Bilateral lesions of the hypothalamic paraventricular nuclei (PVN) induce hyperphagia and obesity, and ghrelin stimulates appetite in rodents and humans. Conversely, corticotrophin-releasing hormone (CRH) and melanotan-II (MT-II, a synthetic structural homologue of alpha-melanocyte-stimulating hormone, alphaMSH) inhibit feeding behavior. The purpose of the present study was to determine whether these peptides are involved in the hyperphagia and obesity induced by PVN lesions. After bilateral electrolytic lesions of the PVN, rats were given ghrelin intraperitoneally (i. p.), or intracerebroventricular (i. c. v.) infusion of CRH or MT-II. We measured the cumulative food intake (FI) for 4 h after ghrelin injection in rats fed AD LIB, and the changes in FI at 15 min, 30 min, 1 h, and 2 h after infusion of CRH and MT-II in rats fasted for 24 h. Ghrelin significantly increased cumulative FI, with maximal response 3 h and 4 h after injection, and at these times, the FI of PVN-lesioned rats was greater than that of sham-operated rats. CRH significantly decreased FI in all experimental animals, but at 1 h, there was a more powerful inhibitory effect on FI in the PVN-lesioned group than in the sham-operated group. MT-II decreased FI in sham-operated, but not in PVN-lesioned rats. Thus, ghrelin and CRH showed more potent orexigenic and anorectic effects in PVN-lesioned rats, respectively, but MT-II lost its inhibitory action on feeding behavior. These results suggest that the hyperphagia and obesity induced by PVN lesions may be related to an increased orexigenic action of ghrelin due to the destruction of endogenous CRH and alphaMSH receptors.
These results suggest that the hyperphagia and obesity induced by PVN lesions may be related to an increased orexigenic action of ghrelin, but not NPY.
In the past few years, a large range of wireless signals such as WiFi, RFID, UWB and Millimeter Wave were utilized for sensing purposes. Among these wireless sensing modalities, WiFi sensing attracts a lot of attention owing to the pervasiveness of WiFi infrastructure in our surrounding environments. While WiFi sensing has achieved a great success in capturing the target's motion information ranging from coarse-grained activities and gestures to fine-grained vital signs, it still has difficulties in precisely obtaining the target size owing to the low frequency and small bandwidth of WiFi signals. Even Millimeter Wave radar can only achieve a very coarse-grained size measurement. High precision object size sensing requires using RF signals in the extremely high-frequency band (e.g., Terahertz band). In this paper, we utilize low-frequency WiFi signals to achieve accurate object size measurement without requiring any learning or training. The key insight is that when an object moves between a pair of WiFi transceivers, the WiFi CSI variations contain singular points (i.e., singularities) and we observe an exciting opportunity of employing the number of singularities to measure the object size. In this work, we model the relationship between the object size and the number of singularities when an object moves near the LoS path, which lays the theoretical foundation for the proposed system to work. By addressing multiple challenges, for the first time, we make WiFi-based object size measurement work on commodity WiFi cards and achieve a surprisingly low median error of 2.6 mm. We believe this work is an important missing piece of WiFi sensing and opens the door to size measurement using low-cost low-frequency RF signals.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.