Proteolysis-targeting chimeras (PROTACs) are molecules that can eliminate disease-causing proteins, but developing them is often slow and complex, limiting how quickly new candidates can be tested. Now, researchers from Tokyo University of Science have developed a three-step "click chemistry" assembly line that rapidly builds functional PROTACs from simple building blocks. The resulting molecules successfully degraded a target protein in cells, paving the way for faster, more flexible development of protein-targeting therapeutics.

Power factor correction (PFC) circuits are ubiquitous in consumer electronics. In a new study, researchers from Chonnam National University present a simple, sensorless control method for boost PFC that eliminates the need for current sensors, thereby reducing cost, noise, and complexity while maintaining high performance. By deriving a new duty cycle equation that only requires voltage measurements and introducing delay compensation, the method demonstrates strong performance in a 1.3 kW prototype across various loads.

In a groundbreaking study, researchers have captured real-time "molecular movies" showing how an enzyme changes shape during catalysis. Using an advanced technique called mix-and-inject serial crystallography at Japan's SACLA X-ray free-electron laser facility, the team observed domain movements and structural changes in the enzyme, copper amine oxidase enzyme over millisecond timescales, revealing dynamics that are nearly impossible to observe by other methods.

35 million euros, 210 scientists, 12 years of research: after the maximum duration of three funding periods, the Transregional Collaborative Research Centre TRR 142 ‘Tailor-made non-linear photonics: From fundamental concepts to functional structures’ is officially winding down in December 2025. Scientists at Paderborn University and TU Dortmund University have achieved great things and literally shone a light into darkness with their research contributions.

Professor Nicholas X. Fang, Jockey Club STEM Professor in the Department of Mechanical Engineering, Faculty of Engineering, and Professor Xiang Zhang, HKU President and Vice-Chancellor, and Chair of Physics in the Department of Physics, Faculty of Science, have been jointly awarded the 2025 Brillouin Medal by the International Phononics Society (IPS). The honour recognises their pioneering discovery of ultrasonic metamaterials with negative elastic modulus.

Natural sunscreens shield the skin from harmful radiation, without triggering allergic reactions. In a recently published study, a group of researchers has discovered a novel compound, β-glucose-bound hydroxy mycosporine-sarcosine, which is produced in thermal cyanobacteria under UV-A/UV-B and salt stress. This compound has a unique biosynthesis pathway, which is different from the typical mycosporine-like amino acids (MAAs) biosynthesis mechanism. This discovery aids industrial biotechnology in the production of natural UV-filter compounds.

Abstract

Purpose – The primary objective of this research is to develop new algorithms in the framework of deep neural networks for the valuation of options under dynamics driven by stochastic volatility models. We aim to use the Heston model for equity options to demonstrate the accuracy of our approach.

Design/methodology/approach – Physics-informed neural networks (PINNs) are trained to minimize a loss function that includes terms from the partial differential equation residuals, initial condition and boundary conditions evaluated at selected points in the space-time domain. Speed and accuracy comparisons are carried out against single hidden-layer neural networks, called physics-informed extreme learning machines (PIELMs). American options are formulated as linear complementarity problems, and PINNs are applied in conjunction with penalty methods for the computation of the option prices.

Findings – For American options under the Heston model, PINNs yield accurate prices. Computed Greeks sensitivities are in close agreement with those reported for mesh-based methods. In contrast to mesh-based penalty methods for American options, PINNs work with smaller values of the penalty term. For the real estate index American option problem, numerical prices obtained using PINNs have comparable accuracies as those obtained by a high-order radial basis functions finite difference scheme.

Practical implications – There is a lack of reliable pricing models for pricing property derivatives. This work contributes to developing accurate neural network algorithms.