The orientation relationship between these clusters and the matrix differs from that observed in conventional steels. These findings provide a direct observation of oxide formation in single-phase Cu–Fe composites and offer a pathway for the design of nanocrystalline materials strengthened by oxide dispersions.Oxygen contamination is a problem which inevitably occurs during severe plastic deformation of metallic powders by exposure to air. Although this contamination can change the morphology and properties of the consolidated materials, there is a lack of detailed information about the behavior of oxygen in nanocrystalline alloys. In this study, aberration-corrected high-resolution transmission electron microscopy and associated techniques are used to investigate the behavior of oxygen during in situ heating of highly strained Cu–Fe alloys. Contrary to expectations, oxide formation occurs prior to the decomposition of the metastable Cu–Fe solid solution. This oxide formation commences at relatively low temperatures, generating nanosized clusters of firstly CuO and later Fe Oxygen contamination during the mixing of precursor powders for nanocrystalline materials affects alloy microstructure, but exactly how remains unclear. Here, the authors show that stable nano-oxides can form easily inside severely deformed Cu-Fe grains during heating. Severe plastic deformation (SPD) can effectively generate novel metallic nanocrystalline materials by drastically refining and mechanically alloying normally immiscible composites10. Now combined with powders processing technique, SPD is extended to produce nanocrystalline alloys with desirable compositions directly from blended powders without any precasting11, which is a convenient low-cost route in manufacturing applicable bulk materials.Nanostructuring and alloying are strategies to obtain enhanced properties for bulk metals13. Oxygen contamination seems to be inevitable during premixing and consolidation for powders processing, as well as in the sequential straining of deformation15. Moreover, it indeed has been realized that oxygen could be incorporated into the nanocrystalline samples during processing, generating discrepant morphologies13, mechanical properties15 and thermal stabilities13. However, to our knowledge, the exact status of such contaminant inside the materials remains unclear, and how it behaves during annealing has never been studied.However, gaseous impurities in the raw materials and introduced during SPD generation in the nanostructures pose a challenge which needs to be addressed prior to industrial application as they will influence material properties16. However, some different types of carbides were detected inside annealed bulk samples, pointing out that contaminants could affect constituents of precipitates and then induce discrepant properties of nanostructured alloys17. Nevertheless, the formation processes of heterogeneous precipitates in nanocrystalline alloys were never investigated directly due to the tiny signal intensities of trace amount of such light elements, which are barely detectable by conventional techniques. The current empirical explanations on the effects of light elements are based on phenomenological assumptions18.For decades, it was believed that pure metal precipitates of already dissolved elements will form inside grains or at grain boundaries after annealing, and some reports indeed supported this by observing nanosized precipitates of alleged pure metal elements29. Therefore, it is reasonable to assume that the potential existence of oxide clusters may affect the properties and microstructures in nanocrystalline materials. Fortunately, the advent of modern in situ high-resolution transmission electron microscopy (HRTEM), combined with image processing technique, enables probing the mechanism behind complicated physicochemical processes at the atomic scale. For example, nowadays novel phase formation31 and transition33, metal-catalyzed process34, deformation twinning generation35, irradiation-induced void formation36 as well as nanocrystal facet development37 have been captured in real-time observations.It is known that oxides are efficient additives to produce so-called oxides dispersion-strengthened steels/refractory metals which have been strenuously developed for decades due to their high temperature strength, stability and enhanced ductility2O3 inside grains are detected at relatively low temperature before the fcc supersaturated solid solution decomposes into Fe-rich and Cu-rich grains. Lattice coherency between oxides and matrix is determined based on different HRTEM images. This work provides, to our knowledge, the first observation of oxygen behavior in nanocrystalline alloys and demonstrates that stable nanosized oxides can easily form inside grains, which may pose a promising route to manipulate mechanical properties by intentionally incorporating light elements before deformation and also assist in quantitatively investigating on the role of oxygen in the grain refinement and intermixing of nanocrystalline alloys.Stimulated by direct atomic-resolution observation, we systematically studied the thermal behaviors of oxygen in high-pressure torsion (HPT) deformed Cu–Fe alloys by means of in situ spherical aberration-corrected HRTEM using a heating holder, via recording atomic-resolved images, diffraction patterns as well as capturing compositional information by electron energy loss spectroscopy (EELS) and energy dispersive X-ray spectroscopy (EDXS), supplemented by X-ray photoelectron spectroscopy (XPS), synchrotron X-ray diffraction (XRD), atom probe tomography (APT) and density-functional theory (DFT) calculations. The results show that the 75 at.%Cu–25 at.%Fe (75Cu–25Fe) alloy has a single face-centered-cubic (fcc) structure at room temperature after severe deformation. When heated, unexpected oxidation processes forming CuO and Fe38. The distribution of dark areas in the BF images fcc, some tiny peaks corresponding to oxides which are marked as (101)CuO, CuO appear when the temperature reaches 260 °C. At an even higher temperature of 340 °C additionally (200)Fe and (211)Fe peaks from Fe can also be clearly observed. Selected area electron diffraction gives structural information of a micron-sized area of the TEM sample, and has higher scattering efficiency than XRD. It is therefore more sensitive to an intensity difference compared to XRD. But it is still relatively insensitive to reflect the onset of oxidation and precipitation at the atomic scale, so the way is to take the advantage of HRTEM (as shown in the following section).The blended powders of 75Cu–25Fe are severely deformed forming a single fcc structure after 100 rotations of high-pressure torsion . The grains are drastically refined from roughly 50 µm down to an average size of 58 nm according to large population statistics  appear which are indexed as reflections of CuO according to the calculations of interplanar spacing. Then after annealing at 100 °C, more diffraction spots appear close to the central spot equivalent to larger spacing, which are indexed as planes of Fe2O3 phase. CuO shows a monoclinic structure with lattice parameters of a = 4.684 Å, b = 3.423 Å, c = 5.129 Å and β = 99.54°40, while Fe2O3 can be recognized having a hexagonal structure with lattice parameters of a = 5.035 Å, b = 5.035 Å, c = 13.752 Å and γ = 120° 42. So the phases of CuO and Fe2O3 can be easily distinguished by the interplanar spacing of low-index planes, such as (002), (101), and so on. When the temperature reaches 260 °C, the FFT becomes more complicated with more subtle spots appearing. By carefully comparing the FFT with previous ones, pure Fe precipitates can be identified by their (110) diffraction spots. One should note that, although CuO (2.034 Å) and (110)Fe (2.037 Å) have similar interplanar spacings, for FFT images obtained at 180 °C and 220 °C, at the circle with a radius of 9.8208 ± 0.4910 1/nm (5% variation) corresponding to interplanar spacing of 2.037 ± 0.102 Å, no clear spots can be detected while other spots from CuO and Fe2O3 phases can be easily recognized. But for the FFT image of the 260 °C-annealed sample, at this circle region, some discernable spots with detectable intensities show up. So these spots can be justified as the evidence of Fe precipitates. The partial reflections of CuO, Fe2O3, and Fe (marked as colorized disks) in the FFT images are selected to generate their distribution mappings by Inverse Fast Fourier Transform (IFFT) with specific conditions of the same circle size, circle numbers and positions for each phase32. The resultant distributions of CuO, Fe2O3 and Fe precipitates are displayed in the third to fifth columns respectively, with the same contrast limits for all images in one column. Generally, the areas of the CuO, Fe2O3, and Fe precipitates increase with the annealing temperature, and finally the dimensions of the oxides are in the range of 10 nm, well consistent with the result of oxide distributions in DF images shown in Fig. 2O3, which means that oxygen diffuses to one specific area during heating, simultaneously triggering the nucleation processes of oxides. From the mapping of Fe precipitates, only tiny areas are marked as Fe agglomerates because of the limited image size.To observe the formation processes of oxides at the atomic scale, in situ HRTEM is employed. Figure 43. During our experiments, two measures have been taken to minimize the potential influences of the electron beam. First, during image recording, the electron beam was spread to fit the size of the fluorescent screen every time. The beam was switched off during the heating process and the imaging was done immediately after the heating was finished. Second, to confirm that oxidation and precipitation are not caused by e-beam irradiation, a series of comparison experiments were carried out, where a region of the sample was exposed to the electron beam continuously with the same dose as in the in situ experiments Fe, a weak peak shows up, which becomes stronger with increasing temperature. Simultaneously, the (111)Cu peak obviously shifts to higher angles as a result of temperature increase above 100 °C. The calculated lattice parameters of the fcc phase, and the averaged residual Fe concentrations in the fcc matrix of samples annealed at different temperatures are presented in Fig. Fe appearance and (111)Cu peak shift, it can be concluded that the dissolved Fe starts to segregate at the temperature of 260 °C, which is in accordance to in situ heating results. The residual Fe concentration in the fcc matrix is systematically measured at different annealing temperatures using the high spatially resolved EDXS, and the result directly confirms the segregation of Fe from the matrix.To investigate whether the TEM sample geometry has an effect on the reactions or processes due to its reduced size, as-deformed bulk materials were ex situ annealed with the same time as in situ heating in above HRTEM investigations. XRD, EDXS, APT and TEM characterizations of ex situ annealed samples are shown in Fig. Cu and [012]Fe, respectively. The two FFT images are calculated based on the Cu and Fe areas marked by white frames. Evidently, the neighboring Cu and Fe grains have an orientation relationship of (02Cu//(200)Fe, which is different from the typical K–S relationship relevant to fcc and bcc structure interface, i.e., (111)fcc//(110)bcc44. A low magnification BF image of the same sample ex situ annealed at 420 °C is shown in Fig. CuO and (200)Fe rings are marked. The average grain size is about 56 nm, and the emergence of (110)CuO diffraction ring confirms the occurrence of oxides inside HPT-deformed samples during annealing. The white arrows in Fig. Fe diffraction ring.Furthermore, APT was employed to detect the oxide clusters for the ex situ annealed sample at 300 °C as shown in Fig. To confirm the conclusions drawn from the in situ heating experiments, EELS mappings are implemented on the ex situ annealed sample at 420 °C. The morphology and distribution of Fe grains are almost identical to those from in situ annealing, with dimensions of about 20–50 nm fcc and (020)CuO// of Cu (Purity 99.9%) and Fe (Purity 99.9%) were fully mixed with composition of 75 at% Cu–25 at.% Fe and then HPT deformed using a two-stage methodIn situ heating experiments were conducted in TEM and STEM to characterize in detail the microstructures and compositions of the HPT-deformed Cu–Fe alloy. The TEM sample was in situ annealed for 10 min at different temperatures using Gatan heating holder, in steps of 40 °C from room temperature to a maximum temperature of 420 °C. All microstructural investigations in this work were undertaken at radius of 3.0 mm from the torsional axis of the HPT-deformed disks. (S)TEM studies were carried out using a field emission gun transmission electron microscope  equipped with an imaging spherical aberration corrector. In STEM mode, a spot size of 0.7 nm of electron beam was used to record high angle annular dark field (HAADF) images. Simultaneous EDXS for nanoscale compositional analysis was also carried out in STEM mode. STEM EELS investigations were done on a probe-corrected FEI Titan³ 60–300 microscope operated at 300 kV equipped with a Gatan GIF Quantum energy filter. The electron beam was perpendicular to the shear plane of the disks for all microstructural investigations in this work.Kα1 radiation (λ = 1.540593 Å). Here it should be emphasized that the X-ray beam width for all the measurements in this work was limited to 2 mm using the relevant incident slit, covering a large area of HPT-deformed disk from the radius of 2 mm to 4 mm. For the whole range scanning of 40–100°, the scanning speed is 0.4°/min with a step of 0.02°, and then an extremely fine scanning speed of 0.1°/min with the step of 0.02° was imposed for the focused range of 40–47° to get better signal to noise ratio and more accurate diffraction angles.X-ray diffraction was conducted on all samples using a Smartlab X-Ray Diffractometer  with Cu APT measurements were conducted in a local electrode atom probe, LEAP 3000 × HR from Cameca Instruments. The measurements were set up in laser mode with energy of 0.8 nJ and a pulse repetition rate of 250 kHz, base temperature of 60 K and a detection rate of 0.005 atoms per pulse. The specimens were prepared by standard sample lift out and annular milling, using a focused ion beam (FIB) FEI Helios 600i Dual Beam workstation. A final cleaning of the tip with low ion energy of 3 kV ensured a Ga content in the analyzed volumes below 0.05 at.%.X-ray photoelectron spectroscopy, synchrotron X-ray diffraction methods and density-functional theory calculation procedures are presented in detail in Supplementary Notes The data that support the findings of this study are available from the corresponding authors upon reasonable request.Supplementary InformationPeer Review File


Here we report the discovery of a Weyl semimetal in MoxWx1−Te2 at x=25%. We use pump-probe angle-resolved photoemission spectroscopy (pump-probe ARPES) to directly observe a topological Fermi arc above the Fermi level, demonstrating a Weyl semimetal. The excellent agreement with calculation suggests that MoxWx1−Te2 is a Type II Weyl semimetal. We also find that certain Weyl points are at the Fermi level, making MoxWx1−Te2 a promising platform for transport and optics experiments on Weyl semimetals.The recent discovery of a Weyl semimetal in TaAs offers the first Weyl fermion observed in nature and dramatically broadens the classification of topological phases. However, in TaAs it has proven challenging to study the rich transport phenomena arising from emergent Weyl fermions. The series Mo A Type II Weyl fermion semimetal has been predicted in MoxWx1−Te2, but it awaits experimental evidence. Here, Belopolski et al. observe a topological Fermi arc in MoxWx1−Te2, showing it originates from a Type II Weyl fermion and offering a new platform to study novel transport phenomena in Weyl semimetals. The recent discovery of the first Weyl semimetal in TaAs has opened a new direction of research in condensed matter physics1234678910111213141617xWx1−Te2 series has been proposed as a new Weyl semimetal222324xWx1−Te2 has a layered crystal structure and is rather widely available as large, high-quality single crystals. Indeed, MoTe2, WTe2 and other transition metal dichalcogenides are already under intense study as a platform for novel electronics26272829xWx1−Te2 offers the possiblity to realize a tunable Weyl semimetal, which may be important for transport measurements and applications. Recently, it was also discovered theoretically that WTe2 hosts a novel type of strongly Lorentz-violating Weyl fermion, or Type II Weyl fermion, long ignored in quantum field theory23313233343536372331323339xWx1−Te2 is a Weyl semimetal. At the same time, it is important to note that ab initio calculations predict that the Weyl points in MoxWx1−Te2 are above the Fermi level2224xWx1−Te2 by pump-probe ARPES to the energy range necessary to study the Weyl points and Fermi arcsxWx1−Te2 for transport, if the Weyl points are far from the Fermi level, then the novel phenomena associated with the emergent Weyl fermions and violation of Lorentz invariance will not be relevant to the material's transport properties.Recently, the MoxWx1−Te2 at doping x=25%. We use pump-probe ARPES to study the band structure above the Fermi level and we directly observe two kinks in a surface state band. We interpret the kinks as corresponding to the end points of a topological Fermi arc surface state. We apply the bulk-boundary correspondance and argue that since the surface state band structure includes a topological Fermi arc, MoxWx1−Te2 is a Weyl semimetalab initio calculation. However, crucially, we find that certain Weyl points have lower binding energy than expected from calculation and, in fact, are located very close to the Fermi level. This unexpected result suggests that our Mo0.25W0.75Te2 samples may be useful to study the unusual transport phenomena of Weyl semimetals and, in particular, those particularly exotic phenomena arising from strongly Lorentz-violating Weyl fermions. Our work also sets the stage for the first tunable Weyl semimetal. Our discovery of a Weyl semimetal in MoxWx1−Te2 provides the first Weyl semimetal outside the TaAs family, as well as a Weyl semimetal which may be tunable and easily accessible in transport studies. Taken altogether with calculation, our experimental results further show that we have realized the first Weyl semimetal with Type II, or strongly Lorentz-violating, emergent Weyl fermions.Here we report the discovery of a Weyl semimetal in MoxWx1−Te2 and study the band structure below the Fermi level. WTe2 crystallizes in an orthorhombic Bravais lattice, space group Pmn21 (#31), lattice constants a=6.282 Å, b=3.496 Å and c=14.07 Å, as shown in 2. There are two bands, one electron and one hole pocket, near the Fermi level, both very near the Γ point of the bulk Brillouin zone, along the Γ−Y line. Although the bands approach each other and Weyl points might be expected to arise where the bands cross, it is now understood that WTe2 is in fact very close to a phase transition between a Weyl semimetal phase and a trivial phase, so that the electronic structure of WTe2 is too fragile to make it a compelling candidate for a Weyl semimetalab initio Wannier function-based tight-binding models for WTe2 and MoTe2 to study MoxWx1−Te2 at arbitrary x  to a Lorentzian distribution and we plot the train of peaks corresponding to the surface state band. We note that we simultaneously fit the topological surface state, the bulk valence and conduction states, and the trivial surface state above the conduction band. In W1 and W2 as read off directly from W2 kink is lower in energy. To illustrate the success of the Lorentzian fit, in Now we show that we observe signatures of a Fermi arc in Mo0.25W0.75Te2. In Emin is at ∼EF in calculation, but at EB∼0.06 eV in experiment. The difference in Emin suggests either that our sample is electron-doped or that the ky position of the Weyl points differs in experiment and theory. Next, crucially, we observe that, in disagreement with calculation, the W1 are located only ∼0.005 eV above EF. This suggests that the Weyl points and Fermi arcs in our Mo0.25W0.75Te2 samples may be accessible in transport. This result is particularly relevent because MoTe2, WTe2 and other transition metal dichalcogenides are already under study as platforms for novel electronics26272829xWx1−Te2 may be at the Fermi level, it is possible that transport measurements may detect a signature of the strongly Lorentz-violating Weyl fermions or other unusual transport phenomena associated with Weyl semimetals in MoxWx1−Te2. We summarize our results in ab initio calculation, we confirm that the kinks correspond to Weyl points. Furthermore, the excellent agreement of our experimental results with calculation shows that we have realized the first Type II Weyl semimetal.To show that we have observed a topological Fermi arc, we compare our experimental observation of two surface state kinks with a numerical calculation of MoxWx1−Te2 and we have argued that MoxWx1−Te2 is a Weyl semimetal because we observe a topological Fermi arc surface state. However, topological Fermi arcs cannot strictly distinguish between bulk Weyl cones that are of Type I or Type II. While the excellent agreement with calculation suggests that MoxWx1−Te2 is a Type II Weyl semimetal, we might ask if we can directly observe a Type II Weyl cone in MoxWx1−Te2 by ARPES. This corresponds to observing the two branches of the bulk Weyl cone, as indicated by the purple dotted circles in 2, MoxWx1−Te2 and MoTe2 predict that all Weyl points are above the Fermi level222324xWx1−Te2.So far we have studied the surface states of MoxWx1−Te2 have chiral charge ±1 .Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


ApoE genotype was determined by ApoE genotyping chip and the plasmatic biochemical characterization was performed on all subjects. There were differences (P < 0.001) in HbA1c, creatinine, and urinary albumin between the two groups. The ApoE ε2 allelic frequency was 7.69% in DN group versus 3.49% in control group , as expected, ApoE E2/E2 and E2/E3 genotype frequency were higher in DN group . The ApoE ε4 allelic frequency was 7.93% in DN group versus 11.54% in control group , and DN group presented a lower frequency of ApoE E3/E4 and E4/E4 genotype frequency . These results suggest ApoE ε2 allele may be a risk factor; however ApoE ε4 allele may play a protective role of DN in Chinese type 2 diabetic patients.Diabetic nephropathy (DN) is one of the major chronic complications of diabetes. Genetic polymorphism of Apolipoprotein E (ApoE) has been proposed to participating in DN. The purpose of the study was to evaluate the relationship between ApoE genetic polymorphism and the presence of DN in Chinese type 2 diabetic patients. We studied 845 diabetic patients who were divided into DN group ( Diabetic nephropathy (DN) is one of the major chronic complications of diabetes mellitus (DM), and approximately 35 percent of type 2 diabetes mellitus (T2DM) patients eventually developed DN. Accompanied with high prevalence of diabetes, DN has now become the major cause of end-stage renal disease (ESRD). About 50 percent new patients required dialysis treatment in Europe is caused by DN . In Chinε2 , ε3 , and ε4 . The alleles form six different phenotypes: 3 homozygous  and 3 heterozygous . The E3/E3 phenotype has the widest distribution in healthy people, E3/E4 and E2/E3 phenotypes have fewer distribution than E3/E3, and E2/E2, E4/E4, and E2/E4 phenotype have the lowest distribution [ApoE is a plasma protein including 299 amino acids which plays an important role in lipid and lipoprotein metabolism. In humans, apoE gene located on the chromosome at position 19q13.2 and SNPs at positions 112 (rs429358) and 158 (rs7412) determine three major alleles: ε3 allele  has normal function [ε3 allele, the affinity of ApoE ε2 to LDLR and LRP is reduced, resulting in the reduction of LDL-C and the accumulation of decomposed products of triglyceride-rich lipoproteins in plasma, whereas ApoE ε4 carriers showed a reduced LDLR affinity and increased LRP affinity which accelerate the metabolism of triglyceride-rich lipoproteins, leading to elevated serum levels of LDL [ApoE is a high affinity ligand of several hepatic lipoprotein receptors such as low-density lipoprotein receptor (LDLR) and LDL-related protein (LRP) which plays important roles in triglyceride lipoprotein and cholesterol metabolism . ApoE gefunction . Compares of LDL . Recentls of LDL .The primary aim of this study was to demonstrate whether ApoE gene polymorphism is an important determinant of DN in Chinese T2DM patients. Secondarily, this genetic study might also add more information about a Chinese population beyond traditional risk factors.We studied 429 patients with DN in China-Japan Friendship Hospital in Beijing, China, from January 2014 to October 2016. All recruited DN patients fulfilled the following inclusion criteria: (1) patients had been diagnosed with T2DM according to the criteria of World Health Organization (WHO) 1999, (2) 24 h urinary albumin > 300 mg and urinary albumin creatinine ratio > 30 mg/(gCr), and (3) all patients have no kidney disease history previously, and any disease that causes urinary albumin changes was excluded, such as ketosis, lupus nephritis, and urinary tract infections.We studied 416 T2DM patients in China-Japan Friendship Hospital in Beijing, China, from January 2014 to October 2016. T2DM was diagnosed according to the criteria of World Health Organization (WHO) 1999. All selected patients have diabetic duration > 10 years, negative urinary albumin measured on three different occasions, and urinary albumin creatinine ratio ≤ 30 mg/(gCr).The protocol was approved by institutional ethical committee of China-Japan Friendship Hospital. Informed consent was obtained from the patients before the study began.A full general revision of antecedents including arterial hypertension and nutritional state was carried out. Plasmatic biochemical characterization included the following: (1) glycemia and lipid profile  and renal function  measured by automatic biochemistry analyzer (SIEMENS) and (2) venous blood samples (10 ml) collected from patients after a 48 h low fat diet and a 12 h overnight fast.ε2, ε3, and ε4), a commercial ApoE genotyping chip  was performed according to the protocols provided by the manufacture. Polymorphic alleles were identified by the fluorescence intensity of the hybridization sites.Genomic DNA was extracted from venous blood according to the manufacturer's recommendations (Qiagen). The concentration of DNA was determined using a NanoDrop 1000 spectrophotometer (Thermo Fisher). DNA samples were frozen at −20°C until processed. For the detection of the three ApoE common alleles (http://biostats.usc.edu/Quanto.html). Data was analyzed with the SPSS 17.0. A P value of <0.05 was considered to be statistically significant.Quantitative clinical data  were non-Gaussian distribution and presented as median (interquartile range), and Wilcoxon test was used to test the differentiation between DN group and control group. Frequencies and percentages described the nonparametric variables and the comparison between these groups was based on the Chi-square test. A logistic regression analysis was carried out using DN as dependent variable. Power calculation was performed by Quanto software version 1.2.4  as DN group and 416 T2DM patients  as control group . Clinica2, P < 0.05) while E3/E4 and E4/E4 genotype frequency were lower  in DN group than in control group. We also observed differences in the distribution of ε2 and ε4 alleles of ApoE between both groups  and the ε4 allele  was lower in DN group than in control group. In the allele statistical processing, the APOE E2/E4 patients were excluded.We observed differences in the distribution of ApoE genotype between the two groups . The E2/h groups . The freε2) and rs429358 (ApoE ε4) , while ApoE ε4 genotyping may decrease the risk of DN comparing with ε3 genotyping . The high value of 95% CI is nearly 1 and may be due to the relatively small sample size which required further research on the expanding sample size.To confirm the association between the ApoE genotyping and the risk of DN occurrence, further multivariate logistic regression analysis was performed. The result shows the risk of getting DN of SNPs rs7412  than in the microalbuminuria group (8.9%) (P = 0.03); however, ApoE ε3 allele frequency was significantly higher in proteinuria group than in stable renal function group [ε4 allele may be a protective factor for DN which can reduce the DN occurrence in T2DM [ε4 allele was significantly different between the DN group and the control group after excluding the patients who have E2/E4 genotype. Simultaneously, the E3/E4 and E4/E4 genotype distribution between DN group  and control group  was notably different (P < 0.05) which was consistent with the above other results.Most of the research showed that ApoE  failure ; Araki r with DN . Kimura on group . Several in T2DM , 30. In ε4 and progression of DN  [ε4 allele is a risk factor of DN and the effect of lipid increasing of ApoE ε4 may accelerate the progression of DN [ε2 and ApoE ε4 alleles are both risk factors for the development of T2DM but also find that ApoE ε2 and ApoE ε4 alleles are associated with an increased risk of DN. Our results conflicted with their conclusion that ApoE ε4 allele is a risk factor of DN. In most of the studies summarized in this meta-analysis, the duration time of DM is short that many potential DN patients may not yet occur DN in the control group, which may lead to statistics confliction. Relatively small sample size summarized by the above meta-analysis may be another reason that leads to difference conclusion which suggests that further large sample studies are needed [On the other hand, another meta-analyses have found no correlation between ApoE 78–1.11) . A smallon of DN . Yin et e needed .There were controversial results in the correlation of ApoE gene polymorphism and DN. The main reason may be because (1) there were racial differences in the distribution of ApoE alleles, (2) different methods used to detect ApoE genotype may affect the accuracy of the results , (3) theε2 mainly through lipid metabolism pathways is involved in DN. Compared with ApoE ε3, affinity of ApoE ε2 with LDL receptor and LDL particles is reduced, resulting in the accumulation of the decomposition products of triglyceride-rich lipoproteins in plasma.Many experimental data and clinical studies have shown that there are relevance between dyslipidemia and glomerular sclerosis. More and more research suggests that hyperlipidemia is involved in diabetic glomerulosclerosis which is a risk factor for the occurrence and development of DN. Currently, the role of ApoE in lipid transport and its following affection on renal function may be the main explanation of the correlation between ApoE polymorphism and DN. In mice with mild renal impairment, ApoE gene knockout can result in a significant increase of plaque size and its aggression in foam cell-rich soft plaque . ApoE ε2ε4 allele and LDL cholesterol [ε4 allele play a protective role in the development and progression of DN? The mechanism is not clear now, and there may be the following reasons. First, high cholesterol can accelerate the deterioration of renal function in patients with DN; however, the effects of ApoE ε4 allele promoting lipid increasing may be significantly weakened in DN patients [ε4 allele protective effects on DN might benefit from unrelated features of lipoprotein metabolism. ApoE gene mainly expressed in mesangial cells and then secreted into the extracellular matrix. Because ApoE have a high affinity with extracellular glycosaminoglycans, when ApoE is synthesized, there may appear biological activity changes or/and replacements of growth factors in the partial of extracellular matrix. Kimura et al. reported that the ApoE ε4 allele is a factor that reduces the relative risk for DN progression because ApoE is synthesized in the kidney and probably could displace growth factors involved in pathogenic through its junction to glycosaminoglycans [β (TGF-β) and platelet-derived growth factor (PDGF) play an important role in the pathogenesis of DN which confined to extracellular proteoglycans, suggesting that ApoE may regulate the levels and biological activity of TGF-β and PDGF in the extracellular matrix and thereby affecting renal effects of DN. A third possibility is that ApoE ε4 gene loci may be associated with a protective gene of kidney and may be a sign of renal protective alleles. Chen et al. studied the ApoE role in the kidney function of rats, finding that rats deficient in ApoE had a proliferation of mesangial cells and overproduction of mesangial matrix which are important aspects that influence the development of kidney diseases including DN, suggesting a protective role for ApoE in kidney function [ε4 allele has the highest regulation capacity of mesangial cell proliferation and mesangial matrix expansion due to an increased interaction with matrix proteoglycans. However, more information is required to find an explanation for the possible protector role of ApoE ε4 allele in the development of DN.It has been revealed that there is high positive correlation between ApoE lesterol ; then, hpatients . Howeveroglycans . Tumor gfunction . Moreoveε3 allele, ApoE ε2 allele carriers have a higher proportion of DN, suggesting that ApoE ε2 allele may be a risk factor of DN. Individuals carrying ApoE ε4 allele showed a lower prevalence of DN which suggest that ApoE ε4 allele may be a protective factor of DN. However, there are still limitations which must be clearly acknowledged. Firstly, this study is limited in a relatively small sample size; another is that the genetic association found in this study may not be generalized to other ethnic groups.In summary, we observed an association between the ApoE polymorphism and DN in Chinese type 2 diabetes patients. Compared with ApoE


IO2) and the subsequent rise in arterial oxygen tensions (PaO2)—coincides with aggravated mortality  traumatic brain injury” [2 in TBI so far remains unknown [The role of hyperox(em)ia in TBI is even more conflicting: clearly, due to the preferential vasoconstrictor effect of hyperoxia in the cerebral circulation , there i” , Damiani injury” . The opt unknown .2 > 300 mmHg) was associated with increased mortality [2 ≤ 299 mmHg) did not affect survival and was even associated with improved organ function at 24 h [2 values of 150–200 mmHg [Finally, the role of hyperox(em)ia after cardiac arrest is not definitely answered either: the available large-scale retrospective analyses as well as more recent data showed that severe hyperoxemia  is common in patients mechanically ventilated already in the ED (nearly 44% of the 688 patients included), but also is an independent predictor of hospital mortality. Moreover, hyperoxemia was directly related to morbidity as mirrored by less ventilator-free, ICU-free, and hospital-free days [2 ≤ 200 mmHg), “moderate” (201 ≤ PaO2 ≤ 300 mmHg), and “severe” (PaO2 > 300 mmHg) hyperoxemia, respectively). Thus, Page et al. extend the available ICU data on the effects of excess hyperox(em)ia to the situation prior to the ICU  and eventually to the prehospital setting.In a single-center observational study in this journal, Page et al.  recently2 to be targeted and the minimal PaO2 needed. Oxygen is crucial for mammalian adenosine triphosphate synthesis as the final electron acceptor in the respiratory chain, but an intramitochondrial PO2 ≈ 0.5–1 mmHg still allows for mitochondrial function. The aforementioned retrospective data unanimously show a U-shaped relation between PaO2 and the risk of mortality, with a sharp increase in mortality upon “hypox(em)ia” as defined by PaO2 < 60 mmHg and the lowest mortality at PaO2 ≈ 150 mmHg [The current discussion on a possible threshold value for excess hyperox(em)ia raises the questions of both the optimal PaO150 mmHg . On the 150 mmHg . The pre150 mmHg  assumes


We find that the magnetocurrent response of hole-only devices correlates closely with changes in the bipolaron concentration, supporting the bipolaron model of unipolar organic magnetoresistance and suggesting that it may be more of an interface than a bulk phenomenon. These results are understood on the basis of a quantitative interface energy level alignment model, which indicates that bipolarons are generally expected to be significant near contacts in the Fermi level pinning regime and thus may be more prevalent in organic electronic devices than previously thought.Bipolaron states, in which two electrons or two holes occupy a single molecule or conjugated polymer segment, are typically considered to be negligible in organic semiconductor devices due to Coulomb repulsion between the two charges. Here we use charge modulation spectroscopy to reveal a bipolaron sheet density >10 Bipolarons - two electrons or holes localized on the same molecule - are generally considered negligible in organic electronic devices. Dhanker et al. show that large bipolaron densities can exist near electrode interfaces and that they are linked to the phenomenon of unipolar organic magnetoresistance. They are typically localized on a single molecule or conjugated polymer segment and consist of an electron or hole dressed by a distortion of the intramolecular nuclear framework, as well as the electronic polarization and lattice relaxation of the surroundings1. Bipolarons consisting of two electrons or two holes on a single-molecular site are also possible, but are difficult to form because their Coulomb repulsion tends to outweigh the stability gained through nuclear reorganization, resulting in Hubbard formation energies U > 0.1 eV3.Polarons are the dominant charge carrying species in disordered organic semiconductorsU), and that this may in turn explain organic magnetoresistance (OMAR) in unipolar devices3. In this context, one might expect bipolaron densities to be particularly pronounced at organic semiconductor/electrode interfaces, where energetic disorder is typically enhanced relative to the bulk5 and Fermi level pinning can lead to large interfacial charge densities8.Most electrical injection and transport models consequently neglect bipolarons. However, it has been pointed out that strong energetic disorder in organic thin films may facilitate bipolaron formation in the density of states (DOS) tail -N,N′-diphenylbenzidine (TPD). Using charge modulation (CM) spectroscopy11 to directly monitor the density of TPD polarons and bipolarons in hole-only devices, we show that the latter can account for >1% of the interfacial charge under forward bias and that variations in the bipolaron density correlate closely with the magnetocurrent response in accord with the bipolaron model of OMAR2. These results are understood by generalizing the interface energetic model of Oehzelt et al.8, which indicates that significant bipolaron concentrations are likely to be common near contacts in the Fermi level pinning regime and therefore that bipolaron-based OMAR may be more of an interfacial than a bulk effect.Here we report the existence of a large (hole) bipolaron density located near the interface between an indium tin oxide (ITO) contact and the common small molecule hole transport material V = 0.55 V (see the inset cyclic voltammetry scan) leads to a decrease in absorbance by the neutral molecule  and to the emergence of two new bands at λ = 484 nm and λ = 1400 nm associated with the TPD cation12. Subsequently increasing the bias to 0.9 V above the second oxidation potential leads to a third absorption band centered at λ = 734 nm due to formation of the dication12.Figure 3. In this case, the large electron affinity of MoO3 induces electron transfer from the highest occupied molecular orbital (HOMO) of TPD, p-doping the film with hole polarons and, evidently, also bipolarons14. Based on the cation and dication absorption cross-sections evaluated from their molar extinction coefficients in solution , we estimate polaron and bipolaron concentrations of P+ ~ 1020 cm−3 and P2+ ~ 2 × 1019 cm−3, respectively. While only a fraction of this polaron density is mobile (the free polaron density obtained from conductivity measurements is an order of magnitude lower)13, this result is notable because it shows that the bipolaron concentration can indeed be significant in organic semiconductors—roughly 20% of the polaron concentration in this case.Figure N-(1-naphthyl)-N-phenylamino]biphenyl (NPD)10, we observe induced absorption (transparency) at λ ~ 500 nm and λ ~ 1415 nm associated with an increase in TPD polaron density under forward (reverse) bias. In the present case, however, we are also able to resolve induced absorption by the TPD bipolaron in forward bias at λ ~ 780 nm since this transition does not overlap spectrally with the polaron as in the case of NPD14.The bipolaron absorption signature is also an evident in un-doped TPD hole-only devices , the sign of each change is consistent with bipolaron-based OMAR, where the magnetic field causes a spin blockade for bipolaron formation  that reduces the number of percolation paths for charge transport18.Figure λ ~ 650 nm using the transfer matrix optical model and assuming that the bipolarons exist in a 1 nm thick sheet adjacent to the ITO. The polaron density (λ ~ 1230 nm) displays a weaker voltage dependence in Fig. 3 or neglecting the plasma treatment in otherwise identical devices. Although the bipolaron CM signal in these latter cases is below our detection limit, it is reasonable to expect that the bipolaron density varies monotonically with the polaron density given that the former is a bimolecular product of the latter19. To this point, the bipolaron-to-polaron ratio (P2+/P+) in the plasma-treated ITO device increases with bias, with the bipolaron concentration reaching ~1% of the total polaron concentration at 6 V as shown in the inset; this represents a lower bound based on the maximum total polaron concentration estimated in Supplementary Figure Figure V < 3 V is roughly a factor of five less than that calculated from the geometric capacitance, which suggests that only a fraction of the capacitive electrode charge transfers in and out of the first TPD monolayer(s)10. Notably, this fraction depends on the ITO surface treatment. The fact that plasma treated ITO yields a larger swing in the number of charged TPD molecules than untreated ITO for the same geometric capacitance and voltage swing indicates that the density of interface states at the Fermi energy (EF) must be higher in the former case. This follows straightforwardly from the higher work function of plasma-treated ITO20, which shifts EF down, closer to the peak of the disorder-broadened HOMO interface DOS8.The linear variation in polaron density observed for 21. The lower current density of the MoO3-based device is somewhat surprising, though not unexpected given the 4 nm thickness employed here22, and is nonetheless consistent with the intermediate interfacial charge density determined in Fig. 2, and suggest that both quantities increase with the interfacial polaron density as the effective anode work function increases  and standard deviation, which may be different at the interface (σi for the first monolayer) than in the bulk 5. As the Fermi level of the system equilibrates, charge is transferred between the electrode and organic layers, giving rise to a spatially varying charge density [ρ(z)] and consequent potential shift [V(z)] in accord with the Poisson equation.To understand the nature of the interfacial charge density in more detail, we generalize the electrostatic energy level alignment model of Oehzelt et al.U, means that singly occupied HOMO states in 3.Acknowledging the possibility of bipolaron formation subject to a Hubbard energy penalty, B = 0), the spin of each polaron interacts with randomly oriented hyperfine fields, enabling triplet pair states to eventually transform into singlets within the typical dwell time that two polarons spend next to one another3. The bipolaron density is thus N−) and bipolaron (N2−) charge density in the lowest unoccupied molecular orbital (LUMO) should also be included in ρ(z)8, though we neglect it in Eqn. EF is close to the HOMO).The charge density in each layer subsequently follows from integrating over the singly occupied states, as well as those that gain an additional hole to become bipolarons:8 for the ITO/TPD system using representative parameters obtained from ultraviolet photoelectron spectroscopy (ITO work function IP = 5.1 eV)23 and a Hubbard energy U = 0.25 eV estimated from the difference between the first and second TPD oxidation potentials shown in the inset of Fig. 12. We take σb = 0.1 eV based on bulk transport measurements of the closely related molecule NPD25 and σi = 0.35 eV in accord with estimates of the interfacial distribution obtained from internal photoemission and impedance spectroscopy27.This model is solved iteratively as described in Ref. mentclass2pt{minim−2). The vast majority of the charge resides in the first monolayer, giving rise to a ~0.3 eV interfacial dipole as discussed previously8 and observed experimentally23. Importantly, bipolarons constitute a significant fraction of this interface charge (P2+/P+ = 0.22) but are negligible in the bulk (P2+/P+ < 10−7). The existence of this substantial bipolaron charge density does not, however, lead to an appreciable change in the energy level alignment as shown by the dashed potential distribution in the upper panel, which is calculated without the possibility of bipolaron formation . In this case, the loss of bipolaron charge density is largely compensated by an increase in the polaron density as dictated by the electrostatics of the system.Figure σi) and the position of the Fermi level relative to the HOMO . The lower panel of Fig. P2+/P+) in the first monolayer increases strongly with σi and saturates with ϕA in the Fermi level pinning regime. Fermi level pinning above ϕA ~ 5 eV is evident from the associated hole injection barriers  plotted in the top panel, which transition from a slope S → 0 (Fermi level pinning)8. The main conclusion from Fig. P2+/P+ > 0.01) over the entire range of σi that have been estimated to date28. This fraction is even higher for alternative interface DOS distributions, such as Lorentzian or exponential functions that decay more slowly than the Gaussian employed here28.Apart from the Hubbard energy, the primary factors that influence the bipolaron density in this model are the width of the interface DOS  for energetically broad interface DOS distributions at contacts in the Fermi level pinning regime. In this context, bipolarons may also be significant at other interfaces that sustain high charge density in a broadened interfacial DOS, such as the channel of organic thin film transistors34, with a 6–31 G** split valence plus polarization basis set. The effect of the surrounding medium is incorporated by using a conductor-like polarizable continuum model (cpcm), where the dielectric constant of the medium is chosen to be 2.5. The excited states were computed using time-dependent DFT at the same level, with fixed nuclear geometries maintained from the respective ground states. All DFT calculations were performed with the G09 suite of programs35.Density functional theory (DFT) calculations were carried-out using the B3LYP functional, where Becke’s three-parameter hybrid exchange functional is combined with the Lee–Yang–Parr correlation functional−7 Torr. Gradient sublimation-purified TPD was deposited at a rate of 0.3 nm s−1 followed by a 100 nm thick Ag cathode contact defined via a shadow mask to yield 2 × 2 mm2 individual device areas. Devices were encapsulated in a nitrogen-filled glove box with a thin layer of Norland optical adhesive.Devices were prepared on pre-patterned ITO-coated glass  substrates that were solvent-cleaned and treated with air plasma for 5 min before loading into a thermal evaporator with a base pressure of ~10+ standard reference electrode in an H-cell with chambers separated by a glass frit with 10–20 μm size pores. The Ag/Ag+ reference electrode consisted of 0.01 M AgNO3 and 0.1 M tetrabutylammonium tetrafluoroborate electrolyte in acetonitrile. Absorption spectra were measured relative to an electrolyte-solvent reference by pipetting solution from the electrochemical cell into quartz cuvettes for analysis in a Varian Cary 6000i spectrophotometer. Supplementary Figure Cyclic voltammetry measurements were performed using a Metrohm Autolab PGSTAT 128 N potentiostat/galvanostat on a solution of 55 μM TPD with 0.5 M tetrabutylammonium tetrafluoroborate dissolved in dichloromethane. Platinum wire mesh working and counter electrodes were used with a Ag/AgR/R) due to a 400 Hz square wave voltage signal was detected synchronously using Si and Ge photodiodes and a lock-in amplifier. Magnetic field-dependent measurements were conducted by repeatedly moving a permanent neodymium pyramid magnet adjacent to, and then away from, a given device and monitoring the resultant change in current and/or reflectivity as detailed in Supplementary Figure 4.Charge modulation spectroscopy measurements were performed using an Energetiq laser-driven Xe light source filtered through a monochromator with order sorting filters. The light was s-polarized using a wire grid polarizer and was incident on devices through the glass substrate at an angle of 45°. The relative change in reflectivity (ΔThe data that support the findings of this study are available from the corresponding author upon reasonable request.Supplementary InformationPeer Review File


This study uses retrospective forecasts made using an APEC Climate Center seasonal forecast model to investigate the cause of errors in predicting the amplitude of El Niño Southern Oscillation (ENSO)-driven sea surface temperature variability. When utilizing Bjerknes coupled stability (BJ) index analysis, enhanced errors in ENSO amplitude with forecast lead times are found to be well represented by those in the growth rate estimated by the BJ index. ENSO amplitude forecast errors are most strongly associated with the errors in both the thermocline slope response and surface wind response to forcing over the tropical Pacific, leading to errors in thermocline feedback. This study concludes that upper ocean temperature bias in the equatorial Pacific, which becomes more intense with increasing lead times, is a possible cause of forecast errors in the thermocline feedback and thus in ENSO amplitude. ENSO is the most dominant natural climate fluctuation on interannual time scales and has an enormous impact on global climate2. Moreover, skillful prediction of the ENSO-driven SST variability makes it possible to provide reliable global seasonal climate prediction of variables, e.g., precipitation and surface temperature5. Therefore, successful ENSO prediction with long lead times gives decision makers an opportunity to consider predicted climate anomalies to reduce the socioeconomic and environmental impacts of ENSO.Long-term ocean memory allows seasonal forecast models to provide a few season-ahead skillful predictions of sea surface temperature (SST) variability associated with the El Niño-Southern Oscillation (ENSO) in the tropical Pacific Ocean7. The recent decade’s coupled models perform better than statistical models7. However, coupled models still have systematic errors in the tropical Pacific climatological mean states. Previous inter-model comparison studies attempted to reveal the relationship between the tropical Pacific mean state and ENSO simulations and highlighted the importance of properly simulating the climatological mean state in the tropical Pacific for realistic simulations of ENSO10. Specifically, the climatological cold bias in the upper tropical Pacific Ocean affects the reliability of simulating the amplitude of ENSO-driven SST variability, leading to an inter-model diversity of ENSO representations11.There has been noticeable progress in the prediction of ENSO events using coupled climate models13. The enhanced model errors regarding the tropical Pacific mean states during forecast runs could affect the predictive capability for ENSO events. Some studies have shown that an improved representation of ENSO variability can be obtained when using a correction method to reduce the tropical Pacific mean states14. To improve ENSO prediction with coupled models, some studies have attempted to understand the source and reason of the mean state biases with hindcast simulations because one can trace the development of the climatological mean bias in the tropical Pacific during model integrations15. However, no study has yet investigated where the mean state errors start and grow or how growing mean state errors dynamically affects the ENSO prediction capability of coupled models as forecast lead times increase. By utilizing hindcast simulations, we can explore how the growing biases are dynamically connected to the errors in ENSO prediction.During coupled model integrations, model drift, where the climate state of the coupled model tends to move toward the model’s own climatology (which is biased from observations), is inevitablewww.apcc21.org for more information). By developing a simple initialization scheme based on coupled nudging, the APCC operationalized the National Center for Atmospheric Research (NCAR) Community Climate System Model version 3 (CCSM3)16 to support the APCC MME system. The APCC seasonal forecast model is called the APCC CCSM3.The APEC Climate Center (APCC) has made great efforts to provide reliable forecast information for the Asia-Pacific region by operating the APCC multi-model ensemble (MME) forecast system  and the root mean square error (RMSE) between the observed Niño 3.4 index and the index from individual forecasts were calculated, as shown in Fig. If we examine the time series of the Niño 3.4 index from the model predictions Fig.  more clo17. The BJ index formula was developed to assess the overall stability of the coupled ENSO mode. Its capability to estimate ENSO stability was successfully verified through a detailed eigen-analysis of an intermediate-coupled model10 and through various simulations of a hybrid-coupled model with different atmospheric and oceanic mean state conditions17. The BJ index has been utilized in many studies for revealing the possible causes of changes in ENSO behavior under different mean states23. The BJ index can estimate the linear ENSO growth rate derived from a coupled system of observations and climate models, and hence it is essentially related to ENSO amplitude. Furthermore, as ENSO-related feedbacks can be partitioned by the BJ index analysis, it is possible to understand errors in the atmosphere-ocean coupling process associated with ENSO amplitude forecast errors.In this study, the Bjerknes coupled stability (BJ) index (see methods) is used to understand the possible causes of ENSO amplitude forecast errorsAs mentioned in the Methods section, we reconstructed monthly datasets from forecasts at 1- to 6-month lead times, and each forecast has five ensemble members. Therefore, we obtained 30 samples each for ENSO amplitude and the BJ index and its related terms . Using these samples, correlation and regression analyses were performed.As found in scatterplots of ENSO amplitude versus the BJ index Fig.  from the−1) is more negative than the BJ index from observations (−0.03 yr−1), whereas ENSO amplitude  at the 1-month lead time is slightly larger than that from the observations. This discrepancy is because the BJ index formula does not consider the possible role of non-linearity, noise, and seasonal cycles that also contribute to ENSO amplitude26. A recent study comparing BJ index terms with direct heat budget terms indicated that non-linearity is not captured by the BJ index27. However, numerous studies have shown that ENSO dynamics are largely linear28, as supported by the success of the ENSO oscillator theories28. The BJ index formula is intended to capture this intrinsic nature of ENSO linear dynamics10. Despite its shortcomings, the significant correlation between the ENSO amplitude and the BJ index strongly indicates that we can still utilize BJ index analysis to reveal the reason for ENSO amplitude forecast errors.In Fig. 11. Among positive feedback terms, the thermocline feedback term from the forecasts has a magnitude of 0.47 ± 0.05 yr−1 at the 1-month lead time, and the magnitude of the feedback term further decreases to 0.14 ± 0.02 yr−1 at a 6-month lead time, which is much smaller than that of the observations (0.75 yr−1). However, there are no clear decreasing tendencies of the other feedback terms with forecast lead times. This is evident in Fig. −1 lead mon−1) is mainly supported by that of the thermocline feedback (−0.06 ± 0.01 yr−1 lead mon−1). In contrast, the thermodynamic damping term, the trend of which has a magnitude of 0.02 ± 0.01 yr−1 lead mon−1, has an increasing tendency. Other terms  have relatively small trend values. Therefore, the results suggest that ENSO amplitude forecast errors could be linked to those in the thermocline feedback.Figure βh) and the surface wind response to SST change (μa) are most strongly correlated with a change in the thermocline feedback . Regression analysis also shows that both response sensitivity coefficients  have relatively large slopes with respect to thermocline feedback. Therefore, an increase in thermocline feedback errors with forecast lead times could be related to errors in the zonal thermocline slope response to wind change and the zonal wind response to SST change. The dominance of the thermocline slope response in the thermocline feedback has been suggested in previous numerical and observational studies21, and some studies have speculated that the thermocline response errors are attributable to an upper ocean cold bias in the tropical Pacific20. Furthermore, under a simple dynamical framework, the thermocline response depends on the mean thermocline depth and the upper ocean mean vertical stratification23. Therefore, we investigate how the upper ocean temperature bias affects those oceanic mean states, and as a result, leads to thermocline response forecast errors.Figure 29 showed that the simulation of the Pacific tropical-extratropical water mass exchange through Pacific Subtropical Cell pathways can induce the thermocline bias in the CCSM3. In other words, the bias in the simulated thermocline may be due to the subduction of the colder water in the extratropical Pacific Ocean  below the thermocline in comparison with the reanalysis. In contrast, the simulated vertical temperature gradients in the ocean above the equatorial thermocline become stronger than those in the ocean reanalysis with an increase in forecast lead time. Moreover, because the vertical temperature gradient difference between forecasts and observations, which is averaged from the surface to thermocline depth , the role of the atmospheric mean bias, which may be related to atmospheric feedback errors, should be investigated to identify whether the ocean or the atmosphere dominates ENSO amplitude.As a concluding remark, this study mainly focused on the role of oceanic mean biases in ENSO-related feedback errors. Because the importance of the atmospheric component of ENSO growth has been highlighted in previous studiesThe atmospheric component of the APCC CCSM3 has a horizontal resolution of T85 (1.4° longitude × 1.4° latitude) and 26 vertical levels; the land surface component has the same horizontal resolution as the atmospheric component; the ocean component of the model has 40 vertical levels and a horizontal resolution of 1° in a longitudinal direction and 1° (1/3° near the equator) in the latitudinal direction; and the sea ice component has the same horizontal resolution as the ocean component.37 datasets. The pentad mean GODAS datasets were interpolated into daily means using piecewise linear interpolation. To generate five ensemble member forecasts, hindcast simulations begin from the initial conditions of the atmosphere, land, and sea ice components in the last five days of each calendar month and all use the same initial oceanic conditions each month. The date of the initial ocean condition (when the forecast run starts) differs from month to month  due to the availability of the pentad mean GODAS data. For example, the hindcast simulations initialized in August used the atmospheric initial conditions from the 27th, 28th, 29th, 30th, and 31st of August, and the oceanic initial conditions from the 23rd were used. Predictions for the month following the initial condition month are referred to as forecasts at a 0-month lead time. Therefore, the full 7-month integration produces forecasts from 0- to 6-month lead times.Hindcast datasets of the APCC CCSM3 were produced by simulating a 7-month integration for each of the 12 calendar months in the 33 years from 1982 to 2014. Hindcast simulations were initiated from five different initial conditions in each month. Using a simple wind-ocean temperature nudging initialization method  were reconstructed to obtain monthly datasets covering the period from 1982–2014 for each lead time. Using the reconstructed datasets, anomalies were then obtained by extracting the climatological seasonal cycle at each lead time from the individual forecasts. See Fig. 38. Simulated ocean subsurface temperature was verified against the GODAS data set.For ENSO forecast verification, the Niño 3.4 index  obtained from the hindcast simulations was compared to that obtained from the optimum interpolation SST version 2 (OISSTv2)BJ denotes the BJ index, a greater magnitude of which implies that the tropical Pacific climate coupled system contributes to a stronger ENSO; ε is the damping rate related to the upper ocean adjustment, which is ignored10; 〈A〉E denotes area-averaged quantities over the eastern region of the equatorial Pacific basin; Lx and Ly represent the longitudinal and latitudinal length scales, respectively, of the eastern boxed region; and H1 (=50 m) is a mixed layer depth. The right-hand side of the BJ index formula, from left to right, denotes: mean advection damping, thermodynamic damping, zonal advective feedback, Ekman feedback, and thermocline feedback. Each positive feedback term is represented as a function of the tropical Pacific Ocean mean state and oceanic and atmospheric response sensitivity coefficients; the latter are computed using a least-squares linear regression from the approximated balance equations, namely, 〈Q〉E = −αs〈T〉E, [τx] = μa〈T〉E, 〈u〉E = βu[τx] + βuh〈h〉W, h〉E − 〈h〉W = βh[τx], and 〈A〉W and [A] denote quantities that are area-averaged over the western boxed region and those averaged zonally over the equatorial Pacific basin , respectively. Q) change associated with change in an anomalous mixed-layer ocean temperature (T); an anomalous surface wind response (τx) to an anomalous mixed-layer ocean temperature change; the response of mixed layer ocean zonal current anomalies (u), ocean upwelling anomalies (w), and an anomalous equatorial thermocline (h) slope to surface wind change; and an effect of anomalous thermocline depth changes on ocean subsurface (a depth of 50 m) temperature anomalies (Tsub). The anomalous thermocline depth is estimated with an oceanic heat content anomaly, which is defined as the vertically averaged ocean temperatures from the ocean surface to a depth of 300 m.The BJ index is formulated as follows (see ref. 〈A〉E) for the APCC CCSM3 is defined as 5°S-5°N, 171°W-82°W. The longitude of the western edge of the eastern boxed region is an average (171°W ± 3°) of those from all members and all forecast lead times. When we used different longitudes from each member and each lead time, similar results were obtained. For the GODAS datasets, the eastern region is defined as 5°S-5°N, 173°W-82°W. The western boxed region  covers from 121°E to the longitude of the western edge of the eastern boxed region.GODAS datasets were used for the observed BJ index. The boxed regions for the APCC CCSM3 and reanalysis  were determined from the spatial pattern of heat content anomalies associated with their own leading ENSO mode (also see ref. The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.Supplementary Information


Because we used the chromatin remodeller Mxi1, our gates showed minimal leak and digital responses. We built a combinatorial library of NOR gates that directly convert guide RNA (gRNA) inputs into gRNA outputs, enabling the gates to be ‘wired' together. We constructed logic circuits with up to seven gRNAs, including repression cascades with up to seven layers. Modelling predicted the NOR gates have effectively zero transcriptional leak explaining the limited signal degradation in the circuits. Our approach enabled the largest, eukaryotic gene circuits to date and will form the basis for large, synthetic, cellular decision-making systems.Natural genetic circuits enable cells to make sophisticated digital decisions. Building equally complex synthetic circuits in eukaryotes remains difficult, however, because commonly used components leak transcriptionally, do not arbitrarily interconnect or do not have digital responses. Here, we designed  The leakiness of commonly used genetic components can make the construction of complex synthetic circuits difficult. Here the authors construct NOR gate architecture, using dCas9 fused to the chromatin remodeller Mxi1, that can be wired together into complex circuits. Living cells make decisions based on information processing genetic programmes. Many of these programmes execute digital functions12345671012dCas9-mediated repression in prokaryotesdCas9. Although dCas9 allows for programmable interconnections, its response function is leaky leading to signal degradation when layered3536Genetic components that implement simple logical operations, which in principle could be interconnected to form complex logic functions, have been demonstrated1415161718192021221924252628182030313233First, we built a universal, single-gene NOR logic gate; the NOR gates are functionally completeMxi1 to take advantage of the eukaryotic cell's ability to repress gene expression, by fusing this domain to dCas9  input stage, driving an output stage, ribozyme-flanked gRNA (RGRk)  target sites that match ri and rj respectively. Since we designed 20 signals, there are 203=8,000 total NOR gates in the set. A NORi,j,k functions as a NOTj,k if the pGRRi,j contains two identical target sites, if the pGRRi,j contains only one target site from the 20 component library  or if ri is simply not used in the circuit. A target sequence of ‘null' refers to a pGRR that contains a target sequence that does not match any gRNA used in the containing circuit.The gate NORA (RGRk) . Accordihis work . The pGRi,j promoter is tightly repressed when gRNA-dCas9-Mxi1 is bound to one or both of its two 20 bp target sites. The core region of the pGRRi,j, the minimal pCYC1 promoter, was chosen based on its successful use with dCas9 in the pasti and rj, further separating the digital ON and digital OFF levels , 16 were repressed to or near the level of Saccharomyces cerevisiae autofluorescence in the presence of the corresponding signal ri  and r11–20 (iRGR design) were paired with all pGRR1-20,null:GFP among noncognate pairs (1–10 and iRGR11–20) when targeted to their cognate pGRR1-20,null:GFP constructs, 16 repressed fluorescence to or near the level of autofluorescence for S. cerevisiae , equivalent to the production of roughly one transcript every 5 to 10 cell divisions. The reported value of L was calculated as the average of the predicted transcriptional leak from the model fits from dCas9-Mxi1 to decrease transcriptional leak compared with steric repression via dCas9, gRNA dose response curves of repression at three pGRR promoter target site positions were performed using dCas9 and dCas9-Mxi1  with increasing circuit depth. Linear regression analysis estimated the slope of the increase in response time per layer to be equal to 184.9±0.2 (s.e.m.) min layer−1 , falls within the sensitive range, indicating the importance of utilizing well-performing NOR gates in large circuits built using our architecture. In addition, these data show the significance of reducing NOR gate leak when constructing larger circuits.Signal degradation was found to be largely dependent on the transcriptional leak parameter, L . As leakdCas9-based modular genetic NOR gates that behave digitally, have low variability and show minimal retroactivity or effects on cell growth. These features made these gates relatively easy to combine into Boolean logic circuits that are among the largest ever built in any organism. In particular, we found that most circuits in We introduced a class of 2+connections2)1/2. For example, the XOR gate had five gates and four connections, producing a complexity of (52+42)1/2=6.4, while the cascade has a complexity of (72+12)1/2=9.2. These complexities compare well with gene circuits developed in Escherichia coli, for example. Our NOR gates enabled extremely simple design and construction of large gene circuits. Before genetic circuits can be made much larger, however, many factors that influence the size and complexity of synthetic genetic circuits must be addressed.First, the gates in any framework must be well behaved. Gates can suffer from retroactivity, where a downstream gate affects the behaviour of upstream gates to which it is not connected by design5556E. coli are ∼60 bp of DNA long, and transcriptional regulation is a fairly well-understood process59606162E. coli in 2030313234Mxi1 repression domain has been used in synthetic contexts to regulate transcription in human cells3039Second, the host organism presents many unique challenges. Each organism can be thought of as a different computer operating system. Promoters, for example, in Third, the method by which circuits are constructed and the genetic tractability of the host affects progress toward building large circuits. For example, the circuits we present here are all singly integrated into the yeast genome, because plasmid-based systems exhibit cell-to-cell variation in copy number. That made the process of building and testing strains slow, costly and cumbersome and in fact limited our ability to build circuits much larger than those shown here. Larger circuits and large libraries of circuit variants will require that we develop, for example, one-pot assembly methods for large DNA constructs62The success or failure of different approaches to building bigger circuits may depend on how well behaved, insulated, simple and scalable the input low-level devices and gates are. In addition, relaxing the requirement that circuits be digital, so that analogue or mixed analogue/digital circuits can be used when appropriate, will likely open up the design space, further increasing the size of the circuits we can build so that one day they can match the size and performance of natural genetic circuits.20. Next, linearized DNA, salmon sperm donor DNA, 50% polyethylene glycol and 1 M LiOAc were combined with 50 μl of competent cells and the mixture was heat shocked at 42 °C for 15 min. The cells were then spun down, supernatant was removed and they were resuspended in H2O and then plated on selective agar media. Transformations were done into MATa W303-1A and MATalpha W303-1B background strains. Matings of the MATa and MATalpha were performed by coculturing both mating types and plating the culture onto selective agar media. All strains and sequences used in this work are detailed in the Yeast transformations were carried out using a standard lithium acetate protocol−1 respectively, helix minimum free energy=6.346 kcal mol−1 and folded without pseudoknots or entanglements. A total of 12 Kinefold simulations were run for each candidate sequence and agglomerated to generate average folding trace data.RGR and iRGR sequences were computationally designed to enable the 5′ hammerhead ribozymes to fold into their target, functionally active, structures. ViennaRNA (RNAfold 2.1.9) was used to simulate long timescale (thermodynamic equilibrium) at an input temperature of 37 °C. Kinefold (kinefold_long_static_bianary 20060404) was used to simulate short timescale folding  with inputs of low and high polymerization rates of 25 and 50 nt sRibozyme target structures needed for both viennaRNA and Kinefold simulation evaluation were determined by folding ribozyme sequences  using RNAfold and Kinefold , respectively. RGR targeting sequences and iRGR insulating sequences were screened in specific 5′ promoter contexts  and in the 3′ context of the targeting sequence and the gRNA handle sequence (gRNA handle: 5′-GTTTTAGAGCTAGAAATAGCAAGTTAAAATAAGGCTAGTCCGTTATCAACTTGAAAAAG TGGCACCGAGTCGGTGCTTTT-3′).Randomly generated 20 bp candidate targeting sequences for RGR, of which the most 5′ 6 bp defined the closing stem of the minimal HH ribozyme, were folded in the context of each promoter to confirm that the target structure was present in the MFE structure (viennaRNA) and that the target structure was present at >90% in the RNA folding trace at both low and high polymerase rates (Kinefold). Targeting sequences that enabled correct folding in the context of each promoter were considered successful. For iRGRs, randomly generated 5′ and 3′ insulating sequences were designed for each of the three promoter types and were screened for function in the same manner. However, to select for the most robust insulating sequences, each was screened against 75 randomly generated and 10 randomly generated 20 bp guide sequences using viennaRNA and Kinefold, respectively.Fluorescence intensity was measured with a BD Accuri C6 flow cytometer equipped with a CSampler plate adapter using excitation wavelengths of 488 and 640 nm and an emission detection filter at 533 nm (FL1 channel). A total of 10,000 events above a 400,000 FSC-H threshold (to exclude debris) were recorded for each sample with and core size of 22 mm using the Accuri C6 CFlow Sampler software. Cytometry data were exported as FCS 3.0 files and processed using the flowCore R software package and custom R scripts  to obtaiCytometry readings were taken with cultures inoculated into synthetic complete with cells from freshly struck out on agar. Colonies were picked from plates and grown for 3 h at 30 °C before reads were taken.Cytometry measurements were taken on cells grown in cultures diluted 1:1,000 from saturated culture for 16 h at 30 °C.βe) concentration of 100 nm. Cytometry measurements were taken over an ∼30 h period. During the time course, cells were periodically diluted to keep them in log growth phase. Experimental data collected for steady state were measured for four strains, each containing four different βe-inducible cascades. Each of the four strains was induced with 18 different doses of βe ranging from 0 to 100 μM in a single batch of 72 cultures. Cells were diluted every 8–15 h to prevent culture saturation. Steady-state fluorescence readings were taken after 5 days when the cultures were in log phase.Cells from saturated culture were diluted 1:100 into fresh media with a Beta Estradiol (dCas9-Mxi1 and green fluorescent protein (GFP) molecular constituents were modelled as follows:A deterministic model of our system was described by three ordinary differential equations characterizing transcription, degradation and repression. The gRNA-rd is the concentration of the dth gRNA-dCas9-Mxi1, d ranges from 1 to D−1, where D is the number of layers in the cascade; rD is the input gRNA driven by the inducible promoter; vd is the promoter strength driving each rd in terms of the maximum steady-state concentration of gRNA from the promoter; G is the measurable normalized concentration of GFP; b is the degradation/dilution rate of all rd; B is the degradation/dilution for GFP; kd is the repression strength of rd to its cognate promoter, in terms of the number of repressors required to suppress a promoter to half strength; to its cognate promoter is modelled with kd, the number of repressors required to suppress a promoter to half-strength; and n is a Hill coefficient. For the transfer function, V, K, nu respectively represent the maximum transcription, Michaelis–Menten constant and Hill coefficient of the inducible promoter; u is the input βe in μM. Concentration is rescaled as the Michaelis–Menten constant or the number of gRNAs required to suppress a NOT gate to half-maximal. Note that the model makes the assumptions that (1) there is no crosstalk between gRNA components, (2) Mxi1 represses transcription completely with no transcriptional leak and (3) dCas9-Mxi1 bind quickly and irreversibly to gRNA.v0ss−v3ss, k0ss−k3ss, Vss, nss were generated from three separate experiments. For each of the three experiments, 17 parameter fits were generated using differential evolution/BFGS and means were calculated for a total of 51 steady-state parameter sets. The means from each experiment were used to determine the experimental error (σ) for estimating each parameter  algorithmarameter . For theperiment . As thercascades .D ∈ {1 … 11}) layers were simulated using the system of ordinary differential equations. Parameters for simulated cascades were generated by resampling parameter sets generated during the fitting procedure. For the kinetic model predictions, 10,000 simulated cascades were generated by resampling parameters from 5 parameter sets estimated from the kinetics experiment. The time-to-half max of GFP (G) was calculated for each cascade length D and plotted in δ) predictions in D=7 were simulated by resampling parameters from the 51 parameter sets estimated from the 3 steady-state experiments. To compare L versus δ, L was sampled from a uniform distribution between 0 and 1. Signal degradation (δ) was calculated as the percent change in dynamic range per additional layer. The dynamic range at each layer d in a cascade of length D was calculated as:Long repression cascades of 1 to 11 (d versus log(ρd) was calculated using linear regression for each of the 100,000 simulations of cascades of length D by:Dynamic range was found to have a log-linear relationship with the length of the cascade, and hence the average slope between D=7. With η being the change in log(ρd) with each additional layer, the percent loss in dynamic range per layer or signal degradation δ is calculated aswith L were binned using a bin size of 0.035 and δ versus L was plotted to generate Values for No data sets were generated during the current study. All data values supporting the experimental conclusions are shown either in main or How to cite this article: Gander, M. W. et al. Digital logic circuits in yeast with CRISPR-dCas9 NOR gates. Nat. Commun.8, 15459 doi: 10.1038/ncomms15459 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Supplementary Figures, Supplementary Tables and Supplementary ReferencesStrain and sequences listR cytometry data processing scripts and mathematical modeling scripts