Gaze understanding—a suggested precursor for understanding others’ intentions—requires recovery of gaze direction from the observed person's head and eye position. This challenging computation is naturally acquired at infancy without explicit external guidance, but can it be learned later if vision is extremely poor throughout early childhood? We addressed this question by studying gaze following in Ethiopian patients with early bilateral congenital cataracts diagnosed and treated by us only at late childhood. This sight restoration provided a unique opportunity to directly address basic issues on the roles of “nature” and “nurture” in development, as it caused a selective perturbation to the natural process, eliminating some gaze-direction cues while leaving others still available. Following surgery, the patients’ visual acuity typically improved substantially, allowing discrimination of pupil position in the eye. Yet, the patients failed to show eye gaze-following effects and fixated less than controls on the eyes—two spontaneous behaviors typically seen in controls. Our model for unsupervised learning of gaze direction explains how head-based gaze following can develop under severe image blur, resembling preoperative conditions. It also suggests why, despite acquiring sufficient resolution to extract eye position, automatic eye gaze following is not established after surgery due to lack of detailed early visual experience. We suggest that visual skills acquired in infancy in an unsupervised manner will be difficult or impossible to acquire when internal guidance is no longer available, even when sufficient image resolution for the task is restored. This creates fundamental barriers to spontaneous vision recovery following prolonged deprivation in early age.
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http://dx.doi.org/10.1073/pnas.2117184119 | DOI Listing |
BMC Oral Health
January 2025
Department of Clinical Dentistry, Faculty of Medicine, University of Bergen, Bergen, Norway.
Background: In the last years, artificial intelligence (AI) has contributed to improving healthcare including dentistry. The objective of this study was to develop a machine learning (ML) model for early childhood caries (ECC) prediction by identifying crucial health behaviours within mother-child pairs.
Methods: For the analysis, we utilized a representative sample of 724 mothers with children under six years in Bangladesh.
BMC Med Imaging
January 2025
Department of Information Technology, Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.
Problem: Breast cancer is a leading cause of death among women, and early detection is crucial for improving survival rates. The manual breast cancer diagnosis utilizes more time and is subjective. Also, the previous CAD models mostly depend on manmade visual details that are complex to generalize across ultrasound images utilizing distinct techniques.
View Article and Find Full Text PDFNPJ Syst Biol Appl
January 2025
Center for Interdisciplinary Digital Sciences (CIDS), Department Information Services and High-Performance Computing (ZIH), Dresden University of Technology, 01062, Dresden, Germany.
Predicting the biological behavior and time to recurrence (TTR) of high-grade diffuse gliomas (HGG) after maximum safe neurosurgical resection and combined radiation and chemotherapy plays a pivotal role in planning clinical follow-up, selecting potentially necessary second-line treatment and improving the quality of life for patients diagnosed with a malignant brain tumor. The current standard-of-care (SoC) for HGG includes follow-up neuroradiological imaging to detect recurrence as early as possible and relies on several clinical, neuropathological, and radiological prognostic factors, which have limited accuracy in predicting TTR. In this study, using an in-silico analysis, we aim to improve predictive power for TTR by considering the role of (i) prognostically relevant information available through diagnostics used in the current SoC, (ii) advanced image-based information not currently part of the standard diagnostic workup, such as tumor-normal tissue interface (edge) features and quantitative data specific to biopsy positions within the tumor, and (iii) information on tumor-associated macrophages.
View Article and Find Full Text PDFCarbohydr Polym
March 2025
College of Chemistry and Environment, Southwest Minzu University, Chengdu, Sichuan 610225, China; Key Laboratory of Fundamental Chemistry of the State Ethnic Commission, College of Chemistry and Environment, Southwest Minzu University, Chengdu, Sichuan 610225, China. Electronic address:
Cholesterol (CHO) is an essential lipid in cell membranes and a precursor for vital living substances. Abnormal CHO levels can cause cardiovascular diseases. Therefore, simple and accurate monitoring of CHO levels is crucial for early diagnosis and effective management of cardiovascular diseases.
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