A Novel Application of Image-to-Image Translation: Chromosome Straightening Framework by Learning from a Single Image

In medical imaging, chromosome straightening plays a significant role in the pathological study of chromosomes and in the development of cytogenetic maps. Whereas different approaches exist for the straightening task, typically geometric algorithms are used whose outputs are characterized by jagged edges or fragments with discontinued banding patterns. To address the flaws in the geometric algorithms, we propose a novel framework based on image-to-image translation to learn a pertinent mapping dependence for synthesizing straightened chromosomes with uninterrupted banding patterns and preserved details. In addition, to avoid the pitfall of deficient input chromosomes, we construct an augmented dataset using only one single curved chromosome image for training models. Based on this framework, we apply two popular image-to-image translation architectures, U-shape networks and conditional generative adversarial networks, to assess its efficacy. Experiments on a dataset comprised of 642 real-world chromosomes demonstrate the superiority of our framework, as compared to the geometric method in straightening performance, by rendering realistic and continued chromosome details. Furthermore, our straightened results improve the chromosome classification by 0.98%-1.39% mean accuracy.Comment: This work has been accepted by CISP-BMEI202

Phosphorylation of AQP4 by LRRK2 R1441G impairs glymphatic clearance of IFNγ and aggravates dopaminergic neurodegeneration

Abstract Aquaporin-4 (AQP4) is essential for normal functioning of the brain’s glymphatic system. Impaired glymphatic function is associated with neuroinflammation. Recent clinical evidence suggests the involvement of glymphatic dysfunction in LRRK2-associated Parkinson’s disease (PD); however, the precise mechanism remains unclear. The pro-inflammatory cytokine interferon (IFN) γ interacts with LRRK2 to induce neuroinflammation. Therefore, we examined the AQP4-dependent glymphatic system’s role in IFNγ-mediated neuroinflammation in LRRK2-associated PD. We found that LRRK2 interacts with and phosphorylates AQP4 in vitro and in vivo. AQP4 phosphorylation by LRRK2 R1441G induced AQP4 depolarization and disrupted glymphatic IFNγ clearance. Exogeneous IFNγ significantly increased astrocyte expression of IFNγ receptor, amplified AQP4 depolarization, and exacerbated neuroinflammation in R1441G transgenic mice. Conversely, inhibiting LRRK2 restored AQP4 polarity, improved glymphatic function, and reduced IFNγ-mediated neuroinflammation and dopaminergic neurodegeneration. Our findings establish a link between LRRK2-mediated AQP4 phosphorylation and IFNγ-mediated neuroinflammation in LRRK2-associated PD, guiding the development of LRRK2 targeting therapy

Precise Antibody-Independent m6A Identification via 4SedTTP-Involved and FTO-Assisted Strategy at Single-Nucleotide Resolution

Innovative detection techniques to achieve precise m6A distribution within mammalian transcriptome can advance our understanding of its biological functions. We specifically introduced the atom-specific replacement of oxygen with progressively larger atoms (sulfur and selenium) at 4-position of deoxythymidine triphosphate to weaken its ability to base pair with m6A, while maintaining A-T* base pair virtually the same as the natural one. 4SedTTP turned out to be an outstanding candidate that endowed m6A with a specific signature of RT truncation, thereby making this “RT-silent” modification detectable with the assistance of m6A demethylase FTO through next-generation sequencing. This antibody-independent, 4SedTTP-involved and FTO-assisted strategy is applicable in m6A identification, even for two closely gathered m6A sites, within an unknown region at single-nucleotide resolution