Reconsolidation theory has supported the notion that active memory is vulnerable to the effects of an amnesic agent. An extension of reconsolidation theory posits that active memory, while necessary for creating vulnerability in memory, is not sufficient. Prediction error (i.e., when expectation is inconsistent with reality) may be a key factor in the destabilization of memory. The present study examined the role of prediction error in appetitive memory reconsolidation. Rats learned to dig in cups of scented sand to retrieve buried sweet cereal rewards. Forty-eight hours following acquisition, a single reactivation trial was given during which a prediction error or no prediction error was included. The prediction error consisted of a single extinction trial, while the no prediction error condition consisted of an additional reinforced trial. Cycloheximide (CHX; 1 mg/kg) or vehicle (VEH: distilled water; 1 mg/kg) was administered intraperitoneally immediately following reactivation. One week following reactivation, rats received 2 nonreinforced test trials. Results showed longer latencies to dig for rats that received CHX following a prediction error (CHX/PE) compared to rats that received VEH (VEH/PE) or did not receive a prediction error (CHX/NoPE or VEH/NoPE). These results add to a growing literature demonstrating that protein synthesis is necessary in appetitive memory reconsolidation only when reactivation includes a prediction error. (PsycINFO Database Record
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ACS Sens
January 2025
Department of Physics and Astronomy, Franklin College of Arts and Sciences, The University of Georgia, Athens, Georgia 30602, United States.
Multiple respiratory viruses can concurrently or sequentially infect the respiratory tract, making their identification crucial for diagnosis, treatment, and disease management. We present a label-free diagnostic platform integrating surface-enhanced Raman scattering (SERS) with deep learning for rapid, quantitative detection of respiratory virus coinfections. Using sensitive silica-coated silver nanorod array substrates, over 1.
View Article and Find Full Text PDFRadiol Med
January 2025
Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
Purpose: Bodyweight loss is commonly found in Nasopharyngeal Carcinoma patients during Concurrent Chemo-radiotherapy (CCRT) and has implications for treatment decisions. However, the prognostic value of this weight loss remains uncertain. We addressed it by proposing a novel index Weight Censorial Score (WCS) that characterizes the patient-specific CCRT response on actual to estimated weight loss.
View Article and Find Full Text PDFRadiology
January 2025
From the Departments of Biomedical Systems Informatics (S.K., Jaewoong Kim, C.H., D.Y.) and Neurology (Joonho Kim, J.Y.), Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea; Department of Radiology, Central Draft Physical Examination Office of Military Manpower Administration, Daegu, Republic of Korea (D.K.); Department of Radiology, Research Institute of Radiological Science and Center for Clinical Imaging Data Science (H.J.S. Y.K., S.J.), and Center for Digital Health (H.J.S., D.Y.), Yongin Severance Hospital, Yonsei University College of Medicine, Yongin, Republic of Korea; Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea (S.H.L.); Departments of Radiology (M.H.) and Neurology (S.J.L.), Ajou University Hospital, Ajou University School of Medicine, Suwon, Republic of Korea; and Institute for Innovation in Digital Healthcare, Severance Hospital, Seoul, Republic of Korea (D.Y.).
Background The increasing workload of radiologists can lead to burnout and errors in radiology reports. Large language models, such as OpenAI's GPT-4, hold promise as error revision tools for radiology. Purpose To test the feasibility of GPT-4 use by determining its error detection, reasoning, and revision performance on head CT reports with varying error types and to validate its clinical utility by comparison with human readers.
View Article and Find Full Text PDFWorld J Gastrointest Surg
January 2025
Department of Colorectal Surgery, Sir Run Shaw Hospital Affiliated with Zhejiang University, Hangzhou 310016, Zhejiang Province, China.
Background: Despite improved survival rates in rectal cancer treatment, many patients experience low anterior resection syndrome (LARS). The preoperative LARS score (POLARS) aims to address the limitations of LARS assessment by predicting outcomes preoperatively to enhance surgical planning.
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Front Radiol
January 2025
Department of Biostatistics & Informatics, Colorado School of Public Health, Aurora, CO, United States.
In neuro-oncology, MR imaging is crucial for obtaining detailed brain images to identify neoplasms, plan treatment, guide surgical intervention, and monitor the tumor's response. Recent AI advances in neuroimaging have promising applications in neuro-oncology, including guiding clinical decisions and improving patient management. However, the lack of clarity on how AI arrives at predictions has hindered its clinical translation.
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