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SUMMARY The molecular basis of the earliest neuronal changes that lead to Alzheimer’s disease (AD) is unclear. Here, we analyze neural cells derived from sporadic AD (SAD), APOE4 gene-edited and control induced pluripotent stem cells (iPSCs). We observe major differences in iPSC-derived neural progenitor (NP) cells and neurons in gene networks related to neuronal differentiation, neurogenesis, and synaptic transmission. The iPSC-derived neural cells from SAD patients exhibit accelerated neural differentiation and reduced progenitor cell renewal. Moreover, a similar phenotype appears in NP cells and cerebral organoids derived from APOE4 iPSCs. Impaired function of the transcriptional repressor REST is strongly implicated in the altered transcriptome and differentiation state. SAD and APOE4 expression result in reduced REST nuclear translocation and chromatin binding, and disruption of the nuclear lamina. Thus, dysregulation of neural gene networks may set in motion the pathologic cascade that leads to AD.

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BedroomsLiving RoomsOffices Bathrooms Figure 1. Synthetic virtual scenes generated by our method. Our model can generate a large variety of such scenes, as well as complete partial scenes, in under two seconds per scene. This performance is enabled by a pipeline of multiple deep convolutional generative models which analyze a top-down representation of the scene. AbstractWe present a new, fast and flexible pipeline for indoor scene synthesis that is based on deep convolutional generative models. Our method operates on a top-down image-based representation, and inserts objects iteratively into the scene by predicting their category, location, orientation and size with separate neural network modules. Our pipeline naturally supports automatic completion of partial scenes, as well as synthesis of complete scenes. Our method is significantly faster than the previous image-based method and generates result that outperforms state-of-the-art generative scene models in terms of faithfulness to training data and perceived visual quality.

Accumulation of N-terminal fragments of mutant huntingtin (mHTT) in the cytoplasm, nuclei and axons of neurons is a hallmark of Huntington's disease (HD), although how these fragments negatively impact neurons remains unclear. We followed the distribution of mHTT in the striata of transgenic R6/2-J2 HD mice as their motor function declined. The fraction of cells with diffuse, perinuclear or intranuclear mHTT changed in parallel with decreasing motor function. In transgenic mice, medium spiny neurons (MSNs) that exhibited perinuclear inclusions expressed cell-cycle markers typically not seen in the striata of normal mice, and these cells are preferentially lost as disease progresses. Electron microscopy reveals that perinuclear inclusions disrupt the nuclear envelope. The progression of perinuclear inclusions being accompanied by cell-cycle activation and culminating in cell death was also observed in 1° cortical neurons. These observations provide a strong correlation between the subcellular location of mHTT, disruption of the nucleus, re-entry into the cell-cycle and eventual neuronal death. They also highlight the fact that the subcellular distribution of mHTT is highly dynamic such that the distribution of mHTT observed depends greatly on the stage of the disease being examined.

Dynamic measurements of infused stem cells generally require animal euthanasia for single-time-point determinations of engraftment. In this study, we used a triple-fusion reporter system for multimodal imaging to monitor human mesenchymal stem cell (hMSC) transplants. Methods: hMSCs were transduced with a triple-fusion reporter, fluc-mrfp-ttk (encoding firefly luciferase, monomeric red fluorescent protein, and truncated herpes simplex virus type 1 sr39 thymidine kinase) by use of a lentiviral vector. Transduced cells were assayed in vitro for the expression of each functional component of the triple-fusion reporter. Transduced and control hMSCs were compared for their potential to differentiate into bone, cartilage, and fat. hMSCs expressing the reporter were then loaded into porous, fibronectin-coated ceramic cubes and subcutaneously implanted into NOD-SCID mice along with cubes that were loaded with wild-type hMSCs and empty cubes. Mice were imaged repeatedly over 3 mo by bioluminescence imaging (BLI), and selected animals underwent CT and PET imaging. Results: Osteogenic, adipogenic, and chondrogenic potential assays revealed retained differentiation potentials between transduced and wild-type hMSCs. Signals from the cubes loaded with reporter-transduced hMSCs were visible by BLI over 3 mo. There was no signal from the empty or wild-type hMSC-loaded control cubes. PET data provided confirmation of the quantitative estimation of the number of cells at one spot (cube). Cubes were removed from some animals, and histologic evaluations showed bone formation in cubes loaded with either reporter-transduced or wild-type hMSCs, whereas empty controls were negative for bone formation. Conclusion: The triple-fusion reporter approach resulted in a reliable method of labeling stem cells for investigation in small-animal models by use of both BLI and small-animal PET imaging. It has the potential for translation into future human studies with clinical PET.

Mouse models for autosomal-dominant polycystic kidney disease (ADPKD), derived from homozygous targeted disruption of Pkd1 gene, generally die in utero or perinatally because of systemic defects. We introduced a loxP site and a loxP-flanked mc1-neo cassette into introns 30 and 34, respectively, of the Pkd1 locus to generate a conditional, targeted mutation. Significantly, before excision of the floxed exons and mc1-neo from the targeted locus by Cre recombinase, mice homozygous for the targeted allele appeared normal at birth but developed polycystic kidney disease with a slower progression than that of Pkd-null mice. Further, the homozygotes continued to produce low levels of full-length Pkd1-encoded protein, suggesting that slight Pkd1 expression is sufficient for renal cyst formation in ADPKD. In this viable model, up-regulation of heparin-binding epidermal growth factor-like growth factor accompanied increased epidermal growth factor receptor signaling, which may be involved in abnormal proliferation of the cyst-lining epithelia. Increased apoptosis in cyst epithelia was only observed in the later period that correlated with the cyst regression. Abnormalities in Na ؉ /K ؉ -ATPase, aquaporin-2, and vasopressin V2 receptor expression were also identified. This mouse model may be suitable for further studies of progression and therapeutic interventions of ADPKD.

Recent past has seen a lot of developments in the field of image-based dietary assessment. Food image classification and recognition are crucial steps for dietary assessment. In the last couple of years, advancements in the deep learning and convolutional neural networks proved to be a boon for the image classification and recognition tasks, specifically for food recognition because of the wide variety of food items. In this paper, we report experiments on food/non-food classification and food recognition using a GoogLeNet model based on deep convolutional neural network. The experiments were conducted on two image datasets created by our own, where the images were collected from existing image datasets, social media, and imaging devices such as smart phone and wearable cameras. Experimental results show a high accuracy of 99.2% on the food/non-food classification and 83.6% on the food category recognition.