ASIC1a Protein Mapping for Novel Stroke Treatments

A three-dimensional visualization of ASIC1a, a membrane protein linked to brain function and stroke, displayed on a computer in the lab of Isabelle Baconguis, Ph.D., at OHSU. New research revealed six major conformations of the protein, providing a potential blueprint for future drug development.
Photo Credit: OHSU/Christine Torres Hicks

Scientific Frontline: Extended "At a Glance" Summary: Mapping the ASIC1a Membrane Protein

The Core Concept: Researchers have successfully mapped six major conformations of human acid-sensing ion channel 1a (ASIC1a), a critical brain membrane protein associated with learning, memory, fear-related behavior, and stroke-induced tissue damage.

Key Distinction/Mechanism: Acid-sensing ion channels respond directly to variations in extracellular pH. During neuronal injuries such as strokes, the localized drop in brain tissue pH activates the ASIC1a channels, which subsequently triggers cellular damage.

Major Frameworks/Components:

• Cryo-Electron Microscopy (Cryo-EM): The advanced structural imaging technology used to capture the protein's intricate, three-dimensional states.
• Recombinant DNA Technology: Utilized to express the specific human gene and generate the human proteins required for high-resolution imaging.
• Conformational Plasticity: The six distinct structural states of the protein, which were captured by systematically altering environmental acidity.

Ultrasound-Controlled Supramolecular Cages

Ultrasound activates polymer chains and transmits mechanical forces through supramolecular nanostructures. This enables molecular cages to be selectively opened and drugs to be released.
Image Credit: © HHU / Tim David

Scientific Frontline: Extended "At a Glance" Summary: Ultrasound-Activated Supramolecular Cages

The Core Concept: Researchers have developed intelligent, palladium-based molecular nanostructures that can be selectively opened, disassembled, and reassembled using mechanical forces generated by ultrasound.

Key Distinction/Mechanism: Unlike traditional dynamic molecules that rely on chemical or thermal triggers, these supramolecular cages are appended with flexible polymer chains that act as molecular ropes. When subjected to ultrasound irradiation, these chains harvest and transmit mechanical energy directly into the nanostructure's scaffold, precisely breaking the palladium-nitrogen bonds to release encapsulated cargo.

Major Frameworks/Components:

• Self-Assembled \(Pd_nL_{2n}\) Supramolecular Architectures: Three-dimensional coordination cages that serve as secure, customizable containers for molecular freight.
• Polymer-Decorated Mechanophores: Flexible polymer chain appendages designed to capture ultrasonic wave energy and translate it into targeted directional force.
• Machine-Learning Interatomic Potentials: Advanced computational simulations optimized specifically for metal-ligand bonds, enabling rapid and highly accurate modeling of bond-breakage forces across thousands of atoms without the processing bottlenecks of traditional quantum chemical calculations.

Manganese Spintronics: Light-Switched Data Storage

A coin-sized area of the new material is illuminated through a mask: The spins change their state, and the material changes color.
Illustration Credit: ©: Katja Heinze / JGU

Scientific Frontline: Extended "At a Glance" Summary: Switching Spin States in Manganese Ions

The Core Concept: Researchers have synthesized a novel manganese-based molecular material that allows for the stable switching of electron spin states using light, functioning as a highly compact data storage device.

Key Distinction/Mechanism: Unlike traditional iron-containing molecular memory devices that max out at temperatures around 130 Kelvin, this new material utilizes manganese. By combining manganese ions with N-heterocyclic carbene ligands, the strong chemical bond stabilizes the low-spin state and creates a high energy barrier. When irradiated with light, the electrons change spin states (shifting the material's color from dark red to light yellow), and thes magnetic data persists at higher temperatures (approximately minus 132 degrees Celsius) even after the light source is removed.

Major Frameworks/Components:

• Spintronics: The study and exploitation of the intrinsic spin of the electron and its associated magnetic moment for solid-state devices.
• Binary Spin States: The alignment of individual electron spins in either a parallel (high-spin) or antiparallel (low-spin) configuration, acting as digital "1s" and "0s."
• N-Heterocyclic Carbene Ligands: Specific chemical ligands used to bind strongly to the manganese ions, thereby widening the energy barrier between the distinct spin states.
• Photomagnetic Relaxation/Switching: The mechanism by which incoming light is utilized to physically alter the electron spin states and write digital information into the material.

Nondestructive Testing Paves Way for Genetic Analysis of Historical Parchments

Photo Credit: Nash Dunn, NC State University.

Scientific Frontline: Extended "At a Glance" Summary: Nondestructive Genetic Analysis of Historical Parchments

The Core Concept: A novel, nondestructive methodology utilizing dry cytology brushes to extract cellular and genetic material from ancient animal-skin parchments without compromising the physical integrity of the historical artifacts.

Key Distinction/Mechanism: Unlike traditional sampling methods that require physically excising or damaging portions of rare manuscripts, this technique employs non-abrasive swabbing combined with forensic-level, next-generation DNA sequencing to harvest and amplify trace genetic sequences safely.

Major Frameworks/Components: 

• Dry cytology brush cellular extraction
• Forensic-level, next-generation sequencing (NGS) and genetic amplification
• Interdisciplinary synthesis of humanities (medieval history) and hard sciences (genetics, population health)

Researchers engineer a light-powered biohybrid cardiac interface

The study’s lead author, Yuyao Kuang, who recently earned a Ph.D. in chemical and biomolecular engineering at UC Irvine, is a member of the research group headed by Herdeline “Digs” Ardoña that developed an optoelectronic biohybrid cardiac interface that can be used in heart drug screening and treatments.
Photo Credit: Steve Zylius / UC Irvine

Scientific Frontline: Extended "At a Glance" Summary: Light-Powered Biohybrid Cardiac Interface

The Core Concept: The light-powered biohybrid cardiac interface is an advanced polymeric device that utilizes light to electrically and mechanically control living heart tissue without the use of traditional metal electrodes.

Key Distinction/Mechanism: Unlike conventional metal electrode-based cardiac stimulation, which can cause tissue damage and contamination over time, this device uses optoelectronic polymer films to convert pulses of visible green light directly into localized electrical currents. Furthermore, it operates distinctly from optogenetics, as it stimulates native, unmodified cardiac tissue without requiring the genetic modification of cells to introduce light-sensitive proteins.

Major Frameworks/Components: 

• Optoelectronic Polymer Film: A blend of conjugated polymers layered on an elastomeric base, featuring donor-acceptor junctions capable of generating surface photocurrents upon illumination.
• Composite Interface Layer: A specialized layer situated between the active polymer and the biological environment to enhance charge transport, aqueous stability, and cellular compatibility.
• Micropatterned Cardiac Cells: Neonatal rat ventricular myocytes cultured in an anisotropic arrangement to accurately replicate the organized fiber architecture of native heart muscle.
• Cantilever Geometry: The assembly of the layers into a muscular thin film that allows for the direct observation and precise quantification of bending motions and mechanical function triggered by light pulses.

Engineered yeast gives the U.S. a green edge in the critical minerals market

Researchers genetically engineered the metabolic pathways in yeast to produce oxalic acid, which can be used to extract free rare earth elements from low-grade ore.
Graphic Credit: Courtesy Dan Herchek/LLNL

Scientific Frontline: Extended "At a Glance" Summary: Engineered Yeast for Rare Earth Element Recovery

The Core Concept: A novel, environmentally sustainable biomanufacturing process that utilizes genetically engineered yeast to produce oxalic acid, which is subsequently used to extract and purify free rare-earth elements (REEs) from low-grade ore.

Key Distinction/Mechanism: Conventional oxalic acid production relies on strong acids and generates environmentally hazardous byproducts. In contrast, this new method employs a low-pH-tolerant yeast strain (Issatchenkia orientalis) with modified metabolic pathways to convert glucose directly into oxalic acid. The resulting fermentation broth acts as an oxidizer that selectively binds to REEs, precipitating them into a solid state with over 99% efficiency while leaving unwanted "junk" metals (like zinc) dissolved in solution.

Origin/History: It was developed through a collaboration between the University of Illinois Urbana-Champaign, Lawrence Livermore National Laboratory (LLNL), and the University of Kentucky, in response to a Defense Advanced Research Projects Agency (DARPA) solicitation aimed at utilizing environmental microbes as bioengineering resources.

Researchers create a never-before-seen molecule and prove its exotic nature with quantum computing

Dyson orbital for electron attachment, calculated using quantum hardware.
Image Credit IBM Research and the University of Manchester.

Scientific Frontline: "At a Glance" Summary: Half-Möbius Topology Molecule

• Main Discovery: Scientists synthesized and characterized a single molecule with a half-Möbius electronic topology, representing the first experimental observation of electrons traveling through a structure in a previously unknown corkscrew-like pattern.
• Methodology: The molecule was assembled atom-by-atom from a custom precursor using precisely calibrated voltage pulses under ultra-high vacuum at near-absolute-zero temperatures, while scanning tunneling microscopy, atomic force microscopy, and an IBM quantum computer were utilized to validate its properties.
• Key Data: The engineered molecule features the chemical formula \(C_{13}Cl_2\) and exhibits an electronic structure that undergoes a 90-degree twist with each circuit, requiring a 32-electron quantum simulation and four complete molecular loops to return to its starting phase.
• Significance: The experiment proves that electronic topology can be deliberately engineered rather than merely found in nature, establishing topology as a switchable degree of freedom for controlling material behaviors and chemical interactions at the molecular scale.
• Future Application: The ability to reversibly switch such molecules between clockwise-twisted, counterclockwise-twisted, and untwisted states offers a powerful new route for developing advanced quantum-centric supercomputing workflows and engineering targeted material properties for next-generation electronics and data storage.
• Branch of Science: Computational Chemistry, Quantum Physics, Solid-State Physics, and Molecular Science.
• Additional Detail: High-fidelity quantum computing simulations identified that a helical pseudo-Jahn-Teller effect is the specific mechanism responsible for the formation of this unprecedented half-Möbius electronic topology.

Scientists develop molecules that may treat Crohn’s disease

Broad scientists designed molecules (pictured in teal) that can bind CARD9 (white with red and blue), a protein linked to inflammatory bowel disease.
Image Credit: Rush et al. Cell. DOI: 10.1016/j.cell.2025.12.013

Scientific Frontline: "At a Glance" Summary

• Main Discovery: Researchers developed small-molecule drug candidates that mimic a rare, protective variant of the CARD9 gene to treat Crohn's disease and other inflammatory bowel diseases.
• Methodology: The team utilized a "binder-first" strategy, screening 20 billion molecules to identify binders to the CARD9 coiled-coil domain, followed by X-ray crystallography and competitive binding assays to isolate compounds that block inflammatory signaling.
• Key Data: The initial library screen evaluated over 20 billion compounds, ultimately yielding molecules that significantly reduced inflammation in both human immune cells and a mouse model expressing the human CARD9 gene.
• Significance: This work validates a complete "genetics-to-therapeutics" pipeline, proving that scaffolding proteins previously considered "undruggable" can be effectively targeted by mimicking naturally occurring protective variants.
• Future Application: Immediate efforts focus on optimizing these compounds for human clinical trials, while the broader methodology provides a blueprint for developing drugs against other difficult genetic targets.
• Branch of Science: Chemical Biology, Immunology, Genetics, and Molecular Biology.
• Additional Detail: The development strategy parallels the success of PCSK9 inhibitors for cholesterol, leveraging the safety profile of a natural genetic variant to guide drug design.

Scientists identify target to treat devastating brain disease

Using near-atomic imaging, OHSU researchers mapped where disease-associated autoantibodies bind to the extracellular domain of the NMDA receptor. The highlighted region — colored yellow through red, based on how frequently it is targeted — reveals small areas of the receptor recognized by autoantibodies in both mice and people with anti-NMDAR encephalitis, making it a promising target for future treatments.
Photo Credit: OHSU/Christine Torres Hicks

Scientific Frontline: Extended "At a Glance" Summary

The Core Concept: Researchers have identified specific "hot spots" on the NMDA receptor where disease-causing autoantibodies bind, pinpointing a precise target for treating the autoimmune condition often called "Brain on Fire" (anti-NMDA receptor encephalitis).

Key Distinction/Mechanism: Current treatments rely on broad immunosuppression, which can be inconsistent and cause significant side effects. This discovery uses near-atomic imaging to map the exact locations on the receptor's extracellular domain where the attack occurs. By identifying these specific binding sites, scientists aim to develop therapies that block the autoantibodies directly rather than suppressing the entire immune system.

Origin/History: The study was published on January 14, 2026, in the journal Science Advances by a team at Oregon Health & Science University (OHSU).

Major Frameworks/Components:

• NMDA Receptor: A critical neurotransmitter receptor in the brain responsible for memory and learning, which becomes the target of the autoimmune attack.
• Cryo-Electron Microscopy (Cryo-EM): The high-resolution imaging technology used to visualize the receptor and antibody interactions at a near-atomic level.
• Comparative Modeling: Researchers confirmed the relevance of their findings by matching autoantibody binding sites in engineered mice with those found in human patients.

Why It Matters: This discovery opens the door to the first targeted drug therapies for anti-NMDA receptor encephalitis, potentially offering a cure that prevents relapse and avoids the risks of long-term immunosuppression. Additionally, these specific markers could lead to blood tests that allow for earlier diagnosis and intervention.

More sustainable epoxy thanks to phosphorus

Empa researcher Arvindh Sekar with the novel epoxy resin that is both flame-retardant and recyclable.
 Photo Credit: Empa

Scientific Frontline: "At a Glance" Summary

• Main Discovery: Empa researchers developed a novel epoxy resin based on a phosphonate ester vitrimer that combines flame-retardancy with full recyclability and repairability, effectively overcoming the permanent crosslinking limitations of traditional thermosets.
• Mechanism: The resin incorporates a functional phosphonate ester molecule that forms a dynamic polymer network; these reversible crosslinks allow the material to melt and be reshaped under specific heat conditions, unlike standard epoxies which burn or decompose.
• Key Properties: The modified material retains the high mechanical hardness and thermal stability of conventional epoxy resins while gaining "self-healing" capabilities, enabling the repair of surface scratches and cuts through the application of heat and pressure.
• Context: Unlike standard fiber-reinforced plastics that are typically incinerated or landfilled, this vitrimer allows for the complete separation and recovery of valuable reinforcement materials, such as carbon fibers, from the polymer matrix.
• Significance: This innovation enables a circular economy for crosslinked polymers, offering immediate applications in lightweight, fire-safe composites for aerospace and rail, as well as transparent protective coatings for wooden flooring.

Machine learning drives drug repurposing for neuroblastoma

Daniel Bexell leads the research group in molecular pediatric oncology, and Katarzyna Radke, first author of the study.
Photo Credit: Lund University

Using machine learning and a large volume of data on genes and existing drugs, researchers at Lund University in Sweden have identified a combination of statins and phenothiazines that is particularly promising in the treatment of the aggressive form of neuroblastoma. The results from experimental trials showed slowing of tumor growth and higher survival rates. 

The childhood cancer, neuroblastoma, affects around 15-20 children in Sweden every year. Most of them fell ill before the age of five. Neuroblastoma is characterized by, among other things, tumors that are often resistant to drug treatment, including chemotherapy. The disease exists in both mild and severe forms, and the Lund University researchers are mainly studying the aggressive form, high-risk neuroblastoma. This variant is the form of childhood cancer with the lowest survival rate. 

Molecular Science: In-Depth Description

Image Credit: Scientific Frontline / AI generated

Molecular Science is the cross-disciplinary study of the structure, properties, composition, reactions, and functional arrangements of molecules. This broad field integrates principles from chemistry, physics, and biology to understand how atoms interact to form matter and how molecular interactions govern natural phenomena. Its primary goal is to elucidate the fundamental rules of molecular behavior to manipulate matter at the nanoscale, enabling the design of new materials, medicines, and energy systems.

Surfing on the waves of the microcosm

A particle (red sphere) is guided from left to its destination (right) using a laser trap (double-cone) by means of a protocol developed in the study, which is described by the parameter λ. A known time-dependent external force field F (t) acts on this environment. The optimised protocol exploits this force field in a way that extracts the maximum amount of work. This can be applied to various external fields, to active particles and to micro-robot transport problems. 
Image Credit: HHU/Kristian S. Olsen

Conditions can get rough in the micro- and nanoworld. To ensure that e.g. nutrients can still be optimally transported within cells, the minuscule transporters involved need to respond to the fluctuating environment. Physicists at Heinrich Heine University Düsseldorf (HHU) and Tel Aviv University in Israel have used model calculations to examine how this can succeed. They have now published their results – which could also be relevant for future microscopic machines – in the scientific journal Nature Communications. 

When planning an ocean crossing, sailors seek a course, which makes optimum use of favorable wind and ocean currents, and maneuver to save time and energy. They also react to random fluctuations in wind and currents and take advantage of fair winds and waves. Such considerations regarding energy costs are also important for transport processes at the micro- and nanoscale. For example, molecular motors should use as little energy as possible when transporting nutrients from A to B between and within biological cells.  

A New Kind of Copper from the Research Reactor

In front of the nuclear reactor at TU Wien
Photo Credit: © TU Wien

The copper isotope Cu-64 plays an important role in medicine: it is used in imaging processes and also shows potential for cancer therapy. However, it does not occur naturally and must be produced artificially — a complex and costly process. Until now, Cu-64 has been generated by bombarding nickel atoms with protons. When a nickel nucleus absorbs a proton, it is transformed into copper. At TU Wien, however, a different pathway has now been demonstrated: Cu-63 can be converted into Cu-64 by neutron irradiation in a research reactor. This works thanks to a special trick — so-called “recoil chemistry.” 

Rice engineers show lab grown diamond films can stop costly mineral buildup in pipes

Pulickel Ajayan and Xiang Zhang
Photo Credit: Jeff Fitlow/Rice University

In industrial pipes, mineral deposits build up the way limescale collects inside a kettle ⎯ only on a far larger and more expensive scale. Mineral scaling is a major issue in water and energy systems, where it slows flow, strains equipment and drives up costs.

A new study by Rice University engineers shows that lab-grown diamond coatings could resolve the issue, providing an alternative to chemical additives and mechanical cleaning, both of which offer only temporary relief and carry environmental or operational downsides.

“Because of these limitations, there is growing interest in materials that can naturally resist scale formation without constant intervention,” said Xiang Zhang, assistant research professor of materials science and nanoengineering and a first author on the study alongside Rice postdoctoral researcher Yifan Zhu. “Our work addresses this urgent need by identifying a coating material that can ‘stay clean’ on its own.”

Molecules assem­bled by hand

Weakly bound KCs molecules are transferred into what is known as their “absolute ground state”.
Image Credit: University of Innsbruck

Researchers from Hanns-Christoph Nägerl's group have produced the world’s first ultracold KCs molecules in their absolute ground state. Starting by mixing clouds of potassium and caesium atoms cooled almost to absolute zero temperature, they were able to use a combination of magnetic fields and laser beams to associate pairs of freely moving atoms into chemically stable molecules. 

As many of us remember from chemistry classes, molecules can only be produced in chemical reactions, which always occur at unpredictable, random times. We may also remember that higher temperatures make reactions faster, and sufficiently low temperatures may stop reactions from taking place altogether. These statements do not apply if chemistry is conducted by physicists. In the last 20 years, several different types of molecules have been produced in gaseous mixtures at temperatures close to absolute zero, using methods that narrow the exact time at which the molecules are made to a few microseconds. Until recently, KCs remained a gaping hole in the table of possible element combinations that have already been turned into molecules in this way. 

New recharge-to-recycle reactor turns battery waste into new lithium feedstock

A photo of the electrochemical cell set-up in the Rice lab
Photo Credit: Jorge Vidal/Rice University

As global electric vehicle adoption accelerates, end-of-life battery packs are quickly becoming a major waste stream. Lithium is costly to mine and refine, and most current recycling methods are energy- and chemical-intensive, often producing lithium carbonate that must be further processed into lithium hydroxide for reuse.

Instead of smelting or dissolving shredded battery materials (“black mass”) in strong acids, a team of engineers at Rice University has developed a cleaner approach by recharging the waste cathode materials to coax out lithium ions into water, where they combine with hydroxide to form high-purity lithium hydroxide.

“We asked a basic question: If charging a battery pulls lithium out of a cathode, why not use that same reaction to recycle?” said Sibani Lisa Biswal, chair of Rice’s Department of Chemical and Biomolecular Engineering and the William M. McCardell Professor in Chemical Engineering. “By pairing that chemistry with a compact electrochemical reactor, we can separate lithium cleanly and produce the exact salt manufacturers want.”

The Power of Geckos: TU Wien Solves the Puzzle of Large Molecules

An example for large molecules with Van-der-Waals forces
Image Credit: Technische Universität Wien

A puzzle in theoretical chemistry has been solved at TU Wien: a new computational method now makes it possible to calculate the forces between large molecules with unprecedented accuracy.

Why can geckos walk up walls? Why does nitrogen become liquid at –196 °C? Many everyday phenomena can be explained by van der Waals forces – weak bonds between molecules that are notoriously difficult to calculate. For years, scientists have struggled with the fact that different computational methods produced conflicting results.

Now, researchers at TU Wien have resolved this discrepancy and found a solution. Ironically, it was the very method long considered the “gold standard” of quantum chemistry that turned out to be the source of the error: it systematically overestimates the energy contained in certain molecular bonds. With an improved variant, the TU Wien team can now correctly predict the behavior of large molecules – an essential step for understanding biological systems and for advancing renewable energy technologies.

Nanopore signals, machine learning unlocks new molecular analysis tool

Illustration of voltage-matrix nanopore profiling. The artistic rendering depicts proteins (colored shapes) being analyzed by solid-state nanopores under varying voltage conditions. By combining nanopore signals with machine learning, researchers can discriminate protein mixtures and detect changes in molecular populations.
Image Credit: ©2025 Sotaro Uemura, The University of Tokyo

Understanding molecular diversity is fundamental to biomedical research and diagnostics, but existing analytical tools struggle to distinguish subtle variations in the structure or composition among biomolecules, such as proteins. Researchers at the University of Tokyo have developed a new analytical approach, which helps overcome this problem. The new method, called voltage-matrix nanopore profiling, combines multivoltage solid-state nanopore recordings with machine learning for accurate classification of proteins in complex mixtures, based on the proteins’ intrinsic electrical signatures.

The study, published in Chemical Science, demonstrates how this new framework can identify and classify “molecular individuality” without the need for labels or modifications. The research holds promise of providing a foundation that could lead to more advanced and wider applications of molecular analysis in various areas, including disease diagnosis.

New AI Model for Drug Design Brings More Physics to Bear in Predictions

This illustration shows the mesh of anchoring points the team obtained by discretizing the manifold, an estimation of the distribution of atoms and the probable locations of electrons in the molecule. This is important because, as the authors note in the new paper, treating atoms as solid points "does not fully reflect the spatial extent that real atoms occupy in three-dimensional space."
Image Credit: Liu et al./PNAS

When machine learning is used to suggest new potential scientific insights or directions, algorithms sometimes offer solutions that are not physically sound. Take for example AlphaFold, the AI system that predicts the complex ways in which amino acid chains will fold into 3D protein structures. The system sometimes suggests "unphysical" folds—configurations that are implausible based on the laws of physics—especially when asked to predict the folds for chains that are significantly different from its training data. To limit this type of unphysical result in the realm of drug design, Anima Anandkumar, Bren Professor of Computing and Mathematical Sciences at Caltech, and her colleagues have introduced a new machine learning model called NucleusDiff, which incorporates a simple physical idea into its training, greatly improving the algorithm's performance.