Cardiac MRI feature-tracking-derived torsion mechanics in systolic and diastolic dysfunction in systemic light-chain cardiac amyloidosis

AIM

To describe the myocardial torsion mechanics in cardiac amyloidosis (CA), and evaluate the correlations between left ventricle (LV) torsion mechanics and conventional parameters using cardiac magnetic resonance imaging feature tracking (CMR-FT).

MATERIALS AND METHODS

One hundred and thirty-nine patients with light-chain CA (AL-CA) were divided into three groups: group 1 with preserved systolic function (LV ejection fraction [LVEF] ≥50%, n=55), group 2 with mildly reduced systolic function (40% ≤ LVEF <50%, n=51), and group 3 with reduced systolic function (LVEF <40%, n=33), and compared with age- and gender-matched healthy controls (n=26). All patients underwent cine imaging and late gadolinium-enhancement (LGE). Cine images were analysed offline using CMR-FT to estimate torsion parameters.

RESULTS

Global torsion, base-mid torsion, and peak diastolic torsion rate (diasTR) were significantly impaired in patients with preserved systolic function (p<0.05 for all), whereas mid-apex torsion and peak systolic torsion rate (sysTR) were preserved (p>0.05 for both) compared with healthy controls. In patients with mildly reduced systolic function, global torsion and base-mid torsion were lower compared to those with preserved systolic function (p<0.05 for both), while mid-apex torsion, sysTR, and diasTR were preserved (p>0.05 for all). In patients with reduced systolic function, only sysTR was significantly worse compared with mildly reduced systolic function (p<0.05). At multivariable analysis, right ventricle (RV) end-systolic volume RVESV index and NYHA class were independently related to global torsion, whereas LVEF was independently related to sysTR. RV ejection fraction (RVEF) was independently related to diasTR. LV global torsion performed well (AUC 0.71; 95% confidence interval [CI]: 0.61, 0.77) in discriminating transmural from non-transmural LGE in AL-CA patients.

CONCLUSION

LV torsion mechanics derived by CMR-FT could help to monitor LV systolic and diastolic function in AL-CA patients and function as a new imaging marker for LV dysfunction and LGE transmurality.

Genetic parameters for bull effects on in vitro embryo production (IVP) and relationship between semen quality traits and IVP performance

In vitro production of embryos (IVP) is increasingly applied in dairy cattle breeding and promises widespread use of females of superior genetic merits. One of the current challenges with implementation of IVP is the variability in blastocyst rates. Several factors contribute to these variabilities, among which is known to be the bull used for oocytes fertilization. The extent of genetic control of bulls' effect on IVP performances is yet to be investigated. This study estimates genetic parameters for bull effects on IVP performance traits including blastocyst rate, hatching rate and an index trait combining Blastocyst rate, Kinetic Score, and Morphology score (BL_M_K). The IVP experiments were performed using oocytes aspirated from slaughterhouse ovaries from Holstein cows, fertilized with semen from 123 Holstein bulls. A total of 77 in vitro fertilization (IVF) experiments with 163 records (different IVF groups) were available for the analysis. The results indicate low to moderate heritability and moderate to high repeatability estimates for bull effects on IVP performance traits. Our study also showed that some semen quality traits had significant effects on IVP performance. This included strong genetic correlations between pre-cryopreservation sperm viability and blastocyst rate as well as BL_M_K score at days 7 and 8. Despite the generally weak bull effect correlations and the high standard errors of the estimates, our results provide initial evidence of a measurable genetic component in the bull's impact on IVP performance traits. However, the high standard errors underscore the need for further studies with a larger sample size.

MFG-E8 facilitates heart repair through M1/M2 polarization after myocardial infarction by inhibiting CaMKII

BACKGROUND

M1/M2 macrophage polarization affects patient outcomes after myocardial infarction (MI). The relationship between milk fat globule-epidermal growth factor 8 (MFG-E8) and Ca2+/calmodulin-dependent protein kinase II (CaMKII) on macrophage polarization after MI is unknown. To investigate the functional role of MFG-E8 in modulating cardiac M1/M2 macrophage polarization after MI, especially its influence on CaMKII signaling.

METHODS

Human ventricular tissue and blood were obtained from patients with MI and controls. MFG-E8-KO mice were constructed (C57BL/6). The mice were randomized to WT-sham, sham-MFG-E8-KO, WT-PBS, rmMFG-E8 (WT injected with rmMFG-E8 10 min after MI), and MFG-E8-KO. The mouse macrophage cell line RAW264.7 was obtained. CaMKII, p-CaMKII, Akt, and NF-κB p65 were determined by qRT-PCR, western blot, and immunofluorescence.

RESULTS

The MFG-E8 levels were significantly enhanced after MI in the hearts and plasma of patients with MI compared with controls. The MFG-E8 levels were significantly increased in the hearts and plasma of mice after MI. MFG-E8 was derived from cardiac fibroblasts. The administration of rmMFG-E8 improved ventricular remodeling and cardiac function after MI. rmMFG-E8 did not suppress infiltrating monocyte/macrophages into the peri-infarct area. rmMFG-E8 suppressed the polarization of macrophages to the M1 phenotype and promoted the polarization of macrophages to the M2 phenotype. rmMFG-E8 suppressed CaMKII-dependent signaling in macrophages.

CONCLUSIONS

MFG-E8 and CaMKII appear to collaboratively regulate myocardial remodeling and M1/M2 macrophage polarization after MI. These observations suggest new roles for MFG-E8 in inhibiting M1 but promoting M2 macrophage polarization.

Components of the tumor immune microenvironment based on m-IHC correlate with prognosis and subtype of triple-negative breast cancer

BACKGROUND AND AIM

The spatial distribution and interactions of cells in the tumor immune microenvironment (TIME) might be related to the different responses of triple-negative breast cancer (TNBC) to immunomodulators. The potential of multiplex IHC (m-IHC) in evaluating the TIME has been reported, but the efficacy is insufficient. We aimed to research whether m-IHC results could be used to reflect the TIME, and thus to predict prognosis and complement the TNBC subtyping system.

METHODS

The clinical, imaging, and prognosis data for 86 TNBC patients were retrospectively reviewed. CD3, CD4, CD8, Foxp3, PD-L1, and Pan-CK markers were stained by m-IHC. Particular cell spatial distributions and interactions in the TIME were evaluated with the HALO multispectral analysis platform. Then, we calculated the prognostic value of components of the TIME and their correlations with TNBC transcriptomic subtypes and MRI radiomic features reflecting TNBC subtypes.

RESULTS

The components of the TIME score were established by m-IHC and demonstrated positive prognostic value for TNBC (p = 0.0047, 0.039, <0.0001 for DMFS, RFS, and OS). The score was calculated from several indicators, including Treg% in the tumor core (TC) or stromal area (SA), PD-L1+ cell% in the SA, CD3 + cell% in the TC, and PD-L1+ /CD8+ cells in the invasive margin and SA. According to the TNBC subtyping system, a few TIME indicators were significantly different in different subtypes and significantly correlated with MRI radiomic features reflecting TNBC subtypes.

CONCLUSION

We demonstrated that the m-IHC-based quantitative score and indicators related to the spatial distribution and interactions of cells in the TIME can aid in the accurate diagnosis of TNBC in terms of prognosis and classification.

Artificial intelligence in breast imaging: Current situation and clinical challenges

Breast cancer ranks among the most prevalent malignant tumours and is the primary contributor to cancer-related deaths in women. Breast imaging is essential for screening, diagnosis, and therapeutic surveillance. With the increasing demand for precision medicine, the heterogeneous nature of breast cancer makes it necessary to deeply mine and rationally utilize the tremendous amount of breast imaging information. With the rapid advancement of computer science, artificial intelligence (AI) has been noted to have great advantages in processing and mining of image information. Therefore, a growing number of scholars have started to focus on and research the utility of AI in breast imaging. Here, an overview of breast imaging databases and recent advances in AI research are provided, the challenges and problems in this field are discussed, and then constructive advice is further provided for ongoing scientific developments from the perspective of the National Natural Science Foundation of China.

Case report: A rare case of left ventricular noncompaction in two Chinese siblings with becker muscular dystrophy caused by deletion of exons 10 to 12 in the DMD gene

Background

Becker muscular dystrophy (BMD) is an inherited X-linked recessive condition resulting from mutations of the DMD gene encoding dystrophin. Left ventricular noncompaction (LVNC) is a rare cardiomyopathy morphologically characterized by abnormal myocardial trabeculae and deep recesses in the left ventricle. LVNC in BMD patients has only rarely been reported.

Case report

In the present study, we identified a deletion mutation in exons 10 to 12 (EX10_12 del) of the DMD gene (reference sequence NM_004006.2) in two Chinese siblings with BMD and LVNC by high throughput targeted next-generation sequencing (NGS) and quantitative polymerase chain reaction (qPCR). The proband was a 22-year-old man admitted with dyspnea, abdominal distention, and polyserositis. It is noteworthy that both the proband and his younger brother manifested progressive muscular atrophy and creatine kinase (CK) elevation. Light and electron microscopy examination of muscle biopsies showed the typical features of dystrophinopathies. Cardiac magnetic resonance imaging and echocardiography demonstrated that both brothers had an enlarged left ventricle, LVNC, and reduced left ventricular ejection fraction. Finally, the proband underwent heart transplantation at age 26 with an event-free follow-up over 4 years post-transplantation.

Conclusion

This case further enriches our knowledge of the symptoms, genotype, cardiac performance, management, and prognosis of BMD patients complicated by LVNC. It is recommended that early comprehensive cardiac evaluation should be considered for patients with BMD to exclude LVNC, as this may have a significant impact on their prognosis.

Multibreed genomic prediction using summary statistics and a breed-origin-of-alleles approach

Because of an increasing interest in crossbreeding between dairy breeds in dairy cattle herds, farmers are requesting breeding values for crossbred animals. However, genomically enhanced breeding values are difficult to predict in crossbred populations because the genetic make-up of crossbred individuals is unlikely to follow the same pattern as for purebreds. Furthermore, sharing genotype and phenotype information between breed populations are not always possible, which means that genetic merit (GM) for crossbred animals may be predicted without the information needed from some pure breeds, resulting in low prediction accuracy. This simulation study investigated the consequences of using summary statistics from single-breed genomic predictions for some or all pure breeds in two- and three-breed rotational crosses, rather than their raw data. A genomic prediction model taking into account the breed-origin of alleles (BOA) was considered. Because of a high genomic correlation between the breeds simulated (0.62-0.87), the prediction accuracies using the BOA approach were similar to a joint model, assuming homogeneous SNP effects for these breeds. Having a reference population with summary statistics available from all pure breeds and full phenotype and genotype information from crossbreds yielded almost as high prediction accuracies (0.720-0.768) as having a reference population with full information from all pure breeds and crossbreds (0.753-0.789). Lacking information from the pure breeds yielded much lower prediction accuracies (0.590-0.676). Furthermore, including crossbred animals in a combined reference population also benefitted prediction accuracies in the purebred animals, especially for the smallest breed population.

Flexible but Refractory Single-Crystalline Hyperbolic Metamaterials

The fabrication of flexible single-crystalline plasmonic or photonic components in a scalable way is fundamentally important to flexible electronic and photonic devices with high speed, high energy efficiency, and high reliability. However, it remains a challenge. Here, we have successfully synthesized flexible single-crystalline optical hyperbolic metamaterials by directly depositing refractory nitride superlattices on flexible fluorophlogopite-mica substrates with magnetron sputtering. Interestingly, these flexible hyperbolic metamaterials show dual-band hyperbolic dispersion of dielectric constants with small dielectric losses and high figures of merit in the visible to near-infrared ranges. More importantly, the optical properties of these nitride-based flexible hyperbolic metamaterials show remarkable stability during 1000 °C heating or after being bent 1000 times. Therefore, the strategy developed in this work offers an easy and scalable route for fabricating flexible, high-performance, and refractory plasmonic or photonic components, which can significantly expand the applications of current electronic and photonic devices.

Association between multiple vitamins and bone mineral density: a cross-sectional and population-based study in the NHANES from 2005 to 2006

BACKGROUND

Bone mineral density (BMD) alterations in response to multivitamin exposure were rarely studied. Our study assessed the association of coexposure to six types of vitamins (i.e., vitamins B12, B9, C, D, A and E) with BMD measurements in adults in the US.

METHODS

Data were collected from participants aged ≥ 20 years (n = 2757) in the U.S. National Health and Nutrition Examination Surveys (NHANES) from 2005 to 2006. Multiple linear regression, restricted cubic splines, principal component analysis (PCA) and weighted quantile sum (WQS) regression were performed for statistical analysis.

RESULTS

The circulating levels of vitamins B12 and C were positively associated with BMDs, and an inverted L-shaped exposure relationship was observed between serum vitamin C and BMDs. PCA identified two principal components: one for 'water-soluble vitamins', including vitamins B12, B9 and C, and one for 'fat-soluble vitamins', including vitamins A, D and E. The former was positively associated with total femur (β = 0.009, 95%CI: 0.004, 0.015) and femoral neck (β = 0.007, 95%CI: 0.002, 0.013) BMDs, and the latter was negatively associated with BMDs with non-statistical significance. The WQS index constructed for the six vitamins was significantly related to total femur (β = 0.010, 95%CI: 0.001, 0.018) and femoral neck (β = 0.008, 95%CI: 0.001, 0.015) BMDs, and vitamins B12 and C weighted the most. The WQS index was inversely related to BMDs with non-statistical significance, and vitamins E and A weighted the most.

CONCLUSION

Our findings suggested a positive association between water-soluble vitamin coexposure and BMD, and the association was mainly driven by vitamins B12 and C. Negative association between fat-soluble vitamin coexposure and BMD was indicated, mainly driven by vitamins E and A. An inverted L-shaped exposure relationship was found between vitamin C and BMD.

Age-dependent genetic and environmental variance of semen quality in Nordic Holstein bulls

The aim of this study was to estimate genetic and environmental parameters, across bull's age, for semen quality traits including pre- and postcryopreservation semen concentration, sperm motility, and sperm viability as well as ejaculate volume and number of doses per ejaculate. A data set on 96,595 ejaculates from 2,831 Nordic Holstein bulls collected between 2006 and 2019 was used. Genetic and environmental parameters were estimated using a random regression model and applying the average-information REML approach. Spline functions were chosen to fit the additive genetic and permanent environmental effects across bull's age, and the optimal number of knots was chosen using cross validation. Residual variance heterogeneity was assumed in different bull age classes. The estimated repeatabilities of semen quality traits ranged from 0.16 to 0.85 across different ages of bulls. The estimated heritabilities of semen quality traits ranged from 0.02 to 0.56 across different ages of bulls. The results indicate possibilities for genetic improvement of semen quality traits through selective breeding.

A Novel Seven Gene Signature-Based Prognostic Model to Predict Distant Metastasis of Lymph Node-Negative Triple-Negative Breast Cancer

Background

The prognosis of lymph node-negative triple-negative breast cancer (TNBC) is still worse than that of other subtypes despite adjuvant chemotherapy. Reliable prognostic biomarkers are required to identify lymph node-negative TNBC patients at a high risk of distant metastasis and optimize individual treatment.

Methods

We analyzed the RNA sequencing data of primary tumor tissue and the clinicopathological data of 202 lymph node-negative TNBC patients. The cohort was randomly divided into training and validation sets. Least absolute shrinkage and selection operator Cox regression and multivariate Cox regression were used to construct the prognostic model.

Results

A clinical prognostic model, seven-gene signature, and combined model were constructed using the training set and validated using the validation set. The seven-gene signature was established based on the genomic variables associated with distant metastasis after shrinkage correction. The difference in the risk of distant metastasis between the low- and high-risk groups was statistically significant using the seven-gene signature (training set: P < 0.001; validation set: P = 0.039). The combined model showed significance in the training set (P < 0.001) and trended toward significance in the validation set (P = 0.071). The seven-gene signature showed improved prognostic accuracy relative to the clinical signature in the training data (AUC value of 4-year ROC, 0.879 vs. 0.699, P = 0.046). Moreover, the composite clinical and gene signature also showed improved prognostic accuracy relative to the clinical signature (AUC value of 4-year ROC: 0.888 vs. 0.699, P = 0.029; AUC value of 5-year ROC: 0.882 vs. 0.693, P = 0.038). A nomogram model was constructed with the seven-gene signature, patient age, and tumor size.

Conclusions

The proposed signature may improve the risk stratification of lymph node-negative TNBC patients. High-risk lymph node-negative TNBC patients may benefit from treatment escalation.

Genetic parameters for rectal temperature, respiration rate, and drooling score in Holstein cattle and their relationships with various fertility, production, body conformation, and health traits

Genetic selection for improved climatic resilience is paramount to increase the long-term sustainability of high-producing dairy cattle, especially in face of climate change. Various physiological indicators, such as rectal temperature (RT), respiration rate score (RR), and drooling score (DS), can be used to genetically identify animals with more effective coping mechanisms in response to heat stress events. In this study, we investigated genetic parameters for RT, RR (score from 1-3), and DS (score from 1-3). Furthermore, we assessed the genetic relationship among these indicators and other economically important traits for the dairy cattle industry. After data editing, 59,265 (RT), 30,290 (RR), and 30,421 (DS) records from 13,592 lactating Holstein cows were used for the analyses. Variance components were estimated based on a multiple-trait repeatability animal model. The heritability ± standard error estimate for RT, RR, and DS was 0.06 ± 0.01, 0.04 ± 0.01, and 0.02 ± 0.01, respectively, whereas their repeatability was 0.19, 0.14, and 0.14, respectively. Moderate genetic correlations of RR with RT and DS (0.26 ± 0.11 and 0.25 ± 0.16) and nonsignificant correlation between RT and DS (-0.11 ± 0.14) were observed. Furthermore, the approximate genetic correlations between RT, RR, and DS with 12 production, 29 conformation, 5 fertility and reproduction, 5 health, and 9 longevity-indicator traits were assessed. In general, the approximate genetic correlations calculated were low to moderate. In summary, 3 physiological indicators of heat stress response were measured in a large number of animals and shown to be lowly heritable. There is a value in developing a selection index including all the 3 indicators to improve heat tolerance in dairy cattle. All the unfavorable genetic relationships observed between heat tolerance and other economically important traits can be accounted for in a selection index to enable improved climatic resilience while also maintaining or increasing productivity in Holstein cattle.

Infective endocarditis complicated by embolic events: Pathogenesis and predictors

BACKGROUND

Infective endocarditis (IE) continues to be associated with great challenges. Embolic events (EE) are frequent and life-threatening complications in IE patients. It remains challenging to predict and assess the embolic risk in individual patients with IE accurately.

HYPOTHESIS

Accurate prediction of embolization is critical in the early identification and treatment of risky and potentially embolic lesions in patients with IE.

METHODS

We searched the PubMed, Web of Science, and Google Scholar databases using a range of related search terms, and reviewed the literatures about the pathogenesis and embolic predictors of IE.

RESULTS

The development of IE and its complications is widely accepted as the result of complex interactions between microorganisms, valve endothelium, and host immune responses. The predictive value of echocardiographic characteristics is the most powerful for EE. In addition, both easily obtained blood biomarkers such as C-reactive protein, mean platelet volume, neutrophil-to-lymphocyte ratio, anti-β2-glycoprotein I antibodies, D-Dimer, troponin I, matrix metalloproteinases, and several microbiological or clinical characteristics might be promising as potential predictors of EE.

CONCLUSION

Our review provides a synthesis of current knowledge regarding the pathogenesis and predictors of embolism in IE along with a review of potentially emerging biomarkers.

Circadian clock genes promote glioma progression by affecting tumour immune infiltration and tumour cell proliferation

Objectives

Circadian rhythm controls complicated physiological activities in organisms. Circadian clock genes have been related to tumour progression, but its role in glioma is unknown. Therefore, we explored the relationship between dysregulated circadian clock genes and glioma progression.

Materials and Methods

Samples were divided into different groups based on circadian clock gene expression in training dataset (n = 672) and we verified the results in other four validating datasets (n = 1570). The GO and GSEA enrichment analysis were conducted to explore potential mechanism of how circadian clock genes affected glioma progression. The single‐cell RNA‐Seq analysis was conducted to verified previous results. The immune landscape was evaluated by the ssGSEA and CIBERSORT algorithm. Cell proliferation and viability were confirmed by the CCK8 assay, colony‐forming assay and flow cytometry.

Results

The cluster and risk model based on circadian clock gene expression can predict survival outcome. Samples were scoring by the least absolute shrinkage and selection operator regression analysis, and high scoring tumour was associated with worse survival outcome. Samples in high‐risk group manifested higher activation of immune pathway and cell cycle. Tumour immune landscape suggested high‐risk tumour infiltrated more immunocytes and more sensitivity to immunotherapy. Interfering TIMELESS expression affected circadian clock gene expression, inhibited tumour cell proliferation and arrested cell cycle at the G0/G1 phase.

Conclusions

Dysregulated circadian clock gene expression can affect glioma progression by affecting tumour immune landscape and cell cycle. The risk model can predict glioma survival outcome, and this model can also be applied to pan‐cancer.

Effect of postprandial hyperglycaemia on culprit plaque rupture in diabetic patients with non-ST segment elevation acute coronary syndrome

Background

Postprandial hyperglycemia was reported to play a key role in established risk factors of coronary artery diseases (CAD) and cardiovascular events. Serum 1,5-anhydroglucitol (1,5-AG) levels are known to be a clinical marker of postprandial hyperglycemia and short-term glycemic excursions. Low serum 1,5-AG levels have been associated with occurrence of CAD; however, the relationship between 1,5-AG levels and coronary plaque rupture has not been fully elucidated. The aim of this study was to evaluate 1,5-AG as a predictor of coronary plaque rupture in diabetic patients with non-ST segment elevation acute coronary syndrome (NSTE-ACS).

Methods

A total of 132 diabetic patients with NSTE-ACS were included in this study. All patients underwent intravascular ultrasound examination, which revealed 38 patients with plaque rupture and 94 patients without plaque rupture in the culprit lesion. Fasting blood glucose (FBS), hemoglobin A1c (HbA1c) and 1,5-AG levels were measured before coronary angiography. Fasting urinary 8-iso-prostaglandin F2α (8-iso-PGF2α) level was measured and corrected by creatinine clearance.

Results

Patients with ruptured plaque had significantly lower serum 1,5-AG levels and a tendency of higher hemoglobin A1c levels than patients without ruptured plaque in our study population. In multivariate analysis, low 1,5-AG levels were an independent predictor of plaque rupture (odds ratio 3.3; p=0.006) in diabetic patients with NSTE-ACS, but HbA1c was not. The area under the receiver-operating characteristic curve for 1,5-AG (0.678, p=0.001) to predict plaque rupture was superior to that for HbA1c (0.618, p=0.034). Levels of 1,5-AG were significantly correlated with urinary 8-iso-PGF2α (r=−0.224, p=0.010).

Conclusions

Postprandial hyperglycaemia appeared to be superior to long-term average blood glucose levels in predicting plaque rupture in culprit lesions, which may be useful to assess the cardiovascular outcomes in diabetic patients.

Funding Acknowledgement

Type of funding source: Public Institution(s). Main funding source(s): Outstanding Clinical Discipline Project of Shanghai Pudong, Beijing Health Special Foundation

Integrated omics analysis of sweat reveals an aberrant amino acid metabolism pathway in Vogt-Koyanagi-Harada disease

Vogt-Koyanagi-Harada (VKH) disease is an autoimmune disease leading to visual impairment. Its pathogenic mechanisms remain poorly understood. Our purpose was to investigate the distinctive protein and metabolic profiles of sweat in patients with VKH disease. In the present study, proteomics and metabolomics analysis was performed on 60 sweat samples (30 VKH patients and 30 normal controls) using liquid chromatography tandem mass spectrometry. Parallel reaction monitoring (PRM) analysis was used to validate the results of our omics analysis. In total, we were able to detect 716 proteins and 175 metabolites. Among them, 116 proteins (99 decreased and 17 increased) were observed to be significantly different in VKH patients when compared to controls. Twenty-one differentially expressed metabolites were identified in VKH patients, of which 18 included choline, L-tryptophan, betaine and L-serine were reduced, while the rest were increased. Our multi-omics strategy reveals an important role for the amino acid metabolic pathway in the pathogenesis of VKH disease. Significant differences in proteins and metabolites were identified in the sweat of VKH patients and, to some extent, an aberrant amino acid metabolism pathway may be a pathogenic factor in the pathogenesis of VKH disease.

Genotype by environment interaction for female fertility traits under conventional and organic production systems in Danish Holsteins

Conventional and organic production systems mainly differ in feeding strategies, outdoor and pasture access, and the use of antibiotic treatments. These environmental differences could lead to a genotype by environment interaction (G × E) and a requirement for including G × E in breeding decisions. The objectives of this study were to estimate variance components and heritabilities for conventional and organic production systems and investigate G × E under these 2 production systems for female fertility traits in Danish Holsteins. The analyzed traits included the interval from calving to first insemination (ICF), the interval from first to last insemination, number of inseminations per conception (NINS), and non-return rate within 56 d after the first insemination. Records of female fertility in heifers and the first 3 lactations in cows as well as grass ratio of feed at herd level were collected during the period from 2011 to 2016. The performances of a trait in heifers and cows (lactation 1 to 3) were considered as different traits. The (co)variance components and the resulting heritabilities and genetic correlations were estimated using 2 models. One was a bivariate model treating performances of a trait under organic and conventional production systems as 2 different traits using a reduced data set, and the other was a reaction norm model with random regression on the production system and the grass ratio of feed using a full data set. The full data set comprised records of 37,836 females from 112 organic herds and 513,599 females from 1,224 conventional herds, whereas the reduced data set comprised records from all these 112 organic herds and 92,696 females from 185 convention herds extracted from the full data set with grass ratio of feed lower than 0.20. All female fertility performances of the organic production system were superior to those of the conventional production system. Besides, heterogeneities in additive genetic variances and heritabilities were observed between conventional and organic production systems for all traits. Furthermore, genetic correlations between these 2 production systems ranged from 0.607 to 1.000 estimated from bivariate models and from 0.848 to 0.999 estimated from reaction norm models. Statistically significant G × E were observed for NINS in heifers, non-return rate within 56 d after the first insemination in heifers, and ICF from the bivariate model, and for ICF and NINS in cows from the reaction norm model.

Transcriptome analysis of the endometrium from Chinese Erhualian sows that differ in calcium ion concentration and litter size

Embryonic survival rate, an important factor in the fecundity of sows, is affected by endometrium-secreting histotroph. A higher concentration of calcium ion has been observed in the uterus of highly prolific Erhualian sows (EH) compared with those of less prolific (EL) sows. This suggests that EH sows have better establishment and maintenance of pregnancies, thus increasing embryonic survival rate during the peri-implantation period. To understand the mechanisms of how the endometrium-secreting histotroph affects embryonic survival rate during the Erhualian peri-implantation period, the expression patterns of endometrial mRNA in the EH and EL sows on day 12 of gestation were analyzed using RNA sequencing technology. A total of 164 differentially expressed genes (DEGs) were identified (P_adj  < 0.05, |log₂ (FC)| ≥ 1), including 46 upregulated and 118 downregulated genes in EH compared to EL. Gene Ontology enrichment indicated that a subset of DEGs was involved in calcium ion binding and cell adhesion. Solute carrier family 8 member A3 and solute carrier family 24 member 4, identified as upregulated genes (P_adj  < 0.05) in EH, were considered key candidate genes expressed in the endometrium affecting embryonic survival rate during the peri-implantation period. The results improve understanding of the genetic mechanism underlying the variation in litter size of Erhualian pigs during the peri-implantation period.

Genetic analysis of skinfold thickness and its association with body condition score and milk production traits in Chinese Holstein population

The skin has many important roles in dairy cattle, and skinfold thickness could be used as an indicator of body fat deposition. The objectives of this study were to estimate genetic parameters of skinfold thickness and to explore its association with body condition score (BCS) and milk production traits in a Chinese Holstein population. Skinfold thicknesses over the neck (STN) and the last rib (STR), BCS, and test-day records of milk production traits were available for 6,416 lactating Holstein cows in the summers of 2015 and 2016 in Beijing, China. Multi-trait animal models were used to estimate variance and covariance components using the DMU software. The average STN was 7.15 ± 1.28 mm, and the average STR was 11.76 ± 1.95 mm (mean ± standard deviation). Estimated heritability was 0.13 ± 0.03 for STN and 0.26 ± 0.04 for STR. We detected a high genetic correlation (0.79 ± 0.08; heritability ± standard error) between STN and STR. Genetic correlations between skinfold thickness and BCS were low to moderate: 0.18 between STR and BCS, and 0.33 between STN and BCS. Genetic correlations between skinfold thickness and milk yield, milk fat percentage, and milk protein percentage were negligible, ranging from -0.02 to 0.15. Collectively, skinfold thickness is characterized as a trait with moderate heritability. Skinfold thickness is sensitive to changes in body condition or fat deposition across parities and lactation stages in milking cows, and we confirmed the complementary nature of skinfold thickness and BCS genetically as well as phenotypically by comparing their changing trends throughout lactation and across lactations. The use of skinfold thickness, together with BCS, can assist in the monitoring of changes in body fat deposition to achieve higher management precision.

Short communication: Improving the accuracy of genomic prediction of body conformation traits in Chinese Holsteins using markers derived from high-density marker panels

This study investigated the efficiency of genomic prediction with adding the markers identified by genome-wide association study (GWAS) using a data set of imputed high-density (HD) markers from 54K markers in Chinese Holsteins. Among 3,056 Chinese Holsteins with imputed HD data, 2,401 individuals born before October 1, 2009, were used for GWAS and a reference population for genomic prediction, and the 220 younger cows were used as a validation population. In total, 1,403, 1,536, and 1,383 significant single nucleotide polymorphisms (SNP; false discovery rate at 0.05) associated with conformation final score, mammary system, and feet and legs were identified, respectively. About 2 to 3% genetic variance of 3 traits was explained by these significant SNP. Only a very small proportion of significant SNP identified by GWAS was included in the 54K marker panel. Three new marker sets (54K+) were herein produced by adding significant SNP obtained by linear mixed model for each trait into the 54K marker panel. Genomic breeding values were predicted using a Bayesian variable selection (BVS) model. The accuracies of genomic breeding value by BVS based on the 54K+ data were 2.0 to 5.2% higher than those based on the 54K data. The imputed HD markers yielded 1.4% higher accuracy on average (BVS) than the 54K data. Both the 54K+ and HD data generated lower bias of genomic prediction, and the 54K+ data yielded the lowest bias in all situations. Our results show that the imputed HD data were not very useful for improving the accuracy of genomic prediction and that adding the significant markers derived from the imputed HD marker panel could improve the accuracy of genomic prediction and decrease the bias of genomic prediction.

A cyclic voltammetry and PM6 semi-empirical molecular orbital method study of the capacity behaviour of an aluminum-8-hydroxyquinoline complex modified carbon paste electrode

A graphite powder surface was modified by aluminum-8-hydroxyquinoline complex, and functionalised as an electron storage and transfer surface for use as one of the electrodes in an electrochemical capacitor.

Establishment of a blue light damage model of human retinal pigment epithelial cells in vitro

To establish a blue-light damage model of human retinal pigment epithelium (RPE). Fourth-generation human RPE cells were randomly divided into two groups. In group A, cells were exposed to blue light (2000 ± 500 lux) for 0 (control), 3, 6, 9, and 12 h, and cell culture was stopped after 12 h. In group B, cells were exposed to blue light at the same intensity and time periods, but cell culture was stopped after 24 h. TdT-mediated dUTP nick-end labeling (TUNEL) assay was performed to determine the most suitable illuminating time with apoptotic index. Flow cytometry was used to determine apoptotic ratio of RPEs. In group A, the apoptotic index of cells that received 6, 9 and 12 h of blue light was higher than that of control. The apoptotic index of cells receiving 9 and 12 h was higher than that of 6 h (P = 0.000). In group B, the apoptotic index and RPE cell apoptosis ratio of cells exposed to 6, 9 and 12 h of blue light were higher than that of 3 h (P = 0.000); and cells receiving 9 and 12 h had higher values than that of 6 h. This study demonstrated that the best conditions to establish a blue light damage model of human retinal pigment epithelial cells in vitro are 2000 ± 500 lux light intensity for 6 h, with 24 h of cell culture post-exposure.

Short communication: Improving accuracy of predicting breeding values in Brazilian Holstein population by adding data from Nordic and French Holstein populations

The present study investigated the improvement of prediction reliabilities for 3 production traits in Brazilian Holsteins that had no genotype information by adding information from Nordic and French Holstein bulls that had genotypes. The estimated across-country genetic correlations (ranging from 0.604 to 0.726) indicated that an important genotype by environment interaction exists between Brazilian and Nordic (or Nordic and French) populations. Prediction reliabilities for Brazilian genotyped bulls were greatly increased by including data of Nordic and French bulls, and a 2-trait single-step genomic BLUP performed much better than the corresponding pedigree-based BLUP. However, only a minor improvement in prediction reliabilities was observed in nongenotyped Brazilian cows. The results indicate that although there is a large genotype by environment interaction, inclusion of a foreign reference population can improve accuracy of genetic evaluation for the Brazilian Holstein population. However, a Brazilian reference population is necessary to obtain a more accurate genomic evaluation.

Including different groups of genotyped females for genomic prediction in a Nordic Jersey population

Including genotyped females in a reference population (RP) is an obvious way to increase the RP in genomic selection, especially for dairy breeds of limited population size. However, the incorporation of these females must be conducted cautiously because of the potential preferential treatment of the genotyped cows and lower reliabilities of phenotypes compared with the proven pseudo-phenotypes of bulls. Breeding organizations in Denmark, Finland, and Sweden have implemented a female-genotyping project with the possibility of genotyping entire herds using the low-density (LD) chip. In the present study, 5 scenarios for building an RP were investigated in the Nordic Jersey population: (1) bulls only, (2) bulls with females from the LD project, (3) bulls with females from the LD project plus non-LD project females genotyped before their first calving, (4) bulls with females from the LD project plus non-LD project females genotyped after their first calving, and (5) bulls with all genotyped females. The genomically enhanced breeding value (GEBV) was predicted for 8 traits in the Nordic total merit index through a genomic BLUP model using deregressed proof (DRP) as the response variable in all scenarios. In addition, (daughter) yield deviation and raw phenotypic data were studied as response variables for comparison with the DRP, using stature as a model trait. The validation population was formed using a cut-off birth year of 2005 based on the genotyped Nordic Jersey bulls with DRP. The average increment in reliability of the GEBV across the 8 traits investigated was 1.9 to 4.5 percentage points compared with using only bulls in the RP (scenario 1). The addition of all the genotyped females to the RP resulted in the highest gain in reliability (scenario 5), followed by scenario 3, scenario 2, and scenario 4. All scenarios led to inflated GEBV because the regression coefficients are less than 1. However, scenario 2 and scenario 3 led to less bias of genomic predictions than scenario 5, with regression coefficients showing less deviation from scenario 1. For the study on stature, the daughter yield deviation/daughter yield deviation performed slightly better than the DRP as the response variable in the genomic BLUP (GBLUP) model. Therefore, adding unselected females in the RP could significantly improve the reliabilities and tended to reduce the prediction bias compared with adding selectively genotyped females. Although the DRP has performed robustly so far, the use of raw data is recommended with a single-step model as an optimal solution for future genomic evaluations.

The dissemination mode of drug-resistant genes in Enterobacter cloacae

BACKGROUND

Enterobacter cloacae (E. cloacae) infection has the highest mortality rate among Enterobacter infections. This study aimed to determine the prevalence and the transmission route of the class I integron, qnr genes, and CTX-M ESBLs genes in clinical isolates and to analyse the association between the prevalence of MDR genes and the antibiotic resistance of E. cloacae.

MATERIALS AND METHODS

The antibiotic susceptibility was tested the agar dilution method. The class I integron, qnr genes, and CTX-M ESBLs genes were detected by polymerase chain reaction (PCR). The prevalence data were analysed with the Chi-square test.

RESULTS

In the 100 clinical isolates, the class I integron-positive rate was 65%, with 12% on chromosome, 15% on plasmids and 38% on both. The positive rate of qnr genes was 37% with plasmid location. The positive rates for qnrA, qnrB and qnrS were 6%, 23% and 8%, respectively. The CTX-M ESBLs-positive rate was 34%. For CTX-M-1 ESBLs, 15% were on chromosome, 6% on plasmids and 4% on both; for CTX-M-9 ESBLs, 1% was on chromosome and 7% on plasmid; for CTX-M-25 ESBLs, 3% were on chromosome and 1% on plasmid.

CONCLUSION

Antibiotic resistance genes may be horizontally and vertically disseminated among E. cloacae, which helps multidrug-resistant (MDR) strains of E. cloacae to be successful nosocomial agents.

Impact of relationships between test and training animals and among training animals on reliability of genomic prediction

One of the factors affecting the reliability of genomic prediction is the relationship among the animals of interest. This study investigated the reliability of genomic prediction in various scenarios with regard to the relationship between test and training animals, and among animals within the training data set. Different training data sets were generated from EuroGenomics data and a group of Nordic Holstein bulls (born in 2005 and afterwards) as a common test data set. Genomic breeding values were predicted using a genomic best linear unbiased prediction model and a Bayesian mixture model. The results showed that a closer relationship between test and training animals led to a higher reliability of genomic predictions for the test animals, while a closer relationship among training animals resulted in a lower reliability. In addition, the Bayesian mixture model in general led to a slightly higher reliability of genomic prediction, especially for the scenario of distant relationships between training and test animals. Therefore, to prevent a decrease in reliability, constant updates of the training population with animals from more recent generations are required. Moreover, a training population consisting of less-related animals is favourable for reliability of genomic prediction.

Quantitative trait loci markers derived from whole genome sequence data increases the reliability of genomic prediction

This study investigated the effect on the reliability of genomic prediction when a small number of significant variants from single marker analysis based on whole genome sequence data were added to the regular 54k single nucleotide polymorphism (SNP) array data. The extra markers were selected with the aim of augmenting the custom low-density Illumina BovineLD SNP chip (San Diego, CA) used in the Nordic countries. The single-marker analysis was done breed-wise on all 16 index traits included in the breeding goals for Nordic Holstein, Danish Jersey, and Nordic Red cattle plus the total merit index itself. Depending on the trait's economic weight, 15, 10, or 5 quantitative trait loci (QTL) were selected per trait per breed and 3 to 5 markers were selected to tag each QTL. After removing duplicate markers (same marker selected for more than one trait or breed) and filtering for high pairwise linkage disequilibrium and assaying performance on the array, a total of 1,623 QTL markers were selected for inclusion on the custom chip. Genomic prediction analyses were performed for Nordic and French Holstein and Nordic Red animals using either a genomic BLUP or a Bayesian variable selection model. When using the genomic BLUP model including the QTL markers in the analysis, reliability was increased by up to 4 percentage points for production traits in Nordic Holstein animals, up to 3 percentage points for Nordic Reds, and up to 5 percentage points for French Holstein. Smaller gains of up to 1 percentage point was observed for mastitis, but only a 0.5 percentage point increase was seen for fertility. When using a Bayesian model accuracies were generally higher with only 54k data compared with the genomic BLUP approach, but increases in reliability were relatively smaller when QTL markers were included. Results from this study indicate that the reliability of genomic prediction can be increased by including markers significant in genome-wide association studies on whole genome sequence data alongside the 54k SNP set.

Monitoring of atherosclerosis evolution by detection of inflammatory states of aortae in a rabbit model using 18F-FDG -PET/CT

AIM

In vivo dynamic evaluation of atherosclerosis could be clinically significant in the prevention of cardiovascular events. We aimed to monitor Fluorine-18 fluorodeoxyglucose (18F-FDG) uptake in different stages of atherosclerosis, and investigate the feasibility of detecting vulnerable plaques using positron emission tomography/computed tomography (PET/CT) angiography.

METHODS

Twenty-two male NZW rabbits were divided into two groups: atherosclerosis group (group A, N.=11) and atherosclerosis and statin group (group S, N.=11). The rabbits underwent two pharmacological triggerings to induce thrombus at the 18th week. In vivo PET/CT scans were performed on four time points: before cholesterol diet (baseline, N.=6), at 8th week (the middle-of-feeding, N.=4), at 18th week (the end-of-feeding, N.=22) and after triggering (post-triggering, N.=15). 18F-FDG uptake by the aorta was expressed as maximal standardized uptake value (SUVmax) and mean SUV (SUVmean). SUVs were measured on serial 7.5 mm arterial segments.

RESULTS

SUVmean and SUVmax were 0.449±0.108 and 0.550±0.132 at baseline, 0.694±0.117 and 0.754±0.129 at the middle-of-feeding, 0.788±0.121 and 0.861±0.139 in group A, and 0.651±0.194 and 0.736±0.243 in group S at the end-of feeding before triggering. SUVmean and SUVmax were 1.128±0.420 and 1.302±0.489 in thrombosis group, 0.774±0.159 and 0.859±0.191 in non-thrombosis group after triggering. Thrombus were identified in 10 of 22 rabbits (45.5%): 8 of 11 (72.3%) in group A, and 2 of 11 (18.2%) in group S (P<0.001).

CONCLUSION

The inflammatory states of atherosclerosis and vulnerable plaque can be detected by quantitative analysis of 18F-FDG uptake. PET/CT may be used for predicting thrombosis events in patients with atherosclerotic disease.

Increasing imputation and prediction accuracy for Chinese Holsteins using joint Chinese-Nordic reference population

This study investigated the effect of including Nordic Holsteins in the reference population on the imputation accuracy and prediction accuracy for Chinese Holsteins. The data used in this study include 85 Chinese Holstein bulls genotyped with both 54K chip and 777K (HD) chip, 2862 Chinese cows genotyped with 54K chip, 510 Nordic Holstein bulls genotyped with HD chip, and 4398 Nordic Holstein bulls genotyped with 54K chip and with deregressed proofs for five milk production traits. Based on these data, the accuracy of imputation from 54K to HD marker data and the accuracy of genomic predictions in Chinese Holstein were assessed. The allele correct rate increased around 2.7 and 1.7% in imputation from the 54K to the HD marker data for Chinese Holstein bulls and cows, respectively, when the Nordic HD-genotyped bulls were included in the reference data for imputation. However, the prediction accuracy was improved slightly when using the marker data imputed based on the combined HD reference data, compared with using the marker data imputed based on the Chinese HD reference data only. On the other hand, when using the combined reference population including 4398 Nordic Holstein bulls, the accuracy of genomic predictions increased 6.5 percentage points together with a reduction of prediction bias. The HD markers did not outperform the 54K markers in genomic prediction based on the present data. The results indicate that for Chinese Holsteins, it is necessary to genotype more individuals with 54K chip to increase reference population rather than increasing marker density.

Short communication: Heterosis by environment and genotype by environment interactions for protein yield in Danish Jerseys

Crossing of lines or strains within and between breeds has been demonstrated to be beneficial for dairy cattle performance. However, even within breed, differences between strains may also give rise to heterosis. A key question is whether an interaction exists between heterosis and environment (H × E) that is independent of genotype by environment (G × E) interactions. In this study, H × E and G × E interactions were estimated in a population of approximately 300,000 Danish Jersey cows. The cows were a mixture of pure Danish Jerseys and crosses of US and Danish Jerseys. The phenotype studied was protein yield. A reaction norm model where the unknown environmental covariates are inferred simultaneously with the other parameters in the model was used to analyze the data. When H × E, but not G × E, was included in the model, heterosis was estimated to be 3.8% for the intermediate environmental level. However, when both H × E and G × E were included in the model, heterosis was estimated to be 4.1% for the intermediate environmental level. Furthermore, when only H × E was included in the model, the regression on the unknown environmental covariate was estimated to be 0.15, interpreted as meaning that an increase of average herd-year protein yield by 1 kg of protein led to an increase in heterosis of 0.15 kg above the average heterosis for a first-cross cow. When both H × E and G × E were included in the model, the regression on the unknown environmental covariate was not significantly different from zero, meaning that heterosis was similar in all environments investigated. The genetic correlation of protein yields for different environmental levels ranged from 0.72 to 0.93, which was significantly different from unity, indicating that G × E exist for protein yield.