Pyroptosis associated with immune reconstruction failure in HIV-1- infected patients receiving antiretroviral therapy: a cross-sectional study.

BACKGROUND: Highly active anti-retroviral therapy (HAART) can successfully suppress human immunodeficiency virus (HIV) viral replication and reconstruct immune function reconstruction in HIV-1-infected patients. However, about 15-30% of HIV-1-infected patients still fail to recover their CD4+ T cell counts after HAART treatment, which means immune reconstruction failure. Pyroptosis plays an important role in the death of CD4+ T cells in HIV-1- infected patients. The study aims to explore the association between the expression of pyroptosis in peripheral blood and immune function reconstruction in HIV-1- infected patients. METHODS: One hundred thirty-five HIV-1-infected patients including immunological non-responders (INR) group, immunological responders (IR) group and normal immune function control (NC) group were analyzed. The expression of GSDMD and Caspase-1 in peripheral blood of HIV-1-infected patients were measured by qPCR. The concentrations of GSDMD, Caspase-1, IL-1ß and IL-18 in the peripheral serum were quantified by ELISA. The associations between the expression of pyroptosis in peripheral blood and immune function reconstruction were analyzed using multivariate logistic models. RESULTS: The relative expression of GSDMD mRNA and caspase-1 mRNA in peripheral blood, as well as the expression of IL-18 cytokine in the INR, were significantly higher than those in the IR and NC (P < 0.05). There was no significant difference in the expression of IL-1ß cytokine (P > 0.05). Multivariate logistic analysis showed that the patients with baseline CD4+ T cell counts less than 100 cells/µL (aOR 7.051, 95% CI 1.115-44.592, P = 0.038), high level of expression of Caspase-1mRNA (aOR 2.803, 95% CI 1.065-7.377, P = 0.037) and IL-18 cytokine (aOR 10.131, 95% CI 1.616-63.505, P = 0.013) had significant poor CD4+ T cell recovery. CONCLUSIONS: The baseline CD4+ T cell counts less than 100 cells/µL, high relative expression of Caspase-1 mRNA, and high expression of IL-18 cytokine are associated factors that affect the reconstruction of immune function.

Potential dependence of OER/EOP performance on heteroatom-doped carbon materials by grand canonical density functional theory.

Revealing the effect of external applied potential on the reaction mechanism and product selectivity is of great significance in electrochemical studies. In this work, the grand canonical density functional theory method was applied to simulate the explicit electrocatalytic process of oxygen evolution reaction and electrochemical ozone production due to the O3 product sensitivity toward the applied potential. Over the Pt/Pd single atom embedded on B/N co-doped graphene (Pt/Pd-BNC) surface, crossover points of O2/O3 selectivity inversion were predicted to be 1.33 and 0.89 V vs standard hydrogen electrode, which were also consistent with the previous experimental results. An in-depth analysis of the energetic terms in the reaction free energies also found the considerable impact of the applied potential on the Helmholtz free energy term, with optimal potential predicted for the key elementary steps, and linear correlations between electrode potential (U) and reaction free energy were found for each elementary step. This study offers extensive knowledge on the potential effect on the O2/O3 selective formation on two-dimensional anode surfaces and provides new insights for investigating the reactivity/selectivity on electrode surfaces in real reaction conditions.

Sintering Rate and Mechanism of Supported Pt Nanoparticles by Multiscale Simulation.

Thermal stability is the key issue in the industrial application of supported metal nanocatalysts. A combination method of density functional theory calculations, machine learning, and molecular dynamics simulation is adopted to study the sintering behavior of supported platinum (Pt) nanoparticles on graphene or TiO2 nanosheet, and analyze sintering mechanisms under different temperatures, particle sizes, and metal support interactions (MSIs). The results show that the agglomeration of supported nanoparticles is mainly based on the mechanism of small particle migration and growth. Small-sized particles with high surface energy determine the sintering rate. In addition, the increase of temperature is conducive to the agglomeration of particles, especially for systems with strong MSI. Based on the analysis of the sintering process, a sintering kinetic model of supported Pt nanoparticles related to particle size, temperature, and MSI is established, which provides theoretical guidance for the design of supported metal catalysts with high thermal stability.

Structural Arrest and Phase Transition in Glassy Nanocellulose Colloids.

From drying blood to oil paint, the developing of a glassy phase from colloids is observed on a daily basis. Colloidal glass is solid soft matter that consists of two intertwined phases: a random packed particle network and a fluid solvent. By dispersing charged rod-like cellulose nanoparticles into a water-ethylene glycol cosolvent, here we demonstrate a new kind of colloidal glass with a high liquid crystalline order, namely, two general superstructures with nematic and cholesteric packing states are preserved and jammed inside the glass matrix. During the glass formation process, structural arrest and phase transition occur simultaneously at high particle concentrations, yielding solid-like behavior as well as a frozen liquid crystal texture that is because of caging of the charged colloids through neighboring long-ranged repulsive interactions.

Multiscale Simulation of Morphology Evolution of Supported Pt Nanoparticles via Interfacial Control.

The structural and electronic properties of the interface are critical for the morphology of supported metal nanoparticles and thus the performance in catalysis, photonics, biomedical research, and other areas. To reveal the intrinsic mechanism of the formation of various morphologies, a multiscale simulation strategy is adopted to bridge the macroscopic structures by experimental observations and microscopic properties by theoretical calculations. This strategy incorporates the density functional theory (DFT) for the interaction energy calculation, the molecular dynamics (MD) simulation for the structure evolution, and theoretical model for the correlation with contact angles. The interaction energies between Pt atoms (four-atom clusters) and substrates are applied for the force field parametrization in the following MD simulation. Simulation results show the binding energies and structural properties such as radial distribution function and coordination number for supported metal nanoparticles with various sizes in detail. Notably, the contact angles of supported nanoparticles are well correlated by the strength of metal-support interactions. This work yields guidelines on the structure modulation of supported metal nanoparticles via interfacial control.

Single and double boron atoms doped nanoporous C2N-h2D electrocatalysts for highly efficient N2 reduction reaction: a density functional theory study.

The electrocatalytical process is the most efficient way to produce ammonia (NH3) under ambient conditions, but developing a highly efficient and low-cost metal-free electrocatalysts remains a major scientific challenge. Hence, single atom and double boron (B) atoms doped 2D graphene-like carbon nitride (C2N-h2D) electrocatalysts have been designed (B@C2N and B2@C2N), and the efficiency of N2 reduction reaction (NRR) is examined by density functional theory calculation. The results show that the single and double B atoms can both be strongly embedded in natural nanoporous C2N with superior catalytic activity for N2 activation. The reaction mechanisms of NRR on the B@C2N and B2@C2N are both following an enzymatic pathway, and B2@C2N is a more efficient electrocatalyst with extremely low overpotential of 0.19 eV comparing to B@C2N (0.29 eV). In the low energy region, the hydrogenation of N2 is thermodynamically more favorable than the hydrogen production, thereby improving the selectivity for NRR. Based on these results, a new double-atom strategy may help guiding the experimental synthesis of highly efficient NRR electrocatalysts.

Micromechanical simulation of the pore size effect on the structural stability of brittle porous materials with bicontinuous morphology.

Brittle porous materials offer a wide variety of promising applications due to their high surface-area-to-volume ratios and controllable porous structures. Getting comprehensive knowledge of the structural stability is of great significance for avoiding the irreversible destruction of these materials. Based on interpenetrating bicontinuous structures, we innovatively adopted a sequential mesoscopic simulation strategy to show the pore size effect on the mechanical stability, which involves structural evolution by the mesoscale dynamic density functional method and mechanical behavior by the highly efficient lattice spring model. Simulation results show that specific surface areas, Young's moduli and fracture strains decrease with the increase of pore widths on the premise of the same porosity. More uniform stress/strain distributions are observed in structures with smaller pore sizes or more uniform defect distributions. From the local stress distribution analysis, the effective stress transfer occurs in the solid phase, which runs through the simulation box along the tensile direction, and the mechanical disparity among systems with different pore sizes is due to different volume fractions and microstructures of the solid phase. Larger pore sizes result in lower Weibull moduli due to the increased heterogeneity and a less predictable failure behavior, and the concentrated defects usually result in mechanical anisotropy.

Controlled Assembly of Nanocellulose-Stabilized Emulsions with Periodic Liquid Crystal-in-Liquid Crystal Organization.

Colloidal particles combined with a polymer can be used to stabilize an oil-water interface forming stable emulsions. Here, we described a novel liquid crystal (LC)-in-LC emulsion composed of a nematic oil phase and a cholesteric or nematic aqueous cellulose nanocrystal (CNC) continuous phase. The guest oil droplets were stabilized and suspended in liquid-crystalline CNCs, inducing distortions and topological defects inside the host LC phase. These emulsions exhibited anisotropic interactions between the two LCs that depended on the diameter-to-pitch ratio of suspended guest droplets and the host CNC cholesteric phase. When the ratio was high, oil droplets were embedded into a cholesteric shell with a concentric packing of CNC layers and took on a radial orientation of the helical axis. Otherwise, discrete surface-trapped LC droplet assemblies with long-range ordering were obtained, mimicking the fingerprint configuration of the cholesteric phase. Thus, the LC-in-LC emulsions presented here define a new class of ordered soft matter in which both nematic and cholesteric LC ordering can be well-manipulated.

Raman scattering from single WS2 nanotubes in stretched PVDF electrospun fibers.

Inorganic WS2 nanotubes (INT-WS2) were embedded into sub-µm polyvinylidene fluoride-co-hexafluropropylene (PVDF-HFP) electrospun fibers. In this report we explore the Raman scattering spectroscopy from a single nanotube during stretching of individual nanocomposite fibers. Red shifts of up to ∼4.7 cm-1 for A1g and E WS2 bands were found before reaching the "tearing point" of the fibers. These shifts may correlate with up to ∼2.8% of the WS2 nanotube elongation. Moreover, the absence of the A1g and E bands' broadening, as well as the nonappearance of the E shear mode in the nanotube Raman spectra, suggest the stretching of the nanotubes as a whole (including inner layers). These results point to the excellent adhesion of the nanotubes' surface to the polymer and to the effective load transfer from the polymer to the WS2 nanotube. In order to elucidate the nature of interaction between the polymer and the nanofiller, we modeled the deformation of composite fibers using an elastic lattice spring model (LSM). The results of the model are fully consistent with our interpretation.

Structural Transition in Liquid Crystal Bubbles Generated from Fluidic Nanocellulose Colloids.

The structural transition in micrometer-sized liquid crystal bubbles (LCBs) derived from rod-like cellulose nanocrystals (CNCs) was studied. The CNC-based LCBs were suspended in nematic or chiral nematic liquid-crystalline CNCs, which generated topological defects and distinct birefringent textures around them. The ordering and structure of the LCBs shifted from a nematic to chiral nematic arrangement as water evaporation progressed. These packed LCBs exhibited a specific photonic cross-communication property that is due to a combination of Bragg reflection and bubble curvature and size.

Curing and Cross-Linking Processes in the Poly(3,3-bis-azidomethyl oxetane)-tetrahydrofuran/Toluene Diisocyanate/Trimethylolpropane System: A Density Functional Theory and Accelerated ReaxFF Molecular Dynamics Investigation.

The physical and chemical properties of solid propellant are influenced by the composition and structure of the binder, with its network structure being formed through curing and cross-linking reactions. Therefore, understanding the mechanisms of these reactions is crucial. In this study, we investigated the curing and cross-linking mechanisms of poly(3,3-bis-azidomethyl oxetane)-tetrahydrofuran (PBT), toluene diisocyanate (TDI), and trimethylolpropane (TMP) using a combination of density functional theory (DFT) calculations and accelerated ReaxFF molecular dynamics (MD) simulations. DFT calculations revealed that the steric effect of the -CH3 group in TDI exerts a significant influence on the curing reaction between TDI and PBT. Additionally, in the cross-linking process, the energy barrier for TDI reacting with TMP was found to be much lower than that for TDI reacting with the PBT-TDI intermediate. Subsequently, we conducted competing reaction processes of TMP/TDI-PBT-TDI cross-linking and TDI-PBT-TDI self-cross-linking using accelerated MD simulations within the fitted ReaxFF framework. The results showed that the successful frequency of TMP/TDI-PBT-TDI cross-linking was substantially higher than that of TDI-PBT-TDI self-cross-linking, consistent with the energy barrier results from DFT calculations. These findings deepen our understanding of the curing and cross-linking mechanisms of the PBT system, providing valuable insights for the optimization and design of solid propellants.

Nitrogen-Rich Conjugated Microporous Polymers with Improved Cobalt(II) Density for Highly Efficient Electrocatalytic Oxygen Evolution.

Developing efficient oxygen evolution catalysts (OECs) made from earth-abundant elements is extremely important since the oxygen evolution reaction (OER) with sluggish kinetics hinders the development of many energy-related electrochemical devices. Herein, an efficient strategy is developed to prepare conjugated microporous polymers (CMPs) with abundant and uniform coordination sites by coupling the N-rich organic monomer 2,4,6-tris(5-bromopyrimidin-2-yl)-1,3,5-triazine (TBPT) with Co(II) porphyrin. The resulting CMP-Py(Co) is further metallized with Co2+ ions to obtain CMP-Py(Co)@Co. Structural characterization results reveal that CMP-Py(Co)@Co has higher Co2+ content (12.20 wt %) and affinity toward water compared with CMP-Py(Co). Moreover, CMP-Py(Co)@Co exhibits an excellent OER activity with a low overpotential of 285 mV vs RHE at 10 mA cm-2 and a Tafel slope of 80.1 mV dec-1, which are significantly lower than those of CMP-Py(Co) (335 mV vs RHE and 96.8 mV dec-1). More interestingly, CMP-Py(Co)@Co outperforms most reported porous organic polymer-based OECs and the benchmark RuO2 catalyst (320 mV vs RHE and 87.6 mV dec-1). Additionally, Co2+-free CMP-Py(2H) has negligible OER activity. Thereby, the enhanced OER activity of CMP-Py(Co)@Co is attributed to the incorporation of Co2+ ions leading to rich active sites and enlarged electrochemical surface areas. Density functional theory (DFT) calculations reveal that Co2+-TBPT sites have higher activity than Co2+-porphyrin sites for the OER. These results indicate that the introduction of rich active metal sites in stable and conductive CMPs could provide novel guidance for designing efficient OECs.

Predicting band gaps of MOFs on small data by deep transfer learning with data augmentation strategies.

Porphyrin-based MOFs combine the unique photophysical and electrochemical properties of metalloporphyrins with the catalytic efficiency of MOF materials, making them an important candidate for light energy harvesting and conversion. However, accurate prediction of the band gap of porphyrin-based MOFs is hampered by their complex structure-function relationships. Although machine learning (ML) has performed well in predicting the properties of MOFs with large training datasets, such ML applications become challenging when the training data size of the materials is small. In this study, we first constructed a dataset of 202 porphyrin-based MOFs using DFT computations and increased the training data size using two data augmentation strategies. After that, four state-of-the-art neural network models were pre-trained with the recognized open-source database QMOF and fine-tuned with our augmented self-curated datasets. The GCN models predicted the band gaps of the porphyrin-based materials with the lowest RMSE of 0.2767 eV and MAE of 0.1463 eV. In addition, the data augmentation strategy rotation and mirroring effectively decreased the RMSE by 38.51% and MAE by 50.05%. This study demonstrates that, when proper transfer learning and data augmentation strategies are applied, machine learning models can predict the properties of MOFs using small training data.

Formation Mechanism of Monocyclic Aromatic Hydrocarbons during Pyrolysis of Styrene Butadiene Rubber in Waste Passenger Car Tires.

The production of aromatic hydrocarbons from the waste tire pyrolysis attracts more and more attention because of its tremendous potential. Based on styrene-butadiene rubber (SBR), which is the main rubber in the waste passenger car tires, this work studies the temperature influence on primary pyrolysis product distribution by experimental techniques (Py-GC/MS, TG-MS), and then, the formation mechanism of monocyclic aromatic hydrocarbons (MAHs) observed in the experiment was analyzed by first-principles calculations. The experimental results show that the MAHs during the pyrolysis mainly include styrene, toluene, and xylene, and subsequent calculations showed that these compounds were formed through a series of primary and secondary reactions. The formation pathways of these typical MAHs were studied via the reaction energy barrier analysis, respectively. It shows that the MAHs were not only derived from the benzene ring in the SBR chain but also generated from short-chain alkenes through the Diels-Alder reaction. The obtained pyrolysis reaction mechanism provides theoretical guidance for the regulation of the pyrolysis product distribution of MAHs.

Oxo dicopper anchored on carbon nitride for selective oxidation of methane.

Selective conversion of methane (CH4) into value-added chemicals represents a grand challenge for the efficient utilization of rising hydrocarbon sources. We report here dimeric copper centers supported on graphitic carbon nitride (denoted as Cu2@C3N4) as advanced catalysts for CH4 partial oxidation. The copper-dimer catalysts demonstrate high selectivity for partial oxidation of methane under both thermo- and photocatalytic reaction conditions, with hydrogen peroxide (H2O2) and oxygen (O2) being used as the oxidizer, respectively. In particular, the photocatalytic oxidation of CH4 with O2 achieves >10% conversion, and >98% selectivity toward methyl oxygenates and a mass-specific activity of 1399.3 mmol g Cu-1h-1. Mechanistic studies reveal that the high reactivity of Cu2@C3N4 can be ascribed to symphonic mechanisms among the bridging oxygen, the two copper sites and the semiconducting C3N4 substrate, which do not only facilitate the heterolytic scission of C-H bond, but also promotes H2O2 and O2 activation in thermo- and photocatalysis, respectively.

A strategy for preparing high-efficiency and economical catalytic electrodes toward overall water splitting.

Electrolyzing water technology to prepare high-purity hydrogen is currently an important field in energy development. However, the preparation of efficient, stable, and inexpensive hydrogen production technology from electrolyzed water is a major problem in hydrogen energy production. The key technology for hydrogen production from water electrolysis is to prepare highly efficient catalytic, stable and durable electrodes, which are used to reduce the overpotential of the hydrogen evolution reaction and the oxygen evolution reaction of electrolyzed water. The main strategies for preparing catalytic electrodes include: (i) choosing cheap, large specific surface area and stable base materials, (ii) modulating the intrinsic activity of the catalytic material through elemental doping and lattice changes, and (iii) adjusting the morphology and structure to increase the catalytic activity. Based on these findings, herein, we review the recent work in the field of hydrogen production by water electrolysis, introduce the preparation of catalytic electrodes based on nickel foam, carbon cloth and new flexible materials, and summarize the catalytic performance of metal oxides, phosphides, sulfides and nitrides in the hydrogen evolution and oxygen evolution reactions. Secondly, parameters such as the overpotential, Tafel slope, active site, turnover frequency, and stability are used as indicators to measure the performance of catalytic electrode materials. Finally, taking the material cost of the catalytic electrode as a reference, the successful preparations are comprehensively compared. The overall aim is to shed some light on the exploration of high-efficiency and economical electrodes in energy chemistry and also demonstrate that there is still room for discovering new combinations of electrodes including base materials, composition lattice changes and morphologies.

Sulfur doped FeOx nanosheet arrays supported on nickel foam for efficient alkaline seawater splitting.

Developing economical, efficient and stable bifunctional catalysts for hydrogen production from seawater is of great significance for hydrogen utilization. Herein, sulfur doped iron oxide nanosheet arrays supported on nickel foam (FeOx-Ni3S2@NF) are prepared by a one-pot solvothermal reaction. Owing to the high intrinsic activity of FeOx-Ni3S2, the large catalytic specific surface area of nanosheet arrays and the fast charge transportation capability achieved by the self-supporting configuration, the FeOx-Ni3S2@NF electrode delivers excellent catalytic performance in alkaline simulated seawater (1 M KOH + 0.5 M NaCl). Impressively, a low overpotential of 120 mV at 50 mA cm-2 with a Tafel slope of 57 mV dec-1 for the hydrogen evolution reaction and an overpotential of 470 mV at 200 mA cm-2 with a Tafel slope of 62 mV dec-1 for the oxygen evolution reaction are achieved. More importantly, the voltage is only 1.5 V at 50 mA cm-2 for continuous overall water splitting for 100 h at 200 mA cm-2 with negligible decay in alkaline simulated seawater with almost 100% Faraday efficiency. This work provides a simple and universal strategy to prepare highly efficient bifunctional catalytic materials, promoting the development of Earth-abundant materials to catalyse seawater splitting to produce high-purity hydrogen.

Symbolic Transformer Accelerating Machine Learning Screening of Hydrogen and Deuterium Evolution Reaction Catalysts in MA2Z4 Materials.

Two-dimensional (2D) materials have been developed into various catalysts with high performance, but employing them for developing highly stable and active nonprecious hydrogen evolution reaction (HER) catalysts still encounters many challenges. To this end, the machine learning (ML) screening of HER catalysts is accelerated by using genetic programming (GP) of symbolic transformers for various typical 2D MA2Z4 materials. The values of the Gibbs free energy of hydrogen adsorption (ΔGH*) are accurately and rapidly predicted via extreme gradient boosting regression by using only simple GP-processed elemental features, with a low predictive root-mean-square error of 0.14 eV. With the analysis of ML and density functional theory (DFT) methods, it is found that various electronic structural properties of metal atoms and the p-band center of surface atoms play a crucial role in regulating the HER performance. Based on these findings, NbSi2N4 and VSi2N4 are discovered to be active catalysts with thermodynamical and dynamical stability as ΔGH* approaches to zero (-0.041 and 0.024 eV). In addition, DFT calculations reveal that these catalysts also exhibit good deuterium evolution reaction (DER) performance. Overall, a multistep workflow is developed through ML models combined with DFT calculations for efficiently screening the potential HER and DER catalysts from 2D materials with the same crystal prototype, which is believed to have significant contribution to catalyst design and fabrication.

High-performance single-atom Ni catalyst loaded graphyne for H2O2 green synthesis in aqueous media.

The electrochemical synthesis of hydrogen peroxide (H2O2) provides a greener and more efficient method compared with classic catalysts containing toxic metals. Herein, we used first-principles density functional theory (DFT) calculations to investigate 174 different single-atom catalysts with graphyne substrates, and conducted a three-step screening strategy to identify the optimal noble metal-free single atom catalyst. It is found that a single Ni atom loaded on γ-graphyne with carbon vacancies (Ni@V-γ-GY) displayed remarkable thermodynamic stability, excellent selectivity, and high activity with an ultralow overpotential of 0.03 V. Furthermore, based on ab-initio molecular dynamic and DFT calculations under the H2O solvent, it was revealed that the catalytic performance for H2O2 synthesis in aqueous phase was much better than that in gas phase condition, shedding light on the hydrogen bond network being beneficial to accelerate the transfer of protons for H2O2 synthesis.

From a Relatively Hydrophobic and Triethylamine (TEA) Adsorption-Selective Core-Shell Heterostructure to a Humidity-Resistant and TEA Highly Selective Sensing Prototype: An Alternative Approach to Improve the Sensing Characteristics of TEA Sensors.

During the detection of industrial toxic gases, such as triethylamine (TEA), poor selectivity and negative humidity impact are still challenging issues. A frequently reported strategy is to employ molecular sieves or metal-organic framework (MOF) membranes so that interference derived from surrounding gases or water vapor can be blocked. Nevertheless, the decline in the response signal was also observed after coating these membranes. Herein, an alternative strategy that is based on a hydrophobic, TEA adsorption-selective p-n conjunction core-shell heterostructure is proposed and is speculated to simultaneously enhance selectivity, sensitivity, and humidity resistance. To verify the practicability of the proposed strategy, a thickness-tunable nitrogen-doped carbon (N-C) shell-coated α-Fe2O3 nano-olive (N-C@α-Fe2O3 NO)-based core-shell heterostructure that is obtained via a unique all-vapor-phase processing method is selected as the research example. After forming the core-shell heterostructure, a relatively hydrophobic and TEA adsorption-selective N-C@α-Fe2O3 NO surface was experimentally confirmed. Particularly, a chemiresistive sensor that comprises N-C@α-Fe2O3 NOs exhibits satisfactory selectivity and response magnitude to TEA when compared with the sensor using α-Fe2O3 NOs. The detection limit can even reduce to be 400 ppb at 250 °C. Furthermore, the sensor based on N-C@α-Fe2O3 NOs shows desirable humidity resistance within the relative humidity (RH) range of 30-90%. For practical usage, a sensing prototype based on the N-C@α-Fe2O3 NO probe is fabricated, and its satisfactory sensing performance further confirms the potential for future applications in industrial organic amine detection. These promising results show a bright future in enhancing the humidity resistance and selectivity as well as sensitivity of chemiresistive sensors by simply designing a hydrophobic and target gas adsorption (e.g., TEA) preferred p-n junction core-shell heterostructure.