The newly emerging coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported in Wuhan, China, but has rapidly spread all over the ...world. Some COVID-19 patients encounter a severe symptom of acute respiratory distress syndrome (ARDS) with high mortality. This high severity is dependent on a cytokine storm, most likely induced by the interleukin-6 (IL-6) amplifier, which is hyper-activation machinery that regulates the nuclear factor kappa B (NF-κB) pathway and stimulated by the simultaneous activation of IL-6-signal transducer and activator of transcription 3 (STAT3) and NF-κB signaling in non-immune cells including alveolar epithelial cells and endothelial cells. We hypothesize that IL-6-STAT3 signaling is a promising therapeutic target for the cytokine storm in COVID-19, because IL-6 is a major STAT3 stimulator, particularly during inflammation. We herein review the pathogenic mechanism and potential therapeutic targets of ARDS in COVID-19 patients.
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•Upgrading of heavy oil was examined over TiO2–ZrO2 mixed catalysts.•Heavy oil could be converted to lighter fuels over TiO2–ZrO2 mixed catalyst.•Carbonaceous residue was suppressed ...upon catalyst cracking by using TiO2–ZrO2 catalyst.•TiO2–ZrO2 comprising TiO2 and ZrO2 in equimolar showed the most effective to upgrade.
Heavy oil upgrading was examined over titania–zirconia mixed oxide (TiO2–ZrO2) catalysts using fixed-bed flow-type reactors. Catalytic cracking of atmospheric residual oil (AR) and oil sand bitumen into lighter fuels such as gas oil and vacuum gas oil (VGO) was carried out in a superheated steam. The upgrading mechanisms were found to occur by carbon–carbon bond cleavage and naphthalene-ring opening caused by cracking, oxidation, or hydrogenolysis. The carbon–carbon bond cleavage reaction over acid sites is a well-known FCC (Fluid Catalytic Cracker) process, whereas coke formation on catalysts is a serious problem. Hence, repetition of the sequence of reactions over a short period of time and immediate regeneration of the catalyst is required. We previously developed a CeO2–ZrO2–Al2O3–FeOX iron oxide catalyst for heavy oil conversion into lighter fuels (Funai et al., 2010a,b; Kondoh et al., 2015). When this catalyst was applied to the degradation of heavy oil, the lattice oxygen in the catalyst was the main active site, and it decomposed the heavy oil through partial oxidative cracking. Although the catalyst showed a high upgrading activity, it was gradually deactivated due to carbon deposition. In contrast, we found TiO2–ZrO2 catalysts exhibited acidic cracking activity for heavy oil cracking under superheated steam conditions. In this study, we conducted experiments with TiO2–ZrO2 catalysts for upgrading heavy oil. The effect of the catalyst composition on the yield of the lighter fuels, catalyst activity, and stability after the reaction was examined. As a result, the yield of light fractions from AR decomposition reached 71mol%-C when using a TiO2–ZrO2 catalyst comprising TiO2 and ZrO2 in equimolar amounts and the catalyst structure remained intact after the reaction.
Squamous cell lung carcinomas account for approximately 25% of new lung carcinoma cases and 40,000 deaths per year in the United States. Although there are multiple genomically targeted therapies for ...lung adenocarcinoma, none has yet been reported in squamous cell lung carcinoma.
Using SNP array analysis, we found that a region of chromosome segment 8p11-12 containing three genes-WHSC1L1, LETM2, and FGFR1-is amplified in 3% of lung adenocarcinomas and 21% of squamous cell lung carcinomas. Furthermore, we demonstrated that a non-small cell lung carcinoma cell line harboring focal amplification of FGFR1 is dependent on FGFR1 activity for cell growth, as treatment of this cell line either with FGFR1-specific shRNAs or with FGFR small molecule enzymatic inhibitors leads to cell growth inhibition.
These studies show that FGFR1 amplification is common in squamous cell lung cancer, and that FGFR1 may represent a promising therapeutic target in non-small cell lung cancer.
Aim
Information processing is supported by the cortico‐cortical transmission of neural oscillations across brain regions. Recent studies have demonstrated that the rhythmic firing of neural ...populations is not random but is governed by interactions with other frequency bands. Specifically, the amplitude of gamma‐band oscillations is associated with the phase of lower frequency oscillations in support of short and long‐range communications among networks. This cross‐frequency relation is thought to reflect the temporal coordination of neural communication. While schizophrenia patients show abnormal oscillatory responses across multiple frequencies at rest, it is unclear whether the functional relationships among frequency bands are intact. This study aimed to characterize the lower frequency (delta/theta, 1–8 Hz) phase and the amplitude of gamma oscillations in healthy subjects and schizophrenia patients at rest.
Methods
Low frequency‐phase (delta‐ and theta‐ band) angles and gamma‐band amplitude relationships were assessed in 142 schizophrenia patients and 128 healthy subjects.
Results
Significant low‐frequency phase alteration related to high‐power gamma was detected across broadly distributed scalp regions in both healthy subjects and patients. In patients, delta phase synchronization related to high‐power gamma was significantly decreased at the frontocentral, right middle temporal, and left temporoparietal electrodes but significantly increased at the left parietal electrode.
Conclusions
High‐power gamma‐related delta phase alteration may reflect a core pathophysiologic abnormality in schizophrenia. Data‐driven measures of functional relationships among frequency bands may prove useful in the development of novel therapeutics. Future studies are needed to determine whether these alterations are specific to schizophrenia or appear in other neuropsychiatric patient populations.
We assessed somatic alleles of six receptor tyrosine kinase genes mutated in lung adenocarcinoma for oncogenic activity. Five of these genes failed to score in transformation assays; however, novel ...recurring extracellular domain mutations of the receptor tyrosine kinase gene ERBB2 were potently oncogenic. These ERBB2 extracellular domain mutants were activated by two distinct mechanisms, characterized by elevated C-terminal tail phosphorylation or by covalent dimerization mediated by intermolecular disulfide bond formation. These distinct mechanisms of receptor activation converged upon tyrosine phosphorylation of cellular proteins, impacting cell motility. Survival of Ba/F3 cells transformed to IL-3 independence by the ERBB2 extracellular domain mutants was abrogated by treatment with small-molecule inhibitors of ERBB2, raising the possibility that patients harboring such mutations could benefit from ERBB2-directed therapy.
The Menzerath law is considered to show an aspect of the complexity underlying natural language. This law suggests that, for a linguistic unit, the size (y) of a linguistic construct decreases as the ...number (x) of constructs in the unit increases. This article investigates this property syntactically, with x as the number of constituents modifying the main predicate of a sentence and y as the size of those constituents in terms of the number of words. Following previous articles that demonstrated that the Menzerath property held for dependency corpora, such as in Czech and Ukrainian, this article first examines how well the property applies across languages by using the entire Universal Dependency dataset ver. 2.3, including 76 languages over 129 corpora and the Penn Treebank (PTB). The results show that the law holds reasonably well for x>2. Then, for comparison, the property is investigated with syntactically randomized sentences generated from the PTB. These results show that the property is almost reproducible even from simple random data. Further analysis of the property highlights more detailed characteristics of natural language.
The performance of deep learning in natural language processing has been spectacular, but the reasons for this success remain unclear because of the inherent complexity of deep learning. This paper ...provides empirical evidence of its effectiveness and of a limitation of neural networks for language engineering. Precisely, we demonstrate that a neural language model based on long short-term memory (LSTM) effectively reproduces Zipf's law and Heaps' law, two representative statistical properties underlying natural language. We discuss the quality of reproducibility and the emergence of Zipf's law and Heaps' law as training progresses. We also point out that the neural language model has a limitation in reproducing long-range correlation, another statistical property of natural language. This understanding could provide a direction for improving the architectures of neural networks.
Aim
Gamma‐band auditory steady‐state response (ASSR) is a neurophysiologic index that is increasingly used as a translational biomarker in the development of treatments of neuropsychiatric disorders. ...While gamma‐band ASSR is generated by distributed networks of highly interactive temporal and frontal cortical sources, the majority of human gamma‐band ASSR studies using electroencephalography (EEG) highlight activity from only a single frontocentral scalp site, Fz, where responses tend to be largest and reductions in schizophrenia patients are most evident. However, no previous study has characterized the relative source contributions to Fz, which is a necessary step to improve the concordance of preclinical and clinical EEG studies.
Methods
A novel method to back‐project the contributions of independent cortical source components was applied to assess the independent sources and their proportional contributions to Fz as well as source‐resolved responses in 432 schizophrenia patients and 294 healthy subjects.
Results
Independent contributions of gamma‐band ASSR to Fz were detected from orbitofrontal, bilateral superior/middle/inferior temporal, bilateral middle frontal, and posterior cingulate gyri in both groups. In contrast to expectations, the groups showed comparable source contribution weight to gamma‐band ASSR at Fz. While gamma‐band ASSR reductions at Fz were present in schizophrenia patients consistent with previous studies, no group differences in individual source‐level responses to Fz were detected.
Conclusion
Small differences in multiple independent sources summate to produce scalp‐level differences at Fz. The identification of independent source contributions to a single scalp sensor represents a promising methodology for measuring dissociable and homologous biomarker targets in future translational studies.
Recent works on portfolio selection report ways to incorporate textual data in addition to price movements. Price, texts, and events as what lies underneath take heterogeneous data form and therefore ...have been processed without any consistent mathematical formulation.
In this article, we propose to generalize portfolio selection by representing all related objects (stocks, news, events) in an embedding vector space, that we call a NEws-STock space with Event Distribution (NESTED). A NESTED forms an inner product vector space (Hilbert space), in which texts and stocks are represented as vectors (embeddings), acquired through a distribution of events. In this article, we first theoretically reformulate Markowitz’s portfolio optimization problem on NESTED. We show how our new formulation has the potential to better incorporate the tail risk, which is represented better in textual data.
One typical method to acquire such embeddings is via neural computing. Our experimental results, obtained by using it on 24 news-price datasets across three markets, showed that the Pareto’s exponent in the negative tail of the generated portfolios increased in all markets, which is evidence that the stock embeddings captured the tail risks. Our method showed a large improvement balancing between the tail risk and non-tail risk, up to 45.5% larger gain and 59.4% larger Information ratio.
The mammalian cell nucleus contains dozens of membrane-less nuclear bodies that play significant roles in various aspects of gene expression. Several nuclear bodies are nucleated by specific ...architectural noncoding RNAs (arcRNAs) acting as structural scaffolds. We have reported that a minor population of cellular RNAs exhibits an unusual semi-extractable feature upon using the conventional procedure of RNA preparation and that needle shearing or heating of cell lysates remarkably improves extraction of dozens of RNAs. Because semi-extractable RNAs, including known arcRNAs, commonly localize in nuclear bodies, this feature may be a hallmark of arcRNAs. Using the semi-extractability of RNA, we performed genome-wide screening of semi-extractable long noncoding RNAs to identify new candidate arcRNAs for arcRNA under hyperosmotic and heat stress conditions. After screening stress-inducible and semi-extractable RNAs, hundreds of readthrough downstream-of-gene (DoG) transcripts over several hundreds of kilobases, many of which were not detected among RNAs prepared by the conventional extraction procedure, were found to be stress-inducible and semi-extractable. We further characterized some of the abundant DoGs and found that stress-inducible transient extension of the 3'-UTR made DoGs semi-extractable. Furthermore, they were localized in distinct nuclear foci that were sensitive to 1,6-hexanediol. These data suggest that semi-extractable DoGs exhibit arcRNA-like features and our semi-extractable RNA-seq is a powerful tool to extensively monitor DoGs that are induced under specific physiological conditions.
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