Robust Physics-based Deep MRI Reconstruction Via Diffusion Purification

Deep learning (DL) techniques have been extensively employed in magnetic resonance imaging (MRI) reconstruction, delivering notable performance enhancements over traditional non-DL methods. Nonetheless, recent studies have identified vulnerabilities in these models during testing, namely, their susceptibility to (\textit{i}) worst-case measurement perturbations and to (\textit{ii}) variations in training/testing settings like acceleration factors and k-space sampling locations. This paper addresses the robustness challenges by leveraging diffusion models. In particular, we present a robustification strategy that improves the resilience of DL-based MRI reconstruction methods by utilizing pretrained diffusion models as noise purifiers. In contrast to conventional robustification methods for DL-based MRI reconstruction, such as adversarial training (AT), our proposed approach eliminates the need to tackle a minimax optimization problem. It only necessitates fine-tuning on purified examples. Our experimental results highlight the efficacy of our approach in mitigating the aforementioned instabilities when compared to leading robustification approaches for deep MRI reconstruction, including AT and randomized smoothing

The contributions of key countries, enterprises and refineries to greenhouse gas emissions in global oil refining 2000-2021

The refining industry is the third-largest source of global greenhouse gas (GHG) emissions from stationary sources, so it is at the forefront of the energy transition and net zero pathways. The dynamics of contributors in this sector such as crucial countries, leading enterprises, and key emission processes are vital to identifying key GHG emitters and supporting targeted emission reduction, yet they are still poorly understood. Here, we established a global sub-refinery GHG emission dataset in a long time series based on life cycle method. Globally, cumulative GHG emissions from refineries reached approximately 34.1 gigatons (Gt) in the period 2000–2021 with an average annual increasing rate of 0.7%, dominated by the United States, EU27&UK, and China. In 2021, the top 20 countries with the largest GHG emissions of oil refining accounted for 83.9% of global emissions from refineries, compared with 79.5% in 2000. Moreover, over the past two decades, 53.9–57.0% of total GHG emissions came from the top 20 oil refining enterprises with the largest GHG emissions in 12 of these 20 countries. Retiring or installing mitigation technologies in the top 20% of refineries with the largest GHG emissions and refineries with GHG emissions of more than 0.1 Gt will reduce the level of GHG emissions by 38.0%–100.0% in these enterprises. Specifically, low-carbon technologies installed on furnaces and boilers as well as steam methane reforming will enable substantial GHG mitigation of more than 54.0% at the refining unit level. Therefore, our results suggest that policies targeting a relatively small number of super-emission contributors could significantly reduce GHG emissions from global oil refining

Nonlinear optical properties in a quantum well with the hyperbolic confinement potential

We have performed theoretical calculation of the nonlinear optical properties in a quantum well (QW) with the hyperbolic confinement potential. Calculation results reveal that the transition energy, oscillator strength, second-order nonlinear optical rectification (OR), geometric factor and nonlinear optical absorption (OA) are strongly affected by the parameters ($\alpha, \sigma$) of the hyperbolic confinement potential. And an increment of the parameter $\alpha$ reduces all these physical quantities, while an increment of the parameter $\sigma$ enhances them, but not for geometric factor. In addition, it is found that one can control the optical properties of QW by tuning these parameters.Comment: 16pages,6 figures,Accepted for publication in Physica

Local Diffusion Homogeneity Provides Supplementary Information in T2DM-Related WM Microstructural Abnormality Detection

Objectives: We aimed to investigate whether an inter-voxel diffusivity metric (local diffusion homogeneity, LDH), can provide supplementary information to traditional intra-voxel metrics (i.e., fractional anisotropy, FA) in white matter (WM) abnormality detection for type 2 diabetes mellitus (T2DM).Methods: Diffusion tensor imaging was acquired from 34 T2DM patients and 32 healthy controls. Voxel-based group-difference comparisons based on LDH and FA, as well as the association between the diffusion metrics and T2DM risk factors [i.e., body mass index (BMI) and systolic blood pressure (SBP)], were conducted, with age, gender and education level controlled.Results: Compared to the controls, T2DM patients had higher LDH in the pons and left temporal pole, as well as lower FA in the left superior corona radiation (p < 0.05, corrected). In T2DM, there were several overlapping WM areas associated with BMI as revealed by both LDH and FA, including right temporal lobe and left inferior parietal lobe; but the unique areas revealed only by using LDH included left inferior temporal lobe, right supramarginal gyrus, left pre- and post-central gyrus (at the semiovale center), and right superior radiation. Overlapping WM areas that associated with SBP were found with both LDH and FA, including right temporal pole, bilateral orbitofrontal area (rectus gyrus), the media cingulum bundle, and the right cerebellum crus I. However, the unique areas revealed only by LDH included right inferior temporal lobe, right inferior occipital lobe, and splenium of corpus callosum.Conclusion: Inter- and intra-voxel diffusivity metrics may have different sensitivity in the detection of T2DM-related WM abnormality. We suggested that LDH could provide supplementary information and reveal additional underlying brain changes due to diabetes

Gut microbiota assemblages of generalist predators are driven by local- and landscape-scale factors

ABSTRACT: The gut microbiomes of arthropods have significant impact on key physiological functions such as nutrition, reproduction, behavior, and health. Spiders are diverse and numerically dominant predators in crop fields where they are potentially important regulators of pests. Harnessing spiders to control agricultural pests is likely to be supported by an understanding of their gut microbiomes, and the environmental drivers shaping microbiome assemblages. This study aimed to deciphering the gut microbiome assembly of these invertebrate predators and elucidating potential implications of key environmental constraints in this process. Here, we used high-throughput sequencing to examine for the first time how the assemblages of bacteria in the gut of spiders are shaped by environmental variables. Local drivers of microbiome composition were globally-relevant input use system (organic production vs. conventional practice), and crop identity (Chinese cabbage vs. cauliflower). Landscape-scale factors, proportion of forest and grassland, compositional diversity, and habitat edge density, also strongly affected gut microbiota. Specific bacterial taxa were enriched in gut of spiders sampled from different settings and seasons. These findings provide a comprehensive insight into composition and plasticity of spider gut microbiota. Understanding the temporal responses of specific microbiota could lead to innovative strategies development for boosting biological control services of predators.info:eu-repo/semantics/publishedVersio

Chitosan-salvianolic acid B coating on the surface of nickel-titanium alloy inhibits proliferation of smooth muscle cells and promote endothelialization

Introduction: Intracranial stents are of paramount importance in managing cerebrovascular disorders. Nevertheless, the currently employed drug-eluting stents, although effective in decreasing in-stent restenosis, might impede the re-endothelialization process within blood vessels, potentially leading to prolonged thrombosis development and restenosis over time.Methods: This study aims to construct a multifunctional bioactive coating to enhance the biocompatibility of the stents. Salvianolic acid B (SALB), a bioactive compound extracted from Salvia miltiorrhiza, exhibits potential for improving cardiovascular health. We utilized dopamine as the base and adhered chitosan-coated SALB microspheres onto nickel-titanium alloy flat plates, resulting in a multifunctional drug coating.Results: By encapsulating SALB within chitosan, the release period of SALB was effectively prolonged, as evidenced by the in vitro drug release curve showing sustained release over 28 days. The interaction between the drug coating and blood was examined through experiments on water contact angle, clotting time, and protein adsorption. Cellular experiments showed that the drug coating stimulates the proliferation, adhesion, and migration of human umbilical vein endothelial cells.Discussion: These findings indicate its potential to promote re-endothelialization. In addition, the bioactive coating effectively suppressed smooth muscle cells proliferation, adhesion, and migration, potentially reducing the occurrence of neointimal hyperplasia and restenosis. These findings emphasize the exceptional biocompatibility of the newly developed bioactive coating and demonstrate its potential clinical application as an innovative strategy to improve stent therapy efficacy. Thus, this coating holds great promise for the treatment of cerebrovascular disease

New tranylcypromine derivatives containing sulfonamide motif as potent LSD1 inhibitors to target acute myeloid leukemia: design, synthesis and biological evaluation

Lysine-specific demethylase 1 (LSD1) is frequently elevated in acute myeloid leukemia (AML) and often leads to tumorigenesis. In recent years, numerous LSD1 inhibitors based on tranylcypromine (TCP) scaffolding have reached clinical trials. Most TCP derivatives were modified at the amino site of cyclopropane motif. Herein, we for the first time introduced a sulfonamide group in TCP benzene ring of series a compounds and performed a systematical study on structure and activity relationships by varying sulfonamide groups. The introduction of sulfonamide significantly increased the targeting capacity of TCP against LSD1. Moreover, we discovered that the Boc attached LSD1 inhibitors (labelled as series b compounds) substantially improved their anti-proliferation capacity towards AML cells. The intracellular thermal shift and LC-MS/MS results implied that Boc enhanced the drug lipophilicity and might be removed under the cancerous acidic environment to release the real pharmacophore, evidenced by the fact that a structurally similar but acidic inert pivaloyl to replace Boc dramatically dropped the cellular anti-proliferation effect. Finally, a benzyl group installed at the amino site to appropriately increase lipophilicity led to trans-4-(2-(benzylamino)-cyclopropyl)-N,N-diethylbenzenesulfonamide a10 that showed better anti-proliferation activity in AML cells and enzymatic inhibition against LSD1. Taken together, our work offers a novel TCP-based structure and provides a prodrug strategy for the discovery of potent LSD1 inhibitors by having appropriate lipophilicity