Explore the vast range of titles available.

The I-mode is a promising tokamak operational regime characterized by a high energy confinement and the absence of type-I edge localized modes (ELMs). However, I-mode plasmas occasionally exhibit small ELM-like events known as pedestal relaxation events (PREs), transiently elevating the heat flux on the divertor targets. These PREs have been observed on ASDEX Upgrade (AUG) and Alcator C-Mod. In this work, BOUT++ simulation using the AUG experimental equilibrium and profiles are conducted. The three-field simulation yields a stable outcome, indicating that the PRE profile is peeling and ballooning (P-B) mode stable. In the six-field nonlinear simulations, an I-mode PRE was successfully reproduced in both a qualitative and near-quantitative sense, with PRE characteristics, including time scales, weakly coherent mode (WCM) frequency, and four eigenfrequencies of precursor oscillations (75, 50, 35 and 16 kHz), all exhibiting excellent agreement with experimental observations. Based on the dominant toroidal mode numbers, the entire evolution can be divided into three phases. The first phase is dominated by drift-wave, exhibiting clear WCM characteristics. During the second phase, when the collapse begins to develop, cross-phase analysis reveals a value close to π / 2 between the potential and electron temperature perturbations, indicating that the interchange mode acts as the direct trigger of the PRE. Further analysis of turbulence and transport confirms that the triggering region is located within the area of WCM turbulence. This work proposes a physical picture of the PRE in which drift-wave turbulence evolves into interchange modes, ultimately leading to a pedestal collapse.

The improved energy confinement mode (I-mode) is widely considered as an important operation regime for ITER. I-mode implementation depends on the specified basic plasma parameters and certain operation conditions, which are discovered by statistical plasma characteristics from a large number of I-mode discharges on a tokamak. The extraction process of I-mode plasma characteristics is complicated, time-consuming, and limited to the sampling rate of the measured signals. Experimental observation of the I-mode is accompanied by the appearance of a weakly coherent mode (WCM). However, it takes much time to accurately scan and quantify WCM characteristics when analyzing many I-mode discharges. Recently, a neural network identification method was developed as an I-mode detector to traverse a whole database as a replacement for manual identification. Two fully connected neural network models were trained with the spectrum of propagation velocity of density perturbation from Doppler backward scattering and the electron density measured by a polarimeter-interferometer system with the experimental advanced superconducting tokamak I-mode database. An accuracy of 98.30% in identifying WCMs in I-mode discharges is achieved with the WCM classification model. In addition, the regime classification model was also utilized to successfully distinguish between the low confinement mode (L-mode), I-mode, and high confinement mode (H-mode) with 96.03% accuracy. Finally, ablation experiments were performed on the regime classifiers, showing that there is potential for further performance improvement with future use of RNN model.

This paper reports the recent observation of a weakly coherent mode (WCM) within a conventional reflectometer on EAST and successfully determines its poloidal wavenumber range. During the transition from the L-mode to I-mode, the line-averaged density remains nearly unchanged while a significant change is observed in the electron cyclotron emission (ECE) signals at the boundary. The difference between the signals for the two channels at the edge increased, coinciding with the appearance of the WCM and a simultaneous rise in the boundary electron temperature. Further investigation unveiled the modulating role of edge temperature ring oscillation (ETRO) (Liu et al 2020 Nucl. Fusion 60 126016) on high-frequency density fluctuations. Statistical results unveil an inverse relationship between the centeral frequency of the WCM and q 95. Simulation results provide additional insights, demonstrating that the simulated ‘WCM’ in the density fluctuations aligns with experimental data in terms of center frequency. Additionally, the radial distribution of the simulated ‘WCM’ closely corresponds to regions with the strongest electron temperature gradients. Finally, through a cross-correlation analysis of the simulated fluctuations, the following phase relationship for the wavenumber range of ‘WCM’ was observed: αT~e>αn~i∼αϕ~>αT~i .

Climate change-reflected in significant environmental changes such as warming, sea level rise, shifts in salinity, oxygen and other ocean conditions-is expected to impact marine organisms and associated fisheries. This study provides an assessment of the potential impacts on, and the vulnerability of, marine biodiversity and fisheries catches in the Arabian Gulf under climate change. To this end, using three separate niche modelling approaches under a 'business-as-usual' climate change scenario, we projected the future habitat suitability of the Arabian Gulf (also known as the Persian Gulf) for 55 expert-identified priority species, including charismatic and non-fish species. Second, we conducted a vulnerability assessment of national economies to climate change impacts on fisheries. The modelling outputs suggested a high rate of local extinction (up to 35% of initial species richness) by 2090 relative to 2010. Spatially, projected local extinctions are highest in the southwestern part of the Gulf, off the coast of Saudi Arabia, Qatar and the United Arab Emirates (UAE). While the projected patterns provided useful indicators of potential climate change impacts on the region's diversity, the magnitude of changes in habitat suitability are more uncertain. Fisheries-specific results suggested reduced future catch potential for several countries on the western side of the Gulf, with projections differing only slightly among models. Qatar and the UAE were particularly affected, with more than a 26% drop in future fish catch potential. Integrating changes in catch potential with socio-economic indicators suggested the fisheries of Bahrain and Iran may be most vulnerable to climate change. We discuss limitations of the indicators and the methods used, as well as the implications of our overall findings for conservation and fisheries management policies in the region.

Multiple myeloma (MM) is an incurable hematological malignancy. Chimeric antigen receptor (CAR)-expressing T cells have been demonstrated successfully in the clinic to treat B-lymphoid malignancies. However, the potential utility of antigen-specific CAR-engineered natural-killer (NK) cells to treat MM has not been explored. In this study, we determined whether CS1, a surface protein that is highly expressed on MM cells, can be targeted by CAR NK cells to treat MM. We successfully generated a viral construct of a CS1-specific CAR and expressed it in human NK cells. In vitro , CS1-CAR NK cells displayed enhanced MM cytolysis and interferon-γ (IFN-γ) production, and showed a specific CS1-dependent recognition of MM cells. Ex vivo , CS1-CAR NK cells also showed similarly enhanced activities when responding to primary MM tumor cells. More importantly, in an aggressive orthotopic MM xenograft mouse model, adoptive transfer of NK-92 cells expressing CS1-CAR efficiently suppressed the growth of human IM9 MM cells and also significantly prolonged mouse survival. Thus, CS1 represents a viable target for CAR-expressing immune cells, and autologous or allogeneic transplantation of CS1-specific CAR NK cells may be a promising strategy to treat MM.

The proposal of configurational entropy maximization to produce massive solid-solution (SS)-strengthened, single-phase high-entropy alloy (HEA) systems has gained much scientific interest. Although most of this interest focuses on the basic role of configurational entropy in SS formability, setting future research directions also requires the overall property benefits of massive SS strengthening to be carefully investigated. To this end, taking the most promising CoCrFeMnNi HEA system as the starting point, we investigate SS formability, deformation mechanisms, and the achievable mechanical property ranges of different compositions and microstructural states. A comparative assessment of the results with respect to room temperature behavior of binary Fe-Mn alloys reveals only limited benefits of massive SS formation. Nevertheless, the results also clarify that the compositional requirements in this alloy system to stabilize the face-centered cubic (fcc) SS are sufficiently relaxed to allow considering nonequiatomic compositions and exploring improved strength–ductility combinations at reduced alloying costs.

Background Particular breast cancer subtypes pose a clinical challenge due to limited targeted therapeutic options and/or poor responses to the existing targeted therapies. While cell lines provide useful pre-clinical models, patient-derived xenografts (PDX) and organoids (PDO) provide significant advantages, including maintenance of genetic and phenotypic heterogeneity, 3D architecture and for PDX, tumor–stroma interactions. In this study, we applied an integrated multi-omic approach across panels of breast cancer PDXs and PDOs in order to identify candidate therapeutic targets, with a major focus on specific FGFRs. Methods MS-based phosphoproteomics, RNAseq, WES and Western blotting were used to characterize aberrantly activated protein kinases and effects of specific FGFR inhibitors. PDX and PDO were treated with the selective tyrosine kinase inhibitors AZD4547 (FGFR1-3) and BLU9931 (FGFR4). FGFR4 expression in cancer tissue samples and PDOs was assessed by immunohistochemistry. METABRIC and TCGA datasets were interrogated to identify specific FGFR alterations and their association with breast cancer subtype and patient survival. Results Phosphoproteomic profiling across 18 triple-negative breast cancers (TNBC) and 1 luminal B PDX revealed considerable heterogeneity in kinase activation, but 1/3 of PDX exhibited enhanced phosphorylation of FGFR1, FGFR2 or FGFR4. One TNBC PDX with high FGFR2 activation was exquisitely sensitive to AZD4547. Integrated ‘omic analysis revealed a novel FGFR2-SKI fusion that comprised the majority of FGFR2 joined to the C-terminal region of SKI containing the coiled-coil domains. High FGFR4 phosphorylation characterized a luminal B PDX model and treatment with BLU9931 significantly decreased tumor growth. Phosphoproteomic and transcriptomic analyses confirmed on-target action of the two anti-FGFR drugs and also revealed novel effects on the spliceosome, metabolism and extracellular matrix (AZD4547) and RIG-I-like and NOD-like receptor signaling (BLU9931). Interrogation of public datasets revealed FGFR2 amplification, fusion or mutation in TNBC and other breast cancer subtypes, while FGFR4 overexpression and amplification occurred in all breast cancer subtypes and were associated with poor prognosis. Characterization of a PDO panel identified a luminal A PDO with high FGFR4 expression that was sensitive to BLU9931 treatment, further highlighting FGFR4 as a potential therapeutic target. Conclusions This work highlights how patient-derived models of human breast cancer provide powerful platforms for therapeutic target identification and analysis of drug action, and also the potential of specific FGFRs, including FGFR4, as targets for precision treatment.

Background Cold damage stress significantly affects rice growth (germination and seedling) and causes serious losses in yield in temperate and high-altitude areas around the globe. Objective This study aimed to explore the cold tolerance (CT) locus of rice and create new cold-tolerant germplasm. We constructed a chromosome segment substitution line (CSSL) with strong CT and fine mapped quantitative trait loci (QTLs) associated with CT by performing the whole-genome resequencing of CSSL with phenotypes under cold treatment. Methods A chromosome CSSL, including 271 lines from a cross between the cold-tolerant wild rice Y11 ( Oryza rufipogon Griff.) and the cold-sensitive rice variety GH998, was developed to map QTLs conferring CT at the germination stage. The whole-genome resequencing was performed on CSSL for mapping QTLs of associated with CT at the germination stage. Results A high-density linkage map of the CSSLs was developed using the whole-genome resequencing of 1484 bins. The QTL analysis using 615,466 single-nucleotide polymorphisms (SNPs) led to the identification of 2 QTLs related to germination rate at low-temperature on chromosome 8 ( qCTG-8 ) and chromosome 11 ( qCTG-11 ). The qCTG-8 and qCTG-11 explained 14.55% and 14.31% of the total phenotypic variation, respectively. We narrowed down qCTG-8 and qCTG-11 to 195.5 and 78.83-kb regions, respectively. The expression patterns of important candidate genes in different tissues, and of RNA-sequencing (RNA-seq) in CSSLs, were identified based on gene sequences in qCTG-8 and qCTG-11 cold-induced expression analysis. LOC_Os08g01120 and LOC_Os08g01390 were identified as candidate genes in qCTG-8 , and LOC_Os11g32880 was identified as a candidate gene in qCTG-11 . Conclusions This study demonstrated a general method that could be used to identify useful loci and genes in wild rice and aid in the future cloning of candidate genes of qCTG-8 and qCTG-11 . The CSSLs with strong CT were supported for breeding cold-tolerant rice varieties.

The Holo-Hilbert spectral analysis (HHSA) method is introduced to cure the deficiencies of traditional spectral analysis and to give a full informational representation of nonlinear and non-stationary data. It uses a nested empirical mode decomposition and Hilbert-Huang transform (HHT) approach to identify intrinsic amplitude and frequency modulations often present in nonlinear systems. Comparisons are first made with traditional spectrum analysis, which usually achieved its results through convolutional integral transforms based on additive expansions of an a priori determined basis, mostly under linear and stationary assumptions. Thus, for non-stationary processes, the best one could do historically was to use the time- frequency representations, in which the amplitude (or energy density) variation is still represented in terms of time. For nonlinear processes, the data can have both amplitude and frequency modulations (intra-mode and inter-mode) generated by two different mechanisms: linear additive or nonlinear multiplicative processes. As all existing spectral analysis methods are based on additive expansions, either a priori or adaptive, none of them could possibly represent the multiplicative processes. While the earlier adaptive HHT spectral analysis approach could accommodate the intra-wave nonlinearity quite remarkably, it remained that any inter-wave nonlinear multiplicative mechanisms that include cross-scale coupling and phase-lock modulations were left untreated. To resolve the multiplicative processes issue, additional dimensions in the spectrum result are needed to account for the variations in both the amplitude and frequency modulations simultaneously. HHSA accommodates all the processes: additive and multiplicative, intra-mode and inter-mode, stationary and nonstationary, linear and nonlinear interactions. The Holo prefix in HHSA denotes a multiple dimensional representation with both additive and multiplicative capabilities.