The study, published in Molecular Psychiatry, was led by senior authors Avram Holmes, associate professor of psychiatry at Robert Wood Johnson Medical School and core faculty member of the Center for Advanced Human Brain Imaging Research within the Rutgers Brain Health Institute, and Rajiv Radhakrishnan, associate professor of psychiatry and radiology and biomedical imaging at Yale University. First author Sidhant Chopra, formerly a postdoctoral fellow in the Holmes Lab, is a McKenzie Research Fellow at Orygen, Australia’s Centre of Excellence in Youth Mental Health, and the University of Melbourne in Australia.

Measuring the Brain’s Synaptic Connections

Synapses are tiny junctions that allow brain cells to communicate with one another across neural circuits. Problems involving these connections are believed to play a role in the cognitive and emotional symptoms of schizophrenia. Until now, however, scientists have had a limited understanding of exactly where synaptic loss occurs in the brains of living people because conventional imaging methods such as magnetic resonance imaging cannot specifically measure synapses.

The research involved 122 people, including 29 diagnosed with schizophrenia, making it one of the largest synaptic density PET imaging studies conducted so far. Compared with healthy participants, people with schizophrenia showed a pronounced and widespread reduction in synaptic connections across several parts of the brain. These included frontal and temporal regions as well as areas involved in memory and emotion. The loss was also considerably greater on the left side of the brain than on the right.

Researchers found that this synaptic pattern did not match the changes in brain volume typically seen with standard MRI scans. That distinction suggests synaptic loss and changes in brain volume may reflect separate biological processes rather than two imaging methods capturing the same underlying change.

A Molecular Pattern Behind Synaptic Loss

The team also discovered that the brain regions showing the greatest synaptic losses tended to contain high concentrations of receptors for important neurotransmitters, including serotonin, gamma-aminobutyric acid and glutamate. The finding suggests that the molecular characteristics of individual brain regions may influence how vulnerable they are to changes associated with schizophrenia.

To explore how synaptic loss might move through the brain, the researchers used computer simulations based on the brain’s structural connections. Their modeling identified an area in the left frontal lobe as a likely starting point from which synaptic loss could spread into connected regions.

“These findings suggest that in schizophrenia, synaptic loss is not random,” Chopra said. “Rather, it follows the brain’s molecular and connectivity architecture, which could eventually help identify where and how to intervene.”

“This detailed mapping of synaptic vulnerability could eventually help identify where and how to intervene to preserve or restore brain function, such as emerging therapies to prevent and regrow synapses,” Holmes added.

Toward More Precise Schizophrenia Treatments

The researchers said future work will build on these results by investigating how synaptic loss changes over time and how it responds to clinical treatments. A better understanding of that progression could ultimately help researchers develop more precise and personalized approaches to schizophrenia care.

The research was led by Prof. Shudong Wang of the Aerospace Information Research Institute of the Chinese Academy of Sciences (AIRCAS). The team sought to overcome two major obstacles to understanding groundwater in the region: limited on-the-ground data and the extremely complex mountainous landscape. The findings were recently published in Environmental Research Letters.

AI and Satellites Reveal Two Decades of Change

To build a clearer picture of what is happening underground, the researchers created an artificial intelligence (AI) powered assessment model that combines observations from multiple satellites, Earth system modeling, and explainable AI.

Using this approach, they reconstructed about 20 years of groundwater storage (GWS) changes across High Mountain Asia. The system also helped identify the main forces driving those changes and allowed the researchers to explore how groundwater risks could develop under future scenarios.

The results show that roughly two-thirds of HMA experienced declining groundwater storage between 2003 and 2020. The largest losses occurred in heavily populated downstream basins where irrigation demands are high, including the Ganges-Brahmaputra, Indus and Amu Darya basins. Some inland areas at higher elevations, however, experienced localized increases in groundwater storage.

Climate and Human Water Use Drive the Decline

Climate-related forces explain nearly half of the observed variation in GWS, with changes involving the cryosphere playing an especially important role.

At the same time, human withdrawals of groundwater have become an increasingly significant source of depletion, particularly in downstream agricultural regions that rely heavily on irrigation. The influence of human water use became even more pronounced after 2010.

Researchers also project that groundwater losses will continue if current patterns of water use remain in place. In some locations, increased glacier melt could temporarily reduce the pace of groundwater decline around the 2060s. But this “buffer effect” cannot continue indefinitely and is expected to be followed by faster losses.

If present water use patterns do not change, groundwater depletion could accelerate further, increasing the threat to agricultural areas downstream that depend on these reserves.

A New Way to Track Groundwater in Mountain Regions

For the analysis, the researchers used a framework guided by existing scientific knowledge while also drawing on large amounts of observational data. Information from multiple satellite sensors was used to estimate GWS changes over the past 20 years.

The framework incorporates a lightweight Transformer architecture designed to account for hydrological memory and delayed effects within mountainous catchments. The researchers also used explainable machine learning methods to determine the physical factors associated with the groundwater changes identified by the system.

To test the reliability of the results, the team compared its findings with thousands of measurements from groundwater wells as well as independent datasets. Those comparisons provided additional support for the study’s conclusions.

By combining remote sensing observations, established hydrological knowledge, and interpretable AI methods, the framework helps address long-standing difficulties in studying High Mountain Asia, including rugged terrain and incomplete information about human water use.

The research was funded by the National Key R&D Program of China and the Key Program of the National Natural Science Foundation of China (NSFC).

During a total solar eclipse, the Moon completely blocks the bright disk of the Sun, making the much fainter solar corona visible. The corona is the Sun’s extremely hot outer atmosphere, and during most eclipses it appears white or silvery. Some people watching last week’s eclipse did see this familiar pearly color. In Spain, however, observers were treated to something different. The corona took on an unusually rich golden hue.

Why the Eclipse Looked Golden

The timing of the eclipse played an important role. In Spain, totality occurred while the setting Sun was already close to the horizon. When the Sun sits that low in the sky, its light must travel through much more of Earth’s atmosphere before reaching an observer.

Along that longer path, molecules in the air scatter shorter wavelengths of visible light, especially blue. This is the same basic process that helps make sunsets appear orange and red. With more blue light removed, the warmer colors that remain become much more noticeable.

Conditions that day added another layer to the effect. An unusually large amount of smoke in the air from nearby forest fires acted like an additional atmospheric filter. Smoke particles scattered even more of the remaining blue wavelengths, intensifying the golden tones in the visible light surrounding the eclipsed Sun.

A Pink Solar Prominence Stood Out

The remarkable featured image was created using multiple exposures and HDR processing. HDR, or high dynamic range imaging, combines exposures with different brightness levels so that both very bright and very faint details can be preserved in a single image. The photograph was captured last week from Benavente, Spain.

Not everything around the Sun was transformed into gold. A large prominence remained visible along the Sun’s left edge. Solar prominences are enormous structures of glowing plasma that extend outward from the Sun’s surface and are often shaped by powerful magnetic fields.

This prominence emitted strongly in light associated with hydrogen, allowing its original bright pink color to survive despite the atmospheric filtering. Against the unusually golden corona, the vivid pink structure made an already rare eclipse scene even more striking.