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Bacterially secreted proteins are necessary for the proper functioning of bacterial cells and communities. Secreted proteins provide bacterial cells with the ability to harvest resources from the exterior, import these resources into the cell, and signal to other bacteria.
Superconducting radio-frequency (SRF) cavities are fundamental building block of modern particle accelerators. They operate at liquid helium temperatures 2-4 K to achieve very high quality factors 1e10-1e11. Trapping of magnetic flux within the superconductor is a significant contribution to the residual RF losses which limit the achievable quality factor. Suitable diagnostic tools are in high demand to understand the mechanisms of flux trapping in technical superconductors and the fundamental components of such diagnostic tool are magnetic field sensors. We have studied the performance of commercially available Hall probes, anisotropic magnetoresistive sensors and flux-gate magnetometers with respect to their sensitivity and capability to detect localized, low magnetic flux amplitudes, of the order of few tens of magnetic flux quantum at liquid helium temperature. Although Hall probes have the lowest magnetic field sensitivity (~96$ nV$/microT at 2 K), their physical dimensions are such that they have the ability to detect the lowest number of trapped vortices among the three type of sensors. Hall probes and anisotropic magnetoresistive sensors have been selected to be used in a setup to map regions of trapped flux on the surface of a single-cell SRF cavity.
Beneficial, facultative endophytes help plants thrive in challenging environments by altering their host's metabolism, but how these cellular scale metabolic changes propagate to the systems biology scale is unknown. In this work, we employed a high-resolution chemical imaging approach to map metabolic changes at the Populus trichocarpa root-zone and cell-type levels combined with machine learning (ML) models to identify root metabolites and exudates that have predictive power over treatment class. We found that a nine-strain consortium of beneficial endophytes differentially altered the metabolome of droughted root tissues in a manner specific to cell type and root zone, with endophyte abundance showing a clear correlation to individual metabolites. Our study demonstrates that integrating spatial metabolomics with ML can reveal localized metabolic patterns linked to root–microbe interactions and generate novel hypotheses about underlying biological mechanisms.
The external quantum efficiency (EQE) or associated spectral response is widely used to evaluate the performance of photovoltaics, light emitting diodes, photodetectors, photodiodes, semiconductor lasers, laser-induced refrigeration of solids etc. For photovoltaic (PV) devices, The EQE is used to determine the spectral mismatch correction that is used to convert a performance measurement from a non-ideal simulator spectrum to a standard spectrum in PV device calibrations. Moreover, EQE can provide important insight into the physics of a PV device. For instance, the EQE shape can be used to infer mechanisms limiting the performance of the device. However, EQE measurements of full-size PV modules remain a challenge in the PV community due to rare availability of reliable module QE measurement tools worldwide and the size and complexity of module architecture that comprises several cells connected in strings (series or/and parallel). Here, we use a customized nondestructive tool made of high-power light emitting diodes to perform high-throughput EQE measurements on PV modules. Circuit simulations show that the measurement system can safely be used to measure both crystalline silicon and thin film-based PV modules with series connected cells without the risk of damage through reverse bias. In addition, EQE mapping combined with electroluminescence show a strong correlation and provide a way to determine both spatial non-uniformity of the spectral response and defects/degradation effects across the module.
Human astrovirus (HAstV) is a known cause of viral gastroenteritis in children worldwide, but HAstV can cause also severe and systemic infections in immunocompromised patients. There are three clades of HAstV: classical, MLB, and VA/HMO. While all three clades are found in gastrointestinal samples, HAstV-VA/HMO is the main clade associated with meningitis and encephalitis in immunocompromised patients. To understand how the HAstV-VA/HMO can infect the central nervous system, we investigated its sequence-divergent capsid spike, which functions in cell attachment and may influence viral tropism. Here we report the high-resolution crystal structures of the HAstV-VA1 capsid spike from strains isolated from patients with gastrointestinal and neuronal disease. The HAstV-VA1 spike forms a dimer and shares a core beta-barrel structure with other astrovirus capsid spikes but is otherwise strikingly different, suggesting that HAstV-VA1 may utilize a different cell receptor, and an infection competition assay supports this hypothesis. Furthermore, by mapping the capsid protease cleavage site onto the structure, the maturation and assembly of the HAstV-VA1 capsid is revealed. Finally, comparison of gastrointestinal and neuronal HAstV-VA1 sequences, structures, and antigenicity suggests that neuronal HAstV-VA1 strains may have acquired immune escape mutations. Overall, our studies on the HAstV-VA1 capsid spike lay a foundation to further investigate the biology of HAstV-VA/HMO and to develop vaccines and therapeutics targeting it.
Epithelial ovarian cancer (EOC) is the most common form of ovarian cancer. The poor prognosis generally associated with this disease has led to the search for improved therapies such as ferroptosis-inducing agents. Ferroptosis is a form of regulated cell death that is dependent on iron and is characterized by lipid peroxidation. Precise mapping of lipids and iron within tumors exposed to ferroptosis-inducing agents may provide insight into processes of ferroptosis in vivo and ultimately assist in the optimal deployment of ferroptosis inducers in cancer therapy. In this work, we present a method for combining matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) with secondary ion mass spectrometry (SIMS) to analyze changes in spatial lipidomics and metal composition, respectively, in ovarian tumors following exposure to a ferroptosis inducer. Tumors were obtained by injecting human ovarian cancer tumor-initiating cells into mice, followed by treatment with the ferroptosis inducer erastin. SIMS imaging detected iron accumulation in the tumor tissue, and sequential MALDI-MS imaging of the same tissue section displayed two chemically distinct regions of lipids. Additionally, one region was associated with the iron-rich area detected with SIMS, and the other region encompassed the remainder of the tissue section. Bulk lipidomics confirmed the lipid assignments putatively assigned from the MALDI-MS data. Overall, we demonstrate the ability of multimodal MSI to identify the spatial locations of iron and lipids in the same tissue section and associate these regions with clinical pathology.
Ni-rich NMC is an attractive Li-ion battery cathode due to its combination of energy density, thermal stability, and reversibility. While higher delivered energy density can be achieved with a more positive charge voltage limit, this approach compromises sustained reversibility. Improved understanding of the local and bulk structural transformations as a function of charge voltage, and their associated impacts on capacity fade are critically needed. Through simultaneous operando synchrotron X-ray diffraction (XRD) and X-ray absorption spectroscopy (XAS) of cells cycled at 3–4.3 or 3–4.7 V, this study presents an in-depth investigation into the effects of voltage window on local coordination, bulk structure, and oxidation state. These measurements are complemented by ex situ X-ray fluorescence (XRF) mapping and scanning electrochemical microscopy mapping (SECM) of the negative electrode, X-ray photoelectron spectroscopy (XPS) of the positive electrode, and cell level electrochemical impedance spectroscopy (EIS). Initially, cycling between 3 and 4.7 V leads to greater delivered capacity due to greater lithium extraction, accompanied by increased structural distortion, moderately higher Ni oxidation, and substantially higher Co oxidation. Continued cycling at this high voltage results in suppressed Ni and Co redox, greater structural distortion, increased levels of transition metal dissolution, higher cell impedance, and 3× greater capacity fade.
Mechanical abuse poses a critical safety risk to Li-ion batteries by inducing internal short circuits that initiate thermal runaway. Remarkably, voltage recovery frequently emerges during thermal runaway initiation, a phenomenon that conventional theories fail to explain. Here, our study develops a new multiphysics mechanism to explain voltage recovery, termed gas-driven short disconnection, whereby internal gas pressure mechanically disengages short-circuit contacts and causes the cell voltage to rebound. This mechanism incorporates gas generation and its structural impact on the short circuit. Real-time optical and thermal imaging and X-ray computed tomography reveal fluid-structure interaction between internal gas flow and adjacent shorting contacts. We establish a mechanistic framework linking gas-driven short disconnection to cell-level voltage and temperature responses, elucidating the extension–truncation pattern of voltage recovery. Furthermore, thermal regime maps show that a voltage recovery duration exceeding 5 s correlates with limited temperature rise below 150 °C, indicating that sustained short-circuit disconnection suppresses Joule heating. Additionally, a dimensionless criterion is deduced from scaling analysis for physical plausibility of gas-driven short disconnection in mechanically abused cells. This finding inspires smart venting control, which regulates gas release to maintain the internal pressure while dissipating gas enthalpy, thereby providing a device-level strategy for thermal runaway mitigation.
Voltage-induced halide segregation greatly limits the optoelectronic applications of mixed-halide perovskite devices, but a mechanistic explanation behind this phenomenon remains unclear. In this work, we use electron microscopy and elemental mapping to directly measure the halide redistribution in mixed-halide perovskite solar cells with quasi-ion-impermeable contact layers under different bias polarities to find iodide and bromide accumulation at the cathode and anode, respectively. This is consistent with a mechanism based on preferential iodide oxidation at the anode, leading to unbalanced I$^{+}_{i}$, I$^{-}_{X}$, and Br$^{-}_{X}$ fluxes. Importantly, switching the anode from "inert" Au to "active" Ag prevents segregation because Ag oxidation precludes the oxidation of lattice iodide, which suggests employing redox-active additives as a general strategy to suppress halide segregation. Finally, these results show that halide perovskite devices operate as solid-state electrochemical cells when threshold voltages are exceeded, providing fresh insight to understand the impacts of voltage bias on halide perovskite devices.
Human immunodeficiency virus (HIV) persistence during antiretroviral therapy (ART) is associated with heightened plasma interleukin-10 (IL-10) levels and PD-1 expression. We hypothesized that IL-10 and PD-1 blockade would lead to control of viral rebound following analytical treatment interruption (ATI). Twenty-eight ART-treated, simian immunodeficiency virus (SIV)mac 239 -infected rhesus macaques (RMs) were treated with anti-IL-10, anti-IL-10 plus anti-PD-1 (combo) or vehicle. ART was interrupted 12 weeks after introduction of immunotherapy. Durable control of viral rebound was observed in nine out of ten combo-treated RMs for >24 weeks post-ATI. Induction of inflammatory cytokines, proliferation of effector CD8 + T cells in lymph nodes and reduced expression of BCL-2 in CD4 + T cells pre-ATI predicted control of viral rebound. Twenty-four weeks post-ATI, lower viral load was associated with higher frequencies of memory T cells expressing TCF-1 and of SIV-specific CD4 + and CD8 + T cells in blood and lymph nodes of combo-treated RMs. These results map a path to achieve long-lasting control of HIV and/or SIV following discontinuation of ART.
The dense array of N-linked glycans on the HIV-1 envelope glycoprotein (Env), known as the “glycan shield,” is a key determinant of immunogenicity, yet intrinsic heterogeneity confounds typical structure–function analysis. Here, we present an integrated approach of single-particle electron cryomicroscopy (cryo-EM), computational modeling, and site-specific mass spectrometry (MS) to probe glycan shield structure and behavior at multiple levels. We found that dynamics lead to an extensive network of interglycan interactions that drive the formation of higher-order structure within the glycan shield. This structure defines diffuse boundaries between buried and exposed protein surface and creates a mapping of potentially immunogenic sites on Env. Analysis of Env expressed in different cell lines revealed how cryo-EM can detect subtle changes in glycan occupancy, composition, and dynamics that impact glycan shield structure and epitope accessibility. Importantly, this identified unforeseen changes in the glycan shield of Env obtained from expression in the same cell line used for vaccine production. Finally, by capturing the enzymatic deglycosylation of Env in a time-resolved manner, we found that highly connected glycan clusters are resistant to digestion and help stabilize the prefusion trimer, suggesting the glycan shield may function beyond immune evasion.
ABSTRACT RNA degradation is an important process that influences the ultimate concentration of individual proteins inside cells. While the main enzymes that facilitate this process have been identified, global maps of RNA turnover are available for only a few species. Even in these cases, there are few sequence elements that are known to enhance or destabilize a native transcript; even fewer confer the same effect when added to a heterologous transcript. To address this knowledge gap, we assayed genome-wide RNA degradation in the cyanobacterium Synechococcus sp. strain PCC 7002 by collecting total RNA samples after stopping nascent transcription with rifampin. We quantified the abundance of each position in the transcriptome as a function of time using RNA-sequencing data and later analyzed the global mRNA decay map using machine learning principles. Half-lives, calculated on a per-ORF (open reading frame) basis, were extremely short, with a median half-life of only 0.97 min. Despite extremely rapid turnover of most mRNA, transcripts encoding proteins involved in photosynthesis were both highly expressed and highly stable. Upon inspection of these stable transcripts, we identified an enriched motif in the 3′ untranslated region (UTR) that had similarity to Rho-independent terminators. We built statistical models for half-life prediction and used them to systematically identify sequence motifs in both 5′ and 3′ UTRs that correlate with stabilized transcripts. We found that transcripts linked to a terminator containing a poly(U) tract had a longer half-life than both those without a poly(U) tract and those without a terminator. IMPORTANCE RNA degradation is an important process that affects the final concentration of individual mRNAs, affecting protein expression and cellular physiology. Studies of how RNA is degraded increase our knowledge of this fundamental process as well as enable the creation of genetic tools to manipulate RNA stability. By studying global transcript turnover, we searched for sequence elements that correlated with transcript (in)stability and used these sequences to guide tool design. This study probes global RNA turnover in a cyanobacterium, Synechococcus sp. strain PCC 7002, that both has a unique array of RNases that facilitate RNA degradation and is an industrially relevant strain that could be used to convert CO 2 and sunlight into useful products.
Electropolishing (EP) and buffered chemical polishing (BCP) are conventional surface preparation techniques for superconducting radiofrequency (SRF) cavities. Both EP and BCP treated SRF cavities display high field Q-slope (HFQS) which degrades performance at high gradients. While high gradient performance in EP cavities can be improved by introducing oxygen via a low temperature bake (LTB) of 120^{°}C by 48 hours, LTB does not consistently remove HFQS in BCP cavities. There is no consensus as to why LTB is not effective on BCP prepared cavities. We examine quench in EP, BCP, EP+LTB, and BCP+LTB treated 1.3 GHz single-cell Nb cavities by studying the heating behavior with field using a temperature mapping system. Cavity performance is correlated to characterizations of surface impurity profile obtained via time of flight secondary ion mass spectrometry studies. We observe a difference in near surface hydrogen concentration following BCP compared to EP that may suggest that the causes of quench in EP and BCP cavities are different.
We present a multilocus phylogeny of the class Dacrymycetes, based on data from the 18S, ITS, 28S, RPB1,RPB2,TEF-1α, 12S, andATP6DNA regions, with c. 90 species including the types of most currently accepted genera. A variety of methodological approaches was used to infer phylogenetic relationships among the Dacrymycetes, from a supermatrix strategy using maximum likelihood and Bayesian inference on a concatenated dataset, to coalescence-based calculations, such as quartet-based summary methods of independent single-locus trees, and Bayesian integration of single-locus trees into a species tree under the multispecies coalescent. We evaluate for the first time the taxonomic usefulness of some cytological phenotypic characters, i.e., vacuolar contents (vacuolar bodies and lipid bodies), number of nuclei of recently discharged basidiospores, and pigments, with especial emphasis on carotenoids. These characters, along with several others traditionally used for the taxonomy of this group (basidium shape, presence and morphology of clamp connections, morphology of the terminal cells of cortical/marginal hyphae, presence and degree of ramification of the hyphidia), are mapped on the resulting phylogenies and their evolution through the class Dacrymycetes discussed. Our analyses reveal five lineages that putatively represent five different families, four of which are accepted and named. Three out of these four lineages correspond to previously circumscribed and published families (Cerinomycetaceae, Dacrymycetaceae, and Unilacrymaceae), and one is proposed as the new family Dacryonaemataceae. Provisionally, only a single order, Dacrymycetales, is accepted with in the class. Furthermore, the systematics of the two smallest families, Dacryonaemataceae and Unilacrymaceae, are investigated to the species level, using coalescence-based species delimitation on multilocus DNA data, and a detailed morphological study including morphometric analyses of the basidiospores. Three species are accepted in Dacryonaema, the type, Da. rufum, the newly combined Da. Macnabbii (basionym Dacrymyces macnabbii), and a new species named Da. macrosporum. Two species are accepted in Unilacryma, the new U. bispora, and the type, U. unispora, the latter treated in a broad sense pending improved sampling across the Holarctic.
Development of efficient energy materials is critical in order to ease the energy demand and reduce our dependence of fossil fuel. Thermoelectric materials are promising due to their capability of generating electrical power by recovering waste heat. The performance of thermoelectric materials is quantified by a dimensionless figure of merit zT, which depends on their properties such as electrical conductivity, Seebeck coefficient and thermal conductivity. Tetrahedrites, a copper antimony sulfosalt mineral, typified by Cu 12-x MxSb 4 S 13 , where M is a transition metal element such as Ni, Zn, Fe or Mn, have great potential for thermoelectric application due to their relatively high zT (close to 1 at 700 K), earth-abundance, environmental friendliness, favorable electrical properties, and most importantly intrinsic low lattice thermal conductivity (less than 1 W m -1 K -1 ) in wide temperature. In addition to energy recovery, reliable energy storage devices are also emerging to relieve the energy demand and improve the efficiency of consuming energy resources. Lithium-ion batteries are known to be reliable and successful electrochemical energy storage devices and appliable in various aspects, including laptops, smartphones and electrical vehicles. Lithium phosphorous oxynitride (LiPON) are widely used as thin-film solid-state electrolytes in Li-ion battery, which is the only demonstrated solid-state electrolyte that is quite stable in direct contact with Li metal at potentials from 0-5 V. However, the structure of LiPON, the effects of N doping, and the origin of its good electrochemical stability remains inconclusive. In this thesis, reliable modeling techniques accompanied with experimental tools, are applied to study the thermoelectric material tetrahedrite and the ionic conductor LiPON, in order to study their structural and dynamical properties. Accurate and efficient density-functional theory (DFT) and density-functional tight-binding (DFTB) methods, combined with molecular dynamics (MD) simulations are utilized in order to investigate the structures and properties of these energy materials. The incoherent and coherent atomic dynamics study of tetrahedrite Cu 10.5 NiZn 0.5 Sb 4 S 13 provides the origin of softening upon cooling by investigate the motion of Cu12e at different temperatures. The dynamic structure factors in the longitudinal and transverse direction will also be discussed. The Cu movement of Cu-rich tetrahedrite Cu 14 Sb 4 S 13 is revealed by Cu self-diffusivity, nuclear density map and “nudged elastic band” (NEB). Moreover, we investigate the effect of simulation cell size and basis sets on the DFT-based MD simulation results using tetrahedrite Cu1 0 Zn 2 Sb 4 S 13 thermoelectric as a model material, showing the advantage of larger cell by accessing smaller Q range. In addition, the low-temperature structural properties of Cu 12 Sb 4 S 13 is measured by neutron diffraction, which indicates that no cubic to tetragonal transition occurs at metal-semiconductor transition (MST) temperature. Thermoelectric properties such as Seebeck coefficient, electrical resistivity and electrical thermal conductivity will also be investigated. DFTB method is implemented to study the structure and transport properties of Li 3 PO 4 and LiPON, while the exploration of N doping effect is included. Lastly, the LiPON/Li interphase will be revealed in order to study the origin of electrochemical stability.
Development of efficient energy materials is critical in order to ease the energy demand and reduce our dependence of fossil fuel. Thermoelectric materials are promising due to their capability of generating electrical power by recovering waste heat. The performance of thermoelectric materials is quantified by a dimensionless figure of merit zT, which depends on their properties such as electrical conductivity, Seebeck coefficient and thermal conductivity. Tetrahedrites, a copper antimony sulfosalt mineral, typified by Cu12-xMxSb4S13, where M is a transition metal element such as Ni, Zn, Fe or Mn, have great potential for thermoelectric application due to their relatively high zT (close to 1 at 700 K), earth-abundance, environmental friendliness, favorable electrical properties, and most importantly intrinsic low lattice thermal conductivity (less than 1 W m-1 K-1) in wide temperature. In addition to energy recovery, reliable energy storage devices are also emerging to relieve the energy demand and improve the efficiency of consuming energy resources. Lithium-ion batteries are known to be reliable and successful electrochemical energy storage devices and appliable in various aspects, including laptops, smartphones and electrical vehicles. Lithium phosphorous oxynitride (LiPON) are widely used as thin-film solid-state electrolytes in Li-ion battery, which is the only demonstrated solid-state electrolyte that is quite stable in direct contact with Li metal at potentials from 0-5 V. However, the structure of LiPON, the effects of N doping, and the origin of its good electrochemical stability remains inconclusive.In this thesis, reliable modeling techniques accompanied with experimental tools, are applied to study the thermoelectric material tetrahedrite and the ionic conductor LiPON, in order to study their structural and dynamical properties. Accurate and efficient density-functional theory (DFT) and density-functional tight-binding (DFTB) methods, combined with molecular dynamics (MD) simulations are utilized in order to investigate the structures and properties of these energy materials. The incoherent and coherent atomic dynamics study of tetrahedrite Cu10.5NiZn0.5Sb4S13 provides the origin of softening upon cooling by investigate the motion of Cu12e at different temperatures. The dynamic structure factors in the longitudinal and transverse direction will also be discussed. The Cu movement of Cu-rich tetrahedrite Cu14Sb4S13 is revealed by Cu self-diffusivity, nuclear density map and "nudged elastic band" (NEB). Moreover, we investigate the effect of simulation cell size and basis sets on the DFT-based MD simulation results using tetrahedrite Cu10Zn2Sb4S13 thermoelectric as a model material, showing the advantage of larger cell by accessing smaller Q range. In addition, the low-temperature structural properties of Cu12Sb4S13 is measured by neutron diffraction, which indicates that no cubic to tetragonal transition occurs at metal-semiconductor transition (MST) temperature. Thermoelectric properties such as Seebeck coefficient, electrical resistivity and electrical thermal conductivity will also be investigated. DFTB method is implemented to study the structure and transport properties of Li3PO4 and LiPON, while the exploration of N doping effect is included. Lastly, the LiPON/Li interphase will be revealed in order to study the origin of electrochemical stability
In this article, we push lightweight XOR-based in-situ encryption to extreme density by proposing a singletransistor XOR memory cell and applying it to 3D NAND, enabling secure data storage without density loss. Using a ferroelectric field-effect transistor (FeFET) as an example technology, we demonstrate that: i) a single-transistor memory can realize the XOR function by exploiting the ability to charge the source and drain separately and control current flow direction, eliminating the need for conventional encrypted cells that rely on complementary devices; ii) with a XOR-based cipher, encryption and decryption can be mapped to in-situ array operations, where ciphertext is stored as the threshold voltage (VTH) states of FeFETs in a NAND string, and decryption is achieved through read operations using key-dependent complementary source/drain bias; iii) the proposed technique is scalable to multi-level cell (MLC) storage by encrypting and decrypting data bit by bit; iv) using an integrated NAND FeFET array, we experimentally demonstrate encryption and decryption operations for both single-level cell (SLC) and MLC storage; v) systemlevel benchmarking shows that the proposed technique achieves 48× and 278× improvements in encryption and decryption throughput, respectively, compared to AES.
Animal models have expanded our understanding of temporal lobe epilepsy (TLE). However, translating these to cell-specific druggable hypotheses is not explored. Herein, we conducted an integrative insilico-analysis of an available transcriptomics dataset obtained from animals with pilocarpine-induced-TLE. A set of 119 genes with subtle-to-moderate impact predicted most forms of epilepsy with ~ 97% accuracy and characteristically mapped to upregulated homeostatic and downregulated synaptic pathways. The deconvolution of cellular proportions revealed opposing changes in diverse cell types. The proportion of nonneuronal cells increased whereas that of interneurons, except for those expressing vasoactive intestinal peptide (Vip), decreased, and pyramidal neurons of the cornu-ammonis (CA) subfields showed the highest variation in proportion. A probabilistic Bayesian-network demonstrated an aberrant and oscillating physiological interaction between nonneuronal cells involved in the blood–brain-barrier and Vip interneurons in driving seizures, and their role was evaluated insilico using transcriptomic changes induced by valproic-acid, which showed opposing effects in the two cell-types. Additionally, we revealed novel epileptic and antiepileptic mechanisms and predicted drugs using causal inference, outperforming the present drug repurposing approaches. These well-powered findings not only expand the understanding of TLE and seizure oscillation, but also provide predictive biomarkers of epilepsy, cellular and causal micro-circuitry changes associated with it, and a drug-discovery method focusing on these events.