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Just yesterday, an unstable sunspot named AR3335 exploded, producing a solar flare that triggered blackouts over the Atlantic Ocean. The resulting solar flare was M2.5 in intensity and caused a shortwave radio blackout. Solar activity has been on the rise for the past few months, and it is expected to increase further until solar maximum, the period of greatest solar activity during the Sun’s 11-year cycle.

Solar flare risk

According to a report by spaceweather.com, NASA’s Solar Dynamics Observatory (SDO) forecasters have observed multiple streams of solar winds hurtling towards Earth from a coronal hole on the Sun’s surface, and these could reach Earth tomorrow, June 21. Moreover, a CME is also expected to deliver a glancing blow on June 22. Both these events have the potential to trigger a G1-class Geomagnetic storm. It could also result in solstice auroras at high latitudes.

Astronomers have mapped 39 interstellar clouds where high-mass stars are expected to form. This large data set shows that the accepted model of low-mass star formation needs to be expanded to explain the formation of high-mass stars. This suggests the formation of high-mass stars is fundamentally different from the formation of low-mass stars, not just a matter of scale.

High-mass stars play an important role in the evolution of the universe through the release of heavy elements and the produced when a massive star explodes in a supernova. Despite their importance, the way form remains poorly understood due to their rarity.

To better understand massive star formation a team led by Kaho Morii, Patricio Sanhueza, and Fumitaka Nakamura used the Atacama Large Millimeter/submillimeter Array (ALMA) to observe 39 infrared dark clouds (IRDCs). IRDCs are massive, cold, and dense clouds of gas and dust; and are thought to be the sites of massive star formation. The team focused on clouds showing no signs of star formation, to understand the beginning of the formation process before ignite. In the 39 clouds, the team found more than 800 stellar seeds, referred to as molecular cloud cores, which astronomers think will evolve into stars.

Eventually, these molecules probably evolved a lipid (fatty) boundary separating the internal environment of the organism from the exterior, forming protocells. Protocells could concentrate and organize better the molecules needed in biochemical reactions, providing a contained and efficient metabolism.

Life on Repeat?

Abiogenesis could have happened more than once. Earth could have birthed self-replicating molecules several times, and maybe early life for thousands or millions of years just consisted of a bunch of different self-replicating RNA molecules, with independent origins, competing for the same building blocks. Alas, due to the ancient and microscopic nature of this process, we may never know.

Tesla announced it produced 10 million 4,680 battery cells at Gigafactory Texas. It is a good sign for the automaker’s production ramp-up, which relies heavily on the new cell.

The 4,680 battery cell format has taken the industry by storm since Tesla unveiled its own cell strategy at Battery Day in 2020.

The automaker claimed the potential to reduce battery cost by over 50% with the new design; it has been trying to bring it to volume production since, but it has run into some bottlenecks.

This study demonstrates that AI can be incredibly effective in helping us identify new drug candidates – particularly at early stages of drug discovery and for diseases with complex biology or few known molecular targets.


A machine learning model has been trained to recognise the key features of chemicals with senolytic activity. It recently found three chemicals able to remove senescent cells without damaging healthy cells.

Molecular structure of oleandrin. Credit: Mplanine, CC BY-SA 4.0, via Wikimedia Commons.

Senescent cells, often referred to as “zombie cells”, are cells that have stopped dividing but remain metabolically active. These cells increase with age and secrete harmful substances that can lead to chronic inflammation and affect the function of nearby cells. This contributes to aging and various age-related diseases like heart disease, diabetes, Alzheimer’s, and certain cancers. Their elimination or reprogramming is a key focus of aging-related research.

That’s the ordinary matter of everyday life: your hair and clothes, your atoms and organs, the food you eat and the dogs that kiss you, the air and the sea, the Sun and the Moon. Everything we know — everything we see — is just 5% of everything in the Universe.

The remaining 95% of the Universe is stuff that we can’t see, don’t yet understand. An extraordinarily vast portion of the cosmos is still unknown. Despite the technological advancements of the last century, even with computers at our fingertips and the worldwide internet and space-based observatories mapping the far reaches of our Universe, there is still so much that we don’t understand.

We have grown leaps and bounds since the days of the ancient Greeks and Egyptians, even since Copernicus and Kepler. But in many ways, we are still novices playing with toy models seeking to understand the stars.

For many years, the fields of physics and chemistry have held the belief that the properties of solid materials are fundamentally determined by the atoms and molecules they consist of. For instance, the crystalline nature of salt is credited to the ionic bond formed between sodium and chloride ions. Similarly, metals such as iron or copper owe their robustness to the metallic bonds between their respective atoms, and the elasticity of rubbers stems from the flexible bonds in the polymers that form them. This principle also applies to substances like fungi, bacteria, and wood.

Or so the story goes.

A new paper recently published in Nature upends that paradigm, and argues that the character of many biological materials is actually created by the water that permeates these materials. Water gives rise to a solid and goes on to define the properties of that solid, all the while maintaining its liquid characteristics.