Arf6 anchors Cdr2 nodes at the cell cortex to control cell size at division

Fission yeast cells prevent mitotic entry until a threshold cell surface area is reached. The protein kinase Cdr2 contributes to this size control system by forming multiprotein nodes that inhibit Wee1 at the medial cell cortex. Cdr2 node anchoring at the cell cortex is not fully understood. Through a genomic screen, we identified the conserved GTPase Arf6 as a component of Cdr2 signaling. Cells lacking Arf6 failed to divide at a threshold surface area and instead shifted to volume-based divisions at increased overall size. Arf6 stably localized to Cdr2 nodes in its GTP-bound but not GDP-bound state, and its guanine nucleotide exchange factor (GEF), Syt22, was required for both Arf6 node localization and proper size at division. In arf6Δ mutants, Cdr2 nodes detached from the membrane and exhibited increased dynamics. These defects were enhanced when arf6Δ was combined with other node mutants. Our work identifies a regulated anchor for Cdr2 nodes that is required for cells to sense surface area.

Ultrasound-guided placement of an anchor wire or injection of methylene blue to aid in the intraoperative localization and excision of peripheral lymph nodes in dogs and cats

OBJECTIVE To evaluate ultrasound-guided placement of an anchor wire (AW) or injection of methylene blue (MB) to aid in the intraoperative localization of peripheral lymph nodes in dogs and cats. ANIMALS 125 dogs and 10 cats with a total of 171 lymphadenectomies. PROCEDURES Medical records of dogs and cats that underwent peripheral lymphadenectomies with or without (N) the AW or MB localization technique were reviewed. Data retrieved included clinical, surgical, and histologic findings. The proportions of successful lymphadenectomies, lymph node characteristics, and complications among the 3 groups were analyzed. RESULTS 143 (84%) lymph nodes were successfully excised. Lymphadenectomy success was significantly affected by the localization technique, with 94% for group AW, 87% for group MB, and 72% for group N. Lymph node size was smaller in groups AW and MB, compared with group N. Duration of lymphadenectomy was shorter in group AW, compared with groups MB and N, and in group MB, compared with group N. Intra- (7%) and postoperative (10%) complications and final diagnosis did not significantly differ among groups. CONCLUSIONS AND CLINICAL RELEVANCE Both lymph node localization techniques were highly successful and reduced surgery time, compared with unassisted lymphadenectomy. Specifically, these techniques were effective for localization of normal-sized and nonpalpable lymph nodes and were efficient and practical options for peripheral lymphadenectomies, particularly for those that were small or nonpalpable.

Localization by Salp Swarm Optimization with Doppler Effect in Wireless Sensor Networks

Wireless sensor networks (WSNs) have lately been widely used due to its abundant practice in methods that have to be spread over a large range. In any wireless application, the position precision of node is an important core component. Node localization intends to calculate the geographical coordinates of unknown nodes by the assistance of known nodes. In a multidimensional space, node localization is well-thought-out as an optimization problem that can be solved by relying on any metaheuristic’s algorithms for optimal outputs. This paper presents a new localization model using Salp Swarm optimization Algorithm with Doppler Effect (LOSSADE) that exploit the strengths of both methods. The Doppler effect iteratively considers distance between the nodes to determine the position of the nodes. The location of the salp leader and the prey will get updated using the Doppler shift. The performance validation of the presented approach simulated by MATLAB in the network environment with random node deployment. A detailed experimental analysis takes place and the results are investigated under a varying number of anchor nodes, and transmission range in the given search area. The obtained simulation results are compared over the traditional algorithm along with other the state-of-the-art methods shows that the proposed LOSSADE model depicts better localization performance in terms of robustness, accuracy in locating target node position and computation time.