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New painkiller stronger than morphine and not addictive

03.09.2018

In the US, a new painkiller has been developed that is not only stronger than morphine and its derivatives, but, unlike them, does not cause any dependence.

The device, so far called AT-121, was developed in an attempt to find a molecule that could act on two key groups of receptors in the brain: mu-opioid receptors, which are usually the main target of opioids and standard analgesics, and nociceptin receptors, which regulate various activities. brain, including feelings of addiction and chemical dependency.

In theory, an agonist that successfully binds to both receptors can provide relief from pain, but without any dependence.

The first results are encouraging. In tests on rhesus monkeys, AT-121 was able to relieve pain, just like morphine, but at a dosage that was 100 times lower.

At the same time, he not only did not cause dependence, but also reduced it in those animals that suffered from addiction to the opioid oxycodone. That is, he can help not only reduce pain, but also fight addiction.

Of course, it remains to be seen whether this substance affects humans as well as monkeys. There is no guarantee, but pharmacologists are confident that future research will be successful.

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The robot chooses fruit 19.03.2013

The unusual software was developed by Indian specialists Shiv Ram Dubey and Anand Singh Jalal. Their automated image processing system very quickly determines the type of fruit, such as distinguishing between oranges and lemons, and also distinguishes varieties of pears, melons, apples and plums. Such a system can be used to sort and pack various fruits and vegetables, as well as to improve the convenience of staff and shoppers.

The system demonstrates a very high accuracy of fruit recognition - up to 99%, regardless of the lighting. This figure was achieved thanks to a very fast comparison of a photograph of an unknown object with a database of all known fruits and vegetables. During the testing of the system, the Indians took photographs of 15 different fruits and vegetables from different angles. Thus, the system was trained to recognize an apple, onion, potato, orange, lime, kiwi, melon, etc. Then the system was offered an unknown fruit or vegetable, the photo of which was compared with the database. Recognition accuracy has reached almost 100%, while no sophisticated equipment for machine sorting is needed - only a video camera and a computer.

The developers are currently working on expanding the capabilities of their algorithm. It is planned that the software will not only be able to distinguish between fruits and vegetables, but also detect damage like mold, rot, etc.

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