Multi-modality cardiac image computing: a survey

Multi-modality cardiac imaging plays a key role in the management of patients with cardiovascular diseases. It allows a combination of complementary anatomical, morphological and functional information, increases diagnosis accuracy, and improves the efficacy of cardiovascular interventions and clinical outcomes. Fully-automated processing and quantitative analysis of multi-modality cardiac images could have a direct impact on clinical research and evidence-based patient management. However, these require overcoming significant challenges including inter-modality misalignment and finding optimal methods to integrate information from different modalities. This paper aims to provide a comprehensive review of multi-modality imaging in cardiology, the computing methods, the validation strategies, the related clinical workflows and future perspectives. For the computing methodologies, we have a favored focus on the three tasks, i.e., registration, fusion and segmentation, which generally involve multi-modality imaging data, either combining information from different modalities or transferring information across modalities. The review highlights that multi-modality cardiac imaging data has the potential of wide applicability in the clinic, such as trans-aortic valve implantation guidance, myocardial viability assessment, and catheter ablation therapy and its patient selection. Nevertheless, many challenges remain unsolved, such as missing modality, modality selection, combination of imaging and non-imaging data, and uniform analysis and representation of different modalities. There is also work to do in defining how the well-developed techniques fit in clinical workflows and how much additional and relevant information they introduce. These problems are likely to continue to be an active field of research and the questions to be answered in the future

Bovine serum albumin in saliva mediates grazing response in Leymus chinensis revealed by RNA sequencing

BACKGROUND: Sheepgrass (Leymus chinensis) is an important perennial forage grass across the Eurasian Steppe and is adaptable to various environmental conditions, but little is known about its molecular mechanism responding to grazing and BSA deposition. Because it has a large genome, RNA sequencing is expensive and impractical except for the next-generation sequencing (NGS) technology. RESULTS: In this study, NGS technology was employed to characterize de novo the transcriptome of sheepgrass after defoliation and grazing treatments and to identify differentially expressed genes (DEGs) responding to grazing and BSA deposition. We assembled more than 47 M high-quality reads into 120,426 contigs from seven sequenced libraries. Based on the assembled transcriptome, we detected 2,002 DEGs responding to BSA deposition during grazing. Enrichment analysis of Gene ontology (GO), EuKaryotic Orthologous Groups (KOG) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways revealed that the effects of grazing and BSA deposition involved more apoptosis and cell oxidative changes compared to defoliation. Analysis of DNA fragments, cell oxidative factors and the lengths of leaf scars after grazing provided physiological and morphological evidence that BSA deposition during grazing alters the oxidative and apoptotic status of cells. CONCLUSIONS: This research greatly enriches sheepgrass transcriptome resources and grazing-stress-related genes, helping us to better understand the molecular mechanism of grazing in sheepgrass. The grazing-stress-related genes and pathways will be a valuable resource for further gene-phenotype studies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2164-15-1126) contains supplementary material, which is available to authorized users

Selection of Ovine Oocytes by Brilliant Cresyl Blue Staining

Sheep oocytes derived from the ovaries collected from the slaughterhouse are often used for research on in vitro embryo production, animal cloning, transgenesis, embryonic stem cells, and other embryo biotechnology aspects. Improving the in vitro culture efficiency of oocytes can provide more materials for similar studies. Generally, determination of oocyte quality is mostly based on the layers of cumulus cells and cytoplasm or cytoplasm uniformity and colors. This requires considerable experience to better identify oocyte quality because of the intense subjectivity involved (Gordon (2003), Madison et al. (1992) and De Loos et al. (1992)). BCB staining is a function of glucose-6-phosphate dehydrogenase (G6PD) activity, an enzyme synthesized in developing oocytes, which decreases in activity with maturation. Therefore, unstained oocytes (BCB−) are high in G6PD activity, while the less mature oocytes stains are deep blue (BCB+) due to insuffcient G6PD activity to decolorize the BCB dye

Random Style Transfer based Domain Generalization Networks Integrating Shape and Spatial Information

Deep learning (DL)-based models have demonstrated good performance in medical image segmentation. However, the models trained on a known dataset often fail when performed on an unseen dataset collected from different centers, vendors and disease populations. In this work, we present a random style transfer network to tackle the domain generalization problem for multi-vendor and center cardiac image segmentation. Style transfer is used to generate training data with a wider distribution/ heterogeneity, namely domain augmentation. As the target domain could be unknown, we randomly generate a modality vector for the target modality in the style transfer stage, to simulate the domain shift for unknown domains. The model can be trained in a semi-supervised manner by simultaneously optimizing a supervised segmentation and an unsupervised style translation objective. Besides, the framework incorporates the spatial information and shape prior of the target by introducing two regularization terms. We evaluated the proposed framework on 40 subjects from the M\&Ms challenge2020, and obtained promising performance in the segmentation for data from unknown vendors and centers.Comment: 11 page

Single-Molecule Real-Time Transcript Sequencing Identified Flowering Regulatory Genes in Crocus Sativus

Background: Saffron crocus (Crocus sativus) is a valuable spice with medicinal uses in gynaecopathia and nervous system diseases. Identify flowering regulatory genes plays a vital role in increasing flower numbers, thereby resulting in high saffron yield. Results: Two full length transcriptome gene sets of flowering and non-flowering saffron crocus were established separately using the single-molecule real-time (SMRT) sequencing method. A total of sixteen SMRT cells generated 22.85 GB data and 75,351 full-length saffron crocus unigenes on the PacBio RS II panel and further obtained 79,028 SSRs, 72,603 lncRNAs and 25,400 alternative splicing (AS) events. Using an Illumina RNA-seq platform, an additional fifteen corms with different flower numbers were sequenced. Many differential expression unigenes (DEGs) were screened separately between flowering and matched non-flowering top buds with cold treatment (1677), flowering top buds of 20 g corms and non-flowering top buds of 6 g corms (1086), and flowering and matched nonflowering lateral buds (267). A total of 62 putative flower-related genes that played important roles in vernalization (VRNs), gibberellins (G3OX, G2OX), photoperiod (PHYB, TEM1, PIF4), autonomous (FCA) and age (SPLs) pathways were identified and a schematic representation of the flowering gene regulatory network in saffron crocus was reported for the first time. After validation by real-time qPCR in 30 samples, two novel genes, PB.20221.2 (p = 0.004, r = 0.52) and PB.38952.1 (p = 0.023, r = 0.41), showed significantly higher expression levels in flowering plants. Tissue distribution showed specifically high expression in flower organs and time course expression analysis suggested that the transcripts increasingly accumulated during the flower development period. Conclusions: Full-length transcriptomes of flowering and non-flowering saffron crocus were obtained using a combined NGS short-read and SMRT long-read sequencing approach. This report is the first to describe the flowering gene regulatory network of saffron crocus and establishes a reference full-length transcriptome for future studies on saffron crocus and other Iridaceae plants