The most effective solutions to the world’s many challenges requires us to work across disciplines and across sectors
Peer-Reviewed Publication
Updates every hour. Last Updated: 28-Oct-2025 08:11 ET (28-Oct-2025 12:11 GMT/UTC)
There are many examples of options to tackle various global challenges that have been implemented in ways that only consider the impact on the challenge they are meant to address. Because of this narrow way of thinking, we are missing out on potential synergies that would help us to deliver to multiple challenges simultaneously. Designing options from the outset to co-deliver to multiple challenges would improve efficiency and reduce total cost. It is vital that we progress beyond narrow ways of thinking, and to adopt a “nexus” approach to tackling global challenges.
A landmark study in China covering 42,703 families affected by rare diseases across 32 provincial regions of China has established a new diagnosis framework for rare diseases. It offers new hope to millions of patients struggling with delayed or incorrect diagnoses.
Researchers developed a deep learning-based multimodal prognostic model that shows strong potential to improve disease-free survival prediction and enable personalized treatment in locally advanced cervical cancer.
The study reveals that Migrion, a chimeric structure of virus and migrasome as an unprecedented unit of viral transmission that integrates viral dissemination with cell migration, providing fresh perspectives on infection dynamics.
Prof. Lijun Zhu and Prof. Xiangrong Wang have shown that unusual magnetoresistance (UMR) arises from interfacial electron scattering, a mechanism called two-vector magnetoresistance. This spin-current-free model explains giant UMR and many experimental observations more consistently than the traditional spin Hall magnetoresistance theory. Their work, published in National Science Review, establishes a unified physical origin of UMR in spintronic systems.
In the quest for sustainable and efficient water treatment solutions, a new study titled "Enhanced Machine Learning Prediction of Biochar Adsorption for Dyes: Parameter Optimization and Experimental Validation" is making significant strides. This research leverages the power of machine learning to optimize the adsorption capabilities of biochar for dye removal, offering a promising approach to tackling water pollution.
Diesel engines have long been a cornerstone of transportation and industry, but their emissions have posed significant environmental and health challenges. A new study titled "Advancements in Diesel Emission Reduction Strategies: A Focus on Water-in-Diesel Emulsion Technology" explores innovative solutions to reduce harmful emissions while enhancing engine performance. This research delves into the potential of water-in-diesel emulsion (WiDE) technology, offering a promising pathway to a cleaner, more efficient future.
Shipping is a vital component of global trade, but its environmental impact extends beyond the well-known emissions of carbon dioxide. A new study titled "Global Distribution and Warming Effect of Brown Carbon from Shipping Emissions" sheds light on the often-overlooked role of brown carbon in contributing to global warming. This research provides a comprehensive analysis of the distribution and radiative effects of brown carbon, a pollutant emitted by ships that has significant climate implications.
In August, the first issue of Volume 31 of Tsinghua Science and Technology was released on SciOpen, an academic publishing platform developed by Tsinghua University Press. This move marks a new chapter for the journal.