Application of deep learning (3-dimensional convolutional neural network) for the prediction of pathological invasiveness in lung adenocarcinoma

To compare results for radiological prediction of pathological invasiveness in lung adenocarcinoma between radiologists and a deep learning (DL) system.Ninety patients (50 men, 40 women; mean age, 66 years; range, 40-88 years) who underwent pre-operative chest computed tomography (CT) with 0.625-mm slice thickness were included in this retrospective study. Twenty-four cases of adenocarcinoma in situ (AIS), 20 cases of minimally invasive adenocarcinoma (MIA), and 46 cases of invasive adenocarcinoma (IVA) were pathologically diagnosed. Three radiologists of different levels of experience diagnosed each nodule by using previously documented CT findings to predict pathological invasiveness. DL was structured using a 3-dimensional (3D) convolutional neural network (3D-CNN) constructed with 2 successive pairs of convolution and max-pooling layers, and 2 fully connected layers. The output layer comprises 3 nodes to recognize the 3 conditions of adenocarcinoma (AIS, MIA, and IVA) or 2 nodes for 2 conditions (AIS and MIA/IVA). Results from DL and the 3 radiologists were statistically compared.No significant differences in pathological diagnostic accuracy rates were seen between DL and the 3 radiologists (P>. 11). Receiver operating characteristic analysis demonstrated that area under the curve for DL (0.712) was almost the same as that for the radiologist with extensive experience (0.714; P=. 98). Compared with the consensus results from radiologists, DL offered significantly inferior sensitivity (P=. 0005), but significantly superior specificity (P=. 02).Despite the small training data set, diagnostic performance of DL was almost the same as the radiologist with extensive experience. In particular, DL provided higher specificity than radiologists

Curated genome annotation of Oryza sativa ssp. japonica and comparative genome analysis with Arabidopsis thaliana

We present here the annotation of the complete genome of rice Oryza sativa L. ssp. japonica cultivar Nipponbare. All functional annotations for proteins and non-protein-coding RNA (npRNA) candidates were manually curated. Functions were identified or inferred in 19,969 (70%) of the proteins, and 131 possible npRNAs (including 58 antisense transcripts) were found. Almost 5000 annotated protein-coding genes were found to be disrupted in insertional mutant lines, which will accelerate future experimental validation of the annotations. The rice loci were determined by using cDNA sequences obtained from rice and other representative cereals. Our conservative estimate based on these loci and an extrapolation suggested that the gene number of rice is ~32,000, which is smaller than previous estimates. We conducted comparative analyses between rice and Arabidopsis thaliana and found that both genomes possessed several lineage-specific genes, which might account for the observed differences between these species, while they had similar sets of predicted functional domains among the protein sequences. A system to control translational efficiency seems to be conserved across large evolutionary distances. Moreover, the evolutionary process of protein-coding genes was examined. Our results suggest that natural selection may have played a role for duplicated genes in both species, so that duplication was suppressed or favored in a manner that depended on the function of a gene

Plasma half-life and tissue distribution of leukocyte cell-derived chemotaxin 2 in mice

金沢大学疾患モデル総合研究センターLeukocyte cell-derived chemotaxin 2 (LECT2) is a hepatokine that causes skeletal muscle insulin resistance. The circulating levels of LECT2 are a possible biomarker that can predict weight cycling because they reflect liver fat and precede the onset of weight loss or gain. Herein, to clarify the dynamics of this rapid change in serum LECT2 levels, we investigated the in vivo kinetics of LECT2, including its plasma half-life and tissue distribution, by injecting 125I-labelled LECT2 into ICR mice and radioactivity tracing. The injected LECT2 was eliminated from the bloodstream within 10 min (approximate half-life, 5 min). In the kidneys, the radioactivity accumulated within 10 min after injection and declined thereafter. Conversely, the radioactivity in urine increased after 30 min of injection, indicating that LECT2 is mainly excreted by the kidneys into the urine. Finally, LECT2 accumulated in the skeletal muscle and liver until 30 min and 2 min after injection, respectively. LECT2 accumulation was not observed in the adipose tissue. These findings are in agreement with LECT2 action on the skeletal muscle. The present study indicates that LECT2 is a rapid-turnover protein, which renders the circulating level of LECT2 a useful rapid-response biomarker to predict body weight alterations. © 2020, The Author(s).CC-BY 4.

RiceFOX: A Database of Arabidopsis Mutant Lines Overexpressing Rice Full-Length cDNA that Contains a Wide Range of Trait Information to Facilitate Analysis of Gene Function

Identification of gene function is important not only for basic research but also for applied science, especially with regard to improvements in crop production. For rapid and efficient elucidation of useful traits, we developed a system named FOX hunting (Full-length cDNA Over-eXpressor gene hunting) using full-length cDNAs (fl-cDNAs). A heterologous expression approach provides a solution for the high-throughput characterization of gene functions in agricultural plant species. Since fl-cDNAs contain all the information of functional mRNAs and proteins, we introduced rice fl-cDNAs into Arabidopsis plants for systematic gain-of-function mutation. We generated >30,000 independent Arabidopsis transgenic lines expressing rice fl-cDNAs (rice FOX Arabidopsis mutant lines). These rice FOX Arabidopsis lines were screened systematically for various criteria such as morphology, photosynthesis, UV resistance, element composition, plant hormone profile, metabolite profile/fingerprinting, bacterial resistance, and heat and salt tolerance. The information obtained from these screenings was compiled into a database named ‘RiceFOX’. This database contains around 18,000 records of rice FOX Arabidopsis lines and allows users to search against all the observed results, ranging from morphological to invisible traits. The number of searchable items is approximately 100; moreover, the rice FOX Arabidopsis lines can be searched by rice and Arabidopsis gene/protein identifiers, sequence similarity to the introduced rice fl-cDNA and traits. The RiceFOX database is available at http://ricefox.psc.riken.jp/

Tensile Properties and Press Formability of a Mg-9Li-1Y Alloy Sheet *

The formability of an experimentally produced Mg-9%Li-1%Y alloy sheet with a thickness of 0.6 mm is investigated. Uniaxial tension tests and some fundamental press-forming tests, such as stretching, deep-drawing, and bore-expanding tests, are carried out at room temperature. The sheet has sufficiently high ductility under uniaxial tension. However, ductility decreases with an increase in strain rate. Even at room temperature, the flow stress is also sensitive to the strain rate. The stress and the work-hardening rate increase with the strain rate. The strain rate sensitivity affects the formability in press forming. The critical punch stroke in the stretching test decreases with an increase in punch speed. However, the limit drawing ratio increases with the punch speed due to the increase in the work-hardening rate. The Erichsen value is estimated to be 9 mm, and the limit drawing ratio is 2.15. It may be concluded that the sheet has sufficiently high formability