Rifabutin corneal deposits localized to the deep stroma using anterior segment optical coherence tomography.

Purpose:To demonstrate that rifabutin-related corneal deposits are localized to the deep stroma using anterior segment optical coherence tomography (OCT) and confocal microscopy. Observations:A 55-year-old male with a history of human immunodeficiency virus (HIV) and disseminated mycobacterium avium complex on rifabutin treatment for 3 years presented with bilateral corneal deposits. Confocal microscopy and anterior segment OCT confirm that rifabutin-related corneal deposits are located in the deep stroma, rather than in the endothelium. Conclusions:And Importance: Rifabutin deposits localize to the deep corneal stroma, and can be seen with both confocal microscopy and anterior segment OCT. Anterior segment OCT is a widely available and easily used diagnostic tool, and can provide utility in the diagnosis of corneal deposits

Moduli spaces of semistable pairs on projective Deligne-Mumford stacks

We generalize the construction of a moduli space of semistable pairs parametrizing isomorphism classes of morphisms from a fixed coherent sheaf to any sheaf with fixed Hilbert polynomial under a notion of stability to the case of projective Deligne-Mumford stacks. We study the deformation and obstruction theories of stable pairs, and then prove the existence of virtual fundamental classes for some cases of dimension two and three. This leads to a definition of Pandharipande-Thomas invariants on three-dimensional smooth projective Deligne-Mumford stacks.Comment: Rewriting the Introductio

The orbifold DT/PT vertex correspondence

We present an orbifold topological vertex formalism for PT invariants of toric Calabi-Yau 3-orbifolds with transverse $A_{n-1}$ singularities. We give a proof of the orbifold DT/PT Calabi-Yau topological vertex correspondence. As an application, we derive an explicit formula for the PT $\mathbb{Z}_{n}$-vertex in terms of loop Schur functions and prove the multi-regular orbifold DT/PT correspondence.Comment: Some minor change

Design of Low-Density Parity-Check Code Pair for Joint Source-Channel Coding Systems Based on Graph Theory

AbstractIn this article, a graph-theoretic method (taking advantage of constraints among sets associated with the corresponding parity-check matrices) is applied for the construction of a double low-density parity-check (D-LDPC) code (also known as LDPC code pair) in a joint source-channel coding (JSCC) system. Specifically, we pre-set the girth of the parity-check matrix for the LDPC code pair when jointly designing the two LDPC codes, which are constructed by following the set constraints. The constructed parity-check matrices for channel codes comprise an identity submatrix and an additional submatrix, whose column weights can be pre-set to be any positive integer numbers. Simulation results illustrate that the constructed D-LDPC codes exhibit significant performance improvement and enhanced flexible frame length (i.e., adaptability under various channel conditions) compared with the benchmark code pair.Abstract In this article, a graph-theoretic method (taking advantage of constraints among sets associated with the corresponding parity-check matrices) is applied for the construction of a double low-density parity-check (D-LDPC) code (also known as LDPC code pair) in a joint source-channel coding (JSCC) system. Specifically, we pre-set the girth of the parity-check matrix for the LDPC code pair when jointly designing the two LDPC codes, which are constructed by following the set constraints. The constructed parity-check matrices for channel codes comprise an identity submatrix and an additional submatrix, whose column weights can be pre-set to be any positive integer numbers. Simulation results illustrate that the constructed D-LDPC codes exhibit significant performance improvement and enhanced flexible frame length (i.e., adaptability under various channel conditions) compared with the benchmark code pair

BPTF promotes glioma development through USP34-mediated de-ubiquitination of FOXC1

Glioma is the most prevalent malignant tumor of the brain, and the study of the molecular mechanisms associated with its development has important clinical significance. Our previous study found that BPTF promotes the malignant phenotype of glioma and is significantly associated with poor prognosis; the downstream regulatory mechanisms are explored in this study. Western blot and immuno-histochemical staining were used to detect protein expression in cells or tissues. BPTF knockdown as well as FOXC1-overexpressing lentiviruses were used in combination for the construction of the U251 cell model, leading to functional rescue experiments. CCK8 assay, flow cytometry, scratch assay, and Transwell assay were used to detect cell proliferation, apoptosis, and migration, respectively. Finally, immuno-precipitation assays, combined with western blot (WB), were used to detect the interaction between proteins as well as the level of ubiquitination modification. The obtained results suggested that BPTF knockdown may inhibit the malignant behavior of glioma cells by downregulating FOXC1 expression. Moreover, FOXC1 expression was significantly higher in glioma tissues than in normal brain tissues and was significantly associated with higher tumor stage and worse patient prognosis. Finally, the mechanism of FOXC1 regulation by BPTF was found to result from the affected protein stability of FOXC1 through USP34-mediated de-ubiquitylation. In conclusion, the BPTF/FOXC1 axis was identified as a key promotor in glioma development and may be a potential target in the inhibition of glioma development

Clinical and Biological Implications of Mutational Spectrum in Acute Myeloid Leukemia of FAB Subtypes M0 and M1

Background/Aims: Acute myeloid leukemia (AML) of French-American-British (FAB) subtypes M0 and M1 are both poorly differentiated AML, but their mutational spectrum and molecular characteristics remain unknown. This study aimed to explore the mutational spectrum and prognostic factors of AML-M0 and M1. Methods: Sixty-five AML patients derived from The Cancer Genome Atlas (TCGA) database were enrolled in this study. Whole-genome sequencing was performed to depict the mutational spectrum of each patient. Clinical characteristics at diagnosis, including peripheral blood (PB) white blood cell counts (WBC), blast percentages in PB and bone marrow (BM), FAB subtypes and the frequencies of known recurrent genetic mutations were described. Survival was estimated using the Kaplan-Meier methods and log-rank test. Univariate and multivariate Cox proportional hazard models were constructed procedure. Results: Forty-six patients had more than five recurrent genetic mutations. FLT3 had the highest mutation frequency (n=20, 31%), followed by NPM1 (n=18, 28%), DNMT3A (n=16, 25%), IDH1 (n=14, 22%), IDH2 (n=12, 18%), RUNX1 (n=11, 17%) and TET2 (n=7, 11%). Univariate analysis showed that age >= 60 years and TP53 mutations had adverse effect on EFS (P=0.015, P=0.036, respectively) and OS (P=0.003, P=0.004, respectively), WBC count >= 50x10(9)/L and FLT3-ITD negatively affected EFS (P=0.003, P=0.034, respectively), whereas NPM1 mutations had favorable effect on OS (P=0.035) and allogeneic hematopoietic stem cell transplantation (allo-HSCT) on EFS and OS (all P= 50x10(9)/L was an independent risk factor for EFS (P=0.002) and TP53 mutations for OS (P=0.043). Conclusions: Our study provided new insights into the mutational spectrum and molecular signatures of AML-M0 and M1. We proposed that FLT3-ITD, NPM1 and TP53 be identified as markers for risk stratification of AML-M0 and M1. Patients with AML-M0 and M1 would likely benefit from allo-HSCT. (C) 2018 The Author(s) Published by S. Karger AG, Base

EffLiFe: Efficient Light Field Generation via Hierarchical Sparse Gradient Descent

With the rise of Extended Reality (XR) technology, there is a growing need for real-time light field generation from sparse view inputs. Existing methods can be classified into offline techniques, which can generate high-quality novel views but at the cost of long inference/training time, and online methods, which either lack generalizability or produce unsatisfactory results. However, we have observed that the intrinsic sparse manifold of Multi-plane Images (MPI) enables a significant acceleration of light field generation while maintaining rendering quality. Based on this insight, we introduce EffLiFe, a novel light field optimization method, which leverages the proposed Hierarchical Sparse Gradient Descent (HSGD) to produce high-quality light fields from sparse view images in real time. Technically, the coarse MPI of a scene is first generated using a 3D CNN, and it is further sparsely optimized by focusing only on important MPI gradients in a few iterations. Nevertheless, relying solely on optimization can lead to artifacts at occlusion boundaries. Therefore, we propose an occlusion-aware iterative refinement module that removes visual artifacts in occluded regions by iteratively filtering the input. Extensive experiments demonstrate that our method achieves comparable visual quality while being 100x faster on average than state-of-the-art offline methods and delivering better performance (about 2 dB higher in PSNR) compared to other online approaches.Comment: Submitted to IEEE TPAM

Federated Learning Attacks and Defenses: A Survey

In terms of artificial intelligence, there are several security and privacy deficiencies in the traditional centralized training methods of machine learning models by a server. To address this limitation, federated learning (FL) has been proposed and is known for breaking down ``data silos" and protecting the privacy of users. However, FL has not yet gained popularity in the industry, mainly due to its security, privacy, and high cost of communication. For the purpose of advancing the research in this field, building a robust FL system, and realizing the wide application of FL, this paper sorts out the possible attacks and corresponding defenses of the current FL system systematically. Firstly, this paper briefly introduces the basic workflow of FL and related knowledge of attacks and defenses. It reviews a great deal of research about privacy theft and malicious attacks that have been studied in recent years. Most importantly, in view of the current three classification criteria, namely the three stages of machine learning, the three different roles in federated learning, and the CIA (Confidentiality, Integrity, and Availability) guidelines on privacy protection, we divide attack approaches into two categories according to the training stage and the prediction stage in machine learning. Furthermore, we also identify the CIA property violated for each attack method and potential attack role. Various defense mechanisms are then analyzed separately from the level of privacy and security. Finally, we summarize the possible challenges in the application of FL from the aspect of attacks and defenses and discuss the future development direction of FL systems. In this way, the designed FL system has the ability to resist different attacks and is more secure and stable.Comment: IEEE BigData. 10 pages, 2 figures, 2 table

A Survey on Deep Clustering: From the Prior Perspective

Facilitated by the powerful feature extraction ability of neural networks, deep clustering has achieved great success in analyzing high-dimensional and complex real-world data. The performance of deep clustering methods is affected by various factors such as network structures and learning objectives. However, as pointed out in this survey, the essence of deep clustering lies in the incorporation and utilization of prior knowledge, which is largely ignored by existing works. From pioneering deep clustering methods based on data structure assumptions to recent contrastive clustering methods based on data augmentation invariances, the development of deep clustering intrinsically corresponds to the evolution of prior knowledge. In this survey, we provide a comprehensive review of deep clustering methods by categorizing them into six types of prior knowledge. We find that in general the prior innovation follows two trends, namely, i) from mining to constructing, and ii) from internal to external. Besides, we provide a benchmark on five widely-used datasets and analyze the performance of methods with diverse priors. By providing a novel prior knowledge perspective, we hope this survey could provide some novel insights and inspire future research in the deep clustering community