MD-IQA: Learning Multi-scale Distributed Image Quality Assessment with Semi Supervised Learning for Low Dose CT

Image quality assessment (IQA) plays a critical role in optimizing radiation dose and developing novel medical imaging techniques in computed tomography (CT). Traditional IQA methods relying on hand-crafted features have limitations in summarizing the subjective perceptual experience of image quality. Recent deep learning-based approaches have demonstrated strong modeling capabilities and potential for medical IQA, but challenges remain regarding model generalization and perceptual accuracy. In this work, we propose a multi-scale distributions regression approach to predict quality scores by constraining the output distribution, thereby improving model generalization. Furthermore, we design a dual-branch alignment network to enhance feature extraction capabilities. Additionally, semi-supervised learning is introduced by utilizing pseudo-labels for unlabeled data to guide model training. Extensive qualitative experiments demonstrate the effectiveness of our proposed method for advancing the state-of-the-art in deep learning-based medical IQA. Code is available at: https://github.com/zunzhumu/MD-IQA

Structural Asymmetry of Phosphodiesterase-9, Potential Protonation of a Glutamic Acid, and Role of the Invariant Glutamine

PDE9 inhibitors show potential for treatment of diseases such as diabetes. To help with discovery of PDE9 inhibitors, we performed mutagenesis, kinetic, crystallographic, and molecular dynamics analyses on the active site residues of Gln453 and its stabilizing partner Glu406. The crystal structures of the PDE9 Q453E mutant (PDE9Q453E) in complex with inhibitors IBMX and (S)-BAY73-6691 showed asymmetric binding of the inhibitors in two subunits of the PDE9Q453E dimer and also the significant positional change of the M-loop at the active site. The kinetic analysis of the Q453E and E406A mutants suggested that the invariant glutamine is critical for binding of substrates and inhibitors, but is unlikely to play a key role in the differentiation between substrates of cGMP and cAMP. The molecular dynamics simulations suggest that residue Glu406 may be protonated and may thus explain the hydrogen bond distance between two side chain oxygens of Glu453 and Glu406 in the crystal structure of the PDE9Q453E mutant. The information from these studies may be useful for design of PDE9 inhibitors

Relationship of Seam Smoldering Velocity and Oxygen Volume Fraction Gradient in Roadway

AbstractSmoldering is an oxygen control reaction and its velocity is determined by oxygen supplying rate. Oxygen volume fraction gradient was used to characterize oxygen supplying rate in roadway according to situation that the velocity of wind flowing is very low during smoldering in roadway. Relationship of smoldering velocity and oxygen volume fraction gradient in roadway during lignite smoldering was researched in experiment drawing support of seam smoldering simulating experiment device in roadway and one-variable linear regression technology was used to establish the relation equation of smoldering velocity and oxygen volume fraction gradient in roadway when lignite was smoldering. This relation equation showed that smoldering velocity and oxygen volume fraction gradient took on linear increasing relationship in roadway during lignite smoldering

Downstream-agnostic Adversarial Examples

Self-supervised learning usually uses a large amount of unlabeled data to pre-train an encoder which can be used as a general-purpose feature extractor, such that downstream users only need to perform fine-tuning operations to enjoy the benefit of "large model". Despite this promising prospect, the security of pre-trained encoder has not been thoroughly investigated yet, especially when the pre-trained encoder is publicly available for commercial use. In this paper, we propose AdvEncoder, the first framework for generating downstream-agnostic universal adversarial examples based on the pre-trained encoder. AdvEncoder aims to construct a universal adversarial perturbation or patch for a set of natural images that can fool all the downstream tasks inheriting the victim pre-trained encoder. Unlike traditional adversarial example works, the pre-trained encoder only outputs feature vectors rather than classification labels. Therefore, we first exploit the high frequency component information of the image to guide the generation of adversarial examples. Then we design a generative attack framework to construct adversarial perturbations/patches by learning the distribution of the attack surrogate dataset to improve their attack success rates and transferability. Our results show that an attacker can successfully attack downstream tasks without knowing either the pre-training dataset or the downstream dataset. We also tailor four defenses for pre-trained encoders, the results of which further prove the attack ability of AdvEncoder.Comment: This paper has been accepted by the International Conference on Computer Vision (ICCV '23, October 2--6, 2023, Paris, France

Baicalein Inhibits Proliferation Activity of Human Colorectal Cancer Cells HCT116 Through Downregulation of Ezrin

Background/Aims: The present study was aimed at examining Ezrin expression in human colorectal cancer (CRC) tissues and elucidating the influence of baicalein on the proliferation of HCT116 cells. Methods: The expression of Ezrin was determined by qRT-PCR and immunohistochemistry. HCT116 cells were divided into four groups－ baicalein groups with various concentrations, pcDNA3.1-Ezrin group, si-Ezrin group and dual inhibitory group (baicalein + si-Ezrin). CCK-8 assay and flow cytometry (FCM) were employed to assess cell proliferation and to detect the distribution of cell cycle respectively. The expression levels of Ezrin protein and cell cycle-associated proteins were detected by using western blot. The proliferation ability of CRC cells was also evaluated in vivo. Results: Ezrin expression in CRC tissues was observably higher than that in adjacent colorectal tissues. With drug concentration and action time of baicalein increasing, the cell propagation capacity of HCT116 cells was decreased and the cell cycle progression was arrested. Ezrin expression was inhibited by the administration of baicalein in a dose-dependent way. The levels of CyclinD1 and CDK4 were also significantly decreased, but the expression of P53 pathway proteins P53 and P21 was markedly upregulated. Conclusion: Baicalein repressed proliferation of human colorectal cancer cells HCT116 and blocked cell cycle through downregulating Ezrin and upregulating P53 pathway-related proteins

Taking the pulse of COVID-19: A spatiotemporal perspective

The sudden outbreak of the Coronavirus disease (COVID-19) swept across the world in early 2020, triggering the lockdowns of several billion people across many countries, including China, Spain, India, the U.K., Italy, France, Germany, and most states of the U.S. The transmission of the virus accelerated rapidly with the most confirmed cases in the U.S., and New York City became an epicenter of the pandemic by the end of March. In response to this national and global emergency, the NSF Spatiotemporal Innovation Center brought together a taskforce of international researchers and assembled implemented strategies to rapidly respond to this crisis, for supporting research, saving lives, and protecting the health of global citizens. This perspective paper presents our collective view on the global health emergency and our effort in collecting, analyzing, and sharing relevant data on global policy and government responses, geospatial indicators of the outbreak and evolving forecasts; in developing research capabilities and mitigation measures with global scientists, promoting collaborative research on outbreak dynamics, and reflecting on the dynamic responses from human societies.Comment: 27 pages, 18 figures. International Journal of Digital Earth (2020

The Effect of Pretreatment Method on the Preparation of Micro-mesoporous ZSM-5/

A series of ZSM-5/γ-Al2O3 composite materials were prepared under various pretreatment method; The physicochemical properties of composite materials were investigated by XRD, SEM, FTIR to find out optimal pretreatment method. The results showed that the composite materials performance better structure property when γ- Al2O3 was firstly immersed in TPAOH solution under reflux condensation for a period of time and then immersed into anhydrous alcohol before mixed with ZSM-5 precursor solution. The result of infrared spectrum indicated that the formation of Al-OH bond played a key role in the synthesis of micro-mesoporous ZSM-5/γ-Al2O3 composite materials

The Effect of Pretreatment Method on the Preparation of Micro-mesoporous ZSM-5/Y-Al2O3 Composite Materials

A series of ZSM-5/γ-Al2O3 composite materials were prepared under various pretreatment method; The physicochemical properties of composite materials were investigated by XRD, SEM, FTIR to find out optimal pretreatment method. The results showed that the composite materials performance better structure property when γ- Al2O3 was firstly immersed in TPAOH solution under reflux condensation for a period of time and then immersed into anhydrous alcohol before mixed with ZSM-5 precursor solution. The result of infrared spectrum indicated that the formation of Al-OH bond played a key role in the synthesis of micro-mesoporous ZSM-5/γ-Al2O3 composite materials