Nature, Published online: 14 April 2026; doi:10.1038/s41586-026-10493-9

Polyclonal selection of immune checkpoint mutations in thyroid autoimmunity

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A dual-symmetry-guided strategy is used to assemble a broad class of complex Archimedean lattices and two-dimensional quasicrystalline structures, providing a general and experimentally accessible route to complex-symmetry materials.

Nature, Published online: 25 March 2026; doi:10.1038/s41586-026-10291-3

New evidence suggests that diffusive oxygen transport through the tracheolar–muscle system is not the limiting factor on insect body size.

arXiv:2602.00086v3 Announce Type: replace-cross Abstract: This paper addresses stock price movement prediction by leveraging LLM-based news sentiment analysis. Earlier works have largely focused on proposing and assessing sentiment analysis models and stock movement prediction methods, however, separately. Although promising results have been achieved, a clear and in-depth understanding of the benefit of the news sentiment to this task, as well as a comprehensive assessment of different architecture types in this context, is still lacking. Herein, we conduct an evaluation study that compares 3 different LLMs, namely, DeBERTa, RoBERTa and FinBERT, for sentiment-driven stock prediction. Our results suggest that DeBERTa outperforms the other two models with an accuracy of 75% and that an ensemble model that combines the three models can increase the accuracy to about 80%. Also, we see that sentiment news features can benefit (slightly) some stock market prediction models, i.e., LSTM-, PatchTST- and tPatchGNN-based classifiers and PatchTST- and TimesNet-based regression tasks models.