https://www.sciencedirect.com/science/article/pii/S0895435621001323
Archive for the 'SciLit' Category
How to use likelihood ratios to interpret evidence from randomized trials – ScienceDirect
November 30, 2025Rare genetic variants confer a high risk of ADHD and implicate neuronal biology | Nature
November 23, 2025https://www.nature.com/articles/s41586-025-09702-8
Demontis, D., Duan, J., Hsu, Y. H., Pintacuda, G., Grove, J., Nielsen, T. T., Thirstrup, J., Martorana, M., Botts, T., Satterstrom, F. K., Bybjerg-Grauholm, J., Tsai, J. H. Y., Glerup, S., Hoogman, M., Buitelaar, J., Klein, M., Ziegler, G. C., Jacob, C., Grimm, O., . . . Børglum, A. D. (2025). Rare genetic variants confer a high risk of ADHD and implicate neuronal biology. Nature.
https://doi.org/10.1038/s41586-025-09702-8
QT:{{”
Common genetic variants associated with the disorder have been identified12,13, but the role of rare variants in ADHD is mostly unknown. Here, by analysing rare coding variants in exome-sequencing data from 8,895 individuals with ADHD and 53,780 control individuals, we identify three genes (MAP1A, ANO8 and ANK2; P < 3.07 × 10−6; odds ratios 5.55–15.13) that are implicated in ADHD.
“}}
Follow-up on error-controlled hypothesis generation
November 22, 2025Chen, W., Jiang, Y., Noble, W. S., & Lu, Y. Y. (2025).
Error-controlled non-additive interaction discovery in machine learning models. Nature Machine Intelligence, 7(9), 1541–1554. https://doi.org/10.1038/s42256-025-01086-8
Crystal structure of globular domain of histone H5 and its implications for nucleosome binding – PubMed
October 19, 2025The International Human Epigenome Consortium: A Blueprint for Scientific Collaboration and Discovery: Cell
October 18, 2025Capstone reviews/perspectives for reference
**IHEC**
The International Human Epigenome Consortium: A Blueprint for Scientific Collaboration and Discovery
Hendrik G. Stunnenberg ∙ The International Human Epigenome Consortium4 ∙ Martin Hirst
Stunnenberg, H. G., Hirst, M., Abrignani, S., Adams, D., De Almeida, M., Altucci, L., Amin, V., Amit, I., Antonarakis, S. E., Aparicio, S., Arima, T., Arrigoni, L., Arts, R., Asnafi, V., Esteller, M., Bae, J., Bassler, K., Beck, S., Berkman, B., . . . Zipprich, G. (2016). The International Human Epigenome Consortium: a blueprint for Scientific collaboration and Discovery. Cell, 167(5), 1145–1149.
https://doi.org/10.1016/j.cell.2016.11.007
** EXRNA**
The Extracellular RNA Communication Consortium: Establishing Foundational Knowledge and Technologies for Extracellular RNA Research
Das, S., Ansel, K. M., Bitzer, M., Breakefield, X. O., Charest, A., Galas, D. J., Gerstein, M. B., Gupta, M., Milosavljevic, A., McManus, M. T., Patel, T., Raffai, R. L., Rozowsky, J., Roth, M. E., Saugstad, J. A., Van Keuren-Jensen, K., Weaver, A. M., Laurent, L. C., Abdel-Mageed, A. B., . . . Zhang, H. (2019). The Extracellular RNA Communication Consortium: Establishing foundational knowledge and technologies for extracellular RNA research. Cell, 177(2), 231–242. https://doi.org/10.1016/j.cell.2019.03.023
**ENCODE3**
Perspectives on ENCODE
The ENCODE Project Consortium, Michael P Snyder 1,2,✉, Thomas R Gingeras 3, Jill E Moore 4, Zhiping Weng 4,5,6, Mark B Gerstein 7, Bing Ren 8,9, Ross C Hardison 10, John A Stamatoyannopoulos 11,12,13, Brenton R Graveley 14, Elise A Feingold 15, Michael J Pazin 15, Michael Pagan 15, Daniel A Gilchrist 15, Benjamin C Hitz 1, J Michael Cherry 1, Bradley E Bernstein 16, Eric M Mendenhall 17,18, Daniel R Zerbino 19, Adam Frankish 19, Paul Flicek 19, Richard M Myers 18
Abascal, F., Acosta, R., Addleman, N. J., Adrian, J., Afzal, V., Aken, B., Ai, R., Akiyama, J. A., Jammal, O. A., Amrhein, H., Anderson, S. M., Andrews, G. R., Antoshechkin, I., Ardlie, K. G., Armstrong, J., Astley, M., Banerjee, B., Barkal, A. A., Barnes, I. H. A., . . . Myers, R. M. (2020).
Perspectives on ENCODE. Nature, 583(7818), 693–698.
https://doi.org/10.1038/s41586-020-2449-8
A computational pipeline for spatial mechano-transcriptomics | Nature Methods
September 7, 2025https://www.nature.com/articles/s41592-025-02618-1
Hallou, A., He, R., Simons, B. D., & Dumitrascu, B. (2025). A computational pipeline for spatial mechano-transcriptomics. Nature Methods. https://doi.org/10.1038/s41592-025-02618-1
Reviews:
https://www.nature.com/articles/s41580-023-00583-1#Sec35
(difficult to follow)
Combining with Spatial transcriptomics:
https://www.nature.com/articles/s41592-025-02618-1
(new thing)
Human exposure to PM10 microplastics in indoor air | PLOS One
July 30, 2025https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0328011
Yakovenko, N., Pérez-Serrano, L., Segur, T., Hagelskjaer, O., Margenat, H., Roux, G. L., & Sonke, J. E. (2025). Human exposure to PM10 microplastics in indoor air. PLOS One.
https://doi.org/10.1371/journal.pone.0328011
Gene name errors are widespread in the scientific literature | Genome Biology | Full Text
July 26, 2025https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-1044-7
Ziemann, M., Eren, Y., & El-Osta, A. (2016). Gene name errors are widespread in the scientific literature. Genome Biology, 17(1). https://doi.org/10.1186/s13059-016-1044-7
Scalable emulation of protein equilibrium ensembles with generative deep learning | Science
July 12, 2025https://www.science.org/doi/10.1126/science.adv9817
Lewis, S., Hempel, T., Jiménez-Luna, J., Gastegger, M., Xie, Y., Foong, A. Y. K., Satorras, V. G., Abdin, O., Veeling, B. S., Zaporozhets, I., Chen, Y., Yang, S., Foster, A. E., Schneuing, A., Nigam, J., Barbero, F., Stimper, V., Campbell, A., Yim, J., . . . Noé, F. (2025, July 10). Scalable emulation of protein equilibrium ensembles with generative deep learning. Science.
https://www.science.org/doi/10.1126/science.adv9817
Aβ∗56 is a stable oligomer that impairs memory function in mice – PMC
June 26, 2025https://pmc.ncbi.nlm.nih.gov/articles/PMC10905009/
Liu, P., Lapcinski, I. P., Hlynialuk, C. J., Steuer, E. L., Loude, T. J., Shapiro, S. L., Kemper, L. J., & Ashe, K. H. (2024). Aβ∗56 is a stable oligomer that impairs memory function in mice. iScience, 27(3), 109239. https://doi.org/10.1016/j.isci.2024.109239
Aβ∗56 is a ∼56-kDa, SDS-stable, A11-reactive, non-plaque-dependent, water-soluble, brain-derived oligomer containing canonical Aβ(1-40).
linkstream2 microblog 