Constraint on the giant planet production by core accretion

The issue of giant planet formation by core instability (CI) far from the central star is rather controversial because the growth of massive solid core necessary for triggering the CI can take longer than the lifetime of the protoplanetary disk. In this work we assess the range of separations at which the CI may operate by (1) allowing for arbitrary (physically meaningful) rate of planetesimal accretion by the core and (2) properly taking into account the dependence of the critical mass for the CI on the planetesimal accretion luminosity. This self-consistent approach distinguishes our work from similar studies in which only a specific planetesimal accretion regime was explored and/or the critical core mass was fixed at some arbitrary level. We demonstrate that the largest separation at which the CI can occur within 3 Myr corresponds to the surface density of solids in the disk higher than 0.1 g cm^{-2} and is 40-50 AU in the minimum mass Solar nebula. This limiting separation is achieved when the planetesimal accretion proceeds at the fastest possible rate, even though the high associated accretion luminosity increases the critical core mass delaying the onset of the CI. Our constraints are independent of the mass of the central star and vary only weakly with the core density and its atmospheric opacity. We also discuss various factors which can strengthen or weaken our limits on the operation of the CI.Comment: 8 pages, 1 figure, submitted to Ap

DOCK2 is involved in the host genetics and biology of severe COVID-19

「コロナ制圧タスクフォース」COVID-19疾患感受性遺伝子DOCK2の重症化機序を解明 --アジア最大のバイオレポジトリーでCOVID-19の治療標的を発見--. 京都大学プレスリリース. 2022-08-10.Identifying the host genetic factors underlying severe COVID-19 is an emerging challenge. Here we conducted a genome-wide association study (GWAS) involving 2, 393 cases of COVID-19 in a cohort of Japanese individuals collected during the initial waves of the pandemic, with 3, 289 unaffected controls. We identified a variant on chromosome 5 at 5q35 (rs60200309-A), close to the dedicator of cytokinesis 2 gene (DOCK2), which was associated with severe COVID-19 in patients less than 65 years of age. This risk allele was prevalent in East Asian individuals but rare in Europeans, highlighting the value of genome-wide association studies in non-European populations. RNA-sequencing analysis of 473 bulk peripheral blood samples identified decreased expression of DOCK2 associated with the risk allele in these younger patients. DOCK2 expression was suppressed in patients with severe cases of COVID-19. Single-cell RNA-sequencing analysis (n = 61 individuals) identified cell-type-specific downregulation of DOCK2 and a COVID-19-specific decreasing effect of the risk allele on DOCK2 expression in non-classical monocytes. Immunohistochemistry of lung specimens from patients with severe COVID-19 pneumonia showed suppressed DOCK2 expression. Moreover, inhibition of DOCK2 function with CPYPP increased the severity of pneumonia in a Syrian hamster model of SARS-CoV-2 infection, characterized by weight loss, lung oedema, enhanced viral loads, impaired macrophage recruitment and dysregulated type I interferon responses. We conclude that DOCK2 has an important role in the host immune response to SARS-CoV-2 infection and the development of severe COVID-19, and could be further explored as a potential biomarker and/or therapeutic target

Seismic exploration at Fuji volcano with active sources : The outline of the experiment and the arrival time data

Fuji volcano (altitude 3,776m) is the largest basaltic stratovolcano in Japan. In late August and early September 2003, seismic exploration was conducted around Fuji volcano by the detonation of 500 kg charges of dynamite to investigate the seismic structure of that area. Seismographs with an eigenfrequency of 2 Hz were used for observation, positioned along a WSW-ENE line passing through the summit of the mountain. A total of 469 seismic stations were installed at intervals of 250-500 m. The data were stored in memory on-site using data loggers. The sampling interval was 4 ms. Charges were detonated at 5 points, one at each end of the observation line and 3 along its length. The first arrival times and the later-phase arrival times at each station for each detonation were recorded as data. P-wave velocities in the surface layer were estimated from the travel time curves near the explosion points, with results of 2.5 km/s obtained for the vicinity of Fuji volcano and 4.0 km5/s elsewhere

Carbon-Resource Recovery from Vinyl Polymers of Cyclic Ketene Acetal Esters Using High-Temperature Water

Vinyl polymer prepared from 2-methylene-4H-benzo[d][1,3]dioxin-4-one (MBDO), a cyclic ketene acetal ester, is a chemically recyclable polymer that is hydrolyzed to salicylic acid (SA) and acetic acid (AA). Despite this potential, the polymer, poly-MBDO required a strong acid or base in organic solvent for the hydrolysis. In this study, we report the quantitative conversion of poly-MBDO to phenol by treatment in high-temperature water. Hydrolysis of poly-MBDO afforded SA, which underwent rapid decarboxylation to phenol. For example, poly-MBDO quantitatively afforded phenol upon heating in water at 300 °C for 5 min and freeze-drying. Although the hydrolysis of the main chain was incomplete, the products were volatile and removed by drying the reaction mixture, leaving the residue of pure phenol. Since SA is industrially synthesized from phenol and CO2, the synthesis of poly-MBDO from phenol is in principle possible. The quantitative conversion of poly-MBDO to phenol can also be considered as upcycling, since phenol is a raw material for various fine chemicals

Application of Convolutional Neural Networks in the Diagnosis of Helicobacter pylori Infection Based on Endoscopic Images

Background and aims: The role of artificial intelligence in the diagnosis of Helicobacter pylori gastritis based on endoscopic images has not been evaluated. We constructed a convolutional neural network (CNN), and evaluated its ability to diagnose H. pylori infection. Methods: A 22-layer, deep CNN was pre-trained and fine-tuned on a dataset of 32, 208 images either positive or negative for H. pylori (first CNN). Another CNN was trained using images classified according to 8 anatomical locations (secondary CNN). A separate test data set (11, 481 images from 397 patients) was evaluated by the CNN, and 23 endoscopists, independently. Results: The sensitivity, specificity, accuracy, and diagnostic time were 81.9%, 83.4%, 83.1%, and 198 s, respectively, for the first CNN, and 88.9%, 87.4%, 87.7%, and 194 s, respectively, for the secondary CNN. These values for the 23 endoscopists were 79.0%, 83.2%, 82.4%, and 230 ± 65 min (85.2%, 89.3%, 88.6%, and 253 ± 92 min by 6 board-certified endoscopists), respectively. The secondary CNN had a significantly higher accuracy than endoscopists (by 5.3%; 95% CI, 0.3-10.2). Conclusion: H. pylori gastritis could be diagnosed based on endoscopic images using CNN with higher accuracy and in a considerably shorter time compared to manual diagnosis by endoscopists