Improving multi-population genomic prediction accuracy using multi-trait GBLUP models which incorporate global or local genetic correlation information.

In the application of genomic prediction, a situation often faced is that there are multiple populations in which genomic prediction (GP) need to be conducted. A common way to handle the multi-population GP is simply to combine the multiple populations into a single population. However, since these populations may be subject to different environments, there may exist genotype-environment interactions which may affect the accuracy of genomic prediction. In this study, we demonstrated that multi-trait genomic best linear unbiased prediction (MTGBLUP) can be used for multi-population genomic prediction, whereby the performances of a trait in different populations are regarded as different traits, and thus multi-population prediction is regarded as multi-trait prediction by employing the between-population genetic correlation. Using real datasets, we proved that MTGBLUP outperformed the conventional multi-population model that simply combines different populations together. We further proposed that MTGBLUP can be improved by partitioning the global between-population genetic correlation into local genetic correlations (LGC). We suggested two LGC models, LGC-model-1 and LGC-model-2, which partition the genome into regions with and without significant LGC (LGC-model-1) or regions with and without strong LGC (LGC-model-2). In analysis of real datasets, we demonstrated that the LGC models could increase universally the prediction accuracy and the relative improvement over MTGBLUP reached up to 163.86% (25.64% on average).

Synergistic Modulation of Electronic Interaction to Enhance Intrinsic Activity and Conductivity of Fe-Co-Ni Hydroxide Nanotube for Highly Efficient Oxygen Evolution Electrocatalyst.

The large-scale hydrogen production and application through electrocatalytic water splitting depends crucially on the development of highly efficient, cost-effective electrocatalysts for oxygen evolution reaction (OER), which, however, remains challenging. Here, a new electrocatalyst of trimetallic Fe-Co-Ni hydroxide (denoted as FeCoNiOx Hy ) with a nanotubular structure is developed through an enhanced Kirkendall process under applied potential. The FeCoNiOx Hy features synergistic electronic interaction between Fe, Co, and Ni, which not only notably increases the intrinsic OER activity of FeCoNiOx Hy by facilitating the formation of *OOH intermediate, but also substantially improves the intrinsic conductivity of FeCoNiOx Hy to facilitate charge transfer and activate catalytic sites through electrocatalyst by promoting the formation of abundant Co3+ . Therefore, FeCoNiOx Hy delivers remarkably accelerated OER kinetics and superior apparent activity, indicated by an ultra-low overpotential potential of 257 mV at a high current density of 200 mA cm-2 . This work is of fundamental and practical significance for synergistic catalysis related to advanced energy conversion materials and technologies.

Motivation, injury prevention, and the incidence of sports injuries: A three-wave longitudinal test of self-determination theory.

This study applied self-determination theory (SDT) as a psychological framework to examine whether psychological need support and autonomous motivation are predictive of sports injury preventive behaviors and the incidence of sports injuries. 2042 secondary school students (mean age = 14.33, male = 44.3%) from China completed a survey of the study variables (using established scales) at three time points (baseline, 1-month follow-up, 3-month follow-up). Structural equation modeling examined the core tenets of SDT by testing if the change-scores of the SDT variables (i.e., psychological need support from PE teachers, students' motivation, and students' behavioral adherence) between baseline and 1-month follow-up, were predictive of sports injury incidence assessed at 3-month follow-up. Our model demonstrated acceptable goodness-of-fit parameters (CFI = 0.97, TLI = 0.96, RMSEA = 0.03, and SRMR = 0.05). The relationships between psychological need support, autonomous motivation, and behavioral adherence were both positive and significant. These SDT variables predicted the future incidence of sports injuries following the motivational pathways of SDT. Our study provides evidence of the predictive power of SDT variables on sports injury preventive behaviors and the incidence of sports injuries: Students who perceive their PE teachers as psychological need supportive possess higher autonomous motivation and behavioral adherence towards sports injury prevention, and are also less likely to encounter sports injuries in the future.

Mitogenome-wide association study on body measurement traits of Wenshang Barred chickens.

Mitochondria are best known for synthesizing ATP through the tricarboxylic acid cycle and oxidative phosphorylation. The cytoplasmic mitochondrial DNA (mtDNA) is important for maintaining the function. This study was designed to reveal the effect of mtDNA on chicken body measurement traits (BMTs). A population of 605 Wenshang Barred chickens were recorded BMTs, including body slope length, keel length, chest width, etc. The single-nucleotide polymorphisms (SNPs) of their mitogenomes were detected by PCR amplification and DNA sequencing. Totally 69 mutations in mitogenome were discovered, including 18 in noncoding region and 51 in coding region. By multi-sequence alignment and haplotype construction, the chickens were clustered into eight haplotypes and further three haplogroups. The association between BMTs and mtDNA SNPs, haplotypes and haplogroups were analyzed in the linear model by ASReml, respectively. Among them, the SNP mt11086 T/C in ND3 was found to significantly affect chest dept (p < .05) and was highly conservative by phylogenetic conservation analyses, which reflected the genetic effect on body size and growth of chickens. No significant association between the mitochondrial haplotypes or haplogroups and BMTs was found. The polymorphic site reflecting body size could be put into chicken breeding programs as the genetic marker.

Longitudinal genome-wide association studies of milk production traits in Holstein cattle using whole-genome sequence data imputed from medium-density chip data.

Longitudinal traits, such as milk production traits in dairy cattle, are featured by having phenotypic values at multiple time points, which change dynamically over time. In this study, we first imputed SNP chip (50-100K) data to whole-genome sequence (WGS) data in a Chinese Holstein population consisting of 6,470 cows. The imputation accuracies were 0.88 to 0.97 on average after quality control. We then performed longitudinal GWAS in this population based on a random regression test-day model using the imputed WGS data. The longitudinal GWAS revealed 16, 39, and 75 quantitative trait locus regions associated with milk yield, fat percentage, and protein percentage, respectively. We estimated the 95% confidence intervals (CI) for these quantitative trait locus regions using the logP drop method and identified 581 genes involved in these CI. Further, we focused on the CI that covered or overlapped with only 1 gene or the CI that contained an extremely significant top SNP. Twenty-eight candidate genes were identified in these CI. Most of them have been reported in the literature to be associated with milk production traits, such as DGAT1, HSF1, MGST1, GHR, ABCG2, ADCK5, and CSN1S1. Among the unreported novel genes, some also showed good potential as candidate genes, such as CCSER1, CUX2, SNTB1, RGS7, OSR2, and STK3, and are worth being further investigated. Our study provided not only new insights into the candidate genes for milk production traits, but also a general framework for longitudinal GWAS based on random regression test-day model using WGS data.

MRI-visible enlarged perivascular spaces: imaging marker to predict cognitive impairment in older chronic insomnia patients.

OBJECTIVE: Perivascular spaces (PVS), components of the glymphatic system in the brain, have been known to be important conduits for clearing metabolic waste, and this process mainly increases during sleep. Sleep disruption might result in PVS dysfunction and cognitive impairment. In this study, we aim to explore whether MRI-visible enlarged perivascular spaces (EPVS) could be imaging markers to predict cognitive impairment in chronic insomnia patients. METHOD: We obtained data from 156 patients with chronic insomnia and 79 age-matched healthy individuals. Using T2-weighted MRI images, visible EPVS in various brain regions were measured and analyzed. The associations between EPVS numbers and cerebrospinal fluid (CSF) ß-amyloid 42 (Aß42), total tau (t-tau), and phosphorylated tau (p-tau) level in chronic insomnia patients were evaluated. RESULT: Our results showed that MRI-visible EPVS in the frontal cortex, centrum semiovale, basal ganglia, and hippocampus of chronic insomnia patients with impaired cognition (ICG) significantly increased than that in normal cognition (NCG) patients. The increased MRI-visible EPVS in the frontal cortex, centrum semiovale, and basal ganglia were also associated with the increased CSF Aß42, t-tau, and p-tau level in ICG patients. MRI-visible EPVS in the basal ganglia and centrum semiovale had high sensitivity and specificity in distinguishing ICG chronic insomnia patients from those with NCG. CONCLUSION: Our study indicated that MRI-visible EPVS in the basal ganglia and centrum semiovale might be valuable imaging markers to predict cognitive impairment in chronic insomnia patients. It will be meaningful to discern those cognitive decline patients in preclinical stage and take some measures to prevent disease progression. KEY POINTS: • Increased MRI-visible EPVS were associated with the increased CSF Aß42, t-tau, and p-tau level in older chronic insomnia patients with impaired cognition.

Assessment of the performance of different imputation methods for low-coverage sequencing in Holstein cattle.

Low-coverage sequencing (LCS) followed by imputation has been proposed as a cost-effective genotyping approach for obtaining genotypes of whole-genome variants. Imputation performance is essential for the effectiveness of this approach. Several imputation methods have been proposed and successfully applied in genomic studies in human and other species. However, there are few reports on the performance of these methods in livestock. Here, we evaluated a variety of imputation methods, including Beagle v4.1, GeneImp v1.3, GLIMPSE v1.1.0, QUILT v1.0.0, Reveel, and STITCH v1.6.5, with varying sequencing depth, sample size, and reference panel size using LCS data of Holstein cattle. We found that all of these methods, except Reveel, performed well in most cases with an imputation accuracy over 0.9; on the whole, GLIMPSE, QUILT, and STITCH performed better than the other methods. For species with no reference panel available, STITCH followed by Beagle would be an optimal strategy, whereas for species with reference panel available, QUILT would be the method of choice. Overall, this study illustrated the promising potential of LCS for genomic analysis in livestock.

miR-34a regulates adipogenesis in porcine intramuscular adipocytes by targeting ACSL4.

BACKGROUND: Intramuscular fat (IMF) content is an important factor in porcine meat quality. Previously, we showed that miR-34a was less abundant in liver tissue from pigs with higher backfat thickness, compared to pigs with lower backfat thickness. The purpose of this present study was to explore the role of miR-34a in adipogenesis. RESULT: Bioinformatics analysis identified Acyl-CoA synthetase long chain family member 4 (ACSL4) as a putative target of miR-34a. Using a luciferase reporter assay, we verified that miR-34a binds the ACSL4 mRNA at the 3'UTR. To examine the role of the miR-34a-ACSL4 interaction in IMF deposition in the pig, mRNA and protein expression of the ACSL4 gene was measured in primary intramuscular preadipocytes transfected with miR-34a mimic and inhibitor. Our results showed that ACSL4 is expressed throughout the entire differentiation process in pig preadipocytes, similar to the lipogenesis-associated genes PPARγ and aP2. Transfection with miR-34a mimic reduced lipid droplet formation during adipogenesis, while miR-34a inhibitor increased lipid droplet accumulation. Transfection with miR-34a mimic also reduced the mRNA and protein expression of ACSL4 and lipogenesis genes, including PPARγ, aP2, and SREBP-1C, but increased the expression of steatolysis genes such as ATGL and Sirt1. In contrast, the miR-34a inhibitor had the opposite effect on gene expression. Further, knockdown of ACSL4 decreased lipid droplet accumulation. CONCLUSIONS: Our results support the hypothesis that miR-34a regulates intramuscular fat deposition in porcine adipocytes by targeting ACSL4.

Long-read sequencing identified intronic repeat expansions in SAMD12 from Chinese pedigrees affected with familial cortical myoclonic tremor with epilepsy.

BACKGROUND: The locus for familial cortical myoclonic tremor with epilepsy (FCMTE) has long been mapped to 8q24 in linkage studies, but the causative mutations remain unclear. Recently, expansions of intronic TTTCA and TTTTA repeat motifs within SAMD12 were found to be involved in the pathogenesis of FCMTE in Japanese pedigrees. We aim to identify the causative mutations of FCMTE in Chinese pedigrees. METHODS: We performed genetic linkage analysis by microsatellite markers in a five-generation Chinese pedigree with 55 members. We also used array-comparative genomic hybridisation (CGH) and next-generation sequencing (NGS) technologies (whole-exome sequencing, capture region deep sequencing and whole-genome sequencing) to identify the causative mutations in the disease locus. Recently, we used low-coverage (~10×) long-read genome sequencing (LRS) on the PacBio Sequel and Oxford Nanopore platforms to identify the causative mutations, and used repeat-primed PCR for validation of the repeat expansions. RESULTS: Linkage analysis mapped the disease locus to 8q23.3-24.23. Array-CGH and NGS failed to identify causative mutations in this locus. LRS identified the intronic TTTCA and TTTTA repeat expansions in SAMD12 as the causative mutations, thus corroborating the recently published results in Japanese pedigrees. CONCLUSIONS: We identified the pentanucleotide repeat expansion in SAMD12 as the causative mutation in Chinese FCMTE pedigrees. Our study also suggested that LRS is an effective tool for molecular diagnosis of genetic disorders, especially for neurological diseases that cannot be positively diagnosed by conventional clinical microarray and NGS technologies.

Hollow Cobalt Phosphide with N-Doped Carbon Skeleton as Bifunctional Electrocatalyst for Overall Water Splitting.

The development of cost-effective, high-performance, and robust bifunctional electrocatalysts for overall water splitting remains highly desirable yet quite challenging. Here, by selecting appreciate precursors of dopamine and a Co-containing metal-organic framework of ZIF-67, we subtly couple their reaction processes to develop a facile approach for the synthesis of a hollow CoP nanostructure with N-doped carbon skeleton (H-CoP@NC). Benefiting from the highly porous nanostructure and conductive carbon skeleton, H-CoP@NC is capable of working as highly active and durable bifunctional electrocatalyst for both hydrogen and oxygen evolution reaction. When further used as the electrocatalyst for overall water splitting, H-CoP@NC delivers excellent activity (cell voltage of 1.72 V at a current density of 10 mA cm-2), close to that of the noble-metal-based benchmark catalyst couple of Pt/C||RuO2. Our work thus provides new insights into the development of transitional metal phosphides based hollow hybrid nanostructures, particularly those with multiple functionalities in sustainable energy conversion technologies and systems.

Influence of Uniaxial Stress on the Shear-Wave Spectrum Propagating in Steel Members.

Structural health monitoring technologies have provided extensive methods to sense the stress of steel structures. However, monitored stress is a relative value rather than an absolute value in the structure's current state. Among all the stress measurement methods, ultrasonic methods have shown great promise. The shear-wave amplitude spectrum and phase spectrum contain stress information along the propagation path. In this study, the influence of uniaxial stress on the amplitude and phase spectra of a shear wave propagating in steel members was investigated. Furthermore, the shear-wave amplitude spectrum and phase spectrum were compared in terms of characteristic frequency (CF) collection, parametric calibration, and absolute stress measurement principles. Specifically, the theoretical expressions of the shear-wave amplitude and phase spectra were derived. Three steel members were used to investigate the effect of the uniaxial stress on the shear-wave amplitude and phase spectra. CFs were extracted and used to calibrate the parameters in the stress measurement formula. A linear relationship was established between the inverse of the CF and its corresponding stress value. The test results show that both the shear-wave amplitude and phase spectra can be used to evaluate uniaxial stress in structural steel members.

Automated Modal Analysis for Tracking Structural Change during Construction and Operation Phases.

The automated modal analysis (AMA) technique has attracted significant interest over the last few years, because it can track variations in modal parameters and has the potential to detect structural changes. In this paper, an improved density-based spatial clustering of applications with noise (DBSCAN) is introduced to clean the abnormal poles in a stabilization diagram. Moreover, the optimal system model order is also discussed to obtain more stable poles. A numerical simulation and a full-scale experiment of an arch bridge are carried out to validate the effectiveness of the proposed algorithm. Subsequently, the continuous dynamic monitoring system of the bridge and the proposed algorithm are implemented to track the structural changes during the construction phase. Finally, the artificial neural network (ANN) is used to remove the temperature effect on modal frequencies so that a health index can be constructed under operational conditions.

Lateral Flow Test for Visual Detection of Multiple MicroRNAs.

The authors describe a rapid and low-cost approach for multiplex microRNA(miRNA) assay on lateral flow nucleic acid biosensor (LFNAB). The principle of assay is based on sandwich-type nucleic acid hybridization reactions to produce gold nanoparticle (GNP)-attached complexes (ssDNA-microRNA-ssDNA/GNPs), which are captured and visualized on the test zone of LFNAB. By designing three different test zones on LFNAB, simultaneous detection of microRNA-21, microRNA-155 and microRNA-210 was achieved with an adding-measuring model by using GNP as visual tag. The method was challenged by testing the microRNAs in spiked serum samples with satisfied results. In our perception, the test is a particularly valuable tool for clinical application and biomedical diagnosis, particularly in limited resource settings.

Stress Prediction for Distributed Structural Health Monitoring Using Existing Measurements and Pattern Recognition.

The stress in structural steel members is the most useful and directly measurable physical quantity to evaluate the structural safety in structural health monitoring, which is also an important index to evaluate the stress distribution and force condition of structures during structural construction and service phases. Thus, it is common to set stress as a measure in steel structural monitoring. Considering the economy and the importance of the structural members, there are only a limited number of sensors that can be placed, which means that it is impossible to obtain the stresses of all members directly using sensors. This study aims to develop a stress response prediction method for locations where there are insufficent sensors, using measurements from a limited number of sensors and pattern recognition. The detailed improved aspects are: (1) a distributed computing process is proposed, where the same pattern is recognized by several subsets of measurements; and (2) the pattern recognition using the subset of measurements is carried out by considering the optimal number of sensors and number of fusion patterns. The validity and feasibility of the proposed method are verified using two examples: the finite-element simulation of a single-layer shell-like steel structure, and the structural health monitoring of the space steel roof of Shenzhen Bay Stadium; for the latter, the anti-noise performance of this method is verified by the stress measurements from a real-world project.

Structural Health Monitoring of a Prestressed Concrete Bridge Based on Statistical Pattern Recognition of Continuous Dynamic Measurements Over 14 Years.

This work describes a vibration-based structural health monitoring of a prestressed-concrete box girder bridge on the A100 Highway in Berlin by applying statistical pattern recognition technique to a huge amount of data continuously collected by an integrated monitoring system during the period from 2000 to 2013. Firstly, the general condition and potential damage of the bridge is described. Then, the dynamic properties are extracted from 20 velocity sensors. Environmental variability captured by five thermal transducers and traffic intensity approximately estimated by strain measurements are also reported. Nonlinear influences of temperature on natural frequencies are observed. Subsequently, the measurements during the first year are used to build a baseline health index. The multiple linear regression (MLR) method is used to characterize the nonlinear relationship between natural frequencies and temperatures. The Euclidean distance of the residual errors is calculated to build a statistical health index. Finally, the indices extracted from the following years gradually deviate; which may indicate structural deterioration due to loss of prestress in the prestressed tendons.

In Vitro Isothermal Nucleic Acid Amplification Assisted Surface-Enhanced Raman Spectroscopic for Ultrasensitive Detection of Vibrio parahaemolyticus.

Detection of pathogenic microorganisms is of great importance for public health and food safety. Traditional protocols can hardly meet the continuously increasing demand in sensitivity and specificity of pathogen detections. In this study, we adopted Vibrio parahaemolyticus (V. parahaemolyticus, Vp) as the model analyte, and developed an antibody-Vp-aptamer heterosandwich-based surface-enhanced Raman scattering (SERS) method in conjunction with in vitro isothermal amplification for sensitive detection of V. parahaemolyticus. The rolling circular amplification (RCA) products provided enormous sites for assembling the Au@Ag nanoparticles and forming excess "hot-spot" sites for Raman measurement. By using this enhanced Raman signal strategy in the detection, a limit of detection (LOD) as low as 1 cfu/mL was successfully achieved for ultrasensitive detection of V. parahaemolyticus. In addition, we have applied this method to artificially contaminated food samples. The detection data indicated that this method is able to determine the concentrations of V. parahaemolyticus in the spiked food samples with satisfactory sensitivity and specificity and, thus, this developed ultrasensitive SERS scheme is well suited for the urgent need in pathogen detection and demonstrated great potential in food safety, environment monitoring, and a clinical setting.

Investigation of Binding Behavior between Drug Molecule 5-Fluoracil and M4 L4 -Type Tetrahedral Cages: Selectivity, Capture, and Release.

Two analogous M4 L4 -type tetrahedral cages (smaller: MOC-19; larger: MOC-22) were synthesized and investigated for their interactions with the anticancer drug 5-fluoracil (5-FU) by NMR spectroscopy, high-resolution electrospray-ionization mass spectrometry (HR-ESI-MS), and molecular simulation. The cage's size and window are of importance for the host-guest binding, and consequently the smaller MOC-19 with a more suitable size of cavity window was found to have much stronger hydrogen-bond interactions with 5-FU. The porous nanoparticles of MOC-19 exhibited outstanding behavior for the controlled release of 5-FU in a simulated human body with liquid phosphate-buffered saline solution.

Nanoreactor Based on Macroporous Single Crystals of Metal-Organic Framework.

A sacrificial template strategy is developed for the synthesis of yolk-shell Au@ZIF-8 nanoreactor. The Au@ZIF-8 nanoreactor possesses single-crystalline metal-organic framework (MOF) shell with intrinsic monodisperse micropores and introduced macropores. In each of the macropores, one Au NP is encapsulated to form a nanoreactor unit. The quantity of the reactor units in the MOF shell can be readily regulated. Such structure features of the Au@ZIF-8 nanoreactor facilitate the size selectivity of reactants, the accessibility of Au nanoparticles to reactants, and the mass transfer of reactants and products. As a result, the Au@ZIF-8 nanoreactor delivers excellent size selectivity, enhanced conversion, and good cycling stability when used to catalyze the aerobic oxidation of alcohols with different molecular size.

Colorimetric Integrated PCR Protocol for Rapid Detection of Vibrio parahaemolyticus.

Rapid detection of pathogens is of great significance for food safety and disease diagnosis. A new colorimetric method for rapid and easy detection of Vibrio parahaemolyticus (V. parahaemolyticus or Vp) has been developed in this research. A specific sequence was designed and integrated with the forward primer for molecular detection of Vp. This specific sequence was tested and treated as the horseradish peroxidase (HRP)-mimicking DNAzyme and could be amplified during the polymerase chain reaction (PCR) process. The products of PCR including the sequence of HRP-mimicking DNAzyme could produce the distinguished color in the presence of catalysis substrates. The optical signal of the catalysis reaction, which is in a linear relationship with the initial template of Vp, could be determined with the naked eye or measured with Ultraviolet-visible (UV-vis) for qualitative and quantitative detections, respectively. Based on the optical signal intensity, rapid and easy detection of Vp was successfully achieved with satisfied sensitivity and specificity. Furthermore, the detection of tdh, trh, tlh and toxR virulence genes of two Vp species (Vp 33847 and Vp 17802) were all performed successfully with this developed colorimetric integrated PCR protocol, which demonstrated potential applicability for the rapid detection of other bacteria.

Relationship between procalcitonin serum levels and functional outcome in stroke patients.

To determine whether serum procalcitonin (PCT) levels at admission were associated with short-term functional outcome after acute ischemic stroke (AIS) in a cohort Chinese sample. We prospectively studied 378 patients with AIS who were admitted within 24 h after the onset of symptoms. PCT and NIH stroke scale (NIHSS) were measured at the time of admission. Short-term functional outcome was measured by modified Rankin scale (mRS) 90 days after admission. The results indicated that the serum PCT levels were significantly higher in AIS patients as compared to normal controls (P < 0.0001). In the 114 patients with an unfavorable functional outcome, serum PCT levels were higher compared with those in patients with a favorable outcome (2.40 (IQR, 1.10-3.69) ng/mL and 0.42 (IQR, 0.10-1.05) ng/mL, respectively, P < 0.001). PCT was an independent prognostic marker of functional outcome [odds ratio (OR) 3.45 (2.29-4.77), adjusted for the NIHSS and other possible confounders] in patients with ischemic stroke, added significant additional predictive value to the clinical NIHSS score. In receiver operating characteristic curve analysis, the prognostic accuracy of PCT was higher compared to Hs-CRP and NIHSS score. PCT is an independent predictor of short-term functional outcome after ischemic stroke in Chinese sample even after correcting for possible confounding factors.