Structure–activity relationship study of antioxidative peptides by QSAR modeling: the amino acid next to C‐terminus affects the activity

Screening, isolation and in vitro assays have been used for characterization of antioxidative peptides derived from food proteins, and incompatible deductions of structural characteristics derived from the isolated peptides have been brought forward. However, there is still little information concerning the structure‐activity relationship of antioxidative peptides. QSAR modeling was performed, respectively, on synthetic tripeptides and tetrapeptides related to LLPHH. According to cumulative squared multiple correlation coefficients (R²), cumulative cross‐validation coefficients (Q²) and relative standard deviation for calibration set (RSD_c), two credible models for tripeptide and tetrapeptide databases, respectively, have been built with partial least squares (PLS) regression (R² for models of tripeptide and tetrapeptide are 0.744 and 0.943, Q² are 0.631 and 0.414, and RSD_c are 0.323 and 0.111, respectively). Meanwhile, according to the cumulative multiple correlation coefficient for the predictive set ($R_{\rm {ext}}^{2}$ ) and the relative standard deviation for the predictive set (RSD_p), the predictive ability of the model for tripeptides also is excellent ($R_{\rm {ext}}^{2}$ and RSD_p are 0.719 and 0.450, respectively). Hydrogen bond property and hydrophilicity of the amino acid residue next to the C‐terminus, and the hydrophobicity as well as electronic propertyof the N‐terminus are more significant; meanwhile, the electronic property of the C‐terminus is beneficial for antioxidant activity. The structural characteristics we found are very useful in understanding and predicting the peptide structures responsible for activity and development of functional foods with peptides as active compounds, or antioxidative peptides as alternatives to other antioxidants. Copyright © 2011 European Peptide Society and John Wiley & Sons, Ltd.     

Estimated genetic parameters for growth‐related traits in large yellow croaker Larimichthys crocea using microsatellites to assign parentage

To estimate the heritabilities of growth‐related traits in large yellow croaker, Larimichthys crocea, three independent full‐factorial crosses were created by crossing four males × four females, seven males × three females and four males × three females (set 1, set 2 and set 3). At 13 months post‐hatch, the juveniles were collected from three cross sets and measured for body mass (M), standard length (L_S) and body height (H_B). In addition, the parentage of the juveniles was assigned by genotyping six or seven polymorphic microsatellite loci. Out of the 959 juveniles, 99·6% could be assigned to a single parental pair. Heritabilities of growth‐related traits were estimated for individual and combined sets with the pedigrees reconstructed by using microsatellite genotypes. The heritability estimates at 13 month‐old were 0·02–0·30 for M, 0·02–0·25 for L_S and 0·03–0·36 for H_B. These results showed that the heritabilities of M, L_S and H_B were different among three sets, which suggested that different breeding strategies should be adopted for different sets.     

Direct Nanoscale Characterization of Deep Levels in AgCuInGaSe2 Using Electron Energy‐Loss Spectroscopy in the Scanning Transmission Electron Microscope

A new experimental framework for the characterization of defects in semiconductors is demonstrated. Through the direct, energy‐resolved correlation of three analytical techniques spanning six orders of magnitude in spatial resolution, a critical mid‐bandgap electronic trap level (E_V + 0.56 eV) within Ag_0.2Cu_0.8In_1?xGa_xSe₂ is traced to its nanoscale physical location and chemical source. This is achieved through a stepwise, site‐specific correlated characterization workflow consisting of device‐scale (≈1 mm²) deep level transient spectroscopy (DLTS) to survey the traps present, scanning probe–based DLTS (scanning‐DLTS) for mesoscale‐resolved (hundreds of nanometers) mapping of the target trap state's spatial distribution, and scanning transmission electron microscope based electron energy‐loss spectroscopy (STEM‐EELS) and X‐ray energy‐dispersive spectroscopy for nanoscale energy‐, structure, and chemical‐resolved investigation of the defect source. This first demonstration of the direct observation of sub‐bandgap defect levels via STEM‐EELS, combined with the DLTS methods, provides strong evidence that the long‐suspected Cu_In/Ga substitutional defects are indeed the most likely source of the E_V + 0.56 eV trap state and serves as a key example of this approach for the fundamental identification of defects within semiconductors, in general.     

Synthesis of Camphecene and Cytisine Conjugates Using Click Chemistry Methodology and Study of Their Antiviral Activity

A series of camphecene and quinolizidine alkaloid (?)‐cytisine conjugates has been obtained for the first time using ‘click’ chemistry methodology. The cytotoxicity and virus‐inhibiting activity of compounds were determined against MDCK cells and influenza virus A/Puerto Rico/8/34 (H1N1), correspondingly, in in vitro tests. Based on the results obtained, values of 50 % cytotoxic dose (CC₅₀), 50 % inhibition dose (IC₅₀) and selectivity index (SI) were determined for each compound. It has been shown that the antiviral activity is affected by the length and nature of linkers between cytisine and camphor units. Conjugate 13 ((1R,5S)‐3‐(6‐{4‐[(2‐{(E)‐[(1R,4R)‐1,7,7‐trimethylbicyclo[2.2.1]heptan‐2‐ylidene]amino}ethoxy)methyl]‐1H‐1,2,3‐triazol‐1‐yl}hexyl)‐1,2,3,4,5,6‐hexahydro‐8H‐1,5‐methanopyrido[1,2‐a][1,5]diazocin‐8‐one), which contains cytisine fragment separated from triazole ring by –C₆H₁₂– aliphatic linker, showed the highest activity at relatively low toxicity (CC₅₀=168 μmol, IC₅₀=8 μmol, SI=20). Its selectivity index appeared higher than that of reference compound, rimantadine. According to theoretical calculations, the antiviral activity of the lead compound 13 can be explained by its influence on the functioning of neuraminidase.     

Satellite detection of cumulative and lagged effects of drought on autumn leaf senescence over the Northern Hemisphere

Climate change has substantial influences on autumn leaf senescence, that is, the end of the growing season (EOS). Relative to the impacts of temperature and precipitation on EOS, the influence of drought is not well understood, especially considering that there are apparent cumulative and lagged effects of drought on plant growth. Here, we investigated the cumulative and lagged effects of drought (in terms of the Standardized Precipitation–Evapotranspiration Index, SPEI) on EOS derived from the normalized difference vegetation index (NDVI3g) data over the Northern Hemisphere extra‐tropical ecosystems (>30°N) during 1982–2015. The cumulative effect was determined by the number of antecedent months at which SPEI showed the maximum correlation with EOS (i.e., R_max‐cml) while the lag effect was determined by a month during which the maximum correlation between 1‐month SPEI and EOS occurred (i.e., R_max‐lag). We found cumulative effect of drought on EOS for 27.2% and lagged effect for 46.2% of the vegetated land area. For the dominant time scales where the R_max‐cml and R_max‐lag occurred, we observed 1–4 accumulated months for the cumulative effect and 2–6 lagged months for the lagged effect. At the biome level, drought had stronger impacts on EOS in grasslands, savannas, and shrubs than in forests, which may be related to the different root functional traits among vegetation types. Considering hydrological conditions, the mean values of both R_max‐cml and R_max‐lag decreased along the gradients of annual SPEI and its slope, suggesting stronger cumulative and lagged effects in drier regions as well as in areas with decreasing water availability. Furthermore, the average accumulated and lagged months tended to decline along the annual SPEI gradient but increase with increasing annual SPEI. Our results revealed that drought has strong cumulative and lagged effects on autumn phenology, and considering these effects could provide valuable information on the vegetation response to a changing climate.     

Cost-benefit relationships in sclerophyllous leaves of the ‘Bana’ vegetation in the Amazon region

This study estimated the construction const (CC) and maintenance cost (MC) of leaf tissue on the basis of dry mass (CC_Mass, MC_Mass) and leaf area (CC_Area, MC_Area), as well as the maximum leaf gas exchange capacity, so as to examine leaf cost:benefit relationship in six dominant species of the ‘Bana’ vegetation. Minimum and maximum CC_Mass averaged 1.71 ± 0.03 and 1.78 ± 0.03 g glucose g⁻¹. The CC_Mass showed a statistically significant positive correlation with crude fibre, and tended to decline as leaves were larger. Thus, smaller leaves tended to be built out of a more expensive material than that found in species bearing larger leaves. The average CC_Area of the ‘Bana’ species was 376 ± 15 g glucose m⁻². A robust correlation was found between CC_Area with leaf dry mass to leaf area ratio, as well as with leaf thickness, but not with leaf density. MC_Mass (g glucose g⁻¹ day⁻¹) and MC_Area (g glucose m⁻² day⁻¹⁾ were positively correlated. Maximum and minimum MC_Mass increased significantly with protein and lipid content, respectively. Maximum carbon assimilation (A _max) was positively correlated with CC_Area. All the species operated at high stomatal conductance (g _s) and C _i/C _a which suggested low short-term water use efficiency. Potential nitrogen use efficiency (PNUE = A _max/N) averaged 35.4 ± 1.8 mmol CO₂ mol⁻¹ N. As the sclerophylly index (g crude fibre g⁻¹ protein) increased, the ratio of CC_Area to A _max increased significantly. This result suggests a trade-off between investments in an expensive resistant sclerophyllous leaf which should maximize carbon gain in the long term.     

WFABC: a Wright–Fisher ABC‐based approach for inferring effective population sizes and selection coefficients from time‐sampled data

With novel developments in sequencing technologies, time‐sampled data are becoming more available and accessible. Naturally, there have been efforts in parallel to infer population genetic parameters from these data sets. Here, we compare and analyse four recent approaches based on the Wright–Fisher model for inferring selection coefficients (s) given effective population size (N_e), with simulated temporal data sets. Furthermore, we demonstrate the advantage of a recently proposed approximate Bayesian computation (ABC)‐based method that is able to correctly infer genomewide average N_e from time‐serial data, which is then set as a prior for inferring per‐site selection coefficients accurately and precisely. We implement this ABC method in a new software and apply it to a classical time‐serial data set of the medionigra genotype in the moth Panaxia dominula. We show that a recessive lethal model is the best explanation for the observed variation in allele frequency by implementing an estimator of the dominance ratio (h).     

Arrhenius and Gleason revisited: new hybrid models resolve an old controversy

Aim Studies have typically employed species–area relationships (SARs) from sample areas to fit either the power relationship or the logarithmic (exponential) relationship. However, the plots from empirical data often fall between these models. This article proposes two complementary and hybrid models as solutions to the controversy regarding which model best fits sample‐area SARs. Methods The two models are and , where S_A is number of species in an area, A, where z, b, c₁ and c₂ are predetermined parameters found by calculation, and where d and n are parameters to be fitted. The number of parameters is reduced from six to two by fixing the model at either end of the scale window of the data set, a step that is justified by the condition that the error or the bias, or both, in the first and the last data points is negligible. The new hybrid models as well as the power model and the logarithmic model are fitted to 10 data sets. Results The two proposed models fit well not only to Arrhenius’ and Gleason’s data sets, but also to the other six data sets. They also provide a good fit to data sets that follow a sigmoid (or triphasic) shape in log–log space and to data sets that do not fall between the power model and the logarithmic model. The log‐transformation of the dependent variable, S, does not affect the curve fit appreciably, although it enhances the performance of the new models somewhat. Main conclusions Sample‐area SARs have previously been shown to be convex upward, convex downward (concave), sigmoid and inverted sigmoid in log–log space. The new hybrid models describe successfully data sets with all these curve shapes, and should therefore produce good fits also to what are termed triphasic SARs.     

Brain region‐specific changes in N‐acylethanolamine contents with time of day

The N‐acylethanolamines (NAEs) exert important behavioral, physiological, and immunological effects through actions at cannabinoid and other receptors. We measured concentrations of three NAEs, the K_m and V_max for fatty acid amide hydrolysis (FAAH), FAAH protein and FAAH mRNA in prefrontal cortex, hippocampus, hypothalamus, amygdala, striatum, and cerebellum at 4 h intervals, starting at 03:00. Significant differences in N‐arachidonylethanolamine contents among the times examined occur in the prefrontal cortex (PFC), hippocampus, hypothalamus, and striatum. N‐Oleoylethanolamine concentrations exhibit large fluctuations over the day in the cerebellum, including a threefold decrease between 19:00 and 23:00. N‐Palmitoylethanolamine and N‐oleoylethanolamine were significantly, positively correlated in all regions examined except the hypothalamus. FAAH K_m values are significantly affected by time of day in PFC, hippocampus and amygdala and FAAH V_max values are significantly affected in PFC, hippocampus and cerebellum. However, correlational data indicate that FAAH does not play a primary role in the circadian regulation of the NAE concentrations. FAAH protein expression is not significantly different among the harvest times in any brain region examined. Concentrations of 2‐arachidonoylglycerol are significantly affected by time of harvest in the striatum and cerebellum, but not in other brain regions. Together, these data indicate that the NAEs exhibit diverse patterns of change with time of day that are likely the result of alterations in biosynthesis, and support the hypothesis that N‐arachidonylethanolamine is a tonic activator of cannabinoid receptor signaling.

     

Molecular architecture of the N‐type ATPase rotor ring from Burkholderia pseudomallei

The genome of the highly infectious bacterium Burkholderia pseudomallei harbors an atp operon that encodes an N‐type rotary ATPase, in addition to an operon for a regular F‐type rotary ATPase. The molecular architecture of N‐type ATPases is unknown and their biochemical properties and cellular functions are largely unexplored. We studied the B. pseudomallei N₁N_o‐type ATPase and investigated the structure and ion specificity of its membrane‐embedded c‐ring rotor by single‐particle electron cryo‐microscopy. Of several amphiphilic compounds tested for solubilizing the complex, the choice of the low‐density, low‐CMC detergent LDAO was optimal in terms of map quality and resolution. The cryoEM map of the c‐ring at 6.1 Å resolution reveals a heptadecameric oligomer with a molecular mass of ~141 kDa. Biochemical measurements indicate that the c₁₇ ring is H⁺ specific, demonstrating that the ATPase is proton‐coupled. The c₁₇ ring stoichiometry results in a very high ion‐to‐ATP ratio of 5.7. We propose that this N‐ATPase is a highly efficient proton pump that helps these melioidosis‐causing bacteria to survive in the hostile, acidic environment of phagosomes.     

Solvent‐accessible surface area: How well can be applied to hot‐spot detection?

A detailed comprehension of protein‐based interfaces is essential for the rational drug development. One of the key features of these interfaces is their solvent accessible surface area profile. With that in mind, we tested a group of 12 SASA‐based features for their ability to correlate and differentiate hot‐ and null‐spots. These were tested in three different data sets, explicit water MD, implicit water MD, and static PDB structure. We found no discernible improvement with the use of more comprehensive data sets obtained from molecular dynamics. The features tested were shown to be capable of discerning between hot‐ and null‐spots, while presenting low correlations. Residue standardization such as _relSASA_i or _rel/resSASA_i, improved the features as a tool to predict ΔΔG_binding values. A new method using support machine learning algorithms was developed: SBHD (Sasa‐Based Hot‐spot Detection). This method presents a precision, recall, and F1 score of 0.72, 0.81, and 0.76 for the training set and 0.91, 0.73, and 0.81 for an independent test set. Proteins 2014; 82:479–490. © 2013 Wiley Periodicals, Inc.     

Genotyping‐by‐sequencing for estimating relatedness in nonmodel organisms: Avoiding the trap of precise bias

There has been remarkably little attention to using the high resolution provided by genotyping‐by‐sequencing (i.e., RADseq and similar methods) for assessing relatedness in wildlife populations. A major hurdle is the genotyping error, especially allelic dropout, often found in this type of data that could lead to downward‐biased, yet precise, estimates of relatedness. Here, we assess the applicability of genotyping‐by‐sequencing for relatedness inferences given its relatively high genotyping error rate. Individuals of known relatedness were simulated under genotyping error, allelic dropout and missing data scenarios based on an empirical ddRAD data set, and their true relatedness was compared to that estimated by seven relatedness estimators. We found that an estimator chosen through such analyses can circumvent the influence of genotyping error, with the estimator of Ritland (Genetics Research, 67, 175) shown to be unaffected by allelic dropout and to be the most accurate when there is genotyping error. We also found that the choice of estimator should not rely solely on the strength of correlation between estimated and true relatedness as a strong correlation does not necessarily mean estimates are close to true relatedness. We also demonstrated how even a large SNP data set with genotyping error (allelic dropout or otherwise) or missing data still performs better than a perfectly genotyped microsatellite data set of tens of markers. The simulation‐based approach used here can be easily implemented by others on their own genotyping‐by‐sequencing data sets to confirm the most appropriate and powerful estimator for their data.     

Inter‐subunit interaction of gastric H+,K+‐ATPase prevents reverse reaction of the transport cycle

The gastric H⁺,K⁺‐ATPase is an ATP‐driven proton pump responsible for generating a million‐fold proton gradient across the gastric membrane. We present the structure of gastric H⁺,K⁺‐ATPase at 6.5 Å resolution as determined by electron crystallography of two‐dimensional crystals. The structure shows the catalytic α‐subunit and the non‐catalytic β‐subunit in a pseudo‐E₂P conformation. Different from Na⁺,K⁺‐ATPase, the N‐terminal tail of the β‐subunit is in direct contact with the phosphorylation domain of the α‐subunit. This interaction may hold the phosphorylation domain in place, thus stabilizing the enzyme conformation and preventing the reverse reaction of the transport cycle. Indeed, truncation of the β‐subunit N‐terminus allowed the reverse reaction to occur. These results suggest that the β‐subunit N‐terminus prevents the reverse reaction from E₂P to E₁P, which is likely to be relevant for the generation of a large H⁺ gradient in vivo situation.     

Pharmacokinetics of nateglinide enantiomers and their metabolites in Goto‐Kakizaki rats,a model for type 2 diabetes mellitus

The pharmacokinetics of (?)‐N‐(trans‐4‐isopropylcyclohexanecarbonyl)‐D ‐phenylalanine (nateglinide) and its enantiomer (L‐enantiomer) was studied in Goto‐Kakizaki (GK) rats after intravenous administration of nateglinide or L‐enantiomer at a dose of 40 μmol/kg body weight. Nateglinide, its L‐enantiomer and their metabolites in serum, bile and urine were determined. The total clearance (CL_tot) and the volume of distribution (V_d) was slightly higher for nateglinide than those for L‐enantiomer in control rats, although the differences were not statistically significant. The cumulative excretions of L‐M1 (major metabolite of L‐enantiomer) and L‐M2 (major metabolite of L‐enantiomer) into bile were almost the same as that of M1 (major metabolite of nateglinide)and M2 (major metabolite of nateglinide). In GK rats, CL_tot and V_d were higher for nateglinide than those for L‐enantiomer. The cumulative excretion of L‐M1 and L‐M2 were not different from those of M1 and M2, respectively, into bile or urine. CL_tot and V_d for nateglinide or L‐enantiomer in GK rats were not different from those in control rats. The total excretion of M1, M2, L‐M1, and L‐M2 into bile or urine in GK rats was not substantially different from that of control rats. These results suggest that the L‐enantiomer of nateglinide shows higher CL_tot and V_d compared with nateglinide, especially in the diabetic state. Chirality, 2010. © 2009 Wiley‐Liss, Inc.     

The impact of vessel size on vulnerability curves: data and models for within‐species variability in saplings of aspen,Populus tremuloides Michx

The objective of this study was to quantify the relationship between vulnerability to cavitation and vessel diameter within a species. We measured vulnerability curves (VCs: percentage loss hydraulic conductivity versus tension) in aspen stems and measured vessel‐size distributions. Measurements were done on seed‐grown, 4‐month‐old aspen (Populus tremuloides Michx) grown in a greenhouse. VCs of stem segments were measured using a centrifuge technique and by a staining technique that allowed a VC to be constructed based on vessel diameter size‐classes (D). Vessel‐based VCs were also fitted to Weibull cumulative distribution functions (CDF), which provided best‐fit values of Weibull CDF constants (c and b) and P₅₀ = the tension causing 50% loss of hydraulic conductivity. We show that P₅₀ = 6.166D^?0.3134 (R² = 0.995) and that b and 1/c are both linear functions of D with R² > 0.95. The results are discussed in terms of models of VCs based on vessel D size‐classes and in terms of concepts such as the ‘pit area hypothesis’ and vessel pathway redundancy.     

Performance of nonparametric species richness estimators in a high diversity plant community

Abstract. The efficiency of four nonparametric species richness estimators — first‐order Jackknife, second‐order Jackknife, Chao2 and Bootstrap — was tested using simulated quadrat sampling of two field data sets (a sandy ‘Dune’ and adjacent ‘Swale’) in high diversity shrublands (kwongan) in south‐western Australia. The data sets each comprised > 100 perennial plant species and > 10 000 individuals, and the explicit (x‐y co‐ordinate) location of every individual. We applied two simulated sampling strategies to these data sets based on sampling quadrats of unit sizes 1/400th and 1/100th of total plot area. For each site and sampling strategy we obtained 250 independent sample curves, of 250 quadrats each, and compared the estimators’ performances by using three indices of bias and precision: MRE (mean relative error), MSRE (mean squared relative error) and OVER (percentage overestimation). The analysis presented here is unique in providing sample estimates derived from a complete, field‐based population census for a high diversity plant community. In general the true reference value was approached faster for a comparable area sampled for the smaller quadrat size and for the swale field data set, which was characterized by smaller plant size and higher plant density. Nevertheless, at least 15–30% of the total area needed to be sampled before reasonable estimates of S_t (total species richness) were obtained. In most field surveys, typically less than 1% of the total study domain is likely to be sampled, and at this sampling intensity underestimation is a problem. Results showed that the second‐order Jackknife approached the actual value of S_t more quickly than the other estimators. All four estimators were better than S_obs (observed number of species). However, the behaviour of the tested estimators was not as good as expected, and even with large sample size (number of quadrats sampled) all of them failed to provide reliable estimates. First‐ and second‐order Jackknives were positively biased whereas Chao2 and Bootstrap were negatively biased. The observed limitations in the estimators’ performance suggests that there is still scope for new tools to be developed by statisticians to assist in the estimation of species richness from sample data, especially in communities with high species richness.     

Structure-function relationship of assimilatory nitrite reductases from the leaf and root of tobacco based on high-resolution structures

Tobacco expresses four isomers of assimilatory nitrite reductase (aNiR), leaf‐type (Nii1 and Nii3), and root‐type (Nii2 and Nii4). The high‐resolution crystal structures of Nii3 and Nii4, determined at 1.25 and 2.3 Å resolutions, respectively, revealed that both proteins had very similar structures. The Nii3 structure provided detailed geometries for the [4Fe–4S] cluster and the siroheme prosthetic groups. We have generated two types of Nii3 variants: one set focuses on residue Met175 (Nii3‐M175G, Nii3‐M175E, and Nii3‐M175K), a residue that is located on the substrate entrance pathway; the second set targets residue Gln448 (Nii3‐Q448K), a residue near the prosthetic groups. Comparison of the structures and kinetics of the Nii3 wild‐type (Nii3‐WT) and the Met175 variants showed that the hydrophobic side‐chain of Met175 facilitated enzyme efficiency (k_cat/K_m). The Nii4‐WT has Lys449 at the equivalent position of Gln448 in Nii3‐WT. The enzyme activity assay revealed that the turnover number (k_cat) and Michaelis constant (K_m) of Nii4‐WT were lower than those of Nii3‐WT. However, the k_cat/K_m of Nii4‐WT was about 1.4 times higher than that of Nii3‐WT. A comparison of the kinetics of the Nii3‐Q448K and Nii4‐K449Q variants revealed that the change in k_cat/K_m was brought about by the difference in Residue 448 (defined as Gln448 in Nii3 and Lys449 in Nii4). By combining detailed crystal structures with enzyme kinetics, we have proposed that Nii3 is the low‐affinity and Nii4 is the high‐affinity aNiR.     

Estimation of growth parameters from published data for several Mediterranean fishes

Two sets of von Bertalanffy growth parameter (VBGP) estimates are provided for several Mediterranean fish stocks. All estimates are based on the non‐linear least square regression and accompanied by uncertainty measures (i.e. standard errors). The first set consists of growth parameters estimated from 73 published length‐at‐age data with no previous VBGP estimations; in this case, fitting was possible for 30 length‐at‐age sets, corresponding to 22 species, two estimates of which (Mycteroperca rubra and Myctophum punctatum) are the first for the Mediterranean. The second set refers to the re‐estimation of VBGPs from 69 published length‐at‐age data with available original VBGP estimates derived from linear methods (i.e. Ford‐Walford, von Bertalanffy and Gulland‐Holt plots); in this case, fitting was possible for 50 sets. Overall VBGP estimation was not possible for 43 and 19 cases for the first and second sets, respectively. This was because either (a) <4 mean length‐at‐age data were available, or (b) fitting was not possible because of an exponential or a very slow linear increase of length with age, or (c) estimates were unrealistic (i.e. L_max/L_∞ < 0.7) mainly because of unrealistic length‐at‐ages and/or insufficient sampling of older individuals. These estimations and re‐estimations enrich the available data on growth parameters of Mediterranean fishes, both in terms of quantity and quality of information.     

High‐Performance Liquid Chromatographic Enantioseparation of Unusual Isoxazoline‐Fused 2‐Aminocyclopentanecarboxylic Acids on (+)‐(18‐Crown‐6)‐2,3,11,12‐Tetracarboxylic Acid‐Based Chiral Stationary Phases

The enantiomers of four unusual isoxazoline‐fused 2‐aminocyclopentanecarboxylic acids were directly separated on chiral stationary phases containing (+)‐(18‐crown‐6)‐2,3,11,12‐tetracarboxylic acid as chiral selector. The nature of the alcoholic modifier (MeOH, EtOH, IPA) exerted a great effect on the retention, whereas the selectivity and resolution did not change substantially. Two types of dependence of retention on alcohol content were detected: k₁ increased continuously with increasing alcohol content or a U‐shaped retention curve was observed. A comparison of the chromatographic data obtained with HCOOH, AcOH, TFA, HClO₄, H₂SO₄, or H₃PO₄ as acidic modifier at a constant concentration demonstrated that in most cases, larger k values were obtained on the application of AcOH or HCOOH, and an increase of the acid content resulted in a decrease of retention. Some mechanistic aspects of the chiral recognition process are discussed with respect to the structures of the analytes and selector. The sequence of elution of the enantiomers was determined in all cases. Chirality 24:817‐824, 2012. © 2012 Wiley Periodicals, Inc.