Self-supervised anomaly detection, staging and segmentation for retinal images.

Unsupervised anomaly detection (UAD) is to detect anomalies through learning the distribution of normal data without labels and therefore has a wide application in medical images by alleviating the burden of collecting annotated medical data. Current UAD methods mostly learn the normal data by the reconstruction of the original input, but often lack the consideration of any prior information that has semantic meanings. In this paper, we first propose a universal unsupervised anomaly detection framework SSL-AnoVAE, which utilizes a self-supervised learning (SSL) module for providing more fine-grained semantics depending on the to-be detected anomalies in the retinal images. We also explore the relationship between the data transformation adopted in the SSL module and the quality of anomaly detection for retinal images. Moreover, to take full advantage of the proposed SSL-AnoVAE and apply towards clinical usages for computer-aided diagnosis of retinal-related diseases, we further propose to stage and segment the anomalies in retinal images detected by SSL-AnoVAE in an unsupervised manner. Experimental results demonstrate the effectiveness of our proposed method for unsupervised anomaly detection, staging and segmentation on both retinal optical coherence tomography images and color fundus photograph images.

The Length and Distribution of Plasma Cell-Free DNA Fragments in Stroke Patients.

A number of studies have shown that plasma cell-free DNA is closely related to the risk of stroke, but the fragmentation status of plasma cell-free DNA and its clinical application value in ischemic stroke are still unclear. In this study, 48 patients with new ischemic stroke and 20 healthy subjects were enrolled. The second-generation high-throughput sequencing technique was used to study the plasma cell-free fragment length and regional distribution of the subjects. As noted in our results, the ratio of plasma cell-free DNA fragments in the disease group was significantly greater than that of the healthy group in the 300-400 bp range; conversely for fragments at the 75-250 bp range, the ratio of plasma cell-free DNA fragments in the patient group was apparently lower than that of the healthy group. In-depth analysis of the proportion of fragments distributed on each component of the genome was carried out. Our results recorded that the plasma cell-free DNA fragments in the disease group were inclined to the EXON, CpG islands, and ALU regions in contrast to that of the healthy group. In particular, fragments within the 300-400 bp range of the disease group were enrichment in the regions of EXON, INTRON, INTERGENIC, LINE, Fragile, ALU, and CpG islands. In summary, our findings suggested that the intracellular DNA degradation profiles could be applied to distinguish the stroke group and the healthy group, which provided a theoretical basis for the clinical diagnosis and prognosis of stroke by profiling the characteristic of plasma cell-free DNA fragments.

Reliable multiplex sequencing with rare index mis-assignment on DNB-based NGS platform.

BACKGROUND: Massively-parallel-sequencing, coupled with sample multiplexing, has made genetic tests broadly affordable. However, intractable index mis-assignments (commonly exceeds 1%) were repeatedly reported on some widely used sequencing platforms. RESULTS: Here, we investigated this quality issue on BGI sequencers using three library preparation methods: whole genome sequencing (WGS) with PCR, PCR-free WGS, and two-step targeted PCR. BGI's sequencers utilize a unique DNA nanoball (DNB) technology which uses rolling circle replication for DNA-nanoball preparation; this linear amplification is PCR free and can avoid error accumulation. We demonstrated that single index mis-assignment from free indexed oligos occurs at a rate of one in 36 million reads, suggesting virtually no index hopping during DNB creation and arraying. Furthermore, the DNB-based NGS libraries have achieved an unprecedentedly low sample-to-sample mis-assignment rate of 0.0001 to 0.0004% under recommended procedures. CONCLUSIONS: Single indexing with DNB technology provides a simple but effective method for sensitive genetic assays with large sample numbers.

Heteroplasmy and Copy Number Variations of Mitochondria in 88 Hepatocellular Carcinoma Individuals.

Hepatocellular carcinoma (HCC) is the third leading cause of cancer mortality worldwide. In this study, we had analysed the copy number variations and heteroplasmic mutations of mitochondria (MT) in 88 HCC individuals. The average copy number of MT genome in normal samples was significantly greater than that in tumor samples. Overall, the number of heteroplasmic mutations in 88 tumor and their matched normal samples were 241 and 173, respectively. There was higher positive ratio of heteroplasmic mutations in tumor samples (86%) than normal samples (73%). Worthwhile mention, ND1 gene harbored greater mutation frequency and more nonsynonymous mutations in tumor samples. Interestingly, 202 tumor-specific heteroplasmic mutations were detected. Moreover, ND1, ND3, ND4, ND5 and ND6 genes had higher ratio of nonsynonymous versus synonymous mutations in tumor-specific heteroplasmic mutations. It might suggest that the disorder of NADH dehydrogenase (complex I) resulted by heteroplasmic mutations may have close relation with tumorigenesis of hepatocellular carcinoma. This study provided theoretical basis for further understanding mechanism of tumorigenesis from the perspective of mitochondrial heteroplasmic mutations.

The mitochondrial genome of the winter stonefly Apteroperla tikumana (Plecoptera, Capniidae).

The mitochondrial genome of Apteroperla tikumana was assembled from transcriptome using SOAPdenovo-Trans. A nearly complete mitogenome, 15 564 bp in length, was obtained, including 13 protein-coding genes, two ribosomal RNA genes, and 22 transfer RNA genes. The base composition is A (34.21%), T (32.29%), C (19.86%), and G (13.64%). A phylogram was reconstructed using the mitogenomes of A. tikumana and its relatives using the distance method (neighbor joining, NJ). This mitogenome will assist a variety of biodiversity researches, especially in taxonomy and phylogeny of stoneflies.