The era of AI requires new educational taxonomies that prepare AI natives for personal and professional success. In a new breakthrough, a researcher from the Educational University of Hong Kong has proposed, in TAO, the novel SCALE taxonomy that integrates scientific literacy, computational thinking, AI literacy, learning to learn/metacognition, and engineering and design thinking. It equips AI natives to engage in meaningful experiences and promotes “authentic learning through creating” in the age of AI.

A new study published in Frontiers of Engineering Management presents a novel blockchain-enabled Open BIM data exchange paradigm based on a traceable semantic differential transaction (tSDT) approach. The tSDT approach minimizes data redundancy and enables semantic-level traceability of BIM changes. A Blockchain 3.0 application named openBIMdisk implements the tSDT approach and provides an intuitive and user-friendly interface for BIM practitioners.

This study evaluates virtual 3D scanned prosections in gross anatomy education. Twenty-nine medical students were divided into physical or virtual teaching groups. Both groups showed significant post-test score improvements, with no significant difference between them. While students found 3D scans effective for learning and exam preparation, they preferred dissection for lab experience. Results indicate virtual 3D scans are a valuable supplementary tool but not a replacement for traditional dissection in medical education. 

Teacher emotion recognition (TER) is crucial for classroom dynamics, yet limited by scarce multimodal data and feature modeling. We present a multimodal TER dataset with 102 lessons and 2,170 video segments, annotated with interaction-based emotional tags. We propose an Emotion Dual-Space Network (EDSN) with a Commonality Space (ECSC) using central moment differences to align modalities, and a Discrimination Space (EDSC) using gradient reversal and orthogonal projection to extract unique features. EDSN achieves 77.0% accuracy and 0.769 F1-score on the dataset, outperforming state-of-the-art models, demonstrating its effectiveness in educational emotion recognition. 

This study determined cryo-EM structures of midnolin-proteasome complexes, providing mechanistic insights to midnolin-catalyzed substrate degradation. Based on structural and mechanistic understanding, authors have engineered the midnolin system for targeted degradation of desired substrates, and provide the first proof-of-principle for degrading a non-native therapeutically high-profile target that is otherwise undruggable.

Mitochondrial DNA mutations cause muscle cells to struggle with energy production, forcing them to rely more on glycolysis and produce excess lactate. Far from being just a waste product, lactate acts as a signal that changes how genes work. Recently, researchers from Qilu Hospital of Shandong University have found that lactate modifies histones in muscle, turning on the stress-response factor GDF15. This work has been published in Science Bulletin, and the new discovery reveals how lactate helps muscles adapt to mitochondrial stress and points to new directions for treating mitochondrial diseases.

Advancements in molecular characterization technologies have accelerated targeted cancer therapy research at unprecedented resolution and dimensionality. Integrating comprehensive multi-omic molecular profiling of a tumor, proteogenomics, marks a transformative milestone for preclinical cancer research. In this paper, we initially provided an overview of proteogenomics in cancer research, spanning genomics, transcriptomics, and proteomics. Subsequently, the applications were introduced and examined from different perspectives, including but not limited to genetic alterations, molecular quantifications, single-cell patterns, different post-translational modification levels, subtype signatures, and immune landscape. We also paid attention to the combined multi-omics data analysis and pan-cancer analysis. This paper highlights the crucial role of proteogenomics in preclinical targeted cancer therapy research, including but not limited to elucidating the mechanisms of tumorigenesis, discovering effective therapeutic targets and promising biomarkers, and developing subtype-specific therapies.