Diffusion Models for Probabilistic Deconvolution of Galaxy Images

Telescopes capture images with a particular point spread function (PSF). Inferring what an image would have looked like with a much sharper PSF, a problem known as PSF deconvolution, is ill-posed because PSF convolution is not an invertible transformation. Deep generative models are appealing for PSF deconvolution because they can infer a posterior distribution over candidate images that, if convolved with the PSF, could have generated the observation. However, classical deep generative models such as VAEs and GANs often provide inadequate sample diversity. As an alternative, we propose a classifier-free conditional diffusion model for PSF deconvolution of galaxy images. We demonstrate that this diffusion model captures a greater diversity of possible deconvolutions compared to a conditional VAE.Comment: Accepted to the ICML 2023 Workshop on Machine Learning for Astrophysic

Quantifying consensus of rankings based on q-support patterns

Rankings, representing preferences over a set of candidates, are widely used in many information systems, e.g., group decision making and information retrieval. It is of great importance to evaluate the consensus of the obtained rankings from multiple agents. An overall measure of the consensus degree provides an insight into the ranking data. Moreover, it could provide a quantitative indicator for consensus comparison between groups and further improvement of a ranking system. Existing studies are insufficient in assessing the overall consensus of a ranking set. They did not provide an evaluation of the consensus degree of preference patterns in most rankings. In this paper, a novel consensus quantifying approach, without the need for any correlation or distance functions as in existing studies of consensus, is proposed based on a concept of q-support patterns of rankings. The q-support patterns represent the commonality embedded in a set of rankings. A method for detecting outliers in a set of rankings is naturally derived from the proposed consensus quantifying approach. Experimental studies are conducted to demonstrate the effectiveness of the proposed approach

Resonant TMR inversion in LiF/EuS based spin-filter tunnel junctions

Resonant tunneling can lead to inverse tunnel magnetoresistance when impurity levels rather than direct tunneling dominate the transport process. We fabricated hybrid magnetic tunnel junctions of CoFe/LiF/EuS/Ti, with an epitaxial LiF energy barrier joined with a polycrystalline EuS spin-filter bar-rier. Due to the water solubility of LiF, the devices were fully packaged in situ. The devices showed sizeable positive TMR up to 16% at low bias voltages but clearly inverted TMR at higher bias voltages. The TMR inversion depends sensitively on the thickness of LiF, and the tendency of inversion disap-pears when LiF gets thick enough and recovers its intrinsic properties

Global research trends of diabetes remission: a bibliometric study

BackgroundResearch on diabetes remission has garnered prominence in recent years. However, to date, no pertinent bibliometric study has been published. This study sought to elucidate the current landscape and pinpoint potential new research directions through a bibliometric analysis of diabetes remission.MethodsWe perused relevant articles on diabetes remission from January 1, 2000, to April 16, 2023, in the Web of Science. We utilized CiteSpace software and VOSviewer software to construct knowledge maps and undertake analysis of countries, institutional affiliations, author contributions, journals, and keywords. This analysis facilitated the identification of current research foci and forecasting future trends.ResultsA total of 970 English articles were procured, and the annual publication volume manifested a steady growth trend. Most of the articles originated from America (n=342, 35.26%), succeeded by China and England. Pertaining to institutions, the University of Newcastle in England proliferated the most articles (n=36, 3.71%). Taylor R authored the most articles (n=35, 3.61%), and his articles were also the most co-cited (n=1756 times). Obesity Surgery dominated in terms of published articles (n=81, 8.35%). “Bariatric surgery” was the most prevalently used keyword. The keyword-clustering map revealed that the research predominantly centered on diabetes remission, type 1 diabetes, bariatric surgery, and lifestyle interventions. The keyword emergence and keyword time-zone maps depicted hotspots and shifts in the domain of diabetes remission. Initially, the hotspots were primarily fundamental experiments probing the feasibilities and mechanisms of diabetes remission, such as transplantation. Over the course, the research trajectory transitioned from basic to clinical concerning diabetes remission through bariatric surgery, lifestyle interventions, and alternative strategies.ConclusionOver the preceding 20 years, the domain of diabetes remission has flourished globally. Bariatric surgery and lifestyle interventions bestow unique advantages for diabetes remission. Via the maps, the developmental milieu, research foci, and avant-garde trends in this domain are cogently portrayed, offering guidance for scholars

TRIM56 promotes malignant progression of glioblastoma by stabilizing cIAP1 protein

Background The tripartite motif (TRIM) family of proteins plays a key role in the developmental growth and therapeutic resistance of many tumors. However, the regulatory mechanisms and biological functions of TRIM proteins in human glioblastoma (GBM) are not yet fully understood. In this study, we focused on TRIM56, which emerged as the most differentially expressed TRIM family member with increased expression in GBM. Methods Western blot, real-time quantitative PCR (qRT-PCR), immunofluorescence (IF) and immunohistochemistry (IHC) were used to study the expression levels of TRIM56 and cIAP1 in GBM cell lines. Co-immunoprecipitation (co-IP) was used to explore the specific binding between target proteins and TRIM56. A xenograft animal model was used to verify the tumor promoting effect of TRIM56 on glioma in vivo. Results We observed elevated expression of TRIM56 in malignant gliomas and revealed that TRIM56 promoted glioma progression in vitro and in a GBM xenograft model in nude mice. Analysis of the Human Ubiquitin Array and co-IPs showed that cIAP1 is a protein downstream of TRIM56. TRIM56 deubiquitinated cIAP1, mainly through the zinc finger domain (amino acids 21–205) of TRIM56, thereby reducing the degradation of cIAP1 and thus increasing its expression. TRIM56 also showed prognostic significance in overall survival of glioma patients. Conclusions TRIM56-regulated post-translational modifications may contribute to glioma development through stabilization of cIAP1. Furthermore, TRIM56 may serve as a novel prognostic indicator and therapeutic molecular target for GBM.publishedVersio

Identification of BST2 Contributing to the Development of Glioblastoma Based on Bioinformatics Analysis

Rigorous molecular analysis of the immune cell environment and immune response of human tumors has led to immune checkpoint inhibitors as one of the most promising strategies for the treatment of human cancer. However, in human glioblastoma multiforme (GBM) which develops in part by attracting immune cell types intrinsic to the human brain (microglia), standard immunotherapy has yielded inconsistent results in experimental models and patients. Here, we analyzed publicly available expression datasets to identify molecules possibly associated with immune response originating from or influencing the tumor microenvironment in primary tumor samples. Using three glioma datasets (GSE16011, Rembrandt-glioma and TCGA-glioma), we first analyzed the data to distinguish between GBMs of high and low tumor cell purity, a reflection of the cellular composition of the tumor microenvironment, and second, to identify differentially expressed genes (DEGs) between these two groups using GSEA and other analyses. Tumor purity was negatively correlated with patient prognosis. The interferon gamma-related gene BST2 emerged as a DEG that was highly expressed in GBM and negatively correlated with tumor purity. BST2high tumors also tended to harbor PTEN mutations (31 vs. 9%, BST2high versus BST2low) while BST2low tumors more often had sustained TP53 mutations (8 versus 36%, BST2high versus BST2low). Prognosis of patients with BST2high tumors was also poor relative to patients with BST2low tumors. Further molecular in silico analysis demonstrated that high expression of BST2 was negatively correlated with CD8+ T cells but positively correlated with macrophages with an M2 phenotype. Further functional analysis demonstrated that BST2 was associated with multiple immune checkpoints and cytokines, and may promote tumorigenesis and progression through interferon gamma, IL6/JAK/STAT3 signaling, IL2/STAT5 signaling and the TNF-α signaling via NF-kB pathway. Finally, a series of experiments confirmed that the expression of BST2 can be significantly increased by IFN induction, and knockdown of BST2 can significantly inhibit the growth and invasion of GBM cells, and may affect the phenotype of tumor-associated macrophages. In conclusion, BST2 may promote the progression of GBM and may be a target for treatment.publishedVersio