Journal articles: 'Gefsoc'

1

Milne, E., R. Al Adamat, N. H. Batjes, M. Bernoux, T. Bhattacharyya, C. C. Cerri, C. E. P. Cerri, et al. "National and sub-national assessments of soil organic carbon stocks and changes: The GEFSOC modelling system." Agriculture, Ecosystems & Environment 122, no. 1 (September 2007): 3–12. http://dx.doi.org/10.1016/j.agee.2007.01.002.

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Al-Adamat, R., Z. Rawajfih, M. Easter, K. Paustian, K. Coleman, E. Milne, P. Falloon, D. S. Powlson, and N. H. Batjes. "Predicted soil organic carbon stocks and changes in Jordan between 2000 and 2030 made using the GEFSOC Modelling System." Agriculture, Ecosystems & Environment 122, no. 1 (September 2007): 35–45. http://dx.doi.org/10.1016/j.agee.2007.01.006.

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Easter, M., K. Paustian, K. Killian, S. Williams, T. Feng, R. Al-Adamat, N. H. Batjes, et al. "The GEFSOC soil carbon modelling system: A tool for conducting regional-scale soil carbon inventories and assessing the impacts of land use change on soil carbon." Agriculture, Ecosystems & Environment 122, no. 1 (September 2007): 13–25. http://dx.doi.org/10.1016/j.agee.2007.01.004.

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Bashaw, Greg J., Hailan Hu, Catherine D. Nobes, and Corey S. Goodman. "A novel Dbl family RhoGEF promotes Rho-dependent axon attraction to the central nervous system midline in Drosophila and overcomes Robo repulsion." Journal of Cell Biology 155, no. 7 (December 24, 2001): 1117–22. http://dx.doi.org/10.1083/jcb.200110077.

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The key role of the Rho family GTPases Rac, Rho, and CDC42 in regulating the actin cytoskeleton is well established (Hall, A. 1998. Science. 279:509–514). Increasing evidence suggests that the Rho GTPases and their upstream positive regulators, guanine nucleotide exchange factors (GEFs), also play important roles in the control of growth cone guidance in the developing nervous system (Luo, L. 2000. Nat. Rev. Neurosci. 1:173–180; Dickson, B.J. 2001. Curr. Opin. Neurobiol. 11:103–110). Here, we present the identification and molecular characterization of a novel Dbl family Rho GEF, GEF64C, that promotes axon attraction to the central nervous system midline in the embryonic Drosophila nervous system. In sensitized genetic backgrounds, loss of GEF64C function causes a phenotype where too few axons cross the midline. In contrast, ectopic expression of GEF64C throughout the nervous system results in a phenotype in which far too many axons cross the midline, a phenotype reminiscent of loss of function mutations in the Roundabout (Robo) repulsive guidance receptor. Genetic analysis indicates that GEF64C expression can in fact overcome Robo repulsion. Surprisingly, evidence from genetic, biochemical, and cell culture experiments suggests that the promotion of axon attraction by GEF64C is dependent on the activation of Rho, but not Rac or Cdc42.

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Leonardo, Nicholas M., and Brian A. Colle. "Verification of Multimodel Ensemble Forecasts of North Atlantic Tropical Cyclones." Weather and Forecasting 32, no. 6 (November 9, 2017): 2083–101. http://dx.doi.org/10.1175/waf-d-17-0058.1.

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Abstract North Atlantic tropical cyclone (TC) forecasts from four ensemble prediction systems (EPSs) are verified using the National Hurricane Center’s (NHC) best tracks for the 2008–15 seasons. The 1–5-day forecasts are evaluated for the 21-member National Centers for Environmental Prediction (NCEP) Global Ensemble Forecast System (GEFS), the 23-member UKMO ensemble (UKMET), and the 51-member European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble, as well as a combination of these ensembles [Multimodel Global (MMG)]. Several deterministic models are also evaluated, such as the Global Forecast System (GFSdet), Hurricane Weather Research and Forecasting Model (HWRF), the deterministic ECMWF model (ECdet), and the Geophysical Fluid Dynamical Laboratory model (GFDL).The ECdet track errors are the smallest on average at all lead times, but are not significantly different from the GEFS and ECMWF ensemble means. All models have a slow bias (90–240 km) in the along-track direction by 120 h, while there is little bias in the cross-track direction. Much of this slow bias is attributed to TCs undergoing extratropical transition (ET). All EPSs are underdispersed in the along-track direction, while the ECMWF is slightly overdispersed in the cross-track direction. The MMG and ECMWF track forecasts have more probabilistic skill than the ECdet and comparable skill to the NHC climatology-based cone forecast. TC intensity errors for the HWRF and GFDL are lower than the coarser models within the first 24 h, but are comparable to the ECdet at longer lead times. The ECMWF and MMG have comparable or better probabilistic intensity forecasts than the ECdet, while the GEFS’s weak bias limits its skill.

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Aljbaae, S., J. Souchay, A. F. B. A. Prado, and T. G. G. Chanut. "A dynamical study of the Gefion asteroid family." Astronomy & Astrophysics 622 (January 24, 2019): A39. http://dx.doi.org/10.1051/0004-6361/201834470.

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The Gefion asteroid family is a group of S-type asteroids located between the 8J:-3A and 5J:-2A mean-motion resonances. The 5J:-2A resonance seems to be responsible for the absence of the right side of the V-shape of this family. We aim in this work to present a detailed study on the Gefion family, motivated by the incompatibility found in previous family age estimations and the fact that this family could be seen as one of the most probable sources of L-chondrite meteorites. After eliminating all possible taxonomical and dynamical interlopers, we use a Monte Carlo method to analyze the semi-major axis evolution of several fictitious families under the influence of the Yarkovsky and Yarkovsky-O’Keefe-Radzievsky-Paddack (YORP) effects. We also perform simulations using symplectic integrators to account for the Yarkovsky effect (diurnal and seasonal versions) and the stochastic YORP effect. We make use of the distribution of the component of the ejection velocity field (vW) perpendicular to the orbital plane and the time dependence of the asymmetry of the distribution of the target function of a fictitious family generated with ejection velocity parameter 20+55−15 m s−1 to obtain an age estimate of 1030+19−67 Myr. We find that 6.5% of asteroids from the Gefion family can reach orbits similar to particles in the current near-Earth objects space; 73% of them are among the Amors asteroids, and the remaining ones are among the Apollos. We only found 0.5% from the Gefion family reaching the Mars-crossing space.

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McGraw, Allison M., Vishnu Reddy, and Juan A. Sanchez. "Do L chondrites come from the Gefion family?" Monthly Notices of the Royal Astronomical Society 476, no. 1 (January 31, 2018): 630–34. http://dx.doi.org/10.1093/mnras/sty250.

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8

Mo, Kingtse C., and Dennis P. Lettenmaier. "Prediction of Flash Droughts over the United States." Journal of Hydrometeorology 21, no. 8 (August 1, 2020): 1793–810. http://dx.doi.org/10.1175/jhm-d-19-0221.1.

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AbstractWe examine reforecasts of flash droughts over the United States for the late spring (April–May), midsummer (June–July), and late summer/early autumn (August–September) with lead times up to 3 pentads based on the NOAA second-generation Global Ensemble Forecast System reforecasts version 2 (GEFSv2). We consider forecasts of both heat wave and precipitation deficit (P deficit) flash droughts, where heat wave flash droughts are characterized by high temperature and depletion of soil moisture and P deficit flash droughts are caused by lack of precipitation that leads to (rather than being the cause of) high temperature. We find that the GEFSv2 reforecasts generally capture the frequency of occurrence (FOC) patterns. The equitable threat score (ETS) of heat wave flash drought forecasts for late spring in the regions where heat wave flash droughts are most likely to occur over the north-central and Pacific Northwest regions is statistically significant up to 2 pentads. The GEFSv2 reforecasts capture the basic pattern of the FOC of P-deficit flash droughts and also are skillful up to lead about 2 pentads. However, the reforecasts overestimate the P-deficit flash drought FOC over parts of the Southwest in late spring, leading to large false alarm rates. For autumn, the reforecasts underestimate P-deficit flash drought occurrence over California and Nevada. The GEFSv2 reforecasts are able to capture the approximately linear relationship between evaporation and soil moisture, but the lack of skill in precipitation forecasts limits the skill of P-deficit flash drought forecasts.

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9

Dell, Helen. "Growing through GEFs." Nature Reviews Cancer 5, no. 3 (February 18, 2005): 156. http://dx.doi.org/10.1038/nrc1574.

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10

Weibel-Orlando, Joan. ": Alcohol, Gender and Culture . Dimitra Gefou-Madianou." American Anthropologist 96, no. 1 (March 1994): 193–94. http://dx.doi.org/10.1525/aa.1994.96.1.02a00380.

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11

Zhang, Zhaoqiang, Qi Ding, Shing Bo Peh, Dan Zhao, Jiyu Cui, Xili Cui, and Huabin Xing. "Mechano-assisted synthesis of an ultramicroporous metal–organic framework for trace CO2 capture." Chemical Communications 56, no. 56 (2020): 7726–29. http://dx.doi.org/10.1039/d0cc03196h.

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Hybrid ultramicroporous ZU-36-Ni (GeFSIX-3-Ni) synthesized by a mechano-assisted thermal transformation method exhibits excellent trace CO₂ capture performance through strong host–guest interactions.

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12

van Buul, Jaap D., Dirk Geerts, and Stephan Huveneers. "Rho GAPs and GEFs." Cell Adhesion & Migration 8, no. 2 (January 2014): 108–24. http://dx.doi.org/10.4161/cam.27599.

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13

Barr, Francis, and David G. Lambright. "Rab GEFs and GAPs." Current Opinion in Cell Biology 22, no. 4 (August 2010): 461–70. http://dx.doi.org/10.1016/j.ceb.2010.04.007.

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14

Zhang, Yue-Hua, Rosemary Burgess, Jodie P. Malone, Georgie C. Glubb, Katherine L. Helbig, Lata Vadlamudi, Sara Kivity, et al. "Genetic epilepsy with febrile seizures plus." Neurology 89, no. 12 (August 25, 2017): 1210–19. http://dx.doi.org/10.1212/wnl.0000000000004384.

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Objective:Following our original description of generalized epilepsy with febrile seizures plus (GEFS+) in 1997, we analyze the phenotypic spectrum in 409 affected individuals in 60 families (31 new families) and expand the GEFS+ spectrum.Methods:We performed detailed electroclinical phenotyping on all available affected family members. Genetic analysis of known GEFS+ genes was carried out where possible. We compared our phenotypic and genetic data to those published in the literature over the last 19 years.Results:We identified new phenotypes within the GEFS+ spectrum: focal seizures without preceding febrile seizures (16/409 [4%]), classic genetic generalized epilepsies (22/409 [5%]), and afebrile generalized tonic-clonic seizures (9/409 [2%]). Febrile seizures remains the most frequent phenotype in GEFS+ (178/409 [44%]), followed by febrile seizures plus (111/409 [27%]). One third (50/163 [31%]) of GEFS+ families tested have a pathogenic variant in a known GEFS+ gene.Conclusion:As 37/409 (9%) affected individuals have focal epilepsies, we suggest that GEFS+ be renamed genetic epilepsy with febrile seizures plus rather than generalized epilepsy with febrile seizures plus. The phenotypic overlap between GEFS+ and the classic generalized epilepsies is considerably greater than first thought. The clinical and molecular data suggest that the 2 major groups of generalized epilepsies share genetic determinants.

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15

Sager, Safiye, Mehmet Kole, Utku Batu, Yakup Cag, and Yasemin Akin. "Evaluation of clinical characteristics between febrile seizures and generalized epilepsy febrile seizure plus." Medicine Science | International Medical Journal 11, no. 3 (2022): 1248. http://dx.doi.org/10.5455/medscience.2022.05.113.

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In the present study, we aimed to compare the characteristics of febrile seizure (FS) and generalized epilepsy with febrile seizure plus (GEFS+) in terms of their clinical prognosis and treatment. Among the 95 patients between 5-18 years of age included in this single-center retrospective cross-sectional hospital-based study, 55 and 40 patients were diagnosed with FS and GEFS+, respectively. Clinical characteristics, family history, and treatment responses of both groups were statistically compared. The FS and GEFS+ groups were not significantly different in terms of the median and mean ages for the onset of FS. Prolonged FS was seen as significantly higher in the FS group than in the GEFS+ group (p=0.014). The mean age of afebrile seizure was 3.5 years in the GEFS+ group. The prevalence of febrile/afebrile seizures in the family was significantly higher in the GEFS+ group than in the FS group. Febrile seizure recurrence risk was significantly higher in GEFS + group. The rate of seizure recurrence was low in both groups, particularly in patients receiving anti-epileptic treatment. Levetiracetam was found to be effective in preventing seizures in both groups. It is important to investigate the risk factors for the development of GEFs in patients presenting with FS.

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16

Radu, Madalina, Eugenia Roza, Daniel Mihai Teleanu, and Raluca Ioana Teleanu. "Genetic epilepsy with febrile seizures plus – an overview." Romanian Journal of Neurology 20, no. 1 (March 31, 2021): 21–27. http://dx.doi.org/10.37897/rjn.2021.1.3.

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Genetic epilepsy with febrile seizures plus (GEFS+) is characterized by a group of genetic epilepsies associated predominately with an autosomal dominant pattern, but also with de novo and autosomal-recessive inheritance, these last two found in a small number of cases. It was believed that GEFS+ is associated only with generalized seizures, but now the term “genetic epilepsy” is preferred because it has been demonstrated that GEFS+ is associated with both generalized and focal seizures. The “GEFS+ family” was defined as a family with more than two individuals with GEFS+ phenotypes, including at least one with febrile seizure or febrile seizure plus. The GEFS+ spectrum includes febrile seizures (FS), febrile seizures plus (FS+), myoclonic seizures, myoclonic-atonic seizures, absences seizures, focal or generalized seizures. The genetic mutations responsible for inhibitor-excitatory imbalance in neurons network were found in sodium voltage-gated channel alpha subunit 1 (SCN1A), sodium voltage-gated channel beta subunit 1 (SCN1B), sodium voltage-gated channel alpha subunit 2 (SCN2A), sodium voltage-gated channel alpha subunit 9 (SCN9A), gamma-aminobutyric acid type A receptor subunit gamma 2 (GABRG2), which are the main gene in GEFS+ genotype.

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17

Sasaki, Kensuke, Kei Arimoto, Kento Kankawa, Chikayo Terada, Tetsuo Yamamori, Akiya Watakabe, and Nobuhiko Yamamoto. "Rho Guanine Nucleotide Exchange Factors Regulate Horizontal Axon Branching of Cortical Upper Layer Neurons." Cerebral Cortex 30, no. 4 (November 20, 2019): 2506–18. http://dx.doi.org/10.1093/cercor/bhz256.

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Abstract Axon branching is a crucial process for cortical circuit formation. However, how the cytoskeletal changes in axon branching are regulated is not fully understood. In the present study, we investigated the role of RhoA guanine nucleotide exchange factors (RhoA-GEFs) in branch formation of horizontally elongating axons (horizontal axons) in the mammalian cortex. In situ hybridization showed that more than half of all known RhoA-GEFs were expressed in the developing rat cortex. These RhoA-GEFs were mostly expressed in the macaque cortex as well. An overexpression study using organotypic cortical slice cultures demonstrated that several RhoA-GEFs strongly promoted horizontal axon branching. Moreover, branching patterns were different between overexpressed RhoA-GEFs. In particular, ARHGEF18 markedly increased terminal arbors, whereas active breakpoint cluster region-related protein (ABR) increased short branches in both distal and proximal regions of horizontal axons. Rho kinase inhibitor treatment completely suppressed the branch-promoting effect of ARHGEF18 overexpression, but only partially affected that of ABR, suggesting that these RhoA-GEFs employ distinct downstream pathways. Furthermore, knockdown of either ARHGEF18 or ABR considerably suppressed axon branching. Taken together, the present study revealed that subsets of RhoA-GEFs differentially promote axon branching of mammalian cortical neurons.

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Zhu, W., C. Xu, J. G. Zhang, H. He, K. H. Wu, L. Zhang, Y. Zeng, Y. Zhou, K. J. Su, and H. W. Deng. "Gene-based GWAS analysis for consecutive studies of GEFOS." Osteoporosis International 29, no. 12 (October 10, 2018): 2645–58. http://dx.doi.org/10.1007/s00198-018-4654-y.

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Machin, Polly A., Elpida Tsonou, David C. Hornigold, and Heidi C. E. Welch. "Rho Family GTPases and Rho GEFs in Glucose Homeostasis." Cells 10, no. 4 (April 16, 2021): 915. http://dx.doi.org/10.3390/cells10040915.

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Dysregulation of glucose homeostasis leading to metabolic syndrome and type 2 diabetes is the cause of an increasing world health crisis. New intriguing roles have emerged for Rho family GTPases and their Rho guanine nucleotide exchange factor (GEF) activators in the regulation of glucose homeostasis. This review summates the current knowledge, focusing in particular on the roles of Rho GEFs in the processes of glucose-stimulated insulin secretion by pancreatic β cells and insulin-stimulated glucose uptake into skeletal muscle and adipose tissues. We discuss the ten Rho GEFs that are known so far to regulate glucose homeostasis, nine of which are in mammals, and one is in yeast. Among the mammalian Rho GEFs, P-Rex1, Vav2, Vav3, Tiam1, Kalirin and Plekhg4 were shown to mediate the insulin-stimulated translocation of the glucose transporter GLUT4 to the plasma membrane and/or insulin-stimulated glucose uptake in skeletal muscle or adipose tissue. The Rho GEFs P-Rex1, Vav2, Tiam1 and β-PIX were found to control the glucose-stimulated release of insulin by pancreatic β cells. In vivo studies demonstrated the involvement of the Rho GEFs P-Rex2, Vav2, Vav3 and PDZ-RhoGEF in glucose tolerance and/or insulin sensitivity, with deletion of these GEFs either contributing to the development of metabolic syndrome or protecting from it. This research is in its infancy. Considering that over 80 Rho GEFs exist, it is likely that future research will identify more roles for Rho GEFs in glucose homeostasis.

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Cario-Toumaniantz, Chrystelle, David Ferland-McCollough, Gilliane Chadeuf, Gilles Toumaniantz, Marianne Rodriguez, Jean-Pierre Galizzi, Brian Lockhart, et al. "RhoA guanine exchange factor expression profile in arteries: evidence for a Rho kinase-dependent negative feedback in angiotensin II-dependent hypertension." American Journal of Physiology-Cell Physiology 302, no. 9 (May 1, 2012): C1394—C1404. http://dx.doi.org/10.1152/ajpcell.00423.2011.

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Sustained overactivation of RhoA is a common component for the pathogenesis of several cardiovascular disorders, including hypertension. Although activity of Rho proteins depends on Rho exchange factors (Rho-GEFs), the identity of Rho-GEFs expressed in vascular smooth muscle cells (VSMC) and participating in the control of Rho protein activity and Rho-dependent functions remains unknown. To address this question, we analyzed by quantitative RT-PCR the expression profile of 28 RhoA-GEFs in arteries of normotensive (saline-treated) and hypertensive (ANG II-treated) rats. Sixteen RhoA-GEFs were downregulated in mesenteric arteries of hypertensive rats, among which nine are also downregulated in cultured VSMC stimulated by ANG II (100 nM, 48 h), suggesting a direct effect of ANG II. Inhibition of type 1 ANG II receptors (losartan, 1 μM) or Rho kinase (fasudil, 10 μM) prevented ANG II-induced RhoA-GEF downregulation. Functionally, ANG II-induced downregulation of RhoA-GEFs is associated with decreased Rho kinase activation in response to endothelin-1, norepinephrine, and U-46619. This work thus identifies a group of RhoA-GEFs that controls RhoA and RhoA-dependent functions in VSMC, and a negative feedback of RhoA/Rho kinase activity on the expression of these RhoA-GEFs that may play an adaptative role to limit RhoA/Rho kinase activation.

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Calvo, Fernando, and Piero Crespo. "Structural and Spatial Determinants Regulating TC21 Activation by RasGRF Family Nucleotide Exchange Factors." Molecular Biology of the Cell 20, no. 20 (October 15, 2009): 4289–302. http://dx.doi.org/10.1091/mbc.e09-03-0212.

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RasGRF family guanine nucleotide exchange factors (GEFs) promote guanosine diphosphate (GDP)/guanosine triphosphate (GTP) exchange on several Ras GTPases, including H-Ras and TC21. Although the mechanisms controlling RasGRF function as an H-Ras exchange factor are relatively well characterized, little is known about how TC21 activation is regulated. Here, we have studied the structural and spatial requirements involved in RasGRF 1/2 exchange activity on TC21. We show that RasGRF GEFs can activate TC21 in all of its sublocalizations except at the Golgi complex. We also demonstrate that TC21 susceptibility to activation by RasGRF GEFs depends on its posttranslational modifications: farnesylated TC21 can be activated by both RasGRF1 and RasGRF2, whereas geranylgeranylated TC21 is unresponsive to RasGRF2. Importantly, we show that RasGRF GEFs ability to catalyze exchange on farnesylated TC21 resides in its pleckstrin homology 1 domain, by a mechanism independent of localization and of its ability to associate to membranes. Finally, our data indicate that Cdc42-GDP can inhibit TC21 activation by RasGRF GEFs, demonstrating that Cdc42 negatively affects the functions of RasGRF GEFs irrespective of the GTPase being targeted.

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22

Ngok, Siu P., and Panos Z. Anastasiadis. "Rho GEFs in endothelial junctions." Tissue Barriers 1, no. 5 (December 2013): e27132. http://dx.doi.org/10.4161/tisb.27132.

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23

Fulmer, Tim. "Going after GEFs in cancer." Science-Business eXchange 2, no. 19 (May 2009): 775. http://dx.doi.org/10.1038/scibx.2009.775.

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Bernards, André, and Jeffrey Settleman. "GEFs in growth factor signaling." Growth Factors 25, no. 5 (January 2007): 355–61. http://dx.doi.org/10.1080/08977190701830375.

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25

Natwick, Dean E., and Sean R. Collins. "Decoding GEFs of animated cells." Nature Chemical Biology 16, no. 8 (July 21, 2020): 812–13. http://dx.doi.org/10.1038/s41589-020-0570-5.

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26

Cornejo-Sanchez, Diana M., Anushree Acharya, Thashi Bharadwaj, Lizeth Marin-Gomez, Pilar Pereira-Gomez, Liz M. Nouel-Saied, Deborah A. Nickerson, et al. "SCN1A Variants as the Underlying Cause of Genetic Epilepsy with Febrile Seizures Plus in Two Multi-Generational Colombian Families." Genes 13, no. 5 (April 25, 2022): 754. http://dx.doi.org/10.3390/genes13050754.

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Genetic epilepsy with febrile seizures plus (GEFS+) is an autosomal dominant disorder with febrile or afebrile seizures that exhibits phenotypic variability. Only a few variants in SCN1A have been previously characterized for GEFS+, in Latin American populations where studies on the genetic and phenotypic spectrum of GEFS+ are scarce. We evaluated members in two multi-generational Colombian Paisa families whose affected members present with classic GEFS+. Exome and Sanger sequencing were used to detect the causal variants in these families. In each of these families, we identified variants in SCN1A causing GEFS+ with incomplete penetrance. In Family 047, we identified a heterozygous variant (c.3530C > G; p.(Pro1177Arg)) that segregates with GEFS+ in 15 affected individuals. In Family 167, we identified a previously unreported variant (c.725A > G; p.(Gln242Arg)) that segregates with the disease in a family with four affected members. Both variants are located in a cytoplasmic loop region in SCN1A and based on our findings the variants are classified as pathogenic and likely pathogenic, respectively. Our results expand the genotypic and phenotypic spectrum associated with SCN1A variants and will aid in improving molecular diagnostics and counseling in Latin American and other populations.

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Cornejo-Sanchez, Diana M., Anushree Acharya, Thashi Bharadwaj, Lizeth Marin-Gomez, Pilar Pereira-Gomez, Liz M. Nouel-Saied, Deborah A. Nickerson, et al. "SCN1A Variants as the Underlying Cause of Genetic Epilepsy with Febrile Seizures Plus in Two Multi-Generational Colombian Families." Genes 13, no. 5 (April 25, 2022): 754. http://dx.doi.org/10.3390/genes13050754.

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Genetic epilepsy with febrile seizures plus (GEFS+) is an autosomal dominant disorder with febrile or afebrile seizures that exhibits phenotypic variability. Only a few variants in SCN1A have been previously characterized for GEFS+, in Latin American populations where studies on the genetic and phenotypic spectrum of GEFS+ are scarce. We evaluated members in two multi-generational Colombian Paisa families whose affected members present with classic GEFS+. Exome and Sanger sequencing were used to detect the causal variants in these families. In each of these families, we identified variants in SCN1A causing GEFS+ with incomplete penetrance. In Family 047, we identified a heterozygous variant (c.3530C > G; p.(Pro1177Arg)) that segregates with GEFS+ in 15 affected individuals. In Family 167, we identified a previously unreported variant (c.725A > G; p.(Gln242Arg)) that segregates with the disease in a family with four affected members. Both variants are located in a cytoplasmic loop region in SCN1A and based on our findings the variants are classified as pathogenic and likely pathogenic, respectively. Our results expand the genotypic and phenotypic spectrum associated with SCN1A variants and will aid in improving molecular diagnostics and counseling in Latin American and other populations.

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28

Cornejo-Sanchez, Diana M., Anushree Acharya, Thashi Bharadwaj, Lizeth Marin-Gomez, Pilar Pereira-Gomez, Liz M. Nouel-Saied, Deborah A. Nickerson, et al. "SCN1A Variants as the Underlying Cause of Genetic Epilepsy with Febrile Seizures Plus in Two Multi-Generational Colombian Families." Genes 13, no. 5 (April 25, 2022): 754. http://dx.doi.org/10.3390/genes13050754.

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Genetic epilepsy with febrile seizures plus (GEFS+) is an autosomal dominant disorder with febrile or afebrile seizures that exhibits phenotypic variability. Only a few variants in SCN1A have been previously characterized for GEFS+, in Latin American populations where studies on the genetic and phenotypic spectrum of GEFS+ are scarce. We evaluated members in two multi-generational Colombian Paisa families whose affected members present with classic GEFS+. Exome and Sanger sequencing were used to detect the causal variants in these families. In each of these families, we identified variants in SCN1A causing GEFS+ with incomplete penetrance. In Family 047, we identified a heterozygous variant (c.3530C > G; p.(Pro1177Arg)) that segregates with GEFS+ in 15 affected individuals. In Family 167, we identified a previously unreported variant (c.725A > G; p.(Gln242Arg)) that segregates with the disease in a family with four affected members. Both variants are located in a cytoplasmic loop region in SCN1A and based on our findings the variants are classified as pathogenic and likely pathogenic, respectively. Our results expand the genotypic and phenotypic spectrum associated with SCN1A variants and will aid in improving molecular diagnostics and counseling in Latin American and other populations.

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29

Medina, Hanoi, Di Tian, Fabio R. Marin, and Giovanni B. Chirico. "Comparing GEFS, ECMWF, and Postprocessing Methods for Ensemble Precipitation Forecasts over Brazil." Journal of Hydrometeorology 20, no. 4 (April 1, 2019): 773–90. http://dx.doi.org/10.1175/jhm-d-18-0125.1.

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Abstract This study compares the performance of Global Ensemble Forecast System (GEFS) and European Centre for Medium-Range Weather Forecasts (ECMWF) precipitation ensemble forecasts in Brazil and evaluates different analog-based methods and a logistic regression method for postprocessing the GEFS forecasts. The numerical weather prediction (NWP) forecasts were evaluated against the Physical Science Division South America Daily Gridded Precipitation dataset using both deterministic and probabilistic forecasting evaluation metrics. The results show that the ensemble precipitation forecasts performed commonly well in the east and poorly in the northwest of Brazil, independent of the models and the postprocessing methods. While the raw ECMWF forecasts performed better than the raw GEFS forecasts, analog-based GEFS forecasts were more skillful and reliable than both raw ECMWF and GEFS forecasts. The choice of a specific postprocessing strategy had less impact on the performance than the postprocessing itself. Nonetheless, forecasts produced with different analog-based postprocessing strategies were significantly different and were more skillful and as reliable and sharp as forecasts produced with the logistic regression method. The approach considering the logarithm of current and past reforecasts as the measure of closeness between analogs was identified as the best strategy. The results also indicate that the postprocessing using analog methods with long-term reforecast archive improved raw GEFS precipitation forecasting skill more than using logistic regression with short-term reforecast archive. In particular, the postprocessing dramatically improves the GEFS precipitation forecasts when the forecasting skill is low or below zero.

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Zaritsky, Assaf, Yun-Yu Tseng, M. Angeles Rabadán, Shefali Krishna, Michael Overholtzer, Gaudenz Danuser, and Alan Hall. "Diverse roles of guanine nucleotide exchange factors in regulating collective cell migration." Journal of Cell Biology 216, no. 6 (May 16, 2017): 1543–56. http://dx.doi.org/10.1083/jcb.201609095.

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Efficient collective migration depends on a balance between contractility and cytoskeletal rearrangements, adhesion, and mechanical cell–cell communication, all controlled by GTPases of the RHO family. By comprehensive screening of guanine nucleotide exchange factors (GEFs) in human bronchial epithelial cell monolayers, we identified GEFs that are required for collective migration at large, such as SOS1 and β-PIX, and RHOA GEFs that are implicated in intercellular communication. Down-regulation of the latter GEFs differentially enhanced front-to-back propagation of guidance cues through the monolayer and was mirrored by down-regulation of RHOA expression and myosin II activity. Phenotype-based clustering of knockdown behaviors identified RHOA-ARHGEF18 and ARHGEF3-ARHGEF28-ARHGEF11 clusters, indicating that the latter may signal through other RHO-family GTPases. Indeed, knockdown of RHOC produced an intermediate between the two phenotypes. We conclude that for effective collective migration, the RHOA-GEFs → RHOA/C → actomyosin pathways must be optimally tuned to compromise between generation of motility forces and restriction of intercellular communication.

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Vutyavanich, Teraporn, Waraporn Piromlertamorn, and Jason Ellis. "Immature Oocytes in “Apparent Empty Follicle Syndrome”: A Case Report." Case Reports in Medicine 2010 (2010): 1–3. http://dx.doi.org/10.1155/2010/367505.

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Empty follicle syndrome (EFS) is a condition in which no oocytes are obtained after an apparently successful ovarian stimulation. Genuine EFS (GEFS) is differentiated from false EFS by an optimal level of human chorionic gonadotropin on the day of oocyte retrieval. Some believe that GEFS does not exist and that it is only a reflection of the margin of error attendant upon the procedure of oocyte aspiration. Others believe that GEFS is caused by dysfunctional folliculogenesis, resulting in early atresia of oocytes. In this report, we present a case of apparent GEFS, in which immature oocytes were identified after filtration of follicular aspirates. Our findings suggest that delayed maturation of oocyte cumulus complexes in response to HCG might be an etiologic mechanism in some cases of GEFS. This creates a situation similar to the aspiration of immature follicles, where germinal vesicle-stage oocytes with dense scanty cumulus cells are often difficult to identify under a dissecting microscope.

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Heron, Sarah E., Brigid M. Regan, Rebekah V. Harris, Alison E. Gardner, Matthew J. Coleman, Mark F. Bennett, Bronwyn E. Grinton, et al. "Association of SLC32A1 Missense Variants With Genetic Epilepsy With Febrile Seizures Plus." Neurology 96, no. 18 (March 23, 2021): e2251-e2260. http://dx.doi.org/10.1212/wnl.0000000000011855.

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ObjectiveTo identify the causative gene in a large unsolved family with genetic epilepsy with febrile seizures plus (GEFS+), we sequenced the genomes of family members, and then determined the contribution of the identified gene to the pathogenicity of epilepsies by examining sequencing data from 2,772 additional patients.MethodsWe performed whole genome sequencing of 3 members of a GEFS+ family. Subsequently, whole exome sequencing data from 1,165 patients with epilepsy from the Epi4K dataset and 1,329 Australian patients with epilepsy from the Epi25 dataset were interrogated. Targeted resequencing was performed on 278 patients with febrile seizures or GEFS+ phenotypes. Variants were validated and familial segregation examined by Sanger sequencing.ResultsEight previously unreported missense variants were identified in SLC32A1, coding for the vesicular inhibitory amino acid cotransporter VGAT. Two variants cosegregated with the phenotype in 2 large GEFS+ families containing 8 and 10 affected individuals, respectively. Six further variants were identified in smaller families with GEFS+ or idiopathic generalized epilepsy (IGE).ConclusionMissense variants in SLC32A1 cause GEFS+ and IGE. These variants are predicted to alter γ-aminobutyric acid (GABA) transport into synaptic vesicles, leading to altered neuronal inhibition. Examination of further epilepsy cohorts will determine the full genotype–phenotype spectrum associated with SLC32A1 variants.

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Zhang, Zhaoqiang, Xili Cui, Lifeng Yang, Jiyu Cui, Zongbi Bao, Qiwei Yang, and Huabin Xing. "Hexafluorogermanate (GeFSIX) Anion-Functionalized Hybrid Ultramicroporous Materials for Efficiently Trapping Acetylene from Ethylene." Industrial & Engineering Chemistry Research 57, no. 21 (May 21, 2018): 7266–74. http://dx.doi.org/10.1021/acs.iecr.8b00950.

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Bai, Yanyang, Xiaoliang Xiang, Chunmei Liang, and Lei Shi. "Regulating Rac in the Nervous System: Molecular Function and Disease Implication of Rac GEFs and GAPs." BioMed Research International 2015 (2015): 1–17. http://dx.doi.org/10.1155/2015/632450.

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Rho family GTPases, including RhoA, Rac1, and Cdc42 as the most studied members, are master regulators of actin cytoskeletal organization. Rho GTPases control various aspects of the nervous system and are associated with a number of neuropsychiatric and neurodegenerative diseases. The activity of Rho GTPases is controlled by two families of regulators, guanine nucleotide exchange factors (GEFs) as the activators and GTPase-activating proteins (GAPs) as the inhibitors. Through coordinated regulation by GEFs and GAPs, Rho GTPases act as converging signaling molecules that convey different upstream signals in the nervous system. So far, more than 70 members of either GEFs or GAPs of Rho GTPases have been identified in mammals, but only a small subset of them have well-known functions. Thus, characterization of important GEFs and GAPs in the nervous system is crucial for the understanding of spatiotemporal dynamics of Rho GTPase activity in different neuronal functions. In this review, we summarize the current understanding of GEFs and GAPs for Rac1, with emphasis on the molecular function and disease implication of these regulators in the nervous system.

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Li, Weiwei, Zhuo Wang, and Melinda S. Peng. "Evaluating Tropical Cyclone Forecasts from the NCEP Global Ensemble Forecasting System (GEFS) Reforecast Version 2." Weather and Forecasting 31, no. 3 (June 1, 2016): 895–916. http://dx.doi.org/10.1175/waf-d-15-0176.1.

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Abstract Tropical cyclone (TC) forecasts from the NCEP Global Ensemble Forecasting System (GEFS) Reforecast version 2 (1985–2012) were evaluated from the climate perspective, with a focus on tropical cyclogenesis. Although the GEFS captures the climatological seasonality of tropical cyclogenesis over different ocean basins reasonably well, large errors exist on the regional scale. As different genesis pathways are dominant over different ocean basins, genesis biases are related to biases in different aspects of the large-scale or synoptic-scale circulations over different basins. The negative genesis biases over the western North Pacific are associated with a weaker-than-observed monsoon trough in the GEFS, the erroneous genesis pattern over the eastern North Pacific is related to a southward displacement of the ITCZ, and the positive genesis biases near the Cape Verde islands and negative biases farther downstream over the Atlantic can be attributed to the hyperactive Africa easterly waves in the GEFS. The interannual and subseasonal variability of TC activity in the reforecasts was also examined to evaluate the potential skill of the GEFS in providing subseasonal and seasonal predictions. The GEFS skillfully captures the interannual variability of TC activity over the North Pacific and the North Atlantic, which can be attributed to the modulation of TCs by the El Niño–Southern Oscillation (ENSO) and the Atlantic meridional mode (AMM). The GEFS shows promising skill in predicting the active and inactive periods of TC activity over the Atlantic. The skill, however, has large fluctuations from year to year. The analysis presented herein suggests possible impacts of ENSO, the Madden–Julian oscillation (MJO), and the AMM on the TC subseasonal predictability.

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Bhattacharjee, Partha S., Li Zhang, Barry Baker, Li Pan, Raffaele Montuoro, Georg A. Grell, and Jeffery T. McQueen. "Evaluation of Aerosol Optical Depth Forecasts from NOAA’s Global Aerosol Forecast Model (GEFS-Aerosols)." Weather and Forecasting 38, no. 2 (February 2023): 225–49. http://dx.doi.org/10.1175/waf-d-22-0083.1.

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Abstract The NWS/NCEP recently implemented a new global deterministic aerosol forecast model named the Global Ensemble Forecast Systems Aerosols (GEFS-Aerosols), which is based on the Finite Volume version 3 GFS (FV3GFS). It replaced the operational NOAA Environmental Modeling System (NEMS) GFS Aerosol Component version 2 (NGACv2), which was based on a global spectral model (GSM). GEFS-Aerosols uses aerosol modules from the GOCART previously integrated in the WRF Model with Chemistry (WRF-Chem), FENGSHA dust scheme, and several other updates. In this study, we have extensively evaluated aerosol optical depth (AOD) forecasts from GEFS-Aerosols against various observations over a timespan longer than one year (2019–20). The total AOD improvement (in terms of seasonal mean) in GEFS-Aerosols is about 40% compared to NGACv2 in the fall and winter season of 2019. In terms of aerosol species, the biggest improvement came from the enhanced representation of biomass burning aerosol species as GEFS-Aerosols is able to capture more fire events in southern Africa, South America, and Asia than its predecessor. Dust AODs reproduce the seasonal variation over Africa and the Middle East. We have found that correlation of total AOD over large regions of the globe remains consistent for forecast days 3–5. However, we have found that GEFS-Aerosols generates some systematic positive biases for organic carbon AOD near biomass burning regions and sulfate AOD over prediction over East Asia. The addition of a data assimilation capability to GEFS-Aerosols in the near future is expected to address these biases and provide a positive impact to aerosol forecasts by the model. Significance Statement The purpose of this study is to quantify improvements associated with the newly implemented global aerosol forecast model at NWS/NCEP. The monthly and seasonal variations of AOD forecasts of various aerosol regimes are overall consistent with the observations. Our results provide a guide to downstream regional air quality models like CMAQ that will use GEFS-Aerosols to provide lateral boundary conditions.

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Gao, Yuan, Jingchuan Xing, Michel Streuli, Thomas L. Leto, and Yi Zheng. "Trp56of Rac1 Specifies Interaction with a Subset of Guanine Nucleotide Exchange Factors." Journal of Biological Chemistry 276, no. 50 (October 10, 2001): 47530–41. http://dx.doi.org/10.1074/jbc.m108865200.

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Signaling specificity of Rho GTPase pathways is achieved in part by selective interaction between members of the Dbl family guanine nucleotide exchange factors (GEFs) and their Rho GTPase substrates. For example, Trio, GEF-H1, and Tiam1 are a subset of GEFs that specifically activate Rac1 but not the closely related Cdc42. The Rac1 specificity of these GEFs appears to be governed by Rac1-GEF binding interaction. To understand the detailed mechanism underlying the GEF specificity issue, we have analyzed a panel of chimeras made between Rac1 and Cdc42 and examined a series of point mutants of Rac1 made at the switch I, switch II, and β2/β3regions for their ability to interact with and to be activated by the GEFs. The results reveal that Rac1 residues of both the switch I and switch II regions are involved in GEF docking and GEF-mediated nucleotide disruption, because mutation of Asp38, Asn39, Gln61, Tyr64, or Arg66/Leu67into Ala results in the loss of GEF binding, whereas mutation at Tyr32, Asp65, or Leu70/Ser71leads to the loss of GEF catalysis while retaining the binding capability. The region between amino acids 53–72 of Rac1 is required for specific recognition and activation by the GEFs, and Trp56in β3appears to be the critical determinant. Introduction of Trp56to Cdc42 renders it fully responsive to the Rac-specific GEFin vitroand in cells. Further, a polypeptide derived from the β3region of Rac1 including the Trp56residue serves as a specific inhibitor for Rac1 interaction with the GEFs. Taken together, these results indicate that Trp56is the necessary and sufficient determinant of Rac1 for discrimination by the subset of Rac1-specific GEFs and suggest that a compound mimicking Trp56action could be explored as an interfering reagent specifically targeting Rac1 activation.

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Malnic, B., and D. S. Kerr. "Using GEFs to Deorphanize Odorant Receptors." Chemical Senses 34, no. 1 (August 12, 2008): 25–26. http://dx.doi.org/10.1093/chemse/bjn058.

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Marei, Hadir, and Angeliki Malliri. "GEFs: Dual regulation of Rac1 signaling." Small GTPases 8, no. 2 (June 17, 2016): 90–99. http://dx.doi.org/10.1080/21541248.2016.1202635.

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Short, Ben. "Rab GEFs emerge from their DENN." Journal of Cell Biology 191, no. 2 (October 11, 2010): 226. http://dx.doi.org/10.1083/jcb.1912iti2.

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Short, Ben. "GEFs help Rabs find their target." Journal of Cell Biology 200, no. 3 (February 4, 2013): 236. http://dx.doi.org/10.1083/jcb.2003iti2.

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Baltanás, Fernando C., Natasha Zarich, Jose M. Rojas-Cabañeros, and Eugenio Santos. "SOS GEFs in health and disease." Biochimica et Biophysica Acta (BBA) - Reviews on Cancer 1874, no. 2 (December 2020): 188445. http://dx.doi.org/10.1016/j.bbcan.2020.188445.

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Grant, Arthur C., and Blanca Vazquez. "A Case of Extended Spectrum GEFS+." Epilepsia 46, s10 (December 2005): 39–40. http://dx.doi.org/10.1111/j.1528-1167.2005.00357.x.

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Robinson, Richard. "Expanding the Regulatory Repertoire of GEFs." PLoS Biology 11, no. 9 (September 10, 2013): e1001654. http://dx.doi.org/10.1371/journal.pbio.1001654.

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Brunklaus, Andreas, Eduardo Pérez-Palma, Ismael Ghanty, Ji Xinge, Eva Brilstra, Berten Ceulemans, Nicole Chemaly, et al. "Development and Validation of a Prediction Model for Early Diagnosis of SCN1A-Related Epilepsies." Neurology 98, no. 11 (January 24, 2022): e1163-e1174. http://dx.doi.org/10.1212/wnl.0000000000200028.

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Background and ObjectivesPathogenic variants in the neuronal sodium channel α1 subunit gene (SCN1A) are the most frequent monogenic cause of epilepsy. Phenotypes comprise a wide clinical spectrum, including severe childhood epilepsy; Dravet syndrome, characterized by drug-resistant seizures, intellectual disability, and high mortality; and the milder genetic epilepsy with febrile seizures plus (GEFS+), characterized by normal cognition. Early recognition of a child's risk for developing Dravet syndrome vs GEFS+ is key for implementing disease-modifying therapies when available before cognitive impairment emerges. Our objective was to develop and validate a prediction model using clinical and genetic biomarkers for early diagnosis of SCN1A-related epilepsies.MethodsWe performed a retrospective multicenter cohort study comprising data from patients with SCN1A-positive Dravet syndrome and patients with GEFS+ consecutively referred for genetic testing (March 2001–June 2020) including age at seizure onset and a newly developed SCN1A genetic score. A training cohort was used to develop multiple prediction models that were validated using 2 independent blinded cohorts. Primary outcome was the discriminative accuracy of the model predicting Dravet syndrome vs other GEFS+ phenotypes.ResultsA total of 1,018 participants were included. The frequency of Dravet syndrome was 616/743 (83%) in the training cohort, 147/203 (72%) in validation cohort 1, and 60/72 (83%) in validation cohort 2. A high SCN1A genetic score (133.4 [SD 78.5] vs 52.0 [SD 57.5]; p < 0.001) and young age at onset (6.0 [SD 3.0] vs 14.8 [SD 11.8] months; p < 0.001) were each associated with Dravet syndrome vs GEFS+. A combined SCN1A genetic score and seizure onset model separated Dravet syndrome from GEFS+ more effectively (area under the curve [AUC] 0.89 [95% CI 0.86–0.92]) and outperformed all other models (AUC 0.79–0.85; p < 0.001). Model performance was replicated in both validation cohorts 1 (AUC 0.94 [95% CI 0.91–0.97]) and 2 (AUC 0.92 [95% CI 0.82–1.00]).DiscussionThe prediction model allows objective estimation at disease onset whether a child will develop Dravet syndrome vs GEFS+, assisting clinicians with prognostic counseling and decisions on early institution of precision therapies (http://scn1a-prediction-model.broadinstitute.org/).Classification of EvidenceThis study provides Class II evidence that a combined SCN1A genetic score and seizure onset model distinguishes Dravet syndrome from other GEFS+ phenotypes.

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Kim, Kwanhyeong, Sang-Ah Lee, and Daeho Park. "Emerging Roles of Ephexins in Physiology and Disease." Cells 8, no. 2 (January 24, 2019): 87. http://dx.doi.org/10.3390/cells8020087.

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Dbl (B-cell lymphoma)-related guanine nucleotide exchange factors (GEFs), the largest family of GEFs, are directly responsible for the activation of Rho family GTPases and essential for a number of cellular events such as proliferation, differentiation and movement. The members of the Ephexin (Eph-interacting exchange protein) family, a subgroup of Dbl GEFs, initially were named for their interaction with Eph receptors and sequence homology with Ephexin1. Although the first Ephexin was identified about two decades ago, their functions in physiological and pathological contexts and regulatory mechanisms remained elusive until recently. Ephexins are now considered as GEFs that can activate Rho GTPases such as RhoA, Rac, Cdc42, and RhoG. Moreover, Ephexins have been shown to have pivotal roles in neural development, tumorigenesis, and efferocytosis. In this review, we discuss the known and proposed functions of Ephexins in physiological and pathological contexts, as well as their regulatory mechanisms.

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Vegad, Urmin, and Vimal Mishra. "Ensemble streamflow prediction considering the influence of reservoirs in Narmada River Basin, India." Hydrology and Earth System Sciences 26, no. 24 (December 16, 2022): 6361–78. http://dx.doi.org/10.5194/hess-26-6361-2022.

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Abstract. Developing an ensemble hydrological prediction system is essential for reservoir operations and flood early warning. However, efforts to build hydrological ensemble prediction systems considering the influence of reservoirs have been lacking in India. We examine the potential of the Extended Range Forecast System (ERFS, 16 ensemble members) and Global Ensemble Forecast System (GEFS, 21 ensemble members) forecast for streamflow prediction in India using the Narmada River Basin as a test bed. We use the variable infiltration capacity (VIC) with reservoir operations (VIC-Res) scheme to simulate the daily river flow at four locations in the Narmada Basin. Streamflow prediction skills of the ERFS forecast were examined for the period 2003–2018 at 1–32 d lead. We compared the streamflow forecast skills of raw meteorological forecasts from ERFS and GEFS at a 1–10 d lead for the summer monsoon (June–September) 2019–2020. The ERFS forecast underestimates extreme precipitation against the observations compared to the GEFS forecast during the summer monsoon of 2019–2020. However, both forecast products show better skills for minimum and maximum temperatures than precipitation. Ensemble streamflow forecast from the GEFS performs better than the ERFS during 2019–2020. The performance of GEFS-based ensemble streamflow forecast declines after 5 days lead. Overall, the GEFS ensemble streamflow forecast can provide reliable skills at a 1–5 d lead, which can be utilized in streamflow prediction. Our findings provide directions for developing a flood early warning system based on ensemble streamflow prediction considering the influence of reservoirs in India.

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Chantalat, Sophie, Rëgis Courbeyrette, Francesca Senic-Matuglia, Catherine L. Jackson, Bruno Goud, and Anne Peyroche. "A Novel Golgi Membrane Protein Is a Partner of the ARF Exchange Factors Gea1p and Gea2p." Molecular Biology of the Cell 14, no. 6 (June 2003): 2357–71. http://dx.doi.org/10.1091/mbc.e02-10-0693.

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The Sec7 domain guanine nucleotide exchange factors (GEFs) for the GTPase ARF are highly conserved regulators of membrane dynamics and protein trafficking. The interactions of large ARF GEFs with cellular membranes for localization and/or activation are likely to participate in regulated recruitment of ARF and effectors. However, these interactions remain largely unknown. Here we characterize Gmh1p, the first Golgi transmembrane-domain partner of any of the high-molecular-weight ARF-GEFs. Gmh1p is an evolutionarily conserved protein. We demonstrate molecular interaction between the yeast Gmh1p and the large ARF-GEFs Gea1p and Gea2p. This interaction involves a domain of Gea1p and Gea2p that is conserved in the eukaryotic orthologues of the Gea proteins. A single mutation in a conserved amino acid residue of this domain is sufficient to abrogate the interaction, whereas the overexpression of Gmh1p can compensate in vivo defects caused by mutations in this domain. We show that Gmh1p is an integral membrane protein that localizes to the early Golgi in yeast and in human HeLa cells and cycles through the ER. Hence, we propose that Gmh1p acts as a positive Golgi-membrane partner for Gea function. These results are of general interest given the evolutionary conservation of both ARF-GEFs and the Gmh proteins.

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Maltas, Joe, Hannah Reed, Andrew Porter, and Angeliki Malliri. "Mechanisms and consequences of dysregulation of the Tiam family of Rac activators in disease." Biochemical Society Transactions 48, no. 6 (November 16, 2020): 2703–19. http://dx.doi.org/10.1042/bst20200481.

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The Tiam family proteins — Tiam1 and Tiam2/STEF — are Rac1-specific Guanine Nucleotide Exchange Factors (GEFs) with important functions in epithelial, neuronal, immune and other cell types. Tiam GEFs regulate cellular migration, proliferation and survival, mainly through activating and directing Rac1 signalling. Dysregulation of the Tiam GEFs is significantly associated with human diseases including cancer, immunological and neurological disorders. Uncovering the mechanisms and consequences of dysregulation is therefore imperative to improving the diagnosis and treatment of diseases. Here we compare and contrast the subcellular localisation and function of Tiam1 and Tiam2/STEF, and review the evidence for their dysregulation in disease.

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Toma-Fukai and Shimizu. "Structural Insights into the Regulation Mechanism of Small GTPases by GEFs." Molecules 24, no. 18 (September 11, 2019): 3308. http://dx.doi.org/10.3390/molecules24183308.

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Small GTPases are key regulators of cellular events, and their dysfunction causes many types of cancer. They serve as molecular switches by cycling between inactive guanosine diphosphate (GDP)-bound and active guanosine triphosphate (GTP)-bound states. GTPases are deactivated by GTPase-activating proteins (GAPs) and are activated by guanine-nucleotide exchange factors (GEFs). The intrinsic GTP hydrolysis activity of small GTPases is generally low and is accelerated by GAPs. GEFs promote GDP dissociation from small GTPases to allow for GTP binding, which results in a conformational change of two highly flexible segments, called switch I and switch II, that enables binding of the gamma phosphate and allows small GTPases to interact with downstream effectors. For several decades, crystal structures of many GEFs and GAPs have been reported and have shown tremendous structural diversity. In this review, we focus on the latest structural studies of GEFs. Detailed pictures of the variety of GEF mechanisms at atomic resolution can provide insights into new approaches for drug discovery.

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Journal articles on the topic 'Gefsoc'

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