Milky Way’s last big collision with another galaxy was much more recent than previously thought

ScientiFix, our weekly feature, offers you a summary of the top global science stories of the week, with links to their sources.

Representational image | Wiki Commons

New Delhi: A groundbreaking study by researchers at the Rensselaer Polytechnic Institute in New York, published in the Monthly Notices of the Royal Astronomical Society, has found that the history of our Milky Way galaxy is different from what we had previously known. Our last major collision with another galaxy was thought to be between 8-11 billion years ago by scientists. However, these researchers have now found that it was only around 3 billion years ago. 

This discovery was enabled by data from the European Space Agency’s Gaia spacecraft, which maps over a billion stars, tracking their movements, luminosity, temperature, and composition. 

One of the main indicators of galaxy collision is the stars that are formed in its wake. The authors of the study looked at these stars, or wrinkles as they called them, in the galaxy to determine the history of the Milky Way, explaining that the cosmos gets less wrinkly — that is, it has less stars — as it ages. 

The Rensselaer scholars noticed that the wrinkles are quite obvious as seen by the Gaia data, and could not possibly have joined us 8 billion years ago. Instead, they realised that these stars were formed during the Virgo Radial Merger with the Milky Way galaxy that happened less than three billion years ago. This reveals new information about our galaxy’s formation and paves the way for further research. Read more here. 

39% of envt journalists say they’ve faced threats for work

A new survey published on 5 June by the Earth Journalism Network and Deakin University in Australia found that over 80 percent of environment journalists say climate and environment stories have more prominence now than they did 10 years ago. However, 39 percent say that they have received threats for their stories, and have had to self-censor while covering these subjects. The report talked about the threat faced by them when covering stories, especially about illegal activities related to the environment.

Titled ‘Covering The Planet: Assessing the State of Climate and Environment Journalism Globally’, it surveyed 744 journalists and editors across 108 countries to understand the challenges facing environment journalists across the globe. In terms of ways to improve environmental reporting, an overwhelming 79 percent of journalists responded by saying more funding in newsrooms is necessary. Read more here. 

Sea sponges in Precambrian era 

Sea sponges are a quite simple and ancient animal group, containing no complex nervous or digestive systems. While the oldest fossils of sea sponges date back to only 500 million years ago, scientists say that based on evolutionary timelines, it is quite likely that they existed before that. Now, a new study published in Nature on 5 June reported the fossil of a 530-million-year-old sea sponge that suggests early sponges lacked mineral skeletons, which is why they couldn’t be fossilised. 

Named Helicolocellus cantori, this fossil was discovered in South China and shows a large, stemmed organism with a unique, grid-like body structure. This structure is similar to certain modern sponges but is made of organic material rather than minerals. The study also indicates that H. cantori is closely related to modern hexactinellid sponges, which are known for their glass-like skeletons.

This discovery supports the idea that sponges existed in the Precambrian era as non-mineralised animals with organic skeletons, which is why there are no sea sponge fossils from this period. Read more here. 

Detecting dementia 9 years before diagnosis

Researchers at Queen Mary, University of London have developed a new method to predict dementia with over 80 percent accuracy up to nine years before diagnosis. This new approach surpasses traditional memory tests and brain shrinkage measurements. The paper was published in Nature Mental Health on 6 June. 

Led by Professor Charles Marshall, the team analysed functional MRI (fMRI) scans to detect changes in the brain’s default mode network (DMN), the first neural network affected by Alzheimer’s disease. Using fMRI data from over 1,100 UK Biobank volunteers, they assessed the connectivity between ten DMN regions and then assigned each patient a probability of developing dementia based on their connectivity patterns. Comparisons with UK Biobank medical records confirmed the model’s high accuracy, even predicting the onset of dementia within a two-year margin of error.

The study also linked genetic risk and social isolation to changes in the DMN, highlighting specific dementia risk factors. This method could revolutionise early dementia detection and treatment strategies. Read more here.