Scientists from the Institut Pasteur have genetically analyzed the remains of former soldiers who retreated from Russia in 1812. They detected two pathogens, those responsible for paratyphoid fever and relapsing fever, which correlate with the symptoms described in historical accounts. The study was published as a preprint on bioRxiv on July 16, 2025. It will be published in the journal Current Biology on October 24.

In the summer of 1812, French emperor Napoleon Bonaparte led about half a million soldiers to invade the Russian Empire. But by December, only a fraction of the army remained alive. Historical records suggest that starvation, cold, and typhus led to their demise. In a new study publishing October 24 in the Cell Press journal Current Biology, a team of microbial paleogenomicists extracted DNA from the soldiers’ teeth and found no trace of typhus. Instead, they identified two pathogens known to cause enteric fever and relapsing fever—ailments which likely contributed to the army’s downfall. 

The hidden Markov model (HMM), a statistical model widely applied in machine learning, has proven effective in addressing various problems in bioinformatics. Once primarily regarded as a mathematical framework for modeling stochastic processes, HMMs have become indispensable tools for solving a wide range of biological sequence problems, from gene prediction to protein structure analysis.

In a comprehensive review published in the journal Immunity & Inflammation, a research team led by Professor Tao Dong at the University of Oxford systematically dissects the central role of T cells in anti-tumor immunity and sheds light on the next-generation cancer immunotherapies. The article, titled "Leveraging T cells for cancer immunotherapy," summarizes current understanding and highlights promising strategies to overcome the challenges that limit the efficacy of current treatments.