An RMIT innovation uses ultrasound to extract leaf protein from discarded cauliflower leaves, identifying a potential new use for vegetable scraps.

Idiopathic pulmonary fibrosis remains a hard-to-treat lung disease with limited effective drugs. A recent study in Engineering used machine learning to screen natural compounds and found dihydromyricetin, a flavonoid from herbs, can block the TGF-β/ALK5 signaling pathway. It alleviates fibrosis and inflammation in cell and mouse models, shows good safety, and offers a new natural-product-based direction for pulmonary fibrosis treatment.

Cardiac hypertrophy often progresses to heart failure, but the underlying link between lysosomes and mitochondria remains unclear. A new study in Engineering finds that the lysosomal protein TRPML1 is significantly reduced in hypertrophic hearts. It directly binds VDAC1 to maintain mitochondrial calcium balance and energy production, providing a potential target for treating pathological cardiac remodeling.

Hydraulic fracturing is moving from experience-based operations to intelligent control. A new study in Engineering introduces an AI-driven framework for subsurface hydraulic fracturing, featuring data-driven analysis, dynamic optimization, and autonomous decision-making. It uses dedicated deep learning models to predict fractures, warn of risks, and forecast production, forming a closed-loop intelligent system. The work also points out current challenges and future directions, supporting the digital shift in unconventional oil and gas development.

Wind turbine blades are hard to recycle, but a new study in Engineering offers a green solution. Researchers have developed a mild catalytic oxidation method to break down epoxy resin from waste blades at 100 °C with a small amount of catalyst. The degraded products directly become high-strength adhesives, while catalysts and fibers can be fully recovered. This eco-friendly approach turns hard-to-dispose waste into valuable materials, supporting the low-carbon and circular development of the wind power industry.

Polyurethane plastic is hard to biodegrade and brings big environmental pressure. A study in Engineering reveals the structure and catalytic mechanism of esterase Aes72, and creates an engineered variant F276A/L141I. This modified enzyme shows stronger activity to break down polyurethane materials, offering a greener enzymatic way for sustainable plastic waste recycling.

The Korea Research Institute of Standards and Science (KRISS, President Dr. Lee Ho Seong) has developed a robot-based ultrahigh-precision electromagnetic wave measurement system using its own system design and control technologies. The system can be applied in key fields such as defense, next-generation communications, and semiconductors.

Infantile epileptic spasms are among the most serious forms of epilepsy in early childhood, yet diagnosing them remains a major clinical challenge.

Today, seizure identification often depends on specialists reviewing hours of clinical video recordings. The process is time-consuming, resource-intensive, and difficult to scale, particularly in regions with limited access to pediatric neurology expertise.

To address this challenge, researchers developed a video-based AI system capable of automatically recognizing seizure-related movement patterns from patient videos.

Trained on a large clinical dataset, the model achieved more than 90% detection accuracy. In external validation studies, it demonstrated higher seizure-detection sensitivity than the average performance of six clinical experts from different medical centers.

The broader significance extends beyond algorithm performance. By transforming routine video recordings into a scalable screening and monitoring tool, such systems could support earlier diagnosis, reduce clinician workload, and expand access to specialized neurological assessment.

AI is not replacing clinicians. Rather, it offers a way to augment clinical expertise and help ensure that critical seizure events are less likely to be missed.

#AIinHealthcare #Neurology #Epilepsy #ComputerVision #DigitalHealth