We should not let concerns about overpopulation hold us back from developing biotechnology to treat age-related diseases. Compassion is the reason that trumps any other argument against developing this technology.
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Category: biotech/medical – Page 2,714
Is it safe to remove senescent cells? This is a common question we hear when talking about senolytic therapies designed to remove these problem cells that accumulate with age and play havoc with the body and its ability to repair.
Mantas from CellAge answers a question from one of our readers about senescent cell removal therapy. The removal of senescent cells has become a very hot topic this year with numerous experiments showing positive results for health and disease mitigation.
Check out the campaign at Lifespan.io and donate to a better healthier future:
https://www.lifespan.io/campaigns/cellage-targeting-senescen…c-biology/
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What humans will look like in 100 years: Expert reveals the genetically modified bodies we’ll need to survive
- Harvard researchers says to survive the next extinction we must leave the Earth
- But to live on other planets we will need to genetically modify our organs
- Experts have previously speculated how humanity will look in 1,000 years’ time
- Video describes scenario in which bodies are part-human part-machine
By Harry Pettit For Mailonline
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More progress in treating MS.
In findings that show the effectiveness of a new strategy for treating multiple sclerosis (MS), researchers are reporting positive results from three large, international, multicenter Phase III clinical trials of the investigational drug ocrelizumab (brand name Ocrevus) in both relapsing multiple sclerosis (RMS) and primary progressive multiple sclerosis (PPMS).
The trial results are published online on Dec. 21, 2016, in The New England Journal of Medicine (NEJM), and are discussed in an accompanying editorial.
In multiple sclerosis, the immune system attacks the body, making it a so-called autoimmune disease. To date, all MS drugs have targeted the immune system’s T cells. Ocrelizumab, in contrast, depletes populations of the immune system’s B cells.
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Humans’ relationship with technology is growing ever-more intimate. In a sense, we have already become cyborgs, tethered to our external electronic devices, outsourcing to them our memories, our sense of direction, our socializing, our lives. But, if the past year’s technological advancements are any indication, our relationship with technology is going to get a whole lot closer. Technology could one day soon become regularly integrated with our biology to manage disease and augment human ability. Here were some of the biggest breakthroughs of the past year on the cyborg front.
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Summary:
- Clinical trial failure rates for small molecules in oncology exceed 94% for molecules previously tested in animals and the costs to bring a new drug to market exceed $2.5 billion
- There are around 2,000 drugs approved for therapeutic use by the regulators with very few providing complete cures
- Advances in deep learning demonstrated superhuman accuracy in many areas and are expected to transform industries, where large amounts of training data is available
- Generative Adversarial Networks (GANs), a new technology introduced in 2014 represent the “cutting edge” in artificial intelligence, where new images, videos and voice can be produced by the deep neural networks on demand
- Here for the first time we demonstrate the application of Generative Adversarial Autoencoders (AAEs), a new type of GAN, for generation of molecular fingerprints of molecules that kill cancer cells at specific concentrations
- This work is the proof of concept, which opens the door for the cornucopia of meaningful molecular leads created according to the given criteria
- The study was published in Oncotarget and the open-access manuscript is available in the Advance Open Publications section
- Authors speculate that in 2017 the conservative pharmaceutical industry will experience a transformation similar to the automotive industry with deep learned drug discovery pipelines integrated into the many business processes
- The extension of this work will be presented at the “4th Annual R&D Data Intelligence Leaders Forum” in Basel, Switzerland, Jan 24-26th, 2017
Thursday, 22nd of December Baltimore, MD — Scientists at the Pharmaceutical Artificial Intelligence (pharma. AI) group of Insilico Medicine, Inc, today announced the publication of a seminal paper demonstrating the application of generative adversarial autoencoders (AAEs) to generating new molecular fingerprints on demand. The study was published in Oncotarget on 22nd of December, 2016. The study represents the proof of concept for applying Generative Adversarial Networks (GANs) to drug discovery. The authors significantly extended this model to generate new leads according to multiple requested characteristics and plan to launch a comprehensive GAN-based drug discovery engine producing promising therapeutic treatments to significantly accelerate pharmaceutical R&D and improve the success rates in clinical trials.
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Cognitive training interventions are a promising approach to mitigate cognitive deficits common in aging and, ultimately, to improve functioning in older adults. Baseline neural factors, such as properties of brain networks, may predict training outcomes and can be used to improve the effectiveness of interventions. Here, we investigated the relationship between baseline brain network modularity, a measure of the segregation of brain sub-networks, and training-related gains in cognition in older adults. We found that older adults with more segregated brain sub-networks (i.e., more modular networks) at baseline exhibited greater training improvements in the ability to synthesize complex information. Further, the relationship between modularity and training-related gains was more pronounced in sub-networks mediating “associative” functions compared with those involved in sensory-motor processing. These results suggest that assessments of brain networks can be used as a biomarker to guide the implementation of cognitive interventions and improve outcomes across individuals. More broadly, these findings also suggest that properties of brain networks may capture individual differences in learning and neuroplasticity.
Trail Registration: ClinicalTrials.gov, NCT#00977418
Citation: Gallen CL, Baniqued PL, Chapman SB, Aslan S, Keebler M, Didehbani N, et al. (2016) Modular Brain Network Organization Predicts Response to Cognitive Training in Older Adults. PLoS ONE 11(12): e0169015. doi:10.1371/journal.pone.0169015
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Graphene has already proven its importance to brain implants as well as other Synbio technology.
Brain cell culture. Left: Normal astrocyte brain cell; Right: cancerous Glioblastoma Multiforme (GBM) version, imaged by Raman spectrography. (credit: B. Keisham et al./ACS Appl. Mater. Interfaces)
By interfacing brain cells with graphene, University of Illinois at Chicago researchers have differentiated a single hyperactive Glioblastoma Multiforme cancerous astrocyte cell from a normal cell in the lab — pointing the way to developing a simple, noninvasive tool for early cancer diagnosis.
In the study, reported in the journal ACS Applied Materials & Interfaces, the researchers looked at lab-cultured human brain astrocyte cells taken from a mouse model. They compared normal astrocytes to their cancerous counterpart, highly malignant brain tumor glioblastoma multiforme.
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