Can red sage protect against diabetic nephropathy?

(Natural News) Diabetic nephropathy, also known as diabetic kidney disease, is a serious complication that can cause chronic kidney disease and end-stage renal disease. This complication is said to be triggered by oxidative stress. Fortunately, researchers from China and Sri Lanka found that this complication can be attenuated with red sage (Salvia miltiorrhiza), or danshen in Chinese medicine, which possesses strong antioxidant properties.

For the study, the researchers evaluated the kidney-protective effect of red sage extract against diabetic nephropathy and analyzed the underlying molecular mechanism in an experimental diabetic nephropathy model. They treated mouse mesangial cells with a high dose of glucose and treated mice with streptozotocin to imitate the hyperglycemic conditions in people with diabetic nephropathy.

The results showed that the treatment with red sage extract reduced metabolic abnormalities linked to hyperglycemic conditions in the experimental diabetic nephropathy model. In streptozotocin-induced mice, red sage extract treatment enhanced renal function, attenuated albuminuria – a symptom of kidney disease – and mitigated the pathological alterations within the glomerulus, a cluster of capillaries around the end of a kidney tubule. In addition, red sage extract also inhibited high glucose-induced reactive oxygen species both in the cells and mice.

Overall, the findings of the study, which were published in The American Journal of Chinese Medicine, suggest that red sage extract may be used to protect the kidneys against diabetic nephropathy due to its powerful antioxidant properties. (Related: Red sage, also known as Chinese sage, found to protect the kidneys of people with severe acute pancreatitis and obstructive jaundice.)

Red sage also protects the heart from disease

Another group of Chinese researchers looked at the medicinal properties of red sage, particularly its effect on cardiovascular disease. In China and other Asian countries, red sage is widely used in traditional medicine to treat cardiovascular disease. To verify the potential heart-protective effects of red sage, the researchers carried out a literature review.

In the review, which was published in the journal Current Pharmaceutical Design, they summarized various literature of the historical traditional Chinese medicine interpretation of the action of red sage, its use in current clinical trials, its main phytochemical compounds, and its pharmacological findings. They identified 39 clinical trials that used red sage alone or in combination with other herbs for the treatment of cardiovascular diseases.

Based on the data they gathered, more than 200 compounds have been identified from red sage — most of which exhibit various pharmacological activities. These include Danshensu, salvianolic acid B, protocatechuic acid, catechin, protocatechualdehyde, tanshinone, tanshinone IIA, tanshinone VI, lithospermate B, cryptotanshinone, and polysaccharides — all of which contribute to the cardioprotective effects of red sage through various cell signaling pathways.

Different animal and laboratory studies have demonstrated that red sage could treat and prevent the development of cardiovascular diseases. Red sage and its compounds have been shown to lower high blood pressure, improve cholesterol levels, and restore blood flow after a heart attack or stroke. These results provided a better understanding of the actions of red sage for the management of cardiovascular disorders.

The findings of this review strongly support the notion that red sage has beneficial effects and can be potentially used as an effective alternative remedy for the management of cardiovascular diseases. (Click to Source)

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New level of intelligence: A new AI can teach itself with a “reinforcement learning algorithm” resulting in “superhuman” abilities within hours


New level of intelligence: A new AI can teach itself with a “reinforcement learning algorithm” resulting in “superhuman” abilities within hours

Even though DeepMind’s AlphaZero played against itself for only four hours, it managed to “synthesize the chess knowledge of one and a half millennium.” AlphaZero managed to surpass both human players and the reigning World Computer Champion Stockfish with 28 wins to 0 in a 100-game match.

Demis Hassabis, DeepMind’s co-founder, is a former chess prodigy. Along with his team, Hassabis aimed to defeat Go, a game that humans had the edge over artificial intelligence (AI). Little did they know that a chess engine would soon be able to learn fast enough to beat us at another game. (Related: Technology in the classroom: Robots could replace teachers in 10 years.)

AlphaZero’s superhuman abilities were documented in the academic paper Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm, which was published on December 5, 2017. The paper revealed that the DeepMind team successfully confirmed that a generic version of their algorithm, which had no specific knowledge other than the rules of the game, “could train itself for four hours at chess, two hours in shogi (Japanese chess) or eight hours in Go and then beat the reigning computer champions – i.e. the strongest known players of those games.”

Stockfish, the reigning TCEC computer chess champion, still failed to make the final this year even though it won 51 games. But when faced with the chess-trained AlphaZero, Stockfish lost 28 games and won none while the remaining 72 games were drawn.

When playing white, AlphaZero scored an outstanding 25 wins and 25 draws. Playing Black, the algorithm only scored 3 wins and 47 draws.

Aside from the rules of chess, AlphaZero was a blank slate. It then played games via a Monte-Carlo algorithm, where “initially random moves would be tried out until a neural network began to learn which options were likely to be more promising.” As it trained, AlphaGo had access to “5,000 first generation TPUs to generate self-play games and 64 2nd-generation TPUs to train the neural networks.”

TPUs are tensor processing units, and they aren’t publicly available yet because Google developed them specifically to handle the calculations required by machine learning. On the other hand, the trained algorithm ran on a single machine that had four TPUs. DeepMind explained that their approach was efficient, and AlphaZero only looked for 80,000 positions per second, which was a marked improvement in contrast to the 70 million positions for Stockfish.

Even though AlphaZero based its computations on a lower number of evaluations, it compensated for the difference by using its deep neural network to hone in on the variations that held more promise, which is definitely a more “human-like” approach to search.

Generic machine-learning algorithms are game-changers, not just for the chess world but the world around us. While there are many roadblocks ahead, we can soon develop a kind of basic consciousness and intelligence, or what is called true AI. It’s also possible that reinforced learning will soon shape AI into “the most intelligent entity in our known universe.”

Future developments hinge on how strongly DeepMind wants to keep their chess-trained algorithm active.

The paper is further detailed on

The pros and cons of AI

Whether you’re for them or against them, we can’t deny that AI has various pros and cons:

  • Pros – Early diagnosis of diseases, driverless cars, and voice-operated assistants.
  • Cons – Rise of overdeveloped AI (e.g. sports or video games), job automation, and security issues. (Click to Source)