Thermal, water, and land cover factors led to contrasting urban and rural vegetation resilience to extreme hot months

With continuing global warming and urbanization, it is increasingly important to understand the resilience of urban vegetation to extreme high temperatures, but few studies have examined urban vegetation at large scale or both concurrent and delayed responses. In this study, we performed an urban-rural comparison using the Enhanced Vegetation Index and months that exceed the historical 90th percentile in mean temperature (referred to as "hot months") across 85 major cities in the contiguous United States. We found that hot months initially enhanced vegetation greenness but could cause a decline afterwards, especially for persistent (≥4 months) and intense (≥+2 °C) episodes in summer. The urban responses were more positive than rural in the western United States or in winter, but more negative during spring-autumn in the eastern United States. The east-west difference can be attributed to the higher optimal growth temperatures and lower water stress levels of the western urban vegetation than the rural. The urban responses also had smaller magnitudes than the rural responses, especially in deciduous forest biomes, and least in evergreen forest biomes. Within each biome, analysis at 1 km pixel level showed that impervious fraction and vegetation cover, local urban heat island intensity, and water stress were the key drivers of urban-rural differences. These findings advance our understanding of how prolonged exposure to warm extremes, particularly within urban environments, affects vegetation greenness and vitality. Urban planners and ecosystem managers should prioritize the long and intense events and the key drivers in fostering urban vegetation resilience to heat waves.

Unraveling the Role of Solvation and Ion Valency on Redox-Mediated Electrosorption through In Situ Neutron Reflectometry and Ab Initio Molecular Dynamics

Solvation and ion valency effects on selectivity of metal oxyanions at redox-polymer interfaces are explored through in situ spatial-temporally resolved neutron reflectometry combined with large scale ab initio molecular dynamics. The selectivity of ReO4- vs MoO42- for two redox-metallopolymers, poly(vinyl ferrocene) (PVFc) and poly(3-ferrocenylpropyl methacrylamide) (PFPMAm) is evaluated. PVFc has a higher Re/Mo separation factor compared to PFPMAm at 0.6 V vs Ag/AgCl. In situ techniques show that both PVFc and PFPMAm swell in the presence of ReO4- (having higher solvation with PFPMAm), but do not swell in contact with MoO42-. Ab initio molecular simulations suggest that MoO42- maintains a well-defined double solvation shell compared to ReO4-. The more loosely solvated anion (ReO4-) is preferably adsorbed by the more hydrophobic redox polymer (PVFc), and electrostatic cross-linking driven by divalent anionic interactions could impair film swelling. Thus, the in-depth understanding of selectivity mechanisms can accelerate the design of ion-selective redox-mediated separation systems for transition metal recovery and recycling.

Tracing mechanistic pathways and reaction kinetics toward equilibrium in reactive molten salts

In the dynamic environment of multi-component reactive molten salts, speciation unfolds as a complex process, involving multiple competing reaction pathways that are likely to face free energy barriers before reaching the reaction equilibria. Herein, we unravel intricate speciation in the AlCl3-KCl melt compositions with rate theory and ab initio molecular dynamics simulations. We find that the compositions with 100 and 50 mol% AlCl3 exclusively comprise neutral Al2Cl6 dimers and charged AlCl4- monomers, respectively. In intermediate AlCl3-KCl compositions, the chemical speciation proves to be a very complex process, requiring over 0.5 nanosecond to reach an equilibrium distribution of multiple species. It is a consequence of the competitive formation and dissociation of additional species, including charged Al dimers, trimers, and tetramers. Here, the species formation occurs through ion exchange events, which we explain by computing free energy landscapes and employing a Marcus-like rate theory. We show that both interspecies and intraspecies ion exchanges are probable and are dictated by the local structural reorganization reflected in the change of local coulombic fields. The species distributions are validated by comparing computed Raman spectra and neutron structure factors with the available experimental data. We find an excellent simulation-experiment agreement in both cases. Nevertheless, Raman spectroscopy turns out to be particularly advantageous for distinguishing between unique species distributions because of the distinct vibrational signatures of different species. The mechanistic insight into reaction dynamics gained in this study will be essential for the advancement of molten salts as reactive media in high-temperature energy applications.

Zr-Porphyrin Metal-Organic Framework as nanoreactor for boosting the formation of hydrogen clathrates

We report the first experimental evidence for rapid formation of hydrogen clathrates under mild pressure and temperature conditions within the cavities of a zirconium-metalloporphyrin framework, specifically PCN-222. PCN-222 has been selected for its 1D mesoporous channels, high water-stability, and proper hydrophilic behavior. Firstly, we optimize a microwave (MW)-assisted method for the synthesis of nanosized PCN-222 particles with precise structure control (exceptional homogeneity in morphology and crystalline phase purity), taking advantage of MW in terms of rapid/homogeneous heating, time and energy savings, as well as potential scalability of the synthetic method. Second, we explore the relevance of the large mesoporous 1D open channels within the PCN-222 to promote the nucleation and growth of confined hydrogen clathrates. Experimental results show that PCN-222 drives the nucleation process at a lower pressure than the bulk system (1.35 kbar vs 2 kbar), with fast kinetics (minutes), using pure water, and with a nearly complete water-to-hydrate conversion. Unfortunately, PCN-222 cannot withstand these high pressures, which lead to a significant alteration of the mesoporous structure while the microporous network remains mainly unchanged.

Secondary Ion Mass Spectral Imaging of Metals and Alloys

Secondary Ion Mass Spectrometry (SIMS) is an outstanding technique for Mass Spectral Imaging (MSI) due to its notable advantages, including high sensitivity, selectivity, and high dynamic range. As a result, SIMS has been employed across many domains of science. In this review, we provide an in-depth overview of the fundamental principles underlying SIMS, followed by an account of the recent development of SIMS instruments. The review encompasses various applications of specific SIMS instruments, notably static SIMS with time-of-flight SIMS (ToF-SIMS) as a widely used platform and dynamic SIMS with Nano SIMS and large geometry SIMS as successful instruments. We particularly focus on SIMS utility in microanalysis and imaging of metals and alloys as materials of interest. Additionally, we discuss the challenges in big SIMS data analysis and give examples of machine leaning (ML) and Artificial Intelligence (AI) for effective MSI data analysis. Finally, we recommend the outlook of SIMS development. It is anticipated that in situ and operando SIMS has the potential to significantly enhance the investigation of metals and alloys by enabling real-time examinations of material surfaces and interfaces during dynamic transformations.

Anoxia begets anoxia: A positive feedback to the deoxygenation of temperate lakes

Declining oxygen concentrations in the deep waters of lakes worldwide pose a pressing environmental and societal challenge. Existing theory suggests that low deep-water dissolved oxygen (DO) concentrations could trigger a positive feedback through which anoxia (i.e., very low DO) during a given summer begets increasingly severe occurrences of anoxia in following summers. Specifically, anoxic conditions can promote nutrient release from sediments, thereby stimulating phytoplankton growth, and subsequent phytoplankton decomposition can fuel heterotrophic respiration, resulting in increased spatial extent and duration of anoxia. However, while the individual relationships in this feedback are well established, to our knowledge, there has not been a systematic analysis within or across lakes that simultaneously demonstrates all of the mechanisms necessary to produce a positive feedback that reinforces anoxia. Here, we compiled data from 656 widespread temperate lakes and reservoirs to analyze the proposed anoxia begets anoxia feedback. Lakes in the dataset span a broad range of surface area (1-126,909 ha), maximum depth (6-370 m), and morphometry, with a median time-series duration of 30 years at each lake. Using linear mixed models, we found support for each of the positive feedback relationships between anoxia, phosphorus concentrations, chlorophyll a concentrations, and oxygen demand across the 656-lake dataset. Likewise, we found further support for these relationships by analyzing time-series data from individual lakes. Our results indicate that the strength of these feedback relationships may vary with lake-specific characteristics: For example, we found that surface phosphorus concentrations were more positively associated with chlorophyll a in high-phosphorus lakes, and oxygen demand had a stronger influence on the extent of anoxia in deep lakes. Taken together, these results support the existence of a positive feedback that could magnify the effects of climate change and other anthropogenic pressures driving the development of anoxia in lakes around the world.

Synthesis and Characterization of Stimuli-Responsive Polymer Brushes in Nanofluidic Channels

Nanochannels with controllable gating behavior are attractive features in a wide range of nanofluidic applications including viral detection, particle sorting, and flow regulation. Here, we use selective sidewall functionalization of nanochannels with a polyelectrolyte brush to investigate the channel gating response to variations in solution pH and ionic strength. The conformational and structural changes of the interfacial brush layer within the channels are interrogated by specular and off-specular neutron reflectometry. Simultaneous fits of the specular and off-specular signals, using a dynamical theory model and a fitting optimization protocol, enable detailed characterization of the brush conformations and corresponding channel geometry under different solution conditions. Our results indicate a collapsed brush state under basic pH, equivalent to an open gate, and an expanded brush state representing a partially closed gate upon decreasing the pH and salt concentration. These findings open new possibilities in noninvasive in situ characterization of tunable nanofluidics and lab-on-chip devices with advanced designs and improved functionality.

Divergent selection and climate adaptation fuel genomic differentiation between sister species of Sphagnum (peat moss)

BACKGROUND AND AIMS

New plant species can evolve through the reinforcement of reproductive isolation via local adaptation along habitat gradients. Peat mosses (Sphagnaceae) are an emerging model system for the study of evolutionary genomics and have well-documented niche differentiation among species. Recent molecular studies have demonstrated that the globally distributed species Sphagnum magellanicum is a complex of morphologically cryptic lineages that are phylogenetically and ecologically distinct. Here, we describe the architecture of genomic differentiation between two sister species in this complex known from eastern North America: the northern S. diabolicum and the largely southern S. magniae.

METHODS

We sampled plant populations from across a latitudinal gradient in eastern North America and performed whole genome and restriction-site associated DNA sequencing. These sequencing data were then analyzed computationally.

KEY RESULTS

Using sliding-window population genetic analyses we find that differentiation is concentrated within 'islands' of the genome spanning up to 400 kb that are characterized by elevated genetic divergence, suppressed recombination, reduced nucleotide diversity and increased rates of non-synonymous substitution. Sequence variants that are significantly associated with genetic structure and bioclimatic variables occur within genes that have functional enrichment for biological processes including abiotic stress response, photoperiodism and hormone-mediated signalling. Demographic modelling demonstrates that these two species diverged no more than 225 000 generations ago with secondary contact occurring where their ranges overlap.

CONCLUSIONS

We suggest that this heterogeneity of genomic differentiation is a result of linked selection and reflects the role of local adaptation to contrasting climatic zones in driving speciation. This research provides insight into the process of speciation in a group of ecologically important plants and strengthens our predictive understanding of how plant populations will respond as Earth's climate rapidly changes.

Recovery of 2,3-Butanediol from Fermentation Broth by Zeolitic Imidazolate Frameworks

The efficient separation of the 2,3-butanediol (2,3-BDO) intermediate from fermentation broth is an important issue in the production of biofuels from biomass-derived intermediates. Two zeolitic imidazolate frameworks ZIF-8 and ZIF-71 were investigated for the adsorption of 2,3-butanediol (2,3-BDO) from fermentation broth via liquid breakthrough adsorption measurements. While both ZIF materials initially show high separation performance, ZIF-71 retains robust separation performance even after aging in ethanol for two years, whereas the capacity of ZIF-8 decreases significantly. The robustness and stability of ZIF-71 are further confirmed with cyclic fixed bed adsorption measurements. The uptake of 2,3-BDO on ZIF-71 reaches >100 g/kg with negligible uptakes of sugars, organic acids, and other alcohols present in the fermentation broth. Excellent selectivity toward 2,3-BDO over water is also achieved. The 2,3-BDO-loaded ZIF-71 can be regenerated efficiently with ethanol as desorbent. These findings indicate that ZIF-71 shows considerable promise as an adsorbent to recover and purify diols from fermentation broths.

Armoring of MgO by a Passivation Layer Impedes Direct Air Capture of CO2

It has been proposed to use magnesium oxide (MgO) to separate carbon dioxide directly from the atmosphere at the gigaton level. We show experimental results on MgO single crystals reacting with the atmosphere for longer (decades) and shorter (days to months) periods with the goal of gauging reaction rates. Here, we find a substantial slowdown of an initially fast reaction as a result of mineral armoring by reaction products (surface passivation). In short-term experiments, we observe fast hydroxylation, carbonation, and formation of amorphous hydrated magnesium carbonate at early stages, leading to the formation of crystalline hydrated Mg carbonates. The preferential location of Mg carbonates along the atomic steps on the crystal surface of MgO indicates the importance of the reactive site density for carbonation kinetics. The analysis of 27-year-old single-crystal MgO samples demonstrates that the thickness of the reacted layer is limited to ∼1.5 μm on average, which is thinner than expected and indicates surface passivation. Thus, if MgO is to be employed for direct air capture of CO2, surface passivation must be circumvented.

Effect of Methyl Groups on Formation of Ordered or Layered Graphitic Materials from Aromatic Molecules

Developing functionally complex carbon materials from small aromatic molecules requires an understanding of how the chemistry and structure of its constituent molecules evolve and crosslink, to achieve a tailorable set of functional properties. Here, molecular dynamics (MD) simulations are used to isolate the effect of methyl groups on condensation reactions during the oxidative process and evaluate the impact on elastic modulus by considering three monodisperse pyrene-based systems with increasing methyl group fraction. A parameter to quantify the reaction progression is designed by computing the number of new covalent bonds formed. Utilizing the previously developed MD framework, it is found that increasing methylation leads to an almost doubling of bond formation, a larger fraction of the new bonds oriented in the direction of tensile stress, and a higher basal plane alignment of the precursor molecules along the direction of tensile stress, resulting in enhanced tensile modulus. Additionally, via experiments, it is demonstrated that precursors with a higher fraction of methyl groups result in a higher alignment of molecules. Moreover, increased methylation results in the lower spread of single molecule alignment which may lead to smaller variations in tensile modulus and more consistent properties in carbon materials derived from methyl-rich precursors.

Hyperspectral mapping of nanoscale photophysics and degradation processes in hybrid perovskite at the single grain level

With solar cells reaching 26.1% certified efficiency, hybrid perovskites are now the most efficient thin film photovoltaic material. Though substantial effort has focussed on synthesis approaches and device architectures to further improve perovskite-based solar cells, more work is needed to correlate physical properties of the underlying film structure with device performance. Here, using cathodoluminescence microscopy coupled with unsupervised machine learning, we quantify how nanoscale heterogeneity globally builds up within a large morphological grain of hybrid perovskite when exposed to extrinsic stimuli such as charge accumulation from electron beams or milder environmental factors like humidity. The converged electron-beam excitation allows us to map PbI2 and the emergence of other intermediate phases with high spatial and energy resolution. In contrast with recent reports of hybrid perovskite cathodoluminescence, we observe no significant change in the PbI2 signatures, even after high-energy electron beam excitation. In fact, we can exploit the stable PbI2 signatures to quantitatively map how hybrid perovskites degrade. Moreover, we show how our methodology allows disentangling of the photophysics associated with photon recycling and band-edge emission with sub-micron resolution using a fundamental understanding of electron interactions in hybrid perovskites.

Microscale Electrochemical Corrosion of Uranium Oxide Particles

Understanding the corrosion of spent nuclear fuel is important for the development of long-term storage solutions. However, the risk of radiation contamination presents challenges for experimental analysis. Adapted from the system for analysis at the liquid-vacuum interface (SALVI), we developed a miniaturized uranium oxide (UO2)-attached working electrode (WE) to reduce contamination risk. To protect UO2 particles in a miniatured electrochemical cell, a thin layer of Nafion was formed on the surface. Atomic force microscopy (AFM) shows a dense layer of UO2 particles and indicates their participation in electrochemical reactions. Particles remain intact on the electrode surface with slight redistribution. X-ray photoelectron spectroscopy (XPS) reveals a difference in the distribution of U(IV), U(V), and U(VI) between pristine and corroded UO2 electrodes. The presence of U(V)/U(VI) on the corroded electrode surface demonstrates that electrochemically driven UO2 oxidation can be studied using these cells. Our observations of U(V) in the micro-electrode due to the selective semi-permeability of Nafion suggest that interfacial water plays a key role, potentially simulating a water-lean scenario in fuel storage conditions. This novel approach offers analytical reproducibility, design flexibility, a small footprint, and a low irradiation dose, while separating the α-effect. This approach provides a valuable microscale electrochemical platform for spent fuel corrosion studies with minimal radiological materials and the potential for diverse configurations.

Hollow Ptychography: Toward Simultaneous 4D Scanning Transmission Electron Microscopy and Electron Energy Loss Spectroscopy

With the recent development of high-acquisition-speed pixelated detectors, 4D scanning transmission electron microscopy (4D-STEM) is becoming routinely available in high-resolution electron microscopy. 4D-STEM acts as a "universal" method that provides local information on materials that is challenging to extract from bulk techniques. It extends conventional STEM imaging to include super-resolution techniques and to provide quantitative phase-based information, such as differential phase contrast, ptychography, or Bloch wave phase retrieval. However, an important missing factor is the chemical and bonding information provided by electron energy loss spectroscopy (EELS). 4D-STEM and EELS cannot currently be acquired simultaneously due to the overlapping geometry of the detectors. Here, the feasibility of modifying the detector geometry to overcome this challenge for bulk specimens is demonstrated, and the use of a partial or defective detector for ptycholgaphic structural imaging is explored. Results show that structural information beyond the diffraction-limit and chemical information from the material can be extracted together, resulting in simultaneous multi-modal measurements, adding the additional dimensions of spectral information to 4D datasets.

The interplay between hydrogen and halogen bonding: substituent effects and their role in the hydrogen bond enhanced halogen bond

The hydrogen bond enhanced halogen bond (HBeXB) has recently been used to effectively improve anion binding, organocatalysis, and protein structure/function. In this study, we present the first systematic investigation of substituent effects in the HBeXB. NMR analysis confirmed intramolecular HBing between the amine and the electron-rich belt of the XB donor (N-H⋯I). Gas-phase density functional theory studies showed that the influence of HBing on the halogen atom is more sensitive to substitution on the HB donor ring (R1). The NMR studies revealed that the intramolecular HBing had a significant impact on receptor performance, resulting in a 50-fold improvement. Additionally, linear free energy relationship (LFER) analysis was employed for the first time to study the substituent effect in the HBeXB. The results showed that substituents on the XB donor ring (R2) had a competing effect where electron donating groups strengthened the HB and weakened the XB. Therefore, selecting an appropriate substituent on the adjacent HB donor ring (R1) could be an alternative and effective way to enhance an electron-rich XB donor. X-ray crystallographic analysis demonstrated that intramolecular HBing plays an important role in the receptor adopting the bidentate conformation. Taken together, the findings imply that modifying distal substituents that affect neighboring noncovalent interactions can have a similar impact to conventional para substitution substituent effects.

Mass Spectral Imaging to Map Plant-Microbe Interactions

Plant-microbe interactions are of rising interest in plant sustainability, biomass production, plant biology, and systems biology. These interactions have been a challenge to detect until recent advancements in mass spectrometry imaging. Plants and microbes interact in four main regions within the plant, the rhizosphere, endosphere, phyllosphere, and spermosphere. This mini review covers the challenges within investigations of plant and microbe interactions. We highlight the importance of sample preparation and comparisons among time-of-flight secondary ion mass spectroscopy (ToF-SIMS), matrix-assisted laser desorption/ionization (MALDI), laser desorption ionization (LDI/LDPI), and desorption electrospray ionization (DESI) techniques used for the analysis of these interactions. Using mass spectral imaging (MSI) to study plants and microbes offers advantages in understanding microbe and host interactions at the molecular level with single-cell and community communication information. More research utilizing MSI has emerged in the past several years. We first introduce the principles of major MSI techniques that have been employed in the research of microorganisms. An overview of proper sample preparation methods is offered as a prerequisite for successful MSI analysis. Traditionally, dried or cryogenically prepared, frozen samples have been used; however, they do not provide a true representation of the bacterial biofilms compared to living cell analysis and chemical imaging. New developments such as microfluidic devices that can be used under a vacuum are highly desirable for the application of MSI techniques, such as ToF-SIMS, because they have a subcellular spatial resolution to map and image plant and microbe interactions, including the potential to elucidate metabolic pathways and cell-to-cell interactions. Promising results due to recent MSI advancements in the past five years are selected and highlighted. The latest developments utilizing machine learning are captured as an important outlook for maximal output using MSI to study microorganisms.

Revealing the Bacterial Quorum-Sensing Effect on the Biofilm Formation of Diatom Cylindrotheca sp. Using Multimodal Imaging

Diatoms contribute to carbon fixation in the oceans by photosynthesis and always form biofouling organized by extracellular polymeric substances (EPS) in the marine environment. Bacteria-produced quorum-sensing signal molecules N-acyl homoserine lactones (AHLs) were found to play an important role in the development of Cylindrotheca sp. in previous studies, but the EPS composition change was unclear. This study used the technology of alcian blue staining and scanning electron microscopy (SEM), confocal laser scanning microscopy (CLSM), and time-of-flight secondary ion mass spectrometry (ToF-SIMS) to directly observe the biofilm formation process. The results showed that AHLs promote the growth rates of diatoms and the EPS secretion of biofilm components. AHLs facilitated the diatom-biofilm formation by a forming process dependent on the length of carbon chains. AHLs increased the biofilm thickness and the fluorescence intensity and then altered the three-dimensional (3D) structures of the diatom-biofilm. In addition, the enhanced EPS content in the diatom-biofilm testified that AHLs aided biofilm formation. This study provides a collection of new experimental evidence of the interaction between bacteria and microalgae in fouling biofilms.

Anti-polyelectrolyte and polyelectrolyte effects on conformations of polyzwitterionic chains in dilute aqueous solutions

Polyzwitterions (PZs) are considered as model synthetic analogs of intrinsically disordered proteins. Based on this analogy, PZs in dilute aqueous solutions are expected to attain either globular (i.e. molten, compact) or random coil conformations. Addition of salt is expected to open these conformations. To the best of our knowledge, these hypotheses about conformations of PZs have never been verified. In this study, we test these hypotheses by studying effects of added salt [potassium bromide (KBr)] on gyration and hydrodynamic radii of poly(sulfobetaine methacrylate) in dilute aqueous solutions using dynamic light scattering and small-angle X-ray scattering, respectively. Effects of zwitteration are revealed by direct comparisons of the PZs with the polymers of the same backbone but containing (1) no explicit charges on side groups such as poly(2-dimethylaminoethyl methacrylate)s and (2) explicit cationic side groups with tertiary amino bromide pendants. Zeta-potential measurements, transmission electron microscopy, and ab initio molecular dynamics simulations reveal that the PZs acquire net positive charge in near salt-free conditions due to protonation but retain coiled conformations. Added KBr leads to nonmonotonic changes exhibiting an increase followed by a decrease in radius of gyration (and hydrodynamic radius), which are called antipolyelectrolyte and polyelectrolyte effects, respectively. Charge regulation and screening of charge-charge interactions are discussed in relation to the antipolyelectrolyte and polyelectrolyte effects, respectively, which highlight the importance of salt in affecting net charge and conformations of PZs.

Porewater constituents inhibit microbially mediated greenhouse gas production (GHG) and regulate the response of soil organic matter decomposition to warming in anoxic peat from a Sphagnum-dominated bog

Northern peatlands store approximately one-third of terrestrial soil carbon. Climate warming is expected to stimulate the microbially mediated degradation of peat soil organic matter (SOM), leading to increasing greenhouse gas (GHG; carbon dioxide, CO2; methane, CH4) production and emission. Porewater dissolved organic matter (DOM) plays a key role in SOM decomposition; however, the mechanisms controlling SOM decomposition and its response to warming remain unclear. The temperature dependence of GHG production and microbial community dynamics were investigated in anoxic peat from a Sphagnum-dominated peatland. In this study, peat decomposition, which was quantified by GHG production and carbon substrate utilization is limited by terminal electron acceptors (TEA) and DOM, and these controls of microbially mediated SOM degradation are temperature-dependent. Elevated temperature led to a slight decrease in microbial diversity, and stimulated the growth of specific methanotrophic and syntrophic taxa. These results confirm that DOM is a major driver of decomposition in peatland soils contains inhibitory compounds, but the inhibitory effect is alleviated by warming.

Monolayer Superconductivity and Tunable Topological Electronic Structure at the Fe(Te,Se)/Bi2 Te3 Interface

The interface between 2D topological Dirac states and an s-wave superconductor is expected to support Majorana-bound states (MBS) that can be used for quantum computing applications. Realizing these novel states of matter and their applications requires control over superconductivity and spin-orbit coupling to achieve spin-momentum-locked topological interface states (TIS) which are simultaneously superconducting. While signatures of MBS have been observed in the magnetic vortex cores of bulk FeTe_0.55 Se_0.45 , inhomogeneity and disorder from doping make these signatures unclear and inconsistent between vortices. Here superconductivity is reported in monolayer (ML) FeTe_1-y Se_y (Fe(Te,Se)) grown on Bi₂ Te₃ by molecular beam epitaxy (MBE). Spin and angle-resolved photoemission spectroscopy (SARPES) directly resolve the interfacial spin and electronic structure of Fe(Te,Se)/Bi₂ Te₃ heterostructures. For y = 0.25, the Fe(Te,Se) electronic structure is found to overlap with the Bi₂ Te₃ TIS and the desired spin-momentum locking is not observed. In contrast, for y = 0.1, reduced inhomogeneity measured by scanning tunneling microscopy (STM) and a smaller Fe(Te,Se) Fermi surface with clear spin-momentum locking in the topological states are found. Hence, it is demonstrated that the Fe(Te,Se)/Bi₂ Te₃ system is a highly tunable platform for realizing MBS where reduced doping can improve characteristics important for Majorana interrogation and potential applications.

Na3 Zr2 Si2 PO12 Solid Electrolyte Membrane for High-Performance Seawater Battery

Seawater batteries (SWBs) have gained tremendous interest in the electrochemical energy storage research field because of their low cost, natural abundance, and potential use for long-duration energy storage. Advancing a SWB to demonstration projects is plagued by the poor electrochemical performance stemming from the poor interfaces of the solid electrolyte (SE), as well as the structural and chemical instabilities and sluggish ionic transport properties. In this study, the anode compartment of a surrogate SWB is constructed with a Na | SE | hard carbon configuration, and tailored dopants are introduced into the Nasicon-type Na₃ Zr₂ Si₂ PO₁₂ (NZSP) SE membrane. After doping with TiO₂ , a much more densely packed pellet with uniformly distributed porous structure is obtained. Changes in surface chemistry and local structure in the bulk are observed, which are believed to contribute to the improved ionic conductivity and higher critical current density of the TiO₂ -doped NZSP. Stable cycling performance with reversible capacities based on different Na storage mechanisms are also demonstrated.

Sodium Rich Vanadium Oxy-Fluorophosphate - Na3.2 Ni0.2 V1.8 (PO4 )2 F2 O - as Advanced Cathode for Sodium Ion Batteries

Conventional sodium-based layered oxide cathodes are extremely air sensitive and possess poor electrochemical performance along with safety concerns when operating at high voltage. The polyanion phosphate, Na₃ V₂ (PO₄ )₃ stands out as an excellent candidate due to its high nominal voltage, ambient air stability, and long cycle life. The caveat is that Na₃ V₂ (PO₄ )₃ can only exhibit reversible capacities in the range of 100 mAh g^-1 , 20% below its theoretical capacity. Here, the synthesis and characterizations are reported for the first time of the sodium-rich vanadium oxyfluorophosphate, Na_3.2 Ni_0.2 V_1.8 (PO₄ )₂ F₂ O, a tailored derivative compound of Na₃ V₂ (PO₄ )₃ , with extensive electrochemical and structural analyses. Na_3.2 Ni_0.2 V_1.8 (PO₄ )₂ F₂ O delivers an initial reversible capacity of 117 mAh g^-1 between 2.5 and 4.5 V under the 1C rate at room temperature, with 85% capacity retention after 900 cycles. The cycling stability is further improved when the material is cycled at 50 °C within 2.8-4.3 V for 100 cycles. When paired with a presodiated hard carbon, Na_3.2 Ni_0.2 V_1.8 (PO₄ )₂ F₂ O cycled with a capacity retention of 85% after 500 cycles. Cosubstitution of the transition metal and fluorine in Na_3.2 Ni_0.2 V_1.8 (PO₄ )₂ F₂ O as well as the sodium-rich structure are the major factors behind the improvement of specific capacity and cycling stability, which paves the way for this cathode in sodium-ion batteries.

Transition metal chalcogenides for next-generation energy storage

Transition-metal chalcogenide nanostructures provide a unique material platform to engineer next-generation energy storage devices such as lithium-ion, sodium-ion, and potassium-ion batteries and flexible supercapacitors. The transition-metal chalcogenide nanocrystals and thin films have enhanced electroactive sites for redox reactions and hierarchical flexibility of structure and electronic properties in the multinary compositions. They also consist of more earth-abundant elements. These properties make them attractive and more viable new electrode materials for energy storage devices compared to the traditional materials. This review highlights the recent advances in chalcogenide-based electrodes for batteries and flexible supercapacitors. The viability and structure-property relation of these materials are explored. The use of various chalcogenide nanocrystals supported on carbonaceous substrates, two-dimensional transition metal chalcogenides, and novel MXene-based chalcogenide heterostructures as electrode materials to improve the electrochemical performance of lithium-ion batteries is discussed. The sodium-ion and potassium-ion batteries offer a more viable alternative to lithium-ion technology as they consist of readily available source materials. Application of various transition metal chalcogenides such as MoS2, MoSe2, VS2, and SnSx, composite materials, and heterojunction bimetallic nanosheets composed of multi-metals as electrodes to enhance the long-term cycling stability, rate capability, and structural strength to counteract the large volume expansion during the ion intercalation/deintercalation processes is highlighted. The promising performances of layered chalcogenides and various chalcogenide nanowire compositions as electrodes for flexible supercapacitors are also discussed in detail. The review also details the progress made in new chalcogenide nanostructures and layered mesostructures for energy storage applications.

Across-model spread and shrinking in predicting peatland carbon dynamics under global change

Large across-model spread in simulating land carbon (C) dynamics has been ubiquitously demonstrated in model intercomparison projects (MIPs), and became a major impediment in advancing climate change prediction. Thus, it is imperative to identify underlying sources of the spread. Here, we used a novel matrix approach to analytically pin down the sources of across-model spread in transient peatland C dynamics in response to a factorial combination of two atmospheric CO₂ levels and five temperature levels. We developed a matrix-based MIP by converting the C cycle module of eight land models (i.e., TEM, CENTURY4, DALEC2, TECO, FBDC, CASA, CLM4.5 and ORCHIDEE) into eight matrix models. While the model average of ecosystem C storage was comparable to the measurement, the simulation differed largely among models, mainly due to inter-model difference in baseline C residence time. Models generally overestimated net ecosystem production (NEP), with a large spread that was mainly attributed to inter-model difference in environmental scalar. Based on the sources of spreads identified, we sequentially standardized model parameters to shrink simulated ecosystem C storage and NEP to almost none. Models generally captured the observed negative response of NEP to warming, but differed largely in the magnitude of response, due to differences in baseline C residence time and temperature sensitivity of decomposition. While there was a lack of response of NEP to elevated CO₂ (eCO₂ ) concentrations in the measurements, simulated NEP responded positively to eCO₂ concentrations in most models, due to the positive responses of simulated net primary production. Our study used one case study in Minnesota peatland to demonstrate that the sources of across-model spreads in simulating transient C dynamics can be precisely traced to model structures and parameters, regardless of their complexity, given the protocol that all the matrix models were driven by the same gross primary production and environmental variables.

Agave REVEILLE1 regulates the onset and release of seasonal dormancy in Populus

Deciduous woody plants like poplar (Populus spp.) have seasonal bud dormancy. It has been challenging to simultaneously delay the onset of bud dormancy in the fall and advance bud break in the spring, as bud dormancy, and bud break were thought to be controlled by different genetic factors. Here, we demonstrate that heterologous expression of the REVEILLE1 gene (named AaRVE1) from Agave (Agave americana) not only delays the onset of bud dormancy but also accelerates bud break in poplar in field trials. AaRVE1 heterologous expression increases poplar biomass yield by 166% in the greenhouse. Furthermore, we reveal that heterologous expression of AaRVE1 increases cytokinin contents, represses multiple dormancy-related genes, and up-regulates bud break-related genes, and that AaRVE1 functions as a transcriptional repressor and regulates the activity of the DORMANCY-ASSOCIATED PROTEIN 1 (DRM1) promoter. Our findings demonstrate that AaRVE1 appears to function as a regulator of bud dormancy and bud break, which has important implications for extending the growing season of deciduous trees in frost-free temperate and subtropical regions to increase crop yield.

How Particle Size Influences Oxidation of Ancient Organic Matter during Weathering of Black Shale

Weathering continuously converts rock to regolith at Earth's surface while regulating the atmospheric concentrations of CO2 and O2. Shale weathering is of particular interest because shale, the most abundant rock type exposed on continents, stores much of the ancient organic carbon (OCpetro) buried in rocks. Using geochemical and mineralogical analysis combined with neutron scattering and imaging, we investigated the weathering profile of OCpetro in saprock in a black shale (Marcellus Formation) in the Ridge and Valley Appalachians in Pennsylvania, U.S.A. Consistent with the low erosion rate of the landscape, we discovered that Marcellus is completely depleted in carbonate, plagioclase, and pyrite in saprock below the soil layer. On the contrary, only ∼60% of OCpetro was depleted in saprock. By comparing the pore structure of saprock to bedrock and samples combusted to remove organic matter (OM), we confirmed that the large particles of OM are preferentially depleted, leaving elongated pores of tens to hundreds of micrometers in length, while the smaller particulates of OM (ranging from ∼5 to ∼200 nm) are largely preserved during weathering. The retarded weathering of small OM particles is attributed to their close association with mineral surfaces in the shale matrix. The texture of OM in shale is underappreciated as an important factor that controls porosity generation and the weathering rate of OCpetro.

Electrostatically-blind quantitative piezoresponse force microscopy free of distributed-force artifacts

The presence of electrostatic forces and associated artifacts complicates the interpretation of piezoresponse force microscopy (PFM) and electrochemical strain microscopy (ESM). Eliminating these artifacts provides an opportunity for precisely mapping domain wall structures and dynamics, accurately quantifying local piezoelectric coupling coefficients, and reliably investigating hysteretic processes at the single nanometer scale to determine properties and mechanisms which underly important applications including computing, batteries and biology. Here we exploit the existence of an electrostatic blind spot (ESBS) along the length of the cantilever, due to the distributed nature of the electrostatic force, which can be universally used to separate unwanted long range electrostatic contributions from short range electromechanical responses of interest. The results of ESBS-PFM are compared to state-of-the-art interferometric displacement sensing PFM, showing excellent agreement above their respective noise floors. Ultimately, ESBS-PFM allows for absolute quantification of piezoelectric coupling coefficients independent of probe, lab or experimental conditions. As such, we expect the widespread adoption of EBSB-PFM to be a paradigm shift in the quantification of nanoscale electromechanics.

Design of Experiments, Chemometrics, and Raman Spectroscopy for the Quantification of Hydroxylammonium, Nitrate, and Nitric Acid

Selecting optimal combinations of preprocessing methods is a major holdup for chemometric analysis. The analyst decides which method(s) to apply to the data, frequently by highly subjective or inefficient means, such as user experience or trial and error. Here, we present a user-friendly method using optimal experimental designs for selecting preprocessing transformations. We applied this strategy to optimize partial least square regression (PLSR) analysis of Stokes Raman spectra to quantify hydroxylammonium (0-0.5 M), nitric acid (0-1 M), and total nitrate (0-1.5 M) concentrations. The best PLSR model chosen by a determinant (D)-optimal design comprising 26 samples (i.e., combinations of preprocessing methods) was compared with PLSR models built with no preprocessing, a user-selected preprocessing method (i.e., trial and error), and a user-defined design strategy (576 samples). The D-optimal selection strategy improved PLSR prediction performance by more than 50% compared with the raw data and reduced the number of combinations by more than 95.5%.

A cross-study analysis of drug response prediction in cancer cell lines

To enable personalized cancer treatment, machine learning models have been developed to predict drug response as a function of tumor and drug features. However, most algorithm development efforts have relied on cross-validation within a single study to assess model accuracy. While an essential first step, cross-validation within a biological data set typically provides an overly optimistic estimate of the prediction performance on independent test sets. To provide a more rigorous assessment of model generalizability between different studies, we use machine learning to analyze five publicly available cell line-based data sets: National Cancer Institute 60, ancer Therapeutics Response Portal (CTRP), Genomics of Drug Sensitivity in Cancer, Cancer Cell Line Encyclopedia and Genentech Cell Line Screening Initiative (gCSI). Based on observed experimental variability across studies, we explore estimates of prediction upper bounds. We report performance results of a variety of machine learning models, with a multitasking deep neural network achieving the best cross-study generalizability. By multiple measures, models trained on CTRP yield the most accurate predictions on the remaining testing data, and gCSI is the most predictable among the cell line data sets included in this study. With these experiments and further simulations on partial data, two lessons emerge: (1) differences in viability assays can limit model generalizability across studies and (2) drug diversity, more than tumor diversity, is crucial for raising model generalizability in preclinical screening.

Multilayer Lateral Heterostructures of Van Der Waals Crystals with Sharp, Carrier-Transparent Interfaces

Research on engineered materials that integrate different 2D crystals has largely focused on two prototypical heterostructures: Vertical van der Waals stacks and lateral heterostructures of covalently stitched monolayers. Extending lateral integration to few layer or even multilayer van der Waals crystals could enable architectures that combine the superior light absorption and photonic properties of thicker crystals with close proximity to interfaces and efficient carrier separation within the layers, potentially benefiting applications such as photovoltaics. Here, the realization of multilayer heterstructures of the van der Waals semiconductors SnS and GeS with lateral interfaces spanning up to several hundred individual layers is demonstrated. Structural and chemical imaging identifies {110} interfaces that are perpendicular to the (001) layer plane and are laterally localized and sharp on a 10 nm scale across the entire thickness. Cathodoluminescence spectroscopy provides evidence for a facile transfer of electron-hole pairs across the lateral interfaces, indicating covalent stitching with high electronic quality and a low density of recombination centers.

ChAdOx1 interacts with CAR and PF4 with implications for thrombosis with thrombocytopenia syndrome

Vaccines derived from chimpanzee adenovirus Y25 (ChAdOx1), human adenovirus type 26 (HAdV-D26), and human adenovirus type 5 (HAdV-C5) are critical in combatting the severe acute respiratory coronavirus 2 (SARS-CoV-2) pandemic. As part of the largest vaccination campaign in history, ultrarare side effects not seen in phase 3 trials, including thrombosis with thrombocytopenia syndrome (TTS), a rare condition resembling heparin-induced thrombocytopenia (HIT), have been observed. This study demonstrates that all three adenoviruses deployed as vaccination vectors versus SARS-CoV-2 bind to platelet factor 4 (PF4), a protein implicated in the pathogenesis of HIT. We have determined the structure of the ChAdOx1 viral vector and used it in state-of-the-art computational simulations to demonstrate an electrostatic interaction mechanism with PF4, which was confirmed experimentally by surface plasmon resonance. These data confirm that PF4 is capable of forming stable complexes with clinically relevant adenoviruses, an important step in unraveling the mechanisms underlying TTS.

Single-Ion Conducting Polymer Nanoparticles as Functional Fillers for Solid Electrolytes in Lithium Metal Batteries

Composite solid electrolytes including inorganic nanoparticles or nanofibers which improve the performance of polymer electrolytes due to their superior mechanical, ionic conductivity, or lithium transference number are actively being researched for applications in lithium metal batteries. However, inorganic nanoparticles present limitations such as tedious surface functionalization and agglomeration issues and poor homogeneity at high concentrations in polymer matrixes. In this work, we report on polymer nanoparticles with a lithium sulfonamide surface functionality (LiPNP) for application as electrolytes in lithium metal batteries. The particles are prepared by semibatch emulsion polymerization, an easily up-scalable technique. LiPNPs are used to prepare two different families of particle-reinforced solid electrolytes. When mixed with poly(ethylene oxide) and lithium bis(trifluoromethane)sulfonimide (LiTFSI/PEO), the particles invoke a significant stiffening effect (E' > 10⁶ Pa vs 10⁵ Pa at 80 °C) while the membranes retain high ionic conductivity (σ = 6.6 × 10^-4 S cm^-1). Preliminary testing in LiFePO₄ lithium metal cells showed promising performance of the PEO nanocomposite electrolytes. By mixing the particles with propylene carbonate without any additional salt, we obtain true single-ion conducting gel electrolytes, as the lithium sulfonamide surface functionalities are the only sources of lithium ions in the system. The gel electrolytes are mechanically robust (up to G' = 10⁶ Pa) and show ionic conductivity up to 10^-4 S cm^-1. Finally, the PC nanocomposite electrolytes were tested in symmetrical lithium cells. Our findings suggest that all-polymer nanoparticles could represent a new building block material for solid-state lithium metal battery applications.

Structural Evolution and Transition Dynamics in Lithium Ion Battery under Fast Charging: An Operando Neutron Diffraction Investigation

Fast charging (<15 min) of lithium-ion batteries (LIBs) for electrical vehicles (EVs) is widely seen as the key factor that will greatly stimulate the EV markets, and its realization is mainly hindered by the sluggish diffusion of Li+ . To have a mechanistic understanding of Li+ diffusion within LIBs, in this study, structural evolutions of electrodes for a Ni-rich LiNi0.6 Mn0.2 Co0.2 O2 (NMC622) || graphite cylindrical cell with high areal loading (2.78 mAh cm-2 ) are developed for operando neutron powder diffraction study at different charging rates. Via sequential Rietveld refinements, changes in structures of NMC622 and Lix C6 are obtained during moderate and fast charging (from 0.27 C to 4.4 C). NMC622 exhibits the same structural evolution regardless of C-rates. For phase transitions of Lix C6 , the stage I (LiC6 ) phase emerges earlier during the stepwise intercalation at a lower state of charge when charging rate is increased. It is also found that the stage II (LiC12 ) → stage I (LiC6 ) transition is the rate-limiting step during fast charging. The LiC12 → LiC6 transition mechanism is further analyzed using the Johnson-Mehl-Avrami-Kolmogorov model. It is concluded as a diffusion-controlled, 1D phase transition with decreasing nucleation kinetics under increasing chargingrates.

Bioprospecting Trichoderma: A Systematic Roadmap to Screen Genomes and Natural Products for Biocontrol Applications

Natural products derived from microbes are crucial innovations that would help in reaching sustainability development goals worldwide while achieving bioeconomic growth. Trichoderma species are well-studied model fungal organisms used for their biocontrol properties with great potential to alleviate the use of agrochemicals in agriculture. However, identifying and characterizing effective natural products in novel species or strains as biological control products remains a meticulous process with many known challenges to be navigated. Integration of recent advancements in various "omics" technologies, next generation biodesign, machine learning, and artificial intelligence approaches could greatly advance bioprospecting goals. Herein, we propose a roadmap for assessing the potential impact of already known or newly discovered Trichoderma species for biocontrol applications. By screening publicly available Trichoderma genome sequences, we first highlight the prevalence of putative biosynthetic gene clusters and antimicrobial peptides among genomes as an initial step toward predicting which organisms could increase the diversity of natural products. Next, we discuss high-throughput methods for screening organisms to discover and characterize natural products and how these findings impact both fundamental and applied research fields.

Country-level land carbon sink and its causing components by the middle of the twenty-first century

BACKGROUND

Countries have long been making efforts by reducing greenhouse-gas emissions to mitigate climate change. In the agreements of the United Nations Framework Convention on Climate Change, involved countries have committed to reduction targets. However, carbon (C) sink and its involving processes by natural ecosystems remain difficult to quantify.

METHODS

Using a transient traceability framework, we estimated country-level land C sink and its causing components by 2050 simulated by 12 Earth System Models involved in the Coupled Model Intercomparison Project Phase 5 (CMIP5) under RCP8.5.

RESULTS

The top 20 countries with highest C sink have the potential to sequester 62 Pg C in total, among which, Russia, Canada, USA, China, and Brazil sequester the most. This C sink consists of four components: production-driven change, turnover-driven change, change in instantaneous C storage potential, and interaction between production-driven change and turnover-driven change. The four components account for 49.5%, 28.1%, 14.5%, and 7.9% of the land C sink, respectively.

CONCLUSION

The model-based estimates highlight that land C sink potentially offsets a substantial proportion of greenhouse-gas emissions, especially for countries where net primary production (NPP) likely increases substantially and inherent residence time elongates.

A Consistent BGK Model with Velocity-Dependent Collision Frequency for Gas Mixtures

We derive a multi-species BGK model with velocity-dependent collision frequency for a non-reactive, multi-component gas mixture. The model is derived by minimizing a weighted entropy under the constraint that the number of particles of each species, total momentum, and total energy are conserved. We prove that this minimization problem admits a unique solution for very general collision frequencies. Moreover, we prove that the model satisfies an H-Theorem and characterize the form of equilibrium.

Thermal decarboxylation for the generation of hierarchical porosity in isostructural metal-organic frameworks containing open metal sites

The effect of metal-cluster redox identity on the thermal decarboxylation of a series of isostructural metal-organic frameworks (MOFs) with tetracarboxylate-based ligands and trinuclear μ3-oxo clusters was investigated. The PCN-250 series of MOFs can consist of various metal combinations (Fe3, Fe/Ni, Fe/Mn, Fe/Co, Fe/Zn, Al3, In3, and Sc3). The Fe-based system can undergo a thermally induced reductive decarboxylation, producing a mixed valence cluster with decarboxylated ligand fragments subsequently eliminated to form uniform mesopores. We have extended the analysis to alternative monometallic and bimetallic PCN-250 systems to observe the cluster's effect on the decarboxylation process. Our results suggest that the propensity to undergo decarboxylation is directly related to the cluster redox accessibility, with poorly reducible metals, such as Al, In, and Sc, unable to thermally reduce at the readily accessible temperatures of the Fe-containing system. In contrast, the mixed-metal variants are all reducible. We report improvements in gas adsorption behavior, significantly the uniform increase in the heat of adsorption going from the microporous to hierarchically induced decarboxylated samples. This, along with Fe oxidation state changes from 57Fe Mössbauer spectroscopy, suggests that reduction occurs at the clusters and is essential for mesopore formation. These results provide insight into the thermal behavior of redox-active MOFs and suggest a potential future avenue for generating mesoporosity using controlled cluster redox chemistry.

Mesoscopic Modeling and Rapid Simulation of Incremental Changes in Epidemic Scenarios on GPUs: Fast What-If Analyses of Localized and Dynamic Effects

In simulation-based studies and analyses of epidemics, a major challenge lies in resolving the conflict between fidelity of models and the speed of their simulation. Another related challenge arises in dealing with the large number of what–if scenarios that need to be explored. Here, we describe new computational methods that together provide an approach to dealing with both challenges. A mesoscopic modeling approach is described that strikes a middle ground between macroscopic models based on coupled differential equations and microscopic models built on fine-grained behaviors at the individual entity level. The mesoscopic approach offers the ability to incorporate complex compositions of multiple layers of dynamics even while retaining the potential for aggregate behaviors at varying levels. It also is an excellent match to the accelerator-based architectures of modern computing platforms in which graphical processing units (GPUs) can be exploited for fast simulation via the parallel execution mode of single instruction multiple thread (SIMT). The challenge of simulating a large number of scenarios is addressed via a method of sharing model state and computation across a tree of what–if scenarios that are localized, incremental changes to a large base simulation. A combination of the mesoscopic modeling approach and the incremental what–if scenario tree evaluation has been implemented in the software on modern GPUs. Synthetic simulation scenarios are presented to demonstrate the computational characteristics of our approach. Results from the experiments with large population data, including USA, UK, and India, illustrate the modeling methodology and computational performance on thousands of synthetically generated what–if scenarios. Execution of our implementation scaled to 8192 GPUs of supercomputing platforms demonstrates the ability to rapidly evaluate what–if scenarios several orders of magnitude faster than the conventional methods.

Mechanism of Electron-Beam Manipulation of Single-Dopant Atoms in Silicon

The precise positioning of dopant atoms within bulk crystal lattices could enable novel applications in areas including solid-state sensing and quantum computation. Established scanning probe techniques are capable tools for the manipulation of surface atoms, but at a disadvantage due to their need to bring a physical tip into contact with the sample. This has prompted interest in electron-beam techniques, followed by the first proof-of-principle experiment of bismuth dopant manipulation in crystalline silicon. Here, we use first-principles modeling to discover a novel indirect exchange mechanism that allows electron impacts to non-destructively move dopants with atomic precision within the silicon lattice. However, this mechanism only works for the two heaviest group V donors with split-vacancy configurations, Bi and Sb. We verify our model by directly imaging these configurations for Bi and by demonstrating that the promising nuclear spin qubit Sb can be manipulated using a focused electron beam.

Molecular origin of viscoelasticity in mineralized collagen fibrils

Bone is mineralized tissue constituting the skeletal system, supporting and protecting the body's organs and tissues. In addition to such fundamental mechanical functions, bone also plays a remarkable role in sound conduction. From a mechanical standpoint, bone is a composite material consisting of minerals and collagen arranged in multiple hierarchical structures, with a complex anisotropic viscoelastic response, capable of transmitting and dissipating energy. At the molecular level, mineralized collagen fibrils are the basic building blocks of bone tissue, and hence, understanding bone properties down to fundamental tissue structures enables better identification of the mechanisms of structural failures and damage. While efforts have focused on the study of micro- and macro-scale viscoelasticity related to bone damage and healing based on creep, mineralized collagen has not been explored at the molecular level. We report a study that aims at systematically exploring the viscoelasticity of collagenous fibrils with different mineralization levels. We investigate the dynamic mechanical response upon cyclic and impulsive loads to observe the viscoelastic phenomena from either shear or extensional strains via molecular dynamics. We perform a sensitivity analysis with several key benchmarks: intrafibrillar mineralization percentage, hydration state, and external load amplitude. Our results show an increase of the dynamic moduli with an increase of the mineral percentage, pronounced at low strains. When intrafibrillar water is present, the material softens the elastic component, but considerably increases its viscosity, especially at high frequencies. This behavior is confirmed from the material response upon impulsive loads, in which water drastically reduces the relaxation times throughout the input velocity range by one order of magnitude, with respect to the dehydrated counterparts. We find that, upon transient loads, water has a major impact on the mechanics of mineralized fibrillar collagen, being able to improve the capability of the tissue to passively and effectively dissipate energy, especially after fast and high-amplitude external loads. Our study provides knowledge of bone mechanics in relation to pathologies deriving from dehydration or traumas. Moreover, these findings show the potential for being used in designing new bioinspired materials not limited to tissue engineering applications, in which passive mechanisms for dissipating energy can prevent structural failures.

Repulsive expansion dynamics in colony growth and gene expression

Spatial expansion of a population of cells can arise from growth of microorganisms, plant cells, and mammalian cells. It underlies normal or dysfunctional tissue development, and it can be exploited as the foundation for programming spatial patterns. This expansion is often driven by continuous growth and division of cells within a colony, which in turn pushes the peripheral cells outward. This process generates a repulsion velocity field at each location within the colony. Here we show that this process can be approximated as coarse-grained repulsive-expansion kinetics. This framework enables accurate and efficient simulation of growth and gene expression dynamics in radially symmetric colonies with homogenous z-directional distribution. It is robust even if cells are not spherical and vary in size. The simplicity of the resulting mathematical framework also greatly facilitates generation of mechanistic insights.

Spatiotemporal dynamics are ubiquitous in biology. To understand these phenomena in nature or to program them using synthetic gene circuits, it is critical to resort to mathematical modeling to deduce mechanistic insights or to explore plausible outcomes. Historically, modeling of spatiotemporal dynamics depends on the use of agent-based models or their continuum counterparts consisting of partial differential equations. Here, we show that a class of colony expansion can be treated as being driven by the steric force generated by growing and diving cells. This approximation leads to a drastically simplified framework consisting of only ordinary differential equations. This framework greatly improves the computational efficiency and facilitates development of mechanistic insights into the dynamics of colony growth and pattern formation.

SARS-CoV-2 suppresses anticoagulant and fibrinolytic gene expression in the lung

Extensive fibrin deposition in the lungs and altered levels of circulating blood coagulation proteins in COVID-19 patients imply local derangement of pathways that limit fibrin formation and/or promote its clearance. We examined transcriptional profiles of bronchoalveolar lavage fluid (BALF) samples to identify molecular mechanisms underlying these coagulopathies. mRNA levels for regulators of the kallikrein-kinin (C1-inhibitor), coagulation (thrombomodulin, endothelial protein C receptor), and fibrinolytic (urokinase and urokinase receptor) pathways were significantly reduced in COVID-19 patients. While transcripts for several coagulation proteins were increased, those encoding tissue factor, the protein that initiates coagulation and whose expression is frequently increased in inflammatory disorders, were not increased in BALF from COVID-19 patients. Our analysis implicates enhanced propagation of coagulation and decreased fibrinolysis as drivers of the coagulopathy in the lungs of COVID-19 patients.

Beyond ecosystem modeling: A roadmap to community cyberinfrastructure for ecological data-model integration

In an era of rapid global change, our ability to understand and predict Earth's natural systems is lagging behind our ability to monitor and measure changes in the biosphere. Bottlenecks to informing models with observations have reduced our capacity to fully exploit the growing volume and variety of available data. Here, we take a critical look at the information infrastructure that connects ecosystem modeling and measurement efforts, and propose a roadmap to community cyberinfrastructure development that can reduce the divisions between empirical research and modeling and accelerate the pace of discovery. A new era of data-model integration requires investment in accessible, scalable, and transparent tools that integrate the expertise of the whole community, including both modelers and empiricists. This roadmap focuses on five key opportunities for community tools: the underlying foundations of community cyberinfrastructure; data ingest; calibration of models to data; model-data benchmarking; and data assimilation and ecological forecasting. This community-driven approach is a key to meeting the pressing needs of science and society in the 21st century.

Nitrogen cycling microbiomes are structured by plant mycorrhizal associations with consequences for nitrogen oxide fluxes in forests

Volatile nitrogen oxides (N2 O, NO, NO2 , HONO, …) can negatively impact climate, air quality, and human health. Using soils collected from temperate forests across the eastern United States, we show microbial communities involved in nitrogen (N) cycling are structured, in large part, by the composition of overstory trees, leading to predictable N-cycling syndromes, with consequences for emissions of volatile nitrogen oxides to air. Trees associating with arbuscular mycorrhizal (AM) fungi promote soil microbial communities with higher N-cycle potential and activity, relative to microbial communities in soils dominated by trees associating with ectomycorrhizal (ECM) fungi. Metagenomic analysis and gene expression studies reveal a 5 and 3.5 times greater estimated N-cycle gene and transcript copy numbers, respectively, in AM relative to ECM soil. Furthermore, we observe a 60% linear decrease in volatile reactive nitrogen gas flux (NOy  ≡ NO, NO2 , HONO) as ECM tree abundance increases. Compared to oxic conditions, gas flux potential of N2 O and NO increase significantly under anoxic conditions for AM soil (30- and 120-fold increase), but not ECM soil-likely owing to small concentrations of available substrate ( NO 3 - ) in ECM soil. Linear mixed effects modeling shows that ECM tree abundance, microbial process rates, and geographic location are primarily responsible for variation in peak potential NOy flux. Given that nearly all tree species associate with either AM or ECM fungi, our results indicate that the consequences of tree species shifts associated with global change may have predictable consequences for soil N cycling.

Density-functional tight-binding for phosphine-stabilized nanoscale gold clusters

We report a parameterization of the second-order density-functional tight-binding (DFTB2) method for the quantum chemical simulation of phosphine-ligated nanoscale gold clusters, metalloids, and gold surfaces. Our parameterization extends the previously released DFTB2 "auorg" parameter set by connecting it to the electronic parameter of phosphorus in the "mio" parameter set. Although this connection could technically simply be accomplished by creating only the required additional Au-P repulsive potential, we found that the Au 6p and P 3d virtual atomic orbital energy levels exert a strong influence on the overall performance of the combined parameter set. Our optimized parameters are validated against density functional theory (DFT) geometries, ligand binding and cluster isomerization energies, ligand dissociation potential energy curves, and molecular orbital energies for relevant phosphine-ligated Au n clusters (n = 2-70), as well as selected experimental X-ray structures from the Cambridge Structural Database. In addition, we validate DFTB simulated far-IR spectra for several phosphine- and thiolate-ligated gold clusters against experimental and DFT spectra. The transferability of the parameter set is evaluated using DFT and DFTB potential energy surfaces resulting from the chemisorption of a PH3 molecule on the gold (111) surface. To demonstrate the potential of the DFTB method for quantum chemical simulations of metalloid gold clusters that are challenging for traditional DFT calculations, we report the predicted molecular geometry, electronic structure, ligand binding energy, and IR spectrum of Au108S24(PPh3)16.

A mechanistic model and therapeutic interventions for COVID-19 involving a RAS-mediated bradykinin storm

Neither the disease mechanism nor treatments for COVID-19 are currently known. Here, we present a novel molecular mechanism for COVID-19 that provides therapeutic intervention points that can be addressed with existing FDA-approved pharmaceuticals. The entry point for the virus is ACE2, which is a component of the counteracting hypotensive axis of RAS. Bradykinin is a potent part of the vasopressor system that induces hypotension and vasodilation and is degraded by ACE and enhanced by the angiotensin1-9 produced by ACE2. Here, we perform a new analysis on gene expression data from cells in bronchoalveolar lavage fluid (BALF) from COVID-19 patients that were used to sequence the virus. Comparison with BALF from controls identifies a critical imbalance in RAS represented by decreased expression of ACE in combination with increases in ACE2, renin, angiotensin, key RAS receptors, kinogen and many kallikrein enzymes that activate it, and both bradykinin receptors. This very atypical pattern of the RAS is predicted to elevate bradykinin levels in multiple tissues and systems that will likely cause increases in vascular dilation, vascular permeability and hypotension. These bradykinin-driven outcomes explain many of the symptoms being observed in COVID-19.

Effect of lattice mismatch and shell thickness on strain in core@shell nanocrystals

Bimetallic nanocrystals with a core@shell architecture are versatile, multifunctional particles. The lattice mismatch between core and shell regions induces strain, affecting the electronic properties of the shell metal, which is important for applications in catalysis. Here, we analyze this strain in core@shell nanocubes as a function of lattice mismatch and shell thickness. Coupling geometric phase analysis from atomic resolution scanning transmission electron microscopy images with molecular dynamics simulations reveals lattice relaxation in the shell within only a few monolayers and an overexpansion in the axial direction. Interestingly, many works report core@shell metal nanocatalysts with optimum performance at greater shell thicknesses. Our findings suggest that not strain alone but secondary factors, such as structural defects or structural changes in operando, may account for observed enhancements in some strain-engineered nanocatalysts; e.g., Rh@Pt nanocubes for formic acid electrooxidation.

Light-responsive expression atlas reveals the effects of light quality and intensity in Kalanchoë fedtschenkoi, a plant with crassulacean acid metabolism

BACKGROUND

Crassulacean acid metabolism (CAM), a specialized mode of photosynthesis, enables plant adaptation to water-limited environments and improves photosynthetic efficiency via an inorganic carbon-concentrating mechanism. Kalanchoë fedtschenkoi is an obligate CAM model featuring a relatively small genome and easy stable transformation. However, the molecular responses to light quality and intensity in CAM plants remain understudied.

RESULTS

Here we present a genome-wide expression atlas of K. fedtschenkoi plants grown under 12 h/12 h photoperiod with different light quality (blue, red, far-red, white light) and intensity (0, 150, 440, and 1,000 μmol m-2 s-1) based on RNA sequencing performed for mature leaf samples collected at dawn (2 h before the light period) and dusk (2 h before the dark period). An eFP web browser was created for easy access of the gene expression data. Based on the expression atlas, we constructed a light-responsive co-expression network to reveal the potential regulatory relationships in K. fedtschenkoi. Measurements of leaf titratable acidity, soluble sugar, and starch turnover provided metabolic indicators of the magnitude of CAM under the different light treatments and were used to provide biological context for the expression dataset. Furthermore, CAM-related subnetworks were highlighted to showcase genes relevant to CAM pathway, circadian clock, and stomatal movement. In comparison with white light, monochrome blue/red/far-red light treatments repressed the expression of several CAM-related genes at dusk, along with a major reduction in acid accumulation. Increasing light intensity from an intermediate level (440 μmol m-2 s-1) of white light to a high light treatment (1,000 μmol m-2 s-1) increased expression of several genes involved in dark CO2 fixation and malate transport at dawn, along with an increase in organic acid accumulation.

CONCLUSIONS

This study provides a useful genomics resource for investigating the molecular mechanism underlying the light regulation of physiology and metabolism in CAM plants. Our results support the hypothesis that both light intensity and light quality can modulate the CAM pathway through regulation of CAM-related genes in K. fedtschenkoi.

Assessment of peritoneal microbial features and tumor marker levels as potential diagnostic tools for ovarian cancer

Epithelial ovarian cancer (OC) is the most deadly cancer of the female reproductive system. To date, there is no effective screening method for early detection of OC and current diagnostic armamentarium may include sonographic grading of the tumor and analyzing serum levels of tumor markers, Cancer Antigen 125 (CA-125) and Human epididymis protein 4 (HE4). Microorganisms (bacterial, archaeal, and fungal cells) residing in mucosal tissues including the gastrointestinal and urogenital tracts can be altered by different disease states, and these shifts in microbial dynamics may help to diagnose disease states. We hypothesized that the peritoneal microbial environment was altered in patients with OC and that inclusion of selected peritoneal microbial features with current clinical features into prediction analyses will improve detection accuracy of patients with OC. Blood and peritoneal fluid were collected from consented patients that had sonography confirmed adnexal masses and were being seen at SIU School of Medicine Simmons Cancer Institute. Blood was processed and serum HE4 and CA-125 were measured. Peritoneal fluid was collected at the time of surgery and processed for Next Generation Sequencing (NGS) using 16S V4 exon bacterial primers and bioinformatics analyses. We found that patients with OC had a unique peritoneal microbial profile compared to patients with a benign mass. Using ensemble modeling and machine learning pathways, we identified 18 microbial features that were highly specific to OC pathology. Prediction analyses confirmed that inclusion of microbial features with serum tumor marker levels and control features (patient age and BMI) improved diagnostic accuracy compared to currently used models. We conclude that OC pathogenesis alters the peritoneal microbial environment and that these unique microbial features are important for accurate diagnosis of OC. Our study warrants further analyses of the importance of microbial features in regards to oncological diagnostics and possible prognostic and interventional medicine.

Noncontact tip-enhanced Raman spectroscopy for nanomaterials and biomedical applications

Tip-enhanced Raman spectroscopy (TERS) has been established as one the most efficient analytical techniques for probing vibrational states with nanoscale resolution. While TERS may be a source of unique information about chemical structure and interactions, it has a limited use for materials with rough or sticky surfaces. Development of the TERS approach utilizing a non-contact scanning probe microscopy mode can significantly extend the number of applications. Here we demonstrate a proof of the concept and feasibility of a non-contact TERS approach and test it on various materials. Our experiments show that non-contact TERS can provide 10 nm spatial resolution and a Raman signal enhancement factor of 10⁵, making it very promising for chemical imaging of materials with high aspect ratio surface patterns and biomaterials.