Stochastic accumulation of feature information in perception and memory

It is now well established that the time course of perceptual processing influences the first second or so of performance in a wide variety of cognitive tasks. Over the last20 years, there has been a shift from modeling the speed at which a display is processed, to modeling the speed at which different features of the display are perceived and formalizing how this perceptual information is used in decision making. The first of these models(Lamberts, 1995) was implemented to fit the time course of performance in a speeded perceptual categorization task and assumed a simple stochastic accumulation of feature information. Subsequently, similar approaches have been used to model performance in a range of cognitive tasks including identification, absolute identification, perceptual matching, recognition, visual search, and word processing, again assuming a simple stochastic accumulation of feature information from both the stimulus and representations held in memory. These models are typically fit to data from signal-to-respond experiments whereby the effects of stimulus exposure duration on performance are examined, but response times (RTs) and RT distributions have also been modeled. In this article, we review this approach and explore the insights it has provided about the interplay between perceptual processing, memory retrieval, and decision making in a variety of tasks. In so doing, we highlight how such approaches can continue to usefully contribute to our understanding of cognition

Acupuncture for dry eye: a randomised controlled trial protocol

<p>Abstract</p> <p>Background</p> <p>Dry eye is usually managed by conventional medical interventions such as artificial tears, anti-inflammatory drugs and surgical treatment. However, since dry eye is one of the most frequent ophthalmologic disorders, safer and more effective methods for its treatment are necessary, especially for vulnerable patients. Acupuncture has been widely used to treat patients with dry eye. Our aim is to evaluate the effectiveness and safety of acupuncture for this condition.</p> <p>Methods/Design</p> <p>A randomised, patient-assessor blinded, sham (non-acupuncture point, shallow acupuncture) controlled study was established. Participants allocated to verum acupuncture and sham acupuncture groups will be treated three times weekly for three weeks for a total of nine sessions per participant. Seventeen points (GV23; bilateral BL2, GB4, TE23, Ex1 (Taiyang), ST1 and GB20; and left SP3, LU9, LU10 and HT8 for men, right for women) have been selected for the verum acupuncture; for the sham acupuncture, points have been selected that do not coincide with a classical acupuncture point and that are located close to the verum points, except in the case of the rim of the eye. Ocular surface disease index, tear film breakup time, the Schirmer I test, medication quantification scale and general assessment of improvement will be used as outcome variables for evaluating the effectiveness of acupuncture. Safety will also be assessed at every visit. Primary and secondary outcomes will be assessed four weeks after screening. All statistical analyses will be performed using analysis of covariance.</p> <p>Discussion</p> <p>The results of this trial will be used as a basis for clarifying the efficacy of acupuncture for dry eye.</p> <p>Trial registration</p> <p>ClinicalTrials.gov NCT00969280.</p

Translational research into gut microbiota: new horizons on obesity treatment: updated 2014

Obesity is currently a pandemic of worldwide proportions affecting millions of people. Recent studies have proposed the hypothesis that mechanisms not directly related to the human genome could be involved in the genesis of obesity, due to the fact that, when a population undergoes the same nutritional stress, not all individuals present weight gain related to the diet or become hyperglycemic. The human intestine is colonized by millions of bacteria which form the intestinal flora, known as gut flora. Studies show that lean and overweight human may present a difference in the composition of their intestinal flora; these studies suggest that the intestinal flora could be involved in the development of obesity. Several mechanisms explain the correlation between intestinal flora and obesity. The intestinal flora would increase the energetic extraction of non-digestible polysaccharides. In addition, the lipopolysaccharide from intestinal flora bacteria could trigger a chronic sub-clinical inflammatory process, leading to obesity and diabetes. Another mechanism through which the intestinal flora could lead to obesity would be through the regulation of genes of the host involved in energy storage and expenditure. In the past five years data coming from different sources established causal effects between intestinal microbiota and obesity/insulin resistance, and it is clear that this area will open new avenues of therapeutic to obesity, insulin resistance and DM2

A Metagenomic Approach to Characterization of the Vaginal Microbiome Signature in Pregnancy

While current major national research efforts (i.e., the NIH Human Microbiome Project) will enable comprehensive metagenomic characterization of the adult human microbiota, how and when these diverse microbial communities take up residence in the host and during reproductive life are unexplored at a population level. Because microbial abundance and diversity might differ in pregnancy, we sought to generate comparative metagenomic signatures across gestational age strata. DNA was isolated from the vagina (introitus, posterior fornix, midvagina) and the V5V3 region of bacterial 16S rRNA genes were sequenced (454FLX Titanium platform). Sixty-eight samples from 24 healthy gravidae (18 to 40 confirmed weeks) were compared with 301 non-pregnant controls (60 subjects). Generated sequence data were quality filtered, taxonomically binned, normalized, and organized by phylogeny and into operational taxonomic units (OTU); principal coordinates analysis (PCoA) of the resultant beta diversity measures were used for visualization and analysis in association with sample clinical metadata. Altogether, 1.4 gigabytes of data containing >2.5 million reads (averaging 6,837 sequences/sample of 493 nt in length) were generated for computational analyses. Although gravidae were not excluded by virtue of a posterior fornix pH >4.5 at the time of screening, unique vaginal microbiome signature encompassing several specific OTUs and higher-level clades was nevertheless observed and confirmed using a combination of phylogenetic, non-phylogenetic, supervised, and unsupervised approaches. Both overall diversity and richness were reduced in pregnancy, with dominance of Lactobacillus species (L. iners crispatus, jensenii and johnsonii, and the orders Lactobacillales (and Lactobacillaceae family), Clostridiales, Bacteroidales, and Actinomycetales. This intergroup comparison using rigorous standardized sampling protocols and analytical methodologies provides robust initial evidence that the vaginal microbial 16S rRNA gene catalogue uniquely differs in pregnancy, with variance of taxa across vaginal subsite and gestational age

A systematic review of platinum and taxane resistance from bench to clinic: an inverse relationship

We undertook a systematic review of the pre-clinical and clinical literature for studies investigating the relationship between platinum and taxane resistance. Medline was searched for (1) cell models of acquired drug resistance reporting platinum and taxane sensitivities and (2) clinical trials of platinum or taxane salvage therapy in ovarian cancer. One hundred and thirty-seven models of acquired drug resistance were identified. 68.1% of cisplatin-resistant cells were sensitive to paclitaxel and 66.7% of paclitaxel-resistant cells were sensitive to cisplatin. A similar inverse pattern was observed for cisplatin vs. docetaxel, carboplatin vs. paclitaxel and carboplatin vs. docetaxel. These associations were independent of cancer type, agents used to develop resistance and reported mechanisms of resistance. Sixty-five eligible clinical trials of paclitaxel-based salvage after platinum therapy were identified. Studies of single agent paclitaxel in platinum-resistant ovarian cancer where patients had previously recieved paclitaxel had a pooled response rate of 35.3%, n=232, compared to 22% in paclitaxel naïve patients n=1918 (p<0.01, Chi-squared). Suggesting that pre-treatment with paclitaxel may improve the response of salvage paclitaxel therapy. The response rate to paclitaxel/platinum combination regimens in platinum-sensitive ovarian cancer was 79.5%, n=88 compared to 49.4%, n=85 for paclitaxel combined with other agents (p<0.001, Chi-squared), suggesting a positive interaction between taxanes and platinum. Therefore, the inverse relationship between platinum and taxanes resistance seen in cell models is mirrored in the clinical response to these agents in ovarian cancer. An understanding of the cellular and molecular mechanisms responsible would be valuable in predicting response to salvage chemotherapy and may identify new therapeutic targets

Theoretical vs. empirical discriminability:the application of ROC methods to eyewitness identification

Abstract ᅟ Receiver operating characteristic (ROC) analysis was introduced to the field of eyewitness identification 5 years ago. Since that time, it has been both influential and controversial, and the debate has raised an issue about measuring discriminability that is rarely considered. The issue concerns the distinction between empirical discriminability (measured by area under the ROC curve) vs. underlying/theoretical discriminability (measured by d’ or variants of it). Under most circumstances, the two measures will agree about a difference between two conditions in terms of discriminability. However, it is possible for them to disagree, and that fact can lead to confusion about which condition actually yields higher discriminability. For example, if the two conditions have implications for real-world practice (e.g., a comparison of competing lineup formats), should a policymaker rely on the area-under-the-curve measure or the theory-based measure? Here, we illustrate the fact that a given empirical ROC yields as many underlying discriminability measures as there are theories that one is willing to take seriously. No matter which theory is correct, for practical purposes, the singular area-under-the-curve measure best identifies the diagnostically superior procedure. For that reason, area under the ROC curve informs policy in a way that underlying theoretical discriminability never can. At the same time, theoretical measures of discriminability are equally important, but for a different reason. Without an adequate theoretical understanding of the relevant task, the field will be in no position to enhance empirical discriminability

Two euAGAMOUS genes control C-function in Medicago truncatula

[EN] C-function MADS-box transcription factors belong to the AGAMOUS (AG) lineage and specify both stamen and carpel identity and floral meristem determinacy. In core eudicots, the AG lineage is further divided into two branches, the euAG and PLE lineages. Functional analyses across flowering plants strongly support the idea that duplicated AG lineage genes have different degrees of subfunctionalization of the C-function. The legume Medicago truncatula contains three C-lineage genes in its genome: two euAG genes (MtAGa and MtAGb) and one PLENA-like gene (MtSHP). This species is therefore a good experimental system to study the effects of gene duplication within the AG subfamily. We have studied the respective functions of each euAG genes in M. truncatula employing expression analyses and reverse genetic approaches. Our results show that the M. truncatula euAG- and PLENA-like genes are an example of subfunctionalization as a result of a change in expression pattern. MtAGa and MtAGb are the only genes showing a full C-function activity, concomitant with their ancestral expression profile, early in the floral meristem, and in the third and fourth floral whorls during floral development. In contrast, MtSHP expression appears late during floral development suggesting it does not contribute significantly to the C-function. Furthermore, the redundant MtAGa and MtAGb paralogs have been retained which provides the overall dosage required to specify the C-function in M. truncatula.This work was funded by grants BIO2009-08134 and BIO2012-39849-C02-01 from the Spanish Ministry of Economy and Competitiveness and the Ramon y Cajal Program (RYC-2007-00627 to CGM). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Serwatowska, J.; Roque Mesa, EM.; Gómez Mena, MC.; Constantin, GD.; Wen, J.; Mysore, KS.; Lund, OS.... (2014). Two euAGAMOUS genes control C-function in Medicago truncatula. PLoS ONE. 9(8):103770-1-103770-12. https://doi.org/10.1371/journal.pone.0103770S103770-1103770-1298Prunet, N., & Jack, T. P. (2013). Flower Development in Arabidopsis: There Is More to It Than Learning Your ABCs. Flower Development, 3-33. doi:10.1007/978-1-4614-9408-9_1Causier, B., Schwarz-Sommer, Z., & Davies, B. (2010). Floral organ identity: 20 years of ABCs. Seminars in Cell & Developmental Biology, 21(1), 73-79. doi:10.1016/j.semcdb.2009.10.005Irish, V. F. (2010). The flowering of Arabidopsis flower development. The Plant Journal, 61(6), 1014-1028. doi:10.1111/j.1365-313x.2009.04065.xHeijmans, K., Morel, P., & Vandenbussche, M. (2012). MADS-box Genes and Floral Development: the Dark Side. Journal of Experimental Botany, 63(15), 5397-5404. doi:10.1093/jxb/ers233Bowman, J. L., Smyth, D. R., & Meyerowitz, E. M. (1989). Genes directing flower development in Arabidopsis. The Plant Cell, 1(1), 37-52. doi:10.1105/tpc.1.1.37Yanofsky, M. F., Ma, H., Bowman, J. L., Drews, G. N., Feldmann, K. A., & Meyerowitz, E. M. (1990). The protein encoded by the Arabidopsis homeotic gene agamous resembles transcription factors. Nature, 346(6279), 35-39. doi:10.1038/346035a0Bradley, D., Carpenter, R., Sommer, H., Hartley, N., & Coen, E. (1993). Complementary floral homeotic phenotypes result from opposite orientations of a transposon at the plena locus of antirrhinum. Cell, 72(1), 85-95. doi:10.1016/0092-8674(93)90052-rPinyopich, A., Ditta, G. S., Savidge, B., Liljegren, S. J., Baumann, E., Wisman, E., & Yanofsky, M. F. (2003). Assessing the redundancy of MADS-box genes during carpel and ovule development. Nature, 424(6944), 85-88. doi:10.1038/nature01741Liljegren, S. J., Ditta, G. S., Eshed, Y., Savidge, B., Bowman, J. L., & Yanofsky, M. F. (2000). SHATTERPROOF MADS-box genes control seed dispersal in Arabidopsis. Nature, 404(6779), 766-770. doi:10.1038/35008089Davies, B., Motte, P., Keck, E., Saedler, H., Sommer, H., & Schwarz-Sommer, Z. (1999). PLENA and FARINELLI: redundancy and regulatory interactions between two Antirrhinum MADS-box factors controlling flower development. The EMBO Journal, 18(14), 4023-4034. doi:10.1093/emboj/18.14.4023Kramer, E. M., Jaramillo, M. A., & Di Stilio, V. S. (2004). Patterns of Gene Duplication and Functional Evolution During the Diversification of the AGAMOUS Subfamily of MADS Box Genes in Angiosperms. Genetics, 166(2), 1011-1023. doi:10.1534/genetics.166.2.1011Becker, A. (2003). The major clades of MADS-box genes and their role in the development and evolution of flowering plants. Molecular Phylogenetics and Evolution, 29(3), 464-489. doi:10.1016/s1055-7903(03)00207-0Irish, V. F. (2003). The evolution of floral homeotic gene function. BioEssays, 25(7), 637-646. doi:10.1002/bies.10292Zahn, L. M., Leebens-Mack, J. H., Arrington, J. M., Hu, Y., Landherr, L. L., dePamphilis, C. W., … Ma, H. (2006). Conservation and divergence in the AGAMOUS subfamily of MADS-box genes: evidence of independent sub- and neofunctionalization events. Evolution Development, 8(1), 30-45. doi:10.1111/j.1525-142x.2006.05073.xFerrandiz, C. (2000). Negative Regulation of the SHATTERPROOF Genes by FRUITFULL During Arabidopsis Fruit Development. Science, 289(5478), 436-438. doi:10.1126/science.289.5478.436Ma, H., Yanofsky, M. F., & Meyerowitz, E. M. (1991). AGL1-AGL6, an Arabidopsis gene family with similarity to floral homeotic and transcription factor genes. Genes & Development, 5(3), 484-495. doi:10.1101/gad.5.3.484Savidge, B., Rounsley, S. D., & Yanofsky, M. F. (1995). Temporal relationship between the transcription of two Arabidopsis MADS box genes and the floral organ identity genes. The Plant Cell, 7(6), 721-733. doi:10.1105/tpc.7.6.721Colombo, M., Brambilla, V., Marcheselli, R., Caporali, E., Kater, M. M., & Colombo, L. (2010). A new role for the SHATTERPROOF genes during Arabidopsis gynoecium development. Developmental Biology, 337(2), 294-302. doi:10.1016/j.ydbio.2009.10.043Fourquin, C., & Ferrándiz, C. (2012). Functional analyses of AGAMOUS family members in Nicotiana benthamiana clarify the evolution of early and late roles of C-function genes in eudicots. The Plant Journal, 71(6), 990-1001. doi:10.1111/j.1365-313x.2012.05046.xKapoor, M., Tsuda, S., Tanaka, Y., Mayama, T., Okuyama, Y., Tsuchimoto, S., & Takatsuji, H. (2002). Role of petuniapMADS3in determination of floral organ and meristem identity, as revealed by its loss of function. The Plant Journal, 32(1), 115-127. doi:10.1046/j.1365-313x.2002.01402.xPan, I. L., McQuinn, R., Giovannoni, J. J., & Irish, V. F. (2010). Functional diversification of AGAMOUS lineage genes in regulating tomato flower and fruit development. Journal of Experimental Botany, 61(6), 1795-1806. doi:10.1093/jxb/erq046Pnueli, L., Hareven, D., Rounsley, S. D., Yanofsky, M. F., & Lifschitz, E. (1994). Isolation of the tomato AGAMOUS gene TAG1 and analysis of its homeotic role in transgenic plants. The Plant Cell, 6(2), 163-173. doi:10.1105/tpc.6.2.163Dreni, L., & Kater, M. M. (2013). MADSreloaded: evolution of theAGAMOUSsubfamily genes. New Phytologist, 201(3), 717-732. doi:10.1111/nph.12555Brunner, A. M. (2000). Plant Molecular Biology, 44(5), 619-634. doi:10.1023/a:1026550205851Perl-Treves, R., Kahana, A., Rosenman, N., Xiang, Y., & Silberstein, L. (1998). Expression of Multiple AGAMOUS-Like Genes in Male and Female Flowers of Cucumber (Cucumis sativus L.). Plant and Cell Physiology, 39(7), 701-710. doi:10.1093/oxfordjournals.pcp.a029424Yu, D., Kotilainen, M., Pöllänen, E., Mehto, M., Elomaa, P., Helariutta, Y., … Teeri, T. H. (1999). Organ identity genes and modified patterns of flower development in Gerbera hybrida (Asteraceae). The Plant Journal, 17(1), 51-62. doi:10.1046/j.1365-313x.1999.00351.xDong, Z., Zhao, Z., Liu, C., Luo, J., Yang, J., Huang, W., … Luo, D. (2005). Floral Patterning in Lotus japonicus. Plant Physiology, 137(4), 1272-1282. doi:10.1104/pp.104.054288Hofer, J. M., & Noel Ellis, T. (2014). Developmental specialisations in the legume family. Current Opinion in Plant Biology, 17, 153-158. doi:10.1016/j.pbi.2013.11.014Fourquin, C., del Cerro, C., Victoria, F. C., Vialette-Guiraud, A., de Oliveira, A. C., & Ferrándiz, C. (2013). A Change in SHATTERPROOF Protein Lies at the Origin of a Fruit Morphological Novelty and a New Strategy for Seed Dispersal in Medicago Genus. Plant Physiology, 162(2), 907-917. doi:10.1104/pp.113.217570Hewitt EJ (1966) Sand and Water Culture Methods Used in the Study of Plant Nutrition. Farnham Royal, UK: Commonwealth Agricultural Bureau.Cheng, X., Wang, M., Lee, H.-K., Tadege, M., Ratet, P., Udvardi, M., … Wen, J. (2013). An efficient reverse genetics platform in the model legumeMedicago truncatula. New Phytologist, 201(3), 1065-1076. doi:10.1111/nph.12575D’ Erfurth, I., Cosson, V., Eschstruth, A., Lucas, H., Kondorosi, A., & Ratet, P. (2003). Efficient transposition of theTnt1tobacco retrotransposon in the model legumeMedicago truncatula. The Plant Journal, 34(1), 95-106. doi:10.1046/j.1365-313x.2003.01701.xTadege, M., Ratet, P., & Mysore, K. S. (2005). Insertional mutagenesis: a Swiss Army knife for functional genomics of Medicago truncatula. Trends in Plant Science, 10(5), 229-235. doi:10.1016/j.tplants.2005.03.009Tadege, M., Wen, J., He, J., Tu, H., Kwak, Y., Eschstruth, A., … Mysore, K. S. (2008). Large-scale insertional mutagenesis using the Tnt1 retrotransposon in the model legume Medicago truncatula. The Plant Journal, 54(2), 335-347. doi:10.1111/j.1365-313x.2008.03418.xCheng, X., Wen, J., Tadege, M., Ratet, P., & Mysore, K. S. (2010). Reverse Genetics in Medicago truncatula Using Tnt1 Insertion Mutants. Plant Reverse Genetics, 179-190. doi:10.1007/978-1-60761-682-5_13Benlloch, R., d’ Erfurth, I., Ferrandiz, C., Cosson, V., Beltrán, J. P., Cañas, L. A., … Ratet, P. (2006). Isolation of mtpim Proves Tnt1 a Useful Reverse Genetics Tool in Medicago truncatula and Uncovers New Aspects of AP1-Like Functions in Legumes. Plant Physiology, 142(3), 972-983. doi:10.1104/pp.106.083543Larkin, M. A., Blackshields, G., Brown, N. P., Chenna, R., McGettigan, P. A., McWilliam, H., … Higgins, D. G. (2007). Clustal W and Clustal X version 2.0. Bioinformatics, 23(21), 2947-2948. doi:10.1093/bioinformatics/btm404Altschul, S. (1997). Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Research, 25(17), 3389-3402. doi:10.1093/nar/25.17.3389Tamura, K., Dudley, J., Nei, M., & Kumar, S. (2007). MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) Software Version 4.0. Molecular Biology and Evolution, 24(8), 1596-1599. doi:10.1093/molbev/msm092Dellaporta, S. L., Wood, J., & Hicks, J. B. (1983). A plant DNA minipreparation: Version II. Plant Molecular Biology Reporter, 1(4), 19-21. doi:10.1007/bf02712670Schmittgen, T. D., & Livak, K. J. (2008). Analyzing real-time PCR data by the comparative CT method. Nature Protocols, 3(6), 1101-1108. doi:10.1038/nprot.2008.73Constantin, G. D., Krath, B. N., MacFarlane, S. A., Nicolaisen, M., Elisabeth Johansen, I., & Lund, O. S. (2004). Virus-induced gene silencing as a tool for functional genomics in a legume species. The Plant Journal, 40(4), 622-631. doi:10.1111/j.1365-313x.2004.02233.xWesley, S. V., Helliwell, C. A., Smith, N. A., Wang, M., Rouse, D. T., Liu, Q., … Waterhouse, P. M. (2001). Construct design for efficient, effective and high-throughput gene silencing in plants. The Plant Journal, 27(6), 581-590. doi:10.1046/j.1365-313x.2001.01105.xGuerineau F, Mullineaux P (1993) Plant transformation and expression vectors. In: Croy R, editor. Plant Molecular Biology. Oxford, UK: Bios Scientific Publishers, Academic Press. pp. 121–147.Clough, S. J., & Bent, A. F. (1998). Floral dip: a simplified method forAgrobacterium-mediated transformation ofArabidopsis thaliana. The Plant Journal, 16(6), 735-743. doi:10.1046/j.1365-313x.1998.00343.xBenlloch, R., Roque, E., Ferrándiz, C., Cosson, V., Caballero, T., Penmetsa, R. V., … Madueño, F. (2009). Analysis of B function in legumes: PISTILLATA proteins do not require the PI motif for floral organ development inMedicago truncatula. The Plant Journal, 60(1), 102-111. doi:10.1111/j.1365-313x.2009.03939.xRoque, E., Serwatowska, J., Cruz Rochina, M., Wen, J., Mysore, K. S., Yenush, L., … Cañas, L. A. (2012). Functional specialization of duplicated AP3-like genes inMedicago truncatula. The Plant Journal, 73(4), 663-675. doi:10.1111/tpj.12068Flanagan, C. A., Hu, Y., & Ma, H. (1996). Specific expression of the AGL1 MADS-box gene suggests regulatory functions in Arabidopsis gynoecium and ovule development. The Plant Journal, 10(2), 343-353. doi:10.1046/j.1365-313x.1996.10020343.xSieburth, L. E., & Meyerowitz, E. M. (1997). Molecular dissection of the AGAMOUS control region shows that cis elements for spatial regulation are located intragenically. The Plant Cell, 9(3), 355-365. doi:10.1105/tpc.9.3.355Busch, M. A. (1999). Activation of a Floral Homeotic Gene in Arabidopsis. Science, 285(5427), 585-587. doi:10.1126/science.285.5427.585Moyroud, E., Minguet, E. G., Ott, F., Yant, L., Posé, D., Monniaux, M., … Parcy, F. (2011). Prediction of Regulatory Interactions from Genome Sequences Using a Biophysical Model for the Arabidopsis LEAFY Transcription Factor. The Plant Cell, 23(4), 1293-1306. doi:10.1105/tpc.111.083329Grønlund, M., Constantin, G., Piednoir, E., Kovacev, J., Johansen, I. E., & Lund, O. S. (2008). Virus-induced gene silencing in Medicago truncatula and Lathyrus odorata. Virus Research, 135(2), 345-349. doi:10.1016/j.virusres.2008.04.005Mandel, M. A., Bowman, J. L., Kempin, S. A., Ma, H., Meyerowitz, E. M., & Yanofsky, M. F. (1992). Manipulation of flower structure in transgenic tobacco. Cell, 71(1), 133-143. doi:10.1016/0092-8674(92)90272-eMizukami, Y., & Ma, H. (1992). Ectopic expression of the floral homeotic gene AGAMOUS in transgenic Arabidopsis plants alters floral organ identity. Cell, 71(1), 119-131. doi:10.1016/0092-8674(92)90271-dCannon, S. B., Sterck, L., Rombauts, S., Sato, S., Cheung, F., Gouzy, J., … Young, N. D. (2006). Legume genome evolution viewed through the Medicago truncatula and Lotus japonicus genomes. Proceedings of the National Academy of Sciences, 103(40), 14959-14964. doi:10.1073/pnas.0603228103Young, N. D., & Bharti, A. K. (2012). Genome-Enabled Insights into Legume Biology. Annual Review of Plant Biology, 63(1), 283-305. doi:10.1146/annurev-arplant-042110-103754Jager, M. (2003). MADS-Box Genes in Ginkgo biloba and the Evolution of the AGAMOUS Family. Molecular Biology and Evolution, 20(5), 842-854. doi:10.1093/molbev/msg089Johansen, B., Pedersen, L. B., Skipper, M., & Frederiksen, S. (2002). MADS-box gene evolution—structure and transcription patterns. Molecular Phylogenetics and Evolution, 23(3), 458-480. doi:10.1016/s1055-7903(02)00032-5Rutledge, R., Regan, S., Nicolas, O., Fobert, P., Côté, C., Bosnich, W., … Stewart, D. (1998). Characterization of an AGAMOUS homologue from the conifer black spruce ( Picea mariana ) that produces floral homeotic conversions when expressed in Arabidopsis. The Plant Journal, 15(5), 625-634. doi:10.1046/j.1365-313x.1998.00250.xParcy, F., Nilsson, O., Busch, M. A., Lee, I., & Weigel, D. (1998). A genetic framework for floral patterning. Nature, 395(6702), 561-566. doi:10.1038/26903Causier, B., Bradley, D., Cook, H., & Davies, B. (2009). Conserved intragenic elements were critical for the evolution of the floral C-function. The Plant Journal, 58(1), 41-52. doi:10.1111/j.1365-313x.2008.03759.xAiroldi, C. A., & Davies, B. (2012). Gene Duplication and the Evolution of Plant MADS-box Transcription Factors. Journal of Genetics and Genomics, 39(4), 157-165. doi:10.1016/j.jgg.2012.02.008Giménez, E., Pineda, B., Capel, J., Antón, M. T., Atarés, A., Pérez-Martín, F., … Lozano, R. (2010). Functional Analysis of the Arlequin Mutant Corroborates the Essential Role of the ARLEQUIN/TAGL1 Gene during Reproductive Development of Tomato. PLoS ONE, 5(12), e14427. doi:10.1371/journal.pone.0014427Kater, M. M., Colombo, L., Franken, J., Busscher, M., Masiero, S., Van Lookeren Campagne, M. M., & Angenent, G. C. (1998). Multiple AGAMOUS Homologs from Cucumber and Petunia Differ in Their Ability to Induce Reproductive Organ Fate. The Plant Cell, 10(2), 171-182. doi:10.1105/tpc.10.2.171Tsuchimoto, S., van der Krol, A. R., & Chua, N. H. (1993). Ectopic expression of pMADS3 in transgenic petunia phenocopies the petunia blind mutant. The Plant Cell, 5(8), 843-853. doi:10.1105/tpc.5.8.843Airoldi, C. A., Bergonzi, S., & Davies, B. (2010). Single amino acid change alters the ability to specify male or female organ identity. Proceedings of the National Academy of Sciences, 107(44), 18898-18902. doi:10.1073/pnas.1009050107Causier, B., Castillo, R., Zhou, J., Ingram, R., Xue, Y., Schwarz-Sommer, Z., & Davies, B. (2005). Evolution in Action: Following Function in Duplicated Floral Homeotic Genes. Current Biology, 15(16), 1508-1512. doi:10.1016/j.cub.2005.07.063Birchler, J. A., & Veitia, R. A. (2007). The Gene Balance Hypothesis: From Classical Genetics to Modern Genomics. The Plant Cell, 19(2), 395-402. doi:10.1105/tpc.106.049338Birchler, J. A., & Veitia, R. A. (2009). The gene balance hypothesis: implications for gene regulation, quantitative traits and evolution. New Phytologist, 186(1), 54-62. doi:10.1111/j.1469-8137.2009.03087.xEdger, P. P., & Pires, J. C. (2009). Gene and genome duplications: the impact of dosage-sensitivity on the fate of nuclear genes. Chromosome Research, 17(5), 699-717. doi:10.1007/s10577-009-9055-9Freeling, M. (2006). Gene-balanced duplications, like tetraploidy, provide predictable drive to increase morphological complexity. Genome Research, 16(7), 805-814. doi:10.1101/gr.368140