A new meta-analysis led by researchers in Japan investigates whether lithium (LIT) supplementation can slow cognitive decline in individuals with mild cognitive impairment (MCI) or Alzheimer’s disease (AD). Building on preclinical evidence of LIT’s neuroprotective effects, the study systematically evaluates data from six randomized controlled trials to clarify its clinical potential. The findings aim to shed light on whether LIT, long used in psychiatry, could play a future role in MCI or AD prevention or treatment.

Researchers have developed a graph-based expert system that improves the accuracy and prediction stability of automated bank reconciliation. By modelling historical transactional data as a network graph, the system can learn complex one-to-many matching scenarios that existing tools often fail to predict correctly. The findings point to more reliable automation for high-risk domains such as finance and accounting.

Magnetic skyrmions are particle-like objects that can be used as information carriers in memory and computing devices. Researchers from Waseda University recently studied the flow behaviors of many skyrmions in structured magnets and found that skyrmions can behave like chiral fluids. They proposed that fully developed skyrmion flows can be used for fluidics, which significantly reduces complexity of skyrmion logic, as it eliminates the need for deterministic creation, precise control, and detection of individual skyrmions.

Researchers at the University of Waterloo have developed a machine learning approach that could help public health officials anticipate disease outbreaks by analyzing vaccine skepticism on social media. Using the mathematical concept of tipping points, the team showed that online misinformation spreads much like a contagion and can signal heightened outbreak risk well before illness appears. Their model, tested on posts from California ahead of a 2014 measles outbreak, detected early warning patterns that traditional tweet-counting methods missed. This work supports Waterloo’s efforts to strengthen evidence-based decision-making and rebuild public trust in science, and the model could eventually be adapted across platforms like TikTok and Instagram to help identify communities nearing a critical shift in vaccination sentiment.