Eat-me Signals
Eat-me Signals - Related Videos
05:57
Fat Preference: A Novel Model of Eating Behavior in Rats
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Cited by 9 •
2014
Dietary fat content influences both energy intake and body fat composition in mammals. By examining rats’ preference for high fat food in a series of choice experiments, it is possible to test genetic differences and pharmacological interventions on their preference for high fat food.
01:23
Binge Eating Disorders
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2025
Binge eating disorder is a significant mental health condition characterized by recurrent episodes of excessive food consumption within a short period, accompanied by a perceived loss of control over eating behavior. Unlike occasional overeating, binge eating disorder is marked by distressing emotions such as guilt, shame, and anxiety following binge episodes. The disorder affects individuals across different ages and backgrounds, with profound implications for physical and psychological...
04:48
Control of Eating Behavior Using a Novel Feedback System
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Cited by 22 •
2018
Subjects eat food from a plate placed on a scale connected to a computer that records the weight loss of the plate during the meal. Feedback on the computer screen allows the subject to adapt her/his eating behavior to reference curves thus normalizing body weight.
04:19
A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis
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2022
Diagnosing eating disorders in healthcare is challenging. Therefore, the present protocol develops an algorithm based on 949 patient responses to a questionnaire, with the diagnosis displayed on an easy-to-use web-based interface. This system facilitates the accurate diagnosis of eating disorders while excluding those believed to have an eating disorder.
06:21
Concept Development and Use of an Automated Food Intake and Eating Behavior Assessment Method
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Cited by 8 •
2021
This protocol shows and explains a new technology-based dietary assessment method. The method consists of a dining tray with multiple built-in weighing scales and a video camera. The device is unique in the sense that it incorporates automated measures of food and drink intake and eating behavior over the course of a meal.
FAQs
A key change is the relocation of phosphatidylserine from the inner to the outer leaflet of the plasma membrane. This exposure provides a surface cue associated with apoptosis or cellular damage. Phagocytes can then detect that altered membrane state through recognition machinery, linking a cell’s condition to its selective removal.
Dedicated receptors on phagocytes participate in recognizing altered cells, while bridging molecules help connect the surface cue with the phagocyte’s recognition system. Together, these components translate a molecular change on the target cell into a cellular response. Their cooperation helps determine which cells are selected for engulfment rather than remaining in surrounding tissue.
Controlled recognition allows dying or damaged cells to be removed without excessive inflammation. This balance supports tissue health while limiting unnecessary immune activation. Because eat-me signals connect cellular damage with phagocytic clearance, studying them helps explain how organisms maintain orderly tissue maintenance and regulate immune responses during cell removal.
Recognition initiates phagocytosis, the process by which a phagocyte encloses the target cell. The engulfed material becomes enclosed within a phagosome, a compartment associated with subsequent degradation and recycling. This sequence converts surface recognition into physical disposal and recovery of cellular material, completing an important stage of tissue maintenance.
A study can follow the sequence from surface-membrane change to phagocyte recognition, engulfment, phagosome formation, and eventual degradation or recycling. Examining these linked events helps distinguish the molecular cue from the later clearance stages. This framework is useful for analyzing how apoptosis or cellular damage leads to orderly removal rather than persistent material in tissue.
Research on these signals connects cell clearance with immune regulation, autoimmune disease, cancer, infection, and therapeutic strategies that alter cellular removal. The same recognition process can therefore be examined in both normal tissue maintenance and disease-related contexts. Its relevance comes from understanding how changing clearance may influence inflammation, immune balance, or the persistence of damaged cells.