Stem Cells


#Artificialintelligence can predict the success of IVF embryos better than do...

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Science Daily explores the issue in more depth (4 July 2017): "However, because the artificial intelligence system is a technique which analyses the embryo through mathematical variables, it offers low subjectivity and high repeatability, making embryo classification more consistent. "Nevertheless," said Professor Rocha, "the artificial intelligence system must be based on learning from a human being -- that is, the experienced embryologists who set the standards of assessment to train the system."" See also EurekAlert (4 July 2017): "The system utilizes a sophisticated architecture of multi-class deep neural networks (DNNs) and DNN ensembles trained on thousands of samples of carefully selected cells of multiple classes: embryonic stem cells, induced pluripotent stem cells, progenitor stem cells, adult stem cells and adult cells to recognize the class and embryonic state of the sample, achieving high accuracy in simulations. The sample sets were augmented with carefully selected and manually curated data from public repositories coming from multiple experiments and generated on different platforms.


Machine learning predicts the look of stem cells

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The Allen Cell Explorer, produced by the Allen Institute for Cell Science in Seattle, Washington, includes a growing library of more than 6,000 pictures of induced pluripotent stem cells (iPS) -- key components of which glow thanks to fluorescent markers that highlight specific genes. Rick Horwitz, director of the Allen Institute for Cell Science, says that the institute's images may hasten progress in stem cell research, cancer research and drug development by revealing unexpected aspects of cellular structure. The Allen Institute's visual emphasis on stem cells dovetails with a number of efforts to catalogue other aspects of cells. Aviv Regev, a computational biologist at the Broad Institute in Cambridge, Massachusetts, who is working on the Human Cell Atlas, says that the Allen Cell Explorer complements her project by focusing on the look of cellular features as opposed to how genes, RNA and proteins interact within the cell.


Scientists Use Stem Cells To Create Functional Artificial Blood

International Business Times

In one new study, researchers created a mix of different types of blood stem cells that produced different kinds of human blood cells when transfused into mice, The Independent reported. This is an important step toward making artificial human blood, as doctors believe that figuring out a way to turn stem cells into blood artificially will eventually lead to this breakthrough. For example, in a study published in March, scientists in England were able to produce about 50,000 red blood cells by coaxing stem cells into transforming into red blood cells. Another problem that stands in our way of successfully making limitless artificial blood is the risk of these new blood cells becoming cancerous, The Independent reported.


Breakthrough reported in quest to make blood cells

The Japan Times

In separate experiments reported in Nature -- one with mice, the other transplanting human stem cells into mouse bone marrow -- researchers demonstrated techniques with the potential to produce all types of blood cells. Human embryonic stem cells -- generic cells which, as the embryo develops, gradually differentiate -- were first isolated in 1998. They began by inducing both embryonic stems cells and iPS to morph into a form of embryonic tissue that -- in a natural process -- gives rise to blood stem cells. Finally, they transplanted these human blood stem cells into the bone marrow of live mice.


Working brain circuitry grown in a lab dish for first time

Daily Mail

Scientists hope to use the mini-brains to watch in real time the triggers for epilepsy, when brain cells become hyperactive, and autism, where they are thought to form bad connections. Human skin cells are transformed into pluripotent stem cells, capable of becoming any part of the body, using four genes in a petri dish. Dr Selina Wray, Alzheimer's Research UK senior research fellow at UCL Institute of Neurology, said: 'This technology will provide researchers with insights into brain development and disease which have not previously been possible.' Human skin cells are transformed into pluripotent stem cells, capable of becoming any part of the body, using four genes in a petri dish.


Machine learning predicts the look of stem cells - PharmaVOICE

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The Allen Cell Explorer, produced by the Allen Institute for Cell Science in Seattle, Washington, includes a growing library of more than 6,000 pictures of induced pluripotent stem cells (iPS) -- key components of which glow thanks to fluorescent markers that highlight specific genes. Rick Horwitz, director of the Allen Institute for Cell Science, says that the institute's images may hasten progress in stem cell research, cancer research and drug development by revealing unexpected aspects of cellular structure. The Allen Institute's visual emphasis on stem cells dovetails with a number of efforts to catalogue other aspects of cells. Aviv Regev, a computational biologist at the Broad Institute in Cambridge, Massachusetts, who is working on the Human Cell Atlas, says that the Allen Cell Explorer complements her project by focusing on the look of cellular features as opposed to how genes, RNA and proteins interact within the cell.


AI Based 3D Stem Cell Image Prediction Could Help Cure Cancer

International Business Times

A new online catalogue made using artificial intelligence (AI) based prediction will have 6,000 different images predicting stem cell structures, which could make mapping a pattern of cells easier. The Allen Cell Explorer made by the Allen Institute for Cell Science in Seattle, Washington will have pictures of induced pluripotent stem cells (iPS), which will glow using fluorescent markers to highlight different genes.The visuals, which have been created using AI-based deep learning analysis and cell lines altered using gene editing tool Crispr will allow researchers to analyze the variations in the cell layouts, which could help cure diseases such as cancer. The catalogue was able to train its AI using gene editing -- reverting adult cells to stem cells and tagging genes, making cell structures grow so that their growth could be traced. Then, all that was needed to be done was training AI to track stem cell development and comparing it with real-world examples to correct any inconsistencies.


Machine learning predicts the look of stem cells

#artificialintelligence

The Allen Cell Explorer, produced by the Allen Institute for Cell Science in Seattle, Washington, includes a growing library of more than 6,000 pictures of induced pluripotent stem cells (iPS) -- key components of which glow thanks to fluorescent markers that highlight specific genes. Rick Horwitz, director of the Allen Institute for Cell Science, says that the institute's images may hasten progress in stem cell research, cancer research and drug development by revealing unexpected aspects of cellular structure. The Allen Institute's visual emphasis on stem cells dovetails with a number of efforts to catalogue other aspects of cells. Aviv Regev, a computational biologist at the Broad Institute in Cambridge, Massachusetts, who is working on the Human Cell Atlas, says that the Allen Cell Explorer complements her project by focusing on the look of cellular features as opposed to how genes, RNA and proteins interact within the cell.


AI predicts the layout of human stem cells

Engadget

The structures of stem cells can vary wildly, even if they're genetically identical -- and that could be critical to predicting the onset of diseases like cancer. That's where the Allen Institute wants to help: it's launching an online database, the Allen Cell Explorer, where deep learning AI predicts the layout of human stem cells. After reverting adult cells to stem cells, researchers tagged genes to make cell structures glow and track their layout. This helped identify a clear relationship between the locations of cell structures, making it possible to predict how a stem cell would develop.


Scientists create first artificial mouse 'embryo' from stem cells

The Japan Times

LONDON – Scientists in Britain have for the first time created a structure that resembles a mouse embryo using a 3D scaffold and two types of stem cells -- research that deepens understanding of the earliest stages of mammalian development. Publishing their results in the journal Science on Thursday, the team, based at Cambridge University, said that while the artificial embryo closely resembled the real thing, it would be unlikely to develop further into a healthy mouse fetus. Currently, human embryos for research are developed from surplus eggs donated through fertility clinics, but Zernicka-Goetz said it should in the future be possible to use the stem cells and scaffold technique to make artificial human embryos for study. The Cambridge team said they now think this was because these experiments used only one type of stem cells -- embryonic stem cells (ESCs) -- and did not allow for the fact that early embryo development requires different types of cells to coordinate closely with each other.