Mariko oi biography sample
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UM171 glues asymmetric CRL3–HDAC1/2 assembly to degrade CoREST corepressors
Main
Degraders are small molecules capable of promoting the ubiquitination and degradation of proteins4,5. These compounds are classified into two categories: the monovalent molecular glues (glues) and the bifunctional proteolysis targeting chimeras (PROTACs). Besides their more drug-like properties, glue degraders are distinct from PROTACs by being capable of inducing high-affinity interactions between an E3 ubiquitin ligase and a neosubstrate without showing detectable affinity to at least one of these protein partners6. Although rapid progress has been made in the logisk design of PROTACs, the development of glue degraders has been protracted due to poor understanding of their functional prerequisites and E3 scaffold preferences. The plant hormones auxin and jasmonate are the first documented glue degraders, which co-opt the F-box proteins—substrate receptors of CUL1–RING ligase (CRL1) complexes
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What Japanese history lessons leave out
"Students learn about the extent of the damage caused by Japan in many countries during the war as well as sufferings that the Japanese people had to experience especially in Hiroshima, Nagasaki and Okinawa in order to understand the importance of international co-operation and peace.
"Based on our guideline, each school decides which specific events they focus on depending on the areas and the situation of the school and the students' maturity."
Matsuoka, however, thinks the government deliberately tries not to teach young people the details of Japan's atrocities.
Having experienced history education in two countries, the way history is taught in Japan has at least one advantage - students come away with a comprehensive understanding of when events happened, in what order.
In many ways, my schoolfriends and I were lucky. Because junior high students were all but guaranteed a place in the senior high school, no
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Summary
Patient heterogeneity precludes cancer treatment and drug development; hence, development of methods for finding prognostic markers for individual treatment is urgently required. Here, we present Pasmopy (Patient-Specific Modeling in Python), a computational framework for stratification of patients using in silico signaling dynamics. Pasmopy converts texts and sentences on biochemical systems into an executable mathematical model. Using this framework, we built a model of the ErbB receptor signaling network, trained in cultured cell lines, and performed in silico simulation of 377 patients with breast cancer using The Cancer Genome Atlas (TCGA) transcriptome datasets. The temporal dynamics of Akt, extracellular signal-regulated kinase (ERK), and c-Myc in each patient were able to accurately predict the difference in prognosis and sensitivity to kinase inhibitors in triple-negative breast cancer (TNBC). Our model applies to any type of signaling network and facilitates t