Introduction: Context processing deficiencies have been established in patients with schizophrenia and it has been proposed that these deficiencies are involved in the formation of positive symptoms.
Method: We administered a temporal context discrimination task to 60 schizophrenia patients and 60 healthy individuals. Pictures were presented in two sessions separated by half an hour and the participants were required to remember afterwards whether the pictures had been presented in the first or the second session.
Results: The number of temporal context errors was significantly increased in the patient group. More specifically, it was highly significantly increased in a subgroup of patients presenting hallucinations, while the patients without hallucinations were equivalent to the healthy individuals. Regression analyses revealed that, independently of memory of the pictures themselves, verbal and visual hallucinations, as well as thought disorganisation, were associated with more temporal context errors. In contrast, affective flattening and anhedonia were associated with fewer of these errors.
Conclusion: Inability to process or remember the temporal context of production of events might be a mechanism underlying both hallucinations and thought disorganisation.
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http://dx.doi.org/10.1016/j.schres.2020.03.014 | DOI Listing |
Local Environ
November 2024
SOPPECOM - Society for Promoting Participative Ecosystem Management, Pune, India.
This paper develops the methodological concept of river co-learning arenas (RCAs) and explores their potential to strengthen innovative grassroots river initiatives, enliven river commons, regenerate river ecologies, and foster greater socio-ecological justice. The integrity of river systems has been threatened in profound ways over the last century. Pollution, damming, canalisation, and water grabbing are some examples of pressures threatening the entwined lifeworlds of human and non-human communities that depend on riverine systems.
View Article and Find Full Text PDFCancer Treat Rev
December 2024
Istituto Nazionale Tumori, IRCCS, Fondazione G. Pascale, Napoli, Italy. Electronic address:
Within the expanding therapeutic landscape for breast cancer (BC), metastatic breast cancer (MBC) remains virtually incurable and tend to develop resistance to conventional treatments ultimately leading to metastatic progression and death. Cellular immunotherapy (CI), particularly chimeric antigen receptor-engineered T (CAR-T) cells, has emerged as a promising approach for addressing this challenge. In the wake of their striking efficacy against hematological cancers, CAR-T cells have also been used where the clinical need is greatest - in patients with aggressive BCs.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Shanghai Institute of Satellite Engineering, Shanghai 201109, China.
Accurate and timely air quality forecasting is crucial for mitigating pollution-related hazards and protecting public health. Recently, there has been a growing interest in integrating visual data for air quality prediction. However, some limitations remain in existing literature, such as their focus on coarse-grained classification, single-moment estimation, or reliance on indirect and unintuitive information from visual images.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Instituto de Inovação Tecnológica-IIT, Universidade de Pernambuco-UPE R. Min. Mario Andreaza, s/n-Várzea, Recife 50950-050, PE, Brazil.
Integrating Machine Learning (ML) in industrial settings has become a cornerstone of Industry 4.0, aiming to enhance production system reliability and efficiency through Real-Time Fault Detection and Diagnosis (RT-FDD). This paper conducts a comprehensive literature review of ML-based RT-FDD.
View Article and Find Full Text PDFAnimals (Basel)
December 2024
College of Life Science, Jiangxi Normal University, Nanchang 330022, China.
In the context of global warming and intensified human activities, the loss and fragmentation of species habitats have been exacerbated. In order to clarify the trends in the current and future suitable wintering areas for hooded cranes (), the MaxEnt model was applied to predict the distribution patterns and trends of hooded cranes based on 94 occurrence records and 23 environmental variables during the wintering periods from 2015 to 2024. The results indicated the following.
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