Positron emission tomography (PET) is a highly sensitive tool for studying physiology and metabolism through positron-emitting radionuclides that label molecular targets in the body with unparalleled specificity, without disturbing their biological function. Here, we introduce a small-animal technique called behavioral task-associated PET (beta-PET) consisting of two scans: the first after a mouse is familiarized with a conditioning chamber, and the second upon recall of contextual threat. Associative threat conditioning occurs between the scans. Beta-PET focuses on brain regions encoding threat memory (e.g., amygdala, prefrontal cortex) and contextual aspects (e.g., hippocampus, subiculum, entorhinal cortex). Our results show that beta-PET identifies a biologically defined functional network encoding contextual threat memory and its uncoupling in a mouse model of long sepsis. Moreover, machine learning algorithms (linear logistic regression) and ordinal trends analysis demonstrate that beta-PET robustly predicts the behavioral defense response and its breakdown during long sepsis.
The Wash'Em process was developed to improve the design of handwashing behaviour change programmes during outbreaks and humanitarian crises. It aims to rapidly create evidence-based, contextualized handwashing programmes. Wash'Em was widely used during the COVID-19 pandemic.
Fear of threatening contexts often generalizes to similar, safe contexts but few studies have investigated how contextual information influences cue generalization. In this study we explored whether fear responses to cues would generalize more broadly in a threatening compared to a safe context. Forty-seven participants underwent a differential cue-in-context conditioning protocol followed by a generalization test while we recorded psychophysiological and subjective responses.
Gastrointestinal polyps are early indicators of many significant diseases within the digestive system, and timely detection of these polyps is crucial for preventing them. Although clinical gastrointestinal endoscopy and interventions help reduce the risk of malignancy, most current methods fail to adequately address the uncertainties and scale issues associated with the presence of polyps, posing a threat to patients' health. Therefore, this paper proposes a novel single-stage method for polyp detection.
School of Computer Science & Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, Central China Normal University, Wuhan, 430079, China. Electronic address:
Background And Objective: Cervical cancer poses a major health threat to women globally. Optical coherence tomography (OCT) imaging has recently shown promise for non-invasive cervical lesion diagnosis. However, obtaining high-quality labeled cervical OCT images is challenging and time-consuming as they must correspond precisely with pathological results.
Background: Anomaly detection is crucial in healthcare data due to challenges associated with the integration of smart technologies and healthcare. Anomaly in electronic health record can be associated with an insider trying to access and manipulate the data. This article focuses around the anomalies under different contexts.
