Injectable breast ‘implant’ offers alternative to traditional surgeries

american Chemical Society

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This gooey paste contains modified human skin cells and could restore breast volume by filling in spaces left after tumor removal.

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Credit: Adapted from ACS Applied Bio Materials 2025, DOI: 10.1021/acsabm.5c01538

Removing part or all of the breast during breast cancer treatment is a potential outcome for some people. Reconstructive surgical procedures often involve prosthetic implants or transplanted tissue from elsewhere in the body. So, researchers reporting in ACS Applied Bio Materials developed a prototype injectable paste derived from human skin cells that could help restore breast volume after tumor removal, with less scarring and shorter healing time than current options.

“By promoting blood vessel growth and tissue remodeling while keeping inflammation low and reducing capsular contracture, the injectable acellular matrix could make breast reconstruction safer, less invasive and more accessible, thereby improving long-term comfort and cosmetic outcomes for patients,” says Pham Ngoc Chien, one of the study’s lead researchers.

During breast cancer treatment, cancerous cells and damaged tissue are often taken out, sometimes resulting in complete removal of the breast. For those who want to keep their breast volume, physicians turn to breast-conserving surgical techniques, where the remaining tissue is rearranged to account for space left by the tumor removal. Sometimes, skin and fat are even donated from other parts of the body to fill in the gaps left behind, like a skin graft. Though this technique preserves the shape of the breast for the patient, it leaves a scar where the tissue was donated from.

An alternative strategy involves acellular dermal matrix (ADM) — skin that has been processed to remove the outermost layer. This leaves a material with important cellular components for healing, including collagen, elastin and growth factors. Currently, ADM is available primarily in sheet form for tendon repair or plastic surgery, but Chien, Chan-Yeong Heo and colleagues wanted to create an injectable form of ADM that would be suitable for space-filling reconstructive breast surgery.

The researchers took a sample of skin donated by a living female participant and processed it through a series of steps including decellularizing, freezing and pulverizing to form small ADM particles. Then they added water to the particles to form a thick paste. The team injected small amounts of this paste into rats to test its biocompatibility and compared it to two commercially available ADM products. After a six-month period, the rats presented no adverse health effects. In fact, the animals treated with the new ADM paste had thinner layers of tissue form around the injected material than the rats treated with the commercially available product. Thinner tissue layers are preferable in breast implant procedures because they’re less likely to cause complications such as infections or hematomas.

Longer-term safety trials and more complex tests are necessary before this material could be considered for clinical use. But the researchers say that this work highlights the potential of their ADM implant to improve breast reconstruction surgery.

The authors acknowledge funding from the Korean Ministry of Trade, Industry, and Energy. The use of human skin samples was approved by the Institutional Review Board of Seoul Asan Hospital.

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Journal

ACS Applied Bio Materials

DOI

10.1021/acsabm.5c01538 

Article Title

“Development and Evaluation of an Injectable Acellular Dermal Matrix for Breast Reconstruction”

 

Location, location, location: Model IDs best spots for offshore energy projects

North Carolina State University

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Researchers have developed a computational model that identifies the best combination of location and energy technologies to maximize offshore energy production, reducing the financial risk associated with investing in offshore projects. The model accounts for different types of wind and marine hydrokinetic technologies, the best location for co-siting these technologies, and the best size of the relevant technologies.

“Offshore energy technologies – such as marine hydrokinetic devices that convert the the ocean’s tides, current and waves into electricity – hold tremendous potential for producing sustainable energy at a reasonable cost,” says Anderson de Queiroz, co-author of a paper on the work and an associate professor of civil, construction and environmental engineering at North Carolina State University. “We also know that putting wind turbines and marine hydrokinetic devices in the same location makes it possible to ensure a reliable flow of energy from offshore sites.

“However, the initial cost of building these offshore sites is considerable, so it is important for utilities to know that a project is going to maximize the return on their investment,” de Queiroz says. “That’s where our work comes in.”

The researchers have developed a model called a portfolio optimization framework. If a utility is considering a range of possible locations for an offshore power facility, the model can determine not only which location is best suited for maximizing energy output, but which combination of wind and hydrokinetic technologies would be able to make the most of that location. The model demonstrated in this paper focused on the use of wind turbines and marine hydrokinetic kites.

“Kites are a subset of hydrokinetic devices that use underwater sails to spin turbines, generating electricity from the movement of the ocean,” de Queiroz says. “However, the model can be modified to account for a range of other marine hydrokinetic technologies.”

To demonstrate the potential of their portfolio optimization framework, the researchers conducted a case study focusing on coastal North Carolina. The case study drew on a wide range of data, covering variables such as windspeeds, ocean currents, the depth of each location, distance from shore, and so on.

“We found that location makes a tremendous difference,” de Queiroz says. “Some places work well for wind turbines, but not for kites; other places work well for kites, but not for turbines.

“But when you find a location that works for both turbines and kites, there are two significant benefits,” de Queiroz says. “First, the cost of energy generation goes down significantly. Second, the stability of energy production goes up – the turbines offset periods when hydrokinetic energy production goes down, and the hydrokinetic devices offset periods when wind production goes down. It really underscores the difference our model can make in terms of maximizing investment in offshore power.

“We’re open to working with the energy sector to help them explore how they might use the model to inform long-term planning decisions related to sustainability and energy security,” says de Queiroz.

The paper, “Fused Portfolio Optimization for Harnessing Marine Renewable Energy Resources,” is published open access in the journal Energy. Corresponding author of the study is Mary Maceda, a Ph.D. student at NC State. The paper was co-authored by Rob Miller, a Ph.D. student at NC State; Victor de Faria, a recent Ph.D. graduate from NC State; Matthew Bryant, a professor of mechanical and aerospace engineering at NC State; and Chris Vermillion, an associate professor of mechanical engineering at the University of Michigan.

This research was done with support from the North Carolina Renewable Ocean Energy Program.

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Journal

Energy

DOI

10.1016/j.energy.2025.139660 

Method of Research

Computational simulation/modeling

Subject of Research

Not applicable

Article Title

Fused Portfolio Optimization for Harnessing Marine Renewable Energy Resources

 

Scientists sound alarm on erosion of long-term environmental data

Researchers highlight urgent need for institutional protection of ecological research amid rising data manipulation and political interference

American Institute of Biological Sciences

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A new Special Report published in the journal BioScience warns that long-term ecological and evolutionary research faces severe threats from lack of recurring funding and governmental/institutional support, to data manipulation and political interference, even as these studies become more crucial for addressing issues of broad societal importance, such as biodiversity loss and climate change.

Led by Vincent A. Viblanc of CNRS Écologie & Environnement in France, the report documents how "in early 2025, several leading environmental datasets maintained by national agencies in countries recently marked by electoral shifts were abruptly taken offline or replaced with curated versions that obscure or distort previously accessible information."

The authors argue that "now more than ever, as manipulated facts and societal distrust in science are increasingly guiding mis- and disinformed politics, governmental programs are urgently needed to support data collection, establish data-grounded facts, inform political spheres, and refuel trust with society at large."

The report highlights the CNRS SEE-Life program as a flagship model for institutional commitment to long-term science. Through sustained recurrent funding, SEE-Life support  79 long-term ecological studies across 28 French research centers and a network of over 100 international partners. Together more than 500 species across all major biomes are monitored, generating exceptional longitudinal datasets spanning 10 to 100 years, with unique longitudinal data ranging from 10 to 100 years of data. To date, the program has produced over 3000 publications and trained over 4900 scientists, including more than 800 PhD students and postdoctoral fellows, constituting one of the most comprehensive long term biodiversity data sets worldwide.

The authors emphasize the enormous economic stakes, noting that healthy ecosystems provide services "estimated at some US$125 trillion per year," while biological invasions alone cost "US$1.288 trillion in 2017 value over 1970–2017."

The authors warn that "when long-term data becomes a target, our ability to understand—and respond to—global environmental change is profoundly compromised."

The full report is available at: https://doi.org/10.1093/biosci/biaf175

 

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Journal

BioScience

DOI

10.1093/biosci/biaf175 

Method of Research

Meta-analysis

Subject of Research

Not applicable

Article Title

Science at Risk: The Urgent Need for Institutional Support of Long-Term Ecological and Evolutionary Research in an Era of Data Manipulation and Disinformation

Article Publication Date

5-Jan-2026

 

Decision-ready forecasts: Bridging climate science and real-world action

Scientists develop decision-ready tools based on subseasonal forecasts

Institute of Atmospheric Physics, Chinese Academy of Sciences

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The cover art weaves together scenes of prosperity—from public health and harvests to emerging sectors like low-altitude economy and clean energy—alongside climate‑intensified storms and wildfires. These elements collectively point to the core theme: subseasonal prediction. This critical forecasting window bridges science and society, offering actionable foresight to support both resilience and sustainable development, as detailed in the landmark UNESCO‑endorsed SEPRESS program review.

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Credit: Advances in Atmospheric Sciences

Subseasonal forecasts,  which predict weather conditions from ten days to two months ahead, are emerging as a powerful tool in the fight against climate-related risks. Striking a balance between short-term precision and long-term planning, these forecasts hit a “sweet spot” for actionable, science-based decision-making. While traditional weather forecasts focus on the next few days, and seasonal outlooks stretch over several months, subseasonal predictions offer a timely middle ground — and one that could be transformative for both governments and industries, if communicated effectively.

A recent review and outlook paper published in Advances in Atmospheric Sciences on January 5 presents how scientists can bridge the gap between complex forecast data and real-world decisions to turn raw climate intelligence into life-saving, economy-boosting action.

“Subseasonal forecasting better balances accuracy and timeliness. It provides sufficiently detailed predictive information while allowing ample time for early warnings and effective decision-making,” said Jing Yang, first author of the study and a professor at Beijing Normal University in Beijing, China.

The advantages are clear: businesses can optimize operations and reduce losses, while governments can better prepare for climate disasters, safeguarding lives and infrastructure. Yet despite its game-changing potential, subseasonal data often remains underutilized. Both the private and public sector may hesitate to make potentially costly decisions based on complex and uncertain forecasts.

“The core challenge is transforming professional meteorological forecast data into tailored, actionable decision-making information for different industries,” said Mengqian Lu, corresponding author of the study and a professor at the Hong Kong University of Science and Technology in Hong Kong. “Establishing a standardized and transferrable 'supply-demand interaction framework' for climate services is vital, and it must be scalable across industries, avoid redundancy, and bring science directly into decision-making process”.

The accuracy of subseasonal predictions depends on many variables. For dangerous weather patterns, heatwaves and wildfires can be predicted up to four weeks out, tropical cyclones two to three weeks out, and floods one to two weeks out. For sustainability efforts, subseasonal forecasts can be used to help manage crop yield, conserve water resources, predict wind and solar energy, and predict sea ice impacts on shipping. All of these different forecasts will include unique complexities that the end user may need help interpreting.

That's where decision-ready tools come in.

 The study recommends new forms of "actionable outputs" — such as risk maps that combine forecast data with local infrastructure, population vulnerability, and resilience metrics. For instance: Wildfire risk maps could show not just the likelihood of fire, but the severity and confidence level of the forecast. Extreme rainfall maps could integrate rainfall intensity, frequency, and probability with flood-prone infrastructure and population density.  

The goal is not just to predict risk — but to communicate it clearly and credibly.

Looking ahead, researchers hope to continue to develop this framework for the real world. “The ultimate goal is to achieve the real-world application of atmospheric science, transforming scientific and technological advancements into economic and social value. Against the backdrop of climate change, we aim to effectively enhance disaster prevention and mitigation efforts as well as optimize resource utilization, thereby developing actionable pathways to genuinely achieve sustainable development goals,” said Lu.

The study also forms part of the UNESCO "International Decade of Sciences for Sustainable Development" (2024–2033) initiative and serves as a key starting point for the "Seamless Prediction and Services Program for Sustainable Natural and Human Environments" (SEPRESS, 2025–2032). The SEPRESS program aims to achieve close integration between scientific research and practical applications through advanced and reliable seamless weather-climate prediction, thereby promoting the sustainable development of global natural and human environments.

Other contributors include Anling Liu, Yuxian Pan, Shentong Li, Xinyao Feng, Shiyu Zhang, and Lu Tang at Beijing Normal University; Tat Fan Cheng, Lun Dai, Wen Deng, and Lujia Zhang at the Hong Kong University of Science and Technology; Miaoni Gao and Han Li at Nanjing University of Information Science and Technology; Tao Zhu and Qing Bao at the Chinese Academy of Sciences; Andrew W. Robertson at Columbia University; Tsz-cheung Lee at Hong Kong Observatory; Frederic Vitart at the European Centre for Medium-Range Weather Forecasts; Ping Liang at the China Meteorological Administration; Jun Jian at the Dalian Maritime University; Linlin Pan at the China Electric Power Research Institute; Stacey New at Arizona State University; Lei Wang at State Key Laboratory of Disaster Prevention and Reduction for Power Grid; Qichao Yao at the Ministry of Emergency Management of China; Xiaolong Jia at the National Climate Center; Xi Liang at the Ministry of Natural Resources, and Yaochi Su at Jiangmen Meteorological Service.

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Journal

Advances in Atmospheric Sciences

DOI

10.1007/s00376-025-5256-1 

Article Title

The “Last-mile Efforts” of Subseasonal Prediction and Services for Climate Resilience and Sustainability: Review and Outlook

Article Publication Date

5-Jan-2026