Development of a novel animal model of rotator cuff tear arthropathy replicating clinical features of progressive osteoarthritis with subchondral bone collapse

OBJECTIVE

To establish an animal model of modified cuff tear arthropathy (mCTA) in order to better replicate the pathophysiology associated with rotator cuff tear-induced humeral head collapse.

DESIGN

mCTA was induced by transection of the rotator cuff, the long head of the biceps brachii (LHB), and superior half of the joint capsule in the right shoulder of 12-week-old rats; the left shoulder underwent sham surgery. The severity of CTA was quantitated using the Murine Shoulder Arthritis Score (MSAS). The trabecular bone of the humeral head and metaphysis was analyzed using bone histomorphometry. The expression of proinflammatory cytokines and catabolic enzymes was evaluated immunohistochemically.

RESULTS

In the mCTA model, the MSAS increased starting from 2 weeks after induction, and there was notable subchondral bone collapse with fibrous cells at 4 weeks. The mCTA cartilage exhibited positive staining for TNF-α, IL-1β/6, MMP-3/13, and ADAMTS5. The trabecular bone volume was reduced not only in the subchondral bone but also in the metaphysis of the humeri, and bone resorption was enhanced in these areas. In the collapsed subchondral bone, both bone formation and resorption were increased. The fibrous cells showed expression of TNF-α, IL-6, and MMP-13, along with specific markers of mesenchymal stem cells. Furthermore, the fibrous cells showed osteoblastic characteristics (RUNX2-positive) and expressed RANKL.

CONCLUSIONS

The LHB and the capsuloligamentous complex are critical stabilizers of the glenohumeral joint, serving to prevent the advancement of CTA following massive rotator cuff tears. Fibrous cells appear to play a role in the humeral head bone resorption.

Nonparallel genome changes within subpopulations over time contributed to genetic diversity within the US Holstein population

Maintaining genetic variation in a population is important for long-term genetic gain. The existence of subpopulations within a breed helps maintain genetic variation and diversity. The 20,990 genotyped animals, representing the breeding animals in the year 2014, were identified as the sires of animals born after 2010 with at least 25 progenies, and females measured for type traits within the last 2 yr of data. K-means clustering with 5 clusters (C1, C2, C3, C4, and C5) was applied to the genomic relationship matrix based on 58,990 SNP markers to stratify the selected candidates into subpopulations. The general higher inbreeding resulting from within-cluster mating than across-cluster mating suggests the successful stratification into genetically different groups. The largest cluster (C4) contained animals that were less related to each animal within and across clusters. The average fixation index was 0.03, indicating that the populations were differentiated, and allele differences across the subpopulations were not due to drift alone. Starting with the selected candidates within each cluster, a family unit was identified by tracing back through the pedigree, identifying the genotyped ancestors, and assigning them to a pseudogeneration. Each of the 5 families (F1, F2, F3, F4, and F5) was traced back for 10 generations, allowing for changes in frequency of individual SNPs over time to be observed, which we call allele frequencies change. Alternative procedures were used to identify SNPs changing in a parallel or nonparallel way across families. For example, markers that have changed the most in the whole population, markers that have changed differently across families, and genes previously identified as those that have changed in allele frequency. The genomic trajectory taken by each family involves selective sweeps, polygenic changes, hitchhiking, and epistasis. The replicate frequency spectrum was used to measure the similarity of change across families and showed that populations have changed differently. The proportion of markers that reversed direction in allele frequency change varied from 0.00 to 0.02 if the rate of change was greater than 0.02 per generation, or from 0.14 to 0.24 if the rate of change was greater than 0.005 per generation within each family. Cluster-specific SNP effects for stature were estimated using only females and applied to obtain indirect genomic predictions for males. Reranking occurs depending on SNP effects used. Additive genetic correlations between clusters show possible differences in populations. Further research is required to determine how this knowledge can be applied to maintain diversity and optimize selection decisions in the future.

Impact of the Comprehensive Awareness Modification of Mouth, Chewing and Meal (CAMCAM) Program on the Attitude and Behavior Towards Oral Health and Eating Habits as Well as the Condition of Oral Frailty: A Pilot Study

OBJECTIVES

Preserving sufficient oral function and maintaining aadequate nutrition are essential for preventing physical frailty and the following long-term care. We recently developed the 6-month Comprehensive Awareness Modification of Mouth, Chewing And Meal (CAMCAM) program, in which participants gather monthly to learn about oral health and nutrition while eating a textured lunch together. This study examined whether the CAMCAM program could improve attitude and behavior towards oral health, mastication, and diet as well as ameliorate oral frailty in community-dwelling older adults.

DESIGN

Single-arm pre-post comparison study.

SETTING AND PARTICIPANTS

A total of 271 community-dwelling adults (72.3 ± 5.7 years of age; 159 women [58.7%]) in 4 Japanese municipalities were recruited, of which 249 participants (92%) were assessed at the final evaluation.

INTERVENTION

Participants gathered once a month at community centers to learn about oral health and nutrition while eating a "munchy" textured lunch containing proper nutrition.

MEASUREMENTS

Oral frailty, frailty, and eating behavior were evaluated with the Oral Frailty Index-8 (OFI-8), Kihon checklist (KCL), and CAMCAM checklist, respectively. Participants were divided into Oral frailty (OF) and Robust groups according to OFI-8 scores. The differences in KCL and CAMCAM checklist results between the OF and Robust groups were statistically tested along with changes in scores after the program.

RESULTS

KCL and CAMCAM checklist scores were significantly lower in the OF group at the initial assessment. OFI-8 and KCL findings were significantly improved in the OF group after completing the program (all P <0.05). Regarding the CAMCAM checklist, awareness of chewing improved significantly in the Robust group (P=0.009), with a similar tendency in the OF group (P=0.080).

CONCLUSION

The findings of this pilot study suggest that the CAMCAM program may improve both oral and systemic frailty in addition to attitudes towards chewing, oral health, and meals, especially in individuals with oral frailty. The CAMCAM program merits expansion as a community-based frailty prevention program.

Anxiety relaxation during MRI with a patient-friendly audiovisual system

INTRODUCTION

Many patients experience anxiety, not limited to claustrophobia, before magnetic resonance imaging (MRI) examination. We performed a non-randomized controlled trial to evaluate whether a patient-friendly audiovisual (AV) system in the MR scanner room reduces patient anxiety.

METHODS

We randomly selected 61 participants from outpatients who required brain MRI examination. Patients were informed that they could choose to undergo an MRI examination with a patient-friendly AV system (Ambient Experience, Philips Healthcare, Best, The Netherlands) or the standard system. To complete the MRI examination without affecting clinical practice, all patients who preferred the patient-friendly AV system were assigned to the preferring AV group. Patients who indicated that either system was acceptable were randomly assigned to the no preference but allocated AV group or control (using the standard system) groups. In both groups, state anxiety using the State-Trait Anxiety Inventory (STAI) was assessed before and after the MRI examination (A-State-before and A-State-after MRI, respectively). The changes in A-State-before and A-State-after MRI were categorized as follows: relieved high-state anxiety, no change in high-state anxiety, stable easiness, and intensified anxiety.

RESULTS

Among the 61 included patients, 19 were assigned to the preferring AV group, 20 to the no preference but allocated AV group, and 22 to the control group. There were no significant differences between the group. However, in patients with high-state anxiety before MRI, the preferring AV group and the no preference but allocated AV group, which used the patient-friendly AV system, relieved high-state anxiety by 63.6% (7 of 11 patients) and 81.8% (9 of 11 patients), respectively. In contrast, the control group using the standard system relieved high-level anxiety by only 42.9% (three out of seven patients).

CONCLUSION

The patient-friendly AV system may reduce anxiety in patients undergoing MRI examinations.

IMPLICATIONS FOR PRACTICE

The patient-friendly AV system may reduce anxiety in patients undergoing MRI examination by providing a more patient-centered MRI examination environment. These findings may help ameliorate negative perceptions associated with MRI examination.

Reducing computational cost of large-scale genomic evaluation by using indirect genomic prediction

Over half a million Holsteins are being genotyped annually in the United States. The computational cost of including all genotypes in single-step genomic (ssG)BLUP is high, although it is feasible to conduct large-scale genomic prediction using an efficient algorithm such as APY (algorithm for proven and young). An effective method to further reduce the computing cost could be the use of indirect genomic predictions (IGP) for genotyped animals when they have neither progeny nor phenotypes. These young genotyped animals have no effect on the other genotyped animals and could have their genomic prediction done indirectly. The main objective of this study was to calculate IGP for various groups of genotyped animals and investigate the reduction in computing time as well as bias and accuracy of the IGP. We compared IGP with genomic (G)EBV for 18 linear type traits in US Holsteins, including 2.3 million (M) genotyped animals. The full data set consisted of 10.9M records for 18 linear type traits up to 2018 calving, 13.6M animals in the pedigree, and 2.3M animals genotyped for 79K SNP. For IGP, ssGBLUP included all genotyped animals except those with neither progeny nor phenotypes by year from 2014 to 2018 (i.e., the target animals). The SNP marker effects were computed based on GEBV for genotyped animals that had progeny, or phenotypes, or both. Further, IGP were calculated for target genotyped animals in each year group. For all genotyped animal groups from 2014 to 2018, the coefficients of determination (R²) of a linear regression of GEBV on IGP were 0.960 for males and 0.954 for females for 18 traits on average. To reduce computing costs, the SNP marker effects were calculated based on GEBV from randomly selected genotyped animals from 15K to 60K. By randomly selecting a small number of genotyped animals, the computing time was dramatically reduced. As more genotyped animals were randomly selected to calculate SNP effects, R² was higher (more accurate) and the regression coefficient was lower (more inflated IGP). In a practical genomic evaluation in US Holsteins, to get sufficient contributions from GEBV, 25K to 35K is a rational number of genotyped animals that can be randomly selected to compute SNP effects and obtain accurate and unbiased IGP. Considering the computing time and both unbiasedness and accuracy of IGP, genomic evaluation can be conducted separately in GEBV for genotyped animals with phenotypes or progeny and in IGP for young genotyped animals. This can be a practical solution when conducting a large-scale genomic evaluation and would enable more frequent evaluation at lower cost, especially when many genotyped animals have neither phenotypes nor progeny.

Genomic prediction of milk-production traits and somatic cell score using single-step genomic best linear unbiased predictor with random regression test-day model in Thai dairy cattle

Cow genotypes are expected to improve the accuracy of genomic estimated breeding values (GEBV) for young bulls in relatively small populations such as Thai Holstein-Friesian crossbred dairy cattle in Thailand. The objective of this study was to investigate the effect of cow genotypes on the predictive ability and individual accuracies of GEBV for young dairy bulls in Thailand. Test-day data included milk yield (n = 170,666), milk component traits (fat yield, protein yield, total solids yield, fat percentage, protein percentage, and total solids percentage; n = 160,526), and somatic cell score (n = 82,378) from 23,201, 82,378, and 13,737 (for milk yield, milk component traits, and SCS, respectively) cows calving between 1993 and 2017, respectively. Pedigree information included 51,128; 48,834; and 32,743 animals for milk yield, milk component traits, and somatic cell score, respectively. Additionally, 876, 868, and 632 pedigreed animals (for milk yield, milk component traits, and SCS, respectively) were genotyped (152 bulls and 724 cows), respectively, using Illumina Bovine SNP50 BeadChip. We cut off the data in the last 6 yr, and the validation animals were defined as genotyped bulls with no daughters in the truncated set. We calculated GEBV using a single-step random regression test-day model (SS-RR-TDM), in comparison with estimated breed value (EBV) based on the pedigree-based model used as the official method in Thailand (RR-TDM). Individual accuracies of GEBV were obtained by inverting the coefficient matrix of the mixed model equations, whereas validation accuracies were measured by the Pearson correlation between deregressed EBV from the full data set and (G)EBV predicted with the reduced data set. When only bull genotypes were used, on average, SS-RR-TDM increased individual accuracies by 0.22 and validation accuracies by 0.07, compared with RR-TDM. With cow genotypes, the additional increase was 0.02 for individual accuracies and 0.06 for validation accuracies. The inflation of GEBV tended to be reduced using cow genotypes. Genomic evaluation by SS-RR-TDM is feasible to select young bulls for the longitudinal traits in Thai dairy cattle, and the accuracy of selection is expected to be increased with more genotypes. Genomic selection using the SS-RR-TDM should be implemented in the routine genetic evaluation of the Thai dairy cattle population. The genetic evaluation should consider including genotypes of both sires and cows.

Genomic predictions for yield traits in US Holsteins with unknown parent groups

The objective of this study was to assess the reliability and bias of estimated breeding values (EBV) from traditional BLUP with unknown parent groups (UPG), genomic EBV (GEBV) from single-step genomic BLUP (ssGBLUP) with UPG for the pedigree relationship matrix (A) only (SS_UPG), and GEBV from ssGBLUP with UPG for both A and the relationship matrix among genotyped animals (A₂₂; SS_UPG2) using 6 large phenotype-pedigree truncated Holstein data sets. The complete data included 80 million records for milk, fat, and protein yields from 31 million cows recorded since 1980. Phenotype-pedigree truncation scenarios included truncation of phenotypes for cows recorded before 1990 and 2000 combined with truncation of pedigree information after 2 or 3 ancestral generations. A total of 861,525 genotyped bulls with progeny and cows with phenotypic records were used in the analyses. Reliability and bias (inflation/deflation) of GEBV were obtained for 2,710 bulls based on deregressed proofs, and on 381,779 cows born after 2014 based on predictivity (adjusted cow phenotypes). The BLUP reliabilities for young bulls varied from 0.29 to 0.30 across traits and were unaffected by data truncation and number of generations in the pedigree. Reliabilities ranged from 0.54 to 0.69 for SS_UPG and were slightly affected by phenotype-pedigree truncation. Reliabilities ranged from 0.69 to 0.73 for SS_UPG2 and were unaffected by phenotype-pedigree truncation. The regression coefficient of bull deregressed proofs on (G)EBV (i.e., GEBV and EBV) ranged from 0.86 to 0.90 for BLUP, from 0.77 to 0.94 for SS_UPG, and was 1.00 ± 0.03 for SS_UPG2. Cow predictivity ranged from 0.22 to 0.28 for BLUP, 0.48 to 0.51 for SS_UPG, and 0.51 to 0.54 for SS_UPG2. The highest cow predictivities for BLUP were obtained with the most extreme truncation, whereas for SS_UPG2, cow predictivities were also unaffected by phenotype-pedigree truncations. The regression coefficient of cow predictivities on (G)EBV was 1.02 ± 0.02 for SS_UPG2 with the most extreme truncation, which indicated the least biased predictions. Computations with the complete data set took 17 h with BLUP, 58 h with SS_UPG, and 23 h with SS_UPG2. The same computations with the most extreme phenotype-pedigree truncation took 7, 36, and 15 h, respectively. The SS_UPG2 converged in fewer rounds than BLUP, whereas SS_UPG took up to twice as many rounds. Thus, the ssGBLUP with UPG assigned to both A and A₂₂ provided accurate and unbiased evaluations, regardless of phenotype-pedigree truncation scenario. Old phenotypes (before 2000 in this data set) did not affect the reliability of predictions for young selection candidates, especially in SS_UPG2.

Controlling bias in genomic breeding values for young genotyped bulls

The objectives of this study were to investigate bias in genomic predictions for dairy cattle and to find a practical approach to reduce the bias. The simulated data included phenotypes, pedigrees, and genotypes, mimicking a dairy cattle population (i.e., cows with phenotypes and bulls with no phenotypes) and assuming selection by breeding values or no selection. With the simulated data, genomic estimated breeding values (GEBV) were calculated with a single-step genomic BLUP and compared with true breeding values. Phenotypes and genotypes were simulated in 10 generations and in the last 4 generations, respectively. Phenotypes in the last generation were removed to predict breeding values for those individuals using only genomic and pedigree information. Complete pedigrees and incomplete pedigrees with 50% missing dams were created to construct the pedigree-based relationship matrix with and without inbreeding. With missing dams, unknown parent groups (UPG) were assigned in relationship matrices. Regression coefficients (b₁) and coefficients of determination (R²) of true breeding values on (G)EBV were calculated to investigate inflation and accuracy in GEBV for genotyped animals, respectively. In addition to the simulation study, 18 linear type traits of US Holsteins were examined. For the 18 type traits, b₁ and R² of GEBV with full data sets on GEBV with partial data sets for young genotyped bulls were calculated. The results from the simulation study indicated inflation in GEBV for genotyped males that were evaluated with only pedigree and genomic information under BLUP selection. However, when UPG for only pedigree-based relationships were included, the inflation was reduced, accuracy was highest, and genetic trends had no bias. For the linear type traits, when UPG for only pedigree-based relationships were included, the results were generally in agreement with those from the simulation study, implying less bias in genetic trends. However, when including no UPG, UPG in pedigree-based relationships, or UPG in genomic relationships, inflation and accuracy in GEBV were similar. The results from the simulation and type traits suggest that UPG must be defined accurately to be estimable and inbreeding should be included in pedigree-based relationships. In dairy cattle, known pedigree information with inbreeding and estimable UPG plays an important role in improving compatibility between pedigree-based and genomic relationship matrices, resulting in more reliable genomic predictions.

Single-step genome-wide association for longitudinal traits of Canadian Ayrshire, Holstein, and Jersey dairy cattle

Estimating single nucleotide polymorphism (SNP) effects over time is essential to identify and validate candidate genes (or quantitative trait loci) associated with time-dependent variation of economically important traits and to better understand the underlying mechanisms of lactation biology. Therefore, in this study, we aimed to estimate time-dependent effects of SNP and identifying candidate genes associated with milk (MY), fat (FY), and protein (PY) yields, and somatic cell score (SCS) in the first 3 lactations of Canadian Ayrshire, Holstein, and Jersey breeds, as well as suggest their potential pattern of phenotypic effect over time. Random regression coefficients for the additive direct genetic effect were estimated for each animal using single-step genomic BLUP, based on 2 random regression models: one considering MY, FY, and PY in the first 3 lactations and the other considering SCS in the first 3 lactations. Thereafter, SNP solutions were obtained for random regression coefficients, which were used to estimate the SNP effects over time (from 5 to 305 d in lactation). The top 1% of SNP that showed a high magnitude of SNP effect in at least 1 d in lactation were selected as relevant SNP for further analyses of candidate genes, and clustered according to the trajectory of their SNP effects over time. The majority of SNP selected for MY, FY, and PY increased the magnitude of their effects over time, for all breeds. In contrast, for SCS, most selected SNP decreased the magnitude of their effects over time, especially for the Holstein and Jersey breeds. In general, we identified a different set of candidate genes for each breed, and similar genes were found across different lactations for the same trait in the same breed. For some of the candidate genes, the suggested pattern of phenotypic effect changed among lactations. Among the lactations, candidate genes (and their suggested phenotypic effect over time) identified for the second and third lactations were more similar to each other than for the first lactation. Well-known candidate genes with major effects on milk production traits presented different suggested patterns of phenotypic effect across breeds, traits, and lactations in which they were identified. The candidate genes identified in this study can be used as target genes in studies of gene expression.

International bull evaluations by genomic BLUP with a prediction population

The purpose of this study was to determine whether multi-country genomic evaluation can be accomplished by multiple-trait genomic best linear unbiased predictor (GBLUP) without sharing genotypes of important animals. Phenotypes and genotypes with 40k SNP were simulated for 25,000 animals, each with 4 traits assuming the same genetic variance and 0.8 genetic correlations. The population was split into 4 subpopulations corresponding to 4 countries, one for each trait. Additionally, a prediction population was created from genotyped animals that were not present in the individual countries but were related to each country's population. Genomic estimated breeding values were computed for each country and subsequently converted to SNP effects. Phenotypes were reconstructed for the prediction population based on the SNP effects of a country and the prediction animals' genotypes. The prediction population was used as the basis for the international evaluation, enabling bull comparisons without sharing genotypes and only sharing SNP effects. The computations were such that SNP effects computed within-country or in the prediction population were the same. Genomic estimated breeding values were calculated by single-trait GBLUP for within-country and multiple-trait GBLUP for multi-country predictions. The true accuracy for the prediction population with reconstructed phenotypes was at most 0.02 less than the accuracy with the original data. The differences increased when countries were assumed unequally sized. However, accuracies by multiple-trait GBLUP with the prediction population were always greater than accuracies from any single within-country prediction. Multi-country genomic evaluations by multiple-trait GBLUP are possible without using original genotypes at a cost of lower accuracy compared with explicitly combining countries' data.

Positive Effects of "Textured Lunches" Gatherings and Oral Exercises Combined with Physical Exercises on Oral and Physical Function in Older Individuals: A Cluster Randomized Controlled Trial

OBJECTIVES

Proper nutrition and physical exercises are essential to prevent frailty in older adults. Proper masticatory performance and oral function may influence on physical activities as well since the mouth is the entrance of nutrition and digestion. Thus, the present study aimed to test the combined program of specially devised lunch gatherings containing textured foods with oral and physical exercises on the improvement of oral and physical function in community-dwelling older adults.

DESIGN

A Cluster randomized controlled trial; Setting and Participants: Eighty-six community-dwelling older adults in Daito city, Japan, were randomly assigned into control (n = 43) or intervention (n = 43) groups.

INTERVENTION

The control group performed the physical exercise regimen only. The intervention group participated in a 12-week physical and oral exercise program and ate a so-called "munchy lunch" that introduced textured foods with proper nutrients together after performing the physical exercise twice a week following brief dietary instruction at the intervention onset. Physical training and lunch gatherings were held at local public centers.

MEASUREMENTS

The differences in measured variables for physical and oral function between baseline and 12 weeks of intervention were statistically tested.

RESULTS

Oral function as measured by tongue pressure increased significantly in the intervention group (p=0.031), but not in the control group. Physical properties and activities, including body fat percentage and results of the timed up and go test, decreased more significantly in the intervention group than in controls (p<0.05).

CONCLUSIONS

Our findings suggest that a combined program of textured lunch gatherings with oral and physical exercises may improve physical and oral function as a preventative approach for frailty in community-dwelling older adults.

First Observation of P-odd γ Asymmetry in Polarized Neutron Capture on Hydrogen

We report the first observation of the parity-violating gamma-ray asymmetry A_{γ}^{np} in neutron-proton capture using polarized cold neutrons incident on a liquid parahydrogen target at the Spallation Neutron Source at Oak Ridge National Laboratory. A_{γ}^{np} isolates the ΔI=1, ^{3}S_{1}→^{3}P_{1} component of the weak nucleon-nucleon interaction, which is dominated by pion exchange and can be directly related to a single coupling constant in either the DDH meson exchange model or pionless effective field theory. We measured A_{γ}^{np}=[-3.0±1.4(stat)±0.2(syst)]×10^{-8}, which implies a DDH weak πNN coupling of h_{π}^{1}=[2.6±1.2(stat)±0.2(syst)]×10^{-7} and a pionless EFT constant of C^{^{3}S_{1}→^{3}P_{1}}/C_{0}=[-7.4±3.5(stat)±0.5(syst)]×10^{-11}  MeV^{-1}. We describe the experiment, data analysis, systematic uncertainties, and implications of the result.

Mogamulizumab-induced photosensitivity in patients with mycosis fungoides and other T-cell neoplasms

BACKGROUND

Mogamulizumab (Mog) is a defucosylated, therapeutic monoclonal antibody, targeting CCR4 and was first approved in Japan for the treatment of adult T-cell leukaemia/lymphoma (ATLL), followed by cutaneous T-cell lymphoma and peripheral T-cell lymphoma.

OBJECTIVE

To retrospectively investigate development of photosensitivity in patients with mycosis fungoides and other T-cell neoplasms after treatment with Mog.

METHODS

We treated seven cutaneous lymphoma patients with Mog. Upon combination treatment with narrow-band UVB, we noticed that four patients developed photosensitivity dermatitis following Mog therapy, including two cases of mycosis fungoides, one case of adult T-cell leukaemia/lymphoma and one case of EB virus-associated T-cell lymphoproliferative disorder. Phototest was performed with UVA and UVB, and immunohistochemical staining for CD4, CD8 and Foxp3 was conducted in both photosensitivity and lymphoma lesions.

RESULTS

Phototest revealed that the action spectrum of the photosensitivity was UVB in three cases and both UVB and UVA in one case. Histopathologically, the photosensitive lesions were characterized by a lichenoid tissue reaction with a CD8⁺ T cell-dominant infiltrate, sharing the feature with chronic actinic dermatitis, an autoreactive photodermatosis with a cytotoxic T-cell response. Foxp3⁺ regulatory T cells (Tregs) were decreased in the photosensitivity lesions compared with the lymphoma lesions.

CONCLUSION

Increased incidence of photosensitivity reaction was observed during Mog treatment. Decreased number of Tregs in the lesional skin suggests that this reaction is possibly induced by autoreactive cytotoxic T cells.

Technical note: Avoiding the direct inversion of the numerator relationship matrix for genotyped animals in single-step genomic best linear unbiased prediction solved with the preconditioned conjugate gradient

This paper evaluates an efficient implementation to multiply the inverse of a numerator relationship matrix for genotyped animals () by a vector (). The computation is required for solving mixed model equations in single-step genomic BLUP (ssGBLUP) with the preconditioned conjugate gradient (PCG). The inverse can be decomposed into sparse matrices that are blocks of the sparse inverse of a numerator relationship matrix () including genotyped animals and their ancestors. The elements of were rapidly calculated with the Henderson's rule and stored as sparse matrices in memory. Implementation of was by a series of sparse matrix-vector multiplications. Diagonal elements of , which were required as preconditioners in PCG, were approximated with a Monte Carlo method using 1,000 samples. The efficient implementation of was compared with explicit inversion of with 3 data sets including about 15,000, 81,000, and 570,000 genotyped animals selected from populations with 213,000, 8.2 million, and 10.7 million pedigree animals, respectively. The explicit inversion required 1.8 GB, 49 GB, and 2,415 GB (estimated) of memory, respectively, and 42 s, 56 min, and 13.5 d (estimated), respectively, for the computations. The efficient implementation required <1 MB, 2.9 GB, and 2.3 GB of memory, respectively, and <1 sec, 3 min, and 5 min, respectively, for setting up. Only <1 sec was required for the multiplication in each PCG iteration for any data sets. When the equations in ssGBLUP are solved with the PCG algorithm, is no longer a limiting factor in the computations.

The relationship between lip-closing force and dental arch morphology in patient with Angle Class I malocclusion

Dental arch morphology and tooth position are affected by lip-closing force (LCF). This study aimed to quantitatively evaluate the relationships between the horizontal or vertical balance of the LCF generated during maximum voluntary pursing-like movements and dental arch length (DAL) or width (DAW) or the lingual inclination of the upper or lower 1st molars (LIUM, LILM) in patients with Angle Class I malocclusion. Sixteen subjects with Angle Class I malocclusion (median age: 23·4 ± 5·9 years) who had never undergone orthodontic treatment were randomly selected. LCF was measured in eight directions during maximum voluntary pursing-like lip-closing movements. Dental arch models were scanned and analysed to obtain DAW, DAL, LIUM and LILM measurements. Mandibular deviation was measured on posteroanterior cephalograms. A significant negative correlation was detected between maxillary DAL and upper LCF. Maxillary DAL, DAW and the DAL/DAW ratio displayed significant negative correlations with total LCF and upper LCF. However, no significant correlations were detected between any mandibular dental arch morphological parameter and LCF. The difference in the LIUM between the deviation and non-deviation sides exhibited a significant positive correlation with the difference in upper LCF between the deviation and non-deviation sides and was significantly negatively correlated with the difference in lower LCF between the deviation and non-deviation sides. These results suggest that upper LCF is related to maxillary DAL, and the horizontal balance of the LCF of the upper and lower lips is related to the LIUM during pursing-like lip-closing movements in patients with Angle Class I malocclusion.

Nutrition-adaptive control of multiple-bacteriocin production by Weissella hellenica QU 13

AIM

To analyse nutrition-adaptive multiple-bacteriocin production by Weissella hellenica QU 13.

METHODS AND RESULTS

Weissella hellenica QU 13 produces two leaderless bacteriocins, weissellicins Y and M. Their production was studied in MRS and APT media by quantification analyses with liquid chromatography mass spectrometry (LC/MS), while transcriptional analysis of biosynthetic genes was performed by real-time reverse transcription (RT)-PCR. Weissellicin Y production was higher in MRS culture than in APT culture, while weissellicin M production was higher in APT culture than in MRS culture. APT medium contains a higher amount of thiamine than MRS medium, to enhance the growth of heterofermentative lactic acid bacteria. Therefore, thiamine addition to MRS culture enhanced the growth of W. hellenica QU 13; consequently, weissellicin Y production was decreased, while weissellicin M production was not affected. Furthermore, real-time RT-PCR analyses indicated that the transcriptional trends of their respective structural genes, welY and welM, were different from each other, and that these two genes' transcriptions responded to nutrition conditions.

CONCLUSION

Weissella hellenica QU 13 was demonstrated to control weissellicins Y and M production based on nutrition conditions. In addition, differential expression behaviour of weissellicins Y and M indicates that each of them would have separate roles to adapt to different environmental situations.

SIGNIFICANCE AND IMPACT OF THE STUDY

This is the first report that describes nutrition-adaptive multiple-bacteriocin production, in which thiamine inhibits bacteriocin production while it enhances the growth of the producer strain.

Accuracy of breeding values in small genotyped populations using different sources of external information-A simulation study

Genetically linked small and large dairy cattle populations were simulated to test the effect of different sources of information from foreign populations on the accuracy of predicting breeding values for young animals in a small population. A large dairy cattle population (P_L) with >20 generations was simulated, and a small subpopulation (P_S) with 3 generations was formed as a related population, including phenotypes and genomic information. Predicted breeding values for young animals in the small population were calculated using BLUP and single-step genomic BLUP (ssGBLUP) in 4 different scenarios: (S1) 3,166 phenotypes, 22,855 pedigree animals, and 1,000 to 6,000 genotypes for P_S; (S2) S1 plus genomic estimated breeding value (GEBV) for 4,475 sires from P_L as external information; (S3) S1 plus 221,580 phenotypes, 402,829 pedigree animals, and 53,558 genotypes for P_L; and (S4) single nucleotide polymorphism (SNP) effects calculated based on P_L data. The ability to predict true breeding value was assessed in the youngest third of the genotyped animals in the small population. When data only from the small population were used and 1,000 animals were genotyped, the accuracy of GEBV was only 1 point greater than the estimated breeding value accuracy (0.32 vs. 0.31). Adding external GEBV for sires from P_L did not considerably increase accuracy (0.33 vs. 0.32 in S1). Combining phenotypes, pedigree, and genotypes for P_S and P_L was beneficial for predicting accuracy of GEBV in the small population, and the prediction accuracy of GEBV in this scenario was 0.38 compared with 0.31 from estimated breeding values. When SNP effects from P_L were used to predict GEBV for young genotyped animals from P_S, accuracy was greatest (0.56). With 6,000 genotyped animal in P_S, accuracy was greatest (0.61) with the combined populations. In a small population with few genotypes, the highest accuracy of evaluation may be obtained by using SNP effects derived from a related large population.

Technical note: Acceleration of sparse operations for average-information REML analyses with supernodal methods and sparse-storage refinements

The objective of this study was to remove bottlenecks generally found in a computer program for average-information REML. The refinements included improvements to setting-up mixed-model equations on a hash table with a faster hash function as sparse matrix storage, changing sparse structures in calculation of traces, and replacing a sparse matrix package using traditional methods (FSPAK) with a new package using supernodal methods (YAMS); the latter package quickly processed sparse matrices containing large, dense blocks. Comparisons included 23 models with data sets from broiler, swine, beef, and dairy cattle. Models included single-trait, multiple-trait, maternal, and random regression models with phenotypic data; selected models used genomic information in a single-step approach. Setting-up mixed model equations was completed without abnormal termination in all analyses. Calculations in traces were accelerated with a hash format, especially for models with a genomic relationship matrix, and the maximum speed was 67 times faster. Computations with YAMS were, on average, more than 10 times faster than with FSPAK and had greater advantages for large data and more complicated models including multiple traits, random regressions, and genomic effects. These refinements can be applied to general average-information REML programs.

Development of Micro Cellular Open Cell Rigid Polyurethane Foams

With the increasing concern over the threat of ozone depletion and global warming, the rigid polyurethane foam insulation industry is facing a majorchallenge of selecting alternatives for chlorofluorocarbons (CFCs). Under the present situation, however, the effective means of solving this problem haven't been taken yet. Moreover, with more concern with the saving of energy worldwide, there is hope of insulators with higher performance.

This paper reports on a micro cellular open cell polyurethane foam, which is very effective as a core material for evacuated insulators. In addition, thermal insulation panels with high performance are developed by utilizing the open cell foam as a core material.

The evacuated insulators, so-called "vacuum insulation panels," have an insulation effectiveness four times better than those of the conventional rigid polyurethane and polyisocyanurate foams (thermal conductivity is 0.005 W/mK)and are also very lightweight compared to those made of inorganic substances such as silica powder. The vacuum insulation panels were manufactured by packing the core material and absorbents in a film-like laminated plastic container, which is suitable for holding a vacuum, followed by sealing in the industrial vacuum level (0.01—0.1 mm Hg).

We have developed the micro cellular (100—200,μm) and 100% open cell foam by selecting polyol compositions, modified polyisocyanates, surfactants and cell opening additives.

The micro cellular open cell foam has excellent physical properties such as heat resistance, compressive strength and low shrinkage as well as non-scorch at the stage of slabstock foaming. These properties will be very important for manufacturing the vacuum insulation panels. The open cell foams were blown by using the most conventional and alternative blowing agents in rigid foam systems.

In the near future, we hope that this open cell foam technology will contribute to the development of environmentally friendly and high performance products in the insulation industry.

Genetic evaluation using single-step genomic best linear unbiased predictor in American Angus

Predictive ability of genomic EBV when using single-step genomic BLUP (ssGBLUP) in Angus cattle was investigated. Over 6 million records were available on birth weight (BiW) and weaning weight (WW), almost 3.4 million on postweaning gain (PWG), and over 1.3 million on calving ease (CE). Genomic information was available on, at most, 51,883 animals, which included high and low EBV accuracy animals. Traditional EBV was computed by BLUP and genomic EBV by ssGBLUP and indirect prediction based on SNP effects was derived from ssGBLUP; SNP effects were calculated based on the following reference populations: ref_2k (contains top bulls and top cows that had an EBV accuracy for BiW ≥0.85), ref_8k (contains all parents that were genotyped), and ref_33k (contains all genotyped animals born up to 2012). Indirect prediction was obtained as direct genomic value (DGV) or as an index of DGV and parent average (PA). Additionally, runs with ssGBLUP used the inverse of the genomic relationship matrix calculated by an algorithm for proven and young animals (APY) that uses recursions on a small subset of reference animals. An extra reference subset included 3,872 genotyped parents of genotyped animals (ref_4k). Cross-validation was used to assess predictive ability on a validation population of 18,721 animals born in 2013. Computations for growth traits used multiple-trait linear model and, for CE, a bivariate CE-BiW threshold-linear model. With BLUP, predictivities were 0.29, 0.34, 0.23, and 0.12 for BiW, WW, PWG, and CE, respectively. With ssGBLUP and ref_2k, predictivities were 0.34, 0.35, 0.27, and 0.13 for BiW, WW, PWG, and CE, respectively, and with ssGBLUP and ref_33k, predictivities were 0.39, 0.38, 0.29, and 0.13 for BiW, WW, PWG, and CE, respectively. Low predictivity for CE was due to low incidence rate of difficult calving. Indirect predictions with ref_33k were as accurate as with full ssGBLUP. Using the APY and recursions on ref_4k gave 88% gains of full ssGBLUP and using the APY and recursions on ref_8k gave 97% gains of full ssGBLUP. Genomic evaluation in beef cattle with ssGBLUP is feasible while keeping the models (maternal, multiple trait, and threshold) already used in regular BLUP. Gains in predictivity are dependent on the composition of the reference population. Indirect predictions via SNP effects derived from ssGBLUP allow for accurate genomic predictions on young animals, with no advantage of including PA in the index if the reference population is large. With the APY conditioning on about 10,000 reference animals, ssGBLUP is potentially applicable to a large number of genotyped animals without compromising predictive ability.

Implementation of genomic recursions in single-step genomic best linear unbiased predictor for US Holsteins with a large number of genotyped animals

The objectives of this study were to develop and evaluate an efficient implementation in the computation of the inverse of genomic relationship matrix with the recursion algorithm, called the algorithm for proven and young (APY), in single-step genomic BLUP. We validated genomic predictions for young bulls with more than 500,000 genotyped animals in final score for US Holsteins. Phenotypic data included 11,626,576 final scores on 7,093,380 US Holstein cows, and genotypes were available for 569,404 animals. Daughter deviations for young bulls with no classified daughters in 2009, but at least 30 classified daughters in 2014 were computed using all the phenotypic data. Genomic predictions for the same bulls were calculated with single-step genomic BLUP using phenotypes up to 2009. We calculated the inverse of the genomic relationship matrix GAPY(-1) based on a direct inversion of genomic relationship matrix on a small subset of genotyped animals (core animals) and extended that information to noncore animals by recursion. We tested several sets of core animals including 9,406 bulls with at least 1 classified daughter, 9,406 bulls and 1,052 classified dams of bulls, 9,406 bulls and 7,422 classified cows, and random samples of 5,000 to 30,000 animals. Validation reliability was assessed by the coefficient of determination from regression of daughter deviation on genomic predictions for the predicted young bulls. The reliabilities were 0.39 with 5,000 randomly chosen core animals, 0.45 with the 9,406 bulls, and 7,422 cows as core animals, and 0.44 with the remaining sets. With phenotypes truncated in 2009 and the preconditioned conjugate gradient to solve mixed model equations, the number of rounds to convergence for core animals defined by bulls was 1,343; defined by bulls and cows, 2,066; and defined by 10,000 random animals, at most 1,629. With complete phenotype data, the number of rounds decreased to 858, 1,299, and at most 1,092, respectively. Setting up GAPY(-1) for 569,404 genotyped animals with 10,000 core animals took 1.3h and 57 GB of memory. The validation reliability with APY reaches a plateau when the number of core animals is at least 10,000. Predictions with APY have little differences in reliability among definitions of core animals. Single-step genomic BLUP with APY is applicable to millions of genotyped animals.

Glomerular capillary regeneration and endothelial cell apoptosis in both reversible and progressive models of glomerulonephritis

In summary, angiogenetic capillary regeneration with endothelial proliferation occurred among mesangiolytic lesions in Thy-1 GN, and the damaged glomerulus recovered its normal structure with the reconstruction of the capillary network. In anti-GBM GN on WKY rats, the damaged glomerulus showed rare capillary regeneration and progressed to global sclerosis. In Thy-1 GN, endothelial cell apoptosis was found in the regenerated capillaries with endothelial cell hypercellularity. On the other hand, in anti-GBM GN on WKY rats, the number of endothelial cell apoptosis increased during the evolution of glomerular sclerosis. We have concluded that glomerular capillary regeneration plays an essential role in the recovery of damaged glomeruli. Moreover, apoptosis is indispensable in regulating the number of intrinsic endothelial cells. We also found that endothelial apoptosis is important in progression of glomerular sclerosis.

Use of genomic recursions and algorithm for proven and young animals for single-step genomic BLUP analyses--a simulation study

The purpose of this study was to examine accuracy of genomic selection via single-step genomic BLUP (ssGBLUP) when the direct inverse of the genomic relationship matrix (G) is replaced by an approximation of G(-1) based on recursions for young genotyped animals conditioned on a subset of proven animals, termed algorithm for proven and young animals (APY). With the efficient implementation, this algorithm has a cubic cost with proven animals and linear with young animals. Ten duplicate data sets mimicking a dairy cattle population were simulated. In a first scenario, genomic information for 20k genotyped bulls, divided in 7k proven and 13k young bulls, was generated for each replicate. In a second scenario, 5k genotyped cows with phenotypes were included in the analysis as young animals. Accuracies (average for the 10 replicates) in regular EBV were 0.72 and 0.34 for proven and young animals, respectively. When genomic information was included, they increased to 0.75 and 0.50. No differences between genomic EBV (GEBV) obtained with the regular G(-1) and the approximated G(-1) via the recursive method were observed. In the second scenario, accuracies in GEBV (0.76, 0.51 and 0.59 for proven bulls, young males and young females, respectively) were also higher than those in EBV (0.72, 0.35 and 0.49). Again, no differences between GEBV with regular G(-1) and with recursions were observed. With the recursive algorithm, the number of iterations to achieve convergence was reduced from 227 to 206 in the first scenario and from 232 to 209 in the second scenario. Cows can be treated as young animals in APY without reducing the accuracy. The proposed algorithm can be implemented to reduce computing costs and to overcome current limitations on the number of genotyped animals in the ssGBLUP method.