Category: 7. Science

Why is Microcarb important?

Rüdiger Lang: 2024 was the hottest year ever recorded, both globally and across Europe – a stark reminder of the urgency of tackling the climate crisis driven by human greenhouse gas emissions. While we know how much carbon dioxide is accumulating in the atmosphere overall, we still lack detailed information about exactly where emissions come from.

The Paris Agreement created momentum to invest in better ways to monitor emissions, and as the first dedicated European CO2 mission, Microcarb is a vital part of Europe’s efforts to track greenhouse gases, hold emitters accountable, and guide climate action. To build a complete picture, we need to separate natural flows of carbon dioxide from those caused by humans and identify sources that remain underrepresented or undetected. If countries can pinpoint emissions more accurately, they can implement targeted policies and, crucially, see whether those measures are working.

Measuring emissions this precisely is extremely challenging, but Microcarb’s sensors achieve accuracy close to 99.98%, making it possible to detect and distinguish both natural and human contributions. Microcarb will quantify how much carbon dioxide is released from both natural and human-made sources and how CO2 moves between the Earth surface, the oceans, the forests, and the atmosphere. The satellite can also zoom in to capture high-resolution snapshots of specific targets such as cities or farming regions.

There is a real need for consistent, reliable data to fill gaps in our understanding, and Microcarb will play an important role in that effort, support more effective climate policies, as well as helping to lay the foundation for larger systems like the Copernicus CO2M constellation.

The origin of some neuropsychiatric diseases, such as autism, bipolar disorder, or depression, and certain neurodegenerative diseases, Alzheimer’s and Parkinson’s, can be found in very early stages of brain formation in the fetus. That is, earlier than previously recognized, according to a study by the Hospital del Mar Research Institute and Yale University, published in Nature Communications.

The work focused “on searching for the origin of mental illnesses in the earliest stages of fetal development, especially in the brain stem cells“, explains Dr. Gabriel Santpere, Miguel Servet researcher and coordinator of the Neurogenomics Research Group at the Biomedical Informatics Research Program of the Hospital del Mar Research Institute, a joint group with Pompeu Fabra University.

To do this, they used a list of nearly 3,000 genes linked to neuropsychiatric diseases, neurodegenerative pathologies, and cortical malformations, and simulated the effect of their alteration on the cells involved in brain development. The results indicate that many of these genes are already functional during the initial phases of fetal development in stem cells, the progenitors that build the brain, creating neurons and their supporting structures.

Achieving this was not easy. This moment of brain development is very difficult to study. For this reason, the researchers combined multiple data from human and mouse brains, as well as in vitro cellular models. As Dr. Nicola Micali, associate researcher at Dr. Pasko Rakic’s lab at Yale University and co-leader of the research, points out, “scientists usually study the genes of mental illnesses in adults, but in this work we discovered that many of these genes already act during the early stages of fetal brain formation, and that their alterations can affect brain development and promote mental disorders later on“.

During the study, specific regulatory networks for each cell type involved in brain development were simulated to see how the activation or deactivation of the analyzed genes linked to various brain diseases affected progenitor cells in their different stages. This allowed them to observe the importance of each gene in the emergence of alterations that cause various diseases. The list ranges from microcephaly and hydrocephaly to autism, depression, bipolar disorder, anorexia, or schizophrenia, and also includes Alzheimer’s and Parkinson’s.

In all these pathologies, genes involved in the earliest phases of brain development when neural stem cells are functional are found. “We cover a wide spectrum of diseases that the brain can have and look at how the genes involved in these conditions behave in neural stem cells”, adds Xoel Mato-Blanco, researcher at the Hospital del Mar Research Institute. At the same time, he points out that the work “identifies temporal windows and cell types where the action of these genes is most relevant, indicating when and where you should target the function of these genes”.

Having this information “is useful to understand the origin of diseases that affect the cerebral cortex, that is, how genetic alterations translate into these pathologies”, says Dr. Santpere. Understanding these mechanisms and the role of each gene in each disease can help develop targeted therapies that act on them, opening opportunities for gene therapy and personalized treatments.

A new artificial intelligence model can improve the process of drug and vaccine discovery by predicting how efficiently specific mRNA sequences will produce proteins, both generally and in various cell types. The new advance, developed through an academic-industrial partnership between The University of Texas at Austin and Sanofi, helps predict how much protein cells will produce, which can minimize the need for trial-and-error experimentation, accelerating the next generation of mRNA therapeutics.

Messenger RNA (mRNA) contains instructions for which proteins to make and how to make them, enabling our bodies to grow and carry out the day-to-day processes of life. Among the most promising areas of health and medicine, the ability to develop new mRNA vaccines and drugs – able to fight viruses, cancers and genetic disorders – involves the frequently challenging process of coaxing cells in a patient’s body to produce enough protein from therapeutic mRNA to effectively combat disease. 

The new model, called RiboNN, stands to guide the design of new mRNA-based therapeutics by illuminating what will yield the highest amount of a protein or better target specific parts of the body such as the heart or liver. The team described their model today in one of two related papers in the journal Nature Biotechnology.

“When we started this project over six years ago, there was no obvious application. We were curious whether cells coordinate which mRNAs they produce and how efficiently they are translated into proteins. That is the value of curiosity-driven research. It builds the foundation for advances like RiboNN, which only become possible much later.”

Can Cenik, Associate professor, Molecular Biosciences, University of Texas, Austin

The work was made possible by funding support from the National Institutes of Health, The Welch Foundation and the Lonestar6 supercomputer at UT’s Texas Advanced Computing Center.

In tests spanning more than 140 human and mouse cell types, RiboNN was about twice as accurate at predicting translation efficiency as earlier approaches. This advance may lend researchers the ability to make predictions in cells in ways that could help expedite treatments for cancer and infectious and hereditary diseases. 

You can think of the way cells in your body make proteins as the way a team of chefs might bake cakes. To cook up a batch of proteins, the chefs in one of your cells (ribosomes) look up the recipe in your own unique protein cookbook (a.k.a. DNA), copy the recipe onto notecards called messenger RNAs (mRNAs), and then combine ingredients (amino acids) according to the recipe to bake up the cakes (proteins).

An mRNA vaccine or therapeutic coaxes these chefs in your cells into making proteins. In the case of a vaccine, they might produce a protein found on the surface of a pathogenic virus or cancer cells, essentially waving a big red flag in front of your immune system to make antibodies against the virus or cancer. In the case of a disorder caused by a genetic mutation, they might produce a protein that your body can’t properly make on its own, reversing the disorder.

Before developing their new predictive model, Cenik and the UT team first curated a set of publicly available data from over 10,000 experiments measuring how efficiently different mRNAs are translated into proteins in different human and mouse cell types. Once they had created this training dataset, AI and machine learning experts from UT and Sanofi came together to develop RiboNN.

One goal of the predictive tool is to one day make therapies that are targeted to a particular cell type, said Cenik, who also is affiliate faculty at UT’s Oden Institute for Computational Engineering and Sciences and a CPRIT scholar, receiving research support from the Cancer Prevention and Research Institute of Texas.

“Maybe you need a next-generation therapy to be made in the liver or the lung or in immune cells,” he said. “This opens up an opportunity to change the mRNA sequence to increase the production of that protein in that cell type.”

In a companion paper also in Nature Biotechnology, the team demonstrated that mRNAs with related biological functions are translated into proteins at similar levels across different cell types. Scientists have long known that the process of transcribing genes with related functions into mRNAs is coordinated, but it hadn’t been previously shown that translating mRNAs into proteins is also coordinated.

Autophagy is essentially the ‘rubbish collection’ of our cells. If there are problems in this process, which is so important for our health, diseases such as Parkinson’s can result. In their latest study, leading cell biologists at the Max Perutz Labs at the University of Vienna investigated mitophagy – a form of autophagy – and came to a remarkable conclusion: the researchers have described a new trigger for mitophagy.

This discovery has led to a reassessment of the hierarchy of factors that trigger autophagy. The newly discovered signalling pathways could also open up novel therapeutic options. The study has been published in the renowned journal Nature Cell Biology.

Autophagy is a self-cleaning process of the cell and is crucial for cell health in the human body. A sophisticated molecular surveillance command identifies suspicious substances – broken cell components, clumped proteins or even pathogens – and initiates their removal. Finally, defective cell components are broken down and recycled.

Mitophagy is a form of autophagy in which mitochondria within a cell are specifically degraded. Dysregulation of mitophagy is particularly associated with Parkinson’s disease. A better understanding of this process is therefore important for combating Parkinson’s.

In a new study led by postdoctoral researcher Elias Adriaenssens from Sascha Martens’ group at the Max Perutz Labs at the University of Vienna, the scientists reveal a new mechanism for triggering mitophagy. Until now, research has focused heavily on the ‘PINK1/Parkin signalling pathway’. Signalling pathways are used to transmit information within cells. These complex networks of molecules control critical cellular functions such as growth, division, cell death and, indeed, mitophagy.

“When we looked at the big picture, it became clear that, apart from the much-studied ‘PINK1/Parkin pathway’, there were huge gaps in our knowledge of other mitophagy pathways. Our laboratory has explored these neglected areas by using biochemical reconstitutions to gain fundamental mechanistic insights.”

Elias Adriaenssens, Study Leader and Postdoctoral Researcher, University of Vienna 

Newly discovered pathways are no exception

“We found that NIX and BNIP3 – two known mitophagy receptors – can trigger autophagy without binding to FIP200 (a protein), which was quite unexpected,” explains Adriaenssens.

FIP200 is considered essential for triggering autophagy. “This presented us with a puzzle. Despite extensive testing, we were unable to detect any interaction between FIP200 and either of the two receptors – which raises the crucial question of how they function without this supposedly crucial component,” he adds.

However, mass spectrometry revealed that other autophagy components, known as WIPI proteins, bind to these mitochondrial receptors. Since WIPI proteins were previously thought to act later in the signalling pathway, their involvement in triggering autophagy was surprising. Follow-up experiments confirmed these interactions and suggested that WIPI-mediated recruitment is not an exception, but may mediate previously unknown pathways in selective autophagy.

“This is an exciting discovery – it reveals a parallel trigger for selective autophagy. Instead of a single, universal mechanism, cells appear to use different molecular strategies depending on the receptor and context. Until now, no one has considered WIPI proteins to be key players in triggering autophagosome formation, but our discovery could change that view,” explains Adriaenssens.

 

Potential for new therapies for Parkinson’s disease

 

Looking ahead, the study raises an important question: How do cells decide between alternative mitophagy signalling pathways – why do some receptors use one and others the other, and what factors determine which pathway is used? Distinguishing between selective mitophagy signalling pathways could pave the way for therapies that specifically activate one pathway to compensate for defects in the other, which has long-term potential for the treatment of Parkinson’s disease.

The moon is becoming a little bit brighter each night as we work through the phases of the lunar cycle.

The lunar cycle is a series of eight unique phases of the moon’s visibility. The whole cycle takes about 29.5 days, according to NASA, and these different phases happen as the Sun lights up different parts of the moon whilst it orbits Earth. 

See what’s happening tonight, July 26.

What is today’s moon phase?

As of Saturday, July 26, the moon phase is Waxing Crescent. There’s still not much to see tonight, with only 4% of the surface visible to us on Earth (according to NASA’s Daily Moon Observation).

It’s the second day of the lunar cycle, and with such limited visibility, there’s nothing for you to spot on the moon’s surface tonight, not even with binoculars or a telescope.

When is the next full moon?

The next full moon will be on August 9. The last full moon was on July 10.

What are moon phases?

According to NASA, moon phases are caused by the 29.5-day cycle of the moon’s orbit, which changes the angles between the Sun, Moon, and Earth. Moon phases are how the moon looks from Earth as it goes around us. We always see the same side of the moon, but how much of it is lit up by the Sun changes depending on where it is in its orbit. This is how we get full moons, half moons, and moons that appear completely invisible. There are eight main moon phases, and they follow a repeating cycle:

Mashable Light Speed

New Moon – The moon is between Earth and the sun, so the side we see is dark (in other words, it’s invisible to the eye).

Waxing Crescent – A small sliver of light appears on the right side (Northern Hemisphere).

First Quarter – Half of the moon is lit on the right side. It looks like a half-moon.

Waxing Gibbous – More than half is lit up, but it’s not quite full yet.

Full Moon – The whole face of the moon is illuminated and fully visible.

Waning Gibbous – The moon starts losing light on the right side.

Last Quarter (or Third Quarter) – Another half-moon, but now the left side is lit.

Waning Crescent – A thin sliver of light remains on the left side before going dark again.

For decades, scientists believed the universe would expand forever, driven endlessly outward by a mysterious force known as dark energy. But a new study has upended that view with a provocative idea: the cosmos may one day stop expanding and instead collapse in on itself in a cataclysmic event called the “Big Crunch.” According to the research, which is currently in preprint and awaiting peer review, this reversal could happen in about 20 billion years. Based on new models and fresh astronomical data, scientists are rethinking the fate of everything we know.

The universe may not expand forever

The traditional model of the universe’s fate was built on the assumption that dark energy is constant and positive, a force pushing galaxies apart faster over time. But researchers analysing data from the Dark Energy Survey (DES) and the Dark Energy Spectroscopic Instrument (DESI) found evidence that dark energy might not be constant after all. Instead, it could vary over time, as proposed by a new theoretical framework called the axion-dark energy (aDE) model.One of the most striking findings in the new study is the possibility that the cosmological constant — which reflects the energy density of space itself — may be negative. If true, this would mean that gravity could eventually overpower expansion. Over time, this shift would cause the universe’s growth to slow, stop, and then reverse into a contraction phase.

What is the Big Crunch

If contraction occurs, all matter and energy could eventually be compressed into a single, dense point — an event known as the Big Crunch. This would be the reverse of the Big Bang. According to the aDE model, the total lifespan of the universe would be about 33.3 billion years, and we are already 13.8 billion years into that span. That leaves approximately 20 billion years before the predicted collapse.

Not a final verdict yet

Although the findings are significant, scientists caution that this new model is not confirmed. It is based on observational trends and evolving theoretical physics. Further investigation using next-generation telescopes and deeper space surveys will be needed to determine whether dark energy truly changes over time and whether a cosmic collapse is on the horizon.

Is the end really the end

Even if the Big Crunch occurs, it might not mark the permanent end of everything. Some theories propose that a collapsing universe could eventually lead to a rebirth — a new Big Bang triggering a fresh universe cycle. While these ideas remain speculative, the study has opened a bold new chapter in understanding how — and when — our universe might end.

When we think of sea animals, we usually picture dolphins, whales, or sharks. But there’s one sea creature that’s quietly amazing– the octopus. With its soft body, eight bendy arms, and smart behaviour, it’s truly one of a kind.

Scientists have studied octopuses for years, and the more they learn, the more fascinating these creatures become. Here are some fun and surprising facts that show just how special octopuses really are: