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Stimulation of renal collecting duct principal cells with antidiuretic hormone (arginine-vasopressin, AVP) results in inhibition of the small GTPase RhoA and the enrichment of the water channel aquaporin-2 (AQP2) in the plasma membrane. The membrane insertion facilitates water reabsorption from primary urine and fine-tuning of body water homeostasis. Rho guanine nucleotide exchange factors (GEFs) interact with RhoA, catalyze the exchange of GDP for GTP and thereby activate the GTPase. However, GEFs involved in the control of AQP2 in renal principal cells are unknown. The A-kinase anchoring protein, AKAP-Lbc, possesses GEF activity, specifically activates RhoA, and is expressed in primary renal inner medullary collecting duct principal (IMCD) cells. Through screening of 18,431 small molecules and synthesis of a focused library around one of the hits, we identified an inhibitor of the interaction of AKAP-Lbc and RhoA. This molecule, Scaff10-8, bound to RhoA, inhibited the AKAP-Lbc-mediated RhoA activation but did not interfere with RhoA activation through other GEFs or activities of other members of the Rho family of small GTPases, Rac1 and Cdc42. Scaff10-8 promoted the redistribution of AQP2 from intracellular vesicles to the periphery of IMCD cells. Thus, our data demonstrate an involvement of AKAP-Lbc-mediated RhoA activation in the control of AQP2 trafficking.
A Case Study of the Use of Logical Data Analysis in the Workmen’s Village in Tell el-Amarna, Egypt
(2025)
The search for patterns in archaeological contexts is crucial to understanding ancient
civilizations, including the organization of their societies and economies. This study
focuses on the interdisciplinary application of mathematical logical data analysis to
Egyptology, particularly examining food production in the Workmen’s Village of
Amarna. The introduction provides historical context about Amarna, founded by
Pharaoh Akhenaten, and outlines the settlement structure and excavations of the
Workmen’s Village. The research utilizes archaeobotanical and archaeological data,
along with digital humanities tools, to identify activity areas related to food production.
The findings reveal spatial patterns in the distribution of tools such as mortars, pestles,
and ovens, providing insights into the self-sufficiency and daily life of the villagers.
Logical data analysis helps in finding rules and patterns in a dataset which are not
visible otherwise, predicting the distribution of unexcavated areas and thus in this case
enhancing our understanding of ancient Egyptian food production practices in state-
planned settlements.