The August episode of 3-Minute 3Rs.
[LA] Nociception is the sense that tells animals they are encountering a potentially damaging stimulus. In people, we call it pain. Most pain research is done with rodents, but nociception is pretty well conserved beyond mammals. That includes invertebrates, such as the fruit fly. Some work has been done in larval drosophila, but larvae exist in a transient state; any quote unquote pain is therefore transient too. To study longer lasting changes in nociception, University of Sydney researcher Greg Neely recent;y described his lab’s efforts to develop an adult fly model. They took advantage of the fly’s natural aversion to surface temperatures above 42 degrees Celsius, and show that after peripheral injury-in this case, a leg amputation-the flys thermal sensitivity changes in a chronic manner. Looking deeper, they saw evidence of a complex mechanism known as central disinhibition at work, along with a role for a conserved gene called Twist in mediating that chain of events.
You can read more about this potential fly replacement for nociception studies in the journal Scientific Advances.
[NC3Rs] Before starting an experiment, a researcher should always have its end in mind. What is the hypothesis? The experimental objectives? And crucially for animal experiments, what signs indicate the experiment should be stopped to prevent unnecessary suffering? It’s a challenging task though, identifying appropriate humane endpoints, as these should be specific to the animal and model but aren’t always described in detail in the literature. Computers, however, are notoriously good at identifying patterns so researchers at the University of Berlin have investigated whether machine learning could be used to define humane endpoints in mouse models of stroke and sepsis. Data was collated from previous studies, focussing on commonly applied humane endpoints such as loss of body weight, changes in body temperature and the use of a sickness severity score. Using these measures, the machine learning based approach was able to predict whether an animal had a high risk of death, with up to 93% accuracy in the mouse model for stroke and 96% accuracy for sepsis. Notably, machine learning could make these predictions one to two days before a humane endpoint would be reached. And the faster we can identify an animal suffering or in pain, the faster we can intervene.
[NA3RsC] A paper in Journal of BioPhotonics sheds some light on the value of fibered confocal fluorescence microscopy. Fibered confocal fluorescence microscopy is a confocal microscope equipped with a fiber-optic bundle which provides light to organs and tissues, enabling collection of real-time images of biologic processes in live animals. With conventional confocal microscopes, cell imaging is limited due to the difficulty with accessing deep tissues and organs. However, advancements in fiber-optic imaging technologies enables improved visualization of tissues and organs, including blood vessels, vasculature and nerves, and mucosal surfaces of the colon. In addition to the many scientific advantages, fibered confocal fluorescence microscopy also enables 3Rs impact. Each animal can be used as its own control with more information obtained from fewer animals, reducing the total number of animals required and inter-animal variability while increasing statistical validity. Also, in vivo imaging is non-invasive providing a valuable refinement to enabling identification of tissues under pathological conditions and responses to drug treatments. Finally, imaging of human organs and tissues could ultimately replace the use of animals, leading to improved clinical relevance making this a valuable translational tool expected to have increased impact in drug research and development.