The results suggest that chaperone-mediated autophagy, a cellular ‘selective cleaning’ system, could become a new therapeutic target. The study, published in Acta Neuropathologica Communications, was conducted using human tissues from clinical trials and opens new avenues for the development of treatments to slow the progression of ALS.

Cancer cells survive by repairing damage to their DNA—even damage that would normally be fatal. One of their most important defense systems is homologous recombination, a high-precision repair pathway that fixes broken DNA using key proteins such as RAD51 and CHK1. While therapies such as PARP inhibitors have successfully targeted this vulnerability, many tumors eventually regain their DNA repair ability and become resistant to treatment.

A research team led by Director MYUNG Kyungjae at the Center for Genomic Integrity within the Institute for Basic Science (IBS), in collaboration with LEE Joo-Yong (Chungnam University) has now uncovered a new strategy to overcome this resistance. Their findings show that cancer cells can be made vulnerable again—not by altering genetic mutations, but by destabilizing the DNA repair machinery itself.

As the spread of infectious diseases accelerates, technologies that can accurately distinguish multiple viruses in a single test are becoming increasingly important. KAIST and an international research team have developed a new diagnostic technology that simultaneously identifies various viruses and variants by controlling the “speed” of gene scissors. This technology is expected to transform responses to emerging infectious diseases, as it can detect multiple infections at once while reducing the complexity of testing procedures.

Two-year collaboration with CQT to develop and implement novel quantum algorithms for molecular discovery

Partnership will use Quantinuum H2 and Helios quantum computers to test key quantum chemistry algorithms

First successful implementation results released

The University of Texas MD Anderson Cancer Center today announced the appointment of Kim Slusser, Ph.D., R.N., as the institution’s inaugural chief nurse executive (CNE), effective May 1.

Background

Infections with liver flukes (Clonorchis sinensis, Opisthorchis viverrini, and O. felineus) cause high burden. Mechanistic models have been employed to disentangle their transmission dynamics and guide the design of control strategies. However, no comprehensive review of these mechanistic models has yet been undertaken.

Methods

In this systematic review, we searched six major databases (PubMed, Web of Science, Korea Med, Cochrane, China National Knowledge Infrastructure [CNKI], and Wanfang Data) for studies published up to 14 May 2025, to identify and evaluate mechanistic models of liver fluke infections. We included all mechanistic transmission models for human liver flukes regardless of language or setting, while excluded non-mechanistic models, reviews, and empirical studies.

Results

Of the 533 records identified, 18 studies were eligible for analysis. Most studies focused on C. sinensis in China and O. viverrini in Lao People’s Democratic Republic, primarily employing population-based model with ordinary differential equations. Findings consistently identified humans as the central reservoir sustaining transmission, while the role of animal reservoir hosts (e.g. cats and dogs) in transmission was less explored (in 6 out of 18 studies) and divergent in different models. Models incorporating host heterogeneity demonstrated the superiority of integrated control strategies-combining mass drug administration, health education, and environmental improvements over single intervention. High frequency, coverage and adherence of measures were shown to be critical for achieving control or even elimination targets.

Conclusion

Results from mechanistic models support the implementation of One Health strategies to improve liver fluke control. This review identifies the need for integrative, data-driven One Health modeling frameworks that incorporate human, animal, and environmental transmission parameters, and address key sources of heterogeneity in host behavior, exposure, and transmission dynamics to support control targets.