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We report unique two-step strain glass transition toward different local strain states in NiTi, i.e. R and B19′ strain glasses. This unique transition is evidenced by dynamic mechanical analysis and in-situ HR-TEM. A comprehensive phase diagram is established to illustrate diverse transition pathways and corresponding tunable superelastic properties. This pathway exploits the integrated transition of different phases, lowering the transition energy barrier, yielding superelasticity with large recoverable strain (6%), ultralow modulus (24 GPa) and robust cyclic and wide-temperature stability. Our investigation provides fresh insights into continuous transition pathways among different strain glass states to achieve exceptional properties in shape memory alloys.

Abstract Age at first farrowing (AFF) is a reproductive trait with low heritability and high importance in the pig industry. To enhance the statistical power of genome‐wide association study (GWAS) and further explore the genetic nature of AFF, we first conducted GWAS meta‐analysis using three Yorkshire populations, and then integrated the Pig Genotype‐Tissue Expression (PigGTEx) resources to interpret their potential regulatory mechanism. Additionally, we compared the AFF in pig with the age at first birth (AFB) of human using GWAS summary statistics. We detected 18 independent variants in GWAS meta‐analysis and 8 genes in gene‐based association analysis significantly associated with AFF. By integrating the PigGTEx resource, we conducted transcriptome‐wide association study (TWAS) and colocalization analysis on 34 pig tissues. In TWAS, we detected 18 significant gene‐tissue pairs, such as DCAF6 in uterus and CREG1 in blood. In colocalization, we found 111 potential candidate tissue‐gene pairs, such as GJD4 and LYPLAL1. We found that the homologous gene, CHST10, might be the potential candidate gene between humans in AFB and pigs in AFF. In conclusion, integrating GWAS meta‐analysis and PigGTEx resources is a meaningful way to decipher the genetic architecture of complex traits. We found that DCAF6, CREG1, GJD4, and LYPLAL1 are candidate genes with high reliability for AFF in swine. The comparative analysis showed that CHST10 might play a potentially critical role in AFB/AFF across human and pigs.

Abstract Recent advancements in machine learning (ML) have revolutionized the field of high-performance materials design. However, developing robust ML models to decipher intricate structure-property relationships in materials remains challenging, primarily due to the limited availability of labeled datasets with well-characterized crystal structures. This is particularly pronounced in materials where functional properties are closely intertwined with their crystallographic symmetry. We introduce a self-supervised probabilistic model (SSPM) that autonomously learns unbiased atomic representations and the likelihood of compounds with given crystal structures, utilizing solely the existing crystal structure data from materials databases. SSPM significantly enhances the performance of downstream ML models by efficient atomic representations and accurately captures the probabilistic relationships between composition and crystal structure. We showcase SSPM’s capability by discovering shape memory alloys (SMAs). Amongst the top 50 predictions, 23 have been confirmed as SMAs either experimentally or theoretically, and a previously unknown SMA candidate, MgAu, has been identified.

Abstract In thermoelectric, phase interface engineering proves effective in reducing the lattice thermal conductivity via interface scattering and amplifying the density-of-states effective mass by energy filtering. However, the indiscriminate introduction of phase interfaces inevitably leads to diminished carrier mobility. Moreover, relying on a singular energy barrier is insufficient for comprehensive filtration of low-energy carriers throughout the entire temperature range. Addressing these challenges, we advocate the establishment of a composite phase interface using atomic layer deposition (ALD) technology. This design aims to effectively decouple the interrelated thermoelectric parameters in ZrNiSn. The engineered coherent dual-interface energy barriers substantially enhance the density-of-states effective mass across the entire temperature spectrum while preser carrier mobility. Simultaneously, the strong interface scattering on phonons is crucial for curtailing lattice thermal conductivity. Consequently, a 40-cycles TiO2 coating on ZrNi1.03Sn0.99Sb0.01 achieves an unprecedented zT value of 1.3 at 873 K. These findings deepen the understanding of coherent composite-phase interface engineering.

Abstract Background Multi-population genomic prediction can rapidly expand the size of the reference population and improve genomic prediction ability. Machine learning (ML) algorithms have shown advantages in single-population genomic prediction of phenotypes. However, few studies have explored the effectiveness of ML methods for multi-population genomic prediction. Results In this study, 3720 Yorkshire pigs from Austria and four breeding farms in China were used, and single-trait genomic best linear unbiased prediction (ST-GBLUP), multitrait GBLUP (MT-GBLUP), Bayesian Horseshoe (BayesHE), and three ML methods (support vector regression (SVR), kernel ridge regression (KRR) and AdaBoost.R2) were compared to explore the optimal method for joint genomic prediction of phenotypes of Chinese and Austrian pigs through 10 replicates of fivefold cross-validation. In this study, we tested the performance of different methods in two scenarios: (i) including only one Austrian population and one Chinese pig population that were genetically linked based on principal component analysis (PCA) (designated as the “two-population scenario”) and (ii) adding reference populations that are unrelated based on PCA to the above two populations (designated as the “multi-population scenario”). Our results show that, the use of MT-GBLUP in the two-population scenario resulted in an improvement of 7.1% in predictive ability compared to ST-GBLUP, while the use of SVR and KKR yielded improvements in predictive ability of 4.5 and 5.3%, respectively, compared to MT-GBLUP. SVR and KRR also yielded lower mean square errors (MSE) in most population and trait combinations. In the multi-population scenario, improvements in predictive ability of 29.7, 24.4 and 11.1% were obtained compared to ST-GBLUP when using, respectively, SVR, KRR, and AdaBoost.R2. However, compared to MT-GBLUP, the potential of ML methods to improve predictive ability was not demonstrated. Conclusions Our study demonstrates that ML algorithms can achieve better prediction performance than multitrait GBLUP models in multi-population genomic prediction of phenotypes when the populations have similar genetic backgrounds; however, when reference populations that are unrelated based on PCA are added, the ML methods did not show a benefit. When the number of populations increased, only MT-GBLUP improved predictive ability in both validation populations, while the other methods showed improvement in only one population.

Abstract The ultrahigh flexibility and elasticity achieved in freestanding single-crystalline ferroelectric oxide membranes have attracted much attention recently. However, for antiferroelectric oxides, the flexibility limit and fundamental mechanism in their freestanding membranes are still not explored clearly. Here, we successfully fabricate freestanding single-crystalline PbZrO3 membranes by a water-soluble sacrificial layer technique. They exhibit good antiferroelectricity and have a commensurate/incommensurate modulated microstructure. Moreover, they also have good shape recoverability when bending with a small radius of curvature (about 2.4 μm for the thickness of 120 nm), corresponding to a bending strain of 2.5%. They could tolerate a maximum bending strain as large as 3.5%, far beyond their bulk counterpart. Our atomistic simulations reveal that this remarkable flexibility originates from the antiferroelectric-ferroelectric phase transition with the aid of polarization rotation. This study not only suggests the mechanism of antiferroelectric oxides to achieve high flexibility but also paves the way for potential applications in flexible electronics.

IntroductionThe hair follicle (HF) is a micro-organ capable of regeneration. A HF cycle consists of an anagen, catagen and telogen. Abnormalities in the HF cycle can lead to many hair disorders such as hair loss. The pig is a good biomedical model, but there are few data on their HF cycle. The aim of this study was to classify the pig HF cycle and determine the feasibility of the pig as an animal model for human HF cycle.MethodsSkin samples from 10 different postnatal (P) days Yorkshire pigs was collected to determine the key time points of the first HF cycle in pig by H&E staining, immunofluorescence staining, q-PCR and western-blot.ResultsBy morphological observation and detection of markers at different stages, pig HF cycle was classified into three main periods - the first anagen until P45, catagen (P45–P85), telogen (P85–P100), and next anagen (>P100). In addition, we examined the expression of important genes AE15, CD34, Versican, Ki67 et al. related to the HF cycle at different stages of pig HF, indicating that pig and human share similarities in morphology and marker gene expression patterns of HF cycle.DiscussionOur findings will facilitate the study of HF cycle and offer researchers a suitable model for human hair research.

Valence electron concentration (VEC) is widely accepted as an effective guideline for designing the mechanical properties of Ti-containing refractory high-entropy alloys (RHEAs). In the present work, a series of Ti–Zr–Nb–Ta and Ti–Zr–Nb–Mo RHEAs with body-centered-cubic (bcc) structure are carefully designed by tailoring their VEC through changing the alloying composition. The elastic properties and mechanical properties are systematically calculated by using a first-principles method. Comparison with available experimental data demonstrates that the employed approach accurately describes the VEC dependence of the elastic and mechanical properties of RHEAs. In general, the elastic stability, elastic properties, ideal shear strength, Vickers hardness, and yield strength increase, whereas Zener anisotropy decreases with increasing VEC. Among all the considered RHEAs, the most isotropic RHEA Ti30Zr30Nb20Mo20 has the best strength-ductility trade-off. Mo has a stronger solid solution strengthening effect than Ta. The higher strength associates with larger lattice distortion induced by increasing VEC. Both elastic stability and mechanical properties are related to the electronic density of states of the alloys. The present work sheds deep insight into the design of high-performance RHEAs through tailoring the VEC.

Abstract The dermis and epidermis, crucial structural layers of the skin, encompass appendages, hair follicles (HFs), and intricate cellular heterogeneity. However, an integrated spatiotemporal transcriptomic atlas of embryonic skin has not yet been described and would be invaluable for studying skin‐related diseases in humans. Here, single‐cell and spatial transcriptomic analyses are performed on skin samples of normal and hairless fetal pigs across four developmental periods. The cross‐species comparison of skin cells illustrated that the pig epidermis is more representative of the human epidermis than mice epidermis. Moreover, Phenome‐wide association study analysis revealed that the conserved genes between pigs and humans are strongly associated with human skin‐related diseases. In the epidermis, two lineage differentiation trajectories describe hair follicle (HF) morphogenesis and epidermal development. By comparing normal and hairless fetal pigs, it is found that the hair placode (Pc), the most characteristic initial structure in HFs, arises from progenitor‐like OGN+/UCHL1+ cells. These progenitors appear earlier in development than the previously described early Pc cells and exhibit abnormal proliferation and migration during differentiation in hairless pigs. The study provides a valuable resource for in‐depth insights into HF development, which may serve as a key reference atlas for studying human skin disease etiology using porcine models.

Abstract Asphaltene is often regarded as an undesirable by‐product of petroleum processing, possesses vast reserves with little market value. The typical routes of consuming asphaltene, namely burning and landfilling, pose significant environmental challenges. In this study, low‐value asphaltene is converted into high‐value ethylated carbon clusters (ECC) using a supercritical ethanol technique. The resulting ECC powder demonstrates promising properties for high density polyethylene (HDPE) composite applications. The effects of incorporating ECC on the mechanical, gas barrier, and anti‐aging properties of the composite are investigated. Results show that a 1 wt.% ECC led to a 4.2% and 43.5% increase in tensile strength and elongation at break, a reduction of 45.8% and 30.7% in oxygen and carbon dioxide permeability. Furthermore, ECC exhibits effective UV spectrum absorption and conversion in the wavelength range of 400–600 nm, providing protection against UV spectrum damage to HDPE. The incorporation of ECC not only enhances the properties of polymer composites but also sequesters carbon within the polymer matrix, enabling the valorization of asphaltene while mitigating environmental impact.

Enhancing corrosion resistance of Mg-Zn alloys with high strength and low cost was critical for broadening their large-scale practical applications. Here we prepared solutionized, peak- and over-aged ZK60 alloys with and without microalloying Ca (0.26 wt.%) to explore the effects of nanoscale precipitates on their corrosion behavior in detail via experimental analyses and theoretical calculations. The results suggested the peak-aged ZK60 alloy with Ca addition showed improved corrosion resistance in comparison with the alloys without Ca, owing to the contribution of Ca on the refinement of precipitates and increase in their number density. Although the precipitates and Mg matrix formed micro-galvanic couples leading to dissolution, the fine and dense precipitates could generate “in-situ pinning” effect on the corrosion products, forming a spider-web-like structure and improving the corrosion inhibition ability accordingly. The pinning effect was closely related to the size and number density of precipitates. This study provided important insight into the design and development of advanced corrosion resistant Mg alloys.

Precursor elastic effects are investigated in a displacive anharmonic spring model and shown to extend greatly into the paraelastic phase. Weak precursor effects can be detected near 2T_{tr}, where T_{tr} is the ferroelastic transition temperature. The precursor effects become strong at T

Abstract Lead sulfide (PbS) presents large potential in thermoelectric application due to its earth‐abundant S element. However, its inferior average ZT (ZTave) value makes PbS less competitive with its analogs PbTe and PbSe. To promote its thermoelectric performance, this study implements strategies of continuous Se alloying and Cu interstitial doping to synergistically tune thermal and electrical transport properties in n‐type PbS. First, the lattice parameter of 5.93 Å in PbS is linearly expanded to 6.03 Å in PbS0.5Se0.5 with increasing Se alloying content. This expanded lattice in Se‐alloyed PbS not only intensifies phonon scattering but also facilitates the formation of Cu interstitials. Based on the PbS0.6Se0.4 content with the minimal lattice thermal conductivity, Cu interstitials are introduced to improve the electron density, thus boosting the peak power factor, from 3.88 μW cm−1 K−2 in PbS0.6Se0.4 to 20.58 μW cm−1 K−2 in PbS0.6Se0.4−1%Cu. Meanwhile, the lattice thermal conductivity in PbS0.6Se0.4−x%Cu (x = 0–2) is further suppressed due to the strong strain field caused by Cu interstitials. Finally, with the lowered thermal conductivity and high electrical transport properties, a peak ZT ~1.1 and ZTave ~0.82 can be achieved in PbS0.6Se0.4 − 1%Cu at 300–773K, which outperforms previously reported n‐type PbS.

Abstract Electron‐correlated materials have been drawing ever‐increasing attention due to their fascinating physical behaviors and extensive application scenarios. In this review, a new method for material research and design (R&D), named structural‐functional unit ordering (SFU ordering), which is presented, overcomes the shortcomings—for example, the limitation of finite chemical elements and long R&D circle‐of conventional strategy and thus provides guidance for the design of these high‐performance functional materials on demand. Meanwhile, with the development of material characterization technologies, SFUs of different scales and types can be directly observed, which, moreover, regulate the corresponding orderings. The review, starts with an introduction of the profile for SFU ordering and the synergistic effect between SFUs. Then, studies on several new high‐performance electronic‐correlated materials, for example, a ferromagnetic semiconductor with local spin, ferromagnetic metals with spin topologies, ferroelectric thin films with polar topologies, piezoelectric thin films with nanopillars enclosed by charged boundaries, thermoelectric materials with local ferromagnetic nanoparticles and topotactic phase transformation with conducting nanofilaments are stated in detail one by one. The vital aspect is the breaking of local symmetry, the construction, the structure, of SFUs and their orderings existing or theoretically existing, together with the enhanced/new performance. All in all, the main comments of the review tend to the remaining challenges, promising design approaches for the SFUs, and their orderings for high‐performance functional materials.

Abstract Background Average backfat thickness (BFT) is a critical complex trait in pig and an important indicator for fat deposition and lean rate. Usually, genome-wide association study (GWAS) was used to discover quantitative trait loci (QTLs) of BFT in a single population. However, the power of GWAS is limited by sample size in a single population. Alternatively, meta-analysis of GWAS (metaGWAS) is an attractive method to increase the statistical power by integrating data from multiple breeds and populations. The aim of this study is to identify shared genetic characterization of BFT across breeds in pigs via metaGWAS. Results In this study, we performed metaGWAS on BFT using 15,353 pigs (5,143 Duroc, 7,275 Yorkshire, and 2,935 Landrace) from 19 populations. We detected 40 genome-wide significant SNPs (Bonferroni corrected P

For relaxor ferroelectrics, correlating their properties and local structures is challenging. Here, the authors correlate the atomic-scale structure and the large dynamic electromechanical property in Bi0.5Na0.5TiO3-based relaxor ferroelectrics.

Thermoelectric material is capable of realizing direct conversion between heat and electricity. Here, the authors obtain high thermoelectric performance in PbSe at low-medium temperatures by importing dense dislocations.

Effects of Zn addition on microstructure and mechanical properties of the extruded Mg97.8Y1.4Co0.8 (at.%, WC) alloy were investigated at room temperature. It was found that the as-cast WC alloy was mainly composed of α-Mg, MgYCo4, Mg3(Co,Y) and 15R-LPSO phases distributed at the grain boundary. All particles of as-homogenized WC alloy were remarkably refined after extrusion, but there was no phase transition during the subsequent homogenized and extruded states. With the replacement of Co from Zn, the as-cast Mg97.8Y1.4Co0.2Zn0.6 (at.%, WZC) alloy consisted of α-Mg, 18R-LPSO with lamellar and blocky shape, and a small amount of rich-Y phases. Parts of 18R-LPSO phases transformed into fine 14H-LPSO phases and stacking faults (SFs) in the grain interior during homogenization and extrusion. The extruded WZC alloy exhibited a smaller average grain size (∼3.2 μm) than the extruded WC alloy (∼3.9 μm) owing to fully dynamic recrystallization (DRX). Both the extruded WC and WZC alloys had a basal plane texture parallel to the normal direction (ND). Tensile testing results indicated that the Zn replacement improved tensile strengths of the extruded WC alloy and maintained the high elongation of the alloy (∼32.2%). The tensile yield strength, ultimate tensile strength and fracture elongation of the extruded WZC alloy were 212 MPa, 281.5 MPa and 32.2%, respectively. The alloy exhibited a good strength and ductility balance. The high tensile strengths of the extruded WZC alloy at room temperature were mainly attributed to grain refinement and the precipitation strengthening of different particles, and the good ductility was mainly due to grain refinement and texture weakening.

Surfaces play a key role during ferroelastic switching and define the interactions of materials with ionic species and biological systems. Here, we perform molecular dynamics simulations and identify ridges and valleys with rounded singularities around the intersections between twin walls and surfaces. Two dominant length scales stem from the elastic bending of the surface layer (>30 lattice units) and local atomic reshuffles (some five lattice units). For static twin walls, which do not shift laterally under external stress, the intrinsic change in Young’s modulus involves softening near valleys and hardening near ridges. The boundary-induced changes in the surface Young’s modulus are of the order of 0.7%.

Abstract Background Compared to medium-density single nucleotide polymorphism (SNP) data, high-density SNP data contain abundant genetic variants and provide more information for the genetic evaluation of livestock, but it has been shown that they do not confer any advantage for genomic prediction and heritability estimation. One possible reason is the uneven distribution of the linkage disequilibrium (LD) along the genome, i.e., LD heterogeneity among regions. The aim of this study was to effectively use genome-wide SNP data for genomic prediction and heritability estimation by using models that control LD heterogeneity among regions. Methods The LD-adjusted kinship (LDAK) and LD-stratified multicomponent (LDS) models were used to control LD heterogeneity among regions and were compared with the classical model that has no such control. Simulated and real traits of 2000 dairy cattle individuals with imputed high-density (770K) SNP data were used. Five types of phenotypes were simulated, which were controlled by very strongly, strongly, moderately, weakly and very weakly tagged causal variants, respectively. The performances of the models with high- and medium-density (50K) panels were compared to verify that the models that controlled LD heterogeneity among regions were more effective with high-density data. Results Compared to the medium-density panel, the use of the high-density panel did not improve and even decreased prediction accuracies and heritability estimates from the classical model for both simulated and real traits. Compared to the classical model, LDS effectively improved the accuracy of genomic predictions and unbiasedness of heritability estimates, regardless of the genetic architecture of the trait. LDAK applies only to traits that are mainly controlled by weakly tagged causal variants, but is still less effective than LDS for this type of trait. Compared with the classical model, LDS improved prediction accuracy by about 13% for simulated phenotypes and by 0.3 to ~ 10.7% for real traits with the high-density panel, and by ~ 1% for simulated phenotypes and by − 0.1 to ~ 6.9% for real traits with the medium-density panel. Conclusions Grouping SNPs based on regional LD to construct the LD-stratified multicomponent model can effectively eliminate the adverse effects of LD heterogeneity among regions, and greatly improve the efficiency of high-density SNP data for genomic prediction and heritability estimation.

Abstract Background Recently, machine learning (ML) has become attractive in genomic prediction, but its superiority in genomic prediction over conventional (ss) GBLUP methods and the choice of optimal ML methods need to be investigated. Results In this study, 2566 Chinese Yorkshire pigs with reproduction trait records were genotyped with the GenoBaits Porcine SNP 50 K and PorcineSNP50 panels. Four ML methods, including support vector regression (SVR), kernel ridge regression (KRR), random forest (RF) and Adaboost.R2 were implemented. Through 20 replicates of fivefold cross-validation (CV) and one prediction for younger individuals, the utility of ML methods in genomic prediction was explored. In CV, compared with genomic BLUP (GBLUP), single-step GBLUP (ssGBLUP) and the Bayesian method BayesHE, ML methods significantly outperformed these conventional methods. ML methods improved the genomic prediction accuracy of GBLUP, ssGBLUP, and BayesHE by 19.3%, 15.0% and 20.8%, respectively. In addition, ML methods yielded smaller mean squared error (MSE) and mean absolute error (MAE) in all scenarios. ssGBLUP yielded an improvement of 3.8% on average in accuracy compared to that of GBLUP, and the accuracy of BayesHE was close to that of GBLUP. In genomic prediction of younger individuals, RF and Adaboost.R2_KRR performed better than GBLUP and BayesHE, while ssGBLUP performed comparably with RF, and ssGBLUP yielded slightly higher accuracy and lower MSE than Adaboost.R2_KRR in the prediction of total number of piglets born, while for number of piglets born alive, Adaboost.R2_KRR performed significantly better than ssGBLUP. Among ML methods, Adaboost.R2_KRR consistently performed well in our study. Our findings also demonstrated that optimal hyperparameters are useful for ML methods. After tuning hyperparameters in CV and in predicting genomic outcomes of younger individuals, the average improvement was 14.3% and 21.8% over those using default hyperparameters, respectively. Conclusion Our findings demonstrated that ML methods had better overall prediction performance than conventional genomic selection methods, and could be new options for genomic prediction. Among ML methods, Adaboost.R2_KRR consistently performed well in our study, and tuning hyperparameters is necessary for ML methods. The optimal hyperparameters depend on the character of traits, datasets etc.

Peripheral nerve injury (PNI) is one of the most common neurological diseases. Recent studies on nerve cells have provided new ideas for the regeneration of peripheral nerves and treatment of physical trauma or degenerative disease-induced loss of sensory and motor neuron functions. Accumulating evidence suggested that magnetic fields might have a significant impact on the growth of nerve cells. Studies have investigated different magnetic field properties (static or pulsed magnetic field) and intensities, various magnetic nanoparticle-encapsulating cytokines based on superparamagnetism, magnetically functionalized nanofibers, and their relevant mechanisms and clinical applications. This review provides an overview of these aspects as well as their future developmental prospects in related fields.

Abstract Two-dimensional materials with ferroelectric properties break the size effect of conventional ferroelectric materials and unlock unprecedented potentials of ferroelectric-related application at small length scales. Using first-principles calculations, a sliding-induced ferroelectric-to-antiferroelectric behavior in bilayer group-IV monochalcogenides (MX, with M = Ge, Sn and X = S, Se) is discovered. Upon this mechanism, the top layer exhibits a reversible intralayer ferroelectric switching, leading to a reversible transition between the ferroelectric and antiferroelectric states in the bilayer MXs. Further results show that the interlayer van der Waals interaction, which is usually considered to be weak, can actually generate an in-plane lattice distortion and thus cause the breaking/forming of intralayer covalent bonds in the top layer, leading to the observed anomalous phenomenon. This unique property has advantages for energy harvesting over existing piezoelectric and triboelectric nanogenerators. The interlayer sliding-induced big polarization change (40 μC cm−2) and ultrahigh polarization changing rate generate an open-circuit voltage two orders of magnitude higher than that of MoS2-based nanogenerators. The theoretical prediction of power output for this bilayer MXs at a moderate sliding speed 1 m s−1 is four orders of magnitude higher than the MoS2 nanogenerator, indicating great potentials in energy harvesting applications.

The filiform corrosion of Mg in NaCl solution was characterized by acoustic emission spectroscopy, measurements of the free-corrosion potential, and optical observations under in situ conditions. Three stages of corrosion were identified: an incubation period, localized attack, and filament propagation. The corrosion mechanisms include the Mg dissolution, the breakdown of hydroxide/oxide surface films, and the burst of gas bubbles. Localized attack and filament propagation are distinguished by a gradual transition from correlated avalanches (wild events) to predominantly stochastic processes (mild events), which still contain some weak avalanche signals. Our approach provides a way to monitor corrosion under in situ conditions.

Mo-Re pre-alloyed powders are crucial raw materials in fabricating Mo-Re alloys, and their properties can significantly impact the properties of the resulting alloys. The powders are usually produced by the co-reduction of a mixture of Mo and Re oxides. However, it remains unclear if the overall characteristics of the produced Mo-Re powders rely on the different combinations of the Mo and Re oxide precursors. Therefore, in this work, a comparative study is conducted on the co-reduction processes of different Mo oxides together with NH4ReO4, along with its influence on the size distribution and phase composition of the resulting Mo-10Re pre-alloyed powders. The results show that MoO3 is more promising than MoO2 as a precursor material. The powders fabricated using MoO3, when compared to MoO2, have a much more uniform size distribution, with a primary particle size ranging from 0.5–4 μm. In addition, it is also beneficial to achieve atomic-scale homogeneous mixing with Mo and Re elements and the formation of a solely Mo(Re) solid solution if MoO3 is used as a precursor oxide. In contrast, such desirable features were not identified when using the MoO2 route. The reason for this discrepancy may relate to whether Mo-O-Re metallurgical bonding has formed during the co-reduction process.

Abstract Background With the emphasis on analysing genotype-by-environment interactions within the framework of genomic selection and genome-wide association analysis, there is an increasing demand for reliable tools that can be used to simulate large-scale genomic data in order to assess related approaches. Results We proposed a theory to simulate large-scale genomic data on genotype-by-environment interactions and added this new function to our developed tool GPOPSIM. Additionally, a simulated threshold trait with large-scale genomic data was also added. The validation of the simulated data indicated that GPOSPIM2.0 is an efficient tool for mimicking the phenotypic data of quantitative traits, threshold traits, and genetically correlated traits with large-scale genomic data while taking genotype-by-environment interactions into account. Conclusions This tool is useful for assessing genotype-by-environment interactions and threshold traits methods.

Cattle have been essential for the development of human civilization since their first domestication few thousand years ago. Since then, they have spread across vast geographic areas following human activities. Throughout generations, the cattle genome has been shaped with detectable signals induced by various evolutionary processes, such as natural and human selection processes and demographic events. Identifying such signals, called selection signatures, is one of the primary goals of population genetics. Previous studies used various selection signature methods and normalized the outputs score using specific windows, in kbp or based on the number of SNPs, to identify the candidate regions. The recent method of iSAFE claimed for high accuracy in pinpointing the candidate SNPs. In this study, we analyzed whole-genome resequencing (WGS) data of ten individuals from Austrian Fleckvieh (Bos taurus) and fifty individuals from 14 Chinese indigenous breeds (Bos taurus, Bos taurus indicus, and admixed). Individual WGS reads were aligned to the cattle reference genome of ARS. UCD1.2 and subsequently undergone single nucleotide variants (SNVs) calling pipeline using GATK. Using these SNVs, we examined the population structure using principal component and admixture analysis. Then we refined selection signature candidates using the iSAFE program and compared it with the classical iHS approach. Additionally, we run Fst population differentiation from these two cattle groups. We found gradual changes of taurine in north China to admixed and indicine to the south. Based on the population structure and the number of individuals, we grouped samples to Fleckvieh, three Chinese taurines (Kazakh, Mongolian, Yanbian), admixed individuals (CHBI_Med), indicine individuals (CHBI_Low), and a combination of admixed and indicine (CHBI) for performing iSAFE and iHS tests. There were more significant SNVs identified using iSAFE than the iHS for the candidate of positive selection and more detectable signals in taurine than in indicine individuals. However, combining admixed and indicine individuals decreased the iSAFE signals. From both within-population tests, significant SNVs are linked to the olfactory receptors, production, reproduction, and temperament traits in taurine cattle, while heat and parasites tolerance in the admixed individuals. Fst test suggests similar patterns of population differentiation between Fleckvieh and three Chinese taurine breeds against CHBI. Nevertheless, there are genes shared only among the Chinese taurine, such as PAX5, affecting coat color, which might drive the differences between these yellowish coated breeds, and those in the greater Far East region.

Genotype by environment (G × E) interaction is fundamental in the biology of complex traits and diseases. However, most of the existing methods for genomic prediction tend to ignore G × E interaction (GEI). In this study, we proposed the genomic prediction method G × EBLUP by considering GEI. Meanwhile, G × EBLUP can also detect the genome-wide single nucleotide polymorphisms (SNPs) subject to GEI. Using comprehensive simulations and analysis of real data from pigs and maize, we showed that G × EBLUP achieved higher efficiency in mapping GEI SNPs and higher prediction accuracy than the existing methods, and its superiority was more obvious when the GEI variance was large. For pig and maize real data, compared with GBLUP, G × EBLUP showed improvement by 3% in the prediction accuracy for backfat thickness, while our findings indicated that the trait of days to 100 kg of pig was not affected by GEI and G × EBLUP did not improve the accuracy of genomic prediction for the trait. A significant advantage was observed for G × EBLUP in maize; the prediction accuracy was improved by ∼5.0 and 7.7% for grain weight and water content, respectively. Furthermore, G × EBLUP was not influenced by the number of environment levels. It could determine a favourable environment using SNP Bayes factors for each environment, implying that it is a robust and useful method for market-specific animal and plant breeding. We proposed G × EBLUP, a novel method for the estimation of genomic breeding value by considering GEI. This method identified the genome-wide SNPs that were susceptible to GEI and yielded higher genomic prediction accuracies and lower mean squared error compared with the GBLUP method.

Genotype imputation from BeadChip to whole-genome sequencing (WGS) data is a cost-effective method of obtaining genotypes of WGS variants. Beagle, one of the most popular imputation software programs, has been widely used for genotype inference in humans and non-human species. A few studies have systematically and comprehensively compared the performance of beagle versions and parameter settings of farm animals. Here, we investigated the imputation performance of three representative versions of Beagle (Beagle 4.1, Beagle 5.0, and Beagle 5.4), and the effective population size (Ne) parameter setting for three species (cattle, pig, and chicken). Six scenarios were investigated to explore the impact of certain key factors on imputation performance. The results showed that the default Ne (1,000,000) is not suitable for livestock and poultry in small reference or low-density arrays of target panels, with 2.47%–10.45% drops in accuracy. Beagle 5 significantly reduced the computation time (4.66-fold–13.24-fold) without an accuracy loss. In addition, using a large combined-reference panel or high-density chip provides greater imputation accuracy, especially for low minor allele frequency (MAF) variants. Finally, a highly significant correlation in the measures of imputation accuracy can be obtained with an MAF equal to or greater than 0.05.

The size of reference population is an important factor affecting genomic prediction. Thus, combining different populations in genomic prediction is an attractive way to improve prediction ability. However, combining multireference population roughly cannot increase the prediction accuracy as well as expected in pig. This may be due to different linkage disequilibrium (LD) pattern differences between population. In this study, we used the imputed whole-genome sequencing (WGS) data to construct LD-based haplotypes for genomic prediction in combined population to explore the impact of different single-nucleotide polymorphism (SNP) densities, variant representation (SNPs or haplotype alleles), and reference population size on the prediction accuracy for reproduction traits. Our results showed that genomic best linear unbiased prediction (GBLUP) using the WGS data can improve prediction accuracy in multi-population but not within-population. Not only the genomic prediction accuracy of the haplotype method using 80 K chip data in multi-population but also GBLUP for the multi-population (3.4–5.9%) was higher than that within-population (1.2–4.3%). More importantly, we have found that using the haplotype method based on the WGS data in multi-population has better genomic prediction performance, and our results showed that building haploblock in this scenario based on low LD threshold (r2 = 0.2–0.3) produced an optimal set of variables for reproduction traits in Yorkshire pig population. Our results suggested that whether the use of the haplotype method based on the chip data or GBLUP (individual SNP method) based on the WGS data were beneficial for genomic prediction in multi-population, while simultaneously combining the haplotype method and WGS data was a better strategy for multi-population genomic evaluation.

Hair placode formation is an important stage of hair follicle morphogenesis and it is a complex process facilitated by non-coding RNAs. In this study, we conducted whole transcriptome sequencing analysis of skin, heart, liver, lung, and kidney tissues of day 41 (E41) normal and hairless pig embryos, and respectively detected 15, 8, and 515 skin-specific differentially expressed (DE) lncRNAs, miRNAs, and mRNAs. Furthermore, 18 competing endogenous RNA (ceRNA) networks were constructed. Following weighted gene co-expression network analysis (WGCNA) of stages E39, E41, E45, E52, and E60, between normal and hairless pig embryos, only two ceRNAs (lncRNA2162.1/miR-29a-5p/BMPR1b and lncRNA627.1/miR-29a-5p/EDAR) that showed period-specific differential expression in E41 skin were retained. Dual-luciferase reporter assays further indicated that EDAR was a direct, functioning target of miR-29a-5p and that no binding site was found in BMPR1b. Moreover, miR-29a-5p overexpression inhibited the mRNA and protein expression of EDAR while no significant differential expression of BMPR1b was detected. In addition, over-expressed lncRNA627.1 reduces the expression of miR-29a-5p and increase EDAR expression while inhibits lncRNA627.1 resulted in a opposite expression trend. Cell proliferation result demonstrated that lower expression of EDAR and lncRNA627.1 inhibited hair placode precursor cells (HPPCs) proliferation in a manner similar to that shown by over-expressed miR-29a-5p. This study identified that miR-29a-5p inhibited HPPCs proliferation via the suppression of EDAR expression in the EDA/EDAR signaling pathway, while lncRNA627.1 rescues EDAR expression. Our study provides a basis for a better understanding of the mechanisms underlying the ceRNA complex, miR29a-5p/EDAR/lncRNA627.1, that could regulate hair placode formation, which may help decipher diseases affecting human hair.

The size of the reference population is critical in order to improve the accuracy of genomic prediction. Indeed, improving genomic prediction accuracy by combining multinational reference populations has proven to be effective. In this study, we investigated the improvement of genomic prediction accuracy in seven complex traits (i.e., milk yield; fat yield; protein yield; somatic cell count; body conformation; feet and legs; and mammary system conformation) by combining the Chinese and Nordic Holstein reference populations. The estimated genetic correlations between the Chinese and Nordic Holstein populations are high with respect to protein yield, fat yield, and milk yield—whereby these correlations range from 0.621 to 0.720—and are moderate with respect to somatic cell count (0.449), but low for the three conformation traits (which range from 0.144 to 0.236). When utilizing the joint reference data and a two-trait GBLUP model, the genomic prediction accuracy in the Chinese Holsteins improves considerably with respect to the traits with moderate-to-high genetic correlations, whereas the improvement in Nordic Holsteins is small. When compared with the single population analysis, using the joint reference population for genomic prediction in younger animals, results in a 2.3 to 8.1 percent improvement in accuracy. Meanwhile, 10 replications of five-fold cross-validation were also implemented in order to evaluate the performance of joint genomic prediction, thereby resulting in a 1.6 to 5.2 percent increase in accuracy. With respect to joint genomic prediction, the bias was found to be quite low. However, for traits with low genetic correlations, the joint reference data do not improve the prediction accuracy substantially for either population.

Yunnan semi-fine wool sheep are among the most important cultivated sheep breeds in China. However, their population structure, genetic characteristics and traits of interest are poorly studied. In this study, we systematically studied the population characteristics and selection signatures of 40 Yunnan semi-fine wool sheep using SNPs obtained from whole-genome resequencing data. A total of 1393 Gb of clean data were acquired. The mapping rate against the reference genome was 91.23% on average (86.01%–92.26%), and the average sequence depth was 9.51X. After filtering, 28,593,198 SNPs and 4,725,259 indels with high quality were obtained. The heterozygosity rate, inbreeding coefficient and effective population size of the sheep were calculated to preliminarily explore their genetic characteristics. The average heterozygosity rate was 0.264, the average inbreeding coefficient was 0.0099, and the effective population size estimated from the heterozygote excess (HE) was 242.9. Based on the Tajima’s D and integrated haplotype score (iHS) approaches, 562 windows and 11,356 core SNPs showed selection signatures in the Yunnan semi-fine wool sheep population. After genome annotation and gene enrichment analysis, we found traces of early domestication in sensory organs, behavioural activity and the nervous system as well as adaptive changes in reproductive and wool traits under selection in this population. Some selected genes related to litter size, including FSHR, BMPR1B and OXT, were identified as being under selection. Specific missense mutations of the FSHR gene that differed from the reference genome were also identified in the population, and we found some SNP variations that may affect litter size. Our findings provide a theoretical basis for the conservation and utilization of Yunnan semi-fine wool sheep. Furthermore, our results reveal some changes common to sheep after domestication and provide a new opportunity to investigate the genetic variation influencing fecundity within a population evolving under artificial selection.

The high mortality of neonatal piglets due to porcine epidemic diarrhea virus (PEDV) infection has caused huge economic losses to the pig industry. The intestinal microbiota is an important barrier against invaders entering the gastrointestinal route. In this study, we examined the differences between intestinal microbiota of PEDV-infected and healthy piglets. According to the viral copy numbers, 16 crossbred (Landrace-Yorkshire) piglets were divided into three groups: uninfected, low virus load, and high virus load groups. Next, 16S rRNA sequencing was performed to determine the microbiota composition in jejunal content and jejunal mucosal samples from the three groups. PEDV infection induced an imbalance in the microbiota of both jejunal content and jejunal mucosa. The abundance of phylum Firmicutes was higher in uninfected piglets than in infected piglets, whereas the abundance of Proteobacteria was lower in uninfected piglets. Principal coordinate analysis showed significant separation of jejunal microbiota between different groups. Linear discriminant analysis (LDA) effect size (LEfSe) identified Lactobacillus salivarius as a potential biomarker among three groups at the level of species. Then, in vitro, L. salivarius was able to suppress the infection of PEDV to IPEC-J2 cells and decreased the expression of GRP78 (Glucose-regulating protein 78). In addition, we detected the mRNA expression of genes involved in the FAK/PI3K/Akt signaling pathway. When IPEC-J2 cells were treated with L. salivarius before PEDV infection, the mRNA expression levels of ITGA1, ITGA5, ITGB5, FAK, PIK3R1, PIK3CA and AKT1 were significantly higher than those in the control cells (without treatment) at different times post-infection, indicating that L. salivarius may upregulate the FAK/PI3K/Akt signaling pathway in IPEC-J2 cells to resist PEDV infection. In summary, PEDV infection altered microbial communities in both jejunal content and jejunal mucosa. L. salivarius has a protective effect against PEDV infection in IPEC-J2 cells. This study provides a potentially effective strategy to prevent the occurrence and control the spread of PED in the pig production.

Seminal plasma contains a large number of extracellular vesicles (EVs). However, the roles of these EVs and their interactions with sperm are not clear. To identify the important molecules affecting sperm motility in EVs, we analyzed RNA from seminal plasma EVs of boars with different sperm motility using whole-transcriptome sequencing and proteomic analysis. In total, 7 miRNAs, 67 lncRNAs, 126 mRNAs and 76 proteins were differentially expressed between the two groups. We observed that EV-miR-222 can obviously improve sperm motility. In addition, the results suggested that miR-222 was transferred into sperm by the EVs and that miR-222 affected sperm apoptosis by inhibiting the expression of EGFR, BCL2L11, BAX, CYCs, CASP9 and CASP3. The results of electron microscopy also showed that overexpression of miR-222 in EVs could reduce sperm apoptosis. The study of the whole transcriptomes and proteomes of EVs in boar semen revealed some miRNAs may play an important role in these EVs interactions with Duroc sperm, and the findings suggest that the release of miR-222 by semen EVs is an important mechanism by which sperm viability is maintained and sperm apoptosis is reduced. Our studies provide a new insight of miR-222 in EVs regulation for sperm motility and sperm apoptosis.

Identifying epigenetic changes is essential for an in-depth understanding of phenotypic diversity and pigs as the human medical model for anatomizing complex diseases. Abnormal sperm DNA methylation can lead to male infertility, fetal development failure, and affect the phenotypic traits of offspring. However, the whole genome epigenome map in pig sperm is lacking to date. In this study, we profiled methylation levels of cytosine in three commercial pig breeds, Landrace, Duroc, and Large White using whole-genome bisulfite sequencing (WGBS). The results showed that the correlation of methylation levels between Landrace and Large White pigs was higher. We found that 1,040–1,666 breed-specific hypomethylated regions (HMRs) were associated with embryonic developmental and economically complex traits for each breed. By integrating reduced representation bisulfite sequencing (RRBS) public data of pig testis, 1743 conservated HMRs between sperm and testis were defined, which may play a role in spermatogenesis. In addition, we found that the DNA methylation patterns of human and pig sperm showed high similarity by integrating public data from WGBS and chromatin immunoprecipitation sequencing (ChIP-seq) in other mammals, such as human and mouse. We identified 2,733 conserved HMRs between human and pig involved in organ development and brain-related traits, such as NLGN1 (neuroligin 1) containing a conserved-HMR between human and pig. Our results revealed the similarities and diversity of sperm methylation patterns among three commercial pig breeds and between human and pig. These findings are beneficial for elucidating the mechanism of male fertility, and the changes in commercial traits that undergo strong selection.

The pig is an increasingly popular biomedical model, but only a few in depth data exist on its studies in hair follicle (HF) morphogenesis and development. Hence, the objective of this study was to identify the suitability of the pig as an animal model for human hair research. We performed a classification of pig HF morphogenesis stages and hair types. All four different hair types sampled from 17 different body parts in pig were similar to those of human. The Guard_2 sub-type was more similar to type II human scalp hair while Guard_1, Awl, Auchene, and Zigzag were similar to type I scalp hair. Based on morphological observation and marker gene expression of HF at 11 different embryonic days and six postnatal days, we classified pig HF morphogenesis development from E41 to P45 into three main periods – induction (E37–E41), organogenesis (E41–E85), and cytodifferentiation (>E85). Furthermore, we demonstrated that human and pig share high similarities in HF morphogenesis occurrence time (early/mid gestational) and marker gene expression patterns. Our findings will facilitate the study of human follicle morphogenesis and research on complex hair diseases and offer researchers a suitable model for human hair research.

Intramuscular fat (IMF) deposition is an important determinant of pork quality and a complex process facilitated by non-coding ceRNAs. In this study, 52 Berkshire × Anqing Sixwhite crossbred pigs were slaughtered to measure eight carcass and pork quality traits. Whole-transcriptome sequencing analysis was performed using longissimus dorsi samples of six low- and high-IMF samples; 34 ceRNA networks, based on 881, 394, 158 differentially expressed (DE) lncRNAs, miRNAs, and mRNAs, were constructed. Following weighted gene co-expression network analysis between the low and high IMF, only one ceRNA, lncRNA4789/miR-381-3p/FABP3, that showed similar DE trend in longissimus dorsi tissue was retained. Dual-luciferase reporter assays further indicated that FABP3 was a direct, functional target of miR-381-3p, where miR-381-3p overexpression inhibited the mRNA and protein expression of FABP3. In addition, overexpressed lncRNA4789 attenuated the effect of miR-381-3p on FABP3 by sponging miR-381-3p. Cell function verification experiment demonstrated that miR-381-3p suppressed IMF deposition by inhibiting preadipocyte cell differentiation and lipid droplet deposition via the suppression of FABP3 expression in the peroxisome proliferator-activated receptor signalling pathway, whereas lncRNA4789 rescued FABP3 expression by sponging miR-381-3p. Our study may aid in identifying novel molecular markers for its optimization in IMF which is of importance in breeding for improving pork quality.

Compound phases often display properties that are symmetry forbidden relative to their nominal, average crystallographic symmetry, even if extrinsic reasons (defects, strain, or imperfections) are not apparent. Specifically, breaking the macroscopic inversion symmetry of a centrosymmetric phase can dominate or significantly change its observed properties while the detailed mechanisms and magnitudes of the deviations of symmetry breaking are often obscure. Here, we choose piezoelectricity as a tool to investigate macroscopic inversion-symmetry breaking in nominally centrosymmetric materials as a prominent example and measure resonant piezoelectric spectroscopy (RPS) and Resonant Ultrasound Spectroscopy (RUS) in 15 compounds, 18 samples, and 21 different phases, including unpoled ferroelectrics, paraelectrics, relaxors, ferroelastics, incipient ferroelectrics, and isotropic materials with low defect concentrations, i.e., NaCl, fused silica, and CaF_{2}. We exclude the flexoelectric effect as a source of the observed piezoelectricity yet observe piezoelectricity in all nominally cubic phases of these samples. By scaling the RPS intensities with those of RUS, we calibrate the effective piezoelectric coefficients using single-crystal quartz as standard. Using this scaling we determine the effective piezoelectric modulus in nominally nonpiezoelectric phases, finding that the “symmetry-forbidden” piezoelectric effect ranges from ∼1 to 10^{−5} pm/V (∼0.5% to ∼2×10^{−5}% of the piezoelectric coefficient of poled ferroelectric lead zirconate titanate). The values for the unpoled ferroelectric phase are only slightly higher than those in the paraelectric phase. The extremely low coefficients are well below the detection limit of conventional piezoelectric measurements and demonstrate RPS as a convenient and ultrahighly sensitive method to measure piezoelectricity. We suggest that symmetry-breaking piezoelectricity in nominally centrosymmetric materials and disordered, unpoled ferroelectrics is a common phenomenon.

The ultrahigh flexibility and elasticity achieved in freestanding single-crystalline ferroelectric oxide membranes have attracted much attention recently. However, for antiferroelectric oxides, the flexibility limit and fundamental mechanism in their freestanding membranes are still not explored clearly. Here, we successfully fabricate freestanding single-crystalline PbZrO3 membranes by a water-soluble sacrificial layer technique. They exhibit good antiferroelectricity and have a commensurate/incommensurate modulated microstructure. Moreover, they also have good shape recoverability when bending with a small radius of curvature (about 2.4 μm for the thickness of 120 nm), corresponding to a bending strain of 2.5%. They could tolerate a maximum bending strain as large as 3.5%, far beyond their bulk counterpart. Our atomistic simulations reveal that this remarkable flexibility originates from the antiferroelectric-ferroelectric phase transition with the aid of polarization rotation. This study not only suggests the mechanism of antiferroelectric oxides to achieve high flexibility but also paves the way for potential applications in flexible electronics. [ABSTRACT FROM AUTHOR]