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Abstract Image quality assessment (IQA) has become a hot issue in the area of image processing, which aims to evaluate image quality automatically by a metric being consistent with subjective evaluation. The first stage of conventional IQA model design is the quality-aware feature selection. Taking advantages of early visual feature, Phase congruency (PC) operates in frequency domain to measure local structures such as edges, corners, lines, etc., by computing the local amplitudes and local energies in multiple scales. Conventional local PC features are calculated with log-Gabor-based filtrations in several orientations, and usually combined with other features for IQA model design. Generally, a directional filter is sensitive to the changes on specific direction, and insensitive to other directions. This leads to multi-directional calculation and much time consumption in practical applications. Recently, researchers suggested that spatially circular symmetric filters, such as gradient magnitude (GM) and Laplacian of Gaussian (LoG), are highly efficient quality features and hence have been widely used in various IQA model designs. With the odd-symmetric and even-symmetric properties of GM and LoG operators, the two features are a suitable pair for PC compositions and can be computed uniformly by a Gaussian function with one scale factor. In this regard, we propose to combine GM and LoG signals to construct a new PC model with non-directional property. With ability to catch different types of distortions, the proposed PC feature can be promoted to a full-reference IQA model simply with average pooling or standard deviation pooling, and shows state-of-the-art performance compared with existing methods. Furthermore, our proposed PC algorithm can take the place of conventional PC component in well-known FSIM metric, which achieves improved performance and spends less in computation cost. This study suggests that the proposed circular symmetric PC feature is a highly efficient quality feature and can be exclusively used in IQA model designs.

Parkinson's disease (PD) is the most common neurodegenerative movement disorder, characterized by the progressive loss of nigrostriatal dopaminergic neurons (DANs), involving the dysregulation of both neurons and glial cells. Cell type- and region-specific gene expression profiles can provide an effective source for revealing the mechanisms of PD. In this study, we adopted the RiboTag approach to obtain cell type (DAN, microglia, astrocytes)- and brain region (substantia nigra, caudate-putamen)-specific translatomes at an early stage in an MPTP-induced mouse model of PD. Through DAN-specific translatome analysis, the glycosphingolipid biosynthetic process was identified as a significantly downregulated pathway in the MPTP-treated mice. ST8Sia6, a key downregulated gene related to glycosphingolipid biosynthesis, was confirmed to be downregulated in nigral DANs from postmortem brains of patients with PD. Specific expression of ST8Sia6 in DANs exerts anti-inflammatory and neuroprotective effects in MPTP-treated mice. Through cell type (microglia vs. astrocyte) and brain region (substantia nigra vs. caudate-putamen) comparisons, nigral microglia showed the most intense immune responses. Microglia and astrocytes in the substantia nigra showed similar levels of activation in interferon-related pathways and interferon gamma (IFNG) was identified as the top upstream regulator in both cell types. This work highlights that the glycosphingolipid metabolism pathway in the DAN is involved in neuroinflammation and neurodegeneration in an MPTP mouse model of PD and provides a new data source for elucidating the pathogenesis of PD.