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Abstract Neuroimaging studies have revealed that the mechanisms of auditory hallucinations are related to morphological changes in multiple cortical regions, but studies on brain network properties are lacking. This study aims to construct intra-individual structural covariance networks and reveal network changes related to auditory hallucinations. T1-weighted MRI images were acquired from 90 schizophrenia patients with persistent auditory hallucinations (pAH group), 55 schizophrenia patients without auditory hallucinations (non-pAH group), and 83 healthy controls (HC group). Networks were constructed using the voxel-based gray matter volume and the intra-individual structural covariance was based on the similarity between the morphological variations of any two regions. One-way ANCOVA was employed to compare global and local network metrics among the three groups, and edge analysis was conducted via network-based statistics. In the pAH group, Pearson correlation analysis between network metrics and clinical symptoms was conducted. Compared with the HC group, both the pAH group (p = 0.01) and the non-pAH group (p = 3.56 × 10−4) had lower nodal efficiency of the left medial superior frontal gyrus. Compared to the non-pAH group and HC group, the pAH group presented lower nodal efficiency of the temporal pole of the left superior temporal gyrus (p = 1.09 × 10−3; p = 7.67 × 10−4) and right insula (p = 0.02; p = 8.99 × 10−6), and lower degree centrality of the right insula (p = 0.04; p = 1.65 × 10−5). The pAH group had a subnetwork with reduced structural covariance centered by the left temporal pole of the superior temporal gyrus. In the pAH group, the normalized clustering coefficient (r = −0.36, p = 8.45 × 10−3) and small-worldness (r = −0.35, p = 9.89 × 10−3) were negatively correlated with the PANSS positive scale score. This study revealed network changes in schizophrenia patients with persistent auditory hallucinations, and provided new insights into the structural architecture related to auditory hallucinations at the network level.

Abstract Background The attrition rate of Chinese medical students is high. This study utilizes a nomogram technique to develop a predictive model for dropout intention among Chinese medical undergraduates based on 19 individual and work-related characteristics. Method A repeated cross-sectional study was conducted, enrolling 3536 medical undergraduates in T1 (August 2020-April 2021) and 969 participants in T2 (October 2022) through snowball sampling. Demographics (age, sex, study phase, income, relationship status, history of mental illness) and mental health factors (including depression, anxiety, stress, burnout, alcohol use disorder, sleepiness, quality of life, fatigue, history of suicidal attempts (SA), and somatic symptoms), as well as work-related variables (career choice regret and reasons, workplace violence experience, and overall satisfaction with the Chinese healthcare environment), were gathered via questionnaires. Data from T1 was split into a training cohort and an internal validation cohort, while T2 data served as an external validation cohort. The nomogram’s performance was evaluated for discrimination, calibration, clinical applicability, and generalization using receiver operating characteristic curves (ROC), area under the curve (AUC), calibration curves, and decision curve analysis (DCA). Result From 19 individual and work-related factors, five were identified as significant predictors for the construction of the nomogram: history of SA, career choice regret, experience of workplace violence, depressive symptoms, and burnout. The AUC values for the training, internal validation, and external validation cohorts were 0.762, 0.761, and 0.817, respectively. The nomogram demonstrated reliable prediction and discrimination, with adequate calibration and generalization across both the training and validation cohorts. Conclusion This nomogram exhibits reasonable accuracy in foreseeing dropout intentions among Chinese medical undergraduates. It could guide colleges, hospitals, and policymakers in pinpointing students at risk, thus informing targeted interventions. Addressing underlying factors such as depressive symptoms, burnout, career choice regret, and workplace violence may help reduce the attrition of medical undergraduates. Trial registration This is an observational study. There is no Clinical Trial Number associated with this manuscript.

Abstract Electronic cigarettes (e-cigs) use, especially among youngsters, has been on the rise in recent years. However, little is known about the long-term effects of the use of e-cigs on brain functional activity. We acquired the resting-state functional magnetic resonance imaging (rs-fMRI) data from 93 e-cigs users with nicotine dependence and 103 health controls (HC). The local synchronization was analyzed via the regional homogeneity (ReHo) method at voxel-wise level. The functional connectivity (FC) between the nucleus accumbens (NAcc), the ventral tegmental area (VTA), and the insula was calculated at ROI-wise level. The support vector machining classification model based on rs-fMRI measures was used to identify e-cigs users from HC. Compared with HC, nicotine-dependent e-cigs users showed increased ReHo in the right rolandic operculum and the right insula (p

Abstract Objective Epidemiological studies revealed an unestablished association between neuroticism and posttraumatic stress disorder (PTSD) and we conducted mendelian randomization (MR) analyses to examine whether neuroticism clusters of worry, depressed affect, and sensitivity to environmental stress and adversity (SESA) were involved in the development of PTSD. Method We obtained data on three neuroticism clusters, PTSD, and nine other psychiatric disorders from genome‐wide association studies summary statistics and employed univariable, multivariable, and mediation MR analyses to explore causal associations among them. Results Neuroticism clusters were linked with PTSD (depressed affect (odds ratio [OR]: 2.94 [95% confidence interval: 2.21–3.92]); SESA (2.69 [1.95–3.71]; worry (1.81 [1.37–2.99])). Neuroticism clusters were also associated with psychiatric disorders, with the depressed effect on panic disorder (PD) (2.60 [1.14–5.91]), SESA on anorexia nervosa (AN) (2.77 [1.95–3.94]) and schizophrenia (2.55 [1.99–3.25]), worry on major depressive disorder (MDD) (2.58 [2.19–3.05]). In multivariable MR, only the SESA‐PTSD association remained (2.60 [2.096, 3.107]) while worry‐PTSD and depressed affect‐PTSD associations attenuated to nonsignificance. Mediation MR analyses suggested that PD mediated 3.76% of the effect of depressed effect on PTSD and AN mediated 10.33% of the effect of SESA on PTSD. Conclusion Delving deeper into neuroticism clusters, we comprehensively understand the role of neuroticism in PTSD.

Abstract The popular convolutional neural networks (CNN) require data augmentation to achieve rotation invariance. We propose an alternative mechanism, Pre-Rotation Only at Inference stage (PROAI), to make CNN rotation invariant. The overall idea is to learn how the human brain observe images. At the training stage, PROAI trains a CNN with a small number using images only at one orientation. At the inference stage, PROAI introduces a pre-rotation operation to rotate each test image into its all-possible orientations and calculate classification scores using the trained CNN with a small number of parameters. The maximum of these classification scores is able to simultaneously estimate both the category and the orientation of each test image. The specific benefits of PROAI have been experimented on rotated image recognition tasks. The results shows that PROAI improves both the classification and orientation estimation performance while greatly reduced the numbers of parameters and the training time. Codes and datasets are publicly available at https://github.com/automlresearch/FRPRF .

Abstract Background Glutamatergic function abnormalities have been implicated in the etiology of treatment-resistant schizophrenia (TRS), and the efficacy of clozapine may be attributed to its impact on the glutamate system. Recently, evidence has emerged suggesting the involvement of immune processes and increased prevalence of antineuronal antibodies in TRS. This current study aimed to investigate the levels of multiple anti-glutamate receptor antibodies in TRS and explore the effects of clozapine on these antibody levels. Methods Enzyme linked immunosorbent assay (ELISA) was used to measure and compare the levels of anti-glutamate receptor antibodies (NMDAR, AMPAR, mGlur3, mGluR5) in clozapine-treated TRS patients (TRS-C, n = 37), clozapine-naïve TRS patients (TRS-NC, n = 39), and non-TRS patients (nTRS, n = 35). Clinical symptom severity was assessed using the Positive and Negative Symptom Scale (PANSS), while cognitive function was evaluated using the MATRICS Consensus Cognitive Battery (MCCB). Result The levels of all four glutamate receptor antibodies in TRS-NC were significantly higher than those in nTRS (p

In this paper, a dynamic modeling method of motor driven electromechanical system is presented, and the uncertainty quantification of mechanism motion is investigated based on this method. The main contribution is to propose a novel mechanism-motor coupling dynamic modeling method, in which the relationship between mechanism motion and motor rotation is established according to the geometric coordination of the system. The advantages of this include establishing intuitive coupling between the mechanism and motor, facilitating the discussion for the influence of both mechanical and electrical parameters on the mechanism, and enabling dynamic simulation with controller to take the randomness of the electric load into account. Dynamic simulation considering feedback control of ammunition delivery system is carried out, and the feasibility of the model is verified experimentally. Based on probability density evolution theory, we comprehensively discuss the effects of system parameters on mechanism motion from the perspective of uncertainty quantization. Our work can not only provide guidance for engineering design of ammunition delivery mechanism, but also provide theoretical support for modeling and uncertainty quantification research of mechatronics system.

As mental health issues become increasingly prominent, we are now facing challenges such as the severe unequal distribution of medical resources and low diagnostic efficiency. This paper integrates finite state machines, retrieval algorithms, semantic-matching models, and medical-knowledge graphs to design an innovative intelligent auxiliary evaluation tool and a personalized medical-advice generation application, aiming to improve the efficiency of mental health assessments and the provision of personalized medical advice. The main contributions include the folowing: (1) Developing an auxiliary diagnostic tool that combines the Mini-International Neuropsychiatric Interview (M.I.N.I.) with finite state machines to systematically collect patient information for preliminary assessments; (2) Enhancing data processing by optimizing retrieval algorithms for efficient filtering and employing a fine-tuned RoBERTa model for deep semantic matching and analysis, ensuring accurate and personalized medical-advice generation; (3) Generating intelligent suggestions using NLP techniques; when semantic matching falls below a specific threshold, integrating medical-knowledge graphs to produce general medical advice. Experimental results show that this application achieves a semantic-matching degree of 0.9 and an accuracy of 0.87, significantly improving assessment accuracy and the ability to generate personalized medical advice. This optimizes the allocation of medical resources, enhances diagnostic efficiency, and provides a reference for advancing mental health care through artificial-intelligence technology.

When a synthetic aperture sonar (SAS) system operates under low-frequency broadband conditions, the azimuth range coupling of the point target reference spectrum (PTRS) is severe, and the high-resolution imaging range is limited. To solve the above issue, we first convert multi-receivers’ signal into the equivalent monostatic signal and then divide the equivalent monostatic signal into range subblocks and the range frequency subbands within each range subblock in order. The azimuth range coupling terms are converted into linear terms based on piece-wise linear approximation (PLA), and the phase error of the PTRS within each subband is less than π/4. Then, we use the chirp-z transform (CZT) to correct range cell migration (RCM) to obtain low-resolution results for different subbands. After RCM correction, the subbands’ signals are coherently summed in the range frequency domain to obtain a high-resolution image. Finally, different subblocks are concatenated in the range time domain to obtain the final result of the whole swath. The processing of different subblocks and different subbands can be implemented in parallel. Computer simulation experiments and field data have verified the superiority of the proposed method over existing methods.

Background Alcohol drinking among adolescents is associated with their health development. However, the prevalence of alcohol drinking among adolescents in Southwestern China remains largely unexplored. This study aimed to investigate the prevalence of alcohol drinking, with a particular focus on gender differences, among primary and middle school students in Zigong, a city in Southwestern China. Additionally, we examined the association between alcohol consumption and demographic and family factors.Methods A school-based cross-sectional survey was conducted in a city in Southwestern China, encompassing a total of 89 360 students from 132 different ordinary schools, including both primary and middle schools. Participants were recruited through cluster sampling. The Alcohol Use Disorders Identification Test Consumption was employed to assess alcohol consumption. Gender differences in the prevalence of alcohol drinkers across various schools and grades were analysed. Multivariable logistic regression analysis was used to investigate factors associated with hazardous drinking.Results Out of the 89 360 participants, 19.0% reported alcohol drinking, with 2.1% classified as hazardous drinkers. There was a higher prevalence of alcohol drinking among boys compared with girls, as well as hazardous drinking. There were significant gender disparities in alcohol drinking observed across various schools and grade levels. A notable divergence between boys and girls was observed starting from grade 10, with a rising prevalence of hazardous drinking among boys and a decline among girls. Additionally, older age, male gender and being left-behind children were identified as risk factors for hazardous drinking, while belonging to a nuclear family and having parents who do not drink were protective factors against hazardous drinking.Conclusions Alcohol consumption is prevalent among Chinese adolescents, with some even classified as hazardous drinkers. These findings may offer valuable insights for policymakers and caregivers, guiding them in formulating appropriate interventions and support strategies.

BackgroundThe overall prevalence of cigarette smokers in China is very high, and China’s total cigarette consumption makes up more than 40% of the world’s consumption. In view of the lack of smoking cessation services and social support in China and the effectiveness of mobile phone apps for quitting smoking in other countries, we carried out a smartphone app–based smoking cessation trial in China. ObjectiveThis study aimed to evaluate the efficacy of a cognitive behavioral therapy (CBT)–based smoking cessation smartphone app among smokers seeking treatment in China. MethodsWe conducted a randomized controlled, web-based pilot clinical trial in China between February 23 and June 27, 2021. Eligible participants were randomly assigned to the smoking cessation app intervention group or the control group in a ratio of 1:1. The intervention group received the CBT smoking cessation intervention using a smartphone app, and the control group received a “thank you” message. The intervention was 4 weeks long, and the patients were followed up for 4 weeks. The primary outcome was self-reported continuous smoking abstinence at week 4 after the quit date. The secondary outcomes included self-reported 7-day point prevalence of smoking abstinence; reduction of the number of cigarettes smoked per day at weeks 1, 2, 3, and 4; and program acceptability. ResultsA total of 973 people were recruited to quit smoking, of whom 262 completed basic information, 56 were excluded, and 206 were randomized and included in the final analysis. There were 189 (91.7%) men and 17 (8.3%) women, with an average age of 34.46 (SD 7.53) years and an average daily smoking rate of 15.93 (SD 7.10) cigarettes/day. We found 30 (29.7%) of the 101 participants in the intervention group and 7 (6.7%) of the 105 participants in the control group reported continuous smoking cessation after the quit date at week 4 (odds ratio 5.92, 95% CI 3.78-9.26; P

Abstract Background This study aimed to assess the prevalence and the gender-specific risk factors of alcohol abuse/dependence among medical undergraduates during the post-COVID‑19 pandemic period in China. Method The Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) was used to identify respondents with alcohol abuse/dependence. A questionnaire on basic demographics and mental distresses (learning burnout, depression symptoms, anxiety symptoms, excessive daytime sleepiness, and history of mental disorders) was used. The logistic regression model was used to explore the associations between the above characteristics and alcohol abuse/dependence. Results A total of 3,412 medical undergraduates were included in the analysis. Males showed a higher prevalence of alcohol abuse/dependence than females (16.6% vs 7.4%, p

Abstract Backgrounds The Smartphone Application-Based Addiction Scale (SABAS) is a validated 6-item measurement tool for assessing problematic smartphone use (PSU). However, the absence of established cutoff points for SABAS hinders its utilities. This study aimed to determine the optimal cutoff point for SABAS through latent profile analysis (LPA) and receiver operating characteristic curve (ROC) analyses among 63, 205. Chinese adolescents. Additionally, the study explored whether PSU screening with SABAS could effectively capture problematic social media use (PSMU) and internet gaming disorder (IGD). Method We recruited 63,205. adolescents using cluster sampling. Validated questionnaires were used to assess PSMU, IGD, and mental health (depression, anxiety, sleep disturbances, well-being, resilience, and externalizing and internalizing problems). Results LPA identified a 3-class model for PSU, including low-risk users (38.6%, n = 24,388.), middle-risk users (42.5%, n = 26,885.), and high-risk users (18.9%, n = 11,932.). High-risk users were regarded as “PSU cases” in ROC analysis, which demonstrated an optimal cut-off point of 23 (sensitivity: 98.1%, specificity: 96.8%). According to the cutoff point, 21.1% (n = 13,317.) were identified as PSU. PSU adolescents displayed higher PSMU, IGD, and worse mental health. PSU screening effectively captured IGD (sensitivity: 86.8%, specificity: 84.5%) and PSMU (sensitivity: 84.5%, specificity: 80.2%). Conclusion A potential ideal threshold for utilizing SABAS to identify PSU could be 23 (out of 36). Employing SABAS as a screening tool for PSU holds the potential to reliably pinpoint both IGD and PSMU.

Abstract Background Depressive and anxiety symptoms affect about one-fourth of Chinese secondary school students. However, the prevalence and correlates of mental distress among secondary school students from Western China remain largely unexplored. This study aimed to examine the prevalence and associations of depressive and anxiety symptoms with demographic, family, school, life, and behavior factors in a large, representative sample of secondary school students in Zigong, a city in Western China. Methods Secondary school students were recruited using cluster sampling. The 9-item Patient Health Questionnaire, the 7-item Generalized Anxiety Disorder Questionnaire, Multidimensional Peer-Victimization Scale, the Pittsburgh Sleep Quality Index, and Nine-Item Internet Gaming Disorder Scale-Short Form were used. Descriptive statistic was used to describe the sociodemographic characteristics of participants. The clustering effect was adjusted by the “survey” package of R to calculate weighted prevalence. Univariate and multivariate logistic regression were used to explore associated factors of depression and anxiety, respectively. Results A total of 63,205 participants were involved, in which the weighted prevalence of depression in all subjects was 23.0% (95% CI: 19.6- 27.0%), and the weighted prevalence of anxiety was 13.9% (95% CI: 11.2- 17.0%). Logistic regression results showed girls, being single-child, non-nuclear family, peer bullying, sleep disturbance, and internet gaming disorder symptoms were positively associated with depressive and anxiety symptoms. Conclusion Depressive and anxiety symptoms were prevalent among secondary school students in Western China. Our results can guide policy strategies for the assessment, prevention, and intervention of psychological status among Chinese secondary school students.

Abstract Background Low-grade inflammation and altered inflammatory markers have been observed in treatment-resistant schizophrenia (TRS). Interleukin-6 (IL-6) is one of the pro-inflammatory cytokines linked with TRS and receives increasing attention. Previous studies showed that patients with TRS might have higher IL-6 levels compared with healthy individuals and treatment-responsive patients. Besides, emerging evidence has suggested that there are sex differences in the associations between IL-6 levels and various illnesses, including chronic hepatitis C, metabolic syndrome, etc.; however, there is limited study on TRS. In this present study, we aimed to compare the serum IL-6 levels of TRS and partially responsive schizophrenia (PRS) and explore potential sex differences in the association of TRS and IL-6 levels. Methods The study population consisted of a total of 90 patients with schizophrenia: 64 TRS patients (45.3% males and 54.7% females) and 26 PRS patients (46.2% males and 53.8% females). We measured serum IL-6 levels using enzyme-linked immunosorbent assay (ELISA) and analyzed them separately by gender, controlling for confounders (age, education, medication, body mass index, and PANSS scores) rigorously. Result The results showed that patients with TRS had higher serum IL-6 levels than patients with PRS (p = 0.002). In females, IL-6 levels increased significantly in the TRS group compared with the PRS group (p = 0.005). And a positive correlation tendency was observed between IL-6 levels and PANSS general sub-scores (r = 0.31, p = 0.039), although this correlation was not significant after correcting for multiple comparisons. Whereas, there were no differences in IL-6 levels between the TRS and PRS (p = 0.124) in males. Conclusion Our findings provided evidence supporting the hypothesis that the inflammatory response system (IRS) may play a role in the pathogenesis of TRS in a sex-dependent manner. In addition, sex differences in the immune dysfunction of individuals with schizophrenia cannot be neglected, and inflammation in male and female TRS should be discussed separately.

AbstractBackground Workplace violence in healthcare settings is a significant public concern that profoundly impacts healthcare workers. However, there is a dearth of knowledge regarding the prevalence of workplace violence and its correlation with suicidal ideation among undergraduate medical students in China during their clinical training. The objective of this study was to evaluate the prevalence of workplace violence inflicted by patients or their family members/visitors and to assess its association with suicidal ideation among undergraduate medical students.Method The snowballing sampling technique was used to recruit Chinese medical students. A question designed by the research team was used to ask medical students about their encounters with workplace violence. Students’ basic demographic information and mental distresses (learning burnout, depression symptoms, anxiety symptoms, alcohol abuse/dependence, excessive daytime sleepiness and history of mental disorders) were also assessed. As appropriate, the data were analysed using descriptive statistics, chi-square tests, independent-sample t-tests and multiple logistic regression.Results Out of the 1402 undergraduate medical students who participated, 493 (35.2%) reported having experienced workplace violence inflicted by patients or their family members/visitors, of which 394 (28.1%) were verbal abuse, 14 (1.0%) were physical aggression, and 85 (6.1%) were suffered from both verbal abuse and physical aggression. Furthermore, students exposed to workplace violence were more likely to report suicidal ideation and had a higher prevalence of learning burnout, depression symptoms, anxiety symptoms, alcohol abuse/dependence and excessive daytime sleepiness. Depression symptoms, history of mental disorders, learning burnout and having a partner were significantly associated with suicidal ideation in this population.Conclusion The prevalence of workplace violence inflicted by patients or their family members/visitors was high among undergraduate medical students in China. This may be associated with their mental distress and suicidal ideation. Consequently, it is crucial to strengthen workplace safety measures and promptly implement interventions to mitigate the potentially serious consequences.

Abstract Background Considerable evidence has been reported that tobacco use could cause alterations in gut microbiota composition. The microbiota-gut–brain axis also in turn hinted at a possible contribution of the gut microbiota to smoking. However, population-level studies with a higher evidence level for causality are lacking. Methods This study utilized the summary-level data of respective genome-wide association study (GWAS) for 211 gut microbial taxa and five smoking phenotypes to reveal the causal association between the gut microbiota and tobacco smoking. Two-sample bidirectional Mendelian randomization (MR) design was deployed and comprehensively sensitive analyses were followed to validate the robustness of results. We further performed multivariable MR to evaluate the effect of neurotransmitter-associated metabolites on observed associations. Results Our univariable MR results confirmed the effects of smoking on three taxa (Intestinimonas, Catenibacterium, and Ruminococcaceae, observed from previous studies) with boosted evidence level and identified another 13 taxa which may be causally affected by tobacco smoking. As for the other direction, we revealed that smoking behaviors could be potential consequence of specific taxa abundance. Combining with existing observational evidence, we provided novel insights regarding a positive feedback loop of smoking through Actinobacteria and indicated a potential mechanism for the link between parental smoking and early smoking initiation of their children driven by Bifidobacterium. The multivariable MR results suggested that neurotransmitter-associated metabolites (tryptophan and tyrosine, also supported by previous studies) probably played a role in the action pathway from the gut microbiota to smoking, especially for Actinobacteria and Peptococcus. Conclusions In summary, the current study suggested the role of the specific gut microbes on the risk for cigarette smoking (likely involving alterations in metabolites) and in turn smoking on specific gut microbes. Our findings highlighted the hazards of tobacco use for gut flora dysbiosis and shed light on the potential role of specific gut microbiota for smoking behaviors.

The existing multi-receiver synthetic aperture sonar (SAS) imaging algorithms are suitable for narrow-beam width, which will lead to a decrease in imaging quality under wide-beam condition and are not in line with the development needs of SAS. We propose a non-linear chirp scaling algorithm (NCSA) for wide beam multi-receiver SAS. Firstly, the point target reference spectrum (PTRS) of each receiver is obtained by the Lagrange inversion theorem (LIT), and then the under-sampled signal in the azimuth frequency domain is obtained through azimuth spectrum extension; Then, considering the cubic term of range frequency in the PTRS and the linear variation of equivalent frequency modulation slope with range, each receiver is imaged using the NCSA, and coherent superposition is performed in the azimuth frequency domain to eliminate spectrum aliasing caused by azimuth spectrum extension; Finally, the azimuth inverse transform is performed on the superimposed signal to obtain the focusing imaging. Computer simulation experiments and field data verify that this method is superior to the existing SAS imaging algorithm, improving the quality of wide-beam imaging, avoiding the interpolation operation of the traditional range-Doppler algorithm, and saving computation cost.

Objectives: To explore the differences between low kiloelectron volt (keV) virtual monoenergetic images (VMIs) using IQon spectral CT and conventional CT (120 kVp) in the diagnosis of osteoporosis. Methods: This retrospective study included 317 patients who underwent IQon spectral CT and dual-energy X-ray absorptiometry (DXA) examination. Commercial deep learning–based software was used for the fully automated extraction of the CT values of the first to fourth lumbar vertebrae (L1–L4) from two different low-keV levels (including 40/70 keV) VMIs and conventional 120 kVp images. The DXA examination results served as the standard of reference (normal [T-score ≥ −1], osteopenia [-2.5 0.05). Conclusions: The performance of the osteoporosis diagnosis model using IQon spectral CT simulating the low tube voltage scanning condition (less than 120 kVp) was also satisfactory. Bone density screening evaluation can be performed with a combination of low-dose lung scanning CT, greatly reducing the radiation dose without affecting the diagnosis.

Objective: To investigate the role of spectral CT multiparametric imaging in the evaluation of cerebral microcirculatory perfusion. Methods: The imaging data of 145 patients with asymptomatic cerebral infarction confirmed by MR were retrospectively analyzed, and all cases underwent head CTA and cranial CT perfusion imaging (CTP) on double-layer detector spectral CT. Single energy level images (MonoE45 keV), iodine density maps, and effective atomic number maps were reconstructed based on spectral CTA data, and CT values, iodine density values, and effective atomic number values were measured in the infarcted area, healthy control area, centrum semiovale and posterior limb of the internal capsule, respectively; perfusion values, such as cerebral blood volume (CBV) values, cerebral blood flow (CBF) values, time to peak (TTP) values, and mean passage time, were measured in the above-mentioned areas on CTP images. (TTP) values, and mean time to passage (MTT) values. CT values, iodine density values, effective atomic number values, and perfused CBV, CBF, TTP, and MTT values were compared between the infarcted area and the healthy side, the center of the hemianopia, and the posterior limb of the internal capsule. The role of spectral CT parameters and perfusion parameters in the evaluation of asymptomatic cerebral infarction was analyzed. Results: CT values, iodine density values, and effective atomic number values were statistically different between the infarcted area and the healthy side; CT values, iodine density values, and effective atomic number values were not statistically different between the infarcted side and the healthy side of the hemispheric centrum and the posterior limb of the internal capsule; CBV and CBF were statistically different between the infarcted side and the healthy side, and MTT and TTP were not statistically different. There were statistically significant differences in TTP between the infarcted area and the healthy side of the hemiaxial center, and no statistically significant differences in CBV, CBF, and MTT. There were no statistical differences in CBV, CBF, TTP, and MTT in the inner capsule area. ROC curve analysis of spectral CT-related parameters and CT perfusion parameters for the diagnosis of asymptomatic cerebral infarction: area under the curve of MonoE 45Kv 0.71, area under the curve of iodine density values 0.76, area under the curve of effective atomic number values 0.74; area under the curve of CBV value 0.64, area under the curve of CBF value 0.61, area under the curve of MTT value 0.50, The area under the TTP curve was 0.52. The area under the ROC curve of the multivariate logistic regression model based on spectral parameters is 0.76, which is higher than that of the logistic regression model with perfusion parameters (P

Two-dimensional phase unwrapping (2-D PU) is the process of converting the measured phase into the real phase in interferometric signal processing. Reliable unwrapping results are critical for digital elevation model generation using interferometric synthetic aperture radar (InSAR) and interferometric synthetic aperture sonar (InSAS). The majority of previous research has concentrated on accuracy, whereas the computational efficiency must be taken into account for the interferometric measurement system that requires real-time processing. This article proposes a low-time-consuming algorithm that can accomplish high-precision 2-D PU for this application scenario. The neural network and a new path-based 2-D PU algorithm make up this algorithm. First, the incorrect region in the gradient field is predicted and corrected using the neural network. The output channelwise variance is then calculated and used to generate the quality maps. Finally, to achieve phase reconstruction, the path-based algorithm performs path planning and flooding integral according to quality maps and compensated gradient. This article also provides a recommended data structure implementation to ensure the algorithm's high efficiency. Experimental results using InSAR and InSAS data show that the proposed algorithm is highly efficient and accurate.

Abstract Background Schizophrenia (SCZ) is a severe and chronic psychiatric disorder with premature age-related physiological changes. However, numerous previous studies examined the epigenetic age acceleration in SCZ patients and yielded inconclusive results. In this study, we propose to explore the epigenetic age acceleration in drug-naive first-episode SCZ (FSCZ) patients and investigate whether epigenetic age acceleration is associated with antipsychotic treatment, psychotic symptoms, cognition, and subcortical volumes. Methods We assessed the epigenetic age in 38 drug-naive FSCZ patients and 38 healthy controls by using three independent clocks, including Horvath, Hannum and Levine algorithms. The epigenetic age measurements in SCZ patients were repeated after receiving 8 weeks risperidone monotherapy. Results Our findings showed significantly positive correlations between epigenetic ages assessed by three clocks and chronological age in both FSCZ patients and healthy controls. Compared with healthy controls, drug-naive FSCZ patients have a significant epigenetic age deceleration in Horvath clock (p = 0.01), but not in Hannum clock (p = 0.07) and Levine clock (p = 0.43). The epigenetic ages of Hannum clock (p = 0.002) and Levine clock (p = 0.01) were significantly accelerated in SCZ patients after 8-week risperidone treatment. However, no significant associations between epigenetic age acceleration and psychotic symptoms, cognitive function, as well as subcortical volumes were observed in FSCZ patients. Conclusion These results demonstrate that distinct epigenetic clocks are sensitive to different aspects of aging process. Further investigations with comprehensive epigenetic clock analyses and large samples are required to confirm our findings.

In this paper, based on the topological description method, the kinematic and dynamic equations of the projectile flight and projectile-artillery coupling system during the whole process of firing are constructed. The factors that can affect the projectile burst points, namely the state parameters of the projectile on the muzzle and state parameters of the barrel muzzle, as well as the factors that affect the barrel muzzle state parameters, are analyzed. On this basis, the design principle of artillery firing accuracy is proposed. The error analysis and the corresponding inverse problem, the extraction method of key parameters affecting artillery implicated motion, the conformal and control method of rotating band are analyzed and presented. Finally, the presented method is verified through a vehicle mounted howitzer case, and the muzzle state parameter interval is obtained meeting the given firing accuracy. In addition, the sensitivity analysis of artillery parameters shows that the less the correlation between the parameters and the barrel, the less the influence on the projectile implicated motion. The analysis of the coupling effect between rifling and the rotating band shows that the uniform rifling is the optimal form for the conformal of the rotating band during firing.

Summary: Background: China has approximately 300 million current smokers, and smoking cessation services are limited. This study aimed to assess the efficacy of a Cognitive Behavioral Theory-based smoking cessation intervention (‘WeChat WeQuit’) via the most popular social media platform in China, WeChat. Methods: A parallel, single-blind, two-arm randomised controlled trial was conducted via WeChat between March 19, 2020 and November 16, 2022. Chinese-speaking adult smokers (n = 2000) willing to quit within one month were recruited and randomised in a 1:1 ratio. The intervention group (n = 1005) received the ‘WeChat WeQuit’ program and the control group (n = 955) received control messages for 14 weeks (2-week prequit and 12-week postquit). Participants were followed up to 26 weeks after the quit date. The primary outcome was self-reported continuous smoking abstinence rate, biochemically validated at 26 weeks. The secondary outcomes were self-reported 7-day and continuous abstinence rates at 6 months. All analyses were by intention to treat. The trial is registered at ClinicalTrials.gov (NCT03169686). Findings: By intention-to-treat analysis, the biochemically verified 26-week continuous abstinence rate was 11.94% in the intervention group and 2.81% in the control group (OR = 4.68, 95% CI: 3.07–7.13, p

With the development of modern military technology, electrical drive technology has become a power source for modern artillery. In fault monitoring of a driving motor mounted on a piece of artillery, various sensors are susceptible to interference from the complex environment, both inside and outside the artillery itself. In this study, we creatively propose a fault diagnosis model based on an attention mechanism, the AdaBoost method and a wavelet noise reduction network to address the difficulty in obtaining high-quality motor signals in complex noisy interference environments. First, multiple fusion wavelet basis, soft thresholding, and index soft filter optimization were used to train multiple wavelet noise reduction networks that could recover sample signals under different noise conditions. Second, a convolutional neural network (CNN) classification module was added to construct end-to-end classification models that could correctly identify faults. The above basis classification models were then integrated into the AdaBoost method with an improved attention mechanism to develop a fault diagnosis model suitable for complex noisy environments. Finally, two experiments were conducted to validate the proposed method. Under motor signals with varying signal-to-noise ratios (SNRs) noises, the proposed method achieved an average accuracy of 92%, surpassing the conventional method by over 8.5%.

Abstract Individuals at Clinical High Risk for Psychosis (CHR-P) demonstrate heterogeneity in clinical profiles and outcome features. However, the extent of neuroanatomical heterogeneity in the CHR-P state is largely undetermined. We aimed to quantify the neuroanatomical heterogeneity in structural magnetic resonance imaging measures of cortical surface area (SA), cortical thickness (CT), subcortical volume (SV), and intracranial volume (ICV) in CHR-P individuals compared with healthy controls (HC), and in relation to subsequent transition to a first episode of psychosis. The ENIGMA CHR-P consortium applied a harmonised analysis to neuroimaging data across 29 international sites, including 1579 CHR-P individuals and 1243 HC, offering the largest pooled CHR-P neuroimaging dataset to date. Regional heterogeneity was indexed with the Variability Ratio (VR) and Coefficient of Variation (CV) ratio applied at the group level. Personalised estimates of heterogeneity of SA, CT and SV brain profiles were indexed with the novel Person-Based Similarity Index (PBSI), with two complementary applications. First, to assess the extent of within-diagnosis similarity or divergence of neuroanatomical profiles between individuals. Second, using a normative modelling approach, to assess the ‘normativeness’ of neuroanatomical profiles in individuals at CHR-P. CHR-P individuals demonstrated no greater regional heterogeneity after applying FDR corrections. However, PBSI scores indicated significantly greater neuroanatomical divergence in global SA, CT and SV profiles in CHR-P individuals compared with HC. Normative PBSI analysis identified 11 CHR-P individuals (0.70%) with marked deviation (>1.5 SD) in SA, 118 (7.47%) in CT and 161 (10.20%) in SV. Psychosis transition was not significantly associated with any measure of heterogeneity. Overall, our examination of neuroanatomical heterogeneity within the CHR-P state indicated greater divergence in neuroanatomical profiles at an individual level, irrespective of psychosis conversion. Further large-scale investigations are required of those who demonstrate marked deviation.

Summary: Genetics have nominated many schizophrenia risk genes and identified convergent signals between schizophrenia and neurodevelopmental disorders. However, functional interpretation of the nominated genes in the relevant brain cell types is often lacking. We executed interaction proteomics for six schizophrenia risk genes that have also been implicated in neurodevelopment in human induced cortical neurons. The resulting protein network is enriched for common variant risk of schizophrenia in Europeans and East Asians, is down-regulated in layer 5/6 cortical neurons of individuals affected by schizophrenia, and can complement fine-mapping and eQTL data to prioritize additional genes in GWAS loci. A sub-network centered on HCN1 is enriched for common variant risk and contains proteins (HCN4 and AKAP11) enriched for rare protein-truncating mutations in individuals with schizophrenia and bipolar disorder. Our findings showcase brain cell-type-specific interactomes as an organizing framework to facilitate interpretation of genetic and transcriptomic data in schizophrenia and its related disorders.

Abstract Studies of schizophrenia (SCZ) have associated auditory verbal hallucinations (AVH) with structural and functional abnormalities in frontal cortex, especially medial prefrontal cortex (mPFC). Although abnormal prefrontal network connectivity associated with language production has been studied extensively, the relationship between mPFC dysfunction (highly relevant to the pathophysiology of SCZ) and AVH has been rarely investigated. In this study, proton magnetic resonance spectroscopy was used to measure metabolite levels in the mPFC in 61 SCZ patients with persistent AVH (pAVH), 53 SCZ patients without AVH (non-AVH), and 59 healthy controls (HC). The pAVH group showed significantly lower levels of N-acetyl-aspartate + N-acetyl-aspartyl-glutamate (tNAA) and glutamate + glutamine (Glx), compared with the non-AVH (tNAA: p = 0.022, Glx: p = 0.012) and HC (tNAA: p = 0.001, Glx: p = 0.001) groups. No difference was found in the levels of tNAA and Glx between non-AVH and HC. The levels of tNAA and Glx in the mPFC was negatively correlated with the severity of pAVH (tNAA: r = −0.24, p = 0.014; Glx: r = −0.30, p = 0.002). In conclusion, pAVH in SCZ patients might be related to decreased levels of tNAA and Glx in the mPFC, indicating that tNAA or Glx might play a key role in the pathogenesis of pAVH.

Abstract Larger thalamic volume has been found in children with obsessive-compulsive disorder (OCD) and children with clinical-level symptoms within the general population. Particular thalamic subregions may drive these differences. The ENIGMA-OCD working group conducted mega- and meta-analyses to study thalamic subregional volume in OCD across the lifespan. Structural T1-weighted brain magnetic resonance imaging (MRI) scans from 2649 OCD patients and 2774 healthy controls across 29 sites (50 datasets) were processed using the FreeSurfer built-in ThalamicNuclei pipeline to extract five thalamic subregions. Volume measures were harmonized for site effects using ComBat before running separate multiple linear regression models for children, adolescents, and adults to estimate volumetric group differences. All analyses were pre-registered ( https://osf.io/73dvy ) and adjusted for age, sex and intracranial volume. Unmedicated pediatric OCD patients (

Introduction China has more than 300 million current smokers. There is a controversy over smokers’ risk of COVID-19 infection. Smoking is a risk factor for COVID-19 disease progression, and the outbreak of COVID-19 may change people’s smoking behaviors. This study assessed people’s attitudes towards ‘smoking and COVID-19’ and changes of smoking behaviors before and after the outbreak of COVID-19. Material and Methods A cross-sectional web survey of 11009 adults in China was conducted between 7 May and 3 August 2020. Attitudes towards ‘smoking and COVID-19’ were compared among non-smokers (n=8837), ex-smokers (n=399) and current smokers (n=1773), and changes in smoking behaviors before and after the outbreak of COVID-19 were assessed among current smokers. Results Fewer current smokers (26.2%) agreed with the statement that ‘Current smokers are more likely than ex-smokers or non-smokers to contract COVID-19’ compared with non-smokers (53%) or ex-smokers (41.4%); fewer current smokers (55.9%) agreed with the statement ‘If contracted, current smokers are more likely than ex-smokers or non-smokers to risk disease progression’ compared with nonsmokers (75.5%) or ex-smokers (68.7%). There were no changes in cigarettes smoked per day (mean ± SD: 13.3 ± 9.55 vs 13.4 ± 9.69, p=0.414), percentage of daily smokers (70.8% vs 71.1%, p=0.882) and percentage of smokers with motivation to quit (intend to quit within the next 6 months, 9.4% vs 10.9%, p=0.148) before and after the outbreak of COVID-19. Conclusions The survey found that fewer current smokers agreed that smoking is a risk-factor for COVID-19 compared with non-smokers or ex-smokers. Among current smokers, there were no changes in their cigarette consumption and motivation to quit before and after the outbreak of COVID-19. More efforts are needed to educate smokers about the health risks of smoking, as well as efforts to promote their motivation to quit.

To improve the imaging quality of conventional imaging algorithms without motion compensation (MOCO) and the efficiency of point-by-point MOCO algorithms for multiple-receiver synthetic aperture sonar (SAS) with azimuth-invariant six-degree of freedom (DOF) motion errors, an azimuth-invariant MOCO and imaging chirp scaling (CS) algorithm is presented in this paper. Taylor series approximation is used to process the range history in double square root form, while considering the fourth-order and inner terms with respect to the azimuth time. Using the method of series reversion and Fourier transform (FT) properties, the analytical two-dimensional frequency spectrum of the point target response of each receiver is derived. On this basis, the azimuth-invariant MOCO and imaging CS algorithm is proposed for six-DOF motion error compensation and multiple-receiver SAS imaging. Because it considers the azimuth-invariant six-DOF motion errors, the proposed algorithm has better imaging quality than conventional imaging algorithms without MOCO. Additionally, it has a significantly higher efficiency than point-by-point MOCO algorithms because the CS algorithm is a fast FT-based algorithm and does not require interpolation processing. The imaging simulation and experimental results verified the effectiveness and efficiency of the proposed algorithm.

Precise orientation information facilitates target recognition of sonar images. Traditional orientation estimation methods, including the Hough transform method, have poor antinoise abilities, so they cannot achieve high estimation precision for sonar images, which usually have low signal-to-noise ratios. The convolutional neural network (CNN) regression method is sensitive to image affine transformations and requires extensive computation, so it cannot achieve strong robustness or high speed. To achieve high-precision, high-speed, and robust orientation estimation of sonar image targets, we present a novel orientation estimation method via the wavelet subimage energy ratio (WSER). The WSER varies with the rotation angles of images and has the highest value when the long axes of targets are vertical. It is translational and scale invariant and does not need supervised training. Therefore, we propose estimating orientations of sonar image targets by finding the max of the WSER to achieve high precision, high speed, and strong robustness to the translation and scale transformations of images. The results of experiments on a self-made sonar image dataset show that the mean absolute error (MAE) of the proposed method is 7.9°, while the MAEs of the CNN regression method and traditional methods are 10.1 and 22.9°, respectively. In addition, the proposed method is six times faster than the CNN regression method. The proposed orientation estimation method has also been applied to align the orientation of sonar images and CNN can achieve state-of-the-art performance for rotated target recognition using the aligned images. Data and codes are publicly available.

Background The risk of major depressive disorder (MDD) and insomnia is higher in patients with coronary heart disease (CHD) than in the general population. In addition, immune inflammation may be a shared aetiological factor for mental disorders and CHD. However, it is unclear whether MDD is associated with poor sleep quality and cell-mediated immune function in patients with CHD.Aims This study investigated the impact of depression on sleep quality and cell-mediated immune functions in patients with CHD and examined discriminative factors in patients with CHD with and without MDD.Methods This cross-sectional retrospective study was conducted at the Zhejiang University School of Medicine affiliated with Sir Run Run Shaw Hospital. The study population consisted of 84 patients with CHD assigned to two groups based on their Hamilton Depression Rating Scale (HAMD) score (CHD with MDD (HAMD score of ≥10) vs without MDD). Subjective sleep quality, systemic inflammatory response and cell-mediated immune functions were assessed in patients with CHD with (n=50) and without (n=34) MDD using the Pittsburgh Sleep Quality Index (PSQI), routine blood tests and flow cytometry. The relationships between variables were ascertained using Pearson’s product–moment, and linear discriminant analysis was used to explore the discriminative factors between groups.Results Patients with CHD with MDD had significantly poorer sleep quality than those without MDD (Z=−6.864, p

Background A high attrition rate in medical students has exacerbated the physician shortage in China. However, few studies have explored the risk factors of dropout intention in medical postgraduates. This study compared the prevalence of dropout intention and mental distress between medical and non-medical postgraduates in China and investigated risk factors for dropout intention. This study also explored the impact of medical postgraduates’ perception of the Chinese healthcare environment on their mental status and dropout intention.Methods This cross-sectional study was conducted using online questionnaires from October 2020 to April 2021. Convenience sampling was used to recruit postgraduates in different majors. Outcomes included dropout intention and potential risk factors, including mental distress, quality of life, and fatigue. Medical postgraduates were additionally assessed for healthcare environment satisfaction, burnout, career choice regret, and experiences of workplace violence. A logistic regression model was constructed to evaluate the association between dissatisfaction, mental distress, and turnover intention.Results A total of 740 medical and 670 non-medical postgraduates participated in the survey. The rates of depression symptoms (33.8% vs. 39.0%, p

BackgroundNurses are at high risk for depression and anxiety symptoms after the outbreak of the COVID-19 pandemic. We aimed to assess the network structure of anxiety and depression symptoms among Chinese nurses in the late stage of this pandemic.MethodA total of 6,183 nurses were recruited across China from Oct 2020 to Apr 2021 through snowball sampling. We used Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder scale-7 (GAD-7) to assess depression and anxiety, respectively. We used the Ising model to estimate the network. The index “expected influence” and “bridge expected influence” were applied to determine the central symptoms and bridge symptoms of the anxiety-depression network. We tested the stability and accuracy of the network via the case-dropping procedure and non-parametric bootstrapping procedure.ResultThe network had excellent stability and accuracy. Central symptoms included “restlessness”, “trouble relaxing”, “sad mood”, and “uncontrollable worry”. “Restlessness”, “nervous”, and “suicidal thoughts” served as bridge symptoms.ConclusionRestlessness emerged as the strongest central and bridge symptom in the anxiety-depression network of nurses. Intervention on depression and anxiety symptoms in nurses should prioritize this symptom.

Uncompensated motion errors can seriously affect the imaging quality of synthetic aperture sonars (SASs). In the existing line-by-line motion compensation (MOCO) algorithms for wide-beam multiple-receiver SAS systems, the approximate form of the range history error usually introduces a significant approximation error, and the residual two-dimensional (2D) range cell migration (RCM) caused by aperture-dependent motion errors is not corrected, resulting in the severe defocus of the image. In this paper, in the presence of translational and rotational errors in a multiple-receiver SAS system, the exact range history error concerning the five-degree-of-freedom (DOF) motion errors of the sway, heave, yaw, pitch, and roll under the non-stop-hop-stop case is derived. Based on this, a two-stage subaperture MOCO algorithm for wide-beam multiple-receiver SAS systems is proposed. We decompose the range history error into the beam-center term (BCT) and the residual spatial-variant term (RSVT) to compensate successively. In the first stage, the time delay and phase error caused by the BCT are compensated receiver-by-receiver through interpolation and phase multiplication in the azimuth-time domain. In the second stage, the data of a single pulse are regarded as a subaperture, and the RSVT is compensated in the subaperture range-Doppler (RD) domain. We divide the range into several blocks to correct RCM caused by the RSVT in the subaperture RD domain, and the phase error caused by the RSVT is compensated by phase multiplication. After compensation, the wide-beam RD algorithm is used for imaging. Simulated and real-data experiments verify the superiority and robustness of the proposed algorithm.

In existing imaging algorithms for wide-beam multiple-receiver synthetic aperture sonar (SAS) systems, the double-square-root (DSR) range history of each receiver is generally converted into the sum of a single-square-root (SSR) range history and an error term using displaced phase center aperture (DPCA) approximation. Therefore, before imaging, each receiver’s error term needs to be individually compensated in the azimuth frequency domain, which is computationally expensive. As a result, a novel wide-beam multiple-receiver SAS system algorithm with low complexity and high precision is suggested. First, the translation relationship between the range histories of the reference receiver and other receivers is used to derive an SSR approximation range history that takes into account the azimuth variance of the non-stop-hop-stop time while ignoring differential range curvature (DRC) between the range histories from different receivers. Then, using the principle of stationary phase (POSP), the two-dimensional (2-D) spectrum of the point target is obtained. Finally, the multiple-receiver data are transformed into monostatic SAS-equivalent data for imaging after phase correction, time delay correction, and azimuth reconstruction. The range-Doppler (RD) algorithm is used as an example to explain the specific steps of the proposed approach. Simulation data and ChinSAS data experiments verify that the proposed algorithm achieves an imaging performance that is comparable to that of the existing wide-beam algorithm, but with much higher computational efficiency, making it suitable for real-time imaging.

Abstract Methamphetamine (MA) could induce functional and structural brain alterations in dependent subjects. However, few studies have investigated resting-state activity in methamphetamine-dependent subjects (MADs). We aimed to investigate alterations of brain activity during resting-state in MADs using fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo). We analyzed fALFF and ReHo between MADs (n = 70) and healthy controls (HCs) (n = 84) and performed regression analysis using MA use variables. Compared to HCs, abstinent MADs showed increased fALFF and ReHo values in the bilateral striatum, decreased fALFF in the left inferior frontal gyrus, and decreased ReHo in the bilateral anterior cingulate cortex, sensorimotor cortex, and left precuneus. We also observed the fALFF values of bilateral striatum were positively correlated with the age of first MA use, and negatively correlated with the duration of MA use. The fALFF value of right striatum was also positively correlated with the duration of abstinence. The alterations of spontaneous cerebral activity in abstinent MADs may help us probe into the neurological pathophysiology underlying MA-related dysfunction and recovery. Since MADs with higher fALFF in the right striatum had shorter MA use and longer abstinence, the increased fALFF in the right striatum might implicate early recovery during abstinence.

Auditory verbal hallucinations (AVHs) are one of the most common and severe symptoms of schizophrenia (SCZ), but the neuroanatomical mechanisms underlying AVHs remain unclear. This study aimed to investigate whether persistent AVHs (pAVH) are associated with cortical thinning of certain brain regions in patients with SCZ. With the use of the 3T magnetic resonance imaging (MRI) technology, we acquired and analyzed data from 79 SCZ patients with pAVH (pAVH group), 60 SCZ patients without AVHs (non-AVH group), and 83 healthy controls (HC group). The severity of pAVH was assessed by the P3 hallucination items in the Positive and Negative Syndrome Scale (PANSS) and the Auditory Hallucinations Rating Scale (AHRS). Cortical thickness analysis was used to compare the region of interest (ROI) cortical thickness between the groups. The relationship between the severity of pAVH and cortical thickness was also explored. Compared with the non-AVH and HC groups, the pAVH group exhibited significantly reduced cortical thickness in the bilateral lateral orbitofrontal region (p < 0.0007, after Bonferroni correction); no significant difference was found between the non-AVH group and the HC group. The cortical thickness of the left lateral orbitofrontal cortex (P3: r = −0.44, p < 0.001; AHRS: r = −0.45, p < 0.001) and the right lateral orbitofrontal cortex (P3: r = −0.36, p = 0.002; AHRS: r = −0.33, p = 0.004) were negatively correlated with the severity of pAVH (after Bonferroni correction, p < 0.0125). Therefore, abnormal thickness of the bilateral lateral orbitofrontal cortices might be associated with pAVHs in SCZ patients.

It has been claimed that individuals with schizophrenia have difficulty in self-recognition and, consequently, are unable to identify the sources of their sensory perceptions or thoughts, resulting in delusions, hallucinations, and unusual experiences of body ownership. The deficits also contribute to the enhanced rubber hand illusion (RHI; a body perception illusion, induced by synchronous visual and tactile stimulation). Evidence based on RHI paradigms is emerging that auditory information can make an impact on the sense of body ownership, which relies on the process of multisensory inputs and integration. Hence, we assumed that auditory verbal hallucinations (AVHs), as an abnormal auditory perception, could be linked with body ownership, and the RHI paradigm could be conducted in patients with AVHs to explore the underlying mechanisms. In this study, we investigated the performance of patients with/without AVHs in the RHI. We administered the RHI paradigm to 80 patients with schizophrenia (47 with AVHs and 33 without AVHs) and 36 healthy controls. We conducted the experiment under two conditions (synchronous and asynchronous) and evaluated the RHI effects by both objective and subjective measures. Both patient groups experienced the RHI more quickly and strongly than HCs. The RHI effects of patients with AVHs were significantly smaller than those of patients without AVHs. Another important finding was that patients with AVHs did not show a reduction in RHI under asynchronous conditions. These results emphasize the disturbances of the sense of body ownership in schizophrenia patients with/without AVHs and the associations with AVHs. Furthermore, it is suggested that patients with AVHs may have multisensory processing dysfunctions and internal timing deficits.

BackgroundPrevious research has suggested that mobile phone applications (apps) may potentially increase quit rates. The purpose of this single-group cohort study sought to examine the feasibility and acceptability of a novel smartphone-based smoking cessation app designed for smoking cessation in China: smoking quit rate.MethodsA total of 180 smokers from two cities of mainland China with willingness to make a quit attempt were invited to this smoking cessation app program, a cognitive behavioral theory (CBT)-based smoking cessation intervention via a smartphone app. Participants received 37- to 44-day intervention (including 7- to 14-day pre-quit preparation and 33-day intervention from quit date). Feasibility and acceptability of the program, and smoking status were assessed at baseline stage (initial installation), pre-quit stage, and post-quit stage (days 7, 15, and 33 after quit date).ResultsA total of 163 (90.6%) participants completed the study. Among them, 76–89% of the participants logged into the app ≥1 time per day across stages (at baseline, during pre-quit stage, and on days 7, 15, and 33 of post-quit stage); approximately 90% of the participants were satisfied with the app across stages. A significant rise in self-reported overall satisfaction with the app is observed from baseline (93% at Time 1) to the end of the program (98% at Time 2, 33 days after quit date) (p = 0.021). Participants who believed/agreed this app can help them to quit smoking significantly increased from 69% at baseline to 97% at day 33 after quit date (p < 0.001). Participants were satisfied with most (80–90%) of the features, especially the information feature. Intention-to-treat analysis showed that the percentage of 33-day self-reported continuous prevalence abstinence was 63.9%, and 7-day point prevalence abstinence rate was 81.7, 87.2, and 77.8% on days 7, 15, and 33 after quit date, respectively.ConclusionsThis study demonstrated the feasibility and acceptability of the smartphone app intervention for smoking cessation and introduced a new digital treatment model, which is expected to overcome barriers facing accessing traditional in-person smoking cessation services and extend nationwide smoking cessation services in China.

ObjectiveAnti-epidemic work against coronavirus disease (COVID) has become routine work in China. Our study was intended to investigate the emotional and psychological state of healthcare workers and look for the association between sociodemographic factors/profession-related condition and emotional state.MethodsA cross-sectional survey was conducted online among healthcare workers from various backgrounds. Symptoms of anxiety and depression were assessed by the Chinese versions of the seven-item Generalized Anxiety Disorder (GAD-7) and the nine-item Patient Health Questionnaire (PHQ-9), respectively. Supplementary questions (Supplementary Material) were recorded to describe the participants’ information about workplace violence, profession, and attitude related to the COVID pandemic. Wherever suitable, independent t-test, and one-way ANOVA were performed to detect group differences of GAD-7 and PHQ-9 total scores after grouping by sociodemographic variables, respectively, such as age, gender, marital status, educational level, after-tax income, department category, job title, experience of workplace violence, and anti-epidemic participation. Multiple linear regression analyses (stepwise method) were utilized in order to look for the potential associated factors of GAD-7 and PHQ-9 total scores.ResultsA total of 2,139 questionnaires with valid response were completed. Approximately 86.44% of participants had minimal symptoms of anxiety, 11.08% mild, 1.59% moderate, and 0.89% severe. Meanwhile, 81.34% had minimal symptoms of depression, 14.07% mild, 2.90% moderate, 1.17% moderately severe, and 0.51% severe. Student’s t-test showed that participants with female gender, with experience of workplace violence scored higher on both GAD-7 and PHQ-9, and participants with experience of anti-epidemic front-line work during pandemic scored lower on both GAD-7 and PHQ-9. ANOVA showed that participants aging from 31 to 40, with higher educational level, with middle level of annual after-tax income, with department of internal medicine or surgery, or with middle level of job title scored higher on both GAD-7 and PHQ-9. Regression analyses showed that female gender, high job title, and the experience of workplace violence positively were associated with anxiety or depression. Doctoral education, department (other vs. psychiatry), job enthusiasm, and professional self-identity were negatively associated with anxiety or depression. Additionally, psychological support was negatively associated with depression.ConclusionAs the epidemic prevention and control against COVID-19 become normalized in China, emotional state of healthcare workers deserves extensive attention. Our study revealed that gender, educational level, department category, job title, the experience of workplace violence, job enthusiasm, and professional self-identity are the most important influencing factors of physician’s anxiety and depression. Self-tailored psychological intervention should be based on the predisposing factors above to mentally prepare healthcare workers for this long-lasting battle against COVID-19.

We have established a highly efficient 96-well format based strategy to characterize nanobody (Nb) from an expressed alpaca Nb repertoire by combining heavy-chain antibody variable region gene cloning with Nb expression and reactivity profiling at the single cell level. Individual alpaca B lymphocytes were isolated based on B cell surface marker and membrane type antigen specific antibodies expression by fluorescence activated cell sorting (FACS). Single cell reverse transcription and polymerase chain reaction (PCR) amplification of CH1 and CH2 domain enable the identification and exclusion of B cell clones that express regular antibodies. The corresponding heavy-chain antibody variable region gene transcripts, which are CH1-CH2 domain negative, are then amplified from single B cell clones by nested PCR. Then Nbs were expressed in Escherichia coli cells and four Nbs showed high affinity against Pseudomonas aeruginosa Exotoxin A (PEA). Moreover, two PEA Nbs that recognize unique epitopes on PEA have been successfully applied to protect human cells from PEA induced apoptosis. In summary, our FACS and single cell reverse transcription polymerase chain reaction (RT-PCR) based strategy for identifying recombinant Nbs from single alpaca B cells allows highly efficient and unbiased characterization of the expressed Nb repertoires by sequence analysis, expression and parallel antibody reactivity testing.

The compensation of slant range motion errors needs to be carried out after range pulse compression in the signal processing of multiple-receiver synthetic aperture sonar (SAS). Whereas range pulse compression cannot be performed as the first step in multiple-receiver SAS chirp scaling (CS) algorithm, as it requires the transmitted signal to be linearly frequency modulated. For this reason, it is difficult to combine CS algorithm with motion compensation. Besides, those imaging algorithms based on interpolation, such as range-Doppler algorithm and wavenumber domain algorithm, have plenty of computation load and large phase errors. Aimed at these problems, a CZT algorithm for multiple-receiver SAS in the non-stop-hop-stop mode is proposed in this paper. The proposed algorithm can correct range cell migration utilizing chirp-z transform, which avoids interpolation. Furthermore, the algorithm is easily combined with motion compensation as it can process pulse-compressed data directly. This paper describes the algorithm in 9 key steps, including the principle of correcting range cell migration utilizing chirp-z transform in discrete domain. In the simulation and sea trial data processing, the proposed algorithm provides image quality equal to the CS algorithm, and the algorithm is slightly more efficient than CS algorithm when combined with motion compensation.

BackgroundMethamphetamine and ketamine are commonly used club drugs. Both of them have been reported to mimic psychotic symptoms of schizophrenia. However, the prevalence and detailed features of psychotic symptoms among methamphetamine use disorder (MUD) and ketamine use disorder (KUD) patients are largely unknown. This study aimed to measure psychotic symptoms among patients with MUD and KUD.MethodsA total sample of 842 patients from voluntary drug rehabilitation centers, including 462 MUD patients and 380 KUD patients, were invited to this study. The Positive and Negative Syndrome Scale (PANSS) was applied to assess psychotic symptoms in these two groups of patients.ResultsThe prevalence of psychotic symptoms was significantly higher among MUD patients than KUD patients (75.1 vs. 50.5%, 95% CI: 3.532 – 11.858, p < 0.001). Compared with KUD patients, MUD patients were more likely to experience positive symptoms (PANSS positive scores: 11.5 ± 6.07 vs. 15.1 ± 8.22, P < 0.001) and negative symptoms (PANSS negative scores: 12.4 ± 6.60 vs. 14.5 ± 8.63, P < 0.001), but not general symptoms (PANSS general scores: 31.2 ± 13.90 vs. 32.2 ± 15.13, P < 0.001).ConclusionsThe current study found that more than half of MUD and KUD patients experienced psychotic symptoms, and that patients with MUD are more likely to experience positive and negative symptoms than patients with KUD. The findings provide a new perspective for exploring the neuropathological mechanism of psychotic symptoms of schizophrenia.

Enormous efforts have been made to unveil the etiology of auditory hallucinations (AHs), and multiple genetic and neural factors have already been shown to have their own roles. Previous studies have shown that AHs in schizophrenia vary from those in other disorders, suggesting that they have unique features and possibly distinguishable mechanisms worthy of further investigation. In this review, we intend to offer a comprehensive summary of current findings related to AHs in schizophrenia from aspects of genetics and transcriptome, neurophysiology (neurometabolic and electroencephalogram studies), and neuroimaging (structural and functional magnetic resonance imaging studies and transcriptome–neuroimaging association study). Main findings include gene polymorphisms, glutamate level change, electroencephalographic alterations, and abnormalities of white matter fasciculi, cortical structure, and cerebral activities, especially in multiple regions, including auditory and language networks. More solid and comparable research is needed to replicate and integrate ongoing findings from multidimensional levels.

Background: The outbreak of the novel coronavirus disease 2019 (COVID-19) has become the greatest public health emergency and has attracted global attention. During the COVID-19 pandemic, the negative affect (NA) of elderly patients with substance use disorders (SUDs) has also become a more serious public concern. The current study aims to clarify the NA and its influencing factors in elderly patients with SUDs during the pandemic.Methods: Two psychiatrists conducted semi-structured interviews with 77 SUD patients aged above 50 years to collect their demographical information and certain drug use characteristics. Barratt Impulse Scale and the Positive and Negative Affect Scale were used to obtain information about patients' self-reported impulsivity and NA.Results: Univariate linear regression analysis showed that NA was positively correlated with the frequency of drug use, type of SUDs, cravings during COVID-19, and impulsivity. Multiple linear regression analysis showed that being female, higher frequency of drug use, stronger cravings, and greater impulsiveness jointly accounted for the variation of NA in elderly patients with SUDs.Conclusions: This study confirmed that, during the COVID-19 pandemic, gender, frequency of drug use, cravings, and impulsivity were associated with NA in elderly patients with SUDs. This study provided a theoretical basis for clinicians to reduce the patients' NA.

Abstract Background Sleep problems are common in the general population. Cigarette smoking is common in the general population of China. Examinations of the prevalence of poor sleep quality among Chinese smokers and nonsmokers are still lacking. This study was designed to examine sleep quality and sleep disturbances among cigarette smokers and nonsmokers in the general population in central China. Methods In this population-based sampling project, we used a multi-stage sampling method to recruit survey participants from September 2012 to October 2012 in rural and urban areas of Hunan province, China. A total of 27,300 subjects were sampled from the general population and 26,282 completed the self-report of cigarette smoking characteristics. Cigarette smoker was defined as having smoked ≥100 cigarette in a lifetime and smoked during the last 28 days. Cigarette smoking characteristics were obtained from smokers, including cigarettes per day, years of smoking, quit attempts, and smoking cravings. The Pittsburgh Sleep Quality Index (PSQI) was applied to assess quality of sleep and sleep disturbances (PSQI score > 5). Results Significantly more smokers than nonsmokers demonstrated poor sleep quality and sleep disturbances. Among smokers, linear regression analyses showed that poor sleep was inversely associated with cigarettes per day, and positively associated with years of smoking, quit attempts, and smoking craving. Logistic regression analysis showed that quit attempts and smoking cravings were associated with higher odds of sleep disturbances. Conclusions Sleep disturbances were more prevalent among cigarette smokers than nonsmokers. Smokers also varied in sleep problems on the basis of the characteristics of their smoking. Smokers should be informed about the link between cigarette smoking and poor sleep quality, and should be advised that one of several important health benefits from smoking cessation could be the improvement of sleep quality. Sleep therapy should be recommended as an adjunctive treatment for smoking cessation.

Introduction: Wernicke's encephalopathy (WE) is a severe neurological syndrome often associated with alcoholism. Clinicians tend to ignore WE in other non-alcoholic clinical settings related to malnutrition and thiamine deficiency, resulting in delayed diagnosis. The diagnosis becomes more difficult when WE is secondary to psychiatric illnesses as symptoms can be masked by the primary disease.Case Presentation: We present a case of a 56-year-old female patient with schizophrenia who was admitted to the hospital for mental and behavioral disorder, without history of alcohol. She presented symptoms of ophthalmoplegia and high muscular tension, and the brain MRI showed symmetric lesions in the bilateral basal ganglia and third ventricle. She responded well to thiamine and was discharged on hospital day 22.Conclusion: The psychiatrists should be on the alert for starvation-induced WE, especially for patients suffering from malnutrition. WE is a preventable and treatable disease, so once suspected of WE, patients ought to take adequate supplements of thiamine immediately.