High-efficiency terahertz-wave generation based on extended interaction oscillator with strongly-coupled 2π mode operation.

A slow-wave structure improvement for enhancing the 2π-mode electronic efficiency is embodied in the validation of an extended interaction oscillator (EIO), which has an electronic efficiency of 6.52% at 0.22 THz from particle-in-cell (PIC) calculations. A 2π-mode bi-periodic slow-wave structure (BPSWS) with staggered long and short slots is utilized for optimizing the circuit performance. The proposed BPSWS has the capability of combining the respective advantages for both π and 2π-mode in terms of coupling performance and output performance, thus supporting a strongly-coupled 2π-mode with higher coupling capability. Compared with the typical mono-periodic SWS (MPSWS), the adopted strongly-coupled 2π-mode effectively improves the characteristic impedance M2R/Q by 103% to 66.79 Ω, the coupling coefficient by 66% to 0.497, and the normalized wave-amplitude by 22%. Accordingly, 503 W of average output power can be derived for the BPSWS-EIO with a 25.7 kV and 0.3 A sheet beam injected. Cold-test experiments were conducted, confirming that the 0.22 THz structure exhibits commendable fabrication precision and consistency and thus demonstrates the expected frequency response.

A reduced vector model predictive controller for a three-level neutral point clamped inverter with common-mode voltage suppression.

This paper presents a novel, state-of-the-art predictive control architecture that addresses the computational complexity and limitations of conventional predictive control methodologies while enhancing the performance efficacy of predictive control techniques applied to three-level voltage source converters (NPC inverters). This framework's main goal is to decrease the number of filtered voltage lifespan vectors in each sector, which will increase the overall efficiency of the control system and allow for common mode voltage reduction in three-level voltage source converters. Two particular tactics are described in order to accomplish this. First, a statistical approach is presented for the proactive detection of potential voltage vectors, with an emphasis on selecting and including the vectors that are most frequently used. This method lowers the computational load by limiting the search space needed to find the best voltage vectors. Then, using statistical analysis, a plan is presented to split the sectors into two separate parts, so greatly limiting the number of voltage vectors. The goal of this improved predictive control methodology is to reduce computing demands and mitigate common mode voltage. The suggested strategy's resilience is confirmed in a range of operational scenarios using simulations and empirical evaluation. The findings indicate a pronounced enhancement in computational efficiency and a notable diminution in common mode voltage, thereby underscoring the efficacy of the proposed methodology. This increases their ability to incorporate renewable energy sources into the electrical grid.

Psychedelics in developmental stuttering to modulate brain functioning: a new therapeutic perspective?

Developmental stuttering (DS) is a neurodevelopmental speech-motor disorder characterized by symptoms such as blocks, repetitions, and prolongations. Persistent DS often has a significant negative impact on quality of life, and interventions for it have limited efficacy. Herein, we briefly review existing research on the neurophysiological underpinnings of DS -specifically, brain metabolic and default mode/social-cognitive networks (DMN/SCN) anomalies- arguing that psychedelic compounds might be considered and investigated (e.g., in randomized clinical trials) for treatment of DS. The neural background of DS is likely to be heterogeneous, and some contribution from genetically determinants of metabolic deficiencies in the basal ganglia and speech-motor cortical regions are thought to play a role in appearance of DS symptoms, which possibly results in a cascade of events contributing to impairments in speech-motor execution. In persistent DS, the difficulties of speech are often linked to a series of associated aspects such as social anxiety and social avoidance. In this context, the SCN and DMN (also influencing a series of fronto-parietal, somato-motor, and attentional networks) may have a role in worsening dysfluencies. Interestingly, brain metabolism and SCN/DMN connectivity can be modified by psychedelics, which have been shown to improve clinical evidence of some psychiatric conditions (e.g., depression, post-traumatic stress disorder, etc.) associated with psychological constructs such as rumination and social anxiety, which also tend to be present in persistent DS. To date, while there have been no controlled trials on the effects of psychedelics in DS, anecdotal evidence suggests that these agents may have beneficial effects on stuttering and its associated characteristics. We suggest that psychedelics warrant investigation in DS.

Multi level perspectives in stock price forecasting: ICE2DE-MDL.

This study proposes a novel hybrid model, called ICE2DE-MDL, integrating secondary decomposition, entropy, machine and deep learning methods to predict a stock closing price. In this context, first of all, the noise contained in the financial time series was eliminated. A denoising method, which utilizes entropy and the two-level ICEEMDAN methodology, is suggested to achieve this. Subsequently, we applied many deep learning and machine learning methods, including long-short term memory (LSTM), LSTM-BN, gated recurrent unit (GRU), and SVR, to the IMFs obtained from the decomposition, classifying them as noiseless. Afterward, the best training method was determined for each IMF. Finally, the proposed model's forecast was obtained by hierarchically combining the prediction results of each IMF. The ICE2DE-MDL model was applied to eight stock market indices and three stock data sets, and the next day's closing price of these stock items was predicted. The results indicate that RMSE values ranged from 0.031 to 0.244, MAE values ranged from 0.026 to 0.144, MAPE values ranged from 0.128 to 0.594, and R-squared values ranged from 0.905 to 0.998 for stock indices and stock forecasts. Furthermore, comparisons were made with various hybrid models proposed within the scope of stock forecasting to evaluate the performance of the ICE2DE-MDL model. Upon comparison, The ICE2DE-MDL model demonstrated superior performance relative to existing models in the literature for both forecasting stock market indices and individual stocks. Additionally, to our knowledge, this study is the first to effectively eliminate noise in stock item data using the concepts of entropy and ICEEMDAN. It is also the second study to apply ICEEMDAN to a financial time series prediction problem.

Spatial Filtering of Interlayer Exciton Ground State in WSe2/MoS2 Heterobilayer.

Long-life interlayer excitons (IXs) in transition metal dichalcogenide (TMD) heterostructure are promising for realizing excitonic condensates at high temperatures. Critical to this objective is to separate the IX ground state (the lowest energy of IX state) emission from other states' emissions. Filtering the IX ground state is also essential in uncovering the dynamics of correlated excitonic states, such as the excitonic Mott insulator. Here, we show that the IX ground state in the WSe2/MoS2 heterobilayer can be separated from other states by its spatial profile. The emissions from different moiré IX modes are identified by their different energies and spatial distributions, which fits well with the rate-diffusion model for cascading emission. Our results show spatial filtering of the ground state mode and enrich the toolbox to realize correlated states at elevated temperatures.

Design, Synthesis, Bioactivity, and Tentative Exploration of Action Mode for Benzyl Ester-Containing Derivatives.

The active splicing strategy has witnessed improvement in bioactivity and antifungal spectra in pesticide discovery. Herein, a series of simple-structured molecules (Y1-Y53) containing chloro-substituted benzyl esters were designed using the above strategy. The structure-activity relationship (SAR) analysis demonstrated that the fatty acid fragment-structured esters were more effective than those containing an aromatic acid moiety or naphthenic acid part. Compounds Y36 and Y41, which featured a thiazole-4-acid moiety and trifluoromethyl aliphatic acid part, respectively, exhibited excellent in vivo curative activity (89.4%, 100 mg/L Y36) and in vitro fungicidal activity (EC50 = 0.708 mg/L, Y41) against Botrytis cinerea. Determination of antifungal spectra and analysis of scanning electron microscopy (SEM), membrane permeability, cell peroxidation, ergosterol content, oxalic acid pathways, and enzymatic assays were performed separately here. Compound Y41 is cost effective due to its simple structure and shows promise as a disease control candidate. In addition, Y41 might act on a novel target through a new pathway that disrupts the cell membrane integrity by inducing cell peroxidation.

Mode conversion of fundamental guided ultrasonic wave modes at part-thickness crack-like defects.

Guided ultrasonic waves can be employed for efficient structural health monitoring (SHM) and non-destructive evaluation (NDE), as they can propagate long distances along thin structures. The scattering (S0 mode) and mode conversion of low frequency guided waves (S0 to A0 and SH0 wave modes) at part-thickness crack-like defects was studied to quantify the defect detection sensitivity. Three-dimensional (3D) Finite Element (FE) modelling was used to predict the mode conversion and scattering of the fundamental guided wave modes. Experimentally, the S0 mode was excited by a piezoelectric (PZT) transducer in an aluminum plate. A laser vibrometer was used to measure the out-of-plane displacement to characterize the mode-converted A0 mode, employing baseline subtraction to achieve mode and pulse separation. Good agreement between FE model predictions and experimental results was obtained for perpendicular incidence of the S0 mode. The influence of defect depth and length on the scattering and mode conversion was studied and the sensitivity for part-thickness defects was quantified. The maximum mode conversion (S0-A0 mode) occurred for ¾ defect depth and the amplitude of the mode-converted A0 and scattered S0 modes mostly increased linearly as the defect length increased with an almost constant A0/S0 mode scattered amplitude ratio. Similar forward and backward scattering amplitude was found for the mode converted A0 mode. The mode conversion of the S0 to SH0 mode has the highest sensitivity for short defects, but the SH0 mode amplitude only increased slightly for longer defects. Employing the information contained in the mode-converted, scattered guided ultrasonic wave modes could improve the detection sensitivity and localization accuracy of SHM algorithms.

Disentangling the role of gray matter volume and concentration in autism spectrum disorder: A meta-analytic investigation of 25 years of voxel-based morphometry research.

Despite over two decades of neuroimaging research, a unanimous definition of the pattern of structural variation associated with autism spectrum disorder (ASD) has yet to be found. One potential impeding issue could be the sometimes ambiguous use of measurements of variations in gray matter volume (GMV) or gray matter concentration (GMC). In fact, while both can be calculated using voxel-based morphometry analysis, these may reflect different underlying pathological mechanisms. We conducted a coordinate-based meta-analysis, keeping apart GMV and GMC studies of subjects with ASD. Results showed distinct and non-overlapping patterns for the two measures. GMV decreases were evident in the cerebellum, while GMC decreases were mainly found in the temporal and frontal regions. GMV increases were found in the parietal, temporal, and frontal brain regions, while GMC increases were observed in the anterior cingulate cortex and middle frontal gyrus. Age-stratified analyses suggested that such variations are dynamic across the ASD lifespan. The present findings emphasize the importance of considering GMV and GMC as distinct yet synergistic indices in autism research.

Monitoring of the disulfide scrambled species by mixed-mode SEC-HPLC during the purification of a bispecific antibody.

Size-exclusion chromatography-high performance liquid chromatography (SEC-HPLC) is an analytical method routinely used for assessing aggregation content in protein samples. As SEC-HPLC separates analytes based on their hydrodynamic radius, it generally lacks the capability of differentiating species that are similar in size. Recently while purifying a bispecific antibody (bsAb), we noticed that SEC-HPLC can provide certain degree of resolution between the target bsAb and a disulfide scrambled form, although these two species were identical in molecular weight. In seeing the unexpected potential of SEC-HPLC at resolving species with similar size, we further tested Zenix SEC-300, a mixed-mode SEC-HPLC column from Sepax, which was reported to be capable of separating protein analytes based on other factors besides size. The Zenix column indeed provided resolution much better than the regular SEC-HPLC column. Upon further optimization, the Zenix column allowed close to baseline separation of the correctly folded and the disulfide scrambled species. The current study, as a complement to the previous reports, further demonstrates that mix-mode SEC-HPLC is capable of separating protein analytes that are close in size but are different in conformation and/or surface characteristics.

Particle Size-Tunable Polydopamine Nanoparticles for Optical and Electrochemical Imaging of Latent Fingerprints on Various Surfaces.

Powder dusting method is the most widely used approach due to its low cost, simplicity, minimal instrument dependence, and extensive applicability for developing latent fingerprints (LFPs). Herein, a novel optical and electrochemical dual-mode method for high-resolution LFP enhancement has been explored based on size-tunable polydopamine (PDA) nanoparticles (NPs) and scanning electrochemical microscopy (SECM). Dark PDAs rich in functional groups and negative charges can combine with the residues of LFPs on various surfaces with high sensitivity and selectivity to realize high-resolution visual fingerprint physical patterns on various porous and nonporous substrates with light color. However, optical visualization is not feasible for LFPs on dark or multicolored surfaces. Fortunately, based on the differences in electrochemical reactivity between ridges and furrows caused by the conductivity and reducibility of PDA powders, SECM can serve as a powerful supplement to optical methods to effectively overcome background color interference and distinctly display fingerprint patterns. Intriguingly, it is noteworthy that the binding amount and particle size of PDA powder significantly affected the optical and electrochemical visualization of LFPs: more powder binding amounts provided darker ridges in optical, and more surface reaction sites (larger powder binding mass at the same particle size or smaller particle size at the same mass) provided higher currents of ridges in electrochemical imaging. It demonstrates that the PDA powder as a dual-mode developer for LFPs offers a promising method for individual identification in forensics.

Cost-effectiveness analysis of pembrolizumab plus chemotherapy versus placebo plus chemotherapy for HER2-negative advanced gastric/gastroesophageal junction cancer in the Chinese healthcare system.

BACKGROUND: This study compares first-line pembrolizumab plus chemotherapy with chemotherapy alone for patients with HER2-negative advanced gastric cancer (GC) and gastroesophageal junction cancer (GEJC) in China. METHODS: A Markov state-transition model was developed based on the phase 3 randomized KEYNOTE-859 clinical trial data. The health state utility values and direct medical costs were derived from the KEYNOTE-859 clinical trial, the relevant literature, and local charges. The measured outcomes included quality-adjusted life-years (QALYs) and the incremental cost-effectiveness ratio (ICER). Probabilistic and one-way sensitivity analyses (OWSA) were performed to assess the uncertainty of the model. RESULTS: In the base analysis, the incremental effectiveness and cost of pembrolizumab plus chemotherapy versus chemotherapy alone were 0.22 QALYs and $16,627.31, respectively, resulting in an ICER of $76,936.60/QALY, which is higher than the willingness-to-pay threshold in China ($35,864.61/QALY). Subgroup analyses revealed that the ICERs of pembrolizumab plus chemotherapy versus chemotherapy alone were $72,762.68 and $34,813.70 in the populations with PD-L1 CPS of 1 or higher (CPS ≥1) and PD-L1 CPS ≥ 10 (CPS ≥10), respectively. CONCLUSIONS: As first-line therapy for patients with locally advanced or metastatic HER2-negative GC/GEJC in China, pembrolizumab plus chemotherapy is less cost-effective than chemotherapy alone, however, in the CPS ≥ 10 subgroup is more.

Laser tattoo removal strategies: Part II: A review of the methods, techniques, and complications involved in tattoo removal.

The rising global popularity of cosmetic and corrective tattoos has concurrently led to an increased demand for their removal. While in the past, methods like surgical excision, chemical destruction, and dermabrasion were employed, lasers have emerged as a reliable and effective tool for tattoo removal. Increasing technological options and combination treatment strategies have raised the importance of understanding the various approaches to laser tattoo removal along with their respective clinical impact. This CME aims to describe the multifaceted aspects of laser tattoo removal, including the method selection, application principles, and safety considerations. Furthermore, it addresses the factors considered when selecting the most suitable laser to achieve optimal treatment outcomes.

Acoustic Skyrmionic Mode Coupling and Transferring in a Chain of Subwavelength Metastructures.

Skyrmions, a stable topological vectorial textures characteristic with skyrmionic number, hold promise for advanced applications in information storage and transmission. While the dynamic motion control of skyrmions has been realized with various techniques in magnetics and optics, the manipulation of acoustic skyrmion has not been done. Here, the propagation and control of acoustic skyrmion along a chain of metastructures are shown. In coupled acoustic resonators made with Archimedes spiral channel, the skyrmion hybridization is found giving rise to bonding and antibonding skyrmionic modes. Furthermore, it is experimentally observed that the skyrmionic mode of acoustic velocity field distribution can be robustly transferred covering a long distance and almost no distortion of the skyrmion textures in a chain of metastructures, even if a structure defect is introduced in the travel path. The proposed localized acoustic skyrmionic mode coupling and propagating is expected in future applications for manipulating acoustic information storage and transfer.

Robust internal model control based on a novel generalized extended state observer and its application on a two-inertia system.

Disturbance observer (DOB) and extended state observer (ESO) are extensively utilized to handle external disturbances and model uncertainties in the control system. Nevertheless, the integration of these two methods to improve disturbance suppression remains an open question. In this research, the disturbance compensation mechanism of DOB is employed to compensate the disturbance estimation error of ESO, thereby achieving an effective integration of DOB and ESO. Additionally, a generalized ESO (GESO) is proposed to replace ESO. A robust internal mode control (RIMC) scheme is then developed by incorporating GESO into a two-degree-of-freedom internal mode control (TDF-IMC) framework. Moreover, the equivalence of RIMC and classical TDF-IMC is given by a rigorous derivation under the frequency domain description. Finally, the RIMC is applied to the control of a two-inertia system to verify its superiority in terms of robustness, disturbance rejection, and resonance suppression.

In vivo movement of retinoblastoma-related protein (RBR) towards cytoplasm during mitosis in Arabidopsisthaliana.

Retinoblastoma protein is central in signaling networks of fundamental cell decisions such as proliferation and differentiation in all metazoans and cancer development. Immunostaining and biochemical evidence demonstrated that during interphase retinoblastoma protein is in the nucleus and is hypophosphorylated, and during mitosis is in the cytoplasm and is hyperphosphorylated. The purpose of this study was to visualize in vivo in a non-diseased tissue, the dynamic spatial and temporal nuclear exit toward the cytoplasm of this protein during mitosis and its return to the nucleus to obtain insights into its potential cytosolic functions. Using high-resolution time-lapse images from confocal microscopy, we tracked in vivo the ortholog in plants the RETINOBLASTOMA RELATED (RBR) protein tagged with Green Fluorescent Protein (GFP) in Arabidopsis thaliana's root. RBR protein exits from dense aggregates in the nucleus before chromosomes are in prophase in less than 2 min, spreading outwards as smaller particles projected throughout the cytosol during mitosis like a diffusive yet controlled event until telophase, when the daughter's nuclei form; RBR returns to the nuclei in coordination with decondensing chromosomal DNA forming new aggregates again in punctuated larger structures in each corresponding nuclei. We propose RBR diffused particles in the cytoplasm may function as a cytosolic sensor of incoming signals, thus coordinating re-aggregation with DNA is a mechanism by which any new incoming signals encountered by RBR may lead to a reconfiguration of the nuclear transcriptomic context. The small RBR diffused particles in the cytoplasm may preserve topologic-like properties allowing them to aggregate and restore their nuclear location, they may also be part of transient cytoplasmic storage of the cellular pre-mitotic transcriptional context, that once inside the nuclei may execute both the pre mitosis transcriptional context as well as new transcriptional instructions.

Atypical intrinsic neural timescale in the left angular gyrus in Alzheimer's disease.

Alzheimer's disease is characterized by cognitive impairment and progressive brain atrophy. Recent human neuroimaging studies reported atypical anatomical and functional changes in some regions in the default mode network in patients with Alzheimer's disease, but which brain area of the default mode network is the key region whose atrophy disturbs the entire network activity and consequently contributes to the symptoms of the disease remains unidentified. Here, in this case-control study, we aimed to identify crucial neural regions that mediated the phenotype of Alzheimer's disease, and as such, we examined the intrinsic neural timescales-a functional metric to evaluate the capacity to integrate diverse neural information-and grey matter volume of the regions in the default mode network using resting-state functional MRI images and structural MRI data obtained from individuals with Alzheimer's disease and cognitively typical people. After confirming the atypically short neural timescale of the entire default mode network in Alzheimer's disease and its link with the symptoms of the disease, we found that the shortened neural timescale of the default mode network was associated with the aberrantly short neural timescale of the left angular gyrus. Moreover, we revealed that the shortened neural timescale of the angular gyrus was correlated with the atypically reduced grey matter volume of this parietal region. Furthermore, we identified an association between the neural structure, brain function and symptoms and proposed a model in which the reduced grey matter volume of the left angular gyrus shortened the intrinsic neural time of the region, which then destabilized the entire neural timescale of the default mode network and resultantly contributed to cognitive decline in Alzheimer's disease. These findings highlight the key role of the left angular gyrus in the anatomical and functional aetiology of Alzheimer's disease.

Differential effects of hypnotherapy and cognitive behavioral therapy on the default mode network of depressed patients.

Hypnosis has been applied in healing procedures since the earliest of recorded history and today it is implemented in a wholesome concept Hypnotherapy (HT1). On a neurophysiological level, hypnosis has been associated with parts of the Default Mode Network (DMN2), but its effects on this network when induced in a treatment setting of a widespread disorder, namely depression, have never been investigated. Depression is associated with abnormal functional connectivity (FC3) of the DMN. Cognitive Behavioral Therapy (CBT4) has proven itself to be an effective treatment for depression; effects of CBT on DMN-related regions are heterogeneous. In the past years, HT was found to be a promising alternative or helpful adjunction. Yet, its underlying mechanisms remain to be unclear. In this original study 75 depressed patients receiving either CBT or HT were included and measured during resting-state before and after therapy with functional near-infrared-spectroscopy (fNIRS5). On symptom level, results show a significant reduction in both groups. On a neurophysiological level, first exploratory analyses hint toward treatment effects in two components of the DMN. However, these effects do not withstand correction for multiple testing. Still, our study is a first stepstone in the investigation of neural mechanisms of HT and offers first ideas about possible implications.

Non-contact elasticity contrast imaging using photon counting.

Significance: Tissues' biomechanical properties, such as elasticity, are related to tissue health. Optical coherence elastography produces images of tissues based on their elasticity, but its performance is constrained by the laser power used, working distance, and excitation methods. Aim: We develop a new method to reconstruct the elasticity contrast image over a long working distance, with only low-intensity illumination, and by non-contact acoustic wave excitation. Approach: We combine single-photon vibrometry and quantum parametric mode sorting (QPMS) to measure the oscillating backscattered signals at a single-photon level and derive the phantoms' relative elasticity. Results: We test our system on tissue-mimicking phantoms consisting of contrast sections with different concentrations and thus stiffness. Our results show that as the driving acoustic frequency is swept, the phantoms' vibrational responses are mapped onto the photon-counting histograms from which their mechanical properties-including elasticity-can be derived. Through lateral and longitudinal laser scanning at a fixed frequency, a contrast image based on samples' elasticity can be reliably reconstructed upon photon level signals. Conclusions: We demonstrated the reliability of QPMS-based elasticity contrast imaging of agar phantoms in a long working distance, low-intensity environment. This technique has the potential for in-depth images of real biological tissue and provides a new approach to elastography research and applications.

"I feel [so alone] nothing" - emotional vulnerability and detachment as transdiagnostic key characteristics of patients with chronic tinnitus: a schema mode model approach.

Background: Gold-standard approaches for chronic tinnitus involve hearing amplification measures and psychological therapy, where applicable. Whilst schema therapy is accumulating evidence as a transdiagnostically useful treatment framework, its applicability for patients with chronic tinnitus has not yet been examined. The present study (a) explores latent dimensions of psychological distress in a sample of chronic tinnitus patients, and (b) examines whether the schema mode model might explain these dimensions - thus constituting a potentially helpful conceptualization and treatment framework. Methods: N = 696 patients with chronic tinnitus completed the Tinnitus Questionnaire, Tinnitus Handicap Inventory, Hospital Anxiety and Depression Scale, Perceived Stress Questionnaire and ICD-10 Symptom Rating. As criterion, patients further completed the Schema Mode Inventory (SMI-r) - which assesses psychological constructs linked to negative self-beliefs ("parent modes"), primary emotions resulting from unmet psychological needs ("child modes"), and secondary emotional or behavioral attempts to reinstate or maintain psychological equilibrium ("coping modes"). A varimax-rotated principal axis factor analysis grouped the primary item pool. Factor scale scores were then correlated with the SMI-r. Results: A three-factor solution explained 37.4% of variance and represented 78% of the included items. Following item content examination, the factors represented (1) General emotional distress, (2) Tinnitus-attributed emotional distress, and (3) Socio-audiological impairment. Factors 1|2 correlated highly (r = 0.70), Factors 2|3 moderately (r = 0.62). Linked to the schema mode model, Factor 1 correlated highly with the "vulnerable child" (r = 0.78), and moderately with the "parent", "angry child", and "detached protector" modes (0.53 < r < 0.65). Factor 2 correlated moderately with the "vulnerable child" (r = 0.53). Factor 3 was largely uncorrelated with SMI-r scores - although a low correlation with the "detached protector" warrants further examination. Conclusion: "General" and "tinnitus-attributed" emotional distress correlate highly - warranting holistic (not symptom-specific) psychological case conceptualization and treatment planning. Viewed from a schema mode perspective, the "vulnerable child" explains substantial variance across both dimensions. Consequently, autobiographically anchored, unmet emotional needs and emotional detachment constitute key treatment targets. Social-audiological impairment should be multimodally conceptualised and treated with hearing aids and psychological support measures, as applicable.

A connectome-based model of delusion in schizophrenia using functional connectivity under working memory task.

Delusion is an important feature of schizophrenia, which may stem from cognitive biases. Working memory (WM) is the core foundation of cognition, closely related to delusion. However, the knowledge of neural mechanisms underlying the relationship between WM and delusion in schizophrenia is poorly investigated. Two hundred and thirty patients with schizophrenia (dataset 1: n = 130; dataset 2: n = 100) were enrolled and scanned for an N-back WM task. We constructed the WM-related whole-brain functional connectome and conducted Connectome-based Predictive Modelling (CPM) to detect the delusion-related networks and built the correlation model in dataset 1. The correlation between identified networks and delusion severity was tested in a separate, heterogeneous sample of dataset 2 that mainly includes early-onset schizophrenia. The identified delusion-related network has a strong correlation with delusion severity measured by the NO.20 item of SAPS in dataset 1 (r = 0.433, p = 2.7 × 10-7, permutation-p = 0.035), and can be validated in the same dataset by using another delusion measurement, that is, the P1 item of PANSS (r = 0.362, p = 0.0005). It can be validated in another independent dataset 2 (NO.20 item of SAPS for r = 0.31, p = 0.0024, P1 item of PANSS for r = 0.27, p = 0.0074). The delusion-related network comprises the connections between the default mode network (DMN), cingulo-opercular network (CON), salience network (SN), subcortical, sensory-somatomotor network (SMN), and visual networks. We successfully established correlation models of individualized delusion based on the WM-related functional connectome and showed a strong correlation between delusion severity and connections within the DMN, CON, SMN, and subcortical network.