins and dextrans.

Saccharides are a popular group of stabilizers in liquid, frozen and freeze dried protein formulations. The current work reviewed the stabilization mechanisms of three groups of saccharides: (i) Disaccharides, specifically sucrose and trehalose; (ii) cyclodextrins (CDs), a class of cyclic oligosaccharides; and (iii) dextrans, a class of polysaccharides. Compared to sucrose, trehalose exhibits a more pronounced preferential exclusion effect in liquid protein formulations, due to its stronger interaction with water molecules. However, trehalose obtains higher phase separation and crystallization propensity in frozen solutions, resulting in the loss of its stabilization function. In lyophilized formulations, sucrose has a higher crystallization propensity. Besides, its glass matrix is less homogeneous than that of trehalose, thus undermining its lyoprotectant function. Nevertheless, the hygroscopic nature of trehalose may result in high water absorption upon storage. Among all the CDs, the ß form is believed to have stronger interactions with proteins than the α- and γ-CDs. However, the stabilization effect, brought about by CD-protein interactions, is case-by-case - in some examples, such interactions can promote protein destabilization. The stabilization effect of hydroxypropyl-ß-cyclodextrin (HPßCD) has been extensively studied. Due to its amphiphilic nature, it can act as a surface-active agent in preventing interfacial stresses. Besides, it is a dual functional excipient in freeze dried formulations, acting as an amorphous bulking agent and lyoprotectant. Finally, dextrans, when combined with sucrose or trehalose, can be used to produce stable freeze dried protein formulations. A strong stabilization effect can be realized by low molecular weight dextrans. However, the terminal glucose in dextrans yields protein glycation, which warrants extra caution during formulation development.

Altered brain functional networks in schizophrenia with persistent negative symptoms: an activation likelihood estimation meta-analysis.

Objective: To investigate brain structural and functional characteristics of three brain functional networks including default mode network (DMN), central executive network (CEN), and salience network (SN) in persistent negative symptoms (PNS) patients. Methods: We performed an activation likelihood estimation (ALE) meta-analysis of functional connectivity (FC) studies and voxel-based morphometry (VBM) studies to detect specific structural and functional alterations of brain networks between PNS patients and healthy controls. Results: Seventeen VBM studies and twenty FC studies were included. In the DMN, PNS patients showed decreased gray matter in the bilateral medial frontal gyrus and left anterior cingulate gyrus and a significant reduction of FC in the right precuneus. Also, PNS patients had a decrease of gray matter in the left inferior parietal lobules and medial frontal gyrus, and a significant reduction of FC in the bilateral superior frontal gyrus in the CEN. In comparison with healthy controls, PNS patients exhibited reduced gray matter in the bilateral insula, anterior cingulate gyrus, left precentral gyrus and right claustrum and lower FC in these brain areas in the SN, including the left insula, claustrum, inferior frontal gyrus and extra-nuclear. Conclusion: This meta-analysis reveals brain structural and functional imaging alterations in the three networks and the interaction among these networks in PNS patients, which provides neuroscientific evidence for more personalized treatment.Systematic Review RegistrationThe PROSPERO (https://www.crd.york.ac.uk/PROSPERO/, registration number: CRD42022335962).

Antenna Placement Optimization for Distributed MIMO Radar Based on a Reinforcement Learning Algorithm.

This paper studies an optimization problem of antenna placement for multiple heading angles of the target in a distributed multiple-input multiple-output (MIMO) radar system. An improved method to calculate the system's coverage area in light of the changing target heading is presented. The antenna placement optimization problem is mathematically modelled as a sequential decision problem for compatibility with reinforcement learning solutions. A reinforcement learning agent is established, which uses the long short-term memory (LSTM)-based proximal policy optimization (PPO) method as the core algorithm to solve the antenna placement problem. Finally, the experimental findings demonstrate that the method can enhance the coverage area of antenna placement and thus has reference value for providing new ideas for the antenna placement optimization of distributed MIMO radar.

The role of the gut microbiome in weight-gain in schizophrenia patients treated with atypical antipsychotics: Evidence based on altered composition and function in a cross-sectional study.

OBJECTIVES: We aimed to explore the interconnection between the weight-gain in schizophrenia patients with atypical antipsychotic treatment and gut microbiome. METHODS: This study employed a cross-sectional design, encompassing a total of 88 schizophrenia patients with long-term atypical antipsychotic treatment. The 16S rRNA gene sequencing was used to identify gut microbiome contents. RESULTS: No significant differences in alpha diversity between normal-weight and overweight schizophrenia treated with atypical antipsychotics. The beta diversity analysis showed that overweight patients clustered tightly while normal-weight patients clustered widely. For taxonomic composition, overweight patients had a lower relative abundance in Porphyromonadaceae at family level and Butyrivibrio at genus level, but higher relative abundance in Ruminococcus2 and Clostridium_XIVa at genus level than normal-weight patients. Function prediction revelated that four pathways (including Cell cycle, Non-homologous end-joining, Vibrio cholerae infection and Meiosis-yeast) were significantly different between groups. Correlation analysis indicated that Klebsiella, Butyrivibrio, Unassigned, Methanosphaera, Holdemania, Anaerotruncus were negatively, while Veillonella was positively correlated with BMI in patients. CONCLUSION: Our findings offer evidence that perturbations in the gut microbiome composition, encompassing taxa such as Porphyromonadaceae, Butyrivibrio, Ruminococcus2, and Clostridium_XIVa, in conjunction with distinct functional pathways including Cell cycle, Non-homologous end-joining, Vibrio cholerae infection, and Meiosis-yeast, might contribute to the weight-gain in schizophrenia treated with atypical antipsychotics.

Empathy deficit in male patients with schizophrenia and its relationships with impulsivity and premeditated violence.

Objective: To explore the pattern of empathy characteristics in male patients with schizophrenia (SCH) and to examine whether empathy deficit is associated with impulsivity and premeditated violence. Methods: One hundred and fourteen male SCH patients were enrolled in this study. The demographic data of all patients were collected and the subjects were divided into two groups, namely, the violent group, including 60 cases, and the non-violent group, comprising 54 cases, according to the Modified Overt Aggression Scale (MOAS). The Chinese version of the Interpersonal Reactivity Index-C (IRI-C) was used to evaluate empathy and the Impulsive/Predicted Aggression Scales (IPAS) was employed to assess the characteristics of aggression. Results: Among the 60 patients in the violent group, 44 patients had impulsive aggression (IA) and 16 patients had premeditated aggression (PM) according to the IPAS scale. In the violent group, the scores of the four subfactors of the IRI-C, i.e., perspective taking (PT), fantasy (FS), personal distress (PD), and empathy concern (EC), were significantly lower than in the non-violent group. Stepwise logistic regression showed that PM was independent influencing factor for violent behaviors in SCH patients. Correlation analysis revealed that EC of affective empathy was positively correlated with PM but not with IA. Conclusion: SCH patients with violent behavior had more extensive empathy deficits compared with non-violent SCH patients. EC, IA and PM are independent risk factors of violence in SCH patients. Empathy concern is an important index to predict PM in male patients with SCH.

A neuromarker for deficit syndrome in schizophrenia from a combination of structural and functional magnetic resonance imaging.

AIM: Deficit schizophrenia (DS), defined by primary and enduring negative symptoms, has been proposed as a promising homogeneous subtype of schizophrenia. It has been demonstrated that unimodal neuroimaging characteristics of DS were different from non-deficit schizophrenia (NDS), however, whether multimodal-based neuroimaging features could identify deficit syndrome remains to be determined. METHODS: Functional and structural multimodal magnetic resonance imaging of DS, NDS and healthy controls were scanned. Voxel-based features of gray matter volume, fractional amplitude of low-frequency fluctuations, and regional homogeneity were extracted. The support vector machine classification models were constructed using these features separately and jointly. The most discriminative features were defined as the first 10% of features with the greatest weights. Moreover, relevance vector regression was applied to explore the predictive values of these top-weighted features in predicting negative symptoms. RESULTS: The multimodal classifier achieved a higher accuracy (75.48%) compared with the single modal model in distinguishing DS from NDS. The most predictive brain regions were mainly located in the default mode and visual networks, exhibiting differences between functional and structural features. Further, the identified discriminative features significantly predicted scores of diminished expressivity factor in DS but not NDS. CONCLUSIONS: The present study demonstrated that local properties of brain regions extracted from multimodal imaging data could distinguish DS from NDS with a machine learning-based approach and confirmed the relationship between distinctive features and the negative symptoms subdomain. These findings may improve the identification of potential neuroimaging signatures and improve the clinical assessment of the deficit syndrome.

A Patch Diversity Transformer for Domain Generalized Semantic Segmentation.

Domain generalization (DG) is one of the critical issues for deep learning in unknown domains. How to effectively represent domain-invariant context (DIC) is a difficult problem that DG needs to solve. Transformers have shown the potential to learn generalized features, since the powerful ability to learn global context. In this article, a novel method named patch diversity Transformer (PDTrans) is proposed to improve the DG for scene segmentation by learning global multidomain semantic relations. Specifically, patch photometric perturbation (PPP) is proposed to improve the representation of multidomain in the global context information, which helps the Transformer learn the relationship between multiple domains. Besides, patch statistics perturbation (PSP) is proposed to model the feature statistics of patches under different domain shifts, which enables the model to encode domain-invariant semantic features and improve generalization. PPP and PSP can help to diversify the source domain at the patch level and feature level. PDTrans learns context across diverse patches and takes advantage of self-attention to improve DG. Extensive experiments demonstrate the tremendous performance advantages of the PDTrans over state-of-the-art DG methods.