Institute of Psychology, Chinese Academy of Sciences
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Born to Fear the Machine? Genetic and Environmental Influences on Negative Attitudes toward AI Agents
No full textDespite the rapid development of artificial intelligence (AI) agents, substantial individual differences in public acceptance persist. To explain the difference in attitudes toward AI agents, existing research has primarily focused on environmental factors. However, evolutionary psychology research suggests that the mechanism of outgroup rejection has a genetic basis, highlighting the need to explore the potential genetic underpinnings of negative attitudes toward AI agents as an outgroup in human society. This study examines the genetic basis of negative attitudes toward AI agents and their relationship with related personality traits, using a twin study design to assess negative attitudes toward AI agents, victim sensitivity, and moral preferences. Univariate genetic analyses revealed significant heritability of these negative attitudes. Bivariate analyses further identify shared genetic influences between victim sensitivity and personal-level fear and wariness toward robots. Similarly, a shared genetic basis is observed between the moral preferences concerning authority and sociotechnical blindness anxiety toward AI agents. These findings extend the understanding of social cognition in AI agents by emphasizing the role of genetic factors in shaping attitudes toward them. Moreover, they provide new insights for enhancing public acceptance of AI agents and optimizing human-machine interactions
A Bibliometric Analysis of Neuroinflammation in Depression from 2004 to 2023: Global Research Hotspots and Prospects
No full textBackground: Neuroinflammation lays a prominent impact in the pathophysiology of depression, and numerous studies have been conducted in recent decades. Bibliometric analysis is of important for understanding the hot spots and research trends in a certain subject field. However, no systematic bibliometric study exists in this field to date. The purpose of the study focused on the trends and hotspots in neuroinflammation of depression and provided future researchers with guidance and sights. Methods: Publications (2004-2023) were obtained from the WoSCC, and analyzed by HistCite, VOSviewer, CiteSpace, and Bibliometrix. The impact of publications was assessed by TGCS. Results: We analyzed 1,496 articles published in 409 journals and authored by 46,533 researchers across 72 countries and regions. The most prolific countries were China, the USA, and Brazil, and the most cited countries were the USA, followed with China and the UK, while the most prolific and cited institution was University Toronto (records=34, TGCS=2,137). Brain Behavior and Immunity is the leading journal that regularly published research in this field (records=93, TGCS=6,247). NLRP3 inflammasome, microglia, TNF-alpha, and brain-derived neurotrophic factor (BDNF) were the basis of neuroinflammation in depression. C-reactive protein, an important marker of inflammation, has been discussed for the longest time in this disease. In recent five years, two most frontier potential areas in studying depression were gut microbiota dysbiosis and BDNF. Conclusions: There remains a strong research basis for neuroinflammation in depression from this were research hotspots in recent years. In the future, chronic stress, hippocampal structure, and gut microbiota will continue to be studied in the field of neuroinflammation in depression. This study may benefit scientists in identifying potential directions for future study and providing clinicians with new ideas for treatment
Differences in types and causes of human errors between high-speed and conventional railway dispatching: the potential impact of automation
No full textDispatcher errors are critical for railway safety, yet the impact of new technology on error types and causes is less understood. High-speed railways (HSR) utilize advanced automated technologies that enhance efficiency but introduce new challenges. This study analyzed 8522 error records from both HSR and conventional rail (CR) dispatchers using a human error classification framework. We categorized these errors into three key task types: monitoring, planning and scheduling, and dispatching instructions. Results showed that HSR dispatchers make more errors in planning and scheduling tasks, particularly decision-making errors influenced by poor crew resource management and adverse mental states. In contrast, they make fewer errors in monitoring and dispatch instructions, with reduced decision errors and violations. Additionally, skill-based errors were less affected by factors such as personal readiness and supervisory issues. We explained these findings by linking them to how automation reduces procedural workload, decreases controllability and predictability, and induces out-of-the-loop unfamiliarity.</p
Develop of Need-supportive Household Chores Education on the SPSS and AMOS model
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The cognitive assessment of secondary school students’ home learning is a hot spot in the research of school labour education. However, the application of Internet and artificial intelligence technology has brought new challenges. To address these issues, we designed an evaluation system based on SPSS and AMOS to assess secondary school students’ perceptions of supportive home education. Firstly, a questionnaire on the perception of supportive home education was designed. This questionnaire has three dimensions: autonomy support, competence support and association support. Then we used SPSS for statistical analysis of data, correlation analysis and exploratory analysis (EFA). Finally, we used AMOS for validated factor analysis (CFA) and structural equation modelling (SEM). The experimental results showed significant correlations between the questionnaire and its three dimensions. These findings can not only provide a reliable tool for future related research, but also help to deepen the integration of theory and practice.</p
Language Use in Chinese University Students With Depressive Symptoms
No full textThis study examined the language use in Chinese university students with depressive symptoms based on negative and positive memory recall tasks. People with depression used more first-person singular pronouns in the negative memory task and more negative words in both memory tasks
The Genetic Landscape of Acute Necrotizing Encephalopathy: Insights Into the Possible Pathogenesis
No full textBackground and Purpose Acute necrotizing encephalopathy (ANE) is a rare and severe type of parainfectious encephalopathy. The pathogenesis and genetic features of ANE remain underinvestigated. In this study we aimed to characterize the genetic profiles of ANE, including novel variants and pathways. Methods We conducted a retrospective cohort study of 16 ANE patients and 7 controls, collecting clinical data, cerebrospinal fluid (CSF) findings, neuroimaging findings, and treatment information. Whole-exome sequencing (WES) was performed to investigate potential function-impacting genetic mutations in RANBP2, CPT II, and RNH1. Enrichment analyses were conducted to explore the associated pathways. Results The median age of the ANE patients was 21 years, and viral infections such as SARSCoV-2 and influenza were common triggers. The CSF interleukin-6 level was elevated in four patients (median=598 pg/mL, interquartile range=101-4,000 pg/mL). WES identified 278 lowfrequency variants. Four pathogenic/likely pathogenic mutations (p.T585M and p.I656V) and one novel mutation of uncertain significance (p.P2733S) were identified in RANBP2, while the susceptibility alleles of p.F352C and p.V368I in CPT II were detected in three patients. Functional enrichment analyses revealed that, relative to the control group, pathways including nucleocytoplasmic transport, defense response to virus, positive regulation of tumor necrosis factor production, and JAK-STAT signaling pathways were significantly enriched in ANE patients. Conclusions This study integrated genetic profiles with the clinical characteristics of ANE patients, and revealed the role of RANBP2 as well as the potential involvement of cytokine pathways in ANE pathogenesis.</p
Comprehensive Analysis of a Dendritic Cell Marker Genes Signature to Predict Prognosis and Immunotherapy Response in Lung Adenocarcinoma
No full textWith the development of immune checkpoints inhibitors (ICIs), immunotherapy has recently taken center stage in cancer treatment. Dendritic cells exert complicated and important functions in antitumor immunity. This study aims to construct a novel dendritic cell marker gene signature (DCMGS) to predict the prognosis and immunotherapy response of lung adenocarcinoma (LUAD). DC marker genes in LUAD were identified by analysis of single-cell RNA sequencing data. 6 genes (G0S2, KLF4, ALDH2, IER3, TXN, CD69) were screened as the most prognosis-related genes for constructing DCMGS on a training cohort from TCGA data set. Patients were divided into high-risk and low-risk groups by DCMGS risk score based on overall survival time. Then, the predictive ability of the risk model was validated in 6 independent cohorts. DCMGS was verified to be an independent prognostic factor in multivariate analysis. Furthermore, we performed pathway enrichment analysis to explore possible biological mechanisms of the powerful predictive ability of DCMGS, and immune cell infiltration landscape and inflammatory activities were exhibited to reflect the immune profile. Notably, we bridged DCMGS with expression of immune checkpoints and TCR/BCR repertoire diversity that can inflect immunotherapy response. Finally, the predictive ability of DCMGS in immunotherapy response was also validated by 2 cohorts that had received immunotherapy. As a result, the patients with lower DCMGS risk scores showed a better prognosis and immunotherapy response. In conclusion, DCMGS was suggested to be a promising prognostic indicator for LUAD and a desirable predictor for immunotherapy response
Expectation violations signal goals in novel human communication
No full textCommunication, often grounded in shared expectations, faces challenges when a Sender and Receiver lack a common linguistic background. Our study explores how people instinctively turn to the fundamental principles of the physical world to overcome such barriers. Specifically, through an experimental game in which Senders convey messages via trajectories, we investigate how they develop novel strategies without relying on common linguistic cues. We build a computational model based on the principle of expectancy violations and a set of common universal priors derived from movement kinetics. The model replicates participant-designed messages with high accuracy and shows how its core variable-surprise-predicts the Receiver's physiological and neuronal responses in brain areas processing expectation violations. This work highlights the adaptability of human communication, showing how surprise can be a powerful tool in forming new communicative strategies without relying on common language.</p
CELECOXIB ADDED TO RISPERIDONE FOR DEPRESSIVE SYMPTOMS IN FIRST-EPISODE AND DRUG NA? VE SCHIZOPHRENIA: PHARMACOGENETIC IMPACT OF BDNF GENE POLYMORPHISMS-EPISODE AND DRUG NA? VE SCHIZOPHRENIA: PHARMACOGENETIC IMPACT OF BDNF GENE POLYMORPHISMS
No full textSex Differences in the Prevalence and Correlates of Suicide Attempts in Patients with First-Episode and Drug-Na?ve Psychotic Major Depression
No full textPurpose: Sex differences play an important role in depression prevalence, symptom profile, treatment response, and disease course. However, sex differences in factors associated with suicide attempts (SAs) in first-episode and drug-na & iuml;ve (FEDN) patients with psychotic major depression (PMD) remain unclear. Methods: In this study, 171 patients with FEDN PMD were recruited. Patients' symptoms were assessed using the Hamilton Rating Scale for Depression (HAMD), Hamilton Anxiety Rating Scale (HAMA), and Positive and Negative Syndrome Scale (PANSS) positive subscale. In addition, metabolic parameters and thyroid hormone levels were measured. Results: The prevalence of SA was remarkably high in both male and female PMD patients (53.19% vs. 50.81%), without significant differences between the two groups. In male PMD patients, the combination of marital status and thyroid-stimulating hormone (TSH) levels was found to effectively distinguish between SA and non-SA cases, with an AUC value of 0.87. In addition, the HAMD score and diastolic blood pressure (BP) were significantly associated with the frequency of SAs in this subgroup. For female PMD patients, the combination of positive score, diastolic BP, TSH, and antithyroglobulin was found to be an effective discriminator between SA and non-SA cases, with an AUC of 0.91. Furthermore, duration of illness, positive score, systolic BP, and thyroid peroxidase antibody were found to be significantly associated with the frequency of SAs in this subgroup. Conclusions: Our results indicate a high incidence of SAs in both men and women with PMD. Several clinically relevant factors, metabolic parameters, and thyroid hormone function contribute to sex differences in SAs in FEDN PMD patients
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