Complex artificial organs could be created by 3D printing a mould of veins, arteries and capillaries in ice, casting that in organic material and then allowing the ice to melt away, resulting in a delicate, hollow network. This leaves a space for the intricate artificial blood vessels that are required to develop lab-grown internal organs. Researchers have been working on artificial organs for decades to help meet the high global demand for transplants of the likes of hearts, kidneys and livers. But creating the blood vessel networks needed to keep them alive is still a challenge. Existing techniques can grow artificial skin or ears, but any flesh or organ material dies off if more than 200 micrometres from a blood vessel, says Philip LeDuc at Carnegie Mellon University in Pennsylvania.

The rapid emergence of increasingly sophisticated'AI ' programs such as CHATgpt will profoundly impact our world in many ways. That will inevitably include Innovation, especially the front end. But will it ultimately help or hurt us? Better access to information should be a huge benefit, and my intuition was to dive in and take full advantage. I still think it has enormous upside, but I also think it needs to be treated with care.

Researchers from the Moscow Institute of Physics and Technology, Ivannikov Institute for System Programming, and the Harvard Medical School-affiliated Schepens Eye Research Institute have developed a neural network capable of recognizing retinal tissues during the process of their differentiation in a dish. Unlike humans, the algorithm achieves this without the need to modify cells, making the method suitable for growing retinal tissue for developing cell replacement therapies to treat blindness and conducting research into new drugs. The study was published in Frontiers in Cellular Neuroscience. In multicellular organisms, the cells making up different organs and tissues are not the same. They have distinct functions and properties, acquired in the course of development. They start out the same, as so-called stem cells, which have the potential to become any kind of cell the mature organism incorporates.

This would allow to expand the applications of the technology for multiple fields including the drug discovery and development of cell replacement therapies to treat blindness. In multicellular organisms, the cells making up different organs and tissues are not the same. They have distinct functions and properties, acquired in the course of development. They start out the same, as so-called stem cells, which have the potential to become any kind of cell the mature organism incorporates. They then undergo differentiation by producing proteins specific to certain tissues and organs. The most advanced technique for replicating tissue differentiation in vitro relies on 3D cell aggregates called organoids.

IMAGE: Researchers from the Moscow Institute of Physics and Technology, Ivannikov Institute for System Programming, and the Harvard Medical School-affiliated Schepens Eye Research Institute have developed a neural network capable of... view more Researchers from the Moscow Institute of Physics and Technology, Ivannikov Institute for System Programming, and the Harvard Medical School-affiliated Schepens Eye Research Institute have developed a neural network capable of recognizing retinal tissues during the process of their differentiation in a dish. Unlike humans, the algorithm achieves this without the need to modify cells, making the method suitable for growing retinal tissue for developing cell replacement therapies to treat blindness and conducting research into new drugs. The study was published in Frontiers in Cellular Neuroscience. In multicellular organisms, the cells making up different organs and tissues are not the same. They have distinct functions and properties, acquired in the course of development.

International Data Corp (IDC) projects that by 2024, two-thirds of employees in high-performing Forbes Global 2000 enterprises will move from static, siloed roles and processes to become part of dynamic, multi-disciplinary, outcome-focused reconfigurable teams. Factors such as the proliferation of network-connected devices, the adoption of cloud services, and the exponential rise in security threats have changed the nature of jobs and skills required. 'It's a work transformation that embraces human-machine collaboration, enables new employee skillsets and work experiences, and supports a rapidly changing workspace model independent of physical location or time of day'. The World Economic Forum estimate for 2020 is 44 zettabytes of data in the digital universe, which would mean approx 40 times more bytes than there are stars in the observable universe. Demand will be high for IT workers with an ability to analyse the dizzying amounts of data being generated given that data is the building block of technologies such as Machine Learning and Artificial Intelligence.