Actin-related proteins are ubiquitous components of chromatin remodelers and are conserved from yeast to man. We have examined the role of the budding yeast actin-related protein Arp6 in gene expression, both as a component of the SWR1 complex (SWR-C) and in its absence. We mapped Arp6 binding sites along four yeast chromosomes using chromatin immunoprecipitation from wild-type and swr1 deleted (swr1Δ) cells. We find that a majority of Arp6 binding sites coincide with binding sites of Swr1, the catalytic subunit of SWR-C, and with the histone H2A variant Htz1 (H2A.Z) deposited by SWR-C. However, Arp6 binding detected at centromeres, the promoters of ribosomal protein (RP) genes, and some telomeres is independent of Swr1 and Htz1 deposition. Given that RP genes and telomeres both show association with the nuclear periphery, we monitored the ability of Arp6 to mediate the localization of chromatin to nuclear pores. Arp6 binding is sufficient to shift a randomly positioned locus to nuclear periphery, even in a swr1Δ strain. Arp6 is also necessary for the pore association of its targeted RP promoters possibly through cell cycle-dependent factors. Loss of Arp6, but not Htz1, leads to an up-regulation of these RP genes. In contrast, the pore-association of GAL1 correlates with Htz1 deposition, and loss of Arp6 reduces both GAL1 activation and peripheral localization. We conclude that Arp6 functions both together with the nucleosome remodeler Swr1 and also without it, to mediate Htz1-dependent and Htz1-independent binding of chromatin domains to nuclear pores. This association is shown to have modulating effects on gene expression.

## This work is dedicated to the memory of Dr Shigeki Mizuno, an outstanding scientist, an excellent teacher (to M.H., N.S. and Y.O.) and a dear friend (to U.W.). AbstractChromatin remodelling and histone-modifying complexes govern the modulation of chromatin structure. While components of these complexes are diverse, nuclear actinrelated proteins (Arps) have been repeatedly found in these complexes from yeast to mammals. In most cases, Arps are required for functioning of the complexes, but the molecular mechanisms of nuclear Arps have as yet been largely unknown. The Arps and actin, sharing a common ancestor, are supposed to be highly similar in the three-dimensional structure of their core regions, including the ATP-binding pocket. The Arp Act3p/Arp4p of Saccharomyces cerevisiae exists within the nucleus, partly as a component of several high molecular mass complexes, including the NuA4 histone acetyltransferase (HAT) complex, and partly as uncomplexed molecules. We observed that mutations in the putative ATP-binding pocket of Act3p/Arp4p increased its concentration in the high molecular mass complexes and, conversely, that an excess of ATP or ATPγ S led to the release of wild-type Act3p/Arp4p from the complexes. These results suggest a requirement of ATP binding by Act3p/Arp4p for its dissociation from the complexes. In accordance, a mutation in the putative ATP binding site of Act3p/Arp4p inhibited the conversion of the NuA4 complex into the smaller piccoloNuA4, which does not contain Act3p/Arp4p and exhibits HAT activity distinct from that of NuA4. Although the in vitro binding activity of ATP by recombinant Act3p/Arp4p was found to be rather weak, our observations, taken together, suggest that the ATP-binding pocket of Act3p/Arp4p is involved in the function of chromatin modulating complexes by regulating their dynamics.

Background: The current study aims to predict the recurrence of cervical cancer patients treated with radiotherapy from radiomics features on pretreatment T1- and T2-weighted MR images. Methods: A total of 89 patients were split into model training (63 patients) and model testing (26 patients). The predictors of recurrence were selected using the least absolute shrinkage and selection operator (LASSO) regression. The machine learning used neural network classifiers. Results: Using LASSO analysis of radiomics, we found 25 features from the T1-weighted and 4 features from T2-weighted MR images, respectively. The accuracy was highest with the combination of T1- and T2-weighted MR images. The model performances with T1- or T2-weighted MR images were 86.4% or 89.4% accuracy, 74.9% or 38.1% sensitivity, 81.8% or 72.2% specificity, and 0.89 or 0.69 of the area under the curve (AUC). The model performance with the combination of T1- and T2-weighted MR images was 93.1% accuracy, 81.6% sensitivity, 88.7% specificity, and 0.94 of AUC. Conclusions: The radiomics analysis with T1- and T2-weighted MR images could highly predict the recurrence of cervix cancer after radiotherapy. The variation of the distribution and the difference in the pixel number at the peripheral and the center were important predictors.

This study showed that (13)C-uracil has desirable pharmacokinetic properties as an in vivo probe of gastric emptying. It is thus suggested that the (13)C-uracil breath test may be useful for the measurement of gastric emptying in humans.

【Objective】 To predict the recurrence of advanced cervical cancer patients treated with radiotherapy from radiomics features on pre-treatment T1- and T2-weighted MRI images. 【Methods】 A total of 90 patients were split into two sets: 67 patients for model training and 23 patients for model testing. The patient outcome was classified into two groups; patients with a recurrence (group I) and without a recurrence (group II). The predictors were selected using the least absolute shrinkage and selection operator (LASSO) regression. The machine learning for the predictive models was sued neural network classifiers. The accuracy, sensitivity, specificity, and the area under the curve (AUC) from the receiver operating characteristic were evaluated. 【Results】 By the LASSO analysis, we found 25 radiomics features from the T1-weighted MRI image and 4 radiomics features from the T2-weighted MRI image. The accuracy of the prediction model was highest with the combination of T1- and T2-weighted MRI images. The model performances with T1-weighted MRI image and T2-weighted MRI image were 86.4% and 89.4% of accuracy, 74.9% and 38.1% of sensitivity, 81.8% and 72.2% of specificity, and 0.89 and 0.69 of AUC. The model performance was improved with the combination of T1- and T2-weighted MRI images, which was 93.1% of accuracy, 81.6% of sensitivity, 88.7% of specificity, and 0.94 of AUC. 【Conclusions】 The radiomics analysis with T1- and T2-weighted MRI images could highly predict the recurrence of the cervix cancer after radiotherapy. The variation of the distribution and the difference of the pixel number at the peripheral and the center were important predictors.