Above 100 GPa shock pressures, sapphire becomes opaque and electrically conducting because of shock-induced defects. Such effects prevent temperature and dc conductivity measurements of materials compressed quasi-isentropically. Opacities and electrical conductivities at ~100 GPa are non-equilibrium, rather than thermodynamic parameters. We have performed electronic structure calculations as a guide in predicting and interpreting shock experiments and possibly to discover a window up to ~200 GPa. Our calculations indicate shocked sapphire does not metallize by band overlap at ~300 GPa, as suggested previously by measured non-equilibrium data. Shock-compressed Al2O3 melts to a metallic liquid at ~500 GPa and 10,000 K and its conductivity increases rapidly to ~2000 Ω−1cm−1 at ~900 GPa. At these high shock temperatures and pressures sapphire is in thermal equilibrium. Calculated conductivity of Al2O3 is similar to those measured for metallic fluid H, N, O, Rb, and Cs. Despite different materials, pressures and temperatures, and compression techniques, both experimental and theoretical, conductivities of all these poor metals reach a common end state typical of strong-scattering disordered materials.Sapphire (Al The experimental conditions at which metallization was observed2 and “very low temperatures”2O3 was used to achieve those extreme conditionsSingle-crystal Al2 contained between two disks of c-cut sapphire. A multiple shock wave is generated by a shock in liquid H2 reverberating between incompressible sapphire anvils. Measured electrical resistivities of shocked sapphirec-cut sapphire to become opaque at shock pressures in the range 100 to 130 GPaMetallic fluid hydrogen (MFH) was made in thermal equilibrium by quasi-isentropic, multiple-shock compression of liquid HFinding the solution is a challenge. Shocked sapphire anvils are out of thermal equilibrium up to some unknown shock pressure and thermally equilibrated at higher pressures. The anvils melt at some as-yet unknown high pressure and possible solid-solid transitions might occur. Relatively little is known about sapphire at shock pressures above 100 GPa; much less is known about other possible anvil materials.To identify materials with improved properties, we are using an integrated theoretical/experimental approach. Electronic structure calculations provide insight on how to interpret experimental results and suggest possible new experiments. Electronic structure calculations yield intrinsic thermodynamic values. Opacity and electrical resistivity of sapphire at 100 GPa pressure are caused by shock-induced defects, which means they are extrinsic. Electronic structure calculations yield equilibrium intrinsic parameters that are estimates of physical limits of improvements that might be made and provide predictions of thermodynamic phenomena, such as melting. In the case of sapphire, the dynamic compression process itself can be varied. Shock-wave profiles have been measured for shocks travelling in seven directions in the sapphire rhombohedral latticeGiant Planets. High pressures and temperatures occur naturally in planetary interiors, which provide challenges to understanding highly condensed matter at extreme conditions792The multiple-shock technique enabled investigations of highly condensed fluid H, N and O up to 180 GPa (1.8 Mbar) and temperatures of a few 1000 K. Metallic monatomic fluid H2O3 are determined using published Hugoniot data of Al2O3 up to 340 GPa142O3 have been calculated at 25 GPa and 100 GPa2O32O3) is a strong material, it can have a complex two-wave elastic-plastic shock wave structure that must be taken into account in analysis of dynamic-compression experiments. For this reason, shock-wave temporal profiles have been measured, which demonstrate that above 90 GPa sapphire has only a single plastic shock waveDynamic pressures in Al2O3 have also been measured from 1.1 to 1.9 TPa. Those Hugoniot data of Al2O3 show that shock pressure increases rapidly with density above 500 GPa, which was proposed to be caused by a transition to a semiconducting liquid on melting2O3 has been calculated up to 370 GPa2O3 has a relatively small component of thermal pressure up to ~400 GPa and thus Al2O3 is ideal for performing shock-reverberation experiments at lower dynamic pressuresEquation-of-state Hugoniot data of Al2O3 is an integral part of those dynamic experiments, electrical properties of Al2O3 under dynamic compression must be determined to interpret measured conductivity voltage histories. Since metal electrodes are inserted through an Al2O3 anvil for the measurement of the electrical current and voltage of a fluid under shock reverberation2O3 anvils is large compared to that of a fluid sample so that current is not shunted through shocked Al2O3 rather than conducted through the fluid sample. For this reason, electrical resistivities of shocked Al2O3 were measured up to 220 GPaSince Al3 Ω−1cm−1 for H and 10−2 Ω−1cm−1 for Al2O3). Thus, measured resistivities of shocked Al2O3 demonstrate negligible effect on conductivity measurements made to date. However, based on extrapolation of measured electrical conductivities of sapphire from 220 to 300 GPa, conductivity of single-shocked crystalline Al2O3 might reach that of a strong-scattering poor metal at a shock pressure of ~300 GPa2O3 does not become a poor metal at a shock pressure of ~300 GPa. Rather, measured conductivities2O3 lattice.At 140 GPa fluid H, N and O are strong-scattering poor metals whose conductivities are ~5 orders of magnitude higher than those of shocked sapphire  chemical bonds of Al2O3, we have computed the equation of state (EOS) of Al2O3. A crucial measure for theoretical EOS data is the principle Hugoniot curve, describing the shock adiabatically through a relation between the initial and final internal energy, pressure and volume, respectively,  and  according to the following Rankine-Hugoniot equation:To explore the physical, electrical and optical properties of AlE1 at temperature T1 is the sum of the ion kinetic energy 3/2kBT1, the time average of the DFT potential energy, and zero-point energy with kB being the Boltzmann constant. The pressure consists of contributions from the electronic Pe and ionic Pi components. The electronic pressure part is evaluated using the force provided by first-principle simulations, which contains contributions from the direct ion-ion interaction and a term from the gradient of the electronic total energy. The ionic pressure part is computed from the ideal gas expression P = Pe + ρnkBT, where ρn is the number density. For the sapphire principal Hugoniot curve, the initial density is ρ = 4.0 g/cm3.where the internal energy ab initio molecular dynamics simulations were performed for different temperatures T. For a given density and a set of temperatures, we plotted (E1 − E0) along with 1/2(V1 − V0)(P0 + P1) as a function of temperature. The intersection of the two curves fixed the principal Hugoniot point  that satisfies Eq. (1). The Hugoniot curve and the relevant optical and electrical data for Al2O3 are reported in ρ = 9.0 g/cm3, the calculated pressure is 1429 GPa and temperature is 49,457 K. The good agreement between the theoretical and the experimental Hugoniot validates the parameters and methodology chosen for the calculations. However, it is important to point out that a measured Hugoniot is relatively insensitive to disorder of a material and defects were not included in the calculations. Thus, this comparison is essentially a self-consistency check. All the calculations were performed under hydrostatic conditions with the pressure and temperature increased in steps.The Hugoniot points are determined by the following way. For a given density, a fixed supercell of 32 Al and 48 O atoms was constructed from the ambient-pressure corundum structure. A series of ω,The electrical conductivity is calculated using the most general formulation given by the Kubo-Greenwood (KG) formulation without assumptions made on the ionic structure or on the electron-ion interactions. This method did not include the electron-electron scatterings. In the framework of the independent particle approximation, the Kubo-Greenwood formulation gives the real part of the electrical conductivity as a function of frequency ω is the frequency, Ω is the volume of the supercell, N is the total number of energy bands used, Ψi,k and εi,k are the electronic eigenstates and eigenvalues for the electronic state i at k, f is the Fermi distribution function, and ω(k) represents the k-point weighing factor. Other relevant properties can be derived from the frequency-dependent real part of the electrical conductivity. It is noteworthy that this equation does not fully take into account electron-electron scattering effects.where dc conductivity σdc can be estimated from the frequency dependence σ(ω) in the limit at which ω → 0. Significant variation of the dc conductivity along the principal Hugoniot is depicted in dc conductivity of sapphire below 300 GPa is 5 Ω−1cm−1 at 220 GPadc conductivity is simply due to the fact that Al2O3 is still in the insulating state. Above 500 GPa, the calculated dc conductivity increases rapidly and reaches 181 Ω−1cm−1 at 533 GPa. At 1112 GPa, the dc conductivity attains a value of 1515 Ω−1cm−1. This value is typical of strong-scattering metallic fluids H, N and O at 100 GPa pressures112The behavior of the frequency-dependent conductivity and reflectivity at different Hugoniot points is shown in T and entropy S. The relative contributions of the two are determined by the nature of chemical bonding in the material. The extremes are compressible van der Waals fluids and weakly compressible strong materials, such as oxides. In this case, up to a shock pressure of ~900 GPa, the pressure is caused by the compression of the relatively strong Al2O3 lattice and a modest shock-induced thermal pressure of the electrons. In this regime, irreversible shock energy is mainly converted to compressing, disordering and heating of the Al2O3 lattice and from the heating and excitation of electrons across the mobility gap into the conduction band of disordered Al2O3. At ~900 GPa, the shock-induced entropy is essentially saturated and shock energy at higher pressures transfers preferentially into thermal energy. Above 900 GPa, the electrical conductivity essentially plateaus at ~2000 Ω−1cm−1. This trend is typical of strong-scattering fluid metals such as H, N and O which have a similar conductivity. The present results show strong solid oxides at high dynamic pressures approaching ~TPa have an electrical conductivity similar those of compressible fluid metals. The essential difference is that H, N and O reach the maximum conductivity at 100–140 GPa at 3000 K or higher. In comparison, to reach the maximum conductivity, strong Al2O3 and, probably other oxides, requires dynamic pressures up to 900 GPa or even higher and shock-induced temperatures of ~30,000 K. The details are dependent on oxide bond strength and shock-induced thermal energy.It is well known that energy dissipation from shock compression is converted into temperature dc conductivity, we have computed the density of states (DOS) of Al2O3 along the Hugoniot (s band (−26 eV to −18 eV) and the O-2p band (−11 eV to 0 eV). The band gap energy separating the occupied states at the top of the valence band and the conduction band decreases with increasing pressure. At ρ = 6.3 g/cm3, the band gap was calculated to be approximately 6 eV. At ρ = 7.24 g/cm3, localized mid-gap band of predominately O-2p character starts to emerge. The increased conductivity depends on the coupled closure of the energy gap. The DOS shows the 2p orbital of O and 3p orbital of Al are responsible for the electron conductivity. It is noteworthy that sapphire becomes opaque and electrically conducting because of shock-induced defects above 100 GPa shock pressures. The investigation of shock-induced effects will require substantially larger supercell and this is beyond the scope of this study.To explain the trend in the Hugoniot . The resN is the total number of total atoms in the system, ri(t) is the atomic position at a time of t and ri(0) is the initial position of atom i, and <…> represents the ensemble average. We have computed the MSD of Al and O atoms for Al2O3 in MD simulations along the Hugoniot. The results summarized in 2O3 is a liquid with mobile Al and O atoms at ρ = 7.24 g/cm3 and 533 GPa. Incidentally this corresponds to the pressure of 533 GPa where the dc conductivity has increased. From the MSD 2D/kbT, where σ is the conductivity, D is the diffusion coefficient, n represents the ionic concentration , z is the valence of the charge carrier , e the elementary charge of an electron, kb is the Boltzmann constant and T the temperature. The calculated bulk ionic conductivity value is 85.9 Ω−1cm−1 at 10,116 K and ρ = 7.24 g/cm3, 142.7 Ω−1cm−1 at 13,767 K and ρ = 7.62 g/cm3 and 313 Ω−1cm−1 at 27,829 K and ρ = 8.4 g/cm3, respectively. Note that the total conductivity is a sum of the electrical and ionic contributions. The calculated dc conductivity as a function of pressure is shown in The atomic mean square displacement (MSD) is an important parameter to investigate the diffusion of a system. The MSD can be calculated for the atomic displacements as a function of time,  the MSD , the dif2O3 structure which was reported to be stable above 130 GPa172O3 has melted and the gap closed as shown in dc conductivity σdc estimated from −1cm−1. We then quenched the high-temperature structure to room temperature at 300 GPa. The quenched glass became an insulator with a band gap of 7 eV  and perovskite phases of Al2O3.We have also investigated the MSD for the dynamical behavior of the Al and O atoms of the quenched solid at 300 GPa. Below 6000 K, the Al and O atoms are not diffusive. Above 10,000 K the Al and O atoms become mobile and Ala liquid . Once ag2O3 at 6.3 g/cm3 using a larger supercell consisted of 270 atoms. The result is shown in 2O3. The molten states were generated by heating the structure in the MD box by raising the temperature. In the absence of a liquid-solid interface, the “melting” condition should correspond to mechanical melting which has a temperature higher than thermodynamic melting2O3 is still degenerate and electron-electron scatterings may only increase the electrical conductivity slightly but will not alter the predicted temperature trend significantly. On the other hand, the importance of electron-electron scattering processes to the electrical conductivity is still a subject of debate. A recent calculation on the electrical conductivity of Fe at high temperature and high pressureFinally, we wish to comment on the calculations. We have tested the system size effect on the electrical conductivity by repeating the calculation on melted AlAb initio molecular dynamics simulations for Al2O3 under shocked compression up to ~1500 GPa have been performed. Finite electrical conductivity in Al2O3 is predicted to exist only in the melt, as the quenched melt is shown to be an insulator. Al2O3 conductivity at 900 GPa of 2000 Ω−1-cm−1 is typical of the conductivities of metallic fluid H, N, and O on completion of crossovers from diatomic insulators to strong-scattering monatomic fluid metals under quasi-isentropic compression. The simulated EOS of Al2O3 is in good agreement with experimental data for the principal Hugoniot. The dc conductivity was found to increase rapidly above 500 GPa, In addition, the calculated mean squared displacements suggest Al2O3 is liquid above ~10,000 K. The present results provide an avenue to understanding of the metallization for shocked Al2O3.Ab initio MD simulations for Al2O3 were performed with the NPT  ensemble recently implemented in Vienna Ab initio Simulation Package (VASP) code26272O3. The duration of the simulation was at least 5 ps. A plane-wave cutoff of 500 eV was used. Brillouin zone sampling of 3 × 3 × 3 k-meshes for the supercell was employed. The time step used in the MD simulation was 1 fs and the self-consistency on the total energy was chosen to be 1 × 10−5 eV.How to cite this article: Liu, H. et al. The electrical conductivity of Al2O3 under shock-compression. Sci. Rep.5, 12823; doi: 10.1038/srep12823 (2015).


III‐HS in oceanic conditions into bioavailable aquatic FeII forms, highlights the importance of river‐derived HS as an iron source for marine organisms. Consequently, such mechanisms are a vital component of the upper‐ocean iron biogeochemistry cycle.Humic substances (HS) are important iron chelators responsible for the transport of iron from freshwater systems to the open sea, where iron is essential for marine organisms. Evidence suggests that iron complexed to HS comprises the bulk of the iron ligand pool in near‐coastal waters and shelf seas. River‐derived HS have been investigated to study their transport to, and dwell in oceanic waters. A library of iron model compounds and river‐derived Fe‐HS samples were probed in a combined X‐ray absorption spectroscopy (XAS) and valence‐to‐core X‐ray emission spectroscopy (VtC‐XES) study at the Fe K‐edge. The analyses performed revealed that iron complexation in HS samples is only dependent on oxygen‐containing HS functional groups, such as carboxyl and phenol. The photoreduction mechanism of Fe For the first time, VtC‐XESX‐ray absorption near edge structure (XANES) and extended X‐ray absorption fine structure (EXAFS) techniques have previously been used to investigate Fe‐HS complexes in lakes and soils.1–15) containing FeII and FeIII oxidation states, and with different ligand scaffolds  were investigated as references. The model compounds reflected the possible oxidation states and coordination modes that might be contained within the aquatic HS samples. The XANES spectra and the first derivative of the model compounds are shown in Figure S2 (Supporting Information), while the edge energies based on the first maximum in the first derivative are tabulated in Table S1 (Supporting Information). The edge energies of the model compounds span a range of about 5 eV, with increasing edge energy upon increasing oxidation state and electronegativity of the first shell atoms. Figure S3 (Supporting Information) shows the normalized XANES spectra and the first derivative of HS samples  differ markedly in the XANES region compared to the HS samples.In Figure III to FeII was observed in NR samples exposed to diffuse natural sunlight on a daily basis  is shown in Figure III complexes with the marine siderophore aquachelin showed a similar timescale, with 70 % of FeIII reduced into FeII after 4.5 hours.Besides a shift in the Fe K‐edges of iron in the NR samples, a small shift and sharpening of the pre‐edge peak (transformation from a centrosymmetric to a non‐centrosymmetric site4 (FeIIIO6), 5 (FeIIIO6), and 13 (FeIIO6). The use of model compounds very similar to 4 and 5 were shown to give the best fitting results in an earlier study of HS.4, 52 % 5) and CB0 13 10 s  supports the previous assignment of FeIIIO6 coordination. As reduction proceeds in the NR and CB0 13 samples, the amounts of 4 (FeIIIO6) and 5 (FeIIIO6) decrease. By comparison, 13 (FeIIO6) increases and reaches its highest proportions in NR 3/21 (64 %) and CB0 13 60s (61 %). The reduced FeII species may possess an FeIIO6 coordination environment, either as [Fe(H2O)6]2+ and/or as lower‐affinity Fe‐HS complexes available to biota, as exemplified in Figure Linear combination fitting was performed to obtain quantitative information on the most likely first shell coordination modes in the photoreduced NR and CB0 13 samples. The normalized spectra of HS were fitted  to model compounds 5 (FeIIIO6), 6 (FeIIIO6), 9 (FeIIIO3N3), 10 (FeIIIO3S3), 12 (FeIIIC2N4), and 14 (FeIIN6) were measured and used to fit the study object, the high molecular weight fraction CB0 13. The model compounds contain different first shell neighbors and geometries that are likely to be present in CB0 13. The k3‐weighted EXAFS spectra are shown in Figure S5 (Supporting Information) and all compounds were fitted close to crystallographic values using FEFF1 (FeIIIO6), 4 (FeIIIO6), 5 (FeIIIO6), and 9 (FeIIIO3N3), leading to the satisfactory fit shown in Figure III in an octahedral configuration, and similar results have been described for Eliott SoilIII in the HS samples is confirmed once more, as the bond distance for FeII is longer (2.10 Å).III and small organic ligands,III coordination environments, such as carboxyl, hydroxy and catecholic groups. Attempts to include Fe−Fe paths gave unsatisfactory fits with oscillations in k‐space that are out of phase with the experimental data , 9 (FeIIIO3N3), and 10 (FeIIIO3S3), as well as HS samples CB0 13, SW, and SW std., to allow resolution of the first shell composition and to distinguish between oxygen, nitrogen, and sulfur ligands. The spectral Kβ2,5 ) and Kβ′′  transitions are given in Figure 9 (FeIIIO3N3) and 10 (FeIIIO3S3), respectively.VtC‐XES experiments were performed on model compounds  9 FeIIION3, and 14 (FeIIIO6) shows only one Kβ′′ line, which is attributed to the six oxygen atoms in the first shell. SW, SW std., and CB0 13 are very similar to 4 (FeIIIO6), unambiguously proving that iron is exclusively surrounded by oxygen atoms in the HS samples, which is an important complement to the XAS data. During transport from freshwaters to the ocean, while in the estuarine mixing zone, Fe‐HS complexes go through dissociation and reassociation of Fe‐HS of a lower molecular weight,Compound III‐HS complexes are continuously released from terrestrial surroundings into freshwaters, and are subsequently transported to open oceans where they are photochemically reduced to crucial bioavailable iron species that are sequestered by phytoplankton. Light reactions in humic‐rich freshwaters are avoided to a large extent since they contain a significantly higher concentration of light absorbing substances compared to oceanic waters.IIIO6; Figure III‐HS in the high molecular weight fraction, CB0 13, form mononuclear complexes  should be addressed to the authors.SupplementaryClick here for additional data file.


The incorrect image appears for The fourth sentence of the “Impact on notification” subsection of the Results incorrectly references The last sentence of the “Empirical TB treatment” subsection of the Results incorrectly references Fig 3. This sentence should reference Table 2. The correct sentence and reference are: When restricted to those with Xpert negative results, the median time to starting TB treatment was 12.5 days (IQR 5–32) whilst for those tested with FM it was 7 days (IQR 4–25) (p<0.0001) (Table 2).


There are errors in the published article. In the Abstract FLO11p should be replaced by Flo11p, and ∆flo11 should be replaced by flo11 mutant. In the section entitled “Cell surface charge variation of 3238-32 and the flo11 mutant in minimal medium at 222 different pHs” 3238∆flo11 should be replaced by 3238-32∆flo11.


Urinary steroid metabolite ratios may improve the diagnostic yield of potential disorders of steroid hormone synthesis.To investigate the range of ratios and their predictive value in children with suspected disorders of steroid synthesis.Twelve ratios were calculated on steroid metabolite data analysed by gas chromatography–mass spectrometry in urine samples collected between 2008–2010 from 93 children. Urine samples were also analysed in 252 children with no known endocrine concerns.Of the 252 controls, 115 (46%) were male with a median age of 10 yr . Of the 93 cases, 38 (41%) were male with a median age of 6.5 yr . Of these, 41 (44%) had at least one ratio greater than the 95% percentile for controls. The most frequently abnormal ratio, found in 18/93 (19%) cases was (THS/(THE + THF + 5αTHF)) suggestive of 11β-hydroxylase deficiency. Over this period, 8 (9%) children were subsequently diagnosed with a steroid hormone disorder; 4 with 21-hydroxylase deficiency, 2 with11β-hydroxylase deficiency and 2 with 5α-reductase deficiency. All except one of these children had at least 1 raised ratio.Urinary steroid metabolite ratios in suspected disorders of hormone synthesis often exceed the reference range for normal children. The predictive value of steroid metabolite ratios in identifying a genetic abnormality may be condition specific and needs further study to improve its clinical utility. Assessment of urinary steroid metabolite excretion is reported to be a valuable tool in the investigation of disorders of steroid hormone synthesis as it offers the opportunity to simultaneously examine many different steroids ,2. It isThe standard method of analysing urinary steroid metabolites involves gas chromatography/mass spectrometry (GC-MS) . Given tThe aims of this study were, therefore, to determine reference ranges for a range of urinary steroid ratios and to explore the clinical utility of such ratios in a typical childhood population under investigation for suspected disorders of steroid synthesis.Of a total of 127 urinary steroid profiles collected between 2008 and 2010 at a single children’s hospital, 31 (24%) cases were excluded as they were 19 years old or over, were undergoing a dexamethasone suppression test or a synacthen stimulation test or were on steroid replacement therapy. Of the 96 eligible cases, sufficient clinical information was unavailable in 3. Of the remaining 93 cases, 38 (41%) were male and the median age at the time of the test was 6.5 years . A total of 17 cases (18%) were <6 months at the time of test; 60 (65%) were 6 months-10 years of age and 16 (17%) were >10 years of age at the time of test.A review of the clinical records was conducted for all cases to confirm the clinical characteristics, diagnosis and outcome. Of the 93 cases, indications for assessment of urinary steroid profile included early signs of puberty in 21 (22%), adrenarche in 16 (17%), suspected disorder of sex development in 10 (11%), congenital adrenal hyperplasia in 8 (9%) and Cushing’s syndrome in 2 (2%). In the remaining 36 (39%) cases, no clear reason for the test was available in the clinical records.Urine samples from two groups of children were collected to develop a reference range. The first group consisted of 96 children with no background of endocrine concerns who had a urine sample collected at presentation for investigation of an acute systemic illness. Eight of these patients were excluded as they had a very high urine free cortisol concentration >1000 nmol/l at the time of urine sample. Urine samples were also collected from 164 healthy school-age children. Of a total of 252 controls, 115 (46%) were male and the median age at sample collection was 10 years (range 1 month-18.5 years). The controls were broadly categorised into three age bands <6 months, 6 months to 10 years and more than 10 years.The urinary steroid metabolite analysis was performed by gas chromatography/mass spectrometry (GC/MS) using the Thermo Scientific Trace Gas Chromatography machine attached to an ITQ900 mass spectrometer. The method for analysis was a modification of the method originally described by Shackleton .Twelve ratios as listed in Table The urine samples from the healthy school children were collected following informed consent as part of a previous study of growth and development that was approved by the local research ethics service. The additional samples that were collected from children attending hospital were approved by the ethics service as part of local assay development.Table Of the 93 cases, 53 (57%) had ratios that were greater than the 95% percentile for controls Table . The numThe most commonly abnormal ratio when cases were separated according to gender and compared with controls was THS/(THE + THF + 5αTHF), with 20 of 53 (38%) cases having ratios greater than the 95% percentile for controls. The most commonly abnormal ratio when cases were separated according to age and compared to controls was DHEA/(THE + THF + 5αTHF) with 19 of 53 (36%) cases. When cases were not split for either age or gender, the most commonly abnormal ratio was THS/(THE + THF + 5αTHF) which was greater than the 95% percentile for controls in 24 of 93 (26%) cases.A total of 8 cases were subsequently diagnosed with a steroid hormone disorder (true positives); 4 (44%) with 21-hydroxylase deficiency, 2 (22%) with 11β-hydroxylase deficiency and 2 (22%) with 5α-reductase deficiency Table . All excThe two cases of 11β-hydroxylase deficiency both had a raised THS/(THE + THF + 5αTHF) ratio, which is suggestive of 11β-hydroxylase deficiency Figure . One of The 2 boys with 5α-reductase deficiency were 46,XY brothers who presented with atypical genitalia. They had consanguineous parents and were lost to follow-up before genetic investigations could be undertaken. One of them had 3 abnormal ratios (THS/(THE + THF + 5αTHF), suggestive of 11β-hydroxylase deficiency and Et/An and THF/5αTHF suggestive of 5α-reductase deficiency) and presented with glandular hypospadias and micropenis  and PT/(THE + THF + 5αTHF) alone. It is, therefore, possible that for 21-hydroxylase deficiency, genetic analysis could be routinely considered in those cases where all 3 ratios for 21-hydroxylase deficiency are raised. Depending on the availability of local resources, an alternative strategy would be to perform genetic analysis first and then pursue urine steroid biochemistry in those cases which do not reveal a gene mutation in CYP21A2.Given that close to half of the cases had at least one abnormal ratio and 19% had two or more abnormal ratios, there is a need to clearly determine cut-offs regarding the number of ratios that need to be abnormal or the extent of abnormality that will prompt the need for genetic analysis. The likelihood of detecting a gene mutation, for instance in the CYP21A2 may be higher if all three ratios are raised to a very high level but published data supporting this, and its corollary, i.e. a low likelihood of a gene mutation in cases where not all ratios are mildly raised, are lacking. Our data also suggest that identification of pathology should not solely rely on steroid metabolite ratios. It is possible that a particular change in a ratio could occur due to different combinations of changes in its numerator and denominator. It would, therefore, be important to also pay attention to the absolute levels of the urine metabolites.In summary, several children who are investigated for a disorder of steroid synthesis have urinary steroid metabolite ratios that are above the reference range for normal healthy children. Some ratios are more specific than others for identifying disorders of androgen excess such as 21-hydroxylase deficiency. The predictive value of single and multiple steroid metabolite ratios in identifying a genetic abnormality needs further exploration.


It is shown that the Sb2Te3 /graphene interface is stable and that coincidence lattices are formed between the epilayers and substrate that depend on the size of the surface unit cell. This demonstrates that there is a significant, although relatively weak, interfacial interaction between the two materials. Lattice matching is thus relevant for vdW epitaxy with two 2D bonded materials and a fundamental design parameter for vdW heterostructures.Van der Waals (vdW) epitaxy is an attractive method for the fabrication of vdW heterostructures. Here Sb The ability to create heterostructures of 2-dimensionally (2D) bonded materials2Te3, a typical 2D bonded material, can form coincidence lattices with reconstructed Si(111) surfacesVdW epitaxy2Te3 thin films were subsequently grown by molecular beam epitaxy (MBE) and characterized by Raman spectroscopy, which showed that the Sb2Te3/graphene interface is stable. Finally, atomic force microscopy (AFM) and x-ray diffraction (XRD) studies on the epilayers reveal two distinct nucleation mechanisms of Sb2Te3 on the graphene. By comparing the in-plane orientation of Sb2Te3 domains grown on graphene with epilayers grown on the buffer layer and on quasi freestanding bilayer graphene the origins of these different nucleation mechanisms are elucidated. Finally, the implications for the synthesis of vdW heterostructures are discussed.Instead of studying vdW epitaxy using passivated substrate surfaces, three types of high quality graphene substratesBefore depositing material on a substrate, it is important to know its topography. Therefore the monolayer epitaxial graphene substrates were studied by tapping-mode AFM. 2Te3 films were deposited on the graphene surfaces by MBE as described in the methods section.The structural properties of the monolayer epitaxial graphene substrates were studied using RHEED. Diffraction pattern taken perpendicular to the SiC < 100 > and < 120 > directions are shown in 2Te3 layers and monolayer epitaxial graphene substrates were studied using Raman spectroscopy. 2Te3 and a region that intentionally was not covered with Sb2Te3 during the deposition. The Raman spectra in the range from 20–200 cm−1 is shown in 2Te3 one can clearly see the presence of the characteristic Raman modes of Sb2Te3, whereas they are absent in the region not covered by Sb2Te3. Note that the sharp lines around 150 cm−1 correspond to the E2 doublet of SiC2Te3 is clearly lower, which is due to the absorption of the light in the Sb2Te3 layer. Nevertheless the spectra are almost identical and the G and 2D peaks, characteristic of graphene, can clearly be observed in both spectra. Furthermore, the defect related peaks, i.e. D, D′ and D + G, are not observed in both spectra. We note that these peaks were also not observed after subtraction of the SiC background signal. This indicates that the graphene structure is unaffected by the deposition of the Sb2Te3 layer and shows that the Sb2Te3/graphene interface is stable. Moreover, the absence of the defect related peaks is a good indication that there is no rehybridization in graphene and thus that there are no covalent bonds formed between graphene and Sb2Te3.The stability of an interface is an important aspect of any epitaxial heterostructure. In order to address this topic, Sb2Te3 films. 2Te3 film with a thickness of 24 nm. It shows that the surface of the 24 nm thick film consists of large flat areas. Those are characterized by terraces separated by 1 nm high steps, as evidenced by the line profile, 2Te3. A more detailed view of the initial growth is obtained by studying surface morphology of an 11 nm thick film, i.e. 2Te3 present in these areas. Furthermore, in 2Te3 layer. It should be pointed out that this particular alignment of the residual part of SiC buffer layer was not observed on all terraces. These observations are therefore consistent with a preferred nucleation of Sb2Te3 on the SiC buffer layer as a cause of the observed ordering.Now we turn to the investigation of the surface topography of the Sbz scan could be indexed as (00n) peaks, indicating that all domains have a (001) out-of-plane orientation. This implies that the domains have a different in-plane orientation. XRD φ-scans on Sb2Te3 (015) and SiC(013) diffraction peak were performed in order to determine the in-plane orientation. The relative orientation of the Sb2Te3 layer with respect to the graphene lattice was determined by considering the 30° rotation of the graphene lattice with respect to the SiC lattices as determined by RHEED, 2Te3 layer grown on graphene consists of domains that are rotated by ±30° with respect to the graphene lattice and of domains that are approximately aligned with the graphene lattice. We note that extended φ-scans showed a 6-fold rotational symmetry, indicating that the film is twinned, as expected from symmetry considerations2Se3 layers grown on graphene182Te3 that are observed are illustrated in the schematics in RHEED patterns taken after the growth see  consiste2Te3 (a = 4.26 Å) was calculated as a function of the rotational angle and the distance between the coincidence lattice points by adapting the approach of Kaneko et al2Te3 lattice is rotated with 30° with respect to graphene. Thus one can expect that this orientation is the most pronounced one, which is consistent with the experimental data. Furthermore, it is observed that a coincidence lattice with the same lattice mismatch can be formed when the rotation between the layers is 2.2° or 8.2°  and Sb2Te3 layers grown on monolayer epitaxial graphene has an orientation that is approximately aligned with the graphene lattice. This suggests that there is another mechanism that influences the in-plane orientation of Sb2Te3. This is consistent with the AFM observations showing that there are two different nucleation densities, and that the growth of Sb2Te3 is affected by the SiC surface regions covered by the (6√3 × 6√3)R30° buffer layer. It is thus important to address the influence of these regions on the epitaxial relationship between Sb2Te3 and graphene. Therefore, additional Sb2Te3 films were grown on SiC substrates mainly covered with the SiC (6√3 × 6√3)R30° buffer layer and on quasi freestanding bilayer graphene substrates. The XRD φ-scan performed on the film grown on the buffer layer substrate, 2Te3 on mono-/bilayer graphene.Besides the orientations that are due to the formation of coincidence lattices, a large part of the Sb2Te3 although a 2D material still can form a coincidence lattice with a reconstructed surface2Te3. The chemical bonding between SiC and the buffer layer results in a (6 × 6) corrugation of the buffer layer. Such a corrugation changes the distance between the carbon and Sb2Te3 layers periodically and hence might influence the interfacial interaction. Therefore, the lattice match of coincidence lattices between Sb2Te3 and the (6 × 6) corrugation were calculated, 2Te3 and the carbon lattice are not rotated with respect for each other. Based on these calculation one thus would expect an alignment of the carbon and Sb2Te3 lattices, which is in full agreement with the experimental results. It is therefore concluded that the epitaxial alignment between Sb2Te3 and the buffer layer is due to the formation of a coincidence lattice between the corrugations of the buffer layer and Sb2Te3.However, it is unclear why the growth on the buffer layer differs so much from the two other cases given that they are topologically identical92Te3 on graphene substrates, 2Te3 domains that are aligned with the graphene lattice, 2Te3 domains that are aligned with the buffer layer account more than 70% of the total amount of domains. This indicates that the amount of domains with a certain orientation is not only affected by the surface chemistry, but also by the growth mode and growth rate of the nucleated layers.Based on these considerations, we conclude that the different nucleation mechanisms of Sb2Te3 and the substrates. If this interaction is solely due to vdW bonding or also involves chemisorption, as for example observed at a hetero-organic interface2Te3 is deposited on monolayer epitaxial graphene and quasi freestanding bilayer graphene, because the same lattice mismatch can be obtained with a much higher density of coincidence lattice sites (rotated by 30°). A possible explanation for this observation is that the relatively weak interaction between the layers reduces the influence of the density of coincidence lattice points on the energy difference between the different orientations. This makes the occurrence of coincidence lattice with large distances between coincidence lattice sites more likely. However, the exact nature and the energetics of bonding between 2D bonded materials is still unclear, as pointed out above, and requires more detailed investigations. Nevertheless, these observations do show that lattice matching still plays an important role during vdW epitaxy and even suggest that coincidence lattice formation might be natural for vdW epitaxy on 2D bonded materials. This implies that the lattice parameter of 2D bonded materials is an important parameter to consider for the design and fabrication of vdW heterostructures.The observation of coincidence lattices between two 2D bonded materials indicates that there is a significant interaction between Sb2Te3 films grown on three different kind of graphene substrates: monolayer epitaxial graphene substrates, quasi freestanding bilayer graphene substrates and on the SiC buffer layer substrates. Raman spectroscopy revealed that graphene forms a stable interface with Sb2Te3. Furthermore, it was shown that the in-plane alignment between substrate and epilayer is determined by the formation of coincidence lattices between Sb2Te3 and graphene (monolayer and bilayer graphene substrates) or the surface corrugations of the buffer layer, demonstrating that there is a significant interaction between 2D materials and that lattice matching still occurs during vdW epitaxy. Contrary to early reports on vdW epitaxyIn summary, the fundamentals of vdW epitaxy were studied by using Sb2Te3 thin films were deposited on three different kind of graphene substrates  using molecular beam epitaxy (MBE). The fabrication and characterization of epitaxial graphene, bilayer graphene and buffer layers on top of SiC(001) substrates used in this study is described in detail elsewhere2Te3 and graphene was considered. Using density functional theory Jin and Jhi calculated the binding energy between graphene and Sb2Te3 and found it to be ~41 meVBT, where kB is Boltzmann’s constant and T the temperature, when T = 475K/ 202 °C. The binding energy thus puts an upper limit on the deposition temperature that can be used. Indeed, we observe a total desorption from the graphene surface for temperatures above 150 °C. Initial deposition with a growth temperature of 135 °C, which is approximately 100 °C below normal deposition conditions2Se3 filmsSbin situ using RHEED using a 20 keV electron acceleration voltage and ex situ using AFM (Veeco Nanoscope III) operated in tapping mode. and XRD  using Cu Kα1 radiation (λ = 1.540598 Å). The Raman spectra were obtained by exciting the Sb2Te3 and graphene/SiC with a laser . The backscattered light was collected using a liquid nitrogen cooled charged coupled device detector without using any polarizer’s. The schematics in the The substrates and films were characterized How to cite this article: Boschker, J. E. et al. Coincident-site lattice matching during van der Waals epitaxy. Sci. Rep.5, 18079; doi: 10.1038/srep18079 (2015).


However, whether remote‐IPC reduced Ca2+‐loading during ischemia and its subsequent involvement in inhibiting MPT pore formation during reperfusion has not been directly shown. We have developed a cellular model of remote IPC to look at the impact of remote conditioning on Ca2+‐regulation and MPT pore opening during simulated ischemia and reperfusion, using fluorescence microscopy. Ventricular cardiomyocytes were isolated from control rat hearts, hearts preconditioned with three cycles of ischemia/reperfusion or naïve myocytes remotely conditioned with effluent collected from preconditioned hearts. Both conventional‐IPC and remote‐IPC reduced the loss of Ca2+‐homeostasis and contractile function following reenergization of metabolically inhibited cells and protected myocytes against ischemia/reperfusion injury. However, only conventional‐IPC reduced the Ca2+‐loading during metabolic inhibition and this was independent of any change in sarcKATP channel activity but was associated with a reduction in Na+‐loading, reflecting a decrease in Na/H exchanger activity. Remote‐IPC delayed opening of the MPT pores in response to ROS, which was dependent on PKCε and NOS‐signaling. These data show that remote‐IPC inhibits MPT pore opening to a similar degree as conventional IPC, however, the contribution of MPT pore inhibition to protection against reperfusion injury is independent of Ca2+‐loading in remote IPC. We suggest that inhibition of the MPT pore and not Ca2+‐loading is the common link in cardioprotection between conventional and remote IPC.Ischemic preconditioning (IPC) inhibits Ca 2+‐loading during the simulated ischemic event but results from a direct PKCε‐dependent inhibition of the mitochondrial permeability transition pore.Remote ischemic preconditioning (IPC) provides a similar level of protection against ischemia–reperfusion injury to that of conventional‐IPC. This study shows that unlike conventional‐IPC, this was independent of any reduction in Na or Ca More specifically at the role of the resting membrane potential (sarcKATP channel activation), the “coupled exchanger” mechanism and MPT pore formation in this protection, using electrophysiology to measure sarcKATP channel activity and fluorescence microscopy to measure diastolic resting membrane potential (RMP) of the cell and mitochondrial membrane potential (Δψm) as a surrogate marker of MPT pore opening  were killed by cervical dislocation, and the heart removed rapidly and immersed in cold Tyrode solution. The hearts were perfused using a constant flow  Langendorff apparatus and single ventricular myocytes were isolated by enzymatic digestion of control “naïve” rat hearts, as previously described (Rodrigo and Samani μL) added to prevent gas exchange and myocytes were incubated at 35°C for 30 min to simulate ischemia. Reperfusion was achieved by sampling (50 μL) of cells through the oil and triturating the myocytes in oxygenated normal Tyrode with a 1‐mL plastic pipette to simulate mechanical injury (30s) and incubating at 35°C for a further 10 min, before staining with calcein and propidium iodide to detect viable and necrotic myocytes . ViableIschemia was simulated by superfusion of electrically stimulated myocytes with metabolic inhibition (MI) Tyrode for 10 min, which contained 2 mmol/L NaCN and 1 mmol/L iodoacetic acid in substrate‐free Tyrode, followed by superfusion of normal Tyrode for 10 min to reenergize the mitochondria and simulate reperfusion‐injury (Rodrigo and Samani SarcKATP currents were activated by perfusing the myocyte with MI‐Tyrode and the sarcKATP current identified by the addition of glybenclamide (10 μmol/L).Myocytes were voltage‐clamped in the whole‐cell configuration at a holding potential of −50 mV and stepped to a test potential of 0 mV for 100 ms at 0.1 Hz. Patch pipettes (2–5 MΩ) were filled with a solution containing (in mmol/L) 140 KCl, 5 EGTA, 0.4 ATP, 0.1 GTP, and 10 HEPES, pH7.3. Data were sampled at 5 kHz using PClamp 10 (Axon instruments), filtered at 2 kHz using an Axopatch 200B patch‐clamp amplifier and Digidata 1440A (Axon Instruments). Mean steady‐state current was measured during the final 10 ms of the test pulse and normalized to cell capacitance (pA/pF). μmol/L) to measure [Ca2+]i; with SBFI (5 μmol/L) to measure [Na+]i, and BCECF to measure pH, for 20 min then washed twice with normal Tyrode to remove any extracellular dye. Myocytes were then transferred to a perfusion chamber mounted on the stage of a Nikon inverting microscope (Nikon TE‐2000E) and continuously superfused at 35°C.Myocytes were loaded with Fura‐2 AM (5 4(3)), that partitions across the sarcolemmal membrane and changes its fluorescence intensity dependent on the membrane potential  for 20 min at room temperature, transferred to the perfusion chamber and constantly superfused with solutions containing 1 μmol/L DiBac4(3) at 35°C during experiments. To calibrate DiBac4(3) fluorescence signal to resting RMP in mV, fluorescence was recorded in response to changes in the bathing potassium concentration from 2.5, 6, 10 to 20 mmol/L and plotted as F1/F0. In separate experiments, the resting membrane potential was recorded in isolated control myocytes and superfused with Tyrode with the same range of potassium concentrations to construct a calibration curve from which recordings of DiBac4(3) were converted to RMP.To record the resting membrane potential (RMP), myocytes were stained with the voltage sensitive dye bis‐ trimethine oxonol , Fura‐2 loaded myocytes with 340/380 at 50 Hz, and SBFI‐loaded myocytes at 340/380 (1 Hz), using a monochromator and emitted light collected using a photomultiplier tube .We used a photomultiplier‐based system to make rapid measurements of pH, [Ca2+]i (Fura‐2), RMP (DiBac4(3)), and mitochondrial membrane potential (TMRE), simultaneously from a number of cells in a single field of view containing 6–10 cells for Fura‐2 or DiBac4(3) with a x20 objective, and 2–3 cells for TMRE with a x40 objective using a video‐imaging system (Perkin‐Elmer). Fura‐2 was excited alternately at 340/380 nm using a Lamda DG‐4 rapid system , and the ratio of the emitted light measured (>510 nmol/L) was recorded. Fluorescence cell images were captured every 10s with an ORCA‐ER CCD camera (Hamamatsu) and Volocity 6.1 software . DiBac4(3) was excited at 480 nm and the emitted light intensity at 535 nm with fluorescence images was captured every 30 sec. DiBac4(3) fluorescence intensity was normalized to the fluorescence at rest in myocytes superfused with normal Tyrode (F1/F0) and converted to RMP in mV using a calibration curve.We used an imaging‐based system to make measurements of i and F(340)‐signal not responding to changes in [Na+]i. F(340) and F(380) and the ratio F(340/380), in which a rapid increase in the F(340) fluorescence is detected in MI‐Tyrode, as reported previously  signal, which did show a gradual decrease as expected for an increase in [Na+]i. The ratio F(340/380), indicates two phases a rapid increase, which was due to the large increase in F(340) responding to the increase in [NADH], and the gradual increase reflecting an increase in [Na+]i which is in agreement with the previous report , and the time to MPT pore opening indicated by the increase in fluorescence to 90% of maximum. The increase in fluorescence signal was fitted with a sigmoidal curve and the time taken to 90% of maximal intensity recorded.We used a technique previously described by Hausenloy et al.  to folloε translocation was performed as previously described .Normal Tyrode solution contained (mmol/L): NaCl 135, KCl 5, NaHε inhibitor peptide εV1‐2 were synthesized by Pepceuticals and were a kind gift from Dr RI Norman, Leicester University.Fura‐2, BCECF, SBFI, and TMRE (Molecular Probes Inc.) was dissolved in DMSO containing 5% pluronic acid (5 mmol/L). The PKCn = hearts; experiments). For calculations of percent necrotic cells  was decreased in IPC‐myocytes to 37.0 ± 2.8%  in remote IPC myocytes to 32.9 ± 3.9% .We have previously shown that “IPC‐myocytes” enzymatically isolated from intact hearts subjected to IPC, were significantly protected against ischemia–reperfusion injury simulated using a cell pelleting technique (Rodrigo and Samani μmol/L) a nonspecific adenosine receptor blocker and naloxone (100 μmol/L) an opioid receptor present at the time of treatment of naïve myocytes with the conditioned perfusate. Either of these agents fully blocked the ability of conditioned perfusate to protect the naïve myocytes against I/R injury from 32.8 ± 3.7% in rIPC‐myocytes , to 48.3 ± 9.5% with 8p‐SP  and 54.1 ± 8.1% with naloxone . The data show that remote IPC of naïve myocytes significantly reduces the level of necrotic injury to similar levels seen in conventional IPC, and this involves adenosine and opioids.We looked at the role of adenosine and opioid receptors, which have been shown to be involved in remote IPC in‐vivo, in our model of rIPC using 8p‐SPT  naïve‐myocytes (ii) IPC myocytes, and (iii) rIPC‐myocyte subjected to metabolic inhibition (8 min) and reenergization (10 min). As the imaging system collects ratio images every 10 sec, this results in aliasing of the fast Ca2+‐transients, which now appear as slow rhythmic oscillations as reported previously  before a steady increase (Fura2 ratio >2.0) in five of seven naïve myocytes, whereas only two of nine IPC‐myocytes and three of nine rIPC‐myocytes showed this uncontrolled increase. The mean of these experiments show that the increase in mean diastolic [Ca2+]i at the end of MI phase was reduced in IPC but not rIPC‐myocytes. Following 10 min of reenergization the mean diastolic ratio had increased in control naïve myocytes to 3.2 ± 0.2 (n = 22) but this was reduced to 2.0 ± 0.1  in IPC‐myocytes and to 2.5 ± 0.2  in rIPC‐myocytes  and others where the [Ca2+]i increases dramatically. We therefore looked at the percentage of myocytes able to maintain a low level of diastolic [Ca2+]i (Fura‐2 ratio), and those that recover contractile function determined as the percentage of myocytes able to contract in response to electrical field stimulation, at the end of 10 min reenergization. 2+]i (Fura2 ratio <2.0) at the end of 10 min reenergization, is significantly greater in both IPC at to 69.9 ± 3.7% (P < 0.01) and rIPC‐myocytes at 61.9 ± 3.7% (P < 0.05), compared to naïve‐myocytes at 45.8 ± 5.9%. This relationship is similar to the recovery of contractile function, with the difference between IPC and rIPC also approaching significance of P = 0.07  has been shown to involve reverse‐mode NCX, driven by an accumulation of [Na+]i  in control naïve‐myocytes and compared this to IPC‐myocytes and rIPC‐myocytes, during superfusion with MI‐Tyrode.The increase in I but had no effect on phase‐1 which is driven by changes in NADH. The bar chart of the mean data .Inhibition of the NHE has been shown to reduce Na‐loading that occurs during ischemia  in control myocytes; 7.17 ± 0.02  in IPC‐myocytes, and 7.21 ± 0.05  in rIPC‐myocytes. Addition of NH4Cl (20 mmol/L) to the superfusate caused in a rapid intracellular alkalinization, which on washout of NH4Cl resulted a rapid acidification and the peak acidification was similar in all three myocyte groups (P < 0.001). The exponential time constant was not altered in rIPC‐myocytes at 54.4 ± 2.9 sec (NS).The resting intracellular pH was not affected by IPC or rIPC with a pH of 7.22 ± 0.02 . Naïve myocytes were isolated from control hearts and these were either remotely conditioned for 15 min to produce rIPC‐myocytes or treated with PMA (1 μmol/L) as a positive control. Western blot analysis of PKCε shows significant translocation from the cytosolic fraction to the particulate fraction in rIPC myocytes comparable to that in conventional IPC myocytes , which was then expressed as a percentage on the naïve band  , prior to being remote IPC with conditioned perfusate. The data show that PKCε or NOS inhibition blocked protection by remote‐IPC of naïve myocytes  in IPC‐myocytes, and 480 ± 28 sec  in rIPC myocytes. This delay in MPT pore opening was similar to that produced by Sanglifehrin‐A  and L‐NAME (100 μmol/L) during treatment with conditioned perfusate.Our data show that opening of MPT pores was significantly delayed from 353 ± 18 sec  in control naïve‐myocytes, to 514 ± 26 sec . The common cellular change in conventional IPC and rIPC‐myocytes, which might explain the cardioprotection in spite of the lack of an effect of Ca2+‐loading in rIPC, is the protection against ROS‐induced opening of the MPT pore.We have previously shown that ischemic preconditioning of the intact rat heart confers a cardioprotective phenotype to the isolated single ventricular myocytes, and this protection mirrors that seen in the intact heart, which may be linked to a decrease in Ca2+‐loading  in which the NHE drives the accumulation of i combines with the availability of ATP from the reenergized mitochondria and the SR to induce large scale oscillations in [Ca2+]i that trigger both hypercontraction and open of the MPT pore (Garcia‐Dorado et al. 2+]i during the MI (Rodrigo and Standen 2+‐homeostasis on reenergization, suggesting a role for the MPT pore in loss of Ca2+‐homeostasis during reenergization (Rodrigo and Standen 2+‐homeostasis also contracted in response to electrical stimulation, suggesting an intact cell membrane and E‐C coupling proteins.Many studies have now shown the inhibition of the NHE is cardioprotective and this is often linked to a reduction in Caε in conventional IPC is well documented (Inagaki et al. ε in our model of rIPC myocytes comparable to the level in conventional‐IPC myocytes, and that inhibition of PKCε blocks both cardioprotection and protection against opening of MPT pore in response to oxidative stress. Furthermore, this appears to involve NOS‐signaling downstream of PKCε, as cardioprotection and the delay in MPT pore opening in rIPC‐myocytes is blocked by L‐NAME, whereas PKCε translocation is still present (Figs. 2+‐homeostasis.Our study shows that rIPC was able to significantly delay the opening of MPT pore in response to oxidative stress of TMRE‐loaded myocytes to a similar level as conventional IPC, which suggests the central and common role of preventing MPT pore opening in protection by remote IPC and conventional IPC. A central signaling role for PKCnt Figs. and 8. Prnt Figs.  and permPrzyklenk et al., first demonstrated that IPC applied to one coronary vascular bed conferred protection to the neighboring myocardium, leading to the suggestion that agents released from the ischemic myocardium were able to travel to and induce protection in naïve myocardium (Przyklenk et al. Evidence is growing to support the involvement of a neural pathway to rIPC (Lim et al. 2+‐loading during metabolic inhibition but that this increase is not a prerequisite of cardioprotection, which is dominated by an inhibition of MPT pore opening. However, it is well documented that an increase in [Ca2+]i contributes to MPT pore formation during reperfusion (Javadov et al. 2+]i could prove important when the preconditioning signals responsible for inhibiting MPT pore opening are reduced, that is, less cycles of IPC, diseased states such as diabetes (Balakumar and Sharma Our data show that conventional IPC results in inhibition of the NHE‐1 activity in the isolated myocytes, which contributes to the reduction in Ca2+]i and ATP availability (Rodrigo and Standen 2+‐loading and MPT pore opening are likely to have an integrated role in reperfusion injury and therefore the mode of protection from remote IPC in the intact heart through prevention of mechanical injury may indeed involve Ca2+‐regulation.Isolated myocytes offer a range of advantages over the intact heart in the drive to unravel the intricacies of the preconditioning pathway (Diaz and Wilson Professor Nick Standen for his support, guidance, and inspiration over the years.Sanglifehrin‐A was obtained from the Novartis Institutes for Biomedical Research, Basel, Switzerland.


A genetically defined asymmetry underlies the inhibitory control of flexor–extensor locomotor movements. Published 14 October 2015The originally published Figure 1 mistakenly used an image from an earlier version of the article, in which the order of the panels had been switched, resulting in a disconnect between Figure 1, the figure legend for Figure 1, and the text.The corrected Figure 1 is shown here:The originally published Figure 1 is also shown for reference:J–L) Sections through the spinal cord showing the relative numbers of V1 cells that undergo Cre only recombination (lacZ-positive) vs those V1 cells that undergo both Cre and Flp recombination (GFP-positive)’ has been removed from the legend of Figure 1 and the text ‘(G–I) Images from E12.5 embryos…’ has been corrected to read ‘(G–J) Images from E12.5 embryos…’Following this change, the sentence, ‘(In addition, the label on the top left side of Figure 2 should have read ‘−FlpO’, rather than ‘_FlpO’.The article has been corrected accordingly.


There is an error in the last paragraph of the subsection ‘CDF2 interacts with DCL1’ in the Results and Discussion. “The results showed that the C-terminal fragments of CDF2 interacted with DCL1 as strongly as the full-length CDF2 ,” should read “The results showed that the C-terminal fragments of CDF2 interacted with DCL1 as strongly as the full-length CDF2 .”There is an error in the caption for


The aim of this study was to investigate the hypothesis that sulphation or phosphorylation of gastrin17 altered ferric ion binding, and/or affinity for the CCK1 or CCK2 receptor. To investigate the effect of tyrosine modification on ferric ion binding, the changes in absorbance of gastrin17, gastrin17SO4 and gastrin17PO4 on addition of Fe3+ ions were monitored. Binding of gastrin17, gastrin17SO4 and gastrin17PO4 to the human CCK1 and CCK2 receptors was assessed by competition with [125I]-Bolton and Hunter-labelled cholecystokinin8 in transiently transfected COS cells. Tyrosine sulphation or phosphorylation increased the affinity of gastrin17 for the first ferric ion bound from 267 to 83 pM and 14 pM, respectively, but had no effect on the stoichiometry of ferric ion binding. In contrast the affinity of gastrin17 for the second ferric ion bound was reduced from 94 pM to 7.32 µM and 671 nM, respectively. While sulphation of gastrin17 increased its affinity for the CCK2 receptor approximately 50 fold, phosphorylation had no effect on receptor binding. These results demonstrate that tyrosine modification may have profound effects on the interaction of gastrins with ferric ions and with the CCK2 receptor.The peptide hormone gastrin However, sulphation of CCK8 does not greatly affect its affinity for the CCK2 receptor, which is found in the gastric mucosa and in the brain  and Gamide (CCK2 receptor) are both members of the seven transmembrane domain family, and share 50 % sequence identity  were purchased from Bachem . Phosphorylated gastrin17 (85 % pure) was from Mimotopes . All peptides had a pyroglutamyl residue at their N-terminus and were C-terminally amidated. The impurities consisted of water and salts.GastrinThe absorption of peptides (10 μM in 10 mM sodium acetate (pH 4.0) containing 100 mM NaCl and 0.005 % Tween 20) at 280 nm in the presence of increasing concentrations of ferric ions from 2.5 to 50 μM was measured against a buffer blank, in 1 ml quartz cuvettes thermostatted at 298 K, with a Cary 5 spectrophotometer .125I]-Bolton and Hunter labelled-CCK8  as described previously ] for the binding of ferric ions to gastrins were fitted to a two-site ordered model with the program BioEqs Royer . Recepto3+ ions on the absorption spectrum of gastrin17, gastrin17SO4 and gastrin17PO4 was first investigated by absorption spectroscopy. A pH value of 4.0 was chosen in order to avoid any problems with precipitation of ferric hydroxides, and to allow direct comparison with previous studies. As reported previously (Baldwin et al. 17 at 280 nm increased to a maximum of 220 % after the addition of 2.0 mol ferric chloride/mol peptide (Fig. d1 and Kd2 of 267 and 94 pM, respectively, in good agreement with the values determined previously (Baldwin et al. 17SO4 (Fig. 17, and in the case of gastrin17PO4 a slight decrease in absorption was initially observed (Fig. 17SO4 and gastrin17PO4 finally reached maxima of 195 % to 220 % after the addition of 2–3 mol ferric chloride/mol peptide. Fitting of the absorption data to a two-site ordered model with the program BioEqs gave values for Kd1 and Kd2 of 83 pM and 7.32 µM, respectively, for gastrin17SO4, and of 14 pM and 671 nM, respectively, for gastrin17PO4 (Table The effect of addition of FeThis data indicates that, although tyrosine sulphation or phosphorylation had no effect on the stoichiometry of ferric ion binding, the affinity of gastrin for the first ferric ion was enhanced, and for the second ferric ion was reduced, by modification of the tyrosine side chain. The possibility that the hydroxyl group of the tyrosine is itself a ligand for the second ferric ion does not appear to be likely as XAFS data suggested that three of the five glutamate side chains act as ferric ion ligands (Baldwin et al. physiological concentrations is essential for biological function. Thus mutation of the glutamate residues essential for binding ferric ions abrogates the biological activity of Ggly as a stimulant of cell proliferation and migration (Pannequin et al. The concentrations of gastrins and of ferric ions used in the above experiments were supra-physiological. The concentration of gastrins was chosen as the minimum concentration that gave a reproducible change in absorbance on addition of ferric ions. Nevertheless our previous publications indicate that the binding of ferric ions to gastrin at 17 to either human CCK1 or CCK2 receptors was then examined. Although sulphation of gastrin17 increased its affinity for the human CCK2 receptor, phosphorylation of gastrin17 had no effect on CCK2 receptor binding (Fig. 50 values for the binding of gastrin17, gastrin17SO4 and gastrin17PO4 to the CCK2 receptor were 61 ± 32, 1.2 ± 0.4 and 58 ± 20 nM, respectively. The IC50 values for the binding of gastrin17 were slightly higher than the values, which range from 0.94 to 6.4 nM, previously reported for the cloned human CCK2 receptor (Ito et al. 17SO4 for the cloned human CCK2 receptor does not appear to have been reported previously, but data for binding to dispersed gastric glands from the guinea pig fundus also suggest that sulphation increases the affinity for the CCK2 receptor, in that case by a factor of tenfold, from 16 to 1.6 nM (Praissman et al. 17, gastrin17SO4 and gastrin17PO4 to the CCK1 receptor was not detected in our experiments (Fig. 17 this result agrees with the data of de Weerth and co-workers, who reported an IC50 value of 1.8 µM (de Weerth et al. 17SO4 and gastrin17PO4 for the CCK1 receptor do not appear to have been reported previously.The effect of tyrosine modification on the binding of gastrin8, where tyrosine sulphation or phosphorylation increased the stoichiometry of ferric ion binding from 1 to 2 without greatly affecting the affinity (Baldwin et al. 17 had no effect on the stoichiometry of ferric ion binding, but enhanced the affinity of gastrin17 for the first ferric ion, and reduced the affinity for the second ferric ion. This difference is not unexpected as the gastrin binding site consists of three of the five glutamate residues, while the CCK8SO4 binding site involves the two aspartate residues, and the CCK8PO4 binding site the phosphate group itself (Baldwin et al. 8 for both the CCK1 and CCK2 receptors (Baldwin et al. 17 for the CCK2 receptor, phosphorylation had no effect. Although the generalization that modification of tyrosine profoundly affects the binding of ferric ions is valid, the differences between two such closely related peptides as gastrin17 and CCK8 indicate that the exact binding details will have to be determined for each peptide individually.In contrast to CCK17 had no effect on the stoichiometry of Fe3+ ion binding, the affinity for the first ferric ion bound was increased from 267 to 83 pM and 14 pM, respectively. Sulphation of gastrin17 increased its affinity for the CCK2 receptor approximately 50 fold, but phosphorylation had no effect on receptor binding. These results imply that tyrosine modification may have profound effects on the biological activities of gastrins.While tyrosine sulphation or phosphorylation of gastrin


In this study, we investigated methods to include the available αs1casein genotype effect in genomic evaluations of French dairy goats.Genomic best linear unbiased prediction methods assume that all markers explain the same fraction of the genetic variance and do not account effectively for genes with major effects such as the αs1casein genotype was included as a fixed effect in genomic evaluation models based only on bucks that were genotyped at the αs1casein locus. Less than 1 % of the females with phenotypes were genotyped at the αs1casein gene. Thus, to incorporate these female phenotypes in the genomic evaluation, two methods that allowed for this large number of missing αs1casein genotypes were investigated. Probabilities for each possible αs1casein genotype were first estimated for each female of unknown genotype based on iterative peeling equations. The second method is based on a multiallelic gene content approach. For each model tested, we used three datasets each divided into a training and a validation set: (1) two-breed population (Alpine + Saanen), (2) Alpine population, and (3) Saanen population.First, the αs1casein genotype had a significant effect on milk yield, fat content and protein content. Including an αs1casein effect in genetic and genomic evaluations based only on male known αs1casein genotypes improved accuracies (from 6 to 27 %). In genomic evaluations based on all female phenotypes, the gene content approach performed better than the other tested methods but the improvement in accuracy was only slightly better (from 1 to 14 %) than that of a genomic model without the αs1casein effect.The αs1casein effect in a genomic evaluation model for French dairy goats is possible and useful to improve accuracy. Difficulties in predicting the genotypes for ungenotyped animals limited the improvement in accuracy of the obtained estimated breeding values.Including the  Using haplotypes instead of single SNPs in a genomic evaluation model was proposed to model the effect of such multiallelic major genes but the number of effects to estimate was considerably larger than with the single SNP model [αs1-casein information on genotyped animals into account. This method uses a multiple trait model that considers information on production traits and the number of copies of a particular allele for genotyped animals related to ungenotyped individuals [αs1-casein polymorphism.With the recent development of molecular technologies, genomic selection is now used for several species, and major genes can be identified and sequenced. Selection for specific alleles of several major genes is already implemented, such as the nd goats , 2. The nd goats , 4. Thisnd goats , 6. Howeaccuracy –9. TheseNP model –12 and tNP model . QTL effNP model . This apNP model . HoweverNP model , 12, 14.NP model . Thus, tNP model , 17. Theividuals . Howeverαs1casein gene. In dairy goats, different alleles of the αs1-casein gene have various effects on protein content, protein yield, milk yield [αs1-casein gene is one of the key factors that determine the technological properties of milk, such as cheese yield and cheese curd formation [casein αs1 gene using allele-specific polymerase chain reaction (PCR) and restriction fragment length polymorphism (RFLP) [casein αs1 locus has not been included in the genetic evaluation of French Alpine and Saanen goats [In French dairy goats, accuracy of genomic selection is not as high as in dairy cattle  owing tolk yield  and fat lk yield , 23. Polormation . In the m (RFLP) . These gen goats .αs1casein gene is a complex gene with at least 17 alleles: alleles A, B1, B2, B3, B4, C, H, L and M are associated with increased levels of αs1casein in the milk, alleles E and I with intermediate levels, alleles D, F and G with reduced levels, and alleles O1, O2, and N have no effect i.e. are null alleles [A, B, C, E and F were identified in French dairy goat populations with alleles E and F predominating in the Alpine and Saanen breeds, before 2000 [αs1-casein gene cannot be captured by a single SNP, especially since some alleles, e.g. allele E, are characterized by the insertion of several nucleotides [αs1casein gene region is limited.The goat  alleles , 28. Allore 2000 . The comleotides . Moreoveαs1casein gene as fixed or as random based on the available genotyping data for the αs1casein gene, in purebred or multi-breed genomic evaluations. First, we undertook a detailed description of the allele frequencies of the αs1casein gene in the French population and the effects of each αs1casein genotype on all traits that are under selection in dairy goats. Then, we tested the impact of including the effect of a known αs1casein genotype in the genomic evaluation based on the daughter yield deviations (DYD) of the males [αs1casein genotype into account in genomic evaluation models based on all females with phenotypes .We used SNP genotypes for 470 Alpine and 353 Saanen males that had been previously obtained with the Illumina goat SNP50 BeadChip  as descrαs1casein locus. Genotypes consisted of 19 pairs of the six alleles A, B, C, E, F and O (Table αs1casein genotypes FO and OO have never been observed in the French dairy goat population. All incomplete genotypes (20 % in this study), e.g. with one missing allele, were ignored. αs1casein genotypes were available for 6276 animals , fat and protein yields (kg) and fat and protein contents (g/kg) as described in , 20. We αs1casein locus for all the females with phenotypes, that had not been genotyped , were obtained separately for each breed based on the iterative peeling procedure implemented in the software developed by Vitezica [−3 for all females and for each genotype probability. For computational reasons, predictions were made separately for three groups of animals per breed, i.e. animals born before 2000, born between 2000 and 2007, and born after 2007. The genotype probabilities were computed using data on all available αs1casein genotypes  and separately on the dataset for each breed by using analysis of variance in the GLM procedure of the SAS® software. For this analysis, a simple model was used where DYD were explained only by a αs1casein genotype effect and a breed effect for the combined dataset. Genotypes with less than 10 animals were excluded from this analysis. The amount of DYD phenotypic variance explained by the αs1casein genotype was estimated by a restricted maximum likelihood (REML) algorithm implemented in the remlf90 software [αs1casein genotype (s) was (were) considered as a normally distributed random effect(s) αs1casein genotypes . Based on the estimated effects of the αs1casein genotypes on protein content, genotypes were classified into three groups according to their effect: strong i.e. more than 1.5 g/kg, intermediate i.e. between 0.5 and 1.5 g/kg and weak i.e. less than 0.5 g/kg, in order to simplify the models that used the predicted genotypes obtained with the iterative peeling approach.The significance of the effect of each software . Estimatαs1casein genotype could be integrated in genomic evaluations based on DYD for production traits and considering only the 3327 genotyped males [1912 Alpine and 1415 Saanen  and αs1casein genotype, as a fixed effect, in genetic (based on pedigree information) or genomic (based on pedigree and 50 K SNP chip data) evaluations based on DYD was compared to models that do not include the effects of αs1casein genotypes. In all cases, genetic and genomic breeding values of animals were estimated with the BLUP model using blupf90 software [These analyses were carried out on a multi-breed (Alpine + Saanen) dataset because the effects of  follows :\documenenotypes . The relsoftware .αs1casein genotype in one-step genomic evaluations for protein content based on recorded females from official genetic evaluations. Since the αs1casein genotype has a clear effect on protein content, only this trait was considered here. In a first approach, we used genotype probabilities at the αs1casein locus that were computed as explained in “The last part of this study consisted in including the effect of the AA, AB, AC, BB and BC), group 2 those that increased protein content from 0.5 to 1.5 g/kg  and group 3 those that increased protein content by less than 0.5 g/kg . The following model used was:αs1casein genotypes, respectively. The column vectors αs1casein genotype groups. For instance, AA, AB, AC, BB, BC) of group 1. αs1casein genotype group. Here, For the second model tested, the 19 possible genotypes were divided into three groups according to their estimated effects on protein content obtained from REML estimations as described above (cf. “αs1casein genotype in genomic (based on pedigree information and SNP genotypes) evaluations based on all female phenotypes. In this study, dairy goats carried six possible alleles at the αs1casein locus. The model used here i.e. Model , plus a random genetic effect  representing the effect of alleles A, B, C, E, F or O respectively on protein content and random residual error . In theory, αs1casein locus and αs1casein locus and 2,669,255 missing values for the ungenotyped females. In this model, genetic values were decomposed as a polygenic effect plus the effect of the αs1casein alleles. According to [A, B, C, E, F and O, respectively, and A, B, C, E, F and O, respectively. In order to include the effect of the alleles with registered gene content in the variance of the genetic value for protein content,  and and4) ane. Model , which we. Model :6\documeαs1casein effect , and a test set of 146 young males born between 2010 and 2011 and with no daughter by January 2013. The breeding values predicted for these 146 young males were compared with their DYD from the official genetic evaluation of January 2015, which were estimated by using a mean of 53 daughters per sire. The validation correlations consisted in Pearson correlations between the EBV or GEBV obtained in 2013 and the DYD obtained in 2015 for these 146 males. For Models  and 353 Saanen (2) progeny-tested males that were genotyped with the goat 50 K BeadChip; 1442 Alpine (3) and 1062 Saanen (4) other males; and 1529 Alpine (5) and 1420 Saanen (6) dams of bucks  and allele E  [A reported in the current study was higher than that previously found in French dairy goats in the 1990s, which is due to genetic selection promoting allele A [C was rather rare, with less than 5 % of the animals carrying this allele in the three subpopulations analyzed. These frequencies of allele C were close to those found in the French dairy goat population in 1989, which ranged from 1 to 2 % depending on the breed considered [C was detected [F and O in a population of highly selected animals  were lower than those reported in females born before 1989, i.e. 7.9 % for progeny-tested males and 18.9 % for dams of bucks versus 28 % in the Alpine and 24 % in the Saanen breeds [αs1casein genotype and their dams were females selected for high protein content [AA , EE  and AE .These differences in frequencies were also observed in American dairy goats e.g. a frequency of 35.7 % for allele E in the Alpine versus 70.5 % in the Saanen breed [A and E were the most frequent alleles in the Alpine and Saanen breeds, respectively. Differences in frequencies for alleles A and E between the Alpine and Saanen breeds were previously reported by Martin and Leroux [A in the Alpine versus 7 % in the Saanen breed. Such a difference may be explained by of the fact that Saanen breeders are less involved in selecting animals on protein yield and content. In addition, the Saanen breed is more inbred than the Alpine breed [A, B or C were preferentially chosen for AI, a program that aimed at managing inbreeding in the Saanen breed reduced the number of progeny-tested bucks carrying a strong allele  that could be used [The first objective of this study was to describe the current troduced . The freF and FF . Howeverallele A . In our detected –42. The  content , 29. In en breed . In our ne breed . Althougαs1casein allele frequencies with those obtained by using predicted alleles or genotypes at the αs1casein locus by an iterative peeling method or gene content approach. Ideally, we should compare true and predicted genotypes using k-fold cross-validations. Given the small number of females  that were genotyped from each breed and each period  considered for the iterative peeling approach, we were only able to look at predicted genotype frequencies. To compare predicted genotypes of females estimated by an iterative peeling or gene content approach to the observed genotypes, we used genotype frequencies obtained for: (1) the 2949 genotyped females , AE  and EE . The predicted frequencies were sometimes underestimated compared to the real frequencies (genotype AE for the Saanen breed) and sometimes overestimated (genotype AA for the Alpine breed and genotypes EE and EF for the Saanen breed). Genotype frequencies obtained with the gene content approach were closer to the real genotype frequencies than those obtained with the iterative peeling method, except for genotype AE in the Saanen breed. Previous reports showed no difference in the ability to predict genotypes between these two methods [F and O in the Saanen breed [Differences between predicted genotype frequencies using the iterative peeling approach and real genotype frequencies were large Fig. , especia methods . The difen breed  between Inference of unknown genotypes is known to be a complex procedure because of the difficulty of obtaining a joint distribution of genotypes and complex traits . In manyαs1casein gene had a significant effect and to estimate the amount of variance explained by the αs1casein genotype. The effect of the genotype at the αs1casein locus, on the five milk production traits that are selected for in French dairy goats, was tested by using analysis of variance . These results were consistent with those found previously in French dairy goats, except that no effect was detected on protein yield [αs1casein haplotypes had a significant effect on protein content, fat yield and fat content in Norwegian dairy goats. The lack of any effect on protein yield can be explained by the highly negative genetic correlation (−0.28) between milk yield and protein content in Norwegian dairy goats [αs1casein gene effect appears to be strengthened from −0.42 to −0.48 [αs1casein genotypes into account in the model.One aim of this study was to identify the traits on which the in yield . Similarry goats . This neto −0.48  by takinαs1casein genotype as a random effect in the model for milk yield, fat content and protein content are in Table αs1casein genotype was largest for the Alpine breed . Polymorphism at the αs1casein locus explained between 24.4 % (Saanen) and 38.2 % (Alpine) of the variance for protein content and between 8.7 % (Saanen) and 18.2 % (Alpine) of the variance for fat content. These results for protein content are consistent with those obtained by [αs1casein genotype was included as fixed effect in the model.Variance components estimated by considering the ained by  who repoαs1casein genotypes ranged from 3.7 for genotype BC to −0.9 g/kg for genotype EF in the Saanen breed , (2) genotypes with an intermediate effect on protein content between 0.5 and 1.5 g/kg  and (3) those with a weak effect on protein content up to 0.5 g/kg (genotypes EE and EF). Estimated effects on protein content were similar for the Alpine and Saanen breeds especially in the case of the genotypes AE, AF and AA with differences less than 0 g/kg. The largest differences between the two breeds were observed for genotypes AB (−0.8 g/kg in the Alpine compared to the Saanen breed) and EE (+0.9 g/kg in the Alpine compared to the Saanen breed). Although ranking of αs1casein genotypes according to their effect on protein content differed in the two breeds, the results for the three categories were similar. Considering the small observed differences between the estimated effects of αs1casein genotypes in the Saanen and Alpine breeds, the differences observed between the estimated variance components are likely explained essentially by differences in allele frequency.For protein content, the estimated effects of the ed Table . Casein es Table : (1) genαs1casein genotype as a fixed effect was first analyzed by using Model (αs1casein genotype in the model [case (1) of Model αs1casein genotype as a fixed effect [case (2) of Model s1 casein genotype [case (3) of Model αs1casein genotype as a fixed effect [case (4) of Model αs1casein genotype was considered as a random effect were similar to those obtained when it was considered as a fixed effect (results not shown). Including the αs1casein genotype as a fixed effect in the genetic (based on pedigree information) or genomic (based on pedigree information and SNP genotypes) models significantly improved validation correlations for all traits except for fat and protein yields .Given the small number of genotyped females . Using  females . For fatαs1casein genotype in the genetic evaluation (based on pedigree information) or in the genomic evaluation (based on pedigree information and SNP genotypes) improved validation correlations in a similar way for milk yield, fat and protein contents.Regardless of adding information on the αs1casein genotype considered as a fixed effect in the model, are in Table αs1casein locus in the Saanen training population  compared with the Alpine population. These genotypes were rare in the Saanen training population but were more frequent in the Saanen validation population: 0.3 versus 3.9 %, (results not shown). Thus, their effects were not well predicted in the Saanen single-breed training population compared with the two-breed population.Validation correlations estimated separately, for each breed, for two-breed and single-breed training populations combining genomic and pedigree information, with the αs1casein genotype in the genomic evaluation based on single-step models was investigated by using the two approaches to estimate missing female genotypes. Table αs1casein genotypes that were obtained with the iterative peeling method for females with phenotypes. In Model (αs1casein genotypes was considered as a random effect (with 3553 levels). In Model (αs1casein genotype (“without αs1casein”) and are in Table αs1casein fixed effects. In Table αs1casein genotype did not exceed those obtained with Model  than those obtained by excluding the effect of the αs1casein genotype especially for single-breed evaluations (Alpine or Saanen). This result is consistent with the findings reported in a study on Canadian Holstein dairy cattle that took the bovine transmembrane growth hormone receptor genotype into account, with an increase from 0.3 to 0.5 % for somatic cell counts and milk yield, respectively [αs1casein genotype on protein content . The higher correlations obtained for the Saanen breed could be the result of the distribution of the αs1casein allele frequencies in the population. In the Saanen population, αs1casein genotypes AE and EE are carried by almost 65 % of the animals, which is nearly equivalent to a biallelic marker and much easier to predict.The relevance of adding information on the In Model   of the females came from unknown parents. Even in a subpopulation of females with known parents and for which one-third of the females have at least one genotyped parent (results not shown), improvements in validation correlations were smaller than expected from the results of the analyses based on DYD. Predicting αs1casein genotypes for non-genotyped animals even when using the gene content approach is particularly difficult in this case because of the large number of alleles considered. Even for individuals with one genotyped parent, the number of possible genotypes was too large to accurately predict their possible αs1casein genotypes. In addition, several αs1casein alleles  have the same effect on some phenotypes , thus calculating predictions with the gene content approach is even more difficult. One solution could be to consider gene content of groups of alleles that have the same effects on the trait.This improvement in validation correlations by including an effect for the αs1casein major gene, which has a complex polymorphism, in the genetic evaluation of French dairy goats. First, genotype frequencies in the Alpine and Saanen population showed differences between males and females and between Alpine and Saanen animals. The αs1casein genotype had an effect on several production traits in French dairy goats: milk yield, fat content and protein content with a large amount of phenotypic variance explained by the αs1casein genotype for protein content. Including an effect of the αs1casein genotype in a genetic evaluation that is based on animals with known αs1casein genotypes , improved accuracy even when SNP genotypes had been taken into account. Including the effect of the αs1casein genotype in genetic evaluations that are based on female phenotypes and genotype probabilities yielded a lower accuracy than the approach that was based on gene content. Finally, improvement in validation correlations, by including the αs1casein effect in the models, was greater for genetic evaluations that were based on animals genotyped at the αs1casein gene. However, a smaller improvement was obtained for genetic evaluations that were based on ungenotyped animals at the αs1casein gene, due to the difficulty in predicting multi-allelic genotypes for this gene.This study set out to determine how to include the effect of the