Identification of genomic regions associated with differences in fleece type in Huacaya and Suri alpacas (Vicugna pacos)

The difference in fleece type is the distinguishing trait between the two types of alpacas (Vicugna pacos), Huacaya and Suri. The Suri fleece type has been found to be inherited dominantly over the Huacaya type, resulting in offspring with the Suri phenotype. The aim of our study was to map genomic regions associated with the two different fleece types. In this study, 91 alpacas (54 Huacayas and 37 Suris) from Germany and Switzerland were genotyped using the 76k alpaca SNP array. Only 59k chromosome-localised markers map to the alpaca reference assembly VicPac3.1, and after quality control 49 866 SNPs, were retained for population structure assessment and to conduct a genome-wide association study. Both principal component and neighbour-joining tree analysis showed that the two fleece-type cohorts overlapped rather than forming two distinct clusters. Genome-wide significantly associated markers were observed in the scaffold region of chromosome 16 (NW_021964192.1), which contains a cluster of keratin genes. A haplotype predominantly found in Suri alpacas has been identified which supports dominant inheritance. Variant filtering of nine whole-genome sequenced alpacas from both fleece types in the critical interval of 0.4 Mb did not reveal perfect segregation of either fleece type for specific variants. To our knowledge, this is the first study to use the recently developed species-specific SNP array to identify genomic regions associated with differences in fleece type in alpacas. There are still some limitations, such as the preliminary status of the reference assembly and the incomplete annotation of the alpaca genome.

A two-stage fine-tuning method for low-resource cross-lingual summarization

Cross-lingual summarization (CLS) is the task of condensing lengthy source language text into a concise summary in a target language. This presents a dual challenge, demanding both cross-language semantic understanding (i.e., semantic alignment) and effective information compression capabilities. Traditionally, researchers have tackled these challenges using two types of methods: pipeline methods (e.g., translate-then-summarize) and end-to-end methods. The former is intuitive but prone to error propagation, particularly for low-resource languages. The later has shown an impressive performance, due to multilingual pre-trained models (mPTMs). However, mPTMs (e.g., mBART) are primarily trained on resource-rich languages, thereby limiting their semantic alignment capabilities for low-resource languages. To address these issues, this paper integrates the intuitiveness of pipeline methods and the effectiveness of mPTMs, and then proposes a two-stage fine-tuning method for low-resource cross-lingual summarization (TFLCLS). In the first stage, by recognizing the deficiency in the semantic alignment for low-resource languages in mPTMs, a semantic alignment fine-tuning method is employed to enhance the mPTMs' understanding of such languages. In the second stage, while considering that mPTMs are not originally tailored for information compression and CLS demands the model to simultaneously align and compress, an adaptive joint fine-tuning method is introduced. This method further enhances the semantic alignment and information compression abilities of mPTMs that were trained in the first stage. To evaluate the performance of TFLCLS, a low-resource CLS dataset, named Vi2ZhLow, is constructed from scratch; moreover, two additional low-resource CLS datasets, En2ZhLow and Zh2EnLow, are synthesized from widely used large-scale CLS datasets. Experimental results show that TFCLS outperforms state-of-the-art methods by 18.88%, 12.71% and 16.91% in ROUGE-2 on the three datasets, respectively, even when limited with only 5,000 training samples.

Dynamic transcriptome landscape of developing maize ear

Seed number and harvesting ability in maize (Zea mays L.) are primarily determined by the architecture of female inflorescence, namely the ear. Therefore, ear morphogenesis contributes to grain yield and as such is one of the key target traits during maize breeding. However, the molecular networks of this highly dynamic and complex grain-bearing inflorescence remain largely unclear. As a first step toward characterizing these networks, we performed a high-spatio-temporal-resolution investigation of transcriptomes using 130 ear samples collected from developing ears with length from 0.1 mm to 19.0 cm. Comparisons of these mRNA populations indicated that these spatio-temporal transcriptomes were clearly separated into four distinct stages stages I, II, III, and IV. A total of 23 793 genes including 1513 transcription factors (TFs) were identified in the investigated developing ears. During the stage I of ear morphogenesis, 425 genes were predicted to be involved in a co-expression network established by eight hub TFs. Moreover, 9714 ear-specific genes were identified in the seven kinds of meristems. Additionally, 527 genes including 59 TFs were identified as especially expressed in ear and displayed high temporal specificity. These results provide a high-resolution atlas of gene activity during ear development and help to unravel the regulatory modules associated with the differentiation of the ear in maize.

A complete telomere-to-telomere assembly of the maize genome

A complete telomere-to-telomere (T2T) finished genome has been the long pursuit of genomic research. Through generating deep coverage ultralong Oxford Nanopore Technology (ONT) and PacBio HiFi reads, we report here a complete genome assembly of maize with each chromosome entirely traversed in a single contig. The 2,178.6 Mb T2T Mo17 genome with a base accuracy of over 99.99% unveiled the structural features of all repetitive regions of the genome. There were several super-long simple-sequence-repeat arrays having consecutive thymine-adenine-guanine (TAG) tri-nucleotide repeats up to 235 kb. The assembly of the entire nucleolar organizer region of the 26.8 Mb array with 2,974 45S rDNA copies revealed the enormously complex patterns of rDNA duplications and transposon insertions. Additionally, complete assemblies of all ten centromeres enabled us to precisely dissect the repeat compositions of both CentC-rich and CentC-poor centromeres. The complete Mo17 genome represents a major step forward in understanding the complexity of the highly recalcitrant repetitive regions of higher plant genomes.

Global epidemiology and burden of tetanus from 1990 to 2019: a systematic analysis for the global burden of disease study 2019

OBJECTIVES

Tetanus is a serious infectious disease. In recent decades, the epidemiology and disease characteristics of tetanus have been reported by many medical workers, but these studies usually have limited sample sizes.

METHODS

We retrieved all the epidemiological data related to "tetanus" from the Global Burden of Disease Study 2019. And a secondary analysis was performed to report the global epidemiology and disease burden of Tetanus.

RESULTS

From 1990 to 2019, the incidence and death rate of tetanus decreased globally. In general, high SDI (sociodemographic index) countries have lower age-standard incidence rates and age-standard death rates than low SDI countries. Moreover, in low SDI regions, newborns were the most high-risk group for tetanus. In high SDI areas, half of the tetanus cases occurred in the 70+ age group. The disease burden of tetanus was significantly higher in males than in females.

CONCLUSION

The disease burden of tetanus decreased significantly globally from 1990 to 2019. Neonatal tetanus is serious in low SDI areas, while the proportion of elderly tetanus is the highest in high SDI areas. The containment of tetanus in all age groups and gender still requires efforts from all sectors.

HEAT SHOCK PROTEIN 90.6 interacts with carbon and nitrogen metabolism components during seed development

Carbon and nitrogen are the two main nutrients in maize (Zea mays L.) kernels, and kernel filling and metabolism determine seed formation and germination. However, the molecular mechanisms underlying the relationship between kernel filling and corresponding carbon and nitrogen metabolism remain largely unknown. Here, we found that HEAT SHOCK PROTEIN 90.6 (HSP90.6) is involved in both seed filling and the metabolism processes of carbon and nitrogen. A single-amino acid mutation within the HATPase_c domain of HSP90.6 led to small kernels. Transcriptome profiling showed that the expression of amino acid biosynthesis- and carbon metabolism-related genes was significantly downregulated in the hsp90.6 mutant. Further molecular evidence showed strong interactions between HSP90.6 and the 26S proteasome subunits REGULATORY PARTICLE NON-ATPASE6 (RPN6) and PROTEASOME BETA SUBUNITD2 (PBD2). The mutation of hsp90.6 significantly reduced the activity of the 26S proteasome, resulting in the accumulation of ubiquitinated proteins and defects in nitrogen recycling. Moreover, we verified that HSP90.6 is involved in carbon metabolism through interacting with the 14-3-3 protein GENERAL REGULATORY FACTOR14-4 (GF14-4). Collectively, our findings revealed that HSP90.6 is involved in seed filling and development by interacting with the components controlling carbon and nitrogen metabolism.

A Review of Fusion Methods for Omics and Imaging Data

The development of omics data and biomedical images has greatly advanced the progress of precision medicine in diagnosis, treatment, and prognosis. The fusion of omics and imaging data, i.e., omics-imaging fusion, offers a new strategy for understanding complex diseases. However, due to a variety of issues such as the limited number of samples, high dimensionality of features, and heterogeneity of different data types, efficiently learning complementary or associated discriminative fusion information from omics and imaging data remains a challenge. Recently, numerous machine learning methods have been proposed to alleviate these problems. In this review, from the perspective of fusion levels and fusion methods, we first provide an overview of preprocessing and feature extraction methods for omics and imaging data, and comprehensively analyze and summarize the basic forms and variations of commonly used and newly emerging fusion methods, along with their advantages, disadvantages and the applicable scope. We then describe public datasets and compare experimental results of various fusion methods on the ADNI and TCGA datasets. Finally, we discuss future prospects and highlight remaining challenges in the field.

The marginal gaps of sequentially milled lithium disilicate crowns using two different milling units

BACKGROUND

The purpose of this study was to compare the marginal gaps of sequentially milled lithium disilicate (LDS) crowns using two different milling units.

METHODS

One lower left first molar typodont tooth prepared for an LDS crown by an undergraduate student in a simulation clinic was selected. The crown preparation was scanned by a TRIOS 3 scanner and twelve LDS crowns milled by an E4D (E4DM) and a Sirona inLab MC X5 (MCX5) milling unit using identical settings. The crowns were seated onto the original crown preparation and three vertical marginal gap measurements were taken at four locations (mid-buccal, mid-lingual, mid-mesial and mid-distal) using a stereomicroscope. The mean marginal gap (MMG) was calculated for each individual tooth surface and each crown.

RESULTS

The MMG for the E4DM (100.40 μm) was not significantly different to the MCX5 (101.08 μm) milling unit (P = 0.8809). In both units, there was a statistically significant trend of increasing MMG with sequentially milled crowns using the same burs (E4DM P = 0.0133; MCX5 P = 0.0240).

CONCLUSIONS

The E4DM and MCX5 milling units produced LDS crowns with similar MMG's and within a clinically acceptable range but with a trend of increasing MMG when analysed sequentially. © 2022 Australian Dental Association.

Failure of sterilization in a dental outpatient facility: Investigation, risk assessment, and management

In 2017, an incident of failed sterilization of dental instruments occurred at a large dental outpatient facility in Singapore. We aim to describe findings of the investigation of the sterilization breach incident, factors related to risk of viral transmission to the potentially affected patients, and the contact tracing process, patient management, and blood test results at a 6-month follow-up. A full assessment of the incident was immediately carried out. The factors related to risk of viral transmission due to affected instruments were analyzed using 3 keys points: breached step(s) and scale of the incident, prevalence of underlying bloodborne diseases and immunity in the Singapore population, health status of potential source patients, and type of dental procedure performed, and health status of affected patients and type of dental procedure received. Up to 72 affected instrument sets were used in 714 potentially affected patients who underwent noninvasive dental procedures. The investigation revealed that there was a lapse in the final step of steam sterilization, resulting in the use of incompletely sterilized items. The assessment determined that there was an extremely low risk of bloodborne virus transmission of diseases to the patients. At the 6-month follow-up, there were no infected/colonized cases found related to the incident. Lapses in the sterilization process for medical and dental instruments can happen, but a risk assessment approach is useful to manage similar incidents. Quick response and proper documentation of the sterilization process can prevent similar incidents.

A Syntax-enhanced model based on category keywords for biomedical relation extraction

Certain categories in multi-category biomedical relationship extraction have linguistic similarities to some extent. Keywords related to categories and syntax structures of samples between these categories have some notable features, which are very useful in biomedical relation extraction. The pre-trained model has been widely used and has achieved great success in biomedical relationship extraction, but it is still incapable of mining this kind of information accurately. To solve the problem, we present a syntax-enhanced model based on category keywords. First, we prune syntactic dependency trees in terms of category keywords obtained by the chi-square test. It reduces noisy information caused by current syntactic parsing tools and retains useful information related to categories. Next, to encode category-related syntactic dependency trees, a syntactic transformer is presented, which enhances the ability of the pre-trained model to capture syntax structures and to distinguish multiple categories. We evaluate our method on three biomedical datasets. Compared with state-of-the-art models, our method performs better on these datasets. We conduct further analysis to verify the effectiveness of our method.

Endothelial-T cell crosstalk contributes to vascular injury in fatty liver disease

 

Cardiovascular complications are often the fundamental causes of death in non-alcoholic fatty liver disease (NAFLD) patients. While there are known systemic mediators in NAFLD that may induce vascular inflammation, the mechanism of endothelial dysfunction remain understudied. In this work, we harnessed the replicative potential of blood outgrowth endothelial cells (BOECs) to develop personalized cell lines from NAFLD patients and healthy controls. Our transcriptomic analysis showed that the top interactome network enriched in NAFLD BOECs comprised of several C-C and C-X-C chemokine ligands involved in immune cell chemotaxis. We previously reported T cell infiltration in mouse model of non-alcoholic steatohepatitis, and here, we confirmed enhanced endothelial chemokine signatures in arterial histological sections. To elucidate endothelial-immune crosstalk, we performed single-cell analysis on human peripheral blood mononuclear cells and found T cell intensification in NAFLD patients compared to healthy controls. Our immunoprofiling by flow cytometry further revealed that NAFLD patients possessed higher levels CD8+ memory cells. Functionally, T cells, instead of monocytes, adhered more pronouncedly to NAFLD BOECs. In evaluating the CXCL12-CXCR4 axis in chemotaxis, CXCR4 antagonist (AMD3100) substantially modulated the migration of patient-derived CD8+ T cells towards NAFLD BOECs, which was not observed in healthy endothelial-T cell chemotaxis coculture. Finally, we validated NAFLD-associated endothelial dysfunction by enumerating two folds more circulating endothelial cells, a biomarker of vascular injury, in the blood samples of NAFLD patients than healthy controls. Our work provides insights for translation to restore blood vessel health and potentially mitigate adverse vascular events in NAFLD.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Industrial Alignment Fund Pre-Positioning grant from the Agency for Science, Technology and Research, Singapore Endothelial-T cell crosstalk in NAFLD

Application of Metabolomics to the Discovery of Biomarkers for Ischemic Stroke in the Murine Model: a Comparison with the Clinical Results

Ischemic stroke (IS) is a major cause of mortality and disability worldwide. However, the pathogenesis of IS remains unknown, and methods for early prediction and diagnosis of IS are lacking. Metabolomics can be applied to biomarker discovery and mechanism exploration of IS by exploring metabolic alterations. In this review, 62 IS metabolomics studies in the murine model published from January 2006 to December 2020 in the PubMed and Web of Science databases were systematically reviewed. Twenty metabolites (e.g., lysine, phenylalanine, methionine, tryptophan, leucine, lactate, serine, N-acetyl-aspartic acid, and glutathione) were reported consistently in more than two-third murine studies. The disturbance of metabolic pathways, such as arginine biosynthesis; alanine, aspartate and glutamate metabolism; aminoacyl-tRNA biosynthesis; and citrate cycle, may be implicated in the development of IS by influencing the biological processes such as energy failure, oxidative stress, apoptosis, and glutamate toxicity. The transient middle cerebral artery occlusion model and permanent middle cerebral artery occlusion model exhibit both common and distinct metabolic patterns. Furthermore, five metabolites (proline, serine, LysoPC (16:0), uric acid, glutamate) in the blood sample and 7 metabolic pathways (e.g., alanine, aspartate, and glutamate metabolism) are shared in animal and clinical studies. The potential biomarkers and related pathways of IS in the murine model may facilitate the biomarker discovery for early diagnosis of IS and the development of novel therapeutic targets.

A Hierarchical Graph Convolution Network for Representation Learning of Gene Expression Data

The curse of dimensionality, which is caused by high-dimensionality and low-sample-size, is a major challenge in gene expression data analysis. However, the real situation is even worse: labelling data is laborious and time-consuming, so only a small part of the limited samples will be labelled. Having such few labelled samples further increases the difficulty of training deep learning models. Interpretability is an important requirement in biomedicine. Many existing deep learning methods are trying to provide interpretability, but rarely apply to gene expression data. Recent semi-supervised graph convolution network methods try to address these problems by smoothing the label information over a graph. However, to the best of our knowledge, these methods only utilize graphs in either the feature space or sample space, which restrict their performance. We propose a transductive semi-supervised representation learning method called a hierarchical graph convolution network (HiGCN) to aggregate the information of gene expression data in both feature and sample spaces. HiGCN first utilizes external knowledge to construct a feature graph and a similarity kernel to construct a sample graph. Then, two spatial-based GCNs are used to aggregate information on these graphs. To validate the model's performance, synthetic and real datasets are provided to lend empirical support. Compared with two recent models and three traditional models, HiGCN learns better representations of gene expression data, and these representations improve the performance of downstream tasks, especially when the model is trained on a few labelled samples. Important features can be extracted from our model to provide reliable interpretability.

POS1095 FOOD SOURCES OF DIETARY FIBRE AND RISK OF TOTAL KNEE REPLACEMENT RELATED TO SEVERE OSTEOARTHRITIS, THE SINGAPORE CHINESE HEALTH STUDY

Background:

Although fibre intake was inversely associated with the risk of symptomatic knee osteoarthritis (KOA) in a US study, this association was partially confounded by lower body mass index (BMI) in those with higher fibre intake.

Objectives:

We evaluated the association between fibre intake and its food sources, and the risk of total knee replacement (TKR) due to severe KOA.

Methods:

We used data from the Singapore Chinese Health Study, a prospective cohort study that recruited 63,257 participants aged 45-74 years from 1993 to 1998. At baseline, we assessed diet using a validated 165-item semi-quantitative food frequency questionnaire, together with BMI and lifestyle factors. Incident TKR cases were identified via record linkage with nationwide hospital discharge database through 2017. We used multivariable Cox regression models to compute hazard ratio (HR) and the corresponding 95% confidence interval (CI) for risk of TKR.

Results:

There were 2,816 cases of incident TKR due to severe KOA. Total fibre intake at baseline was not associated with risk of TKR after adjustment for confounders. Among the food sources of fibre, higher intake of legumes was associated with lower risk of TKR in dose-dependent manner; compared with those having the lowest quartile intake, HR (95% CI) was 0.86 (0.76, 0.96) for the highest quartile (p for trend = 0.004). This association was consistent after including BMI in the model, and homogenous across BMI categories. The consumption of other fibre sources, namely grain products, nuts and seeds, soy food, fruits and vegetables, was not associated with risk of TKR.

Conclusion:

Intake of legumes, but not total fibre, was associated with a reduced risk of TKR. Further research is needed to replicate our findings, and to evaluate possible biological mechanisms that could explain the effect of dietary legumes in pathogenesis or progression of KOA.

Table 1.

Hazard ratios (95% confidence intervals) for risk of total knee replacement according to intake of fibre (only shown total fibre and legumes): The Singapore Chinese Health Study (1993-2017).

Quartiles of energy-adjusted food intakeQ1Q2Q3Q4p for trend 1Total fibreMedian, g/day8.559.4312.1917.70Cases/ person-years528/ 275,050712/ 280,456767/ 284,394809/ 287,955Multivariate Model 11.001.08 (0.96, 1.21)1.12 (1.00, 1.26)1.18 (1.05, 1.32)0.003Multivariate Model 21.001.06 (0.95, 1.19)1.09 (0.97, 1.22)1.11 (0.99, 1.24)0.088LegumesMedian, g/day0.110.432.117.01Cases/ person-years638/ 280,170754/ 278,001756/ 280,407668/ 289,275Multivariate Model 11.000.97 (0.87, 1.09)0.95 (0.84, 1.06)0.84 (0.76, 0.94)<0.001Multivariate Model 21.000.98 (0.87, 1.09)0.94 (0.84, 1.06)0.86 (0.77, 0.96)0.004Multivariate Model 31.000.98 (0.87, 1.09)0.95 (0.84, 1.06)0.86 (0.76, 0.96)0.004

1Linear trend was tested by assigning to participants the median value of the quartile and treating this as a continuous variable. 2 The grain products included noodles and pasta, rice, bread and pancakes, breakfast cereals, biscuits and crackers.

Multivariate model 1: adjusted for age at interview, sex, year of interview, total energy intake, dialect, education level

Multivariate model 2: model 1 plus BMI, sitting duration, sleep, physical activity, smoking, history of hypertension, diabetes, coronary artery disease and stroke.

Multivariate model 3: model 2 plus grain products, legumes, nuts and seeds, soy food, fruits and vegetables.

Q = quartile

Disclosure of Interests:

None declared.

High-throughput organ-on-chip platform with integrated programmable fluid flow and real-time sensing for complex tissue models in drug development workflows

Drug development suffers from a lack of predictive and human-relevant in vitro models. Organ-on-chip (OOC) technology provides advanced culture capabilities to generate physiologically appropriate, human-based tissue in vitro, therefore providing a route to a predictive in vitro model. However, OOC technologies are often created at the expense of throughput, industry-standard form factors, and compatibility with state-of-the-art data collection tools. Here we present an OOC platform with advanced culture capabilities supporting a variety of human tissue models including liver, vascular, gastrointestinal, and kidney. The platform has 96 devices per industry standard plate and compatibility with contemporary high-throughput data collection tools. Specifically, we demonstrate programmable flow control over two physiologically relevant flow regimes: perfusion flow that enhances hepatic tissue function and high-shear stress flow that aligns endothelial monolayers. In addition, we integrate electrical sensors, demonstrating quantification of barrier function of primary gut colon tissue in real-time. We utilize optical access to the tissues to directly quantify renal active transport and oxygen consumption via integrated oxygen sensors. Finally, we leverage the compatibility and throughput of the platform to screen all 96 devices using high content screening (HCS) and evaluate gene expression using RNA sequencing (RNA-seq). By combining these capabilities in one platform, physiologically-relevant tissues can be generated and measured, accelerating optimization of an in vitro model, and ultimately increasing predictive accuracy of in vitro drug screening.

[Establishment of animal models of epidermal growth factor receptor inhibitor-related rashes]

OBJECTIVE

To establish animal models epidermal growth factor receptor inhibitor-related skin rashes using cetuximab, gefitinib or erlotinib.

OBJECTIVE

Female SCID mice were randomly divided into blank control group and high-, moderate-, and low-dose cetuximab groups. The mice in control group received intraperitoneal injection of saline, and those in the 3 cetuximab groups were injected with 80, 40, and 20 mg/kg cetuximab (3 times a week for 4 weeks), respectively. The general skin appearance and skin pathologies of the mice were observed. Female BN rats were randomly divided into blank group, ovalbumin group, gefitinib group and erlotinib group, and in the latter 3 groups, the rats were given ovalbumin (1 mg), gefitinib (37.5 mg/kg), and erlotinib (23.5 mg/kg) by lavage once daily for 45 days, respectively. Skin pathologies of the rats were observed, and serum levels of TNF-α, IL-6 and other inflammatory factors were detected using ELISA.

OBJECTIVE

Intraperitoneal injection of cetuximab did not induce typical skin rashes, scabs or obvious skin inflammation in the mice. In female BN rats, lavage of gefitinib caused obvious skin rashes, scabs and exudation, and obvious inflammatory cell infiltration, keratinosis, spinous layer release and epidermal thickening were observed in the skin. No obvious skin inflammation were observed in the rats in the control, ovalbumin or erlotinib groups. While IgE (P=0.061) and TNF-α concentrations (P=0.057) did not differ significantly among the groups, serum levels of IL-6 was significantly higher in gefitinib group than in the blank control group (P=0.016) but similar between erlotinib group and the blank group (P=0.910).

OBJECTIVE

Intraperitoneal injection of cetuximab can not induce epidermal growth factor receptor inhibitor-related skin rashes in SCID mice. Lavage of gefitinib, but not erlotinib, can be used to establish models of epidermal growth factor receptor inhibitor-related rashes in BN rats.

Quantum circuits with many photons on a programmable nanophotonic chip

Growing interest in quantum computing for practical applications has led to a surge in the availability of programmable machines for executing quantum algorithms1,2. Present-day photonic quantum computers3-7 have been limited either to non-deterministic operation, low photon numbers and rates, or fixed random gate sequences. Here we introduce a full-stack hardware-software system for executing many-photon quantum circuit operations using integrated nanophotonics: a programmable chip, operating at room temperature and interfaced with a fully automated control system. The system enables remote users to execute quantum algorithms that require up to eight modes of strongly squeezed vacuum initialized as two-mode squeezed states in single temporal modes, a fully general and programmable four-mode interferometer, and photon number-resolving readout on all outputs. Detection of multi-photon events with photon numbers and rates exceeding any previous programmable quantum optical demonstration is made possible by strong squeezing and high sampling rates. We verify the non-classicality of the device output, and use the platform to carry out proof-of-principle demonstrations of three quantum algorithms: Gaussian boson sampling, molecular vibronic spectra and graph similarity8. These demonstrations validate the platform as a launchpad for scaling photonic technologies for quantum information processing.

The clinical atlas of cardiomyopathies: data from the prospective DZHK TORCH study

Introduction

Cardiomyopathies (CMPs) are leading causes of heart failure (HF) and sudden cardiac death (SCD). Comparative data of the multiple cardiomyopathy forms are largely missing. The TranslatiOnal Registry for CardiomyopatHies (TORCH) is the largest prospective multicentre CMP registry world-wide. Enrolled patients are comprehensively phenotyped by clinical examinations, state-of-the-art imaging, and molecular investigations. In this study, we present the baseline and 1-year follow-up data.

Methods

TORCH is a national, prospective, multicentre registry within the German Centre for Cardiovascular Research (DZHK) and includes 2300 patients with non-ischemic (primary and secondary) CMP from 20 centres. The minimum follow up was one year. The DZHK-wide harmonization of datasets and SOPs ensure a high level of data quality and comparability across different CMP forms.

Results

Dilated cardiomyopathy (DCM) has the highest prevalence with 64% of all enrolled patients, followed by hypertrophic cardiomyopathy (HCM) with 16%. At baseline, patients with arrhythmogenic right ventricular cardiomyopathy (ARVC) were treated more often with ICD implantation and showed high rates of adequate ICD therapies (65.8%, p&lt;0.05 and 47.8%, p&lt;0.05, respectively). The prevalence of stroke or transient ischemic attack (TIA) was in multivariate analysis significantly higher (p&lt;0.05) in left ventricular non-compaction cardiomyopathy (LVNC, 14.9%), while atrial fibrillation was lower than in other cardiomyopathy forms. Patients with amyloidosis had the worst outcome (HR: 6; 95% CI: 2.5–14.5, P&lt;0.05) with annual mortality of &gt;15% and 12% receiving heart transplantation. In DCM, reverse remodelling with improvement of functional parameters and biomarkers was more often observed in idiopathic and inflammatory cases compared to familial ones. HCM patients had the most favourable outcome.

Conclusion and outlook

TORCH is the largest prospective study focusing on CMPs. We provided for the first time prospectively the clinical data of patients with diverse cardiomyopathies with outcome. Furthermore, comparing the different CMP forms on the clinical and molecular level will be an important step to enable translational research projects.

Funding Acknowledgement

Type of funding source: Public grant(s) – National budget only. Main funding source(s): German Centre for Cardiovascular Research (DZHK)

Correlations of changes in inflammatory factors, glucose and lipid metabolism indicators and adiponectin with alterations in intestinal flora in rats with coronary heart disease

OBJECTIVE

The aim of this study was to explore the correlations of changes in inflammatory factors, glucose and lipid metabolism indicators and adiponectin with alterations in intestinal flora in rats with coronary heart disease.

MATERIALS AND METHODS

A total of 30 male specific pathogen-free rats were randomly assigned into two groups, including: blank group (n=15) and coronary heart disease group (n=15). The rats in the coronary heart disease group were given high-fat diets and pituitrin to establish the model of coronary heart disease. Meanwhile, rats in the blank group were administered with an equal volume of double-distilled water. The alterations in the intestinal flora of rats were detected in the two groups, respectively. In addition, the changes in the levels of inflammatory factors, glucose and lipid metabolism indicators, adiponectin, creatine kinase (CK) and its isoenzyme, as well as troponin, were also examined.

RESULTS

Statistically, significant differences in the levels of glucose and lipid metabolism indicators low-density lipoprotein (LDL) (p=0.040), total cholesterol (TC) (p=0.039), high-density lipoprotein (HDL) (p=0.044), triglyceride (TG) (p=0.000) and blood glucose (p=0.046) were observed between the rats in the coronary heart disease group and blank group. The content of all the glucose and lipid metabolism indicators (except HDL) in coronary heart disease group was significantly higher than the blank group (p<0.05). The rats in the coronary heart disease group had evidently higher levels of CK (p=0.000) and its isoenzyme (p=0.019), as well as troponin (p=0.021), than those in the blank group. The level of serum adiponectin in rats in coronary heart disease group was distinctly lower than that in the blank group, showing statistically significant differences (p<0.05). Besides, the levels of the inflammatory factors interleukin (IL)-2 (p=0.011), transforming growth factor (TGF)-β (p=0.048), tumor necrosis factor-α (TNF-α) (p=0.025) and IL-6 (p=0.038) in rats in the coronary heart disease group were dramatically higher than those in blank group. Rats in coronary heart disease group had remarkably more Actinobacteria, Desulfovibrio, Aristipus and Escherichia coli in the intestine. Meanwhile, the abundance of Flavobacterium, Burkhofer and some probiotics increased significantly in the intestine of rats in blank group (p<0.05). The changes in the abundance of Actinobacteria, Desulfovibrio, Aristipus and Escherichia coli in the intestine of rats were probably correlated with increased levels of glucose and lipid metabolism indicators, inflammatory factors and adiponectin in coronary heart disease group. Moreover, the abundance of intestinal probiotics such as Bifidobacterium and Lactobacillus in rats in coronary heart disease group was notably lower than that in blank group (p<0.05). The decline in the abundance of such intestinal probiotics as Bifidobacterium and Lactobacillus was correlated with the changes in the levels of glucose and lipid metabolism indicators, inflammatory factors and adiponectin. In addition, decreased levels of probiotics weakened normal physiological functions of the intestine and promoted disease progression.

CONCLUSIONS

Inflammatory factors, glucose and lipid metabolism indicators and adiponectin have evident changes in rats with coronary heart disease, which may be correlated with the alterations in the intestinal flora.

Broadband quadrature-squeezed vacuum and nonclassical photon number correlations from a nanophotonic device

We report demonstrations of both quadrature-squeezed vacuum and photon number difference squeezing generated in an integrated nanophotonic device. Squeezed light is generated via strongly driven spontaneous four-wave mixing below threshold in silicon nitride microring resonators. The generated light is characterized with both homodyne detection and direct measurements of photon statistics using photon number-resolving transition-edge sensors. We measure 1.0(1) decibels of broadband quadrature squeezing (~4 decibels inferred on-chip) and 1.5(3) decibels of photon number difference squeezing (~7 decibels inferred on-chip). Nearly single temporal mode operation is achieved, with measured raw unheralded second-order correlations g ⁽²⁾ as high as 1.95(1). Multiphoton events of over 10 photons are directly detected with rates exceeding any previous quantum optical demonstration using integrated nanophotonics. These results will have an enabling impact on scaling continuous variable quantum technology.

Neuroimaging in Zoonotic Outbreaks Affecting the Central Nervous System: Are We Fighting the Last War?

When preparing for the coronavirus disease 2019 pandemic and its effects on the CNS, radiologists should be familiar with neuroimaging appearances in past zoonotic infectious disease outbreaks. Organisms that have crossed the species barrier from animals to humans include viruses such as Hendra, Nipah, Severe Acute Respiratory Syndrome, and influenza, as well as bacteria and others. Brain CT and MR imaging findings have included cortical abnormalities, microinfarction in the white matter, large-vessel occlusion, and features of meningitis. In particular, the high sensitivity of diffusion-weighted MR imaging in detecting intracranial abnormalities has been helpful in outbreaks. Although the coronaviruses causing the previous Severe Acute Respiratory Syndrome outbreak and the current coronavirus disease 19 pandemic are related, it is important to be aware of their similarities as well as potential differences. This review describes the neuroimaging appearances of selected zoonotic outbreaks so that neuroradiologists can better understand the current pandemic and potential future outbreaks.

A multi-omics supervised autoencoder for pan-cancer clinical outcome endpoints prediction

Background

With the rapid development of sequencing technologies, collecting diverse types of cancer omics data become more cost-effective. Many computational methods attempted to represent and fuse multiple omics into a comprehensive view of cancer. However, different types of omics are related and heterogeneous. Most of the existing methods do not consider the difference between omics, so the biological knowledge of individual omics may not be fully excavated. And for a given task (e.g. predicting overall survival), these methods prefer to use sample similarity or domain knowledge to learn a more reasonable representation of omics, but it’s not enough.

Methods

For the purpose of learning more useful representation for individual omics and fusing them to improve the prediction ability, we proposed an autoencoder-based method named MOSAE (Multi-omics Supervised Autoencoder). In our method, a specific autoencoder were designed for each omics according to their size of dimension to generate omics-specific representations. Then, a supervised autoencoder was constructed based on specific autoencoder by using labels to enforce each specific autoencoder to learn both omics-specific and task-specific representations. Finally, representations of different omics that generate from supervised autoencoders were fused in a traditional but powerful way, and the fused representation was used for subsequent predictive tasks.

Results

We applied our method over TCGA Pan-Cancer dataset to predict four different clinical outcome endpoints (OS, PFI, DFI, and DSS). Compared with traditional and state-of-the-art methods, MOSAE achieved better predictive performance. We also tested the effects of each improvement, which all have a positive effect on predictive performance.

Conclusions

Predicting clinical outcome endpoints are very important for precision medicine and personalized medicine. And multi-omics fusion is an effective way to solve this problem. MOSAE is a powerful multi-omics fusion method, which can generate both omics-specific and task-specific representation for given endpoint predictive tasks and improve the predictive performance.

Stimulated four-wave mixing in linearly uncoupled resonators

We experimentally demonstrate stimulated four-wave mixing in two linearly uncoupled integrated $ {{\rm Si}_3}{{\rm N}_4} $Si₃N₄ micro-resonators. In our structure, the resonance combs of each resonator can be tuned independently, with the energy transfer from one resonator to the other occurring in the presence of a nonlinear interaction. This method allows flexible and efficient on-chip control of the nonlinear interaction, and is readily applicable to other third-order nonlinear phenomena.

MiR-29a promotes osteogenic differentiation of mesenchymal stem cells via targeting HDAC4

OBJECTIVE

To investigate the role of miR-29a in regulating the differentiation mesenchymal stem cells into osteoblasts.

MATERIALS AND METHODS

For the first step, the changes of expression of miR-29a during the process of mesenchymal stem cells (MSCs) differentiation into osteoblast were detected. Then, we infected the MSCs with mimics or inhibitors of miR-29a to explore the roles of miR-29a in the differentiation. Further, the prediction and verification of the possible target genes of miR-29a were achieved by bioinformatics analysis and luciferase reporter assay.

RESULTS

MiR-29a was up-regulated during the process of MSCs differentiation into osteoblasts. Overexpression or inhibition of miR-29a using mimics or inhibitors had no significant effect on cell proliferation. Furthermore, the differentiation was enhanced when miR-29a was artificially overexpressed in vitro, whereas silencing of miR-29a attenuated this process. It was evidenced by alkaline phosphatase (ALP) staining, matrix mineralization, and increased expression of osteoblast-specific genes. Furthermore, we determined that the gene HDAC4 might be a direct target of miR-29a.

CONCLUSIONS

In the current study, miR-29a promotes osteogenesis via suppressing HDAC4, indicating that targeting miR-29a may be feasible in the management of osteoporosis.

P5547First results of TranslatiOnal Registry for CardiomyopatHies (TORCH)

Introduction

The cardiomyopathies (CMPs) are a diverse group of cardiac disorders and leading cause of heart failure (HF) and sudden cardiac death (SCD). Clinical courses of CMPs vary considerably even between patients with the same disease entity. The TranslatiOnal Registry for CardiomyopatHies (TORCH) is a comprehensive CMP registry that aims to provide a database and biomaterial bank for basic science and clinical research in this field. The long-term objective of this registry is to increase the understanding of disease pathomechanisms on the way to a better risk stratification as well as identification of new diagnostic and therapeutic approaches in CMP.

Methods

TORCH is a national, prospective, and multicentre registry within the German Centre for Cardiovascular Research (DZHK), which includes 2300 consecutive patients with non-ischemic (primary and secondary) CMP in 20 centres. The minimum follow up time is one year. The DZHK-wide harmonization of datasets and eCRFs (electronic case report form) were performed to ensure a high level of data quality across different study centres.

Results

Seventy percent of the enrolled patients are male. Idiopathic/familial dilated cardiomyopathy (DCM) holds the highest prevalence with 54%, followed by inflammatory DCM/myocarditis with a prevalence of 24%. Hypertrophic cardiomyopathy (HCM) is the third-most prevalent CMP in this registry (16%). Infrequent CMPs such as left ventricular non-compaction (LVNC), arrhythmogenic right ventricular cardiomyopathies (ARVC) are also represented in TORCH with a prevalence of 4% and 2% respectively. Major clinical findings are registered in TORCH. Atrial fibrillation was present with a high prevalence among all CMPs (22%-35%). The highest prevalence of stroke or TIA at baseline was reported in patients with LVNC (15.1%) and the lowest in those with amyloidosis (3.3%). Patients with ARVC had the highest number of ICD implantation and adequate ICD therapy (56.7%, p<0.05; 47.1%, p<0.05). Preliminary data analysis showed higher frequency of therapy refractory heart failure symptoms and worse outcome in patients with familial DCM in comparison to those with inflammatory or idiopathic DCM.

Conclusion and outlook

TORCH represents one of the largest cardiomyopathy registries in Europe. The patients are comprehensively phenotyped through clinical examinations, state-of-the-art imaging modalities, as well as molecular, genetic, and epigenetic investigations. This registry can help researchers design further studies investigating new diagnostic tools or therapeutic strategies in CMPs.

[Clinical analysis of 309 hospitalized children with pertussis-associated pneumonia]

Objective: To investigate the clinical characteristics of pertussis-associated pneumonia and analyze it's risk factors. Methods: Clinical data were taken from Shenzhen Children's Hospital with Bordetella pertussis infection and confirmed by culture or real-time polymerase chain reaction (PCR) of nasopharyngeal secretion from October 2013 to December 2015. Patients were divided into two groups, those with radiologically confirmed pneumonia in the course of their disease and those with not. Clinical data were retrospectively analyzed and compared. T test, Rank sum test or chi square test were used for comparison between groups. Risk factors were analyzed by unconditional Logistic regression analysis. Results: A total of 501 children hospitalized with Bordetella pertussis infection were included. Among them, 309 patients were diagnosed with pneumonia. The median age was 3 (2, 6) months. Symptoms were paroxysmal cough (n=252, 81.6%), tachypnea (n=69, 22.3%), and cyanosis (n=105, 34.0%). The time from onset of cough to radiologically confirmed pneumonia was between 1 and 66 days with a median of 9 (5.5, 15.0) days. The most common pathogen of coinfection was respiratory syncytial virus (RSV)(20 cases). Macrolides were used in 306 cases for (8.2±3.6) days. All cases showed significant improvement. There were more male children (62.1% (192/309) vs. 50.3% (95/189) , χ(2)=6.768, P=0.009), and more instances of comorbidities (13.3% (41/309) vs.5.8% (11/189) , χ(2)=6.957, P=0.008) in the pneumonia group than in the other. The age was younger (3 (2,6) vs.4 (2,6) months, Z=32.91, P=0.000) in pneumonia group than in the other. Male sex, younger age, and underlying disease were independent risk factors for pertussis-associated pneumonia (OR=1.648, 1.486, 2.695, P=0.008, 0.036, 0.005). Conclusions: Pneumonia, as a complication of pertussis, is very easy to see in hospitalized children. The duration of hospitalization is extensive. It is more likely to happen in children who are male, young, and having underlying diseases. Pneumonia is easy to occur in the first 2 weeks of the course of disease.