If you were to stand at the intersection of Maryland Avenue and West 24th Street in Baltimore's Old Goucher neighborhood and travel back in time for 10 years, you would probably be shocked at the transformation. Back then, pavement blanketed the neighborhood. Of the few trees growing along streets, many were sickly or misshapen. Concrete, asphalt, and buildings soaked up the sun's rays in summer to create a sweltering heat island, sending temperatures soaring up to 10 degrees above those of surrounding areas. Heat is a "silent killer," researchers say and can be especially dangerous for older and vulnerable people who are unable to escape into air-conditioned spaces. Old Goucher had a particularly susceptible population: people who came to be treated at the area's methadone clinics. 

Today, Old Goucher is verdant—an increasingly lush oasis amid the concrete jungle. Streets are lined with trees and understory vegetation. Islands of soil have been carved out of sidewalks. Along one block, more than 100 tons of asphalt and concrete were jackhammered and trucked away, replaced by an exuberant if somewhat unruly garden. When people enter the neighborhood, "they feel better," says Kelly Cross, a resident, and president of the Old Goucher Community Association. "It feels somehow different. They can't put their finger on it. But we know why."

Cross and his husband, Mateusz Rozanski, who moved here in 2012, have catalyzed much of the change. They simply wanted to make their neighborhood more livable, and they say the greening has helped attract new coffee shops, bars, and restaurants.

But in the era of global climate change, their work is about to take on much broader significance. Old Goucher has become a key site for one of the best-funded equity-focused urban climate research efforts ever undertaken.

In spring 2022, the U.S. Department of Energy surprised and thrilled climate scientists with a call for proposals for a new and ambitious Urban Integrated Field Laboratories (UIFL) program to deploy the power of modeling and measurement on behalf of climate-stressed cities. Ben Zaitchik, a researcher in the Johns Hopkins Department of Earth and Planetary Sciences, emailed colleagues at universities and agencies around the region and pulled together a team. The researchers proposed something unusual: a climate research project that would evolve in conversation with local community members. "I thought there was a zero percent chance we would win" one of the coveted awards, Zaitchik says.

But the proposal did win, alongside those from three other cities, out of dozens of entries. The team will have a tidy sum—nearly $25 million—to create what Zaitchik hopes will be "the most meaningful urban environmental monitoring system in the world." Zaitchik plans to blanket selected Baltimore neighborhoods, including Old Goucher, with sophisticated instruments to measure temperature and flows of gases, wind, moisture, and heat to create an unprecedented urban climate data set. Researchers in Chicago; Beaumont and Port Arthur, Texas; and Phoenix will similarly be instrumenting their cities.

The task is urgent. Cities around the country and the world are swiftly warming while humanity is rapidly urbanizing. Yet city planners and officials lack data and models to help them protect residents from this warming and its increasingly severe impacts on health and well-being. As a result, cities often have poor visibility into the climate future, putting in place measures that might not have the desired benefits or that could in some cases make things even worse.

"We really need to get it right, now," Zaitchik says. "The investment choices that we make, and the way we deliver on them for cities in the coming five to 10 years, are really going to be determinative for the future of some of these communities."

At the same time that it seeks to aid cities, the Energy Department wants the four program sites to generate data that will help it answer a separate but related question: How do cities affect the climate? Dense urban mosaics of buildings, streets, and green spaces heat and cool the air and change moisture and wind in complex ways that affect not just cities themselves but also surrounding areas. But cities have thus far been a major blind spot for the massive supercomputer models that researchers use to forecast the future of the global climate.

Meeting these science goals will be hard enough. But Zaitchik's team has designed its project to do something arguably even more ambitious: engage Baltimore community members to shape their climate-related priorities and guide their work. The project will be steered by a committee composed of city officials and community leaders like Cross and Rozanski.

While community-based research has deep roots in public health and social science, it is much less common in physical science fields, such as climate studies, where researchers typically design projects around questions they and their funders are interested in. It's also a departure for the Energy Department, says Jennifer Arrigo, an official who oversees the UIFL program. Co-production of research between scientists and communities "is something new for us." But if it succeeds, it could pay off big for Baltimore, the nation, and the world.

A groundbreaking study has revealed that ChatGPT can effectively aid in clinical decision-making, specifically in selecting the appropriate radiological imaging tests for breast cancer screening and breast pain diagnosis. This marks a significant advancement in AI technology.

A new study by investigators from Mass General Brigham has found that artificial intelligence (AI) language models like ChatGPT can accurately identify appropriate imaging services for two important clinical presentations: breast cancer screening and breast pain. Their results suggest that large language models have the potential to assist decision-making for primary care doctors and referring providers in evaluating patients and ordering imaging tests for breast pain and breast cancer screenings. Their results are published in the Journal of the American College of Radiology. 

"In this scenario, ChatGPT's abilities were impressive," said corresponding author Marc D. Succi, MD, associate chair of Innovation and Commercialization at Mass General Brigham Radiology and executive director of the MESH Incubator. "I see it acting like a bridge between the referring healthcare professional and the expert radiologist — stepping in as a trained consultant to recommend the right imaging test at the point of care, without delay. This could reduce administrative time on both referring and consulting physicians in making these evidence-backed decisions, optimize workflow, reduce burnout, and reduce patient confusion and wait times."

ChatGPT is a large language model (LLM) built on data from the internet to answer questions in a human-like way. Since ChatGPT was introduced in November 2022, researchers worldwide are diving into learning how these AI tools can be used in medical scenarios. Published as a preprint on February 7, 2023, this study is the first of its kind to test ChatGPT's clinical decision-making abilities, and the first to test GPT 4 as opposed to older iterations. 

When a primary care doctor orders specialized testing, say for a patient who complains of breast pain, they may not know the best imaging test to choose. It might be an MRI, an ultrasound, a mammogram, or another imaging test. Radiologists generally follow the American College of Radiology's Appropriateness Criteria to make these decisions. These evidence-backed guidelines are well-known to specialists but less known to non-specialists who may need to pick the best imaging test during a patient’s visit. This can confuse the patient's side and can lead to patients getting tests they don't need or getting the wrong tests. 

The researchers asked OpenAI's ChatGPT 3.5 and 4 to help them decide what imaging tests to use for 21 made-up patient scenarios involving the need for breast cancer screening or the reporting of breast pain using the appropriateness criteria. 

They asked the AI in an open-ended way and by giving ChatGPT a list of options. They tested ChatGPT 3.5 as well as ChatGPT 4, a newer, more advanced version. ChatGPT 4 outperformed 3.5, especially when given the available imaging options. For example, when asked about breast cancer screenings, and given multiple choice imaging options, ChatGPT 3.5 answered an average of 88.9% of prompts correctly, and ChatGPT 4 got about 98.4% right.

"This study doesn't compare ChatGPT to existing radiologists because the existing gold standard is a set of guidelines from the American College of Radiology, which is the comparison we performed,” Succi said. “This is purely an additive study, so we are not arguing that the AI is better than your doctor at choosing an imaging test but can be an excellent adjunct to optimize a doctor’s time on non-interpretive tasks."

Integrating AI into medical decision-making could happen at the point of care. When a primary care doctor enters data into an electronic health record, the program could alert them to the best imaging options — providing an answer to the patient about what to expect when they go for the test and suggesting to the doctor the right test to order. 

Researchers added that a more advanced medical AI could be created using datasets from hospitals and other research institutions to make it more specific to health-focused applications. 

"We may be able to finetune ChatGPT with different patient and therapeutic data and knowledge sets to tailor it to specific patient populations," Succi said. "At Mass General Brigham, we have specialized centers of excellence where we care for patients with some of the most complex and rare diseases. We can leverage our experience and lessons learned from caring for these patient cases to train a model to provide support for rare and complex diagnoses and then make that model available to centers around the world, especially centers that may treat these conditions less frequently."

But before any AI would be involved in medical decision-making, it would need to be extensively tested for bias, and privacy concerns, and approved for use in medical settings. New regulations around medical AI could also play a big role in what makes it into patient care interactions. 

Euclid, the European Space Agency’s space telescope, will be launched on July 1 if everything goes to plan. During the coming six years, it will be mapping one-third of the sky.

In six years, Euclid will complete a task that would take older telescopes like Hubble or Webb over a century. The main objective is to solve the problem of dark energy, i.e. why has the expansion of the universe started to accelerate? 

A map to reveal the secrets of dark matter and dark energy

The objective of Euclid is to help us understand two of the most enigmatic, yet key phenomena in the universe; dark matter and dark energy.

“The gravity of dark matter and dark energy affects the movements of galaxies and the expansion of the universe. Though we cannot see either of them directly, they make up some 95% of the universe,” says Professor Hannu Kurki-Suonio from the University of Helsinki.

Euclid will produce a three-dimensional map of the universe with billions of galaxies. The map will cover over one-third of space, up to 10 billion light years away. The further away an observed galaxy is, the further we can see into the past – to 10 billion years ago.

The part of space to be mapped has been selected because that is where the furthermost galaxies are most clearly discernible, avoiding the plane of the Milky Way and our solar system. Euclid will also measure the gravitational lens effect; how the gravitation of dark matter bends the trajectory of light so that it distorts how we see far-away galaxies. In this way, we will be able to map the distribution of dark matter.

The three-dimensional map produced by Euclid will help us study how the universe has expanded and how large-scale structures, like galaxies, have developed during cosmic history. This, in turn, depends on the characteristics of dark matter and dark energy.

Many Finns participating in the endeavor

Euclid will be launched from Cape Canaveral in Florida with a SpaceX Falcon 9 rocket to 1.5 million kilometers from Earth, where it will be able to make observations without interference. There is a telescope on Euclid with a diameter of 1.2 meters, along with two instruments: one for taking sharp images in visual light, the other one for taking spectra and images in infrared. 

Both instruments on Euclid contain a large camera. The images from visible light contain over 600 million pixels and the ones from infrared over 60 million pixels.

Euclid will take images from one area for over an hour, and then it will be turned towards another area. Euclid differs from previous space telescopes specifically in that it can take in a much larger portion of space at one time – the portion of space covered by one image is larger than the full moon can conceal.

Over 300 research institutes and 2,000 researchers from 21 countries are participating in Euclid. The total cost of the project is over one billion euros. The observational data from Euclid will be analyzed in nine separate Euclid science data centers, one of which is located in Finland.

The Finnish scientists have collaborated in developing supercomputing methods, producing simulated data, and developing data quality-assurance methods for Euclid. The Finnish members also hold a strong position in combining observations made from Earth with Euclid data. In addition to the data gathered by the space telescope, we also need a huge amount of data collected from Earth to determine the distances of galaxies.

“In order to collate all this data, we need long-term collaboration between observatories and data centers around the world, but once it is finished, it will also offer scientists the best material for research into the structure of the universe,” says a University Lecturer Aku Venhola from the University of Oulu.

“Data-intensive computation is a swiftly growing field within science. The Finnish Euclid science data center is a spearhead example of this,” says Director Janne Ignatius from CSC, the IT Center for Science.

“The development of efficient methods of data analysis poses cross-discipline challenges between cosmology and IT,” adds Associate Professor Maarit Korpi-Lagg from Aalto University.

Finnish researchers have especially developed methods for computing statistical measures like correlation functions to describe the structure of the universe. After the launch, the Finnish supercomputing center will be responsible for processing 5% of the data from Euclid.

Finnish partners in Euclid are the University of Helsinki, the University of Turku, the University of Oulu, the University of Jyväskylä, Aalto University, and CSC Ltd.

Euclid will start collecting the measurements three months after the launch. The first measurement period will last one year, after which 14 months has been set aside for analysis. The first results from the Euclid project are expected by the end of 2025.

Scientists from the University of Ottawa have invented a unique method to create better molecule-based magnets, known as single-molecule magnets (SMMs). This synthetic tour de force has resulted in a two-coordinate lanthanide complex which has magnet-like properties that are intrinsic to the molecule itself. This discovery opens the door to high-density hard disks, quantum supercomputing applications, and the creation of faster and more compact memory devices. 

Lanthanide ions like to surround themselves with many organic ligands to stabilize and fill their coordination sphere. But thanks to a novel ligand design and synthetic approach, uOttawa scientists have managed to not only isolate the rare and precious two-coordinate species but also to reveal, for the first time, a huge energy level separation, just as theory had predicted. This complex is a synthetic achievement that shows the incredible potential of these molecules.

The research took place at the Department of Chemistry and Biomolecular Sciences at the University of Ottawa and was led by Muralee Murugesu, a full professor at the Faculty of Science, in collaboration with Professor Akseli Mansikkamäki from the University of Oulu, Finland, and with uOttawa post-doctoral fellows Diogo A. Gálico and Alexandros A. Kitos, as well as doctoral students Dylan Errulat and Katie L. M. Harriman. 

“We have shown very exciting results that confirm for the first time what theory had predicted before and also offer a synthetic way to make better molecular magnets. These magnets are very useful for making smaller and faster memory devices and quantum computers because they have nanoscale sizes and special quantum features, such as quantum tunneling of the magnetization or quantum coherence,” said Professor Murugesu.

A Game-Changing Discovery

“We used our CFI-funded equipment to measure the magnetic and luminescent properties of our complexes at very low temperatures, below 10 Kelvin. These measurements showed us the intricate electronic structure of our complexes. We also confirmed our findings with computational studies in collaboration with Professor Mansikkamäki at the University of Oulu, Finland,” adds Professor Murugesu.

Since 2007, the Murugesu Group at the University of Ottawa has been working on single-molecule magnets (SMMs) that can store and process information at the molecular level. This highly anticipated material promises to save energy and space to make electronics faster and better, which could change the way data is stored and usher in a new era of molecular electronics.