Endogenous plant nitroxyl, a new component of nitric oxide biology.

Nitroxyl (HNO), a one-electron reduced and protonated congener of nitric oxide (•NO), was recently discovered in Arabidopsis thaliana. Due to its distinct chemical properties, we believe HNO must be further studied to determine how many physiological processes it impacts.

Quantifying NOx point sources with Landsat and Sentinel-2 satellite observations of NO2 plumes.

We show that the Landsat and Sentinel-2 satellites can detect NO2 plumes from large point sources at 10 to 60 m pixel resolution in their blue and ultrablue bands. We use the resulting NO2 plume imagery to quantify nitrogen oxides (NOx) emission rates for several power plants in Saudi Arabia and the United States, including a 13-y analysis of 132 Landsat plumes from Riyadh power plant 9 from 2009 through 2021. NO2 in the plumes initially increases with distance from the source, likely reflecting recovery from ozone titration. The fine pixel resolutions of Landsat and Sentinel-2 enable separation of individual point sources and stacks, including in urban background, and the long records enable examination of multidecadal emission trends. Our inferred NOx emission rates are consistent with previous estimates to within a precision of about 30%. Sources down to ~500 kg h-1 can be detected over bright, quasi-homogeneous surfaces. The 2009 to 2021 data for Riyadh power plant 9 show a strong summer peak in emissions, consistent with increased power demand for air conditioning, and a marginal slow decrease following the introduction of Saudi Arabia's Ambient Air Standard 2012.

Global-local aware Heterogeneous Graph Contrastive Learning for multifaceted association prediction in miRNA-gene-disease networks.

Unraveling the intricate network of associations among microRNAs (miRNAs), genes, and diseases is pivotal for deciphering molecular mechanisms, refining disease diagnosis, and crafting targeted therapies. Computational strategies, leveraging link prediction within biological graphs, present a cost-efficient alternative to high-cost empirical assays. However, while plenty of methods excel at predicting specific associations, such as miRNA-disease associations (MDAs), miRNA-target interactions (MTIs), and disease-gene associations (DGAs), a holistic approach harnessing diverse data sources for multifaceted association prediction remains largely unexplored. The limited availability of high-quality data, as vitro experiments to comprehensively confirm associations are often expensive and time-consuming, results in a sparse and noisy heterogeneous graph, hindering an accurate prediction of these complex associations. To address this challenge, we propose a novel framework called Global-local aware Heterogeneous Graph Contrastive Learning (GlaHGCL). GlaHGCL combines global and local contrastive learning to improve node embeddings in the heterogeneous graph. In particular, global contrastive learning enhances the robustness of node embeddings against noise by aligning global representations of the original graph and its augmented counterpart. Local contrastive learning enforces representation consistency between functionally similar or connected nodes across diverse data sources, effectively leveraging data heterogeneity and mitigating the issue of data scarcity. The refined node representations are applied to downstream tasks, such as MDA, MTI, and DGA prediction. Experiments show GlaHGCL outperforming state-of-the-art methods, and case studies further demonstrate its ability to accurately uncover new associations among miRNAs, genes, and diseases. We have made the datasets and source code publicly available at https://github.com/Sue-syx/GlaHGCL.

Tracing sources of atmospheric methane using clumped isotopes.

We apply a recently developed measurement technique for methane (CH4) isotopologues* (isotopic variants of CH4-13CH4, 12CH3D, 13CH3D, and 12CH2D2) to identify contributions to the atmospheric burden from fossil fuel and microbial sources. The aim of this study is to constrain factors that ultimately control the concentration of this potent greenhouse gas on global, regional, and local levels. While predictions of atmospheric methane isotopologues have been modeled, we present direct measurements that point to a different atmospheric methane composition and to a microbial flux with less clumping (greater deficits relative to stochastic) in both 13CH3D and 12CH2D2 than had been previously assigned. These differences make atmospheric isotopologue data sufficiently sensitive to variations in microbial to fossil fuel fluxes to distinguish between emissions scenarios such as those generated by different versions of EDGAR (the Emissions Database for Global Atmospheric Research), even when existing constraints on the atmospheric CH4 concentration profile as well as traditional isotopes are kept constant.

Roles of Pbp1, Mkt1, and Dhh1 in the regulation of gene expression in the medium containing non-fermentative carbon sources.

Pbp1, a yeast ortholog of human ataxin-2, is important for cell growth in the medium containing non-fermentable carbon sources. We had reported that Pbp1 regulates expression of genes related to glycogenesis via transcriptional regulation and genes related to mitochondrial function through mRNA stability control. To further analyze the role of Pbp1 in gene expression, we first examined the time course of gene expression after transfer from YPD medium containing glucose to YPGlyLac medium containing glycerol and lactate. At 12 h after transfer to YPGlyLac medium, the pbp1∆ mutant showed decreased expression of genes related to mitochondrial function but no decrease in expression of glycogenesis-related genes. We also examined a role of the Pbp1-binding factor, Mkt1. The mkt1∆ mutant, like the pbp1∆ mutant, showed slow growth on YPGlyLac plate and reduced expression of genes related to mitochondrial function. Furthermore, we found that mutation of DHH1 gene encoding a decapping activator exacerbated the growth of the pbp1∆ mutant on YPGlyLac plate. The dhh1∆ mutant showed reduced expression of genes related to mitochondrial function. These results indicate that Pbp1 and Mkt1 regulate the expression of genes related to mitochondrial function and that the decapping activator Dhh1 also regulates the expression of those genes.

Ion Source Complementarity for Characterization of Complex Organic Mixtures Using Fourier Transform Mass Spectrometry: A Review.

Complex organic mixtures are found in many areas of research, such as energy, environment, health, planetology, and cultural heritage, to name but a few. However, due to their complex chemical composition, which holds an extensive potential of information at the molecular level, their molecular characterization is challenging. In mass spectrometry, the ionization step is the key step, as it determines which species will be detected. This review presents an overview of the main ionization sources employed to characterize these kinds of samples in Fourier transform mass spectrometry (FT-MS), namely electrospray (ESI), atmospheric pressure photoionization (APPI), atmospheric pressure chemical ionization (APCI), atmospheric pressure laser ionization (APLI), and (matrix-assisted) laser desorption ionization ((MA)LDI), and their complementarity in the characterization of complex organic mixtures. First, the ionization techniques are examined in the common direct introduction (DI) usage. Second, these approaches are discussed in the context of coupling chromatographic techniques such as gas chromatography, liquid chromatography, and supercritical fluid chromatography.

Enhancing perceptual, attentional, and working memory demands through variable practice schedules: insights from high-density EEG multi-scale analyses.

Contextual interference (CI) enhances learning by practicing motor tasks in a random order rather than a blocked order. One hypothesis suggests that the benefits arise from enhanced early perceptual/attentional processes, while another posits that better learning is due to highly activated mnemonic processes. We used high-density electroencephalography in a multi-scale analysis approach, including topographic analyses, source estimations, and functional connectivity, to examine the intertwined dynamics of attentional and mnemonic processes within short time windows. We recorded scalp activity from 35 participants as they performed an aiming task at three different distances, under both random and blocked conditions using a crossover design. Our results showed that topographies associated with processes related to perception/attention (N1, P3a) and working memory (P3b) were more pronounced in the random condition. Source estimation analyses supported these findings, revealing greater involvement of the perceptual ventral pathway, anterior cingulate and parietal cortices, along with increased functional connectivity in ventral alpha and frontoparietal theta band networks during random practice. Our results suggest that CI is driven, in the random compared to the blocked condition, by enhanced specific processes such as perceptual, attentional, and working memory processes, as well as large-scale functional networks sustaining more general attentional and executive processes.

Capacity factors for electrical power generation from renewable and nonrenewable sources.

Given the dire consequences of climate change and the war in Ukraine, decarbonization of electrical power systems around the world must be accomplished, while avoiding recurring blackouts. A good understanding of performance and reliability of different power sources underpins this endeavor. As an energy transition involves different societal sectors, we must adopt a simple and efficient way of communicating the transition's key indicators. Capacity factor (CF) is a direct measure of the efficacy of a power generation system and of the costs of power produced. Since the year 2000, the explosive expansion of solar PV and wind power made their CFs more reliable. Knowing the long-time average CFs of different electricity sources allows one to calculate directly the nominal capacity required to replace the current fossil fuel mix for electricity generation or expansion to meet future demand. CFs are straightforwardly calculated, but they are rooted in real performance, not in modeling or wishful thinking. Based on the current average CFs, replacing 1 W of fossil electricity generation capacity requires installation of 4 W solar PV or 2 W of wind power. An expansion of the current energy mix requires installing 8.8 W of solar PV or 4.3 W of wind power.

Defining the challenges of Li extraction with olivine host: The roles of competitor and spectator ions.

The lithium supply issue mainly lies in the inability of current mining methods to access lithium sources of dilute concentrations and complex chemistry. Electrochemical intercalation has emerged as a highly selective method for lithium extraction; however, limited source compositions have been studied, which is insufficient to predict its applicability to the wide range of unconventional water sources (UWS). This work addresses the feasibility and identifies the challenges of Li extraction by electrochemical intercalation from UWS, by answering three questions: 1) Is there enough Li in UWS? 2) How would the solution compositions affect the competition of Li+ to major ions (Na+/Mg2+/K+/Ca2+)? 3) Does the complex solution composition affect the electrode stability? Using one-dimensional olivine FePO4 as the model electrode, we show the complicated roles of major ions. Na+ acts as the competitor ion for host storage sites. The competition from Na+ grants Mg2+ and Ca2+ being only the spectator ions. However, Mg2+ and Ca2+ can significantly affect the charge transfer of Li+ and Na+, therefore affecting the Li selectivity. We point to improving the selectivity of Li+ to Na+ as the key challenge for broadening the minable UWS using the olivine host.

A Gold Needle Tip Array Ultrafast Electron Source with High Beam Quality.

Electron sources are crucial elements in diverse applications such as electron microscopes, synchrotrons, and free-electron lasers. Nanometer-sharp needle tips are electron emitters with the highest beam quality, yet for a single needle the current is limited. Combining the emission of multiple needles promises large current yields while preserving the individual emitters' favorable properties. We present an ultrafast electron source consisting of a lithographically fabricated array of sharp gold tips illuminated with 25 fs laser pulses. The source provides up to 2000 electrons per pulse for moderate laser peak intensities of 1011 W/cm2 and a narrow energy width of 0.5 ± 0.05 eV at low current. The electron beam has a well-behaved Gaussian profile and is highly collimated, yielding a small normalized emittance on the order of nm·rad. These properties are well suited for applications requiring both high current and spatial resolution, such as free-electron light sources and chip-based particle accelerators.

Control of Quantized Spontaneous Emission from Single GaAs Quantum Dots Embedded in Huygens' Metasurfaces.

Advancements in photonic quantum information systems (QIS) have driven the development of high-brightness, on-demand, and indistinguishable semiconductor epitaxial quantum dots (QDs) as single photon sources. Strain-free, monodisperse, and spatially sparse local-droplet-etched (LDE) QDs have recently been demonstrated as a superior alternative to traditional Stranski-Krastanov QDs. However, integration of LDE QDs into nanophotonic architectures with the ability to scale to many interacting QDs is yet to be demonstrated. We present a potential solution by embedding isolated LDE GaAs QDs within an Al0.4Ga0.6As Huygens' metasurface with spectrally overlapping fundamental electric and magnetic dipolar resonances. We demonstrate for the first time a position- and size-independent, 1 order of magnitude increase in the collection efficiency and emission lifetime control for single-photon emission from LDE QDs embedded within the Huygens' metasurfaces. Our results represent a significant step toward leveraging the advantages of LDE QDs within nanophotonic architectures to meet the scalability demands of photonic QIS.

Tailoring Single-Electron Emission Distributions in the Time-Energy Phase Space.

The precise characterization and control of single-electron wave functions emitted from a single-electron source are essential for advancing electron quantum optics. Here, we introduce a method for tailoring a single-electron emission distribution using energy filtering, enabling selective control of the distribution under various energy barrier conditions of the filter. The tailored electron is studied by reconstructing its Wigner distribution in the time-energy phase space using the continuous-variable tomography method. Our results reveal that the filtering cuts the portion of the distribution below the energy-barrier height of the filter in the time-energy space. While the filtering is demonstrated in a classical regime of the emitted electrons, we expect that this study significantly contributes to the design and implementation of advanced experiments toward quantum information processing based on single electrons.

Polarized and Bright Telecom C-Band Single-Photon Source from InP-Based Quantum Dots Coupled to Elliptical Bragg Gratings.

Bright, polarized, and high-purity single-photon sources in telecom wavelengths are crucial components in long-distance quantum communication, optical quantum computation, and quantum networks. Semiconductor InAs/InP quantum dots (QDs) combined with photonic cavities provide a competitive path, leading to optimal single-photon sources in this range. Here, we demonstrate a bright and polarized single-photon source operating in the telecom C-band based on an elliptical Bragg grating (EBG) cavity. With a significant Purcell enhancement of 5.25 ± 0.05, the device achieves a polarization ratio of 0.986, a single-photon purity of g2(0) = 0.078 ± 0.016, and a single-polarized photon collection efficiency of ∼24% at the first lens (NA = 0.65) without blinking. These findings suggest that C-band QD-based single-photon sources are potential candidates for advancing quantum communication.

Engaging Communities in Emerging Infectious Disease Mitigation to Improve Public Health and Safety.

The COVID-19 pandemic highlighted the need for potent community-based tools to improve preparedness. We developed a community health-safety climate (HSC) measure to assess readiness to adopt health behaviors during a pandemic. We conducted a mixed-methods study incorporating qualitative methods (e.g., focus groups) to generate items for the measure and quantitative data from a February 2021 national survey to test reliability, multilevel construct, and predictive and nomologic validities. The 20-item HSC measure is unidimensional (Cronbach α = 0.87). All communities had strong health-safety climates but with significant differences between communities (F = 10.65; p<0.001), and HSC levels predicted readiness to adopt health-safety behaviors. HSC strength moderated relationships between HSC level and behavioral indicators; higher climate homogeneity demonstrated stronger correlations. The HSC measure can predict community readiness to adopt health-safety behaviors in communities to inform interventions before diseases spread, providing a valuable tool for public health authorities and policymakers during a pandemic.

CutFEM-based MEG forward modeling improves source separability and sensitivity to quasi-radial sources: A somatosensory group study.

Source analysis of magnetoencephalography (MEG) data requires the computation of the magnetic fields induced by current sources in the brain. This so-called MEG forward problem includes an accurate estimation of the volume conduction effects in the human head. Here, we introduce the Cut finite element method (CutFEM) for the MEG forward problem. CutFEM's meshing process imposes fewer restrictions on tissue anatomy than tetrahedral meshes while being able to mesh curved geometries contrary to hexahedral meshing. To evaluate the new approach, we compare CutFEM with a boundary element method (BEM) that distinguishes three tissue compartments and a 6-compartment hexahedral FEM in an n = 19 group study of somatosensory evoked fields (SEF). The neural generators of the 20 ms post-stimulus SEF components (M20) are reconstructed using both an unregularized and a regularized inversion approach. Changing the forward model resulted in reconstruction differences of about 1 centimeter in location and considerable differences in orientation. The tested 6-compartment FEM approaches significantly increase the goodness of fit to the measured data compared with the 3-compartment BEM. They also demonstrate higher quasi-radial contributions for sources below the gyral crowns. Furthermore, CutFEM improves source separability compared with both other approaches. We conclude that head models with 6 compartments rather than 3 and the new CutFEM approach are valuable additions to MEG source reconstruction, in particular for sources that are predominantly radial.

Metabolomic and transcriptomic analyses of yellow-flowered crocuses to infer alternative sources of saffron metabolites.

BACKGROUND: The increasing demand for saffron metabolites in various commercial industries, including medicine, food, cosmetics, and dyeing, is driven by the discovery of their diverse applications. Saffron, derived from Crocus sativus stigmas, is the most expensive spice, and there is a need to explore additional sources to meet global consumption demands. In this study, we focused on yellow-flowering crocuses and examined their tepals to identify saffron-like compounds. RESULTS: Through metabolomic and transcriptomic approaches, our investigation provides valuable insights into the biosynthesis of compounds in yellow-tepal crocuses that are similar to those found in saffron. The results of our study support the potential use of yellow-tepal crocuses as a source of various crocins (crocetin glycosylated derivatives) and flavonoids. CONCLUSIONS: Our findings suggest that yellow-tepal crocuses have the potential to serve as a viable excessive source of some saffron metabolites. The identification of crocins and flavonoids in these crocuses highlights their suitability for meeting the demands of various industries that utilize saffron compounds. Further exploration and utilization of yellow-tepal crocuses could contribute to addressing the growing global demand for saffron-related products.

Response to oxalic acid: an important supplement screening against stem rot resistance in groundnut (Arachis hypogaea L.).

BACKGROUND: Stem rot, caused by the soil-borne pathogen Sclerotium rolfsii, pose a serious challenge in the groundnut (Arachis hypogaea L) cultivation. Although this disease is widespread globally but had most adverse impact in groundnut growing regions of United States, India, and Australia. The pathogen primarily targets the crown region of the plant, resulting in systemic collapse and potentially leading to yield losses up to 80%. Effective genetic control measures are essential to mitigate the impact of this disease on groundnut production. Realizing the time and resource-consuming complex field-based phenotyping, the availability of easy and repeatable phenotyping methods may fasten the process of donor and gene discovery efforts. RESULTS: Multi-season phenotyping was performed for stem rot on 184 minicore germplasm accessions, including checks, under two conditions: sick field screening and response to oxalic acid assay. This study demonstrated medium to high heritability (52-63% broad-sense heritability) and significant environmental influence (36%). The response to the oxalic acid assay showed a high proportion of similarity (approximately 80%) with the percent mortality observed in the sick field indicating an easy way of performing precise phenotyping. Notably, seven genotypes-ICG163, ICG721, ICG10479, ICG875, ICG11457, ICG111, and ICG2857-exhibited stable resistance, with less than 30% mortality against stem rot disease. Among these, ICG163, ICG875, and ICG111 displayed low mortality and consistent stability across multiple seasons in both the sick field and controlled conditions of the oxalic acid assay. CONCLUSIONS: The oxalic acid assay developed in this study effectively complements field phenotyping, as a reliable method for assessing stem rot resistance. Seven resistant genotypes identified through this assay can be utilized for the introgression of stem rot resistance into elite genotypes. Given the significant influence of the environment on stem rot resistance, it is essential to implement multi-season phenotyping to obtain precise results. Furthermore, the response to oxalic acid serves as a valuable supplement to traditional field phenotyping, since maintaining uniform disease pressure during field screenings is often challenging.

Boosting the Electrical Performance of PLA-Based Triboelectric Nanogenerators for Sustainable Power Sources and Self-Powered Sensing.

Triboelectric nanogenerators (TENGs) have emerged as a promising technology for harvesting mechanical energy from the ambient environment. However, developing tribopositive materials with strong piezoelectric effects and high electron-donating ability still remains a challenge. Herein, poly(ethylene glycol) monomethyl ether (mPEG) to soft poly(lactic acid) (PLA) is adopted, then PLA/mPEG nanofibers are fabricated under electrospinning and used as the tribopositive material for fabricating robust power density TENGs. The crystallinity and dynamic mechanical properties of PLA/mPEG nanofibers are investigated. The results revealed that the incorporation of mPEG provided an effective approach to elevate the electron-donating ability and charge transfer efficiency in PLA. The PLA/mPEG-based TENGs achieved a high open-circuit voltage of 342.8 V, a short-circuit current of 38.5 µA, and a maximum power density of 116.21 W m-2 over a 2 cm2 contact area at an external load of 106 Ω, respectively. Strikingly, excellent stability and durability are demonstrated after continuous cycles up to 104 cycles. Noteworthy, the TENGs are explored for self-powered sensing applications, with seven TENG units integrated to act as self-powered sensors playing music through buzzers when pressed by fingers. Eventually, this work provides new insights into tuning the structures and properties of electrospun polymers to reinforce the TENG output and self-powered systems.

High-pressure X-ray photon correlation spectroscopy at fourth-generation synchrotron sources.

A new experimental setup combining X-ray photon correlation spectroscopy (XPCS) in the hard X-ray regime and a high-pressure sample environment has been developed to monitor the pressure dependence of the internal motion of complex systems down to the atomic scale in the multi-gigapascal range, from room temperature to 600 K. The high flux of coherent high-energy X-rays at fourth-generation synchrotron sources solves the problems caused by the absorption of diamond anvil cells used to generate high pressure, enabling the measurement of the intermediate scattering function over six orders of magnitude in time, from 10-3 s to 103 s. The constraints posed by the high-pressure generation such as the preservation of X-ray coherence, as well as the sample, pressure and temperature stability, are discussed, and the feasibility of high-pressure XPCS is demonstrated through results obtained on metallic glasses.

IL-22, a vital cytokine in autoimmune diseases.

Interleukin-22 (IL-22) is a vital cytokine that is dysregulated in various autoimmune conditions including rheumatoid arthritis (RA), multiple sclerosis (MS), and Alzheimer's disease (AD). As the starting point for the activation of numerous signaling pathways, IL-22 plays an important role in the initiation and development of autoimmune diseases. Specifically, imbalances in IL-22 signaling can interfere with other signaling pathways, causing cross regulation of target genes which ultimately leads to the development of immune disorders. This review delineates the various connections between the IL-22 signaling pathway and autoimmune disease, focusing on the latest understanding of the cellular sources of IL-22 and its effects on various cell types. We further explore progress with pharmacological interventions related to targeting IL-22, describing how such therapeutic strategies promise to usher in a new era in the treatment of autoimmune disease.