100 research outputs found
Counterion adsorption on flexible polyelectrolytes: comparison of theories
Counterion adsorption on a flexible polyelectrolyte chain in a spherical
cavity is considered by taking a "permuted" charge distribution on the chain so
that the "adsorbed" counterions are allowed to move along the backbone. We
compute the degree of ionization by using self-consistent field theory (SCFT)
and compare with the previously developed variational theory. Analysis of
various contributions to the free energy in both theories reveals that the
equilibrium degree of ionization is attained mainly as an interplay of the
adsorption energy of counterions on the backbone, the translational entropy of
the small ions, and their correlated density fluctuations. Degree of ionization
computed from SCFT is significantly lower than that from the variational
formalism. The difference is entirely due to the density fluctuations of the
small ions in the system, which are accounted for in the variational procedure.
When these fluctuations are deliberately suppressed in the truncated
variational procedure, there emerges a remarkable quantitative agreement in the
various contributing factors to the equilibrium degree of ionization, in spite
of the fundamental differences in the approximations and computational
procedures used in these two schemes. Nevertheless, since the significant
effects from density fluctuations of small ions are not captured by the SCFT,
and due to the close agreement between SCFT and the other contributing factors
in the more transparent variational procedure, the latter is a better
computational tool for obtaining the degree of ionization
Weighted Tardiness Minimization in Job Shops with Setup Times by Hybrid Genetic Algorithm
Ownership and control in a competitive industry
We study a differentiated product market in which an investor initially owns a controlling stake in one of two competing firms and may acquire a non-controlling or a controlling stake in a competitor, either directly using her own assets, or indirectly via the controlled firm. While industry profits are maximized within a symmetric two product monopoly, the investor attains this only in exceptional cases. Instead, she sometimes acquires a noncontrolling stake. Or she invests asymmetrically rather than pursuing a full takeover if she acquires a controlling one. Generally, she invests indirectly if she only wants to affect the product market outcome, and directly if acquiring shares is profitable per se. --differentiated products,separation of ownership and control,private benefits of control
Mutations in HNF1A Result in Marked Alterations of Plasma Glycan Profile
A recent genome-wide association study identified hepatocyte nuclear factor 1-α (HNF1A) as a key regulator of fucosylation. We hypothesized that loss-of-function HNF1A mutations causal for maturity-onset diabetes of the young (MODY) would display altered fucosylation of N-linked glycans on plasma proteins and that glycan biomarkers could improve the efficiency of a diagnosis of HNF1A-MODY. In a pilot comparison of 33 subjects with HNF1A-MODY and 41 subjects with type 2 diabetes, 15 of 29 glycan measurements differed between the two groups. The DG9-glycan index, which is the ratio of fucosylated to nonfucosylated triantennary glycans, provided optimum discrimination in the pilot study and was examined further among additional subjects with HNF1A-MODY (n = 188), glucokinase (GCK)-MODY (n = 118), hepatocyte nuclear factor 4-α (HNF4A)-MODY (n = 40), type 1 diabetes (n = 98), type 2 diabetes (n = 167), and nondiabetic controls (n = 98). The DG9-glycan index was markedly lower in HNF1A-MODY than in controls or other diabetes subtypes, offered good discrimination between HNF1A-MODY and both type 1 and type 2 diabetes (C statistic ≥ 0.90), and enabled us to detect three previously undetected HNF1A mutations in patients with diabetes. In conclusion, glycan profiles are altered substantially in HNF1A-MODY, and the DG9-glycan index has potential clinical value as a diagnostic biomarker of HNF1A dysfunction
Towards a TILLING platform for functional genomics in Piel de Sapo melons
Background
The availability of genetic and genomic resources for melon has increased significantly, but functional genomics resources are still limited for this crop. TILLING is a powerful reverse genetics approach that can be utilized to generate novel mutations in candidate genes. A TILLING resource is available for cantalupensis melons, but not for inodorus melons, the other main commercial group.
Results
A new ethyl methanesulfonate-mutagenized (EMS) melon population was generated for the first time in an andromonoecious non-climacteric inodorus Piel de Sapo genetic background. Diverse mutant phenotypes in seedlings, vines and fruits were observed, some of which were of possible commercial interest. The population was first screened for mutations in three target genes involved in disease resistance and fruit quality (Cm-PDS, Cm-eIF4E and Cm-eIFI(iso)4E). The same genes were also tilled in the available monoecious and climacteric cantalupensis EMS melon population. The overall mutation density in this first Piel de Sapo TILLING platform was estimated to be 1 mutation/1.5 Mb by screening four additional genes (Cm-ACO1, Cm-NOR, Cm-DET1 and Cm-DHS). Thirty-three point mutations were found for the seven gene targets, six of which were predicted to have an impact on the function of the protein. The genotype/phenotype correlation was demonstrated for a loss-of-function mutation in the Phytoene desaturase gene, which is involved in carotenoid biosynthesis.
Conclusions
The TILLING approach was successful at providing new mutations in the genetic background of Piel de Sapo in most of the analyzed genes, even in genes for which natural variation is extremely low. This new resource will facilitate reverse genetics studies in non-climacteric melons, contributing materially to future genomic and breeding studies.González, M.; Xu, M.; Esteras Gómez, C.; Roig Montaner, MC.; Monforte Gilabert, AJ.; Troadec, C.; Pujol, M.... (2011). Towards a TILLING platform for functional genomics in Piel de sapo melons. BMC Research Notes. 4(289):289-299. doi:10.1186/1756-0500-4-289S2892994289The International Cucurbit Genomics Initiative (ICuGI). [ http://www.icugi.org ]González-Ibeas D, Blanca J, Roig C, González-To M, Picó B, Truniger V, Gómez P, Deleu W, Caño-Delgado A, Arús P, Nuez F, García-Mas J, Puigdomènech P, Aranda MA: MELOGEN: an EST database for melon functional genomics. BMC Genomics. 2007, 8: 306-10.1186/1471-2164-8-306.Fita A, Picó B, Monforte A, Nuez F: Genetics of Root System Architecture Using Near-isogenic Lines of Melon. J Am Soc Hortic Sci. 2008, 133: 448-458.Fernandez-Silva I, Eduardo I, Blanca J, Esteras C, Picó B, Nuez F, Arús P, Garcia-Mas J, Monforte AJ: Bin mapping of genomic and EST-derived SSRs in melon (Cucumis melo L.). Theor Appl Genet. 2008, 118: 139-150. 10.1007/s00122-008-0883-3.Deleu W, Esteras C, Roig C, González-To M, Fernández-Silva I, Blanca J, Aranda MA, Arús P, Nuez F, Monforte AJ, Picó MB, Garcia-Mas J: A set of EST-SNPs for map saturation and cultivar identification in melon. BMC Plant Biol. 2009, 9: 90-10.1186/1471-2229-9-90.Mascarell-Creus A, Cañizares J, Vilarrasa J, Mora-García S, Blanca J, González-Ibeas D, Saladié M, Roig C, Deleu W, Picó B, López-Bigas N, Aranda MA, Garcia-Mas J, Nuez F, Puigdomènech P, Caño-Delgado A: An oligo-based microarray offers novel transcriptomic approaches for the analysis of pathogen resistance and fruit quality traits in melon (Cucumis melo L.). BMC Genomics. 2009, 10: 467-10.1186/1471-2164-10-467.Blanca JM, Cañizares J, Ziarsolo P, Esteras C, Mir G, Nuez F, Garcia-Mas J, Pico B: Melon transcriptome characterization. SSRs and SNPs discovery for high throughput genotyping across the species. Plant Genome. 2011, 4 (2): 118-131. 10.3835/plantgenome2011.01.0003.González VM, Benjak A, Hénaff EM, Mir G, Casacuberta JM, Garcia-Mas J, Puigdomènech P: Sequencing of 6.7 Mb of the melon genome using a BAC pooling strategy. BMC Plant Biology. 2010, 10: 246-10.1186/1471-2229-10-246.Moreno E, Obando JM, Dos-Santos N, Fernández-Trujillo JP, Monforte AJ, Garcia-Mas J: Candidate genes and QTLs for fruit ripening and softening in melon. Theor Appl Genet. 2007, 116: 589-602.Essafi A, Díaz-Pendón JA, Moriones E, Monforte AJ, Garcia-Mas J, Martín-Hernández AM: Dissection of the oligogenic resistance to Cucumber mosaic virus in the melon accession PI 161375. Theor Appl Genet. 2009, 118: 275-284. 10.1007/s00122-008-0897-x.Comai L, Henikoff S: TILLING: practical single-nucleotide mutation discovery. Plant J. 2006, 45: 684-94. 10.1111/j.1365-313X.2006.02670.x.Cooper JL, Till BJ, Laport RG, Darlow MC, Kleffner JM, Jamai A, El-Mellouki T, Liu S, Ritchie R, Nielsen N, et al: TILLING to detect induced mutations in soybean. BMC Plant Biol. 2008, 8 (1): 9-10.1186/1471-2229-8-9.Dalmais M, Schmidt J, Le Signor C, Moussy F, Burstin J, Savois V, Aubert G, de Oliveira Y, Guichard C, Thompson R, Bendahmane A: UTILLdb, a Pisum sativum in silico forward and reverse genetics tool. Genome Biol. 2008, 9: R43-10.1186/gb-2008-9-2-r43.Dierking EC, Bilyeu KD: New sources of soybean meal and oil composition traits identified through TILLING. BMC Plant Biol. 2009, 9: 89-10.1186/1471-2229-9-89.Perry J, Brachmann A, Welham T, Binder A, Charpentier M, Groth M, Haage K, Markmann K, Wang TL, Parniske M: TILLING in Lotus japonicus identified large allelic series for symbiosis genes and revealed a bias in functionally defective ethyl methanesulfonate alleles toward glycine replacements. Plant Physiol. 2009, 151 (3): 1281-1291. 10.1104/pp.109.142190.Caldwell DG, McCallum N, Shaw P, Muehlbauer GJ, Marshall DF, Waugh R: A structured mutant population for forward and reverse genetics in Barley (Hordeum vulgare L.). Plant J. 2004, 40 (1): 143-150. 10.1111/j.1365-313X.2004.02190.x.Henikoff S, Bradley JT, Comai L: TILLING. Traditional mutagenesis meets functional genomics. Plant Physiol. 2004, 135: 630-636. 10.1104/pp.104.041061.Wu JL, Wu C, Lei C, Baraoidan M, Bordeos A, Madamba MR, Ramos-Pamplona M, Mauleon R, Portugal A, Ulat VJ, et al: Chemical- and irradiation-induced mutants of indica rice IR64 for forward and reverse genetics. Plant Mol Biol. 2005, 59 (1): 85-97. 10.1007/s11103-004-5112-0.Slade AJ, Fuerstenberg SI, Loeffler D, Steine MN, Facciotti D: A reverse genetic, nontransgenic approach to wheat crop improvement by TILLING. Nat Biotechnol. 2005, 23: 75-81. 10.1038/nbt1043.Till BJ, Cooper J, Tai TH, Colowit P, Greene EA, Henikoff S, Comai L: Discovery of chemically induced mutations in rice by TILLING. BMC Plant Biol. 2007, 7: 19-10.1186/1471-2229-7-19.Xin Z, Wang ML, Barkley NA, Burow G, Franks C, Pederson G, Burke J: Applying genotyping (TILLING) and phenotyping analyses to elucidate gene function in a chemically induced sorghum mutant population. BMC Plant Biol. 2008, 8: 103-10.1186/1471-2229-8-103.Dong C, Dalton-Morgan J, Vincent K, Sharp P: A modified TILLING method for wheat breeding. Plant Genome. 2009, 2: 39-47. 10.3835/plantgenome2008.10.0012.Sestili F, Botticella E, Bedo Z, Phillips A, Lafiandra D: Production of novel allelic variation for genes involved in starch biosynthesis through mutagenesis. Mol Breeding. 2010, 25: 145-154. 10.1007/s11032-009-9314-7.Watanabe S, Mizoguchi T, Aoki K, Kubo Y, Mori H, Imanishi S, Yamazaki Y, Shibata D, Ezura H: Ethylmethanesulfonate (EMS) mutagenesis of Solanum lycopersicum cv. Micro-Tom for large-scale mutant screens. Plant Biotech. 2007, 24: 33-38. 10.5511/plantbiotechnology.24.33.Elias R, Till BJ, Mba Ch, Al-Safadi B: Optimizing TILLING and Ecotilling techniques for potato (Solanum tuberosum L). BMC Res Notes. 2009, 2: 141-10.1186/1756-0500-2-141.Piron F, Nicolaı M, Minoıa S, Piednoir E, Moretti A, Salgues A, Zamir D, Caranta C, Bendahmane A: An induced mutation in tomato eIF4E leads to immunity to two Potyviruses. PLoS ONE. 2010, 5 (6): e11313-10.1371/journal.pone.0011313.Himelblau E, Gilchrist EJ, Buono K, Bizell C, Mentzer L, Vogelzang R, Osborn T, Amasino RM, Parkin IAP, Haughn : Forward and reverse genetics of papid cycling Brassica oleracea. Theor Appl Genet. 2009, 118: 953-961. 10.1007/s00122-008-0952-7.Stephenson P, Baker D, Girin T, Perez A, Amoah S, King GJ, Østergaard L: A rich TILLING resource for studying gene function in Brassica rapa. BMC Plant Biol. 2010, 10: 62-10.1186/1471-2229-10-62.Pitrat M: Melon (Cucumis melo L.). Handbook of Crop Breeding Vol I. Vegetables. Edited by: Prohens J, Nuez F. 2008, New York:Springer, 283-315.Dahmani-Mardas F, Troadec Ch, Boualem A, Leveque S, Alsadon AA, Aldoss AA, Dogimont C, Bendahman A: Engineering Melon Plants with Improved Fruit Shelf Life Using the TILLING Approach. PLoS ONE. 2010, 5: e15776-10.1371/journal.pone.0015776.Nieto C, Piron F, Dalmais M, Marco CF, Moriones E, Gómez-Guillamón ML, Truniger V, Gómez P, Garcia-Mas J, Aranda MA, Bendahmane A: EcoTILLING for the identification of allelic variants of melon eIF4E, a factor that controls virus susceptibility. BMC Plant Biol. 2007, 7: 34-10.1186/1471-2229-7-34.Qin G, Gu H, Ma L, Peng Y, Deng XW, Chen Z, Qu LJ: Disruption of phytoene desaturase gene results in albino and dwarf phenotypes in Arabidopsis by impairing chlorophyll, carotenoid, and gibberellin biosynthesis. Cell Res. 2007, 17: 471-482. 10.1038/cr.2007.40.Codons Optimized to Deliver Deleterious Lesions (CODDLe). [ http://www.proweb.org/input ]Lasserre E, Bouquin T, Hernández JA, Bull J, Pech JC, Balague C: Structure and expression of three genes encoding ACC oxidase homologs from melon (Cucumis melo L.). Mol Gen Genet. 1996, 251 (1): 81-90.Giovannoni JJ: Fruit ripening mutants yield insights into ripening control. Curr Opin Plant Biol. 2007, 10: 1-7. 10.1016/j.pbi.2006.11.012.Davuluri GR, van Tuinen A, Mustilli AC, Manfredonia A, Newman R, Burgess D, Brummell DA, King SR, Palys J, Uhlig J, Pennings HMJ, Bowler C: Manipulation of DET1 expression in tomato results in photomorphogenic phenotypes caused by post-transcriptional gene silencing. Plant J. 2004, 40: 344-354. 10.1111/j.1365-313X.2004.02218.x.Wei S, Li X, Gruber MI, Li R, Zhou R, Zebarjadi A, Hannoufa A: RNAi-mediated suppression of DET1 alters the levels of carotenoids and sinapate esters in seeds of Brassica napus. J Agric Food Chem. 2009, 57 (12): 5326-5333. 10.1021/jf803983w.Wang TW, Zhang CG, Wu W, Nowack LM, Madey E, Thompson JE: Antisense suppression of deoxyhypusine synthase in tomato delays fruit softening and alters growth and development DHS mediates the first of two sequential enzymatic reactions that activate eukaryotic translation initiation factor-5A. Plant Physiol. 2005, 138: 1372-1382. 10.1104/pp.105.060194.Ng PC, Henikoff S: SIFT: predicting amino acid changes that affect protein function. Nucleic Acids Res. 2003, 31 (13): 3812-3814. 10.1093/nar/gkg509.Guzman P, Ecker JR: Exploiting the triple response of Arabidopsis to identify ethylene-related mutants. The Plant Cell. 1990, 2: 513-523.Henikoff S, Comai L: Single-nucleotide mutations for plant functional genomics. Ann Rev Plant Biol. 2003, 54: 375-401. 10.1146/annurev.arplant.54.031902.135009.Greene EA, Codomo CA, Taylor NE, Henikoff JG, Till BJ, Reynolds SH, Enns LC, Burtner C, Johnson JE, Odden AR, et al: Spectrum of chemically induced mutations from a large-scale reverse genetic screen in Arabidopsis. Genetics. 2003, 164 (2): 731-740.Britt AB: DNA damage and repair in plants. Annu Rev Plant Physiol Plant Mol Biol. 1996, 47: 75-100. 10.1146/annurev.arplant.47.1.75.Truniger V, Nieto C, González-Ibeas D, Aranda M: Mechanism of plant eIF4E-mediated resistance against a Carmovirus (Tombusviridae): cap-independent translation of a viral RNA controlled in cis by an (a)virulence determinant. Plant J. 2008, 56 (5): 716-727. 10.1111/j.1365-313X.2008.03630.x.Gao Z, Johansen E, Eyers S, Thomas CL, Ellis THN, Maule AJ: The potyvirus recessive resistance gene, sbm1, identifies a novel role for translation initiation factor eIF4E in cell-to-cell trafficking. Plant J. 2004, 40 (3): 376-385. 10.1111/j.1365-313X.2004.02215.x.Kang BC, Yeam I, Frantz JD, Murphy JF, Jahn MM: The pvr1 locus in Capsicum encodes a translation initiation factor eIF4E that interacts with Tobacco etch virus VPg. Plant J. 2005, 42 (3): 392-405. 10.1111/j.1365-313X.2005.02381.x.Ruffel S, Gallois J, Lesage M, Caranta C: The recessive potyvirus resistance gene pot-1 is the tomato orthologue of the pepper pvr2-eiF4 genes. Mol Genet Genom. 2005, 274 (4): 346-353. 10.1007/s00438-005-0003-x.Nicaise V, German-Retana S, Sanjuán R, Dubrana MP, Mazier M, Maisonneuve B, Candresse T, Caranta C, LeGall O: The Eukaryotic Translation Initiation Factor 4E Controls Lettuce Susceptibility to the Potyvirus Lettuce mosaic virus1. Plant Physiol. 2003, 132: 1272-1282. 10.1104/pp.102.017855.Esteras C, Pascual L, Saladie M, Dogimont C, Garcia-Mas J, Nuez F, Picó B: Use of Ecotilling to identify natural allelic variants of melon candidate genes involved in fruit ripening. Proceedings Plant GEM8 Lisbon. 2009Levin I, Frankel P, Gilboa N, Tanny S, Lalazar A: The tomato dark green mutation is a novel allele of the tomato homolog of the DEETIOLATED1 gene. Theor Appl Genet. 2003, 106: 454-460.Kolotilin I, Koltai H, Tadmor Y, Bar-Or C, Reuveni M, Meir A, Nahon S, Shlomo S, Chen L, I Levin: Transcriptional profiling of high pigment-2dg tomato mutant links early fruit plastid biogenesis with its overproduction of phytonutrients. Plant Physiol. 2007, 145: 389-401. 10.1104/pp.107.102962
Microarray profiling of mononuclear peripheral blood cells identifies novle candidate genes related to chemoradiation response in rectal cancer
Preoperative chemoradiation significantly improves oncological outcome in locally advanced rectal cancer. However there is no effective method of predicting tumor response to chemoradiation in these patients. Peripheral blood mononuclear cells have emerged recently as pathology markers of cancer and other diseases, making possible their use as therapy predictors. Furthermore, the importance of the immune response in radiosensivity of solid organs led us to hypothesized that microarray gene expression profiling of peripheral blood mononuclear cells could identify patients with response to chemoradiation in rectal cancer. Thirty five 35 patients with locally advanced rectal cancer were recruited initially to perform the study. Peripheral blood samples were obtained before neaodjuvant treatment. RNA was extracted and purified to obtain cDNA and cRNA for hybridization of microarrays included in Human WG CodeLink bioarrays. Quantitative real time PCR was used to validate microarray experiment data. Results were correlated with pathological response, according to Mandard´s criteria and final UICC Stage (patients with tumor regression grade 1–2 and downstaging being defined as responders and patients with grade 3–5 and no downstaging as non-responders). Twenty seven out of 35 patients were finally included in the study. We performed a multiple t-test using Significance Analysis of Microarrays, to find those genes differing significantly in expression, between responders (n = 11) and non-responders (n = 16) to CRT. The differently expressed genes were: BC 035656.1, CIR, PRDM2, CAPG, FALZ, HLA-DPB2, NUPL2, and ZFP36. The measurement of FALZ (p = 0.029) gene expression level determined by qRT-PCR, showed statistically significant differences between the two groups. Gene expression profiling reveals novel genes in peripheral blood samples of mononuclear cells that could predict responders and non-responders to chemoradiation in patients with locally advanced rectal cancer. Moreover, our investigation added further evidence to the importance of mononuclear cells’ mediated response in the neoadjuvant treatment of rectal cancer.This investigation was supported by the Fundación Investigación Biomédica Mutua Madrileña. MC, CC and AB were supported by projects P08-TIC-4299 and CTS2200 of Junta de Andalucía, TIN2009-13489 of DGICT, Madrid, and GREIB PYR_2010-02 and 2010_05 of University of Granada
Sphingosine Kinase 1 Regulates the Akt/FOXO3a/Bim Pathway and Contributes to Apoptosis Resistance in Glioma Cells
The aim of this study was to investigate the mechanism through which Sphingosine kinase-1 (SPHK1) exerts its anti-apoptosis activity in glioma cancer cells. We here report that dysregulation of SPHK1 alters the sensitivity of glioma to apoptosis both in vitro and in vivo. Further mechanistic study examined the expression of Bcl-2 family members, including Bcl-2, Mcl-1, Bax and Bim, in SPHK1-overexpressing glioma cells and revealed that only pro-apoptotic Bim was downregulated by SPHK1. Moreover, the transcriptional level of Bim was also altered by SPHK1 in glioma cells. We next confirmed the correlation between SPHK1 and Bim expression in primary glioma specimens. Importantly, increasing SPHK1 expression in glioma cells markedly elevated Akt activity and phosphorylated inactivation of FOXO3a, which led to downregulation of Bim. A pharmacological approach showed that these effects of SPHK1 were dependent on phosphatidylinositol 3-kinase (PI3K). Furthermore, effects of SPHK1 on Akt/FOXO3a/Bim pathway could be reversed by SPHK1 specific RNA interference or SPHK1 inhibitor. Collectively, our results indicate that regulation of the Akt/FOXO3a/Bim pathway may be a novel mechanism by which SPHK1 protects glioma cells from apoptosis, thereby involved in glioma tumorigenesis
TGF-β–FOXO signalling maintains leukaemia-initiating cells in chronic myeloid leukaemia
Two step activation of FOXO3 by AMPK generates a coherent feed-forward loop determining excitotoxic cell fate
Cerebral ischemia and excitotoxic injury induce transient or permanent bioenergetic failure, and may result in neuronal apoptosis or necrosis. We have previously shown that ATP depletion and activation of AMP-activated protein kinase (AMPK) during excitotoxic injury induces neuronal apoptosis by transcription of the proapoptotic BH3 only protein, Bim. AMPK, however, also exerts pro-survival functions in neurons. The molecular switches that determine these differential outcomes are not well understood. Using an approach combining biochemistry, single cell imaging and computational modeling, we here demonstrate that excitotoxic injury activated the bim promoter in a FOXO3-dependent manner. The activation of AMPK reduced AKT activation, and led to dephosphorylation and nuclear translocation of FOXO3. Subsequent mutation studies indicated that bim gene activation during excitotoxic injury required direct FOXO3 phosphorylation by AMPK in the nucleus as a second activation step. Inhibition of this phosphorylation prevented Bim expression and protected neurons against excitotoxic and oxygen/glucose deprivation-induced injury. Systems analysis and computational modeling revealed that these two activation steps defined a coherent feedforward loop; a network motif capable of filtering any effects of short-term AMPK activation on bim gene induction. This may prevent unwanted AMPK-mediated Bim expression and apoptosis during transient or physiological bioenergetic stress
Influence of the Water Content on the Diffusion Coefficients of Li⁺ and Water across Naphthalenic Based Copolyimide Cation-Exchange Membranes
The transport of lithium ions in cation-exchange membranes based on sulfonated copolyimide membranes is reported. Diffusion coefficients of lithium are estimated as a function of the water content in membranes by using pulsed field gradient (PFG) NMR and electrical conductivity techniques. It is found that the lithium transport slightly decreases with the diminution of water for membranes with water content lying in the range 14 < λ < 26.5, where λ is the number of molecules of water per fixed sulfonate group. For λ < 14, the value of the diffusion coefficient of lithium experiences a sharp decay with the reduction of water in the membranes. The dependence of the diffusion of lithium on the humidity of the membranes calculated from conductivity data using Nernst–Planck type equations follows a trend similar to that observed by NMR. The possible explanation of the fact that the Haven ratio is higher than the unit is discussed. The diffusion of water estimated by 1H PFG-NMR in membranes neutralized with lithium decreases as λ decreases, but the drop is sharper in the region where the decrease of the diffusion of protons of water also undergoes considerable reduction. The diffusion of lithium ions computed by full molecular dynamics is similar to that estimated by NMR. However, for membranes with medium and low concentration of water, steady state conditions are not reached in the computations and the diffusion coefficients obtained by MD simulation techniques are overestimated. The curves depicting the variation of the diffusion coefficient of water estimated by NMR and full dynamics follow parallel trends, though the values of the diffusion coefficient in the latter case are somewhat higher. The WAXS diffractograms of fully hydrated membranes exhibit the ionomer peak at q = 2.8 nm⁻1, the peak being shifted to higher q as the water content of the membranes decreases. The diffractograms present additional peaks at higher q, common to wet and dry membranes, but the peaks are better resolved in the wet membranes. The ionomer peak is not detected in the diffractograms of dry membranes.The authors acknowledge financial support provided by the DGICYT (Dirección General de Investigación Cientifíca y Tecnológica) through Grant MAT2011-29174-C02-02
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