72 research outputs found
Gray matter alterations in early and late relapsing-remitting multiple sclerosis evaluated with synthetic quantitative magnetic resonance imaging
Abstract: Extensive gray matter (GM) involvement has been demonstrated in multiple sclerosis (MS) patients. This study was aimed to identify GM alterations in relapsing-remitting MS (RRMS) patients using synthetic quantitative MRI (qMRI). We assessed myelin volume fraction (MVF) in each voxel on the basis of R1 and R2 relaxation rates and proton density in 14 early and 28 late (disease duration 5 years, respectively) RRMS patients, and 15 healthy controls (HCs). The MVF and myelin volumes of GM (GM-MyVol) were compared between groups using GM-based spatial statistics (GBSS) and the Kruskal-Wallis test, respectively. Correlations between MVF or GM-MyVol and disease duration or expanded disability status scale were also evaluated. RRMS patients showed a lower MVF than HCs, predominantly in the limbic and para-limbic areas, with more extensive areas noted in late RRMS patients. Late-RRMS patients had the smallest GM-MyVol (20.44 mL; early RRMS, 22.77 mL; HCs, 23.36 mL). Furthermore, the GM-MyVol in the RRMS group was inversely correlated with disease duration (r = -0.43, p = 0.005). In conclusion, the MVF and MyVol obtained by synthetic qMRI can be used to evaluate GM differences in RRMS patients
Large expert-curated database for benchmarking document similarity detection in biomedical literature search
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe
Aceticlastic and NaCl-Requiring Methanogen "Methanosaeta pelagica" sp. nov., Isolated from Marine Tidal Flat Sediment
Acetate is a key compound for anaerobic organic matter degradation, and so far, two genera, Methanosaeta and Methanosarcina, are only contributors for acetate degradation among methanogens. An aceticlastic methanogen, designated strain 03d30qT, was isolated from a tidal flat sediment in Futtsu, Japan. The phylogenetic analyses based on 16S rRNA and mcrA genes revealed that the isolate belonged to the genus Methanosaeta, but the optimal Na+ concentration for growth shifted to marine environments unlike the other known Methanosaeta species. The quantitative estimation by using a real-time PCR indicated that the 16S rRNA gene of the genus Methanosaeta was detected in the sediments and the relative abundance ranged from 3.9% to 11.8% of the total archaeal 16S rRNA genes. Also, the amount of the genus Methanosaeta increased with increasing depth and was much higher than that of the genus Methanosarcina. This is the first report of marine Methanosaeta species, and on the basis of phylogenetic and characteristic studies, the novel species is proposed, "Methanosaeta pelagica" sp. nov., with types strain 03d30qT
instabilityを除いた深層学習によるノイズ低減法の評価
背景近年、深層学習による拡散強調画像のノイズ除去について多く議論されている。しかし、深層学習による画像生成にでは本来あるべき値から乖離してしまうリスクを除外することができない問題がある。そこで、我々は各ピクセルの値を隣接ピクセルの値の範囲に制限するニューラルネットワークを開発し、この問題の解決を試みた。本研究では提案手法により効果的なノイズ軽減を行えるかどうかについて初期的検討を行った。方法 10人の健常者を対象に拡散強調画像を取得した. 加算を行わない画像(NEX1)を入力し、8回加算画像(NEX8)相当の画像を出力することを目標にニューラルネットワークの設計と学習を行った。生成される各ピクセルの値は、元の画像における自身と隣接ピクセルの範囲を取る。また、学習を効率よく行うため、生成画像と標的画像との差に加えて、生成画像、標的画像から計算される拡散テンソルの差も最小化すべき損失とした。学習とテストはLeave-one-out cross validationにより行い、提案法によるノイズ除去画像を得た。最適化はAdamを初期学習率0.0001で用いた。・画像処理NEX1,NEX8,NEX1に対して私たちの手法でノイズ低減を行ったもの(deep learning Noise Reduction :dNR)それぞれの画像に対してDiffusion tensor imaging(DTI),Neurite orientation dispersion and density imaging(NODDI)を生成した。ROI解析ピクセル間の差異をNEX8と比較し、JHU ICBM-DTI-81 label を用いた ROIごとに平均され、Wilcoxonの符号順位検定を用いて比較を行った。結果図1にNEX1,dNR、NEX8から計算されたisotropic DWI,FA,MDの画像を示す。isotropic DWI,FA,MDにおいてdNRはNEX1と比較してノイズが低減されていることが確認できる。特に深部の領域についてノイズ低減が大きくNEX8の画像に近づいていることが確認できる。考察図1より効果的にデノイズされていることが視覚的に確認できた。各mapにおける平均値の多くがNEX1よりもNEX8に近づいた値となったため効果的にデノイズが行われたといえる。結論今回使用されたdNRは値を制限しながらもノイズを効果的に低減させていることが分かった。第49回 日本磁気共鳴医学会大
Aceticlastic and NaCl-Requiring Methanogen "Methanosaeta pelagica" sp. nov., Isolated from Marine Tidal Flat Sediment
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