Accurate volume alignment of arbitrarily oriented tibiae based on a mutual attention network for osteoarthritis analysis

Damage to cartilage is an important indicator of osteoarthritis progression, but manual extraction of cartilage morphology is time-consuming and prone to error. To address this, we hypothesize that automatic labeling of cartilage can be achieved through the comparison of contrasted and non-contrasted Computer Tomography (CT). However, this is non-trivial as the pre-clinical volumes are at arbitrary starting poses due to the lack of standardized acquisition protocols. Thus, we propose an annotation-free deep learning method, D-net, for accurate and automatic alignment of pre- and post-contrasted cartilage CT volumes. D-Net is based on a novel mutual attention network structure to capture large-range translation and full-range rotation without the need for a prior pose template. CT volumes of mice tibiae are used for validation, with synthetic transformation for training and tested with real pre- and post-contrasted CT volumes. Analysis of Variance (ANOVA) was used to compare the different network structures. Our proposed method, D-net, achieves a Dice coefficient of 0.87, and significantly outperforms other state-of-the-art deep learning models, in the real-world alignment of 50 pairs of pre- and post-contrasted CT volumes when cascaded as a multi-stage network

Emerging biomarkers in psoriatic arthritis

Psoriasis is an immuneâ mediated skin disease which affects 2â 4% of the worldwide population. Approximately 20â 30% of patients with psoriasis develop psoriatic arthritis (PsA), a frequently destructive and disabling condition. As skin manifestations precede joint symptoms in nearly all patients with PsA, identification of biomarkers for early prediction of joint damage is an important clinical need. Because not all patients with PsA respond to treatment in the same fashion, identification of biomarkers capable of predicting therapeutic response is also imperative. Here, we review existing literature and discuss current investigations to identify potential biomarkers for PsA disease activity, with particular emphasis on microRNAs as novel markers of interest. Serum (soluble) biomarkers, peripheral osteoclast precursor as cellular biomarkers, and genetic loci associated with skin and joint disease are also reviewed. © 2015 IUBMB Life, 67(12):923â 927, 2015Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136299/1/iub1453.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136299/2/iub1453_am.pd

Precise Modulation of Triple-Phase Boundaries towards a Highly Functional Exsolved Catalyst for Dry Reforming of Methane under a Dilution-Free System

Dry reforming of methane (DRM) has been emerging as a viable solution to achieving carbon neutrality enhanced by the Paris Agreement as it converts the greenhouse gases of CO2 and CH4 into industrially useful syngas. However, there have been limited studies on the DRM catalyst under mild operating conditions with a high dilution gas ratio due to their deactivation from carbon coking and metal sintering. Herein, we apply the triple-phase boundary (TPB) concept to DRM catalyst via exsolution phenomenon that can secure elongated TPB by controlling the Fe-doping ratio in perovskite oxide. Remarkably, the exsolved catalyst with prolongated TPB shows exceptional CO2 and CH4 conversion rates of 95.9 % and 91.6 %, respectively, stable for 1000 hours under a dilution-free system. DFT calculations confirm that the Lewis acid of support and Lewis base of metal at the TPB promote the adsorption of reactants, resulting in lowering the overall CO2 dissociation and CH4 dehydrogenation energy

Genetic susceptibility to hepatocellular carcinoma in chromosome 22q13.31, findings of a genome-wide association study.

Background and Aim: Chronic hepatitis C virus (HCV) infection, long-term alcohol use, cigarette smoking, and obesity are the major risk factors for hepatocellular carcinoma (HCC) in the United States, but the disease risk varies substantially among individuals with these factors, suggesting host susceptibility to and gene-environment interactions in HCC. To address genetic susceptibility to HCC, we conducted a genome-wide association study (GWAS). Methods: Two case-control studies on HCC were conducted in the United States. DNA samples were genotyped using the Illumian microarray chip with over 710 000 single nucleotide polymorphisms (SNPs). We compared these SNPs between 705 HCC cases and 1455 population controls for their associations with HCC and verified our findings in additional studies. Results: In this GWAS, we found that two SNPs were associated with HCC at Conclusions: SNPs i