An In Vivo Screen Identifies PYGO2 as a Driver for Metastatic Prostate Cancer

Advanced prostate cancer displays conspicuous chromosomal instability and rampant copy number aberrations, yet the identity of functional drivers resident in many amplicons remain elusive. Here, we implemented a functional genomics approach to identify new oncogenes involved in prostate cancer progression. Through integrated analyses of focal amplicons in large prostate cancer genomic and transcriptomic datasets as well as genes upregulated in metastasis, 276 putative oncogenes were enlisted into an in vivo gain-of-function tumorigenesis screen. Among the top positive hits, we conducted an in-depth functional analysis on Pygopus family PHD finger 2 (PYGO2), located in the amplicon at 1q21.3. PYGO2 overexpression enhances primary tumor growth and local invasion to draining lymph nodes. Conversely, PYGO2 depletion inhibits prostate cancer cell invasion in vitro and progression of primary tumor and metastasis in vivo In clinical samples, PYGO2 upregulation associated with higher Gleason score and metastasis to lymph nodes and bone. Silencing PYGO2 expression in patient-derived xenograft models impairs tumor progression. Finally, PYGO2 is necessary to enhance the transcriptional activation in response to ligand-induced Wnt/β-catenin signaling. Together, our results indicate that PYGO2 functions as a driver oncogene in the 1q21.3 amplicon and may serve as a potential prognostic biomarker and therapeutic target for metastatic prostate cancer.Significance: Amplification/overexpression of PYGO2 may serve as a biomarker for prostate cancer progression and metastasis. Cancer Res; 78(14); 3823-33. ©2018 AACR

Learnable Community-Aware Transformer for Brain Connectome Analysis with Token Clustering

Neuroscientific research has revealed that the complex brain network can be organized into distinct functional communities, each characterized by a cohesive group of regions of interest (ROIs) with strong interconnections. These communities play a crucial role in comprehending the functional organization of the brain and its implications for neurological conditions, including Autism Spectrum Disorder (ASD) and biological differences, such as in gender. Traditional models have been constrained by the necessity of predefined community clusters, limiting their flexibility and adaptability in deciphering the brain's functional organization. Furthermore, these models were restricted by a fixed number of communities, hindering their ability to accurately represent the brain's dynamic nature. In this study, we present a token clustering brain transformer-based model ($\texttt{TC-BrainTF}$) for joint community clustering and classification. Our approach proposes a novel token clustering (TC) module based on the transformer architecture, which utilizes learnable prompt tokens with orthogonal loss where each ROI embedding is projected onto the prompt embedding space, effectively clustering ROIs into communities and reducing the dimensions of the node representation via merging with communities. Our results demonstrate that our learnable community-aware model $\texttt{TC-BrainTF}$ offers improved accuracy in identifying ASD and classifying genders through rigorous testing on ABIDE and HCP datasets. Additionally, the qualitative analysis on $\texttt{TC-BrainTF}$ has demonstrated the effectiveness of the designed TC module and its relevance to neuroscience interpretations

Dynamical process of optically trapped singlet ground state 85^{85}Rb133^{133}Cs molecules produced via short-range photoassociation

We investigate the dynamical process of optically trapped X$^{1}$$\Sigma$$^{+}$ (v" = 0) state $^{85}$Rb$^{133}$Cs molecules distributing in J" = 1 and J" = 3 rotational states. The considered molecules, formed from short-range photoassociation of mixed cold atoms, are subsequently confined in a crossed optical dipole trap. Based on a phenomenological rate equation, we provide a detailed study of the dynamics of $^{85}$Rb$^{133}$Cs molecules during the loading and holding processes. The inelastic collisions of $^{85}$Rb$^{133}$Cs molecules in the X$^{1}$$\Sigma$$^{+}$ (v" = 0, J" = 1 and J" = 3) states with ultracold $^{85}$Rb (or $^{133}$Cs) atoms are measured to be 1.0 (2)$\times$10$^{-10}$ cm$^{3}$s$^{-1}$ (1.2 (3)$\times$ 10$^{-10}$ cm$^{3}$s$^{-1}$). Our work provides a simple and generic procedure for studying the dynamical process of trapped cold molecules in the singlet ground states.Comment: 4 figures, 8 page

A detailed study on the reflection component for the black hole candidate MAXI J1836−194

We present a detailed spectral analysis of the black hole candidate MAXI J1836−194. The source was caught in the intermediate state during its 2011 outburst by Suzaku and RXTE. We jointly fit the X-ray data from these two missions using the relxill model to study the reflection component, and a steep inner emissivity profile indicating a compact corona as the primary source is required in order to achieve a good fit. In addition, a reflection model with a lamp-post configuration (relxilllp), which is normally invoked to explain the steep emissivity profile, gives a worse fit and is excluded at 99 per cent confidence level compared to relxill. We also explore the effect of the ionization gradient on the emissivity profile by fitting the data with two relativistic reflection components, and it is found that the inner emissivity flattens. These results may indicate that the ionization state of the disc is not constant. All the models above require a supersolar iron abundance higher than ∼4.5. However, we find that the high-density version of reflionx can describe the same spectra even with solar iron abundance well. A moderate rotating black hole (a* = 0.84–0.94) is consistently obtained by our models, which is in agreement with previously reported values