Generative adversarial network-created brain SPECTs of cerebral ischemia are indistinguishable to scans from real patients

Deep convolutional generative adversarial networks (GAN) allow for creating images from existing databases. We applied a modified light-weight GAN (FastGAN) algorithm to cerebral blood flow SPECTs and aimed to evaluate whether this technology can generate created images close to real patients. Investigating three anatomical levels (cerebellum, CER; basal ganglia, BG; cortex, COR), 551 normal (248 CER, 174 BG, 129 COR) and 387 pathological brain SPECTs using N-isopropyl p-I-123-iodoamphetamine (I-123-IMP) were included. For the latter scans, cerebral ischemic disease comprised 291 uni- (66 CER, 116 BG, 109 COR) and 96 bilateral defect patterns (44 BG, 52 COR). Our model was trained using a three-compartment anatomical input (dataset 'A'; including CER, BG, and COR), while for dataset 'B', only one anatomical region (COR) was included. Quantitative analyses provided mean counts (MC) and left/right (LR) hemisphere ratios, which were then compared to quantification from real images. For MC, 'B' was significantly different for normal and bilateral defect patterns (P = 0.08) reached significance relative to images of real patients. With a minimum of only three anatomical compartments serving as stimuli, created cerebral SPECTs are indistinguishable to images from real patients. The applied FastGAN algorithm may allow to provide sufficient scan numbers in various clinical scenarios, e.g., for "data-hungry" deep learning technologies or in the context of orphan diseases

15-Deoxy-Δ12,14 Prostaglandin J2 Reduces the Formation of Atherosclerotic Lesions in Apolipoprotein E Knockout Mice

AIM: 15-deoxy-Δ¹²,¹⁴ prostaglandin J₂ (15d-PGJ₂) is a ligand of peroxisome proliferator-activated receptor γ (PPARγ) having diverse effects such as the differentiation of adipocytes and atherosclerotic lesion formation. 15d-PGJ₂ can also regulate the expression of inflammatory mediators on immune cells independent of PPARγ. We investigated the antiatherogenic effect of 15d-PGJ₂. METHODS: We fed apolipoprotein (apo) E-deficient female mice a Western-type diet from 8 to 16 wk of age and administered 1 mg/kg/day 15d-PGJ₂ intraperitoneally. We measured atherosclerotic lesions at the aortic root, and examined the expression of macrophage and inflammatory atherosclerotic molecules by immunohistochemical and real-time PCR in the lesion. RESULTS: Atherosclerotic lesion formation was reduced in apo E-null mice treated with 15d-PGJ₂, as compared to in the controls. Immunohistochemical and real-time PCR analyses showed that the expression of MCP-1, TNF-α, and MMP-9 in atherosclerotic lesions was significantly decreased in 15d-PGJ₂ treated mice. The 15d-PGJ₂ also reduced the expression of macrophages and RelA mRNA in atherosclerotic lesions. CONCLUSION: This is the first report 15d-PGJ₂, a natural PPARγ agonist, can improve atherosclerotic lesions in vivo. 15d-PGJ₂ may be a beneficial therapeutic agent for atherosclerosis

CNVs in Three Psychiatric Disorders

BACKGROUND: We aimed to determine the similarities and differences in the roles of genic and regulatory copy number variations (CNVs) in bipolar disorder (BD), schizophrenia (SCZ), and autism spectrum disorder (ASD). METHODS: Based on high-resolution CNV data from 8708 Japanese samples, we performed to our knowledge the largest cross-disorder analysis of genic and regulatory CNVs in BD, SCZ, and ASD. RESULTS: In genic CNVs, we found an increased burden of smaller (500 kb) exonic CNVs in SCZ/ASD. Pathogenic CNVs linked to neurodevelopmental disorders were significantly associated with the risk for each disorder, but BD and SCZ/ASD differed in terms of the effect size (smaller in BD) and subtype distribution of CNVs linked to neurodevelopmental disorders. We identified 3 synaptic genes (DLG2, PCDH15, and ASTN2) as risk factors for BD. Whereas gene set analysis showed that BD-associated pathways were restricted to chromatin biology, SCZ and ASD involved more extensive and similar pathways. Nevertheless, a correlation analysis of gene set results indicated weak but significant pathway similarities between BD and SCZ or ASD (r = 0.25–0.31). In SCZ and ASD, but not BD, CNVs were significantly enriched in enhancers and promoters in brain tissue. CONCLUSIONS: BD and SCZ/ASD differ in terms of CNV burden, characteristics of CNVs linked to neurodevelopmental disorders, and regulatory CNVs. On the other hand, they have shared molecular mechanisms, including chromatin biology. The BD risk genes identified here could provide insight into the pathogenesis of BD